Guide on the Tropical Cyclone Early Warning System
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Estimates of Tropical Cyclone Geometry Parameters Based on Best Track Data
https://doi.org/10.5194/nhess-2019-119 Preprint. Discussion started: 27 May 2019 c Author(s) 2019. CC BY 4.0 License. Estimates of tropical cyclone geometry parameters based on best track data Kees Nederhoff1, Alessio Giardino1, Maarten van Ormondt1, Deepak Vatvani1 1Deltares, Marine and Coastal Systems, Boussinesqweg 1, 2629 HV Delft, The Netherlands 5 Correspondence to: Kees Nederhoff ([email protected]) Abstract. Parametric wind profiles are commonly applied in a number of engineering applications for the generation of tropical cyclone (TC) wind and pressure fields. Nevertheless, existing formulations for computing wind fields often lack the required accuracy when the TC geometry is not known. This may affect the accuracy of the computed impacts generated by these winds. In this paper, empirical stochastic relationships are derived to describe two important parameters affecting the 10 TC geometry: radius of maximum winds (RMW) and the radius of gale force winds (∆AR35). These relationships are formulated using best track data (BTD) for all seven ocean basins (Atlantic, S/NW/NE Pacific, N/SW/SE Indian Oceans). This makes it possible to a) estimate RMW and ∆AR35 when these properties are not known and b) generate improved parametric wind fields for all oceanic basins. Validation results show how the proposed relationships allow the TC geometry to be represented with higher accuracy than when using relationships available from literature. Outer wind speeds can be 15 well reproduced by the commonly used Holland wind profile when calibrated using information either from best-track-data or from the proposed relationships. The scripts to compute the TC geometry and the outer wind speed are freely available via the following URL. -
REPORT of the 46Th MEETING
REPORT OF THE 46th MEETING ARCADIA, CALIFORNIA NOVEMBER 27-29, 2012 2012 NAFC-FMWG Minutes Minutes of the 46th Annual Meeting of the North American Forest Commission – Fire Management Working Group Arcadia, California, USA Angeles National Forest Conference Room November 27-29, 2012 Tuesday November 27th, 2012 Hosted by the US Forest Service 1. Welcome Meeting called to order by Dale Dague of the US Forest Service, who welcomed everyone on behalf of the North American Forest Commission, thanked them for their attendance, and introduced Angeles National Forest Fire Management Officer James Hall. James Hall, Fire Management Officer, US Forest Service Angeles National Forest expressed his pleasure at having this group on the Angeles National Forest as the inaugural meeting in the newly remodeled training facility located at the Angeles National Forest Headquarters. 2. Introductions Roundtable introductions completed (see Appendix 1 for list of delegates in attendance) and Dale Dague conducted a review of the agenda and meeting logistics. 3. Meeting Overview Tuesday, November 27/13 Country Reports – Mexico, Canada, USA Review of 2011 FMWG meeting minutes CONANP Membership Proposal FMWG Charter Review Reducing Emissions from Deforestation and Forest Degradation NAFC website proposal Review FMWG Work Plan and Action Items Hurricane Sandy Report International Liaison Committee (ILC) Update 6th International Wildland Fire Conference Update Wednesday, November 28/13 Field Trip to the Station Fire, Angeles National Forest Banquet for meeting delegates Thursday, November 29/13 Texas Wildfires of 2011 Forest Fire Managers Group (FFMG Update NAFC Update Travel to San Dimas Technology and Development Center (SDTDC) Tour of SDTDC Bilateral Wildfire Agreements update ICS Glossary Update (French Translation) Page 1 of 62 2012 NAFC-FMWG Minutes 4. -
AL012016 Alex.Pdf
NATIONAL HURRICANE CENTER TROPICAL CYCLONE REPORT HURRICANE ALEX (AL012016) 12 – 15 January 2016 Eric S. Blake National Hurricane Center 13 September 2016 NASA-MODIS VISIBLE IMAGE OF ALEX AT 1530 UTC 14 JANUARY 2016. Alex was a very unusual January hurricane in the northeastern Atlantic Ocean, making landfall on the island of Terceira in the Azores as a 55-kt tropical storm. Hurricane Alex 2 Hurricane Alex 12 – 15 JANUARY 2016 SYNOPTIC HISTORY The precursor disturbance to Alex was first noted over northwestern Cuba on 6 January as a weak low along a stationary front. A strong mid-latitude shortwave trough caused the disturbance to intensify into a well-defined frontal wave near the northwestern Bahamas by 0000 UTC 7 January. The extratropical low then moved northeastward, passing about 75 n mi north of Bermuda late on 8 January. Steered under an anomalous blocking pattern over the east-central Atlantic Ocean, the system turned east-southeastward by 10 January, and strengthened to a hurricane-force extratropical low. The change in track caused the system to move over warmer (and anomalously warm) waters, and moderate convection near the center on that day helped initiate the system’s transition to a tropical cyclone. The low began to weaken as it lost its associated fronts, diving to the south-southeast late on 11 January around a mid-latitude trough over the eastern Atlantic. Significant changes were noted the next day, with the large area of gale-force winds shrinking and becoming more symmetric about the cyclone’s center. Convection also increased near the low, and by 1800 UTC 12 January, frontal boundaries appeared to no longer be associated with the cyclone. -
Portugal – an Atlantic Extreme Weather Lab
Portugal – an Atlantic extreme weather lab Nuno Moreira ([email protected]) 6th HIGH-LEVEL INDUSTRY-SCIENCE-GOVERNMENT DIALOGUE ON ATLANTIC INTERACTIONS ALL-ATLANTIC SUMMIT ON INNOVATION FOR SUSTAINABLE MARINE DEVELOPMENT AND THE BLUE ECONOMY: FOSTERING ECONOMIC RECOVERY IN A POST-PANDEMIC WORLD 7th October 2020 Portugal in the track of extreme extra-tropical storms Spatial distribution of positions where rapid cyclogenesis reach their minimum central pressure ECMWF ERA 40 (1958-2000) Events per DJFM season: Source: Trigo, I., 2006: Climatology and interannual variability of storm-tracks in the Euro-Atlantic sector: a comparison between ERA-40 and NCEP/NCAR reanalyses. Climate Dynamics volume 26, pages127–143. Portugal in the track of extreme extra-tropical storms Spatial distribution of positions where rapid cyclogenesis reach their minimum central pressure Azores and mainland Portugal On average: 1 rapid cyclogenesis every 1 or 2 wet seasons ECMWF ERA 40 (1958-2000) Events per DJFM season: Source: Trigo, I., 2006: Climatology and interannual variability of storm-tracks in the Euro-Atlantic sector: a comparison between ERA-40 and NCEP/NCAR reanalyses. Climate Dynamics volume 26, pages127–143. … affected by sting jets of extra-tropical storms… Example of a rapid cyclogenesis with a sting jet over mainland 00:00 UTC, 23 Dec 2009 Source: Pinto, P. and Belo-Pereira, M., 2020: Damaging Convective and Non-Convective Winds in Southwestern Iberia during Windstorm Xola. Atmosphere, 11(7), 692. … affected by sting jets of extra-tropical storms… Example of a rapid cyclogenesis with a sting jet over mainland Maximum wind gusts: Official station 140 km/h Private station 00:00 UTC, 23 Dec 2009 203 km/h (in the most affected area) Source: Pinto, P. -
Improvement of Wind Field Hindcasts for Tropical Cyclones
Water Science and Engineering 2016, 9(1): 58e66 HOSTED BY Available online at www.sciencedirect.com Water Science and Engineering journal homepage: http://www.waterjournal.cn Improvement of wind field hindcasts for tropical cyclones Yi Pan a,b, Yong-ping Chen a,b,*, Jiang-xia Li a,b, Xue-lin Ding a,b a State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China b College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China Received 16 August 2015; accepted 10 December 2015 Available online 21 February 2016 Abstract This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data. -
2021 Rio Grande Valley/Deep S. Texas Hurricane Guide
The Official Rio Grande Valley/Deep South Texas HURRICANE GUIDE 2021 IT ONLY TAKES ONE STORM! weather.gov/rgv A Letter to Residents After more than a decade of near-misses, 2020 reminded the Rio Grande Valley and Deep South Texas that hurricanes are still a force to be reckoned with. Hurricane Hanna cut a swath from Padre Island National Seashore in Kenedy County through much of the Rio Grande Valley in late July, leaving nearly $1 billion in agricultural and property damage it its wake. While many may now think that we’ve paid our dues, that sentiment couldn’t be further from the truth! The combination of atmospheric and oceanic patterns favorable for a landfalling hurricane in the Rio Grande Valley/Deep South Texas region can occur in any season, including this one. Residents can use the experience of Hurricane Hanna in 2020 as a great reminder to be prepared in 2021. Hurricanes bring a multitude of hazards including flooding rain, damaging winds, deadly storm surge, and tornadoes. These destructive forces can displace you from your home for months or years, and there are many recent cases in the United States and territories where this has occurred. Hurricane Harvey (2017), Michael (2018, Florida Panhandle), and Laura (2020, southwest Louisiana) are just three such devastating events. This guide can help you and your family get prepared. Learn what to do before, during and after a storm. Your plan should include preparations for your home or business, gathering supplies, ensuring your insurance is up to date, and planning with your family for an evacuation. -
The Rio Grande River Floods the National Butterfly Center
Jeffrey Glassberg Jeffrey The Rio Grande River Floods the National Butterfly Center by Pat Wogan 24 American Butterflies,Fall 2010 25 Left: An interpretive kiosk on the south side of the National Butterfly Center, just south of the levy, was destroyed by the Above left: The storm track of flooding. July 19, Hurricane Alex. Color shows 2010. storm intensity with blue indicating a tropical depression, cream a category 1 hurricane and yellow a Jeffrey Glassberg Jeffrey category 2 hurricane. Above right: A satellite photo of Left: Volunteers Hurricane Alex as it made landfall. constructing the same interpretive Right: A map of the Rio Grande kiosk in 2009. Watershed in extreme southern One can estimate Texas and northeastern Mexico. the depth of the flooding water Overleaf: A view of the southern at this point by portion of the National Butterfly comparing the two Center on July 19, 2010. photos. It looks to be about five and one-half feet. In late June, 2010, Tropical Depression Although the hurricane’s high winds Alex formed in the Atlantic. Moving into and heavy rainfall led to immediate damage, the Gulf of Mexico, Alex moved rapidly including flooding on South Padre Island, it toward northeastern Mexico and became was the later effects of the hurricane’s rainfall Hurricane Alex on June 30. Intensifying as that caused more serious problems in south it approached land, the storm made landfall Texas. rise. Then came Alex. On July 15, 2010, Within a few days, it became clear that the near Soto la Marina in the state of Tamaulipas, The Rio Grande River Watershed, the life water levels at Falcon Reservoir, about 50 capacity of the floodway was less than was Mexico with sustained winds of more than 100 blood of extreme south Texas, drains only miles northwest of the National Butterfly needed. -
Tropical Weather Discussion
TROPICAL WEATHER DISCUSSION • Purpose The Tropical Weather Discussion describes major synoptic weather features and significant areas of disturbed weather in the tropics. The product is intended to provide current weather information for those who need to know the current state of the atmosphere and expected trends to assist them in their decision making. The product gives significant weather features, areas of disturbed weather, expected trends, the meteorological reasoning behind the forecast, model performance, and in some cases a degree of confidence. • Content The Tropical Weather Discussion is a narrative explaining the current weather conditions across the tropics and the expected short-term changes. The product is divided into four different sections as outline below: 1. SPECIAL FEATURES (event-driven) The special features section includes descriptions of hurricanes, tropical storms, tropical depressions, subtropical cyclones, and any other feature of significance that may develop into a tropical or subtropical cyclone. For active tropical cyclones, this section provides the latest advisory data on the system. Associated middle and upper level interactions as well as significant clouds and convection are discussed with each system. This section is omitted if none of these features is present. 2. TROPICAL WAVES (event-driven) This section provides a description of the strength, position, and movement of all tropical waves analyzed on the surface analysis, from east to west. A brief reason for a wave’s position is usually given, citing surface observations, upper air time sections, satellite imagery, etc. The associated convection is discussed with each tropical wave as well as any potential impacts to landmasses or marine interests. -
NWS Unified Surface Analysis Manual
Unified Surface Analysis Manual Weather Prediction Center Ocean Prediction Center National Hurricane Center Honolulu Forecast Office November 21, 2013 Table of Contents Chapter 1: Surface Analysis – Its History at the Analysis Centers…………….3 Chapter 2: Datasets available for creation of the Unified Analysis………...…..5 Chapter 3: The Unified Surface Analysis and related features.……….……….19 Chapter 4: Creation/Merging of the Unified Surface Analysis………….……..24 Chapter 5: Bibliography………………………………………………….…….30 Appendix A: Unified Graphics Legend showing Ocean Center symbols.….…33 2 Chapter 1: Surface Analysis – Its History at the Analysis Centers 1. INTRODUCTION Since 1942, surface analyses produced by several different offices within the U.S. Weather Bureau (USWB) and the National Oceanic and Atmospheric Administration’s (NOAA’s) National Weather Service (NWS) were generally based on the Norwegian Cyclone Model (Bjerknes 1919) over land, and in recent decades, the Shapiro-Keyser Model over the mid-latitudes of the ocean. The graphic below shows a typical evolution according to both models of cyclone development. Conceptual models of cyclone evolution showing lower-tropospheric (e.g., 850-hPa) geopotential height and fronts (top), and lower-tropospheric potential temperature (bottom). (a) Norwegian cyclone model: (I) incipient frontal cyclone, (II) and (III) narrowing warm sector, (IV) occlusion; (b) Shapiro–Keyser cyclone model: (I) incipient frontal cyclone, (II) frontal fracture, (III) frontal T-bone and bent-back front, (IV) frontal T-bone and warm seclusion. Panel (b) is adapted from Shapiro and Keyser (1990) , their FIG. 10.27 ) to enhance the zonal elongation of the cyclone and fronts and to reflect the continued existence of the frontal T-bone in stage IV. -
Dependency of U.S. Hurricane Economic Loss on Maximum Wind Speed And
Dependency of U.S. Hurricane Economic Loss on Maximum Wind Speed and Storm Size Alice R. Zhai La Cañada High School, 4463 Oak Grove Drive, La Canada, CA 91011 Jonathan H. Jiang Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109 Corresponding Email: [email protected] Abstract: Many empirical hurricane economic loss models consider only wind speed and neglect storm size. These models may be inadequate in accurately predicting the losses of super-sized storms, such as Hurricane Sandy in 2012. In this study, we examined the dependencies of normalized U.S. hurricane loss on both wind speed and storm size for 73 tropical cyclones that made landfall in the U.S. from 1988 to 2012. A multi-variate least squares regression is used to construct a hurricane loss model using both wind speed and size as predictors. Using maximum wind speed and size together captures more variance of losses than using wind speed or size alone. It is found that normalized hurricane loss (L) approximately follows a power law relation c a b with maximum wind speed (Vmax) and size (R). Assuming L=10 Vmax R , c being a scaling factor, the coefficients, a and b, generally range between 4-12 and 2-4, respectively. Both a and b tend to increase with stronger wind speed. For large losses, a weighted regression model, with a being 4.28 and b being 2.52, produces a reasonable fitting to the actual losses. Hurricane Sandy’s size was about 3.4 times of the average size of the 73 storms analyzed. -
The Asian Monsoon in the Superparameterized CCSM and Its Relationship to Tropical Wave Activity
5134 JOURNAL OF CLIMATE VOLUME 24 The Asian Monsoon in the Superparameterized CCSM and Its Relationship to Tropical Wave Activity CHARLOTTE A. DEMOTT Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado CRISTIANA STAN Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland DAVID A. RANDALL Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado JAMES L. KINTER III Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland, and Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, Virginia MARAT KHAIROUTDINOV School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York (Manuscript received 15 November 2010, in final form 7 March 2011) ABSTRACT Three general circulation models (GCMs) are used to analyze the impacts of air–sea coupling and super- parameterized (SP) convection on the Asian summer monsoon: Community Climate System Model (CCSM) (coupled, conventional convection), SP Community Atmosphere Model (SP-CAM) (uncoupled, SP con- vection), and SP-CCSM (coupled, SP). In SP-CCSM, coupling improves the basic-state climate relative to SP- CAM and reduces excessive tropical variability in SP-CAM. Adding SP improves tropical variability, the simulation of easterly zonal shear over the Indian and western Pacific Oceans, and increases negative sea surface temperature (SST) biases in that region. SP-CCSM is the only model to reasonably simulate the eastward-, westward-, and northward-propagating components of the Asian monsoon. CCSM and SP-CCSM mimic the observed phasing of northward- propagating intraseasonal oscillation (NPISO), SST, precipitation, and surface stress anomalies, while SP-CAM is limited in this regard. SP-CCSM produces a variety of tropical waves with spectral characteristics similar to those in observations. -
Chapter 2.1.3, Has Both Unique and Common Features That Relate to TC Internal Structure, Motion, Forecast Difficulty, Frequency, Intensity, Energy, Intensity, Etc
Chapter Two Charles J. Neumann USNR (Retired) U, S. National Hurricane Center Science Applications International Corporation 2. A Global Tropical Cyclone Climatology 2.1 Introduction and purpose Globally, seven tropical cyclone (TC) basins, four in the Northern Hemisphere (NH) and three in the Southern Hemisphere (SH) can be identified (see Table 1.1). Collectively, these basins annually observe approximately eighty to ninety TCs with maximum winds 63 km h-1 (34 kts). On the average, over half of these TCs (56%) reach or surpass the hurricane/ typhoon/ cyclone surface wind threshold of 118 km h-1 (64 kts). Basin TC activity shows wide variation, the most active being the western North Pacific, with about 30% of the global total, while the North Indian is the least active with about 6%. (These data are based on 1-minute wind averaging. For comparable figures based on 10-minute averaging, see Table 2.6.) Table 2.1. Recommended intensity terminology for WMO groups. Some Panel Countries use somewhat different terminology (WMO 2008b). Western N. Pacific terminology used by the Joint Typhoon Warning Center (JTWC) is also shown. Over the years, many countries subject to these TC events have nurtured the development of government, military, religious and other private groups to study TC structure, to predict future motion/intensity and to mitigate TC effects. As would be expected, these mostly independent efforts have evolved into many different TC related global practices. These would include different observational and forecast procedures, TC terminology, documentation, wind measurement, formats, units of measurement, dissemination, wind/ pressure relationships, etc. Coupled with data uncertainties, these differences confound the task of preparing a global climatology.