This dataset contains the results of a farmers’ survey in the Ping Catchment in Thailand. The aim of this survey was to identify the specific socioeconomic impacts that historical droughts in the Ping catchment have had for agricultural communities, and identify factors affecting adaptation decisions, as well as analyse the communications with and amongst farmers at the local scale in the Ping catchment during drought. Villages in the Ping catchment with a history of drought were selected to represent typical agricultural production typologies. In total, 176 questionnaires were completed with a close to even distribution of respondents coming from the provinces of Chiang Mai (n=41), Lamphun (n=45), Kamphaeng Phet (n=45) and Tak (n=45). Full details about this dataset can be found at https://doi.org/10.5285/155e1867-bc9d-44f0-9f85-0f682964f720

This dataset contains high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought data for Central Asia. There are forty-eight different SPEI time scales and the available period is from 1981 - 2018, the data was produced using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation dataset and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation dataset. The SPEI-HR dataset, over time and space, correlates fairly well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) dataset. Furthermore, the SPEI-HR dataset, for 6-month timescale, displayed a good correlation of 0.66 with GLEAM root zone soil moisture and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS).

This dataset consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM). The SPEI dataset covers the whole of the African continent for a 36-year-long period (1981–2016) at a horizontal resolution of 5 km (0.05 deg) and a monthly time resolution. The dataset is provided in NetCDF format with in a Geographic Lat/Lon projection. Due to the lower reliability of SPEI over areas with low hydro-climatic variability, the areas with barren or sparsely vegetated areas in Africa were masked out based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface type product (MCD12Q1).

This dataset provides the projections of meteorological, hydrological, and agricultural droughts for the near-future period (2021-2050) for the Mun River basin, in Northeast Thailand. Near future drought characteristics (duration, intensity, and severity) are projected for climate change (CC) scenario using 8 CMIP6 climate models (CNRM-CM6-1, CNRM-CM6-1-HR, EC-Earth3P, EC-Earth3P-HR, HadGEM3-GC31-HH, HadGEM3-GC31-HM, HadGEM3-GC31-MM, HadGEM3-GC31-LL) for SSP5-8.5 scenario. Full details about this dataset can be found at https://doi.org/10.5285/b11c040d-c3c0-43c5-a7c0-442b067dc526

Data comprise measurements of plant biomass and community composition, soil microbial community composition, greenhouse gas emissions and soil carbon and nitrogen pools from a drought experiment superimposed on a the long-term Colt Park grassland restoration experiment in northern England. Rainfall was manipulated using rain-out shelters on experimental grassland plots where fertiliser application and seed addition have been managed to enhance plant species diversity. The scientific purpose was to test the hypothesis that management aimed at biodiversity restoration increases the resistance and recovery of carbon cycling to short-term summer drought. Full details about this dataset can be found at https://doi.org/10.5285/8a41b2a2-01d7-409e-adf5-fba3f3770f29

5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al [1]. There are seven accumulation periods: 1, 3, 6, 9, 12, 18, 24 months and for each period SPI is calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1862 to 2015. This version supersedes previous versions (version 2 and 3) of the same dataset due to minor errors in the data files. NOTE: the difference between this dataset with the previously published dataset "Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]" (Tanguy et al., 2015; https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0) , apart from the temporal and spatial extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Tanguy et al., 2014; https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e) was used, whereas in this new version, Met Office 5km rainfall grids were used (see supporting information for more details). The methodology to calculate SPI is the same in the two datasets. [1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. Full details about this dataset can be found at https://doi.org/10.5285/233090b2-1d14-4eb9-9f9c-3923ea2350ff

A data set consisting of seventeen functional traits collected on 43 saplings from a Control and 33 saplings from a long-term drought experiment site in a tropical rainforest in NE Amazonia, Brazil. The experiment was designed to exclude 50% of the incoming rainfall to the soil and was conducted over a 1ha area, alongside the experiment there is a control (non- drought plot) of a corresponding size. The samples were collected in 2017, fifteen years after the start of the experiment on trees with a diameter at breast height (1.3m) of 1-10cm. The purpose of the dataset was to assess if traits relating to plant metabolism (photosynthesis and respiration) and plant hydraulic processes had been significantly altered in trees growing under drought conditions. Full details about this dataset can be found at https://doi.org/10.5285/ca147ac9-ac68-4348-b5f0-dcd483ef3a85

This dataset contains the percentage of the total pasture area in each country classified as vulnerable to water scarcity (annual run-off is declining and the water shed is defined as water scarce in 2050). Projections of global changes in water scarcity with the current extent of pasture land were combined to identify the potential country level vulnerabilities of pasture land to water scarcity in 2050. The data relate to an analysis of the impact changes in water availability will have on pasture availability in 2050. Full details about this dataset can be found at https://doi.org/10.5285/ec5cc84e-a8da-4ff8-80d4-26fca1a31e1f

This dataset is a model output, from the Grid-to-Grid hydrological model driven by observed climate data (CEH-GEAR rainfall and MORECS potential evaporation). It provides daily mean river flow (m3/s) for 260 catchments, for the period 1960 to 2015. The catchments correspond to locations of NRFA gauging stations (http://nrfa.ceh.ac.uk/). The data were produced as part of MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity), which was a UK NERC-funded research project (2014-2017) that developed a risk-based approach to drought and water scarcity (http://www.mariusdroughtproject.org/). Full details about this dataset can be found at https://doi.org/10.5285/5f3c1a02-d5c4-4faa-9353-e8b68ce2ace2

[THIS DATASET HAS BEEN WITHDRAWN]. 5km gridded Standardised Precipitation Index (SPI) data for Great Britain, which is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [1]. SPI is calculated for different accumulation periods: 1, 3, 6, 9, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1862 to 2015. This release supersedes the previous version, doi:10.5285/ed7444fc-8c2a-473e-98cd-e68d3cffa2b0, as it addresses localised issues with the source data (Met Office monthly rainfall grids) for the period 1960 to 2000. NOTE: the difference between this dataset with the previously published dataset 'Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]" (Tanguy et al., 2015 [2]), apart from the temporal and spatial extent, is the underlying rainfall data from which SPI was calculated. In the previously published dataset, CEH-GEAR (Keller et al., 2015 [3], Tanguy et al., 2014 [4]) was used, whereas in this new version, Met Office 5km rainfall grids were used (see supporting information for more details). The methodology to calculate SPI is the same in the two datasets. [1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California. [2] Tanguy, M.; Hannaford, J.; Barker, L.; Svensson, C.; Kral, F.; Fry, M. (2015). Gridded Standardized Precipitation Index (SPI) using gamma distribution with standard period 1961-2010 for Great Britain [SPIgamma61-10]. NERC Environmental Information Data Centre. https://doi.org/10.5285/94c9eaa3-a178-4de4-8905-dbfab03b69a0 [3] Keller, V. D. J., Tanguy, M., Prosdocimi, I., Terry, J.A., Hitt, O., Cole, S. J., Fry, M., Morris, D. G., & Dixon, H. (2015). CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological use. Copernicus GmbH. https://doi.org/10.5194/essdd-8-83-2015 [4] Tanguy, M.; Dixon, H.; Prosdocimi, I.; Morris, D. G.; Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC Environmental Information Data Centre. https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e Full details about this dataset can be found at https://doi.org/10.5285/1b228b42-42f8-4aee-b964-2c92a21d5556