Title: Lars Peter Riishojgaard
1Preparation for operational assimilation MODIS
winds in the DAO
- Lars Peter Riishojgaard
- Yan-Qiu Zhu
- Global Modeling and Assimilation Office
- NASA Goddard Space Flight Center
2Overview
- Data assimilation at Goddard and the JCSDA
- Characteristics of the MODIS winds
- Results from pre-operational testing
- Summary and outlook
3GMAO
- New Office at Goddard, formed via a merger of the
DAO and NSIPP (NASA Seasonal to Interannual
Prediction Project) - Head of Office Michele Rienecker
- Modeling
- New model targeted for 04 based on fv dynamical
core, but with NWP-tuned physics - Analysis
- Last PSAS-based system being frozen
- Next system will be based on GSI developed at EMC
4MODIS winds pilot period assimilation experiments
in the DAO
- Control (all standard observations no MODIS
winds) - MODIS winds used as is no filtering, no
modification - Interactive height assignment with ?pmax150 hPa
- Interactive height assignment with ?pmax75 hPa
5(No Transcript)
6(No Transcript)
7Preparation for operational assimilation of MODIS
winds
- Extensive experimentation with near-real time
winds provided by CIMSS starting 07/02/2002 with
versions 1.3r6 and 1.4r1 of the fv-DAS - Main changes with respect to 1.2r5 (pilot period)
- Increased weight given to ITOVS
- Additional ITOVS data in polar areas
- Modified background error covariance
- Main metrics
- Consistency of data delivery
- Quality of MODIS winds
- Contribution to forecast skill
8MODIS experiments
- Basic - MODIS winds used "as is"
- Height adjustment - the heights of MODIS winds
are adjusted by minimizing a cost function - Quality indicator-based selection only MODIS
winds with qi larger than 0.80 are used - Retuned ?o error for MODIS wind is tuned using
maximum likelihood technique - ECMWF filtering over land winds used above 400
hPa over sea, IR winds above 700 hPa and WV
winds above 550 hPa - DAOTOVS exclusion Interactive TOVS retrievals
beyond 65S removed -
9Experimental results
- Innovations (observation minus forecast
residuals) - RAOB heights and winds
- ITOVS heights
- MODIS winds
- Impact
- Troposphere
- Stratosphere
- Forecast skill
10(No Transcript)
11(No Transcript)
12MODIS IR U, V innovations for NH control (solid),
MODIS Arctic
13MODIS WV U, V innovations for NH control (solid),
MODIS Arctic
14RAOB U, V innovations for control (solid), MODIS
Arctic
15RAOB U, V innovations for control (solid), MODIS
SP
16RAOB height innovations for control (solid),
MODIS Arctic region
17RAOB height innovations for control (solid),
MODIS South Pole
18ITOVS height innovations Arctic region
19ITOVS height innovations Antarctic region
20Mean analyzed 500 hPa geopotential heights for
July, 2002, for MODIS I run NH (top left) and
SH (bottom left) RHS shows difference fields
(MODIS minus control).
21NCEP mean anlyzed 500 hPa heights, July 2002,
Anarctica
22Control minus NCEP
MODIS minus NCEP
23(No Transcript)
24(No Transcript)
25(No Transcript)
26(No Transcript)
27(No Transcript)
28(No Transcript)
29(No Transcript)
30Summary
- MODIS winds complement other observations at the
highest latitudes more so in the SH than in the
NH due to the current data sparsity - Consistency of data delivery is acceptable
- Based on independent verification and innovation
statistics, the quality of the information is
acceptable - Positive contribution to forecast skill, but not
where one would expect it the most - Current version of fv-DAS is hostile to
high-latitude wind information
31Outlook
- MODIS winds experiments with new GMAO
assimilation system based on GSI (next-generation
EMC analysis ) - Impact
- Background error covariance
- Timeliness
- MODIS winds from Aqua
- ECMWF verification if possible