Development and testing of a fully-coupled subsurface-land surface-atmosphere hydrometeorological model: High-resolution application in urban terrains

Urban Climate ◽  
2021 ◽  
Vol 40 ◽  
pp. 100985
Author(s):  
Mahdad Talebpour ◽  
Claire Welty ◽  
Elie Bou-Zeid
2018 ◽  
Vol 22 (15) ◽  
pp. 1-19 ◽  
Author(s):  
Xiaolei Fu ◽  
Lifeng Luo ◽  
Ming Pan ◽  
Zhongbo Yu ◽  
Ying Tang ◽  
...  

Abstract Better quantification of the spatiotemporal distribution of soil moisture across different spatial scales contributes significantly to the understanding of land surface processes on the Earth as an integrated system. While observational data for root-zone soil moisture (RZSM) often have sparse spatial coverage, model-simulated soil moisture may provide a useful alternative. TOPMODEL-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS) has been widely studied and actively modified in recent years, while a detailed regional application with evaluation currently is still lacking. Thus, TOPLATS was used to generate high-resolution (30 arc s) RZSM based on coarse-scale (0.125°) forcing data over part of the Arkansas–Red River basin. First, the simulated RZSM was resampled to coarse scale to compare with the results of Mosaic, Noah, and VIC from NLDAS. Second, TOPLATS performance was assessed based on the spatial absolute difference among the models. The comparison shows that TOPLATS performance is similar to VIC, but different from Mosaic and Noah. Last, the simulated RZSM was compared with in situ observations of 16 stations in the study area. The results suggest that the simulated spatial distribution of RZSM is largely consistent with the distribution of topographic index (TI) in most instances, as topography was traditionally considered a major, but not the only, factor in horizontal redistribution of soil moisture. In addition, the finer-resolution RZSM can reflect the in situ soil moisture change at most local sites to a certain degree. The evaluation confirms that TOPLATS is a useful tool to estimate high-resolution soil moisture and has great potential to provide regional soil moisture estimates.


Author(s):  
Luca Furnari ◽  
Linus Magnusson ◽  
Giuseppe Mendicino ◽  
Alfonso Senatore

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.


Author(s):  
Josipa Milovac ◽  
Oliver-Lloyd Branch ◽  
Hans-Stefan Bauer ◽  
Thomas Schwitalla ◽  
Kirsten Warrach-Sagi ◽  
...  

2021 ◽  
Author(s):  
◽  
Christine Sgoff

The weather of the atmospheric boundary layer significantly affects our life on Earth. Thus, a realistic modelling of the atmospheric boundary layer is crucial. Hereby, the processes of the atmospheric boundary layer depend on an accurate representation of the land-atmosphere coupling in the model. In this context the land surface temperature (LST) plays an important role. In this thesis, it is examined if the assimilation of LST can lead to improved estimates of the boundary layer and its processes. To properly assimilate the LST retrievals, a suitable model equivalent in the weather prediction model is necessary. In the weather forecast model of the German Weather Service used here, the LST is modelled without a vegetation temperature. To compensate for this deficit, two different vegetation parameterizations were investigated and the better one, a conductivity scheme, was implemented. In order to make optimal use of the influence of the assimilation of the LST observation on the model system, it is useful to pass on the information of the observation to land and atmosphere already in the assimilation step. For that reason, a fully coupled land-atmosphere prediction model was used. Therefore, the existing control vector of the assimilation system, a local ensemble transform Kalman filter, was extended by the soil temperature and moisture. In two-day case studies in March and August 2017, different configurations of the augmented assimilation system were evaluated based on observing system simulation experiments (OSSE). LST was assimilated hourly over two days in the weakly and strongly coupled assimilation system. In addition, every six hours a free 24-hour forecast was simulated. The experiments were validated with the simulated truth (a high-resolution model run) and compared against an experiment without assimilation. It was shown that the prediction of the boundary layer temperature, especially during the day, and the prediction of the soil temperature, during the whole day and night, could be improved. The best impact of LST assimilation was achieved with the fully coupled system. The humidity variables of the model benefited only partially from the LST assimilation. For this reason, covariances in the model ensemble were investigated in more detail. To check their compatibility with the high-resolution model run the ensemble consistency score was introduced. It was found that the covariances between the LST and the temperatures of the high-resolution model run were better represented in the ensemble than those between the LST and the humidity variables.


2020 ◽  
Vol 13 (1) ◽  
pp. 113
Author(s):  
Antonio-Juan Collados-Lara ◽  
Steven R. Fassnacht ◽  
Eulogio Pardo-Igúzquiza ◽  
David Pulido-Velazquez

There is necessity of considering air temperature to simulate the hydrology and management within water resources systems. In many cases, a big issue is considering the scarcity of data due to poor accessibility and limited funds. This paper proposes a methodology to obtain high resolution air temperature fields by combining scarce point measurements with elevation data and land surface temperature (LST) data from remote sensing. The available station data (SNOTEL stations) are sparse at Rocky Mountain National Park, necessitating the inclusion of correlated and well-sampled variables to assess the spatial variability of air temperature. Different geostatistical approaches and weighted solutions thereof were employed to obtain air temperature fields. These estimates were compared with two relatively direct solutions, the LST (MODIS) and a lapse rate-based interpolation technique. The methodology was evaluated using data from different seasons. The performance of the techniques was assessed through a cross validation experiment. In both cases, the weighted kriging with external drift solution (considering LST and elevation) showed the best results, with a mean squared error of 3.7 and 3.6 °C2 for the application and validation, respectively.


Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 396
Author(s):  
Junxia Yan ◽  
Yanfei Ma ◽  
Dongyun Zhang ◽  
Zechen Li ◽  
Weike Zhang ◽  
...  

Land surface evapotranspiration (ET) and gross primary productivity (GPP) are critical components in terrestrial ecosystems with water and carbon cycles. Large-scale, high-resolution, and accurately quantified ET and GPP values are important fundamental data for freshwater resource management and help in understanding terrestrial carbon and water cycles in an arid region. In this study, the revised surface energy balance system (SEBS) model and MOD17 GPP algorithm were used to estimate daily ET and GPP at 100 m resolution based on multi-source satellite remote sensing data to obtain surface biophysical parameters and meteorological forcing data as input variables for the model in the midstream oasis area of the Heihe River Basin (HRB) from 2010 to 2016. Then, we further calculated the ecosystem water-use efficiency (WUE). We validated the daily ET, GPP, and WUE from ground observations at a crop oasis station and conducted spatial intercomparisons of monthly and annual ET, GPP, and WUE at the irrigation district and cropland oasis scales. The site-level evaluation results show that ET and GPP had better performance than WUE at the daily time scale. Specifically, the deviations in the daily ET, GPP, and WUE data compared with ground observations were small, with a root mean square error (RMSE) and mean absolute percent error (MAPE) of 0.75 mm/day and 26.59%, 1.13 gC/m2 and 36.62%, and 0.50 gC/kgH2O and 39.83%, respectively. The regional annual ET, GPP, and WUE varied from 300 to 700 mm, 200 to 650 gC/m2, and 0.5 to 1.0 gC/kgH2O, respectively, over the entire irrigation oasis area. It was found that annual ET and GPP were greater than 550 mm and 500 gC/m2, and annual oasis cropland WUE had strong invariability and was maintained at approximately 0.85 gC/kgH2O. The spatial intercomparisons from 2010 to 2016 revealed that ET had similar spatial patterns to GPP due to tightly coupled carbon and water fluxes. However, the WUE spatiotemporal patterns were slightly different from both ET and GPP, particularly in the early and late growing seasons for the oasis area. Our results demonstrate that spatial full coverage and reasonably fine spatiotemporal variation and variability could significantly improve our understanding of water-saving irrigation strategies and oasis agricultural water management practices in the face of water shortage issues.


2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Dirk Nikolaus Karger ◽  
Olaf Conrad ◽  
Jürgen Böhner ◽  
Tobias Kawohl ◽  
Holger Kreft ◽  
...  

2016 ◽  
Vol 52 (4) ◽  
pp. 950-964 ◽  
Author(s):  
Alan D. Snow ◽  
Scott D. Christensen ◽  
Nathan R. Swain ◽  
E. James Nelson ◽  
Daniel P. Ames ◽  
...  

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