cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/nccis.data.10000049
title: Projected changes in annual mean temperature (°C) under RCP 8.5 for the 2046-2065 time period based on the Max Planck Institute Coupled Earth System Model (MPI-ESM-LR)

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/dea.carbon.10000053
title: South African Land Cover 1990 Class C Indigenous Forest Resampled to a 1km Grid

description: The 1990 South African National land cover dataset produced by (© GEOTERRAIMAGE - 2014) as a commercial data product was generated from digital, multi-seasonal Landsat 4/5 multispectral imagery, acquired between April 1989 and October 1993. 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 4/5 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 4/5 standard map projection format as provided by the USGS. Class 4 of the 1990 South African National land cover dataset was used to derive South African land cover 1990 Class C Indigenous Forest 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/sarva.saws.10000248
title: Root Mean square difference in percentage (%) between the nine ensemble member change anomalies for the annual total rainfall projected for 2066 - 2095 under the RCP 8.5 pathway

description: Root Mean square difference in percentage (%) between the nine ensemble member change anomalies for the annual total rainfall projected for 2066 - 2095 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 annual change. The projections are generated using thehigh (RCP8.5) pathway which associates CO2 concentrations of approximately 900ppm 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/sarva.csag.10000060
title: Minimum of Minimum Temperature 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.saws.10000168
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the 10% percentile for 2036 - 2065 relative to 1976-2005, for the SON season, under the RCP 8.5 pathway

description: Root Mean Square Difference for seasonal (SON) mean near-surface (2m) temperature (°C) change from the 10% percentile projected for 2036-2065, 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/sarva.beeh.10000385
title: Uncorrected Vapour Pressure (kPa) December

description: Actual vapour pressure, i.e. the variable expressing atmospheric moisture content through the partial pressure exerted by the water vapour present in the atmosphere, to be a conservative climatic element which could be expressed adequately as a relatively consistent monthly value (cf. shaded box which follows). The monthly uncorrected vapour pressure, ed, at any given location in South Africa was subsequently held constant for that entire month and derivatives of ed, such as daily maximum and minimum relative humidity or daily vapour pressure deficit which depend on ratios of uncorrected actual to saturated vapour pressure, were then computed using daily maximum/minimum temperatures (Schulze and Maharaj, 2004) as inputs to daily saturated vapour pressure calculations, which were in turn used with that location`s monthly uncorrected actual vapour pressure.

The derivation of equations for monthly uncorrected actual vapour pressure, ed, over South Africa included, testing a number of hypotheses on factors affecting ed against observed data across a range of latitudes, distances from the ocean, climatic regimes and other factors; the selection, by iterative procedures, of suitable geographic and climatic variables against which to regress ed; the development of month-by-month multiple regression equations of uncorrected ed against altitude, latitude, longitude and continentality as geographical variables, and temperature range as a climatic variable, and their relative importance in the different seasons of the year. In each case reasons were given for the selection of a respective variable.
DOI: 10.15493/nccis.data.10000055
title: Projected changes in annual mean temperature (°C) under RCP 8.5 for the 2046-2065 time period based on the Norwegian Earth System Model (NorESM1-M)

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.csag.10000393
title: Rainfall days per month (> 2mm) 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.10000087
title: The ASCA April 2016 raw Current Meter data collected at Mooring D 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 Current Meters at Mooring D deployed at the following depths: 1000m, 1500m, 2000m, 2500m and 3000m
DOI: 10.15493/sarva.251120-3
title: 2018 coast ecosystem map

description: First version of an integrated coast map including coastal ecosystem types from the terrestrial, marine, and estuarine realms.The coast is not considered a realm, per se, but rather a cross-realm zone within which we have compiled the results from the National Biodiversity Assessment 2018 for the coastal portions of the terrestrial and marine realms and including all estuaries. Inland aquatic features are not included at this time. The cross-realm integration has allowed us to distil and highlight key messages and findings for the coast specifically, which were previously lost when each component of the coast was split among the realms and reported on separately.
DOI: 10.15493/sarva.saws.10000268
title: Root Mean Square Difference in percentage (%) between the nine ensemble member change anomalies of the seasonal percentage rainfall for the median for 2066 - 2095 relative to 1976-2005, for the DJF season, under the RCP 8.5 pathway

description: Root Mean Square Difference in percentage (%) between the nine ensemble member change anomalies of the seasonal percentage rainfall for the median for 2066 - 2095 relative to 1976-2005, for the DJF 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/sarva.saws.10000052
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the median for 2066 - 2095 relative to 1976-2005, for the DJF season, under the RCP 4.5 pathway

description: Root Mean Square Difference for seasonal (DJF) mean near-surface (2m) temperature (°C) change from the median projected for 2066-2095, relative to present (1976 - 2005), under the RCP 4.5 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 medium to low (RCP4.5) pathway which associates CO2 concentrations of approximately 560ppm 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/sarva.saws.10000174
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the 10% percentile for 2066 - 2095 relative to 1976-2005, for the DJF season, under the RCP 8.5 pathway

description: Root Mean Square Difference for Seasonal (DJF) mean near-surface (2m) temperature (°C) change from the 10% percentile 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.020222-1
title: SkiMonkey mounted MicroCAT CTD data from between Yzerfontein and offshore Cape Agulhas on Voyage 185 of the Ellen Khuzwayo, January 2019

description: This expedition obtained the first visual imagery and associated CTD and oxygen sensor data from six seabed areas off the coasts of South Africa, which included the two newly proposed Marine Protected Areas (MPAs) at Browns Bank and Robben Island, as well as a hardground site off Scarborough, a Southern Benguela muddy site and a heavily trawled Benguela Shelf area. At each station the SkiMonkey III towed camera system, with the MicroCAT CTD attached, was deployed off the stern of the ship from the plankton towing winch at a speed of 1 m/s until contact with the seafloor was made. Once on the seafloor, the system was towed behind the vessel at a speed of 1 knot for approximately 20 minutes. Following this, the system was retrieved and the data were downloaded and backed-up appropriately. Note that latitude and longitude information were only recorded at two points per station, when the system touched down on the seafloor and when it was retrieved from the seafloor (i.e. Start_Lat_DD, Start_Lon_DD, End_Lat_DD, End_Lon_DD). The download is divided into station level folders, within which the user can find ReadME documents describing the variables recorded in the data, a _StationLevelData sheet describing the instrument deployment, a _RawData file with data extracted as is from the instrument, and a _CleanData file with processed data as described in the metadata lineage statement. 
description: During deployments, data were stored on the system's internal memory and subsequently downloaded upon retrieval (ASCII engineering units). Quality control processes and procedures were then conducted on the raw data (filenames including _RawData). This included removing unused columns, deleting data collected while the system was out-of-water, and then saving the data in a useable comma delimited format (filenames including _CleanData).
DOI: 10.15493/sarva.saws.10000034
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the median for 2036 - 2065 relative to 1976-2005, for the MAM season, under the RCP 4.5 pathway

description: Root Mean Square Difference for seasonal (MAM) mean near-surface (2m) temperature (°C) change from the median projected for 2036-2065, relative to present (1976 - 2005), under the RCP 4.5 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 medium to low (RCP4.5) pathway which associates CO2 concentrations of approximately 560ppm 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/bea.data.10000079
title: Usable Plantation Residue (t/annum)

description: A South African, Lesotho and Swaziland forestry genera map was received from the Institute for Commercial Forestry Research at the University of KwaZulu-Natal. The forests in the Northern Cape and North-West provinces of South Africa were removed from the map. In South Africa there are no commercial plantations in the Northern Cape and North-West provinces thus these were excluded. Only the Acacia, Pine and Eucalyptus map locations in South Africa were analysed as these were the species that were cultivated for afforestation in the country. The other species, specified as other/mixed were also removed from the map and a South African Commercial Plantations Genera map was drawn.
DOI: 10.15493/sarva.beeh.10000097
title: Heat Units (Standard Deviation) - Winter

description: The concept of the heat unit (or degree day), known since the mid-18th century already, revolves around the development of a plants or organism`s being dependent upon the accumulated heat to which it was subjected during its lifetime, or else during a certain developmental stage. This measure of accumulated heat is known as physiological time. In general it holds that the lower the temperature, the slower the rate of growth and development of plants and invertebrate animals and the amount of heat required to complete a given organism's development does not vary. Physiological time is usually expressed and approximated in units of degree days, also popularly called heat units, where these are an accumulation of mean temperatures above a certain lower threshold value and below an upper developmental threshold (above which growth is considered to remain static or even decline), over a period of time. The degree day concept is not without its limitations. These include that, a linear relationship is assumed between growth and temperature, threshold temperatures may change during the life cycle of a crop or Pest, temperatures exceeding the upper threshold may, in fact, have a detrimental/negative effect on development.

Derivation over South Africa of heat units were done by calculating degree days for the daily temperature fluctuations that occur in nature. These range from degree hours, sine and triangular methods based on hourly temperatures, as well as so-called cut-off methods when the upper threshold of temperature is reached. To estimate heat units (HUs) over South Africa, the 50 year time series of daily maximum and minimum temperatures (Tmxd, Tmnd), generated at each of the 429 700 raster points covering the area at 1` x 1` latitude/longitude, was used (Schulze and Maharaj, 2004). The generation of this time series is described in Section 2a. HUs was computed for each day for a threshold temperature of 10 degree Celsius, i.e. HU = [(Tmxd + Tmnd) / 2 - 10] for HU ≥ 0.0 This method is a considerable advance on the computation of HUs in the previous version of this Atlas (Schulze, 1997), in which HUs were calculated from regression derived monthly means of Tmx and Tmn. From these daily values, monthly as well as seasonal and annual HUs and their standard deviations, could be calculated and mapped.
DOI: 10.15493/sarva.csag.10000442
title: Rainfall days per month 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/