Post on 08-Jan-2016
description
Land Surface Fluxes in Coupled Land/Atmosphere Analysis Systems
Michael Bosilovich, NASA GSFC
And Collaborators
LandFlux Workshop, May 2007
Main Discussion Points
Surface Temperature AssimilationCoupled Analysis of Skin TemperatureValidation: Station Obs, CEOP Fluxes
MERRASurface data products, usefulness for LandFlux
Multi-Model Analysis for CEOP (MAC)7 operational analyses or reanalysesGoal: uncertainty in the physical processes
LandFlux Workshop, May 2007
Ts in Coupled Analysis
Motivation: surface skin temperature (Ts) is a critical state because
it reflects the surface radiative properties and energy budget and can dictate convective initiation.
Reliable Ts field from the operational GMAO DAS (Global Modeling and Assimilation Office Data Assimilation System) is a key requirement from scientific instrument team users.
Method: NCAR Community Land Model (CLM) version 2 land-sfc
model (Dai et al. 2002; Zeng et al. 2002; Bonan et al. 2002) and GEOS4 DAS (Bloom et al. 2005).
ISCCP 3 hourly, 30Km Skin Temperature Ts analysis and coupled bias correction
LandFlux Workshop, May 2007
Data Assimilation Method
PSAS–Analysis Increment (Cohn et al 1998)Incremental Bias Correction – Dee and da
Silva (1998)IBC expanded to consider Diurnal CycleInclude Incremental forcing at every time
step
BGTLETHTRRRRt
TC SSSSLLSS
S )()()(
Bosilovich et al. (2007, JMSJ)
LandFlux Workshop, May 2007
2m Air Temp, Mean BiasJuly 2001
LandFlux Workshop, May 2007
2m Diurnal Temp RangeJuly 2001
LandFlux Workshop, May 2007
LBA Fluxes: CEOP EOP1
a b
c d
e f
CTL Rondonia
CTL Manaus
EXP2 Rondonia
EXP2 Manaus
LandFlux Workshop, May 2007
BALTEX Fluxes: CEOP EOP1
CTL Lindenberg
CTL Cabauw
EXP2 Lindenberg
EXP2 Cabauw
l k
j i
LandFlux Workshop, May 2007
Coupled Ts Analysis Summary
Including Skin T analysis (bias correction) improved air temperature, and in limited comparisons sensible heat flux
Several (possibly systematic) degradations in Latent Heating were noted
Needs diurnally resolved Ts, and likely multivariate analysis (soil moisture, cloud)
This method was tested in GEOS4, but does not directly carry over to GEOS5
LandFlux Workshop, May 2007
MERRA
Modern Era Retrospective-analysis for Research and Applications
GEOS5 – NSIPP GCM Physics, Semi-Lagrangian dynamical core, GSI analysis
Catchment Land surface model(Koster et al)1979-2008 (Possibly longer)½°×⅔° spatial resolution (72 vertical levels)No Land Data Assimilation
LandFlux Workshop, May 2007
Incremental Analysis Update
IAU reduces Spin Down/Up features, allowing hourly output (and analysis tendencies in output)
LandFlux Workshop, May 2007
Atmospheric Water Budget
QIAU – Incremental Analysis Update of 3 Dimensional Water Vapor
Provides an estimate of error/uncertainty in the background modeling
Systematic component of QIAU can be related back to E, P (multiple regression, Schubert and Chang, 1996)
IAUQqVPEt
q
LandFlux Workshop, May 2007
MERRA Surface Diagnostics
Two Dimensional data will be at 1 hourly frequencies
Surface MeteorologyVertical IntegralsRadiation (sfc, TOA, clear sky, all sky)Fluxes and transfer coefficientsLand data (not including lakes/coasts)Lowest Model level forcing
LandFlux Workshop, May 2007
SGP Elk Falls – JUL 2004
GEOS5 Beta 9 Experiment
July 2004
LandFlux Workshop, May 2007
SGP Lamont - JUL2004
Underestimate of LE at Lamont (central facility)
LandFlux Workshop, May 2007
MODIS LST Day
LandFlux Workshop, May 2007
MODIS LST Night
LandFlux Workshop, May 2007
Station temperature comparison
2Degree experimentNCDC Summary of
the DayJuly 2001
LandFlux Workshop, May 2007
Global Precipitation
LandFlux Workshop, May 2007
Dec 2005 03ZDec 15-31 Average
LandFlux Workshop, May 2007
Dec 2005 06Z
LandFlux Workshop, May 2007
Dec 2005 09Z
LandFlux Workshop, May 2007
Dec 2005 12Z
LandFlux Workshop, May 2007
Dec 2005 15Z
LandFlux Workshop, May 2007
Dec 2005 18Z
LandFlux Workshop, May 2007
Dec 2005 21Z
LandFlux Workshop, May 2007
Dec 2005 00Z
LandFlux Workshop, May 2007
Dec 2005 03Z
LandFlux Workshop, May 2007
GEOS5 Hourly Evaporation
LandFlux Workshop, May 2007
Multi-Model Analysis for CEOP
Seven analysis data sets have been contributed to CEOPNCEP, ECPC, CPTEC, MSC, UKMO, JMA, BMRC and GMAO
We will pull together like variables form all the systems into a superensemble with mean and variance
We want to define the range of uncertainty in the physical aspects of the analyses, e.g. surface fluxes and radiation
LandFlux Workshop, May 2007
Ensemble Characteristics
CEOP EOP 3 and 4 (2003 and 2004)Monthly averages to start, then daily and
diurnal cycle Regrid to 1.25° × 1.25°For Monthly, provide the individual members
contribution to the ensemble as well (might be too much at daily frequencies)
LandFlux Workshop, May 2007
2D Surface Variables
Description Units BMRC CPTEC ECPCRII ECPCSFM GMAO JMA MSC NCEP UKMOSurface Pressure Pa × × × × × × × × ×Mean Sea Level Pressure Pa × × × × × ×Surface Air Temperature K × × × × × × × × ×Surface Air Moisture kg kg-1 × × × × × × × ×Surface Eastward Wind m s-1 × × × × × × × ×Surface Northward Wind m s-1 × × × × × × × ×Precipitation kg m-2 s-1 × × × × × × × × ×Convective Precipitation kg m-2 s-1 × × ×Surface Runoff kg m-2 × × × × × ×Liquid equivalent snow depth kg m-2 × × × × × ×Latent Heat Flux W m-2 × × × × × × × ×Sensible Heat Flux W m-2 × × × × × × × ×Surface Incoming Shortwave W m-2 × × × × × × × × ×Surface Incoming Longwave W m-2 × × × × × × × × ×Surface Reflected Shortwave W m-2 × × × × × × × × ×Surface Outgoing Longwave W m-2 × × × × × × × × ×Surface Skin Temperature W m-2 × × × × × ×TOA Longwave Outgoing W m-2 × × × × × × × ×TOA Shortwave Incoming W m-2 × × × × × ×TOA Shortwave Outgoing W m-2 × × × × ×Total Cloud Cover (0-1) × × × × × × × × ×Total Column Water Vapor kg m-2 × × × × × × ×Total Column Condensed Water kg m-2 × × × ×
Also, H, Q, T, U, V at 850, 700, 500, 300 and 200 mb
LandFlux Workshop, May 2007
Zonal Precipitation
JJA(land only)
LandFlux Workshop, May 2007
Zonal Latent Heat
JJA(land only)
JJA(GSSTF obs. only)
JJA(land only)
JJA(GSSTF obs. only)
LandFlux Workshop, May 2007
Bondville LH Time Series
LandFlux Workshop, May 2007
Bondville SH Time Series
LandFlux Workshop, May 2007
Precipitation Anomalies
LandFlux Workshop, May 2007
Multi-model Analysis Summary
7 data sets downloaded and being ensembled in version 1 (GMAO and BMRC near to providing data)
White paper describing the ensemble methods and decisions available for comment
Could provide a sense of the model variability in surface fluxes