Heavy precipitation events over East Africa in a changing climate: results from CORDEX RCMs

Ogega, Obed M.; Koske, James; Kung’u, J.B.; Scoccimarro, Enrico; Endris, Hussen Seid; Mistry, Malcolm

doi:10.1007/s00382-020-05309-z

Cited by 53 publications

(56 citation statements)

References 49 publications

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“…The observed declining trends in the seasonal precipitation over the region is not well captured by the MME, leading to huge biases noted. In agreement with previous studies (i.e., Osima et al, 2018;Ogega et al, 2020) The black dots indicate statistically significant changes at the 95% confidence level while areas, where 70% of models agree on the changes, are marked with sloped black boxes.…”

Section: Climate Extreme Indices Definition and Calculationsupporting

confidence: 91%

“…This study assessed Likewise, the CWD projections exhibit tendencies of intense occurrence around Lake Victoria region whereas no significant changes are observed are over most parts, except for the southern parts of Tanzania where a reduction of up to 4 days in a year is projected. The findings of the present study are in harmony with the recent study that employed large ensemble members from regional climate models (RCMs) models outputs to project changes in extremes precipitation over EA region (Cattaini et al, 2018;Osima et al, 2018;Ogega et al, 2020).…”

Section: Ond Precipitation Extremessupporting

confidence: 89%

“…Overall, the study area will experience varying extremes, such as a reduction in PRCPTOT under 'business as usual' scenario than a modest mitigation policy scenario. A decrease in MAM precipitation could be due to projected earlier onset/cessation dates relative to the baseline period, possibly impacting the long rain season (Ogega et al, 2020). Likewise, the persistent drying patterns are showed in CDD, which is likely to intensify under the SSP5 -8.5 scenario.…”

Section: Mam Precipitation Extremesmentioning

confidence: 98%

“…The region located in the tropics and bound along latitude 12ºS -5ºN and longitude 28º E -42ºE will need humanitarian assistance if no proper mechanism is put in place. Several studies based mainly on CMIP5 or regional climate models (RCMs) have been conducted to examine to historical trends and future projections of extremes events of the EA region (Ongoma et al, 2018c;Gebrechorkos et al, 2018;Osima et al, 2018;Onyutha, 2020;Ogega et al, 2020;Tegegne et al, 2020). Undoubtedly, these studies' overall conclusion shows a varying trend of change, mainly attributed to the data sets employed or period analysed.…”

Section: Introductionmentioning

confidence: 99%

“…Essentially, temperature extremes (i.e., minimum and maximum temperature) show an overall upward tendency in many studies (IPCC, 2014;Ongoma et al, 2018a;Gebrechorkos et al, 2018;Osima et al, 2018). Conversely, projections in precipitation extremes using indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI;Klein Tank et al, 2009;Zhang et al, 2011) are marred by uncertainty and unclear patterns (Osima et al, 2018;Ogega et al, 2020;Onyutha, 2020). To demonstrate, Onyutha (2020) showed significant biases in RCMs employed in simulating maximum wet spell (MWS) over the EA region.…”

Section: Introductionmentioning

confidence: 99%

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Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections

Ayugi¹,

Dike²,

Ngoma³

et al. 2021

Preprint

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This paper presents an analysis of precipitation extremes over the East African region. The study employs six extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) to evaluate possible climate change. Observed datasets and CMIP6 simulations and projections are employed to assess the changes during the two main rainfall seasons of March to May (MAM) and October to December (OND). The study evaluated the capability of CMIP6 simulations in reproducing the observed extreme events during the period 1995 – 2014. Our results show that the multi-model ensemble (herein referred to as MME) of CMIP6 models can depict the observed spatial distribution of precipitation extremes for both seasons, albeit with some noticeable exceptions in some indices. Overall, MME's assessment yields considerable confidence in CMIP6 to be employed for the projection of extreme events over the study area. Analysis of extreme estimations shows an increase (decrease) in CDD (CWD) during 2081 – 2100 relative to the baseline period in both seasons. Moreover, SDII, R95p, R20mm, and PRCPTOT demonstrate significant OND estimates compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while reduction is observed over the Tanzania region. The increase in projected extremes during two main rainfall seasons poses a significant threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. More studies are encouraged to examine the underlying physical features modulating the occurrence of extremes incidences projected for relevant policies.

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Section: Climate Extreme Indices Definition and Calculationsupporting

confidence: 91%

Section: Ond Precipitation Extremessupporting

confidence: 89%

Section: Mam Precipitation Extremesmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections

Ayugi¹,

Dike²,

Ngoma³

et al. 2021

Preprint

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Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa

Ayugi

Jiang

Zhu

et al. 2021

Intl Journal of Climatology

145

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This study examines the improvement in Coupled Model Intercomparison Project Phase Six (CMIP6) models against the predecessor CMIP5 in simulating mean and extreme precipitation over the East Africa region. The study compares the climatology of the precipitation indices simulated by the CMIP models with the CHIRPS data set using robust statistical techniques for 1981-2005. The results display the varying performance of the general circulation models (GCMs) in the simulation of annual and seasonal precipitation climatology over the study domain. CMIP6 multi-model ensemble mean (hereafter MME) shows improved performance in the local annual mean cycle simulation with a better representation of the rainfall within the two peaks, especially the MAM rainfall relative to their predecessor. Moreover, simulation of extreme indices is well captured in CMIP6 models relative to CMIP5. The CMIP6-MME performed better than the CMIP5-MME with lesser biases in simulating Simple Daily Intensity Index (SDII), consecutive dry days (CDD), and very heavy precipitation days >20 mm (R20mm) over East Africa. Remarkably, most CMIP6 models are unable to simulate extremely wet days (R95p). Some CMIP6 models (e.g., NorESM2-MM and CNRM-CM6-1) depict robust performance in reproducing the observed indices across all analyses. OND season shows wet biases for some indices (i.e., R95p, PRCPTOT), except for SDII, CDD, and R20mm in CMIP6 models. Consistent with other studies, the mean ensemble performance for both CMIP5/6 shows better performance as compared with individual models due to the cancellation of some systematic errors in the

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Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models: Part I—Evaluation of historical simulation

Samuel

Wiston

Mphale

et al. 2022

Intl Journal of Climatology

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This study evaluates the ability of the Coordinated Output for Regional Evaluations (CORE) initiated under the Coordinated Regional Climate Downscaling Experiment (CORDEX) to reproduce austral summer extreme precipitation indices over the Zambezi River basin (ZRB) from 1983 to 2005. The ability of the RCMs to simulate the spatial distributions of observed extreme precipitation was assessed using multiple datasets. The spatially averaged performance of the CORDEX‐CORE ensemble mean (CORE‐ENS) and RCM ensembles (RCM‐ENSEMBLES developed from different combinations of CORE‐ENS ensemble members) was evaluated using statistical metrics. The results showed similarities in the spatial distribution of extreme precipitation among the observations. However, there were considerable differences in the magnitude of extreme precipitation among the observations. The frequency of days with very heavy precipitation (R20) showed the largest differences in magnitude among the observations. Although there are differences in magnitude, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES can capture the spatial distribution of extreme precipitation. Specifically, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES overestimated (underestimated) the frequency of rainy days (RR1) and maximum consecutive wet days (CWD) (maximum consecutive dry days [CDD]). In contrast, some members of CORE‐ENS overestimate, while others underestimate, the simple daily intensity index (SDII), the frequency of days with heavy precipitation (R10), and R20, depending on the choice of reference data. The Consortium for Small‐scale MOdelling in CLimate Mode (CCLM) and Regional MOdel (REMO) performed better than the Regional Climate Model (RegCM4.7) in simulating the spatial distributions of extreme precipitation. The regionally averaged uncertainties (biases) of the CORE‐ENS, its ensemble members, and RCMENSEMBLES were within the range of those in the observational datasets, except for CWD (CWD and RR1). Overall, CORE‐ENS performed better than its ensemble members in simulating extreme precipitation.

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Heavy precipitation events over East Africa in a changing climate: results from CORDEX RCMs

Cited by 53 publications

References 49 publications

Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections

Future Changes in Precipitation Extremes Over East Africa Based on CMIP6 Projections

Comparison of CMIP6 and CMIP5 models in simulating mean and extreme precipitation over East Africa

Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models: Part I—Evaluation of historical simulation

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