1. Climatology Software for Matlab Test region: Middle Atlantic Bight Chris Linder and Glen Gawarkiewicz Woods Hole Oceanographic Institution

2. Climatology Software for Matlab Test region: Middle Atlantic Bight Chris Linder and Glen Gawarkiewicz Woods Hole Oceanographic Institution Jen Hua Tai National Taiwan University...and preliminary results from Taiwan!

3. 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

4. Large-scale North Atlantic circulation Southward-flowing Labrador current Northeastward- flowing Gulf Stream

5. 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

6. 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

9. 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

11. Winter and summer shelfbreak jet (Blue = West-flowing current) Max 18 cm/s west Max 25 cm/s west

12. 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

13. Bottlenose dolphin sightings Motivation for planview maps of MAB T/S

14. Winter Summer Bottom boundary layer results: Seasonal differences in upwelling From Linder et al., 2004

15. 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

16. Data sources for MAB planview climatology Total 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

17. 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

18. 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

19. 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)

20. Resolution (degrees) Search radius (km)

21. Winter mid-depth Middle Atlantic Bight example Cutofflowdepth Cutoffhighdepth Output grid example

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

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

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

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

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

27. 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

28. 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

34. Nantucket Shoals Cross-shelf temperature – mean and standard deviation

35. Nantucket Shoals Cross-shelf salinity – mean and standard deviation

36. Nantucket Shoals Geostrophic velocity Winter Summer

37. Relative vorticity Winter Summer

38. 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 (N 2 ) comparison

39. Mean temperature Summer climatology > 90 years of data Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

40. Standard deviation of temperature Summer climatology > 90 years of data Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

41. Mean salinity Summer climatology > 90 years of data Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

42. Standard deviation of salinity Summer climatology > 90 years of data Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

43. Cross-shelf gradient comparison with SINGLE SeaSoar section

44. Stratification comparison with SINGLE SeaSoar section

45. 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

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

48. Planview number of points Winter Summer

49. Planview mean temperature Winter Summer

50. Planview mean salinity Winter Summer

51. Planview standard deviation temperature Winter Summer

52. Planview standard deviation salinity Winter Summer

53. Sample cross-shelf area East China Sea NE of Taiwan

54. Number of points Winter Summer

55. Mean temperature Winter Summer

56. Mean salinity Winter Summer

57. Standard deviation of temperature Winter Summer

58. Standard deviation of salinity Winter Summer

59. 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

61. Extras

62. Bottom boundary layer investigations Motivation for improving cross-shelf method

63. Nantucket Shoals Flux Experiment (1979) moored temperature histograms Scale of subplots: 0-30 C

64. New Jersey Cross-shelf temperature – mean and standard deviation

65. New Jersey Cross-shelf salinity – mean and standard deviation

66. Potential vorticity Winter Summer

67. Summer standard deviation of salinity Summer climatology > 90 years of data Mean over 1 week (26 sections) during summer 1996 Shelfbreak PRIMER cruise

68. 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

69. 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”