- Director's Message
- Table of Contents
- Strategic Goals: Science, Facilities & Technology
- 1. Exploring atmospheric, Earth system, and solar processes, variability, and change
- 2. Investigating the interaction of the atmosphere, the broader Earth system, and human society
- 3. Improving prediction of weather, climate, and other atmospheric phenomena
- 4. Developing community models
- 5. Enabling innovative field experiments and measurement campaigns
- 6. Developing new instrumentation
- Research Catalog
CGD 2008 Profiles in Science: Terrestrial Sciences
Summary
The goal of the Terrestrial Sciences Section (TSS) is to increase scientific understanding of land-atmosphere interactions, in particular surface forcing of climate, through model development, application, and observational analyses and to represent that understanding in climate models. Research in TSS spans a broad knowledge of the relationships among the biosphere, hydrosphere, cryosphere, and atmosphere. Scientists in TSS develop and use appropriate multi-scale models, remote sensing, advanced analytical techniques, and observations to study the role of the terrestrial biosphere in the climate system. Topics of study include the regulation of planetary energetics, planetary ecology, and planetary metabolism through exchanges of energy, momentum, and materials (e.g., water, carbon, mineral aerosols) with the atmosphere and ocean and the response of the climate system to changes in land cover and land use.
Scientists in TSS are involved in developing the land model used in the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). This model, the Community Land Model (CLM), includes biogeophysics and hydrology, the traditional physical core components of land models, and is being further developed to include river routing, biogeochemistry (carbon, nitrogen, mineral aerosols, biogenic volatile organic compounds, water isotopes), and vegetation dynamics. Scientists in TSS actively participate in the CCSM Land Model Working Group and the CCSM Biogeochemistry Working Group, providing strong input to model development and implementing and testing model parameterizations. Model development is based on process studies of the relevant physical, chemical, and biological mechanisms and the numerical modeling techniques required to represent these mechanisms. TSS scientists compare model output with observed atmospheric, ecological, and hydrological data to validate and improve the model on a wide range of spatial and temporal scales. TSS provides a focal point for CGD and university ecological and hydrological research and serves as a resource to these communities in their use of CCSM.
CLM hydrology
In collaboration with the CCSM Land Model Working Group, Keith Oleson and David Lawrence continued to develop the hydrology and biogeophysical parameterizations for CLM. The CLM3.5, released to the public along with technical documentation and improved atmospheric forcing data in May 2007, was further revised to include: improvements to soil hydrology to increase soil moisture variability; snow model and snow albedo improvements; introduction of organic soil and a deeper soil column; and changes to surface aerodynamics including roughness length for sparse/dense canopy, stability functions, and atmospheric reference height.
CLM biogeochemistry
TSS scientists conducted several projects to implement biogeochemistry in CLM and CCSM. This research broadly addresses how biogeochemical coupling of carbon and nitrogen, in conjunction with land use and vegetation dynamics affects climate.
Peter Thornton, in collaboration with the CCSM Biogeochemistry Working Group, continued to develop a model of terrestrial carbon and nitrogen cycles for use with CLM. A critical application of the model has been to study the influence of carbon-nitrogen cycle coupling on present-day and potential future climate-carbon cycle feedbacks. This study found that the introduction of carbon-nitrogen coupling significantly alters the model response to increasing CO2, and the sensitivities of net land carbon flux to variation in temperature and precipitation. The study shows that C-N coupling has an important impact on the magnitude and the sign of climate-carbon cycle feedbacks when exercised in the fully coupled CCSM.
Gordon Bonan and Sam Levis conducted experiments with Thornton's CLM-CN model as well as CLM-CASA', which uses the CASA' biogeochemical model. These experiments documented the behavior of both models for the CCSM Biogeochemistry Working Group and provided the framework for the working group to address biases in both models.
Land cover and land use change
A major research focus for TSS is natural and human-mediated changes in land cover and ecosystem functions and their effects on climate, water resources, and biogeochemistry. The industrial age and growing human population has produced large changes in land surface characteristics, particularly deforestation, cultivation of cropland, and urbanization. Change in land cover from human uses of land is increasingly being recognized as an important forcing of climate. The influence of historical land cover change on climate needs to be considered as a climate forcing in additional to traditional forcings such as greenhouse gases, aerosols, solar variability, and ozone. Future projected land cover changes due to human land uses are also likely to alter climate, especially in the tropics, subtropics, and semiarid regions.
Scientists in TSS have initiated studies of the climate forcing associated with land use. This work has the goal of documenting (a) how changes in land use and land cover have altered present-day climate and are likely to alter future climate and (b) the importance of the land use and land cover change forcing relative to other IPCC SRES forcings. This work involves developing parameterizations of urban land cover, agroecosystems, and soil degradation for use with the CLM. It also involves development of historical and future datasets of land cover change.
Land use forcing of climate
Gordon Bonan, Sam Levis, and Peter Lawrence (University of Colorado) participated in the LUCID (Land-Use and Climate, IDentification of robust impacts) project under the auspices of IGBP-iLEAPS and GEWEX-GLASS. Climate model simulations were performed using potential natural vegetation, 1870 land cover, and present day land cover.
Dynamic vegetation
In addition to human-mediated land use changes, large-scale changes in the geographic distribution of vegetation as a result of past and future climate changes feed back to alter climate. These feedbacks are especially important in arid landscapes, where the albedo contrast between vegetation and soil is large, and in arctic landscapes, where trees and shrubs mask the high albedo of snow.
Sam Levis, Gordon Bonan, and Peter Thornton merged the carbon and nitrogen cycling capability of the CLM-CN model with a previously developed global dynamic vegetation model (CLM-DGVM). Sam Levis also worked with members of the Land Model Working group to introduce arctic and arid shrubs into the DGVM.
Agricultural models
Sam Levis, Gordon Bonan, and Peter Thornton merged concepts of the Agro-IBIS crop model with CLM-CN and the DGVM to simulate agroecosystems.
Urbanization
Keith Oleson, Gordon Bonan, and Johan Feddema (University of Kansas) continued work on the development and testing of an urban land cover parameterization for CLM. 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 model is being applied to document the important of representing cities for climate change simulations.
Oleson is also participating in a project to compare urban surface energy balance schemes, led by Sue Grimmond (Kings's College London), Martin Best (UK Met Office), and Janet Barlow (University of Reading). The purpose of this project is to evaluate the ability of urban models to simulate heat fluxes by performing a multi-step model comparison of urban surface energy balance schemes with observational datasets. Among the key questions to be answered by this project are: What are the main physical processes controlling the urban energy balance which need to be resolved? How complex does a model need to be in order to produce a realistic simulation of urban surface fluxes and temperatures? Which input parameter information is required by an urban model to perform realistically? Are we measuring the correct variables at the correct scales for model evaluation?