The waters off the coast of California are heavily trafficked, not only by ships, but also by those other seagoing behemoths, the great whales. Blue, fin, humpback and gray whales all migrate up and down the West Coast. When whales and ships come into contact, however, the results can be fatal. Ship strikes are a significant cause of mortality for these species, all of which, other than the gray whale, are currently listed as endangered.

If ships knew when whales were in the area then they could steer clear or temporarily slow down. But whales spend most of their time hidden beneath the waves. By the time a ship’s captain spots a whale, it’s often already too late. But a team of scientists from NOAA, Oregon State University, and the University of Maryland Center for Environmental Science are working on a solution.

It’s called WhaleWatch, and it’s the result of decades of work. Bruce Mate of OSU has been tracking whales using satellite tags for more than twenty years. All the while, ocean observing satellites have been recording physical conditions on the ocean. By overlaying the tracking data atop maps showing ocean conditions, the researchers are deciphering the combination of conditions most likely to attract whales. Hopefully, they will soon be able to issue whale advisories based on data as it streams in from the satellites.

What they’re really predicting isn’t the presence of whales themselves, but of dense masses of krill—the tiny, shrimp-like creatures that are a preferred food for many filter feeding whales. Krill are widespread in the ocean, but they only coalesce into dense formations where currents converge and where temperature and other conditions are all just right. For whales, it’s only worth going after krill when they’re in these dense masses, so they can get millions of them in a mouthful. If you know where these krill are, you also know where the whales are likely to be.

The problem is, satellites aren’t able to detect the presence of animals like krill or whales directly. But they are very good at sensing the physical condition of the ocean. Wind speed and direction, temperature gradients, upwellings, eddies, and fronts are all visible to satellites.

The WhaleWatch scientists are using computer models to observe how these underwater and atmospheric systems collide and interact. They’re basically predicting the weather, but beneath the waves instead of above them.

And then, they’re taking it one step further. Daniel Palacios, an oceanographer with NOAA’s Southwest Fisheries Science Center, explained. “We’re making the leap,” Palacios said, “from observing physical processes in the ocean to predicting the biological processes that happen as a result.”

From an economic perspective, the ability to forecast whale activity is icing on a cake. “The satellites are already up there producing data,” Palacios said. “We’re just coming up with creative ways to extract useful products from that data.”

The WhaleWatch program is currently in the proof-of-concept phase, with scientists still working out their statistical techniques. They hope to be making regular forecasts in about 18 months. The lead investigator is Helen Bailey at the University of Maryland Center for Environmental Science.

Ninety-percent of the world’s trade is carried by ship, and that number is projected to grow rapidly in coming years. Hopefully, WhaleWatch and similar programs elsewhere will mean that ship strikes will decrease even as shipping traffic grows.

(Source: NOAA Fisheries)

미국 과학자들, 고래 주의보 준비 중

미국 해양대기청, 오리건 주립대학, 메릴랜드 대학교 환경과학센터가 합동으로 태평양의 고래 이동 패턴을 예측하여 선박들이 고래와 충돌하는 ‘쉽 스트라이크’를 줄일 수 있는 프로그램을 개발 중이다.

웨일워치라고 불리는 이 프로그램은 수십 년의 노력으로 맺은 결실이다. 오리건 주립대학의 브루스 메이트는 위성 태그를 이용하여 20년 이상 고래를 추적해왔다. 그 동안 해양 관찰 위성이 바다의 물리적 조건을 기록했다. 과학자들은 이 두 가지 정보를 결합하여 고래를 끌어들일 확률이 높은 해양 조건의 조합을 분석하고 있다. 머지않아 위성 자료에 기반하여 고래 주의보를 발령할 수 있을 것으로 보인다.

웨일워치 과학자들은 해저 및 기후 시스템이 어떻게 충돌하고 상호작용하는지 관찰하기 위해 컴퓨터 모델을 사용한다. 이를 통해 고래의 먹이가 되는 크릴새우가 밀집할 가능성이 높은 곳을 추정하게 된다. 이 기술은 경제적이기도 하다. 과학자들이 해야 할 일은 위성이 이미 수집한 데이터로부터 유용한 정보를 생산해 내는 창의적 방법을 고안하는 것뿐이기 때문이다.

현재 웨일워치 프로그램은 개념 입증 단계를 거치고 있으며, 과학자들은 약 18개월 후에는 정기 예측을 할 수 있게 되기를 바라고 있다.

번역 정리 김지선