cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.saws.10000216
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal total rainfall 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) rainfall (mm per month) 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 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/bea.data.250320-4
title: Forestry Residue Availability - Eastern Cape and KwaZulu-Natal forestry potential methodology

description: A report describing the methodology used to derive the potential for establishing new forestry areas within the Eastern Cape and KwaZulu-Natal provinces of South Africa.
DOI: 10.15493/sarva.energy.10000025
title: RUR-NOT: Rural Organic Waste - Biogas Digesters (MW)

description: Biomass feasibility assesment dataset extracted from the BioEnergy Atlas for South Africa.

* Assessments are made of impacts of economy of scale, logistics, and placement on techno-economic feasibility of feedstock and processing combinations, leading to identification of a portfolio of feasible project options. These options are illustrative of areas where bioenergy is likely to be a competitive, sustainable alternative.

* Original dataset: https://dx.doi.org/10.15493/BEA.DATA.10000048

* BioEnergy Atlas Synopsis Report: https://dx.doi.org/10.15493/SAEON.BEA.DOCS.10000001
DOI: 10.15493/sarva.beeh.10000432
title: Mean Maize Yield (T/Ha/Season) Medium Season Hybrid Plant Date: 15 December

description: This data set contains Maize, Zea mays L. in South Africa and is the country`s most important field and grain crop. Objectives of the study was to simulate maize yields, and their inter-annual, at a spatial resolution of Quaternary Catchments for 12 different combinations of three plant dates, viz. 15 October, 15 November and 15 December. This was done to evaluate which hybrid lengths and plant dates give the highest yields irrespective of plant dates and hybrid lengths respectively and also which hybrid lengths and plant dates give the lowest coefficients of variation (%) irrespective of plant dates and hybrid lengths respectively.
DOI: 10.15493/sarva.geoss.10000007
title: GRA2: Depth to groundwater (mamsl)

description: Groundwater Resource Assessment Phase 2, 2005.  1x1km waterlevel grid (mamsl)
DOI: 10.15493/sarva.beeh.10000338
title: Extremes (1950 - 2000) Of Minimum Temperatures (C) February

description: When days with very low or very high temperatures are experienced, the question is invariably asked as to whether that `extreme` minimum or maximum temperature was a record, either for the country or province, or for a specific location or month of the year. It is for that reason that `extremes` of temperatures, at both ends of the spectrum, were extracted from the daily temperature database generated by Schulze and Maharaj (2004) for the 51 year period (in this case) from 1950 to 2000, and analysed in tabular and mapped form. While these maps/tables are informative and interesting, there are nevertheless some limitations as to their accuracy, for reasons which are discussed in the shaded blocks containing some scientific background to the analyses.Limitations over South Africa to mapping extremes of temperatures, the generation of daily temperature time series at one arc minute spatial resolution at the 429 700 grid points covering South Africa depends on the selection of "best" control stations, extrapolating to altitudes above that of the highest-lying station in a particular region, as well as computational procedures regarding initial and final daily temperature values (Schulze and Maharaj, 2004). With respect to extreme minimum temperatures, no account has been taken of cold air drainage into valleys, which may aggravate minimum extremes.

Extremes of temperatures were derived from over 970 qualifying stations` records for the 51 year (1950 - 2000) time series of quality controlled daily maximum and minimum values generated at each of the 429 700 one arc minute (i.e. 1.7 x 1.7 km) raster points covering South Africa, using the regional/seasonal lapse rate and infilling techniques developed by Schulze and Maharaj (2004). In order to avoid analysing and mapping anomalous temperature extremes resulting from incorrect recordings, the extremes which were derived are therefore taken as the means of the two highest or lowest values found in the temperature time series at each grid point.
DOI: 10.15493/saeon.egagasini.10000018
title: The ASCA July 2018 (SEAmester III) processed oblique Bongo data for unit 2411

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 was collected during the ASCA project have been obtained from various oceanographic instrumentation. This is the processed product of data collected using an oblique Bongo net for unit 2411.
DOI: 10.15493/saeon.tierberg.10000014
title: Shrub demography 1988-1993

description: This package includes three worksheets, namely “BD8891”, “flowers” and “hosts”. The data are repeated measures of the basal stem diameters (1988-1991), flower production (1988-1993), and host plants of marked individuals of three shrub species (Pteronia empetrifolia, P. pallens and Tripteris sinuata) under two landuse histories and three levels of current herbivory. All marked plants were in permanent (5 m x 5 m) plots in indigenous Prince Albert Succulent Karoo vegetation on Tierberg Karoo Research Centre (TKRC) and on the adjacent farms Argentina (ARG) and Tierberg (TBG). The data collection began in November 1988, 17 months after TKRC was stock-fenced to exclude sheep. Thereafter data were collected intermittently until 1993. Spanning a period of 6 years the data have potential to show the effects of sheep grazing withdrawal on plant growth and reproductive potential for farms with different grazing histories. 

Note: Any publications, thesis, reports etc stemming from this data must be sent to SAEON Databank for records to be kept with the data.
DOI: 10.15493/sarva.saws.10000233
title: Seasonal total rainfall (mm per 3-month season) change from the 10% percentile projected for 2066-2095, relative to present (1976 - 2005), for JJA season under the RCP 8.5 pathway

description: Seasonal (JJA) rainfall (mm per month) 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 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.beeh.10000383
title: Uncorrected Vapour Pressure (kPa) October

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/sarva.beeh.10000176
title: Papaya: Optimum Growth Areas - Criterion 2: Optimum areas should have a low frequency of 4 consecutive days with maximum temperatures > 36 degree Celsius

description: Papaya, or pawpaw (Carica papaya) is a tropical fruit grown widely between latitudes 32 degree N and S. High in Vitamin C, papaya is indigenous to tropical America (ARC, 2005). This fruit, initially brought to the attention of Europe around 1520, was introduced to South Africa in seed form by Jan van Riebeeck in 1652, but only grown commercially in the Lowveld of Mpumalanga for the first time in the early 20th century by a Captain Elphick (ARC, 2005). Papaya needs relatively little water in the rainy summer season in South Africa, but if irrigated every 2 weeks in the dry season it is well adapted to hot, dry areas as the fruit then matures early and is then highly palatable owing to its high sugar content (Smith, 1998). Papaya has high heat requirements, with average daily temperatures for optimum growth between 20 and 30 degree Celsius.

Determination of climatically optimum growth areas for Papaya in South Africa is based on the expert knowledge of Bower (2005) and Moll (2005), climatically optimum growth areas were determined according to the four basic criteria: Criterion 1: Heat units (base 12 degree Celsius) should exceed 2 000 days per annum, Criterion 2: Optimum areas should have a low frequency of 4 consecutive days with maximum temperatures > 36 degree Celsius, Criterion 3: Monthly means of daily average temperatures in December and January should be 23 degree Celsius - 30 degree Celsius and Criterion 4: Optimum growth areas should have a low frequency of 4 consecutive days with minimum temperatures < 17 degree Celsius. Using the 50 year time series of quality controlled daily maximum and minimum temperatures generated by Schulze and Maharaj (2004) at a spatial resolution of 1 arc minute (i.e. 1` x 1` of a degree latitude/longitude), the above four temperature based criteria were first mapped individually and then superimposed to determine the climatically optimum growth areas of papaya in South Africa.
DOI: 10.15493/dea.carbon.10000101
title: Above ground herbaceous biomass for 2014 in t/ha

description: The above ground herbaceous biomass is a very small fraction of the total terrestrial organic carbon stocks and it was calculated with the same model as in the 2014 NTCSA dataset. The equation incorporates Rain Use Efficiency, amount of rain required to enable production per year and tree cover fraction. A mean herbaceous layer is modelled based on mean long term rainfall. The above ground herbaceous biomass was based on harvest factors obtained from the 2002 Agricultural Census. A proportional approach per land use, based on 2014 National Land Cover (NLC) data was used for the soil organinc carbon (SOC) analysis.
DOI: 10.15493/sarva.beeh.10000005
title: A-Pan Equivalent Reference Potential Evaporation (February)

description: Reasons for having selected the A-Pan as a reference for potential evaporation is that the US Weather Bureau Class A evaporimeter is, universally, the most common evaporation pan in usage, having been adopted as the standard evaporation pan since the International Geophysical Year 1957/8. Also when operated properly it is accepted as a reasonably reliable, simple and inexpensive local integrator of atmospheric evaporative demand, particularly for time periods longer than one day. Problems associated with the A-Pan as a reference for potential evaporation is that they are found generally near dams, existing irrigation projects or in areas of low relative relief where commercial agriculture is practiced. These sites are not always representative of higher altitudes where water is generated.

The data from over 570 South African stations at which a minimum of three years` concurrent monthly temperature, rainfall and A-pan evaporation observations are available, were used to develop temperature based equations of A-pan equivalent evaporation for each of the 12 evaporation regions identified in South Africa. The equations, unique for each month and for each region, were used to develop the 12 rasterised images of mean monthly A-pan equivalent evaporation on a 1` x 1` of a degree latitude/longitude grid.
DOI: 10.15493/sarva.beeh.10000223
title: Pinus greggii (N) Growth Areas and Yield Estimation

description: Populations of Pinus greggii are native to two geographical regions in Mexico, viz. a northern population (N) and a southern population (S). In their natural habitat, P. greggii stands from the southern population grow at high altitudes of 1 250 - 2 350 m, where they receive > 1 400 mm rainfall per annum (Dvorak, 2003).This species is, therefore, cold tolerant, but less hardy than P. greggii (N). It is also more drought tolerant than P. patula (Dvorak, 2003). P greggii (S) should, therefore, be established on sites which are too dry for P. patula. Following wide ranging provenance and progeny tests which were carried out in Brazil, Columbia, New Zealand, Zimbabwe and South Africa since the 1980s, the wood of P. greggii (S) has been found to have properties very similar to those of P. patula in terms of density, and it is acceptable for mechanical pulp as well as having excellent structural quality for saw timber (Dvorak, 2003).
DOI: 10.15493/saeon.fynbos.14a3871
title: 14A manual weekly rainfall May 1938 - May 1971

description: Weekly rainfall data collected by a Snowdon gauge with orifice at 1.2 meters above ground in the Langrivier catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/saeon.egagasini.10000059
title: The ASCA June 2018 raw ADCP data collected at Mooring D at 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 at Mooring F.
DOI: 10.15493/sarva.csag.10000267
title: Number of days for Maximum Temperature under 10th 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/sarva.beeh.10000127
title: Monthly Means Of Daily Maximum Relative Humidity (%) May

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/sarva.saws.10000032
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the 90% percentile 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 90% percentile 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/sarva.csag.10000108
title: Rainfall days per month (> 10mm) 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/sarva.csag.10000241
title: Mean of Minimum Temperature 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/sarva.beeh.10000111
title: Standard Deviations Of Daily Maximum Relative Humidity (%) January

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.