Optimal Spectral Decomposition (OSD) for GTSPP Data Analysis

Similar documents
Optimal Spectral Decomposition (OSD) for Ocean Data Analysis

Global Ocean Tripole and Climate Variability

Optimal Spectral Decomposition for ARGO Data Analysis

Effect of Inter and Intra annual Thermohaline Variability on Acoustic Propagation

New Development in Coastal Ocean Analysis and Prediction. Peter C. Chu Naval Postgraduate School Monterey, CA 93943, USA

Non-linear patterns of eddy kinetic energy in the Japan/East Sea

Ocean spectral data assimilation without background error covariance matrix

CHAPTER 2 DATA AND METHODS. Errors using inadequate data are much less than those using no data at all. Charles Babbage, circa 1850

A Modeling Study on Flows in the Strait of Hormuz (SOH)

Steady Flow: rad conv. where. E c T gz L q 2. p v 2 V. Integrate from surface to top of atmosphere: rad TOA rad conv surface

Eddy and Chlorophyll-a Structure in the Kuroshio Extension Detected from Altimeter and SeaWiFS

Coastal Ocean Circulation Experiment off Senegal (COCES)

Upper Ocean Mixing Processes and Circulation in the Arabian Sea during Monsoons using Remote Sensing, Hydrographic Observations and HYCOM Simulations

SIO 210 CSP: Data analysis methods L. Talley, Fall Sampling and error 2. Basic statistical concepts 3. Time series analysis

Applications of an ensemble Kalman Filter to regional ocean modeling associated with the western boundary currents variations

EVALUATION OF THE GLOBAL OCEAN DATA ASSIMILATION SYSTEM AT NCEP: THE PACIFIC OCEAN

The minimisation gives a set of linear equations for optimal weights w:

From El Nino to Atlantic Nino: pathways as seen in the QuikScat winds

Effects of Hurricanes on Ambient Noise in the Gulf of Mexico

Preliminary study of multi-year ocean salinity trends with merged SMOS and Aquarius data.

Littoral Zone Oceanography for ASW/MIW

Toward Accurate Coastal Ocean Modeling

Near-Surface Dispersion and Circulation in the Marmara Sea (MARMARA)

HFR Surface Currents Observing System in Lower Chesapeake Bay and Virginia Coast

Toward Accurate Coastal Ocean Prediction

SIO 210: Data analysis

Forecast of Nearshore Wave Parameters Using MIKE-21 Spectral Wave Model

Impact of frontal eddy dynamics on the Loop Current variability during free and data assimilative HYCOM simulations

Overview of data assimilation in oceanography or how best to initialize the ocean?

Daily OI SST Trip Report Richard W. Reynolds National Climatic Data Center (NCDC) Asheville, NC July 29, 2005

O.M Smedstad 1, E.J. Metzger 2, R.A. Allard 2, R. Broome 1, D.S. Franklin 1 and A.J. Wallcraft 2. QinetiQ North America 2. Naval Research Laboratory

Coastal Ocean Circulation Experiment off Senegal (COCES)

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 5 August 2013

ENSO Outlook by JMA. Hiroyuki Sugimoto. El Niño Monitoring and Prediction Group Climate Prediction Division Japan Meteorological Agency

SIO 210: Data analysis methods L. Talley, Fall Sampling and error 2. Basic statistical concepts 3. Time series analysis

OTC Vertical current structures in the Deep Gulf using EOF analysis S.F. DiMarco, R.O. Reid, and W. D.Nowlin, Jr., Texas A&M University

Improvements to the Wind Driven Component of the OSCAR Surface Current Product

Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea Revealed by Satellite Altimetric Data

Journal of Coastal Develpopment ISSN :

El Niño, South American Monsoon, and Atlantic Niño links as detected by a. TOPEX/Jason Observations

WIND EFFECTS ON CHEMICAL SPILL IN ST ANDREW BAY SYSTEM

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 11 November 2013

Wind induced oscillator dynamics in the Black Sea revealed by Lagrangian drifters

Characteristics of Storm Tracks in JMA s Seasonal Forecast Model

Blue and Fin Whale Habitat Modeling from Long-Term Year-Round Passive Acoustic Data from the Southern California Bight

Ocean Surface Current Climatology in the Northern Gulf of Mexico

General Oceanography Geology 105 Expedition #17 Tracking Drifter Buoys See Due Date in Greensheet or in Module Area of Canvas

Principal Component Analysis of Sea Surface Temperature via Singular Value Decomposition

2013 ATLANTIC HURRICANE SEASON OUTLOOK. June RMS Cat Response

Optimization of an observing system for the North Atlantic Meridional Overturning Circulation!

The global ocean circulation: an elegant dynamical system

Global Ocean Monitoring: A Synthesis of Atmospheric and Oceanic Analysis

PRMS WHITE PAPER 2014 NORTH ATLANTIC HURRICANE SEASON OUTLOOK. June RMS Event Response

Yellow Sea Thermohaline and Acoustic Variability

A computationally efficient approach to generate large ensembles of coherent climate data for GCAM

Data Descriptor World Ocean Isopycnal Level Absolute Geostrophic Velocity (WOIL V) Inverted from GDEM with the P Vector Method

LAGRANGIAN MEASUREMENTS OF EDDY CHARACTERISTICS IN THE CALIFORNIA CURRENT

The Oceanic Component of CFSR

North Pacific Climate Overview N. Bond (UW/JISAO), J. Overland (NOAA/PMEL) Contact: Last updated: September 2008

HEIGHT-LATITUDE STRUCTURE OF PLANETARY WAVES IN THE STRATOSPHERE AND TROPOSPHERE. V. Guryanov, A. Fahrutdinova, S. Yurtaeva

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 25 February 2013

Effect of inter- and intra-annual thermohaline variability on acoustic propagation

Alexander Barth, Aida Alvera-Azc. Azcárate, Robert H. Weisberg, University of South Florida. George Halliwell RSMAS, University of Miami

on climate and its links with Arctic sea ice cover

Evidence of a Barrier Layer in the Sulu and Celebes Seas

GFDL, NCEP, & SODA Upper Ocean Assimilation Systems

SIO 210 Introduction to Physical Oceanography Mid-term examination November 5, 2012; 50 minutes Answer key

AnuMS 2018 Atlantic Hurricane Season Forecast

Analysis of Remotely Sensed Ocean Data by the Optimal Spectral Decomposition (OSD) Method

M. Ballarotta 1, L. Brodeau 1, J. Brandefelt 2, P. Lundberg 1, and K. Döös 1. This supplementary part includes the Figures S1 to S16 and Table S1.

ENSO Cycle: Recent Evolution, Current Status and Predictions. Update prepared by Climate Prediction Center / NCEP 15 July 2013

North American Droughts in the 20th Century: Role of SST Variability and Trend

Lab 12: El Nino Southern Oscillation

NOAA In Situ Satellite Blended Analysis of Surface Salinity: Preliminary Results for

Demonstration and Comparison of of Sequential Approaches for Altimeter Data Assimilation in in HYCOM

A Climatology of Landfalling Hurricane Central Pressures Along the Gulf of Mexico Coast

8.1 Attachment 1: Ambient Weather Conditions at Jervoise Bay, Cockburn Sound

Journal of Computational Physics 148, (1999) Article ID jcph , available online at

How DBCP Data Contributes to Ocean Forecasting at the UK Met Office

DYNAMIC POSITIONING CONFERENCE September 28-30, 2004 ENVIRONMENT METOCEAN PHENOMENA IN THE GULF OF MEXICO AND THEIR IMPACT ON DP OPERATIONS

The role of teleconnections in extreme (high and low) precipitation events: The case of the Mediterranean region

The GLOSCAL project and observations of near sea surface salinity variability

Comparison of of Assimilation Schemes for HYCOM

Annual mean 2N 2S SST without flux correction COLA PAC IPSL HR IPSL LR IPSL TOGA JMA Longitude

Coastal Ocean Circulation Experiment off Senegal (COCES)

ATMOSPHERIC MODELLING. GEOG/ENST 3331 Lecture 9 Ahrens: Chapter 13; A&B: Chapters 12 and 13

Interannual trends in the Southern Ocean sea surface temperature and sea level from remote sensing data

Preparation and dissemination of the averaged maps and fields of selected satellite parameters for the Black Sea within the SeaDataNet project

Case study validation of HWRF-HYCOM and HWRF-POM for Hurricane Isaac (2012)

P-Vector Inverse Method Evaluated Using the Modular Ocean Model (MOM)

Richard W. Reynolds * NOAA National Climatic Data Center, Asheville, North Carolina

CAIBEX workshop Mesoscale experiments and modelling Cape Ghir

Variability in the Slope Water and its relation to the Gulf Stream path

Ch. 11: Hurricanes. Be able to. Define what hurricane is. Identify the life and death of a hurricane. Identify the ways we track hurricanes.

Why Has the Land Memory Changed?

Comparison between Wavenumber Truncation and Horizontal Diffusion Methods in Spectral Models

NCODA Implementation with re-layerization

Geostrophic Circulation in the Tropical North Pacific Ocean Based on Argo Profiles

DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.

A description of these quick prepbufrobs_assim text files is given below.

Transcription:

Optimal Spectral Decomposition (OSD) for GTSPP Data Analysis Peter C Chu (1),Charles Sun (2), & Chenwu Fan (1) (1) Naval Postgraduate School, Monterey, CA 93943 pcchu@nps.edu, http://faculty.nps.edu/pcchu/ (2) NOAA/NODC, Silver Spring, MD 20910 Charles.Sun@noaa.gov GTSPP Meeting, Oostende, Belgium, 5-7 May 2010.

Observational Data

It is an urgent need to establish monthly varying (T, S, u, v) gridded dataset from GTSPP and Argo trajectory data Oceanographic and Climate Studies

Ocean Data Analysis Classical Method Fourier Series Expansion

Joseph Fourier 1768-1830 Fourier was obsessed with the physics of heat and developed the Fourier series and transform to model heat-flow problems.

Fourier Series Expansion For a rectangular region (L x, L y ), the basis functions are sinusoidal functions. i x f ( x, y) aij sin sin L b i j x y cos i x cos j y ij i j Lx Ly j y L

For the Dirichret boundary condition : f = 0 at the boundaries i x f ( x, y) aij sin sin L j y L i j x y The dots represent the Observations.

Linear Algebraic Equations for the Coefficients a ij ob ob i x f ( x1, y1 ) aij sin sin L j y L ob ob 1 1 i j x y ob ob i x f ( x2, y2 ) aij sin sin L... j y L ob ob 2 2 i j x y ob i x f ( xm, ym ) aij sin sin L j y L ob ob ob M M i j x y

Determination of Spectral Coefficients (Ill-Posed Algebraic Equation)

Known a ij Analyzed Field i x f ( x, y) a sin sin L j y ij L i j x y

For the Neumann boundary condition at the boundaries n f 0 i x j y f ( x, y) bij cos cos L L i j x y The dots represent the Observations.

Linear Algebraic Equations for the Coefficients a ij ob ob i x f ( x1, y1 ) bij cos cos L j y L ob ob 1 1 i j x y ob ob i x f ( x2, y2 ) bij cos cos L... j y L ob ob 2 2 i j x y ob i x f ( xm, ym ) bij cos cos L j y L ob ob ob M M i j x y

Known b ij Analyzed Field i x f ( x, y) b cos cos L j y ij L i j x y

For General Ocean Basin Generalized Fourier Series Expansion

Spectral Representation Fourier Series Expansion m Basis functions (not sinusoidal) c any ocean variable

Determination of Basis Functions (1) Eigen Functions of the Laplace Operator (Data and Model Independent) (2) Empirical Orthogonal Functions (Data or Model Dependent)

Eigen Functions of Laplace Operator Basis Functions (Closed Basin) Ψ k Streamfunction Φ m T, S, Velocity Potential

Basis Functions (Open Boundaries)

Boundary Conditions

Spectral Decomposition M 0 m m m 1 T( x, t) T ( x) c ( t) ( x) M 0 m m m 1 S( x, t) S ( x) d ( t) ( x)

Benefits of Using OSD (1) Don t need first guess field (2) Don t need autocorrelation functions (3) Don t require high signal-to-noise ratio (4) Basis functions are pre-determined before the data analysis. They are independent on the data.

Optimal Mode Truncation

Vapnik (1983) Cost Function

Optimal Truncation Gulf of Mexico, Monterey Bay, Louisiana- Texas Shelf, North Atlantic Kopt = 40, Mopt = 30

Determination of Spectral Coefficients (Ill-Posed Algebraic Equation) This is caused by the features of the matrix A.

Rotation Method (Chu et al., 2004) Well-Posed The matrix S is determined by

Errors 0 48 l 1 Tˆ T ( x) T D ( x) T ( x) l l uˆ 24 0 n n n 1 u( x, t) C A k ( x) u( x) u ( x) T, u errors

Noise-to-Signal Ratio Error Estimation αβ, α β ( P) ( P) ( T, T T ') ~ 0.1

OSD Applications (a) Baroclinic Rossby Waves in the tropical North Atlantic at mid-depth (Argo Trajectory Data) (b) Synoptic Current Reversals on the Texas- Louisiana Continental Shelf (Surface Drifting Buoys) (c) Monterey Bay Surface Circulation (CODAR) (d) Synoptic (T, S) Fields for Pacific

(a) Baroclinic Rossby Waves in the tropical North Atlantic at middepth (ARGO)

References Chu, P.C., L.M. Ivanov, and O.M. Melnichenko, 2005: Fall-winter current reversals on the Texas- Lousiana continental shelf. Journal of Physical Oceanography, 35, 902-910 Chu, P.C., L.M. Ivanov, O.M. Melnichenko, and N.C. Wells, 2007: On long baroclinic Rossby Waves in the tropical North Atlantic observed from profiling floats. Journal of Geophysical Research Oceans, 112, C05032, doi:10.1029/2006jc003698. These papers can be downloaded from: http://www.nps.edu/pcchu

Tropical North Atlantic (4 o -24 o N) Important Transition Zone Meridional Overturning Circulation (MOC) (Rahmstorf 2006)

MOC Variation Heat Transport Variation Climate Change

Are mid-depth (~1000 m) ocean circulations steady? If not, what mechanisms cause the change? (Rossby wave propagation)

Argo Observations (Oct-Nov 2004) (a) Subsurface tracks (b) Float positions where (T,S) were measured

Circulations at 1000 m estimated from the original ARGO float tracks (bin method) April 2004 April 2005 It is difficult to use such noisy data into ocean numerical models.

Boundary Configuration Basis Functions for OSD

Basis Functions for Streamfunction Mode-1 and Mode-2

Circulations at 1000 m (March 04 to May 05) Bin Method OSD

Fourier Expansion Temporal Annual and Semi-anuual

Fourier Expansion Temporal Annual and Semi-anuual

Optimization

Annual Component

Semi-annual Component

Time Longitude Diagrams of Meridional Velocity Along 11 o N Annual Semi-Annual

Time Longitude Diagrams of temperature Along 11 o N Annual Semi-Annual Annual Semi-Annual 550 m 950 m

Characteristics of Annual Rossby Waves Western Basin Eastern Basin Western Basin Eastern Basin

(b) Synoptic Current Reversals on the Texas-Louisiana Continental Shelf (Surface Drifting Buoys)

Ocean Velocity Observation 31 near-surface (10-14 m) current meter moorings during LATEX from April 1992 to November 1994 Drifting buoys deployed at the first segment of the Surface Current and Lagrangian-drift Program (SCULP-I) from October 1993 to July 1994.

Moorings and Buoys

LTCS current reversal detected from SCULP-I drift trajectories.

LTCS current reversal detected from the reconstructed velocity data December 30, 1993 January 3, 1994 January 6, 1994

EOF Analysis of the Reconstructed Velocity Filed EOF Variance (%) 01/21/93-05/21/93 12/19/93-04/17/94 10/05/94-11/29/94 1 80.2 77.1 74.4 2 10.1 9.5 9.3 3 3.9 5.6 6.9 4 1.4 3.3 4.6 5 1.1 1.4 2.3 6 0.7 1.1 0.8

Mean and First EOF Mode

Mean Circulation 1. First Period (01/21-05/21/93) 2. Second Period 12/19/93-04/17/94) 3. Third Period (10/05-11/29/94)

EOF1 1. First Period (01/21-05/21/93) 2. Second Period 12/19/93-04/17/94) 3. Third Period (10/05-11/29/94)

Calculated A1(t) Using Current Meter Mooring (solid) and SCULP-1 Drifters (dashed)

8 total reversals observed Uals ~ alongshore wind

Results Alongshore wind forcing is the major factor causing the synoptic current reversal. Other factors, such as the Mississippi- Atchafalaya River discharge and offshore eddies of Loop Current origin, may affect the reversal threshold, but can not cause the synoptic current reversal.

(c) Monterey Bay Surface Circulation (CODAR)

CODAR

Monterey Bay

30 cm/s 37.0 o N 30 cm/s 36.9 o N 36.8 o N 36.7 o N 36.6 o N 122.2 o W 122.1 o W 122.0 o W 121.9 o W 121.8 o W 122.2 o W 122.1 o W 122.0 o W 121.9 o W 121.8 o W Place for comments: left - radar derived currents for 17:00 UT December 1, 1999 right reconstructed velocity field.

Preliminary Comparison of OSD and OI Mean (1990-2009) Visual comparison of the Optimal Spectral Decomposition (OSD)-derived SST (left) to the NOAA Optimally Interpolated (OI) SST (right)

(d) Temporal and spatial variability of Pacific Ocean 1990-2009

Monthly Temperature (10 m) in the Pacific Ocean since 1990 (analyzed from GTSPP)

Monthly Temperature (100 m) in the Pacific Ocean since 1990 (analyzed from GTSPP)

Monthly Temperature (500 m) in the Pacific Ocean since 1990 (analyzed from GTSPP)

Monthly Temperature (1000 m) in the Pacific Ocean since 1990

Conclusions OSD is a useful tool for processing realtime velocity data with short duration and limited-area sampling especially the GTSPP/Argo data. OSD has wide application in ocean data assimilation.

What is next? It is an urgent need to establish monthly varying (T, S, u, v) gridded dataset from GTSPP and Argo trajectory data Oceanographic and Climate Studies

Steps for GTSPP Data Analysis (1) Change the current data format one file for one profile into new data format one file for profiles in a month from January 1990 for individual ocean basin (Atlantic, Pacific, Indian oceans). (2) Reconstruct the profile data with the same month and year into grid points using the Optimal Spectral Decomposition (OSD) method.

4D Global Velocity Data Reference + Geostrophic (T, S)