TWP/SMET/C1 - Poor Performing Sensor

On 4/23/2004 condensation was found inside the target area of the ORG lens. A spare was 
sent and installed but did not solve the problem of high background voltage values causing 
rainrate values to be recorded during no rainfall.  Values range anywhere from 0.06 to 
0.12 mm/hr.  

A new Optical Rain Gage was installed on 01/19/2005 @ 13:30 GMT alleviating the high 
background voltage values that lead to consistent rainfall rates of around 0.11 to 0.15 mm/hr 
on a consistent basis.  

The formula used to calculate rainfall rates from the new Optical Rain Gage is:  RR 
(mm/hr) = 25(V^1.87) - 0.15.

Older model formula = 20(V^2) - 0.05

The two formulas result in comparable data.

• Precipitation mean(precip_mean)
• Precipitation maximum(precip_max)
• Precipitation standard deviation(precip_sd)
• precipitation minimum(precip_min)

TWP/SONDE/C1 - Bad RH at beginning of sounding

It appears that the RH sensor heating circuit failed during this portion of the sounding 
(approximately between 0km and 11km).  The RH oscillates rapidly between low (~5 %RH) and 
not so low (~70 %RH) and the oscillation seems to stop when the temperature is below ~40 
degC.  According to Vaisala these are symptoms of failure in the ASIC (application 
specific integrated circuit) that controls the heating.

• Surface dew point temperature(dp)
• Relative humidity inside the instrument enclosure(rh)

TWP/SONDE/C1 - Bad RH at beginning of sounding

It appears that the RH sensor heating circuit failed during this portion of the sounding 
(approximately between 0km and 12km).  The RH oscillates rapidly between low (~2 %RH) and 
not so low (~80 %RH) and the oscillation seems to stop when the temperature is below ~40 
degC.  According to Vaisala these are symptoms of failure in the ASIC (application 
specific integrated circuit) that controls the heating.

• Surface dew point temperature(dp)
• Relative humidity inside the instrument enclosure(rh)

TWP/MWR/C1 - Reprocessed: Revised Retrieval Coefficients

IN THE BEGINNING (June 1992), the retrieval coefficients used to derive 
the precipitable water vapor (PWV) and liquid water path (LWP) from the 
MWR brightness temperatures were based on the Liebe and Layton (1987) 
water vapor and oxygen absorption model and the Grant (1957) liquid 
water absorption model.

Following the SHEBA experience, revised retrievals based on the more 
recent Rosenkranz (1998) water vapor and oxygen absorption models and 
the Liebe (1991) liquid waer absorption model were developed.  The 
Rosenkranz water vapor absorption model resulted a 2 percent increase 
in PWV relative to the earlier Liebe and Layton model.  The Liebe 
liquid water absorption model decreased the LWP by 10% relative to the 
Grant model.  However, the increased oxygen absorption caused a 
0.02-0.03 mm (20-30 g/m2) reduction in LWP, which was particularly 
significant for low LWP conditions (i.e. thin clouds encountered at 
SHEBA).

Recently, it has been shown (Liljegren, Boukabara, Cady-Pereira, and 
Clough, TGARS v. 43, pp 1102-1108, 2005) that the half-width of the 
22 GHz water vapor line from the HITRAN compilation, which is 5 percent 
smaller than the Liebe and Dillon (1969) half-width used in Rosenkranz 
(1998), provided a better fit to the microwave brightness temperature 
measurements at 5 frequencies in the range 22-30 GHz, and yielded more 
accurate retrievals. Accordingly, revised MWR retrieval coefficients 
have been developed using MONORTM, which utilizes the HITRAN compilation 
for its spectroscopic parameters.  These new retrievals provide 3 
percent less PWV and 2.6 percent greater LWP than the previous 
retrievals based on Rosenkranz (1998).

The Rosenkranz-based retrieval coefficients became active at TWP.C1 
20020504.0200.  The MONORTM-based retrieval coefficients became active 
at TWP.C1 20050630.2100.

Note: The TWP.C1 data for 19961011-20050630 have been reprocessed to apply the

• MWR column precipitable water vapor(vap)
• Averaged total liquid water along LOS path(liq)

• MWR column precipitable water vapor(vap)
• Averaged total liquid water along LOS path(liq)

• Total water vapor along zenith path using tip-derived brightness temperatures(vaptip)
• Total liquid water along zenith path using tip-derived brightness temperatures(liqtip)

TWP/MWR/C1 - New software version (4.15) installed

A problem began with the installation of MWR.EXE version 4.12 in October 2002. The 
software had been upgraded from a "DOS" to a "Windows"-compiled program to address an earlier 
problem.  The software upgrade corrected the earlier problem but introduced a new one that 
caused line-of-sight observing cycles to be skipped, a 15% reduction in the number of tip 
curves, and saturation of CPU usage.  Software versions 4.13 and 4.14 also produced 
these problems.

The new MWR software version (4.15) was installed on 9/13/2005. As a consequence of this 
upgrade, the tip curve frequency increased. The tip cycle time decreased from ~60s to ~50s.

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

• Noise injection temp at 31.4 GHz adjusted to tkbb(tnd31)
• Noise injection temp at nominal temperature at 23.8 GHz(tnd_nom23)
• 23.8 GHz goodness-of-fit coefficient(r23)
• Noise injection temp at 31.4 GHz derived from this tip(tnd31I)
• 31.8 GHz sky brightness temperature derived from tip curve(tbskytip31)
• Total liquid water along zenith path using tip-derived brightness temperatures(liqtip)
• Tip configuration number(tipn)
• Mixer kinetic (physical) temperature(tkxc)
• IR Brightness Temperature(ir_temp)
• Total water vapor along zenith path using tip-derived brightness temperatures(vaptip)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• 31.4 GHz sky signal(tipsky31)
• 23.8 GHz Blackbody signal(bb23)
• Ambient temperature(tkair)
• (tknd)
• 31.4 GHz goodness-of-fit coefficient(r31)
• Blackbody kinetic temperature(tkbb)
• 23.8 GHz blackbody+noise injection signal(bbn23)
• 23.8 GHz sky brightness temperature derived from tip curve(tbskytip23)
• Noise injection temp at 23.8 GHz adjusted to tkbb(tnd23)
• 23.8 GHz sky signal(tipsky23)
• Noise injection temp at nominal temperature at 31.4 GHz(tnd_nom31)
• Temperature correction coefficient at 23.8 GHz(tc23)
• 31.4 GHz blackbody(bb31)
• Blackbody temperature 1(tkbb1)
• Noise injection temp at 23.8 GHz derived from this tip(tnd23I)
• Blackbody temperature 2(tkbb2)
• Temperature correction coefficient at 31.4 GHz(tc31)

TWP/SMET/C1 - Reprocess: Barometric Data Changed from hPa to kPa

Barometric pressure data was converted from hPa to kPa in order to standardize the 
measurement units among ARM sites and to conform to accepted standard units determined by the 
scientific community.

• Barometric Pressure(atmos_pressure)

TWP/SMET/C1 - Reprocess: Tipping bucket rain gauge added

A tipping bucket rain gauge was added to the TWP.C1 SMET suite of instruments on 20061017. 
 Effective 20060926, two new variables (count and rain amount) were added to the end of 
the twpsmet60sC1.b1 datastream.  Between 9/26 and 10/17, the data for these two variables 
are filled with zeros.  Users should not use the data during this period as the zeros 
are not representative of the rain fall at the site.  When reprocessing of this datastream 
occurs these variables will be added for the 19961009-20060926 and data from 
19961009-20061017 will be filled with -9999 (missing).

• base time(base_time)