scholarly journals Fully coupled high-resolution medium-range forecasts: evaluation of the hydrometeorological impact in an ensemble framework

2021 ◽  
Author(s):  
Luca Furnari ◽  
Linus Magnusson ◽  
Giuseppe Mendicino ◽  
Alfonso Senatore
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Ensemble Forecasts ◽  
Soil Moisture Dynamics ◽  
Medium Range ◽  
Fully Coupled ◽  
Moisture Dynamics ◽  
Range Forecasts

Fully coupled atmospheric-hydrological models allow a more realistic representation of the land surface–boundary layer continuum, representing both high-resolution land-surface/subsurface water lateral redistribution and the related feedback towards the atmosphere. This study evaluates the potential contribution of the fully coupled approach in extended-range mesoscale hydrometeorological ensemble forecasts. Previous studies have shown, for deterministic simulations, that the effect of fully coupling for short-range forecasts is minor compared to other sources of uncertainty, however, it becomes not negligible when increasing the forecast period. Through a proof-of-concept consisting of an ensemble (50 members from the ECMWF Ensemble Prediction System) seven-days-in-advance forecast of a high impact event affecting the Calabrian peninsula (southern Italy, Mediterranean basin) on November 2019, the paper elucidates the extent to which the improved representation of the terrestrial water lateral transport in the Weather Research and Forecasting (WRF) – Hydro modeling system affects the ensemble water balance, focusing on the precipitation and the hydrological response, in terms of both soil moisture dynamics and streamflow in 14 catchments spanning over 42% of the region. The fully coupled approach caused an increase of surface soil moisture and latent heat flux from land in the days preceding the event, partially affecting the lower Planetary Boundary Layer. However, when shoreward moisture transport from surrounding sea rapidly increased becoming the dominant process, only a weak signature of soil moisture contribution could be detected, resulting in only slightly higher precipitation forecast and not clear variation trend of peak flow, even though the latter variable increased up to 10% in some catchments. Overall, this study highlighted a remarkable performance of the medium-range ensemble forecasts, suggesting a profitable use of the fully coupled approach for forecasting purposes in circumstances in which soil moisture dynamics is more relevant and needs to be better addressed.

scholarly journals Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data

2018 ◽  
Vol 22 (10) ◽  
pp. 5463-5484 ◽  
Author(s):  
Zun Yin ◽  
Catherine Ottlé ◽  
Philippe Ciais ◽  
Matthieu Guimberteau ◽  
Xuhui Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Yellow River ◽  
Climatic Research Unit ◽  
Surface Model ◽  
Atmospheric Forcing ◽  
Meteorological Forcing ◽  
Soil Moisture Dynamics ◽  
Moisture Variation ◽  
Moisture Dynamics

Abstract. Soil moisture is a key variable of land surface hydrology, and its correct representation in land surface models is crucial for local to global climate predictions. The errors may come from the model itself (structure and parameterization) but also from the meteorological forcing used. In order to separate the two source of errors, four atmospheric forcing datasets, GSWP3 (Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental Prediction), and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim reanalysis data), were used to drive simulations in China by the land surface model ORCHIDEE-MICT(ORganizing Carbon and Hydrology in Dynamic EcosystEms: aMeliorated Interactions between Carbon and Temperature). Simulated soil moisture was compared with in situ and satellite datasets at different spatial and temporal scales in order to (1) estimate the ability of ORCHIDEE-MICT to represent soil moisture dynamics in China; (2) demonstrate the most suitable forcing dataset for further hydrological studies in Yangtze and Yellow River basins; and (3) understand the discrepancies of simulated soil moisture among simulations. Results showed that ORCHIDEE-MICT can simulate reasonable soil moisture dynamics in China, but the quality varies with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows the best performance according to the root mean square error (RMSE) and correlation coefficient, respectively, suggesting that both GSWP3 and WFDEI are good choices for further hydrological studies in the two catchments. The mismatch between simulated and observed soil moisture is mainly explained by the bias of magnitude, suggesting that the parameterization in ORCHIDEE-MICT should be revised for further simulations in China. Underestimated soil moisture in the North China Plain demonstrates possible significant impacts of human activities like irrigation on soil moisture variation, which was not considered in our simulations. Finally, the discrepancies of meteorological variables and simulated soil moisture among the four simulations are analyzed. The result shows that the discrepancy of soil moisture is mainly explained by differences in precipitation frequency and air humidity rather than differences in precipitation amount.

scholarly journals Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

2016 ◽  
Author(s):  
C. Fu ◽  
G. Wang ◽  
M. L. Goulden ◽  
R. L. Scott ◽  
K. Bible ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Hydraulic Redistribution ◽  
Energy Budgets ◽  
Soil Moisture Dynamics ◽  
Community Land Model ◽  
The Us ◽  
Hydrological Impact ◽  
The Impact ◽  
Moisture Dynamics

Abstract. Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) has tackled the magnitude of the HR flux itself or the soil moisture dynamics from which HR magnitude can be directly inferred. Here we incorporated Ryel et al.'s (2002) empirical equation describing HR into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on surface water and energy budgets, and to explore how it may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites characterized by contrasting climate regimes and multiple vegetation types were studied, including the US-Wrc Wind River Crane site in Washington State, the US-SRM Santa Rita Mesquite Savanna site in southern Arizona, and six sites along the Southern California Climate Gradient (US-SCs, g, f, w, c, and d). HR flux, evapotranspiration, and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement match particularly during dry seasons. Our results also reveal that HR has important hydrological impact (on evapotranspiration, Bowen ratio, and soil moisture) in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.

scholarly journals Analysis of surface and root-zone soil moisture dynamics with ERS scatterometer and the hydrometeorological model SAFRAN-ISBA-MODCOU at Grand Morin watershed (France)

2008 ◽  
Vol 5 (4) ◽  
pp. 1903-1926 ◽  
Author(s):  
T. Paris Anguela ◽  
M. Zribi ◽  
S. Hasenauer ◽  
F. Habets ◽  
C. Loumagne
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Root Zone ◽  
Spatial Scales ◽  
Temporal Variations ◽  
Model Verification ◽  
Atmospheric Conditions ◽  
Soil Moisture Dynamics ◽  
Moisture Dynamics ◽  
Rms Errors

Abstract. Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport and vegetation productivity. Its characterization, offers an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, soil moisture dynamics at soil surface (first centimeters) and root-zone (up to 1.5 m depth) are investigated at three spatial scales: local scale (field measurements), 8×8 km2 (hydrological model) and 25×25 km2 scale (ERS scatterometer) in a French watershed. This study points out the quality of surface and root-zone soil moisture data for SIM model and ERS scatterometer for a three year period. Surface soil moisture is highly variable because is more influenced by atmospheric conditions (rain, wind and solar radiation), and presents RMS errors up to 0.08 m3 m−3. On the other hand, root-zone moisture presents lower variability with small RMS errors (between 0.02 and 0.06 m3 m-3). These results will contribute to satellite and model verification of moisture, but also to better application of radar data for data assimilation in future.

Impact of the atmospheric-hydrological fully coupled approach in a high-resolution medium-range forecasts: a case study in the Mediterranean

2021 ◽  
Author(s):  
Luca Furnari ◽  
Linus Magnusson ◽  
Giuseppe Mendicino ◽  
Alfonso Senatore
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Mediterranean Basin ◽  
Mesoscale Model ◽  
Precipitation Forecast ◽  
Ensemble Prediction ◽  
Medium Range ◽  
The Mediterranean ◽  
Fully Coupled ◽  
The Mediterranean Basin

<p>Mediterranean coastal areas are prone to hydrometeorological extremes. Their complex orography often enhances the severity of high impact events and, at the same time, makes forecasts more challenging, particularly in the medium range. Nevertheless, global operational forecasts significantly improved their accuracy in the last decades, while several novelties in mesoscale modelling are emerging, such as the atmospheric-hydrological fully coupled approach, which explicitly describes the complex interactions between the Planetary Boundary Layer (PBL) and land surface including terrestrial lateral water transport. Overall, several clues open new perspectives to define new standards in medium-range forecast performances in the Mediterranean basin.</p><p>This study investigates the skills of the Advanced Research WRF (ARW) mesoscale model both one-way and two-way coupled with the hydrological extension WRF-Hydro in providing a medium-range (7 days) forecast of a severe event hitting the Calabrian peninsula (southern Italy) in November 2019. Such event was simulated in a classical ensemble approach, using the European Center for Medium-Range Weather Forecasting (ECMWF) ensemble product (Ensemble Prediction System – EPS), which consists of 50 members providing the initial and boundary conditions to the mesoscale model. WRF model was applied in two one-way nested domains with 10 km and 2 km horizontal resolutions, encompassing most of the Mediterranean basin. WRF-Hydro was applied in the innermost domain, with NOAH-MP as Land Surface Model. Surface and subsurface routing was performed adopting 200 m as horizontal resolution.</p><p>Results highlighted that the fully coupled approach increased soil moisture and latent heat flux from land in an increasing way in the days preceding the event. Such an increase partially affected the lower PBL layers. However, when shoreward moisture transport from surrounding sea rapidly increased becoming the dominant process, only a weak signature of moisture contribution from land to the atmosphere could be detected, resulting in only slightly higher precipitation forecast and slightly increased hydrological response. Overall, the proof-of-concept carried out in this study highlighted a remarkable performance of the medium-range ensemble forecasts, suggesting a profitable use of the fully coupled approach in the selected study area for forecasting purposes in circumstances in which soil moisture dynamics and exchanges with the atmosphere are of particular interest.</p>

scholarly journals Evaluation of ORCHIDEE-MICT simulated soil moisture over China and impacts of different atmospheric forcing data

2018 ◽  
Author(s):  
Zun Yin ◽  
Catherine Ottlé ◽  
Philippe Ciais ◽  
Matthieu Guimberteau ◽  
Xuhui Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Yellow River ◽  
Precipitation Amount ◽  
Climatic Research Unit ◽  
Surface Model ◽  
Atmospheric Forcing ◽  
Soil Moisture Dynamics ◽  
Moisture Variation ◽  
Moisture Dynamics

Abstract. Four atmospheric forcing datasets: GSWP3 (Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental Prediction) and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim reanalysis data), are used to drive simulations in China by the land surface model ORCHIDEE-MICT. Simulated soil moisture is compared with in-situ and satellite datasets at different spatial and temporal scales in order to: 1) estimate the ability of ORCHIDEE-MICT (ORganizing Carbon and Hydrology in Dynamic EcosystEms: aMeliorated Interactions between Carbon and Temperature) to represent soil moisture dynamics in China; 2) demonstrate the most suitable forcing dataset for further hydrological studies in Yangtze and Yellow river basins; 3) understand the discrepancies of simulated soil moisture among simulations. Results showed that ORCHIDEE-MICT can simulate reasonable soil moisture dynamics in China (median r = 0.53; RMSE = 0.06 m3 m−3), but the quality varies with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows the best performance according to RMSE (RMSEGSWP3 = 0.05 m3 m−3) and correlation coefficient (rWFDEI = 0.64) respectively, suggesting that both GSWP3 and WFDEI are good choices for further hydrological studies. The mismatch between simulated and observed soil moisture is mainly explained by squared bias (SB) and lack of correlation weighted by the standard deviation (LCS). Large SB suggests that the parameterization in ORCHIDEE-MICT should be calibrated for further study in China. High LCS and underestimated soil moisture in the North China Plain demonstrate possible significant impacts of human activities like irrigation on soil moisture variation, which was not considered in our simulations. Finally, the discrepancies (D) of meteorological variables and simulated soil moisture among the four simulations are analyzed. The result shows that the D of soil moisture is mainly caused by the D in precipitation frequency and air humidity rather than precipitation amount.

scholarly journals On the use of AMSU-based products for the description of soil water content at basin scale

2011 ◽  
Vol 15 (9) ◽  
pp. 2839-2852 ◽  
Author(s):  
S. Manfreda ◽  
T. Lacava ◽  
B. Onorati ◽  
N. Pergola ◽  
M. Di Leo ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Land Surface ◽  
Skin Surface ◽  
Soil Moisture Dynamics ◽  
Basin Scale ◽  
Moisture Dynamics

Abstract. Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Besides in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors on board of airborne and/or satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit-A (NOAA-AMSU-A) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months (3 March 2010–18 May 2010), was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements were carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5 yr data time series) was made using soil moisture simulated by a hydrological model. Measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both time series of indices have been filtered by means of an exponential filter to account for the fact that microwave sensors only provide information at the skin surface. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the general trend of soil moisture, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI.

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