Radiative Transfer Modeling for Cobop

1997 ◽  
Author(s):  
Curtis D. Mobley
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Modeling

scholarly journals Microwave temperature and pressure measurements with the Odin satellite: I. Observational method

2002 ◽  
Vol 80 (4) ◽  
pp. 443-454 ◽  
Author(s):  
J R Pardo ◽  
M Ridal ◽  
D Murtagh ◽  
J Cernicharo
Keyword(s):  
Radiative Transfer ◽  
Outer Space ◽  
Atmospheric Temperature ◽  
Upper Atmosphere ◽  
Operational Mode ◽  
Altitude Range ◽  
Molecular Lines ◽  
Temperature And Pressure ◽  
Radiative Transfer Modeling ◽  
Temperature Vertical Profile

The Odin satellite is equipped with millimetre and sub-millimetre receivers for observations of several molecular lines in the middle and upper atmosphere of our planet (~25–100 km, the particular altitude range depending on the species) for studies in dynamics, chemistry, and energy transfer in these regions. The same receivers are also used to observe molecules in outer space, this being the astrophysical share of the project. Among the atmospheric lines that can be observed, we find two corresponding to molecular oxygen (118.75 GHz and 487.25 GHz). These lines can be used for retrievals of the atmospheric temperature vertical profile. In this paper, we describe the radiative-transfer modeling for O2 in the middle and upper atmosphere that we will use as a basis for the retrieval algorithms. Two different observation modes have been planned for Odin, the three-channel operational mode and a high-resolution mode. The first one will determine the temperature and pressure on an operational basis using the oxygen line at 118.75 GHz, while the latter can be used for measurements of both O2 lines, during a small fraction of the total available time for aeronomy, aimed at checking the particular details of the radiative transfer near O2 lines at very high altitudes (>70 km). The Odin temperature measurements are expected to cover the altitude range ~30–90 km. PACS Nos.: 07.57Mj, 94.10Dy, 95.75Rs

Retrieval of Cloud Optical Depth: Synergies between Whole Sky Imagers and Radiative Transfer Modeling.

2021 ◽  
Author(s):  
Caterina Peris-Ferrús ◽  
José Luís Gómez-Amo ◽  
Francesco Scarlatti ◽  
Roberto Román ◽  
Claudia Emde ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Optical Depth ◽  
Cloud Optical Depth ◽  
Radiative Transfer Modeling

scholarly journals High-resolution near-infrared speckle interferometry and radiative transfer modeling of the OH/IR star OH 104.9+2.4

2004 ◽  
Vol 424 (1) ◽  
pp. 165-177 ◽  
Author(s):  
D. Riechers ◽  
Y. Balega ◽  
T. Driebe ◽  
K.-H. Hofmann ◽  
A. B. Men'shchikov ◽  
...  
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Near Infrared ◽  
Speckle Interferometry ◽  
Radiative Transfer Modeling

scholarly journals Applications of the Advanced Radiative Transfer Modeling System (ARMS) to Characterize the Performance of Fengyun–4A/AGRI

2021 ◽  
Vol 13 (16) ◽  
pp. 3120
Author(s):  
Fei Tang ◽  
Xiaoyong Zhuge ◽  
Mingjian Zeng ◽  
Xin Li ◽  
Peiming Dong ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Strong Dependence ◽  
Final Analysis ◽  
Analysis Data ◽  
Water Vapor Absorption ◽  
Absorption Bands ◽  
Geostationary Meteorological Satellite ◽  
Environmental Prediction ◽  
Radiative Transfer Modeling ◽  
Ir Bands

This study applies the Advanced Radiative Transfer Modeling System (ARMS), which was developed to accelerate the uses of Fengyun satellite data in weather, climate, and environmental applications in China, to characterize the biases of seven infrared (IR) bands of the Advanced Geosynchronous Radiation Imager (AGRI) onboard the Chinese geostationary meteorological satellite, Fengyun–4A. The AGRI data are quality controlled to eliminate the observations affected by clouds and contaminated by stray lights during the mid–night from 1600 to 1800 UTC during spring and autumn. The mean biases, computed from AGRI IR observations and ARMS simulations from the National Center for Environmental Prediction (NCEP) Final analysis data (FNL) as input, are within −0.7–1.1 K (0.12–0.75 K) for all seven IR bands over the oceans (land) under clear–sky conditions. The biases show seasonal variation in spatial distributions at bands 11–13, as well as a strong dependence on scene temperatures at bands 8–14 and on satellite zenith angles at absorption bands 9, 10, and 14. The discrepancies between biases estimated using FNL and the European Center for Medium–Range Weather Forecasts Reanalysis–5 (ERA5) are also discussed. The biases from water vapor absorption bands 9 and 10, estimated using ERA5 over ocean, are smaller than those from FNL. Such discrepancies arise from the fact that the FNL data are colder (wetter) than the ERA5 in the middle troposphere (upper–troposphere).

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