Tropical Rainfall Measuring Mission Precipitation Radar Data Research Articles

Twice‐Daily Monsoon Precipitation Maxima in the Himalayas Driven by Land Surface Effects

AbstractThe diurnal cycle of precipitation is important to the hydroclimate in the Himalayas in summer; however, features of the diurnal cycle that affect precipitation from the foothills to glacierized, high‐elevation areas are poorly understood. We investigated the diurnal cycle of precipitation using 3 years of in situ observations recorded close to a glacier at 4,806 m asl, and 17 years of data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the Integrated Multi‐satellitE Retrieval for Global Precipitation Measurement (IMERG). The mechanisms that drive the diurnal cycle were examined using hourly European Center for Medium‐Range Weather Forecasts Re‐Analysis fifth generation (ERA5) data. In situ observations showed that the diurnal precipitation cycle has daytime and nighttime peaks, which both consist of high rainfall frequency and low rainfall intensity. In addition, twice‐daily maxima exist in the TRMM PR data, particularly over two rain bands at around 500–1,000 m asl, and at ∼2,000 m asl. Convective‐type rainfall, with a lower rain‐top height, occurs in the daytime, whereas stratiform‐type rain, with a higher rain‐top height, occurs at night, particularly over terrain at elevations above ∼1,500 m asl. Land surface processes likely cause the two peaks in the diurnal cycle. Daytime surface heating drives upslope flows that promote condensation. At night, surface cooling over the plain to the south of the Himalayas causes low‐level monsoon flows to accelerate, creating a nocturnal jet, which results in large‐scale moisture flux convergence over the southern slopes.

A concise comparison of two rainfall onset definitions using convective properties derived from TRMM precipitation radar data

Most rainfall onset definitions in West Africa were estimated using station-based data. These data and hence the rainfall onset definitions may, however, not be a good representative for the entire climatic zone of the station. Based on existing definitions, a new rainfall onset definition is developed from the Tropical Rainfall Measurement Mission 3B42 gridded rainfall observations. 16 years of data were analyzed, which were taken between mid-April to mid-July over rainforest zones (west coast rainforest, dry rainforest and Nigeria–Cameroon rainforest) and between mid-May to mid-August over savannah zones (Nigeria savannah, and “Central African and South Sudan savannah”). While both definitions yield rather similar results in west coast rainforest, Nigeria–Cameroon rainforest and Nigeria savannah zones; results differ, however, substantially over dry rainforest and the Central African and South Sudan savannah. The new onset definition is further justified using an event-based analysis of mesoscale convective systems, flash counts and other convective parameters. Results have proved the new onset definition to be reliable and relevant for applications in agricultural productivity.

Studies of General Precipitation Features with TRMM PR Data: An Extensive Overview

The Precipitation Radar (PR), the first space-borne precipitation radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, could observe three-dimensional precipitation in global tropical regions and acquire continuous rainfall information with moderate temporal and high spatial resolutions. TRMM PR had carried out 17 years of observations and ended collecting data in April, 2015. So far, comprehensive and abundant research results related to the application of PR data have been analyzed in the current literature, but overall precipitation features are not yet identified, a gap that this review intends to fill. Studies on comparisons with ground-based radars and rain gauges are first introduced to summarize the reliability of PR observations or estimates. Then, this paper focuses on general precipitation features abstracted from about 130 studies, from 2000 to 2018, regarding lightning analysis, latent heat retrieval, and rainfall observation by PR data. Finally, we describe the existing problems and limitations as well as the future prospects of the space-borne precipitation radar data.

Preliminary Study of Nocturnal Rainfall Mechanism over Semi Closed Equatorial Oceans as observed by TRMM-PR

Relation of shape and size of coastal line to coastal rainfall mechanism over Indonesian Maritime Continent (IMC) is not clearly understood. Cendrawasih Bay is a unique coastal line because it is the biggest curvature type in IMC, near equatorial lines and semi-closed oceans. The mechanism of nocturnal rainfall over Cendrawasih Bay has been studied using data from Tropical Rainfall Measuring Mission Precipitation Radar (TRMM-PR) 3B42 product over during 1998–2015. Correlation coefficient of TRMM-PR and observational data from Biak Meteorological Station in 2014 is 0.6. Composite TRMM-PR data showed that nocturnal rainfall over the Cendrawasih Bay began to form at midnight and has peak intensity after midnight. Rain rate intensity over the Cendrawasih Bay is bigger than over inland and adjacent waters with speed of rainfall migration is approximately 5 m/s. Northern monsoon flows and land breeze along curvature coast induced low level convergence over Cendrawasih Bay during late evening until morning.

Climatology of contribution‐weighted tropical rain rates based on TRMM 3B42

AbstractThe climatology of annual mean tropical rain rate is investigated based on merged Tropical Rainfall Measuring Mission (TRMM) 3B42 data. At 0.25° × 0.25° spatial resolution, and 3‐hourly temporal resolution, half the rain is concentrated within only ∼1% of the area of the tropics at any given instant. When plotted as a function of logarithm of rain rate, the cumulative contribution of rate‐ranked rain occurrences to the annual mean rainfall in each grid box is S shaped and its derivative, the contribution‐weighted rain rate spectrum, is Gaussian shaped. The 50% intercept of the cumulative contribution R50 is almost equivalent to the contribution‐weighted mean logarithmic rain rate based on all significant rain occurrences. The spatial patterns of R50 and are similar to those obtained by mapping the fraction of the annual accumulation explained by rain occurrences with rates above various specified thresholds. The geographical distribution of R50 confirms the existence of patterns noted in prior analyses based on TRMM precipitation radar data and reveals several previously unnoticed features.

High‐resolution satellite‐gauge merged precipitation climatologies of the Tropical Andes

AbstractSatellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the Tropical Andes. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) was active for 17 years (1998–2014) and has generated one of the longest single‐sensor, high‐resolution, and high‐accuracy rainfall records. In this study, high‐resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite‐gauge (S‐G) merging approaches. The resulting precipitation products are evaluated by cross validation and catchment water balances (runoff ratios) for 50 catchments across the Tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients but underestimates absolute monthly rainfall rates. The S‐G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge‐only product based on ordinary Kriging. Among the S‐G merging methods, performance of inverse distance interpolation of satellite‐gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g., Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S‐G merged products presented in this study are available in the public domain.

Radar Vertical Profile of Reflectivity Correction with TRMM Observations Using a Neural Network Approach

Abstract Complex terrain poses challenges to the ground-based radar quantitative precipitation estimation (QPE) because of partial or total blockages of radar beams in the lower tilts. Reflectivities from higher tilts are often used in the QPE under these circumstances and biases are then introduced due to vertical variations of reflectivity. The spaceborne Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM) satellite can provide good measurements of the vertical structure of reflectivity even in complex terrain, but the poor temporal resolution of TRMM PR data limits their usefulness in real-time QPE. This study proposes a novel vertical profile of reflectivity (VPR) correction approach to enhance ground radar–based QPEs in complex terrain by integrating the spaceborne radar observations. In the current study, climatological relationships between VPRs from an S-band Doppler weather radar located on the east coast of Taiwan and the TRMM PR are developed using an artificial neural network (ANN). When a lower tilt of the ground radar is blocked, higher-tilt reflectivity data are corrected with the trained ANN and then applied in the rainfall estimation. The proposed algorithm was evaluated with three typhoon precipitation events, and its preliminary performance was evaluated and analyzed.

Correction of Radar QPE Errors for Nonuniform VPRs in Mesoscale Convective Systems Using TRMM Observations

Abstract Mesoscale convective systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) is often found in the stratiform region. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE). A vertical profile of reflectivity (VPR) correction is necessary to reduce such biases. However, existing VPR correction methods for ground-based radars often perform poorly for MCSs owing to their coarse resolution and poor coverage in the vertical direction, especially at far ranges. Spaceborne radars such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), on the other hand, can provide high resolution VPRs. The current study explores a new approach of incorporating the TRMM VPRs into the VPR correction for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar QPE. High-resolution VPRs derived from the Ku-band TRMM PR data are converted into equivalent S-band VPRs using an empirical technique. The equivalent S-band TRMM VPRs are resampled according to the WSR-88D beam resolution, and the resampled (apparent) VPRs are then used to correct for BB effects in the WSR-88D QPE when the ground radar VPR cannot accurately capture the BB bottom. The new scheme was tested on six MCSs from different regions in the United States and it was shown to provide effective mitigation of the radar QPE errors due to BB contamination.

Analysis of Storm Structure over Africa Using the Trmm Precipitation Radar Data

A 5-year mean seasonal analysis of mean storm height data and histograms from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) have been used to study the storm structure of the major climatic regions in Africa and over the adjacent Atlantic ocean. The analysis was carried out in two ways. First, the mean storm height and histogram were analyzed for the entire continent bounded by 40?N to 40?S and 20?W to 60?E. Secondly, the analysis was carried out on sub-regional basis, on which Africa was structured into ten regions: Desert (North), Semi-desert (north), Deciduous forest (North), Brush Grass Savanna (North), Tropical Rainforest, Deciduous forest (South), Brush Grass-Savanna (South), Temperate Grassland/Montane Forest, Steppe (East) and Atlantic Ocean. As observed over Africa, and some parts of the Atlantic Ocean and the Indian Ocean, the storm height over the land is higher than that over the sea because ground surfaces tend to be heated more and convections are more easily developed over the land than over the Ocean. There are high storm counts over the land at 250 mb whereas the storm counts are high over the Ocean at 700 mb. Over the regions, the vertical structure of the histograms reveals a distinct bi-modal distribution in the northern hemisphere and the southern hemisphere, but a unimodal distribution is close to the equator both in the northern and southern hemisphere.

Relating TRMM precipitation radar land surface backscatter response to soil moisture in the Southern United States

Soil moisture is an important variable in the hydrological cycle and plays a vital role in agronomy, meteorology, and hydrology. It regulates the exchange of water and heat between land surface and atmosphere and thus plays an important role in the development of weather patterns. It is difficult to obtain a comprehensive spatio-temporal map of soil moisture because of expensive installation of soil moisture measuring instruments. In this paper, a model to estimate soil moisture (ms) using Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) backscatter (σ°) and Normalized Difference Vegetation Index (NDVI) is developed for the Southern United States. Soil moisture data from Soil and Climate Analysis Network (SCAN) stations is used to calibrate and validate the model. The estimated values of ms compare well with the ground measurements of soil moisture. The model works well for various landcovers but works best for low density vegetated areas (closed shrubland). All the soil moisture estimates in this landcover have an absolute error of less than 8%. The model performance deteriorates with increase in vegetation density (crops and forest). Overall, the model performance is satisfactory for all landcover types with RMSE less than 6.3% and absolute error of 10% or less for 90% of the estimates. Estimation of soil moisture over a large area with low error provides another use of TRMMPR data.

A Ground Validation Network for the Global Precipitation Measurement Mission

Abstract A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA’s Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to “matchup” the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR–GR bias was found to increase with the amount of PR attenuation correction applied, with the PR–GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is >6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%–40%.

TRMM 위성의 강수레이더에서 관측된 동아시아 여름 강수의 특성

The characteristics and vertical structure of the rainfall are examined in terms of rain types using TRMM (Tropical Rainfall Measuring Mission) PR (Precipitation Radar) data during the JJA period of 2002-2006 over three different regions; midlatitude region around the Korean Peninsula (EA1), subtropical East Asia (EA2), and tropical East Asia (EA3). The convective rain fraction in the EA1 region is 12.2%, which is smaller by 6% than those in the EA2 and EA3 regions. EA1 shows less frequent convective rain events, which are about 0.5 times as many as those in EA3. EA1 produces the mean convective rain rate of 10.4 mm/h that is about 40% larger than EA2 and EA3 while all regions have similar mean stratiform rain rate. The relationships between storm height and rain rate indicate that the rain rate is proportional to the storm height. Based on the vertical structure of radar reflectivity, EA1 produces deeper and stronger convective clouds with higher rain rate compared to the other regions. In EA3, radar reflectivity increases distinctly toward the land surface at altitude below 5 km, indicating more dominant coalescence-collision processes than the other regions. Furthermore, the bright band of stratiform rain clouds in EA3 is very distinct. In convective rain clouds, the first EOFs of radar reflectivity profiles are similar among the three regions, while the second EOFs are slightly different. The larger variability exists at upper layers for EA1 while it exits at lower levels for EA3.

Relating Convective and Stratiform Rain to Latent Heating

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.

Statistical Analysis of Oceanic Rainfall Characteristics in the Baiu Season Utilizing TRMM PR Data

Temporal variations of rainfall characteristics over the ocean to the south of the Japan Archipelago during the Baiu season are quantitatively analyzed, and their relationships to the variations of environmental conditions are discussed. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data are utilized for the precipitation, upper-air observation data at six oceanic stations of the Japan Meteorological Agency (JMA), and the reanalysis data produced by JMA are utilized for the environmental data, to study the nine Baiu seasons from 1998 to 2006. Calendar-day averaged time series of nine-year TRMM PR data show a significant increase of tall rain in the latter period of the Baiu season, which accompanies the destabilization of the environmental thermodynamic conditions. Utilizing the values of Convective Available Potential Energy (CAPE), Baiu periods are classified into the earlier-period type (EPT) days and the latter-period type (LPT) days, such that EPT/ LPT days are those with negative/positive CAPE anomalies from the entire Baiu-period average. Between the two periods, the convective rain ratio and the stratiform rain characteristics change significantly. In the EPT days, weak stratiform rain associated with the Baiu front is dominant and characterized by an intensity of ~2.5 mm h -1 and a rain-top height (RTH) of ~5 km. In the LPT days, rain is dominated by cloud clusters along the Baiu front with larger contribution from the convective rain, associated with stronger and deeper stratiform rain characterized by ~5.0 mm h -1 intensity and 7.0-7.5 km RTH. Four rain types are classified with the rainfall characteristics obtained from TRMM PR data at 1 degree x 1 degree grids, with the thresholds of convective rain ratio at 35% and rainfall intensity at 2.5 mm h -1 . Type 1 represents the weak stratiform rain along the Baiu front, type 2 rain has well organized cloud clusters, and type 3-rain corresponds to relatively shallow convective rain often found under the influence of the subtropical high. The type-4-rain region can be interpreted as a temporally-varying mixture of rain types 1 and 2. Statistics of rainfall types and environmental conditions suggest that dominant rainfall characteristics may be diagnosed utilizing environmental variables such as the equivalent potential temperature at 1000 hPa and the mean sea-level pressure.

A C-Band Scatterometer Simultaneous Wind/Rain Retrieval Method

Using collocated ERS scatterometer (ESCAT), Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), and European Centre for Medium-Range Weather Forecasts (ECMWF) data, the effects of rain on ESCAT wind-only retrieval are evaluated. Additional scattering from rain causes estimated wind speeds to appear higher than expected. Selected directions of the rain-corrupted wind vectors are biased toward along-track directions under conditions of heavy rain, which is regardless of the true wind direction. Rain becomes more significant for data acquired at a high incidence angle. To compensate for rain-induced backscatter, a simultaneous wind/rain retrieval (SWRR) method, which simultaneously retrieves wind velocity and surface rain rate from ESCAT measurements with an incidence angle >40deg, is developed by using a C-band wind/rain backscatter model. The performance of SWRR under typical wind/rain conditions is evaluated through simulation and validation with collocated TRMM PR and ECMWF data sets. SWRR is shown to significantly improve wind velocity estimates, and the SWRR estimated surface rain rate has relatively high accuracy in moderate to heavy rain cases. Although SWRR-retrieved rain is somewhat biased, it can be corrected. We note that for ESCAT, about 1.5% of all the collocated measurements is affected by significant rain.

Simulation-Based Performance Evaluation of Adaptive Scan for Spaceborne Rain Radar

The performance of the adaptive scan for spaceborne rain radar, which uses a quick scan for rain search followed by a normal or con-centrated scan only for rainy areas, are studied through a simulation using TRMM (Tropical Rainfall Measuring Mission) Precipitation Radar (PR) data. Trade-off studies are performed to find an optimum quick-scan and rain search method to minimize rain missing and false alarm of rain area. Using the optimum method thus determined, consecutive 8-day TRMM PR data are used to statistically evaluate the performance of the adaptive scan in terms of sensitivity improvement and power consumption saving. It is shown that more than 3-dB improvement in effective signal-to-noise ratio (SNe) can be achieved for 40% of the total observations. Alternatively, about 26% power saving can be achieved if the SNe is kept the same.

Spectral Retrieval of Latent Heating Profiles from TRMM PR Data. Part II: Algorithm Improvement and Heating Estimates over Tropical Ocean Regions

Abstract The spectral latent heating (SLH) algorithm was developed for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Part I of this study. The method uses PR information [precipitation-top height (PTH), precipitation rates at the surface and melting level, and rain type] to select heating profiles from lookup tables. Heating-profile lookup tables 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) utilizing a cloud-resolving model (CRM). To assess its global application to TRMM PR data, the universality of the lookup tables from the TOGA COARE simulations is examined in this paper. Heating profiles are reconstructed from CRM-simulated parameters (i.e., PTH, precipitation rates at the surface and melting level, and rain type) and are compared with the true CRM-simulated heating profiles, which are computed directly by the model thermodynamic equation. CRM-simulated data from the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), South China Sea Monsoon Experiment (SCSMEX), and Kwajalein Experiment (KWAJEX) are used as a consistency check. The consistency check reveals discrepancies between the SLH-reconstructed and Goddard Cumulus Ensemble (GCE)-simulated heating above the melting level in the convective region and at the melting level in the stratiform region that are attributable to the TOGA COARE table. Discrepancies in the convective region are due to differences in the vertical distribution of deep convective heating due to the relative importance of liquid and ice water processes, which varies from case to case. Discrepancies in the stratiform region are due to differences in the level separating upper-level heating and lower-level cooling. Based on these results, improvements were made to the SLH algorithm. Convective heating retrieval is now separated into upper-level heating due to ice processes and lower-level heating due to liquid water processes. In the stratiform region, the heating profile is shifted up or down by matching the melting level in the TOGA COARE lookup table with the observed one. Consistency checks indicate the revised SLH algorithm performs much better for both the convective and stratiform components than does the original one. The revised SLH algorithm was applied to PR data, and the results were compared with heating profiles derived diagnostically from SCSMEX sounding data. Key features of the vertical profiles agree well—in particular, the level of maximum heating. The revised SLH algorithm was also applied to PR data for February 1998 and February 1999. The results are compared with heating profiles derived by the convective–stratiform heating (CSH) algorithm. Because observed information on precipitation depth is used in addition to precipitation type and intensity, differences between shallow and deep convection are more distinct in the SLH algorithm in comparison with the CSH algorithm.

Radar Characteristics of Precipitation Features in the EPIC and TEPPS Regions of the East Pacific

Abstract Ship-based radar data are used to compare the structure of precipitation features in two regions of the east Pacific where recent field campaigns were conducted: the East Pacific Investigation of Climate Processes in the Coupled Ocean–Atmosphere System (EPIC-2001; 10°N, 95°W) in September 2001 and the Tropical Eastern Pacific Process Study (TEPPS; 8°N, 125°W) in August 1997. Corresponding July–September 1998–2004 Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) data are also used to provide context for the field campaign data. An objective technique is developed to identify precipitation features in the ship and TRMM PR data and to develop statistics on horizontal and vertical structure and precipitation characteristics. Precipitation features were segregated into mesoscale convective system (MCS) and sub-MCS categories, based on a contiguous area threshold of 1000 km2 (these features were required to have at least one convective pixel), as well as an “other” (NC) category. Comparison of the satellite and field campaign data showed that the two datasets were in good agreement for both regions with respect to MCS features. Specifically, both the satellite and ship radar data showed that approximately 80% of the rainfall volume in both regions was contributed by MCS features, similar to results from other observational datasets. EPIC and TEPPS MCSs had similar area distributions but EPIC MCSs tended to be more vertically developed and rain heavier than their TEPPS counterparts. In contrast to MCSs, smaller features (NCs and sub-MCSs) sampled by the ship radar in both regions showed important differences compared with the PR climatology. In the EPIC field campaign, a large number of small (<100 km2), shallow (radar echo tops below the melting level) NCs and sub-MCSs were sampled. A persistent dry layer above 800 mb during undisturbed periods in EPIC may have been responsible for the high occurrence of these features. Also, during the TEPPS campaign, sub-MCSs were larger and deeper with respect to the TRMM climatology, which may have been due to the higher than average SSTs during 1997–98 when TEPPS was conducted. Despite these differences, it was found that for sizes greater than about 100 km2, EPIC precipitation features had 30-dBZ echos at higher altitudes and also had higher rain rates than similar sized TEPPS features. These results suggest that ice processes play a more important role in rainfall production in EPIC compared with TEPPS.

Tropical Rainfall Measuring Mission observation and regional model study of precipitation diurnal cycle in the New Guinean region

The diurnal cycle of precipitation in the New Guinean region is studied on the basis of satellite observations from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements and regional atmospheric model simulations. The study focuses on the effects of both the land‐sea breeze and the orographic forcing on the diurnal evolution of precipitation during the rainy season (January–March) in the region. The 7‐year TRMM PR data composite reveals several distinct features of the precipitation diurnal cycle in the region. Precipitation bands develop in the inland coastal region in the late morning to early afternoon and migrate inland from both northeast and southwest sides of the New Guinean Island following the inland penetration of the sea‐breeze fronts. A separate convective rainband develops over the central mountain ridge in the early afternoon as a result of the development of the upslope winds due to the elevated surface warming over the mountain in the morning hours. This mountain ridge rainband intensifies and becomes the dominant rainband as the coastal rainbands associated with the sea‐breeze fronts weaken during the late afternoon and the early evening. In the midnight to the early morning the rainband over the mountaintop weakens as downslope winds develop and splits into two rainbands, propagating away from the mountain ridge, one to the north and one to the south, and weakens over the lowland some distance away from the coasts. Meanwhile a coastal rainband develops offshore on each side of the island in the late evening to midnight and remains strong through early morning before it migrates offshore. As a result, the rainfall rate peaks in the late afternoon to early evening in most land areas except for in the lowland regions between the coastlines and the mountain where the rainfall rate peaks during the midnight, while the rainfall rate peaks in the late evening to early morning in most coastal regions offshore. The distribution of the diurnal amplitude shows two maxima: one over the mountains and the other in the coastal regions offshore. Convective rainfall rate peaks in the late afternoon while stratiform rainfall rate peaks in the midnight to early morning. The latter dominates the large diurnal amplitude over the mountain areas in the early morning. The above broad features are simulated reasonably well in a control experiment with a high‐resolution regional atmospheric model. A sensitivity experiment with the terrain removed is conducted to elucidate the role of orographic forcing in the diurnal evolution of both the local circulation and rainfall patterns. The results show that the orographic forcing affects the diurnal precipitation through three major processes. First, the orography increases the moisture convergence at low levels by blocking and deflecting the mean flow. Second, the upslope winds help initiate convection in the afternoon at the mountaintop. Finally, the deep convection over the mountain acts as a source of propagating gravity waves, which help initiate rainbands in the coastal regions offshore in the late evening to early morning. Implication of the results is discussed.

Rain‐yield per flash calculated from TRMM PR and LIS data and its relationship to the contribution of tall convective rain

Rain‐yields per flash (RPF) over the entire tropics were calculated from 3 years of data collected by a Lightning Imaging Sensor (LIS) and a Precipitation Radar (PR) housed onboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The results confirm that RPF is a reliable indicator of precipitation regimes, with a marked land–ocean contrast and intermediate values over monsoonal regions and continental oceans. Mean RPF values averaged over the entire TRMM region are 3.94 × 108 kg fl−1 over land and 1.96 × 109 kg fl−1 over oceans. A good (−0.55) correlation between RPF and the Tall Convective Rain Contribution with a threshold of −20degC (TCRC–20C) was found especially over land. This result indicates that large amounts of tall convective rain are fundamentally associated with intense updrafts that are able to sustain vigorous lightning activity. The correlation is weaker over ocean, except for that over continental oceans.