Simulation Of Latent Heat Fluxes Research Articles

Assessing the effects of end-members determination on regional latent heat flux simulation in trapezoidal framework based model

Land surface temperature-fractional vegetation coverage (LST-fc) trapezoid framework based models have been widely developed, applied, and verified to estimate regional latent heat flux (LE) and its partitioning process. The basis of operating these models lies in the determination of end-members within the LST-fc trapezoid. However, the knowledge of how the end-members affect the LE and ratio of vegetation latent heat flux (LEv) to latent heat flux (LEv/LE) estimation is lacking in the literature. In this study, three widely used end-members determination methods, viz., determination of actual end-members within the scatter plot of LST-fc (AEM), determination of theoretical end-members through the Zhang's method (Zhang et al., 2005, TEM-Z), and determination of theoretical end-members through Long's method (Long and Singh. 2012b, TEM-L) were inter-compared. The outcome of this study was verified at the 11 Eddy Correlation (EC) observation stations for the 183 test days during 2015 using the Moderate-resolution Imaging Spectroradiometer (MODIS) products, revealing that different end-members combinations greatly alter the LE simulation. However, tuning of end-members do not shift the LEv/LE estimates, and spatial patterns of the LE and LEv/LE remained unchanged. Moreover, the performance of TEM-Z is better than the AEM, while the TEM-L provide relatively unstable performance during the 183 test days. Conclusively, this study endorses to adopt the TEM-Z method to determine the end-members. This study provides a clear understanding of the effect of different end-members to LE and LEv/LE simulation within the LST-fc trapezoid framework, and gives a clear insight for model selection, operation, and subsequent, guidelines for model improvement.

Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)

Abstract. The water and energy transfers at the interface between the Earth's surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface lead to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with three widely used land surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach; 30 m sub-grid surface information was used to calculate the final grid fluxes based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests due to the large flux errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for coniferous forest. The mosaic approach produced fluxes more similar to reality and served to particularly improve the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model.

Simulation of Land Surface Climate over China with RegCM4.5: Verification and Analysis

The ability of RegCM4.5 using land surface scheme CLM4.5 to simulate the physical variables related to land surface state was investigated. The NCEP-NCAR reanalysis data for the period 1964–2003 were used to drive RegCM4.5 to simulate the land surface temperature, precipitation, soil moisture, latent heat flux, and surface evaporation. Based on observations and reanalysis data, a few land surface variables were analyzed over China. The results showed that some seasonal features of land surface temperature in summer and winter as well as its magnitude could be simulated well. The simulation of precipitation was sensitive to region and season. The model could, to a certain degree, simulate the seasonal migration of rainband in East China. The overall spatial distribution of the simulated soil moisture was better in winter than in summer. The simulation of latent heat flux was also better in winter. In summer, the latent heat flux bias mainly arose from surface evaporation bias in Northwest China, and it primarily arose from vegetation evapotranspiration bias in South China. In addition, the large latent heat flux bias in South China during summer was probably due to less precipitation generated in the model and poor representation of vegetation cover in this region.

Surface energy partitioning over four dominant vegetation types across the United States in a coupled regional climate model (Weather Research and Forecasting Model 3–Community Land Model 3.5)

Accurate representation of surface energy partitioning is crucial for studying land surface processes and the climatic influence of land cover and land use change using coupled climate‐land surface models. A critical question for these models, especially for newly coupled ones, is whether they can adequately distinguish differences in surface energy partitioning among different vegetation types. We evaluated 3 years (2004–2006) of surface energy partitioning and surface climate over four dominant vegetation types (cropland, grassland, needleleaf evergreen forest, and broadleaf deciduous forest) across the United States in a recently coupled regional climate model, Weather Research and Forecasting Model 3–Community Land Model 3.5 (WRF3‐CLM3.5), by comparing model output to observations (AmeriFlux, Clouds and the Earth's Radiant Energy System (CERES), and Parameter‐elevation Regressions on Independent Slopes Model (PRISM) data) and to standard WRF model output. We found that WRF3‐CLM3.5 can capture the seasonal pattern in energy partitioning for needleleaf evergreen forest but needs improvements in cropland, grassland, and broadleaf deciduous forest. Correcting the leaf area index representation for cropland and grassland could immediately improve the simulation of latent heat flux and hence the energy partitioning. Adding an irrigation scheme is especially important for cropland in the Midwest, where the strongly coupled soil moisture and precipitation can form a positive feedback that reduces latent heat flux and increases the warm bias. For deciduous forest, the simulated excess latent heat flux before leaf emergence is mainly from soil evaporation, requiring further improvement in the soil evaporation scheme. Finally, the domain‐wide overestimated net radiation contributes to positive biases in sensible, latent, and ground heat flux, as well as surface temperature. The standard WRF simulation has a similar warm bias, implicating errors in modules other than the land surface code. A sensitivity test suggests that improved simulation of downward solar radiation could reduce the energy flux and temperature biases. After adding irrigation process and correcting the leaf area index, WRF3‐CLM3.5 appears reliable for studying conversions between natural grassland and irrigated cropland and between needleleaf evergreen forest and grassland.

Modeling the dynamic root water uptake and its hydrological impact at the Reserva Jaru site in Amazonia

An empirical approach is proposed to represent the impact of dynamic root water uptake by plant roots in two land surface models (Community Land Model version 3 (CLM3) and Integrated Biosphere Simulator version 2 (IBIS2)). This approach is compared with a more physically based approach that simulates the hydraulic redistribution, using the Reserva Jaru site in Amazonia as an example. For each model and each approach, two different root profiles are experimented on, an exponential profile and an observed, deeper profile. In both CLM3 and IBIS2, including dynamic root uptake significantly improves the model simulation of latent heat fluxes, regardless of what root profile is used. In both models, the impact of hydraulic redistribution (as accounted for by the physically based approach) is comparable to that of a low degree of dynamic root water uptake (as accounted for by the empirical approach). The latent heat flux simulation in IBIS2 is closer to observation than is that in CLM3, with or without the impact of dynamic root water uptake. Despite the model improvement due to including dynamic root water uptake, significant biases in soil moisture simulations remain. Assimilating soil moisture observations into the land surface models produces a remarkably improved latent heat flux simulation. Parameterization in surface and subsurface runoff (which influences soil moisture) is suggested as a likely cause for the severe biases in the default model simulations, which highlights the critical importance of correctly simulating the fundamental hydrological processes in land surface models.

Consistent Parameterization of Roughness Length and Displacement Height for Sparse and Dense Canopies in Land Models

Abstract While progress has been made in the treatment of turbulence below, within, and above canopy in land models, not much attention has been paid to the convergence of canopy roughness length and displacement height to bare soil values as the above-ground biomass, or the sum of leaf and stem area indices, becomes zero. Preliminary formulations have been developed to ensure this convergence for the Community Land Model version 3 (CLM3) and are found to significantly improve the wintertime simulation of sensible heat flux (SH) compared with observational data over the Cabauw site in the Netherlands. The simulation of latent heat flux (LH) is also moderately improved. For global offline CLM3 simulations, the new formulations change SH by more than 5 W m−2 over many regions, while the change of LH is less than 1 W m−2 over most of the regions.

Validation of the Integrated Biosphere Simulator over Canadian deciduous and coniferous boreal forest stands

Data collected during the Boreal Ecosystem‐Atmosphere Study (BOREAS) at four different forest stands were used to test surface energy and carbon fluxes simulated by the Integrated Biosphere Simulator (IBIS). These stands included deciduous and conifer species and were located in both the BOREAS northern and southern study areas. Two runs were made: one using the original IBIS model and the other using a version modified to consider an organic soil layer (OSL) covering the mineral soil surface. Results show that the inclusion of the OSL substantially improved the simulation of soil heat flux, as well as of temperature and moisture in the topmost soil layer. Simulations show that latent and sensible heat fluxes, and net ecosystem exchange of carbon, were not affected appreciably by the presence of a thin (10 cm or less) OSL covering the forest floor. With a thick (50 cm) OSL, however, simulation of latent heat flux and net ecosystem exchange of carbon was substantially improved. Consideration of the OSL in the model also led to better simulation of the onsets of soil thawing. Correct estimation of heat diffusion to deep soil through thick organic layers requires a parameterization that accounts for the state of the organic material decomposition. Simulations presented here also show the necessity for using detailed information on soil physical properties for better evaluation of model performance.