Thông tin tài liệu


Nhan đề : 
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations
Tác giả : 
Jure, Brence
Jovan, Tanevski
Jennifer, Adams
Năm xuất bản : 
2023
Nhà xuất bản : 
Springer
Tóm tắt : 
Inversion of radiative transfer models (RTMs) is key to interpreting satellite observations of air quality and greenhouse gases, but is computationally expensive. Surrogate models that emulate the full forward physical RTM can speed up the simulation, reducing computational and timing costs and allowing the use of more advanced physics for trace gas retrievals. In this study, we present the development of surrogate models for two RTMs: the RemoTeC algorithm using the LINTRAN RTM and the SCIATRAN RTM. We estimate the intrinsic dimensionality of the input and output spaces and embed them in lower dimensional subspaces to facilitate the learning task. Two methods are tested for dimensionality reduction, autoencoders and principle component analysis (PCA), with PCA consistently outperforming autoencoders.
Mô tả: 
CC BY
URI: 
https://link.springer.com/article/10.1007/s10994-022-06155-2
https://dlib.phenikaa-uni.edu.vn/handle/PNK/7363
Bộ sưu tập
OER - Công nghệ thông tin
XEM MÔ TẢ

35

XEM TOÀN VĂN

82

Danh sách tệp tin đính kèm: