Terrestrial Sciences Section Narrative

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. Gordon Bonan co-chair’s the CCSM Land Model Working Group, Natalie Mahowald co-chairs the CCSM Biogeochemistry Working Group, and other TSS scientists actively participate in both working groups, 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.

Members of TSS participate in NCAR initiatives in Biogeosciences, Weather and Climate Impact Assessment, Water Cycle, and Wildland Fire.

Community Land Model

Mariana Vertenstein (TSS), Keith Oleson (TSS), Sam Levis (TSS), Forrest Hoffman (Oak Ridge National Laboratory), Peter Thornton (TSS), and Gordon Bonan (TSS) oversaw the release of the third version of the CLM3 for the CCSM3. The model includes a new under-canopy turbulence scheme developed by Xubin Zeng (University of Arizona) and colleagues, which significantly reduces excessively warm daytime ground temperatures in sparsely vegetated areas. The model also includes a dynamic global vegetation model that allows plant community composition to change over time in response to fire and climate change, as well as new capabilities that facilitate implementation of the terrestrial carbon cycle. Model source code, datasets, technical descriptions, and user guides can be found at http://www.cgd.ucar.edu/tss/clm/distribution/clm3.0/index.html.

Oleson and Robert Dickinson (Georgia Tech) analyzed the control CCSM3 simulations for the present-day climate. The model has a prominent winter (DJF) warm temperature bias in Siberia, Alaska, and western Canada. This same region has a cold temperature bias in summer (JJA). Eastern and central United States and the Amazon have pronounced annual dry biases in terms of precipitation.

This figure shows surface air temperature (left) and precipitation (right) biases in CCSM3 at T85 resolution.

Levis and Bonan analyzed the vegetation simulated by the dynamic global vegetation model in CCSM3. Their analyses showed that the prominent dry biases in the United States and the Amazon result in an inability to grow the expected forest vegetation. Changes to CLM3 that reduce the interception of water and increase transpiration result in a better simulation of vegetation.

This figure shows vegetation simulated by CLM3 with its dynamic global vegetation model. Left: CLM3. Right: CLM3 with modifications that reduce interception and increase transpiration. The modifications allow for more extensive forests in eastern U.S. and tropical South America.

This figure shows relative soil water wetness, canopy evaporation, and transpiration simulated by CLM3 (left) and a modified CLM3 (right). The modifications result in relatively wetter soil, reduced interception and canopy evaporation, and increased transpiration.

Hydrology

As part of the NCAR Water Cycle initiative, Oleson, Bonan, and David Lawrence (CCR) participated in the Global Land Atmosphere Coupling Experiment (GLACE). This intercomparison of several atmospheric models has the goal of quantifying and documenting the degree to which the atmosphere responds to anomalies in the land surface states, especially soil moisture. Climate model experiments in which soil water is either prognostically simulated or prescribed from a dataset were compared to determine the degree to which soil moisture influences precipitation. Results from the CAM and the CLM show that land-atmosphere coupling strength is highest in the tropics.

Surface soil water greatly influences the land-atmosphere coupling strength. The model has much greater coupling strength when the top 5 cm of soil is included in the analysis than when only the deeper soil layers are considered.

Biogeochemistry

As part of the NCAR Biogeosciences Initiative, TSS scientists conducted several projects to implement biogeochemistry in CLM and CCSM. This research broadly addresses how biogeochemical coupling of carbon, nitrogen, iron, and sulfur cycles affect climate, air quality, radiative forcing, and ecosystem function on regional to global scales. It involves two specific research agendas related to mineral aerosols and the terrestrial carbon cycle.

Natalie Mahowald's (TSS) work has focused on three main issues: understanding the anthropogenic portion of desert dust, the climate and biogeochemical impacts of desert dust, and incorporating desert dust into the CCSM. In collaboration with university researchers (Jean-Louis Dufresne (UCSB/CNRS France), Chao Luo (University of California, Santa Barbara), Masaru Yoshioka (University of California, Santa Barbara), Mahowald contributed to two papers (one submitted, one published) on the relative proportion of anthoropogenic mineral aerosol sources to the total sources, using Total Ozone Measuring Spectrometer Absorbing Aerosol Index (TOMS AII) and comparisons to observations. Additionally, she has one submitted article with a SOARS student (G. Rivera) and a university researcher (Chao Luo (University of California, Santa Barbara)) using desert dust storm data to constrain the land use fraction of current desert dust concentrations. Additionally she contributed to a paper looking at the importance of diurnal (surface energy flux processes) and synoptic processes in modulating the desert dust cycle (with Chao Luo (University of California, Santa Barbara) and Charles Jones (University of California, Santa Barbara).

Mahowald contributed to two papers dealing with the biogeochemical implications of mineral aerosols (with Greg Okin (Virginia), Ed Boyle (Massachusetts Institute of Technology) and many others). She authored an additional paper evaluating the atmospheric phosphorous sources over the Amazon (with university collaborators) which is in preparation. She worked with Jenny Hand (ASP) to develop the first modeling study of atmospheric iron in mineral aerosols as it is processed in the atmosphere, and has a paper published on this topic, of great importance to the ocean biogeochemistry community. Mahowald's research also examined the impact of desert dust on African easterly waves as derived from observations with Charles Jones (University of California, Santa Barbara) and Chao Luo (University of California, Santa Barbara).

Mahowald has continued to improve the CCSM desert dust modeling codes and has looked at the the response of atmospheric mineral aerosols and seasalts to climate change, using the CCSM in slab ocean model mode, for the current climate, preindustrial, doubled-CO₂ and the last glacial maximum. This work is being done in collaboration with Phil Rasch (CMS), Charlie Zender (University of California, Irvine), Sam Levis (TSS), Masaru Yoshioka (University of California, Santa Barbara) and Bette Otto-Bliesner (CCR).

Peter Thornton (TSS) continued research to develop the carbon and nitrogen biogeochemical algorithms for CLM. The core biogeochemical capabilities for carbon and nitrogen cycling were implemented in CLM during FY 2003. Over the past year these capabilities have been extensively evaluated and expanded, and long offline and coupled simulations have now been executed in a number of different configurations to demonstrate the readiness of the new model (CLM3-CN) for research applications.

Offline simulations driven by the National Center for Environmental Prediction NCEP/NCAR reanalysis surface weather fields have demonstrated that the new land biogeochemistry behaves reasonably under prescribed atmospheric forcing. The first long simulations coupling the new land model to the atmosphere in CCSM3 (with prescribed ocean and ice boundary conditions) have just been completed. The results suggest that both the improved canopy integration scheme and the prognostic carbon and nitrogen cycles have a significant impact on the coupled climate simulation. A major contributor to climate feedback in the new model is the prognostic canopy leaf area, which causes the seasonal, interannual, and long-term dynamics of the canopy to respond directly to the model climate, in contrast to the default land model which prescribes the seasonal cycle and spatial distribution of canopy leaf area from satellite observations. Next steps include simulations to quantify the climate feedbacks due to greenhouse forcing from prognostic carbon fluxes on land, and fully coupled simulations including the carbon cycle biogeochemistry of the oceans.

This figure shows comparison of annual average leaf area index (LAI) for the default implementation of CLM3 in CCSM3 (top), and for the new implementation of CLM3-CN which includes prognostic carbon and nitrogen cycles (bottom). The CLM3 LAI is derived from remote sensing observations and does not respond in any way to the modeled climate. The CLM3-CN LAI is a product of the prognostic development of vegetation canopy carbon and nitrogen state variables, with strong seasonal, interannual, and climatological responsiveness to the modeled surface weather and climate fields. The CLM3-CN result in this example is an intermediate result with nitrogen limitations turned off to achieve more rapid canopy development.

Thornton is participating in the Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) experiments. For this effort, he defined new requirements for the data atmosphere component of CCSM3 and defined the spinup protocol for the C4MIP experiments. He used the C4MIP protocol for prescribed transient landuse changes to define the requirements for the input datasets and the implementation of changing landcover within CLM. All of the raw datasets have been assembled and processed to produce a preindustrial potential vegetation map and a timeseries of landcover from 1900-1990 that includes the fractional gridcell coverage for crops and pasture and their changes through time.

Thornton is Principal Investigator on a project sponsored by the NASA Earth Science Technology Office to develop and implement a research-quality user interface for high-resolution carbon cycle simulation, using the Daymet and Biome-BGC models as technology components. The project involves a close collaboration with researchers in Scientific Computing Division (SCD) to implement this interface as a web-based tool that can connect remote users to not only a set of state-of-the-art modeling tools, but also the high-end computational and data storage resources required to perform and analyze high-resolution simulations over large regions.

Thornton led an effort with Nan Rosenbloom (TSS) and Sylvia Murphy (CCSM Software Engineering Group (SEG)) to produce an updated diagnostics package for CLM that includes new variables for the CN code.

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. TSS scientists worked on several projects to implement land cover and land use change in CLM and to use climate models to study the impact of these processes on climate. This work contributes to the NCAR Weather and Climate Impact Assessment Science Initiative and the NCAR Biogeosciences Initiative.

Johannes Feddema (University of Kansas), Bonan, Oleson, and Mearns (Environmental and Societal Impacts Group (ESIG)) studied the effects of historical and future land cover change on global climate. Climate model simulations were performed with the Parallel Climate Model (PCM) and examined the sensitivity of simulated climate to different specifications of present-day land cover and natural potential vegetation. Uncertainty in the classification of present-day vegetation can produce large differences in the simulated climate. Present-day vegetation has generally cooled surface climate, especially in the mid-latitudes due to the higher albedo of croplands compared to natural vegetation. Climate model simulations using land cover for the year 2100 showed that the land cover forcing of climate can be large, especially in tropical South America and in the United States, where agricultural land is projected to become more extensive by the year 2100.

Bonan, Oleson, and Feddema also worked to develop and implement an urban land cover parameterization for CLM. The parameterization uses concepts from urban canyon models to simulate the radiative balance of a city, turbulent energy fluxes, and the hydrologic cycle.

Agroecosystems differ from other terrestrial ecosystems due to their intensive management. Levis and Bonan worked to implement a crop model in CLM. The CLM is being modified from one crop type with prescribed leaf area index to include corn, wheat, and soybean, and to allow leaf area to grow in response to prevailing atmospheric conditions and management practices. The crop model is based on a model developed by Chris Kucharik, Jon Foley, and colleagues at the University of Wisconsin. This will provide a first order look at the sensitivity of climate to better specification of croplands.

Carbon Data Assimilation

Through the activities of Dave Schimel (TSS), the section holds a leadership position in the development of data assimilation techniques for biogeochemistry and carbon cycle studies.

The carbon cycle is an important and dynamic part of the Earth System. Recent experiments as part of the C4MIP program of model intercomparison have revealed the potential for significant feedbacks between the carbon cycle and the climate system, yet at large scales, the carbon models remain essentially unvalidated. While some aspects of the carbon models can be tested at local (hectare-kilometer) scales, few techniques exist for either estimating parameter values or testing model performance at scales comparable to model grid resolution. We are conducting an integrated program that focuses on combining measurements and innovative modeling techniques at regional scales. This program, the Airborne Carbon in the Mountains Experiment (ACME) focuses on quantifying carbon fluxes in mountain and mountain-valley complex landscapes using airborne and ground-based flux measurement techniques. Mountains might seem like a challenging choice meteorologically, but we selected this region for two reasons. The first consideration is importance. In the mid-latitudes of the Northern Hemisphere, much of the actively growing forests occur in complex landscapes, and so techniques are urgently required. The second consideration is methodological. Much of the uncertainty in carbon models is in the respiratory processes or the release of photosynthetically fixes carbon back to the atmosphere. In level landscapes, this measurement is challenging as eddy covariance fails in (common) stable nighttime conditions. In the mountains, concentration measurements in nighttime drainage flows allows “scaling up” respiratory fluxes to airshed or “carbonshed” scales. This gives access to a key unknown at a range of large scales.

The overall ACME program was carried out in summer 2004 and involved 54 flight hours using the NCAR C-130 and a four-month deployment of the Integrated Surface Flux Facility (ISSF), complementing long term measurements made by the University of Colorado at Niwot Ridge. The project involves Principal Investigators from the University of Colorado, Colorado State University, collaborators from the University of Miami-Florida, University of Montana, and guest scientists from the University of Utah, Scripps Institution of Oceanography, and Washington State University. The project is part of NCAR’s Biogeosciences Initiative, and contributes to the National Science Foundation (NSF) Biocomplexity Program, the NASA Interdisciplinary Science Program, and is part of the interagency North American Carbon Program.

The airborne program explored a number of techniques for estimating carbon fluxes, and focused on separating nighttime and daytime fluxes. Nighttime fluxes were estimated by early morning profiling into the nocturnal boundary layer, while daytime fluxes were estimated using semi-lagrangian experiments and airborne eddy covariance. Results showed clear accumulation of CO₂ in the nocturnal boundary layer and strong daytime drawdown. Results are currently being analyzed using a mesoscale data assimilation system based on the CSU RAMS (RAMDAS) coupled atmospheric-land surface model. The ground-based component, the Carbon in the Mountains Experiment (CME) deployed three ISFF towers on Niwot Ridge, Colorado from July-October 2004, extending a permanent 4-tower flux array maintained by University of Colorado and the US Geological Survey (USGS). All of the towers measure CO₂ concentrations and physical parameters. Two of the ISFF towers also made flux measurements. The towers allow quantification of nighttime advective fluxes and can be inverted to estimate respiration. Each ACME flight included overpasses of the CME site and allow extension of the results across scales.

The CME tower studies will be analyzed using a unique carbon process data assimilation model developed by University of New Hampshire and NCAR scientists which allows forest carbon fluxes from eddy covariance and advective techniques to be inverted into estimates of ecosystem model parameters. Preliminary studies have already demonstrated that key ecosystem parameters can be retrieved using this method. The model is being extended to include satellite vegetation estimates, water cycle measurements and isotopes. The current process model being used is highly simplified from the CLM but includes a number of common process formulations and structure. As the information content of the flux data are better understood, we will move from assimilating into a model of reduced dimensionality (SPACENET) into assimilation of parameters and states in the full CLM. Results from the SPACENET and CLM assimilations can be compared to fluxes estimated from the airborne program using RAMDAS.

Taken together, the experiment provides an innovative way of estimating landscape-scale parameters for land surface models, and a way of validating these models against regional airborne measurements. The separation of the airborne program into daytime (photosynthesis-respiration) and nighttime (respiration alone) fluxes allows the model to be tested much more rigorously than in previous studies where 24-hour measurements were made. This study is a pathfinder for upcoming intensives of the North American Carbon Program where this and other approaches for analyzing large-scale observations, model development, and model testing will be explored.

This figure shows morning and afternoon flight segments of a typical ACME day. On the upper left, early morning vertical profiling and low-level survey flights, along with the upwind segment of a semi-lagrangian flight (extension to the Northwest). Upper right, afternoon flights showing the downwind segment of the semi-lagrangian experiment and low-level eddy covariance surveys. The lower left panel shows typical morning profiles indicating large accumulation of respired CO₂ in the nocturnal boundary layer. These accumulations, also evident in low-level survey flights, suggest that large-scale drainage flows may be used to develop integrated estimates of respiration in the mountains. The lower right panel shows morning and afternoon profiles of CO₂ from the semi-lagrangian experiment, together with the CO profiles used to correct for pollution signals.