cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48331/scielo.htcpxl
title: Presentaciones de las Coordinaciones Nacionales - El portal SciELO España

description: Presentación de Cristina A. Fraga Medín en el panel Presentaciones de las Coordinaciones Nacionales de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es
DOI: 10.15493/sarva.saws.10000084
title: Root Mean Square Difference between the nine ensemble member change anomalies of the seasonal total rainfall for the 10% percentile for 2036 - 2065 relative to 1976-2005, for the MAM season, under the RCP 4.5 pathway

description: Root Mean Square Difference for seasonal (MAM) rainfall (mm per month) 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 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.beeh.10000434
title: Mean Maize Yield (T/Ha/Season) Short Season Hybrid Plant Date: 15 December

description: This data set contains Maize, Zea mays L. in South Africa and is the country`s most important field and grain crop. Objectives of the study was to simulate maize yields, and their inter-annual, at a spatial resolution of Quaternary Catchments for 12 different combinations of three plant dates, viz. 15 October, 15 November and 15 December. This was done to evaluate which hybrid lengths and plant dates give the highest yields irrespective of plant dates and hybrid lengths respectively and also which hybrid lengths and plant dates give the lowest coefficients of variation (%) irrespective of plant dates and hybrid lengths respectively.
DOI: 10.15493/sarva.csag.10000396
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.saws.10000209
title: Seasonal total rainfall (mm per 3-month season) change from the 10% percentile projected for 2036-2065, relative to present (1976 - 2005), for JJA season under the RCP 8.5 pathway

description: Seasonal (JJA) rainfall (mm per month) change from the 10% percentile projected for 2036-2065, relative to present (1976 - 2005), under the RCP 8.5 pathway for the southern African region. To generate the image, nine coarse General Circulation Models (GCM) are downscaled to a finer spatial resolution (0.44°x 0.44°) using the Rossby Centre regional model (RCA4) forcing its lateral boundaries. The model simulated daily rainfall averages, which are used to generate projections of seasonal change. The projections are generated using the high (RCP8.5) pathway which associates CO2 concentrations of approximately 950ppm by the year 2100. The associated RMSD it calculated and shows the uncertainty range of the projected model simulated residual values, and gives a relative perspective of spatial areas associated with higher and lower projection uncertainties.
DOI: 10.15493/saeon.egagasini.10000095
title: Western Indian Ocean Energy Sinks (WOES) 0.25: a CROCO numerical ocean model hindcast at 1/12 degree daily 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.26b1720
title: 26B event rainfall October 2017 - August 2020

description: Event rainfall data collected by Texas Electronics tipping bucket gauge installed at 1.2m above ground at 416 masl in the Swartboschkloof 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.10000128
title: Consecutive Dry Days 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.10000379
title: Median monthly precipitation (mm) 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.10000066
title: Monthly Rainfall and its Inter-Annual Variability (September)

description: Monthly rainfall totals are necessary to many water resources as well as agricultural problems and decisions for which MAPs, or even wet/dry season precipitation totals be they high or low, are of relatively little consequence, because an intra-year distribution of rainfall is required (Schulze, 1997). Monthly rainfall values then serve as an important tool in describing such an intra-year distribution. It should, however, be borne in mind that the use of the calendar month is but a time step of convenience for describing temporal patterns of rainfall, in that it breaks up annual precipitation into components of time long enough to smooth out many of the irregularities of daily rainfalls (Schulze, 1997). Nevertheless, large differences in rainfall can exist from one month to the next. Some of these differences result from major rainfall generating mechanisms changing from one month to the next.

How the maps of median monthly rainfall were derived since time series of monthly rainfall are more variable than those of annual rainfall, the raster surfaces of median monthly rainfall at 1 arc minute spatial resolution (i.e. at 1` x 1` latitude/longitude spacing; 1.7 x 1.7 km; with 429 700 raster points making up South Africa) were calculated by expressing the median rainfall value of a given month at each qualifying rainfall station as a ratio of the MAP surface which was generated by Lynch (2004) using Geographically Weighted Regression. These ratios were then interpolated by Inverse Distance Weighting (IDW) onto the rectangular raster of 1 arc minute. This interpolated raster was then multiplied by the raster of MAP values to give 1` x 1` values of that month's median rainfall. The procedure was then repeated for each of the 12 months of the year (Lynch, 2004).
DOI: 10.15493/sarva.beeh.10000174
title: Oriental Fruit 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). 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). The oriental fruit moth infests all stone fruit and is found in various stages of its life cycle during the entire growing season, this Oriental fruit moth (OFM) larvae pupate in late winter to early spring, with up to five or more generations per season. Infested shoots and terminal leaves wilt and bend over, with this injury known as flagging, and leaves eventually dry up. Flagging stimulates lateral growth below the point of injury, providing wound sites for pathogens (Polk et al., undated). More critical even than flagging is fruit injury, occurring either early in the season or later after pit hardening to final swell, with gum and frass often exuding from the wound area.

Computation of life cycles per annum of codling moth and oriental fruit moth 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.10000420
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/saeon.fynbos.25b1517
title: 25B event rainfall February 2015 - October 2017

description: Event rainfall data collected by Davis Instruments 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 0.2 mm increments.
DOI: 10.15493/saeon.fynbos.32022022
title: Kalkoenkrans Farm rainfall data

description: Monthly rainfall data collected at Kalkoenkrans Farm, Steynsburg district, Eastern Cape. The data was collected using a Snowden 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/sarva.beeh.10000399
title: Banana Yield Estimation (Dryland Ratoon Crop)

description: Modern bananas originated in the southeast Asian and western Pacific regions, with earliest records of cultivation in India about 2 500 years ago (ARC, 2005). Bananas are stress sensitive plants which grow satisfactorily with a MAP of 1 200 mm, ideally well distributed throughout the year (Smith, 1998). Dry spells of more than 7 days are detrimental to yields. Preferring a relative humidity > 60 percent (especially during fruit setting), the mid-day RH should generally exceed 50 percent. The optimum mean monthly temperatures for bananas are 25 - 28 degree Celsius, with a range of 20 - 35 degree Celsius. Growth ceases below 12 degree Celsius and the July mean of daily minima should be at least 8 degree Celsius. Of the 1 200 ha under bananas, 64 percent are in Mpumalanga, 18 percent are in KwaZulu-Natal and a further 18 percent in Limpopo (Statistics SA, 2002). Highest average yields, around 26 t/ha/an, are attained in Mpumalanga, while those in KwaZulu-Natal and Limpopo are 20 t/ha/an, i.e. on the low side by international standards (Statistics SA, 2002).

Determination of banana yield estimates, based on Smith`s climatic criteria. Areas considered climatically unsuitable for banana production and thus eliminated from further analysis were those with MAP < 900 mm (for dryland production), MAT < 16 degree Celsius, July means of daily minimum temperatures < 8 degree Celsius, the averages of the 12 monthly means of daily maximum temperatures < 22 degree Celsius and of minimum temperatures < 10 degree Celsius, as well as areas where the mean of the 12 monthly values of daily minimum RH was < 50 percent.
DOI: 10.15493/sarva.csag.10000010
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.beeh.10000350
title: Standard Deviation (C) Of Daily Minimum Temperature January

description: Minimum (Night-Time) temperatures, there is abundant evidence for the climatic limitation of crop distributions to be described by minimum temperatures, from a perspective of crop survival (on Frost for tolerance levels of crops). Many subtropical crops may be killed at 5 degree Celsius already through chilling injury, even in the absence of frost (Chang, 1968). High minima increase respiration loss, thereby decreasing net photosynthesis.

Daily minimum temperature time series were derived from over 970 qualifying temperature stations` quality controlled daily records for the 50 year period 1950 - 1999. From these time series, 50 years of daily values of minimum temperatures were generated at each of 429 700 one arc minute (i.e. 1.7 km x 1.7 km) raster points covering South Africa, using regional and seasonal lapse rate and infilling/data extension techniques developed by Schulze and Maharaj (2004). Note that in the generation of daily minimum temperatures no account could be taken of cold air drainage into hollows or valleys, which can take place from surrounding higher-lying areas through radiative cooling during calm, stable clear night conditions. Reasons for this are provided in Schulze and Maharaj (2004). From these daily values, monthly means of daily minimum temperatures, as well as standard deviation of daily minimum temperatures for each month of the year, could be computed for purposes of mapping and production of statistics which are tabulated for Swaziland, Lesotho and for each of the nine provinces of the RSA. This approach to mapping minimum temperatures is thus fundamentally different to that used in the previous `South African Atlas of Agrohydrology and Climatology` (Schulze, 1997), in being much more physically based.
DOI: 10.15493/sarva.beeh.10000390
title: Vapour Pressure Deficit (kPa) May

description: Daily values of vapour pressure deficit (VPD) are, however, required far more frequently, particularly when modelling crop potential evaporation using the Penman- Monteith equation (Penman, 1948). In this section a method used to estimate VPD is outlined, the method is verified and then maps and statistics of VPD are presented.

The hypothesis in estimating daily values of VPD at any specified location in South Africa is that actual VP, actual vapour pressure, which is considered to be a conservative climate element, and which may be derived from the monthly regression equations be held constant at that location for a given month. The fluctuating day-to-day daily temperature values at that location are then used with the Tetens (1930) formula given above to calculate a daily saturated VP, saturated vapour pressure. From actual vapour pressure and saturated vapour pressure daily values of VPD (and RH, if desired) can then be computed. This approach is known as the Schulze-Chapman model.
DOI: 10.15493/sarva.saws.10000188
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 SON season, under the RCP 8.5 pathway

description: Root Mean Square Difference for seasonal (SON) 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: 10.48331/scielo.oqjba7/dpjszj
title: 1-Félix de Moya.pptx

description: :unav
DOI: 10.15493/saeon.fynbos.3a3691
title: 3A manual monthly rainfall January 1936 - September 1991

description: Monthly rainfall data collected by a Snowdon gauge with orifice at 1.2 meters above ground in the Tierkloof catchment in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.48331/scielo.oqjba7
title: Diálogos: El porqué de la métrica - Observar o esperar el impacto científico: las métricas de evaluación partir de DORA

description: Presentación de Félix de Moya Anegón en el panel Diálogos: El porqué de la métrica de la Semana SciELO 25 Años. Página del evento: https://25.scielo.org/es
DOI: 10.15493/saeon.fynbos.18b4591
title: 18B manual monthly rainfall February 1945 - September 1991

description: Monthly rainfall data collected by a Snowdon gauge fitted with a Nipher shield. Gauge orifice parallel to the slope, 1.2 meters above ground at Disavlei in the Jonkershoek valley, Western Cape, South Africa.
DOI: 10.15493/sarva.251120-11
title: 2018 Marine ecosystem threat status and protection level

description: This layer includes the threat status and protection level of the Marine Ecosystems 2018 assessed for the National Biodiversity Assessment 2018.
DOI: 10.15493/saeon.ndlovu.10000002
title: SAEON: OWNR & PHALA & SAWC Davis Vantage Pro2 Automated Weather Station - 30 minutes (AirTemp, Rain) 2010/05/27 to current

description: This is a data set collected by three (3) of SAEON Ndlovu Node automated weather stations (AWS), located at the following locations: SAEON/Scientific Services, Kruger National Park, Phalaborwa, Limpopo Province, South Africa (PHALA; -23.945075 latitude, 31.165242 longitude);  Olifants West Nature Reserve, Balule Nature Reserve, Limpopo Province, South Africa (OWNR; -24.227122 latitude, 30.86838 longitude); South African Wildlife College, Mpumalanga Province, South Africa (SAWC; -24.542253 latitude, 31.334914 longitude). The make and model of the stations is Davis Vantage Pro 2.
DOI: 10.15493/sarva.csag.10000168
title: Mean 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: 10.15493/saeon.egagasini.10000020
title: The ASCA July 2018 (SEAmester III) processed oblique Bongo data for unit 1911

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 was collected during the ASCA project have been obtained from various oceanographic instrumentation. This is the processed product of data collected using an oblique Bongo net for unit 1911.