Validation of satellite-borne precipitation radars by raingauges and disdrometers over the northeastern Indian subcontinent

<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>

Spatial patterns of high-elevation precipitation observed through spaceborne precipitation radars

<p>Spaceborne-radar precipitation products at high altitudes entail close attention to geographically inherent retrieval uncertainties. The lowest levels free from surface clutter are ~1 km higher in rugged mountainous areas than those over flatlands. The clutter-removal filter masks precipitation echoes at altitudes below 3 km from the surface at the swath edge over narrow valleys in the Himalayas. In this study, precipitation profiles at levels with clutter interference were estimated using an a priori precipitation profile dataset based on near-nadir observations. The corrected precipitation dataset was generated based on the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) product at a spatial resolution of 0.01° around the Trambau Glacier terminus in the Nepal Himalayas, where ground observation sites were installed in 2016. The occurrence frequency of precipitation was considerably small compared with the in situ observation because of limitations in the sensor sensitivity. The occurrence frequency of light precipitation is increased by the Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) Core Observatory, and the low-level precipitation profile correction mitigates underestimation bias by ~10%. In this presentation, the detectability of fine-scale precipitation climatology and the local characteristics of its diurnal variation at high altitudes are discussed based the combination of the TRMM PR and GPM DPR products.</p>

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.

Karakteristik Ketinggian Melting Layer di Indonesia Berdasarkan Radar Hujan Yang Terpasang Di Satelit TRMM

Ketinggian melting layer atau freezing level height (FH) di Indonesia telah diteliti melalui data radar hujan yang terpasang di satelit Tropical Rainfall Measuring Mission (TRMM). Data yang digunakan adalah data TRMM 2A25 versi 7 selama 2011-2013. Nilai FH dari TRMM dibandingkan dengan nilai yang direkomendasikan oleh model ITU-R P.839. FH di Indonesia memiliki variasi musiman dan diurnal yang signifikan. Rata-rata bulanan FH menunjukkan pola bimodal dengan dua puncak dan dua lembah, mirip dengan pola curah hujan dan temperatur permukaan air laut di Indonesia. Puncak FH teramati pada bulan-bulan basah (musim hujan) ketika temperatur permukaan air laut tinggi. Nilai FH mencapai puncaknya pada sore hari yaitu sekitar jam 18-19 waktu setempat. Adanya perbedaan pola FH antara darat dan laut yang menandakan adanya pengaruh sirkulasi darat-laut (land-sea breezes). Pada dini dan pagi hari, hujan dengan FH > 5 km tidak teramati di daratan tetapi pada siang dan sore hari jumlahnya meningkat, terutama di Sumatera, Kalimantan dan Papua. Nilai FH tertinggi yang teramati dalam penelitian ini adalah 5,55 km yang teramati pada 2013, dan nilai terendah adalah 4,40 km, yang teramati pada 2012. Sebagian besar hujan yaitu sekitar 82% dari total data, memiliki FH lebih rendah dari yang direkomendasikan oleh ITU-R P.839 (5 km). Dengan demikian, model ITU-R menakar FH lebih tinggi dari semestinya. Selain itu, asumsi nilai FH yang konstan (5 km) dalam model ITU-R juga tidak tepat karena nilai FH di Indonesia menunjukkan variasi diurnal dan musiman yang signifikan.Kata kunci : melting layer, Indonesia, TRMM-PR, ITU-R P.839, variasi diurnal, variasi musiman

Relationships between Extreme Rain Rates and Convective Intensities from the Perspectives of TRMM and WSR-88D Radars

TRMM PR 2A25, version 7 (V7), retrievals of reflectivity Z and rainfall rate R are compared with WSR-88D dual-polarimetric S-band radar data for 28 radars over the southeastern United States after matching their horizontal resolution and sampling. TRMM Ku-band measurements are converted to S-band approximations to more directly compare reflectivity estimates. Rain rates are approximated from WSR-88D data using the CSU–hydrometeor identification rainfall optimization (HIDRO) algorithm. Tropics-wide TRMM retrievals confirm previous findings of a low overlap fraction between extreme convective intensity, as approximated by the maximum 40-dBZ height, and extreme near-surface rain rates. WSR-88D data also confirm this low overlap but show that it is likely higher than TRMM PR retrievals indicate. For maximum 40-dBZ echo heights that extend above the freezing level, mean WSR-88D reflectivities at low levels are approximately 2 dB higher than TRMM PR reflectivities. Higher WSR-88D-retrieved rain rates for a given low-level reflectivity combine with these higher low-level reflectivities for a given maximum 40-dBZ height to produce rain rates that are approximately double those retrieved by the TRMM PR for maximum 40-dBZ heights that extend above the freezing level. TRMM PR path-integrated attenuation, and WSR-88D specific differential phase, differential reflectivity, and hail fraction indicate that the TRMM PR 2A25 V7 algorithm is possibly misidentifying low–midlevel hail and/or graupel as greater attenuating liquid, or vice versa. This misidentification, coupled with underestimation of path-integrated attenuation caused by nonuniform beamfilling and higher rain rates produced by specific differential phase (KDP)–R than Z–R relationships, results in low-biased 2A25 V7 rain rates in intense convection.