5. Initial results for the RO-MiRS retrievals from the COSMIC and ATMS data

those from RS92 are equal to 0.39 K with a standard deviation of 2.26 K for clear ocean cases and 0.0 K with a standard deviation of 2.35 K for cloudy ocean cases, respectively. The temperature biases for RO/ATMS results are larger from those over land than from those over oceans for both clear and cloudy conditions. Figure 9 shows comparison results for RO/ATMS global water vapor retrievals. Over ocean surfaces, the retrieved bias is relatively low at all layers. The land retrievals show a larger bias than those over oceans. The global mean water vapor biases from surface to 200 mb for clear/sea, clear land, cloudy/sea, and cloudy/land cases are 0.11, 0.17, 0.11, and 0.11 g/kg, respectively. The temperature and water vapor biases for ATMS-only retrievals relative to those from RS92 are about 10–20% larger than the COSMIC/ATMS results at different levels

RO-MiRS COSMIC/ATMS retrieved water vapor bias with respect to co-located RS92 measurements (red:

RO-MiRS COSMIC/ATMS retrieved temperature bias with respect to co-located RS92 measurements (red:

Global Water Vapor Estimates from Measurements from Active GPS RO Sensors and Passive…

ocean and green: land) for clear (left) and rainy (right) conditions.

DOI: http://dx.doi.org/10.5772/intechopen.79541

ocean and green: land) for clear (left) and rainy (right) conditions.

(not shown).

99

Figure 9.

Figure 8.

We have successfully implemented the RO refractivity forward operator (Eq. (1)) into the current MiRS Version 11. This initial experiment is to demonstrate the feasibility of the proposed fusion approach to simultaneously retrieve global temperature and water profiles and hydrological data products using MiRS from the current operational COSMIC and ATMS data. Ten days of COSMIC-ATMS pairs are collected and inverted using RO-MiRS. Figures 8 and 9 compared the co-located COSMIC and ATMS pairs (collected within 100 km and 15 min) with those temperature and moisture measurements from the Vaisala-RS92 radiosondes, respectively. Figure 8 depicts that the mean temperature biases for RO/ATMS relative to

Global Water Vapor Estimates from Measurements from Active GPS RO Sensors and Passive… DOI: http://dx.doi.org/10.5772/intechopen.79541

#### Figure 8.

regression method described in Section 4.1 is used for the data from the simulation study. The 100 level AIRS vertical grids are used for all AIRS, AMSU, and GPS RO data. With a very high vertical resolution GPS RO refractivity profiles, AIRS and AMSU temperature RMSEs improved from 0.8 and 1.0 K, respectively, between 250 and 100 hPa (tropopause layer) to 0.4 K, which lead to AIRS and AMSU moisture RMSE around the same layer decrease from 4 and 15 ppmv, respectively, to around

The RMSE of temperature for AIRS, AMSU, GPS, and AIRS+AMSU+GPS in the UT/LS is on the left panel, and the RMSE of water vapor for AIRS, AMSU, GPS, and AIRS+AMSU+GPS in the UT/LS is on the right

Since the open-loop tracking algorithm is only applied to COSMIC data, GPS

RO data from COSMIC are used with AIRS data to derive moisture and temperature profiles in the clear skies of the free troposphere. For the UT/LS retrievals, GPS RO from SAC-C, GRACE, CHAMP, COSMIC, and GRAS data can be used to collocate with AIRS data. It can be seen in the left panel of Figure 6 that the region of the largest temperature gradient is around 200 hPa, where the temperature RMSE for AIRS and AMSU is around 1.0 K. The fact that much improved

temperature retrievals from GPS RO data (RMSE is 0.6 K) and from the combined AIRS, AMSU, and GPS RO data (RMSE is 0.3 K) are very useful to construct accurate temperature and moisture structures in the UT/LS region for

5. Initial results for the RO-MiRS retrievals from the COSMIC and

We have successfully implemented the RO refractivity forward operator (Eq. (1)) into the current MiRS Version 11. This initial experiment is to demonstrate the feasibility of the proposed fusion approach to simultaneously retrieve global temperature and water profiles and hydrological data products using MiRS from the current operational COSMIC and ATMS data. Ten days of COSMIC-ATMS pairs are collected and inverted using RO-MiRS. Figures 8 and 9 compared the co-located COSMIC and ATMS pairs (collected within 100 km and 15 min) with those temperature and moisture measurements from the Vaisala-RS92 radiosondes, respectively. Figure 8 depicts that the mean temperature biases for RO/ATMS relative to

than 3 ppmv.

Figure 7.

Green Chemistry Applications

panel.

the entire globe.

ATMS data

98

RO-MiRS COSMIC/ATMS retrieved temperature bias with respect to co-located RS92 measurements (red: ocean and green: land) for clear (left) and rainy (right) conditions.

#### Figure 9.

RO-MiRS COSMIC/ATMS retrieved water vapor bias with respect to co-located RS92 measurements (red: ocean and green: land) for clear (left) and rainy (right) conditions.

those from RS92 are equal to 0.39 K with a standard deviation of 2.26 K for clear ocean cases and 0.0 K with a standard deviation of 2.35 K for cloudy ocean cases, respectively. The temperature biases for RO/ATMS results are larger from those over land than from those over oceans for both clear and cloudy conditions.

Figure 9 shows comparison results for RO/ATMS global water vapor retrievals. Over ocean surfaces, the retrieved bias is relatively low at all layers. The land retrievals show a larger bias than those over oceans. The global mean water vapor biases from surface to 200 mb for clear/sea, clear land, cloudy/sea, and cloudy/land cases are 0.11, 0.17, 0.11, and 0.11 g/kg, respectively. The temperature and water vapor biases for ATMS-only retrievals relative to those from RS92 are about 10–20% larger than the COSMIC/ATMS results at different levels (not shown).