1 / 12

Rennie Selkirk, NASA GSFC/GESTAR Mark Schoeberl , STC

Variability of TTL water vapor A filtered CFH climatology and MLS water vapor for Ticosonde /Costa Rica . Rennie Selkirk, NASA GSFC/GESTAR Mark Schoeberl , STC. ATTREX Science Team Meeting NCAR – 24 October 2013. Sonde processing. Objectives:

thor
Download Presentation

Rennie Selkirk, NASA GSFC/GESTAR Mark Schoeberl , STC

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Variability of TTL water vaporA filtered CFH climatology andMLS water vapor for Ticosonde/Costa Rica Rennie Selkirk, NASA GSFC/GESTAR Mark Schoeberl, STC ATTREX Science Team Meeting NCAR – 24 October 2013

  2. Sonde processing • Objectives: • Highlight the large seasonal variability in TTL WV • Need to remove CFH noise in at scale of ~100 m • Approach: • Low-pass filter – with attention to data gaps • Apply to all variables • Calculate seasonal climoon data from 2005-2011 • Will soon add 2012 and 2013

  3. Temperatures at Costa Rica

  4. CFH Water Vaporwith previous season

  5. RH ice Both seasons show rapid fall off of mean RHice profile at mean coldpoint (dashed lines)

  6. WV tape recorder at Costa Rica(seasonal time averages)

  7. Water Vapor vs Ozone JJA DJF

  8. MLS water vapor intecomparisons • Long-term average data • MLS WV, version 3, interpolated via MERRA to San Jose and in potential temperature • Can be used to compare to CFH seasonal climatology • MLS RDFs: • Back-trajectory-based product • Synthetic high-vertical resolution water vapor (and ozone) profiles • Use to infer day-to-day variability at a sounding location

  9. Sondes vs. MLS v.3 Winter composite (36 sondes) Summer composite (60 sondes)

  10. MLS RDF @ SJOSummer 2007

  11. MLS RDFs vs CFH MLS RDF profile (previous slide) * * * * * * *

  12. Summary • Strong seasonal cycle of water vapor in UTLS at Costa Rica Low-pass filtering of CFH data • Tape recorder prominent • Low-pass filtering reduces instrumental noise • But may reduce frequency of high RH in TTL too strongly • Seasonal average fields consistent with MLS, v.3 • MLS RDFs promising technique for reproducing vertical structure seen in sondes

More Related