cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.csag.10000104
title: Maximum 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/saeon.070621-8
title: Soil benefits of ecological restoration

description: Since soil is a limited resource and can take thousands of years to develop, this layer provides peer reviewed literature about managing, restoring and improving healthy soil which makes it more useful, and capable of high produce and beneficial to people.
DOI: 10.15493/sarva.beeh.10000131
title: Monthly Means Of Daily Maximum Relative Humidity (%) September

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.beeh.10000412
title: Acocks Veld Types

description: This data set contains Acocks` veld types . This study makes a case for using Acocks` (1988) Veld Types as the baseline for use in agrohydrological simulations for reference conditions and also for hydrological impact studies in South Africa.
DOI: 10.15493/sarva.saws.10000019
title: Annual total rainfall (mm per year) change from the 90% percentile, projected for 2066 - 2095 relative to the present (1976-2005) under the of the RCP 4.5 pathway conditions.

description: Annual total rainfall (mm per year) change from the 90% percentile 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 rainfall averages, which are used to generate projections of annual 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/saeon.070621-5
title: Community benefits of ecological restoration

description: This layer provides access to peer reviewed literature on the community benefits of ecological restoration. By restoring landscapes, ecosystem services improve to the benefit of individuals additionally, restoration initiatives also provide employment and impart skills to individuals. The people who are dependant on the ecosystem have a key role in setting priorities and in project implementation.
DOI: 10.48331/scielo.9rk25s/t8osnz
title: 8-Rondineli Saad.pptx

description: :unav
DOI: 10.15493/bea.data.10000037
title: MAI-BUT: Fermentation of Maize Grain to n-Butanol (Catchments)

description: * Technical Challenges - Technology is relatively simple and has high conversion efficiency. * Cost Challenges - Despite efficiency, levelised costs are high, due to mainly 2 factors (1) the input cost of raw material is high, and (2) operating costs are high due to feedstock (methanol) and distillation operations. Selling oilcake has a significant effect on final product cost, with a 50% oilcake internal subsidy reducing the costs by R 6,500/ t (0.65 R/kWh). This would bring production cost into line with current range of diesel prices. * Environmental Challenges - Greenhouse gas savings are significant provided land use changes are carbon neutral. Limiting cultivation to subsistence cropland should assist with this goal. * Social and Institutional Challenges - Conversion of subsistence farmers in former homeland areas, with high reliance on cattle and maize, to a cash crop with side products for own consumption and cattle feed will require significant community involvement. Cooperative farming and marketing channels need to be investigated.
DOI: 10.48331/scielo.9rk25s
title: Modelo SciELO de publicação - Preservação Digital e Segurança da Informação

description: Presentación de Rondineli Saad en el panel Modelo SciELO de publicação de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es
DOI: 10.15493/sarva.beeh.10000257
title: Saturated Vapour Pressure (kPa) July

description: The average energy of the molecules in a liquid such as water is governed by temperature. The higher the temperature, the higher the average energy. Some molecules have higher energies than the average, and if they are on the surface of the liquid, can move fast enough to escape the inter-molecular attractive forces holding the liquid together. They then evaporate from the surface of the liquid. This process can continue until the space above the liquid is saturated with water molecules. Equilibrium is then reached with as many molecules leaving the surface of water as are re-entering it. At this point the pressure exerted by that vapour is called the saturated vapour pressure. The symbol used for saturated vapour pressure is ea and the unit of pressure is kPa. Since the molecular kinetic energy is greater at higher temperature, more molecules can escape the surface and the saturated vapour pressure is correspondingly higher. This relationship is illustrated in the shaded box.

Daily values of saturated vapour pressure were computed from the 50 year daily time series of temperature generated for South Africa at each one of 429 700 raster points at one arc minute interval, using techniques developed by Schulze and Maharaj (2004).
DOI: 10.15493/sarva.csag.10000091
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: 10.48331/scielo.av2ppc/h6tjsd
title: 7-Roberta_Takenaka.pptx

description: :unav
DOI: 10.48331/scielo.av2ppc
title: Modelo SciELO de Publicación - Actualizaciones de la plataforma metodológica y tecnológica

description: Presentación de Roberta Takenaka en el panel Modelo SciELO de Publicación de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es
DOI: 10.15493/sarva.csag.10000170
title: Number of days for Minimum 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: 10.48331/scielo.2vqyvs/oqsy8g
title: 6-Amanda Ramalho.pptx

description: :unav
DOI: 10.48331/scielo.2vqyvs
title: Modelo SciELO de Publicación - SciELO Libros

description: Presentación de Amanda Ramalho en el panel Modelo SciELO de Publicación de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es
DOI: 10.15493/sarva.beeh.10000177
title: Papaya: Optimum Growth Areas - Criterion 3: Monthly means of daily average temperatures in December and January should be 23 degree Celsius - 30 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/sarva.csag.10000285
title: Number of days for Maximum Temperature over 90th percentile 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/saeon.fynbos.20022022
title: Eden Farm Weather Station Data

description: Weather data collected by an automated weather station near Albertinia on Eden Farm. 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/saeon.fynbos.20b1118
title: 20B event rainfall June 2011 - February 2018

description: Event rainfall data collected by Davis Instruments tipping bucket gauge installed at 1.2m above ground at 409 masl at the Uitkyk station in 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/sarva.beeh.10000320
title: Standard Deviations (C) Of Daily Mean Temperature August

description: Under conditions of natural vegetation, mean temperatures are used to distinguish between three broad thermal divisions of plants, viz. mega-thermal plants, which require mean monthly temperatures above 20 degree Celsius for at least 4 months of the year; micro-thermal plants, which grow where 8 months or longer have means below 10 degree Celsius; and the meso-thermal plants of the mid-latitudes, which cover most of South Africa, and whose physiology is adapted to the strong seasonal rhythms which are experienced over most of the southern African subcontinent. Month-by-month variations of mean temperature influence the geographic range and the optimum growth areas of certain vegetation and crop species, especially those with life-cycles extending one year or less. 

Assuming a daily average temperature to be represented by the mean of that days` minimum and maximum temperatures, these averages were derived from the 50 year (1950 – 1999) time series of quality controlled daily minimum and maximum temperatures which were generated from over 970 qualifying temperature stations using infilling and record extension techniques developed by Schulze and Maharaj (2004). From these point location time series, 50 years of daily mean temperature values were derived at each of 429 700 one arc minute (1.7 km x 1.7 km) grid points covering South Africa, using regionally and seasonally determined lapse rates and other physically appropriate spatial interpolation approaches (Schulze and Maharaj, 2004). From the daily values, monthly means and standard deviations of daily values for each month of the year could be computed for purposes of mapping and production of tables of statistics for each of the nine provinces of the RSA as well as for Swaziland and Lesotho.
DOI: 10.15493/sarva.beeh.10000126
title: Monthly Means Of Daily Maximum Relative Humidity (%) April

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.10000182
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 2066 - 2095 relative to 1976-2005, for the JJA season, under the RCP 8.5 pathway

description: Root Mean Square Difference for seasonal (JJA) mean near-surface (2m) temperature (°C) change from the 90% 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/bea.data.10000016
title: Eucalyptus grandis estimates per mesozone

description: *The data shows Eucalyptus grandis yield estimates allocated to mesozones. Yield estimates were derived from Schulze R.E. and Maharaj M. (2007) and then allocated to mesozones by combining with a base mesozone layer obtained from the CSIR Geospatial Analysis Platform (GAP). *E. grandis is native to the east coasts of Queensland and New South Wales in Australia, where it goes by the common name of Rose Gum (Meskimen and Francis, 2005). In its native habitat E. grandis, with its pronounced taproot, grows to 55 m in height on the lower slopes in well drained soils. Determination of Climatically Optimum Growth Areas of E. grandis have been defined in the ICFR's Forestry Toolbox (Kunz, 2004), by mean annual precipitation (MAP) and mean annual temperature (MAT). *E. grandis Yield Estimates Based on Smith`s Rule-Based Approach Using Smith`s (1994) rule-based approach for estimating MAIs of E. grandis, and considering only his climatic criteria and not soil or management factors
DOI: 10.15493/sarva.saws.10000100
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal total rainfall 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) rainfall (mm per month) 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 rainfall 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/nccis.data.10000021
title: Projected changes in annual mean temperature (°C) under RCP 4.5 for the 2015-2035 time period based on the Australian Community Climate and Earth System Simulator (ACCESS1-0)

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.10000113
title: Total soil organic carbon for 2014 in gC.m2

description: ISRIC Africa SoiGrids data were used to calculate a reference layer of soil organic carbon (SOC). It was done by using the organic carbon content and bulk density layers available at 250m resolution and for 6 different depths. The data was aggregated to a depth of 30cm for topsoil and 100cm for subsoil. This layer was converted from t/ha to gC/sqm
DOI: 10.15493/saeon.fynbos.8b1118
title: 8B event rainfall June 2011 - February 2018

description: Event rainfall data collected by Davis Instruments tipping bucket gauge installed at 1.2m above ground at 366 masl in the Langivier 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.