This web map is a component of the Global Drought Monitor. It contains global drought data.Data and Sources: North American Drought Monitor (NADM) - National Drought Mitigation Center (NDMC)European Combined Drought Indicator (CDI) - European Drought Observatory (EDO)CMORPH Daily Standardized Precipitation Index - The National Oceanic and Atmospheric Administration (NOAA) National Integrated Drought Information System (NIDIS)/National Centers for Environmental InformationGPCC Global Drought Index (DI) - Deutscher Wetterdienst (DWD)GPCC Standardized Precipitation Index (SPI) - The National Oceanic and Atmospheric Administration (NOAA) National Integrated Drought Information System (NIDIS)/National Centers for Environmental InformationGPCC Standardized Precipitation Evapotranspiration Index (SPEI) - Consjo Superior de Investigaciones Cientificas (CSIC)MERRA2 Evaporative Demand Drought Index (EDDI) - National Oceanic and Atmospheric Administration (NOAA) Earth System Research Lab (ESRL)VIIRS Vegetation Health Index (VHI) - National Ocean and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS)MODIS Evaporative Stress Index (ESI) - National Aeronautics and Space Administration (NASA)GRACE-Based Root Zone Soil Moisture - National Aeronautics and Space Administration (NASA)/German Aerospace Center (DLR)GRACE-Based Shallow Groundwater - National Aeronautics and Space Administration (NASA)/German Aerospace Center (DLR)GRACE-Based Surface Soil Moisture - National Aeronautics and Space Administration (NASA)/German Aerospace Center (DLR)Global Gridded Population - Center for International Earth Science Information Network (CIESIN)

Global Drought Monitor

The SPEI Global Drought Monitor offers near real-time information about drought conditions at the global scale, with a 1 degree spatial resolution and a monthly time resolution. SPEI time-scales between 1 and 48 months are provided. The calibration period for the SPEI is January 1950 to December 2010. The starting date of the dataset is 1955 in order to provide common information across the different SPEI time-scales.

The dataset is updated during the first days of the following month based on the most reliable and updated sources of climatic data. Mean temperature data are obtained from the NOAA NCEP CPC GHCN_CAMS gridded dataset. Monthly precipitation sums data are obtained from the 'first guess' Global Precipitation Climatology Centre (GPCC). The CPC data with an original resolution of 0.5º, is interpolated to the resolution of 1º.

Currently, the SPEI Global Drought Monitor is based on the Thortnthwaite equation for estimating potential evapotranspiration, PET. This is due to the lack of real-time data sources for computing more robust PET estimations which have larger data requirements. The main advantage of the SPEI Global Drought Monitor is thus its near real-time character, a characteristic best suited for drought monitoring and early warning purposes. For long-term analysis, however, other datasets are to be preferred that rely on more robust methods of PET estimation. Use of the SPEIbase dataset, which is based on the FAO-56 Penman-Monteith model, is thus recommended for climatological studies of drought.

Metadata

Dimensions

longitude: geographical coordinates; latitude: geographical coordinates; time: months.

Variables

spei long_name: "Standard Precipitation-Evapotranspiration Index"; units: "z values"; type: float; range: -3.0E32 to 3.0E32; missing value: 3.0E33f; not a number: nan; longitude long_name: "Longitude values"; cartesian_axis: "X"; units: "degrees_E"; type: float; interval: 0.5; range : -179.75, 179.75; latitude long_name: "Latitude values"; cartesian_axis: "Y"; units: "degrees_N"; type: float; interval: 0.5; range : -89.75, 89.75; time long_name: "Time coordinate values"; cartesian_axis: "T"; units: "Months since 1901-01"; calendar: "Gregorian"; type: double integer; interval: 1; range: January 1901, December 2011;

About this AppThe Drought Aware app provides information about areas in the U.S. affected by drought across different time intervals and over multiple drought intensities. The app shows summaries about the affected population and the potential impacts to crops, agricultural labor, rivers, and reservoirs.Use this AppDisplay drought maps for different weeks by clicking on the time-series chart (top bar) or by scrolling through time using the sector chart (top-left). Hover on each drought intensity level in the sector chart to highlight the areas on the map and display the area percentage. Click on the map to display a panel with summary information for the selected area. The panel includes three categories (1) population, (2) water, and (3) agriculture. App CategoriesThe Drought Aware app summarizes information in three categories:Population: displays the estimated people and households affected by drought at each intensity level, describes some of the vulnerable populations, and lists the related drought risk indexes. The data is available at County and State levels. Water: depicts the major local rivers, the average inter-annual river flow, and the relevant local reservoirs. The data is available at the Subregion Hydrologic Units (HUC4)Agriculture: shows the potential economic impact by major crop, the affected labor, and the agricultural exposure to droughts. The data is available at County and State levels. Drought Definitions Abnormally Dry (D0) Going into drought there is short-term dryness slowing planting, growth of crops or pastures. Coming out of drought there are some lingering water deficits; pastures or crops not fully recovered. Moderate Drought (D1) Some damage to crops and pastures. Streams, reservoirs, or wells low, some water shortages developing or imminent. Voluntary water-use restrictions requested. Severe Drought (D2) Crop or pasture losses likely. Water shortages are common. Water restrictions imposed. Extreme Drought (D3) Major crop/pasture losses. Widespread water shortages or restrictions. Exceptional Drought (D4) Exceptional and widespread crop/pasture losses. Shortages of water in reservoirs, streams, and wells create water emergencies.Data SourcesThe data layers used in this app can be found in ArcGIS Living Atlas of the World:U.S. Drought Monitor American Community Survey (ACS)USDA Census of AgricultureFEMA National Risk IndexNational Water Model (NWM)National Hydrography Dataset (NHD)National Inventory of Dams (NID)National Boundary Dataset (WBD)UpdateThe data behind the app is updated every week once a U.S. Drought Monitor map is released. The update process is automated using a live feed routine. This layer is provided for informational purposes and is not monitored 24/7 for accuracy and currency.RevisionsOct 16, 2024: Official release of the Drought Aware app.

This map displays global drought products and indices and serves as a component in other Global and North American Drought Monitor products.

Drought is a natural hazard with far-reaching impacts that range from economic losses to loss of agriculture and livelihood. Drought can cause or exacerbate water, food, and national security hazards. The maps, tools, and resources on this page address drought conditions around the world.

The Global Drought Information System (GDIS) is a tool for exploring global drought data and learning more about global drought resources, research and education. Tool Components:Monitoring DroughtForecasting DroughtManagement ToolsResearch & EducationData and Sources: North American Drought Monitor (NADM) - National Drought Mitigation Center (NDMC)European Combined Drought Indicator (CDI) - European Drought Observatory (EDO)GPCC Global Drought Index (DI) - Deutscher Wetterdienst (DWD)GPCC Standardized Precipitation Index (SPI) - The National Oceanic and Atmospheric Administration (NOAA) National Integrated Drought Information System (NIDIS)/National Centers for Environmental InformationGPCC Standardized Precipitation Evapotranspiration Index (SPEI) - Consjo Superior de Investigaciones Cientificas (CSIC)MERRA2 Evaporative Demand Drought Index (EDDI) - National Oceanic and Atmospheric Administration (NOAA) Earth System Research Lab (ESRL)VIIRS Vegetation Health Index (VHI) - National Ocean and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS)MODIS Evaporative Stress Index (ESI) - National Aeronautics and Space Administration (NASA)GRACE-Based Root Zone Soil Moisture - National Aeronautics and Space Administration (NASA)/German Aerospace Center (DLR)GRACE-Based Shallow Groundwater - National Aeronautics and Space Administration (NASA)/German Aerospace Center (DLR)GRACE-Based Surface Soil Moisture - National Aeronautics and Space Administration (NASA)/German Aerospace Center (DLR)Global Gridded Population - Center for International Earth Science Information Network (CIESIN)

Drought occurs when a region has an imbalance between water supply and water demand over an extended period of time. Droughts can have significant environmental, economic, and social consequences. Between 1980 and the present time, the cost of drought exceeded 100 billion dollars, making drought monitoring a key factor in planning, preparedness, and mitigation efforts at all levels of government.Data Source: U.S. Drought Monitor, National Drought Mitigation Center, GISData DownloadUpdate Frequency:  Weekly, typically on Friday around 10:00AM UTC. Using the Aggregated Live Feed MethodologyFor Full Historical data: See USA Drought Intensity 2000 - Present Online Item!For Standard Symbology Style: See USA Drought Intensity - Current Conditions - Standard Color Scheme Online Item!Dataset Summary:This feature service provides access to current drought intensity categories for the entire USA. These data have been produced weekly since January 4, 2000 by the U.S. Drought Monitor, see the Full Historical data for the full time series. Drought intensity is classified according to the deviation of precipitation, stream flow, and soil moisture content from historically established norms, in addition to subjective observations and reported impacts from more than 350 partners across the country. New map data is released every Thursday to reflect the conditions of the previous week.Layer Summary:'US_Drought_Current': Polygon areas for most recent weekThis Layer contains a series of drought classification summaries that fall into two groups: Categorical Percent Area and Cumulative Percent Area.Categorical Percent Area statistic is the percent of the area in a certain drought category and excludes areas that are better or worse. For example, the D0 category is labeled as such and only shows the percent of the area experiencing abnormally dry conditions.Cumulative Percent Area statistics combine drought categories for a comprehensive percent of area in drought. For example, the D0-D4 category shows the percent of the area that is classified as D0 or worse.Drought Classification Categories are as follows:ClassDescriptionPossible ImpactsD0Abnormally DryGoing into drought: short-term dryness slows growth of crops/pastures. Coming out of drought: some lingering water deficits; drops/pastures not fully recovered.D1Moderate DroughtSome damage to crops/pastures; streams, reservoirs, or wells are low with some water shortages developing or imminent; voluntary water-use restrictions requested.D2Severe DroughtCrop/pasture losses are likely; water shortages are common and water retrictions are imposed.D3Extreme DroughtMajor crop/pasture losses; widespread water shortages or restrictions.D4Exceptional DroughtExceptional and widespread crop/pasture losses; shortages of water in reservoirs, streams, and wells creating water emergencies.The U.S. Drought Monitor is produced in partnership between the National Drought Mitigation Center at the University of Nebraska-Lincoln, the United States Department of Agriculture, and the National Oceanic and Atmospheric Administration. It is the drought map that the USDA and IRS use to define which farms have been affected by drought conditions, defining who is eligible for federal relief funds.

What does the data show?

The Drought Severity Index is not threshold based. Instead, it is calculated with 12-month rainfall deficits provided as a percentage of the mean annual climatological total rainfall (1981–2000) for that location. It measures the severity of a drought, not the frequency.

12-month accumulations have been selected as this is likely to indicate hydrological drought. Hydrological drought occurs due to water scarcity over a much longer duration (longer than 12 months). It heavily depletes water resources on a large scale as opposed to meteorological or agricultural drought, which generally occur on shorter timescales of 3-12 months. However this categorisation is not fixed, because rainfall deficits accumulated over 12-months could lead to different types of drought and drought impacts, depending on the level of vulnerability to reduced rainfall in a region.

The DSI 12 month accumulations are calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period.

What are the possible societal impacts?

The DSI 12-month accumulations measure the drought severity. Higher values indicate more severe drought. The DSI is based on 12-month rainfall deficits. The impacts of the differing length of rainfall deficits vary regionally due to variation in vulnerability. Depending on the level of vulnerability to reduced rainfall, rainfall deficits accumulated over 12 months could lead to meteorological, agricultural and hydrological drought.

What is a global warming level?

The DSI 12-month accumulations are calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.

The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the DSI 12-month accumulations, an average is taken across the 21 year period.

We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.

What are the naming conventions and how do I explore the data?

This data contains a field for each global warming level and two baselines. They are named ‘DSI12’ (Drought Severity Index for 12 month accumulations), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. E.g. 'DSI12 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'DSI12 2.5 median' is 'DSI12_25_median'.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘DSI12 2.0°C median’ values.

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, DSI 12 month accumulations were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.

Useful links

This dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report. Further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal

scPDSI consists of global maps of monthly self-calibrating Palmer Drought Severity Index (scPDSI) which have been calculated for 1901-2009 based on the CRU TS 3.10.01 data sets.

The Palmer Drought Severity Index (PDSI) is a measure of soil moisture availability that has been used extensively to study droughts and wet spells in the contiguous USA and elsewhere, particularly as the primary indicator of the severity and extent of recent droughts. Recently, the PDSI has become more popular as a drought metric in studies quantifying possible trends in future soil moisture availability and it has been used as the basis for reconstructing past variations in drought.

Historic Agricultural Drought Frequency Maps depict the frequency of severe drought in areas where 30 percent/50 percent of the cropland/grassland has been affected. The historical frequency of severe droughts (as defined by ASI) is based on the entire ASI times series (1984-2023).Phenomenon Mapped: Historic Drought FrequencyUnits: Frequency (percentage)Time Interval: Multi-annualTime Extent: 1984-2023Cell Size: 1 kmPixel Type: 32-bit Signed IntegerData Projection: WGS 1984Mosaic Projection: WGS 1984 Web MercatorSource: Food and Agriculture Organization of the United NationsUpdate Cycle: Annual, 5th of July for the previous crop yearFormula: The number of years when land affected>30 percent/50 percent occurred/(2023-1984+1) *100Pixel value ranges from 0-100 (unit: percentage). Flag: 252: no data; 253: no season; 254: no cropland/grassland.Explore this and related data in this web application.More information please visit FAO GIEWS Earth Observation website

Russia Mean Drought Index data was reported at -0.906 NA in 2021. This records an increase from the previous number of -1.241 NA for 2020. Russia Mean Drought Index data is updated yearly, averaging 0.166 NA from Dec 1960 (Median) to 2021, with 62 observations. The data reached an all-time high of 2.600 NA in 1966 and a record low of -1.408 NA in 2016. Russia Mean Drought Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Environmental: Climate Risk. The SPEI fulfills the requirements of a drought index since its multi-scalar character enables it to be used by different scientific disciplines to detect, monitor, and analyze droughts. Like the sc-PDSI and the SPI, the SPEI can measure drought severity according to its intensity and duration, and can identify the onset and end of drought episodes. The SPEI allows comparison of drought severity through time and space, since it can be calculated over a wide range of climates, as can the SPI.;Global SPEI database (SPEIbase). https://spei.csic.es/database.html;;

Global hydrological model used to carry out simulations of daily river discharge and runoff. Model forced using daily meteorological fields of precipitation, temperature, and radiation for four different time periods, namely: (a) 1960-1999, which represents the baseline climate; (b) 2010-2049 (representing 2030); (c) 2030-2069 (representing 2050); and (d) 2060-2099 (representing 2080). The meteorological data for the baseline climate are taken from the WATCH Forcing data (WFD) (Weedon et al., 2011). The future meteorological data are provided by the ISI-MIP project, and consist of bias-corrected data (Hempel et al., 2013) for an ensemble of five Global Climate Models (GCMs) from the ISIMIP project (Taylor et al., 2012). The GCMs used are GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M. For this study, we used climate projections based on 2 representative concentration pathways (RCPs), namely RCP2.6 and RCP8.5. The resolution of the input meteorological datasets for the current and future climate conditions is 0.5° x 0.5°.

The resulting drought hazard maps express probabilities of occurrence of the intensity of drought conditions. The intensity is measured as the number of months of long-term mean discharge which would be needed to overcome the maximum accumulated deficit volume under a certain return period. The deficit volume is calculated as the monthly flow deficit below the 20-percentile climatological flow. The different return period maps were generated by performing extreme value analysis on the yearly extreme values of the number of months of long-term mean discharge needed to overcome a discharge deficit. Please note that the used climate forcing in future climate still contains bias due to inter and intra annual variability in rainfall. This is not resolved in the bias correction scheme. Therefore, the drought hazard maps prepared with the GCM data still contain bias. This bias should be corrected by a comparison between 1960-1999 GCM runs of risk estimates and 1960-1999 EU-WATCH runs of risk estimates.

Further reading in: Veldkamp, T.I.E., Wada, Y., de Moel, H., Kummu, M., Eisner, S., Aerts, J.C.J.H., Ward, P.J. (in press). Changing mechanism of global water scarcity events: impacts of socioeconomic changes and inter-annual hydro-climatic variability. Global Environmental Change. DOI: 10.1016/j.gloenvcha.2015.02.011

Droughts are natural disasters characterized by atypical dry conditions and high temperatures that persist over a period of time. Droughts disturb natural ecosystems and human activities such as food production. The Standardized Precipitation-Evapotranspiration Index (SPEI) is used for the analysis and monitoring of drought events. SPEI is calculated from difference between precipitation (P) and potential evapotranspiration (PET). SPEI is calculated at different periods (e.g. 1, 3, 6, 9, or 12 months) for drought characterization at different time scales. P - PET is aggregated at different time scales for a given period, allowing drought characterization for short, medium, and long-term trends.This layer shows the classified SPEI values from the SPEI Global Drought Monitor. Each SPEI (e.g. SPEI3) shows the monthly drought index for the specified time scale (e.g. 3-month SPEI).What can you do with this layer? This layer can be used to identify areas subject to dry conditions and assess its frequency over time.Source:SPEI Global Drought MonitorRevisions:Feb 25, 2022: Official release of Feature Service offering.

"مؤشر الجفاف في الولايات المتحدة" هو خريطة يتم إصدارها كل خميس، وتعرض أجزاء من الولايات المتحدة تعاني من الجفاف. تستخدم الخريطة خمسة تصنيفات: جفاف غير طبيعي (D0)، ما يشير إلى المناطق التي قد تكون في طريقها إلى الجفاف أو تتعافى منه، وأربعة مستويات من الجفاف: معتدل (D1)، وشديد (D2)، وقاسٍ …

Droughts are natural disasters characterized by atypical dry conditions and high temperatures that persist over a period of time. Droughts disturb natural ecosystems and human activities such as food production. The Standardized Precipitation-Evapotranspiration Index (SPEI) is used for the analysis and monitoring of drought events. SPEI is calculated from difference between precipitation (P) and potential evapotranspiration (PET). SPEI is calculated at different periods (e.g. 1, 3, 6, 9, or 12 months) for drought characterization at different time scales. P - PET is aggregated at different time scales for a given period, allowing drought characterization for short, medium, and long-term trends.This layer shows the classified SPEI values from the SPEI Global Drought Monitor. Each SPEI (e.g. SPEI3) shows the monthly drought index for the specified time scale (e.g. 3-month SPEI).What can you do with this layer? This layer can be used to identify areas subject to dry conditions and assess its frequency over time.Source:SPEI Global Drought MonitorRevisions:Feb 25, 2022: Official release of Feature Service offering.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Climate Reconstruction. The data include parameters of climate reconstructions|tree ring with a geographic _location of United States Of America. The time period coverage is from 350 to -49 in calendar years before present (BP). See metadata information for parameter and study _location details. Please cite this study when using the data.

The crop condition mapping product monitors cropland pixels affected by drought using Vegetation Indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Red Edge (NDRE), and Green Normalized Difference Vegetation Index (GNDVI), generated from Sentinel-2 images. A binary classification is performed to map drought-affected and unaffected croplands. A random forest model is trained using VI time series data from both drought and non-drought years for each Agro-Ecological Zone (AEZ). The outputs display the spatial characteristics of drought impacts on croplands at a national scale. The dataset includes seasonal crop condition maps for 2016-2022 at a 20m spatial resolution, classifying pixels as 0: non-croplands, 1: unaffected pixels, and 2: drought-affected pixels. Two maps per year are provided for the long rains (season 1) and short rains (season 2). The output is validated through comparison with other datasets such as the Global Drought Observatory, FAO Agriculture Stress Index System (ASIS), East Africa Drought Watch, and reports from the National Drought Management Authority (NDMA). Additionally, user validation has been conducted through engagement with relevant stakeholders, ensuring the outputs align with ground realities and user needs. Each map is accompanied with quality maps based on number of available clear sky observations and classification probability.

Agriculture is an important primary production sector in Canada. Agricultural production, profitability, sustainability and food security depend on many agrometeorological factors, including drought. The Canadian Drought Outlook predicts whether drought across Canada will emerge, stay the same or get better over the target month. The drought outlook is issued on the first Thursday of each calendar month and is valid for 32 days from that date. This series of datasets has been created by AAFC’s National Agroclimate Information Service (NAIS) of the Agro-Climate, Geomatics and Earth Observations (ACGEO) Division of the Science and Technology Branch. The Canadian Drought Outlook maps are generated using Environment and Climate Change Canada’s (ECCC) Global Ensemble Prediction (GEPs) forecast data. Agroclimate indices, such as the Standard Precipitation Index (SPI), the Standard Precipitation Evaporation Index (SPEI), and the Palmer Drought Severity Index (PDSI) are calculated using the GEPs forecast data. These indices are then combined with the current Canadian drought assessment to predict future changes in drought.

This is a collection of 124 global and free datasets allowing for spatial (and temporal) analyses of floods, droughts and their interactions with human societies. We have structured the datasets into seven categories: hydrographic baseline, hydrological dynamics, hydrological extremes, land cover & agriculture, human presence, water management, and vulnerability. Please refer to Lindersson et al. (accepted february 2020 in WIREs Water) for further information about review methodology.

The collection is a descriptive list, holding the following information for each dataset:

• Category - as structured in Lindersson et al. (in preparation).
• Sub-category- as structured in Lindersson et al. (in preparation).
• Abbreviation - official or as specified in Lindersson et al. (in preparation).
• Title - full title of dataset.
• Product(s) - type of product(s) offered by the dataset.
• Period - time period covered by the dataset, not defined for all datasets.
• Temporal resolution - not defined for static datasets.
• Angular spatial resolution - only defined for gridded datasets.
• Metric spatial resolution - only defined for gridded datasets.
• Map scale
• Extent - geographic coverage of dataset given in latitude limits.
• Description
• Creating institute(s)
• Data type - raster, vector or tabular.
• File format
• Primary EO type - specifies if the product primarily is based on remote sensing, ground-based data, or a hybrid between remote sensing and ground-based data.
• Data sources - lists the data sources behind the dataset, to the extent this is feasible.
• Data sources also in this table - data sources that are also included as datasets in this collection.
• Intentionally compatible with - defines other datasets in this collection that the dataset is intentinoally compatible with.
• Citation - dataset reference or credit.
• Documentation - dataset documentation.
• Web address - dataset access link.

NOTE: Carefully consult the data usage licenses as given by the data providers, to assure that the exact permissions and restrictions are followed.

The North America Drought Monitor (NADM) is a cooperative effort between drought experts in Canada, Mexico and the United States to monitor drought across the continent on an ongoing basis. The Drought Monitor was developed as a process that synthesizes multiple indices, outlooks and local impacts, into an assessment that best represents current drought conditions. The final outcome of each Drought Monitor is a consensus of federal, state and academic scientists. Major U.S. participants in the NADM program include NOAA's National Climatic Data Center, NOAA's Climate Prediction Center, the U.S. Department of Agriculture, and the National Drought Mitigation Center. Major participants in Canada and Mexico include Agriculture and Agrifood Canada, the Meteorological Service of Canada, and the National Meteorological Service of Mexico (SMN - Servicio Meteorologico Nacional), respectively.