Environmental Data Platform


Standardised Precipitation-Evapotranspiration Index - ERA5_QM SPEI-6 detail

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The Standardized Precipitation-Evapotranspiration Index (SPEI) represents a standardized measure of what a certain value of surface water balance (precipitation minus potential evapotranspiration) over the selected time period means in relation to expected value of surface water balance for this period. SPEI is calculated on different time scales (1, 2, 3, 6, 12 months). The value of the SPEI index around 0 represents the normal expected conditions for the surface water balance in the selected period based on the long-term average (1981-2020). The value of 1 represents approximately one standard deviation of the surplus in the surface water balance, while the value of -1 is about one standard deviation of the deficit. Drought is usually defined as period when SPEI values fall below -1. Input precipitation data is downscaled from ERA5 reanalysis using quantile mapping. Contains modified Copernicus Climate Change Service information [1978-current year]; Contains modified Copernicus Atmosphere Monitoring Service information [1978-current year]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

Land use, Land cover, collection, SPEI, standardised precipitation-evapotranspiration index, surface water balance anomalies, ERA5, ADO project, ADO, N/A

CC BY 4.0

eurac research - Institute for Earth Observation
bartolomeo.ventura@eurac.edu
Viale Druso, 1 / Drususallee 1, eurac research, Bolzano, Autonomous Province of Bolzano, 39100, Italy


1978-12-31T12:00:00Z 2022-03-24T12:00:00Z

WGS-84 (3035:EPSG)

Grid


Snippet code
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#remotes::install_github(repo="Open-EO/openeo-r-client",ref="develop", dependencies=TRUE)
library(openeo)

# login ----
euracHost = "https://openeo.eurac.edu"
conf = read.csv("./pwd/openeo_eurac_conf.csv") # adapt this path to where you store the conf file.
conf = list(client_id = conf$client_id, secret = conf$secret)
eurac = connect(host = euracHost)
prov = list_oidc_providers()
prov$Eurac_EDP_Keycloak
login(login_type = "oidc", provider = prov$Eurac_EDP_Keycloak, config = conf, con = eurac)

# load colleaction - save result ----
p = processes()
data = p$load_collection(id = "https://openeo.eurac.edu/collections/", 
                                             spatial_extent = list(west = 4.056369,
                                                                                 east = 17.360183,
                                                                                 south = 42.853812,
                                                                                 north = 50.310635),
                                             temporal_extent = list("1978-12-31T12:00:00Z", "2022-03-24T12:00:00Z"))
result = p$save_result(data = data, format="netCDF")

# download results ----
# either directly (suitable for smaller requests)
compute_result(result,
                             format = "netCDF",
                             output_file = "https://openeo.eurac.edu/collections/.nc", 
                             con = eurac)

# or start a batch job (suitable for larger requests)
job_id = create_job(graph = result,
                                   title = "https://openeo.eurac.edu/collections/",
                                   description = "https://openeo.eurac.edu/collections/",
                                   format = "netCDF")
start_job(job = job_id)
result_list = list_results(job = job_id)
download_results(job = job_id, folder = ".")
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#pip install openeo
import openeo

# login ----
euracHost        = "https://openeo.eurac.edu"
eurac = openeo.connect(euracHost).authenticate_oidc(client_id="openEO_PKCE")

# load collection - save result ----
data = eurac.load_collection("https://openeo.eurac.edu/collections/",spatial_extent={'west':4.056369,'east':17.360183,'south':42.853812,'north':50.310635},temporal_extent=["1978-12-31T12:00:00Z", "2022-03-24T12:00:00Z"])

result = data.save_result(format="NetCDF")

# download results ----
# either directly (suitable for smaller requests)
data.download("https://openeo.eurac.edu/collections/.nc",format="netCDF")

# or start a batch job (suitable for larger requests)

job = result.send_job(title = "https://openeo.eurac.edu/collections/",description = "https://openeo.eurac.edu/collections/",out_format = "netCDF")
jobId = job.job_id
job.start_job()

jobResults = job.get_results()
jobResults.download_files('.')

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