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Masafumi Hirose, Yukari N. Takayabu, Atsushi Hamada, Shoichi Shige, and Munehisa K. Yamamoto

Abstract

Observations of the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) over 16 yr yielded hundreds of large precipitation systems (≥100 km) for each 0.1° grid over major rainy regions. More than 90% of the rainfall was attributed to large systems over certain midlatitude regions such as La Plata basin and the East China Sea. The accumulation of high-impact snapshots reduced the significant spatial fluctuation of the rain fraction arising from large systems and allowed the obtaining of sharp images of the geographic rainfall pattern. Widespread systems were undetected over low-rainfall areas such as regions off Peru. Conversely, infrequent large systems brought a significant percentage of rainfall over semiarid tropics such as the Sahel. This demonstrated an increased need for regional sampling of extreme phenomena. Differences in data collected over a period of 16 yr were used to examine sampling adequacy. The results indicated that more than 10% of the 0.1°-scale sampling error accounted for half of the TRMM domain even for a 10-yr data accumulation period. Rainfall at the 0.1° scale was negatively biased in the first few years for over more than half of the areas because of a lack of high-impact samples. The areal fraction of the 0.1°-scale climatology with a 50% accuracy exceeded 95% in the ninth year and in the fifth year for those areas with rainfall >2 mm day−1. A monotonic increase in the degree of similarity of finescale rainfall to the best estimate with an accuracy of 10% illustrated the need for further sampling.

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Kaya Kanemaru, Takuji Kubota, Toshio Iguchi, Yukari N. Takayabu, and Riko Oki

Abstract

Precipitation observation with the Tropical Rainfall Measuring Mission’s (TRMM’s) precipitation radar (PR) lasted for more than 17 years. To study the changes in the water and energy cycle related to interannual and decadal variabilities of climate, homogeneity of long-term PR data is essential. The aim of the study is to develop a precipitation climate record from the 17-yr PR observation. The focus was on mitigating the discontinuities associated with the switching to redundant electronics in the PR in June 2009. In version 7 of the level-1 PR product, a discontinuity in noise power is found at this timing, indicating a change in the signal-to-noise ratio. To mitigate the effect of this discontinuity on climate studies, the noise power of the B-side PR obtained after June 2009 is artificially increased to match that of the A-side PR. Simulation results show that the storm height and the precipitation frequency detected by the PR relatively decrease by 2.17% and 5.15% in the TRMM coverage area (35°S–35°N), respectively, and that the obvious discontinuity of the time series by the storm height and the precipitation fraction caused by the switching to the redundancy electronics is mitigated. Differences in the statistics of other precipitation parameters caused by the switching are also mitigated. The unconditional precipitation rate derived from the adjusted data obtained over the TRMM coverage area decreases by 0.90% as compared with that determined from the original data. This decrease is mainly caused by reductions in the detection of light precipitation.

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Nagio Hirota, Yukari N. Takayabu, Masahiro Watanabe, Masahide Kimoto, and Minoru Chikira

Abstract

The authors demonstrate that an appropriate treatment of convective entrainment is essential for determining spatial distributions of and temporal variations in precipitation. Four numerical experiments are performed using atmospheric models with different entrainment characteristics: a control experiment (Ctl), a no-entrainment experiment (NoEnt), an original Arakawa–Schubert experiment (AS), and an AS experiment with a simple empirical suppression of convection depending on cloud-layer humidity (ASRH). The fractional entrainment rates of AS and ASRH are constant for each cloud type and are very small in the lower troposphere compared with those in the Ctl, in which half of the buoyancy-generated energy is consumed by entrainment. Spatial and temporal variations in the observed precipitation are satisfactorily reproduced in the Ctl, but their amplitudes are underestimated with a so-called double intertropical convergence zone bias in the NoEnt and AS. The spatial variation is larger in the Ctl because convection is more active over humid ascending regions and more suppressed over dry subsidence regions. Feedback processes involving convection, the large-scale circulation, free tropospheric moistening by congestus, and radiation enhance the variations. The temporal evolution of precipitation events is also more realistic in the Ctl, because congestus moistens the midtroposphere, and large precipitation events occur once sufficient moisture is available. The large entrainment in the lower troposphere, increasing free tropospheric moistening by congestus and enhancing the coupling of convection to free tropospheric humidity, is suggested to be important for the realistic spatial and temporal variations.

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Gregory S. Elsaesser, Christian D. Kummerow, Tristan S. L’Ecuyer, Yukari N. Takayabu, and Shoichi Shige

Abstract

A K-means clustering algorithm was used to classify Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) scenes within 1° square patches over the tropical (15°S–15°N) oceans. Three cluster centroids or “regimes” that minimize the Euclidean distance metric in a five-dimensional space of standardized variables were sought [convective surface rainfall rate; ratio of convective rain to total rain; and fractions of convective echo profiles with tops in three fixed height ranges (<5, 5–9, and >9 km)]. Independent cluster computations in adjacent ocean basins return very similar clusters in terms of PR echo-top distributions, rainfall, and diabatic heating profiles. The clusters consist of shallow convection (SHAL cluster), with a unimodal distribution of PR echo tops and composite diabatic heating rates of ∼2 K day−1 below 3 km; midlevel convection (MID-LEV cluster), with a bimodal distribution of PR echo tops and ∼5 K day−1 heating up to about 7 km; and deeper convection (DEEP cluster), with a multimodal distribution of PR echo tops and >20 K day−1 heating from 5 to 10 km. Each contributes roughly 20%–40% in terms of total tropical rainfall, but with MID-LEV clusters especially enhanced in the Indian and Atlantic sectors, SHAL relatively enhanced in the central and east Pacific, and DEEP most prominent in the western Pacific. While the clusters themselves are quite similar in rainfall and heating, specific cloud types defined according to the PR echo top and surface rainfall rate are less similar and exhibit systematic differences from one cluster to another, implying that the degree to which precipitation structures are similar decreases when one considers individual precipitating clouds as repeating tropical structures instead of larger-scale cluster ensembles themselves.

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Shoichi Shige, Yukari N. Takayabu, Wei-Kuo Tao, and Daniel E. Johnson

Abstract

An algorithm, the spectral latent heating (SLH) algorithm, has been developed to estimate latent heating profiles for the Tropical Rainfall Measuring Mission precipitation radar with a cloud-resolving model (CRM). Heating-profile lookup tables for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were produced with numerical simulations of tropical cloud systems in the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. For convective and shallow stratiform regions, the lookup table refers to the precipitation-top height (PTH). For the anvil region, on the other hand, the lookup table refers to the precipitation rate at the melting level instead of PTH. A consistency check of the SLH algorithm was also done with the CRM-simulated outputs. The first advantage of this algorithm is that differences of heating profiles between the shallow convective stage and the deep convective stage can be retrieved. This is a result of the utilization of observed information, not only on precipitation type and intensity, but also on the precipitation depth. The second advantage is that heating profiles in the decaying stage with no surface rain can also be retrieved. This comes from utilization of the precipitation rate at the melting level for anvil regions.

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

Abstract

The spectral latent heating (SLH) algorithm was developed to estimate latent heating profiles for the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR). The method uses TRMM PR information (precipitation-top height, precipitation rates at the surface and melting level, and rain type) to select heating profiles from lookup tables (LUTs). LUTs for the three rain types—convective, shallow stratiform, and anvil rain (deep stratiform with a melting level)—were derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) using a cloud-resolving model (CRM).

The two-dimensional (2D) CRM was used in previous studies. The availability of exponentially increasing computer capabilities has resulted in three-dimensional (3D) CRM simulations for multiday periods becoming increasingly prevalent. In this study, LUTs from the 2D and 3D simulations are compared. Using the LUTs from 3D simulations results in less agreement between the SLH-retrieved heating and sounding-based heating for the South China Sea Monsoon Experiment (SCSMEX). The level of SLH-estimated maximum heating is lower than that of the sounding-derived maximum heating. This is explained by the fact that using the 3D LUTs results in stronger convective heating and weaker stratiform heating above the melting level than is the case if using the 2D LUTs. More condensate is generated in and carried from the convective region in the 3D model than in the 2D model, and less condensate is produced by the stratiform region’s own upward motion.

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Kazuaki Yasunaga, Kunio Yoneyama, Qoosaku Moteki, Mikiko Fujita, Yukari N. Takayabu, Junko Suzuki, Tomoki Ushiyama, and Brian Mapes

Abstract

A field observational campaign [i.e., the Mirai Indian Ocean cruise for the Study of the MJO-convection Onset (MISMO)] was conducted over the central equatorial Indian Ocean in October–December 2006. During MISMO, large-scale organized convection associated with a weak Madden–Julian oscillation (MJO) broke out, and some other notable variations were observed.

Water vapor and precipitation data show a prominent 3–4-day-period cycle associated with meridional wind υ variations. Filtered υ anomalies at midlevels in reanalysis data [i.e., the Japan Meteorological Agency (JMA) Climate Data Assimilation System (JCDAS)] show westward phase velocities, and the structure is consistent with mixed Rossby–gravity waves. Estimated equivalent depths are a few tens of meters, typical of convectively coupled waves. In the more rainy part of MISMO (16–26 November), the 3–4-day waves were coherent through the lower and midtroposphere, while in the less active early November period midlevel υ fluctuations appear less connected to those at the surface.

SST diurnal variations were enhanced in light-wind and clear conditions. These coincided with westerly anomalies in prominent 6–8-day zonal wind variations with a deep nearly barotropic structure through the troposphere. Westward propagation and structure of time-filtered winds suggest n = 1 equatorial Rossby waves, but with estimated equivalent depth greater than is common for convectively coupled waves, although sheared background flow complicates the estimation somewhat.

An ensemble reanalysis [i.e., the AGCM for the Earth Simulator (AFES) Local Ensemble Transform Kalman Filter (LETKF) Experimental Reanalysis (ALERA)] shows enhanced spread among the ensemble members in the zonal confluence phase of these deep Rossby waves, suggesting that assimilating them excites rapidly growing differences among ensemble members.

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Xianan Jiang, Duane E. Waliser, William S. Olson, Wei-Kuo Tao, Tristan S. L’Ecuyer, King-Fai Li, Yuk L. Yung, Shoichi Shige, Stephen Lang, and Yukari N. Takayabu

Abstract

Capitalizing on recently released reanalysis datasets and diabatic heating estimates based on Tropical Rainfall Measuring Mission (TRMM), the authors have conducted a composite analysis of vertical anomalous heating structures associated with the Madden–Julian oscillation (MJO). Because diabatic heating lies at the heart of prevailing MJO theories, the intention of this effort is to provide new insights into the fundamental physics of the MJO. However, some discrepancies in the composite vertical MJO heating profiles are noted among the datasets, particularly between three reanalyses and three TRMM estimates. A westward tilting with altitude in the vertical heating structure of the MJO is clearly evident during its eastward propagation based on three reanalysis datasets, which is particularly pronounced when the MJO migrates from the equatorial eastern Indian Ocean (EEIO) to the western Pacific (WP). In contrast, this vertical tilt in heating structure is not readily seen in the three TRMM products. Moreover, a transition from a shallow to deep heating structure associated with the MJO is clearly evident in a pressure–time plot over both the EEIO and WP in three reanalysis datasets. Although this vertical heating structure transition is detectable over the WP in two TRMM products, it is weakly defined in another dataset over the WP and in all three TRMM datasets over the EEIO.

The vertical structures of radiative heating QR associated with the MJO are also analyzed based on TRMM and two reanalysis datasets. A westward vertical tilt in QR is apparent in all these datasets: that is, the low-level QR is largely in phase of convection, whereas QR in the upper troposphere lags the maximum convection. The results also suggest a potentially important role of radiative heating for the MJO, particularly over the Indian Ocean. Caveats in heating estimates based on both the reanalysis datasets and TRMM are briefly discussed.

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

Abstract

Four Tropical Rainfall Measuring Mission (TRMM) datasets of latent heating were diagnosed for signals in the Madden–Julian oscillation (MJO). In all four datasets, vertical structures of latent heating are dominated by two components—one deep with its peak above the melting level and one shallow with its peak below. Profiles of the two components are nearly ubiquitous in longitude, allowing a separation of the vertical and zonal/temporal variations when the latitudinal dependence is not considered. All four datasets exhibit robust MJO spectral signals in the deep component as eastward propagating spectral peaks centered at a period of 50 days and zonal wavenumber 1, well distinguished from lower- and higher-frequency power and much stronger than the corresponding westward power. The shallow component shows similar but slightly less robust MJO spectral peaks. MJO signals were further extracted from a combination of bandpass (30–90 day) filtered deep and shallow components. Largest amplitudes of both deep and shallow components of the MJO are confined to the Indian and western Pacific Oceans. There is a local minimum in the deep components over the Maritime Continent. The shallow components of the MJO differ substantially among the four TRMM datasets in their detailed zonal distributions in the Eastern Hemisphere. In composites of the heating evolution through the life cycle of the MJO, the shallow components lead the deep ones in some datasets and at certain longitudes. In many respects, the four TRMM datasets agree well in their deep components, but not in their shallow components and in the phase relations between the deep and shallow components. These results indicate that caution must be exercised in applications of these latent heating data.

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