Zobrazeno 1 - 10
of 352
pro vyhledávání: '"D Fairbairn"'
Autor:
G. Abramowitz, A. Ukkola, S. Hobeichi, J. Cranko Page, M. Lipson, M. G. De Kauwe, S. Green, C. Brenner, J. Frame, G. Nearing, M. Clark, M. Best, P. Anthoni, G. Arduini, S. Boussetta, S. Caldararu, K. Cho, M. Cuntz, D. Fairbairn, C. R. Ferguson, H. Kim, Y. Kim, J. Knauer, D. Lawrence, X. Luo, S. Malyshev, T. Nitta, J. Ogee, K. Oleson, C. Ottlé, P. Peylin, P. de Rosnay, H. Rumbold, B. Su, N. Vuichard, A. P. Walker, X. Wang-Faivre, Y. Wang, Y. Zeng
Publikováno v:
Biogeosciences, Vol 21, Pp 5517-5538 (2024)
Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evalu
Externí odkaz:
https://doaj.org/article/0e1f69fbe78f48a0a8a5c2dcdd806470
Autor:
C. Albergel, Y. Zheng, B. Bonan, E. Dutra, N. Rodríguez-Fernández, S. Munier, C. Draper, P. de Rosnay, J. Muñoz-Sabater, G. Balsamo, D. Fairbairn, C. Meurey, J.-C. Calvet
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 4291-4316 (2020)
LDAS-Monde is a global offline land data assimilation system (LDAS) that jointly assimilates satellite-derived observations of surface soil moisture (SSM) and leaf area index (LAI) into the ISBA (Interaction between Soil Biosphere and Atmosphere) lan
Externí odkaz:
https://doaj.org/article/ef2ecb94d2b046b5b4e4b80cebf13ae3
Publikováno v:
Hydrology and Earth System Sciences, Vol 24, Pp 325-347 (2020)
This paper introduces an ensemble square root filter (EnSRF) in the context of jointly assimilating observations of surface soil moisture (SSM) and the leaf area index (LAI) in the Land Data Assimilation System LDAS-Monde. By ingesting those satellit
Externí odkaz:
https://doaj.org/article/4cffe7c5f56d4421bd20b0ece443646a
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4, Pp 291-296 (2018)
Understanding the spatial connectivity of urban infrastructure networks that connect assets to buildings is important for the fine-scale spatial analysis and modelling of the resource flows within cities. However, rarely are spatially explicit repres
Externí odkaz:
https://doaj.org/article/4c991ed0314147339380abc9ae7574b0
Publikováno v:
Hydrology and Earth System Sciences, Vol 22, Pp 2091-2115 (2018)
Physically consistent descriptions of land surface hydrology are crucial for planning human activities that involve freshwater resources, especially in light of the expected climate change scenarios. We assess how atmospheric forcing data uncertai
Externí odkaz:
https://doaj.org/article/c29776cb3ba64d84a403a9b5525593ce
Autor:
C. Albergel, S. Munier, D. J. Leroux, H. Dewaele, D. Fairbairn, A. L. Barbu, E. Gelati, W. Dorigo, S. Faroux, C. Meurey, P. Le Moigne, B. Decharme, J.-F. Mahfouf, J.-C. Calvet
Publikováno v:
Geoscientific Model Development, Vol 10, Pp 3889-3912 (2017)
In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surfa
Externí odkaz:
https://doaj.org/article/5940a7fcc9e549b0bcdfa67933230987
Publikováno v:
Hydrology and Earth System Sciences, Vol 21, Iss 4, Pp 2015-2033 (2017)
This study evaluates the impact of assimilating surface soil moisture (SSM) and leaf area index (LAI) observations into a land surface model using the SAFRAN–ISBA–MODCOU (SIM) hydrological suite. SIM consists of three stages: (1) an atmospheric r
Externí odkaz:
https://doaj.org/article/e8921413b8134320a9971a0bbde23666
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Hydrology and Earth System Sciences, Vol 19, Iss 12, Pp 4811-4830 (2015)
Two data assimilation (DA) methods are compared for their ability to produce an accurate soil moisture analysis using the Météo-France land surface model: (i) SEKF, a simplified extended Kalman filter, which uses a climatological background-erro
Externí odkaz:
https://doaj.org/article/1970cfd3eb0d4feb9c7c992c995423f0