scholarly journals An Urban Parameterization for a Global Climate Model. Part I: Formulation and Evaluation for Two Cities

2008 ◽  
Vol 47 (4) ◽  
pp. 1038-1060 ◽  
Author(s):  
K. W. Oleson ◽  
G. B. Bonan ◽  
J. Feddema ◽  
M. Vertenstein ◽  
C. S. B. Grimmond

Abstract Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities.

2017 ◽  
Author(s):  
Liang Chen ◽  
Paul A. Dirmeyer ◽  
Zhichang Guo ◽  
Natalie M. Schultz

Abstract. Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land use/land cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been well investigated. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These biases are mainly associated with deficiencies over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.


2018 ◽  
Vol 22 (1) ◽  
pp. 111-125 ◽  
Author(s):  
Liang Chen ◽  
Paul A. Dirmeyer ◽  
Zhichang Guo ◽  
Natalie M. Schultz

Abstract. Land surface energy and water fluxes play an important role in land–atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.


2017 ◽  
Vol 30 (3) ◽  
pp. 1159-1176 ◽  
Author(s):  
J. Winckler ◽  
C. H. Reick ◽  
J. Pongratz

Abstract Land-cover change (LCC) happens locally. However, in almost all simulation studies assessing biogeophysical climate effects of LCC, local effects (due to alterations in a model grid box) are mingled with nonlocal effects (due to changes in wide-ranging climate circulation). This study presents a method to robustly identify local effects by changing land surface properties in selected “LCC boxes” (where local plus nonlocal effects are present), while leaving others unchanged (where only nonlocal effects are present). While this study focuses on the climate effects of LCC, the method presented here is applicable to any land surface process that is acting locally but is capable of influencing wide-ranging climate when applied on a larger scale. Concerning LCC, the method is more widely applicable than methods used in earlier studies. The study illustrates the possibility of validating simulated local effects by comparison to observations on a global scale and contrasts the underlying mechanisms of local and nonlocal effects. In the MPI-ESM, the change in background climate induced by extensive deforestation is not strong enough to influence the local effects substantially, at least as long as sea surface temperatures are not affected. Accordingly, the local effects within a grid box are largely independent of the number of LCC boxes in the isolation approach.


2020 ◽  
Vol 20 (3) ◽  
Author(s):  
Rosana Amaral Carrasco ◽  
Mayara Maezano Faita Pinheiro ◽  
José Marcato Junior ◽  
Rejane Ennes Cicerelli ◽  
Paulo Antônio Silva ◽  
...  

2017 ◽  
Vol 124 ◽  
pp. 119-132 ◽  
Author(s):  
Duy X. Tran ◽  
Filiberto Pla ◽  
Pedro Latorre-Carmona ◽  
Soe W. Myint ◽  
Mario Caetano ◽  
...  

Author(s):  
O. N. Nasonova ◽  
Y. M. Gusev ◽  
E. M. Volodin ◽  
E. E. Kovalev

Abstract. The objective of the present study is application of the land surface model SWAP to project climate change impact on northern Russian river runoff up to 2100 using meteorological projections from the atmosphere–ocean global climate model INMCM4.0. The study was performed for the Northern Dvina River and the Kolyma River characterized by different climatic conditions. The ability of both models to reproduce the observed river runoff was investigated. To apply SWAP for hydrological projections, the robustness of the model was evaluated. The river runoff projections up to 2100 were calculated for two greenhouse gas emission scenarios: RCP8.5 and RCP4.5 prepared for the phase five of the Coupled Model Intercomparison Project (CMIP5). For each scenario, several runoff projections were obtained using different models (INMCM4.0 and SWAP) and different post-processing techniques for correcting biases in meteorological forcing data. Differences among the runoff projections obtained for the same emission scenario and the same period illustrate uncertainties resulted from application of different models and bias-correcting techniques.


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