Impacts of a newly-developed aerosol climatology on numerical weather prediction using a global atmospheric forecasting model

Choi, In Sil; Park, Rae-Seol; Lee, Joonsuk

doi:10.1016/j.atmosenv.2018.10.019

Cited by 12 publications

(11 citation statements)

References 40 publications

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“…A large amount of SO 4 is also found in cloudy regions over the northern Pacific Ocean, eastern Atlantic Ocean, and coastal ocean off Peru because most of the transported SO 2 is converted into SO 4 by H 2 O 2 in the clouds. Levels, where hydrophobic and hydrophilic OC exist, include high over South Africa and China owing to emissions from biomass burning, which is consistent with Jeong and Wang [59] and Choi et al [60]. Most sea salt is emitted at high latitudes in the southern hemisphere owing to strong winds, which agrees with the results of Chin et al [12].…”

Section: Comparison Of Nc and Radiation Fluxsupporting

confidence: 89%

“…The domain-averaged downward shortwave and longwave radiation fluxes at the surface were calculated, as summarized in Table 2. In this study, the aerosol concentrations from the simplified chemistry package do not affect radiation directly because of the aerosol direct feedback; therefore, the aerosol climatology was used in order to reduce the computing burden [60]. For this study, we focused only on the aerosol indirect effect.…”

Section: Comparison Of N C and Radiation Fluxmentioning

confidence: 99%

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Aerosol Indirect Effects on the Predicted Precipitation in a Global Weather Forecasting Model

et al. 2019

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Aerosol indirect effects on precipitation were investigated in this study using a Global/Regional Integrated Model system (GRIMs) linked with a chemistry package devised for reducing the heavy computational burden occurring in common atmosphere–chemistry coupling models. The chemistry package was based on the Goddard Chemistry Aerosol Radiation and Transport scheme of Weather Research and Forecasting with Chemistry (WRF-Chem), and five tracers that are relatively important for cloud condensation nuclei (CCN) formation were treated as prognostic variables. For coupling with the cloud physics processes in the GRIMs, the CCN number concentrations derived from the simplified chemistry package were utilized in the cumulus parameterization scheme (CPS) and the microphysics scheme (MPS). The simulated CCN number concentrations were higher than those used in original cloud physics schemes and, overall, the amount of incoming shortwave radiation reaching the ground was indirectly reduced by an increase in clouds owing to a high CCN. The amount of heavier precipitation increased over the tropics owing to the inclusion of enhanced riming effects under deep precipitating convection. The trend regarding the changes in non-convective precipitation was mixed depending on the atmospheric conditions. The increase in small-size cloud water owing to a suppressed autoconversion led to a reduction in precipitation. More precipitation can occur when ice particles fall under high CCN conditions owing to the accretion of cloud water by snow and graupel, along with their melting.

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Section: Comparison Of Nc and Radiation Fluxsupporting

confidence: 89%

Section: Comparison Of N C and Radiation Fluxmentioning

confidence: 99%

Aerosol Indirect Effects on the Predicted Precipitation in a Global Weather Forecasting Model

et al. 2019

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“…Newer satellites will provide data with high spatio-temporal resolution information on the surface boundary which could lead to improvements in NWP forecasts (Parodi et al, 2018) as well as providing data from new satellite-mounted instruments (Carminati, Candy, Bell, & Atkinson, 2018). Satellite data can also be used to improve the climatology fields which are used by NWP models, such as aerosol climatology (Choi, Park, & Lee, 2019).…”

Section: Advances In Physical Modelingmentioning

confidence: 99%

The future of forecasting for renewable energy

Sweeney

Bessa

Browell

et al. 2019

WIREs Energy & Environment

149

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Forecasting for wind and solar renewable energy is becoming more important as the amount of energy generated from these sources increases. Forecast skill is improving, but so too is the way forecasts are being used. In this paper, we present a brief overview of the state‐of‐the‐art of forecasting wind and solar energy. We describe approaches in statistical and physical modeling for time scales from minutes to days ahead, for both deterministic and probabilistic forecasting. Our focus changes then to consider the future of forecasting for renewable energy. We discuss recent advances which show potential for great improvement in forecast skill. Beyond the forecast itself, we consider new products which will be required to aid decision making subject to risk constraints. Future forecast products will need to include probabilistic information, but deliver it in a way tailored to the end user and their specific decision making problems. Businesses operating in this sector may see a change in business models as more people compete in this space, with different combinations of skills, data and modeling being required for different products. The transaction of data itself may change with the adoption of blockchain technology, which could allow providers and end users to interact in a trusted, yet decentralized way. Finally, we discuss new industry requirements and challenges for scenarios with high amounts of renewable energy. New forecasting products have the potential to model the impact of renewables on the power system, and aid dispatch tools in guaranteeing system security. This article is categorized under: Energy Infrastructure > Systems and Infrastructure Wind Power > Systems and Infrastructure Photovoltaics > Systems and Infrastructure

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“…It was implemented in the KIM through initial data of aerosol loading and look-up tables of aerosol spectral optical characteristics. Kimaerclim used aerosol optical characteristics embedded in the rapid radiative transfer model for global circulation models (RRTMG) [32]. Aerosol loading data was manipulated with the inverse of monthly AOD at 550 nm from Monitoring Atmospheric Composition and Climate Reanalysis (MACCRA) [35] and the three-dimensional aerosol mass concentration fields of Model for OZone and Related Chemical Tracers (MOZART) [36].…”

Section: Construction Of Aerosol Climatology and Implementation Of Aerosols Into Radiation Modulementioning

confidence: 99%

“…Their products are decisive in determining the roles of aerosol types in the weather system. However, some studies used aerosol optical properties out of date, or calculated the products of spectral optical characteristics and loading data of each aerosol type without consistency [32]; one type was based on the chemical composition, and other types were based on the geographical regions.…”

Section: Introductionmentioning

confidence: 99%

Weather Effects of Aerosols in the Global Forecast Model

Jeong

2020

Atmosphere

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The weather effects of aerosol types were investigated using well-posed aerosol climatology through the aerosol sensitivity test of thermodynamic and hydrometeor fields, and the weather forecast performances in July of 2017. The largest aerosol direct radiative forcing (ADRF) in July was due to dust aerosols at the surface and atmosphere, and sulfate at the top of the atmosphere (TOA), respectively. The ADRF of total aerosols had unilateral tendencies in thermodynamic and hydrometeor fields. The contribution of individual aerosols was linearly additive to those of total aerosols in the heat fluxes, heating rates, humidity, and convective precipitation. However, no such linearity existed in temperature, geopotential height, cloud liquid or ice contents, and large-scale precipitation. Dust was the most influential forcing agent in July among five aerosol types due to the largest light-absorption capacity. Such unilateral tendencies of total aerosols and a part of the linearity of individual aerosols were exerted on the weather systems. The verification of medium-range forecasts showed that aerosols alleviated the overestimation of surface shortwave (SW) downward fluxes, the negative biases of temperature and geopotential heights at TOA and surface, and the underestimation in light and moderate precipitation. In contrast, they enhanced warm biases at the mid-atmosphere and underestimation in heavy precipitations, particularly negative biases in the intertropical convergence zone (ITCZ). Weather forecast scores including current aerosol information were improved in geopotential height (GPH) of the northern hemisphere (NH); however, they got worse in the temperature and the upper atmosphere GPH of the southern hemisphere (SH), which was mostly due to black carbon (BC) aerosols in the tropical regions. The missing mechanisms such as aerosol–cloud interactions, better aerosol spectral optical properties including mixing states and aging, and the near-real-time (NRT) based aerosol loading data are worthwhile to be tried in the near future for fixing the intrinsic underestimation of precipitation in ITCZ and surface radiative fluxes in the desert and biomass burning area.

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Impacts of a newly-developed aerosol climatology on numerical weather prediction using a global atmospheric forecasting model

Cited by 12 publications

References 40 publications

Aerosol Indirect Effects on the Predicted Precipitation in a Global Weather Forecasting Model

Aerosol Indirect Effects on the Predicted Precipitation in a Global Weather Forecasting Model

The future of forecasting for renewable energy

Weather Effects of Aerosols in the Global Forecast Model

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