Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables

The warming climate significantly modifies the global water cycle. Global evapotranspiration has increased over the past decades, yet climate models agree on the drying trend of land surface. In this study, we conducted an intercomparison analysis of the surface energy partitioning across Coupled Model Intercomparison Phase 5 (CMIP5) simulations and evaluated its behaviour with surface temperature and soil moisture anomalies, against the theoretically derived thermodynamic formula. Different responses over land and sea surfaces to elevated greenhouse gas emissions were found. Under the Representative Concentration Pathway of +8.5 W m−2 (RCP8.5) warming scenario, the multi-model mean relative efficiency anomaly from CMIP5 simulations is 3.83 and −0.12 over global sea and land, respectively. The significant anomaly over sea was captured by the thermodynamic solution based on the principle of maximum entropy production, with a mean relative error of 14.6%. The declining trend over land was also reproduced, but an accurate prediction of its small anomaly will require the inclusions of complex physical processes in future work. Despite increased potential evapotranspiration under rising temperatures, both CMIP5 simulations and thermodynamic principles suggest that the soil moisture-temperature feedback cannot support long-term enhanced evapotranspiration at the global scale. The dissipation of radiative forcing eventually shifts towards sensible heat flux and accelerates the warming over land, especially over South America and Europe.

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Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications

Journal of Applied Meteorology and Climatology ◽

10.1175/2008jamc1662.1 ◽

2009 ◽

Vol 48 (2) ◽

pp. 349-368 ◽

Cited By ~ 45

Author(s):

Dev Niyogi ◽

Kiran Alapaty ◽

Sethu Raman ◽

Fei Chen

Keyword(s):

Boundary Layer ◽

Soil Moisture ◽

Gas Exchange ◽

Surface Energy ◽

Land Surface ◽

Weather Forecasting ◽

Stomatal Resistance ◽

Surface Fluxes ◽

Surface Model ◽

Area Index

Abstract Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.

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Auto-calibration System Developed to Assimilate AMSR-E Data into a Land Surface Model for Estimating Soil Moisture and the Surface Energy Budget

Journal of the Meteorological Society of Japan Ser II ◽

10.2151/jmsj.85a.229 ◽

2007 ◽

Vol 85A ◽

pp. 229-242 ◽

Cited By ~ 118

Author(s):

Kun YANG ◽

Takahiro WATANABE ◽

Toshio KOIKE ◽

Xin LI ◽

Hideyuki FUJII ◽

...

Keyword(s):

Soil Moisture ◽

Surface Energy ◽

Energy Budget ◽

Land Surface ◽

Land Surface Model ◽

Surface Energy Budget ◽

Surface Model ◽

Calibration System

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Simulated and Observed Surface Energy Fluxes and Resulting Playa Breezes during the MATERHORN Field Campaigns

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0161.1 ◽

2017 ◽

Vol 56 (4) ◽

pp. 915-935 ◽

Cited By ~ 8

Author(s):

Jeffrey D. Massey ◽

W. James Steenburgh ◽

Sebastian W. Hoch ◽

Derek D. Jensen

Keyword(s):

Heat Flux ◽

Soil Moisture ◽

Surface Energy ◽

Land Surface ◽

Land Surface Model ◽

Surface Model ◽

Desert Shrub ◽

Noah Land Surface Model ◽

Field Campaigns ◽

Land Surfaces

AbstractWeather Research and Forecasting (WRF) Model simulations of the autumn 2012 and spring 2013 Mountain Terrain Atmospheric Modeling and Observations Program (MATERHORN) field campaigns are validated against observations of components of the surface energy balance (SEB) collected over contrasting desert-shrub and playa land surfaces of the Great Salt Lake Desert in northwestern Utah. Over the desert shrub, a large underprediction of sensible heat flux and an overprediction of ground heat flux occurred during the autumn campaign when the model-analyzed soil moisture was considerably higher than the measured soil moisture. Simulations that incorporate in situ measurements of soil moisture into the land surface analyses and use a modified parameterization for soil thermal conductivity greatly reduce these errors over the desert shrub but exacerbate the overprediction of latent heat flux over the playa. The Noah land surface model coupled to WRF does not capture the many unusual playa land surface processes, and simulations that incorporate satellite-derived albedo and reduce the saturation vapor pressure over the playa only marginally improve the forecasts of the SEB components. Nevertheless, the forecast of the 2-m temperature difference between the playa and desert shrub improves, which increases the strength of the daytime off-playa breeze. The stronger off-playa breeze, however, does not substantially reduce the mean absolute errors in overall 10-m wind speed and direction. This work highlights some deficiencies of the Noah land surface model over two common arid land surfaces and demonstrates the importance of accurate land surface analyses over a dryland region.

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Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions

10.5194/bg-2018-201 ◽

2018 ◽

Cited By ~ 2

Author(s):

Michael M. Loranty ◽

Benjamin W. Abbott ◽

Daan Blok ◽

Thomas A. Douglas ◽

Howard E. Epstein ◽

...

Keyword(s):

Soil Moisture ◽

Thermal Properties ◽

Surface Energy ◽

Terrestrial Ecosystem ◽

Energy Partitioning ◽

Climate Feedback ◽

Permafrost Soil ◽

Thermal Dynamics ◽

Soil Thermal Properties ◽

Permafrost Soils

Abstract. Permafrost soils in arctic and boreal ecosystems store twice the amount of current atmospheric carbon that may be mobilized and released to the atmosphere as greenhouse gases when soils thaw under a warming climate. This permafrost carbon climate feedback is among the most globally important terrestrial biosphere feedbacks to climate warming, yet its magnitude remains highly uncertain. This uncertainty lies in predicting the rates and spatial extent of permafrost thaw and subsequent carbon cycle processes. Terrestrial ecosystem influences on surface energy partitioning exert strong control on permafrost soil thermal dynamics and are critical for understanding permafrost soil responses to climate change and disturbance. Here we review how arctic and boreal ecosystem processes influence permafrost soils and characterize key ecosystem changes that regulate permafrost responses to climate. While many of the ecosystem characteristics and processes affecting soil thermal dynamics have been examined in isolation, interactions between processes are less well understood. In particular connections between vegetation, soil moisture, and soil thermal properties affecting permafrost conditions could benefit from additional research. In particular, connections between vegetation, soil moisture, and soil thermal properties affecting permafrost could benefit from additional research. Changes in ecosystem distribution and vegetation characteristics will alter spatial patterns of interactions between climate and permafrost. In addition to shrub expansion, other vegetation responses to changes in climate and disturbance regimes will all affect ecosystem surface energy partitioning in ways that are important for permafrost. Lastly, changes in vegetation and ecosystem distribution will lead to regional and global biophysical and biogeochemical climate feedbacks that may compound or offset local impacts on permafrost soils. Consequently, accurate prediction of the permafrost carbon climate feedback will require detailed understanding of changes in terrestrial ecosystem distribution and function and the net effects of multiple feedback processes operating across scales in space and time.

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Evaluating the land-surface energy partitioning in ERA5

Geoscientific Model Development ◽

10.5194/gmd-13-4159-2020 ◽

2020 ◽

Vol 13 (9) ◽

pp. 4159-4181 ◽

Cited By ~ 2

Author(s):

Brecht Martens ◽

Dominik L. Schumacher ◽

Hendrik Wouters ◽

Joaquín Muñoz-Sabater ◽

Niko E. C. Verhoest ◽

...

Keyword(s):

Heat Flux ◽

Surface Energy ◽

Latent Heat ◽

Latent Heat Flux ◽

Land Surface ◽

Energy Partitioning ◽

Data Sets ◽

Near Surface ◽

Surface Latent Heat Flux

Abstract. Climate reanalyses provide a plethora of global atmospheric and surface parameters in a consistent manner over multi-decadal timescales. Hence, they are widely used in many fields, and an in-depth evaluation of the different variables provided by reanalyses is a necessary means to provide feedback on the quality to their users and the operational centres producing these data sets, and to help guide their development. Recently, the European Centre for Medium-Range Weather Forecasts (ECMWF) released the new state-of-the-art climate reanalysis ERA5, following up on its popular predecessor ERA-Interim. Different sets of variables from ERA5 were already evaluated in a handful of studies, but so far, the quality of land-surface energy partitioning has not been assessed. Here, we evaluate the surface energy partitioning over land in ERA5 and concentrate on the appraisal of the surface latent heat flux, surface sensible heat flux, and Bowen ratio against different reference data sets and using different modelling tools. Most of our analyses point towards a better quality of surface energy partitioning in ERA5 than in ERA-Interim, which may be attributed to a better representation of land-surface processes in ERA5 and certainly to the better quality of near-surface meteorological variables. One of the key shortcomings of the reanalyses identified in our study is the overestimation of the surface latent heat flux over land, which – although substantially lower than in ERA-Interim – still remains in ERA5. Overall, our results indicate the high quality of the surface turbulent fluxes from ERA5 and the general improvement upon ERA-Interim, thereby endorsing the efforts of ECMWF to improve their climate reanalysis and to provide useful data to many scientific and operational fields.

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The improvement of soil thermodynamics and its effects on land surface meteorology in the IPSL climate model

Geoscientific Model Development ◽

10.5194/gmd-9-363-2016 ◽

2016 ◽

Vol 9 (1) ◽

pp. 363-381 ◽

Cited By ~ 16

Author(s):

F. Wang ◽

F. Cheruy ◽

J.-L. Dufresne

Keyword(s):

Soil Moisture ◽

Thermal Properties ◽

Surface Energy ◽

Surface Temperature ◽

Energy Budget ◽

Land Surface ◽

Climate Model ◽

Surface Energy Budget ◽

Dry Areas ◽

Soil Thermal Properties

Abstract. This paper describes the implementation of an improved soil thermodynamics in the hydrological module of Earth system model (ESM) developed at the Institut Pierre Simon Laplace (IPSL) and its effects on land surface meteorology in the IPSL climate model. A common vertical discretization scheme for the soil moisture and for the soil temperature is adopted. In addition to the heat conduction process, the heat transported by liquid water into the soil is modeled. The thermal conductivity and the heat capacity are parameterized as a function of the soil moisture and the texture. Preliminary tests are performed in an idealized 1-D (one-dimensional) framework and the full model is then evaluated in the coupled land–atmospheric module of the IPSL ESM. A nudging approach is used in order to avoid the time-consuming long-term simulations required to account for the natural variability of the climate. Thanks to this nudging approach, the effects of the modified parameterizations can be modeled. The dependence of the soil thermal properties on moisture and texture lead to the most significant changes in the surface energy budget and in the surface temperature, with the strongest effects on the surface energy budget taking place over dry areas and during the night. This has important consequences on the mean surface temperature over dry areas and during the night and on its short-term variability. The parameterization of the soil thermal properties could therefore explain some of the temperature biases and part of the dispersion over dry areas in simulations of extreme events such as heat waves in state-of-the-art climate models.

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