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The precipitation and temperature data are derived from the CRU TS 3.21 dataset produced by the Climate Research Unit at the University of East Anglia. This is a global gridded dataset of monthly observations over the period 1901-2012. The spatial resolution of the dataset is 0.5°. For details of the dataset see Links to External Data, below.
The precipitation and temperature data are derived from the CRU TS 3.21 dataset produced by the Climate Research Unit at the University of East Anglia. This is a global gridded dataset of monthly observations over the period 1901–2012. The spatial resolution of the dataset is 0.5°. For details of the dataset see Links to External Data, below.


The reliability of the dataset depends on the number of stations used in the interpolation, which is spatially and temporally variable. For a station to be included in the interpolation, its record must be >75% complete over the period 1961-1990. Station data, showing the number of station observations in each grid cell at each time-step (i.e. month), have been averaged over the period 1950-2010 and are shown on the maps below. Station data can influence the gridded value in a given cell if it lies within a predefined Correlation Decay Distance. This is 450 km for precipitation and 1200 km for mean temperature. For Africa, approximately 75% of the grid cells contain station data, or have station data within the correlation decay distance, with valid values over the period 1901-2000. The number of stations used to calculate the interpolated data value at each grid cell has been averaged over all time-steps between 1950 and 2010 and is shown on the maps below.
The reliability of the dataset depends on the number of stations used in the interpolation, which is spatially and temporally variable. For a station to be included in the interpolation, its record must be >75% complete over the period 1961–1990. Station data, showing the number of station observations in each grid cell at each time-step (i.e. month), have been averaged over the period 1950–2010 and are shown on the maps below. Station data can influence the gridded value in a given cell if it lies within a predefined Correlation Decay Distance. This is 450 km for precipitation and 1200 km for mean temperature. For Africa, approximately 75% of the grid cells contain station data, or have station data within the correlation decay distance, with valid values over the period 1901–2000. The number of stations used to calculate the interpolated data value at each grid cell has been averaged over all time-steps between 1950 and 2010 and is shown on the maps below.


[[File:CRU_StationData2.png | 1462x250px | Station data used to produce the TS3.21 dataset]]  
[[File:CRU_StationData2.png | 1462x250px | Station data used to produce the TS3.21 dataset]]  
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The climate zones are taken from the updated Köppen-Geiger climate classification presented by Peel et al. This is a widely used classification scheme that has been updated using long-term station records of monthly precipitation and temperature from the Global Historical Climatology Network (GHCN) version 2.0 dataset. As for the gridded precipitation and temperature data, the reliability of this dataset is dependent on the density of input data. Detailed information on the data and methodology can be found in Peel et al (2007) (see Links to External Data, below).
The climate zones are taken from the updated Köppen-Geiger climate classification presented by Peel et al.(2007). This is a widely used classification scheme that has been updated using long-term station records of monthly precipitation and temperature from the Global Historical Climatology Network (GHCN) version 2.0 dataset. As for the gridded precipitation and temperature data, the reliability of this dataset is dependent on the density of input data. Detailed information on the data and methodology can be found in Peel et al. (2007) (see Links to External Data, below).
   
   



Revision as of 15:49, 16 December 2015

Africa Groundwater Atlas >> Additional resources >> Climate

Dataset description

Long-term average rainfall and temperature (1950-2010)
Long-term average rainfall and temperature (1950-2010)


The precipitation and temperature data are derived from the CRU TS 3.21 dataset produced by the Climate Research Unit at the University of East Anglia. This is a global gridded dataset of monthly observations over the period 1901–2012. The spatial resolution of the dataset is 0.5°. For details of the dataset see Links to External Data, below.

The reliability of the dataset depends on the number of stations used in the interpolation, which is spatially and temporally variable. For a station to be included in the interpolation, its record must be >75% complete over the period 1961–1990. Station data, showing the number of station observations in each grid cell at each time-step (i.e. month), have been averaged over the period 1950–2010 and are shown on the maps below. Station data can influence the gridded value in a given cell if it lies within a predefined Correlation Decay Distance. This is 450 km for precipitation and 1200 km for mean temperature. For Africa, approximately 75% of the grid cells contain station data, or have station data within the correlation decay distance, with valid values over the period 1901–2000. The number of stations used to calculate the interpolated data value at each grid cell has been averaged over all time-steps between 1950 and 2010 and is shown on the maps below.

Station data used to produce the TS3.21 dataset


Climate regions as identified by the Koppen Geiger classification
Climate regions as identified by the Koppen Geiger classification


The climate zones are taken from the updated Köppen-Geiger climate classification presented by Peel et al.(2007). This is a widely used classification scheme that has been updated using long-term station records of monthly precipitation and temperature from the Global Historical Climatology Network (GHCN) version 2.0 dataset. As for the gridded precipitation and temperature data, the reliability of this dataset is dependent on the density of input data. Detailed information on the data and methodology can be found in Peel et al. (2007) (see Links to External Data, below).


Climate Classifications
Af Tropical Rainforest Am Tropical Monsoon Aw Tropical Savannah
BSh Arid Steppe (hot) BSk Arid Steppe (cold)
BWh Arid Desert (hot) BWk Arid Desert (cold)
Cfa Temperate without dry season (hot summer) Cfb Temperate without dry season (warm summer)
Csa Temperate with dry summer (hot summer) Csb Temperate with dry summer (warm summer)
Cwa Temperate with dry winter (hot summer) Cwb Temperate with dry winter (warm summer)


Links to External Data

The CRU TS3.21 dataset is freely available through the Centre for Environmental Data Archival (CEDA). Users must register with CEDA to access the dataset. Use of the data is covered by the following licence: https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.

Data citation:

University of East Anglia Climatic Research Unit; Jones, P.D.; Harris, I. (2013): CRU TS3.21: Climatic Research Unit (CRU) Time-Series (TS) Version 3.21 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2012). NCAS British Atmospheric Data Centre, 24th September 2013. doi:10.5285/D0E1585D-3417-485F-87AE-4FCECF10A992. https://dx.doi.org/10.5285/D0E1585D-3417-485F-87AE-4FCECF10A992


Further information on the development of the preceding dataset (CRU TS3.10) can be found in:

Harris I, Jones PD, Osborn TJ and Lister DH. 2013. Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset. International Journal of Climatology 34(3): 623-642. doi: 10.1002/joc.3711


Detailed information on the Köppen-Geiger climate classification can be found in:

Peel MC, Finlayson BL and McMahon TA. 2007. Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci., 11, 1633-1644. doi:10.5194/hess-11-1633-2007

The updated Köppen-Geiger world climate map used here is freely available electronically in the supplementary material to the paper presented by Peel et al. (2007).


Africa Groundwater Atlas >> Additional resources >> Climate