The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016)
The Australian and African continents, regions prone to hydroclimate extremes (e.g., droughts and floods), but with sparse distribution of rain-gauge that are limited in time, rely heavily on complementary satellite and reanalysis data to provide important crucial information necessary for informing...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | English |
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ELSEVIER SCIENCE BV
2019
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/86613 |
| _version_ | 1848764844637945856 |
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| author | Awange, Joseph Hu, K.X. Khaki, M. |
| author_facet | Awange, Joseph Hu, K.X. Khaki, M. |
| author_sort | Awange, Joseph |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The Australian and African continents, regions prone to hydroclimate extremes (e.g., droughts and floods), but with sparse distribution of rain-gauge that are limited in time, rely heavily on complementary satellite and reanalysis data to provide important crucial information necessary for informing policies and management. The problem, however, is that satellite products suffer from systematic biases while reanalysis products carry over uncertainties from their forcing parameters. Multi-Source Weighted-Ensemble Precipitation (MSWEP) is a new global rainfall-product that merges satellite, rain-gauge and re-analysis data to exploit their advantages and minimise their disadvantages. Although MSWEP has been validated globally, this product, together with its potential applications, e.g., in water storage fluxes, river discharge and climate impacts studies over Australia and Africa, regions with urgent need of reliable products, has however, not been verified. Using GRACE satellite products, GLDAS model data, GRDC runoff products, and ENSO/IOD climate indices; five rainfall products - FLUXNET, BoM, GPCC, CHIRPS, and AgCFSR; and a suite of statistical methods (Pearson, Kolmogorov-Smirnov, PCA and Three-Corner-Hat (TCH)), this study (i) evaluates monthly MSWEP-V2.1 data (1981–2016), and (ii), assesses its potential applications to water storage flux (within the water balance framework), river discharge analysis, and climate impacts studies. The results show good MSWEP correlations and cumulative distribution with BoM product over most of Australia except in regions with heavy monsoonal rainfall, e.g., northern and north-western Australia where it tends to underestimate. Over Africa, MSWEP has no obvious advantages compared to insitu-GPCC, satellite-CHIRPS or reanalysis-AgCFSR. Furthermore, it is unable to reflect on major hydro-climate extremes over west, east and southern Africa, where it underestimates compared to CHIRPS. Its potential applications to water storage flux, discharge and climate impacts over the two continents show better suitability for water storage flux in Africa, while no advantages are seen compared to other rainfall products on other aspects. |
| first_indexed | 2025-11-14T11:25:49Z |
| format | Journal Article |
| id | curtin-20.500.11937-86613 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:25:49Z |
| publishDate | 2019 |
| publisher | ELSEVIER SCIENCE BV |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-866132021-12-06T02:47:34Z The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) Awange, Joseph Hu, K.X. Khaki, M. Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Australia Africa Precipitation MSWEP Evaluation TERRESTRIAL WATER STORAGE WEST-AFRICA GLOBAL PRECIPITATION GREATER HORN RAINFALL CLIMATE DROUGHTS PRODUCTS TRMM DATASETS The Australian and African continents, regions prone to hydroclimate extremes (e.g., droughts and floods), but with sparse distribution of rain-gauge that are limited in time, rely heavily on complementary satellite and reanalysis data to provide important crucial information necessary for informing policies and management. The problem, however, is that satellite products suffer from systematic biases while reanalysis products carry over uncertainties from their forcing parameters. Multi-Source Weighted-Ensemble Precipitation (MSWEP) is a new global rainfall-product that merges satellite, rain-gauge and re-analysis data to exploit their advantages and minimise their disadvantages. Although MSWEP has been validated globally, this product, together with its potential applications, e.g., in water storage fluxes, river discharge and climate impacts studies over Australia and Africa, regions with urgent need of reliable products, has however, not been verified. Using GRACE satellite products, GLDAS model data, GRDC runoff products, and ENSO/IOD climate indices; five rainfall products - FLUXNET, BoM, GPCC, CHIRPS, and AgCFSR; and a suite of statistical methods (Pearson, Kolmogorov-Smirnov, PCA and Three-Corner-Hat (TCH)), this study (i) evaluates monthly MSWEP-V2.1 data (1981–2016), and (ii), assesses its potential applications to water storage flux (within the water balance framework), river discharge analysis, and climate impacts studies. The results show good MSWEP correlations and cumulative distribution with BoM product over most of Australia except in regions with heavy monsoonal rainfall, e.g., northern and north-western Australia where it tends to underestimate. Over Africa, MSWEP has no obvious advantages compared to insitu-GPCC, satellite-CHIRPS or reanalysis-AgCFSR. Furthermore, it is unable to reflect on major hydro-climate extremes over west, east and southern Africa, where it underestimates compared to CHIRPS. Its potential applications to water storage flux, discharge and climate impacts over the two continents show better suitability for water storage flux in Africa, while no advantages are seen compared to other rainfall products on other aspects. 2019 Journal Article http://hdl.handle.net/20.500.11937/86613 10.1016/j.scitotenv.2019.03.148 English ELSEVIER SCIENCE BV restricted |
| spellingShingle | Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Australia Africa Precipitation MSWEP Evaluation TERRESTRIAL WATER STORAGE WEST-AFRICA GLOBAL PRECIPITATION GREATER HORN RAINFALL CLIMATE DROUGHTS PRODUCTS TRMM DATASETS Awange, Joseph Hu, K.X. Khaki, M. The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) |
| title | The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) |
| title_full | The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) |
| title_fullStr | The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) |
| title_full_unstemmed | The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) |
| title_short | The newly merged satellite remotely sensed, gauge and reanalysis-based Multi-Source Weighted-Ensemble Precipitation: Evaluation over Australia and Africa (1981–2016) |
| title_sort | newly merged satellite remotely sensed, gauge and reanalysis-based multi-source weighted-ensemble precipitation: evaluation over australia and africa (1981–2016) |
| topic | Science & Technology Life Sciences & Biomedicine Environmental Sciences Environmental Sciences & Ecology Australia Africa Precipitation MSWEP Evaluation TERRESTRIAL WATER STORAGE WEST-AFRICA GLOBAL PRECIPITATION GREATER HORN RAINFALL CLIMATE DROUGHTS PRODUCTS TRMM DATASETS |
| url | http://hdl.handle.net/20.500.11937/86613 |