Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling

Autor: Anping Chen, Daniel Ricciuto, Jiafu Mao, Jiawei Wang, Dan Lu, Fandong Meng

Publikováno v: Journal of Advances in Modeling Earth Systems, Vol 15, Iss 4, Pp n/a-n/a (2023)

Abstract The parameterization of key photosynthesis parameters is one of the key uncertain sources in modeling ecosystem gross primary productivity (GPP). Solar‐induced chlorophyll fluorescence (SIF) offers a good proxy for GPP since it marks the a

Externí odkaz: https://doaj.org/article/25fb366c7d194611a936745c263984a0

Storm time IRI-Plas model forecast for an African equatorial station

Autor: S.J. Adebiyi, S.O. Ikubanni, B.O. Adebesin, J.O. Adeniyi, B.W. Joshua, I.A. Adimula, O.A. Oladipo, A.O. Olawepo, B.J. Adekoya

Publikováno v: Heliyon, Vol 5, Iss 6, Pp e01844- (2019)

The limitation of ionospheric models in describing short-term ionospheric events has led to the development of data assimilative models e.g. the International Reference Ionosphere extended to Plasmasphere (IRI-Plas) model. This paper compares the IRI

Externí odkaz: https://doaj.org/article/ff37c1a28879457ea3518b573a19bde4

Application of a data-model assimilation method to a 3D surf zone sandbar physical experiment

Autor: Birrien, F., Castelle, B., Marieu, V., Almar, R., Michallet, H.

Publikováno v: Journal of Coastal Research, 2011 Jan 01, 976-980.

Externí odkaz: https://www.jstor.org/stable/26482319

Exploiting the Potential of Satellite Microwave Remote Sensing to Hindcast the Storm Surge in the Gulf of Venice

Autor: Francesco De Biasio, Marco Bajo, Stefano Zecchetto, Antonio della Valle, Stefano Vignudelli, Georg Umgiesser

Publikováno v: IEEE journal of selected topics in applied earth observations and remote sensing
9 (2016): 5089–5105. doi:10.1109/JSTARS.2016.2603235
info:cnr-pdr/source/autori:De Biasio F.; Vignudelli S.; Valle A.D.; Umgiesser G.; Bajo M.; Zecchetto S./titolo:Exploiting the Potential of Satellite Microwave Remote Sensing to Hindcast the Storm Surge in the Gulf of Venice/doi:10.1109%2FJSTARS.2016.2603235/rivista:IEEE journal of selected topics in applied earth observations and remote sensing (Print)/anno:2016/pagina_da:5089/pagina_a:5105/intervallo_pagine:5089–5105/volume:9

The potential of active microwave satellite observations of sea surface height (radar altimetry) and of sea surface wind (radar scatterometry) has been exploited for storm surge modeling purposes. The altimetry observations were assimilated into a st

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c41b5eb2451a072b4d9ca909ff2dba76
http://www.cnr.it/prodotto/i/361825

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