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

Abstract

Three-dimensional distributions of the apparent heat source (Q 1) − radiative heating (QR) estimated from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) utilizing the spectral latent heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated Q 1QR averaged over the tropical oceans is estimated as ∼72.6 J s−1 (∼2.51 mm day−1) and that over tropical land is ∼73.7 J s−1 (∼2.55 mm day−1) for 30°N–30°S. It is shown that nondrizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems: deep systems and congestus. A rough estimate of the shallow-heating contribution against the total heating is about 46.7% for the average tropical oceans, which is substantially larger than the 23.7% over tropical land.

Although cumulus congestus heating linearly correlates with SST, deep-mode heating is dynamically bounded by large-scale subsidence. It is notable that a substantial amount of rain, as large as 2.38 mm day−1 on average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that, even in the region with SSTs warmer than 28°C, large-scale subsidence effectively suppresses the deep convection, with the remaining heating by congestus clouds.

The results support that the entrainment of mid–lower-tropospheric dry air, which accompanies the large-scale subsidence, is the major factor suppressing the deep convection. Therefore, a representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and the resultant large-scale circulation.

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

Abstract

Information from the Tropical Rainfall Measuring Mission (TRMM) level 3 monthly 0.5° × 0.5° Convective and Stratiform Heating (CSH) product and TRMM Microwave Imager (TMI) 2A12 datasets is used to examine the four-dimensional latent heating (LH) structure over the Asian monsoon region between 1998 and 2006. High sea surface temperatures, ocean–land contrasts, and complex terrain produce large precipitation and atmospheric heating rates whose spatial and temporal characteristics are relatively undocumented. Analyses show interannual and intraseasonal LH variations with a large fraction of the interannual variability induced by internal intraseasonal variability. Also, the analyses identify a spatial dipole of LH anomalies between the equatorial Indian Ocean and the Bay of Bengal regions occurring during the summer active and suppressed phases of the monsoon intraseasonal oscillation. Comparisons made between the TRMM CSH and TMI 2A12 datasets indicate differences in the shape of the vertical profile of LH. A comparison of TRMM LH retrievals with sounding budget observations made during the South China Sea Monsoon Experiment shows a high correspondence in the timing of positive LH episodes during the rainy periods. Negative values of atmospheric heating, associated with radiative cooling and with upper-tropospheric cooling from nonsurface-precipitating clouds, are not captured by either of the TRMM datasets. In summary, LH algorithms based on satellite information are capable of representing the spatial and temporal characteristics of the vertically integrated heating in the Asian monsoon region. However, the vertical distribution of atmospheric heating is not captured accurately throughout different convective phases. It is suggested that satellite-derived radiative heating/cooling products are needed to supplement the LH products in order to give a better overall depiction of atmospheric heating.

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

Abstract

The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate–high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.5° horizontal resolution, the occurrence of conditional rain rates over 100 mm day−1 is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations.

An improved convective–stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.

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

Abstract

The diurnal cycle of summer monsoon convection in the coastal, mountainous region of northwestern Mexico is investigated using data from the 2004 North American Monsoon Experiment (NAME). Data from a special sounding network consisting of research and operational sites have been quality controlled and combined with surface, wind profiler, and pibal observations to create a gridded dataset over the NAME domain. This study concentrates on results from the interior portion of the NAME sounding network, where gridded analysis fields are independent of model data. Special attention is given to surface and pibal observations along the western slope of the Sierra Madre Occidental (SMO) in order to obtain an optimal analysis of the diurnally varying slope flows.

Results show a prominent sea-breeze–land-breeze cycle along the western slopes of the SMO. There is a deep return flow above the afternoon sea breeze as a consequence of the elevated SMO immediately to the east. The upslope flow along the western slope of the SMO is delayed until late morning, likely in response to early morning low clouds over the SMO crest and reduced morning insolation over the west-facing slopes. The diurnal cycle of the net radiative heating rate is characterized by a net cooling during most of the daytime except for net heating in the lower and upper troposphere at midday. The diurnal cycle of the apparent heat source Q 1 minus the radiative heating rate QR (providing a measure of net condensational heating) and the apparent moisture sink Q 2 over the SMO is indicative of shallow convection around noon, deep convection at 1800 LT, evolving to stratiform precipitation by midnight, consistent with the radar-observed diurnal evolution of precipitation over this coastal mountainous region as well as the typical evolution of tropical convective systems across a wide range of spatial and temporal scales. Convection over the Gulf of California is strikingly different from that over land, namely, heating and moistening are confined principally to the lower troposphere below 700 hPa, peaking during the nighttime hours.

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

Abstract

Recently the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) project office made available a new product called the convective–stratiform heating (CSH). These are the datasets for vertical profiles of diabatic heating rates (the apparent heat source). These observed estimates of heating are obtained from the TRMM satellite’s microwave radiances and the precipitation radar. The importance of such datasets for defining the vertical distribution of heating was largely the initiative of Dr. W.-K. Tao from NASA’s Goddard Laboratory. The need to examine how well some of the current cumulus parameterization schemes perform toward describing the amplitude and the three-dimensional distributions of heating is addressed in this paper. Three versions of the Florida State University (FSU) global atmospheric model are run that utilize different versions of cumulus parameterization schemes; namely, modified Kuo parameterization, simple Arakawa–Schubert parameterization, and Zhang–McFarlane parameterization. The Kuo-type scheme used here relies on moisture convergence and tends to overestimate the rainfall generally compared to the TRMM estimates. The other schemes used here show only a slight overestimate of rain rates compared to TRMM; those invoke mass fluxes that are less stringent in this regard in defining cloud volumes. The mass flux schemes do carry out a total moisture budget for a vertical column model and include all components of the moisture budget and are not limited to the horizontal convergence of moisture. The authors carry out a numerical experimentation that includes over a hundred experiments from each of these models; these experiments differ only in their use of the cumulus parameterization. The rest of the model physics, resolution, and initial states are kept the same for each set of 117 forecasts. The strategy for this experimentation follows the authors’ previous studies with the FSU multimodel superensemble. This includes a 100-day training and a 17-day forecast phase, both of which include a large number of forecast experiments. The training phase provides a useful statistical database for tagging the systematic errors of the respective models. The forecast phase is designed to minimize the collective bias errors of these member models. In these forecasts the authors also include the ensemble mean and the multimodel superensemble. In this paper the authors examine model errors in their representations of the heating (amplitude, vertical level of maximum, and the geographical distributions). The main message of this study is that some cumulus parameterization schemes overestimate the amplitude of heating, whereas others carry lower values. The models also exhibit large errors in the placement of the vertical level of maximum heating. Some significant errors were also found in the geographical distributions of heating. The ensemble mean largely mimics the model features and also carries some large errors. The superensemble is more selective in reducing the three-dimensional collective bias errors of the models and provides the best short range forecasts, through hour 60, for the heating. This study shows that it is possible to diagnose some of the modeling errors in the heating for individual member models and that information can be important for correcting such features.

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Tristan S. L’Ecuyer and Greg McGarragh

Abstract

This paper outlines recent advances in estimating atmospheric radiative heating rate profiles from the sensors aboard the Tropical Rainfall Measuring Mission (TRMM). The approach employs a deterministic framework in which four distinct retrievals of clouds, precipitation, and other atmospheric and surface properties are combined to form input to a broadband radiative transfer model that simulates profiles of upwelling and downwelling longwave and shortwave radiative fluxes in the atmosphere. Monthly, 5° top of the atmosphere outgoing longwave and shortwave flux estimates agree with corresponding observations from the Clouds and the Earth’s Radiant Energy System (CERES) to within 7 W m−2 and 3%, respectively, suggesting that the resulting products can be thought of as extending the eight-month CERES dataset to cover the full lifetime of TRMM.

The analysis of a decade of TRMM data provides a baseline climatology of the vertical structure of atmospheric radiative heating in today’s climate and an estimate of the magnitude of its response to environmental forcings on weekly to interannual time scales. In addition to illustrating the scope and properties of the dataset, the results highlight the strong influence of clouds, water vapor, and large-scale dynamics on regional radiation budgets and the vertical structure of radiative heating in the tropical and subtropical atmospheres. The combination of the radiative heating rate product described here, with profiles of latent heating that are now also being generated from TRMM sensors, provides a unique opportunity to develop large-scale estimates of vertically resolved atmospheric diabatic heating using satellite observations.

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K-M. Lau and H-T. Wu

Abstract

This study investigates the evolution of cloud and rainfall structures associated with Madden–Julian oscillation (MJO) using Tropical Rainfall Measuring Mission (TRMM) data. Two complementary indices are used to define MJO phases. Joint probability distribution functions (PDFs) of cloud-top temperature and radar echo-top height are constructed for each of the eight MJO phases. The genesis stage of MJO convection over the western Pacific (phases 1 and 2) features a bottom-heavy PDF, characterized by abundant warm rain, low clouds, suppressed deep convection, and higher sea surface temperature (SST). As MJO convection develops (phases 3 and 4), a transition from the bottom-heavy to top-heavy PDF occurs. The latter is associated with the development of mixed-phase rain and middle-to-high clouds, coupled with rapid SST cooling. At the MJO convection peak (phase 5), a top-heavy PDF contributed by deep convection with mixed-phase and ice-phase rain and high echo-top heights (>5 km) dominates. The decaying stage (phases 6 and 7) is characterized by suppressed SST, reduced total rain, increased contribution from stratiform rain, and increased nonraining high clouds. Phase 7, in particular, signals the beginning of a return to higher SST and increased warm rain. Phase 8 completes the MJO cycle, returning to a bottom-heavy PDF and SST conditions similar to phase 1. The structural changes in rain and clouds at different phases of MJO are consistent with corresponding changes in derived latent heating profiles, suggesting the importance of a diverse mix of warm, mixed-phase, and ice-phase rain associated with low-level, congestus, and high clouds in constituting the life cycle and the time scales of MJO.

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Samson Hagos, Chidong Zhang, Wei-Kuo Tao, Steve Lang, Yukari N. Takayabu, Shoichi Shige, Masaki Katsumata, Bill Olson, and Tristan L’Ecuyer

Abstract

This study aims to evaluate the consistency and discrepancies in estimates of diabatic heating profiles associated with precipitation based on satellite observations and microphysics and those derived from the thermodynamics of the large-scale environment. It presents a survey of diabatic heating profile estimates from four Tropical Rainfall Measuring Mission (TRMM) products, four global reanalyses, and in situ sounding measurements from eight field campaigns at various tropical locations. Common in most of the estimates are the following: (i) bottom-heavy profiles, ubiquitous over the oceans, are associated with relatively low rain rates, while top-heavy profiles are generally associated with high rain rates; (ii) temporal variability of latent heating profiles is dominated by two modes, a deep mode with a peak in the upper troposphere and a shallow mode with a low-level peak; and (iii) the structure of the deep modes is almost the same in different estimates and different regions in the tropics. The primary uncertainty is in the amount of shallow heating over the tropical oceans, which differs substantially among the estimates.

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

Abstract

This study documents the characteristics of the large-scale structures and diabatic heating and drying profiles observed during the Tropical Warm Pool–International Cloud Experiment (TWP-ICE), which was conducted in January–February 2006 in Darwin during the northern Australian monsoon season. The examined profiles exhibit significant variations between four distinct synoptic regimes that were observed during the experiment. The active monsoon period is characterized by strong upward motion and large advective cooling and moistening throughout the entire troposphere, while the suppressed and clear periods are dominated by moderate midlevel subsidence and significant low- to midlevel drying through horizontal advection. The midlevel subsidence and horizontal dry advection are largely responsible for the dry midtroposphere observed during the suppressed period and limit the growth of clouds to low levels. During the break period, upward motion and advective cooling and moistening located primarily at midlevels dominate together with weak advective warming and drying (mainly from horizontal advection) at low levels. The variations of the diabatic heating and drying profiles with the different regimes are closely associated with differences in the large-scale structures, cloud types, and rainfall rates between the regimes. Strong diabatic heating and drying are seen throughout the troposphere during the active monsoon period while they are moderate and only occur above 700 hPa during the break period. The diabatic heating and drying tend to have their maxima at low levels during the suppressed periods. The diurnal variations of these structures between monsoon systems, continental/coastal, and tropical inland-initiated convective systems are also examined.

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

Abstract

In this study, satellite passive microwave sensor observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q 1QR) where Q 1 is the apparent heat source and QR is the radiative heating rate in regions of precipitation. The TMI heating algorithm (herein called TRAIN) is calibrated or “trained” using relatively accurate estimates of heating based on spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based on a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically integrated condensation and surface precipitation.

Estimates of Q 1QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q 1 produced by combining TMI Q 1QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q 1 from two field campaigns, although the satellite estimates exhibit heating profile structures with sharper and more intense heating peaks than the rawinsonde estimates.

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