SGP/MWR/B5 - Reprocess: 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).

Although the MWR data will be reprocessed to apply the new monortm-based 
retrievals, for most purposes it will be sufficient to correct the data 
using the following factors:

PWV_MONORTM = 0.9695 * PWV_ROSENKRANZ
LWP_MONORTM = 1.026  * LWP_ROSENKRANZ

The Rosenkranz-based retrieval coefficients became active at SGP.B5 
20020415.2300.  The MONORTM-based retrieval coefficients became active 
at SGP.B5 20050624.2100.

Note: a reprocessing effort is already underway to apply the 
Rosenkranz-based retrieval coefficients to all MWR prior to April 
2002.  An additional reprocessing task will be undertaken to apply 
the MONORTM retrieval to all MWR data when the first is completed. 
Read reprocessing comments in the netcdf file header carefully to 
ensure you are aware which retrieval is in play.

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

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

• Ensemble average for MWR vapor in window centered about balloon release(mean_vap_mwr)
• Ensemble average for MWR liquid in window centered about balloon release(mean_liq_mwr)

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

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

SGP/MWR/B5 - New software version (4.15) installed

A problem began with the installation of MWR.EXE version 4.12 in July 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.

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

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