Low-level circulation over Central Equatorial Africa as simulated from CMIP5 to CMIP6 models

Taguela, Thierry N.; Pokam, Wilfried M.; Dyer, Ellen; James, Rachel; Washington, Richard

doi:10.1007/s00382-022-06411-0

Cited by 7 publications

(3 citation statements)

References 46 publications

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“…S1b; R95), except for MPI-ESM1-2-LR which shows reasonable performances. Although the switch from CMIP5 to CMIP6 has allowed to better simulate the interactions of dynamical and thermodynamic processes in these models over CA (Taguela et al, 2022;Kuete et al, 2023), the fact nevertheless remains that in CMIP6 the contribution of the northern component of the African Esterly Jet (AEJ) remains overestimated as compared to its southern component (Kuete et al, 2023). This overestimation of the AEJ also could explain the simulation of excessive precipitation obtained for the majority of individual models considered in this study, especially in BCC-CSM2-MR, CanESM5, GFDL-ESM4 and MIROC6, which also simulate very heavy precipitation.…”

Section: Spatial Variability Of Duration and Intensity-based Indicesmentioning

confidence: 99%

Evaluation of extreme precipitation events as simulated by CMIP6 models over Central Africa: spatial variability

Komelo,

Fotso-Nguemo,

Ngavom

et al. 2024

Preprint

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Extreme precipitation events have substantial implications for water resources, ecosystems, and human populations in Central Africa (CA). Consequently, understanding the spatial variability of these events is crucial for effective climate change adaptation and water management strategies. In this study, we assess the performance of the state-of-the-art global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating extreme precipitation events over CA. By considering three observational datasets, we evaluated the ability of sixteen CMIP6 models as well their multi-model ensemble-mean (MME), to capture the patterns of extreme precipitation events. We then focus on key metrics such as duration and intensity, based on a total of ten indices of extreme precipitation events, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The results showed that the individual models as well as the MME exhibited acceptable performance in reproducing the patterns of extreme precipitation events, especially when dealing with wet-day amount, frequency, dry spells duration and persistence of extreme precipitation. Moreover, the analyses revealed that CMIP6 models generally have great difficulty in simulating not only the wet spells duration, but also heavy precipitation indices, highlighting the remaining challenges in reproducing local-scale processes governing precipitation variability and extremes precipitation events over the region. The results of this study provide an understanding of both the strengths and limitations of the CMIP6 models over CA, which would help to improve regional climate projections and strengthen the ability of decision makers to assess the future risks associated with extreme precipitation events in the region.

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Section: Spatial Variability Of Duration and Intensity-based Indicesmentioning

confidence: 99%

Evaluation of extreme precipitation events as simulated by CMIP6 models over Central Africa: spatial variability

Komelo,

Fotso-Nguemo,

Ngavom

et al. 2024

Preprint

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“…Little is known about the frequencies of specific winds (e.g., westerlies) from various reanalysis products. There also do not appear to be any systematic validation studies of lower‐troposphere winds from reanalyses, and this is important because reanalyses are used to test the validity of climate models (Taguela et al, 2022). Therefore, the objectives of this study are to (1) assess differences in wind directions among multiple reanalysis products and (2) compare reanalysis winds with winds measured at weather stations.…”

Section: Introductionmentioning

confidence: 99%

Comparisons of reanalysis and measured lower‐troposphere winds over a portion of equatorial Africa

Diem,

Salerno,

Bailey

et al. 2023

Intl Journal of Climatology

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Despite lower‐troposphere wind flow being a major control of rainfall in equatorial Africa, no studies have systematically compared winds from multiple reanalyses nor have attempted to validate the wind directions. Therefore, the objectives of this study are to assess differences in wind directions among multiple reanalysis products and compare reanalysis winds with wind measurements made at weather stations. The study region is western Uganda, part of the transition region between western equatorial Africa (WEA) and eastern equatorial Africa (EEA). Four‐times daily (i.e., 0Z, 6Z, 12Z and 18Z) 10‐m and 850‐hPa winds from 1980 to 2021 are obtained for ECMWF Reanalysis v5 (ERA5), Japan Meteorological Agency 55‐year Reanalysis (JRA55), Modern‐Era Retrospective analysis for Research and Applications Version 2 (MERRA2), NCEP‐NCAR Reanalysis 1 (R1) and NCEP/DOE Reanalysis II (R2). Wind measurements at 10 m and 850 hPa are obtained for six weather stations and two weather stations, respectively. Agreements between pairs of products and between measurements and reanalysis estimates are determined. In addition, differences between reanalyses and measurements with respect to wind vectors are calculated. Results show that the majority of reanalyses have western Uganda within the prevailing easterly flow over EEA and east of the prevailing westerly flow over WEA. Ten‐meter wind measurements also show easterly flow being prevalent throughout western Uganda. R1 is unique among the products due to a relatively large number of westerly days. However, much of the westerly flow is likely artificial, based on station data. MERRA2 has large easterly biases. JRA55 is much more accurate than the other products at reproducing the intra‐annual frequencies of wind directions. JRA55 and ERA5 are the least biased products based on the magnitudes of difference vectors. Therefore, it is recommended that JRA55 and ERA5 continue to be used in examinations of winds in western Uganda.

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“…Nevertheless, global models from the Coupled Model Inter-comparison Project (CMIP) phase 5 (CMIP5) appear to poorly reproduce regional rainfall distribution during the September to November (SON) rainy season (Creese and Washington 2018). The difficulty in simulating rainfall over the region may be partly due to the complexity of Central African climate processes which are not well represented in coupled models Washington 2016, 2018;Crowhurst et al 2020Crowhurst et al , 2021Taguela et al 2022b). The interconnection of the Central African climate with the climate of other regions such as southern Africa (Kuete et al 2019;Howard and Washington 2019) may also contribute to the difficulty of models in representing rainfall over the region.…”

Section: Introductionmentioning

confidence: 99%

How do coupled models represent the African Easterly Jets and their associated dynamics over Central Africa during the September–November rainy season?

et al. 2022

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Climate models are vital to the assessment of the impacts of climate change in the Central African regions. Establishing how well models reproduce key processes is important to the confidence we attach to these tools. This study examines model representation of the September to November characteristics, such as location and intensity, of the African Easterly Jet (AEJ) north and south in a sample of 16 commonly evaluated CMIP5 and CMIP6 models and in two reanalyses (ERA5 and MERRA2). The analysis evolves to assess key drivers of the AEJ from energetic interactions, the characteristics of mid-level highs and thermal lows and the nature of surface thermal heating. Over West Africa, several models miss the southeast-northwest orientation of the AEJ-N core, leading to a gap of around 60 in the location of the jet while most CMIP5 models also fail to locate AEJ-S over southern Central Africa. In general, the spread of simulated AEJ locations around reanalyses is larger for the CMIP5 sample compared to CMIP6 equivalent models, indicating improvement from CMIP5 to CMIP6 in this 16 model subset. However, this improvement in some CMIP6 models (e.g. GISS-E2-1-G and MIROC6) is not related to a maximum surface meridional gradient in temperature. Most CMIP5 and CMIP6 models underestimate the surface temperature gradient over AEJ-N region. As a first order diagnostic of the jet's acceleration, most coupled models better simulate the atmospheric energetic interactions over AEJ-N region that leads to its strong contribution to AEJ-N maintenance compared to AEJ-S. This study strengthens our understanding of the mid-level circulation over Central Africa by detecting gaps in the mechanisms maintaining the AEJ in coupled models and highlights processes that should be improved in future ensembles.

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Low-level circulation over Central Equatorial Africa as simulated from CMIP5 to CMIP6 models

Cited by 7 publications

References 46 publications

Evaluation of extreme precipitation events as simulated by CMIP6 models over Central Africa: spatial variability

Evaluation of extreme precipitation events as simulated by CMIP6 models over Central Africa: spatial variability

Comparisons of reanalysis and measured lower‐troposphere winds over a portion of equatorial Africa

How do coupled models represent the African Easterly Jets and their associated dynamics over Central Africa during the September–November rainy season?

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