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  • Author or Editor: N. Prasad x
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Robert F. Adler
,
Robert A. Mack
,
N. Prasad
,
Ida M. Hakkarinen
, and
H-Y. M. Yeh

Abstract

Aircraft passive microwave observations of deep atmospheric convection at frequencies between 18 and 183 GHz are presented in conjunction with visible and infrared satellite and aircraft observations and ground-based radar observations. Deep convective cores are indicated in the microwave data by negative brightness temperature (TB ) deviations from the land background (270 K) to extreme TB values below 100 K at 37, 92, and 183 GHz and below 200 K at 18 GHz. These TB minima, due to scattering by ice held aloft by the intense updrafts, are well correlated with areas of high radar reflectivity. For this land background case, TB is inversely correlated with rain rate at all frequencies due to TB -ice-rain correlations. Mean ΔT between vertically polarized and horizontally polarized radiance in precipitation areas is approximately 6 K at both 18 GHz and 37 GHz, indicating nonspherical precipitation size ice particles with a preferred horizontal orientation. Convective cores not observed in the visible and infrared data are clearly defined in the microwave observations and borders of convective rain areas are well defined using the high-frequency (90 GHz and greater) microwave observations.

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Hwa-Young M. Yeh
,
N. Prasad
,
Robert A. Mack
, and
Robert F. Adler

Abstract

In Part II of the 29 June 1986 case study, a radiative transfer model is used to simulate the aircraft multichannel microwave brightness temperatures presented in Part I and to study the convective storm structure. Ground-based radar data are used to derive hydrometeor profiles of the storm, based on which the microwave upwelling brightness temperatures are calculated. Various vertical hydrometeor phase profiles and the Marshall and Palmer (M-P) and Sekhon and Srivastava (S-S) ice particle size distributions are experimented in the model. The results are compared with the aircraft radiometric data. The comparison reveals that 1) the M-P distribution well represents the ice particle size distribution, especially in the upper tropospheric portion of the cloud; 2) the S-S distribution appears to better simulate the ice particle size at the lower portion of the cloud, which has a greater effect on the low frequency microwave upwelling brightness temperatures; and 3) in deep convective regions, significant supercooled liquid water (∼0.5 g m−3) may be present up to the −30°C layer, while in less convective areas, frozen hydrometeors are predominant above −10°C level.

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R. Harikumar
,
N. K. Hithin
,
T. M. Balakrishnan Nair
,
P. Sirisha
,
B. Krishna Prasad
,
C. Jeyakumar
,
Shailesh Nayak
, and
S. S. C. Shenoi

Abstract

Ocean state forecast (OSF) along ship routes (OAS) is an advisory service of the Indian National Centre for Ocean Information Services (INCOIS) of the Earth System Science Organization (ESSO) that helps mariners to ensure safe navigation in the Indian Ocean in all seasons as well as in extreme conditions. As there are many users who solely depend on this service for their decision making, it is very important to ensure the reliability and accuracy of the service using the available in situ and satellite observations. This study evaluates the significant wave height (Hs) along the ship track in the Indian Ocean using the ship-mounted wave height meter (SWHM) on board the Oceanographic Research Vessel Sagar Nidhi, and the Cryosat-2 and Jason altimeters. Reliability of the SWHM is confirmed by comparing with collocated buoy and altimeter observations. The comparison along the ship routes using the SWHM shows very good agreement (correlation coefficient > 0.80) in all three oceanic regimes, [the tropical northern Indian Ocean (TNIO), the tropical southern Indian Ocean (TSIO), and extratropical southern Indian Ocean (ETSI)] with respect to the forecasts with a lead time of 48 h. However, the analysis shows ~10% overestimation of forecasted significant wave height in the low wave heights, especially in the TNIO. The forecast is found very reliable and accurate for the three regions during June–September with a higher correlation coefficient (average = 0.88) and a lower scatter index (average = 15%). During other months, overestimation (bias) of lower Hs is visible in the TNIO.

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