Global Analysis Forecast PHY 001 024

This dataset contains data from the product GLOBAL ANALYSIS FORECAST PHY 001 024 provided by the Copernicus Marine Environment Monitoring Service. This product contains daily means of several ocean-related variables such as temperature and salinity on a 1/12 degree lon–lat grid. This dataset is posted here for reproducibility of the results in a paper which applies a convolution-neural-network-integro-difference-equation model for modelling sea-surface temperature; it should not be used for any scientific analyses. More details are available here in Section 4.1. The reference for the published article is:

Zammit-Mangion, A., & Wikle, C. K. (2020). Deep integro-difference equation models for spatio-temporal forecasting. Spatial Statistics, 37, 100408.

데이터와 리소스

추가 정보

필드
소스 https://arxiv.org/pdf/1910.13524.pdf
저자 Copernicus Marine Environment Monitoring Service
관리자 Yi Cao
최종 업데이트 2월 4, 2021, 23:31 (UTC)
생성됨 2월 4, 2021, 22:42 (UTC)