Lars Peter Riishojgaard

Yan-Qiu Zhu

Global Modeling and Assimilation Office

NASA Goddard Space Flight Center

Impact Experiments on GMAO Data Assimilation and Forecast Systems with MODIS Winds During MOWSAP

Presented by Ron Gelaro, NASA/GMAO

MODIS winds

Polar orbiting platform (NASA Terra, Aqua), primarily intended for aerosol/clouds/land surface measurements

Wind vectors calculated using geostationary feature tracking algorithms on high-latitude imagery from two MODIS channels

6.7µ water vapor channel for clear-sky moisture field 11µ window channel for clouds

Coverage in high latitudes (beyond 65o) where successive overpasses cover the same region

Useful complement to geostationary satellite winds that drop off sharply beyond 58o latitudes

Image repeat frequency tied to orbital period of ~100 min. Need for image triplets implies long acquisition time

(animation provided by Key et al., CIMSS)

Unlike geostationary satellites at lower latitudes, it is not be possible to obtain complete polar coverage at a snapshot in time with one or two polar-orbiters. Instead, winds must be derived for areas that are covered by two or three successive orbits, an example of which is shown here. The whitish area is the overlap between three orbits.

(slide provided by Key et al., CIMSS)

Example 6-hour data coverage; MODIS winds (left panel); all other satellite and conventional surface and upper air winds (right panel)

MODIS winds vertical distribution

Water Vapor Observations Infra-Red Observations

GMAO MODIS winds experiments

MOWSAP (MODIS Winds Special Acquisition Period): November 8, 2003-January 31, 2004

Winds generated by CIMSS and by NESDIS (pre-operational mode)

Same algorithm, different code bases Different backgrounds for QC and height assignment

Winds generated from MODIS Aqua and MODIS Terra imagery

Assimilation experiments by GMAO, ECMWF, Met Office, CMC

Experimental setup: 5-day forecast every other day; 42 members in the ensemble

GMAO GEOS4: fvGCM+PSAS analysis (1o x 55 levels)

Innovation statistics for raobs: Arctic

control

control+MODIS

height (m) u-wind (m/s)

RMS (obs – 6hr fcst)

control

MODIS

height (m) u-wind (m/s)

control

Innovation statistics for raobs: AntarcticRMS (obs – 6hr fcst)

control+MODIS

Forecast skill - ACC 500 hPa height NESDIS Winds

Forecast skill - ACC 500 hPa height at 120 hrsNorthern High-Latitudes: 60-90N

Forecast skill - ACC 500 hPa height at 120 hrsSouthern High-Latitudes: 60-90S

Forecast skill - ACC 500 hPa height at 120 hrsSouthern Mid-Latitudes: 60-90N

Forecast error evolution Jan 21, 2004; Control (left), MODIS (right)

Summary

MODIS winds complement other observations in the high 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 statistics, the quality of the

information is acceptable Positive overall contribution to forecast skill

Substantial impact in the SH Impact extends to entire hemisphere Improvements in average forecast skill results primarily from

improving the skill of the worst forecasts Timeliness remains an important issue; current delay is 4-6 hours;

some improvement possible via use of Direct Broadcast capability

Outlook

MODIS winds experiments with new GMAO assimilation system based on grid space analysis (GSI developed at NCEP)

Case study diagnostics; busts? Data density/QC studies WV vs. IR winds Two-satellite winds

End of Talk…Thank You.