Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 25, 2024Open Access

An adaptive variance adjusting strategy for the climatological background error covariance matrix based on deep reinforcement learning

View Full Paper
Ask AI
Bookmark
Share

Authors

LHLilan HuangHLHongze LengJSJunqiang Song

Discussion

Loading...

Member takes

Overview

Key Points

Key points are not available for this paper at this time.

Cite This Study

Huang et al. (2024) studied this question.

synapsesocial.com/papers/68e5f1bfb6db643587586cbchttps://doi.org/10.21203/rs.3.rs-4489846/v1
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation2014 · 25,332 citations
  2. 2Learning skillful medium-range global weather forecasting2023 · 1,401 citations
  3. 3A review of operational methods of variational and ensemble‐variational data assimilation2016 · 532 citations
  4. 4A hybrid variational ensemble data assimilation for the HIgh Resolution Limited Area Model (HIRLAM)2014 · 35 citations
  5. 5A review of forecast error covariance statistics in atmospheric variational data assimilation. II: Modelling the forecast error covariance statistics2008 · 252 citations