scholarly journals A bias-corrected CMIP5 dataset for Africa using CDF-t method. A contribution to agricultural impact studies

2017 ◽  
Author(s):  
Adjoua Moise Famien ◽  
Serge Janicot ◽  
Abe Delfin Ochou ◽  
Mathieu Vrac ◽  
Dimitri Defrance ◽  
...  
Keyword(s):  
West Africa ◽  
Air Temperature ◽  
Climate Models ◽  
Global Climate Models ◽  
Cumulative Distribution ◽  
Shortwave Radiation ◽  
Climate Change Scenarios ◽  
Data Set ◽  
Near Surface ◽  
The Impact

Abstract. The objective of this paper is to present a new data set of bias-corrected CMIP5 global climate models (GCMs) daily data over Africa. This dataset was obtained in using the Cumulative Distribution Function Transform (CDF-t) method, a method that has been applied on several regions and contexts but never on Africa. Here CDF-t is used over the period 1950–2099 combining historical runs and climate change scenarios on 6 variables, precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface down-welling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. Evaluation of the results is carried out over West Africa on a list of priority users-based metrics that was discussed and selected with stakeholders and on simulated yield using a crop model simulating maize growth. Bias-corrected GCMs data are compared with another available dataset of bias-corrected GCMs, and the impact of three different reference datasets on bias-corrections is also examined in details. CDF-t is very effective in removing the biases and in reducing the high inter-GCMs scattering. Differences with other bias-corrected GCMs data are mainly due to the differences between the reference datasets. This is particular true for surface down-welling shortwave radiation, which has impacts in terms of simulated maize yields. Projections of future yields over West Africa have quite different levels, depending on bias-correction method used, but they all show a similar relative decreasing trend over the 21st century.

scholarly journals A bias-corrected CMIP5 dataset for Africa using the CDF-t method – a contribution to agricultural impact studies

2018 ◽  
Vol 9 (1) ◽  
pp. 313-338 ◽  
Author(s):  
Adjoua Moise Famien ◽  
Serge Janicot ◽  
Abe Delfin Ochou ◽  
Mathieu Vrac ◽  
Dimitri Defrance ◽  
...  
Keyword(s):  
West Africa ◽  
Air Temperature ◽  
Climate Model ◽  
Global Climate Model ◽  
Cumulative Distribution ◽  
Shortwave Radiation ◽  
Climate Change Scenarios ◽  
Reference Dataset ◽  
Near Surface ◽  
The Impact

Abstract. The objective of this paper is to present a new dataset of bias-corrected CMIP5 global climate model (GCM) daily data over Africa. This dataset was obtained using the cumulative distribution function transform (CDF-t) method, a method that has been applied to several regions and contexts but never to Africa. Here CDF-t has been applied over the period 1950–2099 combining Historical runs and climate change scenarios for six variables: precipitation, mean near-surface air temperature, near-surface maximum air temperature, near-surface minimum air temperature, surface downwelling shortwave radiation, and wind speed, which are critical variables for agricultural purposes. WFDEI has been used as the reference dataset to correct the GCMs. Evaluation of the results over West Africa has been carried out on a list of priority user-based metrics that were discussed and selected with stakeholders. It includes simulated yield using a crop model simulating maize growth. These bias-corrected GCM data have been compared with another available dataset of bias-corrected GCMs using WATCH Forcing Data as the reference dataset. The impact of WFD, WFDEI, and also EWEMBI reference datasets has been also examined in detail. It is shown that CDF-t is very effective at removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets. This is particularly true for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields. Projections of future yields over West Africa are quite different, depending on the bias-correction method used. However all these projections show a similar relative decreasing trend over the 21st century.

scholarly journals Assessing Future Spatio-Temporal Changes in Crop Suitability and Planting Season over West Africa: Using the Concept of Crop-Climate Departure

Climate ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 102 ◽  
Author(s):  
Temitope S. Egbebiyi ◽  
Chris Lennard ◽  
Olivier Crespo ◽  
Phillip Mukwenha ◽  
Shakirudeen Lawal ◽  
...  
Keyword(s):  
West Africa ◽  
Linear Correlation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Crop Suitability ◽  
Suitable Area ◽  
The Impact ◽  
Planting Season

The changing climate is posing significant threats to agriculture, the most vulnerable sector, and the main source of livelihood in West Africa. This study assesses the impact of the climate-departure on the crop suitability and planting month over West Africa. We used 10 CMIP5 Global climate models bias-corrected simulations downscaled by the CORDEX regional climate model, RCA4 to drive the crop suitability model, Ecocrop. We applied the concept of the crop-climate departure (CCD) to evaluate future changes in the crop suitability and planting month for five crop types, cereals, legumes, fruits, root and tuber and horticulture over the historical and future months. Our result shows a reduction (negative linear correlation) and an expansion (positive linear correlation) in the suitable area and crop suitability index value in the Guinea-Savanna and Sahel (southern Sahel) zone, respectively. The horticulture crop was the most negatively affected with a decrease in the suitable area while cereals and legumes benefited from the expansion in suitable areas into the Sahel zone. In general, CCD would likely lead to a delay in the planting season by 2–4 months except for the orange and early planting dates by about 2–3 months for cassava. No projected changes in the planting month are observed for the plantain and pineapple which are annual crops. The study is relevant for a short and long-term adaptation option and planning for future changes in the crop suitability and planting month to improve food security in the region.

scholarly journals Identification of Potential Drought Areas in West Africa Under Climate Change and Variability

2019 ◽  
Vol 3 (3) ◽  
pp. 429-444 ◽  
Author(s):  
Gandome Mayeul L. D. Quenum ◽  
Nana A. B. Klutse ◽  
Diarra Dieng ◽  
Patrick Laux ◽  
Joël Arnault ◽  
...  
Keyword(s):  
West Africa ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Global Climate Models ◽  
Spatiotemporal Pattern ◽  
Historical Period ◽  
Gulf Of Guinea ◽  
Precipitation Concentration ◽  
The Impact

Abstract The study investigates how the rising global temperature will affect the spatial pattern of rainfall and consequently drought in West Africa. The precipitation and potential evapotranspiration variables that are obtained from the Rossby Centre regional atmospheric model (RCA4) and driven by ten (10) global climate models under the RCP8.5 scenario were used. The model data were obtained from the Coordinated Regional Climate Downscaling Experiment (CORDEX) and analyzed at four specific global warming levels (GWLs) (i.e., 1.5 °C, 2.0 °C, 2.5 °C, and 3.0 °C) above the pre-industrial level. This study utilized four (4) indices: the standardized precipitation index, the precipitation concentration index, the precipitation concentration degree, and the precipitation concentration period over West Africa to explore the spatiotemporal variations in the characteristics of precipitation concentrations. Additionally, studying the impact of the four GWLs on consecutive dry days, consecutive wet days, and frequency of the intense rainfall events led to a better understanding of the spatiotemporal pattern of extreme precipitation. The results show that, at each GWL studied, the onset of rainfall comes 1 month earlier in the Gulf of Guinea compared to the historical period (1971–2000) with increasing rainfall intensity in the whole study domain, and the northeastern part of the study area becomes wetter. The rainfall concentration is uniformly distributed over the Gulf of Guinea and the Savanna zone for both the historical period and RCP8.5 scenario, while the Sahel zone which has shown an irregular concentration of rainfall for the historical period shows a uniform concentration of rainfall under all four GWLs.

Seasonal and Long-Term Changes to Pavement Life Caused by Rising Temperatures from Climate Change

2019 ◽  
Vol 2673 (6) ◽  
pp. 267-278 ◽  
Author(s):  
Jayne F. Knott ◽  
Jo E. Sias ◽  
Eshan V. Dave ◽  
Jennifer M. Jacobs
Keyword(s):  
Climate Change ◽  
Temperature Rise ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Top Down ◽  
Bottom Up ◽  
Pavement Damage ◽  
The Impact

Pavements are vulnerable to reduced life with climate-change-induced temperature rise. Greenhouse gas emissions have caused an increase in global temperatures since the mid-20th century and the warming is projected to accelerate. Many studies have characterized this risk with a top-down approach in which climate-change scenarios are chosen and applied to predict pavement-life reduction. This approach is useful in identifying possible pavement futures but may miss short-term or seasonal pavement-response trends that are essential for adaptation planning. A bottom-up approach focuses on a pavement’s response to incremental temperature change resulting in a more complete understanding of temperature-induced pavement damage. In this study, a hybrid bottom-up/top-down approach was used to quantify the impact of changing pavement seasons and temperatures on pavement life with incremental temperature rise from 0 to 5°C at a site in coastal New Hampshire. Changes in season length, seasonal average temperatures, and temperature-dependent resilient modulus were used in layered-elastic analysis to simulate the pavement’s response to temperature rise. Projected temperature rise from downscaled global climate models was then superimposed on the results to determine the timing of the effects. The winter pavement season is projected to end by mid-century, replaced by a lengthening fall season. Seasonal pavement damage, currently dominated by the late spring and summer seasons, is projected to be distributed more evenly throughout the year as temperatures rise. A 7% to 32% increase in the asphalt-layer thickness is recommended to protect the base and subgrade with rising temperatures from early century to late-mid-century.

scholarly journals Large sensitivity of a Greenland ice sheet model to atmospheric forcing fields

2012 ◽  
Vol 6 (2) ◽  
pp. 1037-1083 ◽  
Author(s):  
A. Quiquet ◽  
H. J. Punge ◽  
C. Ritz ◽  
X. Fettweis ◽  
M. Kageyama ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Global Climate Models ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
The Impact

Abstract. The prediction of future climate and ice sheet evolution requires coupling of ice sheet and climate models. Before proceeding to a coupled setup, we propose to analyze the impact of model simulated climate on an ice sheet. Here, we undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary condition to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyr of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed ones, there are considerable deviations among the ice sheets on regional scales. These can be explained by difficulties in modelling local temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations of each climate model are also due to the differences in the atmospheric general circulation. In the context of coupling ice sheet and climate models, we conclude that appropriate downscaling methods will be needed and systematic corrections of the climatic variables at the interface may be required in some cases to obtain realistic results for the Greenland ice sheet (GIS).

scholarly journals Assessing the Impact of Projected Climate Change on Zoo Visitation in Toronto (Canada)

2016 ◽  
Vol 8 (2) ◽  
pp. 30 ◽  
Author(s):  
Micah J. Hewer ◽  
William A. Gough
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Positive Impact ◽  
Global Climate ◽  
Global Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Local Climate ◽  
The Impact

Weather and climate have been widely recognised as having an important influence on tourism and recreational activities. However, the nature of these relationships varies depending on the type, timing and location of these activities. Climate change is expected to have considerable and diverse impacts on recreation and tourism. Nonetheless, the potential impact of climate change on zoo visitation has yet to be assessed in a scientific manner. This case study begins by establishing the baseline conditions and statistical relationship between weather and zoo visitation in Toronto, Canada. Regression analysis, relying on historical weather and visitation data, measured at the daily time scale, formed the basis for this analysis. Climate change projections relied on output produced by Global Climate Models (GCMs) for the Intergovernmental Panel on Climate Change’s 2013 Fifth Assessment Report, ranked and selected using the herein defined Selective Ensemble Approach. This seasonal GCM output was then used to inform daily, local, climate change scenarios, generated using Statistical Down-Scaling Model Version 5.2. A series of seasonal models were then used to assess the impact of projected climate change on zoo visitation. While accounting for the negative effects of precipitation and extreme heat, the models suggested that annual visitation to the zoo will likely increase over the course of the 21st century due to projected climate change: from +8% in the 2020s to +18% by the 2080s, for the least change scenario; and from +8% in the 2020s to +34% in the 2080s, for the greatest change scenario. The majority of the positive impact of projected climate change on zoo visitation in Toronto will likely occur in the shoulder season (spring and fall); with only moderate increases in the off season (winter) and potentially negative impacts associated with the peak season (summer), especially if warming exceeds 3.5 °C.

scholarly journals Why Do Global Climate Models Struggle to Represent Low-Level Clouds in the West African Summer Monsoon?

2017 ◽  
Vol 30 (5) ◽  
pp. 1665-1687 ◽  
Author(s):  
Lisa Hannak ◽  
Peter Knippertz ◽  
Andreas H. Fink ◽  
Anke Kniffka ◽  
Gregor Pante
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
West African Monsoon ◽  
High Elevation ◽  
West African ◽  
Global Climate Models ◽  
The West ◽  
Near Surface ◽  
Low Level ◽  
The Impact

Abstract Climate models struggle to realistically represent the West African monsoon (WAM), which hinders reliable future projections and the development of adequate adaption measures. Low-level clouds over southern West Africa (5°–10°N, 8°W–8°E) during July–September are an integral part of the WAM through their effect on the surface energy balance and precipitation, but their representation in climate models has received little attention. Here 30 (20) years of output from 18 (8) models participating in phase 5 of the Coupled Model Intercomparison Project (Year of Tropical Convection) are used to identify cloud biases and their causes. Compared to ERA-Interim reanalyses, many models show large biases in low-level cloudiness of both signs and a tendency to too high elevation and too weak diurnal cycles. At the same time, these models tend to have too strong low-level jets, the impact of which is unclear because of concomitant effects on temperature and moisture advection as well as turbulent mixing. Part of the differences between the models and ERA-Interim appear to be related to the different subgrid cloud schemes used. While nighttime tendencies in temperature and humidity are broadly realistic in most models, daytime tendencies show large problems with the vertical transport of heat and moisture. Many models simulate too low near-surface relative humidities, leading to insufficient low cloud cover and abundant solar radiation, and thus a too large diurnal cycle in temperature and relative humidity. In the future, targeted model sensitivity experiments will be needed to test possible feedback mechanisms between low clouds, radiation, boundary layer dynamics, precipitation, and the WAM circulation.

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 Assessment of the Canary current upwelling system in a regionally coupled climate model

2021 ◽  
Author(s):  
Ruben Vazquez ◽  
Ivan Parras-Berrocal ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Rafael Mañanes ◽  
...  
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Horizontal Resolution ◽  
Global Climate Models ◽  
Climate Change Signal ◽  
Climate Modelling ◽  
Near Surface ◽  
Upwelling System ◽  
The Impact ◽  
Mesoscale Processes

AbstractThe Canary current upwelling is one of the major eastern boundary coastal upwelling systems in the world, bearing a high productive ecosystem and commercially important fisheries. The Canary current upwelling system (CCUS) has a large latitudinal extension, usually divided into upwelling zones with different characteristics. Eddies, filaments and other mesoscale processes are known to have an impact in the upwelling productivity, thus for a proper representation of the CCUS and high horizontal resolution are required. Here we assess the CCUS present climate in the atmosphere–ocean regionally coupled model. The regional coupled model presents a global oceanic component with increased horizontal resolution along the northwestern African coast, and its performance over the CCUS is assessed against relevant reanalysis data sets and compared with an ensemble of global climate models (GCMs) and an ensemble of atmosphere-only regional climate models (RCMs) in order to assess the role of the horizontal resolution. The coupled system reproduces the larger scale pattern of the CCUS and its latitudinal and seasonal variability over the coastal band, improving the GCMs outputs. Moreover, it shows a performance comparable to the ensemble of RCMs in representing the coastal wind stress and near-surface air temperature fields, showing the impact of the higher resolution and coupling for CCUS climate modelling. The model is able of properly reproducing mesoscale structures, being able to simulate the upwelling filaments events off Cape Ghir, which are not well represented in most of GCMs. Our results stress the ability of the regionally coupled model to reproduce the larger scale as well as mesoscale processes over the CCUS, opening the possibility to evaluate the climate change signal there with increased confidence.

scholarly journals Modeling the global emission, transport and deposition of trace elements associated with mineral dust

2015 ◽  
Vol 12 (19) ◽  
pp. 5771-5792 ◽  
Author(s):  
Y. Zhang ◽  
N. Mahowald ◽  
R. A. Scanza ◽  
E. Journet ◽  
K. Desboeufs ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Mineral Dust ◽  
Chemical Elements ◽  
Global Climate ◽  
Global Climate Models ◽  
Data Set ◽  
Desert Dust ◽  
Mineral Data ◽  
The Impact

Abstract. Trace element deposition from desert dust has important impacts on ocean primary productivity, the quantification of which could be useful in determining the magnitude and sign of the biogeochemical feedback on radiative forcing. However, the impact of elemental deposition to remote ocean regions is not well understood and is not currently included in global climate models. In this study, emission inventories for eight elements primarily of soil origin, Mg, P, Ca, Mn, Fe, K, Al, and Si are determined based on a global mineral data set and a soil data set. The resulting elemental fractions are used to drive the desert dust model in the Community Earth System Model (CESM) in order to simulate the elemental concentrations of atmospheric dust. Spatial variability of mineral dust elemental fractions is evident on a global scale, particularly for Ca. Simulations of global variations in the Ca / Al ratio, which typically range from around 0.1 to 5.0 in soils, are consistent with observations, suggesting that this ratio is a good signature for dust source regions. The simulated variable fractions of chemical elements are sufficiently different; estimates of deposition should include elemental variations, especially for Ca, Al and Fe. The model results have been evaluated with observations of elemental aerosol concentrations from desert regions and dust events in non-dust regions, providing insights into uncertainties in the modeling approach. The ratios between modeled and observed elemental fractions range from 0.7 to 1.6, except for Mg and Mn (3.4 and 3.5, respectively). Using the soil database improves the correspondence of the spatial heterogeneity in the modeling of several elements (Ca, Al and Fe) compared to observations. Total and soluble dust element fluxes to different ocean basins and ice sheet regions have been estimated, based on the model results. The annual inputs of soluble Mg, P, Ca, Mn, Fe and K associated with dust using the mineral data set are 0.30 Tg, 16.89 Gg, 1.32 Tg, 22.84 Gg, 0.068 Tg, and 0.15 Tg to global oceans and ice sheets.

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