NGEE Kougarok M64 Notes

From IARC 207 Wiki
Jump to navigation Jump to search

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)

Processed through

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

Met Notes

  • Fall 2017: Muskox knock over precip bucket.
  • 10/16/2017 12:00 end of precip season for kougarok.
  • 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.

Radiation Notes

  • I have open questions about PRI index value but the data from the sensors themselves looks ok.
  • Snippet for trying to pin down when the muskox move the CNR4...
    • Need to compare albedo here to K2 Met...
    • ... albedo didn't show anything but incoming shortwave radiation shows a shift on 5/14 so I'm going to 6999 from there till June station visit.
    • 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.
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