Land surface key issues and GLASS progress Land-surface and the key issues Bart van den Hurk...
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Transcript of Land surface key issues and GLASS progress Land-surface and the key issues Bart van den Hurk...
Land surface key issues and GLASS progress
Land-surface and the key issues
Land-surface and the key issues
Bart van den Hurkco-chair GLASS
Land surface key issues and GLASS progress
Overview of key-issuesOverview of key-issues
• Model development (parameterization and model structure)
• Surface characteristics/parameters• Land-atmosphere interaction, feedbacks
and climate change attribution• Data assimilation
Land surface key issues and GLASS progress
General developments in the past decades
General developments in the past decades
• Increases in– number of key components
• ’80s: surface energy• ’90s: surface hydrology• ’00s: surface biochemistry• ’10s: surface feedbacks (?)
– spatial detail• more surface types become relevant (urban,
lakes)• more types of land-atm interaction become
relevant– contribution to predictability at various time scales
Land surface key issues and GLASS progress
Outstanding parameterization issues
(1)
Outstanding parameterization issues
(1)• Hydrology
P-E > 0Often it’s not!We need:– groundwater
redistribution– overland flow (river
routing) and wetland formation
– dynamic calibration procedures
• Snow
Okavanga river Botswana:floodplain extent f(local P)
rms of basin discharge
old schemenew scheme
snow dominatedbasins
Land surface key issues and GLASS progress
Outstanding parameterization issues
(2)
Outstanding parameterization issues
(2)• Biogeochemistry
– Photosynthesis and carbon allocation used to be a “climate application”, but…
– phenology (LAI) and dependence on nutrients and droughts
– (temperature sensitivity of) soil respiration
– releases CH4 from wetlands, BVOC from forest, aerosol from arid or urban areas
anomaly fAPAR summer 2003 (obs and modelled); Ciais et al 2005
Land surface key issues and GLASS progress
Outstanding parameterization issues
(3)
Outstanding parameterization issues
(3)• Human land use and hydrology
management– urban “tiles”– lakes– irrigation
Siebert et al, 2005
Land surface key issues and GLASS progress
Outstanding issues in land-atmosphere
interaction
Outstanding issues in land-atmosphere
interaction• To what extent is land
responsible for land-atm.coupling variability?
• Studies with CRM and LES underway– sign of soilm-precip.feedback
depends on convective parameterizationPCTL
(Pwet-Pdry)
PCTL
positive feedback
negative feedback
Hohenegger et al, in press
Land surface key issues and GLASS progress
Outstanding Land Data Assimilation issues (1)Outstanding Land Data Assimilation issues (1)
• Multiple systems around (GLDAS, NWP systems) or coming up (Land Flux)
• Offline systems rely heavily on precip/rad forcing, coupled (“nudging”) systems on assumed dSM/dRH
• Land Flux from GRP maybe should merge concepts
Science question: willDA reduce the spread in current ET estimates?
Land surface key issues and GLASS progress
Outstanding Land Data Assimilation issues (2)Outstanding Land Data Assimilation issues (2)
• Data assimilation is also developing into new observational types– (SMOS) soil moisture– LAI from NDVI (requires long assimilation
window)
• Data assimilation and parameter estimation become increasingly intertwined– parameterization is increasingly relying on
calibration rather than model structure
• The suite of systems requires a coordinated Land Data Assimilation Intercomparison Project (LDAIP)
Land surface key issues and GLASS progress
Outstanding feedback/ attribution issues (1)
Outstanding feedback/ attribution issues (1)
• Diagnostics for land atmosphere coupling vary widely– (Koster’s , P/sm, LCL/sm, diurnal T/RH)
• …but refer to different processes• …and are not always observable• Integrated framework is being developed
in GLASS
Land surface key issues and GLASS progress
Outstanding feedback/ attribution issues (2)
Outstanding feedback/ attribution issues (2)
• Experiments address land use in climate signal– Land use 1870 and 1992 provided to 7 GCMs
• …but LUCID learns that parameter transfer is far from straightforward– GCMs have different tile structures and model
philosophies (e.g. yes/no phenology, yes/no prognostic albedo, …)
JJA temp responseof land use change
Land surface key issues and GLASS progress
Outstanding application/ operation issues (1)
Outstanding application/ operation issues (1)
• Surface Tile structure– debate on “types of heterogeneity” is not as active
anymore, but will increase again when spatial resolution increases (land param. in LES)
– some land surface types demand complex tiling structure (e.g. floodplains/wetlands with coupling to groundwater)
– tile structure determines interpretation of land use data to a large extent (see LUCID example)
• Coupled/offline operation– e.g. routing/groundwater need horizontal network– data assimilation of LAI needs long time window
Land surface key issues and GLASS progress
Outstanding application/ operation issues (2)
Outstanding application/ operation issues (2)
• Land Information System (LIS)– LIS is increasingly suited for complex
modelling/data assimilation experiments• multiple LSMs coupled to WRF or using
offline forcings data• data assimilation capabilities
– but its portability can probably be improved
• Also ECMWF is integrating offline surface driver into Integrated Forecasting System
Land surface key issues and GLASS progress
Conclusions on outstanding issues
Conclusions on outstanding issues
• Parameterization– new components (groundwater, lakes, urban,
…)– new diagnostics and/or experimental set-up:
• Data assimilation– combination of scheme structures desired– trade-off data assimilation/parameter
calibration revisited
• Infrastructure– need for flexible LIS-type systems will increase
“What is the true contribution of the land component to the climate system?”“Does my land surface model describe this contribution sufficiently well?”
Land surface key issues and GLASS progress
Progress report of GLASS
Progress report of GLASS
• The current structure
Land surface key issues and GLASS progress
Some issues concerning GLASS structure
Some issues concerning GLASS structure
• PILPS-type studies are still quite active (Urban, Snow, Radiation) but does not answer the question: how good should a model be? What benchmark should be considered?
• Data-assimilation is not well visible in structure
• Difference between local and global coupling is artificial
Land surface key issues and GLASS progress
Proposal for new structure (under discussion)
Proposal for new structure (under discussion)
benchmarking
land-atmospherecoupling
model datafusion
metricsGLACE2 LandFlux
LoCo
current projectsnew projects
PILPS-UrbanSnowMIP
LUCID
Coordinated LDAIP
RAMI4PILPSPILPS-Carbon 2
Land surface key issues and GLASS progress
Proposal for new structure (under discussion)
Proposal for new structure (under discussion)
benchmarking
land-atmospherecoupling
model datafusion
metricsGLACE2
LoCo
PILPS-UrbanSnowMIP
LUCID
Land surface key issues and GLASS progress
{
Global Land Atmosphere Coupling Exp 2: GLACE2Global Land Atmosphere Coupling Exp 2: GLACE2
• Adressing potential seasonal predictability from land surface state
• Integration into WCRP/TFSP project
Land surface key issues and GLASS progress
Perform ensembles of retrospective
seasonal forecasts
Initialize land stateswith “observations”,
using GSWP approach
Prescribed SSTs or the use of a coupled ocean
model
Initialize atmosphere with “observations”, via
reanalysis
Evaluate forecasts against
observations
Step 1:
Experiment overviewExperiment overview
Land surface key issues and GLASS progress
Perform ensembles of retrospective
seasonal forecasts
Initialize land stateswith “observations”,
using GSWP approach
Initialize atmosphere with “observations”, via
reanalysis
Evaluate forecasts against
observations
Step 2:
“Randomize” land
initializatio
n!
Experiment overviewExperiment overview
Prescribed SSTs or the use of a coupled ocean
model
Land surface key issues and GLASS progress
Step 3: Compare skill; isolate contribution of realistic land initialization.
Forecast skill obtain in experiment using
realistic land initialization
Forecast skill obtained in identical experiment,
except that land is not initialized to realistic
values
Forecast skill due to land initialization
Experiment overviewExperiment overview
Land surface key issues and GLASS progress
Group/Model Points of Contact
1. NASA/GSFC (USA): GMAO seasonal forecast system (old and new)
2. COLA (USA): COLA GCM, NCAR/CAM GCM
3. Princeton (USA): NCEP GCM
4. IACS (Switzerland): ECHAM GCM
5. KNMI (Netherlands): ECMWF
6. GFDL (USA): GFDL system
7. U. Gothenburg (Sweden): NCAR
8. CCSR/NIES/FRCGC (Japan): CCSR GCM
# models
S. Seneviratne, R. Andreas
E. Wood, L. Luo
P. Dirmeyer, Z. Guo
R. Koster, T. Yamada2
B. van den Hurk, H. Camargo, G. Balsamo
T. Gordon
J.-H. Jeong
T. Yamada
2
1
1
2
1
1
1
11 models
Confirmed participant list
Confirmed participant list
Land surface key issues and GLASS progress
Generation of SST Boundary Conditions
Generation of SST Boundary Conditions
• Needed: SST conditions for forecasts that do not include measurements of SSTs during the forecast period.
• Approach: Determine persistence timescales from observational record (with data exclusion) and reduce initial (measured) SST anomalies with time into the forecast, using those timescales.
Land surface key issues and GLASS progress
“Persisted” SST boundary conditions have been constructed and are now available online. (T. Yamada)
Land surface key issues and GLASS progress
Many groups started simulations
Many groups started simulations
Land surface key issues and GLASS progress
Original timelineOriginal timeline
• Summer 2007:– Finish identifying interested modeling groups
• Summer 2007– Provide data to participants (meteorological
forcing data, atmospheric initialization, SST conditions)
• Summer/Fall 2008– Simulations due
• Fall/Winter 2008– First analyses performed
Land surface key issues and GLASS progress
New timelineNew timeline
• Summer 2007:– Finish identifying interested modeling groups
• Summer 2007– Provide data to participants (meteorological
forcing data, atmospheric initialization, SST conditions)
• Summer/Fall 2008– Simulations due
• Fall/Winter 2008– First analyses performed
Spring 2008
Fall/Winter 2008
FirstSpring 2009
Land surface key issues and GLASS progress
http://gmao.gsfc.nasa.gov/research/GLACE-2/
http://gmao.gsfc.nasa.gov/research/GLACE-2/
Land surface key issues and GLASS progress
Proposal for new structure (under discussion)
Proposal for new structure (under discussion)
benchmarking
land-atmospherecoupling
model datafusion
metricsGLACE2
LoCo
PILPS-UrbanSnowMIP
LUCID
Land surface key issues and GLASS progress
Land Use and Climate – IDentification of robust impacts (LUCID)
Land Use and Climate – IDentification of robust impacts (LUCID)
• Designed to separate land use change and GHG signal
• Multiple phases (prescribed SST coupled models)
• Phase 1:– Fixed SSTs– 4 ensembles (30 yrs, 5 members)
• pre-industrial/present-day vegetation• pre-industrial/present-day GHG & SST
– 7 GCMs– First results presented during sep 2008 Paris
w/s
Land surface key issues and GLASS progress
Major outcomeMajor outcome
• Transfer of common landuse maps to model parameters quite variable– tiling structure– assignment of PFTs
– parameter treatment (fixed/prognostic albedo, z0)
– phenology (prescribed/prognostic LAI)
• Result– Response between models not very uniform– No reason to suspect significant teleconnection
patterns from land use– GRL paper (Pitman et al) being drafted
Land surface key issues and GLASS progress
LUCID JJA LHFLUCID JJA LHF
phenology of LAI
Small difference between forest/crop LAI
Land surface key issues and GLASS progress
Proposal for new structure (under discussion)
Proposal for new structure (under discussion)
benchmarking
land-atmospherecoupling
model datafusion
metricsGLACE2
LoCo
PILPS-UrbanSnowMIP
LUCID
Land surface key issues and GLASS progress
LoCoLoCo
• Multiple processes
• Multiple diagnostics being explored• Proposal for hierarchy of land-atm coupling
maps (see GEWEX News November’08)• Proof of concept to be applied to SGP with
LIS
direct PBL feedback on surface fluxes
Triggering of convection
Fueling convection
rememberinganomalies
PBL cloudformation
Land surface key issues and GLASS progress
Proposal for new structure (under discussion)
Proposal for new structure (under discussion)
benchmarking
land-atmospherecoupling
model datafusion
metricsGLACE2
LoCo
PILPS-UrbanSnowMIP
LUCID
Land surface key issues and GLASS progress
PILPS-Urban (Sue Grimmond, KCL)
http://geography.kcl.ac.uk/micromet/ModelComparison
PILPS-Urban (Sue Grimmond, KCL)
http://geography.kcl.ac.uk/micromet/ModelComparison
• Aimed at evaluation of urban models– range in structure (simple
plane parallel canopies complex multicomponent canyon models)
• Big group (22 models!)• Initial data-set (Vancouver)
released for testing• Presently: models are
running an anonymous city– hierarchy of data releases
(characteristics, calibration, validation)
Land surface key issues and GLASS progress
Proposal for new structure (under discussion)
Proposal for new structure (under discussion)
benchmarking
land-atmospherecoupling
model datafusion
metricsGLACE2
LoCo
PILPS-UrbanSnowMIP
LUCID
Land surface key issues and GLASS progress
SnowMIP (Richard Essery)
SnowMIP (Richard Essery)
• BAMS overview paper submitted• Main results:
– focus on forest– 33 models, 11 countries– sites Canada, US, Switzerland– results:
• accumulation and ablation ~ ok• albedo ~ ok• mass and difference forest/open land vary
widely• soil temperatures too low
Land surface key issues and GLASS progress
SWESWE
accumulation at open sites
Land surface key issues and GLASS progress
Soil TemperatureSoil Temperature
Land surface key issues and GLASS progress
Final remarksFinal remarks
• Parameterization focuses on new components
• Systematic benchmarking of both models and data is not well embedded but needs attention
• Data assimilation will benefit from LDAIC• New infrastructure inspired on LIS should
combine offline modelling, data fusion and benchmarking
• GLASS panel will get new membership