DOI: 10.5061/dryad.msbcc2g7n
title: Vertical ocean heat transport near Antarctic ice shelves: data and processing code

description: Antarctic ice shelves, or the floating extension of terrestrial glaciers,
 help limit Antarctica’s contribution to global sea level rise by slowing
 the export of grounded ice into the Southern Ocean. Identifying the
 distribution of meltwater from the ocean-driven melt of these ice shelves
 helps determine where and at what rate they are thinning, providing
 insight into how quickly their buttressing effect is diminishing. In
 regions with rapid ice shelf melt, the resulting freshwater flux into the
 coastal ocean contains enough buoyancy forcing to reshape coastal currents
 and alter ocean stratification up to thousands of kilometers from the
 meltwater’s source. Global circulation models are employed to help
 understand how ice shelf meltwater modifies the Southern Ocean and are
 extended forward in time to attempt to predict the consequences of a
 future with increased ice melt. However, because they are unable to
 efficiently resolve small scale turbulent mixing, these models make
 assumptions regarding the mechanisms that drive the mixing and use
 parameterizations to simplify the effects of turbulence, such as the
 diffusion rates heat and salinity. While common turbulence
 parameterizations have been found to work well throughout much of the
 Earth’s oceans, the lack of in situ turbulence measurements near
 Antarctica have left parameterizations comparatively uniformed and
 untested near melting ice shelves. This dissertation works to improve the
 understanding of the downstream effects of ice shelf meltwater via the
 collection of rare in situ oceanographic measurements near Antarctic ice
 shelves. Here, we present the identification and analysis of meltwater
 layers within the Southern Ocean near two Antarctic ice shelves. At Nansen
 Ice Shelf, traces of meltwater in the form of frigid Ice Shelf Water were
 observed at the opening of the ice shelf cavity, and vertical heat flux
 estimates derived from direct measurements of microstructure turbulence
 show approximately 10 W m-2 of heat transport into the meltwater from both
 above and below. The position of this layer within the water column was
 heavily modified by the presence of a coastal, submesoscale eddy, which
 lifted the meltwater toward the ice shelf-ocean interface, potentially
 resulting local variations in basal melt rate. On the other hand, at
 Dotson Ice Shelf, ice shelf melt in the form of warmer Glacial Meltwater
 was observed across two layers in front of the ice shelf cavity at
 quantities not observed for over a decade. These meltwater layers were
 determined to be largely derived from different sources, with the deeper
 Subglacial Meltwater layer originating from beneath the western corner of
 Dotson Ice Shelf, and the shallower Ventilated Meltwater layer originating
 from the previous melt of other upstream ice shelves. Here, additional but
 more limited measurements of turbulence were used to validate modeled
 energy dissipation rates, which then again indicate approximately 10 W m-2
 of heat transport through the meltwater: largely upwards through the
 deeper layer and downwards through the shallower layer. Our results show
 that the meltwater layers resulted in the formation of step-like changes
 temperature stratification, which support particularly efficient mixing.
 Together, the observations from these two unique ice shelf systems show
 that melt from ice shelves is intrinsically tied to local oceanography,
 and that our ability to predict how future changes in the Antarctic
 cryosphere will affect global thermohaline circulation relies on the
 accuracy of well-informed ocean mixing parameterizations.
description: In Chapter 2, ship-based conductivity-temperature-depth (CTD) and
 lowered acoustic Doppler current profiler (LADCP) data was collected via
 in situ profiling aboard the Research Vessel Ice Breaker (RVIB)
 <em>Araon</em>. Seafloor bathymetry data was as produced by
 multi-beam sonar aboard the research cruise. Glider CTD and MicroRider
 (MR) data was collected in situ across two missions. Ice shelf bathymetry
 data is from Dow et al. (2018). Sea ice data was derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery via the National Aeronautics and Space Administration (NASA) Worldview platform. Wind data were recorded by Automatic Weather Station (AWS) Manuela, part of the University of Wisconsin-Madison AWS Program. In Chapter 3 and Chapter 4, ship-based vertical microstructure profiler data (VMP), again along with CTD and LADCP data, were collected via in situ profiling aboard the RVIB Araon. Glider-based CTD data were collected in situ across a single mission. Historical CTD and LADCP data were sourced from Jenkins et al. (2018). Landsat imagery was provided courtesy of the U.S. Geological Survey. Sea ice data was derived from Nimbus-7 Passive Microwave Data via the NASA Snow and Ice Data Center Distributed Active Archive Center (Cavalieri et al., 1996). Wind data was derived from ERA5 reanalysis data (Hersbach et al. 2023). In Appendix C, multibeam bathymetry, CTD, LADCP, and vehicle-mounted acoustic Doppler current profiler (VM-ADCP) data were all collected via surveying on the Research Vessel Frantz. Further details regarding the CTD and VM-ADCP datafiles are provided in the <em>CTD_metadata.xlsx</em> and <em>ADCP_metadata.xlsx</em> spreadsheets. Lake Shasta elevations and Shasta Dam flowrates were sourced from the California Data Exchange Center. All data processing for the main chapters, and the majority of processing for Appendix C, took place using MATLAB (version 2024b). In Chapter 2, ship-based CTD and LADCP data was processed using the <em>process_ship.m</em> script, which combines all of the raw ship data files into the <em>ship.mat</em> datafile for this chapter. MR data was processed using the <em>process_MR.m</em> script, which processes all of the MR data files in order, resulting in the <em>MR.mat</em> datafile. Finally, glider data was processed with <em>process_glider.m</em>, which combines data from the two glider missions into a single glider.mat data file for this chapter. In Chapter 3 and Chapter 4, VMP data was processed using the <em>process_VMP.m</em> script, which only processes one raw VMP datafile at a time and thus requires multiple runs with manual user edits (change input filename on line 6) between each run. Ship-based CTD and LADCP data was processed using another <em>process_ship.m</em> script, which combines all of the raw ship data files into the <em>ship.mat</em> datafile for these chapters. Ship-based data was reprocessed to match the format of Jenkins et al. (2018) data with the <em>process_2022_for_Jenkins.m</em> script, the outputs of which are saved as <em>Dotson2022.mat</em>. The <em>process_Jenkins_data.m</em> script then calculates meltwater transport for each study year (variables <em>data_2000</em>, <em>data_2007</em>, <em>data_2009</em>, etc.) which are together saved as <em>all_data.mat</em>. Glider data was processed using another <em>process_glider.m</em> script, which produces the <em>glider.mat</em> datafile for this chapter. Finally, ship- and glider-based turbulence model results were produced with the <em>process_ship_model.m</em> and <em>process_glider_model.m</em> scripts, respectively. In Appendix C, VM-ADCP data were processed using <em>process_transect.m</em>. This script also only processes one data transect or data station at a time, and for each transect/station, requires multiple iterations with manual user edits each time. A first iteration requires the filename to be chosen (line 8). The indices of bad data (line 10), indices of Head Tower interference (line 12), and cutoff depth (line 16) should start as empty arrays. The padding for dam interference should start as 0. After a first run, the output figure is examined and bad indices (line 10) are chosen from identifying major outliers within the velocity data (u, v, w, and speed subplot columns). Head Tower interference indices (line 12) are chosen from examining the amplitude and correlation subplots. A buffer for dam interference (line 14) is chosen if high velocities near the dam are still visible along the deepest velocity data after Step 6 (and carried through remaining steps). A depth cutoff (line 16) is chosen to remove the high velocity spikes at the bottom of the average velocity profile (far right subplot column). If any of these lines (10, 12, 14, 16) were changed, the script is rerun before the output (variable ADCP) can be saved (e.g., as <em>A24_01_T01.mat</em>, <em>A24_01_T02.mat</em>, etc.). All processed data from a single data group were saved together (e.g., as <em>A24_01_processed.mat</em>). See the readme for more information.
description: # **Vertical Ocean Heat Transport near Antarctic Ice Shelves: Data and
 Processing Code**
 [https://doi.org/10.5061/dryad.msbcc2g7n](https://doi.org/10.5061/dryad.msbcc2g7n) ## **Overview** The goal of this collection of files is to allow for the replication of the MATLAB data processing and figure creation found in Vertical Ocean Heat Transport near Antarctic Ice Shelves. The entirety of these files and codes are designed to be run in MATLB version 2024b. Seven folders are provided across this data repository: * *data*: all of the raw and processed data * *ch1*: MATLAB scripts for recreating the figures in Chapter 1 * *ch2*: MATLAB scripts for processing Chapter 2 data and recreating the Chapter 2 figures * *ch3*: MATLAB scripts for processing Chapter 3 data and recreating the Chapter 3 figures * *ch4*: MATLAB scripts for processing Chapter 4 data and recreating the Chapter 4 figures * *apxC*: MATLAB scripts for processing Appendix C data and recreating the Appendix C figures * *other_functions* The contents of these folders are described below.   ### ***data*** The *data* folder is further divided into three folders: *data/ch2*, *data/ch3_ch4*, and *data/apxC*, named according to the relevant chapter where this data is used.   #### ***data/ch2*** Within *data/ch2* is one folder (*MR_raw*), along with 10 ".mat" data files (*bathy.mat*, *glider.mat*, *glider_1.raw.mat*, *glider_2.mat*, *ice_shelf.mat*, *MR.mat*, *sea_ice.mat*, *ship.mat*, *ship_raw.mat*, and *wind_data.mat*). These files are described here: The folder *data/ch2/MR_raw* contains raw autonomous underwater glider-based MicroRider (MR) data, provided as ".P" files native to Rockland Scientific instrumentation, which are typically manipulated using Rockland's ODAS library of MATLAB functions (Douglas et al., 2018). The P-files are named according to glider mission (1 or 2) followed by the P-file number. For example, the seventh P-file collected during the second glider mission is named (*MR2_DAT007.P*).   The data file *bathy.mat* contains seafloor bathymetry data as produced by multi-beam sonar aboard the research cruise, with the variables: * *bedtopo*: topographic elevation (m above sea level, or asl; gridded by location) * *nlat*: latitude (ºN; gridded by location) * *nlon*: longitude (ºE; gridded by location)   The data file *glider.mat* contains processed, glider-based, oceanographic data, producing the data structure *glider* with the variables: * *glider.bed_bathy*: seafloor depth (m bsl) * *glider.chi*: rate of temperature variance dissipation (ºC<sup>2</sup> s<sup>-1</sup>) * *glider.CT*: conservative temperature (ºC) * *glider.d*: depth (m bsl) * *glider.date*: timestamp (DOY) * *glider.ice_draft*: nearby ice shelf draft (m bsl) * *glider.lat*: latitude (ºN) * *glider.lon*: longitude (ºE) * *glider.p*: pressure (dbar) * *glider.Prho*: potential density (kg m<sup>-3</sup>) * *glider.Q*: vertical heat flux (W m<sup>-2</sup>) * *glider.r*: radius from eddy center (km) * *glider.Tz*: vertical temperature gradient (ºC m<sup>-1</sup>) * *glider.SA*: absolute salinity (g kg<sup>-1</sup>) * *glider.z*: elevation (m asl) where, in each case, rows indicate 1 m depth intervals and columns indicate 248 individual profiles.   The two data files *glider1_raw.mat* and *glider2_raw.mat* contain the raw, glider-based oceanographic data, each with the variables: * *Conductivity*: conductivity (cS m<sup>-1</sup>) * *Lat_deadreckoned*: latitude between GPS readings, determined from dead reckoning (ºN) * *Lat_GPS*: latitude from active GPS readings (ºN) * *Lon_deadreckoned*: longitude between GPS readings, determined from dead reckoning (ºE) * *Lon_GPS*: longitude from active GPS readings (ºE) * *Pressure*: pressure (bar) * *Temperature*: temperature (ºC) * *Time*: timestamp (dd-mmm-yyyy hh:mm:ss UTC)   The data file *ice_shelf.mat* contains ice shelf thickness data derived from Dow et al. (2018), with the variables: * *draft*: ice shelf draft (m asl) * *lat*: latitude (ºN) * *lon*: longitude (ºE)   The data file *MR.mat* contains processed glider-based MR data, producing a series of data structures named according to the aforementioned raw P-files, each with the variables * *chi*: rate of temperature variance dissipation (ºC<sup>2</sup> s<sup>-1</sup>) * *date*: timestamp (DOY) * *k*: wavenumber (cpm; columns indicate timestamps; rows indicate the wavenumber domain corresponding to a spectrum at a given time stamp) * *kL*: lower wavenumber integration limit (cpm) * *kU*: upper wavenumber integration limit (cpm) * *MAD*: Mean absolute deviation of the fit between *PSD_clean* and *PSD_theory* between *kL* and *kU* (unitless) * *MADc*: Mean absolute deviation cutoff to determine if a fit is close (unitless) * *p*: pressure (dbar) * *PSD_raw*: raw power spectral density of microstructure temperature (ºC<sup>2</sup> m<sup>-2</sup> cpm<sup>-1</sup>; columns indicate timestamps; rows indicate the spectrum at a given time stamp) * *PSD_clean*: filtered power spectral density of microstructure temperature (ºC<sup>2</sup> m<sup>-2</sup> cpm<sup>-1</sup>; columns indicate timestamps; rows indicate the spectrum at a given time stamp) * *PSD_noise*: theoretical power spectral density of noise from the microstructure temperature probe (ºC<sup>2</sup> m<sup>-2</sup> cpm<sup>-1</sup>; columns indicate timestamps; rows indicate the spectrum at a given time stamp) * *PSD_theory*: Kraichnan theoretical spectral density of microstructure temperature (ºC<sup>2</sup> m<sup>-2</sup> cpm<sup>-1</sup>; columns indicate timestamps; rows indicate the spectrum at a given time stamp)   The data file *sea_ice.mat* contains sea ice boundary data manually derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery via the National Aeronautics and Space Administration (NASA) Worldview platform. The file produces the matrix *ice*, with column 1 indicating longitude (ºE) and column 2 indicating latitude (ºN).   The data file *ship.mat* contains processed ship-based oceanographic data collected from conductivity-temperature-depth (CTD) and lowered acoustic Doppler current profiler (LADCP) instruments aboard the Korean icebreaker RV *ARAON*. The file produces the structure *ship* with the variables: * *ship.bed_bathy*: seafloor depth (m below sea level, or bsl) * *ship.CT*: conservative temperature (ºC) * *ship.d*: depth (m bsl) - *ship.date*: timestamp (DOY) - *ship.ice_draft*: nearby ice shelf draft (m bsl) - *ship.lat*: latitude (ºN) - *ship.lon*: longitude (ºE) - *ship.omega*: eddy azimuthal velocity (m s<sup>-1</sup>; positive clockwise) - *ship.p*: pressure (dbar) - *ship.Prho*: potential density (kg m<sup>-3</sup>) - *ship.r*: radius from eddy center (km) - *ship.SA*: absolute salinity (g kg<sup>-1</sup>) - *ship.u*: eastward velocity (m s<sup>-1</sup>) - *ship.v*: northward velocity (m s<sup>-1</sup>) - *ship.z*: elevation [m asl] where, in each case, rows indicate 1 m depth intervals and columns indicate 65 individual profiles.   The data file *ship_raw.mat* contains the raw ship-based oceanographic data, which produces the MATLAB structure *ship* with the variables: * *ship.ADCP.UU*: eastward velocity (m s<sup>-1</sup>); rows indicate 5 dbar depth intervals; columns indicate 65 individual profiles) * *ship.ADCP.VV*: northward velocity (m s<sup>-1</sup>; rows indicate 5 dbar depth intervals; columns indicate 65 individual profiles) * *ship.ADCP.Dep*: depth of velocity data (m; rows indicate 5 dbar depth intervals; columns indicate 65 individual profiles) * *ship.CTD.End*: timestamp of the end of each profile (UTC; rows indicate 65 individual profiles; columns indicate year, month, day, hour, minute, and second, respectively) * *ship.CTD.Lat*: latitude (ºN; rows indicate 1 dbar depth intervals; columns indicate 65 individual profiles) * *ship.CTD.Lon*: longitude (ºE; rows indicate 1 dbar depth intervals; columns indicate 65 individual profiles) * *ship.CTD.Pre*: pressure of temperature and salinity data (dbar; rows indicate 1 dbar depth intervals; columns indicate 65 individual profiles) * *ship.CTD.Sali*: practical salinity (PSU; rows indicate 1 dbar depth intervals; columns indicate 65 individual profiles) * *ship.CTD.Start*: timestamp of the start of each profile (UTC; rows indicate 65 individual profiles; columns indicate year, month, day, hour, minute, and second, respectively) * *ship.CTD.Temp*: temperature (ºC; rows indicate 1 dbar depth intervals; columns indicate 65 individual profiles)   Finally, the data file *wind_data.mat* contains wind data recorded by Automatic Weather Station (AWS) Manuela, part of the University of Wisconsin-Madison AWS Program, producing two matrices *manuela201812* and *manuela201901* named according to the month of origin. The matrices have columns 1, 2, 5, and 6 corresponding to date (day of the year, or DOY), time stamp number (6 minute interval), temperature (ºC), and wind direction (º; from), respectively.   #### *data/ch3\_ch4* Within *data/ch3_ch4* are three folders (*ADCP_raw*, *Jenkins2018*, *landsat*, *VMP_raw*, and *wind_raw*), along with 8 ".mat" data files (*glider.mat*, *glider_model.mat*, *glider_raw.mat*, *seaice.mat*, *ship.mat*, *ship_CTD_raw.mat*, *ship_model.mat* and *VMP.mat*) and 1 ".nc" data file (*wind.nc*). These files are described here:   The folder *data/ch3_ch4/ADCP_raw* contains raw, ship-based LADCP data, where individual datafiles are named according to the profile number (e.g., *ADCP005*, *ADCP006*, etc.), and produce the data structure *dr* with variables: * *dr.z*: depth (m bsl) * *dr.u* eastward velocity (m s<sup>-1</sup>) * *dr.v*: northward velocity (m s<sup>-1</sup>)   The folder *data/ch3_ch4/Jenkins2018* contains historical CTD and LADCP data sourced from Jenkins et al. (2018). The 9 raw datafiles are named according to measurement year (e.g., *Dotson2000.mat*), each producing a structure *section* that provides metadata, * *section.noofsta*: number of stations (count) * *section.numbers*: overall station numbers according to original data set, corresponding to *SNP* data matrices * *section.latitudes*: latitude (ºN) * *section.longitudes*: longitude (ºE) as well as a set of matrices that contain the data, named according to the profile number from the original data set (e.g., *SNP3*, *SNP4*, etc.). The columns 2, 4-6, and 8-9 of these data matrices provide pressure (dbar), practical salinity (PSU), dissolved oxygen (ml kg<sup>-1</sup>), potential temperature (ºC), eastward velocity (m s<sup>-1</sup>), and northward velocity (m s<sup>-1</sup>), respectively. The processed data from all years are then contained within the datafile *all_data.mat*, which further produces a set of data structures named according to year (e.g., *data_2000*). These processed data structures contain constant variables, * *data_2000.DO_mCDW*: dissolved oxygen concentration of pure mCDW endmember (ml kg<sup>-1</sup>) * *data_2000.DO_WW*: dissolved oxygen concentration of pure WW endmember (ml kg<sup>-1</sup>) * *data_2000.PT_mCDW*: potential temperature of pure mCDW endmember (ºC) * *data_2000.PT_WW*: potential temperature of pure WW endmember (ºC) * *data_2000.SP_mCDW*: practical salinity of pure mCDW endmember (PSU) * *data_2000.SP_WW*: practical salinity of pure WW endmember (PSU) and data matrices, * *data_2000.dist*: distance from previous profile along transect (km) * *data_2000.DO*: dissolved oxygen concentration (ml kg<sup>-1</sup>) * *data_2000.GMW_good*: trustworthy estimates of GMW concentration (g kg<sup>-1</sup>) * *data_2000.P*: pressure (dbar) * *data_2000.P_last*: pressure of deepest measurement (dbar) * *data_2000.PT*: potential temperature (ºC) * *data_2000.SMW_good*: trustworthy estimates of SMW concentration (g kg<sup>-1</sup>) * *data_2000.SP*: practical salinity (PSU) * *data_2000.theta*: bearing from previous profile along transect (º) * *data_2000.u*: eastward water velocity (m s<sup>-1</sup>) * *data_2000.v*: northward water velocity (m s<sup>-1</sup>) * *data_2000.VMW_good*: trustworthy estimates of VMW concentration (g kg<sup>-1</sup>) * *data_2000.z*: depth (m bsl) * *data_2000.z_last*: depth of deepest measurement (m bsl) where rows indicate 1 m pressure bins and columns indicate individual profiles that make up a transect.   The folder *data/ch3_ch4/landsat* contains Landsat imagery, courtesy of the U.S. Geological Survey, as “.TIF” files across 11 bands, 1. Coastal aerosol 2. Blue 3. Green 4. Red 5. Near infrared 6. Shortwave infrared 1 7. Shortwave infrared 2 8. Panchromatic 9. Cirrus 10. Thermal infrared 1 11. Thermal infrared 2 with metadata provided in the ".txt" file.   The folder *data/ch3_ch4/VMP_raw* contains raw, ship-based vertical microstructure turbulence profiler (VMP) data, provided as ".P" files native to Rockland Scientific instrumentation, which are named according to the VMP station (1-26) followed by the overall P-file number. For example, the data from the seventh VMP station consists of the 77th P-file collected and is named this (*VMP26_DAT077.P*). As with the previously described MR data, these P-files are typically manipulated using Rockland's ODAS library of MATLAB functions (Douglas et al., 2018).   Wind data was derived from ERA 5 hourly data via the Copernicus Climate Change Service (Hersbach et al., 2023). The datafile *wind.nc* provides hourly, ERA 5 gridded wind velocity data across the study site via the Copernicus Climate Change Service (Hersbach et al., 2023) for the first two months of 2022.   The folder *data/ch3_ch4/wind_raw* then contains hourly, gridded ERA 5 wind velocity data across the study site for the entire years 1999-2022, via the Copernicus Climate Change Service (Hersbach et al., 2023). The datafiles are named according to year (e.g., *wind1999.nc*) and in the case of each NetCDF (.nc) file, data variables at indices 0-6 correspond to longitude (ºE), latitude (ºN), date (hours since 00:00 on 1 January 1900), easterly wind velocity (m s<sup>-1</sup>), westerly wind velocity (m s<sup>-1</sup>), and air density over the ocean (kg m<sup>-3</sup>).   The data file *glider.mat* contains processed underwater glider-based oceanographic data, producing the data structure *glider* with variables, * *glider.alpha*: thermal expansion coefficient (ºC<sup>-1</sup>) * *glider.beta*: haline contraction coefficient (kg g<sup>-1</sup>) * *glider.cp*: specific heat capacity (J kg-1 K<sup>-1</sup>) * *glider.CT*: conservative temperature (ºC) * *glider.d*: depth (m bsl) * *glider.date*: timestamp (DOY) * *glider*.*epsLOW*: rate of turbulent kinetic energy dissipation estimated from the Law-of-the-Wall relation (W kg<sup>-1</sup>) * *glider*.*DO*: dissolved oxygen concentration (μmol kg<sup>-1</sup>) * *glider*.*GMW_all*: all estimates of Glacial Meltwater (GMW) concentration (g kg<sup>-1</sup>) * *glider*.*GMW_good*: trustworthy estimates of GMW concentration (g kg<sup>-1</sup>) * *glider*.*GMW_OS*: estimates of GMW concentration from only oxygen and salinity data (g kg<sup>-1</sup>) * *glider*.*GMW_OT*: estimates of GMW concentration from only oxygen and temperature data (g kg<sup>-1</sup>) * *glider*.*GMW_TS*: estimates of GMW concentration from only temperature and salinity data (g kg<sup>-1</sup>) * *glider.lat*: latitude (ºN) * *glider.lon*: longitude (ºE) * *glider*.*mCDW_all*: all estimates of modified Circumpolar Deep Water (mCDW) concentration (g kg<sup>-1</sup>) * *glider*.*mCDW_good*: trustworthy estimates of mCDW concentration (g kg<sup>-1</sup>) * *glider*.*mCDW_OS*: estimates of mCDW concentration from only oxygen and salinity data (g kg<sup>-1</sup>) * *glider*.*mCDW_OT*: estimates of mCDW concentration from only oxygen and temperature data (g kg<sup>-1</sup>) * *glider*.*mCDW_TS*: estimates of mCDW concentration from only temperature and salinity data (g kg<sup>-1</sup>) * *glider*.*N2*: squared buoyancy frequency (s<sup>-2</sup>) * *glider.p*: pressure (dbar) * *glider*.*Prho*: potential density (kg m<sup>-3</sup>) * *glider*.*rho*: density (kg m<sup>-3</sup>) * *glider*.*Rrho*: density ratio (unitless) * *glider*.*SA*: absolute salinity (g kg<sup>-1</sup>) * *glider*.*SMW_all*: all estimates of Subglacial Meltwater (SMW) concentration (g kg<sup>-1</sup>) * *glider*.*SMW_good*: trustworthy estimates of SMW concentration (g kg<sup>-1</sup>) * *glider*.*Sz*: vertical salinity gradient (g kg<sup>-1</sup> m<sup>-1</sup>) * *glider*.*Taf*: temperature above freezing (ºC) * *glider*.*Tu*: Turner angle (º) * *glider*.*Tz*: vertical temperature gradient (ºC m<sup>-1</sup>) * *glider*.*VMW_all*: all estimates of Ventilated Meltwater (VMW) concentration (g kg<sup>-1</sup>) * *glider*.*VMW_good*: trustworthy estimates of VMW concentration (g kg<sup>-1</sup>) * *glider*.*WW_all*: all estimates of Winter Water (WW) concentration (g kg<sup>-1</sup>) * *glider*.*WW_good*: trustworthy estimates of WW concentration (g kg<sup>-1</sup>) * *glider*.*WW_OS*: estimates of WW concentration from only oxygen and salinity data (g kg<sup>-1</sup>) * *glider*.*WW_OT*: estimates of WW concentration from only oxygen and temperature data (g kg<sup>-1</sup>) * *glider*.*WW_TS*: estimates of WW concentration from only temperature and salinity data (g kg<sup>-1</sup>) * *glider*.*z*: elevation (m asl) where, in each case, rows indicate 1 m depth bins and columns indicate 67 individual profiles.   The data file *glider_model.mat* contains the results of glider-based modeled data, producing the structure *glider_model*, with variables, * *glider_model.d*: depth (m bsl) * *glider_model.eps_LOW*: rate of turbulent kinetic energy dissipation calculated from the Law-of-the-Wall relation (W kg<sup>-1</sup>) * *glider_model*.*eps_model*: rate of turbulent kinetic energy dissipation calculated from the combination of the Law-of-the-Wall and the spice model (W kg<sup>-1</sup>) * *glider_model.eps_spice*: rate of turbulent kinetic energy dissipation calculated from the spice model (W kg<sup>-1</sup>) * *glider_model.gamma_DF*: mixing coefficient calculated from the empirically-derived formulation presented in this manuscript (unitless) * *glider_model.gamma_O80*: constant mixing coefficient from Osborn (1980) and Giddy et al. (2023) (unitless) * *glider_model.KT_DF*: thermal diffusivity calculated from *glider_model.gamma_DF* (m<sup>2</sup> s<sup>-1</sup>] * *glider_model.KT_O80*: thermal diffusivity calculated from *glider_model.gamma_O80* (m<sup>2</sup> s<sup>-1</sup>) * *glider_model.lat*: latitude (ºN) * *glider_model.lon*: longitude (ºE) * *glider_model.QT_DF*: vertical heat flux calculated from *glider_model.KT \_DF* (W m<sup>-2</sup>) * *glider_model.QT_O80*: vertical heat flux calculated from *glider_model.KT \_O80* (W m<sup>-2</sup>) * *glider_model*.*Rrho*: density ratio (unitless) * *glider_model*.*SMW_all*: all estimates of SMW concentration (g kg<sup>-1</sup>) * *glider_model*.*SMW_good*: trustworthy estimates of SMW concentration (g kg<sup>-1</sup>) * *glider_model*.*VMW_all*: all estimates of VMW concentration (g kg<sup>-1</sup>) * *glider_model*.*VMW_good*: trustworthy estimates of VMW concentration (g kg<sup>-1</sup>) where, in each case, rows indicate 1 m depth bins and columns indicate 66 individual modeled profiles derived from pairs of adjacent CTD profiles.   The datafile *glider_raw.mat* contains raw glider data collected across a single mission, producing variables: * *conductivity*: conductivity (cS m<sup>-1</sup>) * *date*: timestamp (unix time, or number of non-leap seconds since 00:00 1 January 1970) * *latitude*: latitude determined from dead reckoning (ddmm.mmm north) * *longitude*: longitude determined from dead reckoning (ddmm.mmm east) * *oxygen*: dissolved oxygen concentration (ml l<sup>-1</sup>) * *pressure*: pressure (bar) * *temperature*: temperature (ºC)   The data file *seaice.mat* contains sea ice concentration data derived from Nimbus 7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data via the National Snow and Ice Data Center (University of Colorado Boulder; Cavalieri et al., 1996). The datafile contains sea ice concentrations (%) within the 4-dimensional variable *c*, in which the first dimension represents day of the year (indices corresponding to the data in the variable *day*), the second dimension represents the year (indices corresponding to the data in the variable *year*), and the last two dimensions represent the location (indices corresponding to the data in the 2-dimensional variables *lat* and *lon*; ºN and ºE, respectively).   The data file *ship.mat* contains processed ship-based, measured oceanographic data, producing the structure *ship* with the constant variables, * *ship.CT_GMW*: conservative temperature of pure GMW endmember (ºC) * *ship*.*CT_mCDW*: conservative temperature of pure mCDW endmember (ºC) * *ship*.*CT_WW*: conservative temperature of pure WW endmember (ºC) * *ship*.*DO_GMW*: dissolved oxygen concentration of pure GMW endmember (μmol kg<sup>-1</sup>) * *ship*.*DO_mCDW*: dissolved oxygen concentration of pure mCDW endmember (μmol kg<sup>-1</sup>) * *ship*.*DO_WW*: dissolved oxygen concentration of pure WW endmember (μmol kg<sup>-1</sup>) * *ship.SA_GMW*: absolute salinity of pure GMW endmember (g kg<sup>-1</sup>) * *ship.SA_mCDW*: absolute salinity of pure mCDW endmember (g kg<sup>-1</sup>) * *ship.SA_WW*: absolute salinity of pure WW endmember (g kg<sup>-1</sup>) and with the data matrices, * *ship.chi*: rate of temperature variance dissipation (ºC<sup>2</sup> s<sup>-1</sup>) * *ship.CT*: conservative temperature (ºC) * *ship.d*: depth (m bsl) * *ship.date*: timestamp (DOY) * *ship*.*DO*: dissolved oxygen concentration (μmol kg<sup>-1</sup>) * *ship*.*eps*: rate of turbulent kinetic energy dissipation (W kg<sup>-1</sup>) * *ship*.*epsLOW*: rate of turbulent kinetic energy dissipation estimated from the Law-of-the-Wall relation (W kg<sup>-1</sup>) * *ship*.*KT*: thermal diffusivity (m<sup>2</sup> s<sup>-1</sup>) * *ship*.*gamma_OC72*: mixing coefficient calculated from turbulence measurements and the Osborn and Cox (1972) method (unitless) * *ship*.*GMW_all*: all estimates of GMW concentration (g kg<sup>-1</sup>) * *ship*.*GMW_good*: trustworthy estimates of GMW concentration (g kg<sup>-1</sup>) * *ship*.*GMW_OS*: estimates of GMW concentration from only oxygen and salinity data (g kg<sup>-1</sup>) * *ship*.*GMW_OT*: estimates of GMW concentration from only oxygen and temperature data (g kg<sup>-1</sup>) * *ship*.*GMW_TS*: estimates of GMW concentration from only temperature and salinity data (g kg<sup>-1</sup>) * *ship.lat*: latitude (ºN) * *ship.lon*: longitude (ºE) * *ship*.*mCDW_all*: all estimates of mCDW concentration (g kg<sup>-1</sup>) * *ship*.*mCDW_good*: trustworthy estimates of mCDW concentration (g kg<sup>-1</sup>) * *ship*.*mCDW_OS*: estimates of mCDW concentration from only oxygen and salinity data (g kg<sup>-1</sup> * *ship*.*mCDW_OT*: estimates of mCDW concentration from only oxygen and temperature data (g kg<sup>-1</sup>) * *ship*.*mCDW_TS*: estimates of mCDW concentration from only temperature and salinity data (g kg<sup>-1</sup>) * *ship*.*N2*: squared buoyancy frequency (s<sup>-2</sup>) * *ship.p*: pressure (dbar) * *ship*.*Prho*: potential density (kg m<sup>-3</sup>) * *ship*.*rho*: density (kg m<sup>-3</sup>) * *ship*.*Rrho*: density ratio (unitless) * *ship*.*SA*: absolute salinity (g kg<sup>-1</sup>) * *ship*.*SMW_all*: all estimates of SMW concentration (g kg<sup>-1</sup>) * *ship*.*SMW_good*: trustworthy estimates of SMW concentration (g kg<sup>-1</sup>) * *ship*.*Taf*: temperature above freezing (ºC) * *ship*.*Tu*: Turner angle (º) * *ship*.*Tz*: vertical temperature gradient (ºC m<sup>-1</sup>) * *ship*.*u*: eastward water velocity (m s<sup>-1</sup>) * *ship*.*v*: westward water velocity (m s<sup>-1</sup>) * *ship*.*VMW_all*: all estimates of VMW concentration (g kg<sup>-1</sup>) * *ship*.*VMW_good*: trustworthy estimates of VMW concentration (g kg<sup>-1</sup>) * *ship*.*WW_all*: all estimates of WW concentration (g kg<sup>-1</sup>) * *ship*.*WW_good*: trustworthy estimates of WW concentration (g kg<sup>-1</sup>) * *ship*.*WW_OS*: estimates of WW concentration from only oxygen and salinity data (g kg<sup>-1</sup>) * *ship*.*WW_OT*: estimates of WW concentration from only oxygen and temperature data (g kg<sup>-1</sup>) * *ship*.*WW_TS*: estimates of WW concentration from only temperature and salinity data (g kg<sup>-1</sup>) * *ship*.*z*: elevation (m asl) where, in each case, rows indicate 1 m depth bins and columns indicate 157 individual profiles.   The data file *ship_model.mat* contains the results of ship-based modeled data, producing the structure *ship_model*, with the variables * *ship_model.d*: depth (m bsl) - *ship_model.eps_LOW*: rate of turbulent kinetic energy dissipation calculated from the Law-of-the-Wall relation (W kg<sup>-1</sup>) * *ship_model*.*eps_model*: rate of turbulent kinetic energy dissipation calculated from the combination of the Law-of-the-Wall and the spice model (W kg<sup>-1</sup>) - *ship_model*.*eps_spice*: rate of turbulent kinetic energy dissipation calculated from the spice model (W kg<sup>-1</sup>) where, in each case, rows indicate 1 m depth bins and columns indicate 27 individual modeled profiles derived from pairs of adjacent CTD profiles.   The datafile *ship_CTD_raw.mat* contains raw ship-based data, producing a series of MATLAB tables named according to profile number (e.g., *CTD005*, *CTD006*, etc.). Each table contains has rows corresponding to 1 m depth intervals and columns 2, 3, 4, 8, 11, 12, 17 corresponding to pressure (dbar), temperature (ºC), conductivity (mS m<sup>-1</sup>), oxygen (ml l<sup>-1</sup>), latitude (ºN), longitude (ºE), and date (DOY), respectively.   The data file *VMP.mat* contains processed VMP data named according to the VMP station number (i.e., *VMP01* through *VMP26*). Each data structure contains the variables: * *chi_T1*: rate of temperature variance dissipation from temperature probe 1 (ºC<sup>2</sup> s<sup>-1</sup>) * *chi_T2*: rate of temperature variance dissipation from temperature probe 2 (ºC<sup>2</sup> s<sup>-1</sup>) * *date*: timestamp (DOY) * *eps_S1*: rate of turbulent kinetic energy dissipation calculated from shear probe 1 (W kg<sup>-1</sup>) * *eps_S2*: rate of turbulent kinetic energy dissipation calculated from shear probe 2 (W kg<sup>-1</sup>) * *eps_T1*: rate of turbulent kinetic energy dissipation calculated from temperature probe 1 (W kg<sup>-1</sup>) * *eps_T2*: rate of turbulent kinetic energy dissipation calculated from temperature probe 2 (W kg<sup>-1</sup>) * *p*: pressure (dbar)   Finally, the data file *wind.nc* contains hourly, gridded ERA 5 wind velocity data across the study site for the first two months of 2022 via the Copernicus Climate Change Service (Hersbach et al., 2023). Like the previously mentioned wind data, data variables at indices 0-6 correspond to longitude (ºE), latitude (ºN), date (hours since 00:00 on 1 January 1900), easterly wind velocity (m s<sup>-1</sup>), westerly wind velocity (m s<sup>-1</sup>), and air density over the ocean (kg m<sup>-3</sup>).   #### *data/apxC* Within *data/apxC* are two folders (*ADCP *and *CTD*), along with three ".mat" data files (*flowrates_2021.mat*, *flowrates_2024.mat*, and *multibeam.mat*). These files are described here:   The folder *data/apxC/ADCP* contains LADCP and Vehicle-mounted ADCP (VM-ADCP) data collected by Nortek Signature ADCPs mounted on the RV Frantz. Some temperature data were derived from LADCP data and are stored in *data/apxC/ADCP/LADCP*, where the ".mat" data files are numbered according to Group Number (*e.g., L03.mat, L04.mat*) and contain structured variables * *Data.Burst_Pressure*: pressure (dbar) * *Data.Burst_Temperature*: temperature (ºC)   Raw VM-ADCP data files are stored in the folder *data/apxC/ADCP/raw* as “.SigVM” files native to Nortek instrumentation and are named according to the month and year of data collection, along with the data group and range of transect/station numbers that they contain. For example, *A24_01_T01_T05.SigVM* contains data collected in August 2024, from data Group 1, and transects 1-5. They are able to be opened within Nortek’s Signature VM Review software, where were converted to MATLAB format. The corresponding ".mat" data files are stored within *data/apxC/ADCP* and named similarly to the raw data files (though one raw “.SigVM” datafile sometimes produces multiple “.mat” files. These raw MATLAB datafiles contain the structured variables * *A.Echo1_500kHz.amplitudeRaw_dB*: echosounder amplitude (db; rows indicate 1 m depth intervals; columns indicate timestamps) * *A.Echo1_500kHz.binDepth_m*: echosounder depth (m) * *A.Sup.day*: timestamp (day of the month) * *A.Sup.hour*: timestamp (hour of the day) * *A.Sup.minute*: timestamp (minute of the hour) * *A.Sup.month*: timestamp (month of the year) * *A.Sup.second*: timestamp (second of the minute) * *A.Sup.year*: timestamp (year) * *A.Nav.lat_deg*: latitude (ºN) * *A.Nav.long_deg* longitude (ºE) * *A.Wat.backscatter*: return amplitude (db; first dimension indicates 1 m depth intervals; second dimension indicates timestamps; third dimension indicates individual ADCP beams) * *A.Wat.binDepth*: depth (m; rows indicate 1 m depth intervals; columns indicate timestamps) * *A.Wat.correlation*: return correlation (%; first dimension indicates 1 m depth intervals; second dimension indicates timestamps; third dimension indicates individual ADCP beams) * *A.Wat.vEast*: eastward velocity (cm s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *A.Wat.vNorth*: northward velocity (cm s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *A.Wat.vVert*: vertical velocity (cm s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *A.Wat.vMag*: horizontal speed (cm s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps)   The processed datafiles (also within *data/apxC/ADCP*) contain all of the processed velocity data from an entire data group (e.g., *A24_01_processed, A24_02_processed*, etc.), which each contain data structures corresponding to the individual transects/stations (e.g., *A24_01_T01*, *A24_01_T01*, etc.), which in turn contain the variables * *amp*: return amplitude (db; first dimension indicates 1 m depth intervals; second dimension indicates timestamps; third dimension indicates individual ADCP beams) * *amp_mean*: return amplitude, averaged across the beams (db; rows indicate 1 m depth intervals; columns indicate timestamps) * *cor*: return correlation (%; first dimension indicates 1 m depth intervals; second dimension indicates timestamps; third dimension indicates individual ADCP beams) * *cor_mean*: return correlation averaged across the beams (%; rows indicate 1 m depth intervals; columns indicate timestamps) * *d*: depth (ft bsl) * *date*: timestamp (fractional days since 00:00 1 January 0000) * *E_raw*: raw eastward velocity before processing (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *lat*: latitude (ºN) * *lon*: longitude (ºE) * *N_raw*: raw northward velocity before processing (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed*: fully processed three-dimensional speed (ft s<sup>-1</sup>) * *speed_4*: three-dimensional speed after processing Step 4 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed_5*: three-dimensional speed after processing Step 5 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed_6*: three-dimensional speed after processing Step 6 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed_8*: three-dimensional speed after processing Step 8 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed_9*: three-dimensional speed after processing Step 9 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed_10*: three-dimensional speed after processing Step 10 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *speed_raw*: raw three-dimensional speed before processing (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *t*: time elapsed (s) * *u*: fully processed along-TCD velocity (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_4*: along-TCD velocity after processing Step 4 (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_5*: along-TCD velocity after processing Step 5 (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_6*: along-TCD velocity after processing Step 6 (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_8*: along-TCD velocity after processing Step 8 (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_9*: along-TCD velocity after processing Step 9 (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_10*: along-TCD velocity after processing Step 10 (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *u_raw*: raw along-TCD velocity before processing (ft s<sup>-1</sup>; positive to the southeast; rows indicate 1 m depth intervals; columns indicate timestamps) * *U_raw*: raw upward velocity before processing (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v*: fully processed into-TCD velocity (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_4*: into-TCD velocity after processing Step 4 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_5*: into-TCD velocity after processing Step 5 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_6*: into-TCD velocity after processing Step 6 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_8*: into-TCD velocity after processing Step 8 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_9*: into-TCD velocity after processing Step 9 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_10*: into-TCD velocity after processing Step 10 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *v_raw*: raw into-TCD velocity before processing (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *x*: distance along the TCD (ft; positive to the southeast) * *y*: distance away from the TCD (ft; positive to the northeast) * *w*: fully-processed upward velocity (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_4*: upward velocity after processing Step 4 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_5*: upward velocity after processing Step 5 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_6*: upward velocity after processing Step 6 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_8*: upward velocity after processing Step 8 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_9*: upward velocity after processing Step 9 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_10*: upward velocity after processing Step 10 (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *w_raw*: raw upward velocity before processing (ft s<sup>-1</sup>; rows indicate 1 m depth intervals; columns indicate timestamps) * *z*: elevation (ft asl)   The folder *data/apxC/CTD* contains ship-based CTD profiles data collected by Sea-Bird Scientific and RBR Global CTDs. Raw data is stored in the folder *data/apxC/CTD/raw*, where Sea-Bird data files are stored as native “.xml” files and RBR data files are stored as native “.rsk” data files (to be opened within Sea-Bird Seasoft software and RBR Ruskin software, respectively). These raw data files are named according to the month and year of data collection, along with the data group and profile number. For example, the first CTD profile of data Group 2 collected in August of 2024 is named *A24_02_CTD01.rsk*. The corresponding MATLAB datafiles (converted using the aforementioned instrument software) are also found within *data/apxC/CTD* and are named accordingly. The Sea-Bird data (November 2021) contain variables * *zm*: elevation (ft asl) * *TdegC*: temperature (ºC) * *TurbFTU*: turbidity (FTU) while the RBR data (2024) contain variables * *Depth*: elevation (ft asl) * *Temperature*: temperature (ºC) * *Turbidity*: turbidity (FTU) The dates and locations of these CTD profiles are stored in *CTD_metadata.xlsx* within *data/apxC/CTD*. In July 2021, temperature data were derived from LADCP data (raw data are stored in *data/apxC/ADCP/LADCP*). The temperature data are then again stored in *data/apxC/CTD* (e.g., *J21_03_LADCP.mat*, *J21_04_LADCP.mat*) with variables * *p*: pressure (dbar) * *T*: temperature (ºC) Data files *lowrates_2021.mat* and *flowrates_2024.mat* contain data corresponding to flow through the Shasta Dam as downloaded from the California Data Exchange Center ([https://cdec.waterca.gov](https://cdec.waterca.gov)), with variables: * *date*: timestamp (MATLAB datenum format, or fractional days since 00:00 1 January 0000) * *elevation*: lake surface elevation (ft asl) * *flow*: flowrate through the Shasta Dam (cfs)   Finally, the data file *multibeam.mat* contains lake bathymetry data collected via multibeam sonar onboard the RV *Frantz* (collected in 2019), producing the variables * *bathy_lat*: latitude (ºN) * *bathy_lon*: longitude (ºE) * *bathy_x*: distance along the Lake Shasta Dam Temperature Control Device, or TCD (ft; positive to the southeast) * *bathy_y*: distance away from the TCD (ft; positive to the northeast) * *bathy_z*: elevation (ft asl)   ### ***ch1*** In Chapter 1, scripts *fig1_1.m* and *fig1_2b.m* reproduce the figures found throughout the chapter. Images (“.png” files) produced by these scripts are found in the folder *ch1/pngs*.   ### *ch3* In Chapter 2, raw ship-based CTD and LADCP data was processed using the *process_ship.m* script, which combines all of the raw ship data files into the *ship.mat* datafile for this chapter. MR data was processed using the *process_MR.m* script, which processes all of the MR data files in order, resulting in the *MR.mat* datafile. Finally, glider data was processed with *process_glider.m*, which combines data from the two glider missions into a single *glider.mat* data file for this chapter. Scripts *fig2_1.m* through *fig2_13.m* reproduce the figures found throughout the chapter. Images (“.png” files) produced by these scripts are found in the folder *ch2/pngs*.   ### *ch3 and ch4* In Chapter 3 and Chapter 4, VMP data was processed using the *process_VMP.m* script, which only processes one raw VMP datafile at a time and thus requires multiple runs with manual user edits (change input filename on line 6) between each run. Ship-based CTD and LADCP data was processed using another *process_ship.m* script, which combines all of the raw ship data files into the *ship.mat* datafile for these chapters. Ship-based data was reprocessed to match the format of Jenkins et al. (2018) data with the *process_2022_for_Jenkins.m* script, the outputs of which are saved as *Dotson2022.mat*. The *process_Jenkins_data.m* script then calculates meltwater transport for each study year (variables *data_2000*, *data_2007*, *data_2009*, etc.) which are together saved as *all_data.mat*. Glider data was processed using another *process_glider.m* script, which produces the *glider.mat* datafile for this chapter. Finally, ship- and glider-based turbulence model results were produced with the *process_ship_model.m* and *process_glider_model.m* scripts, respectively. Scripts *fig3_1.m* through *fig3_15.m* reproduce the figures found throughout Chapter 3. Images (“.png” files) produced by these scripts are found in the folder *ch3/pngs*. Scripts *fig4_1.m* through *fig4_19.m* reproduce the figures found throughout Chapter 4. Images (“.png” files) produced by these scripts are found in the folder *ch4/pngs*.    ### ***apxC*** In Appendix C, VM-ADCP data were processed using *process_transect.m*. This script also only processes one data transect or data station at a time, and for each transect/station, requires multiple iterations with manual user edits each time. A first iteration requires the filename to be chosen (line 8). The indices of bad data (line 10), indices of Head Tower interference (line 12), and cutoff depth (line 16) should start as empty arrays. The padding for dam interference should start as 0. After a first run, the output figure is examined and bad indices (line 10) are chosen from identifying major outliers within the velocity data (*u*, *v*, *w*, and *speed* subplot columns). Head Tower interference indices (line 12) are chosen from examining the amplitude and correlation subplots. A buffer for dam interference (line 14) is chosen if high velocities near the dam are still visible along the deepest velocity data after Step 6 (and carried through remaining steps). A depth cutoff (line 16) is chosen to remove the high velocity spikes at the bottom of the average velocity profile (far right subplot column). If any of these lines (10, 12, 14, 16) were changed, the script is rerun before the output (variable *ADCP*) can be saved (e.g., as *A24_01_T01.mat*, *A24_01_T02.mat*, etc.). The manually chosen bad indices, tower indices, depth buffer, and max depths are listed in *CTD_metadata.xlsx* within *data/apxC/ADCP*. All processed data from a single data group were saved together (e.g., as *A24_01_processed.mat*). Scripts *figC_1.m* through *figC_18.m* reproduce the figures found throughout Appendix C. Images (“.png” files) produced by these scripts are found in the folder *apxC/pngs*.   ### ***other\_functions*** The *other_functions* folder is required to be active on your path while running the scripts in the chapters and appendix folders. It contains a number of functions and packages indirectly necessary for processing the data and creating the figures: * *bin_via_p.m*: bin data by depth * *get_concentration.m*: water mass concentrations from CTD data * *rotate_velocity.m*: rotate the coordinates system of ADCP data from east-north units to along transect-across transect units * *AMT*: making Antarctic-specific maps (Greene et al., 2017) * *CircularMean*: mean and standard deviation of circular data (Long, 2024) * *cmocean*: oceanography-themed colormaps to improve data visualization (Thyng et al., 2016) * *getContourLineCoordinates*: extract coordinates from contour lines created by contour plots (Danz, 2024) * *gps2DistanceBearing*: distance and bearing between latitudes and longitudes (Huang, 2024) * *gsw*: oceanographic parameters from traditional CTD measurements (McDougall and Barker, 2011) * *Jenkins2018*: meltwater transport from historical CTD/LADCP transects (Jenkins et al., 2018) * *linexline*: intersection point of two lines (Serge, 2024) * *lldistkm*: distances between latitudes and longitudes (Sohrabinia, 2024) * *m_map*: creating maps within MATLAB (Pawlowicz, 2020) * *MIT_seawater*: oceanographic parameters from traditional CTD measurements, (Sharqawy et al., 2010; Nayar et al., 2016) * *odas*: processing raw turbulence microstructure data (Douglas et al., 2018) * *othercolor*: colormaps to improve data visualization (Atkins, 2024) * *parseLandSat8MetaData*: load Landsat 8 images (Abouali, 2024) * *piccolroaz*: quality dissipation estimates from turbulence microstructure data (Piccolroaz et al., 2021) * *slanCM*: colormaps to improve data (Liu, 2024) * *TMD*: implement a tide model for the Antarctic coastline (Erofeeva et al., 2020) * *unixtime2mat*: convert unix time stamps to MATLAB serial date number (Schmidt, 2024) * *windrose*: produce graphical representations of wind data (Pereira, 2024)   ## **Citations** * Abouali, M. (2024). *parseLandSat8MetaData(filename)* [https://www.mathworks.com/matlabcentral/fileexchange/48614-parselandsat8metadata-filename](https://www.mathworks.com/matlabcentral/fileexchange/48614-parselandsat8metadata-filename) (accessed 22 November 2024) * Atkins, J. (2024). *othercolor*. [https://www.mathworks.com/matlabcentral/fileexchange/30564-othercolor](https://www.mathworks.com/matlabcentral/fileexchange/30564-othercolor) (accessed November 20 2024) * Cavalieri, D. J., Parkinson, C. L., Gloersen, P., and Zwally, H. J. (1996). Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1. *NASA Snow and Ice Data Center Distributed Active Archive Center*. [https://doi.org/10.5067/8GQ8LZQVL0VL](https://doi.org/10.5067/8GQ8LZQVL0VL) (accessed 26 October 2023) * Danz, A. (2024). *getContourLineCoordinates*. [https://www.mathworks.com/matlabcentral/fileexchange/74010-getcontourlinecoordinates](https://www.mathworks.com/matlabcentral/fileexchange/74010-getcontourlinecoordinates) (accessed 21 November 2024) * Douglas, W., Lueck, R., McMillan, J. (2018). *ODAS MATLAB Library, Version 4.3*. Victoria, BC, Canada. Rockland Scientific International Inc. [https://rocklandscientific.com/support/tools/software-versions/](https://rocklandscientific.com/support/tools/software-versions/) (accessed 20 November 2024) * Dow, C. F., Lee, W. S., Greenbaum, J. S., Greene, C. A., Blankenship, D. D., Poinar, K., Forrest, A. L., Young, D. A., and Zappa, C. J. (2018). Basal channels drive active surface hydrology and transverse ice shelf fracture. *Science Advances*, *4*(6), eaao7212. [https://doi.org/10.1126/sciadv.aao7212](https://doi.org/10.1126/sciadv.aao7212) * Erofeeva, S., Padman, L., and Howard, S. L. (2020). *Tide Model Driver (TMD) version 2.5*. [https://www.github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5](https://www.github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5) (accessed 20 November 2024) * Giddy, I. S., Fer, I., Swart, S., and Nicholson, S. A. (2023). Vertical convergence of turbulent and double-diffusive heat flux drives warming and erosion of Antarctic Winter Water in summer. *Journal of Physical Oceanography*, *53*(8), 1941-1958. [https://doi.org/10.1175/JPO-D-22-0259.1](https://doi.org/10.1175/JPO-D-22-0259.1) * Greene, C. A., Gwyther, D. W., and Blankenship, D. D. (2017), Antarctic Mapping Tools for MATLAB. *Computers & Geosciences*, *104*, 151-157. [https://doi.org/10.1016/j.cageo.2016.08.003](https://doi.org/10.1016/j.cageo.2016.08.003). [https://www.mathworks.com/matlabcentral/fileexchange/47638-antarctic-mapping-tools](https://www.mathworks.com/matlabcentral/fileexchange/47638-antarctic-mapping-tools) (accessed 19 November 2024) * Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J, Peubey, C., Radu, R., Rozum., I., Schepers, D., Simmons, A., Soci, C., and Thépaut, J. N. (2023) ERA 5 hourly data on single levels from 1940 to present. *Copernicus Climate Change Service (C3S) Climate Data Store*. [https://doi.org/10.24381/cds.adbb2d47](https://doi.org/10.24381/cds.adbb2d47) (Accessed on 21 November 2024) * Huang, Z. (2024). *gps2DistanceBearing*. [https://www.mathworks.com/matlabcentral/fileexchange/106770-gps2distancebearing](https://www.mathworks.com/matlabcentral/fileexchange/106770-gps2distancebearing) (accessed 20 November 2024). * Jenkins, A., Shoosmith, D., Dutrieux, P., Jacobs, S., Kim, T. W., Lee, S. H., Ha, H. K., and Stammerjohn, S. (2018). West Antarctic Ice Sheet retreat in the Amundsen Sea driven by decadal oceanic variability. *Nature Geoscience*, *11*(10), 733-738. [https://doi.org/10.1038/s41561-018-0207-4](https://doi.org/10.1038/s41561-018-0207-4) * Liu, Z. (2024). *200 colormap*. [https://www.mathworks.com/matlabcentral/fileexchange/120088-200-colormap](https://www.mathworks.com/matlabcentral/fileexchange/120088-200-colormap) (accessed 21 November 2024) * Long, D. (2024). *True Circular Mean.* [https://www.mathworks.com/matlabcentral/fileexchange/132118-true-circular-mean](https://www.mathworks.com/matlabcentral/fileexchange/132118-true-circular-mean) (accessed 24 November 2024) * McDougall, T. J., Thorpe, S. A., and Gibson, C. H. (1988). Small-scale turbulence and mixing in the ocean: A glossary. *Small-Scale Turbulence and Mixing in the Ocean*, *3*(9). [https://doi.org/10.1016/S0422-9894(08)70533-6](https://doi.org/10.1016/S0422-9894\(08\)70533-6) * Nayar, K. G., Sharqawy, M. H., Banchik, L. D. and Lienhard V, J. H. (2016). Thermophysical properties of seawater: A review and new correlations that include pressure dependence. *Desalination*, *390*, 1-24. [https://doi.org/10.1016/j.desal.2016.02.024](https://doi.org/10.1016/j.desal.2016.02.024) * Osborn, T. R. (1980). Estimates of the Local Rate of V ertical Diffusion from Dissipation Measurements. *Journal of Physical Oceanography*, *10*(1), 83-89. [https://doi.org/10.1175/1520-0485(1980)010&lt;0083:EOTLRO&gt;2.0.CO;2](https://doi.org/10.1175/1520-0485\(1980\)010%3c0083:EOTLRO%3e2.0.CO;2) * Osborn, T. R., and Cox, C. S. (1972). Oceanic fine structure. *Geophysical Fluid Dynamics*, *3*(4), 321-345. [https://doi.org/10.1080/03091927208236085](https://doi.org/10.1080/03091927208236085) * Pawlowicz, R. (2020). *M_Map: A mapping package for MATLAB, version 1.4. [www.eoas.ubc.ca/~rich/map.html](http://www.eoas.ubc.ca/~rich/map.html) (accessed 19 November 2024). * Pereira, D. (2024). *Wind Rose*. [https://www.mathworks.com/matlabcentral/fileexchange/47248-wind-rose](https://www.mathworks.com/matlabcentral/fileexchange/47248-wind-rose) (accessed 20 November 2024) * Piccolroaz, S., Fernández-Castro, B., Toffolon, M., and Dijkstra, H. A. (2021). A multi-site, year-round turbulence microstructure atlas for the deep perialpine Lake Garda. *Scientific data*, *8*(1), 188. [https://doi.org/10.1038/s41597-021-00965-0](https://doi.org/10.1038/s41597-021-00965-0) * Schmidt, V. (2024). *Covert Unix Time (seconds since Jan 1 1970) to MATLAB Serial Time*. [https://www.mathworks.com/matlabcentral/fileexchange/24024-convert-unix-time-seconds-since-jan-1-1970-to-matlab-serial-time](https://www.mathworks.com/matlabcentral/fileexchange/24024-convert-unix-time-seconds-since-jan-1-1970-to-matlab-serial-time) (accessed 23 November 2024) * Serge (2024). *Line-Line Intersection (N lines, D space)*. [https://www.mathworks.com/matlabcentral/fileexchange/59805-line-line-intersection-n-lines-d-space](https://www.mathworks.com/matlabcentral/fileexchange/59805-line-line-intersection-n-lines-d-space) (accessed 20 November 2024) * Sharqawy, M. H., Lienhard, J. H. and Zubair, S. M. (2010). Thermophysical properties of seawater: a review of existing correlations and data. *Desalination and Water Treatment*, *16*(1-3) 354-380. [https://doi.org/10.5004/dwt.2010.1079](https://doi.org/10.5004/dwt.2010.1079) * Sohrabinia, M. (2024). *LatLon distance*. [https://www.mathworks.com/matlabcentral/fileexchange/38812-latlon-distance](https://www.mathworks.com/matlabcentral/fileexchange/38812-latlon-distance) (accessed 20 November 2024). * Thyng, K. M., Greene, C. A., Hetland, R. D., Zimmerle, H. M., and DiMarco, S. F. (2016). True Colors of Oceanography: Guidelines for Effective and Accurate Colormap Selection. *Oceanography*, *29*(3), 10. [http://dx.doi.org/10.5670/oceanog.2016.66](http://dx.doi.org/10.5670/oceanog.2016.66)