cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.csag.10000118
title: Minimum of Maximum 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: 10.48331/scielo.5use0b/hlafje
title: 2-Edmilson Dias de Freitas.pptx

description: :unav
DOI: 10.15493/sarva.csag.10000265
title: Median monthly precipitation (mm) 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.5use0b
title: Autoridades Nacionais - "SciELO 25 anos"

description: Apresentação de Edmilson Dias de Freitas no painel Autoridades Nacionais da Semana SciELO 25 Anos. Página do evento: https://25.scielo.org/
DOI: 10.15493/sarva.saws.10000237
title: Seasonal total rainfall (mm per 3-month season) change from the median projected for 2066-2095, relative to present (1976 - 2005), for SON season under the RCP 8.5 pathway

description: Seasonal (SON) rainfall (mm per month) 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 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: 10.6084/m9.figshare.22047965
title: Crossover shortage in potato is caused by StMSH4 mutant alleles and leads to either highly uniform unreduced pollen or sterility

description: This zip file contains the data and code necessary to reproduce the figures and results of Clot et al. 2023 "Crossover shortage in potato is caused by <i>StMSH4</i> mutant alleles and leads to either highly uniform unreduced pollen or sterility"
DOI: 10.6084/m9.figshare.22047965.v1
title: Crossover shortage in potato is caused by StMSH4 mutant alleles and leads to either highly uniform unreduced pollen or sterility

description: This zip file contains the data and code necessary to reproduce the figures and results of Clot et al. 2023 "Crossover shortage in potato is caused by <i>StMSH4</i> mutant alleles and leads to either highly uniform unreduced pollen or sterility"
DOI: 10.15493/sarva.csag.10000292
title: Mean of Minimum Temperature for Far Future (2080 - 2100)

description: Model Run: Far future (2080 - 2100) (Far future (2080 - 2100)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/saeon.gfw.180423-2
title: Cathedral Peak Research Catchments Streamflow Data 2016-2022

description: Daily streamflow dataset for Cathedral Peak research catchment weirs CIII, CIV, V, VI, VII and IX. Data is provided in mm and cubic meters per day. The data has been quality controlled as described in the supplementary information.
DOI: 10.15493/saeon.070621-9
title: Water benefits of ecological restoration

description: This layer allows the user to find peer reviewed literature which documents scientific studies of the water related benefits of ecological restoration. Such benefits include improvements to the quality and quantity of water provided by ecological infrastructure.
DOI: 10.15493/saeon.fynbos.47022022
title: Overgauuw Wine Estate rainfall data

description: Monthly rainfall data collected on Overgaauw Wine Estate in Stellenbosch in the Western Cape. 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/sarva.csag.10000312
title: Rainfall days per month (> 10mm) for Near Future (2046-2065)

description: Model Run: Near future (2046 - 2065) (Near future (2046 - 2065)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/saeon.fynbos.49022022
title: Wellwood Farm rainfall data

description: Daily rainfall data from Wellwood Farm, and from adjacent rain gauges operated for several decades - Mountain Gauge, Woodcliffe and Trymore. 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. Note that the digitised data is not complete and has been published as is, notes on the status of the data from SAEON's Arid Lands Node below: We uploaded all available data already by 6th January, all 11000 rainfall records, over 8k from Wellwood, and the rest from adjacent rain gauges operated for several decades, e.g. Mountain Gauge, Woodcliffe, Trymore. Annual totals from Goliadskraal early records are from another farm. Actual individual rainfalls were taken as the “true” data and sums were taken as derived (there were a few errors in summing here and there). The sums were invaluable for proofreading the data done on the 2-D spreadsheet. The 1-D records were derived from that (worksheet called “records”). What is missing is the other information concerning the nature of the precipitation. From 1876 onwards (i.e. year-3) this was always recorded, and later also the time of day or night as in “morning”, “afternoon”, “night” etc. This we have not entered except a trial on the “records” worksheet.
DOI: 10.15493/sarva.csag.10000435
title: Mean of Maximum 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.csag.10000406
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: 10.15493/bea.data.10000001
title: Sugarcane Yield Estimates per mesozone

description: *Data shows sugarcane yield estimates for South Africa allocated to mesozones.
*South Africa is ranked 13th in the world (SA Yearbook, 2005) as a producer of sugarcane. Average sucrose content of the South African crop is approx. 13.5%, varying from 11.9 - 13.8% and inversely related to the year`s rainfall. It takes approximately 8.5 tonne sugarcane to produce 1 t sugar, varying from 8.3 - 10.0 t (SASA, 2005). Of the cane under irrigation, 72% is in KwaZulu-Natal (mainly Pongola and Mfolozi flats) and the remaining 28% in Mpumalanga (Statistics SA, 2002). Estimation of Sugarcane Yield was with the ACRU-Thompson Model equation which related sugarcane water use (total evaporation) to yield as Ysc = 9.53(Ean / 100) - 2.36 and where Ysc = annual sugarcane yield (t/ha), and Ean = annual total evaporation (mm). 
*Data was derived from the following sources:
- Base mesozone dataset, obtained from the CSIR Geospatial Analysis Platform (GAP) 
- Sugarcane yield estimates were derived from Schulze, R.E, Hull , P.J and Maharaj, M (2007)
DOI: 10.15493/sarva.beeh.10000259
title: Saturated Vapour Pressure (kPa) September

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/saeon.fynbos.la4661
title: Lambrechtbos A Kent stream flow volume December 1946 - March 1961

description: Hourly stream flow in cubic meters estimated from stage height measured with a Kent water level recorder at a V-notch weir in Lambrechtbos A catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/sarva.csag.10000114
title: Number of days for Maximum Temperature under 10th percentile for Near Future (2046-2065)

description: Model Run: Near future (2046 - 2065) (Near future (2046 - 2065)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/saeon.fynbos.12b4401
title: 12B manual weekly rainfall April 1944 - May 2001

description: Weekly rainfall data collected by a Snowdon gauge fitted with a Nipher shield. Gauge orifice parallel to the slope, 1.2 meters above ground in the Biesievlei catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/saeon.context.10000004
title: Municipal Ward Boundaries

description: In South Africa, wards are geopolitical subdivisions of municipalities used for electoral purposes. Each metropolitan and local municipality is delimited by the Municipal Demarcation Board into half as many wards as there are seats on the municipal council (rounding up if there are an odd number of seats). After the 2011 local elections, there are 4,277 wards in South Africa. * Data was obtained from the Municipal Demarcation Board and Independent Electoral Commission (IEC).
DOI: 10.15493/saeon.egagasini.10000086
title: The ASCA April 2016 raw MicroCAT 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 MicroCAT sensors at Mooring D at the following depths: 650m, 800m, 1000m and 1500m.
DOI: 10.15493/saeon.egagasini.10000090
title: The ASCA April 2016 raw ADCP data collected at Mooring C3 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) at Mooring C3.
DOI: 10.48331/scielo.mvewl3/s1dviq
title: 7-Sigmar de Mello Rode.pptx

description: :unav
DOI: 10.15493/saeon.ndlovu.10000003
title: SAEON: Lower Olifants-Letaba River Catchments Davis Automated Weather Stations - 30&60 minutes (TEMP, HUM, DEW, AVGk, PRESS, RAIN, UV, SOL) 2007-06-12 to 2018-12-31

description: This is a data set collected by eleven (11) of SAEON Ndlovu Node automated weather stations (AWS), located at across the lower parts of the Olifants and Letaba River catchments: SAEON/Scientific Services, Kruger National Park, Phalaborwa, Limpopo Province, South Africa (phalab_saeon); -23.945075 latitude, 31.165242 longitude);  Environmental offices, Palabora Mining Company, Phalaborwa, Limpopo Province, South Africa (pmc_mine; -23.985003 latitude, 31.149326 longitude); Letaba Exclosures, Kruger National Park , Limpopo Province, South Africa (knp_letaba_exclosure; -23.754902 latitude, 31.432009 longitude); South Gate, Mthimkhulu Communal Reserve, Limpopo Province, South Africa (mth_southGate; -23.661906 latitude, 31.033819 longitude); Mahale Farm, Limpopo Province, South Africa (mahaleFarm; -23.670796 latitude, 30.979561 longitude); House at Phalaubeni, Limpopo Province, South Africa (housePhalau; -23.552313 latitude, 31.048282 longitude); Frans du Toit High School, Phalaborwa, Limpopo Province, South Africa (school_fdt; -23.931972 latitude, 31.139835 longitude); Kingfisher Private School, Phalaborwa, Limpopo Province, South Africa (school_kfr; -23.952143 latitude, 31.142074 longitude); Majeje High School, Lulekani, Limpopo Province, South Africa (school_maj; -23.867528 latitude, 31.085879 longitude); Nkateko High School, Lulekani, Limpopo Province, South Africa (school_nka; -23.866344 latitude, 31.073649 longitude); Sebalamakgolo High School, Namakgale, Limpopo Province, South Africa (school_seb; -23.938219 latitude, 31.040651 longitude). The make and model of the stations is Davis Vantage Pro 2 and -Vantage Vue (schools).
DOI: 10.48331/scielo.mvewl3
title: Autoridades nacionais - ABEC Brasil

description: Apresentação de Sigmar de Mello Rode no painel Autoridades nacionais da Semana SciELO 25 Anos. Página do evento: https://25.scielo.org/
DOI: 10.15493/sarva.beeh.10000222
title: Climatically Suitable Growth Areas for the Pinus elliottii x caribaea hybrid

description: Hybridisation is undertaken among and within pine species with the aim of discovering and developing high-yielding varieties with suitable wood properties, in order to match the hybrids to appropriate sites for commercial production (Nikles, 2000). The Pinus elliottii x caribaea hybrid is proving important in South Africa because P. elliottii and P. caribaea have complementary traits. P. elliottii is straighter, more wind-firm and tolerant of poorly drained soils while P. caribaea, being native to the tropics and sub-tropics of South and Central America, has faster growth, superior branch quality and more uniform wood (Nikles, 2000).This hybrid, as may be seen from its matrix of climatically optimum and sub-optimum growth areas, has been cloned for growth in areas with high temperatures.The accompanying map shows that Pinus ExC grows optimally in the coastal areas of the Eastern Cape, much of eastern KwaZulu-Natal, western Swaziland and eastern Mpumalanga, wherever MAT > 16 degree Celsius.
DOI: 10.15493/sarva.beeh.10000086
title: Heat Units (Standard Deviation) - April

description: The concept of the heat unit (or degree day), known since the mid-18th century already, revolves around the development of a plants or organism`s being dependent upon the accumulated heat to which it was subjected during its lifetime, or else during a certain developmental stage. This measure of accumulated heat is known as physiological time. In general it holds that the lower the temperature, the slower the rate of growth and development of plants and invertebrate animals and the amount of heat required to complete a given organism`s development does not vary. Physiological time is usually expressed and approximated in units of degree days, also popularly called heat units, where these are an accumulation of mean temperatures above a certain lower threshold value and below an upper developmental threshold (above which growth is considered to remain static or even decline), over a period of time. The degree day concept is not without its limitations. These include that, a linear relationship is assumed between growth and temperature, threshold temperatures may change during the life cycle of a crop or Pest, temperatures exceeding the upper threshold may, in fact, have a detrimental/negative effect on development.
Derivation over South Africa of heat units were done by calculating degree days for the daily temperature fluctuations that occur in nature. These range from degree hours, sine and triangular methods based on hourly temperatures, as well as so-called cut-off methods when the upper threshold of temperature is reached. To estimate heat units (HUs) over South Africa, the 50 year time series of daily maximum and minimum temperatures (Tmxd, Tmnd), generated at each of the 429 700 raster points covering the area at 1` x 1` latitude/longitude, was used (Schulze and Maharaj, 2004). The generation of this time series is described in Section 2a. HUs was computed for each day for a threshold temperature of 10 degree Celsius, i.e. HU = [(Tmxd + Tmnd) / 2 - 10] for HU ≥ 0.0 This method is a considerable advance on the computation of HUs in the previous version of this Atlas (Schulze, 1997), in which HUs were calculated from regression derived monthly means of Tmx and Tmn. From these daily values, monthly as well as seasonal and annual HUs and their standard deviations, could be calculated and mapped.
DOI: 10.15493/dea.carbon.10000002
title: Soil Organic Carbon – Reduced by Land Use (gC/sq.m)

description: Soil Organic Carbon (SOC) represents all the organic carbon in the soil to a depth of 1m. SOC is derived from the data provided by the Africa Soil Information System (AfSIS). The organic carbon of soil is reduced by various land uses and agricultural practices and to account for this, the carbon in the top 300mm of the natural soil (SOC0-300) derived from AfSIS was reduced by a factor of 0.2 – 0.5 using the fractional land cover data per 1 X 1 km pixel. Units: average gC/m2within 1km x 1km pixel
DOI: 10.15493/sarva.saws.10000050
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 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 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 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.10000389
title: Mean of Minimum Temperature for Far Future (2080 - 2100)

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