cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15493/sarva.beeh.10000149
title: Moisture Growing Season Mean Start Of Season Based On Fao (1978) Method

description: In order to ascertain when, on average, there is enough water in the soil for sustained plant growth to take place, not only does a certain amount of precipitation have to have occurred, but simultaneously the precipitation must exceed some lower threshold of plant evaporative losses for sustained growth to continue. An average moisture growing season over South Africa was determined by adapting a simple water budgeting approach of the FAO (1978), developed originally for agro-ecological zone mapping of Africa. Using this adapted method, the start of the moisture growing season was first determined followed by the determination of the end of the moisture growing season. From these, the duration of the moisture growing season could then be calculated.

The adapted FAO approach to determining moisture growing season is assumed that during the period when P ≥ 0.3Er sustained plant growth can take place, where P is median monthly precipitation (mm) and means monthly Eapan is taken as the reference potential evaporation, Er. Average daily magnitudes of P and Eapan were derived by interpolative techniques from their respective 1` x 1` grid values, and the above assumption of P ≥ 0.3Er was tested for. Note that the use of long-term climate averages yield only a simple and very smoothed general moisture growing season, in not accounting for any differences in soils nor for the probability of individual daily rainfall events occurring; however, the averaging does eliminate possible `false starts` growth early in the season when isolated rains may fall.
DOI: 10.15493/sarva.beeh.10000103
title: Climatically Optimum Growth Areas Litchis Criterion 3: Means Of Tmax 25 - 33C, Sep - Oct

description: Litchis, Litchi chinensis, are indigenous to subtropical southern China and were first imported to South Africa from Mauritius in the 1870s (ARC, 2005). Of the 7 000 tons of litchis produced annually in South Africa, with a gross value exceeding R25 million, about 60 percent  come from Mpumalanga, 38 percent  from Limpopo and 2 percent from KwaZulu-Natal (Statistics SA, 2002; NDA, 2005).
DOI: 10.15493/sarva.energy.10000026
title: SOY-NOT: Soy Oil - Biodiesel Transesterification (MW)

description: Biomass feasibility assesment dataset extracted from the BioEnergy Atlas for South Africa.

* Assessments are made of impacts of economy of scale, logistics, and placement on techno-economic feasibility of feedstock and processing combinations, leading to identification of a portfolio of feasible project options. These options are illustrative of areas where bioenergy is likely to be a competitive, sustainable alternative.

* Original dataset: https://dx.doi.org/10.15493/BEA.DATA.10000050

* BioEnergy Atlas Synopsis Report: https://dx.doi.org/10.15493/SAEON.BEA.DOCS.10000001
DOI: 10.15493/sarva.energy.10000007
title: Mean Power Density (W/sq.m) - Northern 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/nrf.saiab.20232505
title: Bathymetry data collected from uMdloti Steep, July 2021

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 multi-disciplinary study will begin at the start of implementation of two new MPAs (uThukela MPA and Protea Banks MPA, both proclaimed in 2019), and will generate the relevant data needed to underpin an evidence-based approach to adaptive management of the MPAs, within a “SMART” framework. This framework defines specific objectives for the different MPA zones; develops measurable indicators of success for each zone; sets achievable goals given the limited resources available for planning and management; ensures that the research findings are relevant (to both biodiversity and human stakeholders). This is a rare time-sensitive opportunity to conduct baseline surveys of the geology, benthic biodiversity (sessile and mobile species), reef-associated ichthyoplankton and mero-zooplankton and fish communities of mesophotic (40-150m) soft-coral and sponge-dominated reefs and submarine habitats located in three different management zones at the initiation of management of two brand new MPAs, against which long-term monitoring data can be compared to assess the effectiveness of the MPAs in achieving their objectives.  The balanced sampling design is such that it will also initiate a “natural experiment” that over time will investigate the effect of no-take zones on fish diversity and abundance, benthic community structure, and trophic complexity. This will also enable the determination of the value of the MPA for fisheries sustainability support and resilience to disturbances caused by extrinsic factors such as pollution or climate change. Additionally, this study will assess whether the zonation plan provides for representation of all reef and canyon types within each zone or if there is unbalanced coverage for certain reefs and in certain zones. This is important to assess at the initiation of the MPA, especially to ensure that the interpretation of monitoring results in future, which compare ecosystems and fish on reefs and canyons in the mesophotic zone, are not flawed by natural differences from the outset due to the selection of zone boundaries. This dataset consists of XYZ points below the sea surface and relative to the mean sea level. This data was collected under the ACEP SMART ZONES MPA project (2021 – 2023) using the ACEP Geophysics and Mapping Platform.
description: See metadata file for additional information.
DOI: 10.15493/dea.carbon.10000013
title: Lowveld SAR Woody Fractional Cover (Percent)

description: Woody fraction cover: The woody cover fraction is the fraction of area (0 to 1) projected on a horizontal plane occupied by woody plants. The product was developed through the integration of 2010 ALOS PALSAR-1 synthetic aperture radar images and LiDAR tracks. The LiDAR tracks were processed to derive a canopy height model for woody vegetation above 1 m at 1m pixel size, and to generate a detailed LiDAR woody cover product at 25m pixel size. The dual-polarized (HV, HH) SAR bands were modelled using the LiDAR woody cover as reference data for calibration and validation of the final SAR woody fraction cover map.
 
 Units: Percent Woody fraction cover
DOI: 10.15493/sarva.csag.10000443
title: Rainfall days per month (> 10mm) 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.10000223
title: Seasonal total rainfall (mm per 3-month season) change from the 90% percentile projected for 2066-2095, relative to present (1976 - 2005), for MAM season under the RCP 8.5 pathway

description: 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/sarva.csag.10000274
title: Maximum 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: 10.15493/sarva.csag.10000022
title: Number of days for Minimum 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/sarva.csag.10000146
title: Median monthly precipitation (mm) 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.beeh.10000031
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.saws.10000262
title: Root Mean Square Difference in percentage (%) between the nine ensemble member change anomalies of the seasonal percentage rainfall for the median for 2036 - 2065 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 2036 - 2065 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.saws.10000220
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal total rainfall for the median for 2066-2095 relative to 1976-2005, for the DJF season, under the RCP 8.5 pathway

description: Root Mean Square Difference for seasonal (DJF) 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: 10.15493/sarva.saws.10000098
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 DJF season, under the RCP 4.5 pathway

description: Root Mean Square Difference for seasonal (DJF) rainfall (mm per month) 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 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/bea.data.10000060
title: Infrastructure Assessments

description: SAEON calculated a series of pressure maps to relate population, economic activity and biomass potential to the distribution of current and planned infrastructure. The infrastructure that was considered included: * Operational and decommissioned power stations; * Planned new energy infrastructure, based in NERSA permits; * Eskom planned and current transmission, distribution, and substation infrastructure; * Agriculture infrastructure - silos; * Sawmills and sugar mills; * Waste water treatment works and solid waste disposal sites. In each case, an assessment was made on the basis of four categories (below or over median): 1. Close to infrastructure, and high density of population, economic activity, or biomass potential (possibly problematic); 2. Not close to infrastructure, and high density of population, economic activity, or biomass potential (problematic); 3. Close to infrastructure, and low density of population, economic activity, or biomass potential (not problematic); 4. Not close to infrastructure, and low density of population, economic activity, or biomass potential (not problematic)
DOI: 10.15493/saeon.egagasini.10000105
title: Western Indian Ocean Energy Sinks (WOES) 0.25: a CROCO numerical ocean model hindcast at 1/12 degree monthly climatologies for the south western Indian Ocean from 1993-2014 nested in a 1/4 degree WOES run.

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/saeon.fynbos.10000007
title: Bosboukloof gauging weir hourly stage and estimated flow, 08/2011 - 09/2019

description: Stream water stage measured at a V-notch weir in the Bosboukoof stream in the Jonkershoek Valley. Water levels at the weir measured and logged half hourly by an OTT Orpheus Mini (Hach, Germany) vented pressure transducer. Hourly averages produced from half hourly readings. Streamflow estimated from stage using attached rating curve. (Collection continuing, contact SAEON for updated datasets)
DOI: 10.15493/saeon.tierberg.10000021
title: Nest mounds of the granivorous harvestor ant Messor capensis, Tierberg, 1991 -2005

description: Data on the size and dispersion of nest mounds of the granivorous harvester ant Messor capensis, including nearest neigbour distances, nearest heuweltjies, and the number, size and seed production of plants associated with the nest mounds. Although high in most plant nutrients, soils in the Karoo are generally poor in nitrogen and water infiltrability due to the low organic matter content. The actions of any animals in this region that concentrate organic matter in patches, or contribute to the movement of organic matter underground (such as termites or ants) must influence the local distribution of moisture and plant nutrients in the soil. In the southern Karoo, harvester ants Messor capensis add seed husks and soil to their nest-mounds in layers. Each layer probably represents a brief burst of underground activity following rain, when soil is placed on the mound. This is followed by a longer period of dumping of seed husks and plant matter on the mound. Although some of the plant matter is removed by wind, enough remains to increase the organic content of the soils on the edges of harvester ant nest-mounds. It is hypothesised that soils of Messor capensis nest-mounds in the southern Karoo contain more moisture, have a higher organic matter content and an elevated nutrient status compared to surrounding areas.

Note: Any publications, thesis, reports etc stemming from this data must be sent to SAEON Databank for records to be kept with the data