High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km&#178;) and Rott (55 km&#178;) river catchments in southern Germany, covering a five month period (Jun&#8211;Oct 2016).The sensitivity of 7 land surface parameters is tested using the Latin-Hypercube One-factor-At-a-Time (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent Parameter Estimation and Uncertainty Analysis software (PEST).The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.

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High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

10.5194/hess-2019-478 ◽

2019 ◽

Cited By ~ 1

Author(s):

Benjamin Fersch ◽

Alfonso Senatore ◽

Bianca Adler ◽

Joël Arnault ◽

Matthias Mauder ◽

...

Keyword(s):

Boundary Layer ◽

Land Surface ◽

Hydrological Modeling ◽

Weather Prediction ◽

Surface Model ◽

Near Surface ◽

Ground Heat Flux ◽

The Impact ◽

Fully Coupled ◽

Regional Water

Abstract. The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or largely bound to traditional disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. This study examines the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assesses the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the preAlpine Terrestrial Environmental Observatory (TERENO-preAlpine) for the Ammer (600 km2) and Rott (55 km2) river catchments in southern Germany, covering a five month period (Jun–Oct 2016). The sensitivity of 7 land surface parameters is tested using the Latin-Hypercube One-factor-At-a-Time (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent Parameter Estimation and Uncertainty Analysis software (PEST). The calibration of the offline WRF-Hydro gives Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro, both using the calibrated parameters from the offline model, shows nominal alterations for radiation and precipitation but considerable changes for moisture- and heat fluxes. By comparison with TERENO-preAlpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.

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High-resolution fully coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

Hydrology and Earth System Sciences ◽

10.5194/hess-24-2457-2020 ◽

2020 ◽

Vol 24 (5) ◽

pp. 2457-2481 ◽

Cited By ~ 4

Author(s):

Benjamin Fersch ◽

Alfonso Senatore ◽

Bianca Adler ◽

Joël Arnault ◽

Matthias Mauder ◽

...

Keyword(s):

Boundary Layer ◽

Land Surface ◽

Hydrological Modeling ◽

Weather Prediction ◽

Surface Model ◽

Near Surface ◽

Ground Heat Flux ◽

The Impact ◽

Fully Coupled ◽

Regional Water

Abstract. The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases, and energy. Nonlinear feedback and scale-dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local-area weather prediction. This study examines the ability of the hydrologically enhanced version of the Weather Research and Forecasting model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assesses the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identically calibrated parameter settings for the land surface model (Noah-Multiparametrization; Noah-MP). The simulations are evaluated based on extensive observations at the Terrestrial Environmental Observatories (TERENO) Pre-Alpine Observatory for the Ammer (600 km2) and Rott (55 km2) river catchments in southern Germany, covering a 5-month period (June–October 2016). The sensitivity of seven land surface parameters is tested using the Latin-Hypercube–One-factor-At-a-Time (LH-OAT) method, and six sensitive parameters are subsequently optimized for six different subcatchments, using the model-independent Parameter Estimation and Uncertainty Analysis software (PEST). The calibration of the offline WRF-Hydro gives Nash–Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of the classic WRF and fully coupled WRF-Hydro models, both using the calibrated parameters from the offline model, shows only tiny alterations for radiation and precipitation but considerable changes for moisture and heat fluxes. By comparison with TERENO Pre-Alpine Observatory measurements, the fully coupled model slightly outperforms the classic WRF model with respect to evapotranspiration, sensible and ground heat flux, the near-surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation, whereas soil moisture and precipitation change randomly.

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Dome effect of black carbon and its key influencing factors: A one-dimensional modelling study

10.5194/acp-2017-967 ◽

2017 ◽

Author(s):

Zilin Wang ◽

Xin Huang ◽

Aijun Ding

Keyword(s):

Boundary Layer ◽

Air Pollution ◽

Black Carbon ◽

Rural Areas ◽

Land Surface ◽

Critical Role ◽

Aerosol Layer ◽

Near Surface ◽

Haze Pollution ◽

The Impact

Abstract. Black carbon (BC) has been identified to play a critical role in aerosol-planet boundary layer (PBL) interaction and further deterioration of near-surface air pollution in megacities, which has been named as its dome effect. However, the impacts of key factors that influence this effect, such as the vertical distribution and aging processes of BC, and also the underlying land surface, have not been quantitatively explored yet. Here, based on available in-situ measurements of meteorology and atmospheric aerosols together with the meteorology-chemistry online coupled model, WRF-Chem, we conduct a set of parallel simulations to quantify the roles of these factors in influencing the BC's dome effect and surface haze pollution, and discuss the main implications of the results to air pollution mitigation in China. We found that the impact of BC on PBL is very sensitive to the altitude of aerosol layer. The upper level BC, especially those near the capping inversion, is more essential in suppressing the PBL height and weakening the turbulence mixing. The dome effect of BC tends to be significantly intensified as BC aerosol mixed with scattering aerosols during winter haze events, resulting in a decrease of PBL height by more than 25 %. In addition, the dome effect is more substantial (up to 15 %) in rural areas than that in the urban areas with the same BC loading, indicating an unexpected regional impact of such kind of effect to air quality in countryside. This study suggests that China's regional air pollution would greatly benefit from BC emission reductions, especially those from the elevated sources from the chimneys and also the domestic combustions in rural areas, through weakening the aerosol-boundary layer interactions that triggered by BC.

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The Impact of Error Accounting in a Bayesian Approach to Calibrating Modeled Turbulent Fluxes in an Open-Canopy Forest

Journal of Hydrometeorology ◽

10.1175/jhm-d-17-0030.1 ◽

2017 ◽

Vol 18 (7) ◽

pp. 2029-2042

Author(s):

Tony E. Wong ◽

William Kleiber ◽

David C. Noone

Keyword(s):

Markov Chain ◽

Land Surface ◽

Hydrological Modeling ◽

Soil Layer ◽

Turbulent Fluxes ◽

Surface Model ◽

Model Parameters ◽

Top Soil ◽

The Impact ◽

Calibration Approach

Abstract Land surface models are notorious for containing many parameters that control the exchange of heat and moisture between land and atmosphere. Properly modeling the partitioning of total evapotranspiration (ET) between transpiration and evaporation is critical for accurate hydrological modeling, but depends heavily on the treatment of turbulence within and above canopies. Previous work has constrained estimates of evapotranspiration and its partitioning using statistical approaches that calibrate land surface model parameters by assimilating in situ measurements. These studies, however, are silent on the impacts of the accounting of uncertainty within the statistical calibration framework. The present study calibrates the aerodynamic, leaf boundary layer, and stomatal resistance parameters, which partially control canopy turbulent exchange and thus the evapotranspiration flux partitioning. Using an adaptive Metropolis–Hastings algorithm to construct a Markov chain of draws from the joint posterior distribution of these resistance parameters, an ensemble of model realizations is generated, in which latent and sensible heat fluxes and top soil layer temperature are optimized. A set of five calibration experiments demonstrate that model performance is sensitive to the accounting of various sources of uncertainty in the field observations and model output and that it is critical to account for model structural uncertainty. After calibration, the modeled fluxes and top soil layer temperature are largely free from bias, and this calibration approach successfully informs and characterizes uncertainty in these parameters, which is essential for model improvement and development. The key points of this paper are 1) a Markov chain Monte Carlo calibration approach successfully improves modeled turbulent fluxes; 2) ET partitioning estimates hinge on the representation of uncertainties in the model and data; and 3) despite these inherent uncertainties, constrained posterior estimates of ET partitioning emerge.

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2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1705-2013 ◽

2013 ◽

Vol 17 (5) ◽

pp. 1705-1714 ◽

Cited By ~ 21

Author(s):

F. Zabel ◽

W. Mauser

Keyword(s):

Heat Flux ◽

Land Surface ◽

Regional Climate ◽

Surface Processes ◽

Surface Model ◽

Land Surface Processes ◽

Near Surface ◽

Danube Catchment ◽

Simulated Precipitation ◽

The Impact

Abstract. Most land surface hydrological models (LSHMs) consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice) in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs) generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM) within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2) and the atmospheric part of the RCM MM5 (45 × 45 km2). The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both spatially and temporally. The distribution of precipitation follows the coarse topography representation in MM5, resulting in a spatial shift of maximum precipitation northwards of the Alps. Consequently, simulation of river runoff inherits precipitation biases from MM5. However, by comparing the water balance, the bias of annual average runoff was improved from 21.2% (NOAH/MM5) to 4.4% (PROMET/MM5) when compared to measurements at the outlet gauge of the Upper Danube watershed in Achleiten.

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The CSIRO Mk3L climate system model v1.0 coupled to the CABLE land surface scheme v1.4b: evaluation of the control climatology

Geoscientific Model Development ◽

10.5194/gmd-4-1115-2011 ◽

2011 ◽

Vol 4 (4) ◽

pp. 1115-1131 ◽

Cited By ~ 16

Author(s):

J. Mao ◽

S. J. Phipps ◽

A. J. Pitman ◽

Y. P. Wang ◽

G. Abramowitz ◽

...

Keyword(s):

Land Surface ◽

Land Surface Model ◽

Climate System ◽

System Model ◽

Surface Model ◽

Climate System Model ◽

Near Surface ◽

Land Surface Scheme ◽

Surface Scheme ◽

The Impact

Abstract. The CSIRO Mk3L climate system model, a reduced-resolution coupled general circulation model, has previously been described in this journal. The model is configured for millennium scale or multiple century scale simulations. This paper reports the impact of replacing the relatively simple land surface scheme that is the default parameterisation in Mk3L with a sophisticated land surface model that simulates the terrestrial energy, water and carbon balance in a physically and biologically consistent way. An evaluation of the new model's near-surface climatology highlights strengths and weaknesses, but overall the atmospheric variables, including the near-surface air temperature and precipitation, are simulated well. The impact of the more sophisticated land surface model on existing variables is relatively small, but generally positive. More significantly, the new land surface scheme allows an examination of surface carbon-related quantities including net primary productivity which adds significantly to the capacity of Mk3L. Overall, results demonstrate that this reduced-resolution climate model is a good foundation for exploring long time scale phenomena. The addition of the more sophisticated land surface model enables an exploration of important Earth System questions including land cover change and abrupt changes in terrestrial carbon storage.

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Microscale Numerical Prediction over Montreal with the Canadian External Urban Modeling System

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-013.1 ◽

2011 ◽

Vol 50 (12) ◽

pp. 2410-2428 ◽

Cited By ~ 31

Author(s):

Sylvie Leroyer ◽

Stéphane Bélair ◽

Jocelyn Mailhot ◽

Ian B. Strachan

Keyword(s):

Land Surface ◽

Deterministic Model ◽

Weather Prediction ◽

Grid Size ◽

Metropolitan Region ◽

Balance Model ◽

Surface Model ◽

Limited Area ◽

Computational Domain ◽

Near Surface

AbstractThe Canadian urban and land surface external modeling system (known as urban GEM-SURF) has been developed to provide surface and near-surface meteorological variables to improve numerical weather prediction and to become a tool for environmental applications. The system is based on the Town Energy Balance model for the built-up covers and on the Interactions between the Surface, Biosphere, and Atmosphere land surface model for the natural covers. It is driven by coarse-resolution forecasts from the 15-km Canadian regional operational model. This new system was tested for a 120-m grid-size computational domain covering the Montreal metropolitan region from 1 May to 30 September 2008. The numerical results were first evaluated against local observations of the surface energy budgets, air temperature, and humidity taken at the Environmental Prediction in Canadian Cities (EPiCC) field experiment tower sites. As compared with the regional deterministic 15-km model, important improvements have been achieved with this system over urban and suburban sites. GEM-SURF’s ability to simulate the Montreal surface urban heat island was also investigated, and the radiative surface temperatures from this system and from two systems operational at the Meteorological Service of Canada were compared, that is, the 15-km regional deterministic model and the so-called limited-area model with 2.5-km grid size. Comparison of urban GEM-SURF outputs with remotely sensed observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals relatively good agreement for urban and natural areas.

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Diagnosing Moisture Sources for Flash Floods in the United States. Part II: Terrestrial and Oceanic Sources of Moisture

Journal of Hydrometeorology ◽

10.1175/jhm-d-18-0120.1 ◽

2019 ◽

Vol 20 (8) ◽

pp. 1511-1531 ◽

Cited By ~ 4

Author(s):

Jessica M. Erlingis ◽

Jonathan J. Gourley ◽

Jeffrey B. Basara

Keyword(s):

United States ◽

Boundary Layer ◽

Land Surface ◽

Flash Flood ◽

The United States ◽

Flash Floods ◽

Heat Fluxes ◽

Surface Model ◽

Positive Anomaly ◽

The Impact

Abstract Backward trajectories were derived from North American Regional Reanalysis data for 19 253 flash flood reports published by the National Weather Service to determine the along-path contribution of the land surface to the moisture budget for flash flood events in the conterminous United States. The impact of land surface interactions was evaluated seasonally and for six regions: the West Coast, Arizona, the Front Range, Flash Flood Alley, the Missouri Valley, and the Appalachians. Parcels were released from locations that were impacted by flash floods and traced backward in time for 120 h. The boundary layer height was used to determine whether moisture increases occurred within the boundary layer or above it. Moisture increases occurring within the boundary layer were attributed to evapotranspiration from the land surface, and surface properties were recorded from an offline run of the Noah land surface model. In general, moisture increases attributed to the land surface were associated with anomalously high surface latent heat fluxes and anomalously low sensible heat fluxes (resulting in a positive anomaly of evaporative fraction) as well as positive anomalies in top-layer soil moisture. Over the ocean, uptakes were associated with positive anomalies in sea surface temperatures, the magnitude of which varies both regionally and seasonally. Major oceanic surface-based source regions of moisture for flash floods in the United States include the Gulf of Mexico and the Gulf of California, while boundary layer moisture increases in the southern plains are attributable in part to interactions between the land surface and the atmosphere.

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Examining the Impact of SMAP Soil Moisture Retrievals on Short-Range Weather Prediction under Weakly and Strongly Coupled Data Assimilation with WRF-Noah

Monthly Weather Review ◽

10.1175/mwr-d-19-0017.1 ◽

2019 ◽

Vol 147 (12) ◽

pp. 4345-4366 ◽

Cited By ~ 2

Author(s):

Liao-Fan Lin ◽

Zhaoxia Pu

Keyword(s):

Soil Moisture ◽

Data Assimilation ◽

Land Surface ◽

Weather Prediction ◽

Surface Model ◽

Strongly Coupled ◽

Soil Moisture Data ◽

Analysis Scheme ◽

Coupled Data Assimilation ◽

The Impact

Abstract Remotely sensed soil moisture data are typically incorporated into numerical weather models under a framework of weakly coupled data assimilation (WCDA), with a land surface analysis scheme independent from the atmospheric analysis component. In contrast, strongly coupled data assimilation (SCDA) allows simultaneous correction of atmospheric and land surface states but has not been sufficiently explored with land surface soil moisture data assimilation. This study implemented a variational approach to assimilate the Soil Moisture Active Passive (SMAP) 9-km enhanced retrievals into the Noah land surface model coupled with the Weather Research and Forecasting (WRF) Model under a framework of both WCDA and SCDA. The goal of the study is to quantify the relative impact of assimilating SMAP data under different coupling frameworks on the atmospheric forecasts in the summer. The results of the numerical experiments during July 2016 show that SCDA can provide additional benefits on the forecasts of air temperature and humidity compared to WCDA. Over the U.S. Great Plains, assimilation of SMAP data under WCDA reduces a warm bias in temperature and a dry bias in humidity by 7.3% and 19.3%, respectively, while the SCDA case contributes an additional bias reduction of 2.2% (temperature) and 3.3% (humidity). While WCDA leads to a reduction of RMSE in temperature forecasts by 4.1%, SCDA results in additional reduction of RMSE by 0.8%. For the humidity, the reduction of RMSE is around 1% for both WCDA and SCDA.

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Parametrizating Soil Surface Fluxes in the JULES Land Surface Model

10.5194/ismc2021-49 ◽

2021 ◽

Author(s):

John Edwards

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Heat Waves ◽

Numerical Models ◽

Weather Prediction ◽

Land Surface Model ◽

Soil Surface ◽

Current Status ◽

Surface Model ◽

The Impact

The parametrization of land-atmosphere interactions in numerical weather prediction and climate models is a topic of active and growing interest, especially in connection with extreme events such as heat waves and droughts. Semiarid regions are sensitive to drought and are currently expanding, but they are often poorly represented in numerical models. On forecasting timescales, comparisons of simulated land surface temperature against retrievals from satellites often show significant cold biases around noon, whilst, on climate timescales, land surface models often fail to represent droughts realistically. Inadequate treatment of the land surface, and particularly of soil properties and soil moisture, is likely to contribute to such errors. Efforts to develop improved parametrizations of soil processes in the JULES land surface model for application in weather prediction and climate simulations are underway. Whilst processes at the soil surface are a central part of this, to obtain acceptable performance it is also important to consider the surface flux budget as a whole, including the treatment of the plant canopy. Here, we shall describe the current status of developments aimed at improving the representation of evapotranspiration and ground heat fluxes in the model, noting the major issues encountered. The importance of accurately representing the impact of soil moisture on thermal properties will be stressed. Results from initial studies will be presented and we shall offer a perspective on future developments.

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