Assimilating Earth System Observations at NASA: MERRA

and BeyondSiegfried Schubert, Michael Bosilovich, Michele Rienecker, Max Suarez,

Ron Gelaro, Randy Koster, Julio Bacmeister, Ricardo Todling, Larry Takacs, Emily Liu, Gi-Kong Kim, Man-Li Wu, Phil Pegion, Myong-In Lee, Junye Chen, Steve Bloom, Rolf Reichle, Steven Pawson, Ivanka

Stajner, Arlindo da Silva, Christian Keppenne, Watson Gregg

and many others in NASA’s Global Modeling and Assimilation Office

Presentation at the 3rd WCRP Conference on Reanalysis Tokyo, Japan

28 January - 01 Feb, 2008

1

Overview

• MERRA– The GEOS-5 DAS and observations– Some early results

• Beyond MERRA– Building the components for an

Integrated Earth System Analysis Capability

2

AGCMFinite-volume dynamical core (S.J. Lin)Moist physics (J. Bacmeister, S. Moorthi and M. Suarez)Physics integrated under the Earth System Modeling Framework (ESMF)Generalized vertical coord to 0.01 hPaCatchment land surface model (R. Koster)Prescribed aerosols (P. Colarco)Interactive ozonePrescribed SST, sea-ice

AnalysisGrid Point Statistical Interpolation (GSI from NCEP)Direct assimilation of satellite radiance data using

JCSDA Community Radiative Transfer Model (CRTM)

Variational bias correction for radiances

AssimilationApply Incremental Analysis

Increments (IAU) to reduce shock of data insertion (Bloom et al.)

IAU gradually forces the model integration throughout the 6 hour analysis period

GEOS-5 Atmospheric DAS for MERRA(Supported by NASA MAP Program)

∂qn

∂t⎛

⎝ ⎜

⎞

⎠ ⎟

total

= dynamics (adiabatic ) + physics (diabatic ) + Δq

Model predicted change Correction from DASTotal “observed change”

Analysis

Background (model forecast)Raw analysis (from GSI)

Assimilated analysis(Application of IAU)

03Z 06Z 09Z 12Z 18Z15Z 21Z 00Z 03Z

Initial States for CorrectorAnalysis Tendencies for CorrectorCorrector Segment (1- and 3-hrly products)

3

MERRA Production

2-year spin up at 2-degree resolution1-year spin up at ½ degreeProduct Streams begin: Jan 1 – 1979, 1989 and 1998

Years inStream

MERRA 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08Stream 1 10Stream 2 10Stream 3 9ROSB 21G5-AMIP 26EOS

Spinup years Reduced Observing System Baseline (ROSB)

• Preview/Validation runs:• Jan, Apr, Jul, Oct 2004• July-August 1987• Jan, Jul 2001• Jul 2006

• 2 degree (scout) runs ⇒ preliminary look at data and spin-up of satellite bias estimates.

1010112230

4

Years inStream

MERRA 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08Stream 1 10Stream 2 10Stream 3 9ROSB 21G5-AMIP 26EOS

NovNOAA-18

EOS AquaOct

F08

F15

SSM/IJul DecF10

NovF11

Dec

F13

MayF14

May

Dec Aug

Dec Dec

Apr Jul

Apr Jun

Jul

GOES-08

GOES-10

GOES-12

TIROS-NDec Feb

Jul Apr OctNovNOAA-6

FebSep NOAA-7

May Jun Jul OctNOAA-8

Jan NovNOAA-9

NOAA-10Dec Sep

Nov Jan Sep Sep NOAA-11

JunSep NOAA-12

Satellite Radiance Data Streams

JanNOAA-14

SepNOAA-15NovNOAA-16

JulNOAA-17

Dec

TOVS

ATOVS

EOS Aqua

GOESSounders

5

Satellite Data TOVS (TIROS N, N-6, N-7, N-8 )

1978/10/30 Š 1985/01/01 NCAR

(A)TOVS (N-9; N-10 ; N-11; N-12 )

1985/01/01 - 1997/07/14 NOAA/NESDIS & NCAR

ATOVS (N-14; N-15; N-16; N-18; N-18)

1995/01/19 - present NOAA/NESDIS

EOS/Aqua 2002/10 - present NOAA/NESDIS SSM/I V6 (F08, F10, F11, F13, F14, F15)

1987/7 - present RSS

GOES sounder TB 2001/01 - present NOAA/NCEP SBUV2 ozone (Version 8 retrievals)

1978/10 - present NASA/GSFC/Code 613.3

DATA SOURCE/TYPE PERIOD DATA SUPPLIER Conventional Data Radiosondes 1970 - present NOAA/NCEP PIBAL winds 1970 - present NOAA/NCEP Wind profiles 1992/5/14 - present UCAR CDAS Conventional, ASDAR, and MDCRS aircraft reports 1970 - present NOAA/NCEP

Dropsondes 1970 - present NOAA/NCEP PAOB 1978 - present NCEP CDAS GMS, METEOSAT, cloud drift IR and visible winds

1977 Š present NOAA/NCEP

GOES cloud drift winds 1997 Š present NOAA/NCEP EOS/Terra/MODIS winds 2002/7/01 - present NOAA/NCEP EOS/Aqua/MODIS winds 2003/9/01 - present NOAA/NCEP Surface land observations 1970 - present NOAA/NCEP Surface ship and buoy observations

1977 - present NOAA/NCEP

SSM/I rain rate 1987/7 - present NASA/GSFC SSM/I V6 wind speed 1987/7 - present RSS TMI rain rate 1997/12 - present NASA/GSFC QuikSCAT surface winds 1999/7 - present JPL ERS-1 surface winds 1991/8/5 Š 1996/5/21 CERSAT ERS-2 surface winds 1996/3/19 Š 2001/1/17 CERSAT

A special thanks to Jack Woollen for help with the conventional data streams and Leo Haimberger for the radiosonde corrections!!!!

6

State Variables

7

Zonal Mean u-windJan 2004

NCEP OPS EC OPS JRA-25

GEOS-5

Other

Δ

8

GEOS5 TPW Jan 2004

SSMI TPW Jul 2004

GEOS5 TPW Jul 2004

SSMI TPW Jan 2004

Wentz Retrievals, Version 6

9

TPW - SSM/IJul 2004GEOS-5

10

Water Vapor Budgetfor Jan 2004

Water Vapor Budgetfor Jan 2004 dynamicsdynamics condens+re-evapcondens+re-evap

sfc evaporationsfc evaporation analysisanalysis

sumsum residualresidual

residual =

(qend - qbegin) - sum

sum =

dynamics + (condensation + re-evaporation) + surface evaporation + analysis

mm/day

11

Precipitation

12

Global NCEP R2

JRA25

� MERRA validation and spin-up runs

ERA40

NCEP R1

Area Averaged Precipitation (mm/day)

GPCP

CMAPObs:

13

Precipitation (mm/day)January 2004 July 2004

GEOS-5 GEOS-5

GPCPGPCP

14

Precipitation c.f. GPCP (mm/day)July 2004

15

2004 Tropical Precipitation

16

Mississippi River Basin Daily Prec

17

03Z 02 January 2004

mm/day

Precipitation

MERRA CMORPH

Thanks to Matt Sapiano

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mm/day

3 hourly Precipitation - January 2004

MERRA CMORPH

19

Clouds and Radiation

20

21

MERRA cloud liquid water path*, compares well with SSMI estimates

January 2004

*Comparison with observations is complicated. SSMI LWP contains contributions from convective and precipitating liquid. “True”, i.e., radiatively active, model LWP (tql) does not contain convective (or precipitating) condensate. The convective contribution (qccu) to LWP can be estimated from MERRA output

22

Jul 06

Jul 04

Jul 04EC OPS

qLT

CLOUDSATCloud Tops

Marine Stratus DeckOff Peru

Marine Stratus DeckOff Peru

23

Regional Climate

24

GEOS5GEOS5

JRAJRA

NCEP R1NCEP R1

GPCPGPCP

EC-OPSEC-OPS

CMAPCMAP

GEOS5GEOS5

JRAJRA

NCEP R1NCEP R1

EC-OPSEC-OPS

Monthly Mean Precipitation over India July 2004 (mm/day)

Difference from GPCP

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Latitude-time Cross Section of Precipitation over India 2004 (72.5E-80E)

GPCP(Pentad)

TRMM (daily mean)

JRA(daily mean)

GEOS5(daily mean)

GEOS5(daily mean)

latit

ude

latit

ude

latit

ude

latit

ude

26

GEOS5GEOS5

JRAJRA

NCEP R1NCEP R1

GPCPGPCP

EC-OPSEC-OPS

CMAPCMAP

GEOS5GEOS5

JRAJRA

NCEP R1NCEP R1

EC-OPSEC-OPS

Monthly Mean Precipitation over Americas July 2004 (mm/day)

Difference from GPCP

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Precipitation (mm/d) and 925mb wind

NARR

GEOS-5

Seasonal evolution of North American monsoon (2004)

GEOS-5 reproduces the typical structure of the monsoon rainband. Seasonal march of the rainband is reasonable, with a peak in July.

Maximum rainfall region is located reasonably well in the windward slope of the mountains (the Sierra Madre Occidental).

Southwesterly flows in the Gulf of California and in the upslope of the mountains seem to be benefit from the high-resolution (1/2-degree) data assimilation.

Shading: precipitation rate (mm/d), Arrows: 925 mb windsContours: surface elevation

28

Amplitude of Precipitation Diurnal Cycle (24-h harmonic)

mm/d

Larger diurnal variability over continents than oceans

GEOS-5 tends to overestimate the amplitude over continents and underestimate over oceans

29

0-6Z 6-12Z 12-18Z 18-0Z

GEOS-5GEOS-5

JRAJRA

NCEP R1NCEP R1

NCEP R2NCEP R2

EC-OPSEC-OPS

TRMM

Diurnal variation in precipitation over the United States for July 2004 (mm/day). The July mean is removed.

TRMM

30

Vertical Structure of LLJ: Jul/Aug 2004 v-wind at 35°N

NARR

GEOS-5

31

MERRA FILE COLLECTIONS

• MERRA products are organized into 24 collections in HDF

• Data are produced on three horizontal grids:• Native ----------- (1/2 by 2/3 w/ FV conventions)• Reduced ------- (1 1/4 by 1 1/4 Dateline-edge, Pole-edge)• Reduced FV -- (1 by 1¼ w/ FV conventions)

• In the vertical, 3-D data are at:• 72 model layers• 42 pressure levels

• Temporal resolution:• 3D products are 3-hourly• 2D products are hourly and at native resolution

• Total online collections ~150TB

• Distributed through a modeling data portal at the Goddard DAAC(including GDS, ftp )

32

Summary

• MERRA improves upon many features of existing reanalyses

• Biases generally smaller than climate signals

• Precipitation issues remain: trends; diurnal cycle, summer land

• Comprehensive output suite

• Spin-ups completed and MERRA processing has started

• Expect to complete processing by mid-2009

Next Steps

Developing Components of Future Integrated Earth System

Analysis, with consistent analyses across all

components

GMAO Data Assimilation Systems

Atmosphere Constituents Aerosols

Land Surface Ocean Biology Physical Ocean

Assimilation of AMSRAssimilation of AMSR--E soil moisture retrievalsE soil moisture retrievals

Assimilation of TOPEX/Jason Altimeter DataAssimilation of TOPEX/Jason Altimeter Data

Assimilation of AURA/MLS and OMI OzoneAssimilation of AURA/MLS and OMI OzoneJan 04 Precipitation inJan 04 Precipitation in MERRA MERRA Aerosol Transport Aerosol Transport

35

Soil moisture [m3/m3]

Land data assimilation at the NASA GMAOLand data assimilation at the NASA GMAO

Surface soil moisture (SMMR, TRMM, AMSR-E, SMOS, SMAP)

Snow water equivalent (SWE) and snow cover

(AMSR-E, SSM/I; MODIS)

Ensemble-based land data assimilation system

Land surface data products (incl. root zone soil moisture, evaporation)

Land surface temperature (MODIS,

AVHRR,GOES,… ”ISCCP”)

260 280 300

Snow cover fraction (MODIS)

36

Ocean data assimilationOcean data assimilation in the GMAOin the GMAO

Temperature and salinity profiles from Argo floats

Surface chlorophyll(CZCS, SeaWiFS, MODIS)

Ensemble-based ocean data assimilation system

Ocean state estimates for climate analysis and for short-term climate forecasts

In situ temperature profiles (TAO/PIRATA moorings, XBTs)

Sea Level anomalies (TOPEX/JASON)

SST (AMSR-E; MODIS)

37

AtmosphereMeteorological analysesChemistry constituents: ozone, coupled with meteorologyChemistry constituents: CO, CO2 NOx under developmentChemistry constituents: Aerosol Transport, with source distributions from

satelliteGEOS-5 AGCM, currently 3Dvar, 4Dvar in test phase

Land SurfaceSoil moisture, surface temperature and snowCatchment LSM with EnKF

OceanRetrospective Ocean analyses for seasonal forecastsMOM4: MvOI, EnKF Assimilation in the CGCM coupled to atmospheric

analysisOcean color analyses: ocean time series, removing cross-satellite biases

AtmosphereMeteorological analysesChemistry constituents: ozone, coupled with meteorologyChemistry constituents: CO, CO2 NOx under developmentChemistry constituents: Aerosol Transport, with source distributions from

satelliteGEOS-5 AGCM, currently 3Dvar, 4Dvar in test phase

Land SurfaceSoil moisture, surface temperature and snowCatchment LSM with EnKF

OceanRetrospective Ocean analyses for seasonal forecastsMOM4: MvOI, EnKF Assimilation in the CGCM coupled to atmospheric

analysisOcean color analyses: ocean time series, removing cross-satellite biases

GMAO Assimilation System(s)