Deep Retrieval Architecture of Temperature and Humidity Profiles from Ground-Based Infrared Hyperspectral Spectrometer
نویسندگان
چکیده
Temperature and humidity profiles in the atmospheric boundary layer are essential for climate studies. The ground-based infrared hyperspectral spectrometer has advantage of measuring radiances emitted from atmosphere at a high temporal moderate vertical resolution. In this article, retrieval temperature observations is exploited. Although existing inversion algorithms based on physical models or statistical learning have made some progress, they still suffer computational complexity poor performance. Motivated by strength deep learning, we present architecture (DReA) skillfully designing light-weight one-dimensional convolution neural network (CNN) to retrieve profiles. Experiments were conducted using radiance interferometer (AERI) radiosonde data demonstrate superiority proposed DReA. validation DReA with radiosonde, 802 37 layers below 3 km, presents an excellent ability root mean square error (RMSE) 0.87 K 1.06 g/kg water vapor mixing ratio. Furthermore, thorough comparison commonly used methods such as traditional back propagation (BP) eigenvector (EV) regression method, shows that our method obtains leading solution retrieving
منابع مشابه
Tropospheric ozone profiles from a ground-based ultraviolet spectrometer: a new retrieval method.
We present, to the best of our knowledge, a new method to retrieve tropospheric ozone (O3) profiles from ground-based ultraviolet spectroscopic measurements. This method utilizes radiance spectra in the Huggins bands (i.e., 300-340 nm) measured at three off-axis angles (e.g., 45 degrees, 75 degrees, and 85 degrees) normalized to direct-Sun irradiances or zenith-sky radiances with the total colu...
متن کاملA New Retrieval Method for Tropospheric Ozone Profiles from a Ground-based Ultraviolet Spectrometer
متن کامل
Cloud Detection, Temperature and Water Vapor Retrieval from Hyperspectral Infrared Sounder Observations
New generation meteorological satellites carry infrared sensors able to sense the earth emission spectrum at very high spectral resolution. The related problems of cloud detection and inversion for geophysical parameters are addressed in this paper. © 2005 Optical Society of America OCIS codes: (010.3920) Meteorology; (010.7030) Troposphere
متن کاملLand Surface Temperature and Emissivity Retrieval from Field-Measured Hyperspectral Thermal Infrared Data Using Wavelet Transform
Currently, the main difficulty in separating the land surface temperature (LST) and land surface emissivity (LSE) from field-measured hyperspectral Thermal Infrared (TIR) data lies in solving the radiative transfer equation (RTE). Based on the theory of wavelet transform (WT), this paper proposes a method for accurately and effectively separating LSTs and LSEs from field-measured hyperspectral ...
متن کاملFunctional Modeling of Iranian Precipitation Based on Temperature and Humidity
Functional Data Analysis (FDA) has recently made considerable progress because of easier access to the data that are essentially in the form of curves. Modeling of Iranian precipitation based on temperature and humidity with continuous the essential nature of such phenomena that are continuous functions of time has not been done properly. The corresponding data are generally collected daily or ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Remote Sensing
سال: 2023
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs15092320