scholarly journals Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

2018 ◽  
Vol 11 (2) ◽  
pp. 971-995 ◽  
Author(s):  
Fredrick W. Irion ◽  
Brian H. Kahn ◽  
Mathias M. Schreier ◽  
Eric J. Fetzer ◽  
Evan Fishbein ◽  
...  
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Optimal Estimation ◽  
Atmospheric Temperature ◽  
Horizontal Resolution ◽  
Forward Model ◽  
Retrieval Algorithm ◽  
Cloud Particle ◽  
Cloud Data ◽  
Temperature Water

Abstract. Single-footprint Atmospheric Infrared Sounder spectra are used in an optimal estimation-based algorithm (AIRS-OE) for simultaneous retrieval of atmospheric temperature, water vapor, surface temperature, cloud-top temperature, effective cloud optical depth and effective cloud particle radius. In a departure from currently operational AIRS retrievals (AIRS V6), cloud scattering and absorption are in the radiative transfer forward model and AIRS single-footprint thermal infrared data are used directly rather than cloud-cleared spectra (which are calculated using nine adjacent AIRS infrared footprints). Coincident MODIS cloud data are used for cloud a priori data. Using single-footprint spectra improves the horizontal resolution of the AIRS retrieval from  ∼  45 to  ∼  13.5 km at nadir, but as microwave data are not used, the retrieval is not made at altitudes below thick clouds. An outline of the AIRS-OE retrieval procedure and information content analysis is presented. Initial comparisons of AIRS-OE to AIRS V6 results show increased horizontal detail in the water vapor and relative humidity fields in the free troposphere above the clouds. Initial comparisons of temperature, water vapor and relative humidity profiles with coincident radiosondes show good agreement. Future improvements to the retrieval algorithm, and to the forward model in particular, are discussed.

scholarly journals Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

2017 ◽  
Author(s):  
Fredrick W. Irion ◽  
Brian H. Kahn ◽  
Mathias M. Schreier ◽  
Eric J. Fetzer ◽  
Evan Fishbein ◽  
...  
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Optimal Estimation ◽  
Horizontal Resolution ◽  
Forward Model ◽  
Retrieval Algorithm ◽  
Cloud Particle ◽  
Cloud Data ◽  
Level 2 ◽  
Temperature Water

Abstract. Single-footprint Atmospheric Infrared Sounder spectra are used in an optimal estimation-based algorithm (AIRS-OE) for simultaneous retrieval of atmospheric temperature, water vapor, surface temperature, cloud-top temperature, effective cloud optical depth and effective cloud particle radius. In a departure from currently operational AIRS retrievals (AIRS-V6), cloud scattering and absorption are in the radiative transfer forward model, and Level 1b AIRS thermal infrared data are used directly rather than Level 2 cloud-cleared spectra. Coincident MODIS Level 2 cloud data are used for cloud a priori. Using Level 1b spectra improves the horizontal resolution of the AIRS retrieval from ~ 45 km to ~ 13.5 km at nadir, but as microwave data are not used, retrieval is not made at altitudes below thick clouds. An outline of the AIRS-OE retrieval procedure and information content analysis is presented. Initial comparison of AIRS-OE to AIRS-V6 results show increased horizontal detail in the water vapor and relative humidity fields in the free troposphere above clouds. Comparisions of temperature, water vapor and relative humidity profiles against coincident radiosondes show good agreement. Future improvements to the retrieval algorithm, and to the forward model in particular, are discussed.

Influence of Temperature and Relative Humidity on Perm-Selectivity of PET Packaging Film

2011 ◽  
Vol 295-297 ◽  
pp. 1206-1210
Author(s):  
Yan Feng Guo ◽  
Xian Ping Ma ◽  
Yu Yan ◽  
Yun Gang Fu
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Experimental Studies ◽  
Thermodynamic Temperature ◽  
Packaging Film ◽  
Influence Of Temperature ◽  
Carbon Dioxide Gas ◽  
Pet Film ◽  
Pet Films ◽  
Temperature Water

The main feature of this article is the investigation on the influence of temperature, relative humidity, film thickness on permeability of PET packaging film, the analysis of perm-selectivity of the packaging films for oxygen gas and carbon dioxide gas, and the evaluation on experimental formulas of water vapor, O2 and CO2 gas permeating rates on the basis of gas molecular osmotic reaction kinetics and regression analysis. The comparison between experimental studies and calculation indicates that: (1) with increment of ambient temperature water vapor, O2 and CO2 permeating rate of PET films and PET/Al film also rise, and the logarithm of water vapor, O2 and CO2 gas permeating rates has linear relation with the reciprocal of thermodynamic temperature, and (2) the influence of relative humidity on water vapor permeating rate of PET film with thickness 12µm is the least, and that of PET film with thickness 20µm and PET/Al film with thickness 18µm is a little obvious. (3) The PET films hold remarkable perm-selectivity for O2 and CO2 gas, and CO2 gas permeating rate is about two times of O2 gas, yet O2 and CO2 gas permeating rates of PET/Al film are both very low and have small difference, so the PET/Al film has better barrier performance than the PET film.

Combined Raman lidar for the measurement of atmospheric temperature, water vapor, particle extinction coefficient, and particle backscatter coefficient

2002 ◽  
Vol 41 (36) ◽  
pp. 7657 ◽  
Author(s):  
Andreas Behrendt ◽  
Takuji Nakamura ◽  
Michitaka Onishi ◽  
Rudolf Baumgart ◽  
Toshitaka Tsuda
Keyword(s):  
Water Vapor ◽  
Extinction Coefficient ◽  
Atmospheric Temperature ◽  
Raman Lidar ◽  
Backscatter Coefficient ◽  
Temperature Water

scholarly journals Multiparameter Raman Lidar Measurements for the Characterization of a Dry Stratospheric Intrusion Event

2009 ◽  
Vol 26 (9) ◽  
pp. 1742-1762 ◽  
Author(s):  
Paolo Di Girolamo ◽  
Donato Summa ◽  
Rossella Ferretti
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Relative Humidity ◽  
Potential Temperature ◽  
Atmospheric Temperature ◽  
Deep Penetration ◽  
Raman Lidar ◽  
Dry Air ◽  
Stratospheric Intrusion ◽  
Lidar Measurements

Abstract The University of Basilicata Raman lidar system (BASIL) is operational in Potenza, Italy, and it is capable of performing high-resolution and accurate measurements of atmospheric temperature and water vapor based on the application of the rotational and vibrational Raman lidar techniques in the ultraviolet region. BASIL was recently involved in the 2005 International Lindenberg campaign for Assessment of Humidity and Cloud Profiling Systems and Its Impact on High-Resolution Modeling (LAUNCH 2005) experiment held from 12 September to 31 October 2005. A thorough description of the technical characteristics, measurement capabilities, and performances of BASIL is given in this paper. Measurements were continuously run between 1 and 3 October 2005, covering a dry stratospheric intrusion episode associated with a tropopause folding event. The measurements in this paper represent the first simultaneous Raman lidar measurements of atmospheric temperature, water vapor mixing ratio, and thus relative humidity reported for an extensive observation period (32 h). The use of water vapor to trace intruded stratospheric air allows the clear identification of a dry structure (∼1 km thick) originating in the stratosphere and descending in the free troposphere down to ∼3 km. A similar feature is present in the temperature field, with lower temperature values detected within the dry-air tongue. Relative humidity measurements reveal values as small as 0.5%–1% within the intruded air. The stratospheric origin of the observed dry layer has been verified by the application of a Lagrangian trajectory model. The subsidence of the intruding heavy dry air may be responsible for the gravity wave activity observed beneath the dry layer. Lidar measurements have been compared with the output of both the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) and the European Centre for Medium-Range Weather Forecasts (ECMWF) global model. Comparisons in terms of water vapor reveal the capability of MM5 to reproduce the dynamical structures associated with the stratospheric intrusion episode and to simulate the deep penetration into the troposphere of the dry intruded layer. Moreover, lidar measurements of potential temperature are compared with MM5 output, whereas potential vorticities from both the ECMWF model and MM5 are compared with estimates obtained combining MM5 model vorticity and lidar measurements of potential temperature.

scholarly journals Radiometrically Consistent Climate Fingerprinting Using CrIS and AIRS Hyperspectral Observations

2020 ◽  
Vol 12 (8) ◽  
pp. 1291
Author(s):  
Wan Wu ◽  
Xu Liu ◽  
Qiguang Yang ◽  
Daniel K. Zhou ◽  
Allen M. Larar
Keyword(s):  
Water Vapor ◽  
Atmospheric Temperature ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Climate Data ◽  
Fingerprinting Method ◽  
Level 2

We introduce a novel spectral fingerprinting scheme that can be used to derive long-term atmospheric temperature and water vapor anomalies from hyperspectral infrared sounders such as Cross-track Infrared Sounder (CrIS) and Atmospheric Infrared Sounder (AIRS). It is a challenging task to derive climate trends from real satellite observations due to the difficulty of carrying out accurate cloudy radiance simulations and constructing radiometrically consistent radiative kernels. To address these issues, we use a principal component based radiative transfer model (PCRTM) to perform multiple scattering calculations of clouds and a PCRTM-based physical retrieval algorithm to derive radiometrically consistent radiative kernels from real satellite observations. The capability of including the cloud scattering calculations in the retrieval process allows the establishment of a rigorous radiometric fitting to satellite-observed radiances under all-sky conditions. The fingerprinting solution is directly obtained via an inverse relationship between the atmospheric anomalies and the corresponding spatiotemporally averaged radiance anomalies. Since there is no need to perform Level 2 retrievals on each individual satellite footprint for the fingerprinting approach, it is much more computationally efficient than the traditional way of producing climate data records from spatiotemporally averaged Level 2 products. We have applied the spectral fingerprinting method to six years of CrIS and 16 years of AIRS data to derive long-term anomaly time series for atmospheric temperature and water vapor profiles. The CrIS and AIRS temperature and water vapor anomalies derived from our spectral fingerprinting method have been validated using results from the PCRTM-based physical retrieval algorithm and the AIRS operational retrieval algorithm, respectively.

scholarly journals Residual Temperature Bias Effects in LIMS Stratospheric Ozone and Water Vapor

2020 ◽  
Author(s):  
Ellis Remsberg ◽  
V. Lynn Harvey ◽  
Arlin Krueger ◽  
Murali Natarajan
Keyword(s):  
Water Vapor ◽  
Science Studies ◽  
Stratospheric Ozone ◽  
Atmospheric Temperature ◽  
Diurnal Variations ◽  
Retrieval Algorithm ◽  
Temperature Bias ◽  
Broadband Emission ◽  
Level 3 ◽  
Hemisphere Winter

Abstract. The Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) instrument operated from October 25, 1978, through May 28, 1979. Its Version (V6) profiles were processed and archived in 2002. We present several diagnostic examples of the quality of the V6 stratospheric ozone and water vapor data based on their Level 3 zonal Fourier coefficient products. In particular, we show that there are small differences in the ascending (A) minus descending (D) orbital temperature-pressure or T(p) profiles (their A-D values) that affect (A-D) ozone and water vapor. Systematic A-D biases in T(p) can arise from small radiance biases and/or from viewing anomalies along orbits. There can also be (A-D) differences in T(p) due to not resolving and correcting for all of the atmospheric temperature gradient along LIMS tangent view-paths. An error in T(p) affects the retrievals of ozone and water vapor through: (1) the Planck blackbody function in forward calculations of limb radiance that are part of the iterative retrieval algorithm of LIMS, and (2) the registration of the measured LIMS species radiance profiles in pressure-altitude, particularly for the lower stratosphere. We evaluate V6 ozone profile biases in the upper stratosphere with the aid of comparisons against a monthly climatology of UV-ozone soundings from rocketsondes. We also provide results of time series analyses of V6 ozone, water vapor, and potential vorticity for the middle stratosphere to show that their average (A+D) V6 Level 3 products provide a clear picture of the evolution of those tracers during northern hemisphere winter. We recommend that researchers use the average V6 Level 3 data for their science studies of stratospheric ozone and water vapor wherever diurnal variations of them are unexpected. We also point out that the present-day Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) experiment is providing measurements and retrievals of temperature and ozone, which are essentially free of any anomalous diurnal variations.

scholarly journals An Optimal Estimation Retrieval Algorithm for Microwave Humidity Sounding Channels with Minimal Scan Position Bias

2019 ◽  
Vol 36 (3) ◽  
pp. 409-425 ◽  
Author(s):  
Richard M. Schulte ◽  
Christian D. Kummerow
Keyword(s):  
Incidence Angle ◽  
Optimal Estimation ◽  
Precipitable Water ◽  
Forward Model ◽  
Retrieval Algorithm ◽  
Model Errors ◽  
Inversion Algorithm ◽  
Liquid Water Path ◽  
Small Satellites ◽  
Cloud Liquid Water Path

AbstractA flexible and physical optimal estimation-based inversion algorithm for retrieving atmospheric water vapor and cloud liquid water path from passive microwave radiometers over the global oceans is presented. The algorithm’s main strength lies in its ability to explicitly account for forward model errors that depend on the Earth incidence angle (EIA) at which a given radiometer measurement is made. Validation of total precipitable water (TPW) retrieved from Microwave Humidity Sounder (MHS) measurements against near-coincident estimates of TPW from SuomiNet GPS ground stations shows that retrieved TPW values agree closely with SuomiNet estimates, and somewhat better than values from the Microwave Integrated Retrieval System that are retrieved from the same MHS instruments. More importantly, it is found that the inclusion of appropriate forward model error assumptions, which are tailored to the EIA and sea surface temperature of the scene being considered, are able to almost entirely eliminate EIA-dependent biases in retrieved TPW. This result holds true across all satellites currently carrying an MHS instrument, despite the fact that only measurements from one satellite are used to estimate forward model errors. The consistency achieved by the retrieval algorithm across all view angles suggests that other inversion algorithms, particularly those for cross-track-scanning radiometers and potential future constellations of small satellites, would benefit from the inclusion of nuanced error assumptions that consider the effect of EIA.

Information Content and Uncertainties in Thermodynamic Profiles and Liquid Cloud Properties Retrieved from the Ground-Based Atmospheric Emitted Radiance Interferometer (AERI)

2014 ◽  
Vol 53 (3) ◽  
pp. 752-771 ◽  
Author(s):  
D. D. Turner ◽  
U. Löhnert
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
Retrieval Algorithm ◽  
Electromagnetic Spectrum ◽  
Slight Reduction ◽  
Liquid Water Path ◽  
Cloud Properties ◽  
Mean Square Errors

AbstractThe Atmospheric Emitted Radiance Interferometer (AERI) observes spectrally resolved downwelling radiance emitted by the atmosphere in the infrared portion of the electromagnetic spectrum. Profiles of temperature and water vapor, and cloud liquid water path and effective radius for a single liquid cloud layer, are retrieved using an optimal estimation–based physical retrieval algorithm from AERI-observed radiance data. This algorithm provides a full error covariance matrix for the solution, and both the degrees of freedom for signal and the Shannon information content. The algorithm is evaluated with both synthetic and real AERI observations. The AERI is shown to have approximately 85% and 70% of its information in the lowest 2 km of the atmosphere for temperature and water vapor profiles, respectively. In clear-sky situations, the mean bias errors with respect to the radiosonde profiles are less than 0.2 K and 0.3 g kg−1 for heights below 2 km for temperature and water vapor mixing ratio, respectively; the maximum root-mean-square errors are less than 1 K and 0.8 g kg−1. The errors in the retrieved profiles in cloudy situations are larger, due in part to the scattering contribution to the downwelling radiance that was not accounted for in the forward model. Scattering is largest in one of the spectral regions used in the retrieval, however, and removing this spectral region results in a slight reduction of the information content but a considerable improvement in the accuracy of the retrieved thermodynamic profiles.

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