The CLimate Information toolKit (CLIK) Open Application Program Interface(API) is a service providing programmatic access to data.
In this page you will find explanations and examples showing how to use the CLIK API.
Please process as follows:
Once the API client is installed, it can be used to request data from the datasets.
You can download using the below sample python code.
Dataset:
#!/usr/bin/env python import apccapi c = apccapi.Client() c.retrieve( { 'jobtype': 'MME', 'dataset': 'MME_3MONTH', 'type': 'FORECAST', 'method': 'SCM', 'variable': ['prec', 't2m'], 'period': ['Monthly mean'], 'yearmonth': ['201909'] }, 'mme3.zip' )
#!/usr/bin/env python import apccapi c = apccapi.Client() c.retrieve( { 'jobtype': 'MME', 'dataset': 'MME_6MONTH', 'type': 'FORECAST', 'method': 'GAUS', 'variable': ['prec', 't2m'], 'period': ['Monthly mean', 'Seasonal mean'], 'yearmonth': ['201909'] }, 'mme6.zip' )
#!/usr/bin/env python import apccapi c = apccapi.Client() c.retrieve( { 'jobtype': 'MODEL', 'dataset': 'MODEL', 'type': 'FORECAST', 'institute': 'APCC', 'model': 'SCOPS', 'variable': ['prec', 't2m'], 'yearmonth': ['201909'] }, 'model.zip' )
#!/usr/bin/env python import apccapi c = apccapi.Client() c.retrieve( { 'jobtype': 'CMIP5', 'dataset': 'CMIP5', 'code': 'AD', }, 'cmip5.zip' )
The CLimate Information toolKit (CLIK) Open Application Program Interface(API) is a service providing programmatic access to data.
In this page you will find explanations and examples showing how to use the CLIK API.
Please process as follows:
Once the API client is imported, it can be used to request data from the datasets.
You can download using the below sample java code.
Dataset:
package my.package; import org.apcc.api.client.APIClient; import org.apcc.api.jobdetails.Dataset; import org.apcc.api.jobdetails.JobDetailsMME; public class ClientTest { public static void main(String[] args) { try { APIClient client = new APIClient(); JobDetailsMME mme = new JobDetailsMME(); mme.setDataset(Dataset.DATASET_MME_3MON.datasetName); mme.setType("FORECAST"); mme.setMethod("GAUS"); mme.addPeriod("Monthly mean"); mme.addYearmonth("201909"); mme.addVariable("prec"); mme.addVariable("t2m"); client.run(mme, "mme3.zip"); } catch(Exception ex) { ex.printStackTrace(); } } }
package my.package; import org.apcc.api.client.APIClient; import org.apcc.api.jobdetails.Dataset; import org.apcc.api.jobdetails.JobDetailsMME; public class ClientTest { public static void main(String[] args) { try { APIClient client = new APIClient(); JobDetailsMME mme = new JobDetailsMME(); mme.setDataset(Dataset.DATASET_MME_6MON.datasetName); mme.setType("FORECAST"); mme.setMethod("GAUS"); mme.addPeriod("Monthly mean"); mme.addYearmonth("201909"); mme.addVariable("prec"); mme.addVariable("t2m"); client.run(mme, "mme6-1.zip"); // json type String details = "{\"jobtype\":\"MME\",\"dataset\":\"MME_6MONTH\",\"type\":\"FORECAST\",\"method\":\"SCM\",\"variable\":[\"prec\",\"t2m\"],\"period\":[\"Monthly mean\"],\"yearmonth\":[\"201909\"]}"; client.run(details, "mme6-2.zip"); } catch(Exception ex) { ex.printStackTrace(); } } }
package my.package; import org.apcc.api.client.APIClient; import org.apcc.api.jobdetails.Dataset; import org.apcc.api.jobdetails.JobDetailsModel; public class ClientTest { public static void main(String[] args) { try { APIClient client = new APIClient(); JobDetailsModel model = new JobDetailsModel(); model.setDataset(Dataset.DATASET_MODEL.datasetName); model.setType("FORECAST"); model.setInstitute("APCC"); model.setModel("SCOPS"); model.addYearmonth("202002"); model.addYearmonth("202003"); model.addVariable("prec"); model.addVariable("t2m"); client.run(model, "model.zip"); } catch(Exception ex) { ex.printStackTrace(); } } }
package my.package; import org.apcc.api.client.APIClient; import org.apcc.api.jobdetails.Dataset; import org.apcc.api.jobdetails.JobDetailsCMIP5; public class ClientTest { public static void main(String[] args) { try { APIClient client = new APIClient(); JobDetailsCMIP5 cmip5 = new JobDetailsCMIP5(); cmip5.setDataset(Dataset.DATASET_CMIP5.datasetName); cmip5.setCode("AD"); client.run(cmip5, "cmip5.zip"); } catch(Exception ex) { ex.printStackTrace(); } } }
The CLimate Information toolKit (CLIK) Open Application Program Interface(API) is a service providing programmatic access to data.
In this page you will find explanations and examples showing how to use the CLIK Clipping API.
Please process as follows:
Once the API client is imported, it can be used to request data from the datasets.
You can download using the below sample Python code.
Clipping Open API currently provides only MME Models.
Dataset:
import clippingapi import json import requests c = clippingapi.Client() request = { 'lead_month': '3-MON', # 3-MON, 6-MON 'variable': 'prec', # prec, slp, sst, t2m, t850, z500 'method': 'SCM', # SCM, GAUS 'period': 'Monthly mean', # Monthly mean, #Seasonal mean 'iyear': '2021', # Issued Year 'imonth': '2', # Issued Month 'cowest': '188', # coordinate of west 'coeast': '191', 'conorth': '-11', 'cosouth': '-15', 'return_type': 'png' # Clipping API only provides either .nc or .png files. } c.clip(request)
import clippingapi import json import requests c = clippingapi.Client() request = { 'lead_month': '6-MON', # 3-MON, 6-MON 'variable': 'prec', # prec, slp, sst, t2m, t850, z500 'method': 'SCM', # SCM, GAUS 'period': 'Monthly mean', # Monthly mean, #Seasonal mean 'iyear': '2021', # Issued Year 'imonth': '2', # Issued Month 'cowest': '188', 'coeast': '191', 'conorth': '-11', 'cosouth': '-15', 'return_type': 'nc' # Clipping API only provides either .nc or .png files. } c.clip(request)