“Ishmael” software (by David Mellinger, NOAA PMEL) Spectrogram correlation with synthetic callSpectrogram correlation with synthetic call Varied synthetic.

Slides:



Advertisements
Similar presentations
Reasons for Seasons The seasons on Earth change every 3 months. There are two main causes for the change of seasons: The axis of the Earth is tilted.
Advertisements

Cisco CCNA Sem 1 Chapter 4 Cable Testing, Cabling LAN’s and WAN’s
Multi-Year Examination of Dense Fog at Burlington International Airport John M. Goff NOAA/NWS Burlington, VT.
Scheduling CTC-470.
ES=32 EF=34 LS=33 LF=35 ES=10 EF=16 LS=10 LF=16 ES=4+6=10 EF=10 LS=4
Analysis of 12 years of IMPROVE data in the Columbia River Gorge By Dan Jaffe University of Washington Northwest Air Quality Photo from the Wishram IMPROVE.
Mapping of Fires Over North America Using Satellite Data Sean Raffuse CAPITA, Washington University September,
D1: Critical Events And Critical Paths. D1: Critical Events And Paths A critical path is the list of activities on an activity network that, if they are.
Andy Wood Univ. of Washington Dept. of Civil & Envir. Engr. Statistics related to the merging of short and long lead precipitation predictions in the continental.
Line Efficiency     Percentage Month Today’s Date
GWDAW-10 (December 14, 2005, University of Texas at Brownsville, U.S.A.) Data conditioning and veto for TAMA burst analysis Masaki Ando and Koji Ishidoshiro.
Talk at American Cetacean Society, April 6, 2005 Observing Cetaceans from Pioneer Seamount SFSU Pacific Oceanography Project Michael Hoffman, Carl Vuosalo,
Two- tone unmasking and suppression in a forward-masking situation Robert V. Shannon 1976 Spring 2009 HST.723 Theme 1: Psychophysics.
Control Charts. On a run chart the centerline is the median and the distance of a data point from the centerline is not important to interpretation On.
Page 86 – 87 #18 – 36 even, 37 – 42, 45 – 48, 56, 60 (22 pbs – 22 pts) Math Pacing Statistics - Displaying and Analyzing Data
The Critical Path – Precedence diagram method Luise Lorenz Christina Mohr.
Marine mammals in the Rusalca region : Acoustic recordings and visual sightings Kate Stafford University of Washington Funding NSF_AON (2012-
New Jersey Transit Fatigue Risk Report Assignments for 27 th October December
New earthquake category Nature 447, (3 May 2007) | doi: /nature05780; Received 8 December 2006; Accepted 26 March A scaling law for slow.
Kelly Newman Alan Springer University of Alaska Fairbanks
Look Through the PowerPoint Slides and Answer the Questions on Outcome Related Activity #3 April 3 rd, 2014.
Submission doc.: IEEE /0416r1 Slide 1 Broadband Indoor TVWS Channel Measurement and Characterization at 670 MHz Date: Mar 2012 Ming-Tuo.
By : Afifah Elhan & Noah Joseph
Analysis of Raleigh’s Drought Triggers May 8, 2013 and.
Scheduling CTC-415. Short Interval Scheduling Plan & manage day to day activities Focus on individual activities Goal Oriented to get activity done Two.
Modeling with sine or cosine functions. Project Overview What do you know about the sine graph? What do you know about the equation of the sine function?
May 03, UFE ANALYSIS Old – New Model Comparison Compiled by the Load Profiling Group ERCOT Energy Analysis & Aggregation May 03, 2007.
Audio processing methods on marine mammal vocalizations Xanadu Halkias Laboratory for the Recognition and Organization of Speech and Audio
Data dissemination meeting February 28, 2007 ICAP New York.
Status of coalescing binaries search activities in Virgo GWDAW 11 Status of coalescing binaries search activities in Virgo GWDAW Dec 2006 Leone.
REVISIONS TO PCE INFLATION MEASURES: IMPLICATIONS FOR MONETARY POLICY Dean Croushore University of Richmond Visiting Scholar, Federal Reserve Bank of Philadelphia.
CALMON data 1 Use of daily CALMON data Brian Stewart RAL.
Astronomy: Apparent Motions Making sense of celestial observations.
PHYSICS CLASS ACTIVITY. CLASS ACTIVITY: TUNING FORK FREQUENCY.
NEMO-O DE NEMO First results from the NEMO Test Site G. Riccobene, for the NEMO Collaboration The NEMO Collaboration is performing the Phase 1 of the project,
Copyright © Body Active Consultancy Presented By: Body Active Consultancy APOSHO Western Australia 2011.
Mini Lesson 3: Show and describe variability Make a Histogram Data Literacy Project.
Graphically Representing Data. Objectives: To represent and interpret data displayed on dot plots To represent and interpret data displayed on histograms.
NEMO PHASE II RATE MONITORING AND CORRELATIONS M.G. Pellegriti INFN-LNS KM3 collaboration meeting Roma november 2013.
Policies Controlling Risk
Jan 2016 Solar Lunar Data.
Analysis of LIGO S2 data for GWs from isolated pulsars

8/29/2018 The Quickest Way to Extract Trends and Alerts from Massive Amount of Text Case Study “Economic Recovery & Interest Rates Trends” Company.
Analyzing patterns in the phenomena
Northwest Fisheries Science Center Technical Management Team
ABT & Frequency.
Reasons for Seasons The seasons on Earth change every 3 months. There are two main causes for the change of seasons: The axis of the Earth is tilted.

Reasons for Seasons The seasons on Earth change every 3 months. There are two main causes for the change of seasons: The axis of the Earth is tilted.

LO: How does Latitude affect Insolation?

Grouped Data L.O. All pupils understand why grouped data is sometimes used All pupils can find the modal class.

Jump Processes and Trading Volume
Volume 53, Issue 3, Pages (February 2007)

Reasons for Seasons The seasons on Earth change every 3 months. There are two main causes for the change of seasons: The axis of the Earth is tilted.

Naval Complexes Meeting November 26, 2018
Analysis of Network Outage Reports
Safety Group Program Timeline

Awareness and the EEG power spectrum: analysis of frequencies
NEMSIS V3.5.0 Timeline developed at NEMSIS Annual Meeting 2017
Naval Complexes Meeting September 17, 2018
What Month Were You Born In?
Counting to 100 Counting by ones
Safety Group Program Timeline
Presentation transcript:

“Ishmael” software (by David Mellinger, NOAA PMEL) Spectrogram correlation with synthetic callSpectrogram correlation with synthetic call Varied synthetic call parametersVaried synthetic call parameters Compared detector performance to analyst (LMM)Compared detector performance to analyst (LMM) Analyzing the Date - Call detection Analyzing the Date - Call detection

Right whale and humpback calls Time (s) Frequency (Hz) Time (s) Spectrum level (dB re counts 2 /Hz) Right whale calls: ‘Up-call’ most common (> 80%) Clustered into bouts Humpback whale calls: May appear similar to RW calls Patterned, repeated phrases

Right whale seasonal occurrence Results Right whale calls/day J F M A M J J A S O N D SEBS middle-shelf Earliest yearly right whale detections in late May (2002, 2004) Latest in mid-December (2005) Highest calling rates in Aug., Sep. (2001, 2004, 2005) & Dec. (2005) Longest calling durations in Aug., Sep., Oct. Calling usually lasted 2-3 consecutive days, up to 6 d Intervals between calls 2-49 d (median = 7)

Daily Calling Patterns Hourly calling rates calculated for five periods of day Adjusted by overall calling rate for that day Calling rates were highest during dark period 75% Median Mean 25% *

Conclusions Right whale occurrence varied by season and between years Right whale occurrence varied by season and between years Calls were detected for only a few days at a time Calls were detected for only a few days at a time Calling rates were highest at night Calling rates were highest at night Right whales were in the Southeast Bering Sea as early as May and as late as December Right whales were in the Southeast Bering Sea as early as May and as late as December