scholarly journals A Global Climatology of Temperature and Water Vapor Variance Scaling from the Atmospheric Infrared Sounder

2009 ◽  
Vol 22 (20) ◽  
pp. 5558-5576 ◽  
Author(s):  
Brian H. Kahn ◽  
João Teixeira
Keyword(s):  
Boundary Layer ◽  
Water Vapor ◽  
Seasonal Variations ◽  
Atmospheric Infrared Sounder ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Power Law Exponent ◽  
Large Length ◽  
The Tropics ◽  
Scale Break

Abstract A global climatology of height-resolved variance scaling within the troposphere is presented using derived temperature (T) and water vapor (q) profiles from the Atmospheric Infrared Sounder (AIRS). The power-law exponent of T variance scaling approaches 1.0 outside of the tropics at scales >500–800 km, but it is closer to 0.3 at scales <500 km, similar to exponents obtained from aircraft campaigns, numerical modeling, and theoretical studies. The T exponents in the tropics at all scales become less than 0.3, with a similar pattern observed within the boundary layer in some extratropical regions. For q, the variance scaling differs substantially from T with exponents near 0.5–0.6 in parts of the tropics and subtropics with little to no scale break, showing some consistency with a very limited set of aircraft and satellite studies. Scaling differences as a function of land and ocean, altitude, and cloudy- and clear-sky scenes are quantified. Both T and q exponents indicate peak magnitudes in the midtroposphere and reductions are observed near the boundary layer and upper troposphere. Seasonal variations of T and q scaling reveal a stronger seasonal cycle over land than ocean, especially for T at large length scales. While the zonal variations of T and q exponents vary significantly for scales <500 km, the seasonal variations are much smaller in magnitude. The exponents derived from AIRS could eventually be extrapolated to smaller scales in the absence of additional scale breaks <150 km to provide useful information for constraining subgrid-scale cloud parameterizations.

scholarly journals An improved HIRS upper tropospheric water vapor dataset and its correlations with major climate indices

2012 ◽  
Vol 12 (12) ◽  
pp. 33411-33442 ◽  
Author(s):  
L. Shi ◽  
C. J. Schreck III ◽  
V. O. John
Keyword(s):  
Water Vapor ◽  
Climate Changes ◽  
Regional Climate ◽  
Climate Indices ◽  
Upper Troposphere ◽  
Teleconnection Patterns ◽  
Clear Sky ◽  
Spatial Coverage ◽  
The Tropics ◽  
Atmospheric Variables

Abstract. A new version of the upper tropospheric water vapor dataset is developed using intersatellite calibrated all-sky High-Resolution Infrared Radiation Sounder (HIRS) data. In this dataset, the majority of pixels that do not affect the water vapor processing in the upper troposphere are retained. Compared to the previous version that was based on column-clear-sky data, the new version has a much better daily spatial coverage and provides a better representation of the atmosphere. The HIRS observation patterns are compared to microwave sounder measurements. The differences between the two types of sounders are examined, and the analysis displays that the differences vary with respect to brightness temperature. An examination of the correlations of the HIRS upper tropospheric water vapor with major climate indices shows that the dataset is well correlated with climate indices especially in cold seasons. The selected climate indices track climate variation signals covering regions from the tropics to the poles. The correlation analysis shows the potential of using the upper tropospheric water vapor dataset together with a suite of many atmospheric variables to monitor regional climate changes and locate global teleconnection patterns.

scholarly journals A statistical analysis of the influence of deep convection on water vapor variability in the tropical upper troposphere

2009 ◽  
Vol 9 (15) ◽  
pp. 5847-5864 ◽  
Author(s):  
J. S. Wright ◽  
R. Fu ◽  
A. J. Heymsfield
Keyword(s):  
Water Vapor ◽  
Deep Convection ◽  
Tropical Rainfall Measuring Mission ◽  
Upper Troposphere ◽  
Ambient Relative Humidity ◽  
Wide Range ◽  
Ice Water Content ◽  
The Tropics ◽  
Ice Water ◽  
Tropical Upper Troposphere

Abstract. The factors that control the influence of deep convective detrainment on water vapor in the tropical upper troposphere are examined using observations from multiple satellites in conjunction with a trajectory model. Deep convection is confirmed to act primarily as a moisture source to the upper troposphere, modulated by the ambient relative humidity (RH). Convective detrainment provides strong moistening at low RH and offsets drying due to subsidence across a wide range of RH. Strong day-to-day moistening and drying takes place most frequently in relatively dry transition zones, where between 0.01% and 0.1% of Tropical Rainfall Measuring Mission Precipitation Radar observations indicate active convection. Many of these strong moistening events in the tropics can be directly attributed to detrainment from recent tropical convection, while others in the subtropics appear to be related to stratosphere-troposphere exchange. The temporal and spatial limits of the convective source are estimated to be about 36–48 h and 600–1500 km, respectively, consistent with the lifetimes of detrainment cirrus clouds. Larger amounts of detrained ice are associated with enhanced upper tropospheric moistening in both absolute and relative terms. In particular, an increase in ice water content of approximately 400% corresponds to a 10–90% increase in the likelihood of moistening and a 30–50% increase in the magnitude of moistening.

scholarly journals Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

2015 ◽  
Vol 8 (10) ◽  
pp. 10755-10792
Author(s):  
A. M. Dzambo ◽  
D. D. Turner ◽  
E. J. Mlawer
Keyword(s):  
Water Vapor ◽  
Statistical Significance ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Microwave Radiometers ◽  
The Impact ◽  
Dry Bias ◽  
Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km MSL), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, mid-latitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RH are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

scholarly journals Instantaneous variance scaling of AIRS profiles using a circular area Monte Carlo approach

2018 ◽  
Author(s):  
Jesse Dorrestijn ◽  
Brian H. Kahn ◽  
João Teixeira ◽  
Fredrick W. Irion
Keyword(s):  
Monte Carlo ◽  
Water Vapor ◽  
Large Scale ◽  
Large Temperature ◽  
Scaling Exponent ◽  
Circular Area ◽  
Scaling Exponents ◽  
Monte Carlo Approach ◽  
The Tropics ◽  
Scale Break

Abstract. Satellite observations are used to study the variance scaling of temperature and water vapor in the atmosphere. A high resolution of 13.5 km at nadir, instead of 45 km as in previous Atmospheric Infrared Sounder (AIRS) studies, enables the derivation of the variance-scaling exponents down to length scales of ~ 55 km.With the variable-size circular area Monte Carlo approach the exponents can be computed instantaneously along the track of Aqua, which gives more insight into the scaling behavior of the atmospheric variables in individual Level 2 satellite granules. Scaling exponents are shown to fluctuate heavily between β = −1 and β = −3 at the larger scales, while at the smaller scales they are often closer to β = −2, and they decrease a bit for moisture at the smallest scales that are considered. Outside the tropics, the temperature large-scale variance-scaling exponent is often close to −3 due to large temperature slopes that are present along the track of Aqua, likely as a result of geostrophic turbulence. Around the tropics, this exponent is often closer to −1, because the tropical atmosphere is dominated by smaller-scale processes such as moist convection, leading to an observable reverse scale break. In contrast, water vapor is shown to have large-scale exponents often close to −3 around the tropics, because there, large-scale water vapor slopes are common along the Aqua track. Furthermore, the scale-break length scale turns out to be highly variable and shows a large spread. The presented variance-scaling results are of importance for cloud parameterization purposes.

scholarly journals Evaluation of two Vaisala RS92 radiosonde solar radiative dry bias correction algorithms

2016 ◽  
Vol 9 (4) ◽  
pp. 1613-1626 ◽  
Author(s):  
Andrew M. Dzambo ◽  
David D. Turner ◽  
Eli J. Mlawer
Keyword(s):  
Water Vapor ◽  
Statistical Significance ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Microwave Radiometers ◽  
The Impact ◽  
Dry Bias ◽  
Better Than

Abstract. Solar heating of the relative humidity (RH) probe on Vaisala RS92 radiosondes results in a large dry bias in the upper troposphere. Two different algorithms (Miloshevich et al., 2009, MILO hereafter; and Wang et al., 2013, WANG hereafter) have been designed to account for this solar radiative dry bias (SRDB). These corrections are markedly different with MILO adding up to 40 % more moisture to the original radiosonde profile than WANG; however, the impact of the two algorithms varies with height. The accuracy of these two algorithms is evaluated using three different approaches: a comparison of precipitable water vapor (PWV), downwelling radiative closure with a surface-based microwave radiometer at a high-altitude site (5.3 km m.s.l.), and upwelling radiative closure with the space-based Atmospheric Infrared Sounder (AIRS). The PWV computed from the uncorrected and corrected RH data is compared against PWV retrieved from ground-based microwave radiometers at tropical, midlatitude, and arctic sites. Although MILO generally adds more moisture to the original radiosonde profile in the upper troposphere compared to WANG, both corrections yield similar changes to the PWV, and the corrected data agree well with the ground-based retrievals. The two closure activities – done for clear-sky scenes – use the radiative transfer models MonoRTM and LBLRTM to compute radiance from the radiosonde profiles to compare against spectral observations. Both WANG- and MILO-corrected RHs are statistically better than original RH in all cases except for the driest 30 % of cases in the downwelling experiment, where both algorithms add too much water vapor to the original profile. In the upwelling experiment, the RH correction applied by the WANG vs. MILO algorithm is statistically different above 10 km for the driest 30 % of cases and above 8 km for the moistest 30 % of cases, suggesting that the MILO correction performs better than the WANG in clear-sky scenes. The cause of this statistical significance is likely explained by the fact the WANG correction also accounts for cloud cover – a condition not accounted for in the radiance closure experiments.

scholarly journals Carbon monoxide mixing ratios over Oklahoma between 2002 and 2009 retrieved from Atmospheric Emitted Radiance Interferometer spectra

2010 ◽  
Vol 3 (5) ◽  
pp. 1319-1331 ◽  
Author(s):  
L. Yurganov ◽  
W. McMillan ◽  
C. Wilson ◽  
M. Fischer ◽  
S. Biraud ◽  
...  
Keyword(s):  
Water Vapor ◽  
Great Plains ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Retrieval Algorithm ◽  
Southern Great Plains ◽  
Diurnal Cycles ◽  
Mixing Ratios ◽  
Clear Sky ◽  
The Tropics

Abstract. CO mixing ratios for the lowermost 2-km atmospheric layer were retrieved from downwelling infrared (IR) radiance spectra of the clear sky measured between 2002 and 2009 by a zenith-viewing Atmospheric Emitted Radiance Interferometer (AERI) deployed at the Southern Great Plains (SGP) observatory of the Atmospheric Radiation Measurements (ARM) Program near Lamont, Oklahoma. A version of a published earlier retrieval algorithm was improved and validated. Archived temperature and water vapor profiles retrieved from the same AERI spectra through automated ARM processing were used as input data for the CO retrievals. We found the archived water vapor profiles required additional constraint using SGP Microwave Radiometer retrievals of total precipitable water vapor. A correction for scattered solar light was developed as well. The retrieved CO was validated using simultaneous independently measured CO profiles from an aircraft. These tropospheric CO profiles were measured from the surface to altitudes of 4572 m a.s.l. once or twice a week between March 2006 and December 2008. The aircraft measurements were supplemented with ground-based CO measurements using a non-dispersive infrared gas correlation instrument at the SGP and retrievals from the Atmospheric IR Sounder (AIRS) above 5 km to create full tropospheric CO profiles. Comparison of the profiles convolved with averaging kernels to the AERI CO retrievals found a squared correlation coefficient of 0.57, a standard deviation of ±11.7 ppbv, a bias of -16 ppbv, and a slope of 0.92. Averaged seasonal and diurnal cycles measured by the AERI are compared with those measured continuously in situ at the SGP in the boundary layer. Monthly mean CO values measured by the AERI between 2002 and 2009 are compared with those measured by the AIRS over North America, the Northern Hemisphere mid-latitudes, and over the tropics.

scholarly journals Methodology for Water Monitoring in the Upper Troposphere with Raman Lidar at the Haute-Provence Observatory

2009 ◽  
Vol 26 (10) ◽  
pp. 2149-2160 ◽  
Author(s):  
Christophe Hoareau ◽  
Philippe Keckhut ◽  
Alain Sarkissian ◽  
Jean-Luc Baray ◽  
Georges Durry
Keyword(s):  
Water Vapor ◽  
Time Integration ◽  
Raman Lidar ◽  
Total Water ◽  
Upper Troposphere ◽  
Clear Sky ◽  
Term Evolution ◽  
Calibration Methods ◽  
Calibration Techniques

Abstract A Raman water vapor lidar has been developed at the Haute-Provence Observatory to study the distribution of water in the upper troposphere and its long-term evolution. Some investigations have been proposed and described to ensure a pertinent monitoring of water vapor in the upper troposphere. A new method to take into account the geophysical variability for time integration processes has been developed based on the stationarity of water vapor. Successive measurements, considered as independent, have been used to retrieve H2O profiles that were recorded during the same nighttimes over a few hours. Various calibration methods, including zenith clear-sky observation, standard meteorological radiosondes, and total water vapor column, have been investigated. A method to evaluate these calibration techniques has been proposed based on the variance weakening. For the lidar at the Haute-Provence Observatory, the calibration based on the total water vapor column appears to be the optimum method. Radiosondes also give comparable results, but do not allow lidar to be independent. The clear-sky zenith observation is an original technique, and seems to accurately identify discontinuities. However, it appears to be less reliable, based on the variance investigation, than the two others. It is also sensitive to aerosol loading, which is also expected to vary with time.

scholarly journals Testing Climate Models Using Thermal Infrared Spectra

2008 ◽  
Vol 21 (9) ◽  
pp. 1863-1875 ◽  
Author(s):  
Stephen Leroy ◽  
James Anderson ◽  
John Dykema ◽  
Richard Goody
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Climate Models ◽  
Tropospheric Temperature ◽  
Strong Constraint ◽  
Detection Techniques ◽  
Clear Sky ◽  
Stratospheric Temperature ◽  
Occultation Data ◽  
The Tropics

Abstract An approach to test climate models with observations is presented. In this approach, it is possible to directly observe the longwave feedbacks of the climate system in time series of annual average outgoing longwave spectra. Tropospheric temperature, stratospheric temperature, water vapor, and carbon dioxide have clear and distinctive signatures in the infrared spectrum, and it is possible to detect trends of these signals unambiguously from trends in the outgoing longwave spectrum by optimal detection techniques. This approach is applied to clear-sky data in the tropics simulated from the output of an ensemble of climate models. Estimates of the water vapor–longwave feedback by this approach agree to within estimated errors with truth, and it is likely that an uncertainty of 50% can be obtained in 20 yr of a continuous time series. The correlation of tropospheric temperature and water vapor anomalies can provide a constraint on the water vapor–longwave feedback to 5% uncertainty in 20 yr, or 7% in 10 yr. Thus, it should be possible to place a strong constraint on climate models, which currently show a range of 30% in the water vapor–longwave feedback, in just 10 yr. These results may not hold in the presence of clouds, however, and so it may be necessary to supplement time series of outgoing longwave spectra with GPS radio occultation data, which are insensitive to clouds.

scholarly journals HIRS channel 12 brightness temperature dataset and its correlations with major climate indices

2013 ◽  
Vol 13 (14) ◽  
pp. 6907-6920 ◽  
Author(s):  
L. Shi ◽  
C. J. Schreck III ◽  
V. O. John
Keyword(s):  
Water Vapor ◽  
Brightness Temperature ◽  
Regional Climate ◽  
Climate Indices ◽  
Teleconnection Patterns ◽  
Clear Sky ◽  
Vapor Channel ◽  
Brightness Temperatures ◽  
Spatial Coverage ◽  
The Tropics

Abstract. A new version of the High-Resolution Infrared Radiation Sounder (HIRS) upper tropospheric water vapor channel (channel 12) brightness temperature dataset is developed using intersatellite calibrated data. In this dataset, only those pixels affected by upper tropospheric clouds are discarded. Compared to the previous version that was based on column-clear-sky data, the new version has much better daily spatial coverage. The HIRS observation patterns are compared to microwave sounder measurements. The differences between the two types of sounders vary with respect to brightness temperature with larger differences for higher (dry) values. Correlations between the HIRS upper tropospheric water vapor channel brightness temperatures and several major climate indices show strong signals during cold seasons. The selected climate indices track climate variation signals covering regions from the tropics to the poles. Qualitatively, moist signals are correlated with troughs and ascending branches of the circulation, while dry signals occur with ridges and descent. These correlations show the potential of using the upper tropospheric water vapor channel brightness temperature dataset together with a suite of many atmospheric variables to monitor regional climate changes and locate global teleconnection patterns.

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