cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.csag.10000445
title: Precipitation 90th percentile for Current Climate (1950-1999)

description: Model Run: Control - Current Climate (Observed/current climate as modelled by climate model). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/sarva.gb.10000013
title: Sectoral Gross Value Added (GVA) for wholesale and retail trade; repair of motor vehicles, motor cycles and personal and household goods; hotels and restaurants (SIC6) as a stock from 1995 to 2016

description: The South African Gross Geographic Value Added (GVA) data for each economic sector per year since 1995 to 2016 was supplied by Quantec to the CSIR built environment. This data was disaggregated to a 500m grid using a dasymetric mapping algorithm (https://gap.csir.co.za/gap/images/documents/developing-a-geo-data-frame-using-dasymetric-mapping-principles-to-facilitate-data-integration). and is provided for each year
DOI: 10.15493/saeon.fynbos.29022022
title: Bloemhof Farm rainfall data

description: Since January 1898, daily rainfall records have been collected at Bloemhof Farm outside of Graaff Reinet in the Eastern Cape. Rainfall has been recorded in inches and now in millimeters, along with comments about the weather conditions, the timing and duration of the rainfall and the farming conditions on the farm. Data are handwritten in books, dating back to 1898, and have now been digitised. The data was collected using a Snowden standard rain gauge. This record forms part of a collection of historical rainfall data submitted to SAEON. The data were generated by farmers on a voluntary basis and have been published as submitted.
DOI: 10.15493/bea.data.10000074
title: Availability of Sugar Cane Field Residues

description: Data was derived from the following sources: *The extent of sugar cane cultivation was determined from digitisation of maps published in Gers (2003). * This extent was correlated with two additional sources: crop extent published by DAFF (2014), which excludes sugar cane production and could be used as a verification of extent, and Land Use data (FAO, 2011), which could be used to verify the finer extent of cultivation. * Sugar cane theoretical yields were applied from Schulze, Hull, and Maharaj (2007). * The total area and sugar cane production obtained from the above was correlated with published production figures (DAFF, 2014) and good correlation obtained - calculated sugar cane production of 22.5 Mt/a vs. published production in 2013/14 of 21.3 Mt/a. * Ratios of bagasse, sugar, and residue production was calculated from ratios in Hugo (2014) .
DOI: 10.15493/dea.carbon.10000016
title: Biomes of South Africa

description: Biomes coverage that groups the vegetation types of South Africa, Lesotho and Swaziland at the highest level. This represents a simplification of the biome level groupings of vegetation types
DOI: 10.15493/saeon.fynbos.12b1820
title: 12B event rainfall February 2018 - August 2020

description: Event rainfall data collected by Texas Electronics tipping bucket gauge installed at 1.2m above ground at 337 masl in the Biesievlei catchment of the Jonkershoek valley in the Western Cape of South Africa. Data recorded by a Pendant Event logger (UA-003-64, Onset, Massachusetts, U.S.A). Tipping bucket calibrated to 0.254 mm increments.
DOI: 10.15493/saeon.egagasini.10000036
title: The ASCA April 2015 Scientific Data System one minute averaged data

description: The Agulhas System Climate Array (ACSA) is a mooring array and is designed to provide long-term observations of the Agulhas Current`s volume, heat and salt transport and its variability from mesoscale (eddies), through seasonal to interannual timescales. The ASCA shelf and tall moorings extend 200 km offshore along decending TOPEX/Jason satellite ground track # 96, through the core of the Agulhas Current, with CPIES measurements extending the array to 300 km offshore of Port Elizabeth. The data collected during this project have been obtained from various oceanographic instrumentation. This raw data was collected by the underway Scientific Data System (SDS), designed to collect, integrate and log and display various scientific, navigational and meterological sensors, instruments and systems onboard the ship. This data has been averaged into one minute bins
DOI: 10.15493/sarva.csag.10000249
title: Total precipitation for the month (mm) for Current Climate (1950-1999)

description: Model Run: Control - Current Climate (Observed/current climate as modelled by climate model). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/sarva.beeh.10000443
title: Annual Precipitation (mm) Driest Year In 10 (Per Quaternary Catchment)

description: This data set contains the monthly rainfall and its inter-annual variability  in South Africa (SA). Monthly rainfall values serve an important tool in describing intra-year distribution and are a major contributing factor to the calendar of agrohydrological activities and the month is used, for example, to define the start, duration and end of the rainy season, and also the beginning of the hydrological year.
DOI: 10.15493/sarva.csag.10000295
title: Rainfall days per month (> 10mm) for Current Climate (1950-1999)

description: Model Run: Control - Current Climate (Observed/current climate as modelled by climate model). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/saeon.egagasini.10000055
title: The ASCA June 2018 raw ADCP data collected at Mooring E for all depths

description: The Agulhas System Climate Array (ACSA) is a mooring array and is designed to provide long-term observations of the Agulhas Current`s volume, heat and salt transport and its variability from mesoscale (eddies), through seasonal to interannual timescales. The ASCA shelf and tall moorings extend 200 km offshore along decending TOPEX/Jason satellite ground track # 96, through the core of the Agulhas Current, with CPIES measurements extending the array to 300 km offshore of Port Elizabeth. The data collected during this project have been obtained from various oceanographic instrumentation fixed to each mooring. This raw data was collected by an ADCP (Acoustic Doppler Current Profiler) deployed at 500m depth.
DOI: 10.15493/sarva.csag.10000455
title: Number of days for Minimum Temperature over 90th percentile for Current Climate (1950-1999)

description: Model Run: Control - Current Climate (Observed/current climate as modelled by climate model). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/nccis.data.10000037
title: Projected changes in annual mean temperature (°C) under RCP8.5 for the 2046-2065 time period based on the National Centre for Meteorological Research Coupled Global Climate Model, version 5 (CNRM-CM5)

description: The analyses of future climate change over South Africa as described in the Third National Communication, are from the projections of the Coupled Global Climate Models (CGCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Assessment Report (AR) 5 of the Intergovernmental Panel on Climate Change (IPCC). These projections are used to inform on the uncertainty range of the large-scale climate change futures over the southern African region. At the Council for Scientific Industrial Research (CSIR), a dynamic regional climate model CCAM (conformal-cubic atmospheric model) of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) was used to downscale CMIP5 CGCM projections to 50 km resolution over Africa. These downscalings were for both Representative Concentration Pathway (RCP) 8.5 and Representative Concentration Pathway (RCP) 4.5 of AR5 of the IPCC. RCP 4.5 describes a future with relatively ambitious emission reductions whereas RCP 8.5 describes a future with no reductions in emissions. Emissions in RCP 4.5 peak around 2040, then decline and in RCP 8.5 emissions continue to rise throughout the 21st century. The change in temperature is expressed as an anomaly, the difference between the average climate over a period of the last several decades (1971-2000), and the projected climate (short to medium term 2021 to 2050). The simulations were performed on supercomputers of the CSIRO and on the Centre for High Performance Computing (CHPC) of the Meraka Institute of the CSIR in South Africa.
DOI: 10.15493/sarva.saws.10000189
title: Seasonal mean near-surface (2m) temperature (°C) change from the median projected for 2066 - 2095, relative to present (1976 - 2005), for SON season under the RCP 8.5 pathway

description: Seasonal (SON) mean near-surface (2m) temperature (°C) change from the median projected for 2066-2095, relative to present (1976 - 2005), under the RCP 8.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily temperature averages, which are used to generate projections of seasonal change. The projections are generated using the high (RCP8.5) pathway which associates CO2 concentrations of approximately 950ppm by the year 2100. The associated RMSD it calculated and shows the uncertainty range of the projected model simulated residual values, and gives a relative perspective of spatial areas associated with higher and lower projection uncertainties.
DOI: 10.15493/saeon.egagasini.10000063
title: ASCA June 2018 raw ADCP data at Mooring G for all depths

description: The Agulhas System Climate Array (ACSA) is a mooring array and is designed to provide long-term observations of the Agulhas Current`s volume, heat and salt transport and its variability from mesoscale (eddies), through seasonal to interannual timescales. The ASCA shelf and tall moorings extend 200 km offshore along decending TOPEX/Jason satellite ground track # 96, through the core of the Agulhas Current, with CPIES measurements extending the array to 300 km offshore of Port Elizabeth. The data collected during this project have been obtained from various oceanographic instrumentation fixed to each mooring. This raw data was collected by an ADCP (Acoustic Doppler Current Profiler) at Mooring G deployed at 500m.
DOI: 10.15493/saeon.tierberg.10000019
title: Plant Community

description: These data comprise a single spreadsheet listing plant species and their projected canopy cover values (Braun-Blanquet type estimates) for 115 quadrats (5 m x 5 m). The vegetation was sampled on plains, heuweltjies, washes and drainage lines in the Tierberg Karoo Research Centre (TKRC) that had been moderately stocked with Merino sheep (8 ha/SSU) and then protected from grazing for one year prior to the study, and on plains on the adjacent rangeland (Argentina ranch) that had been heavily stocked with domestic livestock prior to 1960 and then moderately stocked with Dorper sheep (8 ha/SSU).

Acknowledge as follows: Data are the property of SAEON and were collected by SJ Milton, students and assistants, funded by the National Research Foundation, the Percy FitzPatrick Institute, University of Cape Town, and the Department of Science and Technology (DST) through the Biota-DST “Tierberg Reborn project”
DOI: 10.15493/sarva.csag.10000223
title: Maximum of Minimum Temperature for Near Future (2046-2065)

description: Model Run: Near future (2046 - 2065) (Near future (2046 - 2065)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/saeon.egagasini.10000093
title: A Compendium of Research Undertaken through the South African Chapter of the Indian Ocean Rim Association Academic Group

description: South Africa took over as chair of IORA in October 2017 under the theme “IORA: Uniting the peoples of Africa, Asia, Australasia and the Middle East through enhanced cooperation for peace, stability and sustainable development”, and will hold the chairship until October/November 2019. One of the initiatives by the South African Government has been to establish the South African Chapter of the Indian Ocean Rim Association Academic Group (SA IORAG) as of 2016 through support from the Department of Science and Technology, as well as other government departments, agencies and national councils and facilities. The Secretariat for the SA IORAG is hosted at the South African Environmental Observation Network (SAEON) Egagasini Node for Offshore Systems, SAEON is a business unit of the National Research Foundation (NRF). Research contained within this Compendium was supported with funding from the DST and NRF and focuses on the IORA priority areas.
DOI: 10.15493/sarva.saws.10000271
title: Seasonal percentage (%) change in rainfall from the median projected for 2066-2095, relative to present (1976 - 2005), for MAM season under the RCP 8.5 pathway

description: Seasonal percentage (%) change in rainfall from the median projected for 2066-2095, relative to present (1976 - 2005), for MAM season under the RCP 8.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily rainfall averages, which are used to generate projections of seasonal change. The projections are generated using the high (RCP8.5) pathway which associates CO2 concentrations of approximately 950ppm by the year 2100. The associated RMSD it calculated and shows the uncertainty range of the projected model simulated residual values, and gives a relative perspective of spatial areas associated with higher and lower projection uncertainties.
DOI: 10.15493/saeon.egagasini.10000045
title: The ASCA June 2018 raw MicroCAT data at Mooring B for all depths

description: The Agulhas System Climate Array (ACSA) is a mooring array and is designed to provide long-term observations of the Agulhas Current`s volume, heat and salt transport and its variability from mesoscale (eddies), through seasonal to interannual timescales. The ASCA shelf and tall moorings extend 200 km offshore along decending TOPEX/Jason satellite ground track # 96, through the core of the Agulhas Current, with CPIES measurements extending the array to 300 km offshore of Port Elizabeth. The data collected during this project have been obtained from various oceanographic instrumentation fixed to each mooring. This raw data was collected by a MicroCAT sensor at the following depths: 100m, 200m, 300m, 400m, 550m, 700m, 900m and 1100m for Mooring B.
DOI: 10.15493/saeon.tierberg.10000016
title: Tierberg Karoo Research Centre Soil Analysis

description: Data are results of chemical analyses of soil samples collected in the Tierberg Karoo Research Centre (TKRC) livestock exclosure between 1987 and 1998, and on nearby ranches (Argentina, Sandrivier). Soils were collected from plains, drainage lines and zoogenic structures (soil mounds over the nests of termites and ants). In some cases topsoil and subsoil were analysed separately. Soil analyses were all carried out by agricultural soil laboratories.
DOI: 10.15493/sarva.beeh.10000202
title: October Means Of Reference Crop Evaporation (mm) Fao Penman-Monteith Equivalent

description: The FAO (1992) definition of Penman-Monteith derived reference crop evaporation (Erpm) is `The rate of evapotranspiration from a hypothetical crop with an assumed crop height of 0.12 m, a fixed canopy resistance of 70 s.m-1 and albedo of 0.23, which would closely resemble evapotranspiration from an extensive surface of green grass cover of uniform height, actively growing, completely shading the ground and not short of water`. 

The first detailed maps for South Africa of Penman-Monteith equivalent reference crop, Erpm, were derived from monthly ratios of Erpm: A-pan using data at 174 sites (Crosby and Crosby, 1996). From these ratios, Schulze (1997) identified 14 `regions` of similar ratio patterns which were then used to map Erpm from gridded A-pan values. The maps in the present Atlas are based on a much more deterministic and more fundamental approach with daily maximum and minimum temperatures, and hence daily saturated vapour pressures, generated over South Africa on a 1` x 1` (1.7 x 1.7 km) raster for 50 years, based on research by Schulze and Maharaj (2004). Empirically determined month-by-month gridded values of actual vapour pressure for South Africa.
DOI: 10.15493/sarva.beeh.10000110
title: Pinus taeda Growth Areas and Yield Estimation

description: Pinus taeda also commonly known as loblolly pine, is native to North America. Of the three main species of pine grown in South Africa, viz. Pinus patula, P. elliottii and P. taeda, the latter is the most demanding in respect of climate and soil requirements (Smith, 1998). Optimally, P. taeda requires a MAP > 950 mm, although it can be grown with lower rainfall where temperatures are also relatively lower (Smith, 1998). The species is, however, sensitive to drought. Pinus taeda requires mean annual temperatures ≥ 13 degree Celsius, with July (mid-winter) mean temperatures > 8 degree Celsius, but with January (midsummer) means < 26 degree Celsius (Smith, 1998). While resistant to hail, P. taeda is very prone to snow. 

Climatically optimum growth areas for Pinus elliottii have been defined in the ICFR`s Forestry Toolbox (Kunz, 2004), by mean annual precipitation (MAP) and mean annual temperature (MAT), as illustrated in This figure also shows the climatic conditions under which suboptimum growth would take place because conditions may at times be too cold and damage from snow occurs, or because occasional drought may occur. Optimum and sub-optimum growth areas of P. elliottii were mapped by applying these criteria to the one arc minute (1` x 1` of a degree latitude/longitude) databases of MAP (Lynch, 2004) and MAT (Schulze and Maharaj, 2004) for South Africa. Using Smith`s (1994) rule based approach and considering only his climatic criteria and not soil or management factors, Pinus elliottii yield estimates were done.
DOI: 10.15493/dea.carbon.10000073
title: South African Land Cover 2014 Class G Orchards Resampled to a 1km Grid

description: The 2013-14 South African National land cover dataset produced by (© GEOTERRAIMAGE - 2014) as a commercial data product was generated from digital, multi-seasonal Landsat 8 multispectral imagery, acquired between April 2013 and March 2014. In excess of 600 Landsat images were used to generate the land cover information, based on an average of 8 different seasonal image acquisition dates, within each of the 76 x image frames required to cover South Africa. The land cover dataset, which covers the whole of South Africa, is presented in a map-corrected, raster format, based on 30x30m cells equivalent to the image resolution of the source Landsat 8 multi-spectral imagery. The dataset contains 72 x land cover / use information classes, covering a wide range of natural and man-made landscape characteristics. The original land cover dataset was processed in UTM (north) / WGS84 map projection format based on the Landsat 8 standard map projection format as provided by the USGS. Class 16–18 of the 2013-14 South African National land cover dataset was clustered to derive South African land cover 2014 Class G Orchards for the current product and resampled to a 1000 x 1000m grid resolution Albers Equal Area map projection +proj=aea +lat_1=-22 +lat_2=-38 +lat_0=-30 +lon_0=25 +x_0=1400000 +y_0=1300000 +datum=WGS84 +units=m +no_defs
DOI: 10.15493/saeon.fynbos.46022022
title: Wellfound Farm rainfall data

description: Monthly rainfall records collected on Wellfound farm, near Jansenville, Eastern Cape. The data was collected using a Snowden standard rain gauge. This record forms part of a collection of historical rainfall data submitted to SAEON. The data were generated by farmers on a voluntary basis and have been published as submitted.