evaluation of land model simulations across multiple sites and multiple models: results from the...
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Evaluation of land model simulations across multiple sites
and multiple models:Results from the NACP site-level
synthesis effort
Peter Thornton1, Gautam Bisht1, Dan Ricciuto1, NACP Site-Level
Synthesis Participants
1 Oak Ridge National Laboratory, Environmental Sciences Division and ORNL Climate Change Science Institute
Sponsors
• NASA Terrestrial Ecology Program
• DOE, Office of Biological and Environmental Research, Climate and Environmental Sciences Division, Terrestrial Ecosystem Science Program
Premise
• Models can and should serve as tools for the integration and synthesis of our best understanding and knowledge
• Models can and should provide testable (falsifiable) hypotheses
• Through model-data synthesis efforts, those hypotheses can and should be tested, and discarded or improved when confidence is shown to be low
Analysis setting• Subset of sites and models from full NACP
site-level synthesis effort• Forest sites (evergreen and deciduous)• Range of climates• Models that include diurnal cycle• Carbon, sensible heat, latent heat fluxes• Diurnal cycle, seasonal cycle, interannual
variability, long-term mean• Influence of steady-state vs. transient
forcings
12 Models and 13 Sites
• CAN-IBIS• CNCLASS• CLM-CN• ECOSYS• ED2• ISOLSM• LOTEC• ORCHIDEE• SIB• SIBCASA• SSIB2• TECO
• CA-Ca1 Campbell River• CA-Oas Old aspen• CA-Obs Old black spruce• CA-Ojp Old jack pine• CA-Qfo Mature black spruce• CA-TP4 Turkey Point• US-Dk3 Duke Forest pine• US-Ha1 Harvard Forest main• US-Ho1 Howland main• US-Me2 Metolius intermediate• US-MOz Missouri Ozark• US-NR1 Niwot Ridge• US-UMB U Michigan Bio Stn
Diurnal cycle of GPP: US-Dk3
Mean diurnal cycle for June-July-August, y-axis units = umol/m2/s, x-axis is half-hour time step. Results from steady-state simulations
Diurnal cycle of GPP: CA-Obs
Diurnal cycle of GPP: US-UMB
Diurnal cycle of NEE: CA-Oas
Diurnal cycle of NEE: US-Ha1
Diurnal cycle of NEE: US-Dk3
Diurnal cycle of NEE: CLM-CN
Seasonal cycle of CLM-CN: US-Ha1
Findings: 1
• Time-scale of N-limitation mechanism in CLM-CN is wrong.– Evident at both diurnal and seasonal– Original hypothesis that plants respond to N
availability on sub-daily time scale should be rejected
– Introducing new mechanism to buffer N availability in time
Findings: 2
• Evaluation of LE suggests that current basis for estimation of stomatal conductance in CLM-CN is reasonable– This result should be revisited once new N
storage mechanism is added
Findings: 3
• CLM-CN is very sensitive to fine root : leaf allocation patterns– Difficult measurement– Likely candidate parameter for data
assimilation– Evidence emerging from global-scale studies
and comparison to root turnover data that model fine root longevity needs to be modified
• Other models sensitive to this as well?
Findings: 4 (underway)
• Introducing transient forcing (disturbance, rising atmospheric CO2, changing N deposition) seems to improve estimate of decadal-scale NEE– Doesn’t seem to change conclusions obtained
from steady-state simulations– This is the most critical flux for evaluation of
long-term climate-carbon cycle feedbacks
Conclusions
• Approach has proved very useful in identifying strengths and weaknesses in CLM-CN
• This kind of critical evaluation across multiple models provides a path forward for improved future model generations
• Improving modelers’ ability to know what to ask for from observationalists and experimentalists.
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