Identification of deficiencies in seasonal rainfall simulated by CMIP5 climate models

Dunning, C.; Allan, Richard P.; Black, Emily

doi:10.1088/1748-9326/aa869e

Cited by 31 publications

(34 citation statements)

References 69 publications

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“…Some of the characteristics of these regional differences and those between the AMIP and coupled ensembles are also present in studies of East Africa, mostly revolving around model representation of the onset rainy season (AM or MAM). For instance, Rowell et al (2015) showed that coupled CMIP5 have more trouble reproducing trends in this season than AMIP models, while Dunning et al (2017) showed that CMIP5 models simulate late onset in this season. For this reason the transitions from the biases in the Awash basin to the biases in Northwest Ethiopia have proved interesting.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the CMIP5 ensemble in Ethiopia: Creating a reduced ensemble for rainfall and temperature in Northwest Ethiopia and the Awash basin

Dyer

Washington

Taye

2019

Intl Journal of Climatology

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The purpose of this study was to evaluate the historical skill of models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) in two regions of Ethiopia: northwestern Ethiopia and the Awash, one of the main Ethiopian river basins. An ensemble of CMIP5 models was first selected so that atmosphere-only (Atmospheric Model Intercomparison Project, AMIP) and fully coupled simulations could be directly compared, assessing the effects of coupled model sea surface temperature (SST) biases. The annual cycle, seasonal biases, trends, and variability were used as metrics of model skill. In the Awash basin, both coupled and AMIP simulations had late Belg or March-May (MAM) rainy seasons. In connection to this, most models also missed the June rainfall minimum entirely. Northwest Ethiopia, which has a unimodal rainfall cycle in observations, is shown to have bimodal seasonality in models, even in the AMIP simulations. Significant AMIP biases in these regions show that model biases are not related to SST biases alone. Similarly, a clear connection between model resolution and skill was not found. Models simulated temperature with more skill than rainfall, but trends showed an underestimation in Belg (MAM/April-May (AM)) trends, and an overestimation in Kiremt or July-September (JAS/June-September (JJAS)) trends. The models which were shown to have the most skill in a range of categories were HadGEM2-AO, GFDL-CM3, and MPI-ESM-MR. The biases and discrepancies in model skill for different metrics of rainfall and temperature found in this study provide a useful basis for a process-based analysis of the CMIP5 ensemble in Ethiopia.

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Section: Discussionmentioning

confidence: 99%

Evaluating the CMIP5 ensemble in Ethiopia: Creating a reduced ensemble for rainfall and temperature in Northwest Ethiopia and the Awash basin

Dyer

Washington

Taye

2019

Intl Journal of Climatology

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“…Onset and cessation dates were calculated using the methodology of Dunning et al (2016), which extends the methodology of Liebmann et al (2012). For analysis of changes in onset and cessation dates the method is applied separately to the three time periods used (recent period, mid-twenty-first century, and end of the twentyfirst century).…”

Section: B Methodology For Identifying Onset and Cessation Of Rainfamentioning

confidence: 99%

“…The method has three stages; full details of the method can be found in Dunning et al (2016). First, the seasonal regime at each grid point is categorized as being a dominantly annual regime (one wet season per year) or biannual regime (two wet seasons per year).…”

Section: B Methodology For Identifying Onset and Cessation Of Rainfamentioning

confidence: 99%

“…Studies looking at the changing nature of seasonal timing by quantitatively calculating onset and cessation dates tend to focus on the national to regional scale (Vizy et al 2015) or average the results over large spatial areas, such as in Christensen et al (2013) where future projections of onset date, retreat date, and duration are averaged over a northern African and a southern African region, masking spatial variability. Marvel et al (2017) examined changes in the seasonal cycle of zonal mean precipitation and found a later onset at tropical latitudes; however, zonal averaging masks spatial variability, especially as the progression of rainfall is not always zonally contiguous (Liebmann et al 2012;Dunning et al 2016). Cook and Vizy (2012) analyzed future projections of the growing season in Africa in a single regional climate model, run with six ensemble members, with the boundary conditions determined using output from nine climate model simulations from the generation of models from phase 3 of the Coupled Model Intercomparison Project (CMIP3).…”

Section: Introductionmentioning

confidence: 99%

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Later Wet Seasons with More Intense Rainfall over Africa under Future Climate Change

2018

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Later wet seasons with more intense rainfall over Africa under future climate change Article Published Version Dunning, C., Black, E. and Allan, R. (2018) Later wet seasons with more intense rainfall over Africa under future climate change. Journal of Climate, 31. pp. 97199738. ISSN 0894 8755ABSTRACT Changes in the seasonality of precipitation over Africa have high potential for detrimental socioeconomic impacts due to high societal dependence upon seasonal rainfall. Here, for the first time we conduct a continental-scale analysis of changes in wet season characteristics under the RCP4.5 and RCP8.5 climate projection scenarios across an ensemble of CMIP5 models using an objective methodology to determine the onset and cessation of the wet season. A delay in the wet season over West Africa and the Sahel of over 5-10 days on average, and later onset of the wet season over southern Africa, is identified and associated with increasing strength of the Saharan heat low in late boreal summer and a northward shift in the position of the tropical rain belt over August-December. Over the Horn of Africa rainfall during the ''short rains'' season is projected to increase by over 100 mm on average by the end of the twenty-first century under the RCP8.5 scenario. Average rainfall per rainy day is projected to increase, while the number of rainy days in the wet season declines in regions of stable or declining rainfall (western and southern Africa) and remains constant in central Africa, where rainfall is projected to increase. Adaptation strategies should account for shorter wet seasons, increasing rainfall intensity, and decreasing rainfall frequency, which will have implications for crop yields and surface water supplies.

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“…Precipitation over southern West Africa (SWA) is important for agriculture and water resources, yet model simulations of precipitation amount and variability are uncertain over the region (e.g. Cook and Vizy, 2006;Roehrig et al, 2013;Vellinga et al, 2013;Dunning et al, 2017). Accurate observations of precipitation are therefore crucial for understanding the processes responsible for the model discrepancies.…”

Section: Introductionmentioning

confidence: 99%

Spatio‐temporal variability of warm rain events over southern West Africa from geostationary satellite observations for climate monitoring and model evaluation

Young

Williams

Stein

et al. 2018

Quart J Royal Meteoro Soc

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This article presents the spatio‐temporal variability of warm rain events over southern West Africa (SWA) during the summer monsoon season for the first time, using Spinning Enhanced Visible Infrared Radiometer (SEVIRI) observations on the Meteosat geostationary satellites. The delineation of warm rain events is based on the principle that precipitating low‐level clouds are associated with either sufficient water content or large cloud droplet size. Capitalising on the ability of space‐borne radar to resolve vertical cloud structures and detect the presence of precipitation, the delineation is trained by collocated SEVIRI and CloudSat observations. The resulting 12 years of observations from SEVIRI are used to examine the spatial, diurnal, seasonal and interannual variability of warm rain events over SWA. Warm rain events predominate during the monsoon in August, with little interannual variability, and persist over orography in the morning and the coasts after midday, likely enhanced by orographic lifting and land–sea breeze effects. Warm clouds have a much higher probability of precipitation along the coastlines of Liberia and Nigeria compared to the central SWA coastline and further inland. Finally, when evaluating an 8‐day yet high‐spatial resolution model simulation, we find that warm rain frequencies from the simulation agree well with SEVIRI near the coast but simulated warm cloud cover and thus warm rain frequencies are too low over the Gulf of Guinea. The probability of precipitation of warm clouds is also too low inland. The newly developed observations of warm rain create opportunities to further investigate the diurnal cycle of warm rain, study aerosol–cloud–precipitation interactions, and assess the role of warm rain in the water cycle across Africa and beyond.

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Identification of deficiencies in seasonal rainfall simulated by CMIP5 climate models

Cited by 31 publications

References 69 publications

Evaluating the CMIP5 ensemble in Ethiopia: Creating a reduced ensemble for rainfall and temperature in Northwest Ethiopia and the Awash basin

Evaluating the CMIP5 ensemble in Ethiopia: Creating a reduced ensemble for rainfall and temperature in Northwest Ethiopia and the Awash basin

Later Wet Seasons with More Intense Rainfall over Africa under Future Climate Change

Spatio‐temporal variability of warm rain events over southern West Africa from geostationary satellite observations for climate monitoring and model evaluation

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