2017, another strong year for hurricanes (October, 2017)

Date: 
Tuesday, October 3, 2017
Hurricanes Irma (left) and Jose (right) as revealed by the scatterometer-derived ocean surface wind estimates from ASCAT on September 11, 2017.  Note the very large field of Irma’s strong winds covering the entire Florida peninsula.  Jose’s wind field peak intensity is higher at this time, but its area of strong winds is much smaller.  The history of the storm evolution is marked by color-codes circles that show the “Best Track” locations and storm intensity. A click on each of these marks allows the user to view information about the exact storm location, the time of its validity, the maximum winds and the minimum surface pressure – all as reported by the National Hurricane Center. Such data are available from the JPL’s North Atlantic Hurricane Watch, which provides a platform for interactive visualization of multi-parameter observations and allows for on-line analysis.

From a distance, up beyond the destruction, hurricanes are wondrous acts of nature. They form as a way for very warm ocean waters to discharge heat quickly. They’re these efficient and complex areas where the ocean and atmosphere trade energy; Earth’s way of rapidly transporting accumulated heat energy from the tropical regions to the extra-tropics when the regular oceanic or atmospheric circulation mechanisms are too slow to sufficiently export the extra heat.

Dr. Svetla Hristova-Veleva, a scientist in JPL’s Radar Science and Engineering section, has been monitoring hurricanes trying to understand the implications of air-sea interaction on the rapid intensification of hurricanes.  She has also been collaborating with JPL scientists and engineers to develop ideas for new missions and in the processes of designing new instruments, including the next generation dual frequency scatterometer, an instrument which measures wind speed and direction at the ocean surface.

About 10 years ago, Dr. Hristova-Veleva, along with her team at JPL and the Hurricane Science Research Program at NASA HQ, lead by Dr. Ramesh Kakar, created the Tropical Cyclone Information System (TCIS).  TCIS has evolved since, with support from NASA’s Advanced Information Systems Technology Program, lead by Dr. Michael Little. It now has two main components: a global tropical cyclone data archive of ten years and several regional interactive portals that integrate model forecasts with satellite and airborne observations, and allow the user to interactively visualize and analyze the storms.

Sitting next to her in her office, she guided me through a tour of a few memorable hurricanes she had saved in a convenient sharable filing system on the North Atlantic Hurricane Watch section of the site.  She lists off hurricanes she’s worked on, calling them out by name and date like they’re people she knows. “2005 was a big year,” she said as she guided me to a dropdown menu in the global data archive  where we could choose the North Atlantic and see every storm that occurred in that year in that ocean basin, a large domain from the top of Canada all the way across the North Atlantic, down to the equator and across the Caribbean Sea, and the Gulf of Mexico.  It was a long list. Indeed, 2005 must have been a big year.

 

Hurricane Joaquin (2015) as revealed by the large-scale moisture field retrieved from observations by multiple NOAA sounders (in pastel colors) and the detailed precipitation structure captured by the JPL-developed Rain Index, a multi-channel combination of passive microwave observations that come from a number of imagers, including NASA’s Global Precipitation Measurement Mission (stark colors).  Simultaneous visualization of multiple parameters, such as environmental moisture and precipitation structure of the storm, allows for better understanding of the interaction between the storm and its environment.  This image illustrates how the storm drew moisture from the surrounding area and funneled it toward South Carolina, causing historic flooding in the state even though Joaquin did not make a landfall.

She selected the storm Rita and then opened a preview of it. We could see the storm track and also observations by a number of different satellites and a variety of parameters at the bottom of the page such as sea surface temperature, wind speed and sea level pressure along with information about the size and category. We could see when Rita became a tropical storm and how it evolved.

I couldn’t help myself but exclaim in awe and wonder as she continued on with the tour. She navigated through the menu cruising day by day over the storm, looking at what the different instruments recorded, actually seeing what the scatterometers saw at the time of the hurricane. The TCIS database includes data from QuikSCAT, Advanced Microwave Scanning Radiometer (AMSR), Tropical Rainfall Measuring Mission’s (TRMM) Microwave Imager (TMI), SeaWinds as well as precipitable water vapor from AIRS and sea surface temperature from MODIS, AMSR-2 and other sensors (MUR SST). She pointed out ocean vectors, wind speed and direction. Some dates the instrument swath passed nearby, just missing the storm, and on other dates, the swath passed right over the storm like a bulls eye.

Much of Dr. Hristova-Veleva’s recent work revolves around a rain index that she developed to create a rain retrieval algorithm. “Rain contaminates the signal of the scatterometer,” she explained, “so we had to first retrieve the rain, make a correction to the scatterometer signal and then retrieve the winds.” Low frequency passive microwave observations provide information about liquid precipitation (rain), while high frequency channels provide information about the snow and the graupel above. The total column precipitation affects the scatterometer measurements so she developed the rain index to combine information about the entire vertical column of precipitation. The different frequencies of passive microwave radiometer images layered on top of each other looked like a three dimensional view of the internal structure through the hurricane.

Once the rain index was developed, it could be used in many different ways, she continued, “It captures the structure of the storm so now we are using that to understand the rapid intensification of hurricanes.”  I paused and looked away from the swirling colorful patterns on the screen and the incredibly fascinating science to think about the 2017 hurricane season. Harvey, Irma and Maria dominate the news. How many more hurricanes will this year bring?

Sea surface temperatures in the Gulf of Mexico before (left) and after (right) Hurricane Harvey. This data was acquired from NASA’s Multi-Scale Ultra-High Resolution Sea Surface Temperature Data Set.

 

Dr. Hristova-Veleva’s research will help scientists working on the National Hurricane Forecasting Improvement Project, established in 2009, understand what causes some storms to rapidly intensify and thus improve their forecast. So this work is important to better predict and therefore prevent future losses.

To demonstrate how hurricanes can organize and interact with the large-scale environment Dr. Hristova-Veleva selected Hurricane Joaquin, Oct 3, 2015 from the NAHW menu. “The hurricane itself pumps moisture from the near surface over the ocean and carries it upwards,” she explained. “In this particular case, it also drew moisture from the surrounding area and it funneled it toward South Carolina, carrying a very intense moisture plume. There it interacted with another extra-tropical system. The combination of the two created very severe flooding, so even though Hurricane Joaquin did not make a landfall on the U. S., it had a significant impact because it had collected all that water.”

Dr. Hristova-Veleva’s group also developed an on-line wave number analysis tool, which averages the rain index with respect to the storm center in 20-kilometer annuli and computes the azimuthal average. The distance between the peak of the maximum amplitude and the average, in each radial bin, tells you how asymmetrical the storm is, a signature of the intensity of the storm – the more intense the storm, the more organized and symmetric it is. She theorized that the relationship between the radial distribution of the rain intensity/symmetry and that of the wind field, could be a good predictor of whether the hurricane has the potential to intensify or not. Her explanation reminded me of the turbulence created in an unbalanced washing machine. “The location of convective activity with respect to the radius of maximum wind is very important,” she said. If convection happens outside the radius of maximum wind, the released latent heat is more easily dissipated. But when convection happens inside, the theory suggests that the hurricane will intensify because the inside is like a protected solid body that rotates together. The energy that is released during the formation of precipitation (the latent heat) remains inside and is very efficient in lowering the surface pressure, hence, strengthening the storm. This creates more upward motion. When convective towers inside the radius of maximum wind hit the tropopause, the air is forced to go somewhere and some of it sinks in the center of the hurricane. This compressional warming lowers the surface pressure even more and the hurricane gets even more intense.

She continued to show me diagrams comparing the radius of maximum rain and the radius of maximum wind, looking at how they relate to each other and the amount of asymmetry in the precipitation. In the Joaquin time series, which lasted longer than a week, initially the radius of maximum rain is just inside the radius of maximum wind, there is a lot of rain and the storm is asymmetric. Dr. Hristova-Veleva pointed out the moment where the storm intensified rapidly in speed and also in surface pressure. Then, significant precipitation developed outside the radius of maximum wind and the storm weakened.  She plans to develop a statistical study based on the ten-year TCIS database to analyze how often the storms intensify and under what circumstances to find out whether asymmetry or the total amount of rain or both of these factors together are good predictors of rapid intensification.

“The analysis of Harvey suggests to me,” she said, “that what is probably more important, at least during the early phases of the intensification, is the total amount of precipitation (and the associated latent heat that is released during the formation of the precipitation) that is happening near the center of the storm.”

“Wind observations are the limiting factor,” she said. Her team uses the Indian scatterometer SCATSAT, EUMETSAT’s Advanced Scatterometer (ASCAT), NASA’s radiometer wind estimates from SMAP and will soon use NASA’s CYGNSS.

Warm anomalies in both the Atlantic and the Pacific indicate that 2017 will be another strong year for hurricanes and these tools will continue to be an important resource for understanding hurricanes.

Laura Faye Tenenbaum

PO.DAAC Science Team