Land Surface Fluxes in Coupled Land/Atmosphere Analysis Systems Michael Bosilovich, NASA GSFC And Collaborators

LandFlux Workshop, May 2007 Main Discussion Points Surface Temperature Assimilation Coupled Analysis of Skin Temperature Validation: Station Obs, CEOP Fluxes MERRA Surface data products, usefulness for LandFlux Multi-Model Analysis for CEOP (MAC) 7 operational analyses or reanalyses Goal: 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 Cycle Include Incremental forcing at every time step Bosilovich et al. (2007, JMSJ)

LandFlux Workshop, May m Air Temp, Mean Bias July 2001

LandFlux Workshop, May m Diurnal Temp Range July 2001

LandFlux Workshop, May 2007 LBA Fluxes: CEOP EOP1 CTL Rondonia CTL Manaus EXP2 Rondonia EXP2 Manaus

LandFlux Workshop, May 2007 BALTEX Fluxes: CEOP EOP1 CTL Lindenberg CTL Cabauw EXP2 Lindenberg EXP2 Cabauw

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) (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)

LandFlux Workshop, May 2007 MERRA Surface Diagnostics Two Dimensional data will be at 1 hourly frequencies Surface Meteorology Vertical Integrals Radiation (sfc, TOA, clear sky, all sky) Fluxes and transfer coefficients Land 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 experiment NCDC Summary of the Day July 2001

LandFlux Workshop, May 2007 Global Precipitation

LandFlux Workshop, May 2007 Dec Z Dec Average

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LandFlux Workshop, May 2007 Dec Z

LandFlux Workshop, May 2007 GEOS5 Hourly Evaporation

LandFlux Workshop, May 2007 Multi-Model Analysis for CEOP Seven analysis data sets have been contributed to CEOP NCEP, 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 D Surface Variables Also, H, Q, T, U, V at 850, 700, 500, 300 and 200 mb

LandFlux Workshop, May 2007 Zonal Precipitation

LandFlux Workshop, May 2007 Zonal Latent Heat

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