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Global Modeling and Assimilation Office NASA Goddard Space Flight Center Phone : 301-614-5693

JCSDA Science Meeting College Park, MD 24 May 2011 Land assimilation activities in the NASA Global Modeling and Assimilation Office. Rolf Reichle, Gabrielle De Lannoy, Clara Draper, Bart Forman, Randy Koster, Qing Liu & Ally Toure. Global Modeling and Assimilation Office

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Global Modeling and Assimilation Office NASA Goddard Space Flight Center Phone : 301-614-5693

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  1. JCSDA Science Meeting College Park, MD 24 May 2011 Land assimilation activities in the NASA Global Modeling and Assimilation Office Rolf Reichle, Gabrielle De Lannoy, Clara Draper, Bart Forman, Randy Koster, Qing Liu & Ally Toure Global Modeling and Assimilation Office NASA Goddard Space Flight Center Phone: 301-614-5693 Email: Rolf.Reichle@nasa.gov

  2. Outline • Soil moisture • AMSR-E • ASCAT • SMOS & SMAP • Land surface temperature • ISCCP • LaRC • Snow and terrestrial water storage • MODIS • AMSR-E • GRACE

  3. NASA/GMAO re-analysis MERRA: Recently completed GEOS-5 re-analysis • 1979-present (updated w/ ~1 month latency), global, • Lat=0.5º, Lon=0.67º, 72 vertical levels • MERRA-Land: Enhanced product for land surface hydrological applications (Reichle et al., J. Clim., 2011) Gauge & satellite estimates Latest GEOS-5 model version

  4. Soil moisture validation (2002-2009) Skill (pentad anomaly R) vs. SCAN in situ observations • MERRA-Land has • better soil moisture anomalies than MERRA (attributed to GPCP corrections; not shown), and • is comparable to ERA-Interim. Improvements also in canopy interception, latent heat flux, and runoff (not shown). Anomalies≡ mean seasonal cycle removed Skill metric: Anom. time series corr. coeff. R Reichle et al. JCLIM (2011) submitted.

  5. Precipitation corrections v. retrieval assimilation Skill v. SCAN in situ obs Anomalies≡ mean seasonal cycle removed Skill metric: Anom. time series corr. coeff. R • Soil moisture skill increases with • precipitation corrections and • assimilation of surface soil moisture retrievals. Improved root zone soil moisture! See poster for details. Different precipitation forcing inputs Liu et al. JHM (2011) doi:10.1175/JHM-D-10-05000.

  6. Observation error estimation via Triple Co-location Estimated anomaly error std-dev of surface soil moisture (2007-10) • Obtain error std-dev from 3 independent estimates: • active MW • passive MW • modeling ASCAT (active MW) GEOS-5 (model) Active retrievals better in more vegetated areas. Passive retrievals better in more arid conditions. AMSR-E (passive MW) AMSR-E (passive MW) • LPRM retrievals better than NSIDC. • Work in progress! LPRM-X NSIDC Units: Normalized to local anom. soil moisture variability. small errors large errors

  7. SMOS and SMAP SMOS (ESA) SMAP (NASA) Launched Nov 2009 L-band passive 40 km resolution Launch ~2015 L-band active/passive 3-40 km resolution Use SMOS data to prepare for SMAP Level 4 Surface and Root Zone Soil Moistureproduct.

  8. SMOS and SMAP radiometers SMOS: Each location seen from multiple incidence angles during overpass; less accurate (σ = 4 K). SMAP: Each location seen once per overpass at 40°; more accurate (σ = 1.3 K). SMOS soil moisture retrievals based on Tb angular signature.

  9. Surface soil moisture: SMOS retrievals vs. GEOS-5 Mean (4/2010 – 4/2011) m3/m3 GEOS-5 soil moisture wetter than SMOS. SMOS Time series correlation coeff. GEOS-5 Reasonable agreement where expected.

  10. H-pol Tb at 42.5°: SMOS vs. GEOS-5 Mean (4/2010 – 4/2011) K GEOS-5 colder than SMOS. Similar for v-pol and other incidence angles. In progress: Calibrate parameters of L-band radiative transfer model. SMOS Time series correlation coeff. GEOS-5 Reasonable agreement where expected.

  11. Outline • Soil moisture • AMSR-E • ASCAT • SMOS & SMAP • Land surface temperature • ISCCP • LaRC • Snow and terrestrial water storage • MODIS • AMSR-E • GRACE

  12. Land surface temperature (LST) assimilation Validate against in situ observations RMSE of LST [K] Assimilate ISCCP LST retrievals into off-line land models LST estimates from model runs without data assimilation are comparable to each other and superior to ISCCP retrievals. Assimilation of ISCCP observations provides modest, yet statistically significant RMSE improvements (up to 0.7 K). The impact on flux estimates is small (not shown). Assimilation: s0: Without a priori scaling. b0, b8: Without and with dynamic bias correction. ISCCP = International Satellite Cloud Climatology Project Reichle et al. JHM (2010) doi:10.1175/2010JHM1262.1

  13. Evaluation of near-real time Tskin from NASA/LaRC Tskin bias [21z] JFM 2011 GEOS-5 – LaRC 1 Implement afore-mentioned Tskin assimilation method for near-real time, global, geostationary LaRC retrievals (Minnis et al.).

  14. Outline • Soil moisture • AMSR-E • ASCAT • SMOS & SMAP • Land surface temperature • ISCCP • LaRC • Snow and terrestrial water storage • MODIS • AMSR-E • GRACE

  15. Assimilation of MODIS and AMSR-E snow observations Noah land surface model (1 km resolution) 100 km X 75 km domain in northern Colorado AMSR-E MODIS • Multi-scale assimilation of • AMSR-E snow water equivalent (SWE) and • MODIS snow cover fraction (SCF). Validation against in situ obs from COOP (Δ) and Snotel (▪) sites for 2002-2010.

  16. Assimilation of MODIS snow cover fraction (SCF) MODIS Noah SCF assim. 3 Nov 09 25 Dec 09 28 Jan 10 14 Feb 10 25 Mar 10 10 Apr 10 … except during melt season. MODIS SCF successfully adds missing snow, MODIS SCF also improves timing of onset of snow season (not shown). De Lannoy et al. WRR (2011) submitted.

  17. Assimilation of AMSR-E snow water equivalent (SWE) SWE anomalies (40.38N, 106.66W) Assimilation of AMSR-E SWE retrievals did not help. De Lannoy et al. WRR (2011) submitted. cm AMSR-E MERRA SWE 1 Mar 2004 • AMSR-E SWE retrievals and MERRA differ a lot. • Working on intermediate approach betw. retrieval and full radiance assim.

  18. Assimilation of GRACE Terrestrial Water Storage (TWS) Assimilate GRACE TWS (2002-2009) for the Mackenzie river basin. RMSD [mm]: Snow water equivalent • Validate vs. • CMC snow product • GRDC runoff obs. Not shown: Trend issues w/ post-glacial rebound. Assimilation increments Assimilation reduces RMSD Subsurface water SWE RMSD [mm/d]: Runoff Forman et al. (2011) in preparation.

  19. Summary and outlook • Projects underway for soil moisture, LST, snow, and TWS assimilation from various sensors. • Generally (but not always!) assimilation improves estimates of land surface fields. Encountered • expected problems for AMSR-E SWE and • unexpected problems for GRACE. • Include land assimilation in GEOS-5/DAS, focus on LST and soil moisture assimilation. • Continue preparations for SMAP Level 4 soil moisture product, incl. calibration of L-band radiative transfer model.

  20. Thanks for listening! Questions?

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