Open AccessMonitoring of observation errors in the assimilation of satellite ozone data
Author(s) -
Stajner Ivanka,
Winslow Nathan,
Rood Richard B.,
Pawson Steven
Publication year - 2004
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2003jd004118
Subject(s) - data assimilation , environmental science , total ozone mapping spectrometer , ozone , satellite , meteorology , remote sensing , backscatter (email) , residual , assimilation (phonology) , atmospheric sciences , ozone layer , computer science , geology , algorithm , geography , telecommunications , linguistics , philosophy , aerospace engineering , engineering , wireless
Ozone observations from the Solar Backscatter UltraViolet/2 (SBUV/2) instruments and/or the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) have been assimilated in near‐real time at NASA's Data Assimilation Office (DAO) since January 2000. The ozone data assimilation system was used as a tool for detecting and characterizing changes in the observation errors. The forecast model captures the geophysical variability. A change in the observed‐minus‐forecast (O‐F) residuals, which are defined as differences between the incoming ozone observations and the collocated short‐term model forecast, indicates a change in the assimilation system. If the model and the statistical analysis scheme are stable, then it points to a modification in instrument characteristics or a retrieval algorithm. However, sometimes a change in the ozone O‐F residuals is caused by differences in the availability of the meteorological observations or modifications in the meteorological assimilation system whose winds are used to drive the ozone transport model. The O‐F residuals are routinely produced and monitored in the assimilation process. Using examples from the NOAA 14 and NOAA 16 SBUV/2 instruments, and the EP TOMS, we demonstrate that the monitoring of time series of O‐F residual statistics is an effective, sensitive, and robust method for identifying time‐dependent changes in the observation‐error characteristics of ozone. In addition, the data assimilation system was used to assist in the validation of updated calibration coefficients for the NOAA 14 SBUV/2 instrument. This assimilation‐based monitoring work is being extended to ozone data from instruments on new satellites: Environmental satellite (Envisat), Earth Observing System (EOS) Aqua, and EOS Aura.