MIPAS Temperature and Pressure Validation by RO Data

MIPAS and Validation by RO Data Marc Schwaerz and Gottfried Kirchengast Wegener Center (WEGC), Graz, Austria MIPAS Quality Working Group Meeting 40, November 3, 2015

Outline 1 2 Validation and Reference 3 Validation Results Validation Validation 4 Summary

MMValRO project provision of long-term RO validation data provision of long-term RO validation data for long-loop monitoring of trends for spaceborne instrument and climate system variability for in-depth examination of tropospheric and stratospheric profiles retrieved from ESA satellite atmospheric observations for intercomparison of RO data with radiosonde datasets.

MMValRO project RO has unique combination of global coverage high accuracy long-term stability all weather capability up to about 2500 profiles per day

provided atmospheric parameter especially for UTLS region long-term database of temperature specific humidity pressure refractivity density (derived from above parameter) as a function of mean-sea-level altitude

Validation Processing PROF DB PROF DB PROF DB Validation Processing RO Validation (internal) PROF DB PROF DB RO - internal RO-external ECMWF-Colloc Validation Processing External Profile Validation external L2 Profs MIPAS, etc. RO - internal Validation Processing plot generaltion VALID DB validate.globclim.org and internal website plot generaltion VALID DB

Outline 1 2 Validation and Reference 3 Validation Results Validation Validation 4 Summary

validation steps validation steps search for collocated measurements quality control of candidate instruments quality control of reference instruments interpolation to common grid (currently 0 35 km in 100 m steps) gaussian smoothing with width of partner instrument calculation of statistical measures (systematic difference, stdev., etc.) plotting of the data presentation of the data on a web-page validate.globclim.org

collocation criteria collocation criteria reference measurement is used if max. 300 km distance max. 3 h time difference all found collocated measurements are used better sampling

validated dataset qc MIPAS MIPAS ML2PPv6.0 reprocessed dataset from 2002 to 2012 new MIPAS ML2PPv7.03 dataset from 2002 to 2012 MIPAS QC no extra quality control if a profile is present in the dataset then it is used.

reference dataset qc RO RO QC newest versions of OPSv5.6 from 2002 to 2012; bending angle quality flag: 0, 2 refractivity quality flag: 0 dry profile quality flag: 0 physical profile quality flag: 0

reference dataset additional info updates OPSv5.6 inclusion of waveoptics processing, i. e., tropospheric processing provision of physical temperature, pressure, and humidity profiles via 1DVar approach provision of general uncertainties of RO profile data

ad interpolation and smoothing interpolation temperature: linear pressure: log-linear smoothing Gaussian Smoothing Gaussian Smoothing vs. Averaging Kernels

Outline 1 2 Validation and Reference 3 Validation Results Validation Validation 4 Summary

number of MIPAS RO collocations Overview on the number of events of MIPAS and RO data and number of collocations

MIPAS temperarture temperature

MIPASv6.0 vs. ROv5.6 temperature timeseries top: mean difference; middle: standard deviation; bottom: counts

MIPASv7.03 vs. ROv5.6 temperature timeseries top: mean difference; middle: standard deviation; bottom: counts

MIPAS vs. ROv5.6 temperature; July 2003 left panel: MIPASv6.0; right panel: MIPASv7.03

MIPAS vs. ROv5.6 temperature; July 2008 left panel: MIPASv6.0; right panel: MIPASv7.03

MIPAS pressure pressure

MIPASv6.0 vs. ROv5.6 pressure timeseries top: mean difference; middle: standard deviation; bottom: counts

MIPASv7.03 vs. ROv5.6 pressure timeseries top: mean difference; middle: standard deviation; bottom: counts

MIPAS vs. ROv5.6 pressure; January 2003 left panel: MIPASv6.0; right panel: MIPASv7.03

MIPAS vs. ROv5.6 pressure; February 2008 left panel: MIPASv6.0; right panel: MIPASv7.03

MIPASv7.03 quality issue; November 2002

Outline 1 2 Validation and Reference 3 Validation Results Validation Validation 4 Summary

summary summary almost no differences between MIPASv6.0 and v7.03 in temperature RO day/night differences are negligible within RO error bounds differences between MIPASv6.0 and v7.03 in pressure are about 1% to 2% not shown result: GRUAN vs. MIPAS similar to RO.vs.MIPAS

outlook validation with new datasets new RO dataset with new rops processor including: integrated uncertainty propagation per profile starting from L0 uncertainty input. completely new coding of ops based on so-called "base-bandmethod (doing retrieval steps on residual signal) implementation of new ionospheric correction scheme including also non-esa mipas datasets?!

That s it!