Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset. CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring. The z-score (or standard score) is the signed fractional number of standard deviations by which the value of an observation or data point is above the mean value of what is being observed or measured. Observed values above the mean have positive standard scores, while values below the mean have negative standard scores. Z-scores reveals whether a score is typical for a specified data set or if it is atypical. Approximately 5km (0.05°) unit: "mm" dataType: "Float32" noDataValue: -9999

The Secondary Roads Density raster layer is part of the Global Roads Inventory Project (GRIP) dataset, developed to provide a more recent and consistent global roads dataset for use in global environmental and biodiversity assessment models like GLOBIO.

Forecasts of Monthly Precipitation Anomalies. More info on the model in the BAMS article describing the project (Kirtman et al. 2014) at https://journals.ametsoc.org/view/journals/bams/95/4/bams-d-12-00050.1.xml Source: North American Multi-Model Ensemble Approximately 111km (1°) unit: "mm" dataType: "Float32" noDataValue: -9999

Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset. CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring. Approximately 5km (0.05°) unit: "mm" dataType: "Float32" noDataValue: -9999

The Tertiary Roads Density raster layer is part of the Global Roads Inventory Project (GRIP) dataset, developed to provide a more recent and consistent global roads dataset for use in global environmental and biodiversity assessment models like GLOBIO.

The Local Roads Density raster layer is part of the Global Roads Inventory Project (GRIP) dataset, developed to provide a more recent and consistent global roads dataset for use in global environmental and biodiversity assessment models like GLOBIO.

Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset. CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring. The z-score (or standard score) is the signed fractional number of standard deviations by which the value of an observation or data point is above the mean value of what is being observed or measured. Observed values above the mean have positive standard scores, while values below the mean have negative standard scores. Z-scores reveals whether a score is typical for a specified data set or if it is atypical. Approximately 5km (0.05°) unit: "mm" dataType: "Float32" noDataValue: -9999

Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset. CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring. Approximately 5km (0.05°) unit: "mm" dataType: "Float32" noDataValue: -9999

The Highways Density raster layer is part of the Global Roads Inventory Project (GRIP) dataset, developed to provide a more recent and consistent global roads dataset for use in global environmental and biodiversity assessment models like GLOBIO.

Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset. CHIRPS incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and seasonal drought monitoring. Approximately 5km (0.05°) unit: "mm" dataType: "Float32" noDataValue: -9999