NGEE Kougarok M64 Notes

NGEE

Site Visits

• 6/24/2017 (Bob and Lily Site Install)
• 8/19/2017 (Lily and ABOVE Team)
• 10/5/2017 (Bob and Lily Fall Visit)
• 4/3/2018 (Snow Team)
• 6/14/2018 (Bob and Nathan)
• 9/22/2018 (Bobs and CAS)
• 6/20/2021 (Bob and Misha)

Processed through

• AT/RH/Precip / WS / WD / BP through 4/3/2018
• Radiation through 4/3/2018
• VATP through 4/3/2018

Met Notes

2017

• Fall 2017: Muskox knock over precip bucket.
• 10/16/2017 12:00 end of precip season for kougarok.
• Barometric Pressure
  • 2017-10-17 18:00 to 2017-11-22 4:00. Rime ice
• AT/RH/ DP all good

2018

• 6/14/2018 Fixed precip bucket, noticed Musk ox twisted tower center mast at some point so Wind Direction and Radiation have been off for a TBD amount of time.
  • NAN through 6/15/2018 00:00 time step (the test tips)
• 9/22/2018 musk ox twisted center mast a bit again. WD off, Radiation still pretty closer to still on.
• Barometric Pressure
  • 2018-01-15 21:00 to 2018-02-05 20:00 Rime ice
  • 2018-04-29 15:00 to 2018-05-06 18:00 Rime ice ( I think or some other obstruction )
  • Need to compare with Nome / maybe RAWS site in interior? I think there is periodic icing in the fall and again into 2019 but that is in the era when the Teller Bottom logger had failed... oh maybe the Teller 47 site would be useful.
  • Using /var/site/uaf_sp/bin/2022-Jan-Quicklook Barometric Pressure.ipynb
• AT/RH/ DP all good
• Rain Season:
  • Starts on 6/15/18 01:00 after tipping bucket is repaired.
  • Ends 10/15/2018 8:00

2019

• Barometric Pressure
  • Need to compare to Nome.
• AT/RH/ DP all good
• Rain Season:
  • 5/12/19 21:00 Start
  • end unknown. Missing data due to corrupt memory card for first few months of data after final visit in September 2019

2020

• Barometric Pressure
  • Need to compare to Nome.
  • did correct as much as able though using Teller Bottom data.
• AT/RH/DP have a couple oddities crop up in January / February 2020 sensor noise.
  • Perhaps November / December but more subtle and I'm ignoring / don't think it's very significant.
• Rain Season:
  • 4/29/20 22:00 Start
  • 10/22/20 End

2021

• Barometric Pressure
  • all fixed through September 2021.
• AT/RH/DP have a couple oddities crop up in March 2021 sensor noise. Perhaps January / February, too but don't think it's significant.
• Rain Season:
  • 5/8/21 19:00 Start

Radiation Notes

2017

• I have open questions about PRI index value but the data from the sensors themselves looks ok.
• I reviewed photos from June 2017 station visit and October 2017 station visit. The radiation arm appears to have not moved over this interval.

2018

• I know we leveled the radiometer arm on the snow survey trip in early April but I can't remember if the cross arm had moved... I think it maybe had...?
  • I thought maybe Cathy/Bob visited the station and grabbed pictures a day or two before I was able to get up there.
• Declaring data bad 5/14/18 13:00 till station visit on 6/14/18 22:00
• second bump was gentle enough there is no obvious error in SW data from June till September visit even though the Musk Ox twisted 10 degrees or something the station.

Radiation Snippet

• ... for trying to pin down when the muskox move the CNR4...
• Need to compared albedo here to K2 Met... & incoming shortwave radiation
  • ... albedo didn't show anything but incoming shortwave radiation shows a shift on 5/14/18 13:00 so I'm going to 6999 from there till June station visit.

import numpy
import pandas
stryear="2018.csv"

sensor_k2 = "/var/site/uaf_sp/k-met/outputs/k2_met_albedo_" + stryear 
df_k2 = pandas.read_csv(sensor_k2, skiprows=3, index_col=0)
df_k2.index = pandas.to_datetime(df_k2.index)
df_k2 [df_k2>1]= numpy.NaN
df_k2 = df_k2.resample('24H').mean()

path="/var/site/uaf_sp/ngee_koug_met/outputs/years/albedo_Avg/albedo_Avg_" + stryear
df4 = pandas.read_csv(sensor4, skiprows=3, index_col=0)
df4.index = pandas.to_datetime(df4.index)
df4 [df4>100]= numpy.NaN
df4 = df4.resample('24H').mean()
df4.rename(columns = {'Avg' : 'Albedo'}, inplace=True)

outfile = "/var/site/uaf_sp/ngee_koug_met/outputs/koug_summary_albedo.csv"
dataset=pandas.concat([ df4, df_k2]  ,axis=1)
dataset.to_csv(outfile)

Soil Notes

• VATP looks good