Sensor Description
SSM/I was first launched on board the Defense Meteorological Satellite Program (DMSP) F8 satellite in June of 1987. The DMSP series satellites are in sun-synchronous polar orbits at an altitude of approximately 830 km. The instrument is a seven channel linearly polarized passive microwave radiometer operating at frequencies of 19.35, 22.235, 37.0, and 85.5 GHz. Detailed specifications for the spacecraft and instrument are given by Hollinger et al. [1987] and Hollinger [1989, 1991].
SSM/I channel characteristics:
| Center Frequencies (GHz) |
19.35 |
19.35 |
22.235 |
37.0 |
37.0 |
85.5 |
85.5 |
|---|
| Polarization |
V |
H |
V |
V |
H |
V |
H |
| Bandwidth (MHz) |
250 |
250 |
250 |
1000 |
1000 |
1500 |
1500 |
| Sensitivity (K) |
0.6 |
0.6 |
0.6 |
0.6 |
0.6 |
1.1 |
1.1 |
| EFOV (km x km) * |
69 x 43 |
69 x 43 |
60 x 40 |
37 x 28 |
37 x 29 |
15 x 13 |
15 x 13 |
| Sampling Interval (km x km) * |
25 x 25 |
25 x 25 |
25 x 25 |
25 x 25 |
25 x 25 |
12.5 x 12.5 |
12.5 x 12.5 |
| Integration Time (msec) |
7.95 |
7.95 |
7.95 |
7.95 |
7.95 |
3.89 |
3.89 |
| Main Beam Efficiency (%) |
96.1 |
96.5 |
95.5 |
91.4 |
94.0 |
93.2 |
91.1 |
| Beamwidth (half-power, degrees) |
1.87 |
1.87 |
1.65 |
1.10 |
1.10 |
0.43 |
0.45 |
* EFOV and Sampling Interval values are km along track x km across track. Note that the effective field-of-view for the 22 GHz channel is wrongly reported in the SSM/I Users Guide Table 2.1 as 50 x 40 km. The actual FOV is 60 x 40 km, as reported in the SSM/I User's Interpretation Guide.
Channel characteristics shown above are from:
Local observing times:
-
The DMSP Local Observing Times are shown over the 25+ year record of the nine
satellites in the FCDR data record. Note that because the DMSP spacecraft are not maintained in a specific orbit, the local
observing times change as the orbit decays over time due to atmospheric drag. This results in changes to both the Earth
incidence angle or view angle as well as the impact of diurnal cycle variability. If not properly accounted for by the
geophysical retrieval algorithms, both of these factors can lead to time-dependent biases that appear as climate trends. The
plot shows the time of the am or morning pass, which is the ascending pass for all of the sensors except for F08. The pm or
evening pass occurs at the time shown plus 12 hours.
Geolocation
The original SSM/I pixel geolocation is based on predicted spacecraft ephemeris. For the FCDR data we recompute the spacecraft ephemeris using orbital element information contained in two-line element (TLE) files produced by the North American Aerospace Defense Command (NORAD). Using this updated spacecraft ephemeris along with software to compute the pixel geoleocation based on the geometry of the sensor, we perform an examination of geolocation errors and the subsequent impact on the view angle, or Earth incidence angle (EIA). Given that the observed Tb are highly sensitive to the view angle, properly accounting for changes in EIA across an orbit and over time is an important step that must be addressed before attempting to intercalibrate the sensors. Using a previously developed coastline analysis technique, estimates of changes in the spacecraft attitude including deviations in roll, pitch, and yaw have been computed for the life of each of the SSM/I sensors. Applying these corrections results in an improved pixel geolocation, but more importantly provides accurate estimates of the EIA across the scan and throughout each orbit. An analysis of uncertainties in the calculation of EIA shows mean errors within 0.1 degrees, which translates to errors in the calibration of less than 0.2 K for all channels. Equally important, is the availability of improved geolocation and EIA estimates for algorithm developers using the SSM/I data, which is critical for producing unbiased estimates of geophysical parameters for use in climate applications.
Additional Information on Geolocation
Intercalibration
Intercalibration of the SSM/I sensors (including F08, F10, F11, F13, F14, and F15) has been done using multiple techniques. The reason for using several difference approaches is both to quantify calibration differences beween sensors over radiometrically cold (i.e. ocean) and warm (i.e. land) scenes as well as the uncertainty in the resulting calibration differences. Given the lack of an absolute calibration target for the microwave frequencies employed on SSM/I and SSMIS, using multiple approaches provides confidence in the results and a reasonable estimate of the uncertainties. The techniques that have currently been used include the following.
- Coincident overpasses with TRMM TMI: A double difference approach that uses difference between coincident observations from TMI to eliminate diurnal variability along with differences between simulated TBs to account for differences in the channel characteristics. The simulated TBs are computed using both retrieved geophysical parameters based on an optimal estimation algorithm as well as model analyses.
- Coincident overpasses over polar regions: Direct comparisons of TBs from sensors operating concurrently are made over the polar regions, which is the only region that the sun-synchronous DMSP spacecraft view the same scenes simultaneously.
- Model double differences: Geophysical parameters from both global model analysese including MERRA and ECMWF Interim are used to compute simulated TBs from a pair of sensors operating concurrently. Differences between the observed and simulated TBs are then used to compute intercalibration differences. This approach relies on the model to account for diurnal variability, which avoids the need for a non-sunsynchronous satellite like TRMM, but relies on the model's diurnal cycle. Using multiple models helps to reduce/quantify this error, however.
- Vicarious cold calibration: This approach employs an analysis of the cumulative histogram of observed TBs to compute a vicarious cold reference TB, which represents a statistical lower bound on the observed TB. A comparison of the vicarious cold temperatures from different sensors provides a calibration difference for the coldest TBs. Simulations based on model analysis are subsequently used to account for slight variations in the viewing angle of the sensor.
- Vicarious warm calibration: This approach is similar to the vicarious cold calibration, but it uses highly vegetated (i.e. warm) scenes over the Amazon and other jungles/forests with high surface emissivities. A retrieval is used to account for diurnal temperature variations etc.
Additional Information on Intercalibration
