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David I. Duncan, Christian D. Kummerow, and Gregory S. Elsaesser


Life cycles of deep convective raining systems are documented through use of a Lagrangian tracking algorithm applied to high-resolution Climate Prediction Center morphing technique (CMORPH) rainfall data, permitting collocation with related environmental ancillary fields and the International Satellite Cloud Climatology Project (ISCCP) cloud states (). System life cycles are described in terms of propagation speed, duration, and dominant cloud structures. Tracked systems are usually associated with the ISCCP weather state 1 (WS1) deep convection cloud state and an independent, microwave-based deep convective precipitation regime developed here. The distribution and characteristics of tracked systems are found to be similar between ocean basins in terms of system speed and duration, with westward-propagating systems predominant in every basin.

The effects that these systems have on environmental parameters are assessed, stratified according to their average propagation speed and by ocean basin. Regardless of system speed the net effect on the environment is similar, with the largest difference being how quickly changes occur, with net surface radiation decreasing about 150 W m−2 and total precipitable water perturbed by 5–7 kg m−2; sea surface temperature (SST) drops 0.2°–0.3°C over 24 h, with system speed affecting how long SSTs remain depressed. The observed drop in SST is partly caused by the presence of widespread, optically thick clouds that greatly decrease the net surface radiative flux. Quick changes in SSTs caused by tracked systems are captured by buoys but not represented well in gridded SST products, as these regions remain largely under the precipitating cloud cover associated with these systems.

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Corey G. Amiot, Sayak K. Biswas, Timothy J. Lang, and David I. Duncan


Recent upgrades, calibration, and scan-angle bias reductions to the Advanced Microwave Precipitation Radiometer (AMPR) have yielded physically realistic brightness temperatures (T b) from the Olympic Mountains Experiment and Radar Definition Experiment (OLYMPEX/RADEX) dataset. Measured mixed-polarization T b were converted to horizontally and vertically polarized T b via dual-polarization deconvolution, and linear regression equations were developed to retrieve integrated cloud liquid water (CLW), water vapor (WV), and 10-m wind speed (WS) using simulated AMPR T b and modeled atmospheric profiles. These equations were tested using AMPR T b collected during four OLYMPEX/RADEX cases; the resulting geophysical values were compared with independent retrieval (1DVAR) results from the same dataset, while WV and WS were also compared with in situ data. Geophysical calculations using simulated T b yielded relatively low retrieval and crosstalk errors when compared with modeled profiles; average CLW, WV, and WS root-mean-square deviations (RMSD) were 0.11 mm, 1.28 mm, and 1.11 m s−1, respectively, with median absolute deviations (MedAD) of 2.26 × 10−2 mm, 0.22 mm, and 0.55 m s−1, respectively. When applied to OLYMPEX/RADEX data, the new retrieval equations compared well with 1DVAR; CLW, WV, and WS RMSD were 9.95 × 10−2 mm, 2.00 mm, and 2.35 m s−1, respectively, and MedAD were 2.88 × 10−2 mm, 1.14 mm, and 1.82 m s−1, respectively. WV MedAD between the new equations and dropsondes were 2.10 and 1.80 mm at the time and location of minimum dropsonde altitude, respectively, while WS MedAD were 1.15 and 1.53 m s−1, respectively, further indicating the utility of these equations.

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