Chrome Extension
WeChat Mini Program
Use on ChatGLM

Influence of Continental Atmospheric Forcing on the Decadal Variability of the West African Monsoon

Adjoua Moïse Landry Famien, Sandrine Djakouré, Bi Tra Jean Claude Youan,Serge Janicot,Abé Delfin Ochou, Arona Diedhiou

Atmospheric and Climate Sciences(2024)

Cited 0|Views4
Abstract
The West African Monsoon (WAM) is characterized by strong decadal and multi-decadal variability and the impacts can be catastrophic for the local populations. One of the factors put forward to explain this variability involves the role of atmospheric dynamics, linked in particular to the Saharan Heat Low (SHL). This article addresses this question by comparing the sets of preindustrial control and historical simulation data from climate models carried out in the framework of the CMIP5 project and observations data over the 20th century. Through multivariate statistical analyses, it was established that decadal modes of ocean variability and decadal variability of Saharan atmospheric dynamics significantly influence decadal variability of monsoon precipitation. These results also suggest the existence of external anthropogenic forcing, which is superimposed on the decadal natural variability inducing an intensification of the signal in the historical simulations compared to preindustrial control simulations. We have also shown that decadal rainfall variability in the Sahel, once the influence of oceanic modes has been eliminated, appears to be driven mainly by the activity of the Arabian Heat Low (AHL) in the central Sahel, and by the structure of the meridional temperature gradient over the inter-tropical Atlantic in the western Sahel.
More
Translated text
PDF
Bibtex
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
Try using models to generate summary,it takes about 60s
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
GPU is busy, summary generation fails
Rerequest