Downloaded 10/05/21 01:46 PM UTC Only by China, the Philippines, and Japan (Gibney Et Al

OPERATIONAL HAZARD ASSESSMENT OF WAVES AND STORM SURGES FROM TROPICAL CYCLONES IN MEXICO

Christian M. Appendini, Michel Rosengaus, Rafael Meza-Padilla, and Victor Camacho-Magaña

We present a hazard assessment tool for wave and storm surge warning areas based on precomputed simulations using synthetic tropical cyclone events.

n September 2013, two simultaneous tropical increasing the prevention of hydrometeorological cyclones made landfall in Mexico within a 24-h hazards in Mexico. The simultaneous events of 2013 I window: Ingrid in the Gulf of Mexico and Manuel almost certainly served as a catalyst to the develop- in the Pacific. These events generated exceptional ment of CNHyTS; however, Mexico has always faced rainfall (Pedrozo-Acuña et al. 2014) that resulted disasters associated with tropical cyclones. in 192 deaths and estimated economic losses of Mexico is exposed to tropical cyclones from two $5.7 billion (U.S. dollars) (Impact Forecasting 2014). cyclogenesis regions (North Atlantic and eastern Only 4 months later, on 16 January 2014, the Mexican North Pacific), creating different challenges at the president announced the creation of a National Hurri- federal level toward emergency response. Tropical cane and Severe Storms Center (CNHyTS) tasked with cyclones in the eastern North Pacific represent approximately 18% of global events (Frank and Young 2007) and typically strike Mexico or have a direct AFFILIATIONS: Appendini, Meza-Padilla, and Camacho- impact when traveling along the Mexican coast, even Magaña—Laboratorio de Ingeniería y Procesos Costeros, Insti- tuto de Ingeniería, Universidad Nacional Autónoma de México, without landfall. One of the world’s tropical cyclone Sisal, Yucatán, México; Rosengaus—Advisor to the National “hotspots” is located ~500 km south of Los Cabos Water Commission of Mexico, Mexico City, Mexico (tip of the Baja California Peninsula) and 500 km CORRESPONDING AUTHOR E-MAIL: Christian M. Appendini, southwest of Cabo Corrientes (southern end of the bay [email protected] of Bahia Banderas, where Puerto Vallarta is located). The abstract for this article can be found in this issue, following the Between 1949 and 2000, 83 named storms occurred table of contents. within this area, corresponding to approximately DOI:10.1175/BAMS-D-15-00170.1 8 times the density in the Atlantic just east of the In final form 9 May 2016 Florida Peninsula (Rosengaus-Moshinsky et al. 2002). ©2017 American Meteorological Society Mexico experienced the fourth highest number of landfall events between 1970 and 2009, surpassed

AMERICAN METEOROLOGICAL SOCIETY MARCH 2017 | 503 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC only by China, the Philippines, and Japan (Gibney et al. 2009). The Meteorological Development Labora- 2010). The destructive effects of tropical cyclones tory (MDL) of the National Oceanic and Atmospheric threaten the ~11,000 km of Mexican coastline, with Administration (NOAA) developed the Sea Lake and approximately half of the population (~55 million) Overland Surge from Hurricanes (SLOSH) model exposed to the direct effects of tropical cyclones, (Jelesnianski et al. 1992) as an aid to forecast storm representing a sizable fraction of the total popula- surges. The initial conception of SLOSH was to guide tion under tropical cyclone risk in Region IV (North forecasters in the development of weather bulletins at America, Central America, and the Caribbean) of the the NWS, although more recently it has been used to World Meteorological Organization (WMO). delineate storm surge levels in coastal areas (Glahn The Servicio Meteorológico Nacional (SMN), et al. 2009). The SLOSH model provides information which is analogous to the National Weather Service for evacuation planning and advisories based on the (NWS) in the United States, is responsible for weather maximum envelopes of high water (MEOW) and the and meteorological analysis in Mexico. Working maximum of MEOWs (MOMs). A MEOW is a map under the WMO framework, SMN has provided composed of the maximum storm surge level obtained tropical cyclone forecasts and guidance to other at each grid cell for a set of simulations of a particular authorities and to the general public since before storm category, forward speed, trajectory, and initial the announcement of the CNHyTS. Both coastlines tide level, where the uncertainty of landfall location of Mexico also fall under the responsibility of the is given by the run of the same storm with different WMO National Hurricane Center [NHC; also known parallel tracks. An MOM is composed of the maximum as the Regional Specialized Meteorological Center storm surge values obtained from different MEOWs (RSMC)-Miami], which provides frequent forecast for a particular storm category, so that it represents information regarding track, intensity, and wind field the worst case scenarios for such a storm category, extension (6 hourly when a tropical cyclone has been independent of the storm forward speed, trajectory, declared and 3 hourly when such a storm threatens and initial tide level. More recently, in 2007 the MDL the coastline). Moreover, in agreement with SMN, it implemented the P-surge model (Taylor and Glahn issues coastline alerts (watches and warnings) using 2008) in experimental mode to provide probabilities graphical products. of a given storm surge level. The P-surge model uses The NHC products include uncertainty estimates SLOSH to run an ensemble of hypothetical storms on the forecasted track, but forecasts of the destruc- based on an NHC advisory. The ensemble is based on tive effects of tropical cyclones (i.e., wind and rainfall permutations of the forecasted storm, including differ- fields over the continent and wave and storm surges ent tracks, speeds, and wind intensity, with historical along the coastline) are not among its international forecast errors and uncertainty for each parameter responsibilities. Such estimates are critical for haz- incorporated in order to assign a weight for each track. ard management preparedness and response, and The SLOSH model calculates the maximum storm each country under the threat of tropical cyclones surge derived from each storm at every grid cell, and needs to develop their own operational tools for haz- the probability error is included as the weight for each ards warning. In the case of Mexico, a preliminary storm to create a probabilistic storm surge map. CNHyTS was embedded within the existing SMN Acting above the storm surge, waves are another institutional structure in May 2015 and included a important hazard from tropical cyclones. In the 24-h team of forecasters tasked with interpreting United States, wave guidance is provided by the En- NHC bulletins and providing more detailed tropical vironmental Modeling Center (EMC) of the NWS, cyclone guidance related to hazard management. The which has a group of experts dedicated to wave CNHyTS seeks to provide forecasts of the destructive forecasting. The EMC has provided wave guidance effects of tropical cyclones by developing its own op- based on nine grids covering their area of respon- erational tools, starting with rapid wave and storm sibility, ranging from a global resolution of 0.5° to surge forecasting. fine-resolution grids of up to 1/15° covering U.S. In an operational setup, wave and storm surge fore- coastal areas (Chawla et al. 2013). Recently, the EMC casts should be disseminated within minutes of receiv- developed the Nearshore Wave Prediction System ing NHC forecasts. In the United States, where roughly (van der Westhuysen et al. 2013) for local weather half of all fatalities are related to storm surges (Rap- forecast offices, allowing them to perform high- paport 2014), considerable efforts have been devoted resolution wave forecasting consistent with their to storm surge forecasting since the establishment of wind forecasts, where EMC only provides the wave the Storm Surge Unit by the NHC in 1980 (Rappaport boundary conditions.

504 | MARCH 2017 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC The use of operational wave and storm surge mod- background but do need a strong understanding of els in the United States is possible in part because of the physical processes driving wave and storm surge long-term federal funding to the storm surge and wave generation and propagation. This requirement was forecasting programs at NOAA (e.g., the Hurricane important because forecasters at CNHyTS are not Forecast Improvement Project started with a $13 mil- necessarily modelers, as the implementation of de- lion amendment to NOAA’s budget; Gall et al. 2013). terministic/probabilistic numerical models is not a In contrast, developing countries under the NHC short-term goal of the organization. The operational area of responsibility have limited funding for the tool was implemented in test mode in early 2015 and development of operational forecasts. For instance, the has already been used during a hurricane season. SMN has not been involved in operational modeling of ocean hazards and has only had limited funding SYSTEM DATABASE. The Quick Assessment available for research projects in academic institutions. Tool for Waves and Storm Surges under Tropical Furthermore, the use of high-fidelity operational waves Cyclones (QATWaSS-TC) is based on synthetic tropi- and storm surge models requires high-performance cal cyclone wind fields and precalculated wave and computing power and associated support systems (e.g., hydrodynamic simulations gathered into a catalog of secure energy, telecom bandwidth, and redundancy), events (i.e., the system database), which was generated which is not as readily available in developing coun- following a series of steps outlined in Fig. 1. tries as in developed countries. However, developing countries will still benefit from less sophisticated tools Synthetic events and associated wind fields. Using his- that can be developed despite tight time constraints torical events to develop the system database would and budgets. These types of tools could be used by have resulted in a limited scope, as only just over 100 forecasters with knowledge of waves and storm surges, events have made landfall in Mexico since 1980. As an independently of their modeling capabilities. alternative, we used synthetic events to create a robust As one of these tools, one could precompute the database of 3,100 events making landfall over Mexico waves and storm surges of a large set of realistic track, (1,550 each along the Pacific and Gulf of Mexico/ intensity, size, and translation speed combinations for Caribbean Sea coasts). The events represent a variety tropical cyclones and then, under the real-time threat of storm conditions related to track, forward speed, of a tropical cyclone, choose the most similar as a intensity, and landfall location. The generation of syn- proxy for wave and storm surge forecasting. However, thetic events was based on Emanuel et al. (2008), with the brief historical records available do not allow for warm-core vortices randomly seeded across the ocean. an analog tropical cyclone set because the probability These vortices may develop or decay according to the of finding a proper analog would be too low. Instead, ocean temperature climatology, and, if developed, they this type of tool could be based on synthetic tropical are stirred by a beta–advection model driven by large- cyclones, with sufficient precomputing of synthetic scale wind fields obtained through NCEP–NCAR track/intensity cases to enable users to identify analogous synthetic events to be forecast in real time. The creation of the CNHyTS provided the opportunity for the development of such a tool, although the tight schedule of the project (6 months from initial development to implementation) was only possible because of the experience of the working group. Here, we present version 1.0 of an operational tool for forecasting tropical cyclone waves and storm surge hazard areas. The forecasting tool satisfies CNHyTS requirements by demanding low computing power and the ability to be applied in real time under the threat of a tropical cyclone over Mexico. The tool 1) allows forecasts to be achieved within minutes of receiving the track/intensity/extension forecast of the NHC and 2) does not stress the limited material and human resources of a forecasting office that must provide forecasts every 3 or 6 hours. The tool was developed under Fig. 1. Flow diagram used for the generation of the the assumption that users do not need a modeling system database.

AMERICAN METEOROLOGICAL SOCIETY MARCH 2017 | 505 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC reanalysis. The seeded vortices are not considered Cuba (20.7°N, 78.3°W). Bathymetry data included tropical cyclones unless they develop wind speeds of local surveys of select areas and 1-minute gridded at least 21 m s−1. A detailed description of the genera- elevations/bathymetry for the world (ETOPO1) data tion of synthetic events can be found in Emanuel et al. (Amante and Eakins 2009); both domains and their (2006, 2008). Only the seeded vortices that became bathymetries are described in Meza-Padilla et al. tropical cyclones making landfall along the Mexican (2015). Owing to the scarcity of topographic informa- coastline were included in the system database. tion and to computational time constraints, meshes The database of synthetic events was made up were bounded by the shoreline, and flooding and of 2-hourly information for date (year, month, day, drying were not considered in the simulations. It is and hour), position (latitude, longitude), maximum important to mention that some synthetic events were wind speed, radius of maximum wind speed, atmo- generated outside the model domain, so that the swell spheric pressure in the hurricane eye, and neutral generated in the eastern Caribbean Sea or the western atmospheric pressure. This information was used to and southern Pacific was not considered in the simu- generate temporal wind and atmospheric pressure lations. While this can be considered a critical flaw in fields for each of the 3,100 synthetic events. The wind an operational wave forecast system, it was considered fields were generated using the parametric model of acceptable for this rapid forecast tool, where the main Emanuel and Rotunno (2011), as shown in Eq. (1): goal is to provide early warnings to coastal areas in   the vicinity of a possible landfall. However, forecasters + 1 2 2rR mwVfm R mw should use other sources of information (e.g., global  2  fr Vr = − , (1) wave models) to account for swell, since the severity Rr22+ 2 mw of the waves generated by a local tropical cyclone is

where Rmw is the radius of maximum winds, Vm is the also dependent on underlying sea conditions (Ochi maximum wind speed, r is the radial distance from 2003). In cases where swell is present in the area of the eye of the hurricane to any given point surround interest, this could be accounted for by the forecaster.

ing it, f is the Coriolis parameter, and Vr is the wind The MIKE 21 Spectral Wave (SW) wave model speed of the hurricane at radius r. The atmospheric was used to obtain the wave field corresponding to pressure fields were generated based on the model each synthetic tropical cyclone, and the MIKE 21 proposed by Holland (1980), as shown in Eq. (2): Hydrodynamic (HD) Flexible Mesh (FM) model was used to obtain the storm surge generated by B Pr = Pc + (Pn – Pc) exp(–Rmw/r) , (2) each event (i.e., surface elevation). The MIKE 21 SW model is a third-generation spectral model based on

where Pc is the central pressure, Pn is the ambient the wave action equation used to simulate growth, pressure, r is any given distance between the eye of decay, and transformation of wind-generated waves

the hurricane and its surrounding domain, Rmw is (Sørensen et al. 2004). The MIKE 21 HD FM model the maximum wind speed radius, and B is Holland’s solves the momentum, continuity, temperature, sa- shape parameter. For more information on the syn linity, and density equations with turbulent closure thetic events used in this study, the reader is referred scheme equations. It is based on the incompressible to Meza-Padilla et al. (2015). Reynolds-averaged Navier–Stokes (RANS) equations, which are subject to Bousinessq and hydrostatic Numerical modeling. The atmospheric pressure and pressure assumptions. The spatial discretization of wind fields for each synthetic event were used to drive the equations for both models is based on a centered a third-generation wave model and hydrodynamic finite-volume method over unstructured meshes. model. Both models are based on unstructured mesh- Further information about these models can be found es and were constructed for each basin with a coarse in DHI (2016a,b). The models can run in coupled resolution offshore (~10 km) gradually diminishing to mode so that the feedback between waves, currents, a finer resolution along the coast (~1 km). In the case and water levels are considered; however, in this of the hydrodynamic model, a few coastal locations implementation, the models were run uncoupled to were given resolutions of up to ~250 m. The Pacific reduce computational time. Both models were run domain was limited to latitude 12.5°–33.5°N and with a constant water level equal to mean sea level longitude 92°–120°W. The Gulf of Mexico/Caribbean (i.e., no tides were included in the simulations). Since Sea domain included boundaries at the Florida Strait tidal phase during landfall is not considered, forecast- (25°N, 80.5°W to 23°N, 80.5°W) and at the Caribbean ers will need to manually account for it in advisories, Sea between Central America (15°N, 83.3°W) and taking into consideration that the tidal phase may

506 | MARCH 2017 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC nonlinearly increase water levels created by the storm the synthetic events to include in the wave and storm surge (Rego and Li 2010). surge forecast. The QATWaSS-TC database was then As in many other developing countries, Mexico populated with all of the event information (tropical has very few measuring stations for waves and sea cyclone tracks and parameters) as well as the maxi- level. For instance, there are 36 tidal gauges along Texas mum envelope maps, as shown in Fig. 3. alone (NOAA 2016a), compared with 38 tidal stations for the whole of Mexico (UNAM 2016). Similarly, CHARACTERISTICS OF QATWaSS-TC. the only online wave data for Mexico are from the Figure 4 shows the conceptual model of the QA- Mexican Institute of Transport [Instituto Mexicano TWaSS-TC tool, which comprises the catalog of del Transporte (IMT) 2016], with data only available events incorporated into a database accessed through as graphic displays for recent dates. This makes it dif- Google Maps. The tool aims to help forecasters to ficult to calibrate numerical models for Mexican waters delineate vulnerable areas along the coast in rela- or even to assess the accuracy of operational tools tion to waves and storm surge hazards by providing with historical cases. Nonetheless, the hydrodynamic maximum envelope maps for wind, waves, and storm model was calibrated based on Hurricane Ike (2008) surges based on official advisories from the NHC and using tidal gauges near Galveston Bay, while the wave on the selection of synthetic events by the forecaster. model was calibrated based on different NOAA buoys The storm parameters represented by tropical in the Gulf of Mexico, as presented by Ruiz-Salcines cyclones in the database (e.g., translation speed, tra- (2013) for historical hurricanes. The final model setup jectory, landfall location, storm size, and intensity) is described in full by Meza-Padilla et al. (2015). are limited to those of the 3,100 events. However, as the synthetic events used as proxies will most likely Catalog of events. The results from each model (winds, differ in one or more characteristics from the event waves, and storm surge) were analyzed in order to being forecasted, additional uncertainty may affect obtain the maximum values during the lifetime of the accuracy of significant wave height and water each synthetic storm, giving a total of 9,300 matrices of maximum envelopes (3,100 for maximum wind intensity, 3,100 for maximum significant wave height, and 3,100 for maximum surface elevation, with each basin containing 1,550 synthetic tropical cyclones). The maximum value matrices together with the synthetic tropical cyclone tracks and intensity information composed the main database of the QATWaSS-TC. As an example of the information in the database, Fig. 2 shows the maximum envelope for the different parameters for event 903 in the Gulf of Mexico/Caribbean Sea. It is important to note that the wind speed maximum envelopes are not to be used for forecasting the track or Fig. 2. Examples of maximum envelopes for synthetic event 903 in the Gulf of intensity of the storm but Mexico/Caribbean Sea, showing (top left) maximum wind speed (m s−1), (top are part of the system as an right) maximum water level (m), (bottom left) maximum significant wave aid to the forecaster to select height (m), and (bottom right) maximum wave power (kW m−1).

AMERICAN METEOROLOGICAL SOCIETY MARCH 2017 | 507 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC advisories may create up to 20% uncertainty in storm surge estimates.

IMPLEMENTATION OF QATWaSS-TC. To il- lustrate the use of QATWaSS-TC, we present the case of Hurricane Patricia, which formed in the eastern Pacific on 20 October 2015. Though initially estimated to make landfall as a category 5 hurricane, post- analysis of data estimated landfall at approximately 67 m s−1 (i.e., a category 4 hurricane; Kimberlain et al. 2016). We selected Patricia both because it represents an extraordinary event and because 2015 was the first hurricane season to be monitored by the preliminary CNHyTS group. Based on the best track data (NOAA 2016b), Patricia had a maximum intensification rate of 54 m s−1 in 24 h, passing from a tropical storm to Fig. 3. QATWaSS-TC database structure, where lon = longitude, lat = latitude, Vm = maximum sus- a category 5 hurricane during this period. Patricia tained wind speed, Rmw = radius of maximum winds, presented the strongest winds ever recorded in the Pc = central pressure, and Pn = neutral pressure. NHC responsibility area and the lowest pressure on record in the Western Hemisphere (Kimberlain et al. levels. For instance, storm size could be more impor- 2016), second only to Super Typhoon Tip (1979) on a tant than storm intensity for generating higher storm global level. Event analysis by Kimberlain et al. (2016) surge values (Irish et al. 2008), and slower moving indicated that the strongest 1-min-averaged sustained storms may create lesser storm surges (Irish et al. winds were ~95 m s−1, and there was a minimum 2008; Rego and Li 2009) but higher flooded volumes pressure of 872 mb, occurring 11 h before landfall. (Rego and Li 2009; Appendini et al. 2014). Such un- Only 24 h before Patricia made landfall, the uncertainty could be reduced by increasing the number certainty cone from the NHC covered the coastline of synthetic events; however, the time constraints for from north of San Blas, Nayarit, to Melaque, Jalisco implementation did not allow for more simulations. (approximately 400 km of coastline), which put the While the parameters of the forecasted storm are not cities of Puerto Vallarta and Manzanillo, in addition to considered in the automatic selection of synthetic events, the user can manually deselect all tropical cyclones that do not comply with the characteristics of the event to be forecasted. The hazard assessment areas are then only a result of the events selected by the forecaster based on his or her knowledge of tropical cyclones, waves, and storm surge. Other uncertainties involved in the use of this tool reflect the actual forecasts and wind fields used in the wave and storm surge modeling. For example, Cardone and Cox (2009) showed that the real-time estimates of wind speed and storm size Fig. 4. QATWaSS-TC flow diagram, where Hs = significant wave height, produced by warning center WLs = water level, and Ws = wind speed.

508 | MARCH 2017 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC many rural areas, at risk of high seas and storm surges. on Patricia advisory 14 and user-selected synthetic Only 12 h before landfall, the main cities were still events, QATWaSS-TC generates maximum envelope under hurricane warning and voluntary evacuations maps that include individual events’ maximum enve- were taking place. Fortunately, Patricia made landfall lope maps (Fig. 6a), maxima of maximum envelope in an area of low population density and wind speeds maps from several events (Fig. 6b), and the normal- above category 3 force were limited to a concentrated ized maxima of maximum envelope maps (Fig. 6c). area around the eye, resulting in localized damage. Based on the individual plots (e.g., the maximum We used QATWaSS-TC to determine the wave and envelope map of significant wave height; Fig. 6a), the storm surge warning areas. The first step was to pro- user can select and deselect events that passed the vide the system with the actual position of the tropical first selection filter (Figs. 5a,b) and then decide which cyclone as well as a forecast location. We selected the lo- events to use for the warning area assessment (Fig. 5c). cation of the event as provided by the NHC in advisory The user criteria are critical at this stage since the 14, approximately 14 h before landfall (with estimated accuracy of the warning area forecast is based on the landfall at 2315 UTC) and corresponding to the time events included in the maxima of maximum envelope when Patricia achieved maximum intensity winds. maps. After several interactions, and when the user is The location was used together with a search radius satisfied with the choice of events, the system can plot to identify all synthetic events whose tracks passed the maximum values at each element mesh consider- through both radii. When QATWaSS-TC is initialized, ing all selected synthetic events (i.e., the maxima of a display shows an empty map and input dialog boxes maximum envelope; Fig. 6b). (Fig. 5) related to the type of event (e.g., tropical storm, While QATWaSS-TC is composed of 3,100 events, minor category 1 and 2 hurricanes, and major category it is likely that the user will have to use synthetic events 3–5 hurricanes), the event center position (present loca- with different characteristics (e.g., intensity, storm size, tion of the tropical cyclone taking place), the forecast and storm speed) in order to assess hazard areas and position (this could be a landfall location or any other uncertainty for a given storm. For instance, only the location of interest), and the search radius for both posi- Mexican coastline of the Caribbean Sea and near the tions. The default search radius for the present position United States–Mexican border is covered by synthetic is set to 30 km, which we found to be a reasonable value events from all tropical cyclone categories when mak- after several sensitivity tests. For the forecast location, ing landfall (Fig. 7). For other areas, the forecaster will the default is set to a 3-day uncertainty cone radius as need to select a combination of storms with different determined at the beginning of each hurricane season. categories to cover the uncertainty cone. In such maps Both search radii can be modified by the user during (e.g., Fig. 5b), the maxima of maximum envelopes will searches, without restarting the system. be dominated by the most intense storm, and direct After the user inputs search information, a map is interpretation will provide an inaccurate estimate displayed showing all synthetic events that meet the of potentially affected areas. In this case, forecasters search criteria (Figs. 5a,b), from which the user can will have to rely on their own understanding of storm manually select the events to use for the warning as- surge and wave processes and take into consideration sessment (Fig. 5c), and a flag is introduced to the map the uncertainties imposed by the use of a combina- at every landfall location showing coordinates and the tion of events. To aid the forecaster, we implemented a wind speed during landfall. The text is given in Spanish normalized plot for the maxima of maximum envelope since the system is to be used by an official Mexican maps, in which the values for each storm (i.e., waves, institution (for an English translation please see the surface elevation, and wind speed) are normalized appendix). The resolution of the output map interface by the maximum value. In this manner, all events in corresponds to the numerical modeling mesh. the normalized maxima of maximum have the same The user can interact several times with the search scale, with the highest intensity set to 1 (unity) for of events as well as inspect the individual maximum each individual event. For example, if the user selects envelope maps for the different parameters (signifi- a tropical storm, a category 2 event, and a category 5 cant wave height, storm surge, and wind speeds) of event, the normalization will set the maximum values the events selected and listed. This allows the user to of each to 1, so that the user can infer the warning select the events most suitable for the warning assess- areas. If the user is aware of the normalization pro- ment. The system database also contains information cess and a category 3 hurricane is approaching land, on the wave power for each synthetic event, which he or she will know, based on the events used for the can be used to assess swell at a particular location mapping, that the potential areas under threat may far from the storm (Innocentini et al. 2014). Based differ because none of the events in the system was a

AMERICAN METEOROLOGICAL SOCIETY MARCH 2017 | 509 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC Fig. 5. Criteria for synthetic events, including (a) fitting search criteria for tropical cyclones, (b) fitting search criteria for hurricanes, and (c) events selected by the user. Figures are screenshots of the QATWaSS-TC graphic interface; therefore, the text is in Spanish. Please see the appendix for a list of translated terms.

category 3 hurricane. Furthermore, in reality, a storm’s wind speed, significant wave height, or surface eleva- behavior also depends on a variety of other parameters tion. However, under an operational environment it (e.g., bathymetry, coastal morphology, storm size, and is desirable to have a minimum threshold for the translation speed). The user should be aware of the real hazard parameters to determine the warning areas. conditions of the forecast position, and the event that Therefore, the background of the forecaster and his or is being assessed, to provide a sound estimate of the her knowledge of the area are critical. For instance, in warning areas. It is important to note that all maps the Mexican Pacific, the mean annual significant wave derived from QATWaSS-TC are subject to misinterpre- height in deep water is around 1.5 m, while extreme tation and are intended for use by trained forecasters waves (based on 12 h of exceeding the 99th percentile) only. The maps are not suitable or intended for release are above 3.5 m (Reguero et al. 2013; Cox and Swail to the public. 2001), which could provide the threshold for the warn- The QATWaSS-TC is conceived as a qualitative ing areas. In the particular case of Patricia, the maxima tool to aid forecasters and not to provide estimates of of the maximum map of significant wave height (as

510 | MARCH 2017 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC Fig. 6. Maximum envelope maps of significant wave height (m) for (a) individual event 1605; (b) maxima of maximum envelope for events 1940, 2044, 2029, 1734, and 1605; and (c) the normalized maxima of maximum envelope for the same events. Figures are screenshots of the QATWaSS-TC graphic interface; therefore, text is in Spanish. Please see the appendix for a list of translated terms.

obtained using QATWaSS-TC) showed values above waves for this coastline. For this assessment, there were 4 m between the locations of San Blas and Manzanillo synthetic events making landfall as major hurricanes (Fig. 6b), which would trigger a warning of hazardous at the uncertainty cone limits, so that the normalized

AMERICAN METEOROLOGICAL SOCIETY MARCH 2017 | 511 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC the precomputed synthetic events (QATWaSS-TC) showed similar intensities to the analogous events (uncertainty cone tracks), although the values near San Blas were overestimated by the synthetic events. For the operational forecast, this suggests that warning areas would be similar whether QATWaSS-TC or real-time models based on the advisory were used. Here, we only included two synthetic events, which covered the extremes of the uncertainty cone, so high waves could be expected anywhere in between. Comparing the results from both QATWaSS-TC and the simulations using the advisory information to the results using the best track data, we found that the wave warning area for waves above 4 m was equal to those from both the simulations based on the Fig. 7. Wind speed category at each track location for advisory and QATWaSS-TC, with the exception of the 3,100 synthetic events, where blue corresponds to the area south of San Blas; however, the values at the tropical depressions, green to tropical storms, orange coastline were smaller for the best track simulation. to minor hurricanes, and fuchsia to major hurricanes. Finally, we performed a qualitative assessment of QATWaSS-TC using the poststorm damage survey map (Fig. 6c) does not provide an asset to the forecaster. conducted by CNHyTS and NWS/NOAA. The results In the case that there was only one major hurricane in of the survey show property damage and flooding the synthetic database, the individual maximum enve- up to 3.5 m above mean sea level resulting from the lope map for that event would provide the baseline for combined effects of waves and a storm surge ~120 km the significant wave height values that can be obtained southeast of the landfall point (Playa Paraíso). This and then the normalized maxima of the maximum area was part of the extension of the coastline iden- map will provide the extent of the area under risk. We tified as under risk by QATWaSS-TC, lending ad- do acknowledge this is a rough approximation but ditional credibility to the system. one that can provide accurate estimates to delineate warning areas when forecasters have a background CONCLUSIONS. In this study, we developed a in the physical processes underlying waves and storm quick wave and storm surge warning tool for tropical surge generation and propagation as well as in the local cyclones (QATWaSS-TC), which is the first operation- characteristics of the area. al tool for the recently announced National Hurricane To test the accuracy of estimates from QATWaSS- and Severe Storms Center in Mexico. The tool was TC for Patricia-generated waves, we compared the re- developed on a tight budget and within limited time sults to those of the WaveWatch III model of NOAA’s constraints: 6 months from conception to implemen- EMC/National Centers for Environmental Prediction tation. Based on prerun high-fidelity models, the tool (not shown). The wave model provided similar results allows forecasters to provide rapid estimates of wave to QATWaSS-TC, with estimates of significant wave and storm surge warning areas related to tropical height between 4 and 8 m along the coast from San cyclones along the Mexican coastline. When tested Blas to Manzanillo. Nevertheless, the system should using Hurricane Patricia (2015) as an example, the still be considered a qualitative aid for the estimation tool provided accurate estimates for warning areas. of warning areas and should not be used for quantita- Despite the advantages presented by QATWaSS- tive estimates. TC, the approach has several limitations. First, the One of the main advantages of QATWaSS-TC is system database contains only 3,100 synthetic events, that it does not rely on high-performance computing, so events for use as proxies will likely differ in at least which would allow computation of waves and storm one characteristic (e.g., track, translation speed, maxi- surges using data from NHC advisories. To compare mum wind speed, or storm size) from the event being results that could be obtained using real-time fore- forecasted. Second, finescale bathymetry is only avail- cast models to the results from QATWaSS-TC, we able in some localized areas, and topography has not computed wave maximum wave fields from advisory been included, thus no overland flooding is calculated. 14 and best track data for Patricia (Fig. 8). The sig- Finally, quantitative estimates can only provide aids nificant wave height values near the coastline from for the qualitative assessment of warning areas as the

512 | MARCH 2017 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC Fig. 8. QATWaSS-TC database poststorm assessment of waves generated by Hurricane Patricia (2015), showing (a) the best track (larger dots), synthetic events 1605 and 2029 (smaller dots), the forecast track with the 5-day uncertainty cone during NHC advisory 14, and the location of Manzanillo and San Blas; significant wave height maximum envelope maps for synthetic events (b) 1605 and (c) 2029, and for (d) the north track, (e) the south track, (f) the central track of advisory 14 uncertainty cone, and (g) for the best track data.

limitations discussed above result in high uncertainties greater automatization of the tool, enabling a more related to quantitative estimates in nearshore areas. quantitative usage, and in particular would reduce To reduce the uncertainty imposed by the limita- discrepancies that may arise owing to different inter- tion of events, the database could be updated with pretations by different forecasters. additional synthetic events. For example, high-fidelity QATWaSS-TC could be easily adopted in countries models could be run outside of hurricane season to with limited numerical modeling capabilities and produce more precomputed scenarios, which in the without a complex forecasting system (e.g., many case of Mexico could add at least 3,100 events per year, countries in the Caribbean and Central America), considering the same meshes are used. To increase although forecasters would be required to have the quantitative precision of the system, high-fidelity knowledge of waves and storm surge generation and models should also include more accurate bathymetric propagation. While high computing resources are data and topography. However, with approximately needed to precompute scenarios for the system, none 11,000 km of coastline, Mexico is unlikely to perform are needed during the tropical cyclone season, when surveys to gather precise bathymetric and topographi- forecasts of warning areas can be done in minutes. cal data; although this could be feasible for other Latin The system can be developed and implemented under American countries and the Caribbean islands with low budgets and tight schedules, both of which are considerably shorter coastlines (i.e., Cuba and the Ba- common in many developing countries. hamas have about 40% of the coastline of Mexico, and 2/3 of the countries in the area of NHC responsibility ACKNOWLEDGMENTS. The authors thank the have less than 5% of Mexico’s coastline). In the case of Comisión Nacional del Agua (CONAGUA) for providing smaller countries, the use of 3,100 events could provide support under Project CNA-SGT-GASIR-14/2014. The a sufficiently large dataset to reduce the uncertainty authors are very grateful to Professor Kerry Emanuel for imposed. Furthermore, these updates would allow supplying the synthetic events and for allowing their use

AMERICAN METEOROLOGICAL SOCIETY MARCH 2017 | 513 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC in this study, Gonzalo Martin for IT support, and two Restrepo (NWS), Humberto Hernandez Peralta (SMN), anonymous reviewers who greatly helped to improve the and Michel Rosengaus (advisor to CONAGUA). The views manuscript. The CNHyTS and NWS/NOAA storm damage and opinions expressed in this manuscript do not reflect survey was conducted by Orlando Bermudez (NWS), Pedro the opinion of the donor institute.

APPENDIX: GLOSSARY. Altura de ola significante Significant wave height Buscar Search Categoría Category Envolvente Envelope Evento(s) Event(s) Eventos seleccionados Selected events Generar envolvente normalizado Generate normalized envelope (normalized maxima of maximum envelope) Generar envolvente Generate envelope (maxima of maximum envelope map) Gráficar máximos Plot maxima (maximum envelope map) Huracán mayor Major hurricane Huracán menor Minor hurricane Incluir Include Máximo Maximum Medida Measured (here, parameters to display are wind, waves, and storm surge) Nomalizada Normalized Oleaje Waves Posición actual Present position Posición esperada Expected position Quitar Remove Tormenta tropical Tropical storm

REFERENCES Amante, C., and B. Eakins, 2009: ETOPO1 1 arc-minute —, 2016b: MIKE 21 & MIKE 3 flow model FM: Hy- global relief model: Procedures, data sources and drodynamic and transport module. DHI Scientific analysis. NOAA Tech. Memo. NESDIS NGDC-24, Documentation, 54 pp. 19 pp. [Available online at www.ngdc.noaa.gov/mgg Emanuel, K., and R. Rotunno, 2011: Self-stratification /global/relief/ETOPO1/docs/ETOPO1.pdf.] of tropical cyclone outflow. Part I: Implications Appendini, C. M., A. Pedrozo-Acuña, and A. Valle- for storm structure. J. Atmos. Sci., 68, 2236–2249, Levinson, 2014: Storm surge at a western Gulf of doi:10.1175/JAS-D-10-05024.1. Mexico site: Variations on Tropical Storm Arlene. —, S. Ravela, E. Vivant, and C. Risi, 2006: A statistical Int. J. River Basin Manage., 12, 403–410, doi:10.1080 deterministic approach to hurricane risk assessment. /15715124.2014.880709. Bull. Amer. Meteor. Soc., 87, 299–314, doi:10.1175 Cardone, V. J., and T. Cox, 2009: Tropical cyclone wind /BAMS-87-3-299. field forcing for surge models: Critical issues and —, R. Sundararajan, and J. Williams, 2008: Hurri- sensitivities. Nat. Hazards, 51, 29–47, doi:10.1007 canes and global warming: Results from downscaling /s11069-009-9369-0. IPCC AR4 simulations. Bull. Amer. Meteor. Soc., 89, Chawla, A., and Coauthors, 2013: A multigrid wave 347–367, doi:10.1175/BAMS-89-3-347. forecasting model: A new paradigm in operational Frank, W. M., and G. S. Young, 2007: The interannual wave forecasting. Wea. Forecasting, 28, 1057–1078, variability of tropical cyclones. Mon. Wea. Rev., 135, doi:10.1175/WAF-D-12-00007.1. 3587–3598, doi:10.1175/MWR3435.1. Cox, A. T., and V. R. Swail, 2001: A global wave hind- Gall, R., J. Franklin, F. Marks, E. N. Rappaport, and cast over the period 1958–1997: Validation and F. Toepfer, 2013: The Hurricane Forecast Improve- climate assessment. J. Geophys. Res., 106, 2313–2329, ment Project. Bull. Amer. Meteor. Soc., 94, 329–343, doi:10.1029/2001JC000301. doi:10.1175/BAMS-D-12-00071.1. DHI, 2016a: MIKE 21, spectral wave module. DHI Sci- Gibney, E., 2010: Which countries have had the entific Documentation, 62 pp. most tropical cyclones hits? NOAA Atlantic and

514 | MARCH 2017 Unauthenticated | Downloaded 10/05/21 01:46 PM UTC Meteorological Laboratory, Hurricane Research of the 2013 floods in Mexico. Weather, 69, 295–302, Division, accessed 4 April 2016. [Available online at doi:10.1002/wea.2355. www.aoml.noaa.gov/hrd/tcfaq/E25.html.] Rappaport, E. N., 2014: Fatalities in the United States Glahn, B., A. Taylor, N. Kurkowski, and W. A. Shaffer, from Atlantic tropical cyclones: New data and in- 2009: The role of the SLOSH model in National terpretation. Bull. Amer. Meteor. Soc., 95, 341–346, Weather Service storm surge forecasting. Natl. Wea. doi:10.1175/BAMS-D-12-00074.1. Dig., 33, 3–14. [Available online at www.nws.noaa —, and Coauthors, 2009: Advances and challenges at .gov/mdl/pubs/Documents/Papers/Role_of the National Hurricane Center. Wea. Forecasting, 24, _SLOSH_Model_August2009.pdf.] 395–419, doi:10.1175/2008WAF2222128.1. Holland, G. J., 1980: An analytic model of the wind Rego, J. L., and C. Li, 2009: On the importance of the for- and pressure profiles in hurricanes. Mon. Wea. Rev., ward speed of hurricanes in storm surge forecasting: 108, 1212–1218, doi:10.1175/1520-0493(1980)108 A numerical study. Geophys. Res. Lett., 36, L07609, <1212:AAMOTW>2.0.CO;2. doi:10.1029/2008GL036953. Impact Forecasting, 2014: Annual global climate and —, and —, 2010: Nonlinear terms in storm surge catastrophe report: Impact forecasting—2013. predictions: Effect of tide and shelf geometry with Aon Benfield, 66 pp. [Available online at http:// case study from Hurricane Rita. J. Geophys. Res., 115, thoughtleadership.aonbenfield.com/Documents C06020, doi:10.1029/2009JC005285. /20140113_ab_if_annual_climate_catastrophe Reguero, B. G., F. J. Méndez, and I. J. Losada, 2013: _report.pdf.] Variability of multivariate wave climate in Latin IMT, 2016: Red Nacional de Estaciones Oceanográficas America and the Caribbean. Global Planet. Change, y Meteorológicas. Accessed 4 April 2016. [Available 100, 70–84, doi:10.1016/j.gloplacha.2012.09.005. online at http://imt.mx/SitioIMT/DIPC/ServiciosTec- Rosengaus-Moshinsky, M., M. Jiménez-Espinosa, and nologicos/Reneom/reneomDesarrollo.php.] M. T. Vázquez-Conde, 2002: Atlas climatológico Innocentini, V., E. Caetano, and J. T. Carvalho, 2014: A de ciclones tropicales en México. Centro Nacional procedure for operational use of wave hindcasts to para la Prevención de Desastres, Instituto Mexicano identify landfall of heavy swell. Wea. Forecasting, 29, de Tecnología del Agua, 106 pp. [Available online 349–365, doi:10.1175/WAF-D-13-00077.1. at http://cambioclimatico.inecc.gob.mx/descargas Irish, J. L., D. T. Resio, and J. J. Ratcliff, 2008: The influ- /atlas_ciclones.pdf.] ence of storm size on hurricane surge. J. Phys. Ocean- Ruiz-Salcines, P., 2013: Campos de viento para hindcast ogr., 38, 2003–2013, doi:10.1175/2008JPO3727.1. de oleaje: Reanálisis, paramétricos y fusión. M.E. the- Jelesnianski, C., J. Chen, and W. Shaffer, 1992: SLOSH: sis, Department of Ciencias y Técnicas del Agua y del Sea, lake, and overland surges from hurricanes. Medio Ambiente, Universidad de Cantabria, 84 pp. NOAA Tech. Rep. NWS 48, 73 pp. Sørensen, O. R., H. Kofoed-Hansen, M. Rugbjerg, and Kimberlain, T. B., E. S. Blake, and J. P. Cangialosi, 2016: L. S. Sørensen, 2004: A third-generation spectral National hurricane center tropical cyclone report: wave model using an unstructured finite volume Hurricane Patricia. NOAA/NWS Rep. EP202015, 32 technique. Proc. 29th Conf. on Coastal Engineering, pp. [Available online at www.nhc.noaa.gov/data/tcr Lisbon, Portugal, ASCE, 894–906. /EP202015_Patricia.pdf.] Taylor, A. A., and B. Glahn, 2008: Probabilistic guidance Meza-Padilla, R., C. M. Appendini, and A. Pedrozo- for hurricane storm surge. 19th Conf. on Probability Acuña, 2015: Hurricane induced waves and storm and Statistics, New Orleans, LA, Amer. Meteor. Soc., surge modeling for the Mexican coast. Ocean Dyn., 7.4. [Available online at https://ams.confex.com/ams/ 65, 1199–1211, doi:10.1007/s10236-015-0861-7. pdfpapers/132793.pdf.] NOAA, 2016a: Tides and currents. Accessed 4 April UNAM, 2016: Servicio Mareográfico Nacional. Ac- 2016. [Available online at http://tidesandcurrents. cessed 4 April 2016. [Available online at www noaa.gov/map/.] .mareografico.unam.mx/portal.] —, 2016b: Patricia 2015 best track data. Accessed 4 van der Westhuysen, A. J., and Coauthors, 2013: De- April 2016. [Available online at ftp://ftp.nhc.noaa. velopment and validation of the nearshore wave gov/atcf/archive/2015/bep202015.dat.gz.] prediction system. 11th Symp. on the Coastal Environ- Ochi, M. K., 2003: Hurricane Generated Seas. Elsevier ment, Austin, TX, Amer. Meteor. Soc., 4.5. [Available Ocean Engineering Series, Vol. 8, Elsevier, 154 pp. online at https://ams.confex.com/ams/93Annual Pedrozo-Acuña, A., J. A. Breña-Naranjo, and /webprogram/Manuscript/Paper222877/AMS2013 R. Domínguez-Mora, 2014: The hydrological setting _Westhuysen-etal_ext_abstr_paper4-5.pdf.]

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