Extreme precipitation indices over the Volta Basin: CMIP6 model evaluation

• DOI: 10.1016/j.sciaf.2022.e01181
• Publication Date: 2022-05-12T03:09:32Z
• Authors: Jacob Agyekum; Thompson Annor; Emmanuel Quansah; Benjamin Lamptey; Gloria Okafor
• Keywords: Volta Basin; Atmospheric Science; Hydrological Modeling; Science; Climate Change and Variability Research; Precipitation; Coupled model intercomparison project; Climate model; 01 natural sciences; Environmental science; Precipitation indices; Satellite-Based Precipitation Estimation and Validation; Livelihood; Meteorology; Extreme Events; Climate change; Biology; 0105 earth and related environmental sciences; Climatology; Global and Planetary Change; Geography; Ecology; Q; Annual trend; Paleontology; Agriculture; Geology; FOS: Earth and related environmental sciences; Numerical Weather Prediction Models; Flood myth; CMIP6 evaluation; Structural basin; Earth and Planetary Sciences; Climate extremes; Archaeology; FOS: Biological sciences; Environmental Science; Physical Sciences; Probabilistic Forecasting; Climate Modeling; Precipitation Extremes

Climate extreme events affect people whose livelihoods are reliant on the water resources of the Volta Basin in West Africa. Therefore, decision-makers and policymakers need reliable predictions of these extremes on several time scales to develop an Early Warning System (EWS) to combat the devastating impact of extreme climatic events. In that vein, the study evaluated the performance of 41 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating six (6) extreme precipitation events developed by the Expert Team on Climate Change Detection and Indices (ETCCDI), over the Volta Basin for the period 1985–2014. The spatial biases as well as the temporal variations of the indices were analyzed using the simple bias and the Kling-Gupta Efficiency (KGE) respectively. Subsequently, the best models (models with low biases and KGE close to 1) were used to analyze the trends. The modified Mann-Kendall test showed an increasing trend in the observd heavy and very heavy rainy days (R10 mm and R20 mm), very wet and extremely wet days (R95p and R99p) but decreasing trend in the consecutive wet and dry days (CWD and CDD). Generally, models had difficulty reproducing the tempor patterns, however, the MPI-ESM1-2-LR, reproduced well the observéd CDD, R10 mm and R20 mm whereas, the IITM-ESM, TaiESM1 and the CMCC-CM2-SR5 reproduced CWDs, R95p and R99p respectively. The Ensemble mean of the models showed robust performance in reproducing the observéd R95p and R99p. The future evolution of these extreme poses threats to agriculture, and flood occurrence over the basin.<br/>Climate extreme events affect people whose livelihoods are reliant on the water resources of the Volta Basin in West Africa. Therefore, decision-makers and policymakers need reliable predictions of these extremes on several time scales to develop an Early Warning System (EWS) to combat the devastating impact of extreme climatic events. In that vein, the study evaluated the performance of 41 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating six (6) extreme precipitation events developed by the Expert Team on Climate Change Detection and Indices (ETCCDI), over the Volta Basin for the period 1985–2014. The spatial biases as well as the temporal variations of the indices were analyzed using the simple bias and the Kling-Gupta Efficiency (KGE) respectively. Subsequently, the best models (models with low biases and KGE close to 1) were used to analyze trends. The modified Mann-Kendall test showed an increasing trend in the observed heavy and very heavy rainy days (R10 mm and R20 mm), very wet and extremely wet days (R95p and R99p) but decreasing trend in the consecutive wet and dry days (CWD and CDD). Generally, models had difficulty reproducing the temporal patterns, however, the MPI-ESM1-2-LR, reproduced well the observed CDD, R10 mm and R20 mm whereas, the IITM-ESM, TaiESM1 and the CMCC-CM2-SR5 reproduced CWDs, R95p and R99p respectively. The Ensemble mean of the models showed robust performance in reproducing the observed R95p and R99p. The future evolution of these extreme poses threats to agriculture, and flood occurrence over the basin.<br/>Climate extreme events affect people whose livelihoods are reliant on the water resources of the Volta Basin in West Africa. Therefore, decision-makers and policymakers need reliable predictions of these extremes on several time scales to develop an Early Warning System (EWS) to combat the devastating impact of extreme climatic events. In that vein, the study evaluated the performance of 41 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating six (6) extreme precipitation events developed by the Expert Team on Climate Change Detection and Indices (ETCCDI), over the Volta Basin for the period 1985–2014. The spatial biases as well as the temporal variations of the indices were analyzed using the simple bias and the Kling-Gupta Efficiency (KGE) respectively. Subsequently, the best models (models with low biases and KGE close to 1) were used to analyze the trends. The modified Mann-Kendall test showed an increasing trend in the observed heavy and very heavy rainy days (R10 mm and R20 mm), very wet and extremely wet days (R95p and R99p) but decreasing trend in the consecutive wet and dry days (CWD and CDD). Generally, models had difficulty reproducing the temporal patterns, however, the MPI-ESM1-2-LR, reproduced well the observed CDD, R10 mm and R20 mm whereas, the IITM-ESM, TaiESM1 and the CMCC-CM2-SR5 reproduced CWDs, R95p and R99p respectively. The Ensemble mean of the models showed robust performance in reproducing the observed R95p and R99p. The future evolution of these extreme poses threats to agriculture, and flood occurrence over the basin.<br/>تؤثر الأحداث المناخية المتطرفة على الأشخاص الذين تعتمد سبل عيشهم على الموارد المائية لحوض فولتا في غرب إفريقيا. لذلك، يحتاج صانعو القرار وصانعو السياسات إلى تنبؤات موثوقة بهذه الظواهر المتطرفة على عدة نطاقات زمنية لتطوير نظام إنذار مبكر لمكافحة التأثير المدمر للأحداث المناخية المتطرفة. في هذا السياق، قيمت الدراسة أداء 41 نموذجًا من المرحلة السادسة من مشروع المقارنة بين النماذج المقترنة (CMIP6) في محاكاة ستة (6) أحداث هطول أمطار شديدة طورها فريق الخبراء المعني بكشف تغير المناخ ومؤشراته (ETCCDI)، على حوض فولتا للفترة 1985–2014. تم تحليل التحيزات المكانية وكذلك الاختلافات الزمنية للمؤشرات باستخدام التحيز البسيط وكفاءة Kling - Gupta (KGE) على التوالي. بعد ذلك، تم استخدام أفضل النماذج (النماذج ذات التحيزات المنخفضة و KGE القريبة من 1) لتحليل الاتجاهات. أظهر اختبار Mann - Kendall المعدل اتجاهًا متزايدًا في الأيام الممطرة الغزيرة والغزيرة جدًا (R10 مم و R20 مم)، والأيام الرطبة جدًا والرطبة للغاية (R95p و R99p) ولكن الاتجاه يتناقص في الأيام الرطبة والجافة المتتالية (CWD و CDD). بشكل عام، واجهت النماذج صعوبة في إعادة إنتاج الأنماط الزمنية، ومع ذلك، فإن MPI - ESM1 -2 - LR، أعادت إنتاج CDD و R10 مم و R20 مم بشكل جيد، في حين أن IITM - ESM و TaiESM1 و CMCC - CM2 - SR5 أعادت إنتاج CWDs و R95p و R99p على التوالي. أظهر متوسط المجموعة للنماذج أداءً قويًا في إعادة إنتاج R95p و R99p المرصودة. ويشكل التطور المستقبلي لهذه الظواهر المتطرفة تهديدات للزراعة، وحدوث فيضانات فوق الحوض.<br/>Climate extreme events affect people whose livelihoods are reliant on the water resources of the Volta Basin in West Africa. Therefore, decision-makers and policymakers need reliable predictions of these extremes on several time scales to develop an Early Warning System (EWS) to combat the devastating impact of extreme climatic events. In that vein, the study evaluated the performance of 41 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating six (6) extreme precipitation events developed by the Expert Team on Climate Change Detection and Indices (ETCCDI), over the Volta Basin for the period 1985–2014. The spatial biases as well as the temporal variations of the indices were analyzed using the simple bias and the Kling-Gupta Efficiency (KGE) respectively. Subsecuentemente, los mejores modelos (models with low biases and KGE close to 1) were used to analyze the trends. The modified Mann-Kendall test showed an increasing trend in the observed heavy and very heavy rainy days (R10 mm and R20 mm), very wet and extremely wet days (R95p and R99p) but decreasing trend in the consecutive wet and dry days (CWD and CDD). Generally, models had difficulty reproducing the temporal patterns, however, the MPI-ESM1-2-LR, reproduced well the observed CDD, R10 mm and R20 mm whereas, the IITM-ESM, TaiESM1 and the CMCC-CM2-SR5 reproduced CWDs, R95p and R99p respectively. The Ensemble mean of the models showed robust performance in reproducing the observed R95p and R99p. The future evolution of these extreme poses threats to agriculture, and flood occurrence over the basin.<br/>