11 results on '"Kunstmann, Harald"'
Search Results
2. Carbon dioxide fluxes from contrasting ecosystems in the Sudanian Savanna in West Africa
- Author
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Quansah, Emmanuel, Mauder, Matthias, Balogun, Ahmed A, Amekudzi, Leonard K, Hingerl, Luitpold, Bliefernicht, Jan, and Kunstmann, Harald
- Published
- 2015
- Full Text
- View/download PDF
3. Bias correction of daily precipitation for ungauged locations using geostatistical approaches: A case study for the CORDEX‐Africa ensemble
- Author
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Lorenz, Manuel, Bliefernicht, Jan, Kunstmann, Harald, and 1 Institute of Geography University of Augsburg Augsburg Germany
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CORDEX‐Africa ,Atmospheric Science ,Earth sciences ,climate change ,ddc:551.6 ,quantile mapping ,West Africa ,geostatistical approaches ,ddc:550 ,precipitation ,bias correction - Abstract
Climate model simulations typically exhibit a bias, which can be corrected using statistical approaches. In this study, a geostatistical approach for bias correction of daily precipitation at ungauged locations is presented. The method utilizes a double quantile mapping with dry day correction for future periods. The transfer function of the bias correction for the ungauged locations is established using distribution functions estimated by ordinary kriging with anisotropic variograms. The methodology was applied to the daily precipitation simulations of the entire CORDEX‐Africa ensemble for a study region located in the West African Sudanian Savanna. This ensemble consists of 23 regional climate models (RCM) that were run for three different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). The evaluation of the approach for a historical 50‐year period (1950–2005) showed that the method can reduce the inherent strong precipitation bias of RCM simulations, thereby reproducing the main climatological features of the observed data. Moreover, the bias correction technique preserves the climate change signal of the uncorrected RCM simulations. However, the ensemble spread is increased due to an overestimation of the rainfall probability of uncorrected RCM simulations. The application of the bias correction method to the future period (2006–2100) revealed that annual precipitation increases for most models in the near (2020–2049) and far future (2070–2099) with a mean increase of up to 165mm⋅a−1 (18%). An analysis of the monthly and daily time series showed a slightly delayed onset and intensification of the rainy season., Adapting water management strategies to future precipitation projected by climate models is associated with high uncertainty in sparsely gauged catchments. Kriging was utilized to estimate distribution parameters for ungauged locations in a West African region to perform a bias correction of the CORDEX‐Africa ensemble. The application of the bias correction method revealed higher annual precipitation amounts and an intensifaction of the rainy season but only little change to the onset of the rainy season., German Federal Ministry of Education and Research, Bonn (BMBF), West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL)
- Published
- 2022
4. Atmospheric circulation patterns that trigger heavy rainfall in West Africa
- Author
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Bliefernicht, Jan, Rauch, Manuel, Laux, Patrick, Kunstmann, Harald, and 1 Institute of Geography University of Augsburg Augsburg Germany
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circulation pattern ,Atmospheric Science ,Earth sciences ,ddc:551.5 ,classification ,West Africa ,downscaling ,ddc:550 ,heavy rainfall ,ddc:910 - Abstract
Classification of atmospheric circulation patterns (CP) is a common tool for downscaling rainfall, but it is rarely used for West Africa. In this study, a two‐step classification procedure is proposed for this region, which is applied from 1989 to 2010 for the Sudan‐Sahel zone (Central Burkina Faso) with a focus on heavy rainfall. The approach is based on a classification of large‐scale atmospheric CPs (e.g., Saharan Heat Low) of the West African Monsoon using a fuzzy rule‐based method to describe the seasonal rainfall variability. The wettest CPs are further classified using meso‐scale monsoon patterns to better describe the daily rainfall variability during the monsoon period. A comprehensive predictor screening for the seasonal classification indicates that the best performing predictor variables (e.g., surface pressure, meridional moisture fluxes) are closely related to the main processes of the West African Monsoon. In the second classification step, the stream function at 700 hPa for identifying troughs and ridges of tropical waves shows the highest performance, providing an added value to the overall performance of the classification. Thus, the new approach can better distinguish between dry and wet CPs during the rainy season. Moreover, CPs are identified that are of high relevance for daily heavy rainfall in the study area. The two wettest CPs caused roughly half of the extremes on about 6.5% of days. Both wettest patterns are characterized by an intensified Saharan Heat Low and a cyclonic rotation near the study area, indicating a tropical wave trough. Since the classification can be used to condition other statistical approaches used in climate sciences and other disciplines, the presented classification approach opens many different applications for the West African Monsoon region., A two‐step classification of daily atmospheric circulation patterns is used to describe seasonal and daily rainfall variability in West Africa. The approach clearly distinguishes between dry and wet patterns if sea level pressure and stream function at 700 hPa are used. The two wettest patterns trigger about half of heavy rainfall events in Central Burkina Faso. They are characterized by an intensified Saharan Heat Low and a cyclonic rotation indicating a tropical wave trough near the study area., Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
- Published
- 2022
5. Projected Changes in Solar PV and Wind Energy Potential over West Africa: An Analysis of CORDEX-CORE Simulations.
- Author
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Ndiaye, Aissatou, Moussa, Mounkaila Saley, Dione, Cheikh, Sawadogo, Windmanagda, Bliefernicht, Jan, Dungall, Laouali, and Kunstmann, Harald
- Subjects
WIND power ,SOLAR wind ,POTENTIAL energy ,CLIMATE change mitigation ,ENERGY development - Abstract
Renewable energy development is growing fast and is expected to expand in the next decades in West Africa as a contribution to addressing the power demand and climate change mitigation. However, the future impacts of climate change on solar PV and the wind energy potential in the region are still unclear. This study investigates the expected future impacts of climate change on solar PV and wind energy potential over West Africa using an ensemble of three regional climate models (RCMs). Each RCM is driven by three global climate models (GCMs) from the new coordinated high-resolution output for regional evaluations (CORDEX-CORE) under the RCP8.5 scenario. Two projection periods were used: the near future (2021–2050) and the far future (2071–2100). For the model evaluation, reanalysis data from ERA5 and satellite-based climate data (SARAH-2) were used. The models and their ensemble mean (hereafter Mean) show acceptable performance for the simulations of the solar PV potential, the wind power density, and related variables with some biases. The Mean predicts a general decrease in the solar PV potential over the region of about −2% in the near future and −4% in the far future. The wind power density (WPD) is expected to increase by about 20% in the near future and 40% in the far future. The changes for solar PV potential seem to be consistent, although the intensity differs according to the RCM used. For the WPD, there are some discrepancies among the RCMs in terms of intensity and direction. This study can guide governments and policymakers in decision making for future solar and wind energy projects in the region. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
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6. Day-ahead electric load forecast for a Ghanaian health facility using different algorithms
- Author
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Chaaraoui, Samer, Bebber, Matthias, Meilinger, Stefanie, Rummeny, Silvan, Schneiders, Thorsten, Sawadogo, Windmanagda, and Kunstmann, Harald
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neural network ,lcsh:T ,load forecasting ,Westafrika ,Ghana ,lcsh:Technology ,Earth sciences ,SARIMA ,Elektrizitätsversorgung ,Ghanaian health sector ,West Africa ,ddc:550 ,ddc:333.7 ,Medizinische Einrichtung ,ddc:500 ,LSTM - Abstract
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <, 0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >, 1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <, 0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.
- Published
- 2021
7. WASCAL - West African Science Service Center on Climate Change and Adapted Land Use
- Author
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Olusegun, C.F., Gessner, Ursula, Hirner, Andreas, Salack, S., Forkuor, G., Berger, S., Heinzeller, D., Dieng, D., Sylla, B., Kunstmann, Harald, Lamers, John P.A., and Tondoh, J.
- Subjects
Simulations ,Remote Sensing ,Climate ,West Africa ,Landoberfläche - Abstract
With climate change being one of the most severe challenges to Africa in the 21st century, West Africa needs to develop effective adaptation and mitigation measures. WASCAL, the West African Science Service Center on Climate Change and Adapted Land Use, is a large-scale researchfocused climate service center with headquarters in Accra (Ghana) and a research competence center (CoC) in Ouagadougou (Burkina Faso). By the 10 member countries, WASCAL is mandated to tackle the challenges related to climate change and ultimately enhance the resilience of human and environmental systems to climate change and increased variability. It does so by strengthening the research infrastructure and capacity in West Africa related to climate change and by pooling the expertise of ten West African countries and Germany. WASCAL conducts research in the fields of climate, land use, agriculture, ecosystems, markets, livelihoods, and risk management. The center concurrently envisages establishing six observation networks, and works towards developing a range of data products and services.
- Published
- 2017
8. Decadal and multi-year predictability of the West African monsoon and the role of dynamical downscaling
- Author
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Paeth, Heiko, Paxian, Andreas, Sein, Dmitry V., Jacob, Daniela, Panitz, Hans-Jürgen, Warscher, Michael, Fink, Andreas H., Kunstmann, Harald, Breil, Marcus, Engel, Thomas, Krause, Andreas, Toedter, Julian, and Ahrens, Bodo
- Subjects
Earth sciences ,decadal predictability ,West Africa ,monsoon rainfall ,ddc:550 ,lcsh:Meteorology. Climatology ,lcsh:QC851-999 ,dynamical downscaling ,ddc:900 - Abstract
West African summer monsoon precipitation is characterized by distinct decadal variability. Due to its well-documented link to oceanic boundary conditions in various ocean basins it represents a paradigm for decadal predictability. In this study, we reappraise this hypothesis for several sub-regions of sub-Saharan West Africa using the new German contribution to the coupled model intercomparison project phase 5 (CMIP5) near-term prediction system. In addition, we assume that dynamical downscaling of the global decadal predictions leads to an enhanced predictive skill because enhanced resolution improves the atmospheric response to oceanic forcing and land-surface feedbacks. Based on three regional climate models, a heterogeneous picture is drawn: none of the regional climate models outperforms the global decadal predictions or all other regional climate models in every region nor decade. However, for every test case at least one regional climate model was identified which outperforms the global predictions. The highest predictive skill is found in the western and central Sahel Zone with correlation coefficients and mean-square skill scores exceeding 0.9 and 0.8, respectively.
- Published
- 2017
9. Modelled feedback of observed inter-annual vegetation changes on the West African monsoon
- Author
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Klein, C., Heinzeller, D., Bliefernicht, Jan, Gessner, U., Klein, I., and Kunstmann, Harald
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Remote Sensing ,Vegetation dynamics ,Monsoon ,West Africa ,WRF ,Landoberfläche ,Climate Modeling - Published
- 2015
10. Evaporation tagging and atmospheric water budget analysis with WRF: A regional precipitation recycling study for West Africa.
- Author
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Arnault, Joel, Knoche, Richard, Wei, Jianhui, and Kunstmann, Harald
- Subjects
ATMOSPHERIC water vapor analysis ,METEOROLOGICAL precipitation ,METEOROLOGICAL research ,COMPUTER algorithms ,HYDROLOGIC cycle - Abstract
ABSTRACT Regional precipitation recycling is the measure of the contribution of local evaporation E to local precipitation. This study provides a set of two methods developed in the Weather Research and Forecasting WRF model system for investigating regional precipitation recycling mechanisms: (1) tracking of tagged atmospheric water species originating from evaporation in a source region, ie E-tagging, and (2) three-dimensional budgets of total and tagged atmospheric water species. These methods are used to quantify the effect of return flow and nonwell vertical mixing neglected in the computation of the bulk precipitation recycling ratio. The developed algorithms are applied to a WRF simulation of the West African Monsoon 2003. The simulated region is characterized by vertical wind shear condition, i.e., southwesterlies in the low levels and easterlies in the mid-levels, which favors return flow and nonwell vertical mixing. Regional precipitation recycling is investigated in 100 × 100 and 1000 × 1000 km
2 areas. A prerequisite condition for evaporated water to contribute to the precipitation process in both areas is that it is lifted to the mid-levels where hydrometeors are produced. In the 100 × 100 (1000 × 1000) km2 area the bulk precipitation recycling ratio is 0.9 (7.3) %. Our budget analysis reveals that return flow and nonwell vertically mixed outflow increase this value by about +0.2 (2.9) and +0.2 (1.6) %, respectively, thus strengthening the well-known scale-dependency of regional precipitation recycling. [ABSTRACT FROM AUTHOR]- Published
- 2016
- Full Text
- View/download PDF
11. Seasonal Forecasting of the Onset of the Rainy Season in West Africa.
- Author
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Rauch, Manuel, Bliefernicht, Jan, Laux, Patrick, Salack, Seyni, Waongo, Moussa, and Kunstmann, Harald
- Subjects
FORECASTING ,ARID regions ,METEOROLOGICAL services ,STATISTICAL correlation ,LONG-range weather forecasting ,PRECIPITATION forecasting ,SEASONS - Abstract
Seasonal forecasts for monsoonal rainfall characteristics like the onset of the rainy seasons (ORS) are crucial for national weather services in semi-arid regions to better support decision-making in rain-fed agriculture. In this study an approach for seasonal forecasting of the ORS is proposed using precipitation information from a global seasonal ensemble prediction system. It consists of a quantile–quantile-transformation for eliminating systematic differences between ensemble forecasts and observations, a fuzzy-rule based method for estimating the ORS date and graphical methods for an improved visualization of probabilistic ORS forecasts. The performance of the approach is tested for several climate zones (the Sahel, Sudan and Guinean zone) in West Africa for a period of eleven years (2000 to 2010), using hindcasts from the Seasonal Forecasting System 4 of ECMWF. We indicated that seasonal ORS forecasts can be skillful for individual years and specific regions (e.g., the Guinean coasts), but also associated with large uncertainties. A spatial verification of the ORS fields emphasizes the importance of selecting appropriate performance measures (e.g., the anomaly correlation coefficient) to avoid an overestimation of the forecast skill. The graphical methods consist of several common formats used in seasonal forecasting and a new index-based method for a quicker interpretation of probabilistic ORS forecast. The new index can also be applied to other seasonal forecast variables, providing an important alternative to the common forecast formats used in seasonal forecasting. Moreover, the forecasting approach proposed in this study is not computationally intensive and is therefore operational applicable for forecasting centers in tropical and subtropical regions where computing power and bandwidth are often limited. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
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