South Africa’s Future Climate: Trends and Projections

Climate predictions using recent and high-resolution climate models are becoming important for effective decision-making and for designing appropriate climate change adaptation and mitigation strategies. Due to highly variable climate and data scarcity of the upper Blue Nile Basin, previous studies did not detect specific unified trends. This study discusses, the past and future climate projections under CMIP6-SSPs scenarios for the basin. For the models’ validation and selection, reanalysis data were used after comparing with area-averaged ground observational data. Quantile mapping systematic bias correction and Mann–Kendall trend test were applied to evaluate the trends of selected CMIP6 models during the 21st century. Results revealed that, ERA5 for temperature and GPCC for precipitation have best agreement with the basin observational data, MRI-ESM2-0 for temperature and BCC-CSM-2MR for precipitation were selected based on their highest performance. The MRI-ESM2-0 mean annual maximum temperature for the near (long)-term period shows an increase of 1.1 (1.5) °C, 1.3 (2.2) °C, 1.2 (2.8) °C, and 1.5 (3.8) °C under the four SSPs. On the other hand, the BCC-CSM-2MR precipitation projections show slightly (statistically insignificant) increasing trend for the near (long)-term periods by 5.9 (6.1)%, 12.8 (13.7)%, 9.5 (9.1)%, and 17.1(17.7)% under four SSPs scenarios.

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Climate trends at Macquarie Island and expectations of future climate change in the sub-Antarctic

Papers and proceedings of the Royal Society of Tasmania ◽

10.26749/rstpp.143.1.1 ◽

2009 ◽

Vol 143 (1) ◽

pp. 1-8 ◽

Cited By ~ 11

Author(s):

N Adams

Keyword(s):

Climate Change ◽

Future Climate ◽

Future Climate Change ◽

Climate Trends ◽

Macquarie Island

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Assessing Climate Change Impact on Asphalt Binder Grade Selection and its Implications

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211013026 ◽

2021 ◽

pp. 036119812110130

Author(s):

Surya T. Swarna ◽

Kamal Hossain ◽

Harshdutta Pandya ◽

Yusuf A. Mehta

Keyword(s):

Climate Change ◽

Asphalt Binder ◽

Climate Impacts ◽

Future Climate ◽

Pavement Performance ◽

Global Changes ◽

Second Phase ◽

Climate Data ◽

Climate Trends ◽

Change Models

Anthropogenic climate change is having and will continue to have unpredictable effects on Canadian weather. Trends in average annual temperatures have been rapidly increasing over the last 50 years. The severe climatic variations in Canada are in line with global changes in climate occurring as a result of increased greenhouse gas concentrations in the atmosphere. Under the current CO2 emission scenarios, scientists predict the climate trends to further intensify in the near future. It is well known that asphalt binder is highly sensitive to climate factors. For this reason, reviewing asphalt binder grade is a vital step, and can help decelerate pavement deterioration. The objective of this study was to assess the change in asphalt binder grade for the future climate and to determine the influence of change in binder grade on the performance of pavements in Canada. To achieve this, the analysis was carried out in five phases. In the first phase, statistically downscaled climate change models were gathered from the Pacific Climate Impacts Consortium database. In the second phase, the temperature and precipitation data were extracted for the selected locations in southern Canada. In the third phase, the asphalt binder grade was determined for future climate data. In the fourth phase, the pavement materials, traffic, and structural data were collected from the Long-Term Pavement Performance database. Lastly, the pavement performance with the base binder and the upgraded binder were assessed using AASHTOware Mechanistic–Empirical Pavement Design. The results reemphasize the necessity of upgrading the asphalt binder grade in various provinces of Canada.

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Sensitivity of juvenile salmonid growth to future climate trends

River Research and Applications ◽

10.1002/rra.1390 ◽

2010 ◽

Vol 27 (5) ◽

pp. 663-669 ◽

Cited By ~ 21

Author(s):

W. N. Beer ◽

J. J. Anderson

Keyword(s):

Future Climate ◽

Climate Trends

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On the contribution of internal climate variability to European future climate trends

Tellus A Dynamic Meteorology and Oceanography ◽

10.1080/16000870.2020.1788901 ◽

2020 ◽

Vol 72 (1) ◽

pp. 1-17

Author(s):

T. Koenigk ◽

L. Bärring ◽

D. Matei ◽

G. Nikulin ◽

G. Strandberg ◽

...

Keyword(s):

Climate Variability ◽

Future Climate ◽

Climate Trends ◽

Internal Climate Variability

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Quantifying the Role of Internal Climate Variability in Future Climate Trends

Journal of Climate ◽

10.1175/jcli-d-14-00830.1 ◽

2015 ◽

Vol 28 (16) ◽

pp. 6443-6456 ◽

Cited By ~ 79

Author(s):

David W. J. Thompson ◽

Elizabeth A. Barnes ◽

Clara Deser ◽

William E. Foust ◽

Adam S. Phillips

Keyword(s):

Climate Change ◽

Climate Variability ◽

Internal Variability ◽

Ensemble Member ◽

Future Climate ◽

Analytic Model ◽

Climate Trends ◽

Internal Climate Variability ◽

Large Ensembles

Abstract Internal variability in the climate system gives rise to large uncertainty in projections of future climate. The uncertainty in future climate due to internal climate variability can be estimated from large ensembles of climate change simulations in which the experiment setup is the same from one ensemble member to the next but for small perturbations in the initial atmospheric state. However, large ensembles are invariably computationally expensive and susceptible to model bias. Here the authors outline an alternative approach for assessing the role of internal variability in future climate based on a simple analytic model and the statistics of the unforced climate variability. The analytic model is derived from the standard error of the regression and assumes that the statistics of the internal variability are roughly Gaussian and stationary in time. When applied to the statistics of an unforced control simulation, the analytic model provides a remarkably robust estimate of the uncertainty in future climate indicated by a large ensemble of climate change simulations. To the extent that observations can be used to estimate the amplitude of internal climate variability, it is argued that the uncertainty in future climate trends due to internal variability can be robustly estimated from the statistics of the observed climate.

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