NIM/ECOR/M1 - Missing data

Data are missing and unrecoverable.

• lon(lon)
• rotated covariance vt(cvar_rot_vt)
• 0=real or 1=dummy value of lv(real_lv)
• 0=real or 1=dummy value of rho(real_rho)
• variance of v(var_rot_v)
• h(h)
• momentum flux (dynamic)(k)
• rotated covariance vq(cvar_rot_vq)
• variance of w(var_rot_w)
• skewness of variable u(skew_u)
• number of q samples removed due to spikes(n_spk_q)
• variance of t(var_t)
• wT covariance(cvar_wt)
• covariance ut(cvar_ut)
• kurtosis of variable q(kurt_q)
• number of valid c samples(n_good_c)
• variance of variable w(var_w)
• skewness of variable t(skew_t)
• rotated covariance wq(cvar_rot_wq)
• kurtosis of variable v(kurt_v)
• number of w samples removed due to spikes(n_spk_w)
• latent heat of vaporization(lv)
• rotated covariance uq(cvar_rot_uq)
• kurtosis of variable u(kurt_u)
• kurtosis of variable t(kurt_t)
• skewness of variable v(skew_v)
• number of t samples removed due to spikes(n_spk_t)
• variance of variable u(var_u)
• rotated covariance uw(cvar_rot_uw)
• covariance of tq(cvar_tq)
• skewness of variable w(skew_w)
• Down-boom wind velocity (u)(mean_u)
• average atmospheric pressure (IGRA internal sensor)(atm_pres)
• number of bad or out of range c samples(n_bad_c)
• rotated covariance ut(cvar_rot_ut)
• kurtosis of variable w(kurt_w)
• number of v samples removed due to spikes(n_spk_v)
• rotated mean w(mean_rot_w)
• skewness of variable q(skew_q)
• Dummy altitude for Zeb(alt)
• rotated mean v(mean_rot_v)
• number of valid q samples(n_good_q)
• number of c samples removed due to spikes(n_spk_c)
• skewness of variable c(skew_c)
• number of u samples removed due to spikes(n_spk_u)
• 0=real or 1=dummy value of cp(real_cp)
• number of valid t samples(n_good_t)
• covariance vq(cvar_vq)
• CO2 flux(fc)
• number of samples with \IRGA hardware problem\ flag(n_bad_irga)
• latent heat flux(lv_e)
• condensation pressure(cp)
• rotated covariance vw(cvar_rot_vw)
• covariance wq(cvar_wq)
• uw covariance(cvar_uw)
• mean horizontal wind speed(mean_rot_u)
• Friction velocity(ustar)
• number of samples with IRGA optical path blocked flag(n_bad_irga_light)
• mean value of out of range values and spikes of c -9999 if no spikes(mean_spk_c)
• standard deviation of wind direction(std_wind_dir)
• variance of u(var_rot_u)
• vw covariance(cvar_vw)
• number of samples with bad sonic status flag(n_bad_son_ic)
• covariance of tc(cvar_tc)
• mean value of out of range values and spikes of t -9999 if no spikes(mean_spk_t)
• number of bad or out of range w samples(n_bad_w)
• rotated covariance wt(cvar_rot_wt)
• mean value of \spike\ u samples(mean_spk_u)
• mean value of \spike\ v samples(mean_spk_v)
• covariance uc(cvar_uc)
• vector averaged wind direction(wind_dir)
• variance of q(var_q)
• standard deviation of wind elevation angle(std_elev)
• mean value of \spike\ w samples(mean_spk_w)
• vertical (elevation) wind angle(elev)
• Time offset of tweaks from base_time(time_offset)
• number of bad or out of range v samples(n_bad_v)
• rotated covariance wc(cvar_rot_wc)
• Virtual temperature (T)(mean_t)
• number of valid v samples(n_good_v)
• mean value of out of range values and spikes of q -9999 if no spikes(mean_spk_q)
• Cross-boom wind velocity (v)(mean_v)
• number of valid u samples(n_good_u)
• Vertical angle of wind(phi)
• time(time)
• Vertical wind velocity (w)(mean_w)
• number of bad or out of range u samples(n_bad_u)
• covariance uq(cvar_uq)
• variance of c(var_c)
• covariance uv(cvar_uv)
• average voltage of IRGA cooler(mean_cooler)
• rotated covariance uv(cvar_rot_uv)
• Retrieved water vapor density profile(rho)
• covariance wc(cvar_wc)
• number of bad or out of range q samples(n_bad_q)
• vector averaged wind speed(wind_spd)
• lat(lat)
• covariance vt(cvar_vt)
• rotated covariance vc(cvar_rot_vc)
• 0=real or 1=dummy value of mr(real_mr)
• variance of variable v(var_v)
• covariance of qc(cvar_qc)
• kurtosis of variable c(kurt_c)
• number of bad or out of range t samples(n_bad_t)
• Water vapor density (q)(mean_q)
• covariance vc(cvar_vc)
• base time(base_time)
• mean co2 concentration (c)(mean_c)
• mixing ratio(mr)
• number of valid w samples(n_good_w)
• rotated covariance uc(cvar_rot_uc)
• average temperature (IGRA internal sensor)(temp_irga)

NIM/SKYRAD/M1 - IRTs do not agree with AERI

Since deployment at PYE, and then at NIM, the AMF SKYRAD IRT measured about 10K higher sky 
temperatures than the AERI and the MWRP IRT measureed about 20K higher than the AERI.  
Several actions were taken to diagnose the problem including confirming the correct 
configuration of the IRTs and data logger, cleaning the mirror and lens, and replacing the mirror.

After several days of rain beginning 6/2/2006, the three instruments came into agreement. 
It is unknown whether this was a problem with the AERI, MWRP-IRT or SKYRAD-IRT.

• Sky Infra-Red Temperature(sky_ir_temp)
• Sky Infra Red Temperature Minima(sky_ir_temp_min)
• Sky Infra Red Temperature Maxima(sky_ir_temp_max)

NIM/MET/M1 - Software problem

Intermittent Failure of Logger to read data from the Barometer.

• Barometric Pressure(atmos_pressure)

NIM/MET/M1  - Optical Rain Gauge Failure

The optical rain gauge on the met system did not record precipitation during this time 
period.

• Precipitation rate mean(precip_rate_mean)
• Precipitation rate maximum(precip_rate_max)
• Precipitation rate minimum(precip_rate_min)
• Precipitation rate standard deviation(precip_rate_sd)

NIM/ECOR/M1 - Flux Data Suspect for Some Wind Directions

NIM: For some wind directions the horizontal fetch was not representative of the field in 
which the AMF was located.  Therefore, for the wind direction ranges 90-170 (buildings) 
and 220-280 (trees) degrees, the fluxes are affected by insufficient fetch and  surfaces, 
buildings, or vegetation that are not similar to the local field conditions.

• CO2 flux(fc)
• latent heat flux(lv_e)
• h(h)
• Friction velocity(ustar)

NIM/SKYRAD/M1 - Tracker inoperative

Starting on 9/12 the NIM radiometer tracker drifted enough due to sinking supports and a 
drifting clock that the direct normal measurments (NIP) and the downwelling hemispheric 
diffuse shortwave measurments (8-48) were adversely affected in the afternoon hours.  The 
shortwave hemispheric global instrument (PSP) and downelling hemispheric longwave shaded1 
and shaded2 (PIR) are unaffected by this problem. 

The tracker problem greatly affected direct measurements and affected the diffuse 
measurement to a lesser extent. There are no redundant measurements for these instruments.  
However, during this time range the data collected before local noon (aprox 1140GMT) for all 
shortwave Skyrad instruments appear to be good.

• Instantaneous Direct Normal Shortwave Irradiance, Pyheliometer Thermopile
  Voltage(inst_direct_normal)
• Instantaneous Uncorrected Downwelling Shortwave Diffuse, Shaded Pyranometer
  Thermopile Voltage(inst_diffuse)

• Shortwave Direct Normal Irradiance, Pyrgeometer(short_direct_normal)
• Downwelling Shortwave Hemispheric Irradiance, Pyranometer, Standard Deviation(down_short_diffuse_hemisp_std)
• Shortwave Direct Normal Irradiance, Pyrgeometer, Maxima(short_direct_normal_max)
• Shortwave Direct Normal Irradiance, Pyrgeometer, Standard Deviation(short_direct_normal_std)
• Shortwave Direct Normal Irradiance, Pyrgeometer, Minima(short_direct_normal_min)
• Downwelling Shortwave Diffuse Hemispheric Irradiance, Ventilated Pyranometer(down_short_diffuse_hemisp)
• Downwelling Shortwave Diffuse Hemispheric Irradiance, Ventilated Pyranometer,
  Maxima(down_short_diffuse_hemisp_max)
• Downwelling Shortwave Diffuse Hemispheric Irradiance, Ventilated Pyranometer,
  Minima(down_short_diffuse_hemisp_min)

• null(Raw data stream - documentation not supported)

NIM/ECOR/M1 - Effects on ECOR CO2 Flux and Concentration By Aircraft

Aircraft landings, departures, and running aircraft on the airport pad
were found to produce large spikes in the half hourly CO2 flux and small spikes in CO2 
concentration on many days during the entire deployment of the AMF at NIM.  This influence 
was found on 40% of the days in March and April 2006 and sometimes for multiple periods in 
a day; this was typical of  the year of data.  The spikes range from only several 
micromoles s-1 m-2 to one hundred or more for flux (a typical spike was in the twenties) and 
near zero to 1.0 mmoles m-3 for CO2 concentration (typically around 0.15).

The aircraft influence was caused by persistent easterly winds; the airport
terminal pad and the nearest part of the runway were almost directly to the
east of the ECOR location.

Occasionally an influence on water vapor density was detected, but this was fairly rare 
and usually of very small magnitude.

• rotated covariance vc(cvar_rot_vc)
• covariance wc(cvar_wc)
• rotated covariance wc(cvar_rot_wc)
• covariance of tc(cvar_tc)
• CO2 flux(fc)
• rotated covariance uc(cvar_rot_uc)
• variance of c(var_c)
• covariance vc(cvar_vc)
• covariance uc(cvar_uc)
• mean co2 concentration (c)(mean_c)

NIM/MET/M1 - ORG Data Incorrect

The ORG measured around 9cm of rain in a short period while other co-located sensors 
measured no precip.

Use the Present Weather Detector data instead or set the ORG rainfall to 0mm during this 
time period.

• Precipitation rate mean(precip_rate_mean)
• Precipitation rate maximum(precip_rate_max)
• Precipitation rate minimum(precip_rate_min)
• Precipitation rate standard deviation(precip_rate_sd)

NIM/MET/M1 - ORG Data Underestimated Precipitation

The ORG underestimated precipitation by about 38% during the entire NIM deployment.  No 
troubleshooting technique or replacement of gage was successful in correcting the problem.

• Precipitation rate mean(precip_rate_mean)
• ORG carrier mean(org_carrier_mean)
• Precipitation rate maximum(precip_rate_max)
• Precipitation rate minimum(precip_rate_min)
• Precipitation rate standard deviation(precip_rate_sd)

NIM/MET/M1 - Reprocess: ORG Data has very small rainrate values

The ORG data is collected via analog signal and not digital.  Therefore, we
   continuously collect data even when no rain is occurring.  We also capture
   small events such as leaves, large bugs, dust, etc blowing through the
   measurement path.  Because this discrete event occurs quickly the value is
   usually captured for 1 or 2 seconds.  This value is then averaged to the
   minute producing rainrate on the order of .009 mm/hr or less.  These values
   are not indicative of rain and should be removed from the record or summing
   over long periods can bias the climate record.  We are reprocessing the data
   to remove these small values and are adjusting the collection program to
   remove them before ingest.

• Precipitation rate mean(precip_rate_mean)
• Precipitation rate maximum(precip_rate_max)
• Precipitation rate minimum(precip_rate_min)
• Precipitation rate standard deviation(precip_rate_sd)

NIM/MET/M1 - Wind Speed data contain offset due to induced voltage

The marine model of the RM Young wind sensor needs twisted pair shielded cable.  The 
manufacturer did not originally supply the pigtail with twisted pair shielded cable.  Use of 
twisted pair shielded cable for the rest of the cable run to the logger was also not 
specified.  This caused an induced voltage in the wind speed line from the wind direction 
excitation.  The induced voltage varied from sensor to sensor and probably changed anytime 
the cable was replaced or parts of the wind sensor were repaired or replaced. The induced 
voltage has been seen to vary from 0.15 m/s to as much as 1.08 m/s.

• Wind speed arithmetic standard deviation(wind_spd_arith_sd)
• Wind speed arithmetic maximum(wind_spd_arith_max)
• Vector-averaged Wind Speed(wind_spd_vec_avg)
• Wind speed arithmetic average(wind_spd_arith_avg)
• Wind speed arithmetic minimum(wind_spd_arith_min)