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0.04
TPW
SpecHum
0.03
0.02
0.01
0
−0.01
−0.02
−0.03
−0.04
−0.05
−0.06
0
5
10
15
20
25
assimilation/forecast cycle
Fig. 9.9 Forecast error sensitivity (J Kg 1 ) to the observation error variance weight coefficient
s o for SSMI total precipitable water observations (TPW) and for the radiosonde specific humidity
observations (SpecHum) during each assimilation/forecast cycle
The sensitivity results obtained for the radiosondes indicate that, in general, the
information provided by temperature measurements is underweighted whereas
the information provided by specific humidity measurements is overweighted in
the DAS. The geographical distribution of the forecast error sensitivity to the
assigned
o
-weight coefficient for radiosonde temperature and specific humidity
measurements is shown in Figs. 9.10 and 9.11 , respectively. These maps display
the cumulative values of the sensitivities over the time period of study, vertically
integrated, and at a horizontal bin resolution of
2:5 ı .
The sensitivity analysis of the radiance data distinguishes the Advanced
Microwave Sounding Unit (AMSU)-A from the Infrared Atmospheric Sounding
Interferometer (IASI), the Atmospheric Infrared Sounder (AIRS), and the Special
Sensor Microwave Imager Sounder (SSMIS) instruments. For each instrument,
the forecast error sensitivity to the assigned observation error variance weight
coefficient was monitored during each assimilation/forecast episode and the results
are displayed in
s o -sensitivities associated with AMSU-A
indicate a conservative use of information and that reducing the
Fig. 9.12 . Positive
o
values assigned
to this instrument is of potential benefit to the forecasts. Systematic negative
s o -sensitivities are noticed for IASI and provide an indication that further inflation
of the
o
values assigned to this instrument is of potential benefit to the forecasts.
Negative sensitivity values are also noticed in the majority of the analysis/forecast
episodes for AIRS and SSMIS instruments.
 
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