cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.csag.10000405
title: Maximum of Minimum Temperature for Current Climate (1950-1999)

description: Model Run: Control - Current Climate (Observed/current climate as modelled by climate model). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/sarva.csag.10000335
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/sarva.saws.10000028
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal mean near-surface (2m) temperature for the median for 2036 - 2065 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 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 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.10000385
title: Minimum 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.010221
title: South African Health Subdistrict Boundaries

description: This dataset demarcates the boundaries of the health subdistricts across South Africa. Health subdistricts were generated in the largest metropolitan municipalities in South Africa including the City of Cape Town,  City of Ekurhuleni, City of Johannesburg, City of Tshwane, Mangaung Metropolitan Municipality, Nelson Mandela Bay Metropolitan Municipality. Buffalo City Metropolitan Municipality and eThekwini Metropolitan Municipality do not currently contain any further health subdistricts. The rest of the boundaries are based on the 2016 Local Municipality boundaries. This shapefile was downloaded from the National Department of Health servers on 08-May-2020. 

City of Cape Town: CT Eastern SD, CT Khayelitsha SD, CT Klipfontein SD, CT Mitch Plain SD, CT Northern SD, CT Southern SD, CT Tygerberg SD, CT Western SD

City of Ekurhuleni: Ekurhuleni E1 SD, Ekurhuleni E2 SD, Ekurhuleni N1 SD, Ekurhuleni N2 SD, Ekurhuleni S1 SD, Ekurhuleni S2 SD

City of Johannesburg: Johannesburg A SD, Johannesburg B SD, Johannesburg C SD, Johannesburg D SD, Johannesburg E SD, Johannesburg F SD, Johannesburg G SD

City of Tshwane: Tshwane 1 SD, Tshwane 2 SD, Tshwane 3 SD, Tshwane 4 SD, Tshwane 5 SD, Tshwane 6 SD, Tshwane 7 SD

Mangaung Metropolitan Municipality: Bloemfontein SD, Botshabelo SD, Naledi SD, Thaba N`chu SD

Nelson Mandela Bay Metropolitan Municipality: N Mandela A SD, N Mandela B SD, N Mandela C SD
DOI: 10.15493/saeon.fynbos.ne6691
title: Nerine Belfort stream flow volume October 1966 - October 1991

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 Langrivier catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/sarva.csag.10000237
title: Minimum 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/saeon.fynbos.22b8092
title: 22B manual weekly rainfall April 1980 - April 1992

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 at Swartbrug in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/sarva.csag.10000145
title: Consecutive Dry Days 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.10000034
title: IAP-NOT: Invasive Alien Plants - Pelleting

description: * Technical Challenges - Existing expertise and infrastructure in respect of `Working for Water` programmes exist, and pelleting equipment can easily be scaled to suit requirements. * Cost Challenges - The ten top projects are feasible, producing wood pellets within the range of current fuelwood and charcoal prices locally. * 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. * Environmental Challenges - The net impact on greenhouse gas emissions is at best neutral, given that sequestrated carbon will be removed in the short term and may not be replaced by indigenous biomass entirely. If pellets are used mostly for fuelwood replacement, net effects are limited to production emissions.
DOI: 10.15493/dea.carbon.10000103
title: Below ground herbaceous biomass for 1990 in t/ha

description: Below ground herbaceous values were calculated with the same set of equations as used for above ground herbaceous layers. Agricultural biomass is  reduced with a factor of 0.2  of the above ground biomass while a ratio of 1:1 is assumed between above ground and below ground herbaceous biomass for natural vegetation. National Land Cover 1990 (NLC1990) was used to calculate biomass per land cover class for 1990.
DOI: 10.15493/sarva.csag.10000229
title: Precipitation 90th percentile for Far Future (2080 - 2100)

description: Model Run: Far future (2080 - 2100) (Far future (2080 - 2100)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/sarva.csag.10000054
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/dea.carbon.10000106
title: Above Ground Litter for 1990 in t/ha

description: Above ground litter consists of downed wood, leaves and dung on the soil surface. It was calculated per biome based on a simple model including litterfall and decay rates as a function of rainfall. This was validated against the fuel load datasets. Biome factors calculated by Powell (2009), Shea et al (1996), Weider & Wright (1995) and van Wilgen et al (1990) were used.
DOI: 10.15493/nrf.saiab.20232507
title: Bathymetry data collected from uMhlanga, January 2020

description: African Coelacanth Ecosystem Programme (ACEP) Smart Zones MPA
description: This dataset forms part of the South African Institute for Aquatic Biodiversity (SAIAB)'s collection of Bathymetry data for the African Coelacanth Ecosystem Programme (ACEP) Smart Zones MPA.  This hydrographic survey assesses the application of multibeam bathymetry data in biological research. This dataset consists of XYZ points below the sea surface and relative to the mean sea level. This data was collected under the ACEP Geo-Benthic trials (2020) using the ACEP Geophysics and Mapping Platform
description: See metadata file for additional information.
DOI: 10.15493/sarva.energy.10000014
title: Wind Speed (m/s) - Western Cape

description: Purpose: 
This data set was created for the WASA project and the Department of Energy, South Africa. The wind resource maps were designed specifically for inclusion in GIS-based strategic environmental assessments (SEA) for wind power in Western Cape and parts of Northern and Eastern Cape.

Methodology:
Reference is made to the information and documentation available from www.wasaproject.info and www.wasa.csir.co.za.

Limitations:
The data set is limited by the operational envelopes of the wind atlas methodology and the WAsP models. The accuracy depends on a) the accuracy of the VNWA, which has been verified against the data from 10 WASA measurement masts, b) the WAsP microscale modelling and c) the input topographical data.

In complex terrain (RIX > 5%), the wind resources may be significantly over-estimated by the WAsP microscale modelling. Above and close to built-up areas like cities, towns and villages, the results are less reliable. Close to and above forested areas, the results are also less reliable and should be interpreted and used accordingly.

The data set was designed specifically for planning purposes and should be used with utmost care for design, development and detailed assessments of actual wind farms; where local, on-site measurements are strongly recommended. The wind resource maps are subject to change without notice if and when more accurate and reliable data, models and procedures become available.

Available documentation:
The wind atlas methodology is described in the European Wind Atlas (1989); the application of WAsP in the program documentation, see www.wasp.dk. The Verified Numerical Wind Atlas for South Africa is a product of the Wind Atlas for South Africa project and is described further on the WASA download pages http://wasadata.csir.co.za/wasa1/WASAData.

Acknowledgements:
WASA project for Frogfoot application and provision of wind-climatological and topographical data. WAsP development teams at DTU Wind Energy and World in a Box Oy for Frogfoot development.
DOI: 10.15493/sarva.beeh.10000030
title: Codling Moth Life Cycles Per Annum Present Climate

description: The codling moth, Cyclia pomonella, is a native of Eurasia. The larva familiarly known as "apple worm" is one of the most serious pests of apples, with injury especially severe in processing orchards (relative to fruit destined for fresh use). Codling moth larvae also attack pears, walnuts, quince and other fruit (OSU Factsheet, 2005). The larvae usually tunnels to the core of the apple, pushing out a mass of chewed material called frass, thereby greatly lowering the market value and storage quality of the fruit, as well as making it unfit for people to eat (OSU Factsheet, 2005).

Life cycles per annum were determined by computing degree days (base 10 degree Celsius), utilising 50 years of daily values of maximum and minimum temperatures generated by techniques described in Schulze and Maharaj (2004) at each of - 430 000 one arc minute (1` x 1` latitude by longitude) grid points covering South Africa. The degree days accumulated over one year were then divided by the days required for one life cycle to be completed by codling moths (603 days) and oriental fruit moths (535 days), respectively.
DOI: 10.15493/sarva.csag.10000291
title: Maximum 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.beeh.10000047
title: Frequency of Frost Occurrences

description: Neither the median dates of first and last frosts nor the median duration of the frost period give any indications on the number of years within the 50 year time series of temperature values used in the study (Schulze and Maharaj, 2004) in which frost actually occurred, nor on the number of frost occurrences within a year, nor on the variability of frost occurrences from year to year.

In the mapping statistics of frost over South Africa, the temperature database used in this study contained quality controlled time series of daily maximum and minimum temperatures from > 970 qualifying temperature stations, the records of which had been infilled and extended (where necessary) to a common 50 year time period 1950 - 1999 by techniques described in Schulze and Maharaj (2004). These daily station records were then used with regionally and seasonally determined temperature lapse rates to generate 50 years of daily maximum and minimum temperatures at each of 429 700 one arc minute (1.7 x 1.7 km) raster points covering the RSA, Lesotho and Swaziland. At each raster point a minimum temperature of ≤ 0 degree Celsius in the 50 year daily time series was designated a `heavy frost day`. Any raster point where < 5 years out of the 50 had experienced least one heavy frost day that point was deemed to be `frost free`.
DOI: 10.48331/scielo.0xd4za/mai3mj
title: 3-Susan Veldsman.pptx

description: :unav
DOI: 10.48331/scielo.0xd4za
title: Those of us who do: Open Access Plataforms - Accelerating progress to Open Science in Africa

description: Presentation by Susan Veldsman in the Those of us who do: Open Access Plataforms panel of the SciELO 25 Years Week. Event page: https://25.scielo.org/en
DOI: 10.15493/bea.data.250320-9
title: Harvested forestry residue

description: A geospatial layer of Department of Environment, Forestry and Fisheries (DEFF) forestry regions and associated potential total harvesting residue annually available from wattle, pine and eucalyptus for 2020-2035.
DOI: 10.15493/sarva.csag.10000074
title: Rainfall days per month (> 10mm) for Far Future (2080 - 2100)

description: Model Run: Far future (2080 - 2100) (Far future (2080 - 2100)). The Self-Organizing Map Downscaling (SOMD) was developed at the Climate Systems Analysis Group (CSAG)[1], University of Cape Town. This is a leading empirical downscaled technique and provides meteorological station level response to global climate change forcing (See Hewitson and Crane (2006) for methodological details and Wilby et al. (2004) for a review of this and other statistical downscaling methodologies). Downscaling of a General Circulation Model (GCM) is accomplished by deriving the normative local response from the atmospheric state on a given day, as defined from historical observed data.  [1] http://www.csag.uct.ac.za/
DOI: 10.15493/saeon.fynbos.6b4491
title: 6B manual monthly rainfall January 1944 - September 1991

description: Monthly rainfall data collected by a Snowdon gauge fitted with a Nipher shield. Gauge orifice parallel to the slope, with orifice at 1.2 meters above ground in the Tierkloof catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/sarva.saws.10000132
title: Root Mean Square Difference between the nine ensemble member change anomalies of the annual mean near-surface (2m) temperature for the 10% percentile for 2066-2095 relative to 1976-2005, under the RCP 8.5 pathway

description: Root Mean Square Difference for annual mean near-surface (2m) temperature (°C) change from the 10th 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 annual 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.10000289
title: Number of days for Minimum 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/sarva.saws.10000280
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 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 SON 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/sarva.saws.10000231
title: Seasonal total rainfall (mm per 3-month season) change from the median 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 themedian 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: 10.48331/scielo.viuqqs/evpksg
title: 5-Julio Zetter Patino.pptx

description: :unav
DOI: 10.48331/scielo.viuqqs
title: Presentaciones de las Coordinaciones Nacionales - Colección SciELO-México - Balance, proyectos y perspectivas

description: Presentación de Julio Zetter Patiño en el panel Presentaciones de las Coordinaciones Nacionales de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es