Zong-Liang Yang

The Community Climate System Model Version 4

AbstractThe fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Nino–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulati...

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 Project for Intercomparison of Land-surface Parameterization Schemes

The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS) is described and the first stage science plan outlined. PILPS is a project designed to improve the parameterization of the continental surface, especially the hydrological, energy, momentum, and carbon exchanges with the atmosphere. The PILPS Science Plan incorporates enhanced documentation, comparison, and validation of continental surface parameterization schemes by community participation. Potential participants include code developers, code users, and those who can provide datasets for validation and who have expertise of value in this exercise. PILPS is an important activity because existing intercomparisons, although piecemeal, demonstrate that there are significant differences among current global climate models such as cloud and convection parameterizations. It is also clear that too few sensitivity studies have been undertaken with the result that there is not yet enough information to indicate which simplifications or omissions are important for the near-surface continental climate, hydrology, and biogeochemistry. PILPS emphasizes sensitivity studies with and intercomparisons of existing land surface codes and the development of areally extensive datasets for their testing and validation. 111 refs., 4 tabs.

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.

The community Noah land surface model with multiparameterization options (Noah‐MP): 1. Model description and evaluation with local‐scale measurements

[1] This first paper of the two‐part series describes the objectives of the community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah‐MP). The Noah‐MP’s performance is evaluated at various local sites using high temporal frequency data sets, and results show the advantages of using multiple optional schemes to interpret the differences in modeling simulations. The second paper focuses on ensemble evaluations with long‐term regional (basin) and global scale data sets. The enhanced conceptual realism includes (1) the vegetation canopy energy balance, (2) the layered snowpack, (3) frozen soil and infiltration, (4) soil moisture‐groundwater interaction and related runoff production, and (5) vegetation phenology. Sample local‐scale validations are conducted over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site, the W3 catchment of Sleepers River, Vermont, and a French snow observation site. Noah‐MP shows apparent improvements in reproducing surface fluxes, skin temperature over dry periods, snow water equivalent (SWE), snow depth, and runoff over Noah LSM version 3.0. Noah‐MP improves the SWE simulations due to more accurate simulations of the diurnal variations of the snow skin temperature, which is critical for computing available energy for melting. Noah‐MP also improves the simulation of runoff peaks and timing by introducing a more permeable frozen soil and more accurate simulation of snowmelt. We also demonstrate that Noah‐MP is an effective research tool by which modeling results for a given process can be interpreted through multiple optional parameterization schemes in the same model framework.

Development of a simple groundwater model for use in climate models and evaluation with Gravity Recovery and Climate Experiment data

Received 17 May 2006; revised 24 October 2006; accepted 26 December 2006; published 7 April 2007. [1] Groundwater interacts with soil moisture through the exchanges of water between the unsaturated soil and its underlying aquifer under gravity and capillary forces. Despite its importance, groundwater is not explicitly represented in climate models. This paper developed a simple groundwater model (SIMGM) by representing recharge and discharge processes of the water storage in an unconfined aquifer, which is added as a single integration element below the soil of a land surface model. We evaluated the model against the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage change (DS) data. The modeled total water storage (including unsaturated soil water and groundwater) change agrees fairly well with GRACE estimates. The anomaly of the modeled groundwater storage explains most of the GRACE DS anomaly in most river basins where the water storage is not affected by snow water or frozen soil. For this reason, the anomaly of the modeled water table depth agrees well with that converted from the GRACE DS in most of the river basins. We also investigated the impacts of groundwater dynamics on soil moisture and evapotranspiration through the comparison of SIMGM to an additional model run using gravitational free drainage (FD) as the model’s lower boundary condition. SIMGM produced much wetter soil profiles globally and up to 16% more annual evapotranspiration than FD, most obviously in arid-to-wet transition regions.

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...

Parameter estimation of a land surface scheme using multicriteria methods

Attempts to create models of surfaceߚ;atmosphere interactions with greater physical realism have resulted in land surface schemes (LSS) with large numbers of parameters. The hope has been that these parameters can be assigned typical values by inspecting the literature. The potential for using the various observational data sets that are now available to extract plot-scale estimates for the parameters of a complex LSS via advanced parameter estimation methods developed for hydrological models is explored in this paper. Results are reported for two case studies using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The traditional single-criterion methods were found to be of limited value. However, a multicriteria approach was found to be effective in constraining the parameter estimates into physically plausible ranges when observations on at least one appropriate heat flux and one properly selected state variable are available.

The Project for Intercomparison of Land-surface Parameterization / / Schemes PILPS Phase 2 c Red-Arkansas River basin experiment: 1. Experiment description and summary intercomparisons

Abstract Sixteen land-surface schemes participating in the Project for the Intercomparison of Land-surface Schemes (PILPS) Phase 2(c) were run using 10 years (1979–1988) of forcing data for the Red–Arkansas River basins in the Southern Great Plains region of the United States. Forcing data (precipitation, incoming radiation and surface meteorology) and land-surface characteristics (soil and vegetation parameters) were provided to each of the participating schemes. Two groups of runs are presented. (1) Calibration–validation runs, using data from six small catchments distributed across the modeling domain. These runs were designed to test the ability of the schemes to transfer information about model parameters to other catchments and to the computational grid boxes. (2) Base-runs, using data for 1979–1988, designed to evaluate the ability of the schemes to reproduce measured energy and water fluxes over multiple seasonal cycles across a climatically diverse, continental-scale basin. All schemes completed the base-runs but five schemes chose not to calibrate. Observational data (from 1980–1986) including daily river flows and monthly basin total evaporation estimated through an atmospheric budget analysis, were used to evaluate model performance. In general, the results are consistent with earlier PILPS experiments in terms of differences among models in predicted water and energy fluxes. The mean annual net radiation varied between 80 and 105 W m −2 (excluding one model). The mean annual Bowen ratio varied from 0.52 to 1.73 (also excluding one model) as compared to the data-estimated value of 0.92. The run-off ratios varied from a low of 0.02 to a high of 0.41, as compared to an observed value of 0.15. In general, those schemes that did not calibrate performed worse, not only on the validation catchments, but also at the scale of the entire modeling domain. This suggests that further PILPS experiments on the value of calibration need to be carried out.

Validation of the Snow Submodel of the Biosphere-Atmosphere Transfer Scheme with Russian Snow Cover and Meteorological Observational Data

Snow cover is one of the most important variables affecting agriculture, hydrology, and climate, but detailed measurements are not widely available. Therefore, the effectiveness and validity of snow schemes in general circulation models have been difficult to assess. Using long-term snow cover data from the former Soviet Union, this paper focuses on the validation of the snow submodel in the Biosphere‐Atmosphere Transfer Scheme (BATS) using 6 years of data (1978‐83) at six stations. Fundamental uncertainties in the datasets limit the accuracy of our assessment of the model’s performance. In the absence of a wind correction for the gauge-measured precipitation and with the standard rain‐snow transition criterion (2.28C), the model gives reasonable simulations of snow water equivalent and surface temperature for all of the six stations and the six winters examined. In particular, the time of accumulation and the end of ablation and the alteration due to aging are well captured. With some simple modifications of the code, the model can also reproduce snow depth, snow cover fraction, and surface albedo. In view of the scheme’s simplicity and efficiency, these results are encouraging. However, if a wind correction is applied to the gauge-measured precipitation, the model shows increased rootmean-square errors in snow water equivalent for all six stations except Tulun. Perhaps, the better agreement without wind correction means that the snow has blown beyond the area of snow measurement, as might be accounted for only by a detailed regional snow‐wind distribution model. This study underlines four aspects that warrant special attention: (i) estimation of the downward longwave radiation, (ii) separation of the aging processes for snowpack density and snow surface albedo, (iii) parameterization of snow cover fraction, and (iv) choice of critical temperature for rain‐snow transition.