Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

Abstract

Latent heating profiles associated with three TOGA COARE active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the two-dimensional version of the Goddard Cumulus Ensemble (GCE) Model, and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm. The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/I), shipborne radars and the GCE model. Diagnostically determined latent heating profiles are calculated using 6 hourly soundings used for validation.The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that estimated by the GCE model and SSM/I in both December convective episodes. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but it is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50 % for December 19-27, 42 % for December 11-17 and 56 % for the February 9-13 case. These results are consistent with large-scale analyses. Accurate estimates of stratiform amount are needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20 %) than the radar for all three convective episodes. The SSM/I derived stratiform amount is about 37 % for December 19-27, 48 % for December 11-17 and 41 % for the February 9-13 case.Temporal variability of CSH algorithm retrieved latent heating profiles using either the GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile, and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good rainfall retrieval from SSM/I for a convective event can lead to a good latent heating retrieval.Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, agree well with those derived by soundings for the December 10-17 convective period.

Vertical Heating Structures Associated with the MJO as Characterized by TRMM Estimates, ECMWF Reanalyses, and Forecasts: A Case Study during 1998/99 Winter

“…The large rainfall amounts over these regions as shown in Fig. 1e are consistent with strong heating in the atmosphere, indicating dominant role of LH to the total Q 1 (e.g., Tao et al 1993a;Olson et al 1999). It is noted that the mean heating patterns in the two EC models bear larger amplitudes than those by TRMM estimates.…”

“…The two TRMM LH products employed in this study are based on ''trained'' radiometer heating (TRAIN; Grecu and Olson 2006;Grecu et al 2009) and the convective-stratiform heating (CSH; Tao et al 1993bTao et al , 2000Tao et al , 2001 algorithms. The former utilizes both TRMM precipitation radar (PR) and microwave imager (TMI), while the latter only uses the PR.…”

Effects of vertical wind shear and cloud radiative processes on responses of rainfall to the large‐scale forcing during pre‐summer heavy rainfall over southern China

“…Additional information like cloud contents, vertical motion, and the fall speed of precipitation particles has been also used in partitioning methods (e.g. Tao et al, , 2000Sui et al, 1994;Xu, 1995;Lang et al, 2003). Lang et al (2003) conducted a comparison study using six different partitioning methods based on surface rain-rate, mass fluxes, apparent heating and moistening, hydrometeor contents, reflectivity and vertical velocity CFAD (Contoured Frequency with Altitude Diagram), microphysics, and latent heat retrieval (Churchill and House, 1984;Caniaux et al, 1994;Steiner et al, 1995;Xu, 1995;Lang et al, 2003), and showed that the method based on surface rain-rate was consistently the most stratiform whereas the method based on radar information below the melting level and the fall speed of precipitation particles was consistently the most convective.…”

Effects of Vertical Wind Shear, Radiation, and Ice Clouds on Precipitation Distributions During a Landfall of Severe Tropical Storm, Bilis (2006)

“…Convectivestratiform rainfall partitioning schemes have been developed based on the amplitude and spatial variations of radar reflectivity or surface rainfall rate in previous studies (e.g., Churchill and Houze 1984;Caniaux et al 1994;Steiner et al 1995). Additional information such as the cloud mixing ratio, vertical motion, and fall speeds of precipitation particles have been also used in separation schemes (e.g., Tao et al , 2000Sui et al 1994;Xu 1995;Lang et al 2003). Thus, the convective-stratiform rainfall partition may introduce uncertainty.…”