Fragility to Resilience in Central and West Asia and North Africa (F2R-CWANA)

Satellite-based regional scale climate data extractor for CWANA

© IWMI-Central Asia, 2022

Short description

This web-app has been developed to ease the weather data acquisition process. This web-app allows the user to extract long-term monthly scale temperature and precipitation data for selected countries in the CWANA region. Users are required to indicate the country of interest and the desired time period. Consequently, the web-app presents annual weather information and time-series precipitation and temperature data as well as meteorological drought indices such as Standard Precipitation Index (SPI) and Standard Temperature Index (STI). Additionally, the platform allows users to generate spatial maps for weather parameters and to export data in the form of maps, tables and figures. This web-app automatically retrieves up-to-date weather data from the ERA5-Land archive.

In order to extract the regional scale climate data, please indicate the area of interest by selecting an area from the bar. The dynamics of climate parameters over time will be demonstrated in the graph and map view. By clicking the button in the corner of the graph, the table form and picture form of the data can be obtained.

Weather Data sources:

ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. This dataset includes all 50 variables as available on CDS.

The data presented here is a subset of the full ERA5-Land dataset post-processed by ECMWF. Monthly-mean averages have been pre-calculated to facilitate many applications requiring easy and fast access to the data, when sub-monthly fields are not required.

ERA5-Land data is available from 1981 to three months in real-time. More information can be found at the Copernicus Climate Data Store.

In addition to precipitation and temperature data, this tool allows monitoring of drought and flood events through WMO recommended Standard Precipitation Index (SPI) as well as the Standard Temperature Index (SPI).

SPI is based on the conversion of precipitation data into probabilities using gamma distribution. The negative output value of SPI represents drought intensity, with the following categories: > 0 is no drought, 0 to −0.99 is mild drought, −1.00 to −1.49 is moderate drought, −1.50 to −1.99 is severe drought and ≤ -2.00 is extreme drought (McKee et al., 1993). The main advantages of the SPI are a simple calculation that uses only precipitation data and its multi-temporal character.

The SPI is a z-score deviation from the mean in units of the standard deviation, calculated from the precipitation values for each pixel location of a composite period for each year during a given reference period. The equation below shows the general calculation of the SPI.

where SPIijk is the z-value for the pixel i during timeframe j for year k, Pijk is the precipitation value for pixel i during timeframe j for year k, Pij is the mean for pixel i during timeframe j over n years, and σij is the standard deviation of pixel i during week j over n years.

Moreover, the same approach has been used for temperature-based drought events using Standard Temperature Index. The same formula and categories have been employed. In order to have the same categorization as SPI, STI values have been inverted by multiplying by -1.

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This tool has been developed for scientific purposes within the project "F2R-CWANA - From Fragility to Resilience in Central and West Asia and North Africa" implemented by IWMI-Central Asia under CWANA initiative. The primary CGIAR Action Area is Resilient Agrifood Systems. The geographical scope of the project: Egypt, Lebanon, Morocco, Uzbekistan, Sudan.