View Source

ERA5–Drought is freely accessible to anyone, anywhere in the world via the ECMWF Cross Data Store (XDS): LINK

The landing page provides an overview of the dataset, its availability and metadata. Under the tab 'Download Data' users can explore the dataset through a dynamic web interface that automatically indicates availability of the selected index for a specific time period and vice versa. To download data, users need to register under an open-source license. After login, data can be downloaded via the web interface directly, through the submission of a request, or using an Application Program Interface (API). Codes for the selection of the data via the API or python scripts are provided upon selection and facilitate access to a broad range of users.

Licensing

The ERA–Drought dataset, like any other dataset included in one of the ECMWF or Copernicus Climate Data Stores, is subject to the CC-BY 4.0 license. This license follows a full free and open data policy, allowing anyone, anywhere in the world, to access and use the data.

How to install the API

Instructions on how to install the API can be found here: LINK

Download examples

Example 1: SPI-1 for all months in 2023

import cdsapi
dataset = "derived-drought-historical"
request = {
    'variable': ['standardised_precipitation_index'],
    'accumulation_period': ['12'],
    'product_type': ['reanalysis'],
    'version': '1_0',
    'year': ['2023'],
    'month': ['1','2','3','4','5','6','7','8','9','10','11','12']
}
client = cdsapi.Client()
client.retrieve(dataset, request).download()

Example 2: SPI-12 for all calendar years in 2020–2023

import cdsapi
dataset = "derived-drought-historical"
request = {
    'variable': ['standardised_precipitation_index'],
    'accumulation_period': ['12'],
    'product_type': ['reanalysis'],
    'version': '1_0',
    'year': ['2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022', '2023'],
    'month': ['12']
}
client = cdsapi.Client()
client.retrieve(dataset, request).download()

Example 3: Quality criteria for the SPI-12 retrieved in Example 2, i.e. for December data

import cdsapi
dataset = "derived-drought-historical"
request = {
    'variable': ['probability_of_zero_precipitation_spi', 'test_for_normality_spi'],
    'accumulation_period': ['12'],
    'product_type': ['reanalysis'],
    'version': '1_0',
    'month': ['12']
}
client = cdsapi.Client()
client.retrieve(dataset, request).download()

Example 4: Ensemble data for the SPI-12 for each calendar year (same as Example 2 but downloading the ensemble)

import cdsapi

dataset = "derived-drought-historical"
request = {
    'variable': ['standardised_precipitation_index'],
    'accumulation_period': ['12'],
    'product_type': ['ensemble_members'],
    'version': '1_0',
	'year': ['2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016', '2017', '2018', '2019', '2020', '2021', '2022', '2023'],
    'month': ['12']
}

client = cdsapi.Client()
client.retrieve(dataset, request).download()