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Article ; Online: Assimilation of GNSS and Synoptic Data in a Convection Permitting Limited Area Model

Andreas Wagner / Benjamin Fersch / Peng Yuan / Thomas Rummler / Harald Kunstmann

Frontiers in Earth Science, Vol

Improvement of Simulated Tropospheric Water Vapor Content

2022 Volume 10

Abstract: The assimilation of observations in limited area models (LAMs) allows to find the best possible estimate of a region’s meteorological state. Water vapor is a crucial constituent in terms of cloud and precipitation formation. Its highly variable nature in ...

Abstract	The assimilation of observations in limited area models (LAMs) allows to find the best possible estimate of a region’s meteorological state. Water vapor is a crucial constituent in terms of cloud and precipitation formation. Its highly variable nature in space and time is often insufficiently represented in models. This study investigates the improvement of simulated water vapor content within the Weather Research and Forecasting model (WRF) in every season by assimilating temperature, relative humidity, and surface pressure obtained from climate stations, as well as geodetically derived Zenith Total Delay (ZTD) and precipitable water vapor (PWV) data from global navigation satellite system (GNSS) ground stations. In four case studies we analyze the results of high-resolution convection-resolving WRF simulations (2.1 km) between 2016 and 2018 each in every season for a 650 × 670 km domain in the tri-border-area Germany, France and Switzerland. The impact of 3D VAR assimilation of different variables and combinations thereof, background error option, as well as the temporal and spatial resolution of assimilation is evaluated. Both column values and profiles derived from radiosondes are addressed. Best outcome was achieved when assimilating ZTD and synoptic data at an hourly resolution and a spatial thinning distance of 10 km. It is concluded that the careful selection of assimilation options can additionally improve simulation results in every season. Clear effects of assimilation on the water budgets can also be seen.
Keywords	assimilation ; WRF ; GNSS ; water vapor ; data thinning ; background error ; Science ; Q
Subject code	551
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Evaluating the uncertainty of climate model structure and bias correction on the hydrological impact of projected climate change in a Mediterranean catchment

Alfonso Senatore / Domenico Fuoco / Mario Maiolo / Giuseppe Mendicino / Gerhard Smiatek / Harald Kunstmann

Journal of Hydrology: Regional Studies, Vol 42, Iss , Pp 101120- (2022)

2022

Abstract: Study region: Crati River Basin, Southern Italy, Central Mediterranean. Study focus: We evaluate the combined effect of multiple global and regional climate model (GCM-RCM) combinations and bias correction (BC) methods on the hydrological impact of ... ...

Abstract	Study region: Crati River Basin, Southern Italy, Central Mediterranean. Study focus: We evaluate the combined effect of multiple global and regional climate model (GCM-RCM) combinations and bias correction (BC) methods on the hydrological impact of projected climate change. Under the representative concentration pathway RCP4.5, 15 EURO-CORDEX members, combining 6 GCMs and five high-resolution (0.11°) RCMs, provide the meteorological input for a spatially distributed hydrological model. RCM-derived input data are uncorrected and corrected through three empirical methods, leading to 60 different simulations for three ~30-year future periods in 2020–2096, compared to the baseline 1975–2005. The combined uncertainty of the climate models and correction methods is evaluated for the main hydrological variables using an analysis of variance (ANOVA) method. New hydrological insights for the region: Results highlight a considerable agreement in projecting a decreasing trend of available water resources (on average, −70 % for snow, −8 % for root zone soil moisture and −17 % for river runoff in the period 2070–2096), due to the remarkable mean temperature increase and less accentuated precipitation reduction. The uncertainty evaluation shows that (1) the primary source of uncertainty is the driving GCM, and (2) BC methods smooth the projected hydrological impact in a not negligible way, especially concerning discharge (for each future period, the reduction projected without bias correction is about 3 % higher than with BC), therefore contributing to the total uncertainty.
Keywords	Climate change hydrological impact ; GCM-RCM combinations ; Change factor ; Bias correction ; ANOVA ; Mediterranean catchments ; Physical geography ; GB3-5030 ; Geology ; QE1-996.5
Subject code	550
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Publisher Correction

Tanja C. Portele / Christof Lorenz / Berhon Dibrani / Patrick Laux / Jan Bliefernicht / Harald Kunstmann

Scientific Reports, Vol 11, Iss 1, Pp 1-

Seasonal forecasts offer economic benefit for hydrological decision making in semi-arid regions

2021 Volume 2

Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2021-08-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Seasonal forecasts offer economic benefit for hydrological decision making in semi-arid regions

Tanja C. Portele / Christof Lorenz / Berhon Dibrani / Patrick Laux / Jan Bliefernicht / Harald Kunstmann

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 15

Abstract: Abstract Increasing frequencies of droughts require proactive preparedness, particularly in semi-arid regions. As forecasting of such hydrometeorological extremes several months ahead allows for necessary climate proofing, we assess the potential ... ...

Abstract	Abstract Increasing frequencies of droughts require proactive preparedness, particularly in semi-arid regions. As forecasting of such hydrometeorological extremes several months ahead allows for necessary climate proofing, we assess the potential economic value of the seasonal forecasting system SEAS5 for decision making in water management. For seven drought-prone regions analyzed in America, Africa, and Asia, the relative frequency of drought months significantly increased from 10 to 30% between 1981 and 2018. We demonstrate that seasonal forecast-based action for droughts achieves potential economic savings up to 70% of those from optimal early action. For very warm months and droughts, savings of at least 20% occur even for forecast horizons of several months. Our in-depth analysis for the Upper-Atbara dam in Sudan reveals avoidable losses of 16 Mio US$ in one example year for early-action based drought reservoir operation. These findings stress the advantage and necessity of considering seasonal forecasts in hydrological decision making.
Keywords	Medicine ; R ; Science ; Q
Subject code	650
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Remote Sensing of Complex Permittivity and Penetration Depth of Soils Using P-Band SAR Polarimetry

Anke Fluhrer / Thomas Jagdhuber / Alireza Tabatabaeenejad / Hamed Alemohammad / Carsten Montzka / Peter Friedl / Ehsan Forootan / Harald Kunstmann

Remote Sensing, Vol 14, Iss 2755, p

2022 Volume 2755

Abstract: A P-band SAR moisture estimation method is introduced for complex soil permittivity and penetration depth estimation using fully polarimetric P-band SAR signals. This method combines eigen- and model-based decomposition techniques for separation of the ... ...

Abstract	A P-band SAR moisture estimation method is introduced for complex soil permittivity and penetration depth estimation using fully polarimetric P-band SAR signals. This method combines eigen- and model-based decomposition techniques for separation of the total backscattering signal into three scattering components (soil, dihedral, and volume). The incorporation of a soil scattering model allows for the first time the estimation of complex soil permittivity and permittivity-based penetration depth. The proposed method needs no prior assumptions on land cover characteristics and is applicable to a variety of vegetation types. The technique is demonstrated for airborne P-band SAR measurements acquired during the AirMOSS campaign (2012–2015). The estimated complex permittivity agrees well with climate and soil conditions at different monitoring sites. Based on frequency and permittivity, P-band penetration depths vary from 5 cm to 35 cm. This value range is in accordance with previous studies in the literature. Comparison of the results is challenging due to the sparsity of vertical soil in situ sampling. It was found that the disagreement between in situ measurements and SAR-based estimates originates from the discrepancy between the in situ measuring depth of the top-soil layer (0–5 cm) and the median penetration depth of the P-band waves (24.5–27 cm).
Keywords	AirMOSS ; polarimetric decomposition ; soil moisture ; multi-layer SPM ; Science ; Q
Subject code	550
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Seasonal sub-basin-scale runoff predictions

Maurus Borne / Christof Lorenz / Tanja C. Portele / Eduardo Sávio P.R. Martins / Francisco das Chagas Vasconcelos Junior / Harald Kunstmann

Journal of Hydrology: Regional Studies, Vol 42, Iss , Pp 101146- (2022)

A regional hydrometeorological Ensemble Kalman Filter framework using global datasets

2022

Abstract: Study region: The São Francisco River Basin (SFRB) in Brazil Study focus: In semi-arid regions, interannual variability of seasonal rainfall and climate change is expected to stress water availability and increase the recurrence and intensity of extreme ... ...

Abstract	Study region: The São Francisco River Basin (SFRB) in Brazil Study focus: In semi-arid regions, interannual variability of seasonal rainfall and climate change is expected to stress water availability and increase the recurrence and intensity of extreme events such as droughts or floods. Local decision makers therefore need reliable long-term hydro-meteorological forecasts to support the seasonal management of water resources, reservoir operations and agriculture. In this context, an Ensemble Kalman Filter framework is applied to predict sub-basin-scale runoff employing global freely available datasets of reanalysis precipitation (ERA5-Land) as well as bias-corrected and spatially disaggregated seasonal forecasts (SEAS5-BCSD). Runoff is estimated using least squares predictions, exploiting the covariance structures between runoff and precipitation. The performance of the assimilation framework was assessed using different ensemble skill scores. New hydrological insights for the region: Our results show that the quality of runoff predictions are closely linked to the performance of the rainfall seasonal predictions and allows skillful predictions up to two months ahead in most sub-basins. The anthropogenic conditions such as in the Western Bahia state, however, must be taken under consideration, since non-stationary runoff time-series have poorer skill as such unnatural variations can not be captured by long-term covariances. In sub-basins which are dominated by little anthropogenic influence, the presented framework provides a promising and easily transferable approach for skillful operational seasonal runoff predictions on sub-basin scale.
Keywords	Hydro-meteorology ; Seasonal forecast ; River basin management ; Data-assimilation ; Physical geography ; GB3-5030 ; Geology ; QE1-996.5
Subject code	550
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Inverse distributed modelling of streamflow and turbulent fluxes: A sensitivity and uncertainty analysis coupled with automatic optimization

Soltani, Mohsen / Patrick Laux / Matthias Mauder / Harald Kunstmann

Journal of hydrology. 2019 Apr., v. 571

2019

Abstract: The interactions of hydrological variables in the terrestrial hydrological cycle are complex. To better predict the variables, distributed and physically based models are used as they account for the complexity of interactions. In this study, we ... ...

Abstract	The interactions of hydrological variables in the terrestrial hydrological cycle are complex. To better predict the variables, distributed and physically based models are used as they account for the complexity of interactions. In this study, we addressed the joint simulation of water- and energy fluxes and the potential benefit of flux measurements in the parameter estimation process. For this purpose, we applied the hydrological model GEOtop to a prealpine catchment in southern Germany (River Rott, 55 km2) over two recent summer episodes, as a test case. Due to its complexity, the model is computationally demanding and only a limited number of forward runs can be afforded in inverse modelling and parameter estimation. We applied the gradient-based nonlinear Gauss-Marquardt-Levenberg (GML) parameter estimation method and linked the GEOtop model to the Parameter ESTimation tool (PEST). Using this developed GEOtop-PEST interface, we particularly investigated the value added by including turbulent flux data in the parameter estimation process, and analyse the impact of the additional flux data on the uncertainty bounds of the parameters. To better understand the interplay of the model parameters and to identify the dominating parameters in the calibration process, we also conducted a Principal Component Analysis (PCA). We were able to identify a set of model parameters that reproduced both observed streamflow and turbulent heat fluxes reasonably well. The majority of the estimated parameters were highly sensitive to the considered variables. We showed that the confidence bounds of estimated parameters are narrowed significantly when considering not only streamflow observations but also turbulent flux measurements in the calibration process. In this manner, correlations between estimated parameters could also be reduced.
Keywords	calibration ; energy flow ; heat transfer ; hydrologic cycle ; hydrologic models ; principal component analysis ; rivers ; stream flow ; summer ; uncertainty ; uncertainty analysis ; value added ; watersheds ; Germany
Language	English
Dates of publication	2019-04
Size	p. 856-872.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1473173-3
ISSN	0022-1694
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2019.02.033
Database	NAL-Catalogue (AGRICOLA)

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Article: Copula‐based downscaling of daily precipitation fields

Lorenz, Manuel / Jan Bliefernicht / Barbara Haese / Harald Kunstmann

Hydrological processes. 2018 Nov. 15, v. 32, no. 23

2018

Abstract: A novel stochastic downscaling approach to simulate ensembles of daily precipitation fields using the Gaussian copula is presented. In contrast to many other statistical downscaling techniques, this approach uses spatial correlation (correlograms) to ... ...

Abstract	A novel stochastic downscaling approach to simulate ensembles of daily precipitation fields using the Gaussian copula is presented. In contrast to many other statistical downscaling techniques, this approach uses spatial correlation (correlograms) to derive the transfer function between predictors and predictands for a parsimonious model structure. Daily regional climate model (RCM) simulations for a region in Central Europe in two different spatial resolutions (7 and 42 km) served as a training set to derive the statistics necessary to simulate fine scale precipitation values. The model was calibrated with RCM simulations for the year 1971, and the evaluation was performed for the period 1972–2000 to emulate the typical problem of limited availability of fine scale data. A comprehensive evaluation of the downscaling approach comprising the spatial correlations and statistical distributions of the simulated precipitation fields and several further performance measures was performed. The distribution of simulated precipitation is in close agreement with values simulated from a distribution function that was fitted to the complete evaluation period. Average Brier skill scores of 0.5 indicate a good performance of reproducing the daily dynamical simulations for most regions. A comparison with precipitation fields interpolated with inverse distance weighting revealed an average added skill of 42% for different precipitation thresholds; 87% of the dry days and 71% of the wet days were simulated correctly. An advantage of the proposed method over deterministic downscaling techniques is that ensembles of predictand fields are generated. Thus, the uncertainty that is inherent to downscaling can be estimated. The method has the potential to be used in other downscaling applications to generate ensembles of spatially correlated predictands based on other predictors. As copulas treat the dependence structure separately from the marginal distributions of the predictors and predictands, it is possible to simulate meteorological variables from any desired distribution function.
Keywords	atmospheric precipitation ; climate models ; hydrology ; uncertainty ; Central European region
Language	English
Dates of publication	2018-1115
Size	p. 3479-3494.
Publishing place	John Wiley & Sons, Ltd
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	1479953-4
ISSN	1099-1085 ; 0885-6087
ISSN (online)	1099-1085
ISSN	0885-6087
DOI	10.1002/hyp.13271
Database	NAL-Catalogue (AGRICOLA)

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Article: Turbulent flux variability and energy balance closure in the TERENO prealpine observatory: a hydrometeorological data analysis

Soltani, Mohsen / Harald Kunstmann / Matthias Mauder / Patrick Laux

Theoretical and applied climatology. 2018 Aug., v. 133, no. 3-4

2018

Abstract: The temporal multiscale variability of the surface heat fluxes is assessed by the analysis of the turbulent heat and moisture fluxes using the eddy covariance (EC) technique at the TERrestrial ENvironmental Observatories (TERENO) prealpine region. The ... ...

Abstract	The temporal multiscale variability of the surface heat fluxes is assessed by the analysis of the turbulent heat and moisture fluxes using the eddy covariance (EC) technique at the TERrestrial ENvironmental Observatories (TERENO) prealpine region. The fast and slow response variables from three EC sites located at Fendt, Rottenbuch, and Graswang are gathered for the period of 2013 to 2014. Here, the main goals are to characterize the multiscale variations and drivers of the turbulent fluxes, as well as to quantify the energy balance closure (EBC) and analyze the possible reasons for the lack of EBC at the EC sites. To achieve these goals, we conducted a principal component analysis (PCA) and a climatological turbulent flux footprint analysis. The results show significant differences in the mean diurnal variations of the sensible heat (H) and latent heat (LE) fluxes, because of variations in the solar radiation, precipitation patterns, soil moisture, and the vegetation fraction throughout the year. LE was the main consumer of net radiation. Based on the first principal component (PC1), the radiation and temperature components with a total mean contribution of 29.5 and 41.3%, respectively, were found to be the main drivers of the turbulent fluxes at the study EC sites. A general lack of EBC is observed, where the energy imbalance values amount 35, 44, and 35% at the Fendt, Rottenbuch, and Graswang sites, respectively. An average energy balance ratio (EBR) of 0.65 is obtained in the region. The best closure occurred in the afternoon peaking shortly before sunset with a different pattern and intensity between the study sites. The size and shape of the annual mean half-hourly turbulent flux footprint climatology was analyzed. On average, 80% of the flux footprint was emitted from a radius of approximately 250 m around the EC stations. Moreover, the overall shape of the flux footprints was in good agreement with the prevailing wind direction for all three TERENO EC sites.
Keywords	climatology ; diurnal variation ; eddy covariance ; energy balance ; heat transfer ; hydrometeorology ; latent heat ; principal component analysis ; soil water ; solar radiation ; temperature ; vegetation ; wind direction
Language	English
Dates of publication	2018-08
Size	p. 937-956.
Publishing place	Springer Vienna
Document type	Article
ZDB-ID	1463177-5
ISSN	1434-4483 ; 0177-798X
ISSN (online)	1434-4483
ISSN	0177-798X
DOI	10.1007/s00704-017-2235-1
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data

Christof Lorenz / Carsten Montzka / Thomas Jagdhuber / Patrick Laux / Harald Kunstmann

Remote Sensing, Vol 10, Iss 11, p

2018 Volume 1842

Abstract: Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture ... ...

Abstract	Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture satellite missions SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) are able to provide soil moisture estimates on global scales and in kilometer accuracy. However, the SMOS data record has an appropriate length of 7.5 years since late 2009, but with a coarse resolution of ∼25 km only. In contrast, a spatially-enhanced SMAP product is available at a higher resolution of 9 km, but for a shorter time period (since March 2015 only). Being the fundamental observable from passive microwave sensors, reliable brightness temperatures (Tbs) are a mandatory precondition for satellite-based soil moisture products. We therefore develop, evaluate and apply a copula-based data fusion approach for combining SMAP Enhanced (SMAP_E) and SMOS brightness Temperature (Tb) data. The approach exploits both linear and non-linear dependencies between the two satellite-based Tb products and allows one to generate conditional SMAP_E-like random samples during the pre-SMAP period. Our resulting global Copula-combined SMOS-SMAP_E (CoSMOP) Tbs are statistically consistent with SMAP_E brightness temperatures, have a spatial resolution of 9 km and cover the period from 2010 to 2018. A comparison with Service Soil Climate Analysis Network (SCAN)-sites over the Contiguous United States (CONUS) domain shows that the approach successfully reduces the average RMSE of the original SMOS data by 15%. At certain locations, improvements of 40% and more can be observed. Moreover, the median NSE can be enhanced from zero to almost 0.5. Hence, CoSMOP, which will be made freely available to the public, provides a first step towards a global, long-term, high-resolution and multi-sensor brightness temperature product, and thereby, also soil moisture.
Keywords	brightness temperature ; soil moisture ; copula ; data fusion ; SMAP ; SMOS ; Science ; Q
Subject code	550
Language	English
Publishing date	2018-11-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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