Underwater Glider Observations for Atlantic Tropical Cyclone Studies and Forecasts

Gustavo Jorge Goni, Scott Glenn, Jili Dong, Ruth Curry, Robert E. Todd, Travis Miles, Julio Morell, Hyun-Sook Kim, Becky Baltes, Glen G. Gawarkiewicz, and Joleen Heiderich

In the North Atlantic basin, tropical cyclones (TCs) originate and intensify from June to November with approximately 12 tropical storms and two to three hurricanes forming each year. These storms frequently affect highly populated coastal areas, causing large economic and social impacts (Figure 1). Under appropriate atmospheric conditions, TC intensification and weakening have been linked to ocean properties, such as upper-ocean heat content (Mainelli et al., 2008) and stratification (Seroka et al., 2016), which can be estimated using both in situ and satellite observations. Autonomous underwater gliders (Rudnick, 2016) offer cost-effective opportunities to assess these and other upper-ocean conditions by collecting targeted and sustained observations.

Figure 1. Atlantic hurricane tracks during the period 1993–2010, with color circles indicating the position where they intensified. The background color shows the average Tropical Cyclone Heat Potential during the same period. From Goni et al. (2017)

 

Several programs in recent years have used gliders to better understand air-sea processes during high-wind events, with a specific goal of improving hurricane intensity forecasts. Observations collected by these efforts are transmitted in real time to the Global Telecommunication System (GTS) and distributed through institutional web pages and the Integrated Ocean Observing System Glider Data Assembly Center. Delayed-time data are also used for in-depth analysis and studies of ocean-​atmosphere interactions due to hurricane-force winds. Glider missions have already returned tens of thousands of profiles of temperature, salinity, dissolved oxygen, and chlorophyll. Data sets obtained from these missions include unique temperature and salinity observations sampled under tropical cyclone wind conditions for Tropical Storm (TS) Barry (2007), Hurricane Irene (2011), Hurricane Sandy (2012), Hurricane Arthur (2014), TS Bertha (2014), Hurricane Gonzalo (2014), Hurricane Fay (2014), TS Erika (2015), Hurricane Joaquin (2015), Hurricane Hermine (2016), and Hurricane Matthew (2016). This article describes these efforts and their principal scientific accomplishments with the intent of laying the foundation for a coordinated, distributed and sustained observation system to improve TC research and forecasting capabilities.

 

Caribbean Sea and Tropical Atlantic Ocean

Figure 2. (a) Underwater glider transects (black lines) superimposed to the altimetry-​derived upper-ocean heat content (Tropical Cyclone Heat Potential) for mid-October 2014, with Hurricane Gonzalo (2014) and Fay (2014) tracks (circles). (b) Impact of a glider temperature profile in the initialization of HWRF-HYCOM. (c) Impact of glider and other ocean data to reduce error in tropical cyclone intensity (maximum wind speed) during the forecast of Hurricane Gonzalo tested on October 13, 2014. From Goni et al. (2017)

Glider operations along predetermined tracks off Puerto Rico in the Caribbean Sea and tropical Atlantic Ocean are conducted by the National Oceanographic and Atmospheric Administration (NOAA) Atlantic Oceanographic and Meteorological Laboratory (AOML) in conjunction with the Caribbean Coastal Association for Coastal Ocean Observations (CARICOOS). TC Gonzalo developed in the tropical North Atlantic on October 12, 2014, and then passed ~85 km northeast of the location of one of these gliders as it intensified from a Category-2 hurricane into a Category-3 hurricane. As Gonzalo passed north of Puerto Rico, sea surface temperature cooling was largely suppressed by the presence of a low-salinity layer in the upper 20 m of the ocean (i.e., a barrier layer). Maximum observed upper-ocean cooling was limited to 0.4°C when Gonzalo was closest to the glider. The presence of this barrier layer may have favored the storm’s intensification; Gonzalo continued intensifying into a Category-4 hurricane (Goni et al., 2015). Glider observations collected before, during, and after the passage of Gonzalo were assimilated into the high-resolution Hurricane Weather and Research Forecast (HWRF)-Hybrid Coordinate Ocean Model (HYCOM) coupled forecast system at the NOAA Environmental Modeling Center to assess the impact of underwater glider and other ocean observations on Hurricane Gonzalo intensity forecasts. Results indicated that assimilation of underwater glider observations significantly improved the pre-storm thermal and saline model initializations, in particular of the barrier layer (Figure 2a,b). The main result of this work was that the errors in maximum wind speed and minimum pressure for the 126-hour forecast when its center was northeast of Puerto Rico were reduced by 50% to 90% (Figure 2c–e) by assimilating underwater glider data and conventional ocean observations, including satellite altimetry observations.

 

Subtropical North Atlantic

In October 2014, Hurricanes Fay and Gonzalo hit Bermuda during the same week. One glider deployed by the Bermuda Institute of Ocean Sciences (BIOS) two days after the passage of Fay was directly under the eyewall of Category-3 Hurricane Gonzalo. Within the cold wake created by the two TCs, gliders observed a 4°C surface temperature drop, a 50 m deepening of the mixed layer, and breaking internal waves along its boundary. Each storm resulted in heat storage reductions of approximately 3–4 J m–2 in the upper 250 m. Surface heat flux was a factor in the intensification of Fay from a tropical storm to a hurricane as it passed Bermuda. A key result obtained from the glider observations is that Hurricane Gonzalo weakened from Category-4 to -3 as it traveled over the cold wake produced by Hurricane Fay (Figure 2a).

 

Middle Atlantic Bight Shelf

The passage of TCs over the continental shelf of the Middle Atlantic Bight has been observed by gliders for several years. Rutgers University conducted glider missions during hurricanes Irene (2011) and Sandy (2012). Observations during Hurricane Irene (2011) revealed that ahead-of-eye-center surface cooling and thermocline deepening may have contributed to weakening of this cyclone over the continental shelf (Glenn et al., 2016). In addition, onshore wind stress ahead of the storm caused two-layer circulation under stratified summer conditions on the continental shelf and resulted in shear-​induced mixing across the thermocline that led to surface cooling. Sensitivity studies in an atmospheric model showed that this rapid surface cooling and resulting air-sea flux changes contributed to the weakening of Irene before landfall (Seroka et al., 2016).

A glider deployed five days ahead of the forecast landfall location of Hurricane Sandy (2012) on the New Jersey coast also carried an acoustic Doppler current profiler to measure vertical shear to assess the upper-ocean mixing. Observations showed that downwelling-favorable winds as Sandy approached limited the supply of cold bottom waters to be mixed upward, and surface cooling was limited to 1°–2°C (Zambon et al., 2014), contributing only slightly to the weakening of Sandy over the continental shelf. In the aftermath of Hurricane Sandy, the multi-institution TEMPESTS program was initiated to collect observations that would improve forecasts of the intensity of storms impacting the US Northeast. Rutgers University, Woods Hole Oceanographic Institution, the University of Maine, and University of Maryland each operated gliders in rapid-response mode during the 2014–2016 hurricane seasons. These gliders measured the continental shelf response to Hurricanes Arthur (2014) and Hermine (2016). Both storms caused cooling, mixed layer deepening, and westward flow over the continental shelf. Hurricane Arthur traveled through the region much more quickly than Hurricane Hermine, which stalled and dissipated south of New England; only Hermine produced inertial oscillations following its passage (Figure 3).

Figure 3. Glider observations of the effects of Hurricanes Arthur (2014) and Hermine (2016) in the Middle Atlantic Bight. Tracks of (a) Arthur and (b) Hermine with maximum sustained winds indicated by colors and tracks (blue) of Woods Hole Oceanographic Institution-operated gliders deployed in response to the storms. (c–d) Vertically averaged currents measured by the gliders before, during, and after the storms as the gliders moved offshore; only Hermine generated inertial oscillations (d). Time series of (e) surface temperatures and (f) mixed layer thicknesses measured by the gliders during Arthur (red) and Hermine (blue). From Goni et al. (2017)

 

Gulf of Mexico

Several glider observational and analysis efforts are currently in place in the Gulf of Mexico. During the 2012 and 2013 summer seasons, a collaborative effort between NOAA, universities, and private industry included the validation of NCEP global RTOFS (global operational Real-Time Ocean Forecast System at the NOAA National Centers for Environmental Prediction) forecasts using available glider observations in the northern central Gulf of Mexico. The purpose of this work was to carry out targeted observations of the ocean conditions before, during, and after the passage of a hurricane and to conduct assessments of RTOFS. Comparison results show that ocean model upper conditions agreed with the observations, having highly correlated sea surface temperature, mixed-layer depth, and depth of 26°C isotherm, with RMS differences of 0.4°C, 8 m, and 19 m, respectively. From 2010 to 2013, gliders operating under this effort collected more than 2,100 profiles to 1,000 m depth, and covered a distance of over 2,400 nautical miles in the Gulf. In addition to temperature and salinity measurements, gliders also collected water column salinity, dissolved oxygen, and chromophoric dissolved organic matter.

 

Outlook and Recommendations

Gliders deployed in the tropical Atlantic during hurricane season continue to provide key upper-ocean observations to initialize numerical ocean-atmosphere coupled forecast models, to properly identify areas that may be responsible for storm weakening and intensification, and to improve intensity forecast model output. In addition, gliders provide a means to better understand the processes responsible for the rapid evolution of the ocean and its important feedback on the atmosphere during the passage of cyclones. In 2017, glider deployments are planned in the Caribbean, the Gulf of Mexico, and along the entire US East Coast during the Atlantic hurricane season; observations collected under a variety of programs will be coordinated under the NOAA Hurricane Field Program.

Though gliders have been successfully deployed in rapid-​response mode ahead of storms in the Middle Atlantic Bight, the logistical hurdles for such operations are significant. With lead times typically less than one week based on forecast accuracy, gliders used in rapid-response mode are usually deployed within two to three days of storm arrival. This short lead time prevents comprehensive measurement of pre-storm conditions (e.g., complete cross-shelf transects) and suboptimal placement of gliders during storm passage. Sustained glider operations during the storm season (such as in those currently in place in the Caribbean Sea and near Bermuda) have provided critical information to appropriately initialize numerical ocean models during pre-storm conditions. Given the positive impact of the upper-ocean observations collected by these projects, the following recommendations are provided to further increase their contributions with the aim of improving Atlantic hurricane intensity studies and forecasts:

  • Continue to assess the impact of glider observations in conjunction with observations from other components of the ocean observing system, to determine the most appropriate and cost-effective sampling strategies
  • Maintain or enhance the Caribbean Sea, Gulf of Mexico, and tropical North Atlantic glider network to enable impact assessment studies
  • Further investigate the impact of implementing a comprehensive underwater glider rapid response to aid in the monitoring of upper ocean heat content assessments prior to the passage of Atlantic hurricanes
  • Conduct numerical ocean simulation experiments to assess the impact of glider data, and all upper-ocean thermal data, on Atlantic hurricane intensity forecasts
  • Include additional sensors on the gliders, when possible, to enable multidisciplinary studies geared toward assessing the impact of hurricanes on ecosystems, carbon dioxide fluxes, fisheries, etc.

 

References

Glenn, S., T. Miles, G. Seroka, Y. Xu, R. Forney, F. Yu, H. Roarty, O. Schofield, and J. Kohut. 2016. Stratified coastal ocean interactions with tropical cyclones. Nature Communications 7:10887, https://doi.org/10.1038/ncomms10887.

Goni, G.J., J.A. Knaff, and I-I Lin. 2015. Tropical cyclone heat potential. In “State of the Climate in 2014”. Bulletin of the American Meteorological Society 96(7):S121–S122.

Goni, G.J., R.E. Todd, S.R. Jayne, G. Halliwell, S. Glenn, J. Dong, R. Curry, R. Domingues, F. Bringas, L. Centurioni, and others. 2017. Autonomous and Lagrangian ocean observations for Atlantic tropical cyclone studies and forecasts. Oceanography 30(2):92–103, https://doi.org/10.5670/oceanog.2017.227.

Mainelli, M., M. DeMaria, L. Shay, and G. Goni. 2008. Application of oceanic heat content estimation to operational forecasting of recent Atlantic category 5 hurricanes. Weather Forecasting 23(1):3–16, https://doi.org/10.1175/​2007WAF2006111.1.

Rudnick, D.L. 2016. Ocean research enabled by underwater gliders. Annual Review of Marine Science 8:519–541, https://doi.org/10.1146/annurev-marine-122414-033913.

Seroka, G., T. Miles, Y. Xu, J. Kohut, O. Schofield, and S. Glenn. 2016. Hurricane Irene sensitivity to stratified coastal ocean cooling. Monthly Weather Review 144:3,507–3,530, https://doi.org/10.1175/MWR-D-15-0452.1.

Zambon, J.B., R. He, and J.C. Warner. 2014. Tropical to extratropical: Marine environmental changes associated with Superstorm Sandy prior to its landfall. Geophysical Research Letters 41:8,935–8,943, https://doi.org/​10.1002/2014GL061357.

 

Acknowledgments

The NOAA/AOML component of this work was originally funded by the Disaster Relief Appropriations Act of 2013, also known as the Sandy Supplemental, and is currently funded by the NOAA research grant NA14OAR4830103, by NOAA Atlantic Oceanographic and Meteorological Laboratory, by CARICOOS (Caribbean Coastal Observing System), and by the NOAA Integrated Ocean Observing System (IOOS). The TEMPESTS component of this work is supported by NOAA through the Cooperative Institute for the North Atlantic Region (NA13OAR4830233) with analysis additional support from the WHOI Summer Student Fellowship Program.

 

Authors

Gustavo Jorge Goni, Atlantic Oceanographic and Meteorological Laboratory, National Oceanic and Atmospheric Administration, Miami, FL, USA, gustavo.goni@noaa.gov

Scott Glenn, Department of Marine and Coastal Sciences, Rutgers University, New Brunswick, NJ, USA, glenn@marine.rutgers.edu

Jili Dong, Environmental Modeling Center, National Oceanic and Atmospheric Center, College Park, MD, USA, jili.dong@noaa.gov

Ruth Curry, Bermuda Institute of Ocean Sciences, St. George’s, Bermuda, ruth.curry@bios.edu

Robert E. Todd, Woods Hole Oceanographic Institution, Woods Hole, MA, USA, rtodd@whoi.edu

Travis Miles, Department of Marine and Coastal Sciences, Rutgers University, New Brunswick, NJ, USA, tnmiles@marine.rutgers.edu

Julio Morell, University of Puerto Rico, Mayaguez Campus, Mayaguez, Puerto Rico, julio.morell@upr.edu

Hyun-Sook Kim, Environmental Modeling Center, National Oceanic and Atmospheric Center, College Park, MD, USA, hyun.sook.kim@noaa.gov

Becky Baltes, US Integrated Ocean Observing System Program, National Oceanic and Atmospheric Administration, Silver Spring, MD, USA, becky.baltes@noaa.gov

Glen G. Gawarkiewicz, Woods Hole Oceanographic Institution, Woods Hole, MA, USA, gleng@whoi.edu

Joleen Heiderich, MIT-WHOI Joint Program, Woods Hole Oceanographic Institution, Woods Hole, MA, USA, joleenh@mit.edu