FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4229534874> ?p ?o ?g. }

• W4229534874 abstract "Abstract. Numerical prediction of aerosol particle properties has become an important activity at many research and operational weather centres due to growing interest from a diverse set of stakeholders, such as air quality regulatory bodies, aviation and military authorities, solar energy plant managers, providers of climate services, and health professionals. The prediction of aerosol particle properties in Numerical Weather Prediction (NWP) models faces a number of challenges owing to the complexity of atmospheric aerosol processes and their sensitivity to the underlying meteorological conditions. Errors in aerosol prediction concern all processes involved in the aerosol life cycle. These include errors on the source terms (for both anthropogenic and natural emissions), errors directly dependent on the meteorology (e.g., mixing, transport, scavenging by precipitation), as well as errors related to aerosol chemistry (e.g., nucleation, gas-aerosol partitioning, chemical transformation and growth, hygroscopicity). The main goal of current research on aerosol forecast consists in prioritizing these errors and trying to reduce the most important ones through model development and data assimilation. Aerosol particle observations from satellite and ground-based platforms have been crucial to guide model development of the recent years, and have been made more readily available for model evaluation and assimilation. However, for the sustainability of the aerosol particle prediction activities around the globe, it is crucial that quality aerosol observations continue to be made available from different platforms (space, near-surface, and aircraft) and freely shared. This white paper reviews current requirements for aerosol observations in the context of the operational activities carried out at various global and regional centres. Some of the requirements are equally applicable to aerosol-climate research. However, the focus here is on the global operational prediction of aerosol properties such as mass concentrations and optical parameters. Most operational models are based on bulk schemes that do not predict the size distribution of the aerosol particles. Others are based on a mix of bin and bulk schemes with limited capability to simulate the size information. However the next generation of aerosol operational models will have the capability to predict both mass and number density which will provide a more complete description of the aerosols properties. A brief overview of the state-of-the-art is provided with an introduction on the importance of aerosol prediction activities. The criteria on which the requirements for aerosol observations are based are also outlined. Assimilation and evaluation aspects are discussed from the perspective of the user requirements." @default.
• W4229534874 created "2022-05-11" @default.
• W4229534874 creator A5008664770 @default.
• W4229534874 creator A5010059066 @default.
• W4229534874 creator A5011809949 @default.
• W4229534874 creator A5013559764 @default.
• W4229534874 creator A5014234058 @default.
• W4229534874 creator A5018401359 @default.
• W4229534874 creator A5022712902 @default.
• W4229534874 creator A5023905980 @default.
• W4229534874 creator A5027757707 @default.
• W4229534874 creator A5029876178 @default.
• W4229534874 creator A5035964624 @default.
• W4229534874 creator A5036419391 @default.
• W4229534874 creator A5037663818 @default.
• W4229534874 creator A5042031409 @default.
• W4229534874 creator A5044593088 @default.
• W4229534874 creator A5044758677 @default.
• W4229534874 creator A5052166339 @default.
• W4229534874 creator A5057603836 @default.
• W4229534874 creator A5060389948 @default.
• W4229534874 creator A5062518836 @default.
• W4229534874 creator A5067207325 @default.
• W4229534874 creator A5067769357 @default.
• W4229534874 creator A5072436785 @default.
• W4229534874 creator A5077051671 @default.
• W4229534874 creator A5079834362 @default.
• W4229534874 creator A5080431729 @default.
• W4229534874 creator A5085173198 @default.
• W4229534874 creator A5087269535 @default.
• W4229534874 creator A5090286585 @default.
• W4229534874 date "2018-02-27" @default.
• W4229534874 modified "2023-09-27" @default.
• W4229534874 title "Status and future of Numerical Atmospheric Aerosol Prediction with a focus on data requirements" @default.
• W4229534874 doi "https://doi.org/10.5194/acp-2018-42" @default.
• W4229534874 hasPublicationYear "2018" @default.
• W4229534874 type Work @default.
• W4229534874 citedByCount "0" @default.
• W4229534874 crossrefType "posted-content" @default.
• W4229534874 hasAuthorship W4229534874A5008664770 @default.
• W4229534874 hasAuthorship W4229534874A5010059066 @default.
• W4229534874 hasAuthorship W4229534874A5011809949 @default.
• W4229534874 hasAuthorship W4229534874A5013559764 @default.
• W4229534874 hasAuthorship W4229534874A5014234058 @default.
• W4229534874 hasAuthorship W4229534874A5018401359 @default.
• W4229534874 hasAuthorship W4229534874A5022712902 @default.
• W4229534874 hasAuthorship W4229534874A5023905980 @default.
• W4229534874 hasAuthorship W4229534874A5027757707 @default.
• W4229534874 hasAuthorship W4229534874A5029876178 @default.
• W4229534874 hasAuthorship W4229534874A5035964624 @default.
• W4229534874 hasAuthorship W4229534874A5036419391 @default.
• W4229534874 hasAuthorship W4229534874A5037663818 @default.
• W4229534874 hasAuthorship W4229534874A5042031409 @default.
• W4229534874 hasAuthorship W4229534874A5044593088 @default.
• W4229534874 hasAuthorship W4229534874A5044758677 @default.
• W4229534874 hasAuthorship W4229534874A5052166339 @default.
• W4229534874 hasAuthorship W4229534874A5057603836 @default.
• W4229534874 hasAuthorship W4229534874A5060389948 @default.
• W4229534874 hasAuthorship W4229534874A5062518836 @default.
• W4229534874 hasAuthorship W4229534874A5067207325 @default.
• W4229534874 hasAuthorship W4229534874A5067769357 @default.
• W4229534874 hasAuthorship W4229534874A5072436785 @default.
• W4229534874 hasAuthorship W4229534874A5077051671 @default.
• W4229534874 hasAuthorship W4229534874A5079834362 @default.
• W4229534874 hasAuthorship W4229534874A5080431729 @default.
• W4229534874 hasAuthorship W4229534874A5085173198 @default.
• W4229534874 hasAuthorship W4229534874A5087269535 @default.
• W4229534874 hasAuthorship W4229534874A5090286585 @default.
• W4229534874 hasBestOaLocation W42295348742 @default.
• W4229534874 hasConcept C126314574 @default.
• W4229534874 hasConcept C147947694 @default.
• W4229534874 hasConcept C153294291 @default.
• W4229534874 hasConcept C166957645 @default.
• W4229534874 hasConcept C205649164 @default.
• W4229534874 hasConcept C24552861 @default.
• W4229534874 hasConcept C2779343474 @default.
• W4229534874 hasConcept C2779345167 @default.
• W4229534874 hasConcept C39432304 @default.
• W4229534874 hasConceptScore W4229534874C126314574 @default.
• W4229534874 hasConceptScore W4229534874C147947694 @default.
• W4229534874 hasConceptScore W4229534874C153294291 @default.
• W4229534874 hasConceptScore W4229534874C166957645 @default.
• W4229534874 hasConceptScore W4229534874C205649164 @default.
• W4229534874 hasConceptScore W4229534874C24552861 @default.
• W4229534874 hasConceptScore W4229534874C2779343474 @default.
• W4229534874 hasConceptScore W4229534874C2779345167 @default.
• W4229534874 hasConceptScore W4229534874C39432304 @default.
• W4229534874 hasFunder F4320332999 @default.
• W4229534874 hasLocation W42295348741 @default.
• W4229534874 hasLocation W422953487410 @default.
• W4229534874 hasLocation W422953487411 @default.
• W4229534874 hasLocation W42295348742 @default.
• W4229534874 hasLocation W42295348743 @default.
• W4229534874 hasLocation W42295348744 @default.
• W4229534874 hasLocation W42295348745 @default.
• W4229534874 hasLocation W42295348746 @default.
• W4229534874 hasLocation W42295348747 @default.
• W4229534874 hasLocation W42295348748 @default.
• W4229534874 hasLocation W42295348749 @default.
• W4229534874 hasOpenAccess W4229534874 @default.

• next