The Common Land Model

2003 ◽  
Vol 84 (8) ◽  
pp. 1013-1024 ◽  
Author(s):  
Yongjiu Dai ◽  
Xubin Zeng ◽  
Robert E. Dickinson ◽  
Ian Baker ◽  
Gordon B. Bonan ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Transfer Scheme ◽  
Soil System ◽  
Common Land Model ◽  
The Common ◽  
Academy Of Sciences ◽  
Ice Water

The Common Land Model (CLM) was developed for community use by a grassroots collaboration of scientists who have an interest in making a general land model available for public use and further development. The major model characteristics include enough unevenly spaced layers to adequately represent soil temperature and soil moisture, and a multilayer parameterization of snow processes; an explicit treatment of the mass of liquid water and ice water and their phase change within the snow and soil system; a runoff parameterization following the TOPMODEL concept; a canopy photo synthesis-conductance model that describes the simultaneous transfer of CO2 and water vapor into and out of vegetation; and a tiled treatment of the subgrid fraction of energy and water balance. CLM has been extensively evaluated in offline mode and coupling runs with the NCAR Community Climate Model (CCM3). The results of two offline runs, presented as examples, are compared with observations and with the simulation of three other land models [the Biosphere-Atmosphere Transfer Scheme (BATS), Bonan's Land Surface Model (LSM), and the 1994 version of the Chinese Academy of Sciences Institute of Atmospheric Physics LSM (IAP94)].

scholarly journals Implementation of a soil albedo scheme in the CABLEv1.4b land surface model and evaluation against MODIS estimates over Australia

2014 ◽  
Vol 7 (5) ◽  
pp. 2121-2140 ◽  
Author(s):  
J. Kala ◽  
J. P. Evans ◽  
A. J. Pitman ◽  
C. B. Schaaf ◽  
M. Decker ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Albedo ◽  
Near Infrared ◽  
Land Surface Model ◽  
Surface Model ◽  
Transfer Scheme ◽  
Control Simulation ◽  
Common Land Model ◽  
Australian Continent

Abstract. Land surface albedo, the fraction of incoming solar radiation reflected by the land surface, is a key component of the Earth system. This study evaluates snow-free surface albedo simulations by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour L'Observation de la Terre (SPOT) albedo. We compare results from offline simulations over the Australian continent. The control simulation has prescribed background snow-free and vegetation-free soil albedo derived from MODIS whilst the experiments use a simple parameterisation based on soil moisture and colour, originally from the Biosphere Atmosphere Transfer Scheme (BATS), and adopted in the Common Land Model (CLM). The control simulation, with prescribed soil albedo, shows that CABLE simulates overall albedo over Australia reasonably well, with differences compared to MODIS and SPOT albedos within ±0.1. Application of the original BATS scheme, which uses an eight-class soil classification, resulted in large differences of up to −0.25 for the near-infrared (NIR) albedo over large parts of the desert regions of central Australia. The use of a recalibrated 20-class soil colour classification from the CLM, which includes a higher range for saturated and VIS (visible) and NIR soil albedos, reduced the underestimation of the NIR albedo. However, this soil colour mapping is tuned to CLM soil moisture, a quantity which is not necessarily transferrable between land surface models. We therefore recalibrated the soil color map using CABLE's climatological soil moisture, which further reduced the underestimation of the NIR albedo to within ±0.15 over most of the continent as compared to MODIS and SPOT albedos. Small areas of larger differences of up to −0.25 remained within the central arid parts of the continent during summer; however, the spatial extent of these large differences is substantially reduced as compared to the simulation using the default eight-class uncalibrated soil colour map. It is now possible to use CABLE coupled to atmospheric models to investigate soil-moisture–albedo feedbacks, an important enhancement of the model.

Evaluation of Temperature Simulation over Northern Thailand from Regional Climate Model Coupled with Land Surface Model

2017 ◽  
Vol 866 ◽  
pp. 108-111
Author(s):  
Theerapan Saesong ◽  
Pakpoom Ratjiranukool ◽  
Sujittra Ratjiranukool
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Global Analysis ◽  
Regional Climate ◽  
Land Surface Model ◽  
Analysis Data ◽  
Surface Model ◽  
Northern Thailand ◽  
Weather Model

Numerical Weather Model called The Weather Research and Forecasting model, WRF, developed by National Center for Atmospheric Research (NCAR) is adapted to be regional climate model. The model is run to perform the daily mean air surface temperatures over northern Thailand in 2010. Boundery dataset provided by National Centers for Environmental Prediction, NCEP FNL, (Final) Operational Global Analysis data which are on 10 x 10. The simulated temperatures by WRF with four land surface options, i.e., no land surface scheme (option 0), thermal diffusion (option 1), Noah land-surface (option 2) and RUC land-surface (option 3) were compared against observational data from Thai Meteorological Department (TMD). Preliminary analysis indicated WRF simulations with Noah scheme were able to reproduce the most reliable daily mean temperatures over northern Thailand.

Hydrologic Sensitivities of Colorado River Runoff to Changes in Precipitation and Temperature*

2012 ◽  
Vol 13 (3) ◽  
pp. 932-949 ◽  
Author(s):  
Julie A. Vano ◽  
Tapash Das ◽  
Dennis P. Lettenmaier
Keyword(s):  
Land Surface ◽  
Colorado River ◽  
Climate Model ◽  
Land Surface Model ◽  
Annual Runoff ◽  
Surface Model ◽  
Fractional Change ◽  
Infiltration Capacity ◽  
Community Land Model ◽  
Runoff Change

Abstract The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at ⅛° latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitation and/or runoff regimes; hence, the highest values are for models biased low in runoff production, and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.

scholarly journals Evaluation of Snow Water Equivalent in NARCCAP Simulations, Including Measures of Observational Uncertainty

2017 ◽  
Vol 18 (9) ◽  
pp. 2425-2452 ◽  
Author(s):  
Rachel R. McCrary ◽  
Seth McGinnis ◽  
Linda O. Mearns
Keyword(s):  
Land Surface ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Dominant Role ◽  
Regional Climate ◽  
Land Surface Model ◽  
Surface Model ◽  
Observational Uncertainty ◽  
Snow Water ◽  
Noah Land Surface Model

Abstract This study evaluates snow water equivalent (SWE) over North America in the reanalysis-driven NARCCAP regional climate model (RCM) experiments. Examination of SWE in these runs allows for the identification of bias due to RCM configuration, separate from inherited GCM bias. SWE from the models is compared to SWE from a new ensemble observational product to evaluate the RCMs’ ability to capture the magnitude, spatial distribution, duration, and timing of the snow season. This new dataset includes data from 14 different sources in five different types. Consideration of the associated uncertainty in observed SWE strongly influences the appearance of bias in RCM-generated SWE. Of the six NARCCAP RCMs, the version of MM5 run by Iowa State University (MM5I) is found to best represent SWE despite its use of the Noah land surface model. CRCM overestimates SWE because of cold temperature biases and surface temperature parameterization options, while RegCM3 (RCM3) does so because of excessive precipitation. HadRM3 (HRM3) underestimates SWE because of warm temperature biases, while in the version of WRF using the Grell scheme (WRFG) and ECPC-RSM (ECP2), the misrepresentation of snow in the Noah land surface model plays the dominant role in SWE bias, particularly in ECP2 where sublimation is too high.

scholarly journals Simulating the thermal regime and thaw processes of ice-rich permafrost ground with the land-surface model CryoGrid 3

2016 ◽  
Vol 9 (2) ◽  
pp. 523-546 ◽  
Author(s):  
S. Westermann ◽  
M. Langer ◽  
J. Boike ◽  
M. Heikenfeld ◽  
M. Peter ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Regime ◽  
Land Surface ◽  
Climate Model ◽  
Late Quaternary ◽  
Land Surface Model ◽  
Hydrological Regime ◽  
Surface Model ◽  
Conductive Heat ◽  
Permafrost Thaw

Abstract. Thawing of permafrost in a warming climate is governed by a complex interplay of different processes of which only conductive heat transfer is taken into account in most model studies. However, observations in many permafrost landscapes demonstrate that lateral and vertical movement of water can have a pronounced influence on the thaw trajectories, creating distinct landforms, such as thermokarst ponds and lakes, even in areas where permafrost is otherwise thermally stable. Novel process parameterizations are required to include such phenomena in future projections of permafrost thaw and subsequent climatic-triggered feedbacks. In this study, we present a new land-surface scheme designed for permafrost applications, CryoGrid 3, which constitutes a flexible platform to explore new parameterizations for a range of permafrost processes. We document the model physics and employed parameterizations for the basis module CryoGrid 3, and compare model results with in situ observations of surface energy balance, surface temperatures, and ground thermal regime from the Samoylov permafrost observatory in NE Siberia. The comparison suggests that CryoGrid 3 can not only model the evolution of the ground thermal regime in the last decade, but also consistently reproduce the chain of energy transfer processes from the atmosphere to the ground. In addition, we demonstrate a simple 1-D parameterization for thaw processes in permafrost areas rich in ground ice, which can phenomenologically reproduce both formation of thermokarst ponds and subsidence of the ground following thawing of ice-rich subsurface layers. Long-term simulation from 1901 to 2100 driven by reanalysis data and climate model output demonstrate that the hydrological regime can both accelerate and delay permafrost thawing. If meltwater from thawed ice-rich layers can drain, the ground subsides, as well as the formation of a talik, are delayed. If the meltwater pools at the surface, a pond is formed that enhances heat transfer in the ground and leads to the formation of a talik. The model results suggest that the trajectories of future permafrost thaw are strongly influenced by the cryostratigraphy, as determined by the late Quaternary history of a site.

scholarly journals Assessment of the Urban Impact on Surface and Screen-Level Temperature in the ALADIN-Climate Driven SURFEX Land Surface Model for Budapest

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 709
Author(s):  
Gabriella Zsebeházi ◽  
Sándor István Mahó
Keyword(s):  
Surface Temperature ◽  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Land Surface Model ◽  
Surface Model ◽  
Urban Impact ◽  
Model Driven ◽  
The Impact

Land surface models with detailed urban parameterization schemes provide adequate tools to estimate the impact of climate change in cities, because they rely on the results of the regional climate model, while operating on km scale at low cost. In this paper, the SURFEX land surface model driven by the evaluation and control runs of ALADIN-Climate regional climate model is validated over Budapest from the aspect of urban impact on temperature. First, surface temperature of SURFEX with forcings from ERA-Interim driven ALADIN-Climate was compared against the MODIS land surface temperature for a 3-year period. Second, the impact of the ARPEGE global climate model driven ALADIN-Climate was assessed on the 2 m temperature of SURFEX and was validated against measurements of a suburban station for 30 years. The spatial extent of surface urban heat island (SUHI) is exaggerated in SURFEX from spring to autumn, because the urbanized gridcells are generally warmer than their rural vicinity, while the observed SUHI extent is more variable. The model reasonably simulates the seasonal means and diurnal cycle of the 2 m temperature in the suburban gridpoint, except summer when strong positive bias occurs. However, comparing the two experiments from the aspect of nocturnal UHI, only minor differences arose. The thorough validation underpins the applicability of SURFEX driven by ALADIN-Climate for future urban climate projections.

scholarly journals Land surface model influence on the simulated climatologies of temperature and precipitation extremes in the WRF v3.9 model over North America

2020 ◽  
Vol 13 (11) ◽  
pp. 5345-5366
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Temperature ◽  
Wrf Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Temperature And Precipitation ◽  
Model Ensembles ◽  
Precipitation Events

Abstract. The representation and projection of extreme temperature and precipitation events in regional and global climate models are of major importance for the study of climate change impacts. However, state-of-the-art global and regional climate model simulations yield a broad inter-model range of intensity, duration and frequency of these extremes. Here, we present a modeling experiment using the Weather Research and Forecasting (WRF) model to determine the influence of the land surface model (LSM) component on uncertainties associated with extreme events. First, we analyze land–atmosphere interactions within four simulations performed by the WRF model from 1980 to 2012 over North America, using three different LSMs. Results show LSM-dependent differences at regional scales in the frequency of occurrence of events when surface conditions are altered by atmospheric forcing or land processes. The inter-model range of extreme statistics across the WRF simulations is large, particularly for indices related to the intensity and duration of temperature and precipitation extremes. Our results show that the WRF simulation of the climatology of heat extremes can be 5 ∘C warmer and 6 d longer depending on the employed LSM component, and similarly for cold extremes and heavy precipitation events. Areas showing large uncertainty in WRF-simulated extreme events are also identified in a model ensemble from three different regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX) project, revealing the implications of these results for other model ensembles. Thus, studies based on multi-model ensembles and reanalyses should include a variety of LSM configurations to account for the uncertainty arising from this model component or to test the performance of the selected LSM component before running the whole simulation. This study illustrates the importance of the LSM choice in climate simulations, supporting the development of new modeling studies using different LSM components to understand inter-model differences in simulating extreme temperature and precipitation events, which in turn will help to reduce uncertainties in climate model projections.

scholarly journals Ability of a land surface model to predict climate induced changes in northern Russian river runoff during the 21st century

2015 ◽  
Vol 371 ◽  
pp. 59-64 ◽  
Author(s):  
O. N. Nasonova ◽  
Y. M. Gusev ◽  
E. M. Volodin ◽  
E. E. Kovalev
Keyword(s):  
River Runoff ◽  
Land Surface ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Global Climate ◽  
Global Climate Model ◽  
Land Surface Model ◽  
Climatic Conditions ◽  
Surface Model ◽  
Russian River

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.

Applying Scaled Vegetation Greenness Metrics to Constrain Simulated Transpiration Anomalies: A Study over Australia*

2013 ◽  
Vol 15 (4) ◽  
pp. 1607-1623 ◽  
Author(s):  
Mark Decker ◽  
Andy J. Pitman ◽  
Jason Evans
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Land Surface Model ◽  
Surface Model ◽  
Land Surface Models ◽  
Model Simulations ◽  
Vegetation Greenness ◽  
Surface Models ◽  
The Mean ◽  
Climate Model Simulations

Abstract The feasibility of using vegetation greenness metrics as a proxy for transpiration variability over Australia is demonstrated. Several global evapotranspiration datasets, one of which provides transpiration data and is constructed independently of the vegetation greenness measurements, are compared to four satellite-based observations representative of the state of the vegetation over several regions in Australia. Further estimates of the transpiration are obtained by decomposing the evapotranspiration datasets using an ensemble of land surface model simulations. On monthly time scales, the greenness anomaly metrics show a near one-to-one relationship with the transpiration estimates when the time series are appropriately scaled by the mean. The authors demonstrate that anomalous vegetation greenness metrics, when properly scaled, provide a tool for evaluating transpiration variability simulated by land surface models and observation-based evapotranspiration datasets that include transpiration. These methods provide a new test to help constrain the dynamic behavior of the land surface in climate model simulations.

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