“Warm Rain” in the Tropics: Seasonal and Regional Distributions Based on 9 yr of TRMM Data

2009 ◽  
Vol 22 (3) ◽  
pp. 767-779 ◽  
Author(s):  
Chuntao Liu ◽  
Edward J. Zipser

Abstract How much precipitation is contributed by warm rain systems over the tropics? What is the typical size, intensity, and echo top of warm rain events observed by the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar over different regions of the tropics? What proportion of warm raining areas is actually attached to the edges of cold systems? Are there mesoscale warm raining systems, and if so, where and when do they occur? To answer these questions, a 9-yr TRMM precipitation feature database is used in this study. First, warm rain features in 20°S–20°N are selected by specifying precipitation features 1) with minimum infrared brightness temperature > 0°C, 2) with TRMM Precipitation Radar (PR) echo top below freezing level, or 3) without any ice-scattering signature in the microwave observations, respectively. Then, the geographical, seasonal, and diurnal variations of the rain volume inside warm rain features defined in these three ways are presented. The characteristics of warm rain features are summarized. Raining pixels with cloud-top temperature above 0°C contribute 20% of the rainfall over tropical oceans and 7.5% over tropical land. However, about half of the warm pixels over oceans and two-thirds of the warm pixels over land are attached to cold precipitation systems. A large amount of warm rainfall occurs over oceans near windward coasts during winter. Most of the warm rain systems have small size < 100 km2 and weak radar echo with a modal maximum near-surface reflectivity around 23 dBZ. However, mesoscale warm rain systems with strong radar echoes do occur in large regions of the tropical oceans, more during the nighttime than during daytime. Though the mean height of the warm precipitation features over oceans is lower than that over land, there is no significant regional difference in its size and intensity.

2010 ◽  
Vol 23 (2) ◽  
pp. 419-439 ◽  
Author(s):  
Ulrike Romatschke ◽  
Socorro Medina ◽  
Robert A. Houze

Abstract Temporal and spatial variations of convection in South Asia are analyzed using eight years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data and NCEP reanalysis fields. To identify the most extreme convective features, three types of radar echo structures are defined: deep convective cores (contiguous 3D convective echo ≥40 dBZ extending ≥10 km in height) represent the most vertically penetrative convection, wide convective cores (contiguous convective ≥40 dBZ echo over a horizontal area ≥1000 km2) indicate wide regions of intense multicellular convection, and broad stratiform regions (stratiform echo contiguous over an area ≥50 000 km2) mark the mesoscale convective systems that have developed the most robust stratiform regions. The preferred locations of deep convective cores change markedly from India’s east coast in the premonsoon to the western Himalayan foothills in the monsoon. They form preferentially in the evening and over land as near-surface moist flow is capped by dry air aloft. Continental wide convective cores show a similar behavior with an additional nocturnal peak during the monsoon along the Himalayan foothills that is associated with convergence of downslope flow from the Himalayas with moist monsoonal winds at the foothills. The oceanic wide convective cores have a relatively weak diurnal cycle with a midday maximum. Convective systems exhibiting broad stratiform regions occur primarily in the rainiest season and regions—during the monsoon, over the ocean upstream of coastal mountains. Their diurnal patterns are similar to those of the wide convective cores.


2013 ◽  
Vol 52 (9) ◽  
pp. 2001-2008 ◽  
Author(s):  
K. Saikranthi ◽  
T. Narayana Rao ◽  
B. Radhakrishna ◽  
S. Vijaya Bhaskara Rao

AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes > 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.


2021 ◽  
Vol 13 (5) ◽  
pp. 2293-2306
Author(s):  
Lilu Sun ◽  
Yunfei Fu

Abstract. Clouds and precipitation have vital roles in the global hydrological cycle and the radiation budget of the atmosphere–Earth system and are closely related to both the regional and the global climate. Changes in the status of the atmosphere inside clouds and precipitation systems are also important, but the use of multi-source datasets is hampered by their different spatial and temporal resolutions. We merged the precipitation parameters measured by the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) with the multi-channel cloud-top radiance measured by the visible and infrared scanner (VIRS) and atmospheric parameters in the ERA5 reanalysis dataset. The merging of pixels between the precipitation parameters and multi-channel cloud-top radiance was shown to be reasonable. The 1B01-2A25 dataset of pixel-merged data (1B01-2A25-PMD) contains cloud parameters for each PR pixel. The 1B01-2A25 gridded dataset (1B01-2A25-GD) was merged spatially with the ERA5 reanalysis data. The statistical results indicate that gridding has no unacceptable influence on the parameters in 1B01-2A25-PMD. In one orbit, the difference in the mean value of the near-surface rain rate and the signals measured by the VIRS was no more than 0.87 and the standard deviation was no more than 2.38. The 1B01-2A25-GD and ERA5 datasets were spatiotemporally collocated to establish the merged 1B01-2A25 gridded dataset (M-1B01-2A25-GD). Three case studies of typical cloud and precipitation events were analyzed to illustrate the practical use of M-1B01-2A25-GD. This new merged gridded dataset can be used to study clouds and precipitation systems and provides a perfect opportunity for multi-source data analysis and model simulations. The data which were used in this paper are freely available at https://doi.org/10.5281/zenodo.4458868 (Sun and Fu, 2021).


2013 ◽  
Vol 52 (2) ◽  
pp. 408-424 ◽  
Author(s):  
Qing Cao ◽  
Yang Hong ◽  
Jonathan J. Gourley ◽  
Youcun Qi ◽  
Jian Zhang ◽  
...  

AbstractThis study presents a statistical analysis of the vertical structure of precipitation measured by NASA–Japan Aerospace Exploration Agency’s (JAXA) Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in the region of southern California, Arizona, and western New Mexico, where the ground-based Next-Generation Radar (NEXRAD) network finds difficulties in accurately measuring surface precipitation because of beam blockages by complex terrain. This study has applied TRMM PR version-7 products 2A23 and 2A25 from 1 January 2000 to 26 October 2011. The seasonal, spatial, intensity-related, and type-related variabilities are characterized for the PR vertical profile of reflectivity (VPR) as well as the heights of storm, freezing level, and bright band. The intensification and weakening of reflectivity at low levels in the VPR are studied through fitting physically based VPR slopes. Major findings include the following: precipitation type is the most significant factor determining the characteristics of VPRs, the shape of VPRs also influences the intensity of surface rainfall rates, the characteristics of VPRs have a seasonal dependence with strong similarities between the spring and autumn months, and the spatial variation of VPR characteristics suggests that the underlying terrain has an impact on the vertical structure. The comprehensive statistical and physical analysis strengthens the understanding of the vertical structure of precipitation and advocates for the approach of VPR correction to improve surface precipitation estimation in complex terrain.


2015 ◽  
Vol 28 (22) ◽  
pp. 8791-8824 ◽  
Author(s):  
Cheng Tao ◽  
Haiyan Jiang

Abstract Shear-relative distributions of four types of precipitation/convection in tropical cyclones (TCs) are statistically analyzed using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. The dataset of 1139 TRMM PR overpasses of tropical storms through category-2 hurricanes over global TC-prone basins is divided by future 24-h intensity change. It is found that increased and widespread shallow precipitation (defined as where the 20-dBZ radar echo height <6 km) around the storm center is a first sign of rapid intensification (RI) and could be used as a predictor of the onset of RI. The contribution to total volumetric rain and latent heating from shallow and moderate precipitation (20-dBZ echo height between 6 and 10 km) in the inner core is greater in RI storms than in non-RI storms, while the opposite is true for moderately deep (20-dBZ echo height between 10 and 14 km) and very deep precipitation (20-dBZ echo height ≥14 km). The authors argue that RI is more likely triggered by the increase of shallow–moderate precipitation and the appearance of more moderately to very deep convection in the middle of RI is more likely a response or positive feedback to changes in the vortex. For RI storms, a cyclonic rotation of frequency peaks from shallow (downshear right) to moderate (downshear left) to moderately and very deep precipitation (upshear left) is found and may be an indicator of a rapidly strengthening vortex. A ring of almost 90% occurrence of total precipitation is found for storms in the middle of RI, consistent with the previous finding of the cyan and pink ring on the 37-GHz color product.


2007 ◽  
Vol 46 (5) ◽  
pp. 667-672 ◽  
Author(s):  
Yunfei Fu ◽  
Guosheng Liu

Abstract Rain-type statistics derived from Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) standard product show that some 70% of raining pixels in the central Tibetan Plateau summer are stratiform—a clear contradiction to the common knowledge that rain events during summer in this region are mostly convective, as a result of the strong atmospheric convective instability resulting from surface heating. In examining the vertical distribution of the stratiform rain-rate profiles, it is suspected that the TRMM PR algorithm misidentifies weak convective rain events as stratiform rain events. The possible cause for this misidentification is believed to be that the freezing level is close to the surface over the plateau, so that the ground echo may be mistakenly identified as the melting level in the PR rain classification algorithm.


2021 ◽  
Author(s):  
Fumie Murata ◽  
Toru Terao ◽  
Yusuke Yamane ◽  
Masashi Kiguchi ◽  
Azusa Fukushima ◽  
...  

<p>The near surface rain (NSR) dataset of the Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) and the Global Precipitation Mission (GPM) Dual Precipitation Radar (DPR) was validated using around 40 tipping bucket raingauges installed over the northeastern Indian subcontinent, and disdrometers in the Meghalaya Plateau, India. The comparison during 2006-2014 showed significant overestimation of TRMM PR in Assam and Bengal plains during pre-monsoon season (March to May), and significant underestimation of TRMM PR over the Indian subcontinent during monsoon season (June to September). Whereas, the comparison during 2014-2019 showed significant overestimation of GPM DPR over only Meghalaya during monsoon season. The validation of rain-drop size distribution parameters: Dm and Nw showed positive correlation between GPM DPR derived values and Parsivel disdrometers observed ones, while unrealistic concentration of Nw on 30-40 dB was derived by GPM DPR. In the southern slope of the Meghala Plateau, NSR of TRMM PR at Cherrapunji, where is known as the heaviest rainfall station, on the plateau observed smaller rainfall than that in the adjacent valley. However, newly installed raingauges in the valley showed rather less rainfall than that on the plateau. The validity of the satellite derived rainfall distribution over the complicated terrain are discussed.</p>


2018 ◽  
Vol 57 (4) ◽  
pp. 821-836 ◽  
Author(s):  
FengJiao Chen ◽  
ShaoXue Sheng ◽  
ZhengQing Bao ◽  
HuaYang Wen ◽  
LianSheng Hua ◽  
...  

AbstractUtilizing the cloud parameters derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner and the near-surface rainfall detected by the TRMM Precipitation Radar, the differences of cloud parameters for precipitating clouds (PCs) and nonprecipitating clouds (NPCs) are examined in tropical cyclones (TCs) during daytime from June to September 1998–2010. A precipitation delineation scheme that is based on cloud parameter thresholds is proposed and validated using the independent TC datasets in 2011 and observational datasets from Terra/MODIS. Statistical analysis of these results shows that the differences in the effective radius of cloud particles Re are small for PCs and NPCs, while thick clouds with large cloud optical thickness (COT) and liquid water path (LWP) can be considered as candidates for PCs. The probability of precipitation increases rapidly as the LWP and COT increase, reaching ~90%, whereas the probability of precipitation reaches a peak value of only 30% as Re increases. The combined threshold of a brightness temperature at 10.8 μm (BT4) of 270 K and an LWP of 750 g m−2 shows the best performance for precipitation discrimination at the pixel levels, with the probability of detection (POD) reaching 68.2% and false-alarm ratio (FAR) reaching 31.54%. From MODIS observations, the composite scheme utilizing BT4 and LWP also proves to be a good index, with POD reaching 77.39% and FAR reaching 24.2%. The results from this study demonstrate a potential application of real-time precipitation monitoring in TCs utilizing cloud parameters from visible and infrared measurements on board geostationary weather satellites.


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