Bute Inlet Wirewalker Deployment

Last updated: 2026-09-21 15:11:57 PDT

Current maestro number: 209761

Summary

date	Number of Upcasts	Mean Ascent Rate (m/s)	Mean Cast Length (s)	Depth Profile
2026-09-21	1.00	0.00	9,587.88
2026-09-20	1.00	0.01	25,303.12
2026-09-19	0.00	NA	NA
2026-09-18	1.00	0.06	3,586.75

Profiling Diagnostics

Depth Profiles

sectionArray = transpose(section_data)

// Render one variable as a time-depth section. Each profile is a column of
// 1-m-binned squares coloured by value; sparse profiles read as gaps.
function sectionPlot(variable, label) {
  const data = sectionArray.filter(
    d => Number.isFinite(d[variable]) && Number.isFinite(d.depth_bin)
  )
  return Plot.plot({
    width: 1200,
    height: 500,
    style: {fontSize: "15px"},
    marginLeft: 60,
    marginBottom: 45,
    marginRight: 20,
    y: {reverse: true, label: "Depth (m)", domain: globalDomain.pressure_dbar},
    x: {label: "Time (PST)", type: "time", tickFormat: "%b %d"},
    color: {scheme: "turbo", legend: true, label: label, domain: d3.extent(data, d => d[variable])},
    marks: [
      Plot.dot(data, {
        x: d => new Date(d.profile_ms),
        y: "depth_bin",
        fill: variable,
        symbol: "square",
        r: 5
      }),
      Plot.tip(data, Plot.pointer({
        x: d => new Date(d.profile_ms),
        y: "depth_bin",
        channels: {
          Time: d => new Date(d.profile_ms).toLocaleString("en-US", {timeZone: pst_tz}),
          Depth: d => d.depth_bin.toFixed(1) + " m",
          [label]: d => d[variable].toFixed(2)
        },
        format: {x: false, y: false, fill: false}
      }))
    ]
  })
}

colorVariables = new Map([
  ["None", "none"],
  ["Temperature (C)", "temperature_c"],
  ["Conductivity (mS/cm)", "conductivity_m_s_cm"],
  ["Dissolved O2 (mL/L)", "dissolved_o2"],
  ["Backscatter (counts)", "backscatter_counts"],
  ["Chlorophyll (counts)", "chlorophyll_counts"],
  ["CDOM (counts)", "cdom_counts"]
])
viewof selectedDate = Inputs.select(dates, {label: "Select date", value: dates.at(-1)})
viewof selectedVariable = Inputs.select(colorVariables, {label: "Colour by"})

rawArray = transpose(raw_data)
castsArray = transpose(casts_data)
windArray = transpose(wind_data)

filteredRaw = rawArray.filter(d => d.date_str === selectedDate)
filteredCasts = castsArray.filter(d => d.date_str === selectedDate)
filteredWind = windArray.filter(d => d.date_str === selectedDate)

globalDomain = ({
  temperature_c: d3.extent(rawArray, d => d.temperature_c),
  conductivity_m_s_cm: d3.extent(rawArray, d => d.conductivity_m_s_cm),
  dissolved_o2: d3.extent(rawArray, d => d.dissolved_o2),
  backscatter_counts: d3.extent(rawArray, d => d.backscatter_counts),
  chlorophyll_counts: d3.extent(rawArray, d => d.chlorophyll_counts),
  cdom_counts: d3.extent(rawArray, d => d.cdom_counts),
  pressure_dbar: d3.extent(rawArray, d => d.pressure_dbar),
  wind_spd: [0, d3.max(windArray, d => d.WindSpd_Max)]
})

pstFormat = d => d.toLocaleTimeString("en-US", {timeZone: pst_tz, hour: "2-digit", minute: "2-digit"})

dayStart = new Date(new Date(selectedDate + "T00:00:00-08:00") - 60 * 60 * 1000)
dayEnd = new Date(selectedDate + "T23:59:59-08:00")

variableLabels = new Map([
  ["temperature_c", "Temperature (C)"],
  ["conductivity_m_s_cm", "Conductivity (mS/cm)"],
  ["dissolved_o2", "Dissolved O2 (mL/L)"],
  ["backscatter_counts", "Backscatter (counts)"],
  ["chlorophyll_counts", "Chlorophyll (counts)"],
  ["cdom_counts", "CDOM (counts)"]
])

Plot.plot({
    width: 1200,
    height: 200,
    style: {fontSize: "15px"},
    marginLeft: 60,
    marginBottom: 5,
    y: {label: "Wind Speed (m/s)", domain: globalDomain.wind_spd},
    x: {label: null, type: "time", tickFormat: pstFormat, domain: [dayStart, dayEnd], ticks: d3.timeHour.every(2), axis: null},
    marks: [
        Plot.ruleY([0]),
        Plot.areaY(filteredWind, {
            x: d => new Date(d.time_ms),
            y: "WindSpd_Max",
            fill: "#dce6f1",
            curve: "step"
        }),
        Plot.line(filteredWind, {
            x: d => new Date(d.time_ms),
            y: "WindSpd_Avg",
            stroke: "steelblue",
            strokeWidth: 2,
            curve: "step"
        }),
        Plot.dot(filteredWind, {
            x: d => new Date(d.time_ms),
            y: "WindSpd_Avg",
            fill: "steelblue",
            r: 3
        }),
        Plot.tip(filteredWind, Plot.pointer({
            x: d => new Date(d.time_ms),
            y: "WindSpd_Avg",
            channels: {
                "Avg": d => d.WindSpd_Avg + " m/s",
                "Max": d => d.WindSpd_Max + " m/s",
                "Min": d => d.WindSpd_Min + " m/s",
                "Direction": d => d.WindDir_Avg + "\u00B0"
            },
            format: {x: false, y: false}
        }))
    ]
})

Plot.plot({
    width: 1200,
    height: 500,
    style: {fontSize: "15px"},
    marginLeft: 60,
    marginBottom: 45,
    y: {reverse: true, label: "Pressure (dbar)", domain: globalDomain.pressure_dbar},
    x: {label: "Time (PST)", type: "time", tickFormat: pstFormat, domain: [dayStart, dayEnd], ticks: d3.timeHour.every(2)},
    ...(selectedVariable !== "none" ? {color: {scheme: "turbo", legend: true, label: variableLabels.get(selectedVariable), marginLeft: 20, domain: globalDomain[selectedVariable]}} : {}),
    marks: [
        Plot.line(filteredRaw, {
            x: d => new Date(d.datetime_ms),
            y: "pressure_dbar",
            stroke: selectedVariable === "none" ? "black" : "#ccc"
        }),
        Plot.dot(filteredRaw, {
            x: d => new Date(d.datetime_ms),
            y: "pressure_dbar",
            fill: selectedVariable !== "none" ? selectedVariable : "black",
            r: 1.5
        }),
        Plot.tip(filteredRaw, Plot.pointer({
            x: d => new Date(d.datetime_ms),
            y: "pressure_dbar",
            channels: {
                Time: "time_label",
                Pressure: "pressure_label",
                Temperature: "temp_label",
                Conductivity: "cond_label",
                "Dissolved O2": "do_label",
                "Backscatter": "backscatter_label",
                "Chlorophyll": "chlorophyll_label",
                "CDOM": "cdom_label"
            },
            format: {x: false, y: false}
        }))
    ]
})

Section

sectionVariables = new Map([
  ["Temperature (C)", "temperature_c"],
  ["Conductivity (mS/cm)", "conductivity_m_s_cm"],
  ["Dissolved O2 (mL/L)", "dissolved_o2"],
  ["Backscatter (counts)", "backscatter_counts"],
  ["Chlorophyll (counts)", "chlorophyll_counts"],
  ["CDOM (counts)", "cdom_counts"]
])
viewof sectionVariable = Inputs.select(sectionVariables, {label: "Variable"})

sectionPlot(sectionVariable, variableLabels.get(sectionVariable))

Wind vs Pressure Range

hourlyArray = transpose(hourly_data)

Plot.plot({
    width: 800,
    height: 500,
    style: {fontSize: "15px"},
    marginLeft: 60,
    marginBottom: 50,
    x: {label: "Avg wind speed (m/s)"},
    y: {label: "Hourly pressure range (dbar)"},
    marks: [
        Plot.dot(hourlyArray, {
            x: "WindSpd_Avg",
            y: "pressure_range",
            fill: "black",
            r: 3
        }),
        Plot.tip(hourlyArray, Plot.pointer({
            x: "WindSpd_Avg",
            y: "pressure_range",
            channels: {
                "Hour": "hour_label",
                "Wind Avg": d => d.WindSpd_Avg + " m/s",
                "Wind Max": d => d.WindSpd_Max + " m/s",
                "Pressure Range": d => d.pressure_range.toFixed(2) + " dbar"
            },
            format: {x: false, y: false}
        }))
    ]
})

Wind vs Profiles (Second Moment)

windCastsArray = transpose(wind_casts_data)

Plot.plot({
    width: 600,
    height: 400,
    style: {fontSize: "15px"},
    marginLeft: 60,
    marginBottom: 50,
    x: {label: "Second moment of wind speed (m\u00B2/s\u00B2)"},
    y: {label: "Number of upcasts"},
    marks: [
        Plot.dot(windCastsArray, {
            x: "second_moment",
            y: "Number of Upcasts",
            fill: "black",
            r: 5
        }),
        Plot.text(windCastsArray, {
            x: "second_moment",
            y: "Number of Upcasts",
            text: "date_label",
            dy: -12,
            fontSize: 13
        })
    ]
})

Wind vs Profiles (Mean)

Plot.plot({
    width: 600,
    height: 400,
    style: {fontSize: "15px"},
    marginLeft: 60,
    marginBottom: 50,
    x: {label: "Mean wind speed (m/s)"},
    y: {label: "Number of upcasts"},
    marks: [
        Plot.dot(windCastsArray, {
            x: "mean_wind",
            y: "Number of Upcasts",
            fill: "black",
            r: 5
        }),
        Plot.text(windCastsArray, {
            x: "mean_wind",
            y: "Number of Upcasts",
            text: "date_label",
            dy: -12,
            fontSize: 13
        })
    ]
})

Distribution of Ascent Rates

Battery Diagnostics

Prediction

Raw Voltages

Percent Voltages

About

This report tracks a Wirewalker, a wave-powered profiling platform. Data are served from the Hakai Institute ERDDAP server. For questions about the data, contact data@hakai.org.