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The Dynamical–Statistical–Analog Ensemble Forecast for Landfalling Typhoon Daily Precipitation (DSAEF_LTP_D) model is introduced in this paper. To improve the DSAEF_LTP_D model's forecasting ability, tropical cyclone (TC) translation speed was introduced. Taking Supertyphoon Lekima (2019), which produced widespread heavy rainfall from 9 to 11 August 2019 as the target TC, two simulation experiments associated with the prediction of daily precipitation were conducted: the first involving the DSAEF_LTP_D model containing only the TC track (the actual trajectory of the TC center), named DSAEF_LTP_D-1; and the second containing both TC track and translation speed, named DSAEF_LTP_D-2. The results show the following: 1) With TC translation speed added into the model, the forecasting performance for heavy rainfall (24-h accumulated precipitation exceeding 50 and 100 mm) on 9 and 10 August improves, being able to successfully capture the center of heavy rainfall, but the forecasting performance is the same as DSAEF_LTP_D-1 on 11 August. 2) Compared with four numerical weather prediction (NWP) models (i.e., ECMWF, GFS, GRAPES, and SMS-WARMS), the TS100 + TS50 (the sum of TS values for predicting 24-h accumulated precipitation of ≥100 and ≥50 mm) of DSAEF_LTP_D-2 is comparable to the best performer of the NWP models (ECMWF) on 9 and 10 August, while the performance of DSAEF_LTP_D model for predicting heavy rainfall on 11 August is poor. 3) The newly added similarity regions make up for the deficiency that the similarity regions are narrower when the TC track is northward, which leads to DSAEF_LTP_D-2 having a better forecasting performance for heavy rainfall on 11 August, with the TS100 + TS50 increasing from 0.3021 to 0.4286, an increase of 41.87%. [ABSTRACT FROM AUTHOR]

Seventeen years of 3‐hr, 0.25° resolution, precipitation data from the Tropical Rainfall Measurement Mission (TRMM) multi‐satellite precipitation analysis (TMPA) product are used to develop a global climatology of precipitation in tropical cyclones (TCs). Due to very large SDs for rainfall in each stratification by intensity class or cyclone basin, our methodology concentrates on frequency distributions and percentage representation in different rainfall rate categories. The stratifications reveal that the TC rainfall climatologies are dependent on three inter‐related factors: TC intensity, TC size and TC basin. The interdependence of the three is examined. The distributions of TC intensity classes in the different basins are not a significant contributor to the fact that certain basins (Northwest Pacific, North Atlantic) have higher TC rainfall rates than other basins (Northeast Pacific, South Indian). In contrast to this, the distributions of TC size classes between basins are a significant contributor to why some basins are wetter than others. A climatology is also presented of lifetime accumulated rainfall (LAR) in TCs. The record LAR belongs to hurricane Ivan in 2004, with 300 km3 of rain over the 0–350 km radius, and 432 km3 over 0–500 km. The largest LAR values occur almost exclusively in two cyclone basins: The Northwest Pacific and the North Atlantic. Not unexpectedly, LAR is determined primarily by TC duration, which accounts for around 70% of the variance. Examination of the full 17‐year dataset reveals a decreasing trend in both median and extreme TC rainfall rates in all basins except the Northeast Pacific. However, mechanisms responsible for this decrease are yet to be identified and may be primarily due to the sample size or data inhomogeneities. The difference between the trends and those expected from physical principles is a concern which we hope will be taken up by other investigators. [ABSTRACT FROM AUTHOR]

Recent research has strengthened the understanding of the links between climate and tropical cyclones (TCs) on various timescales. Geological records of past climates have shown century-long variations in TC numbers. While no significant trends have been identified in the Atlantic since the late 19th century, significant observed trends in TC numbers and intensities have occurred in this basin over the past few decades, and trends in other basins are increasingly being identified. However, understanding of the causes of these trends is incomplete, and confidence in these trends continues to be hampered by a lack of consistent observations in some basins. A theoretical basis for maximum TC intensity appears now to be well established, but a climate theory of TC formation remains elusive. Climate models mostly continue to predict future decreases in global TC numbers, projected increases in the intensities of the strongest storms and increased rainfall rates. Sea level rise will likely contribute toward increased storm surge risk. Against the background of global climate change and sea level rise, it is important to carry out quantitative assessments on the potential risk of TC-induced storm surge and flooding to densely populated cities and river deltas. Several climate models are now able to generate a good distribution of both TC numbers and intensities in the current climate. Inconsistent TC projection results emerge from modeling studies due to different downscaling methodologies and warming scenarios, inconsistencies in projected changes of large-scale conditions, and differences in model physics and tracking algorithms. WIREs Clim Change 2016, 7:65-89. doi: 10.1002/wcc.371 For further resources related to this article, please visit the . [ABSTRACT FROM AUTHOR]

Tropical cyclone (TC) rainfall over the Australian continent is studied using observations from 41 TC seasons 1969/1970 to 2009/2010. A total of 318 storms, whose centers either crossed the coastline or were located within 500 km of the coast, are considered in this study. Mean seasonal (November to April) contributions by TCs to the total rainfall are largest along the northern coastline from 120°-150°E. However, the percentage contributions by TCs are greatest west of 125°E, with mean coastal values of 20-40% and inland values of approximately 20%. Further east, percentages near the coast are only around 10%, and even lower inland. Inland penetration by TC rainfall is generally greatest over western portions of the continent, associated with greater inland penetration of TC tracks. During the peak of the TC season (January to March), TCs contribute around 40% to the rainfall total of coastal regions west of 120°E, while during December, TCs contribute approximately 60-70% to the total rainfall west of 115°E. Rain from TCs varies sharply between TC seasons, with some longitude bands receiving no TC rain during some seasons. For the 110°-115°E longitude band the TC rain contribution is not consistent, varying interannually from 0 to 86%. This has an impact on water supplies, with storage dams falling to low levels during some years, while filling to capacity during TC-related flood events in other years. This underlines why it is important to understand TC rainfall characteristics over the Australian continent. [ABSTRACT FROM AUTHOR]

Real-time gridded 24-h quantitative precipitation forecasts from seven operational NWP models are verified over the Australian continent. All forecasts have been mapped to a 1° latitude-longitude grid and have been verified against an operational daily rainfall analysis, mapped to the same grid. The verification focuses on two large subregions: the northern tropical monsoon regime and the southeastern subtropical regime. Statistics are presented of the bias score, probability of detection, and false alarm ratio for a range of rainfall threshold values. The basic measure of skill used in this study, however, is the Hanssen and Kuipers (HK) score and its two components: accuracy for events and accuracy for nonevents. For both regimes the operational models tend to overestimate rainfall in summer and to underestimate it in winter. In the southeastern region the models have HK scores ranging from 0.5 to 0.7, and easily outperform a forecast of persistence. Thus for the current operational NWP models, the 24-h rain forecasts can be considered quite skillful in the subtropics. On the other hand, model skill is quite low in the northern regime with HK values of only 0.2-0.6. During the summer wet season the low skill is associated with an inability to simulate the behavior of tropical convective rain systems. During the winter dry season, it is associated with a low probability of detection for the occasional rainfall event. Thus it could be said that models have no real skill at rainfall forecasts in this monsoonal wet season regime. Model skill falls dramatically for occurrence thresholds greater than 10 mm day&sup-1;. This implies that the models are much better at predicting the occurrence of rain than they are at predicting the magnitude and location of the peak values. [ABSTRACT FROM AUTHOR]

With the increasing incidence of heavy rainfall events, particularly over the monsoon regions, the highly dense populations are more vulnerable [1]. Despite the considerable efforts, NWP models still have very limited ability to forecast TC rainfall, especially for the extremely heavy rainfall and rainfall produced around TC landfalling. Built upon the important progresses in science and prediction of monsoon heavy rainfall, including heavy rainfall associated with tropical cyclones in the monsoon regions, and high-priority research topics proposed by the international monsoon science community, the following directions are recommended for future monsoon-heavy-rainfall research. More detailed studies are needed on how extreme monsoon rainfall will change as the climate warms, how the global warming, large-scale circulation [17], and local urban effects impact the heavy rainfall changes over the densely populated vulnerable urban areas, how anthropogenic and natural aerosols influence monsoon heavy rainfall under various synoptic conditions, what are the relationships of circulations and associated heavy rainfall among different monsoon regions (e.g., South Asia, East Asia, Australia), what are the roles played by land/sea-air interaction in modulating the monsoon circulation and rainfall. [Extracted from the article]