Assessment of Surface Exchange Coefficients in the Noah-MP Land Surface Model for Different Land Cover Types over China

2020 ◽  
Author(s):  
Xia Zhang ◽  
Liang Chen ◽  
Zhuguo Ma ◽  
Yanhong Gao
Keyword(s):  
Surface Energy ◽  
Land Cover ◽  
Coupling Strength ◽  
Land Surface ◽  
Land Surface Model ◽  
Coupling Scheme ◽  
Surface Model ◽  
Surface Exchange ◽  
Land Cover Types ◽  
Simulated Surface

<p>The parameterization of surface exchange coefficients (C<sub>h</sub>) representing land–atmosphere coupling strength plays a key role in land surface modeling. Previous studies have found that land–atmosphere coupling in land surface models (LSMs) is overestimated, which affects the predictability of weather and climate evolution. To improve the representation of land–atmosphere interactions in LSMs, this study investigated the dynamic canopy-height-dependent coupling strength in the offline Noah LSM with multiparameterization options (Noah-MP) when applied to China. Comparison with the default Noah-MP LSM showed the dynamic scheme significantly improved the C<sub>h</sub> calculations and realistically reduced the biases of simulated surface energy and water components against observations. It is noteworthy that the improvements brought by the dynamic scheme differed across land cover types. The scheme was found superior in reproducing the observed C<sub>h</sub> as well as surface energy and water variables for short vegetation (grass, crop, and shrub), while the improvement for tall canopy (forest) was found not significant, although the estimations were reasonable. The improved version benefits from the treatment of the roughness length for heat. Overall, the dynamic coupling scheme markedly affects the simulation of land–atmosphere interactions, and altering the dynamics of surface coupling has potential for improving the representation of land–atmosphere interactions and thus furthering LSM development.</p>

scholarly journals Ecosystem Feedbacks to Climate Change in California: Development, Testing, and Analysis Using a Coupled Regional Atmosphere and Land Surface Model (WRF3–CLM3.5)

2011 ◽  
Vol 15 (15) ◽  
pp. 1-38 ◽  
Author(s):  
Z. M. Subin ◽  
W. J. Riley ◽  
J. Jin ◽  
D. S. Christianson ◽  
M. S. Torn ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Cover ◽  
Air Temperature ◽  
Land Surface ◽  
Vegetation Change ◽  
Land Surface Model ◽  
Natural Vegetation ◽  
Surface Model ◽  
Temperature Changes ◽  
Model Version

Abstract A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California’s climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California’s climate was assessed by comparing simulations by WRF3–CLM3.5 and WRF3–Noah to observations from 1982 to 1991. Using WRF3–CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of −0.7° to +1°C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2°–1.2°C reductions in summer daily-mean 2-m air temperature and 2.0°–3.7°C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate–vegetation interactions.

scholarly journals Effects of Surface Coupling Strength in WRF/Noah-MP Model on Regional Climate Simulations Over China

2021 ◽  
Author(s):  
Xia Zhang ◽  
Liang Chen ◽  
Zhuguo Ma ◽  
Jianping Duan ◽  
Danqiong Dai ◽  
...  
Keyword(s):  
Coupling Strength ◽  
Land Surface ◽  
Numerical Models ◽  
Exchange Process ◽  
Regional Climate ◽  
Surface Fluxes ◽  
Surface Model ◽  
Surface Exchange ◽  
Climate Simulations ◽  
Simulated Precipitation

Abstract Land–atmosphere energy and moisture exchange can strongly influence local and regional climate. However, high uncertainty exits in the representation of land–atmosphere interactions in numerical models. The parameterization of surface exchange process is greatly affected by varying the parameter Czil which, however, is typically set to a domain-wide constant value. In this study, we examine the sensitivity of regional climate simulations over China to different surface exchange strengths using three Czil schemes (default without Czil , constant Czil = 0.1, and dynamic canopy-height-dependent Czil -h schemes) in the 13-km-resolution Weather Research and Forecasting model coupled with a Noah land surface model with multi-parameterization options (WRF/Noah-MP). Our results demonstrate that the Czil -h scheme substantially reduces the overestimations of land–atmosphere coupling strength in the other two schemes, and comparisons with the ChinaFLUX observations indicate the capability of the Czil -h scheme to better match the observed surface energy and water variations. The results of the Czil schemes applying to four typical climate zones of China present that the Czil -h simulations are in the closest agreements with the field observations. The Czil -h scheme can narrow the positive discrepancies of simulated precipitation and surface fluxes as well as the negative biases of Ts in areas of Northeast, North China, Eastern Northwest, and Southwest. Especially, the above remarkable improvements produced by the Czil -h scheme are primarily over areas covering short vegetation. Also noted that the precipitation simulated by the Czil -h scheme exhibits more intricate and unclear changes compared with surface fluxes simulations due to the non-local impacts of surface exchange strength resulted from the fluidity of the atmosphere. Overall, our findings highlight the applicability of the dynamical Czil as a better physical alternative to treat the surface exchange process in atmosphere coupling models.

scholarly journals Challenging a Global Land Surface Model in a Local Socio-Environmental System

Land ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 398
Author(s):  
Kyla M. Dahlin ◽  
Donald Akanga ◽  
Danica L. Lombardozzi ◽  
David E. Reed ◽  
Gabriela Shirkey ◽  
...  
Keyword(s):  
Land Cover ◽  
Stress Responses ◽  
Land Surface ◽  
Plant Stress ◽  
Land Surface Model ◽  
Grid Cell ◽  
Surface Model ◽  
Area Index ◽  
Community Land Model ◽  
Natural Grasslands

Land surface models (LSMs) predict how terrestrial fluxes of carbon, water, and energy change with abiotic drivers to inform the other components of Earth system models. Here, we focus on a single human-dominated watershed in southwestern Michigan, USA. We compare multiple processes in a commonly used LSM, the Community Land Model (CLM), to observational data at the single grid cell scale. For model inputs, we show correlations (Pearson’s R) ranging from 0.46 to 0.81 for annual temperature and precipitation, but a substantial mismatch between land cover distributions and their changes over time, with CLM correctly representing total agricultural area, but assuming large areas of natural grasslands where forests grow in reality. For CLM processes (outputs), seasonal changes in leaf area index (LAI; phenology) do not track satellite estimates well, and peak LAI in CLM is nearly double the satellite record (5.1 versus 2.8). Estimates of greenness and productivity, however, are more similar between CLM and observations. Summer soil moisture tracks in timing but not magnitude. Land surface reflectance (albedo) shows significant positive correlations in the winter, but not in the summer. Looking forward, key areas for model improvement include land cover distribution estimates, phenology algorithms, summertime radiative transfer modelling, and plant stress responses.

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