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This paper introduces the Method of Microwave Rainfall Normalization (MMN) for the Global Satellite Mapping of Precipitation (GSMaP) algorithm in its latest version (V05, algorithm version 8), released in December 2021. The method aims to mitigate the discrepancy of GSMaP rainfall estimates among passive microwave (PMW) imagers/sounders (MWIs/MWSs) due to differences in sensor specifications and retrieval algorithms. The basic idea of the MMN module is to calibrate target PMW sensors with reference sensors (the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI)) using the cumulative distribution function (CDF) of the rain rate. Differences between the CDF and normalization table for MWSs are greater than MWIs due to different rain retrieval algorithms. More (less) MWS rainfall is detected over the ocean (land) than GMI rainfall. Matchup rainfall data between GMI and a target PMW sensor are compared to evaluate MMN performance. The monthly mean rainfall and mean bias error were improved for almost all PMW sensors. This study leaves open the possibility for further inter-calibration and improvement of rain detection and heavy rainfall retrievals. [ABSTRACT FROM AUTHOR]

An orographic/nonorographic rainfall classification scheme has been introduced for the operational algorithm of the Global Satellite Mapping of Precipitation (GSMaP) for passive microwave radiometers. However, problems of overestimations and false alarms of heavy orographic rainfall remain unresolved. This is because the current scheme selected lower constant thresholds of orographic rainfall conditions for global application and used values of orographically forced upward motion w derived from near-surface atmospheric data. This study improves the conceptual model of the warm-rain process for considering the strength of the upstream flow of the low-level troposphere. Under a weak upstream current, rain reaches the foothills of the windward mountain slope because of sufficient time for condensation and precipitation enhancement by the topography. Conversely, under a strong upstream current, precipitation enhancement occurs nearer to the mountain peak. This is because the upstream current flows so quickly that there is insufficient time for enhancement of precipitation over the foothills of the windward mountain slope. After implementing a variable threshold for w that depends on the mean horizontal low-level wind, the area of orographic enhancement of rain was detected reasonably well in cases of both strong and weak winds. To improve the accuracy of estimates of orographic rainfall, an adjustment to the rain estimation was introduced using a lower-frequency channel. The biases of the rainfall estimate for the adjusted scheme from the Tropical Rainfall Measuring Mission Precipitation Radar were improved for the cases considered here as well as for the Asian region of heavy orographic rainfall over land. [ABSTRACT FROM AUTHOR]

We incorporate an orographic/nonorographic rainfall classification scheme into the Global Satellite Mapping of Precipitation algorithm for passive microwave radiometers. It improves rainfall estimation over the entire Asian region. However, low verification scores over the United States and Mexico result because vertical profiles of rainfall over the Sierra Madre Mountains are high even for orographic rainfall conditions. In this region, lightning activity is vigorous, with large amounts of solid particles such as graupels, occurring with strong convections. Hence, the orographic/nonorographic rainfall classification scheme is switched off for regions where strong lightning activity occurs in the rainfall type database. The revised zonal mean rainfall amounts obtained from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager are now in better agreement with those from the version 7 of the TRMM Precipitation Radar over the United States and Mexico, as well as Asia. [ABSTRACT FROM AUTHOR]

Representative patterns from multichannel microwave brightness temperature Tb in the midlatitude oceanic region, observed by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), are studied during precipitation events detected by the TRMM precipitation radar (PR) for three summer and winter seasons using empirical orthogonal function (EOF) analysis. The first three patterns are interpreted as rain liquid water, solid particles, and rain type based on the frequency distributions of vertical profiles of the radar reflectivity factor and the heights of the storm top, cloud top, and freezing level. The first EOF (EOF1) correlates with the near-surface rain rate. While the eigenvector for the 85.5-GHz channel is less significant for EOF1 variability in summer, those in all channels contribute equally to the variability in winter. This difference suggests that summer precipitation is caused by additional solid particles formed in developing precipitation systems. The second EOF (EOF2) represents the number of solid particles and also corresponds to the near-surface rain rate. This result suggests an increase of solid particles with the development of precipitation systems. EOF2 varies largely by echo-top height in summer and by echo-top height and freezing height in winter. The positive component score has double Tb peaks. Dividing the score into two patterns according to these peaks reveals highly developed precipitation systems, such as convective rainbands and frontal systems, and weak precipitation with shallow systems caused by cold outbreaks in the winter case. The negative component score also shows shallow and weak precipitation systems with warm rain. The third EOF (EOF3) is related to rain type. Vertical profiles show a significant bright band with a small height difference between the echo top and freezing level for negative EOF3, while positive EOF3 has no bright band with a high echo top relative to the freezing height. The results indicate that stratiform and convective precipitation systems can be characterized by EOF3. [ABSTRACT FROM AUTHOR]

Tropical Rainfall Measuring Mission (TRMM) data during June–August 1998–2003 are used to investigate diurnal variations of rain and cloud systems over the tropics and midlatitudes. The peak time of the coldest minimum brightness temperature derived from the Visible and Infrared Scanner (VIRS) and the maximum rain rate derived from the Precipitation Radar (PR) and the TRMM Microwave Imager (TMI) are compared. Time distributions are generally consistent with previous studies. However, it is found that systematic shifts in peak time relative to each sensor appeared over land, notably over western North America, the Tibetan Plateau, and oceanic regions such as the Gulf of Mexico. The peak time shift among PR, TMI, and VIRS is a few hours. The relationships among the amplitude of diurnal variation, convective frequency, storm height, and rain amount are further investigated and compared to the systematic peak time shifts. The regions where the systematic shift appears correspond to large amplitude of diurnal variation, high convective frequency, and high storm height. Over land and over ocean near the coast, the relationships are rather clear, but not over open ocean. The sensors likely detect different stages in the evolution of convective precipitation, which would explain the time shift. The PR directly detects near-surface rain. The TMI observes deep convection and solid hydrometeors, sensing heavy rain during the mature stage. VIRS detects deep convective clouds in mature and decaying stages. The shift in peak time particularly between PR (TMI) and VIRS varies by region. [ABSTRACT FROM AUTHOR]

Reliability information of satellite precipitation products is required for various applications. This study describes and evaluates a reliability flag of the Global Satellite Mapping of Precipitation Near-Real-Time precipitation product (GSMaP_NRT). This flag was developed to characterize the reliability of GSMaP_NRT data simply and qualitatively by considering its algorithm characteristics. The reliability at each pixel is represented by any one of ten levels (10 being the best and 1 the worst) by considering three major factors: 1) "surface type reliability"--which takes into account that estimation of rainfall using passive microwave sensors is better over the oceans than over land and coastal areas; 2) "low-temperature reliability"--which takes into account the lower reliability due to surface snow cover in low-temperature conditions; and 3) "Moving Vector with Kalman Filter (MVK) propagation reliability"--which means that the reliability gets worse with the increase in time since the last overpass of the passive microwave sensor. To evaluate the utility of the reliability flag, statistical indices are calculated for each reliability level using gauge-calibrated ground radar data around Japan. It is found that the reliability flag represents the differences in GSMaP accuracy: the accuracy worsens as the reliability decreases. The GSMaP errors exhibit seasonal changes that are well represented by the ten levels of the reliability flag, indicating that the reliability flag can be used to catch seasonal variations in GSMaP accuracy due to changes in environmental factors. This study also raises the possibility of improving the reliability flag by using information related to heavy orographic rainfall. It is shown how the error features of heavy orographic rainfall differ from those of the total rainfall, and it is suggested that heavy orographic rainfall information can be utilized to further improve the reliability flag. [ABSTRACT FROM AUTHOR]

Heavy ice precipitation (HIP) flags in the products of dual‐frequency precipitation radar (DPR) on board the Global Precipitation Measurement (GPM) core satellite indicate the existence of large ice particles. In this study, we analyzed the distribution of a HIP band detected along the warm front of an oceanic extratropical cyclone. The HIP band was more than 125 km long and probably exceeded the 245‐km range of the Ku‐band precipitation radar. We found two zones with distinct microphysical processes in the HIP band. Ice particles near the echo top height showed little change in their median size with height, where frontogenetical updraft was maximum. This suggests that particles are generated and grown in this zone by the updrafts. In the zone below, the particle sizes increased as the height decreased, implying particles aggregate as they fall. Plain Language Summary: Bands of heavy snowfall are often reported in the presence of extratropical cyclones over land. However, observations of bands of heavy snowfall over the ocean are limited. In this study, we detected a band of heavy snowfall occurring over the ocean using satellite‐borne precipitation radar for the first time. This signal had a narrow width of 10–20 km and a length that was likely greater than the 245‐km swath of the Ku‐band radar. We examined the change in precipitation echoes with height for the snowfall to understand how ice particles grow and subsequently result in heavy snowfall. The analysis suggested that in the upper layer of the heavy snowfall band, ice particles are produced and grown by an upward flow, and that in the middle layer, they collide with other ice crystals, resulting in larger crystals, which subsequently fall. Further statistical analysis of similar signals could reveal the structure and driving mechanisms for heavy snowfall over the land and ocean in future studies. Key Points: We detected a heavy ice precipitation (HIP) band along the warm front of an oceanic cyclone observed by GPM/DPRIce particles are grown by updraft near the echo top height of the HIP band and then aggregate in the zone below [ABSTRACT FROM AUTHOR]

This study examined the vertical gradient of radar reflectivity below the detected bright band in stratiform regions from the Tropics to the extratropical latitudes using data from the Ku‐band (13.6 GHz) precipitation radar on board the Global Precipitation Measurement (GPM) Core Observatory. Stratiform precipitation profiles with reflectivity decreasing (increasing) from the melting level toward the surface occur frequently in the tropical oceans (mid‐ and high‐latitude oceans). High fractions of downward increasing stratiform pixels are found over the North Pacific Ocean throughout the year and over East Asia except for winter. In contrast, the North American continent and the adjacent North Atlantic Ocean are characterized by low fractions of downward‐increasing pixels during summer. The difference is consistent with the dominant type of convection over East Asia (warm‐type clouds) and over the North American continent (cold‐type clouds). Even in the tropical oceans such as the Atlantic and eastern Pacific intertropical convergence zones, there are some areas with moderate fractions of downward‐increasing stratiform pixels where the warm rain process dominates. The downward reduction of reflectivity in the stratiform region of MCSs is obviously due to evaporation, which is a function of lower‐tropospheric relative humidity. The downward increase of reflectivity in stratiform regions over the midlatitude oceans appears the result of raindrop growth. This is achieved via the collection of cloud droplets while falling through low‐level clouds produced by large‐scale vertical motion in the lower troposphere due to large‐scale convergence associated with synoptic‐scale systems. This study examined the vertical structure of radar reflectivity below the detected bright band in stratiform regions using data from the Ku‐band precipitation radar on board the Global Precipitation Measurement (GPM) Core Observatory. Reflectivity decreases toward the surface in the stratiform region of mesoscale convection [(a) and (c)], indicating a downward reduction of rainwater content. In stratiform regions of synoptic‐scale weather systems, such as extratropical cyclones [(b) and (d)], reflectivity increases toward the surface, indicating a downward increase of rainwater content. [ABSTRACT FROM AUTHOR]

Rainfall over the coastal regions of western India [Western Ghats (WG)] and Myanmar [Arakan Yoma (AY)], two regions experiencing the heaviest rainfall during the Asian summer monsoon, is examined using a Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) dataset spanning 16 years. Rainfall maxima are identified on the upslope of the WG and the coastline of AY, in contrast to the offshore locations observed in previous studies. Continuous rain with slight nocturnal and afternoon-evening maxima occurs over the upslope of the WG, while an afternoon peak over the upslope and a morning peak just off the coast are found in AY, resulting in different locations of the rainfall maxima for the WG (upslope) and AY (coastline). Large rainfall amounts with small diurnal amplitudes are observed over the WG and AY under strong environmental flow perpendicular to the coastal mountains, and vice versa. Composite analysis of the boreal summer intraseasonal oscillation (BSISO) shows that the rain anomaly over the WG slopes lags behind the northward-propagating major rainband. The cyclonic systems associated with the BSISO introduces a southwest wind anomaly behind the major rainband, enhancing the orographic rainfall over the WG, and resulting in the phase lag. This lag is not observed in the AY region where more closed cyclonic circulations occur. Diurnal variations in rainfall over the WG regions are smallest during the strongest BSISO rainfall anomaly phase. [ABSTRACT FROM AUTHOR]

The authors improve the high-resolution Global Satellite Mapping of Precipitation (GSMaP) product for Typhoon Morakot (2009) over Taiwan by using an orographic/nonorographic rainfall classification scheme. For the estimation of the orographically forced upward motion used in the orographic/nonorographic rainfall classification scheme, the optimal horizontal length scale for averaging the elevation data is examined and found to be about 50 km. It is inferred that as the air ascends en masse on the horizontal scale, it becomes unstable and convection develops. The orographic/nonorographic rainfall classification scheme is extended to the GSMaP algorithm for all passive microwave radiometers in orbit, including not just microwave imagers but also microwave sounders. The retrieved rainfall rates, together with infrared images, are used for the high-resolution rainfall products, which leads to much better agreement with rain gauge observations. [ABSTRACT FROM AUTHOR]

In this study, the spatial variability in precipitation at a 0.1° scale is investigated using long-term data from the Tropical Rainfall Measuring Mission Precipitation Radar. Marked regional heterogeneities emerged for orographic rainfall on characteristic scales of tens of kilometers, high concentrations of small-scale systems (<10 km) over alpine areas, and sharp declines around mountain summits. In detecting microclimates, an additional concern is suspicious echoes observed around certain geographical areas with relatively low rainfall. A finescale land-river contrast can be extracted in the diurnal behavior of rainfall in medium-scale systems (10-100 km), corresponding to the course of the Amazon River. In addition, rainfall enhancement over small islands (0.1°-1°) was identified in terms of the storm scale. Even 0.1°-scale flat islands experience more rainfall than the adjacent ocean, primarily as a result of localized small or moderate systems. By contrast, compared with small islands, high-impact large-scale systems (>100 km) result in more rainfall over the adjacent ocean. Finescale hourly data represented the abrupt asymmetric fluctuation in rainfall across the coastline in the tropics and subtropics (30°S-30°N). Significant diurnal modulations in the rainfall due to large-scale systems are found over tropical offshore regions of vast landmasses but not over small islands or in the midlatitudes between 30° and 36°. Rainfall enhancement over small tropical islands is generated by abundant afternoon rainfall, which results from medium-scale storms that are regulated by the island size and inactivity of rainfall over coastal waters. [ABSTRACT FROM AUTHOR]

Observations of the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM PR) over 16 yr yielded hundreds of large precipitation systems (⩾100 km) for each 0.1° grid over major rainy regions. More than 90% of the rainfall was attributed to large systems over certain midlatitude regions such as La Plata basin and the East China Sea. The accumulation of high-impact snapshots reduced the significant spatial fluctuation of the rain fraction arising from large systems and allowed the obtaining of sharp images of the geographic rainfall pattern. Widespread systems were undetected over low-rainfall areas such as regions off Peru. Conversely, infrequent large systems brought a significant percentage of rainfall over semiarid tropics such as the Sahel. This demonstrated an increased need for regional sampling of extreme phenomena. Differences in data collected over a period of 16 yr were used to examine sampling adequacy. The results indicated that more than 10% of the 0.1°-scale sampling error accounted for half of the TRMM domain even for a 10-yr data accumulation period. Rainfall at the 0.1° scale was negatively biased in the first few years for over more than half of the areas because of a lack of high-impact samples. The areal fraction of the 0.1°-scale climatology with a 50% accuracy exceeded 95% in the ninth year and in the fifth year for those areas with rainfall >2 mm day-1. A monotonic increase in the degree of similarity of finescale rainfall to the best estimate with an accuracy of 10% illustrated the need for further sampling. [ABSTRACT FROM AUTHOR]