moving towards a global biogeophysical parameter ... · moving towards a global biogeophysical...
TRANSCRIPT
![Page 1: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/1.jpg)
Moving towards a global biogeophysical parameter optimization for CLM5
Katie Dagon Land Model Working GroupNCAR ASP Postdoc June 19, 2018
With input and assistance from: Gordon Bonan, Rosie Fisher, David John Gagne, Daniel Kennedy, Dave Lawrence, Danica Lombardozzi, Ben Sanderson, Bill Sacks, and Sean Swenson
![Page 2: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/2.jpg)
What role do parameter choices play in overall land model uncertainty?
Bonan and Doney (2018)
Sources of Model Uncertainty
6/19/18 2K. Dagon
• Initial conditions
• Model forcing
• Model structure
• Parameters
![Page 3: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/3.jpg)
CLM Biogeophysical Processes
6/19/18 K. Dagon 3
Image: CLM5 Tech Note
![Page 4: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/4.jpg)
Research Questions
1. What are the highly sensitive CLM biogeophysicalparameters?
2. Given a set of sensitive parameters and using existing observational datasets, what are the optimal values?
3. How are the results of global and regional climate modeling studies impacted by parameter uncertainty?
6/19/18 K. Dagon 4
![Page 5: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/5.jpg)
CLM5 Parameter Ensemble• CLM5SP, 4°x5° resolution, 20 year runs (sample last 5
years)
6/19/18 K. Dagon 5
![Page 6: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/6.jpg)
CLM5 Parameter Ensemble• CLM5SP, 4°x5° resolution, 20 year runs (sample last 5
years)• One-at-a-time min/max perturbations: 34 parameters
• 10 PFT-dependent parameters (params file)• 3 namelist parameters (user_nl_clm)• 21 hard-coded parameters (SourceMods)
6/19/18 K. Dagon 6
![Page 7: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/7.jpg)
CLM5 Parameter Ensemble• CLM5SP, 4°x5° resolution, 20 year runs (sample last 5
years)• One-at-a-time min/max perturbations: 34 parameters
• 10 PFT-dependent parameters (params file)• 3 namelist parameters (user_nl_clm)• 21 hard-coded parameters (SourceMods)
• 7 Outputs to assess sensitivity1. Gross Primary Productivity (GPP)2. Evapotranspiration (ET)3. Transpiration Fraction = Transpiration/ET4. Sensible Heat Flux (SH)5. 10cm Soil Moisture6. Total Column Soil Moisture7. Water Table Depth
6/19/18 K. Dagon 7
![Page 8: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/8.jpg)
34 parameters top 6• Based on sensitivity metric, pattern correlations,
availability of relevant observational data
6/19/18 K. Dagon 8
Name Description
medlynslope Medlyn slope of conductance-photosynthesis relationship
kmax Plant segment max conductance (PHS)
fff Surface runoff parameter; decay factor for fractional saturated area
dint Fraction of saturated soil for moisture value at which dry surface layer initiates
dleaf Characteristic dimension of leaves in the direction of wind flow (leaf boundary layer resistance)
baseflow_scalar Scalar multiplier for base flow rate
![Page 9: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/9.jpg)
Sensitivity Metric
6/19/18 K. Dagon 9
Parameter Effect (PE) = |Xmax – Xmin| (then global mean, annual mean)
![Page 10: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/10.jpg)
Sensitivity to GPP for final 6 parameters(annual mean, last 5 years)
𝜇𝜇mol CO2 m-2 s-1
6/19/18 K. Dagon 10
Sensitivity MetricParameter Effect (PE) = |Xmax – Xmin| (then global mean, annual mean)
![Page 11: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/11.jpg)
Sensitivity to GPP for final 6 parameters(annual mean, last 5 years)
Global mean values:
𝜇𝜇mol CO2 m-2 s-1
6/19/18 K. Dagon 11
Name GPP PEdleaf 0.07kmax 0.82medlynslope 0.36baseflow_scalar 0.01fff 0.34dint 0.10
Sensitivity MetricParameter Effect (PE) = |Xmax – Xmin| (then global mean, annual mean)
![Page 12: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/12.jpg)
Pattern Correlations• What are the spatial correlations of the PE between these
parameters?• All output combinations for each parameter reveals overlapping
outputs (e.g., ET and SH)• All pairwise parameter combinations for each output reveals
overlapping parameters
6/19/18 K. Dagon 12
![Page 13: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/13.jpg)
Pattern Correlations• What are the spatial correlations of the PE between these
parameters?• All output combinations for each parameter reveals overlapping
outputs (e.g., ET and SH)• All pairwise parameter combinations for each output reveals
overlapping parameters
6/19/18 K. Dagon 13
dleaf kmax medlynslope baseflow_scalar fff dintdleaf 1 0.34 0.70 0.08 0.62 0.69kmax 0.34 1 0.36 0.09 0.18 0.003
medlynslope 0.70 0.36 1 0.19 0.67 0.65
baseflow_scalar 0.08 0.09 0.19 1 0.13 0.16fff 0.62 0.18 0.67 0.13 1 0.70dint 0.69 0.003 0.65 0.16 0.70 1
![Page 14: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/14.jpg)
CLM5 Optimization Ensemble
• Use Latin Hypercube sampling to generate 100 random parameter sets for top 6 parameters• Including unique ranges for each PFT as applicable
• Run 100 simulations with CLM5SP, 4°x5° resolution• Build and train a neural network to emulate model output
given parameter values
6/19/18 K. Dagon 14
![Page 15: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/15.jpg)
Training the Neural Network
6/19/18 K. Dagon 15
Model Output (global mean GPP)
Model Input (parameter values)
100 simulations
100 parameter sets for 6 parameters
P1 P2 P3 P4 P5 P6S1 x1,1 x1,2 x1,3 x1,4 x1,5 x1,6
S2 x2,1 x2,2 x2,3 x2,4 x2,5 x2,6
S3 x3,1 x3,2 x3,3 x3,4 x3,5 x3,6
… … … … … … …S100 x100,1 x100,2 x100,3 x100,4 x100,5 x100,6
![Page 16: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/16.jpg)
Training the Neural Network
6/19/18 K. Dagon 16
Observations(GPP, ET, etc.)
Model Input (parameter values)
1000s of parameter sets for 6 parameters
P1 P2 P3 P4 P5 P6S1 x1,1 x1,2 x1,3 x1,4 x1,5 x1,6
S2 x2,1 x2,2 x2,3 x2,4 x2,5 x2,6
S3 x3,1 x3,2 x3,3 x3,4 x3,5 x3,6
… … … … … … …… … … … … … …… … … … … … …S1000+ … … … … … …
Which parameter set(s) produces optimal value for given observation(s)?
![Page 17: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/17.jpg)
Summary and Future Work
• Narrowed the CLM5 biogeophysical parameter space through one-at-a-time parameter sensitivity simulations
• Built a simple neural network and trained model output (GPP) against model input (parameter values)
Up next:• Optimize parameter sets using observational datasets
with trained neural network• Apply results to climate change simulations
6/19/18 17K. Dagon
Contact: [email protected]
![Page 18: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/18.jpg)
Backup
6/19/18 18K. Dagon
![Page 19: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/19.jpg)
CLM Hydrologic Processes
6/19/18 K. Dagon 19
Image: LMWG
![Page 20: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/20.jpg)
Previous Work: CLM4.5 Parameter Sensitivity Study
6/19/18 K. Dagon 20
Focused on land surface hydrology: evapotranspiration and soil moisture
![Page 21: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/21.jpg)
Testing equilibrium time: 30 years of CLM5SP spin-up under default parameter values; the same 5 years of GSWP forcing data repeated
Is 15 years of spin-up enough?
Soil moisture trends:0.98 kgm-2/yr (30 years)-0.08 kgm-2/yr (last 15 years)
-- Latent Heat-- Sensible Heat
Heat flux trends:-0.006 Wm-2/yr (LH)0.014 Wm-2/yr (SH)0.011 Wm-2/yr (SH, last 15 yrs)
6/19/18 K. Dagon 21
![Page 22: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/22.jpg)
Improving PFT parameter ranges based on observational data
• dleaf: characteristic dimension of leaves in the direction of wind flow (previously constant for all PFTs)• 1 dataset from the TRY database with concurrent measurements of
leaf width and PFT information (leaf type, phenology, growth form)• Enough to get reasonable leaf width ranges for each PFT• dleaf = f*(leaf_width), where f = leaf shape-dependent factor
Campbell and Norman (1998)Parkhurst et al. (1968)
6/19/18 K. Dagon 22
![Page 23: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/23.jpg)
• medlynslope: slope of stomatal conductance-photosynthesis relationship• Genus or species-based linear regressions to obtain slope values• Min and max values from set of slopes for each PFT
y = 3.1887xR² = 0.1865
0
0.05
0.1
0.15
0.2
0.25
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
Acer
Improving PFT parameter ranges based on observational data
medlynslope for genus Acer contributes to range of values for broadleaf deciduous PFT
6/19/18 K. Dagon 23
![Page 24: Moving towards a global biogeophysical parameter ... · Moving towards a global biogeophysical parameter optimization for CLM5 Katie Dagon Land Model Working Group NCAR ASP Postdoc](https://reader036.vdocuments.net/reader036/viewer/2022062915/5e9d1e038ac0bd6f664f2e6c/html5/thumbnails/24.jpg)
Parameter Name PE rank PC rank Type CLM5 default value Min value Max value Units
medlynslope 1 33 P ranges [1.62, 5.79] ranges [0.53, 3.46] ranges [4.03, 7.70]𝜇𝜇mol H2O/𝜇𝜇mol CO2
kmax 2 24 P 2.00E-08 2.00E-09 3.80E-08 s-1
fff 3 19 HC 0.5 0.02 5 m-1
dint 4 16 HC 0.8 0.5 1 --
dleaf 10 23 P 0.04ranges [0.000144,
0.0081]ranges [0.00108,
0.243] m
baseflow_scalar 17 2 N 0.001 0.0005 0.1 --
Summarizing the top 6 parameters
Parameter Effect (PE) = |Xmax – Xmin| (then global mean, annual mean)Ranked sensitivity to 7 outputsAverage rank across outputs to generate most sensitive parameters (larger PE implies higher rank)
Pattern Correlation (PC) = spatial correlation of PE between all pairwise combinations of parameters Summed correlations for each pair across 7 outputs Average across parameters; compute rank (smaller PC implies higher rank)
Type denotes PFT-dependent (P), namelist (N), or hard-coded (HC)Move HC parameters into the namelistTackle PFT and namelist parameters separately
6/19/18 K. Dagon 24