ARL Weekly News – July 8, 2022
HYSPLIT in Support of World Athletics Championships
In preparation for the upcoming World Athletics Championships, (a biennial international track and field event) to be held in Eugene, OR from July 15-24, 2022 ARL’s HYSPLIT development team set up hourly atmospheric dispersion simulations over Hayward Field in Eugene where the event will be centered. This effort will support NWS’s Weather Forecast Office in Portland, OR which will be providing decision support services to local emergency management personnel before and during the event. The automated HYSPLIT simulations were requested by NWS Western Region Headquarters in Salt Lake City, UT. (Sonny.Zinn@noaa.gov, Mark.Cohen@noaa.gov)
Dr. Tilden P. Meyers promoted to Senior Scientist (ST) for ARL
Effective on June 19, 2022, Dr. Tilden P. Meyers was promoted to the rank of Senior Scientist (ST) for ARL. He has served as a research scientist on numerous projects and modeling efforts throughout his 37 plus years of service within ARL. His work improves the understanding and representation of the earth surface and boundary layer interactions in both weather and climate models, especially as it relates to water and greenhouse gas processes and predictions in the planetary boundary layer. This research plays a critical role in helping communities to adapt and increase resilience to climate change and associated extreme events. In the field of biometeorology, he is considered by his peers to be a world-renowned expert in micrometeorological instrumentation and in modeling of the soil-plant-atmosphere system. He has led work on convective initiation, atmospheric feedback loops, and impacts of drought and extreme heat events on vegetation functioning. His research findings have improved representation of carbon, water and energy fluxes in land-surface models, and turbulence parameterizations in numerical weather prediction models. His new position will provide leadership for research engaged in the development and improvement of boundary layer understanding, including sophisticated dispersion models and other tools for emergency response, air quality, and climate applications.
This new ST position at ARL will provide leadership for research engaged in the development and improvement of the scientific understanding of the boundary layer. This includes the development of (1) sophisticated measurement and modeling techniques applied to the improvement of weather prediction; and (2) improved dispersion models for emergency response, air quality forecasting, and climate applications. Most critically, this position provides a strategic focus for boundary layer research across the various OAR laboratories and programs that will effectively allow for a more coordinated and focused research effort ensuring that resources are best applied to those activities that will be most beneficial to the improvement of models and ultimately improved weather forecast and climate outlook products to best meet user requirements. Since the ARL Director, Ariel Stein, has been designated as the OAR steward for boundary layer research, having this ST position at ARL will allow for a more strategic direction at the Lab Director level, as well as with other STs from other labs, allowing for a more direct interaction with SES-level management across OAR, as well as in providing the external research community with a designated senior level scientist to aid in fostering those extramural boundary layer research efforts. In addition, Dr. Meyers will provide: scientific leadership in planning and conducting research to better understand the meteorological processes in the atmosphere (dynamical and radiative); skill in modeling and analysis of satellite and airborne atmospheric composition data to elucidate issues related to the behavior of the boundary layer; and the ability to translate the scientific information to decision-support applications, such as characterizing and predicting extreme climate and weather related events.
Dr. Meyers is recognized both nationally and internationally as a world-class expert in atmospheric turbulence and diffusion. He has authored over 200 peer-reviewed publications and at NOAA his publications have resulted in a top 5 rating by garnering over 28,000 citations to his work resulting in a very impressive and laudable H-index of 80. Tilden received his B.S. degree in Meteorology from the University of Wisconsin and both his M.S. in Agricultural Meteorology and PhD in Micro-meteorology from Purdue University. He was also a prior recipient of the NOAA Administrator’s Award, NOAA Bronze Award, and the Department of Commerce Gold Medal Award. We welcome Tilden into his new ST position and look forward to great things via his leadership with respect to furthering both ARL’s and OAR’s work in the boundary layer.
ARL 2022 Interns – Jenifer Vivar
Jenifer Vivar is currently pursuing a master’s degree in data science at the City College of New York (CUNY). Miss Vivar has been a NOAA-CESSRST fellow researcher for the last year focusing on Mixing Layer Height (MLH) and pollutant transmissions. During the NERTO internship at ARL, Jenifer is working on comparing different algorithms that calculate MLH with Alice Crawford, Nebila Lichiheb, and Christopher Loughner. She is also attempting a machine learning algorithm implementation to determine MLH and expects to graduate in the Spring of 2023.
Development and evaluation of the Aerosol Forecast Member in the National Center for Environment Prediction (NCEP)’s Global Ensemble Forecast System (GEFS-Aerosols v1).
Zhang, L., Montuoro, R., McKeen, S. A., Baker, B., Bhattacharjee, P. S., Grell, G. A., Henderson, J., Pan, L., Frost, G. J., McQueen, J., Saylor, R., Li, H., Ahmadov, R., Wang, J., Stajner, I., Kondragunta, S., Zhang, X., and Li, F.: Development and evaluation of the Aerosol Forecast Member in the National Center for Environment Prediction (NCEP)’s Global Ensemble Forecast System (GEFS-Aerosols v1), Geosci. Model Dev., 15, 5337–5369, https://doi.org/10.5194/gmd-15-5337-2022, 2022.
Abstract: The National Oceanic and Atmospheric Administration (NOAA)’s National Weather Service (NWS) is on its way to deploying various operational prediction applications using the Unified Forecast System (https://ufscommunity.org/, last access: 18 June 2022), a community-based coupled, comprehensive Earth modeling system. An aerosol model component developed in collaboration between the Global Systems Laboratory, Chemical Science Laboratory, Air Resources Laboratory, and Environmental Modeling Center (GSL, CSL, ARL, EMC) was coupled online with the FV3 Global Forecast System (FV3GFS) using the National Unified Operational Prediction Capability (NUOPC)-based NOAA Environmental Modeling System (NEMS) software framework. This aerosol prediction system replaced the NEMS GFS Aerosol Component version 2 (NGACv2) system in the National Center for Environment Prediction (NCEP) production suite in September 2020 as one of the ensemble members of the Global Ensemble Forecast System (GEFS), dubbed GEFS-Aerosols v1. The aerosol component of atmospheric composition in the GEFS is based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). GEFS-Aerosols includes bulk modules from the Goddard Chemistry Aerosol Radiation and Transport model (GOCART). Additionally, the biomass burning plume rise module from High-Resolution Rapid Refresh (HRRR)-Smoke based on WRF-Chem was implemented. The GOCART dust scheme was replaced by the FENGSHA dust scheme (developed by ARL). The Blended Global Biomass Burning Emissions Product (GBBEPx version 3) provides biomass burning emission and fire radiative power (FRP) data. The global anthropogenic emission inventories are derived from the Community Emissions Data System (CEDS). All sub-grid-scale transport and deposition are handled inside the atmospheric physics routines, which required consistent implementation of positive definite tracer transport and wet scavenging in the physics parameterizations used by the NCEP’s operational FV3GFS. This paper describes the details of GEFS-Aerosols model development and evaluation of real-time and retrospective runs using different observations from in situ measurement and satellite and aircraft data. GEFS-Aerosols predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational NGACv2 system with the fundamental updates (e.g., dust and fire emission) in the atmospheric and chemical transport model.