Climatology Software for MatlabTest region: Middle Atlantic Bight

Chris Linder and Glen Gawarkiewicz

Woods Hole Oceanographic Institution

Climatology Software for MatlabTest region: Middle Atlantic Bight

Chris Linder and Glen Gawarkiewicz

Woods Hole Oceanographic Institution

Jen Hua Tai

National Taiwan University

...and preliminary results from Taiwan!

Outline

• Overview of the Middle Atlantic Bight test region• Previous climatology research and motivation for new

software• Matlab planview climatology program

– Seasonal mean and standard deviation results for Middle Atlantic Bight

• Matlab cross-shelf climatology program– Seasonal mean and standard deviation results for

Nantucket Shoals subregion

• Comparison of output fields to observations• Preview of application of climatology to SCS/ECS

Large-scale North Atlantic circulation

• Southward-flowing Labrador current

• Northeastward-flowing Gulf Stream

Middle Atlantic Bight

Shelfbreak front

• Separates cold, fresh shelf water from warm, salty slope water

• Slope of front leads to strong baroclinic jet

• Gulf Stream rings• Filaments,

meanders

• Typical cross-shelf temperature, salinity, and density plots for winter and summer time periods

• Winter (left-hand side): steeply sloping isopycnals, clear division between shelf and slope water masses

• Summer (right-hand side): “cold pool” over shelf, isopycnal slope flattened by seasonal thermocline

Figure courtesy C. Flagg and T. Hopkins, from Houghton et al., 1988

Initial climatology of the shelfbreak front 1994-1996

• Goal: determine seasonal differences in the position, strength, and cross-shelf gradients of the shelfbreak front at three locations

• Challenge: How do we synthesize 100 years of hydrographic data into three cross-shelf sections?

• Assumption: across-shelf gradients are much stronger than along-shelf – CTD data can be sorted into bins based on cast depth to preserve water mass characteristics

Winter and summer shelfbreak jet(Blue = West-flowing current)

Max 18 cm/s west Max 25 cm/s west

Motivation for climatology tools• Multiple projects

– Correlation with bottlenose dolphin sightings– Bottom boundary layer detachment (publications: Pickart 2002,

Linder et al., 2004)– Characterizing uncertainty initiative: desire to identify regions of high

variability, and thus high error in acoustic propagation calculations

• How could we map out these areas of high variability?– Given a set of CTD observations, compute planview and cross-shelf

maps of the mean and standard deviation of temperature and salinity

• Can tools be created to analyze these problems globally?– Standard ASCII input file format– Program as a Matlab function

• Industry-standard platform-independent plotting and analysis program• Allows for easily changed user-defined input parameters

Bottlenose dolphin sightingsMotivation for planview maps of MAB T/S

Winter Summer

Bottom boundary layer results:Seasonal differences in upwelling

From Linder et al., 2004

Improvements over 1998 climatology

• 40% more data available

• Four 3-month seasons instead of bi-monthly improves statistics

• Fixed horizontal bin size of 10km doubles the resolution in low bottom slope areas such as the continental shelf

• Addition of planview analysis feature

Data sources for MAB planview climatologyTotal 41345 CTD casts

• Hydrobase2 (Curry, 2002) 21835 casts– Raw profiles from World Ocean Database 1998,

WOCE, ICES, BarKode

• Quality controlled data from other sources– NMFS dataset (M. Taylor) 19200 casts– Shelf-Edge Exchange Processes project (C.

Flagg) 310 casts

Seasonal definition and data distribution

• Spring = April 1 to June 30 30%

• Summer = July 1 to Sept 30 24%

• Fall = Oct 1 to Dec 31 20%

• Winter = Jan 1 to March 31 26%

• Majority of data from 1990-2002

Methods – Planview

• Assumptions– No cross-shelf or along-shelf flow assumptions

required

• Averaging scheme– Season and depth range selected by user– Resolution (degrees), search range (km),

minimum to comprise mean selected by user– T/S averaged for each node using a Hamming

window spatial weighting function

Planview climatology program inputs

– Input data specifications• Data file, in ASCII text format: location, date, T, S • Season: a listing of all months to include in average• Domain boundaries: define box in degrees lat/lon• Cutoffhighdepth and cutofflowdepth: only CTD casts taken at

depths in between these bounds will be included• Slice depth limits: data points must be in between these depth

bounds– Averaging and output grid specifications:

• Gridspacing: spacing in decimal degrees of output grid• Search radius: casts must be closer than this distance from the

output grid node to be included in the mean; larger radius means more overlap and smoother results

• Minnumpts : minimum number of points to comprise a good average (NaN is assigned to output otherwise)

Resolution (degrees)

Search radius (km)

Winter mid-depth Middle Atlantic Bight example

Cutofflowdepth

Cutoffhighdepth

Output grid

example

Sample planview output – MAB mid-depth (40-55m)Number of casts per grid node

Sample planview output – MAB mid-depth (40-55m)Mean temperature

Sample planview output – MAB mid-depth (40-55m)Standard deviation of temperature

Sample planview output – MAB mid-depth (40-55m)Mean salinity

Sample planview output – MAB mid-depth (40-55m)Standard deviation of salinity

Methods – Cross-shelf• Assumptions

– Cross-shelf gradients are much higher than along-shelf– Currents and water properties align with local bathymetry

• Averaging scheme– Season (specific months) and vertical and horizontal bin

sizes specified by user– User selects baseline isobath– Program sorts each cast into proper “bin” based on its

perpendicular distance to the baseline; once T/S data is binned, mean and standard deviation are computed for each bin

Cross-shelf climatology program inputs– Input data specifications

• Data file: in ASCII text format: location, date, T, S • Season: a listing of all months to include in average• Baseline isobath: midpoint of the x-axis for the analysis and figures• Domain boundaries: define box in degrees lat/lon

– Averaging and output grid specifications: • Maximum depth: data points deeper than this will be excluded• Extent of output grid onshore and offshore: measured in km from

the baseline isobath - the horizontal extent of the climatology• Horizontal bin size: in kilometers - horizontal resolution• Vertical bin size: in meters - vertical resolution• Minnumpts: minimum number of points to comprise a good average

(NaN is assigned to output otherwise)• Smoothing: amount of smoothing (can be zero) applied by PlotPlus

ppzgrid routine adapted for Matlab

Nantucket ShoalsCross-shelf temperature – mean and standard deviation

Nantucket ShoalsCross-shelf salinity – mean and standard deviation

Nantucket Shoals Geostrophic velocityWinter Summer

Relative vorticityWinter Summer

Comparison with observations

• Climatology sections vs. summer Shelfbreak PRIMER 1996 experiment SeaSoar mean section– Mean T/S– Standard deviation T/S

• Comparison with individual high-resolution SeaSoar sections from winter and summer– Cross-shelf T/S gradient comparison– Stratification (N2) comparison

Mean temperature

Summer climatology> 90 years of data

Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

Standard deviation of temperature

Summer climatology> 90 years of data

Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

Mean salinity

Summer climatology> 90 years of data

Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

Standard deviation of salinity

Summer climatology> 90 years of data

Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

Cross-shelf gradient comparison with SINGLE SeaSoar section

Stratification comparison with SINGLE SeaSoar section

Preliminary figures of Taiwan area

• Planview maps: mean & standard deviation temperature and salinity, summer and winter, 40km search radius for near-surface (0-15m)

• Cross-shelf sample area for East China Sea northeast of Taiwan: mean & standard deviation temperature and salinity, summer and winter

Grid setup for planview case - 0.25 degree grid spacing, 40km search radius, 0-15m depth

Planview number of points

Winter Summer

Planview mean temperature

Winter Summer

Planview mean salinity

Winter Summer

Planview standard deviation temperature

Winter Summer

Planview standard deviation salinity

Winter Summer

Sample cross-shelf areaEast China Sea NE of Taiwan

Number of points

Winter Summer

Mean temperature

Winter Summer

Mean salinity

Winter Summer

Standard deviation of temperature

Winter Summer

Standard deviation of salinity

Winter Summer

Conclusions and Future Work

• Programs can be run in any data-rich ocean area

• Numerous applications– Finding variability hotspots– Initializing numerical models

• Continuing to improve climatology and look at different areas near Taiwan– Comparisons with ODB climatology and

synoptic fields

Extras

Bottom boundary layer investigations Motivation for improving cross-shelf method

Nantucket Shoals Flux Experiment (1979) moored temperature histograms

Scale of subplots: 0-30 C

New JerseyCross-shelf temperature – mean and standard deviation

New JerseyCross-shelf salinity – mean and standard deviation

Potential vorticityWinter Summer

Summer standard deviation of salinity

Summer climatology> 90 years of data

Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

Other climate analyses:NOAA CTD data (1990-2002)

Scatter (gray), monthly mean (line) and standard deviation (bar)

a. 5m temperature minus 20m temperature

b. Strength of maximum stratification

c. Location in the water column of maximum stratification

Dominant empirical orthogonal function (EOF) modes of variability over 1 week from SeaSoar observations-- another way to location areas of maximum variability

Subsurface maximum,

“heart of the frontal zone”