scholarly journals Multimodel GCM-RCM Ensemble-Based Projections of Temperature and Precipitation over West Africa for the Early 21st Century

2012 ◽  
Vol 2012 ◽  
pp. 1-19 ◽  
Author(s):  
I. Diallo ◽  
M. B. Sylla ◽  
F. Giorgi ◽  
A. T. Gaye ◽  
M. Camara
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Seasonal Temperature ◽  
Temperature And Precipitation

Reliable climate change scenarios are critical for West Africa, whose economy relies mostly on agriculture and, in this regard, multimodel ensembles are believed to provide the most robust climate change information. Toward this end, we analyze and intercompare the performance of a set of four regional climate models (RCMs) driven by two global climate models (GCMs) (for a total of 4 different GCM-RCM pairs) in simulating present day and future climate over West Africa. The results show that the individual RCM members as well as their ensemble employing the same driving fields exhibit different biases and show mixed results in terms of outperforming the GCM simulation of seasonal temperature and precipitation, indicating a substantial sensitivity of RCMs to regional and local processes. These biases are reduced and GCM simulations improved upon by averaging all four RCM simulations, suggesting that multi-model RCM ensembles based on different driving GCMs help to compensate systematic errors from both the nested and the driving models. This confirms the importance of the multi-model approach for improving robustness of climate change projections. Illustrative examples of such ensemble reveal that the western Sahel undergoes substantial drying in future climate projections mostly due to a decrease in peak monsoon rainfall.

scholarly journals Estimating the potential impact of climate change on sunflower yield in the Konya province of Turkey

2021 ◽  
pp. 1-13
Author(s):  
Hudaverdi Gurkan ◽  
Vakhtang Shelia ◽  
Nilgun Bayraktar ◽  
Y. Ersoy Yildirim ◽  
Nebi Yesilekin ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Model Performance ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Adaptation To Climate Change ◽  
Impact Of Climate Change ◽  
The Impact

Abstract The impact of climate change on agricultural productivity is difficult to assess. However, determining the possible effects of climate change is an absolute necessity for planning by decision-makers. The aim of the study was the evaluation of the CSM-CROPGRO-Sunflower model of DSSAT4.7 and the assessment of impact of climate change on sunflower yield under future climate projections. For this purpose, a 2-year sunflower field experiment was conducted under semi-arid conditions in the Konya province of Turkey. Rainfed and irrigated treatments were used for model analysis. For the assessment of impact of climate change, three global climate models and two representative concentration pathways, i.e. 4.5 and 8.5 were selected. The evaluation of the model showed that the model was able to simulate yield reasonably well, with normalized root mean square error of 1.3% for the irrigated treatment and 17.7% for the rainfed treatment, a d-index of 0.98 and a modelling efficiency of 0.93 for the overall model performance. For the climate change scenarios, the model predicted that yield will decrease in a range of 2.9–39.6% under rainfed conditions and will increase in a range of 7.4–38.5% under irrigated conditions. Results suggest that temperature increases due to climate change will cause a shortening of plant growth cycles. Projection results also confirmed that increasing temperatures due to climate change will cause an increase in sunflower water requirements in the future. Thus, the results reveal the necessity to apply adequate water management strategies for adaptation to climate change for sunflower production.

scholarly journals Changes in Köppen-Geiger climate types under a future climate for Australia: hydrological implications

2012 ◽  
Vol 16 (9) ◽  
pp. 3341-3349 ◽  
Author(s):  
R. S. Crosbie ◽  
D. W. Pollock ◽  
F. S. Mpelasoka ◽  
O. V. Barron ◽  
S. P. Charles ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Cold Climate ◽  
Future Climate ◽  
Temperate Climate ◽  
Climate Change Scenarios ◽  
Australian Continent

Abstract. The Köppen-Geiger climate classification has been used for over a century to delineate climate types across the globe. As it was developed to mimic the distribution of vegetation, it may provide a useful surrogate for making projections of the future distribution of vegetation, and hence resultant hydrological implications, under climate change scenarios. This paper developed projections of the Köppen-Geiger climate types covering the Australian continent for a 2030 and 2050 climate relative to a 1990 historical baseline climate using 17 Global Climate Models (GCMs) and five global warming scenarios. At the highest level of classification for a +2.4 °C future climate (the upper limit projected for 2050) relative to the historical baseline, it was projected that the area of the continent covered by – tropical climate types would increase from 8.8% to 9.1%; – arid climate types would increase from 76.5% to 81.7%; – temperate climate types would decrease from 14.7% to 9.2%; – cold climate types would decrease from 0.016% to 0.001%. Previous climate change impact studies on water resources in Australia have assumed a static vegetation distribution. If the change in projected climate types is used as a surrogate for a change in vegetation, then the major transition in climate from temperate to arid in parts of Australia under a drier future climate could cause indirect effects on water resources. A transition from annual cropping to perennial grassland would have a compounding effect on the projected reduction in recharge. In contrast, a transition from forest to grassland would have a mitigating effect on the projected reduction in runoff.

scholarly journals Changes in Köppen-Geiger climate types under a future climate for Australia: hydrological implications

2012 ◽  
Vol 9 (6) ◽  
pp. 7415-7440 ◽  
Author(s):  
R. S. Crosbie ◽  
D. W. Pollock ◽  
F. S. Mpelasoka ◽  
O. V. Barron ◽  
S. P. Charles ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Cold Climate ◽  
Future Climate ◽  
Temperate Climate ◽  
Climate Change Scenarios ◽  
Australian Continent

Abstract. The Köppen-Geiger climate classification has been used for over a century to delineate climate types across the globe. As it was developed to mimic the distribution of vegetation it may provide a useful surrogate for making projections of the future distribution of vegetation, and hence resultant hydrological implications, under climate change scenarios. This paper developed projections of the Köppen-Geiger climate types covering the Australian continent for a 2030 and 2050 climate relative to a 1990 historical baseline climate using 17 Global Climate Models (GCMs) and five global warming scenarios. At the highest level of classification for a +2.4 °C future climate (the upper limit projected for 2050) relative to the historical baseline, it was projected that the area of the continent covered by: – Tropical climate types would increase from 8.8% to 9.1% – Arid climate types would increase from 76.5% to 81.7% – Temperate climate types would decrease from 14.7% to 9.2% – Cold climate types would decrease from 0.016% to 0.001%. Previous climate change impact studies on water resources in Australia have assumed a static vegetation distribution. If the change in projected climate types is used as a surrogate for a change in vegetation, then the major transition in climate from Temperate to Arid in parts of Australia under a drier future climate could cause indirect effects on water resources. For a transition from annual cropping to perennial grassland this would have a compounding effect on the projected reduction in recharge. In contrast, a transition from forest to grassland would have a mitigating effect on the projected reduction in runoff.

scholarly journals Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Fabiani Denise Bender ◽  
Paulo Cesar Sentelhas
Keyword(s):  
Climate Change ◽  
Solar Radiation ◽  
Climate Models ◽  
Global Climate Models ◽  
Future Climate ◽  
Weather Data ◽  
Data Series ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Project Climate Change

The quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series (1980–2009) in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid- and end-of-century periods (2040–2069 and 2070–2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. The Bristow–Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.

scholarly journals Climate change projections of maximum temperature in the pre-monsoon season in Bangladesh using statistical downscaling of global climate models

2021 ◽  
Vol 18 ◽  
pp. 99-114
Author(s):  
M. Bazlur Rashid ◽  
Syed Shahadat Hossain ◽  
M. Abdul Mannan ◽  
Kajsa M. Parding ◽  
Hans Olav Hygen ◽  
...  
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Climate Models ◽  
Global Climate ◽  
Monsoon Season ◽  
Global Climate Models ◽  
Future Climate ◽  
Maximum Temperature ◽  
Climate Projections ◽  
Future Climate Projections

Abstract. The climate of Bangladesh is very likely to be influenced by global climate change. To quantify the influence on the climate of Bangladesh, Global Climate Models were downscaled statistically to produce future climate projections of maximum temperature during the pre-monsoon season (March–May) for the 21st century for Bangladesh. The future climate projections are generated based on three emission scenarios (RCP2.6, RCP4.5 and RCP8.5) provided by the fifth Coupled Model Intercomparison Project. The downscaling process is undertaken by relating the large-scale seasonal mean temperature, taken from the ERA5 reanalysis data set, to the leading principal components of the observed maximum temperature at stations under Bangladesh Meteorological Department in Bangladesh, and applying the relationship to the GCM ensemble. The in-situ temperature data has only recently been digitised, and this is the first time they have been used in statistical downscaling of local climate projections for Bangladesh. This analysis also provides an evaluation of the local data, and the local temperatures in Bangladesh show a close match with the ERA5 reanalysis. Compared to the reference period of 1981–2010, the projected maximum pre-monsoon temperature in Bangladesh indicate an increase by 0.7/0.7/0.7 ∘C in the near future (2021–2050) and 2.2/1.2/0.8 ∘C in the far future (2071–2100) assuming the RCP8.5/RCP4.5/RCP2.6 scenario, respectively.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

scholarly journals Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 139
Author(s):  
Manashi Paul ◽  
Sijal Dangol ◽  
Vitaly Kholodovsky ◽  
Amy R. Sapkota ◽  
Masoud Negahban-Azar ◽  
...  
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Crop Yields ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
River Watershed ◽  
Temperature And Precipitation ◽  
The Impact

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.

The challenge of combining initialised and uninitialised decadal projections

2020 ◽  
Author(s):  
James Murphy
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Internal Climate Variability ◽  
Climate Risks ◽  
Early Results ◽  
Ensemble Mean ◽  
Decadal Climate

<p>The challenge of combining initialised and uninitialised decadal projections</p><p>James Murphy, Robin Clark, Nick Dunstone, Glen Harris, Leon Hermanson and Doug Smith</p><p>During the past 10 years or so, exploratory work in initialised decadal climate prediction, using global climate models started from recent analyses of observations, has grown into a coordinated international programme that contributes to IPCC assessments. At the same time, countries have continued to develop and update their national climate change scenarios.  These typically cover the full 21<sup>st</sup> century, including the initial decade that overlaps with the latest initialised forecasts. To date, however, national scenarios continue to be based exclusively on long-term (uninitialised) climate change simulations, with initialised information regarded as a separate stream of information.</p><p>We will use early results from the latest UK national scenarios (UKCP), and the latest CMIP6 initialised predictions, to illustrate the potential and challenges associated with the notion of combining both streams of information. This involves assessing the effects of initialisation on predictability and uncertainty (as indicated, for example, by the skill of ensemble-mean forecasts and the spread amongst constituent ensemble members). Here, a particular challenge involves interpretation of the “signal-to-noise” problem, in which ensemble-mean skill can sometimes be found which is larger than would be expected on the basis of the ensemble spread. In addition to initialisation, we will also emphasise the importance of understanding how the assessment of climate risks depends on other features of prediction system design, including the sampling of model uncertainties and the simulation of internal climate variability.</p>

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

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