"The Quantitative applications of high-resolution late Holocene proxy data sets: estimating climate sensitivity and thermohaline circulation influences" project, part of the Natural Environment Research Council (NERC) RAPID Climate Change Research Programme, was led by Prof Keith Briffa of the University of East Anglia and co-investigators at the University of East Anglia (Round 1 - NER/T/S/2002/00440 - Duration 1 Jul 2003 - 30 Jun 2008). This dataset contains self-calibrating Palmer Drought Severity Index data.

[This dataset is embargoed until January 4, 2027]. This dataset provides physiological, morphological, and functional trait measurements for twelve African savanna tree species belonging to the Vachellia and Senegalia genera (Fabaceae family). The data encompasses six species classified as encroaching (increasing in density in African savannas) and six non-encroaching species, facilitating comparative analysis of traits facilitating encroachment ability. The variables capture sapling responses to a factorial combination of environmental conditions, specifically atmospheric carbon dioxide concentration, water availability, and interspecific grass competition. The dataset details plant performance under elevated CO2 versus ambient CO2 and contrasts well-watered and water-limited conditions. Furthermore, the data includes comparative metrics for trees grown with and without competition from the grass species Themeda triandra. All measurements were derived from saplings grown for 11 months in large pots containing local savanna soil within open-top chambers (Rhodes University Elevated CO2 Facility, Makhanda, South Africa), culminating in physiological assessments and destructive harvesting for morphological analysis. The work was supported by the Natural Environment Research Council (Grant NE/T000759/1). Full details about this dataset can be found at https://doi.org/10.5285/f7b8e72f-9bbe-4a03-8140-fada73e95b8c

Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al., 2015; https://doi.org/10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902). SPI 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. NOTE: the difference between this dataset with the previously published dataset 'Standardised Precipitation Index time series for IHU Groups (1961-2012) [SPI_IHU_groups]' (Tanguy et al., 2015; https://doi.org/10.5285/dfd59438-2170-4472-b810-bab33a83d09f), apart from the temporal 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). Within Historic Droughts project (grant number: NE/L01016X/1), the Met Office has digitised historic rainfall and temperature data to produce high quality historic rainfall and temperature grids, which motivated the change in the underlying data to calculate SPI. The methodology to calculate SPI is the same in the two datasets. This release supersedes the previous version, https://doi.org/10.5285/047d914f-2a65-4e9c-b191-09abf57423db, as it addresses localised issues with the source data (Met Office monthly rainfall grids) for the period 1960 to 2000. [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/a01e09b6-4b40-497b-a139-9369858101b3

Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) Hydrometric Areas (Kral et al., 2015; https://doi.org/10.5285/3a4e94fc-4c68-47eb-a217-adee2a6b02b3). SPI 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. NOTE: the difference between this dataset with the previously published dataset 'Standardised Precipitation Index time series for IHU hydrometric areas (1961-2012)' [SPI_IHU_HA] (Tanguy et al., 2015; https://doi.org/10.5285/5e1792a0-ae95-4e77-bccd-2fb456112cc1), apart from the temporal 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 documentation for more details). Within Historic Droughts project (grant number: NE/L01016X/1), the Met Office has digitised historic rainfall and temperature data to produce high quality historic rainfall and temperature grids, which motivated the change in the underlying data to calculate SPI. The methodology to calculate SPI is the same in the two datasets. This release supersedes the previous version, https://doi.org/10.5285/d8655cc9-b275-4e77-9e6c-1b16eee5c7d5, as it addresses localised issues with the source data (Met Office monthly rainfall grids) for the period 1960 to 2000. [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/a754cae2-d6a4-456e-b367-e99891d7920f