Issue image

More articles from Issue 7, 2019

Douglas-fir seedling quality in biochar-amended peat substrates

Maximizing seed germination in five species of the genus Acacia (Fabaceae Mimosaceae)

Growth characteristics of one-year-old seedlings of three autochthonous oak species in suboptimal growing conditions

Physio-biochemical characterization of two acacia species (A. karroo Hayn and A. saligna Labill.) under saline conditions

TREND-RUN model application of surface temperature and its implications for South African forestry and reforestation using local weather services data

Citations

Crossref Logo

3

Crossref Logo

Jaco-Pierre van der Merwe, Elane van Heerden, Ilaria Germishuizen, Nanette Christie, James Kok, Thandekile Ncongwane, Katharine Spencer, Mandlakazi Melane, Shawn D. Mansfield, Yolandi Ernst

(2025)

High-resolution climate downscaling using terrain features and global circulation models: applications for species suitability in the management of plantation forestry

Journal of Forestry Research, 37(1)

10.1007/s11676-025-01938-4

Crossref Logo

René Tato Loua, Hassan Bencherif, Nelson Bègue, Nkanyiso Mbatha, Thierry Portafaix, Alain Hauchecorne, Venkataraman Sivakumar, Zoumana Bamba

(2020)

Surface Temperature Trend Estimation over 12 Sites in Guinea Using 57 Years of Ground-Based Data

Climate, 8(6)

10.3390/cli8060068

Crossref Logo

Melezwa Nkamisa, Simbarashe Ndhleve, Motebang D.V. Nakin, Asabonga Mngeni, Hlekani M. Kabiti

(2022)

Analysis of trends, recurrences, severity and frequency of droughts using standardised precipitation index: Case of OR Tambo District Municipality, Eastern Cape, South Africa

Jàmbá: Journal of Disaster Risk Studies, 14(1)

10.4102/jamba.v14i1.1147

TREND-RUN model application of surface temperature and its implications for South African forestry and reforestation using local weather services data

Raven Jimmy ,
Raven Jimmy
Pramanathan Govender ,
Pramanathan Govender
Hassan Bencherif ,
Hassan Bencherif
Matthew Moodley
Matthew Moodley

Published: 01.12.2018.

Volume 0, Issue 7 (2019)

pp. 50-72;

https://doi.org/10.21750/refor.7.05.67

Abstract

Temperature can directly and indirectly impact the livelihood of inhabitants of a country and the natural environment as a whole. The surface temperature trend approximations for South Africa (SA) were calculated using a linear-regression fitting model. The model was adapted at The University of Reunion Island and was referred to as the Trend-Run model. The geophysical signal of the model was split into a sum of oscillations, which was used to clarify most of its variability. The trend values were calculated from the residual terms as a linear function. The model used atmospheric oscillations, which included Annual (AO), Semi-Annual (SAO), Quasi-Biennial Oscillations (QBO), El Niño-Southern Oscillation (ENSO), the 11-years solar cycle-Sun Spot Number (SSN) and Indian Ocean Dipole (IOD). The South African Weather Service (SAWS) data were used for the study. Data sets over a 31-year period, from March 1980 to December 2011, were used to measure the validity of the Trend-Run model, to determine the contribution and effect of this particular oscillation, and the validity of the model. The Trend-Run model showed very high applicability to the surface temperatures in all provinces across the SA region under investigation. High coefficient of determination values between (0.70-0.91) were recorded for surface temperatures across all provinces in the country with minor variations. The AO, ENSO and SAO were the highest contributing forcings in the model, thereby showing their high relevance to the success of this model in the study area. The temperature increases are expected to negatively impact on the biomes of SA, including the forest biome. Selected tree species of Acacia, Eucalyptus and Pinus could be impacted negatively with rising temperatures, which would negatively impact on the forestry industry in SA. As expected, the model did obtain a high success rate that ranged from 70% to 91% in the areas under study, however, there was still room for improvement by the possible inclusion of additional atmospheric forcings to the model that maybe be applicable to the weather and forestry distribution in SA.

References

Bègue, N., Bencherif, H., Sivakumar, V., Kirgis, G., Mze, N., & Leclair de Bellevue, J. (2010). Temperature variability and trends in the UT-LS over a subtropical site: Reunion (20.8° S, 55.5° E). Atmospheric Chemistry and Physics, 10(17), 8563–8574. https://doi.org/10.5194/acp-10-8563-2010
BEHERA, S. K., & YAMAGATA, T. (2003). Influence of the Indian Ocean Dipole on the Southern Oscillation. Journal of the Meteorological Society of Japan. Ser. II, 81(1), 169–177. https://doi.org/10.2151/jmsj.81.169
Bencherif, H., Diab, R. D., Portafaix, T., Morel, B., Keckhut, P., & Moorgawa, A. (2006). Temperature climatology and trend estimates in the UTLS region as observed over a southern subtropical site, Durban, South Africa. Atmospheric Chemistry and Physics, 6(12), 5121–5128. https://doi.org/10.5194/acp-6-5121-2006
Bennett, B. M., & Kruger, F. J. (2013). Ecology, forestry and the debate over exotic trees in South Africa. Journal of Historical Geography, 42, 100–109. https://doi.org/10.1016/j.jhg.2013.06.004
The City of Mbombela Climate Change Response: Climate Change Response Internal Draft Strategy. (2017).

Citation

Copyright

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Most read articles