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/MWRP/M1 - Instrument noise problem

There are spikes and elevated noise in MWRP data. The origine of the spikes is RF 
interference from various sources.  All brightness temperatures are affected, but in particular 
the 5 K-band channels. LWP retrievals are noisy and affected by spikes as a result.

• Raw data stream - documentation not supported(raw)

• Retrieved cloud liquid water content(liquidWaterContent)
• Derived relative humidity(relativeHumidity)
• Derived virtual temperature(virtualTemperature)
• Interpolated water vapor mixing ratio(waterVaporMixingRatio)
• Retrieved liquid water path using only 23.835 and 30.0 GHz(liquidWaterPath2)
• air temperature (NGM250 predicted)(temperature)
• Retrieved water vapor density(waterVaporDensity)
• Interpolated dewpoint temperature(dewpointTemperature)
• Retrieved liquid water path(liquidWaterPath)
• Retrieved total precipitable water vapor using only 23.835 and 30.0 GHz(totalPrecipitableWater2)
• Microwave brightness temperature(brightnessTemperature)
• Total precipitable water vapor, from microwave radiometer(totalPrecipitableWater)

• Raw data stream - documentation not supported(raw)

NIM/MWR/M1 - Instrument noise problem/RF interference

Data are affected by intermittent spikes that become more frequent starting in March 2006. 
Spikes affect data mostly around 9 AM and 18:00 PM. The origin of the spikes is probably 
RF interference.

• Averaged total liquid water along LOS path(liq)
• Sky brightness temperature at 23.8 GHz(tbsky23)
• MWR column precipitable water vapor(vap)
• 31.4 GHz sky signal(sky31)
• Sky brightness temperature at 31.4 GHz(tbsky31)
• 23.8 GHz sky signal(sky23)

• Raw data stream - documentation not supported(Raw data stream - documentation not supported)

• 31.4 GHz sky signal(tipsky31)
• 31.4 GHz sky brightness temperature derived from tip curve(tbsky31tip)
• 23.8 GHz sky brightness temperature derived from tip curve(tbsky23tip)
• Total water vapor along zenith path using tip-derived brightness temperatures(vaptip)
• 23.8 GHz sky signal(tipsky23)
• Total liquid water along zenith path using tip-derived brightness temperatures(liqtip)

NIM/MWRP/M1 - IRT Sensor Calibration

Discrepancies between the MWRP and Skyrad IRT were observed in January. The MWRP IRT 
readings were constantly higher than those of the skyrad IRT. Some changes were introduced to 
the MWRP IRT to address the problem (see DQR D060602.2). On May 3, the IRT mirror was 
replaced. After the change in the mirror, the MWRP IRT readings became about 5-8 C lower. On 
June 3 the agreement between MWRP and Skyrad IRT became satisfactory (2-5 degree C 
difference).

It is hard to numerically quantify the difference in the IRT readings caused by the change 
in the mirror. We can only warn the user that between January 1 and June 3 the MWRP 
readings are 8 to 15 degree higher than the skyrad IRT.

• Raw data stream - documentation not supported(raw)

• Zenith-pointing infrared temperature at 10um(infraredTemperature)

• Raw data stream - documentation not supported(raw)

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/MWRP/M1 - Reprocessed - New retrieval coefficients

Occasionally, the retrieved relative humidity was exceeding 120%. Upon reviewing the data 
it was noticed that the high values were appearing in the highest layers (above 8 km) and 
especially during spring season. Since retrievals at the highest levels are mainly 
affected by the climatology used to constrain the retrievals, we reviewed the statistical 
coefficients that were used to retrieve temperature and humidity. It was discovered that, in 
the training dataset (radiosonde), there were a few outliers (invalid radiosonde 
soundings) that had escaped the screening process and were affecting the computations of the 
retrieval coefficients.

We recomputed the retrieval coefficients with the newly screened set of radiosonde data 
and reprocessed all the previous data at Niamey.  The reprocessed data were archived in 
August 2006.

The new coefficients improve temperature and humidity profiles in two ways. The relative 
humidity will not exceed 120% in the upper layers and the temperature profiles will be in 
better agreement with the sonde in the first 4 km.

• Expected root-mean-square error in liquid water path retrieval(liquidWaterPathRmsError)
• Expected root-mean-square error in liquid water content retrieval(liquidWaterContentRmsError)
• Expected root-mean-square error in liquid water path retrieval using only 23.835
  and 30.0 GHz(liquidWaterPath2RmsError)
• Retrieved cloud liquid water content(liquidWaterContent)
• Derived relative humidity(relativeHumidity)
• Derived virtual temperature(virtualTemperature)
• Interpolated water vapor mixing ratio(waterVaporMixingRatio)
• Expected root-mean-square error in precipitable water retrieval(totalPrecipitableWaterRmsError)
• Expected root-mean-square error in water vapor density retrieval(waterVaporDensityRmsError)
• Retrieved liquid water path using only 23.835 and 30.0 GHz(liquidWaterPath2)
• air temperature (NGM250 predicted)(temperature)
• Retrieved water vapor density(waterVaporDensity)
• Interpolated dewpoint temperature(dewpointTemperature)
• Retrieved liquid water path(liquidWaterPath)
• Cloud base height(cloudBaseHeight)
• Retrieved total precipitable water vapor using only 23.835 and 30.0 GHz(totalPrecipitableWater2)
• Expected root-mean-square error in temperature retrieval(temperatureRmsError)
• Expected root-mean-square error in precipitable water retrieval using only
  23.835 and 30.0 GHz(totalPrecipitableWater2RmsError)
• Total precipitable water vapor, from microwave radiometer(totalPrecipitableWater)

NIM/MWRP/M1 - 51.25 GHz channel calibration drifted

After a power outage on May 5 the 51.25 GHz had a slight change in the calibration. The 
resulting LWP computed by using all 6 channels increased of about 0.025 mm (25 g/m2).

• Microwave brightness temperature(brightnessTemperature)

NIM/MWR/M1 - Reprocessed: Recalibration to correct for occasional overheating.

The radiometer was intermittently thermally unstable resulting in poor calibrations for 
four brief time periods.  These data have been reprocessed to apply corrected calibrations. 
 The affected time periods were:

20060302-20060303
20060423-20060425
20060512-20060515
20060531-20060603

• 23.8 GHz blackbody+noise injection signal(bbn23)
• Noise injection temp at 31.4 GHz adjusted to tkbb(tnd31)
• Mixer kinetic (physical) temperature(tkxc)
• MWR column precipitable water vapor(vap)
• Temperature correction coefficient at 23.8 GHz(tc23)
• 23.8 GHz Blackbody signal(bb23)
• (tknd)
• Noise injection temp at nominal temperature at 23.8 GHz(tnd_nom23)
• Noise injection temp at nominal temperature at 31.4 GHz(tnd_nom31)
• Sky brightness temperature at 31.4 GHz(tbsky31)
• Blackbody kinetic temperature(tkbb)
• 23.8 GHz sky signal(sky23)
• Averaged total liquid water along LOS path(liq)
• Sky brightness temperature at 23.8 GHz(tbsky23)
• Temperature correction coefficient at 31.4 GHz(tc31)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• 31.4 GHz sky signal(sky31)
• Noise injection temp at 23.8 GHz adjusted to tkbb(tnd23)
• 31.4 GHz blackbody(bb31)

• 31.4 GHz blac2body+noise injection signal(bbn31)
• Mixer kinetic (physical) temperature(tkxc)
• Noise injection temp at 31.4 GHz adjusted to tkbb(tnd31)
• 31.4 GHz blackbody(bb31)
• Noise injection temp at 23.8 GHz adjusted to tkbb(tnd23)
• 31.4 GHz goodness-of-fit coefficient(r31)
• 31.4 GHz sky signal(tipsky31)
• 31.4 GHz sky brightness temperature derived from tip curve(tbsky31tip)
• 23.8 GHz goodness-of-fit coefficient(r23)
• 23.8 GHz blackbody+noise injection signal(bbn23)
• Total water vapor along zenith path using tip-derived brightness temperatures(vaptip)
• Noise injection temp at nominal temperature at 31.4 GHz(tnd_nom31)
• Temperature correction coefficient at 31.4 GHz(tc31)
• Noise injection temp at nominal temperature at 23.8 GHz(tnd_nom23)
• 23.8 GHz Blackbody signal(bb23)
• 23.8 GHz sky brightness temperature derived from tip curve(tbsky23tip)
• 23.8 GHz sky signal(tipsky23)
• Total liquid water along zenith path using tip-derived brightness temperatures(liqtip)
• Temperature correction coefficient at 23.8 GHz(tc23)
• Blackbody kinetic temperature(tkbb)
• (tknd)

NIM/TSI/M1 - Shadowband Misalignment

From installation, the shadowband was positioned south at solar noon until the vernal 
equinox when it began to migrate counter-clockwise until reaching east 37 days later on 4/26 
(about 9 days before mid-spring). The shadowband at solar noon continued to migrate until 
reaching its most northerly position (~15 deg) on the summer solstice (if everything was 
perfectly aligned, it probably would have been pointed north on this day). It then began 
to migrate clockwise and reached east again 56 days later on 8/16 (about 14 days after 
mid-summer). As expected, the shadowband reached its most southerly position on the 
autumnal equinox but was about 10 deg off of being due south. 

With the apparent alignment problem, I don't understand why the shadowband was mostly 
blocking the sun. When I started noticing this offset in May, I chose to leave it alone 
because I felt that adjusting the shadowband to where I thought it should be would cause it to 
not block the sun at either sunrise or sunset. 

The alignment was corrected on 9/29 (6 days after the day of the autumnal equinox).

• JPG data stream - documentation not supported(JPEG data stream - documentation not yet available)

• PNG data stream - documentation not supported(png)

• (MPEG data stream - documentation not yet available)

NIM/MWRP/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 measured 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. 
The cause of the discrepancy was probably dust accumulation on the lens of the instrument

• Zenith-pointing infrared temperature at 10um(infraredTemperature)

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)