scholarly journals Closing the Energy Balance using a Canopy Heat Capacity – A physically based Approach for the Land Component JSBACHv3.11

2018 ◽  
Author(s):  
Marvin Heidkamp ◽  
Andreas Chlond ◽  
Felix Ament
Keyword(s):  
Heat Capacity ◽  
Energy Balance ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Climate Models ◽  
Finite Thickness ◽  
Soil Layer ◽  
Surface Fluxes ◽  
Delayed Response ◽  
Stable Conditions

Abstract. Land surface-atmosphere interaction is one of the most important characteristic for understanding the terrestrial climate system, as it determines the exchange fluxes of energy and water between the land and the overlying air mass. In several current climate models, it is common practice to use an unphysical approach to close the surface energy balance within the uppermost soil layer with finite thickness and heat capacity. In this study, a different approach is investigated by means of a physical based estimation of the canopy heat capacity SkIn+. Therefore, in a first step, results of an offline simulation of the land component JSBACH of the MPI-ESM – constrained with atmospheric observations – are compared to energy- and water fluxes derived from eddy covariance measurements observed at the CASES-99 field experiment in Kansas where only shallow vegetation prevails. This comparison of energy and evapotranspiration fluxes with observations at the site-level provides an assessment of the model's capacity to correctly reproduce the coupling between the land and the atmosphere throughout the diurnal cycle. In a further step, a global coupled land-atmosphere experiment is performed using an AMIP type simulation over thirty years to evaluate the regional impact of the SkIn+ scheme on longer time scale, in particular, in respect to the effect of the canopy heat capacity. The results of the offline experiment show that SkIn+ leads to a warming during the day and to a cooling in the night relative to the old reference scheme, thereby improving the performance in the representation of the modeled surface fluxes on diurnal time scales. In particular: nocturnal heat releases unrealistically destroying the stable boundary layer disappear and phase errors are removed. On the global scale, for regions with no or low vegetation and a pronounced diurnal cycle, the nocturnal cooling prevails due to the fact that stable conditions at night maintain the delayed response in temperature, whereas the daytime turbulent exchange amplifies it. For the tropics and boreal forests as well as high latitudes, the scheme tends to warm the system.

scholarly journals Closing the energy balance using a canopy heat capacity and storage concept – a physically based approach for the land component JSBACHv3.11

2018 ◽  
Vol 11 (8) ◽  
pp. 3465-3479 ◽  
Author(s):  
Marvin Heidkamp ◽  
Andreas Chlond ◽  
Felix Ament
Keyword(s):  
Heat Capacity ◽  
Energy Balance ◽  
Diurnal Cycle ◽  
Heat Storage ◽  
Finite Thickness ◽  
Soil Layer ◽  
Surface Fluxes ◽  
Delayed Response ◽  
Stable Conditions ◽  
Physically Based

Abstract. Land surface–atmosphere interaction is one of the most important characteristic for understanding the terrestrial climate system, as it determines the exchange fluxes of energy and water between the land and the overlying air mass. In several current climate models, it is common practice to use an unphysical approach to close the surface energy balance within the uppermost soil layer with finite thickness and heat capacity. In this study, a different approach is investigated by means of a physically based estimation of the canopy heat storage (SkIn+). Therefore, as a first step, results of an offline simulation of the land component JSBACH of the Max Planck Institute Earth system model (MPI-ESM) – constrained with atmospheric observations – are compared to energy fluxes and water fluxes derived from eddy covariance measurements observed at the CASES-99 field experiment in Kansas, where shallow vegetation prevails. This comparison of energy and evapotranspiration fluxes with observations at the site-level provides an assessment of the model's capacity to correctly reproduce the diurnal cycle. Following this, a global coupled land–atmosphere experiment is performed using an AMIP (Atmospheric Model Intercomparison Project) type simulation over 30 years to evaluate the regional impact of the SkIn+ scheme on a longer timescale, in particular, with respect to the effect of the canopy heat storage. The results of the offline experiment show that SkIn+ leads to a warming during the day and to a cooling at night relative to the old reference scheme, thereby improving the performance in the representation of the modeled surface fluxes on diurnal timescales. In particular: nocturnal heat releases unrealistically destroying the stable boundary layer disappear and phase errors are removed. On the global scale, for regions with no or low vegetation and a pronounced diurnal cycle, the nocturnal cooling prevails due to the fact that stable conditions at night maintain the delayed response in temperature, whereas the daytime turbulent exchange amplifies it. For the tropics and boreal forests as well as high latitudes, the scheme tends to warm the system.

scholarly journals Development of a Unified Land Model for Prediction of Surface Hydrology and Land–Atmosphere Interactions

2011 ◽  
Vol 12 (6) ◽  
pp. 1299-1320 ◽  
Author(s):  
Ben Livneh ◽  
Pedro J. Restrepo ◽  
Dennis P. Lettenmaier
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Climate Models ◽  
A Priori ◽  
Model Performance ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Frozen Soil ◽  
Surface Model ◽  
Soil Moisture Accounting

Abstract A unified land model (ULM) is described that combines the surface flux parameterizations in the Noah land surface model (used in most of NOAA’s coupled weather and climate models) with the Sacramento Soil Moisture Accounting model (Sac; used for hydrologic prediction within the National Weather Service). The motivation was to develop a model that has a history of strong hydrologic performance while having the ability to be run in the coupled land–atmosphere environment. ULM takes the vegetation, snow model, frozen soil, and evapotranspiration schemes from Noah and merges them with the soil moisture accounting scheme from Sac. ULM surface fluxes, soil moisture, and streamflow simulations were evaluated through comparisons with observations from the Ameriflux (surface flux), Illinois Climate Network (soil moisture), and Model Parameter Estimation Experiment (MOPEX; streamflow) datasets. Initially, a priori parameters from Sac and Noah were used, which resulted in ULM surface flux simulations that were comparable to those produced by Noah (Sac does not predict surface energy fluxes). ULM with the a priori parameters had streamflow simulation skill that was generally similar to Sac’s, although it was slightly better (worse) for wetter (more arid) basins. ULM model performance using a set of parameters identified via a Monte Carlo search procedure lead to substantial improvements relative to the a priori parameters. A scheme for transfer of parameters from streamflow simulations to nearby flux and soil moisture measurement points was also evaluated; this approach did not yield conclusive improvements relative to the a priori parameters.

scholarly journals Effects of Land Surface Schemes on WRF-Simulated Geopotential Heights over China in Summer 2003*

2016 ◽  
Vol 17 (3) ◽  
pp. 829-851 ◽  
Author(s):  
Xin-Min Zeng ◽  
B. Wang ◽  
Y. Zhang ◽  
Y. Zheng ◽  
N. Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Surface Fluxes ◽  
Forecast Errors ◽  
Large Area ◽  
Pressure Fields ◽  
Temperature And Pressure

Abstract To quantify and explain effects of different land surface schemes (LSSs) on simulated geopotential height (GPH) fields, we performed simulations over China for the summer of 2003 using 12-member ensembles with the Weather Research and Forecasting (WRF) Model, version 3. The results show that while the model can generally simulate the seasonal and monthly mean GPH patterns, the effects of the LSS choice on simulated GPH fields are substantial, with the LSS-induced differences exceeding 10 gpm over a large area (especially the northwest) of China, which is very large compared with climate anomalies and forecast errors. In terms of the assessment measures for the four LSS ensembles [namely, the five-layer thermal diffusion scheme (SLAB), the Noah LSS (NOAH), the Rapid Update Cycle LSS (RUC), and the Pleim–Xiu LSS (PLEX)] in the WRF, the PLEX ensemble is the best, followed by the NOAH, RUC, and SLAB ensembles. The sensitivity of the simulated 850-hPa GPH is more significant than that of the 500-hPa GPH, with the 500-hPa GPH difference fields generally characterized by two large areas with opposite signs due to the smoothly varying nature of GPHs. LSS-induced GPH sensitivity is found to be higher than the GPH sensitivity induced by atmospheric boundary layer schemes. Moreover, theoretical analyses show that the LSS-induced GPH sensitivity is mainly caused by changes in surface fluxes (in particular, sensible heat flux), which further modify atmospheric temperature and pressure fields. The temperature and pressure fields generally have opposite contributions to changes in the GPH. This study emphasizes the importance of choosing and improving LSSs for simulating seasonal and monthly GPHs using regional climate models.

scholarly journals Model Estimates of Land-Driven Predictability in a Changing Climate from CCSM4

2013 ◽  
Vol 26 (21) ◽  
pp. 8495-8512 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Sanjiv Kumar ◽  
Michael J. Fennessy ◽  
Eric L. Altshuler ◽  
Timothy DelSole ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Land Surface ◽  
Climate Models ◽  
Temporal Structure ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Ensemble Forecasts ◽  
Climate System Model ◽  
Subsurface Soil

Abstract The climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future settings. Predictability is defined in terms of the model's ability to predict its own interannual variability. Predictability from the land surface in this model is relatively weak compared to estimates from other climate models but has much of the same spatial and temporal structure found in previous studies. Several factors appear to contribute to the weakness, including a low correlation between surface fluxes and subsurface soil moisture, less soil moisture memory (lagged autocorrelation) than other models or observations, and relative insensitivity of the atmospheric boundary layer to surface flux variations. Furthermore, subseasonal cyclical behavior in plant phenology for tropical grasses introduces spurious unrealistic predictability at low latitudes during dry seasons. Despite these shortcomings, intriguing changes in predictability are found. Areas of historical land use change appear to have experienced changes in predictability, particularly where agriculture expanded dramatically into the Great Plains of North America, increasing land-driven predictability there. In a warming future climate, land–atmosphere coupling strength generally increases, but added predictability does not always follow; many other factors modulate land-driven predictability.

scholarly journals TopoSCALE: deriving surface fluxes from gridded climate data

2013 ◽  
Vol 6 (2) ◽  
pp. 3381-3426 ◽  
Author(s):  
J. Fiddes ◽  
S. Gruber
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Climate Models ◽  
Good Description ◽  
Longwave Radiation ◽  
Surface Fluxes ◽  
Swiss Alps ◽  
Climate Data ◽  
Heterogeneous Terrain ◽  
Reference Methods

Abstract. Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by e.g. topography and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that leverages the good description of the atmospheric column provided by climate models, together with high resolution DEM's, to derive a consistent topography-based, scaling of coarse grid climate variables to fine-scale. We test the method together with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure-levels: air temperature, relative humidity, wind speed and incoming longwave radiation. It is expected that this method can be used to improve inputs to numerical simulations in complex and/or remote terrain especially when statistical methods are not possible due to lack of observations i.e. remote areas or future periods.

scholarly journals Simulation of land surface temperatures: comparison of two climate models and satellite retrievals

2009 ◽  
Vol 2 (1) ◽  
pp. 309-340
Author(s):  
J. M. Edwards
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Diurnal Cycle ◽  
Land Surface ◽  
General Circulation ◽  
Climate Models ◽  
Surface Flux ◽  
Spatial Coverage ◽  
Diurnal Range ◽  
Satellite Retrievals

Abstract. Recently there has been significant progress in the retrieval of land surface temperature from satellite observations. Satellite retrievals of surface temperature offer several advantages, including broad spatial coverage, and such data are potentially of great value in assessing general circulation models of the atmosphere. Here, retrievals of the land surface temperature over the contiguous United States are compared with simulations from two climate models. The models generally simulate the diurnal range realistically, but show significant warm biases during the summer. The models' diurnal cycle of surface temperature is related to their surface flux budgets. Differences in the diurnal cycle of the surface flux budget between the models are found to be more pronounced than those in the diurnal cycle of surface temperature.

Local Advection of Momentum, Heat, and Moisture during the Melt of Patchy Snow Covers

1995 ◽  
Vol 34 (7) ◽  
pp. 1705-1715 ◽  
Author(s):  
Glen E. Liston
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Land Surface ◽  
Lower Boundary ◽  
Conservation Equation ◽  
Surface Fluxes ◽  
Balance Model ◽  
Snow Covered Area ◽  
Covered Area ◽  
Heat And Moisture

Abstract A numerical atmospheric boundary layer model, based on higher-order turbulence closure assumptions, is developed and used to simulate the local advection of momentum, heat, and moisture during the melt of patchy snow covers over a 10-km horizontal domain. The coupled model includes solution of the mass continuity equation, the horizontal and vertical momentum equations, an E−ε turbulence model, an energy equation, and a water vapor conservation equation. Atmospheric buoyancy is accounted for, and a land surface energy balance model is implemented at the lower boundary. Model integrations indicate that advective processes occurring at local scales produce nonlinear horizontal variations in surface fluxes. Under conditions of the numerical experiments, the energy available to melt snow-covered regions has been found to increase by as much as 30% as the area of exposed vegetation increases upwind of the snow cover. The melt increase is found to vary in a largely linear fashion with decreasing snow-covered area for snow-covered areas greater than 25% and in a strongly nonlinear fashion below that value. Decreasing the ratio of patch size to total area, or increasing the patchiness, of the snow cover also leads to nonlinear increases in the energy available to melt the snow. In the limit of a snow cover composed of small patches, melt energy is found to increase linearly as the fractional snow-covered area decreases. In addition, for the purpose of computing grid-average surface fluxes during snowmelt in regional atmospheric models, the results of this study indicate that separate energy balance computations can be performed over the snow-covered and vegetation-covered regions, and the resulting fluxes can be weighted in proportion to the fractional snow cover to allocate the total energy flux partitioning within each surface grid cell.

scholarly journals A Scheme to Estimate Diurnal Cycle of Evapotranspiration from Geostationary Meteorological Satellite Observations

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2369
Author(s):  
Jing Lu ◽  
Li Jia ◽  
Chaolei Zheng ◽  
Ronglin Tang ◽  
Yazhen Jiang
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Surface Energy ◽  
Diurnal Cycle ◽  
Land Surface ◽  
Measurement Errors ◽  
Surface Energy Balance ◽  
Energy Balance Equation ◽  
Shortwave Radiation ◽  
Atmospheric Conditions

The diurnal cycle of evapotranspiration (ET) is significant in studying the dynamics of land–atmosphere interactions. The diurnal ET cycle can be considered as an indicator of dry/wet surface conditions. However, the accuracy of current models in estimating the diurnal ET cycle is generally low. This study developed an improved scheme to estimate the diurnal cycle of ET by solving the surface energy balance equation combined with simplified parameterization, with daily ET as the constraint. Meteosat Second Generation (MSG) land surface temperature, and longwave and shortwave radiation products were the primary inputs. Daily ET was from the remote sensing-based ETMonitor model. The estimated instantaneous (30 min) ET from the improved scheme outperformed the official MSG instantaneous ET product when compared with in situ half-hourly measurements at 35 flux sites from the FLUXNET2015 dataset, and was also comparable with European Center for Medium-Range Weather Forecasts (ECMWF) ERA5 ET data, with an R2 of 0.617 and root mean square error (RMSE) of 65.8 W/m2 for the improved scheme. Results were largely improved compared with those without daily ET as the constraint. The improved method was stable for the estimation of ET’s diurnal cycle at the similar atmospheric conditions and the accuracy was comparative at different land cover surfaces. Errors in the input variables and the simplification of surface heat flux parameterization affected surface energy balance closure, which can lead to instability of the solution of constants in the simplified parameterization and further to the uncertainty of ET’s diurnal cycle estimation. Measurement errors, different source areas in measured variables, and inconsistent spatial representativeness between remote sensing and site measurements also impacted the evaluation.

Fire impact on water and carbon fluxes in a wild olive-based ecosystem

2021 ◽  
Author(s):  
Matteo Curreli ◽  
Nicola Montaldo ◽  
Roberto Corona ◽  
Gabriel G. Katul
Keyword(s):  
Land Surface ◽  
Soil Layer ◽  
Carbon Assimilation ◽  
Carbon Fluxes ◽  
Surface Fluxes ◽  
State Variables ◽  
Rainy Period ◽  
Wild Olive ◽  
Autumn And Winter ◽  
The Impact

<p>Fire, harvesting and beetles attacks are important disturbances for the forested ecosystems. The aim of this study is to examine the impact of the disturbances on water and carbon fluxes using a eddy‐covariance (EC) – based tower in a wild-olive forest.</p><p>The study has been performed at the Orroli site, Sardinia (Italy), which is an experimental site for the FLUXMED project of the Water Joint Programming Initiative. From 2003, a 10 m micrometeorological tower equipped with eddy-covariance system has been used to measuring water, carbon and energy surface fluxes, as well as key state variables (e.g. leaf and soil skin temperature, radiations, air humidity and wind velocity).</p><p>The landscape is covered by patchy vegetation: wild olives trees in clumps and herbaceous species, drying to bare soil in late spring. The climate is Mediterranean maritime with long droughts from May to October, and rainy period is concentrated in the autumn and winter months. In this ecosystem water uptake by olive’s roots, from underlying substrate to the shallow soil layer, allow woody vegetation and grass to remain physiologically active during dry conditions.</p><p>In summer 2017, which was a very dry season, an extended fire affected the forested area, impacting the north – west footprint of the tower, with consequences also to the close trees due to beetle attack, probably related to the sensitive conditions of the trees after the drought.</p><p>We compared pre-disturbance with post-disturbance land surface fluxes. Both fire and beetle attack, altered the partitioning of available energy to lE and H, evapotranspiration (ET) and carbon assimilation. Results show a reduction of evapotranspiration and carbon assimilation during the growing season. Differently, in autumn and winter the difference between pre-disturbance and post-disturbance was negligible due to low physiological activities of vegetation.</p>

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