GEOS-5 Observation Impact Calculations

Methodology
Observation impacts are computed using the adjoint of the GEOS-5 atmospheric data assimilation system, including the GEOS-5 forecast model and Gridpoint Statistical Interpolation (GSI) analysis scheme. The calculation is based on the technique proposed by Langland and Baker (2004), and extended for nonlinear analysis schemes such as the GSI as described by Trémolet (2008) and Gelaro et al. (2010). The technique efficiently estimates the impacts of all observations simultaneously on a selected measure of forecast error. The results can be easily aggregated by data type, location, channel, or other observation attribute. For synoptic-scale motions, application of the technique is limited to forecast ranges of 1–3 days owing to the linearity assumptions inherent in the use of adjoint models.

Impact Measure
The results shown are for a global measure of 24-h forecast error that combines errors in wind, temperature, specific humidity and surface pressure with respect to the verifying analysis from the surface to 1 hPa in terms of moist total energy (J/kg). Observation impact is taken to be the difference in this error measure between 24-h forecasts initialized from the analysis and corresponding background state, where this difference is due entirely to the assimilation of the observations. Negative (positive) values of observation impact indicate that assimilation of a given set of observations has improved (degraded) the 24-h forecast. The GEOS-5 adjoint model currently includes parameterizations of surface drag, vertical mixing, moist convection and large-scale precipitation (Holdaway et al. 2013).

Plot Details
Currently, observation impacts in GEOS-5 are computed once each day for the 24-h forecast initialized at 00z. The results are plotted in two forms: summary diagrams showing average values for each observing system or channel over the selected time interval, and time series. For the summary diagrams, the values are averaged over the number of cases in the interval, and the color shading denotes the average number of observations for a given observing system or channel per case in this interval. For the time series diagrams, the plotted values are sums for each case, and the color shading denotes the magnitude of the plotted values. A universal color scale is used in the time series diagrams so that results for different observing systems can be easily compared. Results shown for bounded geographical regions, such as the Northern Hemisphere, show the contributions from observations in those regions (only) to the reduction of the global forecast error measure.

References:

Gelaro R., Langland R. H., Pellerin S., Todling R., 2010: The THORPEX observation impact intercomparison experiment. Mon. Weather Rev., 138, 4009–4025

Holdaway, D., R. Errico, R. Gelaro and J. G. Kim, 2013: Inclusion of linearized moist physics in NASA's Goddard Earth Observing System data assimilation tools. To appear in Mon. Weather Rev.

Langland, R. H. and Baker, N., 2004: Estimation of observation impact using the NRL atmospheric variational data assimilation adjoint system. Tellus, 56A, 189–201.

Trémolet, Y., 2008: Computation of observation sensitivity and observation impact in incremental variational data assimilation. Tellus, 60A, 964–978.

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