The Impact of the Ice Phase and Radiation on a Midlatitude Squall Line System

Chin, H S

doi:10.1175/1520-0469(1994)051<3320:tiotip>2.0.co;2

Cited by 33 publications

(24 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The presence of this amount of cloud water is a good indication of a saturated area (100 % Relative humidity). This method has been adapted by Chin (1994), Cotton (personal communication) and Redelsperger et al (1999).…”

Section: Goddard Cumulus Ensemble (Gce) Modelmentioning

confidence: 99%

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

Tao

Lang

Simpson

et al. 2000

Journal of the Meteorological Society of Japan

View full text Add to dashboard Cite

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.

show abstract

Section: Goddard Cumulus Ensemble (Gce) Modelmentioning

confidence: 99%

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

Tao

Lang

Simpson

et al. 2000

Journal of the Meteorological Society of Japan

View full text Add to dashboard Cite

show abstract

“…A version of that scheme that has been modified to account for the interaction of the microphysics with radiative transfer (Chin, 1994) is used to replace the original scheme. Following Chin (1994), the optical depth ( τ ), single scattering albedo (ω ) and asymmetry factor (g) are defined as:…”

Section: B Radiationmentioning

confidence: 99%

Using NORAPS for forecasting heavy precipitation with topographic forcing

Kong¹,

Leach²

1997

View full text Add to dashboard Cite

“…While the basic spatial distribution is similar to the simple condensation scheme, the amounts are less by a factor of 2 to 3 and are more realistic and closer to the observed values. In addition to the Rutledge and Hobbs microphysical scheme, Chin's scheme (Chin 1994, Chin et al 1995) is available for use in NORAPS. This scheme has been used to simulate both midlatitude and tropical squall-line systems with prominent anvils and radar-observable mesoscale structures, such as bright melting bands and transition zones.…”

Section: New Physics Capabilities and Their Application To A Major Camentioning

confidence: 99%

“…The modified Harshvardhan (1987) long-and shortwave radiation transfer schemes (Chin 1994;Chin et al 1995) were implemented in NORAPS, and preliminary testing was completed. Realistic treatment of radiative transfer is important to get the three dimensional heating, resulting in the proper storm structure.…”

Section: New Physics Capabilities and Their Application To A Major Camentioning

confidence: 99%

“…A benchmark solution for the squall-line system was produced using Chin's nonhydrostatic cloud model (Chin 1989;Chin 1994;Chin et al 1995;Chin and Wilhelmson 1996) with an explicit ice microphysics scheme. Then the hybrid cloud parameterization (the Emanuel cumulus scheme and Chin's mesoscale version of a bulk microphysics scheme) was used in Chin's 2-D nonhydrostatic mesoscale model, and its performance was evaluated by comparison with results from the explicit cloud model.…”

Section: An Examination Of Hybrid Cloud Parameterization Schemesmentioning

confidence: 99%

See 1 more Smart Citation