DETERMINATION OF GASEOUS COMPOSITION IN THE MIDDLE ATMOSPHERE BY USING HIGH SPECTRAL RESOLUTION METHODS

One of the crucial problems in study on the middle atmosphere is to determine the concentration and distribution of some trace gases.In this aspect,sounding methods with high spectral resolution have been developed by many scientists.Some major trace gases and their spectral characteristics,space-borne limb method for determination of trace gases in the middle atmosphere are introduced,requirements for used methods and instruments,development and challenge encountered by sounding of trace gases with high spectral resolution are discussed in this paper.

Luojia-HSSR:A high spatial-spectral resolution remote sensing dataset for land-cover classification with a new 3D-HRNet

High Spatial and Spectral Resolution(HSSR)remote-sensing images can provide rich spectral bands and detailed ground information,but there is a relative lack of research on this new type of remote-sensing data.Although there are already some HSSR datasets for deep learning model training and testing,the data volume of these datasets is small,resulting in low classification accuracy and weak generalization ability of the trained models.In this paper,an HSSR dataset Luojia-HSSR is constructed based on aerial hyperspectral imagery of southern Shenyang City of Liaoning Province in China.To our knowledge,it is the largest HSSR dataset to date,with 6438 pairs of 256×256 sized samples(including 3480 pairs in the training set,2209 pairs in the test set,and 749 pairs in the validation set),covering area of 161 km2 with spatial resolution 0.75 m,249 Visible and Near-Infrared(VNIR)spectral bands,and corresponding to 23 classes of field-validated ground coverage.It is an ideal experimental data for spatial-spectral feature extraction.Furthermore,a new deep learning model 3D-HRNet for interpreting HSSR images is proposed.The conv-neck in HRNet is modified to better mine the spatial information of the images.Then,a 3D convolution module with attention mechanism is designed to capture the global-local fine spectral information simultaneously.Subsequently,the 3D convolution is inserted into the HRNet to optimize the performance.The experiments show that the 3D-HRNet model has good interpreting ability for the Luojia-HSSR dataset with the Frequency Weighted Intersection over Union(FWIoU)reaching 80.54%,indicating that the Luojia-HSSR dataset constructed in this paper and the proposed 3D-HRnet model have good applicable prospects for processing HSSR remote sensing images.

High resolution full-spectrum water Raman lidar

Knowledge of the temporal-spatial distribution of water content in atmosphere and water phase change in cloud is important for atmospheric study. For this purpose, we have developed a high resolution full-spectrum water Raman lidar that can collect Raman signals from ice, water droplets and water vapor simultaneously. A double-grating polychromator and a 32-channel photomultiplier-tube detector are used to obtain a spectral resolution of-0.19 nm in the full Raman spectrum range of water, Preliminary observations present the water Raman spectrum characteristics of both the mixed-phase cloud and humid air under cloudless condition.

NASA’s Mission ACTIVATE: Objectives, Strategies, and Limitations

The primary goal of this report is to describe the operational concepts of NASA’s ACTIVATE mission. ACTIVATE hopes to improve the understanding of aerosol dispersion and models, provide accurate data for aerosols’ characterization and ozone profiles, and establish knowledge of the relationships between aerosols and water. ACTIVATE’s science objectives are to quantify Na-CCN-Nd relationships and reduce uncertainty in model cloud droplet activation parameterizations, improve process-level understanding and model representation of factors governing cloud micro/macro-physical properties and how they couple with cloud effects on aerosol, plus assess advanced remote sensing capabilities for retrieving aerosol and cloud properties related to aerosol-cloud interactions. ACTIVATE utilizes the fixed-wing B-200 King Air to collect data. Data collected by ACTIVATE is highly relevant for meteorologists and environmental scientists looking to understand more about aerosol-cloud formations. Finally, ACTIVATE is a 5-year mission spanning from January 2019 to December 2023 and has used, and will continue to use, instruments such as the High Spectral Resolution Lidar-2 (HSRL-2), the Research Scanning Polarimeter (RSP), and the Diode Laser Hygrometer (DLH).

Rapid discovery and identification of 68 compounds in the active fraction from Xiao-Xu-Ming decoction(XXMD) by HPLC-HRMS and MTSF technique

Xiao-Xu-Ming decoction（XXMD） was a traditional Chinese prescription and first recorded in ＂Bei Ji Qian Jin Yao Fang＂.It has been widely used to treat theoplegia and the sequel of theoplegia in China.In the present work,high-performance liquid chromatography coupled with high resolution mass spectrometry（HPLC-HRMS） combined with the mass spectral tree similarity filter technique（MTSF）was used to rapidly discover and identify the compounds of the active fraction of XXMD.A total of 3362 compounds were automatically detected by HPLC-HRMS,and final 68 compounds were identified in the active fraction of XXMD.including 14 templated compounds（reference compounds）,50 related compounds fished by MTSF technique,and 4 unrelated compounds identified by manual method.This study successfully applied MTSF technology for the first time to discover and identify the components of Chinese prescription.The results demonstrated that MTSF technique should be useful to the discovery and identification of compounds in Chinese prescription.This study also proved that MTSF can be applied to the targeted phytochemical separation.