Data Quality Reports for Session: 106593 User: spohle Completed: 07/20/2007

TABLE OF CONTENTS

DQR IDSubjectData Streams Affected
D060106.15NIM/ECOR/M1 - Missing datanim30ecorM1.b1
D060530.1NIM/ECOR/M1 - Data Suspect for NW and East Wind Directionsnim30ecorM1.b1
D070215.5NIM/ECOR/M1 - Effects on ECOR CO2 Flux and Concentration By Aircraftnim30ecorM1.b1


DQRID : D060106.15
Start DateStart TimeEnd DateEnd Time
12/11/2005083012/13/20051230
01/28/2006033001/30/20060800
08/25/2006193008/29/20060730
Subject:
NIM/ECOR/M1 - Missing data
DataStreams:nim30ecorM1.b1
Description:
Data are missing and unrecoverable.
Measurements:nim30ecorM1.b1:
  • east longitude for all the input platforms.(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)
  • rotated variance v(var_rot_v)
  • corrected sensible heat flux(h)
  • momentum flux (dynamic)(k)
  • rotated covariance vq(cvar_rot_vq)
  • rotated variance w(var_rot_w)
  • skewness of variable u(skew_u)
  • number of q samples removed due to spikes(n_spk_q)
  • variance of variable 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)
  • altitude above sea levelaltunits(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)
  • specific heat of moist air(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)
  • rotated variance 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 variable 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)
  • mean sonic temperature (t), i.e. virtual temperature(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 offset from midnight of date of file. For CO data, this is identical to
    time_offset and is included for compatibility.(time)
  • mean w (vertical) wind component(mean_w)
  • number of bad or out of range u samples(n_bad_u)
  • covariance uq(cvar_uq)
  • variance of variable 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)
  • north latitude for all the input platforms.(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)
  • mean water vapor concentration (q)(mean_q)
  • covariance vc(cvar_vc)
  • Time offset from 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)

Back To Table of Contents

DQRID : D060530.1
Start DateStart TimeEnd DateEnd Time
11/26/2005153001/07/20072359
Subject:
NIM/ECOR/M1 - Data Suspect for NW and East Wind Directions
DataStreams:nim30ecorM1.b1
Description:
Data for these wind directions must be closely evaluated to determine if it is correct or 
incorrect.  Problem will remain for the entire extend of the NIM deployment.
Measurements:nim30ecorM1.b1:
  • rotated covariance uw(cvar_rot_uw)
  • vw covariance(cvar_vw)
  • rotated covariance wc(cvar_rot_wc)
  • mean value of out of range values and spikes of t -9999 if no spikes(mean_spk_t)
  • CO2 flux(fc)
  • mean sonic temperature (t), i.e. virtual temperature(mean_t)
  • corrected sensible heat flux(h)
  • latent heat flux(lv_e)
  • rotated covariance vw(cvar_rot_vw)
  • rotated mean w(mean_rot_w)
  • mean water vapor concentration (q)(mean_q)
  • covariance wq(cvar_wq)
  • rotated covariance wt(cvar_rot_wt)
  • rotated covariance wq(cvar_rot_wq)
  • mean value of out of range values and spikes of q -9999 if no spikes(mean_spk_q)
  • momentum flux (dynamic)(k)
  • mean co2 concentration (c)(mean_c)
  • uw covariance(cvar_uw)
  • covariance wc(cvar_wc)
  • mean value of \spike\ w samples(mean_spk_w)
  • wT covariance(cvar_wt)
  • mean w (vertical) wind component(mean_w)
  • friction velocity(ustar)
  • mean value of out of range values and spikes of c -9999 if no spikes(mean_spk_c)

Back To Table of Contents

DQRID : D070215.5
Start DateStart TimeEnd DateEnd Time
11/26/2005153001/07/20072330
Subject:
NIM/ECOR/M1 - Effects on ECOR CO2 Flux and Concentration By Aircraft
DataStreams:nim30ecorM1.b1
Description:
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.
Measurements:nim30ecorM1.b1:
  • 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 variable c(var_c)
  • covariance vc(cvar_vc)
  • covariance uc(cvar_uc)
  • mean co2 concentration (c)(mean_c)

Back To Table of Contents


END OF DATA