Figure 1. Spatial
domain of the satellite-derived estimation of surface air temperature (TA)
and specific humidity (Qa). The stars denote
the locations of the moored buoys in the TAO and PIRATA domains as well the
WHOI buoy in the Arabian Sea. Temporal
Domain for available SSM/I sensors.
Figure 2a.
Schematic representation of the artificial neural network (ANN) architecture
used to estimate TA. The first layer contains the input parameters
of total precipitable water (TPW), sea surface temperature (SST), surface
wind (Wind), and cloud liquid water (CLW) whereas the output layer contains
the target TA. The
architecture is denoted as 4-15-10-1x and contains fifteen nodes in the first
hidden layer and 10 nodes in the second hidden layer.
Figure 2b.
Schematic representation of the artificial neural network (ANN) architecture
used to estimate QA. The first layer contains the input parameters
of total precipitable water (TPW), sea surface temperature (SST), surface
wind (Wind), cloud liquid water (CLW), and rain rate (RR) whereas the output
layer contains the target QA.
The architecture is denoted as 5-15-6-1x and contains fifteen nodes in the
first hidden layer and 6 nodes in the second hidden layer.
Figure 3. Validation
of TA estimated with ANN model and buoy observations for validation
samples in the TAO and PIRATA domains (top left and right). Sample sizes (N),
correlation coefficient, mean bias (satellite minus buoy) (°C) and rms
errors (°C) are indicated
in the figure. The comparison of NCEP/NCAR TA (2 m) and buoy observations
(3 m) are shown in the bottom.
Figure 4. Same as in
Fig 3, but for validation of Qa. Units are in g kg-1.
Figure 6a. Spatial
distribution of Ta rms (°C) errors
between satellite estimates and buoy observations over 12 years in the TAO
domain.
Figure 6b. Spatial
distribution of Qa rms (g kg-1) errors between satellite estimates
and buoy observations over 12 years in the TAO domain.
Figure 6c. Spatial
distribution of number of observations used to calculate rms in Figures 6a
and 6b.
Figure 6d. Spatial
distribution of NCEP-ANN Ta and Qa rms errors over the TAO domain.
Figure 6e. Spatial
distribution of LHF rms (W m-2) errors between satellite estimates
and buoy observations over 12 years in the TAO domain.
Figure 6f. Spatial
distribution of SHF rms (W m-2) errors between satellite estimates
and buoy observations over 12 years in the TAO domain.
Figure 6g.Spatial distribution
of number of observations used to calculate rms in Figures 6d and 6e.
Figure 6h.Spatial distribution
of NCEP-ANN LHF and SHF rms errors over the TAO domain.
Figure 7a-h.
Same as in Fig. 6a-h, but for moored buoys in the PIRATA domain.
Figure 8.
15 year mean and standard deviation of satellite-derived
Ta field.
Period:
October 1987 to September 2002.
Figure 9.
15 year mean and standard deviation of satellite-derived Qa field.
Period:
October 1987 to September 2002.
Figure 10. 15 year mean
and standard deviation of satellite-derived LHF field.
Period:
October 1987 to September 2002.
Figure 11. 15 year mean
and standard deviation of satellite-derived SHF field.
Period: October
1987 to September 2002.
Figure 12. Relative sensitivity of input parameters on resulting LHF and SHF rms with respect to buoy data for ANN and NCEP inputs for the TOGA TAO domain.
Figure 13. Relative
sensitivity of input parameters on resulting LHF and SHF rms with
respect to buoy data for ANN and NCEP inputs for the Pirata domain.