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Title: Terrestrial Biogeochemistry in the Community Climate System Model (CCSM)

Authors:
 [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Center for Computational Sciences
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1003661
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Physics Conference Series; Journal Volume: 46
Country of Publication:
United States
Language:
English

Citation Formats

Hoffman, Forrest M. Terrestrial Biogeochemistry in the Community Climate System Model (CCSM). United States: N. p., 2006. Web. doi:10.1088/1742-6596/46/1/051.
Hoffman, Forrest M. Terrestrial Biogeochemistry in the Community Climate System Model (CCSM). United States. doi:10.1088/1742-6596/46/1/051.
Hoffman, Forrest M. Sun . "Terrestrial Biogeochemistry in the Community Climate System Model (CCSM)". United States. doi:10.1088/1742-6596/46/1/051.
@article{osti_1003661,
title = {Terrestrial Biogeochemistry in the Community Climate System Model (CCSM)},
author = {Hoffman, Forrest M},
abstractNote = {},
doi = {10.1088/1742-6596/46/1/051},
journal = {Journal of Physics Conference Series},
number = ,
volume = 46,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2006},
month = {Sun Jan 01 00:00:00 EST 2006}
}
  • The primary goal of the project entitled “Incorporation of the HYbrid Coordinate Ocean Model (HYCOM) into the Community Climate System Model (CCSM): Evaluation and Climate Applications” was to systematically investigate the performance of the HYbrid Coordinate Ocean Model (HYCOM) as an alternative oceanic component of the NCAR’s Community Climate System Model (CCSM). We have configured two versions of the fully coupled CCSM3/HYCOM: one with a medium resolution (T42) Community Atmospheric Model (CAM) and the other with higher resolution (T85). We have performed a comprehensive analysis of the 400-year fully coupled CCSM3/HYCOM simulations and compared the results with those from CCSM3/POPmore » and with climatological observations, and also we have performed tuning of critical model parameters, including Smagorinsky viscosity, isopycnal diffusivity, and background vertical diffusivity. The analysis shows that most oceanic features are well represented in the CCSM3/HYCOM. The coupled CCSM3/HYCOM (T42) has been integrated for 400 years, and the results have been archived and transferred to the High Performance Computer in the Florida State Univesity. In the last year, we have made comprehensive diagnostics of the long-term simulations by the comparison with the original CCSM3/POP simulation and with the observations. To gain some understanding of the model biases, the mean climate and modes of climate variability of the two models are compared with observations. The examination includes the Northern and Southern Annular Modes (NAM and SAM), the Pacific-North-American (PNA) pattern, the Atlantic Multidecadal Oscillation (AMO), and the main Southern Ocean SST mode. We also compared the performance of ENSO simulation in the coupled models. This report summarizes the main findings from the comparison of long-term CCSM3/HYCOM and CCSM3/POP simulations.« less
  • 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 themore » 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 that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.« less
  • Global climate models (GCMs) have not effectively considered how responses of arctic marine ecosystems to a warming climate will influence the global climate system. A key response of arctic marine ecosystems that may substantially influence energy exchange in the Arctic is a change in dimethylsulfide (DMS) emissions, because DMS emissions influence cloud albedo. This response is closely tied to sea ice through its impacts on marine ecosystem carbon and sulfur cycling, and the ice-albedo feedback implicated in accelerated arctic warming. To reduce the uncertainty in predictions from coupled climate simulations, important model components of the climate system, such as feedbacksmore » between arctic marine biogeochemistry and climate, need to be reasonably and realistically modeled. This research first involved model development to improve the representation of marine sulfur biogeochemistry simulations to understand/diagnose the control of sea-ice-related processes on the variability of DMS dynamics. This study will help build GCM predictions that quantify the relative current and possible future influences of arctic marine ecosystems on the global climate system. Our overall research objective was to improve arctic marine biogeochemistry in the Community Climate System Model (CCSM, now CESM). Working closely with the Climate Ocean Sea Ice Model (COSIM) team at Los Alamos National Laboratory (LANL), we added 1 sea-ice algae and arctic DMS production and related biogeochemistry to the global Parallel Ocean Program model (POP) coupled to the LANL sea ice model (CICE). Both CICE and POP are core components of CESM. Our specific research objectives were: 1) Develop a state-of-the-art ice-ocean DMS model for application in climate models, using observations to constrain the most crucial parameters; 2) Improve the global marine sulfur model used in CESM by including DMS biogeochemistry in the Arctic; and 3) Assess how sea ice influences DMS dynamics in the arctic marine environment and predict how it will do so in the future.« less
  • With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon-LAnd Model Intercomparison Project (C-LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) - Carnegie-Ames-Stanford Approach (CASA) and carbon-nitrogen (CN). Bothmore » models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO{sub 2} measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1-3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO{sub 2} and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr{sup -1} for CASA vs. 1.2 Pg C yr{sup -1} for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988-2004 based on comparison with atmospheric inversion results from TRANSCOM (r=0.66 for CASA and r=0.73 for CN). Adding (CASA) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C-LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community-wide platform for model-data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C-LAMP are publicly available on the Earth System Grid.« less
  • Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climatemore » feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.« less