Xubin Zeng

The common land model

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 la...

The Land Surface Climatology of the Community Land Model Coupled to the NCAR Community Climate Model

The land surface parameterization used with the community climate model (CCM3) and the climate system model (CSM1), the National Center for Atmospheric Research land surface model (NCAR LSM1), has been modified as part of the development of the next version of these climate models. This new model is known as the community land model (CLM2). In CLM2, the surface is represented by five primary subgrid land cover types (glacier, lake, wetland, urban, vegetated) in each grid cell. The vegetated portion of a grid cell is further divided into patches of up to 4 of 16 plant functional types, each with its own leaf and stem area index and canopy height. The relative area of each subgrid unit, the plant functional type, and leaf area index are obtained from 1-km satellite data. The soil texture dataset allows vertical profiles of sand and clay. Most of the physical parameterizations in the model were also updated. Major model differences include: 10 layers for soil temperature and soil water with explicit treatment of liquid water and ice; a multilayer snowpack; runoff based on the TOPMODEL concept; new formulation of ground and vegetation fluxes; and vertical root profiles from a global synthesis of ecological studies. Simulations with CCM3 show significant improvements in surface air temperature, snow cover, and runoff for CLM2 compared to LSM1. CLM2 generally warms surface air temperature in all seasons compared to LSM1, reducing or eliminating many cold biases. Annual precipitation over land is reduced from 2.35 mm day21 in LSM1 to 2.14 mm day21 in CLM2. The hydrologic cycle is also different. Transpiration and ground evaporation are reduced. Leaves and stems evaporate more intercepted water annually in CLM2 than LSM1. Global runoff from land increases from 0.75 mm day21 in LSM1 to 0.84 mm day21 in CLM2. The annual cycle of runoff is greatly improved in CLM2, especially in arctic and boreal regions where the model has low runoff in cold seasons when the soil is frozen and high runoff during the snowmelt season. Most of the differences between CLM2 and LSM1 are attributed to particular parameterizations rather than to different surface datasets. Important processes include: multilayer snow, frozen water, interception, soil water limitation to latent heat, and higher aerodynamic resistances to heat exchange from ground.

Intercomparison of bulk aerodynamic algorithms for the computation of sea surface fluxes using TOGA COARE and TAO data

Abstract A bulk aerodynamic algorithm is developed for all stability conditions for the computation of ocean surface fluxes. It provides roughness lengths of wind, humidity, and temperature for a wind speed range from 0 to 18 m s−1: zo = 0.013u2∗/g + 0.11ν/u∗ and ln(zo/zot) = ln(zo/zoq) = 2.67Re1/4∗ − 2.57 as derived using the Tropical Oceans Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE) data constrained by other observations under high wind conditions. Using the TOGA COARE ship data and the multiyear hourly TOGA Tropical Atmosphere–Ocean moored buoy data, intercomparison of six different algorithms, which are widely used in research, operational forecasting, and data reanalysis, shows that algorithms differ significantly in heat and momentum fluxes under both very weak and very strong wind conditions, but agree with each other under moderate wind conditions. Algorithms agree better for wind stress than for heat fluxes. Based on past observations, probable deficiencies in r...

The Community Land Model and Its Climate Statistics as a Component of the Community Climate System Model

Abstract Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on the simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack tha...

Derivation and Evaluation of Global 1-km Fractional Vegetation Cover Data for Land Modeling

Abstract Fractional vegetation cover (συ) is needed in the modeling of the land–atmosphere exchanges of momentum, energy, water, and trace gases. From global 1-km, 10-day composite Advanced Very High Resolution Radiometer normalized difference vegetation index (NDVI) data from April 1992 to March 1993, global 1-km συ is derived based on the annual maximum NDVI value for each pixel in comparison with the NDVI value that corresponds to 100% vegetation cover for each International Geosphere–Biosphere Program land cover type. This dataset is pixel dependent but season independent, with the seasonal variation of vegetation greenness in a pixel accounted for by the leaf area index. The authors’ algorithm is found to be insensitive to the use of a specific land cover classification. In comparison with an independent dataset derived by DeFries et al. by using a more sophisticated statistical approach, the current dataset has a similar spatial distribution but systematically smaller συ (particularly over shrubland...

Coupling of the Common Land Model to the NCAR Community Climate Model

Abstract The Common Land Model (CLM), which results from a 3-yr joint effort among seven land modeling groups, has been coupled with the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3). Two 15-yr simulations of CCM3 coupled with CLM and the NCAR Land Surface Model (LSM), respectively, are used to document the relative impact of CLM versus LSM on land surface climate. It is found that CLM significantly reduces the summer cold bias of surface air temperature in LSM, which is associated with higher sensible heat fluxes and lower latent heat fluxes in CLM, and the winter warm bias over seasonally snow-covered regions, especially in Eurasia. CLM also significantly improves the simulation of the annual cycle of runoff in LSM. In addition, CLM simulates the snow mass better than LSM during the snow accumulation stage. These improvements are primarily caused by the improved parameterizations in runoff, snow, and other processes (e.g., turbulence) in CLM. The new land boundary data (...

Evaluation of the Reanalysis Products from GSFC, NCEP, and ECMWF Using Flux Tower Observations

AbstractReanalysis products produced at the various centers around the globe are utilized for many different scientific endeavors, including forcing land surface models and creating surface flux estimates. Here, flux tower observations of temperature, wind speed, precipitation, downward shortwave radiation, net surface radiation, and latent and sensible heat fluxes are used to evaluate the performance of various reanalysis products [NCEP–NCAR reanalysis and Climate Forecast System Reanalysis (CFSR) from NCEP; 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and ECMWF Interim Re-Analysis (ERA-Interim) from ECMWF; and Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Global Land Data Assimilation System (GLDAS) from the Goddard Space Flight Center (GSFC)]. To combine the biases and standard deviation of errors from the separate stations, a ranking system is utilized. It is found that ERA-Interim has the lowest overall bias in 6-hourly air temper...

Evaluation of the Utility of Satellite-Based Vegetation Leaf Area Index Data for Climate Simulations

Abstract In this study the utility of satellite-based leaf area index (LAI) data in improving the simulation of near-surface climate with the NCAR Community Climate Model, version 3 (CCM3), GCM is evaluated. The use of mean LAI values, obtained from the Advanced Very High Resolution Radiometer Pathfinder data for the 1980s, leads to notable warming and decreased precipitation over large parts of the Northern Hemisphere lands during the boreal summer. Such warming and decreased rainfall reduces discrepancies between the simulated and observed near-surface temperature and precipitation fields. The impact of interannual vegetation extremes observed during the 1980s on near-surface climate is also investigated by utilizing the maximum and minimum LAI values from the 10-yr LAI record. Surface energy budget analysis indicates that the dominant impact of interannual LAI variations is modification of the partitioning of net radiant energy between latent and sensible heat fluxes brought about through changes in th...

Global Vegetation Root Distribution for Land Modeling

Abstract Vegetation root distribution is one of the factors that determine the overall water holding capacity of the land surface and the relative rates of water extraction from different soil layers for vegetation transpiration. Despite its importance, significantly different root distributions are used by different land surface models. Using a comprehensive global field survey dataset, vegetation root distribution (including rooting depth) has been developed here for three of the most widely used land cover classifications [i.e., the Biosphere–Atmosphere Transfer Scheme (BATS), International Geosphere–Biosphere Program (IGBP), and version 2 of the Simple Biosphere Model (SiB2)] for direct use by any land model with any number of soil layers.

Which Bulk Aerodynamic Algorithms are Least Problematic in Computing Ocean Surface Turbulent Fluxes

Bulk aerodynamic algorithms are needed to compute ocean surface turbulent fluxes in weather forecasting and climate models and in the development of global surface flux datasets. Twelve such algorithms are evaluated and ranked using direct turbulent flux measurements determined from covariance and inertial-dissipation methods from 12 ship cruises over the tropical and midlatitude oceans (from about 58 St o 608N). The four least problematic of these 12 algorithms based upon the overall ranking for this data include the Coupled Ocean‐Atmosphere Response Experiment (COARE) version 3.0 and The University of Arizona (UA) schemes as well as those used at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration (NASA) Data Assimilation Office for version 1 of the Goddard Earth Observing System reanalysis (GEOS-1). Furthermore, the four most problematic of these algorithms are also identified along with possible explanations. The overall ranking is not substantially affected by the use of the average of covariance and inertialdissipation flux measurements or by taking into consideration measurement uncertainties. The differences between computed and observed fluxes are further evaluated as a function of near-surface wind speed and sea surface temperature to understand the rankings. Finally, several unresolved issues in terms of measurement and algorithm uncertainties are raised.