cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/saeon.egagasini.10000049
title: The ASCA June 2018 raw MicroCAT data collected at Mooring C 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 a MicroCAT sensor at Mooring C for the following depths: 100m, 400m, 550m, 750m, 1000m, 1250m, 1500m, 1750m and 2000m.
DOI: 10.15493/bea.data.10000025
title: AWB-COF: All Woody Biomass - Co-Generation (Catchments)

description: * Technical Challenges - ESKOM may have some risks associated with introduction of co-firing at power stations, and may elect to do so only at selected sites. The most feasible location is in Mpumalanga Highveld, but the availability of biomass is somewhat dependent on maize residues which may be highly variable. Western Cape option may not be feasible since power stations have been decommissioned. * Cost Challenges - Costs are acceptable comparable to current electricity from coal costs. * Policy Challenges - The projects are feasible, and well aligned with existing expertise and infrastructure in respect of `Working for Water` programmes. Integration with DEA `Working for Energy` required and incorporation into IPP programmes needed. * Environmental Challenges - The net impact on greenhouse gas emissions is sizable, despite land use change effects, given the significant reduction in GHG as CO2 equivalents in comparison to coal. If natural vegetation replaces invasives at more or less the same annual increment, LUC effects are near zero.
DOI: 10.5683/sp2/9h31oy
title: Improving speech perception in noise in young and older adults using transcranial magnetic stimulation

description: This dataset contains the experimental materials and stimuli as well as r scripts that were used in Brisson, V., Tremblay, P. (2021), Improving speech perception in noise in young and older adults using transcranial magnetic stimulation. Brain and Language. The task is an original auditory discrimination task that includes identical or different pairs of French syllables that were selected based on SyllabO+, a corpus and database of spoken Quebec French (Bédard et al., 2017). The stimuli and tasks were developed at the Speech and hearing neuroscience laboratory in Quebec City (www.speechneurolab.ca). The R scripts for the linear mixed-model analyses and regression analyses are also provided.
DOI: 10.15493/saeon.egagasini.10000069
title: The ASCA April 2016 raw CTD profile data collected for decktests

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 the ASCA project have been obtained from various oceanographic instrumentation. This raw data was collected by the shipborne CTD (Conductivity, Temperature, Depth) sensor as a decktest.
DOI: 10.15493/sarva.csag.10000304
title: Mean of Maximum 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/sarva.saws.10000264
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 SON season, under the RCP 4.5 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 SON season, 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/sarva.csag.10000421
title: Number of days for Minimum Temperature over 90th percentile for Near Future (2046-2065)

description: Model Run: Near future (2046 - 2065) (Near future (2046 - 2065)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/nccis.data.10000005
title: Linear trend in longest hot spell (1931-2015) defined as the number of days with at least 6 consecutive days when maximum temperature (TX) > 90th percentile of the baseline average.

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.10000307
title: Monthly Means Of Daily Average Temperature (C) 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.saws.10000035
title: Seasonal mean near-surface (2m) temperature (°C) change from the 10% percentile projected for 2036-2065, 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 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.10000347
title: Rainfall days per month (> 2mm) 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.fynbos.31022022
title: Moordenaarswerf Farm rainfall data

description: Daily rainfall data collected on Moordenaarswerf Farm, near Loeriesfontein in the Northern Cape. The data was collected using a standard rain gauge. 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.25b1720
title: 25B event rainfall October 2017 - August 2020

description: Event rainfall data collected by Texas Electronics tipping bucket gauge installed at 1.2m above ground at 873 masl in the Bosboukloof 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 0.254 mm increments.
DOI: 10.15493/sarva.csag.10000301
title: Number of days for Maximum Temperature under 10th 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.csag.10000174
title: Minimum of Minimum Temperature 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: 10.25835/epj4ecfj
title: µCT data of additively manufactured multimaterial concentrated wound stator teeth

description: This dataset contains micro-computed tomography images (µCT Scanner: Bruker SkyScan 1275) of multimaterial concentrated wound stator teeth. The data was collected for quality assurance of the component after additive manufacturing in order to examine the cooling channels for powder residues. This dataset includes the metadata of the examination and the corresponding layer images. For further information about the data and resulting models, it is referred to: Oel, M.; Rossmann, J.; Bode, B.; Meyer, I.; Ehlers, T.; Hackl, C. M.; Lachmayer, R. (2023). Multi-material laser powder bed fusion additive manufacturing of concentrated wound stator teeth. Additive Manufacturing Letters, Volume 7, p. 100165, ISSN 2772-3690, https://doi.org/10.1016/j.addlet This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) project number – 432176896 & 445707542.
DOI: 10.15493/sarva.csag.10000102
title: Number of days for Minimum Temperature under 10th 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.csag.10000057
title: Number of days for Minimum 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.csag.10000233
title: Number of days for Maximum Temperature under 10th 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.egagasini.10000094
title: Western Indian Ocean Energy Sinks (WOES) 0.25: a CROCO numerical ocean model hindcast at 1/4 degree daily for the south western Indian Ocean from 1993-2014.

description: This realistic ocean simulation was run using the Coastal and Regional Ocean COmmunity model (CROCO), based on the Regional Ocean Modelling System (ROMS), which has 60 terrain-following vertical levels. This output (WOES 0.25) is the largest grid of a triply nested configuration: WOES I, WOES II and WOES III, with horizontal resolutions of ~22.5, 7.5 and 2.5 km respectively. Monthly ouputs of the 0.25 degree GLORYS ocean reanalysis is used to force the boundaries of WOES I. The surface forcing for this model is provided by a bulk formulation using daily ERA-Interim atmospheric reanalysis (with a resolution of ~80 km) and using a relative wind approach. The output is saved as daily averages, in monthly netcdf files spanning January 1993 - December 2014. WOES 0.25 spans 55.7degS to 3.18388 degS and 10degW to 102.25degE and covers most of the Southern Subtropical Indian Ocean and a part of the Southern Atlantic Ocean. Model output includes: averaged free-surface (zeta), averaged vertically integrated u-momentum component (ubar), averaged vertically integrated v-momentum component (vbar), averaged u-momentum component (u), averaged v-momentum component (v), averaged potential temperature (temp), averaged salinity (salt), averaged vertical momentum component (w). 

Numerical computations were performed on the IDRIS (Institut du Developpement et des Ressources en Informatique Scientifique) IBM "ADA" computer facility (under grant A0020107630)
DOI: 10.15493/sarva.beeh.10000212
title: July Standard Deviations Of Daily Reference Crop Evaporation (mm) Fao Penman-Monteith Equivalent

description: The first detailed maps for South Africa of Penman-Monteith equivalent reference crop, Erpm, were derived from monthly ratios of Erpm: A-pan using data at 174 sites (Crosby and Crosby, 1996). From these ratios, Schulze (1997) identified 14 `regions` of similar ratio patterns which were then used to map Erpm from gridded A-pan values. The maps in the present Atlas are based on a much more deterministic and more fundamental approach with daily maximum and minimum temperatures, and hence daily saturated vapour pressures, generated over South Africa on a 1` x 1` (1.7 x 1.7 km) raster for 50 years, based on research by Schulze and Maharaj (2004). Empirically determined month-by-month gridded values of actual vapour pressure for South Africa.

The FAO (1992) definition of Penman-Monteith derived reference crop evaporation (Erpm) is `The rate of evapotranspiration from a hypothetical crop with an assumed crop height of 0.12 m, a fixed canopy resistance of 70 s.m-1 and albedo of 0.23, which would closely resemble evapotranspiration from an extensive surface of green grass cover of uniform height, actively growing, completely shading the ground and not short of water`.
DOI: 10.15493/sarva.251120-9
title: 2018 Estuary ecosystem threat status and protection level

description: This layer includes the threat status, protection level and condition of the Estuarine Ecosystems 2018 assessed for the National Biodiversity Assessment 2018.
DOI: 10.15493/sarva.saws.10000169
title: Seasonal mean near-surface (2m) temperature (°C) change from the 90% percentile 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 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 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.csag.10000279
title: Rainfall days per month (> 2mm) for Far Future (2080 - 2100)

description: Model Run: Far future (2080 - 2100) (Far future (2080 - 2100)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/