scholarly journals Analysis of Climate Change and Extreme Climatic Events in the Lake Victoria Region of Tanzania

2020 ◽  
Vol 2 ◽  
Author(s):  
Philbert Modest Luhunga ◽  
Alexander Elias Songoro
Keyword(s):  
Climate Change ◽  
Lake Victoria ◽  
Regional Climate ◽  
Future Climate ◽  
Emission Scenarios ◽  
Climate Condition ◽  
Lake Victoria Region ◽  
Rcp 8.5 ◽  
Maximum Temperatures ◽  
Future Climate Condition

The understanding of climate change impacts and the associated climate extreme events at regional and local scales is of critical importance for planning and development of feasible adaptation strategies. In this paper, we present an analysis of climate change and extreme climate events in the Lake Victoria region of Tanzania, focusing on the Kagera and Geita regions. We use daily simulated climate variables (rainfall and minimum and maximum temperatures) from the Coordinated Regional Climate Downscaling Experiment Program Regional Climate Models (CORDEX_RCMs) for the analysis. Extreme climate event, rainfall, and minimum and maximum temperatures time series during historical (1971–2000) climate condition are compared to future climate projection (2011–2100) under two Representative Concentration Pathway (RCP): RCP 4.5 and RCP 8.5 emission scenarios. The existence, magnitude, and statistical significance of potential trends in climate data time series are estimated using the Mann–Kendall (MK) non-parametric test and Theil-SEN slope estimator methods. Results show that during historical (1971–2000) climate, the Lake Victoria region of Tanzania experienced a statistically significant increasing trend in temperature. The annual minimum and maximum temperatures in the Kagera and Geita regions have increased by 0.54–0.69°C, and 0.51–0.69°C, respectively. The numbers of warm days (TX90p) and warm nights (TN90p) during the historical climate have increased, while the numbers of cold days (TX10p) and cold nights (TN10p) have decreased significantly. However, in future climate condition (2011–2100) under both RCP 4.5 and RCP 8.5 emission scenarios, the Lake Victoria region is likely to experience increased temperatures and rainfall. The frequency of cold events (cold days and cold nights) is likely to decrease, while the frequency of warm events (warm days and warm nights) is likely to increase significantly. The number of consecutive wet days, the intensity of very wet days, and the number of extreme wet days are likely to increase. These results indicate that in future climate condition, socioeconomic livelihoods of people in the Kagera and Geita regions are likely to experience significant challenges from climate-related stresses. It is, therefore, recommended that appropriate planning and effective adaptation policies are in place for disaster risk prevention.

scholarly journals Evaluating the climate change effects on temperature, precipitation and evapotranspiration in eastern Iran using CMPI5

2021 ◽  
Author(s):  
Guangli Fan ◽  
Amjad Sarabandi ◽  
Mostafa Yaghoobzadeh
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Maximum Temperature ◽  
Emission Scenarios ◽  
Future Period ◽  
Climate Change Effects ◽  
Eastern Iran ◽  
Large Fluctuations ◽  
Rcp 8.5 ◽  
Maximum Temperatures

Abstract In this study, the trend of climate changes during a future period from 2020 to 2039 has been evaluated using the data of the Fifth Climate Change Report under two emission scenarios RCP 4.5 and RCP 8.5 for Neishabour plain, Iran. Eleven models such as CESM, EC EARTH, HADGEM, MPI, NORESM, CANESM, CSIROM, GFDLCM2, GISS E2, IPSL and MIROC ESM have been used to evaluate changes in minimum and maximum temperatures, precipitation, and evapotranspiration. The results showed that GFDLCM2, MPI and IPSL models were more accurate in terms of precipitation and GISS E2 and GFDLCM2 models were the suitable option for predicting the maximum and minimum temperatures and evapotranspiration. Considering the evaluated parameters, minimum temperature, maximum temperature and evapotranspiration had approximately the constant trends and were accompanied by a slight increase and decrease for the next two decades, but for the precipitation, large fluctuations were predicted for the next period. Moreover, in the study years for the four parameters in all simulated models, the RCP 8.5 scenario has estimated a higher amount than the RCP 4.5 scenario.

scholarly journals Modeling Current and Future Climate Change in the UAE using Various GCMs in MarksimGCMR

2019 ◽  
Vol 13 (1) ◽  
pp. 56-64
Author(s):  
Latifa Saeed Al Blooshi ◽  
Sofyan Alyan ◽  
Ngaina Joshua Joshua ◽  
Taoufik Saleh Ksiksi
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Future Climate Change ◽  
Emission Scenarios ◽  
Gas Concentration ◽  
Climate Research ◽  
Current Century ◽  
Huge Impact ◽  
Rcp 8.5 ◽  
Maximum Temperatures

Introduction: Changes in climate have impacts on natural and human systems on all continents and across the oceans. Most countries, including the UAE, are expected to experience a huge impact of climate change, due to the undergoing rapid growth and huge urban developments. Materials & Methods: Representative Concentration Pathways, or RCPs, represent the latest generation of scenarios that are used as potential inputs into climate models to show imposed greenhouse-gas concentration pathways during the 21st century. Four emission scenarios have been used for climate research; namely RCP 2.6, RCP 4.5 and RCP 6 and RCP 8.5. RCP 4.5 and RCP 8.5 are used. The aims of this study are to assess different RCPs and their appropriateness to predict temperatures and rainfall and to study the effect of climate change on three different cities in the UAE. Results & Conclusion: The results show a strong correlation between the present Tmax vs Tmax 2020, Tmax 2040, Tmax 2060, Tmax 2080 and Tmax 2095 for both RCP4.5 and RCP8.5. This means that maximum temperatures are going to increase in the coming years based on the predictions according to the different scenarios using MarksimGCMR. Precipitation projections shows greater variation than temperature. In this paper the amount of increase in temperatures and precipitation change is shown for the end of the current century.

scholarly journals Development of Statistically Downscaled Regional Climate Model based on Representative Concentration Pathways for Ipoh, Subang and KLIA Sepang in Peninsular Malaysia

2021 ◽  
Vol 945 (1) ◽  
pp. 012022
Author(s):  
Chin Kah Seng ◽  
Tan Kok Weng ◽  
Akihiko Nakayama
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Simulated Data ◽  
Peninsular Malaysia ◽  
Future Climate ◽  
Monthly Average ◽  
Maximum Temperatures

Abstract Climate change is one of the challenging global issues that our world is facing and it is intensely debated on the international agenda. It is a fact that climate change has brought about many disastrous events on a global scale which affect our livelihoods. Climate models are commonly used by researchers to study the magnitude of the changing climate and to simulate future climate projections. Most climate models are developed based on various interactions among the Earth’s climate components such as the land surface, oceans, atmosphere and sea-ice. In this study, the second-generation Canadian Earth System Model (CanESM2) was statistically downscaled to develop a regional climate model (RCM) based on three representative concentration pathways (RCPs): RCP2.6, RCP4.5 and RCP8.5. The RCM will be used to simulate the average minimum and maximum temperatures and average precipitation for Ipoh, Subang and KLIA Sepang in Peninsular Malaysia for the years 2006 to 2100. The simulated data were bias corrected using the historical observation data of monthly average minimum and maximum temperatures and monthly average rainfall retrieved from the Malaysian Meteorological Department (MMD). The different trends of the simulated data for all the three locations based on the RCP2.6, RCP4.5 and RCP8.5 were evaluated for future climate projection.

scholarly journals Coupled application of R and WetSpa models for assessment of climate change impact on streamflow of Werie Catchment, Tigray, Ethiopia

2020 ◽  
Author(s):  
Selam Kidanemariam ◽  
Haddush Goitom ◽  
Yigzaw Desta
Keyword(s):  
Climate Change ◽  
Baseline Period ◽  
Future Climate ◽  
Calibration Data ◽  
Climate Variables ◽  
Emission Scenarios ◽  
Climate Data ◽  
Validation Data ◽  
Data Set ◽  
Rcp 8.5

Abstract This research assesses the streamflow response of Werie River to climate change. Baseline (1980–2009) climate data of precipitation, maximum and minimum temperature were analyzed using delta based statistical downscaling approach in R software packages to predict future 90 years (2010–2099) periods under two emission scenarios of Representative Concentration Pathways (RCP) 4.5 and RCP 8.5, indicating medium and extremely high emission scenarios respectively. Generated future climate variables indicate Werie will experience a significant increase in precipitation, and maximum and minimum air temperature for both RCPs. Further, Water and Energy Transfer between Soil, Plants, and Atmosphere (WetSpa) was applied to assess the water balance of Werie River. The WetSpa model reproduced the streamflow well with performance statistics values of R2 = 0.84 and 0.85, Nash–Sutcliffe efficiency = 0.72 and 0.72, and model bias = –0.14 and –0.15 for the calibration data set of 1999–2010 and validation data of 2011–2014 respectively. Finally, by taking the downscaled future climate variables as input, WetSpa future prediction shows that there will an increase in the Werie catchment mean annual streamflow up to 29.6% for RCP 4.5 and 35.6% for RCP 8.5 compared to the baseline period.

scholarly journals Impacts of climate change on the seasonality of low flows in 134 catchments in the River Rhine basin using an ensemble of bias-corrected regional climate simulations

2013 ◽  
Vol 17 (10) ◽  
pp. 4241-4257 ◽  
Author(s):  
M. C. Demirel ◽  
M. J. Booij ◽  
A. Y. Hoekstra
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Future Climate ◽  
Low Flow ◽  
River Rhine ◽  
Emission Scenarios ◽  
Low Flows ◽  
Current Climate ◽  
The Future

Abstract. The impacts of climate change on the seasonality of low flows were analysed for 134 sub-catchments covering the River Rhine basin upstream of the Dutch-German border. Three seasonality indices for low flows were estimated, namely the seasonality ratio (SR), weighted mean occurrence day (WMOD) and weighted persistence (WP). These indices are related to the discharge regime, timing and variability in timing of low flow events respectively. The three indices were estimated from: (1) observed low flows; (2) simulated low flows by the semi-distributed HBV model using observed climate as input; (3) simulated low flows using simulated inputs from seven combinations of General Circulation Models (GCMs) and Regional Climate Models (RCMs) for the current climate (1964–2007); (4) simulated low flows using simulated inputs from seven combinations of GCMs and RCMs for the future climate (2063–2098) including three different greenhouse gas emission scenarios. These four cases were compared to assess the effects of the hydrological model, forcing by different climate models and different emission scenarios on the three indices. Significant differences were found between cases 1 and 2. For instance, the HBV model is prone to overestimate SR and to underestimate WP and simulates very late WMODs compared to the estimated WMODs using observed discharges. Comparing the results of cases 2 and 3, the smallest difference was found for the SR index, whereas large differences were found for the WMOD and WP indices for the current climate. Finally, comparing the results of cases 3 and 4, we found that SR decreases substantially by 2063–2098 in all seven sub-basins of the River Rhine. The lower values of SR for the future climate indicate a shift from winter low flows (SR > 1) to summer low flows (SR < 1) in the two Alpine sub-basins. The WMODs of low flows tend to be earlier than for the current climate in all sub-basins except for the Middle Rhine and Lower Rhine sub-basins. The WP values are slightly larger, showing that the predictability of low flow events increases as the variability in timing decreases for the future climate. From comparison of the error sources evaluated in this study, it is obvious that different RCMs/GCMs have a larger influence on the timing of low flows than different emission scenarios. Finally, this study complements recent analyses of an international project (Rhineblick) by analysing the seasonality aspects of low flows and extends the scope further to understand the effects of hydrological model errors and climate change on three important low flow seasonality properties: regime, timing and persistence.

scholarly journals Determining future aflatoxin contamination risk scenarios for corn in Southern Georgia, USA using spatio-temporal modelling and future climate simulations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ruth Kerry ◽  
Ben Ingram ◽  
Esther Garcia-Cela ◽  
Naresh Magan ◽  
Brenda V. Ortiz ◽  
...  
Keyword(s):  
Strong Association ◽  
Growth Period ◽  
Aflatoxin Contamination ◽  
Adaptation Strategies ◽  
Future Climate ◽  
Climate Data ◽  
Emissions Scenarios ◽  
Rcp 8.5 ◽  
Maximum Temperatures ◽  
Southern Georgia

AbstractAflatoxins (AFs) are produced by fungi in crops and can cause liver cancer. Permitted levels are legislated and batches of grain are rejected based on average concentrations. Corn grown in Southern Georgia (GA), USA, which experiences drought during the mid-silk growth period in June, is particularly susceptible to infection by Aspergillus section Flavi species which produce AFs. Previous studies showed strong association between AFs and June weather. Risk factors were developed: June maximum temperatures > 33 °C and June rainfall < 50 mm, the 30-year normals for the region. Future climate data were estimated for each year (2000–2100) and county in southern GA using the RCP 4.5 and RCP 8.5 emissions scenarios. The number of counties with June maximum temperatures > 33 °C and rainfall < 50 mm increased and then plateaued for both emissions scenarios. The percentage of years thresholds were exceeded was greater for RCP 8.5 than RCP 4.5. The spatial distribution of high-risk counties changed over time. Results suggest corn growth distribution should be changed or adaptation strategies employed like planting resistant varieties, irrigating and planting earlier. There were significantly more counties exceeding thresholds in 2010–2040 compared to 2000–2030 suggesting that adaptation strategies should be employed as soon as possible.

Realised added value in dynamical downscaling of Australian climate change

2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Future Climate ◽  
Added Value ◽  
Climate Projections ◽  
Eastern Australia ◽  
Australian Alps ◽  
Future Climate Projections

&lt;p&gt;Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, &amp;#8216;realised added value&amp;#8217;, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.&lt;/p&gt;

scholarly journals Regionalization of Climate Change Simulations over the Eastern Mediterranean

2009 ◽  
Vol 22 (8) ◽  
pp. 1944-1961 ◽  
Author(s):  
Bariş Önol ◽  
Fredrick H. M. Semazzi
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Temperature Increase ◽  
Climate Model ◽  
Eastern Mediterranean ◽  
Regional Climate ◽  
Future Climate ◽  
Climate Change Projections ◽  
Model Simulations ◽  
The Future

Abstract In this study, the potential role of global warming in modulating the future climate over the eastern Mediterranean (EM) region has been investigated. The primary vehicle of this investigation is the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 (ICTP-RegCM3), which was used to downscale the present and future climate scenario simulations generated by the NASA’s finite-volume GCM (fvGCM). The present-day (1961–90; RF) simulations and the future climate change projections (2071–2100; A2) are based on the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) emissions. During the Northern Hemispheric winter season, the general increase in precipitation over the northern sector of the EM region is present both in the fvGCM and RegCM3 model simulations. The regional model simulations reveal a significant increase (10%–50%) in winter precipitation over the Carpathian Mountains and along the east coast of the Black Sea, over the Kackar Mountains, and over the Caucasus Mountains. The large decrease in precipitation over the southeastern Turkey region that recharges the Euphrates and Tigris River basins could become a major source of concern for the countries downstream of this region. The model results also indicate that the autumn rains, which are primarily confined over Turkey for the current climate, will expand into Syria and Iraq in the future, which is consistent with the corresponding changes in the circulation pattern. The climate change over EM tends to manifest itself in terms of the modulation of North Atlantic Oscillation. During summer, temperature increase is as large as 7°C over the Balkan countries while changes for the rest of the region are in the range of 3°–4°C. Overall the temperature increase in summer is much greater than the corresponding changes during winter. Presentation of the climate change projections in terms of individual country averages is highly advantageous for the practical interpretation of the results. The consistence of the country averages for the RF RegCM3 projections with the corresponding averaged station data is compelling evidence of the added value of regional climate model downscaling.

scholarly journals Regional Climate Model Emulator based on Deep Learning: Concept and First Evaluation of a Novel Hybrid Downscaling Approach

2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre
Keyword(s):  
Climate Change ◽  
Network Architecture ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Near Surface ◽  
The Way

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.

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