Tropical Rainfall Measuring Mission Precipitation Radar Research Articles

Development of a Precipitation Climate Record from Spaceborne Precipitation Radar Data. Part II: Temporal Adjustment of the Calibration Change Using the Ocean Normalized Radar Cross Section

Abstract We analyze the calibration stability of the 17-yr precipitation radar (PR) data on board the Tropical Rainfall Measuring Mission (TRMM) satellite to develop a precipitation climate record from the spaceborne precipitation radar data of the TRMM and following satellite missions. Since the PR measures the normalized radar cross section (NRCS) over the ocean surface, the temporal change in the NRCS whose variability is insensitive to the sea surface wind is regarded as the temporal change of the PR calibration. The temporal change of the PR calibration in TRMM, version 7, is found to be 0.19 dB decade−1 from 1998 to 2013. The calibration change is simply adjusted to evaluate the NRCS time series and the near-surface precipitation trend analysis within the latitudinal band between 35°S and 35°N. The NRCS time series at nadir and off-nadir are uncorrelated before the calibration adjustment, but they are correlated after the adjustment. The 0.19 dB decade−1 change of the PR calibration causes an overestimation of 0.08 mm day−1 decade−1 or 2.9% decade−1 for the linear trend of the near-surface precipitation. Even after the adjustment, agreement of the results among the satellite products depends on the analysis period. The temporal stability of the data quality is also important to evaluate the plausible trend analysis. The reprocessing of the PR data in TRMM, version 8 (or later), takes into account the temporal adjustment of the calibration change based upon the results of this study, which can provide more credible data for a long-term precipitation analysis. Significance Statement The stability of long-term data is very important for climate research so that an account of temporal calibration changes in the sensor must be made. In this study, we investigate the calibration stability of the TRMM PR data and evaluate its impact on the precipitation trend analysis. The temporal change of the PR calibration is estimated to be 0.19 dB decade−1. Compensating for this change improves the consistency of precipitation trend analysis between the PR and other precipitation datasets. The reprocessed PR data provide more probable data for long-term precipitation analysis.

Rain/no-rain classification from combined radar- Radiometer data using machine learning

Satellites with microwave-based sensors are launched to study and estimate global precipitation due to the instrument's sensitivity to precipitation, as well as their global coverage. The Tropical Rainfall Measuring Mission (TRMM) mission jointly launched by NASA of US and JAXA of Japan to study the global rain within the tropics had two microwave-based instruments on board; the Precipitation Radar (PR) and the TRMM Microwave Imager (TMI). Radar, being an active instrument, measures rainfall by detecting the echo accurately over both land and oceans. On the other hand, the passive instrument, radiometer, senses radiation emerging from the land/ocean surface, passing through the raining atmosphere. Due to the absence of contrast over land pixels, radiometers do not perform well over land surfaces in the detection of rainfall. Hence, over land rain screening algorithms are predominantly based on high-frequency channels which are sensitive to the scattering of radiation. However, their performance in screening the pixel for rain is based on threshold values. The present study demonstrates a superior algorithm powered by machine learning (ML) techniques. We apply the artificial neural network (ANN) and the random forest algorithm for screening the pixels over land for rainfall. The algorithms are trained with TMI measured brightness temperatures, while the TRMM PR detected rain flag is used as the truth. The ML models were trained with 2012 JJAS data over the Indian landmass. The performance of the ML models is tested with the monthly data of 2012 and with the 2013 JJAS dataset over the same region to demonstrate the robustness of the model. The imbalance of the dataset (a small fraction of rain cases as compared to no-rain cases) has been addressed using the synthetic minority oversampling technique (SMOTE). A comparison is made between the two ML algorithms against the GPROF algorithm, which is implemented in the operational data product for the TRMM version 7 data product. Results show that the ML-based methods performed better as compared to the GPROF. On the 2013 JJAS dataset, the maximum F1 score obtained was 0.65 for the actual dataset, while the score with oversampled dataset was 0.68. For the same dataset, the GPROF algorithm showed an F1 score of 0.59. Apart from the nine brightness temperatures as input, new derived features were also selected based on two feature selection methods: mutual information and analysis of variance. It was seen that the models' performance on the two feature sets obtained from the two methods were very much similar.

Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil

The Northeast region of Brazil (NEB) has a high rate of deaths from lightning strikes (18% of the country’s total). The region has states, such as Piauí, with high mortality rates (1.8 deaths per million), much higher than the national rate (0.8) and the NEB rate (0.5). In this sense, the present work analyzes the microphysical characteristics of clouds with and without the occurrence of total lightning. For this purpose, data from the Lightning Imaging Sensor (LIS), TRMM Microwave Imager (TMI) and Precipitation Radar (PR), aboard the Tropical Rainfall Measuring Mission (TRMM) satellite from 1998 to 2013 were used. The TRMM data were analyzed to establish a relationship between the occurrence of lightning and the clouds’ microphysical characteristics, comparing them as a function of lightning occurrence classes, spatial location and atmospheric profiles. A higher lightning occurrence is associated with higher values of ice water path (>38.9 kg m−2), rain water path (>2 kg m−2), convective precipitation (>5 mm h−1) and surface precipitation (>7 mm h−1), in addition to slightly higher freezing level height values. Reflectivity observations (>36 dBZ) demonstrated typical convective profile curves, with higher values associated with classes with higher lightning densities (class with more than 6.8 flash km−2 year−1).

Characterizing Ice-Scattering Homogeneity in TRMM Microwave Imagers and Its Influence on Oceanic Rain-Rate Estimation Bias of TRMM Precipitation Radar

Precipitation homogeneity is one of the main factors that contribute to the difference in the rain-rate estimation from meteorological satellites. Using the Tropical Rainfall Measuring Mission (TRMM) products, this paper aims to characterize the homogeneity of ice-scattering signals from TRMM Microwave Imagers (TMIs) as related to rain-rate estimation bias with TRMM Precipitation Radar (PR). Statistical information about the polarization-corrected brightness temperature (PCT) from the TMI 85 GHz band is obtained over the global ocean in the tropics. The characteristics are the fraction of PCT below a given threshold, the minimum value, and the standard deviation that are calculated at a 0.25° × 0.25°grid level. The average values of rain-rate estimation from TRMM PR and TMI in the same grid position and time are then compared. This result indicates that the rain-rate estimation bias is influenced by the homogeneity and organization of precipitation systems. Using the statistical signature of ice-scattering signals at the grid level, an adjustment was implemented for TMI rain-rate estimation. The results could produce rain-rate estimations that conform more to PR, particularly for the inhomogeneous precipitation system mostly affected by stratiform rain. The characterization of ice-scattering signals as a proxy to the precipitation homogeneity, as presented in this research, could be implemented in order to improve the accuracy of satellite rain-rate estimation in the future.

Tropical TGF Paradox: A Perspective From TRMM Precipitation Radar

AbstractThe Terrestrial Gamma‐ray Flash (TGF) to lightning ratio, computed over the three tropical chimneys, presents a paradox: African thunderstorms produce the most lightning but yield the lowest fraction of TGFs when compared to American and Southeast Asian thunderstorms. To understand the physical insights into this asymmetry, Tropical Rainfall Measuring Mission Precipitation Radar measurements are used to depict the vertical precipitation structure and infer the vertical electrical charge fraction distribution of the observed thunderstorms in the three regions and the thunderstorms during TGF occurrences detected by the AGILE, Fermi‐GBM, and RHESSI sensors. Regional differences show that African thunderstorms are taller, smaller, and have a higher concentration of denser ice particles (graupel and or hail) above the freezing level in addition to having more lightning flashes per thunderstorm. The overall TGF‐related thunderstorms are taller, more intense (0.5–1.5 dBZ) and present similar radar reflectivity decay with height independent of the region. The two dimensional precipitation vertical distribution diagrams indicate that TGF thunderstorms develop to a mature stage. Independent of the region, thunderstorms show a midlevel negative charge center varying from 4.6 to 8.1 km in height and an upper level positive charge center ranging from 7.4 to 14.6 km. TGF thunderstorms have thicker positive inferred charge layer and present larger vertical distances between the opposite charging layers in comparison with the overall thunderstorm population, here defined as Climatology. African TGF thunderstorms have higher fraction of positive charges near the negative layer, helping to produce more and shorter lightning discharges.

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 Synoptic Evolution Comparison of the Smallest and Largest MCSs in Subtropical South America between Spring and Summer

AbstractSubtropical South America (SSA) east of the Andes Mountains is a global hotspot for mesoscale convective systems (MCSs). Wide convective cores (WCCs) are typically embedded within mature MCSs, contribute over 40% of SSA’s warm-season rainfall, and are often associated with severe weather. Prior analysis of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data identified WCCs in SSA and associated synoptic conditions during austral summer. As WCCs also occur during the austral spring, this study uses the 16-year TRMM PR dataset and ERA5 reanalysis to compare anomalies in environmental conditions between austral spring (SON) and summer (DJF) for the largest and smallest WCCs in SSA. During both seasons, large WCCs are associated with an anomalous mid-level trough that slowly crosses the Andes Mountains and a northerly South American low-level jet (SALLJ) over SSA, though the SON trough and SALLJ anomalies are stronger and located farther northeastward than in DJF. A synoptic pattern evolution resembling large WCC environments is illustrated through a multi-day case during the RELAMPAGO field campaign (10-13 November 2018). Unique high-temporal resolution soundings showed strong mid-level vertical wind shear associated with this event, induced by the juxtaposition of the northerly SALLJ and southerly near-surface flow. It is hypothesized that the Andes help create a quasi-stationary trough/ridge pattern such that favorable synoptic conditions for deep convection persist for multiple days. For the smallest WCCs, anomalously weaker synoptic-scale forcing was present compared to the largest events, especially for DJF, pointing to future work exploring MCS formation under weaker synoptic conditions.

Diurnal Variations of Precipitation over the Steep Slopes of the Himalayas Observed by TRMM PR and VIRS

This study investigates diurnal variations of precipitation during May–August, 1998–2012, over the steep slopes of the Himalayas and adjacent regions (flat Gangetic Plains–FGP, foothills of the Himalayas–FHH, the steep slope of the southern Himalayas–SSSH, and the Himalayas-Tibetan Plateau tableland–HTPT). Diurnal variations are analyzed at the pixel level utilizing collocated TRMM precipitation radar and visible infrared data. The results indicate that rain parameters (including rain frequency, rain rate, and storm top altitude) are predominantly characterized by afternoon maxima and morning minima at HTPT and FGP, whereas, maximum rain parameters at FHH typically occur in the early morning. Rain parameters at SSSH are characterized by double peaks; one in the afternoon and one at midnight. Over HTPT and FGP, convective activity is strongest in the afternoon with the thickest crystallization layer. Over FHH, the vertical structure of precipitation develops most vigorously in the early morning when the most intense collision and growth of precipitation particles occurs. Over SSSH, moist convection is stronger in the afternoon and at midnight with strong mixing of ice and water particles. The results of harmonic analysis show that rain bands move southward from lower elevation of SSSH to FHH with apparent southward propagation of the harmonic phase from midnight to early morning. Moreover, the strongest diurnal harmonic is located at HTPT, having a diurnal harmonic percentage variance of up to 90%. Large-scale atmospheric circulation patterns exhibit obvious diurnal variability and correspond well to the distribution of precipitation.

The Synoptically-Influenced Extreme Precipitation Systems over Asian-Australian Monsoon Region Observed by TRMM Precipitation Radar

The Synoptically-Influenced Extreme Precipitation Systems over Asian-Australian Monsoon Region Observed by TRMM Precipitation Radar

Fundamental Characteristics of Tropical Rain Cell Structures as Measured by TRMM PR

Rain cells are the most elementary unit of precipitation system in nature. In this study, fundamental geometric and physical characteristics of rain cells over tropical land and ocean areas are investigated by using 15-yr measurements of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The rain cells are identified with a minimum bounding rectangle (MBR) method. The results indicate that about 50% of rain cells occur at length of about 20 km and width of 15 km. The proportion of rain cells with length > 200 km and width > 100 km is less than 1%. There is a a log-linear relationship between the mean length and width of rain cells. Usually, for the same horizontal geometric parameters, rain cells tend to be square horizontally and lanky vertically over land, while vertically squatty over ocean. The rainfall intensity of rain cells varies from 0.4 to 10 mm h−1 over land to 0.4–8 mm h−1 over ocean. Statistical results indicate that the occurrence frequency of rain cells decreases as the areal fraction of convective precipitation in rain cells increases, while such frequency remains almost invariant when the areal fraction of stratiform precipitation varies from 10% to 80%. The relationship between physical and geometric parameters of rain cells shows that the mean rain rate of rain cells is more frequently associated with the increase of their area, with the increasing rate over land greater than that over ocean. The results also illustrate that heavy convective rain rate prefers to occur in larger rain cells over land while heavy stratiform rain rate tends to appear in larger rain cells over ocean. For the same size of rain cells, the areal fraction and the contribution of convective precipitation are about 10%–15% higher over land than over ocean.

Conversion of the Vertical Profile of Reflectivity From Ku-Band to C-Band Based on the Drop Size Distribution Measurements of the Global Precipitation Measurement Mission Dual-Frequency Precipitation Radar

The ground-based radar quantitative precipitation estimation (QPE) faces various challenges including the overestimation caused by the bright band (BB) in the stratiform region and the underestimation in mountainous areas when the terrain-enhanced precipitation occurs at the levels below ground-based radar measurements. The vertical precipitation structure provided by spaceborne radars, i.e., the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the Global Precipitation Measurement mission (GPM) Dual-frequency PR (DPR), is valuable for mitigating the above problems. Since the spaceborne radars and ground-based radars usually operate in different frequencies, e.g., the TRMM PR and the KuPR of GPM DPR work in Ku-band (13.8 and 13.6 GHz, respectively) and the ground-based radars in western China work in C-band (5.4 GHz), the reflectivity conversion from Ku-band to C-band is necessary before the vertical profile of reflectivity (VPR) measured by spaceborne radars can be utilized to improve the ground-based radar QPE in western China. This study presents a conversion method using GPM DPR measurements, i.e., the drop size distribution (DSD) for different precipitation types (the stratiform with/without BB and the convective cases) and particle phases (the solid, melting, and liquid). Using the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> -matrix method, the reflectivity difference between Ku-band and C-band is found and the Ku-band to C-band conversion relations are derived with the linear regression. These conversion relations have been validated by matching and comparing the converted C-band reflectivity with the C-band ground-based radar measurements. The results demonstrate the effectiveness and reliability of the conversion. This method can be extended for the reflectivity conversion in other frequencies and can facilitate the incorporation of reflectivity measurements from various instruments.

Precipitation measurement from SARAL AltiKa and passive microwave radiometer observations

ABSTRACT This study attempts to exploit ‘Satellite with Advanced Research and Global Observation Satellite (Argos) and Ka-band Altimeter (ALtiKa)’ (SARAL/AltiKa) and Passive Microwave Radiometer (PMR) measurements for the retrieval of precipitation and rain rate (R Rain) over the global oceans. The altimetric measurements are affected by the presence of rain and these measurements are thus required to be identified. In this research, the concurrent SARAL and Tropical Rainfall Measuring Mission – Precipitation Radar (TRMM-PR) measurements are used to show the rain sensitivity of some of the altimeter derived parameters and PMR-derived Brightness Temperature. Based on the probability distribution of rain-sensitive parameters, a probabilistic rain identification algorithm is proposed, which is optimized to reduce the false-alarm cases for rain estimation. In the second step, a Genetic Algorithm (GA)-based rain measurement algorithm is developed. The algorithm is applied to a full year (2016) of independent SARAL measurements, compared with collocated Global Precipitation Measurement (GPM) Mission Microwave Imager (GMI) and Special Sensor Microwave Imager Sounder (SSMIS) measurements. Within TRMM latitudinal coverage area (i.e. < ± 40° latitudes), the comparison with GMI and SSMIS shows correlation coefficient (r) of 0.78 and 0.76 and root mean square difference (RMSD) of 0.48 and 0.43 (mm h−1), respectively. The comparison, beyond latitudinal coverage of TRMM-PR (i.e. outside ± 40° latitudes), with GMI and SSMIS, shows r of 0.63 and 0.60 and RMSD of 0.59 and 0.55 (mm h−1), respectively. The algorithm is further applied to measure rain associated with a tropical cyclone. These rain measurements are then compared with near-concurrent rain measurements from SSMIS, and comparison results are presented in the paper.

Analysis of Surface Cross-Sectional Data Taken During the 90° Yaw Experiment of the TRMM Precipitation Radar

During the descent of the Tropical Rainfall Measuring Mission satellite at the end of its mission, three types of special experiments were conducted; wide swath, 90° yaw (90Y: along-track scanning), and dense sampling. In this article, the results from the analysis of 90° yaw experimental data are shown in terms of a normalized radar cross section (NRCS) of the surface. The advantage of the 90Y experiment is that obtaining the incident angle dependency of the NRCS enables deduction of the conditions at the surface, especially over the ocean. The slope and intercept are calculated from the NRCS–incident angle plot except for angles near nadir. The slope correlates well with the sea-surface wind speed and therefore the rain attenuation can be estimated from the intercept and compared with the attenuation estimated from the radar reflectivity factor of the rain profile. The effect of the rain drops striking the sea surface is also examined by comparing the wind speed–slope relationship.

Estimates of Spaceborne Precipitation Radar Pulsewidth and Beamwidth Using Sea Surface Echo Data

Calibration consistency between Ku-band radars flown on the Tropical Rainfall Measuring Mission's (TRMM's) precipitation radar (PR) and the global precipitation measurement (GPM) mission's dual-frequency PR (DPR) can be attained by the use of the normalized radar cross section (NRCS) or σ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> over the oceans. With the use of the sea surface echo (SSE) data obtained from the spaceborne PRs, this article aims to estimate the radar parameters of pulsewidth and beamwidth and to evaluate the bias in the NRCS estimates caused by the discrete range sampling. Since the SSE shape is closely related to the received pulsewidth and the two-way cross-track beamwidth, those parameters are individually estimated from the SSE shapes. The SSE shapes are also used to evaluate the impact of the discrete range sampling on the NRCS statistics. The pulsewidth and beamwidth estimated from the SSEs compare well with the level-1 values and accurately reflect changes in the configuration of the radars. The NRCS statistics in GPM version 06 show that the calibration consistency between GPM KuPR and TRMM PR is evaluated within the range of -0.39 to +0.03 dB (-0.48 to +0.11 dB) with (without) the peak correction.

Subtropical South American Hailstorm Characteristics and Environments.

Hailstorms in subtropical South America are known to be some of the most frequent anywhere in the world, causing significant damage to the local agricultural economy every year. Convection in this region tends to be orographically forced, with moisture supplied from the Amazon rainforest by the South American low-level jet. Previous climatologies of hailstorms in this region have been limited to localized and sparse observational networks. Due to the lack of sufficient ground-based radar coverage, objective radar-derived hail climatologies have also not been produced for this region. As a result, this study uses a 16-year dataset of TRMM Precipitation Radar and Microwave Imager observations to identify possible hailstorms remotely, using 37-GHz brightness temperature as a hail proxy. By combining satellite instruments and ERA-Interim reanalysis data, this study produces the first objective study of hailstorms in this region. Hailstorms in subtropical South America have an extended diurnal cycle, often occurring in the overnight hours. Additionally, they tend to be multi-cellular in nature, rather than discrete. High-probability hailstorms (≥ 50% probability of containing hail) tend to be deeper by 1-2 km and horizontally larger by greater than 15,000 km2 than storms having a low-probability of containing hail (< 25% probability of containing hail). Finally, hailstorms are supported synoptically by strong upper- and lower-level jets, anomalously warm and moist low levels, and enhanced instability. The findings of this study will support the forecasting of these severe storms and mitigation of their damages within this region.

Postdeployment Calibration of a Tropical UHF Profiling Radar via Surface- and Satellite-Based Methods

Wind profiling radars are usually not calibrated with respect to reflectivity because such calibrations are both unnecessary for good wind measurements and costly. However, reflectivity from calibrated profilers can reveal many atmospheric attributes beyond winds. Establishing ways to calibrate these radars even after they have been taken out of service would expand the utility of archived profiler data. We have calibrated one operating mode of a 915-MHz profiler deployed at Manus, Papua New Guinea (1992–2001), using two methods. The first method adjusts a radar parameter until the profiler’s estimate of rainfall during stratiform events closely matches surface observations. The second adjusts the parameter so that mean brightband heights observed by the profiler (July 1992–August 1994) match the mean brightband reflectivities over the profiler as observed by the TRMM Precipitation Radar (January 1998–July 2001). The results differ by about 5% and yield very similar precipitation errors during tested stratiform events. One or both of these methods could be used on many other wind profilers, whether they have been decommissioned or are currently operational. Data from such calibrated profilers will enable research employing the equivalent reflectivity factor observed by profilers to be compared with that from other radars, and will also enable turbulent studies with C n2.

Vertical characteristics of radar reflectivity and DSD parameters in intense convective clouds over South East South Asia during the Indian Summer monsoon: GPM observations

ABSTRACTGlobal precipitation measurement (GPM) launched in February 2014 as a legacy of Tropical Rainfall Measuring Mission (TRMM). Both satellites carry precipitation radar (PR), which measures the three-dimension structure of precipitation from space. Compared to TRMM PR, GPM has dual-polarized radar (DPR) and provides the raindrop size distribution (DSD) including mass-weighted mean diameter (Dm, in mm) and normalized DSD scaling parameter for concentration (Nw, in mm–1 m–3) (DSD parameters), along with radar reflectivity factor (Ze) from the surface to 21.875 km. Here we investigated the regional differences in intense convective clouds over South East & South Asia (SESA) and explored the differences in the East and West coast of India, by selecting the various areas. We defined two types of clouds, namely Cumulonimbus towers (CbTs) and intense convective clouds (ICCs) based on the Ze and height thresholds. CbTs must consist of 20 dBZ at 12 km, with echo base height less than 3 km, where ICCs are classified based on Ze threshold at 8 km (ICC8) and 3 km (ICC3). The average vertical profiles of CbTs indicate a strong west to east gradient, as the west side/coast of India has intense CbTs, with higher hydrometeors size, and decreases at east side/coast of India. The results reveal that the western side of India (Western Himalaya Foothills and Western Ghats) consists of fewer CbTs, but they are more intense. ICC3s are distributed nearly uniformly over the SESA but show the regional differences in Ze and DSD parameters in the vertical profiles. Despite various height and Ze thresholds used in the present study, WHF has the strongest vertical profile for all type of cloud cells, and indicate the importance of specific features and orographic modulated flow. The hydrometeors size is highest over Western Himalaya Foothills and least over the Bay of Bengal. Hydrometeors concentration shows the north-south gradient and higher over oceanic areas. Two coastal areas, Western Ghats and Myanmar show the different characteristics. Western Ghats CbTs are more intense, with higher hydrometeors size, whereas Myanmar has weaker convection and consists of small-sized hydrometeors. Hydrometeors size and concentration show the opposite characteristics, as hydrometeors size is higher for intense average Ze profiles, whereas hydrometeors concentration is less for intense average Ze profiles.

Characteristics of Intense Convection in Subtropical South America as Influenced by El Niño–Southern Oscillation

AbstractEl Niño–Southern Oscillation (ENSO) is known to have teleconnections to atmospheric circulations and weather patterns around the world. Previous studies have examined connections between ENSO and rainfall in tropical South America, but little work has been done connecting ENSO phases with convection in subtropical South America. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) has provided novel observations of convection in this region, including that convection in the lee of the Andes Mountains is among the deepest and most intense in the world with frequent upscale growth into mesoscale convective systems. A 16-yr dataset from the TRMM PR is used to analyze deep and wide convection in combination with ERA-Interim reanalysis storm composites. Results from the study show that deep and wide convection occurs in all phases of ENSO, with only some modest variations in frequency between ENSO phases. However, the most statistically significant differences between ENSO phases occur in the three-dimensional storm structure. Deep and wide convection during El Niño tends to be taller and contain stronger convection, while La Niña storms contain stronger stratiform echoes. The synoptic and thermodynamic conditions supporting the deeper storms during El Niño is related to increased convective available potential energy, a strengthening of the South American low-level jet (SALLJ), and a stronger upper-level jet stream, often with the equatorward-entrance region of the jet stream directly over the convective storm locations. These enhanced synoptic and thermodynamic conditions provide insight into how the structure of some of the most intense convection on Earth varies with phases of ENSO.

Improving Satellite-Based Subhourly Surface Rain Estimates Using Vertical Rain Profile Information

Abstract Quantifying time-averaged rain rate, or rain accumulation, on subhourly time scales is essential for various application studies requiring rain estimates. This study proposes a novel idea to estimate subhourly time-averaged surface rain rate based on the instantaneous vertical rain profile observed from low-Earth-orbiting satellites. Instantaneous rain estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) are compared with 1-min surface rain gauges in North America and Kwajalein atoll for the warm seasons of 2005–14. Time-lagged correlation analysis between PR rain rates at various height levels and surface rain gauge data shows that the peak of the correlations tends to be delayed for PR rain at higher levels up to around 6-km altitude. PR estimates for low to middle height levels have better correlations with time-delayed surface gauge data than the PR’s estimated surface rain rate product. This implies that rain estimates for lower to middle heights may have skill to estimate the eventual surface rain rate that occurs 1–30 min later. Therefore, in this study, the vertical profiles of TRMM PR instantaneous rain estimates are averaged between the surface and various heights above the surface to represent time-averaged surface rain rate. It was shown that vertically averaged PR estimates up to middle heights (~4.5 km) exhibit better skill, compared to the PR estimated instantaneous surface rain product, to represent subhourly (~30 min) time-averaged surface rain rate. These findings highlight the merit of additional consideration of vertical rain profiles, not only instantaneous surface rain rate, to improve subhourly surface estimates of satellite-based rain products.

Vertical Distribution of Radar Reflectivity Factor in Intense Convective Clouds over Indonesia

.