Early Results from the RELAMPAGO Lightning Mapping Array
American Geophysical Union (AGU) Fall Meeting（2018）
Marshall Space Flight Center
Abstract
In austral spring of 2018, an 11station NASA lightning mapping array (LMA) will be installed in the Cordoba region of Argentina, in support of GOES16/ 17 Geostationary Lightning Mapper (GLM) calibration and validation, as well as the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. This region of Argentina is well known for frequent, intense thunderstorms and severe weather. Lightning observations in storms that initiate, become severe, and grow upscale are expected to be obtained by GLM and the LMA during the LMA’s multimonth deployment. We hypothesize that, similar to the analogous U.S. High Plains, anomalously charged thunderstorms with frequent inverted lightning at low levels are common in this region, which may have implications for GLM detection efficiency. Deployment logistics and experimental approach will be explained, and some early results from the LMA (including comparison to GLM) will be presented.
MoreTranslated text
求助PDF
上传PDF
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined