HIRDLS Ozone V003 (v2.04.09) Characteristics B. Nardi, C. Randall, V.L. Harvey & HIRDLS Team HIRDLS Science Meeting Boulder, Jan 30, 2008.

Slides:



Advertisements
Similar presentations
REFERENCES Alexander et al (2008): Global Estimates of Gravity Wave Momentum Flux from HIRDLS Observations. JGR 113 D15S18 Ern et al (2004): Absolute Values.
Advertisements

SBUV/2 Observations of Atmospheric Response to Solar Variations Matthew DeLand Science Systems and Applications, Inc. (SSAI) Background -SBUV/2 instruments.
SCILOV-10 Validation of SCIAMACHY limb operational NO 2 product F. Azam, K. Weigel, Ralf Bauer, A. Rozanov, M. Weber, H. Bovensmann and J. P. Burrows ESA/ESRIN,
SCILOV-10 Validation of SCIAMACHY limb operational BrO product F. Azam, K. Weigel, A. Rozanov, M. Weber, H. Bovensmann and J. P. Burrows ESA/ESRIN, Frascati,
Variability in Ozone Profiles at TexAQS within the Context of an US Ozone Climatology Mohammed Ayoub 1, Mike Newchurch 1 2, Brian Vasel 3 Bryan Johnson.
Validation of Tropospheric Emission Spectrometer (TES) nadir stare ozone profiles using ozonesonde measurements during Arctic Research on the Composition.
Validation of Tropospheric Emission Spectrometer (TES) nadir stare ozone profiles using ozonesonde measurements during Arctic Research on the Composition.
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.
Microwindow Selection for the MIPAS Reduced Resolution Mode INTRODUCTION Microwindows are the small subsets of the complete MIPAS spectrum which are used.
Chiara Piccolo and Anu Dudhia Atmospheric, Oceanic and Planetary Physics, Department of Physics, Oxford University, Oxford, UK Predicted.
Comparisons of TES v002 Nadir Ozone with GEOS-Chem by Ray Nassar & Jennifer Logan Thanks to: Lin Zhang, Inna Megretskaia, Bob Yantosca, Phillipe LeSager,
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.
Is there a Summertime Middle East Ozone Maximum in the Upper Troposphere? Matthew Cooper, Randall Martin, Bastien Sauvage, OSIRIS Team, ACE Team GEOS-Chem.
1 Improved Sea Surface Temperature (SST) Analyses for Climate NOAA’s National Climatic Data Center Asheville, NC Thomas M. Smith Richard W. Reynolds Kenneth.
Assimilation of EOS-Aura Data in GEOS-5: Evaluation of ozone in the Upper Troposphere - Lower Stratosphere K. Wargan, S. Pawson, M. Olsen, J. Witte, A.
Variability of Tropical to Extra-tropical Transport in the Lower Stratosphere Mark Olsen UMBC/GSFC Anne Douglass, Paul Newman, and Eric Nash.
Predictions of Solar Wind Speed and IMF Polarity Using Near-Real-Time Solar Magnetic Field Updates C. “Nick” Arge University of Colorado/CIRES & NOAA/SEC.
CHEM Science Team March 2000 Cloud processes near the tropopause HIRDLS will measure cloud top altitude and aerosol concentrations: the limb view gives.
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.
Cloud algorithms and applications for TEMPO Joanna Joiner, Alexander Vasilkov, Nick Krotkov, Sergey Marchenko, Eun-Su Yang, Sunny Choi (NASA GSFC)
Y. J. ORSOLINI Norwegian Institute for Air Research – NILU C. RANDALL LASP, University of Colorado, Boulder, USA G. MANNEY NASA Jet Propulsion.
Using GPS data to study the tropical tropopause Bill Randel National Center for Atmospheric Research Boulder, Colorado “You can observe a lot by just watching”
Irion et al., May 3, 2005 Page 1 Ozone validation for AIRS V4 Fredrick W. Irion, Michael R. Gunson Jet Propulsion Laboratory California Institute of Technology.
HIRDLS Validation Status (v ) B. Nardi, J. Gille & HIRDLS Team AURA, Science Meeting Pasadena, Oct 1-5, 2007.
Orbit Characteristics and View Angle Effects on the Global Cloud Field
HIRDLS Validation Overview
Page 1 Validation by Model Assimilation and/or Satellite Intercomparison - ESRIN 9–13 December 2002 Monitoring of near-real-time SCIAMACHY, MIPAS, and.
SCIAMACHY long-term validation M. Weber, S. Mieruch, A. Rozanov, C. von Savigny, W. Chehade, R. Bauer, and H. Bovensmann Institut für Umweltphysik, Universität.
Stratospheric temperature trends from combined SSU, SABER and MLS measurements And comparisons to WACCM Bill Randel, Anne Smith and Cheng-Zhi Zou NCAR.
Upper Tropospheric Ozone and Relative Humidity with respect to Ice: Seasonal Inter-comparison between GEOS CCM, MOZAIC and MLS Richard Damoah 1, H. B.
REFERENCES Alexander et al (2008): Global Estimates of Gravity Wave Momentum Flux from HIRDLS Observations. JGR 113 D15S18 Ern et al (2004): Absolute Values.
Assessment of SBUV Profile Algorithm Using High Vertical Resolution Sensors Assessment of SBUV Profile Algorithm Using High Vertical Resolution Sensors.
NASA Ocean Color Research Team Meeting, Silver Spring, Maryland 5-7 May 2014 II. Objectives Establish a high-quality long-term observational time series.
Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) - Middle Atmospheric Observations from the International Space Station Masato Shiotani.
ACE Comparisons Kaley Walker, Ashley Jones, Chris Boone, Chris Sioris, Felicia Kolonjari, Sean McLeod, Peter Bernath and Tom McElroy MOHAVE-2009 #2 Workshop.
1 Longitudinally-dependent ozone recovery in the Antarctic polar vortex revealed by satellite-onboard ILAS-II observation in 2003 Kaoru Sato Department.
NASA/GSFC Tropospheric Ozone Residual M. Schoeberl NASA/GSFC M. Schoeberl NASA/GSFC.
Measuring the Antarctic Ozone Hole with the new Ozone Mapping and Profiler Suite (OMPS) Natalya Kramarova, Paul Newman, Eric Nash, PK Bhartia, Richard.
First global view of the Extratropical Tropopause Transition Layer (ExTL) from the ACE-FTS Michaela I. Hegglin, University of Toronto, CA Chris Boone,
 We also investigated the vertical cross section of the vertical pressure velocity (dP/dt) across 70°W to 10°E averaged over 20°S-5°S from December to.
Evaluation of OMI total column ozone with four different algorithms SAO OE, NASA TOMS, KNMI OE/DOAS Juseon Bak 1, Jae H. Kim 1, Xiong Liu 2 1 Pusan National.
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.
AIRS science team meeting Camp Springs, February 2003 Holger Vömel University of Colorado and NOAA/CMDL Upper tropospheric humidity validation measurements.
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.
UTLS Chemical Structure, ExTL Summary of the talks –Data sets –Coordinates –Thickness of the ExTL (tracers based) Outstanding questions Discussion.
UTLS Workshop Boulder, Colorado October , 2009 UTLS Workshop Boulder, Colorado October , 2009 Characterizing the Seasonal Variation in Position.
Ozone PEATE 2/20/20161 OMPS LP Release 2 - Status Matt DeLand (for the PEATE team) SSAI 5 December 2013.
(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.
PRELIMINARY VALIDATION OF IAPP MOISTURE RETRIEVALS USING DOE ARM MEASUREMENTS Wayne Feltz, Thomas Achtor, Jun Li and Harold Woolf Cooperative Institute.
Effects of January 2010 stratospheric sudden warming in the low-latitude ionosphere L. Goncharenko, A. Coster, W. Rideout, MIT Haystack Observatory, USA.
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.
Upgrade from SGP V5.02 to V6.00: Conclusions from delta-validation of Diagnostic Data Set D. Hubert, A. Keppens, J. Granville, F. Hendrick, J.-C. Lambert.
Daily Tropospheric Ozone Residual from OMI-MLS
METO 637 Lesson 12.
Static Stability in the Global UTLS Observations of Long-term Mean Structure and Variability using GPS Radio Occultation Data Kevin M. Grise David W.
Mars Climate Sounder observations of wave structure in the North polar middle atmosphere of Mars during the summer season Paulina Wolkenberg1 and John.
J. Kar (UT), H. Bremer (UB), James R. Drummond (UT), F
R2971 Seq0100 Scn003 Hohenpeissenberg (48N, 11W)
Kris Wargan & Natalya A. Kramarova(*)
HIRS Observations of a Decline in High Clouds since 1995 February 2002
Variability of CO2 From Satellite Retrievals and Model Simulations
Evaluation of the MERRA-2 Assimilated Ozone Product
University of Colorado and NCAR START08/Pre HIPPO Workshop
Validation of TES version 2 ozone profiles
Intercomparison of tropospheric ozone measurements from TES and OMI
The Mars Pathfinder Atmospheric Structure Investigation/Meteorology (ASI/MET) Experiment by J. T. Schofield, J. R. Barnes, D. Crisp, R. M. Haberle, S.
Evaluation of IRI-2012 by comparison with JASON-1 TEC and incoherent scatter radar observations during the solar minimum period Eun-Young Ji,
Presentation transcript:

HIRDLS Ozone V003 (v ) Characteristics B. Nardi, C. Randall, V.L. Harvey & HIRDLS Team HIRDLS Science Meeting Boulder, Jan 30, 2008

1 km OZONESONDE Profile Comparisons 1 km Fine vertical scale features are resolved. At highly variable early-spring high latitude, effect of sampling different air-masses is accentuated: smallest scales do not match. High latitude Mid-latitude Low latitude

1 km MLO [19.5 o N, 156 o W] TMF [34.5 o N, 118 o W] OZONE Lidar Profile Comparisons 1 km

OZONE Lidar comparisons – Statistical Differences Mauna Loa Observatory [19.5 o N, 156 o W]Table Mountain Facility [34.5 o N, 118 o W] HIRDLS bias is generally low, 5-10%, except region ~ 5-25 hPa, 5-10% high bias.

OZONESONDE Comparisons – Statistical Differences

INTEX-B AROTAL Lidar Tight coincidence criteria (50km, 3hrs) shows low bias of <5%, except region hPa, where it’s <10%.

MLS v2.2 Zonal Mean 2006Jul 2006Oct 2006Feb2006May O 3 Percent Diff (%) Pressure (hPa) Pressure surfaces 1 hPa 3 hPa 51 hPa 100 hPa O 3 Percent Diff (%) 31 hPa 10 hPa Latitude

Anticyclone border HIRDLS v MLS v2.2 Polar Vortex border

Shown is the ozone standard deviation in different equivalent latitude and potential temperature bins. Results are in terms of percentage of mean VMR (black lines, 10%; white lines, 100%). This variability includes both the atmospheric variability and the random error of the HIRDLS data. The atmospheric variability is a minimum in summer, so the variability in high latitude summer is an upper bound of the HIRDLS precision. This is estimated at 2-8% between K (1-50 hPa). Ozone Estimated Precision (v ) December 22June 20 ~50 km, ~1 hPa -- ~15 km, ~120hPa --

SUMMARY 1.An estimate of the HIRDLS ozone precision is 5-10% between 1-50 hPa, based on the variability of HIRDLS measurements in regions of minimum geophysical variability 2.HIRDLS ozone is reliable between 1 hPa – 100 hPa at mid and high latitudes and between 1 – 50 hPa at low latitudes. 3.HIRDLS ozone accuracy is better than 10% between hPa (HIRDLS biased generally low). Some lidars and sondes indicate better accuracy: 5% between hPa, and between hPa, respectively. 4.A region of slightly positive 5% HIRDLS bias exists in a limited pressure range within hPa at nearly all latitudes; this is observed by comparisons with sondes (SHADOZ, WAVES), lidars (MLO, TMF) and satellites (ACE, MLS). 5.At low latitudes a high HIRDLS bias begins at ~50 hPa and increases rapidly with increasing pressure. This may be caused by spikes indirectly related to the presence of clouds. 6.Ozonesonde and lidar profile comparisons give a strong indication that HIRDLS is capable of detecting fine vertical structure in the ozone field on the order of 1 to 2 km. 7.HIRDLS is capable of resolving low ozone pocket features associated with anticyclones in the highly variable northern winter high latitudes.

Odds & Ends 1. At mid and high latitude HIRDLS ozone may be reliable to several hundred hPa in the absence of local cloud features. Systematic bias is unknown due to lack of statistics; 2. The lower boundary for usable tropical lower stratospheric ozone may be extended earthward (~68 hPa) by using the HIRDLS 12.1 micron extinction parameter to screen data. 3. Negative values of retrieved total error ("O3Precision") indicate a >50% contribution to the error from a priori sources, and thus a strong a priori influence in the result. This is typically not an issue with tropical lower stratospheric ozone. 4. Upcoming release has increased vertical range, spaceward of 1 hPa, and at the earthward limit as well. The low bias is somewhat lessened, especially in the lower stratosphere. 5. A priority for future ozone improvements is in diminishing the effects of clouds in the ozone retrieval and screening remaining cloud at low latitudes. HIRDLS Data Quality Document (Updated version to be posted very soon) 5.2 Ozone SpeciesOzone (O3) Data Field Name: O3 Useful Range: 1hPa – 100+ hPa Vertical Resolution: km Contact: Bruno Nardi Validation Paper: Nardi et al., Initial Validation of Ozone Measurements from the High Resolution Dynamic Limb Sounder (HIRDLS), in review, J. Geophys. Res., 2007

HIRDLS Data Quality Document 5.2 Ozone SpeciesOzone (O3) Data Field Name: O3 Useful Range: 1hPa – 100+ hPa Vertical Resolution: km Contact: Bruno Nardi Validation Paper: Nardi et al., Initial Validation of Ozone Measurements from the High Resolution Dynamic Limb Sounder (HIRDLS), in review, J. Geophys. Res., 2007

ACE-FTS (satellite solar occultation) ACE satellite comparisons since May 2006 show agreement to within ~10% between hPa in the NH (left) and between hPa in the SH (right), with HIRDLS biased generally low.

Figure A single orbit curtain plot comparison with MLS (Left: MLS; Middle: HIRDLS; Right: Difference) indicates HIRDLS is tends to be 10% lower earthward of ~30 hPa and is generally 10% high above ~1hPa and rapidly increases. HIRDLS ozone tends to be slightly lower than MLS, especially in the (night-time) descending node (RHS of panels).

Mean Difference 1 σ of Differences Individual Differences.... ….. Figure Ozone difference between 97 SHADOZ Network (low latitude) ozonesonde profiles and 1042 coincident HIRDLS profiles, in terms of mixing ratio, left and in terms of percent (of sonde values), right. Shown are the mean difference (solid blue), the standard deviation (dashed blue) and the individual differences (black dots) from which these are derived. SHADOZ Network

Figure Ozone difference between 73 MLO lidar profiles and the 659 coincident HIRDLS profiles, in terms of mixing ratio, left, and percent (of sonde values), right. MLO lidar

Figure ACE satellite solar occultation comparisons since May 2006 show agreement to within ~10% (bottom) between hPa in the Northern Hemisphere (left) and between hPa in the Southern Hemisphere (right), with HIRDLS biased generally low. ACE satellite

Figure Mercator representations of the ozone percent difference between HIRDLS and collocated MLS (v2.2) for 2006-July-15, at pressure levels, 1 hPa, 3 hPa, 10 hPa, 31 hPa, 51 hPa and 100 hPa, as indicated over each sub-plot. The ozone fields for this day are relatively quiescent. Clearly illustrated in this and the previous figure is that in the tropics earthward of ~60 hPa HIRDLS ozone tends to be very high with respect to MLS. This is probably related to the presence of high cloud-tops. MLS (v2.2)

Figure Comparisons of HIRDLS profiles with: ozonesonde profile from La Reunion Island (left), and with MLO lidar profiles (right).

Anticyclone border HIRDLS v MLS v2.2 Polar Vortex border Ozone

Figure An estimate of the HIRDLS ozone precision based on ozone variability in equivalent latitude bins. High precision estimates at winter-hemisphere high latitudes (LHS of top plots; RHS of bottom plots) may be indicative of the breakdown of the estimate rather than of an actual deterioration of HIRDLS precision.