Projected changes in the seasonal cycle of extreme rainfall events from CORDEX simulations over Central Africa

Fotso‐Nguemo, Thierry C.; Diallo, Ismaïla; Diakhaté, Moussa; Vondou, Derbetini A.; Mbaye, Mamadou; Haensler, Andreas; Gaye, Amadou Thierno; Tchawoua, Clément

doi:10.1007/s10584-019-02492-9

Cited by 33 publications

(22 citation statements)

References 44 publications

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“…The many future changes analyses in extreme precipitation were based on the simulations of regional climate models. Most of the regional climate model validations show that they are performing reasonably well in reproducing the spatial patterns of observed precipitation (DeGateano and Castellano, 2017;Fotso-Nguemo et al, 2019;Harpa et al, 2019;Janković et al, 2019;Jiang et al, 2012;Kjellström and Ruosteenoja, 2007;Li et al, 2019;Mihailović et al, 2016). Therefore, they provide a reliable basis for the forecasting of future precipitation and other climate indices.…”

Section: Datamentioning

confidence: 95%

“…All of the disasters caused economic damage and also took away a huge number of humans lives. Because of that, many worldwide studies of climate changes and their impact on different aspects of the environment, have been performed so far, and their number is still growing today (Aktar, 2013;Cavicchia et al, 2018;Cooper, 2019;DeGateano and Castellano, 2017;Fotso-Nguemo et al, 2019;Huang, Wang et al, 2018;Soltani et al, 2016;Tan et al, 2017). Among them, those related to temperature and precipitation extremes play an important role.…”

Section: Introductionmentioning

confidence: 99%

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Future changes in extreme precipitation in central Serbia

Erić

Kadović

Djurdjević

et al. 2021

Journal of Hydrology and Hydromechanics

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This paper presents the results of a study focused on the projected changes in extreme precipitation during the 21st century in Central Serbia. The changes are investigated on the basis of historical and modelled data sets of daily precipitation. The historical observation data were recorded at 18 synoptic weather stations in Central Serbia and modelled data were extracted from the regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model) under the A1B scenario. The average number of days in a year with precipition ≥ 20, 30, 40 and 50 mm (R20, R30, R40 and R50), the share of daily precipitation above the 20, 30, 40 and 50 mm (P20, P30, P40, P50) in the total annual precipitation and the monthly distribution of these heavy daily precipitation are used as indices of changes in extreme precipitation. These indices, for the three periods 2011–2040, 2041–2070 and 2071–2100, are determined and compared with those obtained for the historical reference period 1961–1990. The results have shown that the main changes in extreme precipitation in Central Serbia will be in their spatial distribution, and the uncertainty of the occurrence of extreme events will decrease. In the future the increase will be more pronounced than the decrease of these indices. We strongly emphasize the benefit of this paper for both the prevention of natural disasters in the study area and for the improvement of the regional climate model.

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Section: Datamentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Future changes in extreme precipitation in central Serbia

Erić

Kadović

Djurdjević

et al. 2021

Journal of Hydrology and Hydromechanics

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“…Given the fact that frequency and intensity of rainy days are major sources which highly contribute to total precipitation (Camberlin et al, 2009), and that only intensity of rainy days is strongly underestimated by the model during most seasons, it appears that the dry biases reported in Figures 2m-p and 4 are likely connected to the less intense events simulated by the model. It is worth to mention that the CCLM's behaviour to simulate too much rainy days but less intense events is typical of most GCMs and RCMs models (Crétat et al, 2014;Diallo et al, 2016;Vondou and Haensler, 2017;Sonkoué et al, 2018;Fotso-Nguemo et al, 2019;Tamoffo et al, 2019b). Figures 8 and 9 present, respectively, the seasonal mean patterns of LWS and LDS from GPCP, TRMM, ERAINT and CCLM, averaged over the period 1998-2008.…”

Section: Daily Extreme Indicesmentioning

confidence: 99%

“…The model-simulated precipitation is compared against two satellite-derived observational datasets: (a) the Global Precipitation Climatology Project 1DD (GPCP version 1.2; Huffman et al, 2009) and (b) the Tropical Rainfall Measurement Mission 3B42 (TRMM-3B42 version 7; Huffman et al, 2010). GPCP and TRMM have been chosen because they represent the best available daily precipitation map over the CA region (Diallo et al, 2015;Camberlin et al, 2019;Fotso-Nguemo et al, 2019;Nicholson et al, 2019). GPCP 1DD is available from October 1996 to near present on a spatial scale of 1 × 1 of longitude and latitude.…”

Section: Datasetsmentioning

confidence: 99%

“…Daily precipitation characteristics have been evaluated based on six selected indicators of hydro-climatic extremes (listed in Table 1), which have already demonstrated their effectiveness over the globe (Sillmann et al, 2013;Giorgi et al, 2019), Europe (Dosio and Fischer, 2018) and several regions of Africa (e.g., Diallo et al, 2016;Klutse et al, 2016;Pinto et al, 2016;Pokam et al, 2018;Sonkoué et al, 2018;Fotso-Nguemo et al, 2019). It is worth mentioning that for the computation of the daily precipitation characteristics, we have also carried out tests by varying the rainy day threshold from 1 to 3 mm/ day.…”

Section: Statistical Metricsmentioning

confidence: 99%

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An evaluation of COSMO‐CLM regional climate model in simulating precipitation over Central Africa

Fotso‐Nguemo

Diallo

Pokam

et al. 2019

Intl Journal of Climatology

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In this study, an analysis of present day climate simulation (1998–2008) is presented for the Central African (CA) region with the COnsortium for Small‐scale MOdelling in CLimate Mode (CCLM) regional climate model, forced by the ERA‐Interim (ERAINT) reanalysis data. The ability of the CCLM to simulate the observed precipitation with particular focus on the mean spatial pattern, low‐level circulation, seasonal cycles, and daily characteristics is evaluated. Likewise, the added value of the regional model CCLM compared to the driving ERAINT reanalysis is also investigated. It is shown that ERAINT and CCLM exhibit quite different sign of bias, which is an indication of the importance of internal variability and fine scale processes representation for the simulation of surface climate. Despite the CCLM is constantly dry over southern CA, the model succeeds to reproduce reasonably the mean spatial patterns of precipitation and low‐level circulation features, along with the associated seasonal cycles over the whole CA and majority of the five selected analysis sub‐regions. Results also show that daily precipitation indices are well represented, although the better performance greatly depends on the considered seasons. Nevertheless, CCLM substantially outperforms the ERAINT daily precipitation characteristics, thus highlighting the added value of the downscaling exercise over the region. The analysis of daily precipitation indices also reveals that the dry character of the model could probably be connected to the underestimation of the simulated less intense events, which in turn result to an overestimation of the simulated dry spell duration.

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Develop medium‐ to long‐term climate information services to enhance comprehensive climate risk management in Africa

et al. 2023

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Increasing climate change risks in Africa, emerging from global warming and their interaction with non‐climate risks such as market, have increased the need for comprehensive Climate Risk Management (CRM) that considers both climatic and non‐climatic risks and enables actions that address the underlying drivers of vulnerability to these risks. However, comprehensive CRM requires holistic Climate Information Services (CIS), that is, CIS that balances between components focused on provision of short‐ and long‐term climate information for both local and non‐local decision makers. In this article, we ask: to what extent is CIS in Africa holistic? We review recent and ongoing CIS interventions in Africa to determine whether a balance of components between short‐ and long‐term CIS for local and non‐local decision makers is achieved for holistic CIS. We find a focus on provision of short‐term, that is, Sub‐Seasonal‐to‐Seasonal (S2S) CIS for local and non‐local decision makers, with limited focus on medium‐ to long‐term (MLT) CIS, particularly MLT CIS for local decision makers which represents the biggest gap to achieving holistic CIS in Africa. We present a supported case that ensuring holistic CIS in Africa will require a portfolio‐based approach to CIS development, particularly focusing on MLT CIS for local decision makers. We further highlight the need for integration of this MLT CIS for local decision makers into existing CIS. Achieving this will require: (a) experimentation and innovation with different CIS formats, products and timeframes to enable learning and flexibility to achieve desired goals; (b) capacity development of producers and consumers of climate information to ensure that they have the skills and expertise to understand and generate, and articulate needs and consume MLT CIS respectively; and (c) coordinated allocation of financial resources to ensure that all components of the holistic CIS are advanced.

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Projected changes in the seasonal cycle of extreme rainfall events from CORDEX simulations over Central Africa

Cited by 33 publications

References 44 publications

Future changes in extreme precipitation in central Serbia

Future changes in extreme precipitation in central Serbia

An evaluation of COSMO‐CLM regional climate model in simulating precipitation over Central Africa

Develop medium‐ to long‐term climate information services to enhance comprehensive climate risk management in Africa

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