cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.beeh.10000228
title: Monthly Means Of Daily Solar Radiation (Mj/M2/Day) February

description: These daily estimates of solar radiation were derived using modifications for South African conditions of the Bristow and Campbell (1984) equation. The daily values can be used as input in other equations such as the Penman-Monteith equation for potential crop evaporation.

The method of estimation of daily solar radiation loadings over South Africa and its verification are as follows: based on the premise that clear sky solar radiation is determined essentially by extraterrestrial solar radiation modulated by an atmospheric extinction function, and dependent on high maximum temperatures associated with a high diurnal range in temperature, while cloudy/rainy conditions are associated with a low diurnal temperature range, the Bristow and Campbell (1984) equation was modified for South African conditions by regionally optimised expressions of clear sky depletion for atmospheric water vapour content, and by month-by-month regionalised expressions for solar radiation extinction by cloudy/rainy conditions. Other than the optimised regional/monthly coefficients and the computation of extraterrestrial radiation, which is undertaken with trigonometrical geometry functions, the only other variables used were daily maximum and minimum temperatures. The latter were determined for the 50 year period 1950 - 1999 at each of 429 700 one arc minute (1.7 x 1.7 km) raster points over South Africa by techniques outlined in Schulze and Maharaj (2004).
DOI: 10.15493/sarva.beeh.10000354
title: Standard Deviation (C) Of Daily Minimum Temperature May

description: Minimum (Night-Time) temperatures, there is abundant evidence for the climatic limitation of crop distributions to be described by minimum temperatures, from a perspective of crop survival (on Frost for tolerance levels of crops). Many subtropical crops may be killed at 5 degree Celsius already through chilling injury, even in the absence of frost (Chang, 1968). High minima increase respiration loss, thereby decreasing net photosynthesis.

Daily minimum temperature time series were derived from over 970 qualifying temperature stations` quality controlled daily records for the 50 year period 1950 - 1999. From these time series, 50 years of daily values of minimum temperatures were generated at each of 429 700 one arc minute (i.e. 1.7 km x 1.7 km) raster points covering South Africa, using regional and seasonal lapse rate and infilling/data extension techniques developed by Schulze and Maharaj (2004). Note that in the generation of daily minimum temperatures no account could be taken of cold air drainage into hollows or valleys, which can take place from surrounding higher-lying areas through radiative cooling during calm, stable clear night conditions. Reasons for this are provided in Schulze and Maharaj (2004). From these daily values, monthly means of daily minimum temperatures, as well as standard deviation of daily minimum temperatures for each month of the year, could be computed for purposes of mapping and production of statistics which are tabulated for Swaziland, Lesotho and for each of the nine provinces of the RSA. This approach to mapping minimum temperatures is thus fundamentally different to that used in the previous `South African Atlas of Agrohydrology and Climatology` (Schulze, 1997), in being much more physically based.
DOI: 10.15493/sarva.sdg.10000010
title: Number of maternal deaths associated with childbirth

description: Sustainable development Goal 3.1.1 Number of maternal deaths associated with childbirth for the years of 2016 and 2015 per 100 000 births. This data was derived from the 2016 StatsSA community survey and the StatsSA birth register. The data was dasymetrically mapped to a 500m grid using the 2008 spot dwelling count
DOI: 10.48331/scielo.vpgwbp/kvdspz
title: 1 Joanna Ball.pdf

description: :unav
DOI: 10.48331/scielo.vpgwbp
title: Those of us who do Open Access Plataforms – Metadata - DOAJ at 20: towards a more diverse, inclusive and equitable index

description: Presentation by Joanna Ball in the Those of us who do Open Access Plataforms – Metadata panel of the SciELO 25 Years Week. Event page: https://25.scielo.org/en
DOI: 10.15493/saeon.fynbos.19b1118
title: 19B event rainfall June 2011 - February 2018

description: Event rainfall data collected by Davis Instruments tipping bucket gauge installed at 1.2m above ground at 298 masl in the Biesievlei catchment of the Jonkershoek valley in the Western Cape of South Africa. Data recorded by a Pendant Event logger (UA-003-64, Onset, Massachusetts, U.S.A). Tipping bucket calibrated to 0.2 mm increments.
DOI: 10.17638/datacat.liverpool.ac.uk/2469
title: Conductance, NMR and SERS data for a set of DPPA organometallic complexes

description: See title
description: See README.txt
DOI: 10.48331/scielo.dd3pw9/meeupf
title: 3-Nathi Madondo.pptx

description: :unav
DOI: 10.48331/scielo.dd3pw9
title: Dialogues: Diversity, Equity, and Inclusion in Open Science Program - Inclusion through writing: SAJS Inclusive Language Policy

description: Presentation by in the Dialogues: Diversity, Equity, and Inclusion in Open Science Program panel of the SciELO 25 Years Week. Event page: https://25.scielo.org/en
DOI: 10.15493/sarva.beeh.10000303
title: Monthly Means Of Daily Average Temperature (C) April

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.saws.10000171
title: Seasonal mean near-surface (2m) temperature (°C) change from the median projected for 2066 - 2095, relative to present (1976 - 2005), for DJF season under the RCP 8.5 pathway

description: Seasonal (DJF) mean near-surface (2m) temperature (°C) change from the median projected for 2066-2095, relative to present (1976 - 2005), under the RCP 8.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily temperature averages, which are used to generate projections of seasonal change. The projections are generated using the high (RCP8.5) pathway which associates CO2 concentrations of approximately 950ppm by the year 2100. The associated RMSD it calculated and shows the uncertainty range of the projected model simulated residual values, and gives a relative perspective of spatial areas associated with higher and lower projection uncertainties.
DOI: 10.15493/sarva.beeh.10000191
title: Positive Chill Units - September

description: Certain biennial plants which have a dormant (i.e. rest) season during winter may require a period of accumulated minimum temperatures below a threshold in order to stimulate growth, develop leaves, flower or set fruit. Deciduous trees, for example, need a certain period of winter chilling for completion of their seasonal dormancy. Insufficient winter chilling may result in delayed foliation, reduced fruit set (including fruits remaining small and being misshapen as they ripen) and reduced fruit quality (including reduced firmness, and/or greener fruit coloration). The required amount of chilling for completion of the rest period varies between species, cultivars and different locations. Many chill accumulation models have been formulated, most of them requiring hourly temperatures to have either been observed or estimated. The Linsley-Noakes PCU model was used to produce maps of chill units in this Atlas. The techniques by which PCUs were computed and then mapped are described in the shaded sections which follow.

Derivation of hourly values of temperature for the determination of PCUs hourly values of temperature were determined from the 50 year time series of daily maximum and minimum temperatures generated at each of the 429 700 raster points covering South Africa, using the techniques described by Schulze and Maharaj (2004). For each daytime and night-time cycle the sine-log equations derived by Linsley-Noakes et al. (1995) were employed. In these equations the estimation of hourly temperatures is based on the observation that the daytime solar cycle follows a sine curve from sunrise to sunset, whereas night-time cooling may be described by a logarithmic equation.
DOI: 10.15493/sarva.beeh.10000395
title: Vapour Pressure Deficit (kPa) October

description: Daily values of vapour pressure deficit (VPD) are, however, required far more frequently, particularly when modelling crop potential evaporation using the Penman- Monteith equation (Penman, 1948). In this section a method used to estimate VPD is outlined, the method is verified and then maps and statistics of VPD are presented.

The hypothesis in estimating daily values of VPD at any specified location in South Africa is that actual VP, actual vapour pressure, which is considered to be a conservative climate element, and which may be derived from the monthly regression equations be held constant at that location for a given month. The fluctuating day-to-day daily temperature values at that location are then used with the Tetens (1930) formula given above to calculate a daily saturated VP, saturated vapour pressure. From actual vapour pressure and saturated vapour pressure daily values of VPD (and RH, if desired) can then be computed. This approach is known as the Schulze-Chapman model.
DOI: 10.15493/sarva.csag.10000211
title: Rainfall days per month (> 2mm) 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.saws.10000059
title: Seasonal mean near-surface (2m) temperature (°C) change from the 10% percentile projected for 2066 - 2095, relative to present (1976 - 2005), for MAM season under the RCP 4.5 pathway

description: Seasonal (MAM) mean near-surface (2m) temperature (°C) change from the 10% 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 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.beeh.10000284
title: Extremes (1950 - 2000) Of Maximum Temperatures (C) October

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.10000064
title: The ASCA June 2018 raw Current Meter 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. 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 G deployed at the following depths: 1000m, 1500m, 2000m, 3000m and 4200m.
DOI: 10.15493/dea.carbon.10000081
title: South African Land Cover 2014 Class O Bare Resampled to a 1km Grid

description: The 2013-14 South African National land cover dataset produced by (© GEOTERRAIMAGE - 2014) as a commercial data product was generated from digital, multi-seasonal Landsat 8 multispectral imagery, acquired between April 2013 and March 2014. In excess of 600 Landsat images were used to generate the land cover information, based on an average of 8 different seasonal image acquisition dates, within each of the 76 x image frames required to cover South Africa. The land cover dataset, which covers the whole of South Africa, is presented in a map-corrected, raster format, based on 30x30m cells equivalent to the image resolution of the source Landsat 8 multi-spectral imagery. The dataset contains 72 x land cover / use information classes, covering a wide range of natural and man-made landscape characteristics. The original land cover dataset was processed in UTM (north) / WGS84 map projection format based on the Landsat 8 standard map projection format as provided by the USGS. Class 40–41 of the 2013-14 South African National land cover dataset was clustered to derive South African land cover 2014 Class O Bare 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.csag.10000258
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: 10.48331/scielo.gyzl0k/ukbfvq
title: 4-Marilin Sanchez Rada.pptx

description: :unav
DOI: 10.48331/scielo.gyzl0k
title: Presentaciones de las Coordinaciones Nacionales - SciELO Bolivia

description: Presentación de Marilin Sánchez Rada en el panel Presentaciones de las Coordinaciones Nacionales de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es
DOI: 10.15493/saeon.tierberg.10000015
title: Decay

description: Two sets of data are included in the data set “decay”. Both deal with decay rates of organic matter at Tierberg Karoo Research Centre under a mean annual rainfall of 170 mm/year. The first documents the rate of disappearance of wood of four species of Karoo shrubs differing in specific density of wood. The second data set deals with the rate of disappearance of faecal pellets of merino sheep – wither buried below the soil surface or placed on the soil surface in three habitats – namely plains with a low density of wildlife, a sheep farm stocked at 6 ha/SSU and in association with wildlife and termitaria (Microhodotermes viator). Our published conclusions were that wood on the soil surface has a half-life of 9-18 years and that sheep dung pellets had half-lives of 5 to 10 years, breaking down more rapidly when buried than on the surface.

Acknowledge as follows: Data are the property of SAEON and were collected by SJ Milton, students and assistants, funded by the National Research Foundation, the Percy FitzPatrick Institute, University of Cape Town, and the Department of Science and Technology (DST) through the Biota-DST “Tierberg Reborn project”
DOI: 10.15493/dea.carbon.10000065
title: South African Land Cover 1990 Class O Bare 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 40–41 of the 1990 South African National land cover dataset was clustered to derive South African land cover 1990 Class O Bare 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.10000229
title: Seasonal total rainfall (mm per 3-month season) change from the 90% 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 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/bea.data.10000043
title: SUG-BUT: Butanol Fermentation from Sugarcane (Catchments)

description: * Technical Challenges - Rapid development of the feedstock source will be required, since the ethanol content of fuel cannot be increased incrementally. In the lead-up to full production at a facility, the sugar may be processed through traditional channels. * Cost Challenges - None of the projects are feasible; producing ethanol within the cost range of petrol in the recent past is only possible through subsidisation of the sugar input costs. Capital costs are low but operating costs are high. Utilising bagasse for electricity generation can offset the high operating costs. * Policy Challenges - Regulation of ethanol production similar to the wine industry will be required with regulation of a large number of small producers. * Environmental Challenges - Greenhouse gas mitigation depends strongly on (1) co-generation of electricity from bagasse to supply process energy and (2) whether land use change is minimised. Converting subsistence cropland to sugar cane cultivation will have a significant impact on biodiversity and water use.
DOI: 10.15493/bea.data.10000058
title: Planning Substations

description: Eskom provided the BioEnergy Atlas with a set of data to describe their current and planned infrastructure:
* High voltage transmission lines and substations;
* Medium voltage distribution lines and substations;
* Planned new transmission lines;
* Planned new substations.
All of these were aggregated to meso-zones (planning and analysis zones used for the Atlas) in the following way:
* Distribution and transmission lines: presence or absence of lines;
* Substations: count of medium voltage substations, and proximity (5km) to high voltage substations