Sea Level Fingerprints Indicate Climate Changes

Researchers have reported the first observation of sea level “fingerprints,” tell-tale differences in sea level rise around the world in response to changes in continental water and ice sheet mass, the American Geophysical Union reported.

Scientists have a solid understanding of the physics of sea level fingerprints but have never had a direct detection of the phenomenon until now.

As ice sheets and glaciers undergo climate-related melting, they alter Earth’s gravity field, which causes nonuniform sea level change.

The team calculated sea level fingerprints using time-variable gravity data collected by the twin satellites of NASA’s Gravity Recovery & Climate Experiment between April 2002 and October 2014. During that time, the global mean sea level grew by about 1.8 mm per year, with 43 percent of the increased water mass coming from Greenland, 16 percent from Antarctica and 30 percent from mountain glaciers. The scientists verified their calculations of sea level fingerprints associated with these mass variations via ocean-bottom pressure readings from stations in the tropics.

With improved understanding through GRACE data and other techniques, scientists can now take any point on the global ocean and determine how much the sea level there will rise as a result of glacier ice melt.

 

ALAMO Tracks Irma Effects For Better Hurricane Prediction

As Hurricane Irma approached U.S. shores in September, researchers sponsored by the U.S. Office of Naval Research (ONR) used air-dropped autonomous sensors to compile real-time ocean observations to help forecasters predict the strength of future tropical storms. This marks the first time the sensors—called ALAMO (Air-Launched Autonomous Micro Observer) sensors—were used in hurricane prediction research. While standard computerized prediction models rely on atmospheric data like air temperature, humidity, altitude and wind speed and direction, the ALAMO sensors measure oceanographic phenomena beneath the sea surface. Hurricane Irma is one of the strongest storms ever recorded in the Atlantic Ocean. Such storms are notoriously difficult to predict, presenting a volatile meteorological cocktail that can change direction, speed and strength quickly and unexpectedly.

The sensor data will be used to improve the Navy’s Coupled Ocean/Atmosphere Mesoscale Prediction System-Tropical Cyclone—COAMPS-TC, which uses complex algorithms to predict hurricane intensity by processing real-time and historical meteorological data, fed by information from satellites.

 

Buoys with Acoustic Recorders Support German Offshore Wind

A species of porpoise endemic to the German coast is very sensitive to sound waves. In order to avoid disturbing its natural habitat, German legislation imposes a maximum sound level that must not be exceeded, especially by offshore wind farms.

Since 2014, RTsys has been providing buoys equipped with acoustic recorders, which analyze data in real time. These buoys are based on underwater acoustic recommendations and standards. RTsys is now recognized and authorized by German authorities. Offshore wind farm personnel can use these buoys to manage construction work, enabling them to make quick and reliable decisions.

 

ONC WERA Radar Shows Value As Early-Warning System

Installation of Ocean Networks Canada’s (ONC) WERA high-frequency oceanographic radar near Tofino on the west coast of Vancouver Island was completed March 2015 by ASL Environmental Sciences Inc. of Victoria, British Columbia; Northern Radar Inc. of St. John’s, Newfoundland; and Helzel Messtechnik GmbH of Germany. The primary goals of the radar, which provides oceanographic data and tsunami monitoring in near real time under all weather conditions, are to detect tsunamis generated off the west coast of Vancouver Island and, in the future, provide valuable warning time.

On October 14, 2016 at 05:45 UTC the ocean radar system sent out a tsunami alert after it detected and identified the distinctive signatures of a changing surface velocity potentially associated with a tsunami. There was, however, no seismic activity at that time to trigger an earthquake-generated tsunami.

Although there was no tectonic activity, the system did record an event with an unusual wave propagation current that coincided with the passage of an atmospheric cold front. Weather conditions around October 14 were characterized by strong winds and a stormy sea state caused by the remnants of Typhoon Songda 2016, a tropical disturbance formed west–southwest of Hawaii that crossed the Pacific Ocean and struck the Pacific Northwest region of the U.S. and Canada as a powerful extratropical cyclone. The abrupt changes in atmospheric pressure generated a meteorological tsunami.

Analysis of data from the tide gauge in Tofino showed a sea level disturbance with a maximum height of 80 cm nearshore. The radar was able to detect signatures of the event 20 minutes before the waves reached Bamfield and 1 hour in advance for Tofino.

The radar data from the British Columbia coast demonstrates the high sensitivity, reliability and potential of WERA for hazardous event detection and its value for early-warning systems.

 

Network of Monitoring Buoys For Kiel Canal Project

OSIL has supplied a network of seven 1.9-m data buoys to DHI in Denmark in support of a long-term monitoring project in Kiel, Germany. The sturdy buoy systems each incorporate two Sea-Bird Scientific WET Labs multiparameter water quality sensors; one mounted at the surface within the robust central buoy structure to prevent damage to the instrument and the other on a mooring frame that is  suspended 2 m above the seabed and accommodates a Nortek AWAC on a gimbal to monitor currents and waves. The exclusive mooring design includes a data swivel to ensure that the subsea instruments can continually report data without the risk of cable entanglements in the dynamic environment.

The buoys have a substantial power consumption rate owing to the high sampling frequency and real-time data transmitted almost continuously, as required by the client.