Special Issue "Precipitation Variability and Change in Africa"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology and Meteorology".

Deadline for manuscript submissions: closed (28 February 2018)

Special Issue Editor

Guest Editor
Dr. Martin Stendel

Danish Meteorological Institute, Copenhagen, Denmark.
Website | E-Mail
Interests: climate variability and change; regional climate modelling with a focus on Africa; precipitation and the hydrological cycle over East Africa; critical appraisal of observations datasets

Special Issue Information

Dear Colleagues,

Sub-Saharan Africa is one of the most vulnerable regions to climate change, while, at the same time, several aspects of regional climate dynamics are still poorly understood. Projections of climate change using global circulation models (GCMs) generally agree on a temperature increase of 3 to 4 °C by the end of the 21st century. However, the projections of precipitation patterns, arguably the most important single climate variable in large parts of Africa, differ considerably between models due to model physics, resolution and the parameterization of subgrid-scale (e.g., convective) processes. In particular, differences in the treatment of soil moisture between models seem to play a crucial role. Changes in the onset and decay of the rainy season(s) have been documented, and some models even project a transition from a unimodal rainfall region (characterizing the inner tropics under present-day climate) to a bimodal regime with two dry and two wet seasons. As farming in most regions of sub-Saharan Africa is closely linked to the occurrence and timing of sufficient rainfall, the onset, length, precipitation amount and reliability of the rainy season will have a large effect on crop productivity and harvest.

This Special Issue aims at advancing our current knowledge on African precipitation and its past and future changes. Articles addressing modeling issues, both with GCMs or downscaled regional scenarios, as well as aspects of model physics and parameterization are welcome. As there is a lack of observations in many parts of Africa, analyses of observations or of historical data are especially encouraged. Further, articles on precipitation characteristics, such as timing of dry and wet seasons, rainfall regimes, and their changes are welcome.

Dr. Martin Stendel
Guest Editor

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Keywords

  • Sub-Saharan Africa

  • modelling and observation of precipitation and the hydrological cycle

  • stability of the onset, decay, duration

  • reliability of the wet season and its amount of precipitation

  • rainfall regimes and their variability over time

  • modelling aspects of African precipitation

Published Papers (6 papers)

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Open AccessArticle Improving Quantitative Rainfall Prediction Using Ensemble Analogues in the Tropics: Case Study of Uganda
Atmosphere 2018, 9(9), 328; https://doi.org/10.3390/atmos9090328
Received: 25 December 2017 / Revised: 26 March 2018 / Accepted: 7 April 2018 / Published: 22 August 2018
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Abstract
Accurate and timely rainfall prediction enhances productivity and can aid proper planning in sectors such as agriculture, health, transport and water resources. However quantitative rainfall prediction is normally a challenge and for this reason, this study was conducted with an aim of improving
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Accurate and timely rainfall prediction enhances productivity and can aid proper planning in sectors such as agriculture, health, transport and water resources. However quantitative rainfall prediction is normally a challenge and for this reason, this study was conducted with an aim of improving rainfall prediction using ensemble methods. It first assessed the performance of six convective schemes (Kain–Fritsch (KF); Betts–Miller–Janjić (BMJ); Grell–Fretas (GF); Grell 3D ensemble (G3); New–Tiedke (NT) and Grell–Devenyi (GD)) using the root mean square error (RMSE) and mean error (ME) focusing on the March–May 2013 rainfall period over Uganda. 18 ensemble members were then generated from the three best performing convective schemes (i.e., KF, GF and G3). The daily rainfall predicted by the three ensemble methods (i.e., ensemble mean (ENS); ensemble mean analogue (EMA) and multi–member analogue ensemble (MAEM)) was then compared with the observed daily rainfall and the RMSE and ME computed. The results shows that the ENS presented a smaller RMSE compared to individual schemes (ENS: 10.02; KF: 23.96; BMJ: 26.04; GF: 25.85; G3: 24.07; NT: 29.13 and GD: 26.27) and a better bias (ENS: −1.28; KF: −1.62; BMJ: −4.04; GF: −3.90; G3: −3.62; NT: −5.41 and GD: −4.07). The EMA and MAEM presented 13 out of 21 stations and 17 out of 21 stations respectively with smaller RMSE compared to ENS thus demonstrating additional improvement in predictive performance. This study proposed and described MAEM and found it producing comparatively better quantitative rainfall prediction performance compared to the other ensemble methods used. The MAEM method should be valid regardless the nature of the rainfall season. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessArticle Long-Term Rainfall Trends over the Tanzania Coast
Atmosphere 2018, 9(4), 155; https://doi.org/10.3390/atmos9040155
Received: 28 February 2018 / Revised: 30 March 2018 / Accepted: 4 April 2018 / Published: 20 April 2018
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Abstract
Spatial and temporal rainfall trends over the Tanzanian coast are analysed and trends for over 50 years are investigated. This type of study is crucial at this time because the area under study is now one of the world’s economic hotspots, as major
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Spatial and temporal rainfall trends over the Tanzanian coast are analysed and trends for over 50 years are investigated. This type of study is crucial at this time because the area under study is now one of the world’s economic hotspots, as major gas fields have been discovered and the area also has high potential for oil field discoveries. Methods applied in this study include the Mann-Kendall test for rainfall data to detect the long-term trends, while Sen’s slope estimator test was used for finding the magnitude of change over time. The results exhibited rainfall trend patterns with substantial variations between the stations. The Z value of the Mann-Kendall test showed various months with negative trend at a significance level ≥95%. The few months that showed a positive trend were not statistically significant. Generally, rainfall trends varied in different months for different stations. However, the most outstanding observation on individual months is July, which showed a highly statistically significant (99.9%) reduction in rainfall for the whole coastal area, including the regions of Mtwara, Dar es Salaam and Tanga. The last part of this paper describes the relationship between July rainfall and the horizontal winds from the National Centre for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) re-analysis. It is observed that the strength of the anticyclonic flow over the southwest Indian Ocean, which is associated with the westward fluxes of moisture, is responsible for rainfall over the whole coastal area of Tanzania during July. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessArticle Precipitation Extremes in Dynamically Downscaled Climate Scenarios over the Greater Horn of Africa
Atmosphere 2018, 9(3), 112; https://doi.org/10.3390/atmos9030112
Received: 11 November 2017 / Revised: 24 February 2018 / Accepted: 13 March 2018 / Published: 18 March 2018
Cited by 1 | PDF Full-text (26835 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study first assesses the performance of regional climate models in the Coordinated Regional Climate Downscaling Experiment (CORDEX) in reproducing observed extreme precipitation indices over the Greater Horn of Africa (GHA) region during 1989–2005. The study then assesses projected changes in these extremes
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This study first assesses the performance of regional climate models in the Coordinated Regional Climate Downscaling Experiment (CORDEX) in reproducing observed extreme precipitation indices over the Greater Horn of Africa (GHA) region during 1989–2005. The study then assesses projected changes in these extremes during 2069–2098 compared to 1976–2005. The Regional Climate Model (RCM) simulations are made using two RCMs, with large-scale forcing from four CMIP5 Global limate Models(GCMs) under two Representative Concentration Pathways (RCP4.5 and RCP8.5). We found that RCM simulations have reasonably captured observed patterns of moderate precipitation extreme indices (MPEI). Pattern correlation coefficients between simulated and observed MPEI exceed 0.5 for all except the Simple Daily Intensity Index (SDII). However, significant overestimations or underestimations exist over localized areas in the region. Projected changes in Total annual Precipitation (PRCPTOT) and the annual number of heavy (>10 mm) and very heavy (>20 mm) precipitation days by 2069–2098 show a general north-south pattern, with decreases over the southern half and increases over the northern half of the GHA. These changes are often greatest over parts of Somalia, Eritrea, the Ethiopian highlands and southern Tanzania. Maximum one- and five-day precipitation totals over a year and SDII (ratio of PRCPTOT to rainy days) are projected to increase over a majority of the GHA, including areas where PRCPTOT is projected to decrease, suggesting fewer, but heavier rainy days in the future. Changes in the annual sum of daily precipitation above the 95th and 99th percentiles are statistically significant over a few locations, with the largest projected decrease/increase over Eritrea and northwestern Sudan/Somalia. Projected changes in Consecutive Dry Days (CDD) suggest longer periods of dryness over the majority of the GHA, except the central portions covering northern Uganda, southern South Sudan, southeastern Ethiopia and Somalia. Substantial increases in CDD are located over southern Tanzania and the Ethiopian highlands. The magnitude and the spatial extent of statistically-significant changes in all MPEI increase from RCP4.5 to RCP8.5, and the separation between positive and negative changes becomes clearer under RCP8.5. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessArticle Utilization of Global Precipitation Datasets in Data Limited Regions: A Case Study of Kilombero Valley, Tanzania
Atmosphere 2017, 8(12), 246; https://doi.org/10.3390/atmos8120246
Received: 3 October 2017 / Revised: 16 November 2017 / Accepted: 27 November 2017 / Published: 7 December 2017
Cited by 1 | PDF Full-text (10981 KB) | HTML Full-text | XML Full-text | Correction | Supplementary Files
Abstract
This study explored the potential for bias correction of global precipitation datasets (GPD) to support streamflow simulation for water resource management in data limited regions. Two catchments, 580 km2 and 2530 km2, in the Kilombero Valley of central Tanzania were
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This study explored the potential for bias correction of global precipitation datasets (GPD) to support streamflow simulation for water resource management in data limited regions. Two catchments, 580 km2 and 2530 km2, in the Kilombero Valley of central Tanzania were considered as case studies to explore three GPD bias correction methods: quantile mapping (QM), daily percentages (DP) and a model based (ModB) bias correction. The GPDs considered included two satellite rainfall products, three reanalysis products and three interpolated observed data products. The rainfall-runoff model HBV was used to simulate streamflow in the two catchments using (1) observed rain gauge data; (2) the original GPDs and (3) the bias-corrected GPDs as input. Results showed that applying QM to bias correction based on limited observed data tends to aggravate streamflow simulations relative to not bias correcting GPDs. This is likely due to a potential lack of representativeness of a single rain gauge observation at the scale of a hydrological catchment for these catchments. The results also indicate that there may be potential benefits in combining streamflow and rain gauge data to bias correct GPDs during the model calibration process within a hydrological modeling framework. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessArticle Variability of Precipitation in Arid Climates Using the Wavelet Approach: Case Study of Watershed of Gabes in South-East Tunisia
Atmosphere 2017, 8(9), 178; https://doi.org/10.3390/atmos8090178
Received: 20 July 2017 / Revised: 7 September 2017 / Accepted: 15 September 2017 / Published: 20 September 2017
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Abstract
This study examines the variability of precipitation in the south-east of Tunisia through the analysis of data about annual and monthly precipitation at five stations in the Watershed of Gabes, from 1977 to 2015. Standardized precipitation ratio, wavelet and coherence wavelet analyses were
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This study examines the variability of precipitation in the south-east of Tunisia through the analysis of data about annual and monthly precipitation at five stations in the Watershed of Gabes, from 1977 to 2015. Standardized precipitation ratio, wavelet and coherence wavelet analyses were applied to examine the temporal variability of monthly and annual precipitation and to determine the effect of climatic fluctuations on rainfall variability. Results of wavelet analysis showed varied energy bands at the studied stations at annual and inter-annual scales. The depicted bands spread according to intervals of 1-, 2- to 4-, 4- to 8- and 8- to 12-year cycles, obviously influenced by regional factors including altitude, proximity to the Mediterranean Sea and global fluctuations. Eventually, an analysis of wavelet coherence showed a strong correlation between precipitation and Mediterranean Oscillation (MO) in Gabes Watershed at different temporal scales. Contribution of the MO ranged between 51% and 93% of fluctuations (8–12 years) in the different examined rainfall stations. Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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Open AccessCorrection Correction: Koutsouris et al. Utilization of Global Precipitation Datasets in Data Limited Regions: A Case Study of Kilombero Valley, Tanzania. Atmosphere, 2017, 8, 246
Atmosphere 2018, 9(4), 148; https://doi.org/10.3390/atmos9040148
Received: 3 April 2018 / Revised: 3 April 2018 / Accepted: 3 April 2018 / Published: 16 April 2018
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Abstract
The authors would like to correct the published article [1], following the detection of editorial mistakes by the main author, as explained below[...] Full article
(This article belongs to the Special Issue Precipitation Variability and Change in Africa)
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