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A Machine Learning Tutorial for Operational Meteorology, Part I: Traditional Machine Learning [PDF]
Weather and Forecasting 37 (2022) 1509-1529, 2022 Recently, the use of machine learning in meteorology has increased greatly. While many machine learning methods are not new, university classes on machine learning are largely unavailable to meteorology students and are not required to become a meteorologist. The lack of formal instruction has contributed to perception that machine learning methods are
R. Chase +4 more
arxiv +3 more sources
Atmospheric Chemistry and Physics, 2021 . A framework was developed to quantitatively assess the contribution of meteorology variations in the trend of particular matter (PM) concentrations and to separate the impacts of meteorology from the control measures in the trend, based upon an ...
Sunling Gong, Shuxiao Wang, Lei Zhang
exaly +2 more sources
Meteorology influencing springtime air quality, pollution transport, and visibility in Korea
Elementa, 2019 In an environment with many local, remote, persistent, and episodic sources of pollution, meteorology is the primary factor that drives periods of unhealthy air quality and reduced visibility.
Edward J Hyer +2 more
exaly +2 more sources
, 2020 . China has suffered from increasing levels of ozone pollution in urban areas despite the implementation of various stringent emission reduction measures since 2013.
Yiming Liu, Tao Wang
semanticscholar +2 more sources
Meteorology-normalized impact of the COVID-19 lockdown upon NO2 pollution in Spain
Atmospheric Chemistry and Physics, 2020 . The spread of the new coronavirus SARS-CoV-2 that causes COVID-19 forced the Spanish Government to implement extensive lockdown measures to reduce the number of hospital admissions, starting on 14 March 2020.
H. Petetin +6 more
semanticscholar +1 more source
Atmospheric Chemistry and Physics, 2019 . Fine particulate matter (PM2.5) is a severe air pollution problem in China. Observations of PM2.5 have been available since 2013 from a large network operated by the China National Environmental Monitoring Center (CNEMC).
S. Zhai +8 more
semanticscholar +1 more source
Meteorology-driven variability of air pollution (PM1) revealed with explainable machine learning
Atmospheric Chemistry and Physics, 2020 . Air pollution, in particular high concentrations of particulate matter smaller than 1 µm in diameter (PM1), continues to be a major health problem, and meteorology is known to substantially influence atmospheric PM concentrations.
Roland Stirnberg +8 more
semanticscholar +1 more source
, 2001 We present a first description and evaluation of GEOS-CHEM, a global three- dimensional (3-D) model of tropospheric chemistry driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Data Assimilation ...
I. Bey +9 more
semanticscholar +1 more source
Statistical Physics in Meteorology [PDF]
Physica A 336 (2004) 93-101, 2004 Various aspects of modern statistical physics and meteorology can be tied together. The historical importance of the University of Wroclaw in the field of meteorology is first pointed out. Next, some basic difference about time and space scales between meteorology and climatology is outlined.
arxiv +1 more source
The CAMELS data set: catchment attributes and meteorology for large-sample studies
, 2017 . We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b).
N. Addor +3 more
semanticscholar +1 more source