Assessing the Capabilities of Three Regional Climate Models over CORDEX Africa in Simulating West African Summer Monsoon Precipitation

This study evaluates the ability of three Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) to simulate the characteristics of rainfall pattern during the West Africa Summer Monsoon from 1998 to 2008. The seasonal climatology, annual rainfall cycles, and wind fields of the RCMs output were assessed over three homogenous subregions and validated using precipitation data from eighty-one (81) ground observation stations and TRMM satellite data. Furthermore, the ability of the RCMs to simulate response to El Nino and La Nina events was assessed. Results show that two of the RCMs (RCA and REMO) simulated the main features of the rainfall climatology and associated dynamics over the three subregions (Guinea Coast, Savannah, and Sahel) of West Africa. The RCMs also capture the African Easterly Jet (AEJ) and Tropical Easterly Jet (TEJ) with little variations in position and intensity. Analysis shows significant biases in individual models depending on subregion and season under consideration which may be attributed to strong cyclonic circulation observed at 850 mb pressure level. In general, the study shows RCA and REMO fairly simulate West Africa rainfall adequately and can therefore be used for the assessment of West African Summer Monsoon and future climate projections.

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Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall

Journal of Climate ◽

10.1175/jcli-d-12-00708.1 ◽

2013 ◽

Vol 26 (21) ◽

pp. 8453-8475 ◽

Cited By ~ 108

Author(s):

Hussen Seid Endris ◽

Philip Omondi ◽

Suman Jain ◽

Christopher Lennard ◽

Bruce Hewitson ◽

...

Keyword(s):

Large Scale ◽

Climate Models ◽

Southern Oscillation ◽

Global Climate ◽

Regional Climate ◽

Regional Climate Models ◽

Eastern Africa ◽

Annual Rainfall ◽

Climate Projections ◽

Ensemble Mean

Abstract This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño–Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region.

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Regional Climate Scenarios for use in Nordic Water Resources Studies

Hydrology Research ◽

10.2166/nh.2003.0014 ◽

2003 ◽

Vol 34 (5) ◽

pp. 399-412 ◽

Cited By ~ 19

Author(s):

M. Rummukainen ◽

J. Räisänen ◽

D. Bjørge ◽

J.H. Christensen ◽

O.B. Christensen ◽

...

Keyword(s):

Water Resources ◽

Climate Models ◽

Global Climate ◽

Regional Climate ◽

Regional Climate Models ◽

Climate Projections ◽

Climate Scenarios ◽

Soil Frost ◽

Nordic Region ◽

Regional Climate Projections

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

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New Approach for Bias Correction and Stochastic Downscaling of Future Projections for Daily Mean Temperatures to a High-Resolution Grid

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-19-0086.1 ◽

2019 ◽

Vol 58 (12) ◽

pp. 2617-2632 ◽

Cited By ~ 1

Author(s):

Qifen Yuan ◽

Thordis L. Thorarinsdottir ◽

Stein Beldring ◽

Wai Kwok Wong ◽

Shaochun Huang ◽

...

Keyword(s):

High Resolution ◽

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Climate Change Signal ◽

Climate Projections ◽

Data Product ◽

Temporal Features ◽

Stochastic Downscaling

AbstractIn applications of climate information, coarse-resolution climate projections commonly need to be downscaled to a finer grid. One challenge of this requirement is the modeling of subgrid variability and the spatial and temporal dependence at the finer scale. Here, a postprocessing procedure for temperature projections is proposed that addresses this challenge. The procedure employs statistical bias correction and stochastic downscaling in two steps. In the first step, errors that are related to spatial and temporal features of the first two moments of the temperature distribution at model scale are identified and corrected. Second, residual space–time dependence at the finer scale is analyzed using a statistical model, from which realizations are generated and then combined with an appropriate climate change signal to form the downscaled projection fields. Using a high-resolution observational gridded data product, the proposed approach is applied in a case study in which projections of two regional climate models from the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) ensemble are bias corrected and downscaled to a 1 km × 1 km grid in the Trøndelag area of Norway. A cross-validation study shows that the proposed procedure generates results that better reflect the marginal distributional properties of the data product and have better consistency in space and time when compared with empirical quantile mapping.

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Simulating future precipitation extremes in a complex Alpine catchment

Natural Hazards and Earth System Science ◽

10.5194/nhess-13-263-2013 ◽

2013 ◽

Vol 13 (2) ◽

pp. 263-277 ◽

Cited By ~ 9

Author(s):

C. Dobler ◽

G. Bürger ◽

J. Stötter

Keyword(s):

Climate Change ◽

Large Scale ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Precipitation Extremes ◽

Climate Projections ◽

Research Station ◽

Climate Change Scenarios ◽

Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

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A tale of two futures: contrasting scenarios of future precipitation for West Africa from an ensemble of regional climate models

Environmental Research Letters ◽

10.1088/1748-9326/ab7fde ◽

2020 ◽

Vol 15 (6) ◽

pp. 064007 ◽

Cited By ~ 5

Author(s):

Alessandro Dosio ◽

Andrew G Turner ◽

Alain T Tamoffo ◽

Mouhamadou Bamba Sylla ◽

Christopher Lennard ◽

...

Keyword(s):

West Africa ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models

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Impact of climate change on hydrological conditions in a tropical West African catchment using an ensemble of climate simulations

Hydrology and Earth System Sciences ◽

10.5194/hess-21-2143-2017 ◽

2017 ◽

Vol 21 (4) ◽

pp. 2143-2161 ◽

Cited By ~ 28

Author(s):

Yacouba Yira ◽

Bernd Diekkrüger ◽

Gero Steup ◽

Aymar Yaovi Bossa

Keyword(s):

Climate Change ◽

Water Resources ◽

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

West African ◽

Climate Projections ◽

Impact Of Climate Change ◽

Budget Analysis ◽

High Uncertainty

Abstract. This study evaluates climate change impacts on water resources using an ensemble of six regional climate models (RCMs)–global climate models (GCMs) in the Dano catchment (Burkina Faso). The applied climate datasets were performed in the framework of the COordinated Regional climate Downscaling Experiment (CORDEX-Africa) project.After evaluation of the historical runs of the climate models' ensemble, a statistical bias correction (empirical quantile mapping) was applied to daily precipitation. Temperature and bias corrected precipitation data from the ensemble of RCMs–GCMs was then used as input for the Water flow and balance Simulation Model (WaSiM) to simulate water balance components.The mean hydrological and climate variables for two periods (1971–2000 and 2021–2050) were compared to assess the potential impact of climate change on water resources up to the middle of the 21st century under two greenhouse gas concentration scenarios, the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicate (i) a clear signal of temperature increase of about 0.1 to 2.6 °C for all members of the RCM–GCM ensemble; (ii) high uncertainty about how the catchment precipitation will evolve over the period 2021–2050; (iii) the applied bias correction method only affected the magnitude of the climate change signal; (iv) individual climate models results lead to opposite discharge change signals; and (v) the results for the RCM–GCM ensemble are too uncertain to give any clear direction for future hydrological development. Therefore, potential increase and decrease in future discharge have to be considered in climate change adaptation strategies in the catchment. The results further underline on the one hand the need for a larger ensemble of projections to properly estimate the impacts of climate change on water resources in the catchment and on the other hand the high uncertainty associated with climate projections for the West African region. A water-energy budget analysis provides further insight into the behavior of the catchment.

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Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

10.5194/egusphere-egu21-12054 ◽

2021 ◽

Author(s):

Gaby S. Langendijk ◽

Diana Rechid ◽

Daniela Jacob

Keyword(s):

Climate Change ◽

Urban Areas ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Climate Change Impacts ◽

Regional Climate Models ◽

Climate Projections ◽

Climate Data ◽

Urban Rural

Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2&#176;C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.

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Performance evaluation of bias adjustment methods for wave climate projections in the Mediterranean Sea

10.5194/egusphere-egu21-13557 ◽

2021 ◽

Author(s):

Andrea Lira Loarca ◽

Giovanni Besio

Keyword(s):

Bias Correction ◽

Temporal Variability ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Wave Climate ◽

Mapping Method ◽

Climate Projections ◽

Bias Adjustment ◽

Distribution Mapping

Global and regional climate models are the primary tools to investigate the climate system response to different scenarios and therefore allow to make future projections of different atmospheric variables which are used as input for wave generation models to assess future wave climate. Adequate projections of future wave climate are needed in order to analyze climate change impacts and hazards in coastal areas such as flooding and erosion with waves being the predominant factor with varied temporal variability.&#160;Bias adjustment methods are commonly used for climate impact variables dealing with systematic errors (biases) found in global and regional climate models.&#160; While bias correction techniques are extended in the climate and hydrological impact modeling scientific communities, there is still a lack of consensus regarding their use in sea climate variables (Parker & Hill, 2017; Lemos et al, 2020; Lira-Loarca et at, 2021)In these work we assess the performance of different bias-adjustment methods such as the Empirical Gumbel Quantile Mapping (EGQM) method as a standard method which takes into the account the extreme values of the distribution takes, the Distribution Mapping method using Stationary Mixture Distributions (DM-stMix) allowing for a better representation of each variable in the mean regime and tails and the Distribution Mapping method using Non-Stationary Mixture Distributions (DM-nonstMix) as an improved methods which allows to take into account the temporal variability of wave climate according to different baseline periods such as monthly, seasonal, yearly and decadal. The performance of the different bias adjustment methods will be analyzed with particular interest on the futural temporal behavior of wave climate. The advantages and drawbacks of each bias adjustment method as well as their complexity will be discussed.&#160;References:<ul><li>Lemos, G., Menendez, M., Semedo, A., Camus, P., Hemer, M., Dobrynin, M., Miranda, P.M.A. (2020). On the need of bias correction methods for wave climate projections, Global and Planetary Change, 186, 103109.</li> <li>Lira-Loarca, A., Cobos, M., Besio, G., Baquerizo, A. (2021) Projected wave climate temporal variability due to climate change. Stoch Environ Res Risk Assess.</li> <li>Parker, K. & Hill, D.F. (2017) Evaluation of bias correction methods for wave modeling output, Ocean Modelling 110, 52-65</li> </ul>

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Intraseasonal Precipitation Variability over West Africa under 1.5 °C and 2.0 °C Global Warming Scenarios: Results from CORDEX RCMs

Climate ◽

10.3390/cli8120143 ◽

2020 ◽

Vol 8 (12) ◽

pp. 143

Author(s):

Obed M. Ogega ◽

Benjamin A. Gyampoh ◽

Malcolm N. Mistry

Keyword(s):

Global Warming ◽

West Africa ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Future Change ◽

North West ◽

Intensity Index ◽

South West Africa ◽

Projected Changes

This study assessed the performance of 24 simulations, from five regional climate models (RCMs) participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX), in representing spatiotemporal characteristics of precipitation over West Africa, compared to observations. The top five performing RCM simulations were used to assess future precipitation changes over West Africa, under 1.5 °C and 2.0 °C global warming levels (GWLs), following the representative concentration pathway (RCP) 8.5. The performance evaluation and future change assessment were done using a set of seven ‘descriptors’ of West African precipitation namely the simple precipitation intensity index (SDII), the consecutive wet days (CWD), the number of wet days index (R1MM), the number of wet days with moderate and heavy intensity precipitation (R10MM and R30MM, respectively), and annual and June to September daily mean precipitation (ANN and JJAS, respectively). The performance assessment and future change outlook were done for the CORDEX–Africa subdomains of north West Africa (WA-N), south West Africa (WA-S), and a combination of the two subdomains. While the performance of RCM runs was descriptor- and subregion- specific, five model runs emerged as top performers in representing precipitation characteristics over both WA-N and WA-S. The five model runs are CCLM4 forced by ICHEC-EC-EARTH (r12i1p1), RCA4 forced by CCCma-CanESM2 (r1i1p1), RACMO22T forced by MOHC-HadGEM2-ES (r1i1p1), and the ensemble means of simulations made by CCLM4 and RACMO22T. All precipitation descriptors recorded a reduction under the two warming levels, except the SDII which recorded an increase. Unlike the WA-N that showed less frequency and more intense precipitation, the WA-S showed increased frequency and intensity. Given the potential impact that these projected changes may have on West Africa’s socioeconomic activities, adjustments in investment may be required to take advantage of (and enhance system resilience against damage that may result from) the potential changes in precipitation.

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