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Richard H. Johnson, Paul E. Ciesielski, Tristan S. L’Ecuyer, and Andrew J. Newman

function of height above sea level using a 0.5° resolution topographic dataset, and then averaged over the land and gulf portions of the EBA. d. Other data sources Surface winds over the GoC and the eastern Pacific are obtained from National Aeronautics and Space Administration (NASA) Quick Scatterometer (QuikSCAT), which provides wind estimates nominally twice per day at 25-km horizontal resolution ( Liu 2002 ). Precipitation estimates at 3-h intervals, 0.25° resolution are based on the TRMM 3B42v6

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Manuel D. Zuluaga, Carlos D. Hoyos, and Peter J. Webster

entire tropical band between 37°S and 37°N at 19 vertical levels from the surface to a height of 18 km with a 0.5° × 0.5° horizontal resolution at daily and monthly resolution. Base LUT profiles representing the vertical heating structure of convective, stratiform, and shallow precipitating systems over land and ocean were used to derive the CSH data in this study. CSH data using these base LUT profiles have been directly compared to observed heating estimates (S. Lang 2008, personal communication

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Yasu-Masa Kodama, Masaki Katsumata, Shuichi Mori, Sinsuke Satoh, Yuki Hirose, and Hiroaki Ueda

in the intensive observation period (IOP) of the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). Schumacher et al. (2007) noted that low-level (∼750 hPa) heating and mid- and upper-level cooling were frequently observed in Q1 atmospheric heat source profiles in the ITCZ over the central Pacific. Cooling was evaluated by heat and moisture budget analyses using aerological data from the Kwajalein Experiment. The low-level heating was maintained by

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Wei-Kuo Tao, Stephen Lang, Xiping Zeng, Shoichi Shige, and Yukari Takayabu

dominate the distribution in terms of occurrence. These results imply that there is a general relationship between rainfall intensity and stratiform amount, one that might be used to help formulate a retrieval algorithm. There are, however, differences in the probability distributions between oceanic and land regions. These differences are mainly in the highly convective region. For highly convective rain, both the peak occurrence and the tail of the distribution containing the extreme rainfall rates

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Tristan S. L’Ecuyer and Greg McGarragh

HERB 2008 can be found in LS03 . The HERB algorithm has recently undergone significant refinements to improve its accuracy and extend its range of applicability. The most significant of these is the extension of the algorithm to land surfaces, using a model of visible albedo and infrared emissivity that represents the characteristics of 20 different land surface types identified in the International Geosphere/Biosphere Programme (IGBP) land surface classification. A complete description of these

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Yukari N. Takayabu, Shoichi Shige, Wei-Kuo Tao, and Nagio Hirota

Project (JRA25) data and the Japanese Climate Data Assimilation System (JCDAS); and for SST we used the National Oceanic and Atmospheric Administration (NOAA) optimum interpolation (OI) SST data. The analysis period is 8 yr from 1998 to 2005. 3. Q 1 − Q R versus SST Eight-year unconditional mean Q 1 − Q R profiles averaged for 30°N–30°S at all longitudes are depicted in Fig. 1 , separately for over the ocean and over land. Two peaks in the convective heating at ∼5 and ∼2 km are apparent over

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Shoichi Shige, Yukari N. Takayabu, Satoshi Kida, Wei-Kuo Tao, Xiping Zeng, Chie Yokoyama, and Tristan L’Ecuyer

Ciesielski (2002) but is more bottom heavy, probably because of different analysis domains. Note that the SLH-retrieved Q 1 Rp profiles are not the same as in Part II , because the LUTs in this study are not the same as in Part II . Differences in heights above sea level over land (i.e., terrain) are also taken into account by the SLH algorithm used in this study. As pointed out in Part II , key features of the vertical profiles agree well, particularly the level of maximum heating. In the tropics

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Shaocheng Xie, Timothy Hume, Christian Jakob, Stephen A. Klein, Renata B. McCoy, and Minghua Zhang

radiative and turbulent fluxes, a weighted average was applied to the data collected from the limited number of surface flux sites. The weights used in computing the area mean of the surface radiative fluxes were based on the land and ocean fraction within the analysis domain, 0.57 and 0.43, respectively. For the sensible and latent heat fluxes, the weights for data collected at each site (i.e., Darwin Harbour, Fogg Dam, Howard Springs, Daly River, and the ship) were guided by the frequencies of the

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T. N. Krishnamurti, Arindam Chakraborty, and A. K. Mishra

–Atmosphere Response Experiment (TOGA COARE) and Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) events. Lau et al. (2000) and Johnson and Ciesielski (2002) have pioneered examining vertical distribution of heating using field experiment datasets, especially those from South China Sea Monsoon Experiment (SCSMEX). Yuter et al. (2005) have studied the diurnal change of latent heating within the context of the Tropical Rainfall Measuring Mission (TRMM) Kwajalein Experiment (KWAJEX

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Mircea Grecu, William S. Olson, Chung-Lin Shie, Tristan S. L’Ecuyer, and Wei-Kuo Tao

of heating profiles over land, although much more difficult from passive microwave radiometry due to the reduced precipitation signal, must also be considered if the atmospheric energy budget is to be “closed.” Because land regions tend to be rich in data relative to ocean regions, large-scale analyses of pressure, temperature, humidity, and winds could be adjusted using satellite passive microwave and visible–infrared estimates of water and energy fluxes to provide improved estimates of diabatic

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