Causes of Dome Seeing

Remote Analysis Activities

(numbering system continued from last year's Exercise 6)

Exercise 6a - Plot DIMM seeing measurements versus wind velocity

Make a plot of DIMM seeing measurements plotted against the wind velocity.

Two challenges:
  • the DIMM seeing and the wind data are recorded in two different telemetry streams, it is necessary to correlate the two measurements in time. DIMM measurements are not continuous (can be interupted by clouds or the slewing of the telescope), but can be reported every 5 seconds. Wind measurements are continuous and are reported once a second.
  • It may necessary to time-filter (average) the data over both short (36 sec, to reduce short-term jitter in the measurements) and long timescales (a years worth of data) to find the interesting signal. It may also be necessary to do some averaging to manage the data volume as there can be 6000 DIMM measurements per night.

Existing Tools:
  • Make plot of DIMM seeing vs time with /lbt/lbto/supportscripts/TelemetrySupport/dimmplot_hdfextract.py
  • Extract telemetry of DIMM seeing vs time without making plot /lbt/lbto/supportscripts/TelemetrySupport/dimmplot_hdfextract.py -n
  • Make plot of Wind velocity and direction vs time with /lbt/lbto/supportscripts/TelemetrySupport/windplot_hdfextract.py
  • awk 'BEGIN { FS = "," } { total += $4 } END { print total/NR }' /tmp/dimm.20210621jfind40839.tmp (calculates average of column 4 which is seeing_zenith in DIMM CSV file)

;How to convert telemetry time in MJD microseconds to UT hours:
; This is IDL code, so xdata is an array of values.
   xdata = data.field1[0,*] / 1000000.0d ; convert MJD microseconds to MJD seconds
   xdata = xdata / 86400.0 ; convert MJD second to MJD days (floating point(
   today = long(xdata[jj-1]) ; MJD days (last line in file) truncate to integer day of today
; 01-JAN-2009 is 54832 MJD
; 01-JUN-2009 is 54983 MJD
; 01-JUL-2009 is 55013 MJD
  xdata = xdata - today ; subtract integer day to get time of each entry in fractional day
  xdata = xdata * 24.0 ; convert fractional day to UT Hours

Header of CSV telemetry file for wind: cat /tmp/wind.20210628jfind40839.tmp
time_stamp, tai_offset, alive, alive_time, alive_temperature, alive_pressure, alive_humidity, alive_wind, timestamp, temperature, dewpoint, humidity, pressure, windspeed, winddirection, raw_winddirection, rain, alive_front, windspeed_front, winddirection_front, raw_winddirection_front, sky_quality_monitor_alive, sky_brightness_timestamp, sky_brightness
5131573164168270,37000000,1,1,1,1,1,1,1624856364,10.6999998,1.29999995,52.2000008,692.799988,8.19999981,99.6498413,250,0,1,1.20000005,89.6498413,240,1,1624856356,22.0200005
5131573165172804,37000000,1,1,1,1,1,1,1624856365,10.6999998,1.29999995,52.2000008,692.799988,9.89999962,102.649841,253,0,1,1.70000005,73.6498413,224,1,1624856356,22.0200005
5131573166208448,37000000,1,1,1,1,1,1,1624856366,10.6999998,1.29999995,52.2000008,692.799988,6.0999999,115.649841,266,0,1,3.5999999,75.6498413,226,1,1624856366,22.0200005
5131573167212537,37000000,1,1,1,1,1,1,1624856367,10.6999998,1.29999995,52.2000008,692.799988,8.10000038,94.6498413,245,0,1,4.5,83.6498413,234,1,1624856366,22.0200005
5131573168216823,37000000,1,1,1,1,1,1,1624856368,10.6999998,1.29999995,52.2000008,692.799988,6.5999999,101.649841,252,0,1,5.5,112.649841,263,1,1624856366,22.0200005
5131573169221484,37000000,1,1,1,1,1,1,1624856369,10.6999998,1.29999995,52.2000008,692.799988,8.60000038,92.6498413,243,0,1,4.5999999,117.649841,268,1,1624856366,22.0200005
5131573170226331,37000000,1,1,1,1,1,1,1624856370,10.6999998,1.29999995,52.2000008,692.799988,8.39999962,104.649841,255,0,1,4.80000019,85.6498413,236,1,1624856366,22.0200005

Header of CSV telemetry for DIMM: head /tmp/dimm.20210621jfind40839.tmp
time_stamp, tai_offset, seeing, seeing_zenith, r0, dimm_elevation, dimm_azimuth, star_magnitude, seeing_lbt, samples, mean_flux, para, perp, sigma_d_para, sigma_d_perp
5130962345000000,37000000,1.21131825,1.18881059,9.17816067,75.7483139,161.379868,0.00100000005,1.60391724,300,30.9953671,1.19962835,1.22300828,1.8103954379547893,1.5847944415031656
5130962350000000,37000000,1.20319653,1.18085611,9.24011421,75.7535095,161.451401,0.00100000005,1.59293997,300,30.7912979,1.16290903,1.24348414,1.7640977449035078,1.6068746033221666
5130962355000000,37000000,1.2114563,1.18897879,9.17711449,75.758667,161.522842,0.00100000005,1.60342646,300,30.5135155,1.1530838,1.26982868,1.751668443116011,1.6351944677410148
5130962360000000,37000000,1.19258022,1.17046821,9.32236958,75.763588,161.59079,0.00100000005,1.57811475,300,30.8672256,1.17585218,1.20930827,1.7804446219614263,1.5699866279996455
5130962365000000,37000000,1.17840481,1.15657604,9.43451118,75.7702026,161.683411,0.00100000005,1.55903947,300,30.6566792,1.17267442,1.1841352,1.7764339768296851,1.54270492472332
5130962370000000,37000000,1.17205644,1.15036654,9.48561192,75.7771759,161.771072,0.00100000005,1.55030715,300,30.6613121,1.1910373,1.1530757,1.7995847784128758,1.5089098685916873
5130962375000000,37000000,1.17888641,1.15708625,9.43065643,75.7824478,161.845139,0.00100000005,1.55899644,300,30.5903912,1.22226369,1.13550901,1.838817411163024,1.4897289394708537
5130962380000000,37000000,1.19482565,1.17274642,9.30484962,75.787468,161.916016,0.00100000005,1.57973981,300,30.5140915,1.26391912,1.12573206,1.8908942668130715,1.4790322336757429
5130962385000000,37000000,1.20185995,1.1796658,9.25039005,75.7922897,161.984894,0.00100000005,1.58858824,300,30.1392651,1.29828787,1.10543215,1.9336462210673342,1.4567728932340074

Technique:

  • Extract DIMM telemetry data to get DIMM measurements of seeing as a function of time.
  • For each DIMM data point, extract Wind data for the previous 6 sec (6 sec is a convenient time to average the wind, and also approximately the DIMM sampling time)
  • Average the wind data over this 6 sec interval.
  • Save the values for Time, DIMM seeing_zenith, wind velocity, wind direction, wind aspect in another file.
  • John and James made a script called dimm_wind.py to do this on 20210707.
  • Use the file to generate the plot of DIMM seeing vs Wind Velocity.

Exercise 6b - Plot DIMM seeing measurements versus wind direction

Make a plot of DIMM seeing measurements plotted against the wind direction (wind azimuth = direction wind is coming from, 0 = North).

Exercise 6c - Plot DIMM seeing measurements versus wind aspect

Make a plot of DIMM seeing measurements plotted against the wind aspect (direction wind is coming from relative to where telescope is pointing, 0 = face on).

James Findikyan report

James Findikyan's Summer 2021 research ended here. See the link below for his report covering his Summer 2020 and Summer 2021 research.

  • jfindikyan 2022.pdf: Analysis of Trends in Large Binocular Telescope Dome Seeing (11/09/2021)

Exercise 7a - Plot DIMM seeing measurements versus telescope temperature differences

Make a plot of DIMM seeing measurements plotted against the difference between telescope steel temperature (middle windbrace steel) and ambient air temperature (right extension air).

Exercise 7b - Plot DIMM seeing measurements versus telescope temperature differences

Make a plot of DIMM seeing measurements plotted against the difference between telescope steel temperature (lower C-ring steel) and ambient air temperature (right extension air).

Mountain Activities (28-29 June 2021)

  • DONE Learn about the DIMM
  • DONE Learn about the Telescope
  • DONE Learn about nighttime observing
  • Operate the DIMM during the Night
  • Collect some raw DIMM data
  • DONE Assist John in cleaning the DIMM optics

-- JohnHill - 28 May 2021

I Attachment Action Size Date Who Comment
jfindikyan 2022.pdfpdf jfindikyan 2022.pdf manage 908 K 17 Nov 2021 - 17:54 JohnHill James Findikyan paper based on Summer 2020 and Summer 2021 research
Topic revision: r6 - 17 Nov 2021, JohnHill
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