cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.saws.10000240
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal total rainfall for the 10% percentile for 2066-2095 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 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.saws.10000022
title: Root Mean Square Difference between the nine ensemble member change anomalies of the annual total rainfall for the median for 2066 - 2095 relative to 1976-2005, under the RCP 4.5 pathway

description: Root Mean Square Difference for annual total rainfall (mm per year) change from the median projected for 2036-2065, relative to present (1976 - 2005), under the RCP 4.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily 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/nccis.data.10000009
title: Linear trend in the annual number of cold nights (1931-2015) defined as the annual number of days when minimum temperature (TN) < 10th percentile

description: An updated analysis of trends in South African temperatures is presented in The Third National Communication (TNC) to UNFCCC published in 2018. The analysis builds on the studies of Kruger & Sekele (2012) and Mackellar et al. (2014). 

A total of 27 weather stations was used for for temperature trends analysis spanning the period 1931-2015. Apart from the trends in the annual mean minimum, maximum and average temperatures, and average diurnal temperature range, the analyses also includes the determination of trends in extreme temperatures, of which the indices considered are based on those developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI) (Wang and Feng, 2013).  The base period, from which the annual index values of all indices are determined (except the annual maxima and minima) was selected as 1981 – 2010, which can be considered to be the present general norm for similar trend studies. The trends were tested for significance at the 95% confidence level.

The analysis demonstrates that, South Africa has been warming significantly over the period 1931-2015. Over the western parts of the country, including much of the Western and Northern Cape, and also in the east over Gauteng, Limpopo and the east coast of KwaZulu-Natal, the observed rate of warming has been 2 °C/century or even higher – in the order of twice the global rate of temperature increase.  Associated increases in the annual number of hot days have also occurred, but there have been decreases in the annual number of cold nights over most of the country.
DOI: 10.15493/sarva.beeh.10000317
title: Standard Deviations (C) Of Daily Mean Temperature May

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.10000054
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the 10% percentile for 2066 - 2095 relative to 1976-2005, for the DJF season, under the RCP 4.5 pathway

description: Root Mean Square Difference for seasonal (DJF) mean near-surface (2m) temperature (°C) change from the 10% percentile projected for 2066-2095, relative to present (1976 - 2005), under the RCP 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.10000032
title: Cold Spells

description: In South Africa cold spells are defined as 3 or more consecutive days with minimum temperatures below 2.5 degree Celsius, severe cold spells are 3 or more consecutive days with minima below freezing point, i.e. 0 degree Celsius, while extreme cold spells are defined as 3 or more consecutive days with temperatures below -2.5 degree Celsius. In South Africa the main causes of cold spells are outbreaks of Antarctic air which follow cold fronts, and in the southern hemisphere with its vast tracts of oceans, these cold fronts are frequently well developed. Cold spells affect many sectors, including health, especially exposure to low temperatures, energy, with marked increases in electricity consumption for heating purposes. In agriculture some consequences of cold spells include frost and freeze impacts, especially if the cold spells occur early or livestock losses, where the livestock has not been protected from the cold.

The temperature database created for South Africa by Schulze and Maharaj (2004) was used to compute frequencies of cold spells. In this temperature database daily maximum and minimum temperatures were generated for the 50 year period 1950 - 1999 at 429 - 700 one arc minute grid points covering the area, by using observed daily temperatures of varying durations from 973 temperature stations with quality controlled data which were infilled and extended to the common 50 year period by techniques outlined in Schulze and Maharaj (2004) and interpolated/extrapolated using regional and monthly temperature lapse rates.  What was not accounted for in mapping cold spell occurrences at each of the grid points was whether a point was located in a valley, and therefore subject to cross-sectional nocturnal cold air drainage from crest to valley bottom in the winter months, or on a crest. Schulze and Maharaj (2004) found some differences between minimum temperatures from stations located in valleys vs those on crests, but were not able to map such temperature differences because of the complex dynamics of determining longitudinal cold air drainage within a valley, i.e. from higher altitudes of the upper valley to the lower altitudes of the lower valley.
DOI: 10.15493/sarva.csag.10000191
title: Minimum 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.251120-5
title: 2018 artificial wetlands

description: Artificial wetlands of the South African Inventory of Inland Aquatic Ecosystems (SAIIAE). This data set is part of the Inventory released with the launch of the NBA 2018. National Wetland Map 5 includes inland wetlands and estuaries, but are associated with river line data and many other data sets within the South African Inventory of Inland Aquatic Ecosystems (SAIIAE). Please ensure you obtain the full geodatabase and relevant reports to understand the appropriate use of the data. Appropriate use and a disclaimer is provided under the relevant reports below.
DOI: 10.25345/c54j0b76f
title: MassIVE MSV000093082 - Alterations in lipidome profiles distinguish early-onset hyperuricemia, gout, and the effect of urate-lowering treatment
title: Background Currently, it is not possible to predict whether patients with hyperuricemia (HUA) will develop gout and how this progression may be affected by urate-lowering treatment (ULT). Our study aimed to evaluate differences in plasma lipidome between patients with asymptomatic HUA detected &lt; 40 years (HUA&lt;40) and &gt; 40 years, gout patients with disease onset &lt; 40 years (Gout&lt;40) and &gt; 40 years, and normouricemic healthy controls (HC). Methods Plasma samples were collected from 94 asymptomatic HUA (77% HUA&lt;40) subjects, 196 gout patients (59% Gout&lt;40), and 53 HC. A comprehensive targeted lipidomic analysis was performed to semi-quantify 608 lipids in plasma. Univariate and multivariate statistics and advanced visualizations were applied. Results Both HUA and gout patients showed alterations in lipid profiles with the most significant upregulation of phosphatidylethanolamines and downregulation of lysophosphatidylcholine plasmalogens/plasmanyls. More profound changes were observed in HUA&lt;40 and Gout&lt;40 without ULT. Multivariate statistics differentiated HUA&lt;40 and Gout&lt;40 groups from HC with an overall accuracy of &gt; 95%. Conclusion Alterations in the lipidome of HUA and Gout patients show a significant impact on lipid metabolism. The most significant glycerophospholipid dysregulation was found in HUA&lt;40 and Gout&lt;40 patients, together with a correction of this imbalance with ULT. Keywords LC-MS, Lipidomics, Glycerophospholipids, Hyperuricemia, Gout, Urate-lowering treatment
DOI: 10.15493/sarva.beeh.10000171
title: Monthly Means Of Daily Minimum Relative Humidity (%) October

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.10000272
title: Root Mean Square Difference in percentage (%) between the nine ensemble member change anomalies of the seasonal percentage rainfall for the median for 2066 - 2095 relative to 1976-2005, for the MAM season, under the RCP 8.5 pathway

description: Root Mean Square Difference in percentage (%) between the nine ensemble member change anomalies of the seasonal percentage rainfall for the median for 2066 - 2095 relative to 1976-2005, for the MAM season, under the RCP 8.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily rainfall averages, which are used to generate projections of seasonal change. The projections are generated using the high (RCP8.5) pathway which associates CO2 concentrations of approximately 950ppm by the year 2100. The associated RMSD it calculated and shows the uncertainty range of the projected model simulated residual values, and gives a relative perspective of spatial areas associated with higher and lower projection uncertainties.
DOI: 10.15493/dea.carbon.10000102
title: Above ground herbaceous biomass for 2018 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 the 2018 South African National Land Cover (SANLC2018)  data was used for the soil organinc carbon (SOC) analysis.
DOI: 10.15493/sarva.saws.10000224
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal total rainfall for the 90% percentile for 2066-2095 relative to 1976-2005, for the MAM season, under the RCP 8.5 pathway

description: Root Mean Square Difference for seasonal (MAM) mean rainfall (mm per month) 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/saeon.tierberg.10000009
title: Scorpion Burrows

description: A small dataset containing counts of scorpion burrows carried out on three occasions (2005, 2006, 2008) inside wildlife exclosures, in surrounding rangeland (accessed by wildlife including bat-eared foxes and other predators), and on an adjacent sheep ranch (access by wildlife and sheep). All counts were in defined quadrats 5 m x 5 m in size. It was assumed that a clearly defined burrow indicated the presence of a live scorpion (Opisthophthalmus palidipes).

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/saeon.fynbos.bo1120
title: Bosboukloof stream flow and stage height August 2011 - August 2020

description: Hourly average and halfhourly sample stream flow in cumec estimated from stage height measured with an OTT Orpheus Mini in the stilling well at a V-notch weir in Bosboukloof catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/saeon.egagasini.10000051
title: The ASCA June 2018 raw ADCP data collected at Mooring D for all depths

description: The Agulhas System Climate Array (ACSA) is a mooring array and is designed to provide long-term observations of the Agulhas Current`s volume, heat and salt transport and its variability from mesoscale (eddies), through seasonal to interannual timescales. The ASCA shelf and tall moorings extend 200 km offshore along decending TOPEX/Jason satellite ground track # 96, through the core of the Agulhas Current, with CPIES measurements extending the array to 300 km offshore of Port Elizabeth. The data collected during this project have been obtained from various oceanographic instrumentation fixed to each mooring. This raw data was collected by an ADCP (Acoustic Doppler Current Profiler).
DOI: 10.15493/sarva.beeh.10000322
title: Standard Deviations (C) Of Daily Mean Temperature October

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/bea.data.250320-16
title: Sugarmill production information

description: A spatial dataset of the locations and production volume of sugar mills in South Africa - derived from the mill production data supplied by the South African Sugarcane Research Institute (SASRI).
DOI: 10.15493/sarva.csag.10000149
title: Number of days for Maximum Temperature over 90th percentile for Current Climate (1950-1999)

description: Model Run: Control - Current Climate (Observed/current climate as modelled by climate model). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/sarva.021221
title: Education Management Information Systems (EMIS) Schools Masterlist Data

description: This dataset is a national master schools list, consisting of ordinary public schools as well as independent schools in South Africa for Quarter 4 of 2020, ending March 2021. These schools are collectively known as the ordinary schools of South Africa. This data are assembled by the Education Management Information Systems (EMIS) unit in the Department of Basic Education (DBE), from databases uploaded on Learner Unit Record Information and Tracking System (LURITS) and Provincial Data Warehouses. EMIS maintains an integrated education information system, therefore, this dataset was originally published as spreadsheets (one for each of the provinces), containing the locations of schools and associated attribute data. The data has now been republished by SAEON as a single shapefile, containing 9 provincial layers with the locations of ordinary schools in South Africa. The dataset compromises of 23 857 schools generated from  utilising multiple geocoding methods to provide a comprehensive spatial inventory.
DOI: 10.15493/saeon.fynbos.lb6108
title: Lambrechtbos B Belfort stream flow volume March 1961 - October 2008

description: Hourly stream flow in cubic meters estimated from stage height measured with Belfort 5-FW liquid level recorder at a V-notch weir in Lambrechtbos B catchment in the Jonkershoek valley, Western Cape, South Africa.