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Heavy rainfall produced by tropical cyclones (TCs) frequently causes wide-spread damage. TCs have different patterns of rain depending on their development stage, geographical location, and surrounding environmental conditions. However, an objective system for classifying TC rain patterns has not yet been established. This study objectively classifies rain patterns of North Atlantic TCs using a Convolutional Autoencoder (CAE). The CAE is trained with 11,991 images of TC rain rates obtained from satellite precipitation estimates during 2000−2020. The CAE consists of an encoder which compresses the original TC rain image into low-dimensional features and a decoder which reconstructs an image from the compressed features. Then, TC rain images are classified by applying a k -means method to the compressed features from the CAE. We identified six TC rain patterns over the North Atlantic and confirmed that they exhibited unique characteristics in their spatial patterns (e.g., area, asymmetry, dispersion) and geographical locations. Furthermore, the characteristics of rain patterns in each cluster were closely related to storm intensity and surrounding environmental conditions of moisture supply, vertical wind shear, and land interaction. This classification of TC rain patterns and further investigations into their evolution and spatial variability can improve forecasts and help mitigate damage from these systems.

With varying tangential winds and combinations of stratiform and convective clouds, tropical cyclones (TCs) can be difficult to accurately portray when mosaicking data from ground-based radars. This study utilizes the Dual-frequency Precipitation Radar (DPR) from the Global Precipitation Measurement Mission (GPM) satellite to evaluate reflectivity obtained using four sampling methods of Weather Surveillance Radar 1988-Doppler data, including ground radars (GRs) in the GPM ground validation network and three mosaics, specifically the Multi-Radar/Multi-Sensor System plus two we created by retaining the maximum value in each grid cell (MAX) and using a distance-weighted function (DW). We analyzed Hurricane Laura (2020), with a strong gradient in tangential winds, and Tropical Storm Isaias (2020), where more stratiform precipitation was present. Differences between DPR and GR reflectivity were larger compared to previous studies that did not focus on TCs. Retaining the maximum value produced higher values than other sampling methods, and these values were closest to DPR. However, some MAX values were too high when DPR time offsets were greater than 120 s. The MAX method produces a more consistent match to DPR than the other mosaics when reflectivity is <35 dBZ. However, even MAX values are 3–4 dBZ lower than DPR in higher-reflectivity regions where gradients are stronger and features change quickly. The DW and MRMS mosaics produced values that were similar to one another but lower than DPR and MAX values.

There continues to be a need to relate rainfall produced by tropical cyclones (TCs) to moisture in the near-storm environment. This research measured the distribution of volumetric rainfall around 43 TCs at the time of landfall over the U.S. Gulf Coast. The spatial patterns of rainfall were related to atmospheric moisture, storm intensity, vertical wind shear, and storm motion. We employed a geographic information system (GIS) to perform the spatial analysis of satellite-derived rain rates and total precipitable water (TPW), which was measured on the day before landfall. Mann–Whitney U tests revealed statistically significant differences in conditions when TCs were grouped by location. TCs moving over Texas entrained dry air from the continent to produce less rainfall to the left of their moving direction. As moisture was plentiful, rainfall symmetry during landfall over the central Gulf Coast was mainly determined by the vector of vertical wind shear and storm intensity. For landfalls over the Florida peninsula, interaction with a cooler and drier air mass left of center created an uplift boundary that corresponded with more rainfall on the TC’s left side when the moisture boundary represented by the 40 mm contour of TPW existed 275–350 km from the storm center.

Irene was the most destructive tropical cyclone (TC) of the 2011 Atlantic hurricane season due to flooding from rainfall. This study used a Geographic Information System to identify TCs with similar tracks and examine the spatial attributes of their rainfall patterns. Storm-total rainfall was calculated from the Unified Precipitation Dataset for 11 post-1948 storms and statistics corresponding to the top 10% of rainfall values left of track were computed. Irene-type tracks occur every 6.6 years. Floyd (1999) produced the highest rainfall overall and was the closest analog to Irene, yet Irene produced more rainfall in the northeastern U.S. where higher values of precipitable water existed. Areas of high rainfall expanded as five TCs moved north due to synoptic-scale forcing during extratropical transition. However, Irene and three other TCs did not exhibit this pattern. The amount of moisture in the environment surrounding the TC, rather than storm speed or intensity, exhibited the strongest correlations with rainfall totals and their spatial distribution. These results demonstrate the high variability that exists in the production of rainfall among TCs experiencing similar steering flow, and show that advection of moisture from the tropics is key to higher rainfall totals in the mid-latitudes.

The western Gulf Coast and Caribbean coast are regions that are highly vulnerable to precipitation associated with tropical cyclones (TCs). Defining the spatial dimensions of TC rain fields helps determine the timing and duration of rainfall for a given location. Therefore, this study measured the area, dispersion, and displacement of light and moderate rain fields associated with 35 TCs making landfalls in this region and explored conditions contributing to their spatial variability. The spatial patterns of satellite-estimated rain rates are determined through hot spot analysis. Rainfall coverage is largest as TCs approach the western Caribbean coast, and smaller as TCs move over the Gulf of Mexico (GM) after making landfall over the Yucatan Peninsula. The rain fields are displaced eastward and northward over the western and central Caribbean Sea and the central GM. Rainfall fields have more displacement toward the west and south, which is over land, when TCs move over the southern GM, possibly as a result of the influence of Central American gyres. The area and dispersion of rainfall are significantly correlated with storm intensity and total precipitable water. The displacement of rainfall is significantly correlated with vertical wind shear. Over the Bay of Campeche, TC precipitation extends westward, which may be related to the convergence of moisture above the boundary layer from the Pacific Ocean and near-surface convergence enhanced by land. Additionally, half of the storms produce rainfall over land about 48 h before landfall. TCs may produce light rainfall over land for more than 72 h in this region.

A tropical cyclone (TC) is a cyclonic weather system with compact, centrally organized precipitation. As a TC transitions from a symmetric warm-core cyclone to an extratropical system, or as the TC dissipates, the weather system loses its characteristic central, symmetric qualities. In this article, we demonstrate a shape metric methodology that can be used to assess the overall evolution of and the spatiotemporal positions of significant changes to synoptic-scale precipitation structure. We first illustrate this methodology using three-hourly North American Regional Reanalysis (NARR) accumulated precipitation in Hurricane Katrina (2005) and then extend the analysis to all 2004 to 2015 U.S. landfalling TCs. To quantify the shape of the precipitation pattern, we construct a binary image by limiting the search radius to a distance of 600 km from the TC center and applying a minimum threshold based on the 90th percentile of precipitation observed within the search radius. Using the fundamental geographic concept of compactness, we formulate a suite of shape metrics that encompass the characteristic geometries of TCs moving into the midlatitudes: asymmetry, fragmentation, and dispersiveness. As we demonstrate with Hurricane Katrina, a moving Mann-Whitney U test reveals significant shape changes during the TC life cycle. These evolutionary periods correspond to structural changes observed by National Hurricane Center forecasters. Extending the analysis to all 2004 to 2015 storms, we observe increasing (decreasing) compactness in the eastern and central (western) Gulf of Mexico. Dispersiveness increases prior to landfall in most cases; however, asymmetry and fragmentation increase more commonly in western (vs. eastern) Gulf landfalls.

When a hurricane undergoes extratropical transition (ET), its rainbands evolve from a circular and compact shape to a more elongated, fragmented, and dispersed configuration with an exposed circulation center. This study calculates five metrics to measure these spatial changes in reflectivity regions as Hurricane Isabel (2003) underwent ET. A mosaic of observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) network is compared to reflectivity simulated by the Advanced Research Weather Research and Forecasting (WRF-ARW) Model. Six simulations are performed by varying the cumulus and microphysics parameterizations to produce a range of reflectivity configurations. A bias correction is applied to model-simulated reflectivity prior to the calculation of spatial metrics because lower reflectivity values are generally underrepresented, while higher values are generally overrepresented. However, the simulation with Kain–Fritsch cumulus and Morrison two-moment microphysics overpredicts reflectivity by 3–4 dBZ at all levels. We demonstrate that the spatial metrics effectively capture structural changes as reflectivity regions became more fragmented and dispersed and the center became more exposed. In this case study, the results were more sensitive to the choice of cumulus physics, compared with the choice of microphysics. The Kain–Fritsch simulations produce shapes that are too circular and solid when compared with WSR-88D observations, as the hurricanes lack distinct outer rainbands. Simulations with Tiedtke cumulus produce an elongated main reflectivity region as in WSR-88D, but with separate inner and outer rainbands that are too dispersed and fragmented. These results demonstrate the value in measuring spatial patterns rather than assessing model performance using visual inspection alone.

This study investigated spatial variations in rainfall accompanying tropical cyclones (TCs) over the western North Pacific (WNP) from June to October over 1998–2019 according to phases of El Niño–Southern Oscillation (ENSO). The rainfall characteristics of TCs include rainfall strength (RS) in the core region, total rainfall area (RA), and total rainfall volume (RV), all of which were calculated from satellite precipitation data. Spatial variation in mean RS presents a west–east dipole pattern (i.e., increases in the west of 125°E and decreases in the east during La Niña, and vice versa during El Niño) similar to that of maximum wind speed ( V max ), indicating a close relationship between them. On the other hand, both of mean RA and RV homogeneously increase during La Niña over the entire basin while they decrease during El Niño. The environmental conditions around TCs, including sea surface temperature, total column water, and divergence in the upper and lower troposphere during La Niña appear generally favorable for precipitation, while those during El Niño are unfavorable. Using multivariable regression models, we quantified the contributions of V max and environmental conditions to the variations in TC rainfall. Overall results suggest that the variation in RS according to ENSO are mainly related to V max , while those of RA and RV are strongly controlled by environmental conditions.

Tropical cyclones are incredibly destructive and deadly, inflicting immense losses to coastal properties and infrastructure. Hurricane-induced coastal floods are often the biggest threat to life and the coastal environment. A quick and accurate estimation of coastal flood extent is urgently required for disaster rescue and emergency response. In this study, a combined Digital Elevation Model (DEM) based water fraction (DWF) method was implemented to simulate coastal floods during Hurricane Harvey on the South Texas coast. Water fraction values were calculated to create a 15 km flood map from multiple channels of the Advanced Technology Microwave Sound dataset. Based on hydrological inundation mechanism and topographic information, the coarse-resolution flood map derived from water fraction values was then downscaled to a high spatial resolution of 10 m. To evaluate the DWF result, Storm Surge Hindcast product and flood-reported high-water-mark observations were used. The results indicated a high overlapping area between the DWF map and buffered flood-reported high-water-marks (HWMs), with a percentage of more than 85%. Furthermore, the correlation coefficient between the DWF map and CERA SSH product was 0.91, which demonstrates a strong linear relationship between these two maps. The DWF model has a promising capacity to create high-resolution flood maps over large areas that can aid in emergency response. The result generated here can also be useful for flood risk management, especially through risk communication.

This study examined whether varying moisture availability and roughness length for the land surface under a simulated Tropical Cyclone (TC) could affect its production of precipitation. The TC moved over the heterogeneous land surface of the southeastern U.S. in the control simulation, while the other simulations featured homogeneous land surfaces that were wet rough, wet smooth, dry rough, and dry smooth. Results suggest that the near-surface atmosphere was modified by the changes to the land surface, where the wet cases have higher latent and lower sensible heat flux values, and rough cases exhibit higher values of friction velocity. The analysis of areal-averaged rain rates and the area receiving low and high rain rates shows that simulations having a moist land surface produce higher rain rates and larger areas of low rain rates in the TC’s inner core. The dry and rough land surfaces produced a higher coverage of high rain rates in the outer regions. Key differences among the simulations happened as the TC core moved over land, while the outer rainbands produced more rain when moving over the coastline. These findings support the assertion that the modifications of the land surface can influence precipitation production within a landfalling TC.