Relationships inferred from AIRS-CALIPSO synergy

Slides:



Advertisements
Similar presentations
Lidar observations of mixed-phase clouds Robin Hogan, Anthony Illingworth, Ewan OConnor & Mukunda Dev Behera University of Reading UK Overview Enhanced.
Advertisements

Robin Hogan, Richard Allan, Nicky Chalmers, Thorwald Stein, Julien Delanoë University of Reading How accurate are the radiative properties of ice clouds.
A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.
1 Met Office, UK 2 Japan Meteorological Agency 3 Bureau of Meteorology, Australia Assimilation of data from AIRS for improved numerical weather prediction.
1 An initial CALIPSO cloud climatology ISCCP Anniversary, July 2008, New York Dave Winker NASA LaRC.
Horizontal variability of water and its relationship to cloud fraction near the tropical tropopause Using aircraft observations of water vapor to improve.
1. The problem of mixed-phase clouds All models except DWD underestimate mid-level cloud –Some have separate “radiatively inactive” snow (ECMWF, DWD) –Met.
Atmospheric structure from lidar and radar Jens Bösenberg 1.Motivation 2.Layer structure 3.Water vapour profiling 4.Turbulence structure 5.Cloud profiling.
Surface Skin Temperatures Observed from IR and Microwave Satellite Measurements Catherine Prigent, CNRS, LERMA, Observatoire de Paris, France Filipe Aires,
Validating the moisture predictions of AMPS at McMurdo using ground- based GPS measurements of precipitable water Julien P. Nicolas 1, David H. Bromwich.
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.
Lidar algorithms to retrieve cloud distribution, phase and optical depth Y. Morille, M. Haeffelin, B. Cadet, V. Noel Institut Pierre Simon Laplace SYMPOSIUM.
1 Une description statistique multi-variable des nuages au dessus de l’océan tropical à partir des observations de jour de l’A-train en haute résolution.
Influence of ice supersaturation, temperature and dynamics on cirrus occurrence near the tropopause N. Lamquin (1), C.J. Stubenrauch (1), P.-H. Wang (2)
Applications and Limitations of Satellite Data Professor Ming-Dah Chou January 3, 2005 Department of Atmospheric Sciences National Taiwan University.
Diagnosing Climate Change from Satellite Sounding Measurements – From Filter Radiometers to Spectrometers William L. Smith Sr 1,2., Elisabeth Weisz 1,
The fear of the LORD is the beginning of wisdom 陳登舜 ATM NCU Group Meeting REFERENCE : Liu., H., J. Anderson, and Y.-H. Kuo, 2012: Improved analyses.
Operation of Backscatter Lidar at Buenos Aires (34.6 S / 58.5 W) for the Retrieval and Analysis the Atmospheric Parameters in Cirrus Clouds, Tropopause.
New Products from combined MODIS/AIRS Jun Li, Chian-Yi Liu, Allen Huang, Xuebao Wu, and Liam Gumley Cooperative Institute for Meteorological Satellite.
Introduction Invisible clouds in this study mean super-thin clouds which cannot be detected by MODIS but are classified as clouds by CALIPSO. These sub-visual.
LMD LMD Science Team CALIPSO – March M.Chiriaco, H.Chepfer, V.Noel, A.Delaval, M.Haeffelin Laboratoire de Météorologie Dynamique, IPSL, France P.Yang,
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
Optical properties Satellite observation ? T,H 2 O… From dust microphysical properties to dust hyperspectral infrared remote sensing Clémence Pierangelo.
LASE Measurements During IHOP Edward V. Browell, Syed Ismail, Richard A. Ferrare, Susan A Kooi, Anthony Notari, and Carolyn F. Butler NASA Langley Research.
Hyperspectral Infrared Alone Cloudy Sounding Algorithm Development Objective and Summary To prepare for the synergistic use of data from the high-temporal.
Verification Verification with SYNOP, TEMP, and GPS data P. Kaufmann, M. Arpagaus, MeteoSwiss P. Emiliani., E. Veccia., A. Galliani., UGM U. Pflüger, DWD.
Testing LW fingerprinting with simulated spectra using MERRA Seiji Kato 1, Fred G. Rose 2, Xu Liu 1, Martin Mlynczak 1, and Bruce A. Wielicki 1 1 NASA.
TEMIS user workshop, Frascati, 8-9 October 2007 TEMIS – VITO activities Felix Deutsch Koen De Ridder Jean Vankerkom VITO – Flemish Institute for Technological.
Retrieval of Methane Distributions from IASI
Yuying Zhang, Jim Boyle, and Steve Klein Program for Climate Model Diagnosis and Intercomparison Lawrence Livermore National Laboratory Jay Mace University.
Lagrangian Analysis of Tropical Cirrus and Upper-Tropospheric Humidity Z. JOHNNY LUO City College of New York, CUNY.
Radiative Impacts of Cirrus on the Properties of Marine Stratocumulus M. Christensen 1,2, G. Carrió 1, G. Stephens 2, W. Cotton 1 Department of Atmospheric.
Use of Solar Reflectance Hyperspectral Data for Cloud Base Retrieval Andrew Heidinger, NOAA/NESDIS/ORA Washington D.C, USA Outline " Physical basis for.
In situ observations of water vapor and cirrus IWC in the Pacific TTL during ATTREX Troy Thornberry, Drew Rollins, Ru-Shan Gao, David Fahey Paul Bui, Sarah.
Studying impacts of the Saharan Air Layer on hurricane development using WRF-Chem/EnKF Jianyu(Richard) Liang Yongsheng Chen 6th EnKF Workshop York University.
TOMS Ozone Retrieval Sensitivity to Assumption of Lambertian Cloud Surface Part 1. Scattering Phase Function Xiong Liu, 1 Mike Newchurch, 1,2 Robert Loughman.
How accurately we can infer isoprene emissions from HCHO column measurements made from space depends mainly on the retrieval errors and uncertainties in.
Daily observation of dust aerosols infrared optical depth and altitude from IASI and AIRS and comparison with other satellite instruments Christoforos.
ITSC-1227 February-5 March 2002 Use of advanced infrared sounders in cloudy conditions Nadia Fourrié and Florence Rabier Météo France Acknowledgement G.
Validation of Satellite-derived Clear-sky Atmospheric Temperature Inversions in the Arctic Yinghui Liu 1, Jeffrey R. Key 2, Axel Schweiger 3, Jennifer.
TOMS Ozone Retrieval Sensitivity to Assumption of Lambertian Cloud Surface Part 2. In-cloud Multiple Scattering Xiong Liu, 1 Mike Newchurch, 1,2 Robert.
UCLA Vector Radiative Transfer Models for Application to Satellite Data Assimilation K. N. Liou, S. C. Ou, Y. Takano and Q. Yue Department of Atmospheric.
Three-year analysis of S-HIS dual-regression retrievals using co-located AVAPS and CPL Measurements D. H. DeSlover, H. E. Revercomb, J. K. Taylor, F. Best,
UNIVERSITY OF BASILICATA CNR-IMAA (Consiglio Nazionale delle Ricerche Istituto di Metodologie per l’Analisi Ambientale) Tito Scalo (PZ) Analysis and interpretation.
NASA, CGMS-44, 7 June 2016 Coordination Group for Meteorological Satellites - CGMS LIMB CORRECTION OF POLAR- ORBITING IMAGERY FOR THE IMPROVED INTERPRETATION.
ECMWF The ECMWF Radiation Transfer schemes 1 Photon path distribution method originally developed by Fouquart and Bonnel (1980). [see lecture notes for.
A-Train Symposium, April 19-21, 2017, Pasadena, CA
Challenges associated with ice and large particles in the TTL
W. Smith, D. Spangenberg, S. Sun-Mack, P.Minnis
Aeolus in heterogeneous atmospheric conditions
Carbon monoxide from shortwave infrared measurements of TROPOMI: Algorithm, Product and Plans Jochen Landgraf, Ilse Aben, Otto Hasekamp, Tobias Borsdorff,
Seasonal variability of the tropical tropopause dehydration
Cloud Property Retrievals over the Arctic from the NASA A-Train Satellites Aqua, CloudSat and CALIPSO Douglas Spangenberg1, Patrick Minnis2, Michele L.
Winds in the Polar Regions from MODIS: Atmospheric Considerations
How well can we determine the tropopause
HIRS Observations of a Decline in High Clouds since 1995 February 2002
AVHRR operational cloud masks intercomparison
Han, J. , W. Wang, Y. C. Kwon, S. -Y. Hong, V. Tallapragada, and F
Dennis L. Hartmann and Kristin Larson
Dennis L. Hartmann and Kristin Larson
ECV definitions Mapping of ECV product with OSCAR variables
Item Taking into account radiosonde position in verification
Dorota Jarecka1 Wojciech W. Grabowski2 Hanna Pawlowska1
Inhomogeneous radiative properties of cirrus clouds
Cirrus Clouds near the mid-latitude tropopause
AIRS (Atmospheric Infrared Sounder) Level 1B data
Simulations of the transport of idealized short-lived tracers
GLAS Cloud Statistics and Their Implications for a Hybrid Mission
Can the increase of Polar Stratospheric Clouds explain the Antarctic Winter Tropospheric warming? Tom Lachlan-Cope (W. M. Connolley, J. Turner, H. Roscoe,
Presentation transcript:

Relationships inferred from AIRS-CALIPSO synergy Upper Tropospheric Humidity and Cirrus Clouds: Relationships Inferred by Combined AIRS and CALIPSO Data, Evaluation of ECMWF Forecasts and Influence of Vertical Resolution on Ice Supersaturation N. Lamquin (1), C. J. Stubenrauch (1), K. Gierens (2), J. Pelon (3) (1) C.N.R.S./ I.P.S.L. Laboratoire de Météorologie Dynamique, Ecole Polytechnique, France (2) Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany (3) C.N.R.S./I.P.S.L. Service d’Aéronomie, Paris, France qs integrated by steps of 1 hPa: Relationships inferred from AIRS-CALIPSO synergy Colocation: August 2006 – July 2007 Night, +60°/-60° latitude coverage Lamquin, Stubenrauch and Pelon., JGR 2008 ps calculated by Sonntag’s formulae (Sonntag, 1990): q determined by means of the mixing ratio in the AIRS layer: q = w / (1+w) RHice = q/qsat AIRS (Atmospheric Infrared Sounder) L2, version 5, NASA Temperature and water vapor vertical profiles, quality flags… (Susskind et al. 2003, 2006; Tobin et al. 2006) RHice calculation in 50 to 100 hPa – thick pressure layers CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) Data from NASA Langley Research Center Atmospheric Science Data Center archived at ICARE and Climserv (IPSL) High cloud top and base pressure: sub-visible cirrus, thin and thick cirrus number of cloud layers, tropopause… Estimation of highest cloud optical depth, colocations with retrieved AIRS cloud properties Stubenrauch et al., JGR 2008 Midlatitudes 250-300 hPa Distance of top of highest cloud to tropopause Separation into two classes of optical depth Midlatitudes 300-400 hPa Mean RHice remains < 100% even for clouds extending over the whole pressure layer (influence of vertical and horizontal humidity variability, supersaturation occuring over smaller vertical extents than cloud appear ?) If significant, higher mean RHice for lowest optical depths at comparable geometrical thickness (more depletion of water vapor for largest optical depths) Greater influence of geometrical thickness on mean RHice than optical depth (15 - 35 % vs. 5 – 10 %) Difficulties for detection of ice supersaturation Tropics 150-200 hPa Tropics 200-250 hPa Multiple-scattering contribution increasing with optical depth Evaluation of ECMWF (European Center for Medium-range Weather Forecasts) forecasts with new ice supersaturation scheme using AIRS and CALIPSO Lamquin, Gierens, Stubenrauch, and Chatterjee, ACPD 2008 Comparison AIRS-CALIPSO, LMD vs. L2 retrievals, high clouds. From study in Stubenrauch et al. (JGR 2008) Ice supersaturation in the upper troposphere is an explicit feature in the Integrated Forecast System, operational since Sept 13, 2006, was introduced by Tompkins et al. (2007), it adopts the supersaturated relative humidity (RH) threshold using empirical approximation of the results of Koop et al. (2000) given by Kärcher and Lohmann (2002), f(T). It has produced some changes in the statistics of UTH and cloud fraction in the IFS (decrease in high-level cloud cover). Small adjustments for vertical griddings ← Colocation: Europe window One year Two resolutions of ECMWF forecasts → Spin up phase for the model to reach constant ice supersaturation occurrence → Good agreement between ECMWF UTH and CALIPSO high clouds Comparisons between ECMWF forecasted UTH and AIRS UTH show a good agreement for clear (or mostly clear) scenes. Cloudy scenes take into account a variability of RHi values found in AIRS subject to biases due to the vertical resolution, this has to be taken into account to evaluate the forecast of the nucleation of high clouds. Influence of vertical resolution on ice supersaturation occurrence Confronting two resolutions in the ECMWF forecasts, Comparison with radiosoundings High cloud nucleation in the model resets RHi to 100% while AIRS sees a variability of situations. Distributions consistent with previous results (first part of poster). Contact: nicolas.lamquin@lmd.polytechnique.fr