Upper Tropospheric Ozone and Relative Humidity with respect to Ice: Seasonal Inter-comparison between GEOS CCM, MOZAIC and MLS Richard Damoah 1, H. B.

Slides:



Advertisements
Similar presentations
Imposed ozone calculations Qualitatively same behaviour in all models (which qualitiatively agrees with the observations). Significant quantitative differences.
Advertisements

Update on the Regional Workshop and overview of Japanese Research Projects “The One Atmosphere” IGAC-SPARC Joint Workshop in Kyoto, October 25 and 26 First.
Aircraft GC 2006 ems GC Streets ems East Asian contrib Lightning contrib Aircraft GC 2006 ems GC Streets ems No Asian No Lightning Long-range transport.
Interpreting MLS Observations of the Variabilities of Tropical Upper Tropospheric O 3 and CO Chenxia Cai, Qinbin Li, Nathaniel Livesey and Jonathan Jiang.
Assimilation of TES O 3 data in GEOS-Chem Mark Parrington, Dylan Jones, Dave MacKenzie University of Toronto Kevin Bowman Jet Propulsion Laboratory California.
CO 2 in the middle troposphere Chang-Yu Ting 1, Mao-Chang Liang 1, Xun Jiang 2, and Yuk L. Yung 3 ¤ Abstract Measurements of CO 2 in the middle troposphere.
Remote Sensing of the Oceans and Atmosphere Tom Collow December 10, 2009.
Menglin Jin Department of Atmospheric & Oceanic Science University of Maryland, College park Observed Land Impacts on Clouds, Water Vapor, and Rainfall.
National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California Atmospheric Infrared Sounder.
Comparisons of TES v002 Nadir Ozone with GEOS-Chem by Ray Nassar & Jennifer Logan Thanks to: Lin Zhang, Inna Megretskaia, Bob Yantosca, Phillipe LeSager,
National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory Princeton, NJ Evolution of Stratospheric.
Attribution of Stratospheric Temperature Trends to Forcings A coupled chemistry-climate model (CCM) study Richard S. Stolarski NASA GSFC In collaboration.
Influence of the Brewer-Dobson Circulation on the Middle/Upper Tropospheric O 3 Abstract Lower Stratosphere Observations Models
(a)(b)(c) Simulation of upper troposphere CO 2 from two-dimensional and three-dimensional models Xun Jiang 1, Runlie Shia 2, Qinbin Li 1, Moustafa T Chahine.
Ability of GEO-CAPE to Detect Lightning NOx and Resulting Upper Tropospheric Ozone Enhancement Conclusions When NO emissions from lightning were included.
Herman G.J. Smit/FZJ-COST723-WG-I Overview Noordwijk March 2004 COST723-WG1- Working Group I: Data and Measurement Techniques Overview Herman G.J.
Sensitivity of Methane Lifetime to Sulfate Geoengineering: Results from the Geoengineering Model Intercomparison Project (GeoMIP) Giovanni Pitari V. Aquila,
Cloud algorithms and applications for TEMPO Joanna Joiner, Alexander Vasilkov, Nick Krotkov, Sergey Marchenko, Eun-Su Yang, Sunny Choi (NASA GSFC)
Intercomparison methods for satellite sensors: application to tropospheric ozone and CO measurements from Aura Daniel J. Jacob, Lin Zhang, Monika Kopacz.
El Niño-Southern Oscillation in Tropical Column Ozone and A 3.5-year signal in Mid-Latitude Column Ozone Jingqian Wang, 1* Steven Pawson, 2 Baijun Tian,
Interannual Variabilities of High Clouds Seen by AIRS and Comparison with CAM5 simulations Yuk Yung, Hui Su, Katie, Hazel et al.
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
Past and Future Changes in Southern Hemisphere Tropospheric Circulation and the Impact of Stratospheric Chemistry-Climate Coupling Collaborators: Steven.
Assessment of SBUV Profile Algorithm Using High Vertical Resolution Sensors Assessment of SBUV Profile Algorithm Using High Vertical Resolution Sensors.
The effect of pyro-convective fires on the global troposphere: comparison of TOMCAT modelled fields with observations from ICARTT Sarah Monks Outline:
HIRDLS Ozone V003 (v ) Characteristics B. Nardi, C. Randall, V.L. Harvey & HIRDLS Team HIRDLS Science Meeting Boulder, Jan 30, 2008.
HIRDLS – Oxford Open Science Meeting HIRDLS Observations of Cirrus Near the Tropopause Based upon: Spring 2008 AGU Joint Assembly Ft. Lauderdale, Florida.
The European Heat Wave of 2003: A Modeling Study Using the NSIPP-1 AGCM. Global Modeling and Assimilation Office, NASA/GSFC Philip Pegion (1), Siegfried.
PDFS of Upper Tropospheric Humidity Darryn Waugh, Ju-Mee Ryoo, Tak Igusa Johns Hopkins University.
A Long Term Data Record of the Ozone Vertical Distribution IN43B-1150 by Richard McPeters 1, Stacey Frith 2, and Val Soika 3 1) NASA GSFC
Status of the Development of a Tropospheric Ozone Product from OMI Measurements Jack Fishman 1, Jerald R. Ziemke 2,3, Sushil Chandra 2,3, Amy E. Wozniak.
The Influence of loss saturation effects on the assessment of polar ozone changes Derek M. Cunnold 1, Eun-Su Yang 1, Ross J. Salawitch 2, and Michael J.
Improved understanding of global tropospheric ozone integrating recent model developments Lu Hu With Daniel Jacob, Xiong Liu, Patrick.
1 Monitoring Tropospheric Ozone from Ozone Monitoring Instrument (OMI) Xiong Liu 1,2,3, Pawan K. Bhartia 3, Kelly Chance 2, Thomas P. Kurosu 2, Robert.
Climatic implications of changes in O 3 Loretta J. Mickley, Daniel J. Jacob Harvard University David Rind Goddard Institute for Space Studies How well.
UTLS Workshop Boulder, Colorado October , 2009 UTLS Workshop Boulder, Colorado October , 2009 Characterizing the Seasonal Variation in Position.
Critical Assessment of TOMS-derived Tropospheric Ozone: Comparisons with Other Measurements and Model Evaluation of Controlling Processes M. Newchurch.
This report presents analysis of CO measurements from satellites since 2000 until now. The main focus of the study is a comparison of different sensors.
Midlats: MOZAIC [40-60N, 0-75 W] 250 hPa layer Evaluation of upper tropospheric moisture in the GEOS5CCM and MERRA reanalyses and implications for contrail.
Monitoring Global Droughts from Space Zhong Liu 1,4, W.L. Teng 2,4, S. Kempler 4, H. Rui 3,4, G. Leptoukh 4, and E. Ocampo 3,4 1 George Mason University,
(a)(b)(c) Simulation of upper troposphere CO 2 from two-dimensional and three-dimensional models Xun Jiang 1, Runlie Shia 2, Qinbin Li 1, Moustafa T Chahine.
Identifying amplifying African waves from analysis of their temperature anomalies: how can the NAMMA aircraft, radiosonde and satellite data be merged.
SCIAMACHY CO validation. 7 April 2010 SCIAMACHY CO SRON 2 FTS paper - In total 19 surface stations that measure CO total columns based on Fourier.
NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS SURFACE PRESSURE MEASUREMENTS FROM THE ORBITING CARBON OBSERVATORY-2.
NASA, CGMS-43, May 2015 Coordination Group for Meteorological Satellites - CGMS Use of Satellite Observations in NASA Reanalyses: MERRA-2 and Future Plans.
A Study of Variability in Tropical Tropospheric Water Vapor Robert L. Herman 1, Robert F. Troy 2, Holger Voemel 3, Henry B. Selkirk 4, Susan S. Kulawik.
Figures from “The ECMWF Ensemble Prediction System”
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.
Yuqiang Zhang1, Owen R, Cooper2,3, J. Jason West1
SCSL SWAP/LYRA workshop
The impacts of dynamics and biomass burning on tropical tropospheric Ozone inferred from TES and GEOS-Chem model Junhua Liu
Stratosphere Issues in the CFSR
Retrieval of tropospheric NO2 from GOME
Seasonal Differences of UTLS Exchange Processes between Spring and Summer in the Subtropics and Polar Region Simone Tilmes, Laura Pan, Louisa Emmons, Hans.
Interannual Variations in Stratospheric Water Vapor
Lu Hu Global budget of tropospheric ozone: long-term trend and recent model advances Lu Hu With Loretta Mickley,
Multimodel Ensemble Reconstruction of Drought over the Continental U.S
Analysis of CO in the tropical troposphere using Aura satellite data and the GEOS-Chem model: insights into transport characteristics of the GEOS meteorological.
Evaluation of the MERRA-2 Assimilated Ozone Product
Intercomparison of tropospheric ozone measurements from TES and OMI –
The effect of tropical convection on the carbon monoxide distribution in the upper troposphere inferred from Aura Satellite data and GEOS-Chem model Junhua.
Pawan K. Bhartia NASA Goddard Space Flight Center
Harvard University and NASA/GFSC
Troposphere-to-Stratosphere Transport of VSLS
Multimodel Ensemble Reconstruction of Drought over the Continental U.S
Fig. 1 Area over which VIC simulated soil moisture has been spatially averaged. Blue shadded area represents contributing area above Sacramento.
Simulations of the transport of idealized short-lived tracers
Intercomparison of tropospheric ozone measurements from TES and OMI
Benchmarking of chemical mechanisms
Presentation transcript:

Upper Tropospheric Ozone and Relative Humidity with respect to Ice: Seasonal Inter-comparison between GEOS CCM, MOZAIC and MLS Richard Damoah 1, H. B. Selkirk 1, Q. Liang 1, M. Manyin 2, L. Oman 3, L. Ott 3, A. R. Douglass 3, S. Pawson 3, and R. Stolarski 4 1 Universities Space Research Association (GESTAR/NASA), Greenbelt MD 2 System Science and Applications, Inc. Lanham, MD 3 NASA Goddard Space Flight Center, Greenbelt, MD 4 Johns Hopkins University, Baltimore, MD Scatter plot of MLS ozone versus the model’s ozone at 147 hPa for the MLS and 150 hPa level for the model in northern mid- latitude (30N-60N). Similarly, the red shows the scatter for January while black shows that for July. Here the points are compact even at 600 ppbv. Overall, the model predicts higher ozone in both seasons compared with the MLS with July (black) showing a slight better agreement than January (red). Global distribution of MLS ozone climatology and GEOS CCM ozone output. The upper row show the MLS distribution at 147 hPa. The second row show that for the model at 150 hPa and the bottom row showing the absolute difference between them. The left column is for January and right July. There is fairly good agreement between the MLS and the model especially in January. The model over estimates the ozone of more than 300 ppbv at northern high latitudes. MOZAIC (upper row) and GEOS CCM (middle row) ozone at 250 hPa. The bottom row shows the absolute difference between the model and the observation. Left panel show January comparison while right panel show that for July. The model shows a reasonable agreement (+ and – 70 ppbv) with MOZAIC especially in January. At high northern latitudes in July the model over estimates the ozone up to about 200 ppbv. Model and MOZAIC relative humidity with respect to ice at 250 hPa. The model has been sampled to spatially coincide with MOZAIC locations. January and July distributions are shown in the left and right panels, respectively. Again the best agreement between the model and MOZIAC with respective to relative humidity ice is seen in January. The model shows over estimation at high latitudes up to about 50% with various patches of negative values within the region. MLS relative humidity ice (147 hPa) versus the model’s relative ice (150 hPa) in northern mid-latitude (30N-60N). Again MLS with the model show a compact distribution and close to the one to one line than shown in the MOZAIC versus the model above. MOZAIC AND MLS We have used 15 years of observational data set from the Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft (MOAZIC) to test the model’s predictability of upper tropospheric ozone and relative humidity with respect to ice. We also constructed 6 years seasonal climatology of ozone and relative humidity derived from the Microwave Limb Sounder (MLS) measurements for comparison with the model output. MODEL The Goddard Earth Observing System Chemistry Climate Model (GEOS CCM ) was used to simulate 16 years of ensemble runs in sequence using 2005 trace-gas emissions and historical SSTs. Simulations with (perturbed) and without (control) aircraft emissions were initiated. The perturbed run used AEDT 2006 aircraft emissions. For the purpose of this poster, we have compared the seasonal climatology of upper tropospheric ozone and relative humidity with respect to ice derived from the perturbed simulations, with observational data. Scatter plot of MOZAIC ozone versus the model’s ozone at 250 hPa level. Red shows the scatter for January while black shows that for July. In both seasons MOAZIC and the model show a compact distribution up to about 150 ppbv, and a distribution over wide region at values greater than 150 ppbv. MOZAIC relative humidity with respect to ice versus relative humidity ice predicted by the model at 250 hPa. Blue and black points show January and July distributions, respectively. The points show a spread over wide area. Relative humidity with respect to ice from MLS and the model. Left and right columns show January and July distributions, respectively. The upper row show the MLS RHI at147 hPa and middle row the model’s RHI at 150 hPa. The bottom row show the absolute difference between. Qualitatively, the model’s distribution agrees fairly well with the MLS distributions especially in January. The CCM predicts higher values in the tropics up to 60%. However, for July in the southern polar region the model underestimate the relative humidity ice more than 80% compared with the MLS. CONCLUSION We have compared a seasonal climatology of upper tropospheric ozone and relative humidity with respect to ice derived from 16 years of ensemble simulations with the Goddard Earth Observing System Chemistry Climate Model (GEOS CCM), 6 years of observations from the Aura’s Microwave Limb Sounder (MLS) and a 15-year data set from the Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft (MOAZIC) project. The model showed fairly good agreement with the observations especially in the January season. Difference between the model (over estimates) and MOZAIC ranges between +70 and -70 ppbv in January and +250 to - 70 ppbv in July for ozone. With MLS at 147 hPa level the difference is between and – 50 ppbv in January and between +300 and – 50 ppbv in July. The model over estimates the RHI up to 60% in the tropics, however, in parts of the Antarctic region the MLS over estimates the RHI more than 80%.