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.