cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.beeh.10000145
title: Monthly Means Of Daily Average Relative Humidity (%) November

description: Daily minimum and maximum relative humidity is necessary as relative humidity, defined for practical purposes as the ratio of actual to saturated vapour pressure, expressed as a percentage generally varies considerably in the course of a day because, despite actual vapour pressure, ed, remaining relatively constant, saturated vapour pressure, ea, varies curvilinearly with temperature. The minimum RH of a day is thus experienced during the hottest part of the day when ea is high and the ratio of ed : ea is therefore small. Conversely, the maximum RH of a day is experienced around sunrise when temperatures are low, thus ea is low and the ratio of ed : ea therefore approaches unity.

In computations of daily RHmin and RHmax, the uncorrected actual vapour pressure, ed , is assumed not to change significantly in the course of a day. Because uncorrected ed at any specific location has been shown to be predictable over South Africa on a month-by-month basis with a high degree of confidence when using predominantly geographical factors in multiple regression equations for each month the ed at any location is therefore held at a relatively constant value for any given month of the year, varying only slightly on a day-by-day basis within that month because temperature range is a variable in the regression equation. However, at that specific location the saturated vapour pressure, ea , can vary considerably from one day to the next, as well as within a given day between morning and midday, because it is related to temperature. Therefore, RHmin and RHmax can range considerably within a given day and vary markedly from one day to the next.
DOI: 10.15493/saeon.egagasini.10000065
title: The ASCA June 2018 raw Mooring G MicroCAT data collected 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. This raw data was collected by MIcrocat Sensors at Mooring G deployed at the following depths: 400m, 550m, 700m, 900m, 1100m, 1300m, 1500m, 1750m, 2000m, 2500m, 3000m, 3500m and 4200m.
DOI: 10.15493/sarva.beeh.10000398
title: Banana Yield Estimation (Dryland Plant Crop)

description: Modern bananas originated in the southeast Asian and western Pacific regions, with earliest records of cultivation in India about 2 500 years ago (ARC, 2005). Bananas are stress sensitive plants which grow satisfactorily with a MAP of 1 200 mm, ideally well distributed throughout the year (Smith, 1998). Dry spells of more than 7 days are detrimental to yields. Preferring a relative humidity > 60 percent (especially during fruit setting), the mid-day RH should generally exceed 50 percent. The optimum mean monthly temperatures for bananas are 25 - 28 degree Celsius, with a range of 20 - 35 degree Celsius. Growth ceases below 12 degree Celsius and the July mean of daily minima should be at least 8 degree Celsius. Of the 1 200 ha under bananas, 64 percent are in Mpumalanga, 18 percent are in KwaZulu-Natal and a further 18 percent in Limpopo (Statistics SA, 2002). Highest average yields, around 26 t/ha/an, are attained in Mpumalanga, while those in KwaZulu-Natal and Limpopo are 20 t/ha/an, i.e. on the low side by international standards (Statistics SA, 2002).

Determination of banana yield estimates, based on Smith`s climatic criteria. Areas considered climatically unsuitable for banana production and thus eliminated from further analysis were those with MAP < 900 mm (for dryland production), MAT < 16 degree Celsius, July means of daily minimum temperatures < 8 degree Celsius, the averages of the 12 monthly means of daily maximum temperatures < 22 degree Celsius and of minimum temperatures < 10 degree Celsius, as well as areas where the mean of the 12 monthly values of daily minimum RH was < 50 percent.
DOI: 10.15493/sarva3.data.10000005
title: Percentage of Households in Informal and Traditional Dwellings

description: The data was derived from the 2011 national census. 

The household counts for informal and traditional dwellings were obtained from the census small area layer data.

A 500m grid was used to map the dwelling frame distribution for South Africa. The resulting dataset was then intersected with the small area layer for the purpose of esmating the area percentages of dwellings within each grid cell. The area percentages for the grid cells were multiplied with the corresponding census count for each small area in order to map households by the type of dwelling.
DOI: 10.15493/sarva.csag.10000360
title: Mean 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/dea.carbon.10000091
title: South African Land Cover 2018 Class I Pineapple Resampled to a 1km Grid

description: Raster-based land cover dataset representing the full South African landscape for the full year 2018. Derived from 20m Sentinel 2 imagery acquired between 01 January 2018 and 31 December 2018. land cover information classes based on new Gazetted land cover standards and legend content used in 2013-14 national land cover data. All land cover and land-use classes generated using automated modelling procedures for full operational repeatability and change detection. Class 35 of the 2018 South African National land cover dataset was used to derive South African land cover 2018 Class I Pineapple 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.10000128
title: Root Mean Square Difference between the nine ensemble member change anomalies of the annual mean near-surface (2m) temperature for the 90% percentile for 2066-2095 relative to 1976-2005, under the RCP 8.5 pathway

description: Root Mean Square Difference for annual mean near-surface (2m) temperature (°C) change from the 90th 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 annual 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.10000017
title: Actual Vapour Pressure (January)

description: Actual vapour pressure is the variable expressing atmospheric moisture content through the partial pressure exerted by the water vapour present in the atmosphere. 

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 as inputs to daily saturated vapour pressure calculations, which were in turn used with that location's monthly uncorrected actual vapour pressure.
DOI: 10.15493/dea.carbon.10000003
title: Above Ground Woody Biomass (gC/sq.m)

description: AGBwoodyis estimated using the product of tree cover fraction (TCF) and height (Hveg), which were both estimated with coarse resolution satellite data, as a proxy for the volume woody vegetation. This volume is converted to aboveground biomass using constant, biome-specific Biomass Calibration Factor (BCFbiome). AGBwoody= (Hveg* TCF) * BCFbiomeUnits: (Two AGBwoodyoutputs are provided in two units) 1. average gC/m2within 1km x 1km pixel 2. average tonne Dry Matter / hectare (tDM/ha) within 1km x 1km pixel
DOI: 10.15493/sarva.sdg.10000004
title: Total number of houses from the 2011 census with access to electricity, as well as the number households that use electricity for cooking, heating and lighting

description: Total number of houses from the 2011 census with access to electricity dasymetrically mapped to a 500m grid using the 2008 spot dwelling count. The data provides an indication of the total number of households per 500m grid cell that use electricity for Cooking, Heating and Lighting
DOI: 10.15493/sarva.csag.10000147
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/dea.carbon.10000099
title: South African Land Cover 2018 Class Q Fallow Resampled to a 1km Grid

description: Raster-based land cover dataset representing the full South African landscape for the full year 2018. Derived from 20m Sentinel 2 imagery acquired between 01 January 2018 and 31 December 2018. Land cover information classes based on new Gazetted land cover standards and legend content used in 2013-14 national land cover data. All land cover and land-use classes generated using automated modelling procedures for full operational repeatability and change detection. Class 42–46 of the 2018 South African National land cover dataset was clustered to derive South African land cover 2018 Class Q Fallow 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.10000235
title: Seasonal total rainfall (mm per 3-month season) change from the 90% percentile projected for 2066-2095, relative to present (1976 - 2005), for SON season under the RCP 8.5 pathway

description: Seasonal (SON) rainfall (mm per month) change from the 90% 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 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.csag.10000365
title: Precipitation 90th percentile 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.fynbos.13b1118
title: 13B event rainfall June 2011 - February 2018

description: Event rainfall data collected by Davis Instruments tipping bucket gauge installed at 1.2m above ground at 439 masl in the Tierkloof 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 0.2 mm increments.
DOI: 10.15493/saeon.tierberg.10000004
title: Fertilizer Trial

description: This file contained data collected on a Nitrogen and Potassium addition trial established on the Tierberg Karoo Research Centre site in April 1998. The trial comprises 5 x 5 m plots with three randomly allocated replicates of the following treatments, N, K, N+K, Control. Nutrients were added in dry form at the rate of 10 g/square meter twice annually (April and September) from 1998 to 2008. The SE corner of each plot (2 x 2 m) was cleared of all above-ground vegetation in April 1998. The trial was originally established to test the hypothesis that the difference in the vegetation on and off heuweltjies (Microhodotermes viator nest areas) is caused by N and K availability rather than physical disturbance.
DOI: 10.15493/sarva.csag.10000029
title: Rainfall days per month (> 2mm) for Far Future (2080 - 2100)

description: Model Run: Far future (2080 - 2100) (Far future (2080 - 2100)). 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/bea.data.10000023
title: AWB-BIC: All Woody Biomass - Biomass Integrated Combined Gasification Cycle (Catchments)

description: * Technical Challenges - Existing expertise and infrastructure in respect of `Working for Water` programmes and in respect of harvesting and eradication projects required for conversion to electricity. It may be simpler and less risky to generate new sources of renewable electricity rather than converting existing power stations to co-firing. * Cost Challenges - There may be as many as 40 viable projects, all having a 20-year lifetime - with significant capital investment required. Since residues from plantations, sugar bagasse, and agricultural residues are also included, some plants may have a longer viable lifetime. * Policy Challenges - The projects are feasible and well aligned with existing expertise and infrastructure in respect of `Working for Water` programmes. Integration with DEA `Working for Energy` required and incorporation into IPP programmes needed. * Environmental Challenges - The net impact on greenhouse gas emissions is sizable, despite land use change effects, given the significant reduction in GHG as CO2 equivalents in comparison to coal. If natural vegetation replaces invasives at more or less the same annual increment, LUC effects are near zero.
DOI: 10.15493/sarva.energy.10000002
title: Global Horizontal Irradiation [Long Term Average of Yearly Sum]

description: Long term average of yearly sum of global horizontal irradiation (GHI) in kWh/m2, covering the period 1994-2013.

*Solar radiation data calculated by SolarGIS satellite-based model developed by GeoModel Solar, regionally adapted to ground measurements.
DOI: 10.15493/sarva.251120-7
title: Estuarine functional zone map

description: An extraction of the dune base line from the first version of an integrated coast map including coastal ecosystem types from the terrestrial, marine, and estuarine realms. The dune base line separates the shore from the backshore. The dune base represents the beginning of Tilney's (1985) Zone I of dune pioneer species and represents a more defensible and ecologically relevant approximation of a decadal scale dynamic ‘high water mark'.
DOI: 10.15493/saeon.egagasini.10000098
title: The ASCA July 2019 (SEAmester IV) raw CTD Profile data, SA Agulhas Voyage 037

description: The Agulhas System Climate Array (ASCA) is a mooring array and is designed to provide long-term observations of the Agulhas Current volume, heat and salt transport of the and it`s 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 the ASCA project have been obtained from various oceanographic instrumentation. This raw data was collected by Conductivity, Temperature, Depth (CTD) sensor deployments.
DOI: 10.15493/sarva.geoss.10000008
title: GRA2: Depth to groundwater (mbgl)

description: Groundwater Resource Assessment Phase 2, 2005.  1x1km waterlevel grid (mbgl)
DOI: 10.15493/sarva.sdg.10000008
title: Percentage of urban population living in informal housing and their access to services

description: Sustainable development goal sdg 11.1.1a and 11.1.1d Percentage of Urban population living in informal dwellings and their access to electricity, water, sanitation and refuse removal. This data was derived from the StatsSA 2011 census and disaggregated using a dasymetric mapping technique to a 500m grid based off the number of dwellings in that grid from the 2008 spot building count
DOI: 10.15493/sarva.beeh.10000453
title: Runoff and Streamflow and Their Variability

description: This dataset contains the runoff, streamflow and their variability in South Africa (SA). Distribution patterns over SA of annual runoff and streamflow attributes show highest quaternary catchments flows in excess of 100 mm and > 200 mm, the "wettest" is KwaZulu-Natal while below 25 mm and even < 10 mm occur predominantly in Northern Cape. Distribution patterns over SA of monthly runoff and streamflow attributes in the summer period range from < 2 mm equivalent in the western third of SA to > 40 mm equivalent in the east. During winter, flows are reduced to < 2 mm over 80 percent of SA.
DOI: 10.15493/sarva.csag.10000198
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/saeon.egagasini.10000077
title: The ASCA April 2016 raw Current Meter data collected 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 Current Meter at Mooring B for the following depth: 1000m.
DOI: 10.15493/saeon.gfw.10000001
title: Graminoid basal cover and biomass estimations in the Brotherton burning trial

description: The contribution of grass basal cover is an important measurement in rangeland science and is known as a proximate for grassland functional health and general range condition. Increased basal cover of grasses contributes to improved infiltration and reduces sediment losses. The importance of the Maloti-Drakensberg mountain range for water production has been emphasized and interest into the factors that influence basal cover and associated water delivery have followed. Measurements of basal cover in the Drakensberg have however, been constrained by timeous and inaccurate measurements (esp. the Hardy & Tainton (1993) method) associated with common techniques. This basal cover data was collected using a quadrat based technique which may be conveniently coupled to estimating herbaceous biomass. The method was tested on the Brotherton fire trial. 
The method is straight forward. A quadrat of 0.500x0.500 m with 10 cm divisions along horizontal and vertical axes gives 25 sub quadrats each representing 4 % of the area covered by the quadrat. Therefore, basal cover in the 25 sub quadrats can be scored from 0 – 4 % in increments of one then, the total summed to give percentage basal cover. To improve the visibility of basal cover quadrats should be clipped before estimating basal cover. Furthermore, clippings may be weighed for estimation of herbaceous biomass. A CyberTraker application for recording the data has been developed for field use. Photos were taken of each quadrat making data verifiable by viewing photos. For the purposes of this verification, sub quadrats were consistently recorded from left to right, beginning at row one to five in the quadrats (see labelling in fig. 1).  
A pilot study indicated that between six to eight quadrats per sample area (or treatment) are required. By placing six quadrats per plot at Brotherton, basal cover was estimated in the Brotherton field trial. Clippings were collected so that herbaceous biomass could be estimated. Sampling was done in winter after the autumn and winter burns, in these plots clipping was not necessary and biomass could not be collected.