This is a geospatial data repository for agricultural economists interested in climate, production or soil data. Everything listed here is openly accessible. Most of it is global or quasi-global, with a few Africa-specific products. For development economists with interest in other open source data sets, I would refer you to a major and comprehensive data set collection effort on DEVECONDATA.

I add datasets to this list as I find them (sometimes with a bit of a time lag), so if you’re aware of a useful data source not included here, please send me an email! Also, I’ve only worked with a selection of these datasets, and don’t claim to be an expert on any of them. This is more like a personal, jotting-down-for-memory’s-sake list turned public. So if I’m getting anything wrong, please do write and correct me!

Re-analysis temperature and precipitation datasets:

• Re-analysis datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF). While the ECMWF primarily forecasts weather, they additionally provide re-analysis (modeled) datasets of recent weather patterns, such as the ERA-interim dataset, with atmospheric variables at varying intervals (e.g., hourly, daily, monthly) at a 79-km grid between 1979 and today.
• The 20th Century Reanalysis Datasets on temperature, precipitation, air pressure, and other climate characteristics. Available at hourly intervals, daily, or monthly, at a 2×2° grid stretching from 90° N to 90° S, beginning in 1850. Estimates are based on global pressure records, hence the ability to estimate prior to the advent of satellites.
• GPCC Full Data Reanalysis Version 7, from the Global Precipitation Climatology Center. Contains monthly precipitation totals from January 1901 to December 2013, stretching from 90° N to 90° S, with a spatial resolution of 0.5, 1.0, and 2.5 degrees lat/long. This reanalysis data is based on the interpolated GPCC data listed below. Download here.
• Africa Rainfall Climatology version 2 (ARC2) from the National Oceanic and Atmospheric Administration (NOAA). This project provides historical re-analysis rainfall data for Africa between 1983 and 2012, gridded at ~0.1° spatial resolution (~10km). Monthly and daily data here. Also possibly available at 10-day intervals.
• NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA). This project provides re-analysis data on a range of weather and climate variables, at a range of time-scales, gridded at 2/3° longitude and 0.5° latitude.
• CHIRPS data from the Climate Hazards Group (CHG). The quasi-global rainfall data span 50° S to 50° N, gridded at 0.05° resolution. Data includes totals by day, pentad (6 pentads = 1 month) or dekad (3 dekads = 1 month), from 1981 until near-present.
• TRMM data from NASA’s Tropical Rainfall Measuring Mission. This is another quasi-global rainfall data spanning 50° S to 50° N, and gridded at 0.25° resolution. The data begin in 1997 and end in 2015, and are gridded at a three-hour temporal resolution.
• Global Land Surface Temperature (LST) from the Terrestrial Hydrology Research Group at Princeton. The hourly, global dataset covers 1970-2009, gridded at 0.5°. In GrADS format.
• Global Land Data Assimilation Systems (GLADIS) from NASA. This is a collection of global datasets at various spatial (0.25° – 1° resolution) and temporal (3 hour or monthly) resolutions, covering 1948/1979/2000 until 2012/the present. They are each made via similar (not identical) land surface models , and each dataset contains predicted soil moisture, soil temperature, and many other variables.
• Multi-Source Weighted-Ensemble Precipitation (MSWEP) retrospective, a global precipitation dataset stretching from 1997-2016, with a 3-hour temporal resolution and a 0.1° spatial resolution. The dataset is created via many data sources, including satellite sources and other reanalysis datasets. This dataset and others were evaluated and compared here.
• European Space Agency data on soil moisture, beginning in 1978, at 0.25° spatial resolution, monthly. View data here, download here.

Interpolated temperature and precipitation datasets:

• Global Precipitation Climatology Center (GPCC) data on precipitation. Version 7 spans 1901 to 2013, and is based on data from from 67,200 stations world-wide. Contains monthly totals at 0.5° x 0.5°, 1.0° x 1.0°, and 2.5° x 2.5° latitude by longitude.
• Willmott and Matsuura’s Gridded Monthly Time Series V 4.01. These datasets provide monthly, interpolated temperature averages and monthly precipitation totals for the entire world, from 1900 to 2014, in grids size 0.5° latitude by 0.5°.
• Climate Research Unit (CRU) time series datasets from the University of East Anglia. Contains monthly averages for precipitation, temperature and a few other variables. A global dataset excluding Antarctica, covering 1901-2014 and gridded at 0.5°. Data here, after applying for (instantaneous) access. More info here. The CRU also creates/provides other datasets, listed here.

Flood and Drought Indices/Data:

• Palmer Drought Severity Index (PDSI) from Aiguo Dai and co-authors. Modeled using NCEP climate prediction precipitation data and surface temperature data from CRU as inputs, PDSI captures atmospheric moisture (i.e. meteorological drought) through a standardized index ranging from -10 (dry) to 10 (wet). The effect of temperature on atmospheric moisture, or potential evapotranspiration, is calculated through Thornthwaite’s (1948) formula. Four years of lagged temperature and precipitation data contributed to the PDSI index of each grid-month, capturing the “build up” of drought. While atmospheric moisture is correlated with soil moisture, or agricultural drought, it is not identical; more details can be found here. The PDSI data is global, at a 2.5° spatial resolution, in monthly time-steps, and the most recent scPDSIpm data covers 1950 to 2014. Interpretation of a PDSI value depends on local mean climate conditions; each grid-month value essentially compares moisture over the last 4 years to the historical grid mean. Thus, a value of +4 might imply floods in the central US but only moderate rainfall in northern Africa.
• Standardized Precipitation Index (SPI) from NCAR/UCAR. The SPI is the number of standard deviations by which precipitation (they use CRU) lies above or below a long-term mean. Temperature data is not incorporated. Data is global, at 1° spatial resolution, in monthly time steps, and available with “long-term mean” defined around 3-month, 6-month, and 12-month intervals. Interpretation of index values, as with PDSI, changes with mean rainfall. For example, the 6-month SPI value for each grid-month compares a moving 6-month precipitation record against the long-term (since 1948) distribution for the same 6-month period. More info here.
• Standardized Precipitation Evapotranspiration Index (SPEI). This index is available in multiple datasets, each with “long-term mean” defined by different month-intervals (1 mo, 6 mo, etc.), like SPI. Unlike SPI, but like PDSI, SPEI also allows for temperature to effect drought conditions through potential evapotranspiration (PET). (SPEI version 1 used the Thornthwaite equation of PDSI to calculate PET; the current version uses the supposedly superior Penman-Montheith equation.) Datasets should be chosen according to analysis intent: shorter month-intervals will predict soil water content and river discharge, medium time scales relate to reservoir storage/discharge, and long time scales should predict groundwater storage. Data is global, with 0.5° spatial resolution, covering 1901-2014, and long-term means defined as anything between 1 and 38 months in the various datasets. More info here.
• The Africa & Latin America Flood and Drought Monitors, run out of Princeton University. This effort contains a range of historical/monitored and forecasted data (hydrologic, soil moisture, precipitation, etc.) at daily, weekly or monthly time scales, gridded at 0.25° resolution. Info on data construction here.

Gridded soil/land datasets and databases:

• Harmonized World Soil Database from FAO, IIASA, ISRIC, ISSCAS, and JRC. This massive database provides interpolated soil quality estimates for the entire world, including nutrient availability and a number of other variables, in grids spaced at 30 arc sections (approximately 1 km).
• Africa-specific soil nutrient maps from AfSIS/ISRIC. This source provides data on a soil macro- and micronutrients in 250-meter grids, for the African continent. Same data available here.
• Global soil characteristics maps from ISRIC. This source provides data on a great number of soil characteristics, again in 250-meter grids. For information on methods (both these data and the Africa-specific nutrients), see here. More general info through ISRIC website.
• Soil Map of the World from FAO/UNESCO. The link is down as of March 2016, but generally if “Digital Soil Map of the World (Geonetwork)” will lead to this ESRI shapefile of soil types across the world, as well as Erdas and IDRISI files.
• Global Land Surface Model from the Terrestrial Hydrology Research Group at Princeton. A global dataset of land surface hydrology, created via multiple land surface simulations.

Gridded crop production/suitability datasets:

• IFPRI’s Spatial Production Allocation Model (SPAM) database compiles crop production data gridded at 10×10 km resolution for several countries.
• FAO’s Global Agro-Ecological Zones (GAEZ) data, which provides spatially referenced time series data as well as time-averaged data on climactic variables, crop suitability/productivity variables, and yields and production gaps.

List of Further Climate Lists:

• Asian-Pacific Data Research Center list of climate datasets
• NOAA’s “Information Access Matrix” for gridded data on atmosphere, ocean and land
• The Physical Sciences Division of the Earth System Science Research Lab lists these gridded climate datasets and other types of geospatial data

Bonus datasets:

• High-resolution 2015 settlement data from the Center for International Earth Science Information Network. These layers provide human population distributions at a resolution of 1 arc-second (approximately 30 m in most areas) for the year 2015, in both rural and urban areas. At the moment, layers exist only for Burkina Faso, Ghana, Haiti, Ivory Coast, Madagascar, Malawi, Mexico, the Philippines, Rwanda, South Africa, Sri Lanka, Thailand, and Uganda.
• Copernicus global land cover map for Africa in 2015. Apparently years 2016 and 201 are coming. More details here.