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  • 1
    Publication Date: 2024-01-26
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Riverbed clogging is key to assessing vertical connectivity in the hyporheic zone and is often quantified using single‐parameter or qualitative approaches. However, clogging is driven by multiple, interacting physical and bio‐geochemical parameters, which do not allow for a conclusive assessment of hyporheic connectivity with single‐parameter approaches. In addition, existing qualitative assessments lack transparency and repeatability. This study introduces a Multi‐Parameter Approach to quantify Clogging and vertical hyporheic connectivity (MultiPAC), which builds on standardized measurements of physical (grain size characteristics, porosity, hydraulic conductivity) and bio‐geochemical (interstitial dissolved oxygen) parameters. We apply MultiPAC at three gravel‐bed rivers and show how the set of parameters provides a representative appreciation of physical riverbed clogging, thus quantifying vertical hyporheic connectivity. However, more parameters are required to fully characterize biological clogging. In addition, MultiPAC locates clogged layers in the hyporheic zone through multi‐parameter vertical profiles over the riverbed depth. The discussion outlines the relevance of MultiPAC to guide field surveys.〈/p〉
    Description: https://github.com/Ecohydraulics/kf-converter-w-flopy
    Keywords: ddc:550.724 ; colmation ; dissolved oxygen ; grain size ; hydraulic conductivity ; porosity ; siltation
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2022-03-30
    Description: With increasing resolution of numerical weather prediction (NWP) models, classical subgrid‐scale processes become increasingly resolved on the model grid. In particular, turbulence in the planetary boundary layer (PBL) is vertically already partially resolved in contemporary models. For classical local PBL schemes, resulting up‐gradient heat transports cannot be treated correctly. Thus, nonlocal turbulence schemes have been developed in the past. As the horizontal grid sizes of NWP models become smaller than a few kilometers, the large turbulence eddies in the PBL will also start to become partially resolved in the horizontal direction. A very flexible way to formulate nonlocal turbulent exchange is the transilient matrix method, which is used here to develop a new turbulence parameterization. The resulting NLT3D scheme applies transilient mixing matrices to subgrid‐scale transports in all three dimensions. We compare results of WRF real‐case simulations including our scheme, a classical local turbulence scheme (MYNN), and an existing nonlocal one‐dimensional scheme (ACM2) with observations from field campaigns over homogeneous terrain (CASES‐99) and complex terrain (CAPTEX). Over homogeneous terrain, all three schemes similarly well capture the observed surface fluxes and radiosonde profiles, whereas over complex terrain more differences become obvious. During a tracer release experiment (CAPTEX) over the Appalachian mountain region, the mixing and vertical extent of the PBL turn out to be decisive to reproduce the observed advection speed of the tracer‐marked air mass. Deeper mixing not only accelerates surface winds but also enables tracer to travel faster at higher altitudes and then mix back to the ground. As results from a version of NLT3D with only standard horizontal Smagorinsky diffusion (NLT1D) demonstrate, simulating three‐dimensional turbulence can be beneficial already at horizontal grid sizes of a few kilometers.
    Description: Decreasing grid sizes in numerical weather prediction models demand the inclusion of nonlocal effects and horizontal turbulence in turbulence parameterizations. This is the motivation for the development of the nonlocal three‐dimensional turbulence (NLT3D) scheme. Vertical nonlocal mixing accelerates the horizontal transport of near‐surface tracers by fast advection at higher altitudes (see figure), and horizontal turbulence enhances tracer dispersion. As validated by observations, both effects are beneficial to the forecast quality already at grid sizes of a few kilometers.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: ddc:551.6
    Language: English
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  • 3
    Publication Date: 2022-08-04
    Description: The 2011/2012 summer drought in Southeastern South America (SESA) was a short but devastating event. What would this event have looked like under pre‐industrial conditions, or in a +2 degC world? We find that climate change causes the region to be at a higher risk of drought. However, we found no large‐scale changes in the half‐month water budgets. We show that the climate change induced positive precipitation trend in the region outweighs the increased temperatures and potential evapotranspiration during the 2011/2012 drought. image
    Keywords: ddc:551.5
    Language: English
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  • 4
    Publication Date: 2022-03-31
    Description: Aerosol can affect clouds in various ways. Beside the microphysical impact of aerosol particles on cloud formation, the interference of aerosol with atmospheric radiation leads to changes in local heating, surface fluxes and thus mesoscale circulations, all of which may also modify clouds. Rather little is known about these so‐called semi‐direct effects in realistic settings – a reason why this study investigates the impact of absorbing aerosol particles on cloud and radiation fields over Germany. Using advanced high‐resolution simulations with grid spacings of 312 and 625 m, numerical experiments with different aerosol optical properties are contrasted using purely scattering aerosol as a control case and realistic absorbing aerosol as a perturbation. The combined effect of surface dimming and atmospheric heating induces positive temperature and negative moisture anomalies between 800 and 900 hPa, impacting low‐level cloud formation. Decreased relative humidity as well as increased atmospheric stability below clouds lead to a reduction of low‐level cloud cover, liquid water path and precipitation. It is further found that direct and semi‐direct effects of absorbing aerosol forcing have similar magnitudes and contribute equally to a reduction of net radiation at the top of the atmosphere.
    Description: Atmospheric aerosol particles can absorb solar radiation, altering the thermal structure of the atmosphere and surface fluxes. Using advanced high‐resolution simulations over Germany with grid spacings of 312 and 625 m, we find that boundary‐layer absorbing aerosol reduces low‐level cloud cover, liquid water path and precipitation. Direct and semi‐direct effects have similar magnitudes and contribute equally to a positive absorbing aerosol forcing.
    Description: German Ministry for Education and Research EU Horizon 2020 project CONSTRAIN
    Description: https://cera-www.dkrz.de/WDCC/ui/cerasearch/entry?acronym=DKRZ_LTA_1174_ds00001
    Keywords: ddc:551.5
    Language: English
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  • 5
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Reliable prediction of heavy precipitation events causing floods in a world of changing climate is crucial for the development of appropriate adaption strategies. Many attempts to provide such predictions have already been conducted but there is still much potential for improvement left. This is particularly true for statistical downscaling of heavy precipitation due to changes present in the corresponding atmospheric drivers. In this study, a circulation pattern (CP) conditional downscaling to the station level is proposed which considers occurring frequency changes of CPs. Following a strict circulation‐to‐environment approach we use atmospheric predictors to derive CPs. Subsequently, precipitation observations are used to derive CP conditional cumulative distribution functions (CDFs) of daily precipitation. Raw precipitation time series are sampled from these CDFs. Bias correction is applied to the sampled time series with quantile mapping (QM) and parametric transfer functions (PTFs) as methods being tested. The added value of this CP conditional downscaling approach is evaluated against the corresponding common non‐CP conditional approach. The performance evaluation is conducted by using Kling–Gupta Efficiency (KGE), root mean squared error (RMSE), and mean absolute error (MAE) metrics. In both cases the applied bias correction is identical. Potential added value can therefore only be attributed to the CP conditioning. It can be shown that the proposed CP conditional downscaling approach is capable of yielding more reliable and accurate downscaled daily precipitation time series in comparison to a non‐CP conditional approach. This can be seen in particular for the extreme parts of the distribution. Above the 95th percentile, an average performance gain of +0.24 and a maximum gain of +0.6 in terms of KGE is observed. These findings support the assumption of conserving and utilizing atmospheric information through CPs can be beneficial for more reliable statistical precipitation downscaling. Due to the availability of these atmospheric predictors in climate model output, the presented method is potentially suitable for downscaling precipitation projections.〈/p〉
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview
    Description: https://cdc.dwd.de/portal/
    Keywords: ddc:551.5 ; bias correction ; circulation patterns ; ERA5 ; extreme events ; heavy precipitation ; simulated annealing ; statistical downscaling
    Language: English
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  • 6
    Publication Date: 2022-04-01
    Description: Using a household and plot‐level survey conducted in Ethiopia, this study analyses the difference in farmers' adoption of sustainable land management (SLM) practices between their rainfed and irrigated plots. The paper also investigates the varying influence of different types of irrigation water management systems and associated irrigation technologies on the adoption of SLM practices in irrigated plots. After controlling for heterogeneity among different irrigation water management systems and technologies, we found that access to irrigation play major role in enhancing farmers' motivation to adopt more SLM practices. Furthermore, the combined effect of irrigation water management system and irrigation technology on type and number of SLM practices adopted is quite varied and very significant. The evidence highlights that farmers adopt more SLM practices in their plots with pump irrigation compared with those plots where gravity irrigation is applied because pump irrigation systems enhance complementarities with SLM practices. Finally, the findings underscore that the type of irrigation water management and the irrigation technology applied play an important role in restoring degraded lands and maintaining soil fertility, even when farmers' adoption of irrigation was not explicitly triggered by concerns for soil health.
    Description: Center for Development Research (ZEF), University of Bonn
    Description: CGIAR Research Program on Water, Land, and Ecosystems
    Description: Deutscher Akademischer Austauschdienst (DAAD) http://dx.doi.org/10.13039/501100001655
    Description: Dr. Hermann Eiselen Doctoral Program of the Foundation Fiat
    Description: Federal Ministry for Economic Cooperation and Development (BMZ) of Germany, The Water‐Energy‐Food Nexus: Global, Basin and Local Case Studies of Resource Use Efficiency Under Growing Natural Resource Scarcity
    Keywords: ddc:631
    Language: English
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  • 7
    Publication Date: 2022-12-05
    Description: 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.
    Description: 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.
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Keywords: ddc:551.5 ; circulation pattern ; classification ; downscaling ; heavy rainfall ; West Africa
    Language: English
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  • 8
    Publication Date: 2023-01-14
    Description: 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.
    Description: 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.
    Description: German Federal Ministry of Education and Research, Bonn (BMBF), West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL)
    Keywords: ddc:551.6 ; bias correction ; climate change ; CORDEX‐Africa ; geostatistical approaches ; precipitation ; quantile mapping ; West Africa
    Language: English
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  • 9
    Publication Date: 2022-10-13
    Description: Accurate and reliable precipitation data with high spatial and temporal resolution are essential in studying climate variability, water resources management, and hydrological forecasting. A range of global precipitation data are available to this end, but how well these capture actual precipitation remains unknown, particularly for mountain regions where ground stations are sparse. We examined the performance of three global high‐resolution precipitation products for capturing precipitation over Central Asia, a hotspot of climate change, where reliable precipitation data are particularly scarce. Specifically, we evaluated MSWEP, CHIRPS, and GSMAP against independent gauging stations for the period 1985–2015. Our results show that MSWEP and CHIRPS outperformed GSMAP for wetter periods (i.e., winter and spring) and wetter locations (150–600 mm·year−1), lowlands, and mid‐altitudes (0–3,000 m), and regions dominated by winter and spring precipitation. MSWEP performed best in representing temporal precipitation dynamics and CHIRPS excelled in capturing the volume and distribution of precipitation. All precipitation products poorly estimated precipitation at higher elevations (〉3,000 m), in drier areas (〈150 mm), and in regions characterized by summer precipitation. All products accurately detected dry spells, but their performance decreased for wet spells with increasing precipitation intensity. In sum, we find that CHIRPS and MSWEP provide the most reliable high‐resolution precipitation estimates for Central Asia. However, the high spatial and temporal heterogeneity of the performance call for a careful selection of a suitable product for local applications considering the prevailing precipitation dynamics, climatic, and topographic conditions.
    Description: We present the first quantitative evaluation of global high‐resolution (below 12 km) precipitation products against independent ground observations over Central Asia. Our results show that MSWEP was best at representing temporal precipitation dynamics, and CHIRPS was most prominent in representing the volume and distribution of precipitation. This is especially the case of wet seasons, altitudes below 3,000 m, and regions dominated by spring and winter precipitation. Our analysis provides key insights on the precipitation products' suitability for local hydrological applications.
    Description: Leibniz‐Institut für Agrarentwicklung in Transformationsökonomien
    Description: Volkswagen Foundation http://dx.doi.org/10.13039/501100001663
    Keywords: ddc:551.6
    Language: English
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  • 10
    Publication Date: 2024-03-12
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Flow‐dependent errors in tropical analyses and short‐range forecasts are analysed using global observing‐system simulation experiments assimilating only temperature, only winds, and both data types using the ensemble Kalman filter (EnKF) Data Assimilation Research Testbed (DART) and a perfect model framework. The idealised, homogeneous observation network provides profiles of wind and temperature data from the nature run for January 2018 using the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) forced by the observed sea‐surface temperature. The results show that the assimilation of abundant wind observations in a perfect model makes the temperature data in the Tropics largely uninformative. Furthermore, the assimilation of wind data reduces the background errors in specific humidity twice as much as the assimilation of temperature observations. In all experiments, the largest analysis uncertainties and the largest short‐term forecast errors are found in regions of strong vertical and longitudinal gradients in the background wind, especially in the upper troposphere and lower stratosphere over the Indian Ocean and Maritime Continent. The horizontal error correlation scales are on average short throughout the troposphere, just several hundred km. The correlation scales of the wind variables in precipitating regions are half of those in nonprecipitating regions. In precipitating regions, the correlations are elongated vertically, especially for the wind variables. Strong positive cross‐correlations between temperature and specific humidity in the precipitating regions are explained using the Clausius–Clapeyron equation.〈/p〉
    Description: China Scholarship Council http://dx.doi.org/10.13039/501100004543
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: ddc:551.6 ; ensemble Kalman filter data assimilation ; forecast‐error correlations ; mass and wind observations ; temperature–moisture cross‐correlations ; Tropics
    Language: English
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