Ian T. Baker

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...

TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002-2003

The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.

Evaluation of forest snow processes models (SnowMIP2)

Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up t ...

Seasonal drought stress in the Amazon: Reconciling models and observations

[1] The Amazon Basin is crucial to global circulatory and carbon patterns due to the large areal extent and large flux magnitude. Biogeophysical models have had difficulty reproducing the annual cycle of net ecosystem exchange (NEE) of carbon in some regions of the Amazon, generally simulating uptake during the wet season and efflux during seasonal drought. In reality, the opposite occurs. Observational and modeling studies have identified several mechanisms that explain the observed annual cycle, including: (1) deep soil columns that can store large water amount, (2) the ability of deep roots to access moisture at depth when near-surface soil dries during annual drought, (3) movement of water in the soil via hydraulic redistribution, allowing for more efficient uptake of water during the wet season, and moistening of near-surface soil during the annual drought, and (4) photosynthetic response to elevated light levels as cloudiness decreases during the dry season. We incorporate these mechanisms into the third version of the Simple Biosphere model (SiB3) both singly and collectively, and confront the results with observations. For the forest to maintain function through seasonal drought, there must be sufficient water storage in the soil to sustain transpiration through the dry season in addition to the ability of the roots to access the stored water. We find that individually, none of these mechanisms by themselves produces a simulation of the annual cycle of NEE that matches the observed. When these mechanisms are combined into the model, NEE follows the general trend of the observations, showing efflux during the wet season and uptake during seasonal drought.

TransCom model simulations of hourly atmospheric CO2 : experimental overview and diurnal cycle results for 2002

[1] A forward atmospheric transport modeling experiment has been coordinated by the TransCom group to investigate synoptic and diurnal variations in CO2. Model simulations were run for biospheric, fossil, and air-sea exchange of CO2 and for SF6 and radon for 2000-2003. Twenty-five models or model variants participated in the comparison. Hourly concentration time series were submitted for 280 sites along with vertical profiles, fluxes, and meteorological variables at 100 sites. The submitted results have been analyzed for diurnal variations and are compared with observed CO2 in 2002. Mean summer diurnal cycles vary widely in amplitude across models. The choice of sampling location and model level account for part of the spread suggesting that representation errors in these types of models are potentially large. Despite the model spread, most models simulate the relative variation in diurnal amplitude between sites reasonably well. The modeled diurnal amplitude only shows a weak relationship with vertical resolution across models; differences in near-surface transport simulation appear to play a major role. Examples are also presented where there is evidence that the models show useful skill in simulating seasonal and synoptic changes in diurnal amplitude.

Photosynthetic control of atmospheric carbonyl sulfide during the growing season.

Climate models incorporate photosynthesis-climate feedbacks, yet we lack robust tools for large-scale assessments of these processes. Recent work suggests that carbonyl sulfide (COS), a trace gas consumed by plants, could provide a valuable constraint on photosynthesis. Here we analyze airborne observations of COS and carbon dioxide concentrations during the growing season over North America with a three-dimensional atmospheric transport model. We successfully modeled the persistent vertical drawdown of atmospheric COS using the quantitative relation between COS and photosynthesis that has been measured in plant chamber experiments. Furthermore, this drawdown is driven by plant uptake rather than other continental and oceanic fluxes in the model. These results provide quantitative evidence that COS gradients in the continental growing season may have broad use as a measurement-based photosynthesis tracer.

Effect of climate on interannual variability of terrestrial CO2 fluxes

This paper was published as Global Biogeochemical Cycles, 2002, 16 (4), GB1102. Copyright

Evaluation of continental carbon cycle simulations with North American flux tower observations

Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. The skill of models that provide continental-scale carbon flux estimates, however, remains largely untested. This paper evaluates the performance of continental-scale flux estimates from 17 models against observations from 36 North American flux towers. Fluxes extracted from regional model simulations were compared with co-located flux tower observations at monthly and annual time increments. Site-level model simulations were used to help interpret sources of the mismatch between the regional simulations and site-based observations. On average, the regional model runs overestimated the annual gross primary productivity (5%) and total respiration (15%), and they significantly underestimated the annual net carbon uptake (64%) during the time period 2000- 2005. Comparison with site-level simulations implicated choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models performed the best at simulating carbon exchange at deciduous broadleaf sites, likely because a number of models used prescribed phenology to simulate seasonal fluxes. The models did not perform as well for crop, grass, and evergreen sites. The regional models matched the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but they have very little skill at interannual correlation and minimal skill at interannual magnitude of variability. The comparison of site vs. regional-level model runs demonstrated that (1) the interannual correlation is higher for site-level model runs, but the skill remains low; and (2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best-performing regional models that did not use flux tower calibration were CLM-CN, CASA-GFEDv2, and SIB3.1. Two flux tower calibrated, empirical models, EC-MOD and MOD17þ, performed as well as the best process-based models. This suggests that (1) empirical, calibrated models can perform as well as complex, process-based models and (2) combining process- based model structure with relevant constraining data could significantly improve model performance.

Role of deep soil moisture in modulating climate in the Amazon rainforest

Received 28 December 2009; accepted 19 January 2010; published 2 March 2010. [1] Both local and large‐scale processes affect the Amazon hydrologic cycle. We investigate the impact of deep soils on the atmosphere through local feedbacks. The Simple Biosphere model, version 3 (SiB3), is coupled to a single column model. Historically, land surface schemes parameterize soil moisture stress based on shallow soils and incorrectly capture seasonal cycles in the Amazon. Following observations, SiB3 is updated to allow deep roots to access soil moisture at depth. The new (“Unstressed”) version of SiB3 has a stronger hydrologic cycle, with increased evapotranspiration and moisture export during the dry season. The boundary layer responds through changes in its depth, relative humidity, and turbulent kinetic energy, and these changes feed back to influence wet season onset and intensity. Differences in atmospheric latent heating could affect circulation in a global model. The results have important consequences for modeling the Amazon hydrologic cycle and climate in global climate models. Citation: Harper, A. B., A. S. Denning, I. T. Baker, M. D. Branson, L. Prihodko, andD.A.Randall (2010),Roleof deepsoil moistureinmodulatingclimateintheAmazonrainforest,Geophys.Res.Lett.,

Seasonal fluxes of carbonyl sulfide in a midlatitude forest

Significance The flux of carbonyl sulfide (OCS) provides a quantitative, independent measure of biospheric activity, especially stomatal conductance and carbon uptake, at the ecosystem scale. We describe the factors controlling the hourly, daily, and seasonal fluxes of OCS based on 1 year of observations in a forest ecosystem. Vegetation dominated uptake of OCS, with daytime fluxes accounting for 72% of the total uptake for the year. Nighttime fluxes had contributions from both incompletely closed stomata and soils. Net OCS emission was observed at high temperature in summer. Diurnal and seasonal variations in OCS flux show variable stoichiometry relative to photosynthetic uptake of CO2. An effective model framework is shown, using an explicit representation of ecosystem processing of OCS. Carbonyl sulfide (OCS), the most abundant sulfur gas in the atmosphere, has a summer minimum associated with uptake by vegetation and soils, closely correlated with CO2. We report the first direct measurements to our knowledge of the ecosystem flux of OCS throughout an annual cycle, at a mixed temperate forest. The forest took up OCS during most of the growing season with an overall uptake of 1.36 ± 0.01 mol OCS per ha (43.5 ± 0.5 g S per ha, 95% confidence intervals) for the year. Daytime fluxes accounted for 72% of total uptake. Both soils and incompletely closed stomata in the canopy contributed to nighttime fluxes. Unexpected net OCS emission occurred during the warmest weeks in summer. Many requirements necessary to use fluxes of OCS as a simple estimate of photosynthesis were not met because OCS fluxes did not have a constant relationship with photosynthesis throughout an entire day or over the entire year. However, OCS fluxes provide a direct measure of ecosystem-scale stomatal conductance and mesophyll function, without relying on measures of soil evaporation or leaf temperature, and reveal previously unseen heterogeneity of forest canopy processes. Observations of OCS flux provide powerful, independent means to test and refine land surface and carbon cycle models at the ecosystem scale.