Monitoring and Modelling of Soil Moisture in Lower Franconia (Germany)

2020 ◽  
Author(s):  
Julian Krause ◽  
Christian Schäfer ◽  
Birgit Terhorst ◽  
Roland Baumhauer ◽  
Heiko Paeth
Keyword(s):  
Soil Moisture ◽  
Extreme Precipitation ◽  
Regional Climate ◽  
Earth System Model ◽  
System Model ◽  
Future Scenarios ◽  
Earth System ◽  
Extreme Precipitation Events ◽  
Lower Franconia ◽  
Precipitation Events

<p>This research is part of the integrated project “BigData@Geo - Advanced Environmental Technology Using AI In The Web” funded by the European Regional Development Fund (ERDF). The aim of this ERDF-project is to develop a high-resolution regional earth system model for the region of Lower Franconia. One sub-project is dedicated to regional soil moisture modelling created with WaSiM-ETH based on soil moisture monitoring data. The second sub-project aims to improve the resolution of the regional climate model REMO. Both models will be combined to form the earth system model.</p><p>Lower Franconia is amongst the regions in Germany, which will be strongly affected by climate change. Regional climate models show that average temperatures will rise and dry periods as well as extreme precipitation events occur more often. However, it is still not known, what effect the changing climate conditions – especially dry periods and extreme precipitation events – will have on the soils in Lower Franconia.</p><p>Yields of forestry and agriculture (including viticulture and pomiculture) depend very much on the availability of soil water. During the growing season the water retention capacity of soils is therefore highly relevant. Up to present, datasets as well as modelling results of future scenarios on soil moisture are only scarcely available on local as well as on regional scale. In order to generate future scenarios, calculation of the soil moisture regime forms the base in order to evaluate present day conditions as well as to develop prognostic studies. As we intend to obtain most realistic parameters, generation of real-time data with high temporal resolution at selected sites is crucial. They are characteristic for Lower Franconia serving as calibration regions for modelling approaches. The operating monitoring stations record soil moisture and - temperature as well as meteorological parameters.</p><p>In order to obtain data on dynamics and causes of soil moisture fluctuation as well as to understand process flows, soil geographical surveys form an essential component of our research design for selected sites related to the monitoring stations. Furthermore, relevant sedimentological and pedological parameters such as grain size distribution, permeability, and bulk density are analyzed in the laboratory. Thus, our representative test sites combine detailed ground-truth data combining soil moisture and soil quality and thus, form consecutive modules as parts of soil moisture models. These modules drive and control the modelling procedures of the sub-project and they further serve for assessment and calibration of the area-wide hydrological and climate modelling in the “BigData@Geo” ERDF-project.</p>

scholarly journals Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Historical Period ◽  
Mountainous Regions ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

The effect of climate change on urban drainage: an evaluation based on regional climate model simulations

2006 ◽  
Vol 54 (6-7) ◽  
pp. 9-15 ◽  
Author(s):  
M. Grum ◽  
A.T. Jørgensen ◽  
R.M. Johansen ◽  
J.J. Linde
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Rain Gauge ◽  
Urban Drainage ◽  
Extreme Precipitation Events ◽  
Rainfall Extremes ◽  
The Future ◽  
Precipitation Events

That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 × 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at time-scales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.

scholarly journals Regional Climate Simulations With the Community Earth System Model

2018 ◽  
Vol 10 (6) ◽  
pp. 1245-1265 ◽  
Author(s):  
A. Gettelman ◽  
P. Callaghan ◽  
V. E. Larson ◽  
C. M. Zarzycki ◽  
J. T. Bacmeister ◽  
...  
Keyword(s):  
Regional Climate ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Climate Simulations ◽  
Community Earth System Model

scholarly journals Bergen Earth system model (BCM-C): model description and regional climate-carbon cycle feedbacks assessment

2010 ◽  
Vol 3 (1) ◽  
pp. 123-141 ◽  
Author(s):  
J. F. Tjiputra ◽  
K. Assmann ◽  
M. Bentsen ◽  
I. Bethke ◽  
O. H. Otterå ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Regional Climate ◽  
Earth System Model ◽  
System Model ◽  
Model Description ◽  
Earth System ◽  
Carbon Cycle Model ◽  
Enhanced Production ◽  
Positive Climate

Abstract. We developed a complex Earth system model by coupling terrestrial and oceanic carbon cycle components into the Bergen Climate Model. For this study, we have generated two model simulations (one with climate change inclusions and the other without) to study the large scale climate and carbon cycle variability as well as its feedback for the period 1850–2100. The simulations are performed based on historical and future IPCC CO2 emission scenarios. Globally, a pronounced positive climate-carbon cycle feedback is simulated by the terrestrial carbon cycle model, but smaller signals are shown by the oceanic counterpart. Over land, the regional climate-carbon cycle feedback is highlighted by increased soil respiration, which exceeds the enhanced production due to the atmospheric CO2 fertilization effect, in the equatorial and northern hemisphere mid-latitude regions. For the ocean, our analysis indicates that there are substantial temporal and spatial variations in climate impact on the air-sea CO2 fluxes. This implies feedback mechanisms act inhomogeneously in different ocean regions. In the North Atlantic subpolar gyre, the simulated future cooling of SST improves the CO2 gas solubility in seawater and, hence, reduces the strength of positive climate carbon cycle feedback in this region. In most ocean regions, the changes in the Revelle factor is dominated by changes in surface pCO2, and not by the warming of SST. Therefore, the solubility-associated positive feedback is more prominent than the buffer capacity feedback. In our climate change simulation, the retreat of Southern Ocean sea ice due to melting allows an additional ~20 Pg C uptake as compared to the simulation without climate change.

scholarly journals Development of Observation-based Global Multi-layer Soil Moisture Products for 1970 to 2016

2021 ◽  
Author(s):  
Yaoping Wang ◽  
Jiafu Mao ◽  
Mingzhou Jin ◽  
Forrest M. Hoffman ◽  
Xiaoying Shi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Earth System Model ◽  
System Model ◽  
Surface Model ◽  
Earth System ◽  
Model Simulations ◽  
The Earth ◽  
Wide Range ◽  
In Situ Observations

Abstract. Soil moisture (SM) datasets are critical to understanding the global water, energy, and biogeochemical cycles and benefit extensive societal applications. However, individual sources of SM data (e.g., in situ and satellite observations, reanalysis, offline land surface model simulations, Earth system model simulations) have source-specific limitations and biases related to the spatiotemporal continuity, resolutions, and modeling/retrieval assumptions. Here, we developed seven global, gap-free, long-term (1970–2016), multi-layer (0–10, 10–30, 30–50, and 50–100 cm) SM products at monthly 0.5° resolution (available at https://doi.org/10.6084/m9.figshare.13661312.v1) by synthesizing a wide range of SM datasets using three statistical methods (unweighted averaging, optimal linear combination, and emergent constraint). The merged products outperformed their source datasets when evaluated with in situ observations and the latest gridded datasets that did not enter merging because of insufficient spatial, temporal, or soil layer coverage. Assessed against in situ observations, the global mean bias of the synthesized SM data ranged from −0.044 to 0.033 m3/m3, root mean squared error from 0.076 to 0.104 m3/m3, and Pearson correlation from 0.35 to 0.67. The merged SM datasets also showed the ability to capture historical large-scale drought events and physically plausible global sensitivities to observed meteorological factors. Three of the new SM products, produced by applying any of the three merging methods onto the source datasets excluding the Earth system models, were finally recommended for future applications because of their better performances than the Earth system model–dependent merged estimates. Despite uncertainties in the raw SM datasets and fusion methods, these hybrid products create added value over existing SM datasets because of the performance improvement and harmonized spatial, temporal, and vertical coverages, and they provide a new foundation for scientific investigation and resource management.

scholarly journals Using CYGNSS Data to Monitor China’s Flood Inundation during Typhoon and Extreme Precipitation Events in 2017

2019 ◽  
Vol 11 (7) ◽  
pp. 854 ◽  
Author(s):  
Wei Wan ◽  
Baojian Liu ◽  
Ziyue Zeng ◽  
Xi Chen ◽  
Guiping Wu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Global Navigation Satellite System ◽  
Extreme Precipitation ◽  
Land Surface ◽  
Satellite System ◽  
Navigation Satellite ◽  
Flood Inundation ◽  
Extreme Precipitation Events ◽  
Global Navigation Satellite ◽  
Precipitation Events

NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( T b C ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology.

scholarly journals Hydrometeorological Conditions Preceding Extreme Streamflow for the Charles and Mystic River Basins of Eastern Massachusetts

2019 ◽  
Vol 20 (9) ◽  
pp. 1795-1812 ◽  
Author(s):  
Laurie Agel ◽  
Mathew Barlow ◽  
Mathias J. Collins ◽  
Ellen Douglas ◽  
Paul Kirshen
Keyword(s):  
Soil Moisture ◽  
Extreme Precipitation ◽  
River Basins ◽  
Total Precipitation ◽  
Extreme Precipitation Events ◽  
Intense Precipitation ◽  
The Mean ◽  
Eastern Massachusetts ◽  
Hydrometeorological Conditions ◽  
Precipitation Events

Abstract Hydrometeorological links to high streamflow events (HSFEs), 1950–2014, for the Mystic and Charles watersheds in the Metro Boston region of Massachusetts are examined. HSFEs are defined as one or more continuous days of streamflow above the mean annual maxima for a selected gauge in each basin. There are notable differences in the HSFEs for these two basins. HSFEs last from 1 to 3 days in the Mystic basin, while HSFEs for the Charles can last from 3 to 9 days. The majority of Mystic HSFEs are immediately preceded by extreme precipitation (occurring within 24 h), while only half of those for the Charles are preceded by extreme precipitation (in this case occurring 2–5 days earlier). While extreme precipitation events are often linked to HSFEs, other factors are often necessary in generating high streamflow, particularly for the Charles, as more than 50% of HSFEs occur at times when streamflow, soil moisture, and total precipitation are statistically above average for a period of at least 2 weeks before the HSFE. Approximately 52% and 80% of HSFEs occur from February to June for the Mystic and Charles, respectively, and these HSFEs are frequently linked to the passage of strong coastal lows, which produce extreme precipitation in the form of both rain and snow. For these coastal lows, Mystic HSFEs are linked to a strong moisture feed along the Massachusetts coastline and intense precipitation, while Charles HSFEs are linked to strong cyclones located off the Mid-Atlantic and longer-duration precipitation.

scholarly journals Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

2012 ◽  
Vol 16 (12) ◽  
pp. 4517-4530 ◽  
Author(s):  
S. C. van Pelt ◽  
J. J. Beersma ◽  
T. A. Buishand ◽  
B. J. J. M. van den Hurk ◽  
P. Kabat
Keyword(s):  
Time Series ◽  
Regional Climate Model ◽  
Extreme Precipitation ◽  
Climate Model ◽  
Regional Climate ◽  
Future Change ◽  
Model Simulations ◽  
Rhine Basin ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks. In this study a relatively simple method has been developed to get a better description of the range of changes in extreme precipitation events. Five bias-corrected RCM simulations of the 1961–2100 climate for a single greenhouse gas emission scenario (A1B SRES) were available for the Rhine basin. To increase the size of this five-member RCM ensemble, 13 additional GCM simulations were analysed. The climate responses of the GCMs are used to modify an observed (1961–1995) precipitation time series with an advanced delta change approach. Changes in the temporal means and variability are taken into account. It is found that the range of future change of extreme precipitation across the five-member RCM ensemble is similar to results from the 13-member GCM ensemble. For the RCM ensemble, the time series modification procedure also results in a similar climate response compared to the signal deduced from the direct model simulations. The changes from the individual RCM simulations, however, systematically differ from those of the driving GCMs, especially for long return periods.

scholarly journals Assessment of the spatio-temporal variability of the added value on precipitation of convection-permitting simulation over the Iberian Peninsula using the RegIPSL regional earth system model

2021 ◽  
Author(s):  
Namendra Kumar Shahi ◽  
Jan Polcher‬ ◽  
Sophie Bastin ◽  
Romain Pennel ◽  
Lluís Fita
Keyword(s):  
Iberian Peninsula ◽  
Regional Climate ◽  
Temporal Distribution ◽  
Heavy Precipitation ◽  
Earth System Model ◽  
Added Value ◽  
System Model ◽  
Earth System ◽  
Precipitation Frequency ◽  
Spatio Temporal

Abstract In this study, we have assessed the added value on the spatio-temporal distribution of the precipitation of convection-permitting simulation (3km) compared to the parent coarser-scale parameterized convection simulation (20km) with the high-resolution observational datasets i.e. SPREAD (5km) and IBERIA01 (10km) over the Iberian Peninsula in all four seasons during 2000-2009. Both simulations are evaluation runs based on ERA-Interim reanalysis and performed with the RegIPSL regional earth system model in the frame of the European Climate Prediction system (EUCP) H2020 project and COordinated Regional climate Downscaling Experiment (CORDEX). We have not found significant improvement in the convection-permitting simulation compared to the parent coarser-scale simulation for the seasonal mean precipitation of the Iberian Peninsula except the spatial variation over mountainous peaks. The kilometer-scale simulation significantly underestimates the observed seasonal mean precipitation over the western parts of the Iberian Peninsula compared to the coarser-scale simulation, which may be attributed to a change of local dynamics in the kilometer-scale simulation with a weakening and southward shifts of the westerly winds and also an enhancement of warm and dry southerly winds over the Iberian Peninsula. However, the added value of kilometer-scale simulation over the driving coarser-scale simulation is obtained for various indices; in the representation of the spatio-temporal distribution of the wet-day precipitation frequency and intensity, and the extreme/heavy precipitation events for each season at both resolutions i.e. downscaled and upscaled. It has also been noted that the spatio-temporal distribution of precipitation for all metrics used varies between the two observational datasets for all seasons.

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