SGP/MWR/B6 - High noise level, poor calibration

The data from this instrument (serial number 18) have become increasingly noisy, most 
likely due to a failing local oscillator.  A consequence of this increased noise level has 
been few valid calibration scans ("tip curves") since 1 April 2002: during the period 26-31 
March 2002 1496 valid tip curves were acquired, whereas only 729 were acquired during 
April, 387 during May, 143 during June, 243 during July.  As a result, the calibration was 
not as well-maintained as usual.  The measured brightness temperatures and retrieved 
precipitable water vapor and liquid water path should be regarded as suspect.  The instrument 
was replaced with serial number 04 on 2 August 2002.

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

• 23.8 GHz sky signal(sky23)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• 23.8 GHz sky+noise injection signal(23skyn)
• 23.8 GHz Blackbody signal(23bb)
• Averaged total liquid water along LOS path(liq)
• 31.4 GHz blackbody(bb31)
• 31.4 GHz blackbody(31bb)
• 23.8 GHz blackbody+noise injection signal(bbn23)
• 23.8 GHz sky signal(23sky)
• 23.8 GHz Blackbody signal(bb23)
• 23.8 GHz sky brightness temperature(23tbsky)
• Noise injection temp at nominal temperature at 23.8 GHz(noise_injection_temp_23)
• MWR column precipitable water vapor(vap)
• 31.4 GHz sky+noise injection signal(31skyn)
• Sky brightness temperature at 23.8 GHz(tbsky23)
• 31.4 GHz blackbody+noise injection signal(31bbn)
• Temperature correction coefficient at 31.4 GHz(temperature_correction_coef_31)
• 23.8 GHz blackbody+noise injection signal(23bbn)
• Sky brightness temperature at 31.4 GHz(tbsky31)
• Noise injection temp at nominal temperature at 31.4 GHz(noise_injection_temp_31)
• 31.4 GHz noise injection brightness temperature(31unoise)
• 31.4 GHz sky signal(sky31)
• 31.4 GHz sky brightness temperature(31tbsky)
• Temperature correction coefficient at 23.8 GHz(temperature_correction_coef_23)
• 23.8 GHz noise injection brightness temperature(23unoise)
• 31.4 GHz sky signal(31sky)
• 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 23.8 GHz adjusted to tkbb(tnd23)
• Averaged total liquid water along LOS path(liq)
• Temperature correction coefficient at 31.4 GHz(tc31)
• Noise injection temp at 31.4 GHz adjusted to tkbb(tnd31)
• Noise injection temp at nominal temperature at 31.4 GHz(tnd_nom31)
• Temperature correction coefficient at 23.8 GHz(tc23)
• MWR column precipitable water vapor(vap)
• Noise injection temp at nominal temperature at 23.8 GHz(tnd_nom23)
• 23.8 GHz Blackbody signal(bb23)
• Sky brightness temperature at 31.4 GHz(tbsky31)
• 31.4 GHz sky brightness temperature(31tbsky)
• 31.4 GHz sky signal(sky31)
• Sky brightness temperature at 23.8 GHz(tbsky23)
• 31.4 GHz blackbody(bb31)
• 23.8 GHz sky brightness temperature(23tbsky)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• 23.8 GHz sky signal(sky23)
• 23.8 GHz blackbody+noise injection signal(bbn23)

SGP/MWR/B6 - Incorrect MWR warmup configuration

The local oscillator warm-up delay in the MWR configuration file was set to 
720 milliseconds instead of the typical 100 milliseconds which substantially 
increased the duration of the observing cycle.

• Total liquid water along zenith path using tip-derived brightness temperatures(liqtip)
• 23.8 GHz blackbody+noise injection signal(bbn23)
• Total water vapor along zenith path using tip-derived brightness temperatures(vaptip)
• 23.8 GHz sky brightness temperature derived from tip curve(tbskytip23)
• 31.4 GHz sky signal(tipsky31)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• 31.8 GHz sky brightness temperature derived from tip curve(tbskytip31)
• Noise injection temp at 31.4 GHz derived from this tip(tnd31I)
• 23.8 GHz sky signal(tipsky23)
• Noise injection temp at 23.8 GHz derived from this tip(tnd23I)
• 23.8 GHz Blackbody signal(bb23)
• 31.4 GHz blackbody(bb31)

• 23.8 GHz sky signal(sky23)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• Averaged total liquid water along LOS path(liq)
• Sky brightness temperature at 31.4 GHz(tbsky31)
• 23.8 GHz Blackbody signal(bb23)
• Sky brightness temperature at 23.8 GHz(tbsky23)
• 31.4 GHz blackbody(bb31)
• 23.8 GHz blackbody+noise injection signal(bbn23)
• 31.4 GHz sky signal(sky31)

• 23.8 GHz Blackbody signal(bb23)
• Averaged total liquid water along LOS path(liq)
• Sky brightness temperature at 31.4 GHz(tbsky31)
• 31.4 GHz sky brightness temperature(31tbsky)
• 31.4 GHz sky signal(sky31)
• Sky brightness temperature at 23.8 GHz(tbsky23)
• 31.4 GHz blackbody(bb31)
• 23.8 GHz sky brightness temperature(23tbsky)
• MWR column precipitable water vapor(vap)
• 31.4 GHz blac2body+noise injection signal(bbn31)
• 23.8 GHz sky signal(sky23)
• 23.8 GHz blackbody+noise injection signal(bbn23)

SGP/MWR/C1 - Intermittent Negative Sky Brightness Temperatures

Several related and recurring problems with the SGP MWRs have been
reported dating back to 1999.  These problems were due to the
occurrence of blackbody signals (in counts) that were half of those
expected. The symptoms included noisy data (especially at Purcell),
spikes in the data (especially at Vici), negative brightness
temperatures, and apparent loss of serial communication between the
computer and the radiometer, which results in a self-termination of the
MWR program (especially at the CF).

Because these all initially appeared to be hardware-related problems,
the instrument mentor and SGP site operations personnel (1) repeatedly
cleaned and replaced the fiber optic comm. components, (2) swapped
radiometers, (3) sent radiometers back to Radiometrics for evaluation
(which has not revealed any instrument problems), and (4) reconfigured
the computer's operating system.  Despite several attempts to isolate
and correct it, the problem persisted.

It became apparent that some component of the Windows98 configuration
conflicted with the DOS-based MWR program or affected the serial port
or the contents of the serial port buffer. This problem was finally
corrected by upgrading the MWR software with a new Windows-compatible
program.

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

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

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

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

SGP/MWR/B1 - Intermittent Negative Sky Brightness Temperatures

Several related and recurring problems with the SGP MWRs have been
reported dating back to 1999.  These problems were due to the
occurrence of blackbody signals (in counts) that were half of those
expected. The symptoms included noisy data (especially at Purcell),
spikes in the data (especially at Vici), negative brightness
temperatures, and apparent loss of serial communication between the
computer and the radiometer, which results in a self-termination of the
MWR program (especially at the CF).

Because these all initially appeared to be hardware-related problems,
the instrument mentor and SGP site operations personnel (1) repeatedly
cleaned and replaced the fiber optic comm. components, (2) swapped
radiometers, (3) sent radiometers back to Radiometrics for evaluation
(which has not revealed any instrument problems), and (4) reconfigured
the computer's operating system.  Despite several attempts to isolate
and correct it, the problem persisted.

It became apparent that some component of the Windows98 configuration
conflicted with the DOS-based MWR program or affected the serial port
or the contents of the serial port buffer. This problem was finally
corrected by upgrading the MWR software with a new Windows-compatible
program.

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

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

SGP/MWR/B4 - Intermittent Negative Sky Brightness Temperatures

Several related and recurring problems with the SGP MWRs have been
reported dating back to 1999.  These problems were due to the
occurrence of blackbody signals (in counts) that were half of those
expected. The symptoms included noisy data (especially at Purcell),
spikes in the data (especially at Vici), negative brightness
temperatures, and apparent loss of serial communication between the
computer and the radiometer, which results in a self-termination of the
MWR program (especially at the CF).

Because these all initially appeared to be hardware-related problems,
the instrument mentor and SGP site operations personnel (1) repeatedly
cleaned and replaced the fiber optic comm. components, (2) swapped
radiometers, (3) sent radiometers back to Radiometrics for evaluation
(which has not revealed any instrument problems), and (4) reconfigured
the computer's operating system.  Despite several attempts to isolate
and correct it, the problem persisted.

It became apparent that some component of the Windows98 configuration
conflicted with the DOS-based MWR program or affected the serial port
or the contents of the serial port buffer. This problem was finally
corrected by upgrading the MWR software with a new Windows-compatible
program.

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

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

SGP/MWR/B5 - Intermittent Negative Sky Brightness Temperatures

Several related and recurring problems with the SGP MWRs have been
reported dating back to 1999.  These problems were due to the
occurrence of blackbody signals (in counts) that were half of those
expected. The symptoms included noisy data (especially at Purcell),
spikes in the data (especially at Vici), negative brightness
temperatures, and apparent loss of serial communication between the
computer and the radiometer, which results in a self-termination of the
MWR program (especially at the CF).

Because these all initially appeared to be hardware-related problems,
the instrument mentor and SGP site operations personnel (1) repeatedly
cleaned and replaced the fiber optic comm. components, (2) swapped
radiometers, (3) sent radiometers back to Radiometrics for evaluation
(which has not revealed any instrument problems), and (4) reconfigured
the computer's operating system.  Despite several attempts to isolate
and correct it, the problem persisted.

It became apparent that some component of the Windows98 configuration
conflicted with the DOS-based MWR program or affected the serial port
or the contents of the serial port buffer. This problem was finally
corrected by upgrading the MWR software with a new Windows-compatible
program.

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

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

SGP/MWR/B6 - Intermittent Negative Sky Brightness Temperatures

Several related and recurring problems with the SGP MWRs have been
reported dating back to 1999.  These problems were due to the
occurrence of blackbody signals (in counts) that were half of those
expected. The symptoms included noisy data (especially at Purcell),
spikes in the data (especially at Vici), negative brightness
temperatures, and apparent loss of serial communication between the
computer and the radiometer, which results in a self-termination of the
MWR program (especially at the CF).

Because these all initially appeared to be hardware-related problems,
the instrument mentor and SGP site operations personnel (1) repeatedly
cleaned and replaced the fiber optic comm. components, (2) swapped
radiometers, (3) sent radiometers back to Radiometrics for evaluation
(which has not revealed any instrument problems), and (4) reconfigured
the computer's operating system.  Despite several attempts to isolate
and correct it, the problem persisted.

It became apparent that some component of the Windows98 configuration
conflicted with the DOS-based MWR program or affected the serial port
or the contents of the serial port buffer. This problem was finally
corrected by upgrading the MWR software with a new Windows-compatible
program.

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

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

SGP/MWR/C1 - Incorrect min and max values

The values of valid_min and valid_max applied to fields tkxc and tknd were incorrect. They 
should be 303 and 333, respectively.

• Mixer kinetic (physical) temperature(tkxc)
• (tknd)

SGP/MWR/B1  - min/max/delta values incorrect

The values of valid_min, valid_max, and valid_delta for fields tkxc and tknd were 
incorrect. They should be 303, 333, and 0.5 K, respectively.

• (tknd)
• Mixer kinetic (physical) temperature(tkxc)

SGP/MWR/B4  - min/max/delta values incorrect

The values of valid_min, valid_max, and valid_delta for fields tkxc and tknd were 
incorrect. They should be 303, 333, and 0.5 K, respectively.

• Mixer kinetic (physical) temperature(tkxc)
• (tknd)

SGP/MWR/B5  - min/max/delta values incorrect

The values of valid_min, valid_max, and valid_delta for fields tkxc and tknd were 
incorrect. They should be 303, 333, and 0.5 K, respectively.

• (tknd)
• Mixer kinetic (physical) temperature(tkxc)

SGP/MWR/B6  - min/max/delta values incorrect

The values of valid_min, valid_max, and valid_delta for fields tkxc and tknd were 
incorrect. They should be 303, 333, and 0.5 K, respectively.

• Mixer kinetic (physical) temperature(tkxc)
• (tknd)

SGP/AERI/B1 - Increased radiative uncertainty during hot summer afternoons

The ambient temperature of the AERI enclosures at the boundary facilities
often exceeded 308 K during hot summer afternoons.  This threshold marked
the maximum end of the "acceptable" range of temperatures that the 
ambient blackbody should maintain.  The issue is that if the hot 
blackbody and ambient blackbody temperatures are too close together, then 
the radiative calibration becomes more uncertain.  It should be noted 
that the hot blackbody's temperature is maintained at roughly 333 K.  

Using the calibration equation, an uncertainty analysis was performed
to see how much "additional" uncertainty resulted in the AERI
observations when the ambient temperature was between 308-315 K (315 K
was the maximum temperature that the ambient blackbody reached during
the summer).  The analysis compared the radiative uncertainties from the
Hillsboro (B1) AERI (chosen at random) with the AERI-01 at the SGP/CF
over a 5-year period.  Plot1 (below) shows the time-series of ambient
blackbody temperatures for the two instruments, along with histograms to
show the distribution of the temperatures.  The boundary facility
instrument did suffer from higher temperatures in the summer
time periods.  Plot2 (bleow) shows the relative radiative uncertainty
for each instrument.  The CF instrument has a maximum radiative
uncertainty of around 0.18% during the summer, while the BF instrument's
maximum radiative uncertainty is about 0.25%.  This plot demonstrates
that the radiative uncertainty is significantly larger for the BF
instrument in the summer relative to the CF instrument.  However, the
absolute radiative accuracy for the AERI is specified to be better than
1% of the ambient radiance, and both the CF and the BF AERIs are well
within this uncertainty.  

In short, there is significantly higher radiative uncertainty in the
BF AERIs during the hot summer afternoons, but the uncertainty is well
within the specified accuracy of the instrument.

plot1:  aeri_abb_temp.lamont_hillsboro.png 

plot2:  aeri_relative_error.lamont_hillsboro.png 

• Mean of radiance spectra ensemble(mean_rad)

• Mean of radiance spectra ensemble(mean_rad)

SGP/AERI/B4 - Increased radiative uncertainty during hot summer afternoons

The ambient temperature of the AERI enclosures at the boundary facilities
often exceeded 308 K during hot summer afternoons.  This threshold marked
the maximum end of the "acceptable" range of temperatures that the 
ambient blackbody should maintain.  The issue is that if the hot 
blackbody and ambient blackbody temperatures are too close together, then 
the radiative calibration becomes more uncertain.  It should be noted 
that the hot blackbody's temperature is maintained at roughly 333 K.  

Using the calibration equation, an uncertainty analysis was performed
to see how much "additional" uncertainty resulted in the AERI
observations when the ambient temperature was between 308-315 K (315 K
was the maximum temperature that the ambient blackbody reached during
the summer).  The analysis compared the radiative uncertainties from the
Hillsboro (B1) AERI (chosen at random) with the AERI-01 at the SGP/CF
over a 5-year period.  Plot1 (below) shows the time-series of ambient
blackbody temperatures for the two instruments, along with histograms to
show the distribution of the temperatures.  The boundary facility
instrument did suffer from higher temperatures in the summer
time periods.  Plot2 (bleow) shows the relative radiative uncertainty
for each instrument.  The CF instrument has a maximum radiative
uncertainty of around 0.18% during the summer, while the BF instrument's
maximum radiative uncertainty is about 0.25%.  This plot demonstrates
that the radiative uncertainty is significantly larger for the BF
instrument in the summer relative to the CF instrument.  However, the
absolute radiative accuracy for the AERI is specified to be better than
1% of the ambient radiance, and both the CF and the BF AERIs are well
within this uncertainty.  

In short, there is significantly higher radiative uncertainty in the
BF AERIs during the hot summer afternoons, but the uncertainty is well
within the specified accuracy of the instrument.

plot1:  aeri_abb_temp.lamont_hillsboro.png 

plot2:  aeri_relative_error.lamont_hillsboro.png 

• Mean of radiance spectra ensemble(mean_rad)

• Mean of radiance spectra ensemble(mean_rad)

SGP/AERI/B5 - Increased radiative uncertainty during hot summer afternoons

The ambient temperature of the AERI enclosures at the boundary facilities
often exceeded 308 K during hot summer afternoons.  This threshold marked
the maximum end of the "acceptable" range of temperatures that the 
ambient blackbody should maintain.  The issue is that if the hot 
blackbody and ambient blackbody temperatures are too close together, then 
the radiative calibration becomes more uncertain.  It should be noted 
that the hot blackbody's temperature is maintained at roughly 333 K.  

Using the calibration equation, an uncertainty analysis was performed
to see how much "additional" uncertainty resulted in the AERI
observations when the ambient temperature was between 308-315 K (315 K
was the maximum temperature that the ambient blackbody reached during
the summer).  The analysis compared the radiative uncertainties from the
Hillsboro (B1) AERI (chosen at random) with the AERI-01 at the SGP/CF
over a 5-year period.  Plot1 (below) shows the time-series of ambient
blackbody temperatures for the two instruments, along with histograms to
show the distribution of the temperatures.  The boundary facility
instrument did suffer from higher temperatures in the summer
time periods.  Plot2 (bleow) shows the relative radiative uncertainty
for each instrument.  The CF instrument has a maximum radiative
uncertainty of around 0.18% during the summer, while the BF instrument's
maximum radiative uncertainty is about 0.25%.  This plot demonstrates
that the radiative uncertainty is significantly larger for the BF
instrument in the summer relative to the CF instrument.  However, the
absolute radiative accuracy for the AERI is specified to be better than
1% of the ambient radiance, and both the CF and the BF AERIs are well
within this uncertainty.  

In short, there is significantly higher radiative uncertainty in the
BF AERIs during the hot summer afternoons, but the uncertainty is well
within the specified accuracy of the instrument.

plot1:  aeri_abb_temp.lamont_hillsboro.png 

plot2:  aeri_relative_error.lamont_hillsboro.png 

• Mean of radiance spectra ensemble(mean_rad)

• Mean of radiance spectra ensemble(mean_rad)

SGP/AERI/B6 - Increased radiative uncertainty during hot summer afternoons

The ambient temperature of the AERI enclosures at the boundary facilities
often exceeded 308 K during hot summer afternoons.  This threshold marked
the maximum end of the "acceptable" range of temperatures that the 
ambient blackbody should maintain.  The issue is that if the hot 
blackbody and ambient blackbody temperatures are too close together, then 
the radiative calibration becomes more uncertain.  It should be noted 
that the hot blackbody's temperature is maintained at roughly 333 K.  

Using the calibration equation, an uncertainty analysis was performed
to see how much "additional" uncertainty resulted in the AERI
observations when the ambient temperature was between 308-315 K (315 K
was the maximum temperature that the ambient blackbody reached during
the summer).  The analysis compared the radiative uncertainties from the
Hillsboro (B1) AERI (chosen at random) with the AERI-01 at the SGP/CF
over a 5-year period.  Plot1 (below) shows the time-series of ambient
blackbody temperatures for the two instruments, along with histograms to
show the distribution of the temperatures.  The boundary facility
instrument did suffer from higher temperatures in the summer
time periods.  Plot2 (bleow) shows the relative radiative uncertainty
for each instrument.  The CF instrument has a maximum radiative
uncertainty of around 0.18% during the summer, while the BF instrument's
maximum radiative uncertainty is about 0.25%.  This plot demonstrates
that the radiative uncertainty is significantly larger for the BF
instrument in the summer relative to the CF instrument.  However, the
absolute radiative accuracy for the AERI is specified to be better than
1% of the ambient radiance, and both the CF and the BF AERIs are well
within this uncertainty.  

In short, there is significantly higher radiative uncertainty in the
BF AERIs during the hot summer afternoons, but the uncertainty is well
within the specified accuracy of the instrument.

plot1:  aeri_abb_temp.lamont_hillsboro.png 

plot2:  aeri_relative_error.lamont_hillsboro.png 

• Mean of radiance spectra ensemble(mean_rad)

• Mean of radiance spectra ensemble(mean_rad)

SGP/MWR/C1 - 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 as follows (BCR 456):
SGP/C1 (Lamont)     4/16/2002, 2000
SGP/B1 (Hillsboro)  4/12/2002, 1600
SGP/B4 (Vici)       4/15/2002, 2300
SGP/B5 (Morris)     4/15/2002, 2300
SGP/B6 (Purcell)    4/16/2002, 2200
SGP/E14(Lamont)     4/16/2002, 0000
NSA/C1 (Barrow)     4/25/2002, 1900 
NSA/C2 (Atqasuk)    4/18/2002, 1700
TWP/C1 (Manus)      5/04/2002, 0200
TWP/C2 (Nauru)      4/27/2002, 0600
TWP/C3 (Darwin)     inception

The MONORTM-based retrieval coefficients became active as follows (BCR 984):

SGP/C1 (Lamont)     6/28/2005, 2300
SGP/B1 (Hillsboro)  6/24/2005, 2100
SGP/B4 (Vici)       6/24/2005, 2100
SGP/B5 (Morris)     6/24/2005, 2100
SGP/B6 (Purcell)    6/24/2005, 1942
SGP/E14(Lamont)     6/28/2005, 2300
NSA/C1 (Barrow)     6/29/2005, 0000 
NSA/C2 (Atqasuk)    6/29/2005, 0000
TWP/C1 (Manus)      6/30/2005, 2100
TWP/C2 (Nauru)      6/30/2005, 2100
TWP/C3 (Darwin)     6/30/2005, 2100
PYE/M1 (Pt. Reyes)  4/08/2005, 1900**

** At Pt. Reyes, the original retrieval coefficients implemented in March 2005 were based 
on a version of the Rosenkranz model that had been modified to use the HITRAN half-width 
at 22 GHz and to be consistent with the water vapor continuum in MONORTM.  These 
retrievals yield nearly identical results to the MONORTM retrievals.  Therefore the Pt. Reyes 
data prior to 4/08/2005 may not require reprocessing.

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

• 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)

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

• 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)

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

SGP/MWR/B1 - 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.B1 20020412.1600.  The 
MONORTM-based retrieval coefficients became active at SGP.B1 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)

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

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

SGP/MWR/B4 - 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.B4 20020415.2300.  The 
MONORTM-based retrieval coefficients became active at SGP.B4 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.

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

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

• 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)

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

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

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/B6 - 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.B6 
20020416.2200.  The MONORTM-based retrieval coefficients became active 
at SGP.B6 20050624.1942.

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.

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

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

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

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

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