Introduction
We provide a simple and powerful REST API to integrate weather forecast and observed data into your business or application.
This API reference provides information on available endpoints and how to interact with it. We have code bindings in Python, Shell and JavaScript! You can view code examples in the dark area to the right.
If you can’t find the answer to your question or need help, please explore and contact us through our dev support channel: servicedesk@somarmeteorologia.com.br
Domains
The domains used by the API are:
https://nimbus.somar.io
https://dev.nimbus.somar.io
This if using stage of API, use domain and documentation below.
Domain: https://stage.nimbus.somar.io
Documentation: https://stage.docs.nimbus.somar.io
The developer environment has the same scalability as production, and its key is valid in both environments.
The new features first come into the developer environment and follow a transition pipeline for production to ensure they work.
We strongly advise that during your validation or API integration period you use the production environment without any kind of differentiation.
Authentication
All API requests must be authenticated with a valid access token passed as header.
The API expects for the 'x-api-key' to be included in all requests to the server in a header that looks like the following:
To authorize, use this code:
import requests
import json
response = requests.get('api_endpoint_here',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "api_endpoint_here" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('api_endpoint_here', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
API Usage
Usage
You can find information on how many requests have been consumed for your key, how many are still available and which endpoints within the application you have access to.
import requests
import json
response = requests.get('https://nimbus.somar.io/usage',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/usage" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/usage', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
[{
"plan_id": "12345",
"plan_name": "Personalized",
"api_key_id": "123456789",
"quota": {
"limit": 4000,
"offset": 0,
"period": "DAY",
"remaining": 3990
},
"allowed_routes": [{
"stage": "dev",
"routes": ["/forecast/10days/GET", "/forecast/15days/GET", "/forecast/7days/GET"]
}, {
"stage": "prod",
"routes": ["/forecast/10days/GET", "/forecast/15days/GET", "/forecast/7days/GET"]
}]
}]
Periods
The periods can be DAY, WEEK, MONTH.
Remaining
The value in the remaining key is relative to the period of the key.
Weather Conditions
The relationship to the weather variable API responses are as follows:
| Parameter | Description |
|---|---|
| PN | Poucas nuvens |
| CC | Céu claro |
| NB | Céu nublado |
| EN | Céu enconberto |
| PI | Pancadas isoladas |
| PC | Pancadas de chuva |
| CH | Chuvoso |
| NC | Nublado com chuva |
Interpretation of the API response should be performed as follows.
{
"points": {
"weather_conditions": [
4,
4,
3
]
},
"meta": {
"units": {
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
]
}
}
}
The interpreted result of the API response is:
{
"points": {
"weather_conditions": [
"PI",
"PI",
"EN"
]
}
}
The count used for this is from 0 in the units -> weather key, relative to the weather_conditions key.
Nowcast
Get hourly
This endpoint returns a forecast with 336hrs (14 days and 12 hours)
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/hourly?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/hourly?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/hourly?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-09-09 00:00",
"2020-09-09 01:00",
"2020-09-09 02:00",
"2020-09-09 03:00",
"2020-09-09 04:00",
"2020-09-09 05:00",
"2020-09-09 06:00",
"2020-09-09 07:00",
"2020-09-09 08:00",
"2020-09-09 09:00",
"2020-09-09 10:00",
"2020-09-09 11:00",
"2020-09-09 12:00",
"2020-09-09 13:00",
"2020-09-09 14:00",
"2020-09-09 15:00",
"2020-09-09 16:00",
"2020-09-09 17:00",
"2020-09-09 18:00",
"2020-09-09 19:00",
"2020-09-09 20:00",
"2020-09-09 21:00",
"2020-09-09 22:00",
"2020-09-09 23:00",
"2020-09-10 00:00",
"2020-09-10 01:00",
"2020-09-10 02:00",
"2020-09-10 03:00",
"2020-09-10 04:00",
"2020-09-10 05:00",
"2020-09-10 06:00",
"2020-09-10 07:00",
"2020-09-10 08:00",
"2020-09-10 09:00",
"2020-09-10 10:00",
"2020-09-10 11:00",
"2020-09-10 12:00",
"2020-09-10 13:00",
"2020-09-10 14:00",
"2020-09-10 15:00",
"2020-09-10 16:00",
"2020-09-10 17:00",
"2020-09-10 18:00",
"2020-09-10 19:00",
"2020-09-10 20:00",
"2020-09-10 21:00",
"2020-09-10 22:00",
"2020-09-10 23:00",
"2020-09-11 00:00",
"2020-09-11 01:00",
"2020-09-11 02:00",
"2020-09-11 03:00",
"2020-09-11 04:00",
"2020-09-11 05:00",
"2020-09-11 06:00",
"2020-09-11 07:00",
"2020-09-11 08:00",
"2020-09-11 09:00",
"2020-09-11 10:00",
"2020-09-11 11:00",
"2020-09-11 12:00",
"2020-09-11 13:00",
"2020-09-11 14:00",
"2020-09-11 15:00",
"2020-09-11 16:00",
"2020-09-11 17:00",
"2020-09-11 18:00",
"2020-09-11 19:00",
"2020-09-11 20:00",
"2020-09-11 21:00",
"2020-09-11 22:00",
"2020-09-11 23:00",
"2020-09-12 00:00",
"2020-09-12 01:00",
"2020-09-12 02:00",
"2020-09-12 03:00",
"2020-09-12 04:00",
"2020-09-12 05:00",
"2020-09-12 06:00",
"2020-09-12 07:00",
"2020-09-12 08:00",
"2020-09-12 09:00",
"2020-09-12 10:00",
"2020-09-12 11:00",
"2020-09-12 12:00",
"2020-09-12 13:00",
"2020-09-12 14:00",
"2020-09-12 15:00",
"2020-09-12 16:00",
"2020-09-12 17:00",
"2020-09-12 18:00",
"2020-09-12 19:00",
"2020-09-12 20:00",
"2020-09-12 21:00",
"2020-09-12 22:00",
"2020-09-12 23:00",
"2020-09-13 00:00",
"2020-09-13 01:00",
"2020-09-13 02:00",
"2020-09-13 03:00",
"2020-09-13 04:00",
"2020-09-13 05:00",
"2020-09-13 06:00",
"2020-09-13 07:00",
"2020-09-13 08:00",
"2020-09-13 09:00",
"2020-09-13 10:00",
"2020-09-13 11:00",
"2020-09-13 12:00",
"2020-09-13 13:00",
"2020-09-13 14:00",
"2020-09-13 15:00",
"2020-09-13 16:00",
"2020-09-13 17:00",
"2020-09-13 18:00",
"2020-09-13 19:00",
"2020-09-13 20:00",
"2020-09-13 21:00",
"2020-09-13 22:00",
"2020-09-13 23:00",
"2020-09-14 00:00",
"2020-09-14 01:00",
"2020-09-14 02:00",
"2020-09-14 03:00",
"2020-09-14 04:00",
"2020-09-14 05:00",
"2020-09-14 06:00",
"2020-09-14 07:00",
"2020-09-14 08:00",
"2020-09-14 09:00",
"2020-09-14 10:00",
"2020-09-14 11:00",
"2020-09-14 12:00",
"2020-09-14 13:00",
"2020-09-14 14:00",
"2020-09-14 15:00",
"2020-09-14 16:00",
"2020-09-14 17:00",
"2020-09-14 18:00",
"2020-09-14 19:00",
"2020-09-14 20:00",
"2020-09-14 21:00",
"2020-09-14 22:00",
"2020-09-14 23:00",
"2020-09-15 00:00",
"2020-09-15 01:00",
"2020-09-15 02:00",
"2020-09-15 03:00",
"2020-09-15 04:00",
"2020-09-15 05:00",
"2020-09-15 06:00",
"2020-09-15 07:00",
"2020-09-15 08:00",
"2020-09-15 09:00",
"2020-09-15 10:00",
"2020-09-15 11:00",
"2020-09-15 12:00",
"2020-09-15 13:00",
"2020-09-15 14:00",
"2020-09-15 15:00",
"2020-09-15 16:00",
"2020-09-15 17:00",
"2020-09-15 18:00",
"2020-09-15 19:00",
"2020-09-15 20:00",
"2020-09-15 21:00",
"2020-09-15 22:00",
"2020-09-15 23:00",
"2020-09-16 00:00",
"2020-09-16 01:00",
"2020-09-16 02:00",
"2020-09-16 03:00",
"2020-09-16 04:00",
"2020-09-16 05:00",
"2020-09-16 06:00",
"2020-09-16 07:00",
"2020-09-16 08:00",
"2020-09-16 09:00",
"2020-09-16 10:00",
"2020-09-16 11:00",
"2020-09-16 12:00",
"2020-09-16 13:00",
"2020-09-16 14:00",
"2020-09-16 15:00",
"2020-09-16 16:00",
"2020-09-16 17:00",
"2020-09-16 18:00",
"2020-09-16 19:00",
"2020-09-16 20:00",
"2020-09-16 21:00",
"2020-09-16 22:00",
"2020-09-16 23:00",
"2020-09-17 00:00",
"2020-09-17 01:00",
"2020-09-17 02:00",
"2020-09-17 03:00",
"2020-09-17 04:00",
"2020-09-17 05:00",
"2020-09-17 06:00",
"2020-09-17 07:00",
"2020-09-17 08:00",
"2020-09-17 09:00",
"2020-09-17 10:00",
"2020-09-17 11:00",
"2020-09-17 12:00",
"2020-09-17 13:00",
"2020-09-17 14:00",
"2020-09-17 15:00",
"2020-09-17 16:00",
"2020-09-17 17:00",
"2020-09-17 18:00",
"2020-09-17 19:00",
"2020-09-17 20:00",
"2020-09-17 21:00",
"2020-09-17 22:00",
"2020-09-17 23:00",
"2020-09-18 00:00",
"2020-09-18 01:00",
"2020-09-18 02:00",
"2020-09-18 03:00",
"2020-09-18 04:00",
"2020-09-18 05:00",
"2020-09-18 06:00",
"2020-09-18 07:00",
"2020-09-18 08:00",
"2020-09-18 09:00",
"2020-09-18 10:00",
"2020-09-18 11:00",
"2020-09-18 12:00",
"2020-09-18 13:00",
"2020-09-18 14:00",
"2020-09-18 15:00",
"2020-09-18 16:00",
"2020-09-18 17:00",
"2020-09-18 18:00",
"2020-09-18 19:00",
"2020-09-18 20:00",
"2020-09-18 21:00",
"2020-09-18 22:00",
"2020-09-18 23:00",
"2020-09-19 00:00",
"2020-09-19 01:00",
"2020-09-19 02:00",
"2020-09-19 03:00",
"2020-09-19 04:00",
"2020-09-19 05:00",
"2020-09-19 06:00",
"2020-09-19 07:00",
"2020-09-19 08:00",
"2020-09-19 09:00",
"2020-09-19 10:00",
"2020-09-19 11:00",
"2020-09-19 12:00",
"2020-09-19 13:00",
"2020-09-19 14:00",
"2020-09-19 15:00",
"2020-09-19 16:00",
"2020-09-19 17:00",
"2020-09-19 18:00",
"2020-09-19 19:00",
"2020-09-19 20:00",
"2020-09-19 21:00",
"2020-09-19 22:00",
"2020-09-19 23:00",
"2020-09-20 00:00",
"2020-09-20 01:00",
"2020-09-20 02:00",
"2020-09-20 03:00",
"2020-09-20 04:00",
"2020-09-20 05:00",
"2020-09-20 06:00",
"2020-09-20 07:00",
"2020-09-20 08:00",
"2020-09-20 09:00",
"2020-09-20 10:00",
"2020-09-20 11:00",
"2020-09-20 12:00",
"2020-09-20 13:00",
"2020-09-20 14:00",
"2020-09-20 15:00",
"2020-09-20 16:00",
"2020-09-20 17:00",
"2020-09-20 18:00",
"2020-09-20 19:00",
"2020-09-20 20:00",
"2020-09-20 21:00",
"2020-09-20 22:00",
"2020-09-20 23:00",
"2020-09-21 00:00",
"2020-09-21 01:00",
"2020-09-21 02:00",
"2020-09-21 03:00",
"2020-09-21 04:00",
"2020-09-21 05:00",
"2020-09-21 06:00",
"2020-09-21 07:00",
"2020-09-21 08:00",
"2020-09-21 09:00",
"2020-09-21 10:00",
"2020-09-21 11:00",
"2020-09-21 12:00",
"2020-09-21 13:00",
"2020-09-21 14:00",
"2020-09-21 15:00",
"2020-09-21 16:00",
"2020-09-21 17:00",
"2020-09-21 18:00",
"2020-09-21 19:00",
"2020-09-21 20:00",
"2020-09-21 21:00",
"2020-09-21 22:00",
"2020-09-21 23:00",
"2020-09-22 00:00",
"2020-09-22 01:00",
"2020-09-22 02:00",
"2020-09-22 03:00",
"2020-09-22 04:00",
"2020-09-22 05:00",
"2020-09-22 06:00",
"2020-09-22 07:00",
"2020-09-22 08:00",
"2020-09-22 09:00",
"2020-09-22 10:00",
"2020-09-22 11:00",
"2020-09-22 12:00",
"2020-09-22 13:00",
"2020-09-22 14:00",
"2020-09-22 15:00",
"2020-09-22 16:00",
"2020-09-22 17:00",
"2020-09-22 18:00",
"2020-09-22 19:00",
"2020-09-22 20:00",
"2020-09-22 21:00",
"2020-09-22 22:00",
"2020-09-22 23:00"
],
"points": {
"location": {
"latitude": -10.48,
"longitude": -40.51,
"elevation": 790,
"sunrise": "05:38",
"sunset": "17:38",
"timezone": -3,
"ref": "None"
},
"forecast": {
"precipitation": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
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0,
0,
0,
0,
0.1,
0.1,
0.1,
0,
0,
0,
0,
0,
0,
0,
0,
0.2,
0.4,
0.6,
0.8,
1.0,
1.0,
1.0,
0.8,
0.6,
0.4,
0.2,
0,
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],
"temperature": [
29.0,
32.0,
32.0,
30.9,
27.7,
24.2,
21.0,
18.5,
16.9,
16.3,
16.8,
18.1,
20.0,
22.3,
24.8,
27.1,
29.1,
30.4,
31.0,
30.9,
30.0,
28.7,
27.1,
25.5,
24.0,
22.8,
21.9,
21.4,
21.1,
21.0,
21.0,
21.0,
21.1,
21.3,
21.7,
22.2,
23.0,
24.0,
25.1,
26.2,
27.1,
27.8,
28.0,
27.8,
27.2,
26.2,
25.1,
24.0,
23.0,
22.1,
21.4,
20.9,
20.3,
19.7,
19.0,
18.3,
17.6,
17.2,
17.2,
17.8,
19.0,
20.8,
23.1,
25.6,
27.9,
29.8,
31.0,
31.4,
30.9,
29.7,
28.0,
26.0,
24.0,
22.2,
20.7,
19.6,
19.0,
18.8,
19.0,
19.5,
20.3,
21.3,
22.5,
23.7,
25.0,
26.3,
27.4,
28.4,
29.2,
29.8,
30.0,
29.9,
29.5,
28.7,
27.7,
26.4,
25.0,
23.5,
22.0,
20.7,
19.8,
19.1,
19.0,
19.3,
20.1,
21.1,
22.4,
23.7,
25.0,
26.1,
27.0,
27.6,
28.0,
28.1,
28.0,
27.7,
27.2,
26.6,
25.8,
25.0,
24.0,
23.0,
22.0,
21.0,
20.1,
19.5,
19.0,
18.9,
19.1,
19.7,
20.8,
22.2,
24.0,
25.9,
27.7,
29.2,
30.0,
30.0,
29.0,
27.1,
24.5,
21.6,
18.8,
16.5,
15.0,
15.0,
15.0,
15.8,
17.2,
18.7,
20.0,
20.9,
21.4,
21.7,
21.9,
22.3,
23.0,
24.1,
25.4,
26.9,
28.4,
29.4,
30.0,
29.9,
29.3,
28.2,
26.8,
25.3,
24.0,
22.9,
22.1,
21.5,
21.0,
20.5,
20.0,
19.4,
18.9,
18.5,
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394.0,
394.0,
394.0,
394.0,
394.0,
394.0,
406.9,
423.5,
441.5,
458.5,
472.0,
480.0,
481.6,
477.1,
467.8,
455.7,
442.8,
431.0,
421.6,
414.8,
410.2,
406.9,
404.0,
400.8,
397.0,
394.0,
394.0,
394.0,
394.8,
403.0,
415.5,
431.1,
447.9,
463.5,
475.8,
483.0,
484.1,
479.5,
470.1,
457.9,
444.6,
432.0,
421.4,
413.1,
407.0,
402.6,
399.1,
396.0,
394.0,
394.0,
394.0,
394.0,
396.0,
404.0,
415.3,
428.9,
443.3,
456.5,
466.9,
473.0,
474.2,
470.6,
463.2,
453.3,
442.4,
432.0,
422.9,
415.4,
409.4,
404.5,
400.1,
396.0,
394.0,
394.0,
394.0,
394.0,
396.7,
407.0,
421.2,
437.9,
455.4,
471.4,
483.8,
491.0,
492.1,
487.5,
478.3,
466.1,
452.7,
440.0,
429.0,
420.3,
413.8,
408.9,
405.1,
402.0,
399.4,
397.8,
398.0,
400.8,
407.0,
417.0,
430.3,
445.9,
462.1,
476.7,
488.0,
494.5,
495.4,
491.0,
482.3,
470.7,
457.9,
445.5,
434.4,
425.2,
417.6,
411.4,
406.1,
401.3,
397.0,
394.0,
394.0,
395.0,
401.0,
411.0,
424.8,
441.0,
457.7,
472.8,
484.2,
490.4,
490.6,
485.1,
475.4,
463.0,
449.9,
437.7,
427.5,
419.7,
413.7,
408.9,
404.5,
400.0,
395.3,
394.0,
394.0,
394.0,
394.2,
404.0,
418.4,
436.1,
455.1,
472.9,
487.1,
496.0,
498.5,
494.8,
486.1,
474.1,
460.8,
448.0,
436.8,
427.5,
419.9,
413.4,
407.3,
401.0,
394.7,
394.0,
394.0,
394.0,
394.0,
401.0,
416.1,
434.6,
454.4,
472.7,
486.9,
495.0,
496.2,
490.7,
479.9,
465.9,
450.9,
437.0,
425.4,
416.7,
410.4,
405.7,
401.8,
398.0,
394.1,
394.0,
394.0,
394.0,
396.5,
407.0,
422.0,
440.2,
459.5,
477.2,
490.9,
498.9,
500.0,
494.7,
484.3,
470.6,
455.7,
441.7,
429.7,
420.1,
412.8,
407.0,
401.9,
397.0,
394.0,
394.0,
394.0,
394.0,
395.3,
407.0,
423.4,
443.2,
463.9,
482.9,
497.6,
506.0,
506.0,
501.6,
490.6,
476.4,
461.1,
447.0,
435.3,
426.6,
420.5,
416.1,
412.5,
409.0,
405.4,
402.1,
400.2,
400.9,
405.3,
414.0,
426.8,
442.5,
459.2,
474.8,
487.0,
494.3,
495.6,
491.4,
482.6,
471.1,
458.7,
447.0,
437.3,
429.8,
424.6,
420.8,
417.8,
415.0,
412.2,
409.8,
408.5,
409.2,
412.8,
420.0,
430.7,
444.5,
460.0,
475.8,
490.1,
501.0,
506.0,
506.0,
499.9,
486.1,
466.5,
443.0,
419.1,
399.7,
394.0,
402.2,
443.0
],
"upward_short_wave_radiation": [
18.0,
0.0,
0.0,
0.0,
0.0,
0.0,
28.0,
58.2,
82.8,
99.9,
108.0,
108.0,
104.0,
92.6,
77.6,
60.9,
44.4,
29.7,
18.0,
9.8,
4.8,
2.4,
1.4,
0.8,
0.0,
0.0,
0.0,
0.0,
2.0,
9.3,
21.0,
36.7,
54.8,
73.0,
88.5,
98.8,
102.0,
97.6,
86.3,
70.1,
51.8,
33.9,
19.0,
8.4,
2.2,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
5.9,
17.0,
32.7,
51.5,
70.9,
87.8,
99.6,
104.0,
100.3,
89.3,
73.0,
54.2,
35.6,
20.0,
8.8,
2.2,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.0,
7.6,
19.0,
35.0,
54.0,
73.4,
90.3,
101.8,
106.0,
101.9,
90.5,
73.7,
54.5,
35.8,
20.0,
8.8,
2.4,
0.0,
0.0,
0.1,
0.0,
0.0,
0.0,
0.0,
0.0,
0.7,
10.0,
23.8,
40.8,
58.6,
74.4,
85.5,
90.0,
87.0,
77.1,
62.3,
45.1,
28.2,
14.0,
3.9,
0.0,
0.0,
0.0,
0.0,
0.0,
0.9,
1.5,
3.1,
7.0,
14.4,
26.0,
41.5,
59.4,
77.3,
92.7,
102.9,
106.0,
101.4,
89.9,
73.3,
54.4,
35.8,
20.0,
8.5,
1.6,
0.0,
0.0,
0.0,
0.0,
0.5,
0.9,
2.4,
6.2,
13.5,
25.0,
40.3,
58.0,
75.8,
90.9,
100.9,
104.0,
99.4,
88.1,
71.8,
53.3,
35.2,
20.0,
9.0,
2.5,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
1.6,
8.0,
19.0,
34.3,
52.3,
70.8,
86.9,
98.0,
102.0,
98.2,
87.4,
71.4,
52.9,
34.6,
19.0,
7.6,
0.7,
0.0,
0.0,
0.0,
0.0,
0.9,
1.9,
3.8,
8.0,
15.5,
27.0,
42.1,
59.5,
76.8,
91.5,
101.2,
104.0,
99.4,
88.0,
71.9,
53.4,
35.4,
20.0,
8.8,
1.9,
0.0,
0.0,
0.0,
0.0,
0.5,
1.0,
2.6,
6.7,
14.2,
26.0,
41.6,
59.5,
77.5,
92.8,
102.9,
106.0,
101.4,
89.9,
73.4,
54.5,
35.9,
20.0,
8.3,
1.2,
0.0,
0.0,
0.0,
0.0,
1.2,
2.5,
4.9,
9.7,
17.9,
30.0,
45.7,
63.6,
81.2,
96.0,
105.5,
108.0,
102.8,
90.8,
73.9,
54.7,
35.9,
20.0,
8.4,
1.4,
0.0,
0.0,
0.0,
0.0,
0.7,
1.4,
3.2,
7.4,
15.1,
27.0,
42.7,
60.6,
78.5,
93.5,
103.3,
106.0,
100.9,
89.0,
72.3,
53.4,
35.2,
20.0,
9.3,
3.2,
0.7,
0.4,
0.6,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
8.0,
22.0,
39.4,
57.8,
74.4,
86.5,
92.0,
90.0,
81.1,
67.0,
50.2,
33.4,
19.0,
8.4,
2.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.8,
5.0,
13.0,
24.9,
40.0,
57.1,
74.4,
89.7,
101.0,
106.3,
104.0,
93.5,
74.8,
49.1,
19.0,
0.0,
0.0,
0.0,
0.0,
19.0
],
"angstrom_index": [
1.35,
4.0,
3.6,
0.6,
3.15,
4.0,
3.83,
1.4,
3.55,
4.0,
3.7,
0.25,
2.85,
4.0,
3.2,
1.05,
3.2,
4.0,
3.5,
1.9,
3.4,
4.0,
3.6,
1.75,
4.0,
4.0,
3.8,
1.4,
3.35,
4.0,
3.95,
1.3,
3.15,
4.0,
3.75,
1.0,
2.8,
4.0,
3.6,
0.6,
2.85,
4.0,
3.75,
1.1,
3.0,
4.0,
3.85,
1.2,
3.0,
4.0,
3.8,
1.15,
2.9,
4.0,
3.85,
1.25
]
}
},
"meta": {
"updated_at": "2020-09-09 15:27",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
Use a specific latitude and longitude or city.
HTTP Request
GET https://nimbus.somar.io/forecast/hourly?latitude=<LAT>&longitude=<LON>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/hourly?city=<CITY>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| reference | Reference name |
Get hourly regional
This endpoint returns a 120hrs forecast(5 days), hour by hour
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/hourly/regional?city=SaoPaulo-SP', headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/hourly/regional?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/hourly/regional?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-09-10 00:00",
"2020-09-10 01:00",
"2020-09-10 02:00",
"2020-09-10 03:00",
"2020-09-10 04:00",
"2020-09-10 05:00",
"2020-09-10 06:00",
"2020-09-10 07:00",
"2020-09-10 08:00",
"2020-09-10 09:00",
"2020-09-10 10:00",
"2020-09-10 11:00",
"2020-09-10 12:00",
"2020-09-10 13:00",
"2020-09-10 14:00",
"2020-09-10 15:00",
"2020-09-10 16:00",
"2020-09-10 17:00",
"2020-09-10 18:00",
"2020-09-10 19:00",
"2020-09-10 20:00",
"2020-09-10 21:00",
"2020-09-10 22:00",
"2020-09-10 23:00",
"2020-09-11 00:00",
"2020-09-11 01:00",
"2020-09-11 02:00",
"2020-09-11 03:00",
"2020-09-11 04:00",
"2020-09-11 05:00",
"2020-09-11 06:00",
"2020-09-11 07:00",
"2020-09-11 08:00",
"2020-09-11 09:00",
"2020-09-11 10:00",
"2020-09-11 11:00",
"2020-09-11 12:00",
"2020-09-11 13:00",
"2020-09-11 14:00",
"2020-09-11 15:00",
"2020-09-11 16:00",
"2020-09-11 17:00",
"2020-09-11 18:00",
"2020-09-11 19:00",
"2020-09-11 20:00",
"2020-09-11 21:00",
"2020-09-11 22:00",
"2020-09-11 23:00",
"2020-09-12 00:00",
"2020-09-12 01:00",
"2020-09-12 02:00",
"2020-09-12 03:00",
"2020-09-12 04:00",
"2020-09-12 05:00",
"2020-09-12 06:00",
"2020-09-12 07:00",
"2020-09-12 08:00",
"2020-09-12 09:00",
"2020-09-12 10:00",
"2020-09-12 11:00",
"2020-09-12 12:00",
"2020-09-12 13:00",
"2020-09-12 14:00",
"2020-09-12 15:00",
"2020-09-12 16:00",
"2020-09-12 17:00",
"2020-09-12 18:00",
"2020-09-12 19:00",
"2020-09-12 20:00",
"2020-09-12 21:00",
"2020-09-12 22:00",
"2020-09-12 23:00",
"2020-09-13 00:00",
"2020-09-13 01:00",
"2020-09-13 02:00",
"2020-09-13 03:00",
"2020-09-13 04:00",
"2020-09-13 05:00",
"2020-09-13 06:00",
"2020-09-13 07:00",
"2020-09-13 08:00",
"2020-09-13 09:00",
"2020-09-13 10:00",
"2020-09-13 11:00",
"2020-09-13 12:00",
"2020-09-13 13:00",
"2020-09-13 14:00",
"2020-09-13 15:00",
"2020-09-13 16:00",
"2020-09-13 17:00",
"2020-09-13 18:00",
"2020-09-13 19:00",
"2020-09-13 20:00",
"2020-09-13 21:00",
"2020-09-13 22:00",
"2020-09-13 23:00",
"2020-09-14 00:00",
"2020-09-14 01:00",
"2020-09-14 02:00",
"2020-09-14 03:00",
"2020-09-14 04:00",
"2020-09-14 05:00",
"2020-09-14 06:00",
"2020-09-14 07:00",
"2020-09-14 08:00",
"2020-09-14 09:00",
"2020-09-14 10:00",
"2020-09-14 11:00",
"2020-09-14 12:00",
"2020-09-14 13:00",
"2020-09-14 14:00",
"2020-09-14 15:00",
"2020-09-14 16:00",
"2020-09-14 17:00",
"2020-09-14 18:00",
"2020-09-14 19:00",
"2020-09-14 20:00",
"2020-09-14 21:00",
"2020-09-14 22:00",
"2020-09-14 23:00"
],
"points": {
"location": {
"latitude": -23.6412819,
"longitude": -46.4896739,
"elevation": 754,
"sunrise": "06:07",
"sunset": "17:58",
"timezone": -3,
"ref": "None"
},
"forecast": {
"precipitation": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0.05,
0.2,
0.09,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"temperature": [
20.48,
20.66,
21.0,
20.75,
20.53,
20.04,
19.8,
19.7,
19.58,
19.59,
20.47,
22.72,
25.53,
28.23,
29.87,
31.12,
31.83,
32.22,
32.24,
31.63,
30.26,
28.2,
26.84,
25.92,
25.27,
23.77,
21.67,
21.01,
20.09,
19.12,
18.36,
17.83,
17.45,
17.22,
17.64,
19.21,
22.02,
24.54,
26.46,
27.89,
28.42,
28.33,
28.17,
27.42,
25.71,
23.96,
23.14,
22.74,
22.47,
22.24,
22.34,
22.63,
22.36,
21.8,
21.4,
21.16,
21.11,
21.18,
21.78,
23.84,
26.44,
28.68,
30.06,
31.07,
31.81,
32.37,
32.5,
31.43,
29.69,
28.39,
27.65,
26.96,
26.19,
25.56,
24.98,
24.35,
23.62,
23.18,
22.65,
22.14,
21.69,
21.31,
21.84,
23.29,
25.48,
27.28,
28.75,
29.94,
30.89,
31.45,
31.24,
30.23,
28.89,
27.24,
26.25,
25.64,
25.11,
24.39,
23.83,
23.19,
22.82,
22.55,
22.08,
21.56,
21.05,
20.68,
21.11,
22.7,
24.84,
26.42,
27.6,
28.49,
29.16,
28.45,
25.68,
23.52,
21.73,
20.0,
18.87,
17.95
],
"rel_humidity": [
74.8,
72.5,
73.81,
76.49,
76.07,
77.96,
78.1,
75.65,
73.93,
69.88,
62.47,
51.83,
42.61,
33.9,
28.36,
23.77,
21.53,
20.06,
20.0,
23.36,
30.95,
42.19,
47.71,
48.45,
46.53,
54.17,
66.45,
65.21,
70.28,
77.98,
83.63,
86.77,
88.47,
89.48,
87.0,
77.68,
60.88,
47.65,
41.21,
38.92,
42.17,
47.14,
49.75,
54.19,
62.1,
67.12,
66.53,
65.39,
65.53,
65.23,
62.42,
59.66,
59.73,
61.41,
61.74,
60.22,
57.82,
55.09,
51.08,
44.07,
36.99,
31.75,
28.17,
25.1,
22.6,
20.89,
20.89,
27.76,
36.91,
38.5,
38.55,
39.91,
41.28,
39.56,
38.18,
36.78,
37.29,
35.89,
35.23,
35.68,
36.92,
38.25,
38.54,
36.85,
32.58,
29.18,
25.46,
21.25,
18.41,
18.35,
23.2,
29.68,
32.17,
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],
"indexTT": [
48.35,
49.2,
48.76,
47.61,
46.97,
45.41,
44.5,
44.55,
45.18,
45.21,
45.09,
45.35,
45.07,
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48.17,
48.4,
48.3,
48.28,
48.94,
49.02,
48.68,
48.15,
47.55,
47.34,
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46.99,
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45.75,
45.14,
44.38,
44.4,
44.33,
44.36,
44.4,
46.0,
47.96,
48.93,
49.21,
49.43,
48.52,
47.26,
47.22,
48.69,
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47.19,
46.96,
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46.25,
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47.39,
46.93,
46.52,
46.72,
46.48,
47.35,
48.17,
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51.81,
51.65,
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44.46,
43.71,
43.23,
43.33,
42.71,
42.0,
41.62,
41.01,
39.69,
39.18,
40.6,
40.73,
40.9,
42.32,
44.71,
45.42,
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42.92,
42.2,
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39.8,
38.8,
37.41,
36.14,
37.0,
37.23,
36.93,
36.78,
36.85,
36.18,
35.78,
36.09,
37.57,
38.24,
38.85,
40.55,
42.94,
41.15,
39.0,
37.25,
35.15,
35.16,
33.93
],
"indexCAPE": [
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1.8,
8.31,
35.98,
45.06,
26.26,
22.76,
15.82,
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0.0,
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2.34,
11.0,
23.51,
32.59,
36.1,
43.25,
43.13,
66.31,
181.63,
326.65,
328.41,
222.89,
98.34,
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59.83,
214.2,
372.5,
458.3,
491.01,
439.08,
291.98,
153.07,
82.05,
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34.58,
25.31,
21.47,
18.15,
3.63,
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0.0,
0.0,
0.0,
0.01,
0.1,
1.1,
5.66,
15.53,
31.1,
51.41,
68.98,
87.51,
194.13,
342.69,
225.88,
117.28,
85.49,
51.96,
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22.52,
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2.35,
1.94,
0.93,
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"thunderstorm_alert": [
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"hail_storm": [
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"angstrom_index": [
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]
}
},
"meta": {
"updated_at": "2020-09-10 00:28",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"frost": [
"Low chances",
"High chances",
"Snow"
],
"lightning": "%",
"radiation": "w/m²",
"visibility": "m",
"weather_condition": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"thunderstorm_alert": [
"Ok",
"Atention",
"Alert"
],
"hail_storm": [
"Ok",
"Moderate",
"Atention",
"Alert"
]
}
}
}
Regional models are a category of models that work with a limited area, thus allowing a higher resolution, as well much more representative parameters for each region. (Check with your plan covers this model)
HTTP Request
GET https://nimbus.somar.io/forecast/hourly/regional?model=<MODEL>&latitude=<LAT>&longitude=<LON>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/hourly/regional?model=<MODEL>&city=<CITY>&reference=<REFERENCE>
Query Parameters
| Parameter | Default | Description |
|---|---|---|
| latitude | Latitude | |
| longitude | Longitude | |
| city | City | |
| model | wrf | The desired model nomenclature |
| reference | Reference name |
Models
| Model | Description |
|---|---|
| wrf | WRF (Weather Research and Forecast) model is the state of the art model for high resolution and high accuracy forecasts. |
Forecast
Get daily
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/daily?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/daily?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/daily?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00",
"2020-05-26 00:00",
"2020-05-27 00:00",
"2020-05-28 00:00",
"2020-05-29 00:00",
"2020-05-30 00:00",
"2020-05-31 00:00",
"2020-06-01 00:00",
"2020-06-02 00:00"
],
"days": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00",
"2020-05-26 00:00",
"2020-05-27 00:00",
"2020-05-28 00:00",
"2020-05-29 00:00",
"2020-05-30 00:00",
"2020-05-31 00:00",
"2020-06-01 00:00",
"2020-06-02 00:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"precipitation_daily_acu": [
0,
0,
0,
2.0,
6.0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"precipitation_daily_max": [
0,
0,
0,
2.0,
6.0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"precipitation_daily_min": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"temperature_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.0,
12.25,
13.25,
14.25,
14.75,
15.0,
14.25,
14.25,
14.333333015441895
],
"temperature_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0,
22.0,
23.0,
23.0,
22.0,
22.0,
21.0,
21.0,
20.0
],
"temperature_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0,
8.0,
9.0,
10.0,
11.0,
12.0,
11.0,
11.0,
11.0
],
"rel_humidity_daily_avg": [
64.75,
66.25,
57.25,
78.0,
82.0,
75.75,
76.25,
75.25,
78.0,
82.5,
84.75,
84.0,
85.5,
85.25,
82.33333587646484
],
"rel_humidity_daily_max": [
81.0,
82.0,
74.0,
92.0,
91.0,
87.0,
90.0,
89.0,
92.0,
94.0,
95.0,
94.0,
95.0,
94.0,
94.0
],
"rel_humidity_daily_min": [
30.0,
43.0,
25.0,
53.0,
66.0,
55.0,
57.0,
56.0,
56.0,
62.0,
66.0,
64.0,
67.0,
69.0,
69.0
],
"wind_speed_daily_avg": [
3.132499933242798,
1.5625,
3.6075000762939453,
6.372499942779541,
6.554999828338623,
5.482500076293945,
3.747499942779541,
1.4900000095367432,
1.8875000476837158,
2.677500009536743,
2.9724998474121094,
5.164999961853027,
3.690000057220459,
1.5299999713897705,
2.8999998569488525
],
"wind_speed_daily_max": [
3.890000104904175,
3.0,
4.019999980926514,
7.230000019073486,
8.229999542236328,
6.849999904632568,
5.360000133514404,
2.109999895095825,
2.690000057220459,
4.53000020980835,
4.449999809265137,
5.769999980926514,
4.46999979019165,
2.9000000953674316,
3.7699999809265137
],
"wind_speed_daily_min": [
2.490000009536743,
0.800000011920929,
3.259999990463257,
5.369999885559082,
4.889999866485596,
3.7300000190734863,
2.2300000190734863,
0.4399999976158142,
1.2599999904632568,
1.6399999856948853,
1.1200000047683716,
4.519999980926514,
2.5799999237060547,
0.4300000071525574,
2.0999999046325684
],
"wind_direction_daily_avg": [
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"wind_direction_daily_max": [
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"wind_direction_daily_min": [
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7,
336,
4,
353,
340,
325,
340,
342,
294,
307,
310,
307,
320,
307,
304,
307,
323,
298,
315,
338,
328,
166,
83,
81,
43,
0,
7,
345,
337,
311,
350,
340,
332,
302,
309,
169,
152,
153,
137,
145,
114,
124,
109,
94,
86,
322,
125,
356,
336,
289,
138,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"wind_gust_daily_avg": [
3.384999990463257,
1.9850000143051147,
4.122499942779541,
7.950000286102295,
6.684999942779541,
6.150000095367432,
4.342499732971191,
1.8200000524520874,
2.4574999809265137,
3.3650002479553223,
3.3324999809265137,
5.164999961853027,
3.8500001430511475,
2.247499942779541,
3.116666793823242
],
"wind_gust_daily_max": [
3.890000104904175,
3.0,
5.590000152587891,
9.319999694824219,
8.229999542236328,
6.849999904632568,
5.440000057220459,
2.5999999046325684,
3.259999990463257,
4.730000019073486,
4.510000228881836,
5.769999980926514,
4.46999979019165,
2.9000000953674316,
3.7699999809265137
],
"wind_gust_daily_min": [
2.7100000381469727,
1.5800000429153442,
3.259999990463257,
5.570000171661377,
5.409999847412109,
4.730000019073486,
2.7200000286102295,
1.2699999809265137,
1.2599999904632568,
2.2699999809265137,
1.9199999570846558,
4.519999980926514,
3.2200000286102295,
1.590000033378601,
2.75
],
"pressure_daily_avg": [
1023.25,
1022.25,
1020.5,
1016.0,
1014.75,
1019.25,
1018.75,
1018.25,
1018.5,
1019.25,
1019.75,
1019.5,
1019.75,
1019.25,
1019.0
],
"pressure_daily_max": [
1025.0,
1024.0,
1023.0,
1018.0,
1018.0,
1021.0,
1021.0,
1020.0,
1020.0,
1021.0,
1022.0,
1021.0,
1021.0,
1021.0,
1021.0
],
"pressure_daily_min": [
1021.0,
1020.0,
1018.0,
1014.0,
1012.0,
1017.0,
1016.0,
1016.0,
1017.0,
1017.0,
1018.0,
1018.0,
1018.0,
1017.0,
1017.0
],
"weather_conditions_daily_avg": [
0,
0,
0,
3,
3,
0,
0,
0,
0,
0,
2,
2,
2,
2,
1
],
"atmospheric_conditions_daily_avg": [
1,
1,
0,
2,
0,
0,
0,
0,
0,
0,
1,
0,
0,
1,
2
],
"thermal_sensation_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.0,
12.25,
13.25,
14.25,
14.75,
15.0,
14.25,
14.25,
14.333333015441895
],
"thermal_sensation_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0,
22.0,
23.0,
23.0,
22.0,
22.0,
21.0,
21.0,
20.0
],
"thermal_sensation_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0,
8.0,
9.0,
10.0,
11.0,
12.0,
11.0,
11.0,
11.0
],
"thunderstorm_alerts_daily_avg": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"frost_alert_daily_avg": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"etp": [
3.299999952316284,
3.5999999046325684,
3.5,
2.799999952316284,
1.7999999523162842,
1.2999999523162842,
1.600000023841858,
3.0,
3.700000047683716,
3.4000000953674316,
3.200000047683716,
1.100000023841858,
1.7000000476837158,
3.0,
3.4000000953674316
],
"downward_long_wave_radiation": [
1280.0,
1407.0,
1290.0,
1473.0,
1297.0,
1102.0,
1143.0,
1209.0,
1216.0,
1239.0,
1360.0,
1468.0,
1224.0,
1407.0,
1048.0
],
"downward_short_wave_radiation": [
815.0,
654.0,
801.0,
494.0,
413.0,
806.0,
796.0,
789.0,
790.0,
792.0,
717.0,
73.0,
680.0,
553.0,
722.0
],
"upward_long_wave_radiation": [
1662.85302734375,
1697.2266845703125,
1687.38916015625,
1679.5181884765625,
1587.0,
1524.0,
1546.0,
1623.96044921875,
1662.0,
1663.167724609375,
1680.23681640625,
1563.275390625,
1568.5230712890625,
1637.14453125,
1277.37109375
],
"upward_short_wave_radiation": [
98.0,
78.0,
97.0,
57.0,
50.0,
98.0,
97.0,
96.0,
96.0,
97.0,
87.0,
8.0,
82.0,
63.0,
86.0
]
}
},
"meta": {
"updated_at": "2020-05-19 19:29",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
Get a daily forecast for a specific latitude and longitude or city.
HTTP Request
GET https://nimbus.somar.io/forecast/daily?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/daily?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name |
Get 7 days
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/7days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/7days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/7days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00"
]
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"precipitation_daily_acu": [
0,
0,
0,
2.0,
6.0,
0,
0
],
"precipitation_daily_max": [
0,
0,
0,
2.0,
6.0,
0,
0
],
"precipitation_daily_min": [
0,
0,
0,
0,
0,
0,
0
],
"temperature_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.333333015441895
],
"temperature_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0
],
"temperature_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0
],
"rel_humidity_daily_avg": [
64.75,
66.25,
57.25,
78.0,
82.0,
75.75,
73.33333587646484
],
"rel_humidity_daily_max": [
81.0,
82.0,
74.0,
92.0,
91.0,
87.0,
90.0
],
"rel_humidity_daily_min": [
30.0,
43.0,
25.0,
53.0,
66.0,
55.0,
57.0
],
"wind_speed_daily_avg": [
3.132499933242798,
1.5625,
3.6075000762939453,
6.372499942779541,
6.554999828338623,
5.482500076293945,
4.253333568572998
],
"wind_speed_daily_max": [
3.890000104904175,
3.0,
4.019999980926514,
7.230000019073486,
8.229999542236328,
6.849999904632568,
5.360000133514404
],
"wind_speed_daily_min": [
2.490000009536743,
0.800000011920929,
3.259999990463257,
5.369999885559082,
4.889999866485596,
3.7300000190734863,
2.869999885559082
],
"wind_direction_daily_avg": [
133,
93,
88,
119,
70,
63,
351
],
"wind_direction_daily_max": [
133,
93,
88,
119,
70,
63,
351
],
"wind_direction_daily_min": [
133,
93,
88,
119,
70,
63,
351
],
"wind_gust_daily_avg": [
3.384999990463257,
1.9850000143051147,
4.122499942779541,
7.950000286102295,
6.684999942779541,
6.150000095367432,
4.883333206176758
],
"wind_gust_daily_max": [
3.890000104904175,
3.0,
5.590000152587891,
9.319999694824219,
8.229999542236328,
6.849999904632568,
5.440000057220459
],
"wind_gust_daily_min": [
2.7100000381469727,
1.5800000429153442,
3.259999990463257,
5.570000171661377,
5.409999847412109,
4.730000019073486,
3.8499999046325684
],
"pressure_daily_avg": [
1023.25,
1022.25,
1020.5,
1016.0,
1014.75,
1019.25,
1018.6666870117188
],
"pressure_daily_max": [
1025.0,
1024.0,
1023.0,
1018.0,
1018.0,
1021.0,
1021.0
],
"pressure_daily_min": [
1021.0,
1020.0,
1018.0,
1014.0,
1012.0,
1017.0,
1016.0
],
"weather_conditions_daily_avg": [
0,
0,
0,
3,
3,
0,
0
],
"atmospheric_conditions_daily_avg": [
1,
1,
0,
2,
0,
0,
0
],
"thermal_sensation_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.333333015441895
],
"thermal_sensation_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0
],
"thermal_sensation_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0
],
"thunderstorm_alerts_daily_avg": [
0,
0,
0,
0,
0,
0,
0
],
"frost_alert_daily_avg": [
0,
0,
0,
0,
0,
0,
0
],
"etp": [
3.299999952316284,
3.5999999046325684,
3.5,
2.799999952316284,
1.7999999523162842,
1.2999999523162842,
1.600000023841858
],
"downward_long_wave_radiation": [
1280.0,
1407.0,
1290.0,
1473.0,
1297.0,
1102.0,
854.0
],
"downward_short_wave_radiation": [
815.0,
654.0,
801.0,
494.0,
413.0,
806.0,
796.0
],
"upward_long_wave_radiation": [
1662.85302734375,
1697.2266845703125,
1687.38916015625,
1679.5181884765625,
1587.0,
1524.0,
1168.0
],
"upward_short_wave_radiation": [
98.0,
78.0,
97.0,
57.0,
50.0,
98.0,
97.0
]
}
},
"meta": {
"updated_at": "2020-05-19 19:29",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
You can retrieve weather forecast for 7 days based in your plan. This endpoint only accepts queries per city.
HTTP Request
GET https://nimbus.somar.io/forecast/7days?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| city | City |
| reference | Reference name |
Get 10 days
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/10days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/10days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/10days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00",
"2020-05-26 00:00",
"2020-05-27 00:00",
"2020-05-28 00:00"
],
"days": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00",
"2020-05-26 00:00",
"2020-05-27 00:00",
"2020-05-28 00:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"precipitation_daily_acu": [
0,
0,
0,
2.0,
6.0,
0,
0,
0,
0,
0
],
"precipitation_daily_max": [
0,
0,
0,
2.0,
6.0,
0,
0,
0,
0,
0
],
"precipitation_daily_min": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"temperature_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.0,
12.25,
13.25,
14.666666984558105
],
"temperature_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0,
22.0,
23.0,
23.0
],
"temperature_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0,
8.0,
9.0,
10.0
],
"rel_humidity_daily_avg": [
64.75,
66.25,
57.25,
78.0,
82.0,
75.75,
76.25,
75.25,
78.0,
78.66666412353516
],
"rel_humidity_daily_max": [
81.0,
82.0,
74.0,
92.0,
91.0,
87.0,
90.0,
89.0,
92.0,
93.0
],
"rel_humidity_daily_min": [
30.0,
43.0,
25.0,
53.0,
66.0,
55.0,
57.0,
56.0,
56.0,
62.0
],
"wind_speed_daily_avg": [
3.132499933242798,
1.5625,
3.6075000762939453,
6.372499942779541,
6.554999828338623,
5.482500076293945,
3.747499942779541,
1.4900000095367432,
1.8875000476837158,
3.0233333110809326
],
"wind_speed_daily_max": [
3.890000104904175,
3.0,
4.019999980926514,
7.230000019073486,
8.229999542236328,
6.849999904632568,
5.360000133514404,
2.109999895095825,
2.690000057220459,
4.53000020980835
],
"wind_speed_daily_min": [
2.490000009536743,
0.800000011920929,
3.259999990463257,
5.369999885559082,
4.889999866485596,
3.7300000190734863,
2.2300000190734863,
0.4399999976158142,
1.2599999904632568,
1.9800000190734863
],
"wind_direction_daily_avg": [
133,
93,
88,
119,
70,
63,
351,
58,
3,
7
],
"wind_direction_daily_max": [
133,
93,
88,
119,
70,
63,
351,
58,
3,
7
],
"wind_direction_daily_min": [
133,
93,
88,
119,
70,
63,
351,
58,
3
],
"wind_gust_daily_avg": [
3.384999990463257,
1.9850000143051147,
4.122499942779541,
7.950000286102295,
6.684999942779541,
6.150000095367432,
4.342499732971191,
1.8200000524520874,
2.4574999809265137,
3.7100002765655518
],
"wind_gust_daily_max": [
3.890000104904175,
3.0,
5.590000152587891,
9.319999694824219,
8.229999542236328,
6.849999904632568,
5.440000057220459,
2.5999999046325684,
3.259999990463257,
4.730000019073486
],
"wind_gust_daily_min": [
2.7100000381469727,
1.5800000429153442,
3.259999990463257,
5.570000171661377,
5.409999847412109,
4.730000019073486,
2.7200000286102295,
1.2699999809265137,
1.2599999904632568,
2.2699999809265137
],
"pressure_daily_avg": [
1023.25,
1022.25,
1020.5,
1016.0,
1014.75,
1019.25,
1018.75,
1018.25,
1018.5,
1019.0
],
"pressure_daily_max": [
1025.0,
1024.0,
1023.0,
1018.0,
1018.0,
1021.0,
1021.0,
1020.0,
1020.0,
1021.0
],
"pressure_daily_min": [
1021.0,
1020.0,
1018.0,
1014.0,
1012.0,
1017.0,
1016.0,
1016.0,
1017.0,
1017.0
],
"weather_conditions_daily_avg": [
0,
0,
0,
3,
3,
0,
0,
0,
0,
0
],
"atmospheric_conditions_daily_avg": [
1,
1,
0,
2,
0,
0,
0,
0,
0,
0
],
"thermal_sensation_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.0,
12.25,
13.25,
14.666666984558105
],
"thermal_sensation_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0,
22.0,
23.0,
23.0
],
"thermal_sensation_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0,
8.0,
9.0,
10.0
],
"thunderstorm_alerts_daily_avg": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"frost_alert_daily_avg": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"etp": [
3.299999952316284,
3.5999999046325684,
3.5,
2.799999952316284,
1.7999999523162842,
1.2999999523162842,
1.600000023841858,
3.0,
3.700000047683716,
3.4000000953674316
],
"downward_long_wave_radiation": [
1280.0,
1407.0,
1290.0,
1473.0,
1297.0,
1102.0,
1143.0,
1209.0,
1216.0,
927.0
],
"downward_short_wave_radiation": [
815.0,
654.0,
801.0,
494.0,
413.0,
806.0,
796.0,
789.0,
790.0,
792.0
],
"upward_long_wave_radiation": [
1662.85302734375,
1697.2266845703125,
1687.38916015625,
1679.5181884765625,
1587.0,
1524.0,
1546.0,
1623.96044921875,
1662.0,
1261.167724609375
],
"upward_short_wave_radiation": [
98.0,
78.0,
97.0,
57.0,
50.0,
98.0,
97.0,
96.0,
96.0,
97.0
]
}
},
"meta": {
"updated_at": "2020-05-19 19:29",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
You can retrieve a weather forecast for 10 days based on your plan.
HTTP Request
GET https://nimbus.somar.io/forecast/10days?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/10days?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| periods | Boolean |
| reference | Reference name |
Get 15 days
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/15days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/15days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/15days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00",
"2020-05-26 00:00",
"2020-05-27 00:00",
"2020-05-28 00:00",
"2020-05-29 00:00",
"2020-05-30 00:00",
"2020-05-31 00:00",
"2020-06-01 00:00",
"2020-06-02 00:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"precipitation_daily_acu": [
0,
0,
0,
2.0,
6.0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"precipitation_daily_max": [
0,
0,
0,
2.0,
6.0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"precipitation_daily_min": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"temperature_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.0,
12.25,
13.25,
14.25,
14.75,
15.0,
14.25,
14.25,
14.333333015441895
],
"temperature_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0,
22.0,
23.0,
23.0,
22.0,
22.0,
21.0,
21.0,
20.0
],
"temperature_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0,
8.0,
9.0,
10.0,
11.0,
12.0,
11.0,
11.0,
11.0
],
"rel_humidity_daily_avg": [
64.75,
66.25,
57.25,
78.0,
82.0,
75.75,
76.25,
75.25,
78.0,
82.5,
84.75,
84.0,
85.5,
85.25,
82.33333587646484
],
"rel_humidity_daily_max": [
81.0,
82.0,
74.0,
92.0,
91.0,
87.0,
90.0,
89.0,
92.0,
94.0,
95.0,
94.0,
95.0,
94.0,
94.0
],
"rel_humidity_daily_min": [
30.0,
43.0,
25.0,
53.0,
66.0,
55.0,
57.0,
56.0,
56.0,
62.0,
66.0,
64.0,
67.0,
69.0,
69.0
],
"wind_speed_daily_avg": [
3.132499933242798,
1.5625,
3.6075000762939453,
6.372499942779541,
6.554999828338623,
5.482500076293945,
3.747499942779541,
1.4900000095367432,
1.8875000476837158,
2.677500009536743,
2.9724998474121094,
5.164999961853027,
3.690000057220459,
1.5299999713897705,
2.8999998569488525
],
"wind_speed_daily_max": [
3.890000104904175,
3.0,
4.019999980926514,
7.230000019073486,
8.229999542236328,
6.849999904632568,
5.360000133514404,
2.109999895095825,
2.690000057220459,
4.53000020980835,
4.449999809265137,
5.769999980926514,
4.46999979019165,
2.9000000953674316,
3.7699999809265137
],
"wind_speed_daily_min": [
2.490000009536743,
0.800000011920929,
3.259999990463257,
5.369999885559082,
4.889999866485596,
3.7300000190734863,
2.2300000190734863,
0.4399999976158142,
1.2599999904632568,
1.6399999856948853,
1.1200000047683716,
4.519999980926514,
2.5799999237060547,
0.4300000071525574,
2.0999999046325684
],
"wind_direction_daily_avg": [
133,
93,
88,
119,
70,
63,
351,
58,
3,
7,
336,
4,
353,
340
],
"wind_direction_daily_max": [
133,
93,
88,
119,
70,
63,
351,
58,
3,
7,
336,
4,
353,
340
], ],
"wind_direction_daily_min": [
133,
93,
88,
119,
70,
63,
351,
58,
3,
7,
336,
4,
353,
340,
325
],
"wind_gust_daily_avg": [
3.384999990463257,
1.9850000143051147,
4.122499942779541,
7.950000286102295,
6.684999942779541,
6.150000095367432,
4.342499732971191,
1.8200000524520874,
2.4574999809265137,
3.3650002479553223,
3.3324999809265137,
5.164999961853027,
3.8500001430511475,
2.247499942779541,
3.116666793823242
],
"wind_gust_daily_max": [
3.890000104904175,
3.0,
5.590000152587891,
9.319999694824219,
8.229999542236328,
6.849999904632568,
5.440000057220459,
2.5999999046325684,
3.259999990463257,
4.730000019073486,
4.510000228881836,
5.769999980926514,
4.46999979019165,
2.9000000953674316,
3.7699999809265137
],
"wind_gust_daily_min": [
2.7100000381469727,
1.5800000429153442,
3.259999990463257,
5.570000171661377,
5.409999847412109,
4.730000019073486,
2.7200000286102295,
1.2699999809265137,
1.2599999904632568,
2.2699999809265137,
1.9199999570846558,
4.519999980926514,
3.2200000286102295,
1.590000033378601,
2.75
],
"pressure_daily_avg": [
1023.25,
1022.25,
1020.5,
1016.0,
1014.75,
1019.25,
1018.75,
1018.25,
1018.5,
1019.25,
1019.75,
1019.5,
1019.75,
1019.25,
1019.0
],
"pressure_daily_max": [
1025.0,
1024.0,
1023.0,
1018.0,
1018.0,
1021.0,
1021.0,
1020.0,
1020.0,
1021.0,
1022.0,
1021.0,
1021.0,
1021.0,
1021.0
],
"pressure_daily_min": [
1021.0,
1020.0,
1018.0,
1014.0,
1012.0,
1017.0,
1016.0,
1016.0,
1017.0,
1017.0,
1018.0,
1018.0,
1018.0,
1017.0,
1017.0
],
"weather_conditions_daily_avg": [
0,
0,
0,
3,
3,
0,
0,
0,
0,
0,
2,
2,
2,
2,
1
],
"atmospheric_conditions_daily_avg": [
1,
1,
0,
2,
0,
0,
0,
0,
0,
0,
1,
0,
0,
1,
2
],
"thermal_sensation_daily_avg": [
18.25,
17.75,
18.75,
19.75,
17.5,
13.0,
10.0,
12.25,
13.25,
14.25,
14.75,
15.0,
14.25,
14.25,
14.333333015441895
],
"thermal_sensation_daily_max": [
24.0,
25.0,
27.0,
25.0,
23.0,
20.0,
19.0,
22.0,
23.0,
23.0,
22.0,
22.0,
21.0,
21.0,
20.0
],
"thermal_sensation_daily_min": [
15.0,
12.0,
13.0,
14.0,
13.0,
7.0,
6.0,
8.0,
9.0,
10.0,
11.0,
12.0,
11.0,
11.0,
11.0
],
"thunderstorm_alerts_daily_avg": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"frost_alert_daily_avg": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"etp": [
3.299999952316284,
3.5999999046325684,
3.5,
2.799999952316284,
1.7999999523162842,
1.2999999523162842,
1.600000023841858,
3.0,
3.700000047683716,
3.4000000953674316,
3.200000047683716,
1.100000023841858,
1.7000000476837158,
3.0,
3.4000000953674316
],
"downward_long_wave_radiation": [
1280.0,
1407.0,
1290.0,
1473.0,
1297.0,
1102.0,
1143.0,
1209.0,
1216.0,
1239.0,
1360.0,
1468.0,
1224.0,
1407.0,
1048.0
],
"downward_short_wave_radiation": [
815.0,
654.0,
801.0,
494.0,
413.0,
806.0,
796.0,
789.0,
790.0,
792.0,
717.0,
73.0,
680.0,
553.0,
722.0
],
"upward_long_wave_radiation": [
1662.85302734375,
1697.2266845703125,
1687.38916015625,
1679.5181884765625,
1587.0,
1524.0,
1546.0,
1623.96044921875,
1662.0,
1663.167724609375,
1680.23681640625,
1563.275390625,
1568.5230712890625,
1637.14453125,
1277.37109375
],
"upward_short_wave_radiation": [
98.0,
78.0,
97.0,
57.0,
50.0,
98.0,
97.0,
96.0,
96.0,
97.0,
87.0,
8.0,
82.0,
63.0,
86.0
]
}
},
"meta": {
"updated_at": "2020-05-19 19:29",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
You can retrieve a weather forecast for 15 days based on your plan.
HTTP Request
GET https://nimbus.somar.io/forecast/15days?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/15days?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| periods | Boolean |
| reference | Reference name |
Sub-seasonal forecast
Get monthly
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/monthly?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/monthly?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/monthly?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
{
"initi": "2020-05-19 06:00",
"final": "2020-06-17 06:00"
},
{
"initi": "2020-06-18 06:00",
"final": "2020-07-17 06:00"
},
{
"initi": "2020-07-18 06:00",
"final": "2020-08-16 06:00"
}
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"monthly_max_temperature": [
19.893114058176675,
21.10474770863851,
22.778021176656086
],
"monthly_min_temperature": [
14.535126145680746,
13.430932474136352,
14.411373710632324
],
"monthly_thermal_amplitude": [
5.357987912495931,
7.673815234502157,
8.366647466023762
],
"monthly_temperature": [
16.989828936258952,
16.66848478317261,
18.010067049662272
],
"monthly_accumulated_precipitation": [
279.1913823187351,
7.909672245383263,
14.272454112768173
],
"monthly_accumulated_etp": [
64.8395437002182,
64.4661077260971,
67.94933533668518
]
}
},
"meta": {
"updated_at": "2020-05-19 09:08",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"etp": "mm"
}
}
}
Get a monthly forecast for a specific latitude and longitude or city.
HTTP Request
GET https://nimbus.somar.io/forecast/monthly?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/monthly?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name |
Get 30 days
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/30days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/30days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/30days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 06:00",
"2020-05-20 06:00",
"2020-05-21 06:00",
"2020-05-22 06:00",
"2020-05-23 06:00",
"2020-05-24 06:00",
"2020-05-25 06:00",
"2020-05-26 06:00",
"2020-05-27 06:00",
"2020-05-28 06:00",
"2020-05-29 06:00",
"2020-05-30 06:00",
"2020-05-31 06:00",
"2020-06-01 06:00",
"2020-06-02 06:00",
"2020-06-03 06:00",
"2020-06-04 06:00",
"2020-06-05 06:00",
"2020-06-06 06:00",
"2020-06-07 06:00",
"2020-06-08 06:00",
"2020-06-09 06:00",
"2020-06-10 06:00",
"2020-06-11 06:00",
"2020-06-12 06:00",
"2020-06-13 06:00",
"2020-06-14 06:00",
"2020-06-15 06:00",
"2020-06-16 06:00",
"2020-06-17 06:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"precipitation": [
0.056767433881759644,
0,
0,
0.4399683475494385,
15.844732284545898,
44.89187240600586,
1.5000615119934082,
0.08085183054208755,
0,
0,
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],
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"wind_direction": [
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"pressure": [
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],
"weather_conditions": [
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1,
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],
"thunderstorm_alerts": [
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1,
0,
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],
"thermal_sensation": [
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],
"max_sensation": [
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24.01731703016493,
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"min_sensation": [
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"frost_alert": [
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],
"etp": [
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2.3653812408447266,
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2.06573748588562,
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1.9414364099502563,
1.9414364099502563
],
"downward_long_wave_radiation": [
1402.908935546875,
1370.7249755859375,
1365.805419921875,
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1303.618896484375,
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],
"downward_short_wave_radiation": [
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334.5498352050781,
116.18775177001953,
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356.212158203125,
565.3316650390625,
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],
"upward_long_wave_radiation": [
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1552.488525390625,
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],
"upward_short_wave_radiation": [
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130.09609985351562,
126.432373046875,
126.62202453613281,
51.088417053222656,
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136.7119903564453,
133.0154266357422,
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96.1532211303711,
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]
}
},
"meta": {
"updated_at": "2020-05-19 09:08",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"prec_prob": "%",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
You can search weather forecast for until 30 days based in plan that you using.
HTTP Request
GET https://nimbus.somar.io/forecast/30days?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/30days?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name |
Get 45 days
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/45days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/45days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/45days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 06:00",
"2020-05-20 06:00",
"2020-05-21 06:00",
"2020-05-22 06:00",
"2020-05-23 06:00",
"2020-05-24 06:00",
"2020-05-25 06:00",
"2020-05-26 06:00",
"2020-05-27 06:00",
"2020-05-28 06:00",
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"forecast": {
"precipitation": [
0.056767433881759644,
0,
0,
0.4399683475494385,
15.844732284545898,
44.89187240600586,
1.5000615119934082,
0.08085183054208755,
0,
0
],
"temperature": [
18.824644088745117,
19.359586715698242,
18.883825302124023,
19.692514419555664,
19.551362991333008,
16.896339416503906,
15.828611373901367,
16.13727378845215,
17.514820098876953,
18.058198928833008
],
"max_temperature": [
22.46466827392578,
24.152278900146484,
24.09707260131836,
23.8635196685791,
22.003244400024414,
18.38502311706543,
18.644731521606445,
20.728199005126953,
22.921388626098633,
24.01732063293457
],
"min_temperature": [
15.417205810546875,
16.429214477539062,
16.211782455444336,
15.86740493774414,
17.970169067382812,
15.427639961242676,
14.038402557373047,
13.745279312133789,
13.450150489807129,
13.989575386047363
],
"rel_humidity": [
62.96822738647461,
59.998905181884766,
57.617767333984375,
57.83722686767578,
78.12373352050781,
94.76325988769531,
75.46481323242188,
62.226593017578125,
56.40239715576172,
58.100589752197266
],
"wind_speed": [
3.4700000286102295,
3.799999952316284,
3.1600000858306885,
4.050000190734863,
4.679999828338623,
5.150000095367432,
3.2300000190734863,
3.440000057220459,
3.9800000190734863,
2.700000047683716
],
"wind_direction": [
84,
63,
25,
176,
343,
230,
309,
335,
331,
253
],
"pressure": [
1023.6478881835938,
1022.41357421875,
1020.7127075195312,
1018.1690673828125,
1015.9232177734375,
1014.6679077148438,
1016.386474609375,
1016.560546875,
1017.0572509765625,
1017.733642578125
],
"weather_conditions": [
0,
0,
0,
1,
3,
4,
1,
0,
0,
0
],
"atmospheric_conditions": [
1,
1,
1,
1,
1,
2,
1,
1,
1,
1
],
"thunderstorm_alerts": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"thermal_sensation": [
18.80209576957847,
19.311658189943806,
18.81657228112877,
19.61161493272052,
19.520403485999804,
16.70397960028661,
15.63146214382689,
15.71518270135801,
17.18781783876763,
18.055743181538205
],
"max_sensation": [
22.46466742621528,
24.15228101942274,
24.097069634331596,
23.863516913519966,
22.00324164496528,
18.36928473578559,
18.644731309678818,
20.728200276692707,
22.921388414171005,
24.01731703016493
],
"min_sensation": [
15.41720496283637,
16.417120201720643,
16.107157847880885,
15.276869314839093,
17.627951118428594,
15.427640279134113,
13.261989770410336,
12.81911552651217,
12.24778471071505,
13.44663471408552
],
"frost_alert": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"etp": [
2.3177120685577393,
2.3653812408447266,
2.3653812408447266,
2.413882255554199,
2.413882255554199,
2.1042680740356445,
2.1042680740356445,
2.1194908618927,
2.1892900466918945,
2.1892900466918945,
2.3954384326934814
],
"downward_long_wave_radiation": [
1402.908935546875,
1370.7249755859375,
1365.805419921875,
1401.275146484375,
1552.200439453125,
1557.6971435546875,
1403.4168701171875,
1318.338134765625,
1233.93505859375,
1278.08642578125
],
"downward_short_wave_radiation": [
742.3240966796875,
749.7091064453125,
729.0908813476562,
720.8073120117188,
334.5498352050781,
116.18775177001953,
378.384765625,
675.8541259765625,
768.630615234375,
752.382080078125,
695.7022094726562
],
"upward_long_wave_radiation": [
1640.0843505859375,
1651.9576416015625,
1640.43994140625,
1653.0946044921875,
1658.1910400390625,
1620.226318359375,
1587.498046875,
1584.00244140625,
1603.44580078125,
1604.03173828125,
1636.075927734375
],
"upward_short_wave_radiation": [
129.03953552246094,
130.09609985351562,
126.432373046875,
126.62202453613281,
51.088417053222656,
18.74220085144043,
65.6014633178711,
115.97320556640625,
136.7119903564453,
133.0154266357422,
121.39058685302734
]
}
},
"meta": {
"updated_at": "2020-05-19 09:08",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"prec_prob": "%",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
You can retrive a weather forecast with 45 days, based in your plan options.
HTTP Request
GET https://nimbus.somar.io/forecast/45days?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/45days?city=<CITY>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| reference | Reference name |
Seasonal forecast
Get CCM3
import requests
import json
response = requests.get('https://nimbus.somar.io/forecast/climate/ccm3?city=SaoPaulo-SP&days=7&member=avg',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/forecast/climate/ccm3?city=SaoPaulo-SP&days=7&member=avg" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/forecast/climate/ccm3?city=SaoPaulo-SP&days=7&member=avg', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-19 00:00",
"2020-05-20 00:00",
"2020-05-21 00:00",
"2020-05-22 00:00",
"2020-05-23 00:00",
"2020-05-24 00:00",
"2020-05-25 00:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "None"
},
"forecast": {
"convective_precipitation": [
0,
0.5710829496383667,
0,
2.401496171951294,
4.8128342628479,
3.0230371952056885,
0.5306161642074585
],
"stratiform_precipitation": [
0,
0,
0,
0,
0,
0,
0
],
"total_precipitation": [
0,
0.6069879531860352,
0,
2.4058098793029785,
5.1391825675964355,
2.9999728202819824,
0.528351366519928
],
"max_temperature": [
21.988189697265625,
22.239431381225586,
21.77591896057129,
22.060272216796875,
21.146942138671875,
20.4146728515625,
20.983062744140625
],
"min_temperature": [
17.756093978881836,
18.05605125427246,
18.545583724975586,
17.982736587524414,
17.808847427368164,
17.66782569885254,
17.71044921875
],
"avg_temperature": [
19.415496826171875,
19.67165184020996,
19.708354949951172,
19.53498077392578,
19.04001235961914,
18.713481903076172,
19.045122146606445
]
}
},
"meta": {
"updated_at": "2020-05-19 12:50",
"units": {
"precipitation": "mm.period",
"temperature": "C"
}
}
}
Get ccm3 daily forecast data for a specific latitude and longitude or city. This model is an ensemble.
HTTP Request
GET https://nimbus.somar.io/forecast/climate/ccm3?lat=<LAT>&lon=<LON>&member=<MEMBER>&reference=<REFERENCE>
GET https://nimbus.somar.io/forecast/climate/cmm3?city=<CITY>&member=<MEMBER>&reference=<REFERENCE>
Query Parameters
| Parameter | Type | Possible values | Description |
|---|---|---|---|
| latitude | float | Latitude | |
| longitude | float | Longitude | |
| city | string | City | |
| initi_date | date | Initial Date | |
| final_date | date | Final Date | |
| days | integer | Days | |
| periods | bool | Separation by period: dawn, morning, afternoon and night | |
| member | string | avg, emax, emin | Members of resulting ensemble |
Historic
This data is observed and consolidated, and have a minimal of 24hrs latency
Get 30Days
import requests
import json
response = requests.get('https://nimbus.somar.io/history/30days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/history/30days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/history/30days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-12 06:00",
"2020-05-13 06:00",
"2020-05-14 06:00",
"2020-05-15 06:00",
"2020-05-16 06:00",
"2020-05-17 06:00",
"2020-05-18 06:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"observed": {
"precipitation": [
0,
0,
0.1964189112186432,
0,
0,
0,
0
],
"temperature": [
18.78972625732422,
19.18778944015503,
18.59159517288208,
15.788590908050537,
19.3943452835083,
18.811660289764404,
18.016358375549316
],
"max_temperature": [
26.47569465637207,
24.987625122070312,
21.309295654296875,
16.99454116821289,
24.327138900756836,
26.022457122802734,
25.387977600097656
],
"min_temperature": [
11.103757858276367,
13.387953758239746,
15.873894691467285,
14.582640647888184,
14.461551666259766,
11.600863456726074,
10.644739151000977
],
"max_rel_humidity": [
89.18852233886719,
83.25667572021484,
91.6163101196289,
92.96448516845703,
93.12593078613281,
95.54795837402344,
94.31549072265625
],
"min_rel_humidity": [
30.30415916442871,
42.23429870605469,
68.78843688964844,
79.8919448852539,
43.5096435546875,
28.935083389282227,
33.991065979003906
],
"max_pressure": [
1020.932373046875,
1017.634521484375,
1019.31689453125,
1021.1224975585938,
1019.640869140625,
1021.2021484375,
1023.4518432617188
],
"min_pressure": [
1014.178955078125,
1012.7354125976562,
1013.288818359375,
1017.565673828125,
1014.272216796875,
1015.0457153320312,
1017.408935546875
],
"wind_gust": [
7.531764030456543,
11.121869087219238,
8.084187507629395,
7.1883649826049805,
6.104550838470459,
4.377012252807617,
6.520904064178467
],
"frost_alert": [
0,
0,
0,
0,
0,
0,
0
],
"etp": [
1.8477373123168945,
1.9349548816680908,
1.7959121465682983,
1.2215930223464966,
1.9756768941879272,
1.8351887464523315,
1.6603834629058838
],
"wetting": [
-0.0212040264159441,
-0.03478175774216652,
1.5197817087173462,
2.127779006958008,
0.2781636416912079,
4.545218467712402,
2.338677167892456
],
"downward_total_radiation": [
363.2767639160156,
219.15634155273438,
207.1370086669922,
201.4152374267578,
289.411865234375,
328.4449462890625,
353.37310791015625
]
}
},
"meta": {
"updated_at": "2020-05-19 05:06",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_gust": "m/s",
"pressure": "hpa",
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"wetting": "h",
"total_radiation": "W/m²"
}
}
}
Get daily historic data, for a specific latitude and longitude or city. With a maximum of 30 prior days.
HTTP Request
GET https://nimbus.somar.io/history/30days?lat=<LAT>&lon=<LON>&periods=<PERIODS>
GET https://nimbus.somar.io/history/30days?city=<CITY>&periods=<PERIODS>
Query Parameters
| Parameter | Description |
|---|---|
| lat | Latitude |
| lon | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name (optional) |
Get 90 Days
import requests
import json
response = requests.get('https://nimbus.somar.io/history/90days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/history/90days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/history/90days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-12 06:00",
"2020-05-13 06:00",
"2020-05-14 06:00",
"2020-05-15 06:00",
"2020-05-16 06:00",
"2020-05-17 06:00",
"2020-05-18 06:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"observed": {
"precipitation": [
0,
0,
0.1964189112186432,
0,
0,
0,
0
],
"temperature": [
18.78972625732422,
19.18778944015503,
18.59159517288208,
15.788590908050537,
19.3943452835083,
18.811660289764404,
18.016358375549316
],
"max_temperature": [
26.47569465637207,
24.987625122070312,
21.309295654296875,
16.99454116821289,
24.327138900756836,
26.022457122802734,
25.387977600097656
],
"min_temperature": [
11.103757858276367,
13.387953758239746,
15.873894691467285,
14.582640647888184,
14.461551666259766,
11.600863456726074,
10.644739151000977
],
"max_rel_humidity": [
89.18852233886719,
83.25667572021484,
91.6163101196289,
92.96448516845703,
93.12593078613281,
95.54795837402344,
94.31549072265625
],
"min_rel_humidity": [
30.30415916442871,
42.23429870605469,
68.78843688964844,
79.8919448852539,
43.5096435546875,
28.935083389282227,
33.991065979003906
],
"max_pressure": [
1020.932373046875,
1017.634521484375,
1019.31689453125,
1021.1224975585938,
1019.640869140625,
1021.2021484375,
1023.4518432617188
],
"min_pressure": [
1014.178955078125,
1012.7354125976562,
1013.288818359375,
1017.565673828125,
1014.272216796875,
1015.0457153320312,
1017.408935546875
],
"wind_gust": [
7.531764030456543,
11.121869087219238,
8.084187507629395,
7.1883649826049805,
6.104550838470459,
4.377012252807617,
6.520904064178467
],
"frost_alert": [
0,
0,
0,
0,
0,
0,
0
],
"etp": [
1.8477373123168945,
1.9349548816680908,
1.7959121465682983,
1.2215930223464966,
1.9756768941879272,
1.8351887464523315,
1.6603834629058838
],
"wetting": [
-0.0212040264159441,
-0.03478175774216652,
1.5197817087173462,
2.127779006958008,
0.2781636416912079,
4.545218467712402,
2.338677167892456
],
"downward_total_radiation": [
363.2767639160156,
219.15634155273438,
207.1370086669922,
201.4152374267578,
289.411865234375,
328.4449462890625,
353.37310791015625
],
"drought": [
1,
2,
3,
4,
5,
6,
7
],
"thermal_amplitude": [
15.371936798095703,
11.599671363830566,
5.43540096282959,
2.411900520324707,
9.86558723449707,
14.42159366607666,
14.74323844909668
]
}
},
"meta": {
"updated_at": "2020-05-19 05:06",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_gust": "m/s",
"pressure": "hpa",
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"wetting": "h",
"total_radiation": "W/m²"
}
}
}
Get daily historic data, for a specific latitude and longitude or city. With a maximum of 90 prior days.
HTTP Request
GET https://nimbus.somar.io/history/90days?lat=<LAT>&lon=<LON>&periods=<PERIODS>
GET https://nimbus.somar.io/history/90days?city=<CITY>&periods=<PERIODS>
Query Parameters
| Parameter | Description |
|---|---|
| lat | Latitude |
| lon | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name (optional) |
Get 365 Days
import requests
import json
response = requests.get('https://nimbus.somar.io/history/365days?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/history/365days?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/history/365days?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-12 06:00",
"2020-05-13 06:00",
"2020-05-14 06:00",
"2020-05-15 06:00",
"2020-05-16 06:00",
"2020-05-17 06:00",
"2020-05-18 06:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"observed": {
"precipitation": [
0,
0,
0.1964189112186432,
0,
0,
0,
0
],
"temperature": [
18.78972625732422,
19.18778944015503,
18.59159517288208,
15.788590908050537,
19.3943452835083,
18.811660289764404,
18.016358375549316
],
"max_temperature": [
26.47569465637207,
24.987625122070312,
21.309295654296875,
16.99454116821289,
24.327138900756836,
26.022457122802734,
25.387977600097656
],
"min_temperature": [
11.103757858276367,
13.387953758239746,
15.873894691467285,
14.582640647888184,
14.461551666259766,
11.600863456726074,
10.644739151000977
],
"max_rel_humidity": [
89.18852233886719,
83.25667572021484,
91.6163101196289,
92.96448516845703,
93.12593078613281,
95.54795837402344,
94.31549072265625
],
"min_rel_humidity": [
30.30415916442871,
42.23429870605469,
68.78843688964844,
79.8919448852539,
43.5096435546875,
28.935083389282227,
33.991065979003906
],
"max_pressure": [
1020.932373046875,
1017.634521484375,
1019.31689453125,
1021.1224975585938,
1019.640869140625,
1021.2021484375,
1023.4518432617188
],
"min_pressure": [
1014.178955078125,
1012.7354125976562,
1013.288818359375,
1017.565673828125,
1014.272216796875,
1015.0457153320312,
1017.408935546875
],
"wind_gust": [
7.531764030456543,
11.121869087219238,
8.084187507629395,
7.1883649826049805,
6.104550838470459,
4.377012252807617,
6.520904064178467
],
"frost_alert": [
0,
0,
0,
0,
0,
0,
0
],
"etp": [
1.8477373123168945,
1.9349548816680908,
1.7959121465682983,
1.2215930223464966,
1.9756768941879272,
1.8351887464523315,
1.6603834629058838
],
"wetting": [
-0.0212040264159441,
-0.03478175774216652,
1.5197817087173462,
2.127779006958008,
0.2781636416912079,
4.545218467712402,
2.338677167892456
],
"downward_total_radiation": [
363.2767639160156,
219.15634155273438,
207.1370086669922,
201.4152374267578,
289.411865234375,
328.4449462890625,
353.37310791015625
],
"drought": [
1,
2,
3,
4,
5,
6,
7
],
"thermal_amplitude": [
15.371936798095703,
11.599671363830566,
5.43540096282959,
2.411900520324707,
9.86558723449707,
14.42159366607666,
14.74323844909668
]
}
},
"meta": {
"updated_at": "2020-05-19 05:06",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_gust": "m/s",
"pressure": "hpa",
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"wetting": "h",
"total_radiation": "W/m²"
}
}
}
Get daily historic data, for a specific latitude and longitude or city. With a maximum of 365 prior days.
HTTP Request
GET https://nimbus.somar.io/history/365days?lat=<LAT>&lon=<LON>&periods=<PERIODS>
GET https://nimbus.somar.io/history/365days?city=<CITY>&periods=<PERIODS>
Query Parameters
| Parameter | Description |
|---|---|
| lat | Latitude |
| lon | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name (optional) |
Observed
This endpoint returns near real time data, with a max latency of 45min.
Get hourly
import requests
import json
response = requests.get('https://nimbus.somar.io/observed/hourly?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/observed/hourly?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/observed/hourly?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-18 22:00",
"2020-05-18 23:00",
"2020-05-19 00:00",
"2020-05-19 01:00",
"2020-05-19 02:00",
"2020-05-19 03:00",
"2020-05-19 04:00",
"2020-05-19 05:00",
"2020-05-19 06:00",
"2020-05-19 07:00",
"2020-05-19 08:00",
"2020-05-19 09:00",
"2020-05-19 10:00",
"2020-05-19 11:00",
"2020-05-19 12:00",
"2020-05-19 13:00",
"2020-05-19 14:00",
"2020-05-19 15:00",
"2020-05-19 16:00",
"2020-05-19 17:00",
"2020-05-19 18:00",
"2020-05-19 19:00",
"2020-05-19 20:00",
"2020-05-19 21:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "None"
},
"observed": {
"precipitation": [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0
],
"temperature": [
18.34000015258789,
16.950000762939453,
16.290000915527344,
15.461019515991211,
14.566726684570312,
13.9591703414917,
14.850000381469727,
14.430000305175781,
15.3100004196167,
15.619999885559082,
15.449999809265137,
15.579999923706055,
15.09000015258789,
15.5,
15.430000305175781,
17.670000076293945,
18.6200008392334,
19.90999984741211,
21.360000610351562,
22.690000534057617,
23.6200008392334,
24.270000457763672,
23.520000457763672,
20.40999984741211
],
"rel_humidity": [
90.26000213623047,
99.98999786376953,
99.98999786376953,
72.1402359008789,
76.7984390258789,
79.66664123535156,
99.98999786376953,
99.98999786376953,
99.98999786376953,
99.98999786376953,
99.98999786376953,
99.98999786376953,
99.98999786376953,
83.0,
99.98999786376953,
97.2300033569336,
91.73999786376953,
84.05000305175781,
78.02999877929688,
65.73999786376953,
61.43000030517578,
56.45000076293945,
71.77999877929688,
90.37000274658203
],
"wind_speed": [
1.1299999952316284,
0.3799999952316284,
0.0,
0.6700000166893005,
0.8299999833106995,
0.6499999761581421,
0.0,
0.0,
2.259999990463257,
1.3200000524520874,
2.069999933242798,
2.069999933242798,
2.069999933242798,
2.9000000953674316,
1.1299999952316284,
3.950000047683716,
6.579999923706055,
3.759999990463257,
2.069999933242798,
2.630000114440918,
1.1299999952316284,
1.8799999952316284,
0.1899999976158142,
2.630000114440918
],
"wind_direction": [
183,
13,
180,
225,
241,
238,
0,
360,
187,
16,
3,
293,
276,
312,
31,
334,
5,
227,
169,
148,
336,
115,
3,
34
],
"wind_gust": [
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
],
"pressure": [
1020,
1020,
1022,
1023,
1023,
1023,
1022,
1022,
1021,
1021,
1022,
1022,
1022,
1024,
1024,
1023,
1022,
1022,
1021,
1020,
1019,
1019,
1018,
1019
],
"dew_point": [
13.100000381469727,
12.699999809265137,
12.699999809265137,
12.862659454345703,
12.913176536560059,
12.705680847167969,
12.563989639282227,
12.600000381469727,
13.100000381469727,
13.300000190734863,
12.899999618530273,
12.600000381469727,
12.5,
12.600000381469727,
12.899999618530273,
12.600000381469727,
12.5,
14.0,
12.199999809265137,
11.5,
11.199999809265137,
10.0,
13.899999618530273,
14.300000190734863
],
"cloud_cover": [
0.43143004179000854,
0.29404309391975403,
0.3659103214740753,
0.45542261004447937,
0.4322013854980469,
0.3318386971950531,
0.31112825870513916,
0.5640892386436462,
0.6182852387428284,
0.5800791382789612,
0.5660618543624878,
0.43479663133621216,
0.4093799293041229,
0.75,
0.35455694794654846,
0.25,
0.25,
0.3648225665092468,
0.3472788631916046,
0.34557655453681946,
0.3111972510814667,
0.36582809686660767,
0.32525718212127686,
0.36038556694984436
],
"categorical_rain": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
]
}
},
"meta": {
"updated_at": "2020-05-19 21:35",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"dew_point": "C"
}
}
}
Returns hourly observed data for a specific latitude and longitude or city. For a maximum of 96 past hours.
HTTP Request
GET https://nimbus.somar.io/observed/hourly?latitude=<LAT>&longitude=<LON>
GET https://nimbus.somar.io/observed/hourly?city=<CITY>
Query Parameters
| Parameter | Type | Possible values | Description |
|---|---|---|---|
| latitude | float | Latitude | |
| longitude | float | Longitude | |
| city | string | City | |
| hours | integer | 1,...,96 | The amount of past hours that will be returned in the API response. |
Get daily
import requests
import json
response = requests.get('https://nimbus.somar.io/observed/daily?city=SaoPaulo-SP',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/observed/daily?city=SaoPaulo-SP" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/observed/daily?city=SaoPaulo-SP', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2020-05-12 06:00",
"2020-05-13 06:00",
"2020-05-14 06:00",
"2020-05-15 06:00",
"2020-05-16 06:00",
"2020-05-17 06:00",
"2020-05-18 06:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"observed": {
"precipitation": [
0,
0,
0.1964189112186432,
0,
0,
0,
0
],
"temperature": [
18.78972625732422,
19.18778944015503,
18.59159517288208,
15.788590908050537,
19.3943452835083,
18.811660289764404,
18.016358375549316
],
"max_temperature": [
26.47569465637207,
24.987625122070312,
21.309295654296875,
16.99454116821289,
24.327138900756836,
26.022457122802734,
25.387977600097656
],
"min_temperature": [
11.103757858276367,
13.387953758239746,
15.873894691467285,
14.582640647888184,
14.461551666259766,
11.600863456726074,
10.644739151000977
],
"max_rel_humidity": [
89.18852233886719,
83.25667572021484,
91.6163101196289,
92.96448516845703,
93.12593078613281,
95.54795837402344,
94.31549072265625
],
"min_rel_humidity": [
30.30415916442871,
42.23429870605469,
68.78843688964844,
79.8919448852539,
43.5096435546875,
28.935083389282227,
33.991065979003906
],
"max_pressure": [
1020.932373046875,
1017.634521484375,
1019.31689453125,
1021.1224975585938,
1019.640869140625,
1021.2021484375,
1023.4518432617188
],
"min_pressure": [
1014.178955078125,
1012.7354125976562,
1013.288818359375,
1017.565673828125,
1014.272216796875,
1015.0457153320312,
1017.408935546875
],
"wind_gust": [
7.531764030456543,
11.121869087219238,
8.084187507629395,
7.1883649826049805,
6.104550838470459,
4.377012252807617,
6.520904064178467
],
"frost_alert": [
0,
0,
0,
0,
0,
0,
0
],
"etp": [
1.8477373123168945,
1.9349548816680908,
1.7959121465682983,
1.2215930223464966,
1.9756768941879272,
1.8351887464523315,
1.6603834629058838
],
"wetting": [
-0.0212040264159441,
-0.03478175774216652,
1.5197817087173462,
2.127779006958008,
0.2781636416912079,
4.545218467712402,
2.338677167892456
],
"downward_total_radiation": [
363.2767639160156,
219.15634155273438,
207.1370086669922,
201.4152374267578,
289.411865234375,
328.4449462890625,
353.37310791015625
],
"drought": [
1,
2,
3,
4,
5,
6,
7
],
"thermal_amplitude": [
15.371936798095703,
11.599671363830566,
5.43540096282959,
2.411900520324707,
9.86558723449707,
14.42159366607666,
14.74323844909668
]
}
},
"meta": {
"updated_at": "2020-05-19 05:06",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_gust": "m/s",
"pressure": "hpa",
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"wetting": "h",
"total_radiation": "W/m²"
}
}
}
Get daily observed data for a specific latitude and longitude or city.
HTTP Request
GET https://nimbus.somar.io/observed/daily?latitude=<LAT>&longitude=<LON>&reference=<REFERENCE>
GET https://nimbus.somar.io/observed/daily?city=<CITY>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| reference | Reference name |
Clima
Get daily
import requests
import json
response = requests.get('https://nimbus.somar.io/climate/daily?city=SaoPaulo-SP&days=15',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/climate/daily?city=SaoPaulo-SP&days=15" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/climate/daily?city=SaoPaulo-SP&days=15', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
"2010-05-19 06:00",
"2010-05-20 06:00",
"2010-05-21 06:00",
"2010-05-22 06:00",
"2010-05-23 06:00",
"2010-05-24 06:00",
"2010-05-25 06:00",
"2010-05-26 06:00",
"2010-05-27 06:00",
"2010-05-28 06:00",
"2010-05-29 06:00",
"2010-05-30 06:00",
"2010-05-31 06:00",
"2010-06-01 06:00",
"2010-06-02 06:00",
"2010-06-03 06:00"
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"observed": {
"precipitation": [
3.9821226596832275,
3.6964266300201416,
2.1961166858673096,
5.229040622711182,
4.151275634765625,
3.046980857849121,
8.069395065307617,
2.162271738052368,
0.8778133392333984,
0.6906915307044983,
2.1773784160614014,
0.9777919054031372,
1.296659231185913,
3.0237932205200195,
2.216203451156616,
2.604184150695801
],
"max_precipitation": [
25.847848892211914,
36.312347412109375,
27.77312660217285,
42.55268478393555,
18.960365295410156,
14.93871784210205,
117.98340606689453,
18.298185348510742,
8.8299560546875,
5.979281425476074,
14.258336067199707,
7.954739570617676,
13.364762306213379,
20.605361938476562,
15.80427360534668,
15.49482536315918
],
"prob_precipitation": [
46.147151947021484,
37.975502014160156,
15.044923782348633,
29.978261947631836,
45.45020294189453,
38.477638244628906,
32.99684524536133,
26.2397518157959,
10.281905174255371,
22.92163848876953,
26.863445281982422,
15.882107734680176,
25.8756046295166,
40.948360443115234,
34.12852478027344,
31.555158615112305
],
"temperature": [
18.74602460861206,
18.791518688201904,
19.188230991363525,
19.01146364212036,
18.18500328063965,
17.837945461273193,
18.502891063690186,
18.89369773864746,
18.126879692077637,
17.88027334213257,
18.0622878074646,
18.06098222732544,
18.348735809326172,
18.332737922668457,
18.116477489471436,
17.943767547607422
],
"max_temperature": [
22.14983558654785,
23.06086540222168,
23.46891212463379,
22.938121795654297,
21.892065048217773,
21.657468795776367,
22.700016021728516,
23.113101959228516,
22.3893985748291,
22.071535110473633,
22.43308448791504,
22.747989654541016,
22.55344581604004,
22.52292251586914,
22.105436325073242,
22.15403175354004
],
"min_temperature": [
15.34221363067627,
14.522171974182129,
14.907549858093262,
15.084805488586426,
14.477941513061523,
14.01842212677002,
14.305766105651855,
14.674293518066406,
13.864360809326172,
13.689011573791504,
13.69149112701416,
13.373974800109863,
14.144025802612305,
14.142553329467773,
14.127518653869629,
13.733503341674805
],
"abs_max_temperature": [
27.397911071777344,
28.748455047607422,
28.171722412109375,
29.539430618286133,
27.622364044189453,
26.51424789428711,
27.378137588500977,
28.22271156311035,
27.59991455078125,
27.05360221862793,
26.787080764770508,
27.39339828491211,
27.520021438598633,
27.832000732421875,
28.005870819091797,
27.646495819091797
],
"abs_min_temperature": [
11.775525093078613,
9.030074119567871,
6.982365608215332,
9.324421882629395,
9.923995971679688,
9.249829292297363,
8.566553115844727,
10.212810516357422,
8.51879596710205,
8.690218925476074,
7.50773286819458,
7.703948497772217,
9.485217094421387,
9.840442657470703,
8.291218757629395,
7.764330863952637
]
}
},
"meta": {
"updated_at": "2019-03-06 19:29",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"precipitation prob": "% non limited"
}
}
}
Get climatology daily data for a specific latitude and longitude or city.
HTTP Request
GET https://nimbus.somar.io/climate/daily?latitude=<LAT>&longitude=<LON>&reference=<REFERENCE>
GET https://nimbus.somar.io/climate/daily?city=<CITY>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| days | Days |
| reference | Reference name |
Get monthly
import requests
import json
response = requests.get('https://nimbus.somar.io/climate/monthly?city=SaoPaulo-SP&days=15',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/climate/monthly?city=SaoPaulo-SP&days=15" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/climate/monthly?city=SaoPaulo-SP&days=15', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": [
{
"initi": "2010-05-19 06:00",
"final": "2010-06-03 06:00"
}
],
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"observed": {
"monthly_max_temperature": [
22.497389435768127
],
"monthly_min_temperature": [
14.256225228309631
],
"monthly_thermal_amplitude": [
8.241164207458496
],
"monthly_temperature": [
18.37680733203888
],
"monthly_accumulated_precipitation": [
46.39814513921738
]
}
},
"meta": {
"updated_at": "2019-03-06 19:29",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"precipitation prob": "% non limited"
}
}
}
Get climatology monthly data for a specific latitude and longitude or city.
HTTP Request
GET https://nimbus.somar.io/climate/monthly?lat=<LAT>&lon=<LON>&reference=<REFERENCE>
GET https://nimbus.somar.io/climate/monthly?city=<CITY>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| reference | Reference name |
Agriculture
Phytosanitary Calendar
import requests
import json
response = requests.get('https://nimbus.somar.io/agriculture/phyto?latitude=-29.6873064&longitude=-53.8154769&days=15&crops=soja,algodao,cafe',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/agriculture/phyto?latitude=-29.6873064&longitude=-53.8154769&days=15&crops=soja,algodao,cafe" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/agriculture/phyto?latitude=-29.6873064&longitude=-53.8154769&days=15&crops=soja,algodao,cafe', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"status": 200,
"data": [{
"data": "2019-02-12",
"timestamp": 1549958400.0,
"alerta": [{
"cultura": "soja",
"nome": "Ferrugem Asi\u00e1tica",
"status": 1
}, {
"cultura": "soja",
"nome": "Antracnose",
"status": 1
},
{
"cultura": "cafe",
"nome": "Rhizoctoniose",
"status": 1
}, {
"cultura": "cafe",
"nome": "Antranose",
"status": 1
}]
}]
}
Phytosanitary alerts based on weather forecast
HTTP Request
GET https://nimbus.somar.io/agriculture/phyto?latitude=<LATITIDE>&longitude=<LONGITUDE>&days=<DAYS>&crops=<CROP_1,CROP_2,CROP_N>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| days | Days, max = 15 |
| crops | Crop codes separated by comma, check the table below to see the domain |
Crops and diseases
List of crops and diseases that can be alarmed
| Crops | Param code | Diseases |
|---|---|---|
| Soja | soja |
Ferrugem Asiática, Antracnose, Mancha Alvo, Mofo Branco, Mela |
| Feijão | feijao |
Mosaico Dourado, Fusariose, Antranose, Crestamento Bacteriano, Mela |
| Milho | milho |
Ferrugem, Mancha Branca, Diplodia, Fusariose, Macrofomina |
| Trigo | trigo |
Giberela, Brusone, Ferrugem da Folha, Oidio |
| Café | cafe |
Ferrugem do Café, Cercosporiose, Rhizoctoniose, Antranose |
| Algodão | algodao |
Ramulose, Tombamento, Mancha Angular, Alternaria, Podridão das Maças, Mofo Branco |
| Arroz | arroz |
Brusone, Escaldadura, Mancha Estreita, Mancha Parda, Falso Carvão |
| Cana-de-açucar | cana |
Mosaico, Escaldadura das Folhas, Estrias Vermelhas, Raquitismo da Soqueira, Carvão |
| Fruticultura | fruticultura |
Antracnose, Ferrugem, Fusariose, Gomose, Oidio |
| Hortaliças | hortalicas |
Mancha Purpura, Antracnose, Mildio, Ferrugem, Podridão Branca, Phytophthora, Podridão Mole |
What is the domain and the status meaning?
| cod | meaning |
|---|---|
| 1 | No Alert |
| 2 | Attention |
| 2 | Alert |
Water Balance
import requests
import json
response = requests.get('http://nimbus.somar.io/agriculture/waterbalance?latitude=-23.541409&longitude=-46.733401&days=93&crop=ABF&slt=FAr',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "http://nimbus.somar.io/agriculture/waterbalance?latitude=-23.541409&longitude=-46.733401&days=93&crop=ABF&slt=FAr" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('http://nimbus.somar.io/agriculture/waterbalance?latitude=-23.541409&longitude=-46.733401&days=93&crop=ABF&slt=FAr', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"latitude": -23.541409,
"longitude": -46.733401,
"status": "Sucesso",
"reqType": {
"initi_date": "2019-03-02",
"final_date": "2019-03-04",
"crop": "Am",
"slt": "SiAg"
},
"waterBalance": [
{
"date": "2019-09-21",
"timestamp": 1569056400,
"etp": 4.281315803527832,
"p_etp": -4.281315803527832,
"alt": -2.7533689857800425,
"neg_acum": -15.409165814518929,
"etr": 2.7533689857800425,
"arm": 17.949432901036502,
"exc": 0,
"def": 1.5279468177477895,
"isna": 0.6431127980587764,
"exc_10day_acu": 38.439498315756865,
"def_10day_acu": 3.3586040904095817
}
]
}
Water balance is the result of the amount of water entering and leaving a certain portion of the soil in a given time interval.
You must provide latitude, longitude, period length in days, and soil/crop info from either:
- Only general crop CAD (keyword: gen)
- Only crop type estimated from mean CAD = 1.3 (keyord: crop),
- Soil type and crop type (keywords: slt, crop respectively)
HTTP Request
GET http://nimbus.somar.io/agriculture/waterbalance?latitude=<LATITUDE>&longitude=<LONGITUDE>&days=<DAYS>&crop=<CROPS>&slt=<SLT>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| days | Days (max 270 days forward) |
| initi_date | Initial Date (start in 01/07/2018) |
| final_date | Final Date (max 270 days forward) |
| crop | Crop code |
| slt | Soil code |
| gen | General CAD |
The query period must be given either in days OR initial and final dates Evapotranspiration data are currently available from 04/01/2019, so requests starting before this date will return rogue values. Water balance considers a period of 90 days (or the period between 04/01/2019 and initial date) before the request to iterate over the water storage and provide a good starting value.
Crops
List of crops supported by our solution This is used to calculate the CAD from the mean depth of the radicular structure of the crop type
| Param code | Crop type |
|---|---|
| ABF | Arroz-Batata-Feijao-Algodao |
| Am | Amendoim |
| CCC | Cana-Citrus-Cafe |
| Ef | EspeciesFlorestais |
| Hr | Hortalicas |
| MS | Milho-Soja |
| Tr | Trigo |
Soils
List of soils supported by our solution If no soil information is given, the CAD is calculated from the crop info and a mean CAD
| Param code | Soil Type |
|---|---|
| Arenoso | Ar |
| Franco-arenoso | FAr |
| Franco | Fr |
| Franco-argiloso | FrAg |
| Siltoso-argiloso | SiAg |
| Argiloso | Ag |
General CADs
List of general CADs supported by our solution The general CAD can be used if no specific information about the soil and crop can be given A specific numerical value can also be used, and if it is well determined can improve the water balance calculation If this parameter is used, it overrides the soil and crop information for the water balance calculation
| Param code | General CAD |
|---|---|
| CtAn | Culturas Anuais |
| CtPr | Culturas Perenes |
| EsFr | Especies Florestais |
| HrOr | Hortalicas-Olericolas |
| User-defined |
Water Balance
List of general result water balance
| Keys | Description |
|---|---|
| etp | Evapotranspiração potencial |
| p_etp | Precipitação - tp |
| alt | Alteração do armazenamento |
| neg_acum | Negativo acumulado |
| etr | Evapotranspiração real |
| arm | Armazenamento (água no solo, mm) |
| exc | Excedente (mm) |
| def | Déficit (mm) |
| isna | Índice de satisfação de necessidade de água (0 - 1) |
| exc_10day_acu | Acumulado dos últimos 10 dias do Excedente (mm) |
| def_10day_acu | Acumulado dos últimos 10 dias do Déficit (mm) |
Crop penalization
import requests
import json
response = requests.get('https://nimbus.somar.io/agriculture/penalization?latitude=-23.541409&longitude=-46.733401&crop=arroz&pp=5000&cycle=precoce&days=93&soil=FAr',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/agriculture/penalization?latitude=-23.541409&longitude=-46.733401&crop=arroz&pp=5000&cycle=precoce&days=93&soil=FAr" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/agriculture/penalization?latitude=-23.541409&longitude=-46.733401&crop=arroz&pp=5000&cycle=precoce&days=93&soil=FAr', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"latitude": -23.541409,
"longitude": -46.733401,
"penalizacao": [{
"timestamp": 1552802400,
"data": "2019-03-17",
"etc": 2.11,
"kc": 0.75,
"ky": 0.6,
"pr": 5000.0,
"arm": 32.8
}]
}
From the production potential of a crop, the penalization formula indicates the loss of productivity due to climatic conditions (distribution of rainfall along the productive cycle and water balance in the soil).
HTTP Request
GET https://nimbus.somar.io/agriculture/penalization?latitude=<LATITUDE>&longitude=<LONGITUDE>&crop=<CROP>&pp=<PP>&cycle=<CYCLE>&days=<DAYS>&soil=<SOIL>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| days | Quantity of days forward |
| initi_date | Initial date |
| final_date | Final date |
| crop | Crop code |
| pp | Productive potential in kg/ha |
| cycle | Cycle type |
| soil | Soil type |
| gen | General CAD |
The query period must be given either in days OR initial and final dates
Crop
List of available crops to penalize
| Crops | Param code |
|---|---|
| Algodão | algodao |
| Soja | soja |
| Milho | milho |
| Arroz | arroz |
| Trigo | trigo |
| Café | cafe |
| Cana-de-açucar | cana |
Cycle types
List of cycle types for the crops
| Crops | Param code |
|---|---|
| Early | precoce |
| Medium | medio |
| Late | tardio |
For each crop, the cycle type indicates a number of days
| Cycle | Algodão | Soja | Milho | Arroz | Trigo | Café | Cana-de-açucar |
|---|---|---|---|---|---|---|---|
| Early | 125 | 110 | 100 | 105 | 100 | 240 | 365 |
| Medium | 150 | 125 | 120 | 120 | 120 | 240 | 365 |
| Late | 175 | 140 | 150 | 135 | 130 | 240 | 365 |
Soils
List of soils supported by our solution
| Param code | Soil Type |
|---|---|
| Arenoso | Ar |
| Franco-arenoso | FAr |
| Franco | Fr |
| Franco-argiloso | FrAg |
| Siltoso-argiloso | SiAg |
| Argiloso | Ag |
General CADs
List of general CADs supported by our solution The general CAD can be used if no specific information about the soil and crop can be given A specific numerical value can also be used, and if it is well determined can improve the water balance calculation If this parameter is used, it overrides the soil and crop information for the water balance calculation
| Param code | General CAD |
|---|---|
| CtAn | Culturas Anuais |
| CtPr | Culturas Perenes |
| EsFr | Especies Florestais |
| HrOr | Hortalicas-Olericolas |
| User-defined |
Hybrid
To access this endpoints contact our support or sails team
Get compare observed
import requests
import json
response = requests.get('https://nimbus.somar.io/hybrid/compare?city=SaoPaulo-SP&days=90',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/hybrid/compare?city=SaoPaulo-SP&days=90" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/hybrid/compare?city=SaoPaulo-SP&days=90', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": {
"period": [
{
"initi": "2020-05-19 06:00",
"final": "2020-06-17 06:00"
},
{
"initi": "2020-06-18 06:00",
"final": "2020-07-17 06:00"
},
{
"initi": "2020-07-18 06:00",
"final": "2020-08-16 06:00"
}
],
"period-1": [
{
"initi": "2019-05-19 06:00",
"final": "2019-06-17 06:00"
},
{
"initi": "2019-06-18 06:00",
"final": "2019-07-17 06:00"
},
{
"initi": "2019-07-18 06:00",
"final": "2019-08-16 06:00"
}
]
},
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"hybrid": {
"downward_long_wave_radiation": {
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},
"downward_short_wave_radiation": {
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},
"upward_long_wave_radiation": {
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},
"upward_short_wave_radiation": {
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98.08921813964844,
105.64970397949219,
104.14227294921875,
107.79875183105469,
110.7603530883789,
42.32927703857422,
88.3565673828125,
91.1112289428711,
104.23856353759766,
101.50498962402344,
109.98711395263672,
120.65325927734375,
111.48008728027344,
116.59042358398438,
120.1246109008789,
122.61815643310547,
112.2236328125,
114.36761474609375,
100.8069076538086,
109.58045196533203,
120.11746978759766,
120.2938003540039,
89.37309265136719,
115.0075454711914,
123.31220245361328,
123.5895004272461,
124.79615020751953,
128.72950744628906,
128.61863708496094,
131.40017700195312,
118.74166870117188,
98.86007690429688,
118.89837646484375,
117.688720703125,
125.99976348876953,
51.69040298461914,
123.49834442138672,
125.25086975097656,
34.35310363769531,
53.16965103149414,
105.85789489746094,
130.08958435058594,
136.77857971191406,
36.4160270690918,
58.66655731201172,
130.83670043945312,
142.94862365722656,
145.2069854736328,
138.9124298095703,
138.20941162109375,
138.9475860595703,
146.68923950195312,
148.3459930419922,
149.5684814453125,
151.1568145751953,
151.65037536621094,
144.9004364013672,
151.8493194580078,
149.4505615234375,
152.135986328125
]
},
"monthly_max_temperature": {
"period": [
19.893114058176675,
21.10474770863851,
22.778021176656086
],
"period-1": [
23.92811368306478,
22.871707661946616,
23.819661458333332
]
},
"monthly_min_temperature": {
"period": [
14.535126145680746,
13.430932474136352,
14.411373710632324
],
"period-1": [
14.12394552230835,
12.929683128992716,
12.991768487294515
]
},
"monthly_thermal_amplitude": {
"period": [
5.357987912495931,
7.673815234502157,
8.366647466023762
],
"period-1": [
9.80416816075643,
9.942024532953898,
10.827892971038818
]
},
"monthly_temperature": {
"period": [
16.989828936258952,
16.66848478317261,
18.010067049662272
],
"period-1": [
19.026029602686563,
17.900695395469665,
18.405714972813925
]
},
"monthly_accumulated_precipitation": {
"period": [
279.1913823187351,
7.909672245383263,
14.272454112768173
],
"period-1": [
54.63036719337106,
117.28670924156904,
3.1628695279359818
]
},
"monthly_accumulated_etp": {
"period": [
64.8395437002182,
64.4661077260971,
67.94933533668518
],
"period-1": [
56.80716526508331,
51.07700335979462,
55.28722879290581
]
}
}
},
"meta": {
"updated_at": "2020-05-19 09:08",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"prec_prob": "%",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
Get comparison of forecast and observed for a specific latitude and longitude.
HTTP Request
GET https://nimbus.somar.io/hybrid/compare?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| periods | Separation by period: dawn, morning, afternoon and night |
| reference | Reference name |
| last_years | Quantity of last years for consultation observed |
Get compare climate
import requests
import json
response = requests.get('https://nimbus.somar.io/hybrid/climate?city=SaoPaulo-SP&days=90',headers={'x-api-key':'api-key'}).json()
print(json.dumps(response))
curl "https://nimbus.somar.io/hybrid/climate?city=SaoPaulo-SP&days=90" -H "x-api-key: api-key"
const axios = require('axios');
axios.get('https://nimbus.somar.io/hybrid/climate?city=SaoPaulo-SP&days=90', {headers: {"x-api-key": "api-key"}})
.then(function (response) {
// handle success
console.log(response);
})
.catch(function (error) {
// handle error
console.log(error);
})
.then(function () {
// always executed
});
We suppressed the full response to focus on the data structure. The above command returns JSON structured like this:
{
"periods": {
"period": [
{
"initi": "2020-05-19 06:00",
"final": "2020-06-17 06:00"
},
{
"initi": "2020-06-18 06:00",
"final": "2020-07-17 06:00"
},
{
"initi": "2020-07-18 06:00",
"final": "2020-08-16 06:00"
}
],
"climate": [
{
"initi": "2010-05-19 06:00",
"final": "2010-06-17 06:00"
},
{
"initi": "2010-06-18 06:00",
"final": "2010-07-17 06:00"
},
{
"initi": "2010-07-18 06:00",
"final": "2010-08-16 06:00"
}
]
},
"points": {
"location": {
"latitude": -23.54,
"longitude": -46.63,
"elevation": 626,
"sunrise": "06:35",
"sunset": "17:30",
"timezone": -3,
"ref": "SaoPaulo-SP"
},
"hybrid": {
"downward_long_wave_radiation": {
"period": [
1402.908935546875,
1370.7249755859375,
1365.805419921875,
1401.275146484375,
1552.200439453125,
1557.6971435546875,
1403.4168701171875,
1318.338134765625,
1233.93505859375,
1278.08642578125,
1348.6142578125,
1471.33984375,
1564.869384765625,
1558.110595703125,
1438.967529296875,
1304.1273193359375,
1475.508056640625,
1542.8048095703125,
1466.14306640625,
1559.1328125,
1522.5535888671875,
1468.62109375,
1546.9847412109375,
1506.8626708984375,
1455.72900390625,
1472.8173828125,
1507.8480224609375,
1385.452392578125,
1303.618896484375,
1410.6219482421875,
1382.0694580078125,
1325.1285400390625,
1327.235595703125,
1308.025146484375,
1287.3770751953125,
1346.56396484375,
1496.635009765625,
1400.950439453125,
1454.3192138671875,
1421.5301513671875,
1451.3974609375,
1173.4150390625,
1201.14892578125,
1306.3328857421875,
1279.222412109375,
1239.5631103515625,
1221.1475830078125,
1266.7266845703125,
1338.903564453125,
1427.3262939453125,
1370.796875,
1300.9527587890625,
1308.78466796875,
1428.785400390625,
1328.6280517578125,
1311.848876953125,
1312.5467529296875,
1311.1656494140625,
1286.704833984375,
1286.867919921875,
1261.1734619140625,
1319.32177734375,
1389.0615234375,
1365.7154541015625,
1396.55859375,
1356.717529296875,
1493.014404296875,
1365.0535888671875,
1401.29052734375,
1531.4931640625,
1466.66943359375,
1426.822998046875,
1336.9034423828125,
1343.988037109375,
1491.9488525390625,
1446.2637939453125,
1286.028076171875,
1237.22314453125,
1210.5167236328125,
1234.502197265625,
1295.3580322265625,
1303.172119140625,
1261.639404296875,
1256.609130859375,
1258.96435546875,
1279.6431884765625,
1288.701416015625,
1326.328857421875,
1316.2303466796875,
1332.66455078125,
1311.399658203125
]
},
"downward_short_wave_radiation": {
"period": [
742.3240966796875,
749.7091064453125,
729.0908813476562,
720.8073120117188,
334.5498352050781,
116.18775177001953,
378.384765625,
675.8541259765625,
768.630615234375,
752.382080078125,
695.7022094726562,
636.063720703125,
147.31727600097656,
102.4050521850586,
273.645751953125,
669.8233642578125,
311.2471008300781,
162.25643920898438,
448.55413818359375,
102.42140197753906,
218.12075805664062,
420.56793212890625,
136.76303100585938,
403.8674011230469,
185.72427368164062,
107.33056640625,
141.29345703125,
356.212158203125,
565.3316650390625,
502.8492431640625,
575.0518188476562,
579.7432861328125,
618.920166015625,
612.0435791015625,
624.99365234375,
645.7866821289062,
262.70953369140625,
528.2586669921875,
545.6134643554688,
594.496337890625,
592.032958984375,
612.72216796875,
686.4899291992188,
653.4110107421875,
674.0394897460938,
700.8406372070312,
698.3465576171875,
651.31005859375,
671.9465942382812,
611.6170654296875,
652.2628784179688,
708.1170654296875,
705.8270263671875,
558.4963989257812,
684.1217651367188,
721.4019775390625,
723.0446166992188,
730.2137451171875,
749.357177734375,
753.1569213867188,
762.424560546875,
700.3219604492188,
584.1854248046875,
704.9605712890625,
707.047119140625,
741.0028076171875,
330.9869689941406,
727.745849609375,
736.8916015625,
207.54881286621094,
368.0106201171875,
644.8343505859375,
769.8765869140625,
800.9471435546875,
262.10003662109375,
337.7373352050781,
760.888427734375,
833.4388427734375,
846.8692626953125,
808.9389038085938,
826.2645874023438,
827.8402709960938,
865.1948852539062,
869.8006591796875,
881.271484375,
889.9754028320312,
891.0223388671875,
855.1575317382812,
895.611328125,
885.2378540039062,
897.8619995117188
]
},
"upward_long_wave_radiation": {
"period": [
1640.0843505859375,
1651.9576416015625,
1640.43994140625,
1653.0946044921875,
1658.1910400390625,
1620.226318359375,
1587.498046875,
1584.00244140625,
1603.44580078125,
1604.03173828125,
1636.075927734375,
1656.383544921875,
1625.700927734375,
1605.39404296875,
1577.5428466796875,
1585.0987548828125,
1601.945556640625,
1609.04833984375,
1618.42138671875,
1620.7275390625,
1608.40576171875,
1605.765869140625,
1625.3558349609375,
1634.1610107421875,
1588.314453125,
1533.6439208984375,
1565.6480712890625,
1549.1761474609375,
1552.488525390625,
1580.052978515625,
1591.06494140625,
1572.3233642578125,
1584.5291748046875,
1580.8900146484375,
1576.3839111328125,
1596.21826171875,
1609.5787353515625,
1598.0540771484375,
1618.33154296875,
1635.974365234375,
1638.3289794921875,
1490.8759765625,
1508.7969970703125,
1545.0338134765625,
1560.3970947265625,
1556.300048828125,
1551.8138427734375,
1569.23583984375,
1602.6915283203125,
1634.89208984375,
1634.222900390625,
1612.1490478515625,
1602.403076171875,
1632.791015625,
1611.985595703125,
1623.4119873046875,
1623.795166015625,
1626.491455078125,
1617.4642333984375,
1602.3197021484375,
1606.33837890625,
1611.337158203125,
1627.1026611328125,
1644.690185546875,
1652.9991455078125,
1650.3363037109375,
1640.979736328125,
1643.636962890625,
1643.0859375,
1597.553955078125,
1603.402099609375,
1628.16748046875,
1629.6346435546875,
1626.9090576171875,
1583.844970703125,
1572.3121337890625,
1573.393310546875,
1571.6724853515625,
1572.3040771484375,
1583.843994140625,
1612.130126953125,
1619.62109375,
1613.526611328125,
1613.3480224609375,
1626.663818359375,
1641.4197998046875,
1648.64794921875,
1666.6363525390625,
1667.5496826171875,
1650.906494140625,
1649.3310546875
]
},
"upward_short_wave_radiation": {
"period": [
129.03953552246094,
130.09609985351562,
126.432373046875,
126.62202453613281,
51.088417053222656,
18.74220085144043,
65.6014633178711,
115.97320556640625,
136.7119903564453,
133.0154266357422,
121.39058685302734,
110.32318115234375,
24.389034271240234,
17.37824249267578,
45.01287078857422,
116.30813598632812,
54.12192916870117,
24.479236602783203,
74.2733383178711,
15.077652931213379,
34.0496711730957,
66.43561553955078,
19.79493522644043,
65.90408325195312,
28.68067169189453,
16.20702362060547,
22.55319595336914,
55.47575759887695,
96.1532211303711,
86.34910583496094,
101.24629974365234,
98.08921813964844,
105.64970397949219,
104.14227294921875,
107.79875183105469,
110.7603530883789,
42.32927703857422,
88.3565673828125,
91.1112289428711,
104.23856353759766,
101.50498962402344,
109.98711395263672,
120.65325927734375,
111.48008728027344,
116.59042358398438,
120.1246109008789,
122.61815643310547,
112.2236328125,
114.36761474609375,
100.8069076538086,
109.58045196533203,
120.11746978759766,
120.2938003540039,
89.37309265136719,
115.0075454711914,
123.31220245361328,
123.5895004272461,
124.79615020751953,
128.72950744628906,
128.61863708496094,
131.40017700195312,
118.74166870117188,
98.86007690429688,
118.89837646484375,
117.688720703125,
125.99976348876953,
51.69040298461914,
123.49834442138672,
125.25086975097656,
34.35310363769531,
53.16965103149414,
105.85789489746094,
130.08958435058594,
136.77857971191406,
36.4160270690918,
58.66655731201172,
130.83670043945312,
142.94862365722656,
145.2069854736328,
138.9124298095703,
138.20941162109375,
138.9475860595703,
146.68923950195312,
148.3459930419922,
149.5684814453125,
151.1568145751953,
151.65037536621094,
144.9004364013672,
151.8493194580078,
149.4505615234375,
152.135986328125
]
},
"monthly_max_temperature": {
"period": [
19.893114058176675,
21.10474770863851,
22.778021176656086
],
"climate": [
22.803585815429688,
22.766723950703938,
23.12447738647461
]
},
"monthly_min_temperature": {
"period": [
14.535126145680746,
13.430932474136352,
14.411373710632324
],
"climate": [
13.96839952468872,
13.015181064605713,
12.738034089406332
]
},
"monthly_thermal_amplitude": {
"period": [
5.357987912495931,
7.673815234502157,
8.366647466023762
],
"climate": [
8.835186290740968,
9.751542886098227,
10.386443297068277
]
},
"monthly_temperature": {
"period": [
16.989828936258952,
16.66848478317261,
18.010067049662272
],
"climate": [
18.385992670059203,
17.890952507654827,
17.93125573794047
]
},
"monthly_accumulated_precipitation": {
"period": [
279.1913823187351,
7.909672245383263,
14.272454112768173
],
"climate": [
79.56297115981579,
50.58638706803322,
43.75544993579388
]
}
}
},
"meta": {
"updated_at": "2020-05-19 09:08",
"units": {
"precipitation": "mm.period",
"temperature": "C",
"humidity": "%",
"wind_speed": "m/s",
"wind_direction": "deg",
"pressure": "hpa",
"weather": [
"CC",
"PN",
"NB",
"EN",
"PI",
"NC",
"PC",
"CH"
],
"atmospheric": [
"Very_Stable",
"Stable",
"Unstable",
"Very_Unstable",
"Alert"
],
"sensation": "C",
"prec_prob": "%",
"thunderstorm": [
"Ok",
"Atention",
"Alert"
],
"frost": [
"Low chances",
"High chances",
"Snow"
],
"etp": "mm",
"short_wave_radiation": "W/m²",
"long_wave_radiation": "W/m²"
}
}
}
Hybrid comparison with climatology.
HTTP Request
GET https://nimbus.somar.io/hybrid/climate/monthly?latitude=<LAT>&longitude=<LON>&periods=<PERIODS>&reference=<REFERENCE>
Query Parameters
| Parameter | Description |
|---|---|
| latitude | Latitude |
| longitude | Longitude |
| city | City |
| initi_date | Initial Date |
| final_date | Final Date |
| reference | Reference name |
Errors
The Nimbus API uses the following error codes:
| Error Code | Meaning |
|---|---|
| 100 | Continue |
| 101 | Switching Protocols |
| 102 | Processing |
| 200 | OK |
| 201 | Created |
| 202 | Accepted |
| 203 | Non-Authoritative Information |
| 204 | No Content |
| 205 | Reset Content |
| 206 | Partial Content |
| 300 | Multiple Choices |
| 301 | Moved Permanently |
| 302 | Found |
| 303 | See Other |
| 304 | Not Modified |
| 305 | Use Proxy |
| 306 | Unused |
| 307 | Temporary Redirect |
| 308 | Permanent Redirect |
| 400 | Bad Request -- Your request is invalid. |
| 401 | Unauthorized -- Your API key is wrong. |
| 402 | Payment Required |
| 403 | Forbidden -- The kitten requested is hidden for administrators only. |
| 404 | Not Found -- The specified kitten could not be found. |
| 405 | Method Not Allowed -- You tried to access a kitten with an invalid method. |
| 406 | Not Acceptable -- You requested a format that isn't json. |
| 407 | Proxy Authentication Required |
| 408 | Request Timeout |
| 409 | Conflict |
| 410 | Gone -- The kitten requested has been removed from our servers. |
| 411 | Length Required |
| 412 | Precondition Failed |
| 413 | Request Entity Too Large |
| 414 | Request-URI Too Long |
| 415 | Unsupported Media Type |
| 416 | Requested Range Not Satisfiable |
| 417 | Expectation Failed |
| 418 | I'm a teapot. |
| 422 | Unprocessable Entity |
| 428 | Precondition Required |
| 429 | Too Many Requests -- You're requesting too many kittens! Slow down! |
| 431 | Request Header Fields Too Large |
| 451 | Unavailable For Legal Reasons |
| 500 | Internal Server Error -- We had a problem with our server. Try again later. |
| 501 | Not Implemented |
| 502 | Bad Gateway |
| 503 | Service Unavailable -- We're temporarily offline for maintenance. Please try again later. |
| 504 | Gateway Timeout |
| 505 | HTTP Version Not Supported |
| 511 | Network Authentication Required |
| 520 | Web server is returning an unknown error |
| 522 | Connection timed out |
| 524 | A timeout occurred |