Impact of OMI data on assimilated ozone Kris Wargan, I. Stajner, M. Sienkiewicz, S. Pawson, L. Froidevaux, N. Livesey, and P. K. Bhartia   Data and approach   Impact of OMI data on assimilated tropospheric ozone   Impact on forecast skill Plan of talk Goddard Space Flight Center GLOBAL MODELING AND ASSIMILATION OFFICE

Assimilation of Aura ozone data at NASA’s GMAO MODEL   transport within a general circulation model constrained by meteorological analyses   parameterizations for stratospheric photochemistry and heterogeneous ozone loss   a parameterization of the tropospheric chemistry DATA   The Microwave Limb Sounder (MLS): ozone profiles:   20 levels 216 – 0.14 hPa   ~ 3,500 profiles a day, near global coverage   Ozone Monitoring Instrument (OMI): US retrieved ozone total column   Data averaged onto a 2°× 2.5° grid   Reflectivity < 15%

Forecast field from model Analyzed field GENERAL CIRCULATION MODEL Assimilation of Aura ozone at NASA’s GMAO OMI and MLS Observations STATISTICAL ANALYSIS Observation Minus Forecast (O-F)

Two experiments are compared:   Control: ozone is transported within the GCM but no ozone data are assimilated   OMI and MLS data are assimilated In the assimilation the stratosphere is constrained by both, MLS profiles and OMI total column observations. Below 215 hPa the only data constraints come from OMI hence impacts of OMI on the tropospheric ozone are expected Approach

Impact of OMI data on tropospheric ozone column in the Tropics Monthly mean of OMI Observation minus forecast (O-F) residuals, October 2005 Monthly mean difference: Tropospheric column from assimilation minus model [DU] [DU] Analyzed tropospheric O responds to OMI O-Fs Analyzed tropospheric O 3 responds to OMI O-Fs

Mean tropospheric O3 in 2005 SHADOZ Sondes ModelAssimilation  The model underestimates ozone column in the tropics   Assimilation increases the ozone column Impact of OMI data on tropospheric ozone column in the Tropics  Tropopause computed using sonde temperature profiles  O3 integrated from surface to tropopause

Mean tropospheric O3 in 2005 SHADOZ Sondes ModelAssimilation   The model underestimates ozone column in the tropics   Assimilation increases the ozone column leading to   Better agreement with sondes over the Atlantic   Overestimation over the Pacific   Note zonally symmetric climatology assumed in the OMI retrieval algorithm Impact of OMI data on tropospheric ozone column in the Tropics Note: the Samoa sondes may be 7-9% low compared to Dobson measurements (S. Oltmans, personal communication)

ModelAssimilation  The underestimates ozone column in the tropics  The model underestimates ozone column in the tropics  Assimilation brings it up leading to  Better agreement with sondes over the Atlantic  Overestimation over the Pacific  Note zonally symmetric climatology assumed in the OMI retrieval algorithm Impact of OMI data on tropospheric ozone column in the Tropics Root mean square difference with sondes

OMI Total Ozone larger by up to 10 DU than model prediction over the Amazon in November 2004 and October Zeng et al (Submitted) show evidence that fire frequency in the Amazon in 2005 was twice the average over the previous 7 years following an intense drought. The model uses climatological estimates of biomass burning [DU] Mean OMI O-F Nov 2004 Mean OMI O-F Oct 2005 The Amazon region

Impact of assimilated ozone on NWP In GEOS-5 the analyzed ozone is used in the forward model for assimilation of infrared radiances and in the radiative heating rate computations We compare 3 experiments:   SBUV (version 8) ozone assimilated   MLS profiles assimilated   MLS and OMI assimilated

Impact of assimilated ozone on NWP Anomaly correlation SBUVMLS MLS+OMI 500-mb Heights, 80S – 20S, October 2004   Forecast skill is calculated as timeseries of anomaly correlations between forecasts and verifying analyses   The monthly mean for October 2004 SH is shown here   Impact of OMI data is seen for 7+ day forecasts

Impact of assimilated ozone on NWP Forecast initialized on Oct 5th Forecast initialized on Oct 7th SBUVMLS MLS+OMI 500-mb Heights, 80S – 20S  Two special cases, one showing poor the other good forecast skills past day 5  Both indicate positive impact of OMI and MLS data

Summary  Retrieved ozone data from OMI and MLS were assimilated  Examples of impacts of assimilation on tropospheric ozone were shown:  Increase of (underestimated) tropical ozone column  Increase over regions of intense biomass burning  It was demonstrated that assimilation of OMI and MLS ozone can improve forecast of 500 mb height fields.

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Impact of assimilated ozone on NWPSBUV MLSMLS+OMI 500-mb Heights, 80S – 20S 240h forecast error