Representation and diurnal variation of upper tropospheric humidity in observations and models (original) (raw)
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Journal of Geophysical Research, 2011
1] The depiction of water vapor in the upper troposphere in Geophysical Fluid Dynamics Laboratory (GFDL) climate model and ERA-40 reanalysis is evaluated through a model-to-radiance approach. Brightness temperatures of High-Resolution Infrared Radiation Sounder (HIRS) 6.7 mm channel, Special Sensor for Microwave Water Vapor Profiler (SSM/T-2) 183.31 ± 1 GHz channel, and Microwave Sounding Unit (MSU) 60 GHz channel simulated with data from the GFDL climate model and ERA-40 reanalysis show a distinct cold and moist bias in the upper troposphere compared to satellite observations, particularly over the subtropics. Temperature biases are a common feature in many climate models and complicate the interpretation of radiance-based comparisons with satellite data. We introduce a new method for evaluating the water vapor distribution which combines both HIRS 6.7 mm and SSM/T-2 183.31 ± 1 GHz channels and is much less sensitive to tropospheric temperature biases. Using this method, we show that GFDL climate model has a more humid upper troposphere over dry subtropical area than ERA-40 reanalysis. The geographical distribution of the humidity bias is found to exhibit a close association with differences in the 500 hPa vertical pressure velocity, suggesting that much of the bias in tropical upper tropospheric relative humidity can be attributed to errors in simulating the intensity of large-scale tropical circulation. Given the strong dependence of upper tropospheric water vapor on the large-scale circulation, these results suggest that long-term monitoring of upper tropospheric water vapor from satellites may also offer insight into variations in the large-scale atmospheric circulation. Citation: Chung, E.-S., B. J. Soden, B.-J. Sohn, and J. Schmetz (2011), Model-simulated humidity bias in the upper troposphere and its relation to the large-scale circulation,
Journal of Geophysical Research, 2012
1] The goal of this study is to determine how H 2 O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H 2 O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity. Citation: Risi, C., et al. (2012), Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations,
RELATIONSHIP BETWEEN MONTHLY MEAN WATER VAPOUR WIND FIELDS AND THE UPPER TROPOSPHERIC HUMIDITY
The paper describes first results of a pilot study investigating the relationship between the monthly mean fields of wind and humidity in the upper troposphere. The wind fields are derived from successive METEOSAT images in the water vapour channel (WV: 5.7 -7.1 μm) and the up-per tropospheric relative humidity (UTH) is inferred from water vapour image data with a physical retrieval scheme. Quantitative information on the large scale circulation in the upper troposphere can be derived from WV wind fields, since the WV wind vectors are numerous enough to provide a dense spatial coverage, and thus clearly depict the atmospheric flow in the upper troposphere. The monthly mean wind field of January 1992 is employed to estimate the large scale divergence; values are within a range of about – 5⋅ 10 –6 s –1 and 5⋅ 10 –6 s –1 for a scale of about 1500 km. The spatial pattern ofthe UTH field closely resembles the divergence of the wind field suggesting that the UTH fields are principally det...
Determination and significance of upper-tropospheric humidity
Atmospheric Chemistry and Physics Discussions, 2018
We present a novel retrieval for upper-tropospheric humidity (UTH) from HIRS channel 12 radiances that successfully bridges the wavelength change from 6.7 to 6.5 µm that occurred from HIRS 2 on NOAA 14 to HIRS 3 on NOAA 15. The jump in average brightness temperature (T 12) that this change caused (about −7 K) could be fixed with a statistical intercalibration method (Shi and Bates, 2011). Unfortunately, the retrieval of UTHi based on the intercalibrated data was not satisfying at the high tail of the distribution of UTHi. Attempts to construct a better intercalibration in the low T 12 range (equivalent to the high UTHi range) were either not successful (Gierens et al., 2018) or required additional statistically determined corrections to the measured brightness temperatures (Gierens and Eleftheratos, 2017). The new method presented here is based on the original one (Soden and Bretherton, 1993; Stephens et al., 1996; Jackson and Bates, 2001), but it extends linearisations in the formulation of water vapour saturation pressure and in the temperature-dependence of the Planck function to second order. To achieve the second-order formulation we derive the retrieval from the beginning, and we find that the most influential ingredient is the use of different optical constants for the two involved channel wavelengths (6.7 and 6.5 µm). The result of adapting the optical constant is an almost perfect match between UTH data measured by HIRS 2 on NOAA 14 and HIRS 3 on NOAA 15 on 1004 common days of operation. The method is applied to both UTH and UTHi, the upper-tropospheric humidity with respect to ice. For each case retrieval coefficients are derived. We present a number of test applications, e.g. on computed brightness temperatures based on high-resolution radiosonde profiles, on the brightness temperatures measured by the satellites on the mentioned 1004 common days of operation. Further we present time series of the occurrence frequency of high UTHi cases and we show the overall probability distribution of UTHi. The two latter applications expose clear indications of moistening of the upper troposphere over the last 35 years. Finally, we discuss the significance of UTH. We state that UTH algorithms cannot be judged for their correctness or incorrectness, since there is no true UTH. Instead, UTH algorithms should fulfill a number of usefulness-postulates, that we suggest and discuss. In the course of this discussion an alternative method to estimate the weighting function is presented.
Upper-tropospheric humidity changes under constant relative humidity
Atmospheric Chemistry and Physics Discussions, 2015
Theoretical derivations are given on the change of upper-tropospheric humidity (UTH) in a warming climate. Considered view is that the atmosphere, getting moister with increasing temperatures, will retain a constant relative humidity. In the present study we show that the upper-tropospheric humidity, a weighted mean over a relative humidity profile, will change in spite of constant relative humidity. The simple reason for this is that the weighting function, that defines UTH, changes in a moister atmosphere. Through analytical calculations using observations and through radiative transfer calculations we demonstrate that two quantities that define the weighting function of UTH can change: the water vapour scale height and the peak emission altitude. Applying these changes to real profiles of relative humidity shows that absolute UTH changes typically do not exceed 1 %. If larger changes would be observed they would be an indication of climatological changes of relative humidity. As ...
Evaluation of model-simulated upper troposphere humidity using 6.7 μm satellite observations
Journal of Geophysical Research, 1997
Use of mesoscale models to simulate details of upper tropospheric relative humidity (UTRH) fields represents an important step toward understanding the evolution of small-scale water vapor structures that are responsible for cirrus growth and dissipation. Because mesoscale model UTRH simulations require initialization and verification and since radiosonde measurements of relative humidity are unreliable in the upper troposphere, we use GOES 6.7 •m water vapor observations to validate the Pennsylvania State University/National Center for Atmospheric Research nonhydrostatic mesoscale model (MM5) simulations of UTRH. To accomplish this task, MM5 temperature and moisture profiles are used in a forward calculation of the clear-sky 6.7 •m brightness temperature (T6.7), which is converted into UTRH. A statistical analysis is done to evaluate MM5 simulations of T6.7 and UTRH against the GOES 7 observations. For the simulations, an average correlation coefficient of 0.80 was found with a dry bias of 1.6 K. In terms of UTRH, the average correlation coefficient was 0.65 with a dry bias of 3.3%. We also found that MM5 fails to simulate accurately extrema in the UTRH field.
Evaluation of model-simulated upper troposphere humidity using 6.7 mum satellite observations
Journal of Geophysical Research, 1997
Use of mesoscale models to simulate details of upper tropospheric relative humidity (UTRH) fields represents an important step toward understanding the evolution of small-scale water vapor structures that are responsible for cirrus growth and dissipation. Because mesoscale model UTRH simulations require initialization and verification and since radiosonde measurements of relative humidity are unreliable in the upper troposphere, we use GOES
Bulletin of the American Meteorological Society, 1995
This paper describes the results from a collaborative study between the European Space Operations Center, the European Organization for the Exploitation of Meteorological Satellites, the National Oceanic and Atmospheric Administration, and the Cooperative Institute for Meteorological Satellite Studies investigating the relationship between satellite-derived monthly mean fields of wind and humidity in the upper troposphere for March 1994. Three geostationary meteorological satellites GOES-7, Meteosat-3, and Meteosat-5 are used to cover an area from roughly 160°W to 50°E. The wind fields are derived from tracking features in successive images of upper-tropospheric water vapor (WV) as depicted in the 6.5-JI absorption band. The upper-tropospheric relative humidity (UTH) is inferred from measured water vapor radiances with a physical retrieval scheme based on radiative forward calculations. Quantitative information on large-scale circulation patterns in the upper troposphere is possible with the dense spatial coverage of the WV wind vectors. The monthly mean wind field is used to estimate the large-scale divergence; values range between about-5 x 10-6 and 5 x 10-6 sec 1 when averaged over a scale length of about 1000-2000 km. The spatial patterns of the UTH field and the divergence of the wind field closely resemble one another, suggesting that UTH patterns are principally determined by the large-scale circulation. Since the upper-tropospheric humidity absorbs upwelling radiation from lower-tropospheric levels and therefore contributes significantly to the atmospheric greenhouse effect, this work implies that studies on the climate relevance of water vapor should include threedimensional modeling of the atmospheric dynamics. The fields of UTH and WV winds are useful parameters for a climate-monitoring system based on satellite data. The results from this 1-month analysis suggest the desirability of further GOES and Meteosat studies to characterize the changes in the upper-tropospheric moisture sources and sinks over the past decade.
Comparing upper tropospheric humidity data from
sat.ltu.se
Atmospheric humidity plays an important role in the Earth's 4 climate. Microwave satellite data provide valuable humidity observations in 5 the upper troposphere with global coverage. In this study, we compare up-6 per tropospheric humidity (UTH) retrieved from the Advanced Microwave 7 Sounding Unit (AMSU-B) and the Microwave Humidity Sounder (MHS) against 8 radiosonde data measured at four of the central facilities of the Atmospheric 9 Radiation Measurement (ARM) program. The Atmospheric Radiative Trans-10 fer Simulator (ARTS) was used to simulate satellite brightness temperatures 11 from the radiosonde profiles. Strong ice clouds were filtered out, as their in-12 fluence on microwave measurements leads to incorrect UTH values. Day and 13