Tropical Cyclone Center Research Articles

The G-IV Inner Circumnavigation: A Story of Successful Organic Interactions Between Research and Operations at NOAA

Abstract This study describes the research-to-operations process leading to a recent change in tropical cyclone (TC) reconnaissance sampling patterns as well as observing-system experiments that evaluated the impact of that change on numerical weather prediction model forecasts of TCs. A valuable part of this effort was having close, multipronged connections between the TC research and operational TC prediction communities at the National Oceanic and Atmospheric Administration (NOAA). Related to this work, NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) and National Hurricane Center (NHC) have a long history of close collaboration to improve TC reconnaissance. Similar connections between AOML and NOAA’s Environmental Modeling Center (EMC) also laid a foundation for the observing-system experiments conducted here. More specifically, AOML and NHC collaborated in 2018 to change how NHC uses NOAA’s Gulfstream-IV (G-IV) jet during TC synoptic surveillance missions. That change added a second circumnavigation at approximately 1.5° from TC centers, when possible. Preliminary experiments suggest that the change improved track forecasts, though the intensity results are more mixed. Despite the somewhat small sample size over a 3-yr period, the track improvement does agree with prior work. This effort has led to additional work to more fully examine G-IV sampling strategies.

The Characteristics of Tropical Cyclones and Associated High Winds in Shanghai from 2005 to 2020

The characteristics of 21 tropical cyclones (TCs) and associated high winds in Shanghai from 2005 to 2020 are analyzed based on the TC best track data, surface observations, and ERA5 reanalysis dataset. Results indicate that 95% of the TCs causing high winds in Shanghai were generated during July to September, and located to the south of Shanghai for ~80% of the impact time. Divided into four categories according to tracks, the TCs show significant discrepancies in genesis month and location, intensity, size, and duration. The findings of high winds in Shanghai highlight the combination effect of TC intensity, track, and the distance between TCs and Shanghai normalized by TC size (NDSH-TC). The maximum 10‐min sustained (Vmax) and extreme 3‐s wind speeds (Vex) in Shanghai only increase slightly with TC intensity, due to the fact that the stronger TCs are usually farther away from Shanghai. The Vmax and Vex differ in response to different TC tracks and reach the maximum value under TCs moving northward across the land west of Shanghai and the sea east of Shanghai, respectively. The urban and coastal wind speeds are the smallest and the largest respectively, indicating that the largest underlying surface roughness is associated with the most rapid urban construction. The wind speeds under the influence of TCs in four quadrants of Shanghai also present different variations with the NDSH-TC. Additionally, the wind direction in Shanghai is regularly related to the relative position between the TC center and Shanghai. A case study combined with TC In‐Fa (2106) verified the validity of the conclusions, which can provide a reference for TC forecasters to make more accurate wind field predictions.

Tropical cyclone FANTALA's three turnbacks in the northeast of Madagascar Island.

The unique Tropical cyclone (TC) Fantala appeared in the central Indian Ocean (12.4°S, 73.5°E) at 00Z on April 11 in 2016 and moved northwestward along the northeast of Madagascar at 18 Z on April 15. Then, two incomprehensible turnbacks formed a unique TC track. The dynamic mechanisms of the three turnbacks were first studied based on remote sensing and multisource reanalysis data. The results reveal that the wind field with upper divergence and lower convergence promotes the development of Fantala. The anticyclone high pressure on the middle level atmosphere is an important factor for TC turnbacks. On 15 April, the TC made the first turnback to turn northwest due to the southward anticyclone weakened to moving northwest. On 18 April, the TC made the second turnback along the anticyclone edge due to the northern high-pressure and southern low-pressure trough. On 22 April, the TC made the third turnback because the anticyclonic high press center broke into two small independent anticyclonic centers in the southwest and northeast, which created a barrier band and pushed the northern TC to move to the northwest. Meanwhile, the vertical wind shear (VWS) also provides favorable conditions for TC turnbacks. On April 18, the middle atmosphere of the TC was affected by strong easterly shear and weak southerly shear, and the second turnback was completed. On April 22, the middle level environment was affected by strong westerly shear and weak north shear, and the third turnback was completed. Additionally, heat transport from the ocean to the atmosphere provides favorable conditions for TC development. On April 18, The maximum mean latent heat flux over northeastern Madagascar was 112.94 W/m2, Tropical Cyclone Heat Potential was 39.05 kJ/cm2, and the maximum wind speed at the center of the TC was 155 kts. On April 22, The heat transfer from the equator increased by 18.08 W/m2 compared with the latent heat on 21 April, the Tropical Cyclone Heat Potential was 33.30 kJ/cm2, the maximum wind speed in the TC center was 90 kts, the high PV centerspread down from 850 mb to 900 mb. This study deepens the understanding of track forecasting during the development of a TC.

Determination of Low-Intensity Tropical Cyclone Centers in Geostationary Satellite Images Using a Physics-Enhanced Deep-Learning Model

Determination of Low-Intensity Tropical Cyclone Centers in Geostationary Satellite Images Using a Physics-Enhanced Deep-Learning Model

A Novel Tropical Cyclone Center Positioning Method Using Himawari-8 Over Western North Pacific

A Novel Tropical Cyclone Center Positioning Method Using Himawari-8 Over Western North Pacific

Developing a Data-Driven Transfer Learning Model to Locate Tropical Cyclone Centers on Satellite Infrared Imagery

Abstract In this paper, a data-driven transfer learning (TL) model for locating tropical cyclone (TC) centers from satellite infrared images in the northwest Pacific is developed. A total of 2450 satellite infrared TC images derived from 97 TCs between 2015 and 2018 were used for this paper. The TC center location model (ResNet-TCL) with added residual fully connected modules is built for the TC center location. The MAE of the ResNet-TCL model is 34.8 km. Then TL is used to improve the model performance, including obtaining a pretrained model based on the ImageNet dataset, transferring the pretrained model parameters to the ResNet-TCL model, and using TC satellite infrared imagery to fine-train the ResNet-TCL model. The results show that the TL-based model improves the location accuracy by 14.1% (29.3 km) over the no-TL model. The model performance increases logarithmically with the amount of training data. When the training data are large, the benefit of increasing the training samples is smaller than the benefit of using TL. The comparison of model results with the best track data of TCs shows that the MAEs of TCs center is 29.3 km for all samples and less than 20 km for H2–H5 TCs. In addition, the visualization of the TL-based TC center location model shows that the TL model can accurately extract the most important features related to TC center location, including TC eye, TC texture, and contour. On the other hand, the no-TL model does not accurately extract these features.

ProxyVis—A Proxy for Nighttime Visible Imagery Applicable to Geostationary Satellite Observations

Abstract Visible satellite imagery is widely used by operational weather forecast centers for tropical and extratropical cyclone analysis and marine forecasting. The absence of visible imagery at night can significantly degrade forecast capabilities, such as determining tropical cyclone center locations or tracking warm-topped convective clusters. This paper documents ProxyVis imagery, an infrared-based proxy for daytime visible imagery developed to address the lack of visible satellite imagery at night and the limitations of existing nighttime visible options. ProxyVis was trained on the VIIRS day/night band imagery at times close to the full moon using VIIRS IR channels with closely matching GOES-16/17/18, Himawari-8/9, and Meteosat-9/10/11 channels. The final operational product applies the ProxyVis algorithms to geostationary satellite data and combines daytime visible and nighttime ProxyVis data to create full-disk animated GeoProxyVis imagery. The simple versions of the ProxyVis algorithm enable its generation from earlier GOES and Meteosat satellite imagery. ProxyVis offers significant improvement over existing operational products for tracking nighttime oceanic low-level clouds. Further, it is qualitatively similar to visible imagery for a wide range of backgrounds and synoptic conditions and phenomena, enabling forecasters to use it without special training. ProxyVis was first introduced to National Hurricane Center (NHC) operations in 2018 and was found to be extremely useful by forecasters becoming part of their standard operational satellite product suite in 2019. Currently, ProxyVis implemented for GOES-16/18, Himawari-9, and Meteosat-9/10/11 is being used in operational settings and evaluated for transition to operations at multiple NWS offices and the Joint Typhoon Warning Center. Significance Statement This paper describes ProxyVis imagery, a new method for combining infrared channels to qualitatively mimic daytime visible imagery at nighttime. ProxyVis demonstrates that a simple linear regression can combine just a few commonly available infrared channels to develop a nighttime proxy for visible imagery that significantly improves a forecaster’s ability to track low-level oceanic clouds and circulation features at night, works for all current geostationary satellites, and is useful across a wide range of backgrounds and meteorological scenarios. Animated ProxyVis geostationary imagery has been operational at the National Hurricane Center since 2019 and is also currently being transitioned to operations at other NWS offices and the Joint Typhoon Warning Center.

Role of Midlatitude Baroclinic Condition in Heavy Rainfall Events Directly Induced by Tropical Cyclones in South Korea

Abstract Recurving tropical cyclones (TCs) in the western North Pacific often cause heavy rainfall events (HREs) in East Asia. However, how their interactions with midlatitude flows alter the characteristics of HREs remains unclear. The present study examines the synoptic–dynamic characteristics of HREs directly resulting from TCs in South Korea with a focus on the role of midlatitude baroclinic condition. The HREs are categorized into two clusters based on midlatitude tropopause patterns: strongly (C1) and weakly (C2) baroclinic conditions. C1, which is common in late summer, is characterized by a well-defined trough–ridge couplet and jet streak at the tropopause. As TCs approach, the trough–ridge couplet amplifies, but is anchored by divergent TC outflow. This leads to phase locking of the upstream trough with TCs and thereby prompts substantial structural changes of TCs reminiscent of extratropical transition. The synergistic TC–midlatitude flow interactions allow for widely enhanced quasigeostrophic forcing for ascent to the north of the TC center. This allows HREs to occur even before TC landfall with more inland rainfall than C2 HREs. In contrast, C2, which is mainly observed in midsummer, does not accompany the undulating tropopause. In the absence of strong interactions with midlatitude flows, TCs rapidly dissipate after HREs while maintaining their tropical features. The upward motion is confined to the inherent TC convection, and thus HREs occur only when TCs are located in the vicinity of the country. These findings suggest that midlatitude baroclinic condition determines the spatial extent of TC rainfall and the timing of TC-induced HREs in South Korea. Significance Statement This study suggests that the midlatitude flows can substantially modulate heavy rainfall events directly caused by tropical cyclones. By analyzing the 42-yr tropical cyclone–induced heavy rainfall events in South Korea, it is found that tropical cyclones and midlatitude flows strongly interact with each other, especially when the midlatitude flows meander in conjunction with a strong jet stream. Their synergistic interactions result in a poleward expansion of the tropical cyclones’ precipitation shields, leading to heavy rainfall events even before they make landfall in the country. Consequently, it is advisable to carefully monitor the midlatitude conditions as well as tropical cyclones themselves as earlier heavy rainfall warnings may be necessary depending on the former.

Sensitivity of Tropical Cyclone Development to the Vortex Size Under Vertical Wind Shear

AbstractThe sensitivity of tropical cyclone (TC) intensification to its inner size in a sheared environment is investigated in this study. Previous research indicated that TCs with smaller sizes spin up more quickly in a quiescent environment. In contrast, our idealized numerical simulations show that TCs with larger inner‐core sizes experience faster growth within a certain size range under the vertical wind shear (VWS) because stronger upper‐level outflows are established quickly for larger TCs. The presence of strong outflow diminishes the impact of VWS, causing the TC re‐alignment. In more detail, the stronger outflow locally reduces the shear, allowing the convective asymmetry to propagate to the upshear side and migrate inward toward the TC center more rapidly. The upshear convection leads to a stronger outflow and thus a greater blocking effect on the upper‐level wind, effectively reducing the VWS and thus allowing subsequent faster TC growth. Our analysis reveals that the TC re‐alignment at an earlier stage allows for significant differences in surface heat flux (surface latent heat flux [SLHF]) distribution based on size. Larger TCs exhibit larger areas of high SLHF, which create favorable thermodynamic conditions for TC developments. Conversely, smaller vortices have limited SLHF underneath, resulting in a prolonged intensification process. Furthermore, the boundary layer recovery mechanism effectively counteracts the low‐level ventilation pathway imposed by the shear. This mechanism supports the downstream deep convection development on the upshear side. This study presents a new perspective, highlighting that the impact of shear on TCs is contingent upon their sizes upon entering a sheared environment.

Tropical Cyclone-Induced Sea Surface Temperature Responses in the Northern Indian Ocean

Tropical cyclones (TCs) exert a significant influence on the upper ocean, leading to sea surface temperature (SST) changes on a global scale. However, TC-induced SST responses exhibit considerable variability in the northern Indian Ocean (NIO), and the general understanding of these responses remains limited. This paper investigates the SST changes caused by 96 TCs over an 18-year period in the NIO. Through a composite analysis utilizing satellite SST data, a comprehensive study is conducted to examine the relationship between TC characteristics, including wind speed and translation speed, and the associated SST changes. The overall findings reveal that within a radius of 300 km from the TC center, SST decreases were observed at 1702 (86%) locations, with an average SST response to TC of −0.46 °C and a maximum decrease of −2.07 °C. The most significant reduction in SST typically occurred two days after the passage of TCs, followed by a gradual recovery period exceeding 15 days for the SSTs to return to their initial values. Consistent with findings in other ocean basins, stronger and slower-moving TCs induced more substantial cooling effects. Conversely, at 279 (14%) locations, particularly associated with TCs of weaker intensities, SST increases were observed following the TC passage. Notably, 140 of these locations were situated at low latitudes, specifically between 8° N and 15° N. This study provides a quantitative analysis of the comprehensive SST response to TCs in the NIO.

Examining the Predictability of Tropical Cyclogenesis over the East Sea of Vietnam through the Ensemble-Based Data Assimilation System

In this study, we conducted experiments to assess the forecasting capabilities for tropical cyclone (TC) genesis over the east sea of Vietnam using the ensemble-based data assimilation system (EPS-DA) by WRF-LETKF. These experiments covered forecast lead times of up to 5 days and spanned a period from 2012 to 2019, involving a total of 45 TC formation events. The evaluation involved forecast probability assessments and positional and timing error analysis. Results indicated that successful forecasting depends on the lead time and initial condition quality. For TC formation from an embryo vortex to tropical depression intensity, the EPS-DA system demonstrated improved accuracy as the forecast cycle approached the actual formation time. TC centers converged towards observed locations, highlighting the potential of assimilation up to 5 days before formation. We examined statistical variations in dynamic and thermodynamic variables relevant to TC processes, offering an objective system assessment. Our study emphasized that early warnings of TC development appear linked to formation-time environmental conditions, particularly strong vorticity and enhanced moisture processes.

Variation Trends of Asymmetrical Precipitable Water Vapor Outside the Tropical Cyclone Center Over the WNP and WSP Ocean

AbstractPrecipitable water vapor (PWV) is one of the crucial driving forces for tropical cyclone (TC) genesis. Under the impact of global warming, TCs have changed their way to concentrate PWV from the ambient atmosphere. This study starts with the asymmetric characteristics of PWV in the TC's north and south sides using altimetry‐satellite‐based PWV profiles paired with 367 TCs over the western Pacific Ocean between 2008 and 2020. The results suggest that the TC‐concentrated PWV has a north‐leaning and south‐leaning property over the western North Pacific (WNP) and western South Pacific (WSP), respectively. Moreover, it is observed that the radius of TC‐concentrated PWV has broadened by 5.44% (5.83%) over the WNP (WSP) from 2008 to 2020. In contrast, the PWV gradient has decreased by 23.5% (17.5%) over the WNP (WSP). Our findings highlight that the TC‐concentrated PWV can be used as an important indicator of TC responses to global warming.

Strengthening cold wakes lead to decreasing trend of tropical cyclone rainfall rates relative to background environmental rainfall rates

Tropical cyclone (TC) rainfall is an important component of global precipitation. Based on a 22-year satellite-based record of observed precipitation from 1998 to 2019, we find that composite rainfall rates averaged within 500 km of TCs have increased. However, the background precipitation rate in the TC-affected regions has also increased. Therefore we find, by subtracting the background increase in precipitation rate from the TC precipitation composite, that TC precipitation rates--relative to the background--have decreased, and that TC-related extreme precipitation rates near the TC center have also decreased. Besides TC intensity and environmental sea surface temperature, the TC-induced sea surface cooling, typically formed like a cold wake feature, is indicated to be a potentially important contributor to TC rainfall changes. The cold wake diminishes the upward transport of surface enthalpy flux and leads to a decrease of moisture in the boundary layer, being unfavorable for the rainfall. The relative decreasing rainfall trend of TCs to the background is therefore attributed to the strengthening sea surface cooling induced by TCs. The TC-ocean interaction is suggested to be fully resolved in state-of-the-art global and regional climate models in order to improve TC rainfall simulations and projections.

Quantifying the Rightward Bias Extent of Tropical Cyclones' Cold Wakes

AbstractAlthough the cold wake of tropical cyclones (TCs) is recognized to be typically rightward biased relative to TC track (in the North Hemisphere), it remains unclear to what extent the rightward bias should be for specified TCs. Based on numerical simulations and observational statistics, this study shows that the distance of cold wake rightward bias is closely related to latitude, translation speed and radius of maximum wind (RMW) of a TC, but is independent from maximum surface wind and radial wind profile outside the RMW, namely TC intensity and size. A semi‐empirical equation is derived to represent the rightward bias extent of cold wakes. For TCs with slower translation speed, smaller RMW, or at higher latitudes, the cold wakes are less asymmetric relative to the TC track. Atmospheric simulations also show that the TC tends to be weaker and more asymmetric as the cold wake is closer to TC center.

Development and Evaluation of Multi-week Tropical Cyclone Strike Probability Forecasts in the Philippines

Tropical cyclone (TC) forecast, provided a few weeks in advance, can be beneficial for the preparation and mitigation of disaster risks in TC-vulnerable countries such as the Philippines. In this study, TC strike probability forecasts with a lead time of up to 4 wk were derived by combining the TC tracks from each ensemble member of the three models – namely, NCEP Coupled Forecast System version 2 (CFSv2), European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (ECMWF), and NCEP Global Ensemble Forecast System version 12 (GEFSv12) – to show how likely it is for a TC to form or strike an area within the 300-km radius of the TC center. To assess its performance, real-time-derived TC strike probability forecasts over the Tropical Cyclone Information Domain (TCID) of the Philippines (bounded by 0–27 °N and 110–155 °E) covering the period from 06 Oct 2020–31 Oct 2022 were evaluated. Verification metrics revealed that the skill and reliability of the TC forecasts vary with lead time and the TC being forecasted. Week 1 forecasts are reliable and can be helpful for decision-making, whereas Week 2 forecasts are considered most reliable only up to the 51–60% probability interval. On the other hand, forecasts with 3–4-wk lead times are reliable for probabilities less than 20%. The case study performed using five TCs with different intensity classifications has shown that generally, forecasts for TCs with stronger intensity have higher skill than forecasts for relatively weaker ones. It was also observed that the magnitude of the probability values varies with the intensity changes within the validity period. These findings suggest that multi-model ensemble forecasts can be utilized for the improvement and eventual operationalization of multi-week TC strike probability forecasts over the Philippines.

Evaluating the Impacts of COSMIC-2 GNSS RO Bending Angle Assimilation on Atlantic Hurricane Forecasts Using the HWRF Model

Abstract This study evaluates the impact of assimilating Global Navigation Satellite System (GNSS) radio occultation (RO) bending angles from Formosa Satellite Mission-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) receiver satellites on Hurricane Weather Research and Forecasting (HWRF) Model tropical cyclone (TC) forecasts. Launched in June 2019, the COSMIC-2 mission provides significantly higher tropics data coverage compared to its predecessor COSMIC constellation. GNSS RO measurements yield information about atmospheric pressure, temperature, and water vapor profiles. HWRF is cycled with and without COSMIC-2 bending angle data assimilation for six 2020 Atlantic hurricane cases. COSMIC-2 assimilation has little impact on HWRF track forecasts, consistent with HWRF’s design limiting cycled data assimilation impacts on surrounding large-scale flows; however, COSMIC-2 assimilation results in a statistically significant ∼8%–12% mean absolute forecast error reduction in minimum central sea level pressure for t = 36-, 54-, 60-, and 108–120-h lead times. Forecasts initialized from analyses assimilating COSMIC-2 observations also have a 1%–4% smaller 600–700-hPa specific humidity (SPFH) root-mean-squared deviation compared to radiosondes and dropwindsondes for most lead times. While not all HWRF intensity forecasts benefit from COSMIC-2 assimilation, a few show notable improvement. For example, assimilating two COSMIC-2 profiles within the inner core of developing Hurricane Hanna (2020) increases 800-hPa SPFH by up to 1 g kg−1 locally, helping to correct a dry bias. The forecast initialized from this analysis better captures Hanna’s observed intensification rate, likely because its moister inner core facilitates development of persistent deep convection near the TC center, where diabatic heating is more efficiently converted to cyclonic wind kinetic energy. Significance Statement Tropical cyclone (TC) intensification can be strongly sensitive to the lower-to-midtropospheric water vapor distribution near the storm. The COSMIC-2 GNSS radio occultation (RO) receiver satellite mission provides denser spatial coverage of atmospheric water vapor and temperature profiles over the tropics compared to other GNSS RO observation platforms. Herein, using six 2020 Atlantic TC cases, we evaluate the impacts of assimilating COSMIC-2 RO bending angles into a regional forecast model that already assimilates clear-sky satellite radiances. It is shown that COSMIC-2 assimilation yields a modest ∼10% intensity forecast skill improvement for several lead times, although more substantial intensity forecast improvement is found for a few forecasts where the COSMIC-2 observation assimilation helps correct a lower-to-midtropospheric water vapor bias.

Climatology of Tropical Cyclone Rainfall Magnitude at Different Landfalling Stages: An Emphasis on After-Landfall Rain

Abstract Estimating the magnitude of tropical cyclone (TC) rainfall at different landfalling stages is an important aspect of the TC forecast that directly affects the level of response from emergency managers. In this study, a climatology of the TC rainfall magnitude as a function of the location of the TC centers within distance intervals from the coast and the percentage of the raining area over the land is presented on a global scale. A total of 1834 TCs in the period from 2000 until 2019 are analyzed using satellite information to characterize the precipitation magnitude, volumetric rain, rainfall area, and axial-symmetric properties within the proposed landfalling categories, with an emphasis on the postlandfall stages. We found that TCs experience rainfall maxima in regions adjacent to the coast when more than 50% of their rainfall area is over the water. TC rainfall is also analyzed over the entire TC extent and the portion over land. When the total extent is considered, rainfall intensity, volumetric rain, and rainfall area increase with wind speed intensity. However, once it is quantified over the land only, we found that rainfall intensity exhibits a nearly perfect inversely proportional relation with the increase in TC rainfall area. In addition, when a TC with life maximum intensity of a major hurricane makes landfall as a tropical depression or tropical storm, it usually produces the largest spatial extent and the highest volumetric rain. Significant Statement This study aims to describe the cycle of tropical cyclone (TC) precipitation magnitude through a new approach that defines the landfall categories as a function of the percentage of the TC precipitating area over the land and ocean, along with the location of the TC centers within distance intervals from the coast. Our central hypothesis is that TC rainfall should exhibit distinct features in the long-term satellite time series for each of the proposed stages. We particularly focused on the overland events due to their effects on human activities, finding that the TCs that at some point of their life cycle reached major hurricane strength and made landfall as a tropical storm or tropical depression produced the highest volumetric rain over the land surface. This research also presents key observational evidence of the relationship between the rain rate, raining area, and volumetric rain for landfalling TCs.

Poleward Migration of Spatial Asymmetry in Tropical Cyclone Precipitation over the Western North Pacific

Comprehensive understanding of the spatial characteristics of tropical cyclone (TC) precipitation is essential for effective socioeconomic planning and scientific research. The present study examines the spatial asymmetry in TC precipitation over the western North Pacific (WNP) concerning various factors, including latitudes, sea surface temperature (SST), TC intensity, and translation speed, based on satellite observations. The results reveal a significant poleward migration of TC precipitation asymmetry particularly above 15° N. Furthermore, the asymmetry exhibits considerable sensitivity to changes in TC center latitudes and SSTs, characterized by anticlockwise and northeastward migration, respectively. The poleward migration of TC precipitation spatial asymmetry is primarily due to the poleward decreasing SST, increasing vertical wind shear and increasing TC translation speed. These findings contribute to a comprehensive understanding of TC behavior over the WNP and provide valuable insights for disaster preparedness and mitigation efforts.

Effects of Tropical Cyclones on Ozone Pollution in Hainan Island

Based on the 181 tropical cyclones data in the western North Pacific Ocean from 2015 to 2020, hourly ozone (O3) concentration data, and meteorological observation data of 18 cities and counties in Hainan Island, this study analyzed the impacts of tropical cyclones on ozone pollution in Hainan Island. We found that 40 (22.1%) tropical cyclones experienced O3 pollution in Hainan Island during the lifetime of tropical cyclones in the past six years. During the years with more tropical cyclones, more O3- polluted days occurred in Hainan Island. Highly polluted days, which were defined as more than or equal to three cities and counties exceeding the standard, were the most serious in 2019 with 39 (54.9%) polluted days. The tropical cyclones related to high pollution (HP) showed an increasing trend, with the trend coefficient and climatic trend rate of 0.725 (exceeding the 95% significance level) and 0.667 a-1, respectively. Tropical cyclone intensity was positively correlated with the maximum 8 h moving average (O3-8h) concentration in Hainan Island. Among them, HP-type tropical cyclones accounted for 35.4% of all samples in the typhoon (TY) intensity level. Cluster analysis of tropical cyclone paths showed that tropical cyclones from the South China Sea (type A) were the most common of the 67 (37%) and were the most likely to cause large-scale and high-concentration O3 pollution events in Hainan Island. The average number of HP tropical cyclones and ρ(O3-8h) of Hainan Island in type A were 7 and 121.90 μg·m-3, respectively. In addition, the tropical cyclone centers were located generally in the middle part of the South China Sea and the western Pacific Ocean near the Bashi Strait during the HP period. The change in meteorological conditions in Hainan Island under the influence of HP tropical cyclones was conducive to the increase in O3 concentration.

Assimilation of Coyote Small Uncrewed Aircraft System Observations in Hurricane Maria (2017) Using Operational HWRF

Abstract This study presents an initial demonstration of assimilating small uncrewed aircraft system (sUAS) data into an operational model with a goal to ultimately improve tropical cyclone (TC) analyses and forecasts. The observations, obtained using the Coyote sUAS in Hurricane Maria (2017), were assimilated into the operational Hurricane Weather Research and Forecast (HWRF) system as they could be in operations. Results suggest that the Coyote data can benefit HWRF forecasts. A single-cycle case study produced the best results when the Coyote observations were assimilated at greater horizontal resolution with more relaxed quality control (QC) than comparable flight-level high-density observations currently used in operations. The case study results guided experiments that cycled HWRF for a roughly 4-day period that covered all Coyote flights into Maria. The cycled experiment that assimilated the most data improved initial inner-core structure in the analyses and better agreed with other aircraft observations. The average errors in track and intensity decreased in the subsequent forecasts. Intensity forecasts were too weak when no Coyote data were assimilated, and assimilating the Coyote data made the forecasts stronger. Results also suggest that a symmetric distribution of Coyote data around the TC center is necessary to maximize its benefits in the current configuration of operational HWRF. Although the sample size was limited, these experiments provide insight for potential operational use of data from newer sUAS platforms in future TC applications. Significance Statement This study represents the first time that observations from a small uncrewed aircraft system (sUAS) have been assimilated into an operational numerical model. Including these data was shown to have potential for improving forecasts of tropical cyclone track and intensity. The data were obtained using the Coyote sUAS, but these results are expected to be applicable to newer platforms that will be operational soon.