Cargando…

Identifying errors in dust models from data assimilation

Airborne mineral dust is an important component of the Earth system and is increasingly predicted prognostically in weather and climate models. The recent development of data assimilation for remotely sensed aerosol optical depths (AODs) into models offers a new opportunity to better understand the...

Descripción completa

Detalles Bibliográficos
Autores principales:	Pope, R. J., Marsham, J. H., Knippertz, P., Brooks, M. E., Roberts, A. J.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2016
Materias:	Research Letters
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5082526/ https://www.ncbi.nlm.nih.gov/pubmed/27840459 http://dx.doi.org/10.1002/2016GL070621

Ejemplares similares

The importance of rare, high‐wind events for dust uplift in northern Africa
por: Cowie, Sophie M., et al.
Publicado: (2015)

Quantifying global dust devil occurrence from meteorological analyses
por: Jemmett-Smith, Bradley C, et al.
Publicado: (2015)

Are vegetation-related roughness changes the cause of the recent decrease in dust emission from the Sahel?
por: Cowie, Sophie M, et al.
Publicado: (2013)

The role of deep convection and nocturnal low-level jets for dust emission in summertime West Africa: Estimates from convection-permitting simulations
por: Heinold, B, et al.
Publicado: (2013)

The formation of a large summertime Saharan dust plume: Convective and synoptic-scale analysis
por: Roberts, A J, et al.
Publicado: (2014)

Forecast error correction using dynamic data assimilation
por: Lakshmivarahan, Sivaramakrishnan, et al.
Publicado: (2016)

Multiscale Representation of Observation Error Statistics in Data Assimilation
por: Chabot, Vincent, et al.
Publicado: (2020)

Climatology of nocturnal low-level jets over North Africa and implications for modeling mineral dust emission
por: Fiedler, S, et al.
Publicado: (2013)

Evaluating the Impact of Assimilating Aerosol Optical Depth Observations on Dust Forecasts Over North Africa and the East Atlantic Using Different Data Assimilation Methods
por: Choi, Yonghan, et al.
Publicado: (2020)

Assimilation of Both Column‐ and Layer‐Integrated Dust Opacity Observations in the Martian Atmosphere
por: Ruan, Tao, et al.
Publicado: (2021)

Data assimilation
por: Guzzi, Rodolfo
Publicado: (2015)

Data Assimilation
por: Evensen, Geir
Publicado: (2009)

Atmospheric modeling, data assimilation, and predictability
por: Kalnay, Eugenia, 1942-
Publicado: (2003)

Cross‐Saharan transport of water vapor via recycled cold pool outflows from moist convection
por: Trzeciak, Tomasz M., et al.
Publicado: (2017)

The mysterious long-range transport of giant mineral dust particles
por: van der Does, Michèlle, et al.
Publicado: (2018)

Nonlinear data assimilation
por: Van Leeuwen, Peter Jan, et al.
Publicado: (2015)

Accounting for Location Error in Kalman Filters: Integrating Animal Borne Sensor Data into Assimilation Schemes
por: Sengupta, Aritra, et al.
Publicado: (2012)

Dynamic calibration of agent-based models using data assimilation
por: Ward, Jonathan A., et al.
Publicado: (2016)

Correction to ‘Learning earth system models from observations: machine learning or data assimilation?’
por: Geer, A. J.
Publicado: (2022)

Reconstructing Mammalian Sleep Dynamics with Data Assimilation
por: Sedigh-Sarvestani, Madineh, et al.
Publicado: (2012)

Assimilation of SMAP Brightness Temperature Observations in the GEOS Land–Atmosphere Data Assimilation System
por: Reichle, Rolf H., et al.
Publicado: (2021)

Sources of cosmic dust in the Earth's atmosphere
por: Carrillo‐Sánchez, J. D., et al.
Publicado: (2016)

Data assimilation in operator algebras
por: Freeman, David, et al.
Publicado: (2023)

Impact of assimilated and interactive aerosol on tropical cyclogenesis
por: Reale, O, et al.
Publicado: (2014)

Data Assimilation to extract Soil Moisture Information from SMAP Observations
por: Kolassa, Jana, et al.
Publicado: (2017)

Improved Parameterization for the Size Distribution of Emitted Dust Aerosols Reduces Model Underestimation of Super Coarse Dust
por: Meng, Jun, et al.
Publicado: (2022)

Multi-mission satellite remote sensing data for improving land hydrological models via data assimilation
por: Khaki, M., et al.
Publicado: (2020)

Accurate state estimation from uncertain data and models: an application of data assimilation to mathematical models of human brain tumors
por: Kostelich, Eric J, et al.
Publicado: (2011)

Data Assimilation Methods for Neuronal State and Parameter Estimation
por: Moye, Matthew J., et al.
Publicado: (2018)

Probabilistic forecasting and Bayesian data assimilation
por: Reich, Sebastian, et al.
Publicado: (2015)

Data assimilation: a mathematical introduction
por: Law, Kody, et al.
Publicado: (2015)

Dynamic meteorology data assimilation methods
por: Bengtsson, Lennart, et al.
Publicado: (1981)

Computational methods for data evaluation and assimilation
por: Cacuci, Dan Gabriel
Publicado: (2013)

Data assimilation: the ensemble Kalman filter
por: Evensen, Geir
Publicado: (2007)

Perspectives for Tibetan Plateau data assimilation
por: Yang, Zong-Liang, et al.
Publicado: (2020)

A new data assimilation method for high-dimensional models
por: Wang, Guangjie, et al.
Publicado: (2018)

An epidemiological modelling approach for COVID-19 via data assimilation
por: Nadler, Philip, et al.
Publicado: (2020)

Coarse particles and dust storm mortality.
por: Mage, D T
Publicado: (2000)

Bayesian sequential data assimilation for COVID-19 forecasting
por: Daza-Torres, Maria L., et al.
Publicado: (2022)

Error in key model input
por: Schabas, Richard
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_ak5n9kdgq2p90g55kl6goadive