Abstract The Tropical Rainfall Measuring Mission (TRMM) Kwajalein Experiment (KWAJEX) was designed to obtain an empirical physical characterization of precipitating convective clouds over the tropical ocean. Coordinated datasets were collected by three aircraft, one ship, five upper-air sounding sites, and a variety of continuously recording remote and in situ surface-based sensors, including scanning Doppler radars, profilers, disdrometers, and rain gauges. This paper describes the physical characterization of the Kwajalein cloud population that has emerged from analyses of datasets that were obtained during KWAJEX and combined with long-term TRMM ground validation site observations encompassing three rainy seasons. The spatial and temporal dimensions of the precipitation entities exhibit a lognormal probability distribution, as has been observed over other parts of the tropical ocean. The diurnal cycle of the convection is also generally similar to that seen over other tropical oceans. The largest precipitating cloud elements—those with rain areas exceeding 14 000 km2—have the most pronounced diurnal cycle, with a maximum frequency of occurrence before dawn; the smallest rain areas are most frequent in the afternoon. The large systems exhibited stratiform rain areas juxtaposed with convective regions. Frequency distributions of dual-Doppler radar data showed narrow versus broad spectra of divergence in the stratiform and convective regions, respectively, as expected because strong up- and downdrafts are absent in the stratiform regions. The dual-Doppler profiles consistently showed low-level convergence and upper-level divergence in convective regions and midlevel convergence sandwiched between lower- and upper-level divergence in stratiform regions. However, the magnitudes of divergence are sensitive to assumptions made in classifying the radar echoes as convective or stratiform. This sensitivity implies that heating profiles derived from satellite radar data will be sensitive to the details of the scheme used to separate convective and stratiform rain areas. Comparison of airborne passive microwave data with ground-based radar data indicates that the pattern of scattering of 85-GHz radiance by ice particles in the upper portions of KWAJEX precipitating clouds is poorly correlated with the precipitation pattern at lower levels while the emission channels (10 and 19 GHz) have brightness temperature patterns that closely correspond to the lower-level precipitation structure. In situ ice particle imagery obtained by aircraft at upper levels (∼11 km) shows that the concentrations of ice particles of all densities are greater in the upper portions of active convective rain regions and lower in the upper portions of stratiform regions, probably because the active updrafts convey the particles to upper levels, whereas in the stratiform regions sedimentation removes the larger ice particles over time. Low-level aircraft flying in the rain layer show similar total drop concentrations in and out of convective cells, but they also show a sudden jump in the concentration of larger raindrops at the boundaries of the cells, indicating a discontinuity in growth processes such as coalescence at the cell boundary.
This paper presents an overview of the results from the first major mesoscale atmospheric campaign of the Large‐Scale Biosphere‐Atmosphere Experiment in Amazonia (LBA) Program. The campaign, collocated with a Tropical Rainfall Measuring Mission (TRMM) satellite validation campaigns, was conducted in southwest Rondônia in January and February 1999 during the wet season. Highlights on the interaction between clouds, rain, and the underlying landscape through biospheric processes are presented and discussed.
Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (mu) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a mu of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing mu to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.
Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists—in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems—to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.
There are some interesting day versus night differences in the water vapor and carbon monoxide concentrations near the tropopause over tropical land and ocean from 4 years of EOS Microwave Limb Sounder (MLS) observations. To interpret these differences, the diurnal cycle of deep convection reaching near tropical tropopause summarized from a decade of tropical rainfall measuring mission (TRMM) observations. We also present the diurnal cycle of the cold point tropopause temperature and height derived from 2 years of constellation observing system for meteorology ionosphere and climate (COSMIC) GPS temperature profiles, the day versus night differences of occurrence of thin clouds from 2 years of cloud‐aerosol lidar and infrared pathfinder satellite observations (CALIPSO) and 16 years of stratospheric aerosol and gaseous experiment (SAGE) II. In the tropical upper troposphere, day versus night differences of water vapor and carbon monoxide are consistent with the diurnal cycle of the vertical transport of water vapor and carbon monoxide–rich air from the surface by deep convection. However, in the tropical tropopause layer (TTL) over land, day versus night differences of water vapor concentration are more consistent with the diurnal variations of temperature in a saturated TTL, which is related to the diurnal cycle of cooling in the TTL induced by deep convection. The day versus night differences of occurrences of thin clouds in the TTL are also consistent with the freeze drying, controlled by the diurnal cycles of temperature in the TTL.
Abstract With 15 yr of the Tropical Rainfall Measuring Mission (TRMM) observations, the passive microwave radiometers [TRMM Microwave Imager (TMI)] and the precipitation radar (PR) report a close geographical distribution of annual precipitation between 36°S and 36°N. However, large discrepancies between PR and TMI precipitation retrievals are also found over several specific regions, such as central Africa, the Amazon, the tropical east Pacific, and north Indian Ocean. To understand these discrepancies, the PR near-surface and the TMI surface precipitation retrievals are compared at both pixel and precipitation system levels using collocated pixels and a precipitation feature database from 1998 to 2012. Over land, the TMI overestimates precipitation in deep and intense convective systems, but misses significant amounts of warm rainfall in shallow systems. Over the ocean, because of the partial beam filling of large footprints of the lower-frequency sensors, the TMI reports a larger precipitation area than the PR and underestimates the precipitation rate in the convective precipitation region. The TMI tends to overestimate precipitation compared to the PR in a large proportion of shallow systems over the tropical east Pacific and trade wind regions with large-scale descent. The PR tends to overestimate precipitation compared to the TMI in a large proportion of shallow systems over rainy oceans, such as the west Pacific and the Atlantic ITCZ. All these findings imply that there are still large uncertainties in the precipitation climatology over some regions. Further ground validation campaigns are still needed, especially over the ocean.
High-resolution passive microwave observations within the stratiform regions of two different tropical oceanic mesoscale convective systems are investigated in detail. The observations were obtained from the Advanced Microwave Precipitation Radiometer (AMPR) during the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The AMPR records data at 10.7, 19.35, 37.1, and 85.5 GHz. Data collected during one ER-2 leg over the stratiform regions of each system are examined in detail. (Each leg is well coordinated with the low-flying WP-3s.) The passive microwave observations of the two stratiform regions, with similar surface rain rates, are found to differ significantly from one another. The average 85.5-GHz brightness temperature was 30 K colder on 22 February compared with 20 February. This greater ice scattering on 22 February is found to be consistent with the simultaneous radar reflectivity profile, which shows that upper-level reflectivities are greater through a deep layer. This and comparison of the two meteorological situations suggest a more recent injection of ice particles from the adjacent active convection region on 22 February, and demonstrate that the 85.5-GHz temperatures are sensitive to these differences. The 19.35- and 37.1-GHZ brightness temperatures were somewhat higher for a given 10.7-GHz temperature an 20 February. That system has a stronger bright band, and higher radar reflectivities below the melting level, suggesting greater vertically integrated rain water content. The radar reflectivities on 20 February decreased markedly with distance below the melting level, implying that a greater proportion of the rain evaporated. It is suggested that the brightness temperatures of the three lower frequencies were somewhat sensitive to these differences in the vertical distribution of precipitation within the rain layer between the two cases. Indications are that many of the differences between these two stratiform regions on these two days result from differences in their stage of evolution. At the time the detailed analyses were made for the 20 February case, the stratiform region had more time to mature compared with the newly formed stratiform region sampled on 22 February.
Abstract The long-standing mainstay of support for C. T. R. Wilson’s global circuit hypothesis is the similarity between the diurnal variation of thunderstorm days in universal time and the Carnegie curve of electrical potential gradient. This rough agreement has sustained the widespread view that thunderstorms are the “batteries” for the global electrical circuit. This study utilizes 10 years of Tropical Rainfall Measuring Mission (TRMM) observations to quantify the global occurrence of thunderstorms with much better accuracy and to validate the comparison by F. J. W. Whipple 80 years ago. The results support Wilson’s original ideas that both thunderstorms and electrified shower clouds contribute to the DC global circuit by virtue of negative charge carried downward by precipitation. First, the precipitation features (PFs) are defined by grouping the pixels with rain using 10 years of TRMM observations. Thunderstorms are identified from these PFs with lightning flashes observed by the Lightning Imaging Sensor. PFs without lightning flashes but with a 30-dBZ radar echo-top temperature lower than −10°C over land and −17°C over ocean are selected as possibly electrified shower clouds. The universal diurnal variation of rainfall, the raining area from the thunderstorms, and possibly electrified shower clouds in different seasons are derived and compared with the diurnal variations of the electric field observed at Vostok, Antarctica. The result shows a substantially better match from the updated diurnal variations of the thunderstorm area to the Carnegie curve than Whipple showed. However, to fully understand and quantify the amount of negative charge carried downward by precipitation in electrified storms, more observations of precipitation current in different types of electrified shower clouds are required.
Abstract Latent heating (LH) from precipitation systems with different sizes, depths, and convective intensities is quantified with 15 years of LH retrievals from version 7 Precipitation Radar (PR) products of the Tropical Rainfall Measuring Mission (TRMM). Organized precipitation systems, such as mesoscale convective systems (MCSs; precipitation area > 2000 km2), contribute to 88% of the LH above 7 km over tropical land and 95% over tropical oceans. LH over tropical land is mainly from convective precipitation, and has one vertical mode with a peak from 4 to 7 km. There are two vertical modes of LH over tropical oceans. The shallow mode from about 1 to 4 km results from small, shallow, and weak precipitation systems, and partially from congestus clouds with radar echo top between 5 and 8 km. The deep mode from 5 to 9 km is mainly from stratiform precipitation in MCSs. MCSs of different regions and seasons have different LH vertical structure mainly due to the different proportion of stratiform precipitation. MCSs over ocean have a larger fraction of stratiform precipitation and a top-heavy LH structure. MCSs over land have a higher percentage of convective versus stratiform precipitation, which results in a relatively lower-level peak in LH compared to MCSs over the ocean. MCSs during monsoons have properties of LH in between those typical land and oceanic MCSs. Consistent with the diurnal variation of precipitation, tropical land has a stronger LH diurnal variation than tropical oceans with peak LH in the late afternoon. Over tropical oceans in the early morning, the shallow mode of LH peaks slightly earlier than the deep mode. There are almost no diurnal changes of MCSs LH over oceans. However, the small convective systems over land contribute a significant amount of LH at all vertical levels in the afternoon, when the contribution of MCSs is small.
