scholarly journals The NPOESS Airborne Sounding Testbed Interferometer—Remotely Sensed Surface and Atmospheric Conditions during CLAMS

2005 ◽  
Vol 62 (4) ◽  
pp. 1118-1134 ◽  
Author(s):  
W. L. Smith ◽  
D. K. Zhou ◽  
A. M. Larar ◽  
S. A. Mango ◽  
H. B. Howell ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Three Dimensional ◽  
Atmospheric Temperature ◽  
Satellite System ◽  
High Spectral Resolution ◽  
Aircraft Measurements ◽  
Atmospheric Conditions ◽  
Infrared Radiance ◽  
Cross Track ◽  
Temperature Water

Abstract During the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS), the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I), flying aboard the high-altitude Proteus aircraft, observed the spatial distribution of infrared radiance across the 650–2700 cm−1 (3.7–15.4 μm) spectral region with a spectral resolution of 0.25 cm−1. NAST-I scans cross track with a moderate spatial resolution (a linear ground resolution equal to 13% of the aircraft altitude at nadir). The broad spectral coverage and high spectral resolution of this instrument provides abundant information about the surface and three-dimensional state of the atmosphere. In this paper, the NAST-I measurements and geophysical product retrieval methodology employed for CLAMS are described. Example results of surface properties and atmospheric temperature, water vapor, ozone, and carbon monoxide distributions are provided. The CLAMS NAST-I geophysical dataset is available for use by the scientific community.

scholarly journals Deriving Atmospheric Temperature of the Tropopause Region–Upper Troposphere by Combining Information from GPS Radio Occultation Refractivity and High-Spectral-Resolution Infrared Radiance Measurements

2008 ◽  
Vol 47 (9) ◽  
pp. 2300-2310 ◽  
Author(s):  
Eva E. Borbas ◽  
W. Paul Menzel ◽  
Elisabeth Weisz ◽  
Dezso Devenyi
Keyword(s):  
Bayesian Estimation ◽  
Spectral Resolution ◽  
Radio Occultation ◽  
Estimation Method ◽  
Principal Component ◽  
Atmospheric Temperature ◽  
High Spectral Resolution ◽  
Statistical Regression ◽  
Infrared Radiance ◽  
Tropopause Region

Abstract Global positioning system radio occultation (GPS/RO) measurements from the Challenging Minisatellite Payload (CHAMP) and Satelite de Aplicaciones Cientificas-C (SAC-C) satellites are used to improve tropospheric profile retrievals derived from the Aqua platform high-spectral-resolution Atmospheric Infrared Sounder (AIRS) and broadband Advanced Microwave Sounding Unit (AMSU) measurements under clear-sky conditions. This paper compares temperature retrievals from combined AIRS, AMSU, and CHAMP/SAC-C measurements using different techniques: 1) a principal component statistical regression using coefficients established between real (and in a few cases calculated) measurements and radiosonde atmospheric profiles; and 2) a Bayesian estimation method applied to AIRS plus AMSU temperature retrievals and GPS/RO temperature profiles. The Bayesian estimation method was also applied to GPS/RO data and the AIRS Science Team operational level-2 (version 4.0) temperature products for comparison. In this study, including GPS/RO data in the tropopause region produces the largest improvement in AIRS–AMSU temperature retrievals—about 0.5 K between 100 and 300 hPa. GPS/RO data are found to provide valuable upper-tropospheric information that improves the profile retrievals from AIRS and AMSU.

scholarly journals Added-value of GEO-hyperspectral Infrared Radiances for Local Severe Storm Forecasts Using the Hybrid OSSE Method

2021 ◽  
Author(s):  
Pei Wang ◽  
Zhenglong Li ◽  
Jun Li ◽  
Timothy J. Schmit
Keyword(s):  
Spectral Resolution ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Added Value ◽  
High Spectral Resolution ◽  
Vertical Resolution ◽  
Severe Storm ◽  
Impact Studies ◽  
High Vertical Resolution ◽  
The Impact

AbstractHigh spectral resolution (or hyperspectral) infrared (IR) sounders onboard low earth orbiting satellites provide high vertical resolution atmospheric information for numerical weather prediction (NWP) models. In contrast, imagers on geostationary (GEO) satellites provide high temporal and spatial resolution which are important for monitoring the moisture associated with severe weather systems, such as rapidly developing local severe storms (LSS). A hyperspectral IR sounder onboard a geostationary satellite would provide four-dimensional atmospheric temperature, moisture, and wind profiles that have both high vertical resolution and high temporal/spatial resolutions. In this work, the added-value from a GEO-hyperspectral IR sounder is studied and discussed using a hybrid Observing System Simulation Experiment (OSSE) method. A hybrid OSSE is distinctively different from the traditional OSSE in that, (a) only future sensors are simulated from the nature run and (b) the forecasts can be evaluated using real observations. This avoids simulating the complicated observation characteristics of the current systems (but not the new proposed system) and allows the impact to be assessed against real observations. The Cross-track Infrared Sounder (CrIS) full spectral resolution (FSR) is assumed to be onboard a GEO for the impact studies, and the GEO CrIS radiances are simulated from the ECMWF Reanalysis v5 (ERA5) with the hyperspectral IR all-sky radiative transfer model (HIRTM). The simulated GEO CrIS radiances are validated and the hybrid OSSE system is verified before the impact assessment. Two LSS cases from 2018 and 2019 are selected to evaluate the value-added impacts from the GEO CrIS-FSR data. The impact studies show improved atmospheric temperature, moisture, and precipitation forecasts, along with some improvements in the wind forecasts. An added-value, consisting of an overall 5% Root Mean Square Error (RMSE) reduction, was found when a GEO CrIS-FSR is used in replacement of LEO ones indicating the potential for applications of data from a GEO hyperspectral IR sounder to improve local severe storm forecasts.

scholarly journals McRALI: a Monte Carlo high-spectral-resolution lidar and Doppler radar simulator for three-dimensional cloudy atmosphere remote sensing

2021 ◽  
Vol 14 (1) ◽  
pp. 199-221
Author(s):  
Frédéric Szczap ◽  
Alaa Alkasem ◽  
Guillaume Mioche ◽  
Valery Shcherbakov ◽  
Céline Cornet ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Multiple Scattering ◽  
Spectral Resolution ◽  
Doppler Radar ◽  
Three Dimensional ◽  
High Spectral Resolution ◽  
Doppler Velocity ◽  
Monte Carlo Code ◽  
Cloudy Atmosphere ◽  
Radar Signals

Abstract. The aim of this paper is to present the Monte Carlo code McRALI that provides simulations under multiple-scattering regimes of polarized high-spectral-resolution (HSR) lidar and Doppler radar observations for a three-dimensional (3D) cloudy atmosphere. The effects of nonuniform beam filling (NUBF) on HSR lidar and Doppler radar signals related to the EarthCARE mission are investigated with the help of an academic 3D box cloud characterized by a single isolated jump in cloud optical depth, assuming vertically constant wind velocity. Regarding Doppler radar signals, it is confirmed that NUBF induces a severe bias in velocity estimates. The correlation of the NUBF bias of Doppler velocity with the horizontal gradient of reflectivity shows a correlation coefficient value around 0.15 m s−1 (dBZ km-1)-1, close to that given in the scientific literature. Regarding HSR lidar signals, we confirm that multiple-scattering processes are not negligible. We show that NUBF effects on molecular, particulate, and total attenuated backscatter are mainly due to unresolved variability of cloud inside the receiver field of view and, to a lesser extent, to the horizontal photon transport. This finding gives some insight into the reliability of lidar signal modeling using independent column approximation (ICA).

Detection of atmospheric temperature by using polarization high-spectral-resolution lidar

2021 ◽  
Vol 60 (8) ◽  
pp. 2109
Author(s):  
Jun Wang ◽  
Jingzhe Pang ◽  
Ning Chen ◽  
Wanlin Zhang ◽  
Jingjing Liu ◽  
...  
Keyword(s):  
Spectral Resolution ◽  
Atmospheric Temperature ◽  
High Spectral Resolution ◽  
High Spectral Resolution Lidar

scholarly journals High spectral resolution lidar at the university of wisconsin-madison

2018 ◽  
Vol 176 ◽  
pp. 01024
Author(s):  
Ilya I. Razenkov ◽  
Edwin W. Eloranta
Keyword(s):  
Spectral Resolution ◽  
Atmospheric Temperature ◽  
High Spectral Resolution ◽  
Science And Engineering ◽  
Extinction Cross Section ◽  
University Of Wisconsin ◽  
Atmospheric Temperature Profile ◽  
Field Campaigns ◽  
The University ◽  
High Spectral Resolution Lidar

This paper describes the modifications done on the University of Wisconsin-Madison High Spectral Resolution Lidar (HSRL) that improved the instrument’s performance. The University of Wisconsin HSRL lidars designed by our group at the Space Science and Engineering Center were deployed in numerous field campaigns in various locations around the world. Over the years the instruments have undergone multiple modifications that improved the performance and added new measurement capabilities such as atmospheric temperature profile and extinction cross-section measurements.

scholarly journals Advances in atmospheric temperature profile measurements using high spectral resolution lidar

2018 ◽  
Vol 176 ◽  
pp. 01023
Author(s):  
Ilya I. Razenkov ◽  
Edwin W. Eloranta
Keyword(s):  
Temperature Profile ◽  
Spectral Resolution ◽  
Atmospheric Temperature ◽  
High Spectral Resolution ◽  
Absolute Calibration ◽  
Temperature Sensitive ◽  
Backscatter Coefficient ◽  
Rayleigh Backscattering ◽  
Atmospheric Temperature Profile ◽  
High Spectral Resolution Lidar

This paper reports the atmospheric temperature profile measurements using a University of Wisconsin-Madison High Spectral Resolution Lidar (HSRL) and describes improvements in the instrument performance. HSRL discriminates between Mie and Rayleigh backscattering [1]. Thermal motion of molecules broadens the spectrum of the transmitted laser light due to Doppler effect. The HSRL exploits this property to allow the absolute calibration of the lidar and measurements of the aerosol volume backscatter coefficient. Two iodine absorption filters with different line widths are used to resolve temperature sensitive changes in Rayleigh backscattering for atmospheric temperature profile measurements.

scholarly journals Minimum Local Emissivity Variance Retrieval of Cloud Altitude and Effective Spectral Emissivity—Simulation and Initial Verification

2004 ◽  
Vol 43 (5) ◽  
pp. 795-809 ◽  
Author(s):  
Hung-Lung Huang ◽  
William L. Smith ◽  
Jun Li ◽  
Paolo Antonelli ◽  
Xiangqian Wu ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Spectral Resolution ◽  
Single Layer ◽  
Spectral Emissivity ◽  
Pressure Level ◽  
High Spectral Resolution ◽  
Mean Square ◽  
Atmospheric Conditions ◽  
Wide Range ◽  
Mean Square Errors

Abstract This paper describes the theory and application of the minimum local emissivity variance (MLEV) technique for simultaneous retrieval of cloud pressure level and effective spectral emissivity from high-spectral-resolution radiances, for the case of single-layer clouds. This technique, which has become feasible only with the recent development of high-spectral-resolution satellite and airborne instruments, is shown to provide reliable cloud spectral emissivity and pressure level under a wide range of atmospheric conditions. The MLEV algorithm uses a physical approach in which the local variances of spectral cloud emissivity are calculated for a number of assumed or first-guess cloud pressure levels. The optimal solution for the single-layer cloud emissivity spectrum is that having the “minimum local emissivity variance” among the retrieved emissivity spectra associated with different first-guess cloud pressure levels. This is due to the fact that the absorption, reflection, and scattering processes of clouds exhibit relatively limited localized spectral emissivity structure in the infrared 10–15-μm longwave region. In this simulation study it is shown that the MLEV cloud pressure root-mean-square errors for a single level with effective cloud emissivity greater than 0.1 are ∼30, ∼10, and ∼50 hPa, for high (200– 300 hPa), middle (500 hPa), and low (850 hPa) clouds, respectively. The associated cloud emissivity root-mean-square errors in the 900 cm−1 spectral channel are less than 0.05, 0.04, and 0.25 for high, middle, and low clouds, respectively.

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