ARL Weekly News – January 6, 2023

Announcements and Events

Wildfire Modeling Position Posted

The atmospheric transport group at ARL has a HYSPLIT position posted at GMU to work on wildfires within the HYSPLIT group. Wildfire modeling is a growing research interest across NOAA. The applicant can have a Master’s or PhD, and does not require the applicant to be a U.S. Citizen or Green Card holder. Link: https://jobs.gmu.edu/postings/56180

AMS Meeting

At the AMS Meeting, Chris Loughner will present a HYSPLIT analysis that identifies synoptic scale wind patterns in the New York City metropolitan area and relates the influence of these regional wind patterns on the formation of sea breeze circulations and air pollution loadings in a talk titled “The influence of synoptic scale wind patterns on sea breezes, ground level ozone, and column integrated nitrogen dioxide in the New York City metropolitan area.” Other ARL presentations are posted here: https://www.arl.noaa.gov/arl-research-presented-at-2023-ams-annual-meeting-in-denver/

LANTERN Assignment at PMEL

John Kochendorfer will begin a Leveraging Abilities Needs Talents Energies Resources Network (L·A·N·T·E·R·N) position with the OAR/Pacific Marine Environmental Laboratory (PMEL) on January 17. The assignment will last 120 days, and be mainly virtual. The goal is to help the PMEL director’s office with many facets of lab management, provide John with some exposure to supervisory and management work, and promote cross-laboratory collaboration.

Media Mentions

Inside Climate News Rides in ARL’s Mobile Laboratory

ARL’s Xinrong Ren and Phil Stratton research on measuring greenhouse gases in the Baltimore Washington Metropolitan region by using an instrumented SUV were highlighted on Inside Climate News. The mobile platform, dubbed NOAA’s ARC, detects pollutants in the region and can alert local facilities and agencies to unexpected rises in emissions that might be easily mitigated.

Volcanic Ash

Volcanic ash forecasting capabilities were mentioned in an OAR story about NOAA’s research and efforts on volcanoes. The Mauna Loa eruption in late November was one example of HYSPLIT volcanic ash model capabilities, which generated an ashfall advisory to aviation officials. A number of other NOAA capabilities such as air quality alerts, tsunami alerts, and climate modeling were also discussed.

Small UAS work

A news story discusses efforts that ARL’s small Uncrewed Aircraft Systems (sUAS) team supports. AOML researchers used the Altius 600 sUAS aircraft to monitor Hurricane Ian. AOML and ATDD use the small UAS to collect data on storms or hurricanes that that are too dangerous for scientists to venture into. The item was included in NOAA Research’s Top Accomplishments from 2022 and OAR’s biggest research stories from the last 12 months.

Climate Queries

Howard Diamond provided fact checking to USA Today on claims of global cooling dating back in 1974 based on popular media articles. Dr. Diamond provided references and assured the reporter that climate models, particularly those that have been running for a sufficient time period, have proved to make fairly accurate predictions. Furthermore, climate models have already predicted many of the phenomena for which we now have empirical evidence. Climate models form a reliable guide to potential climate change, and mainstream climate models have also accurately projected global surface temperature changes we now experience.

Publications

Published: Special Issue of Remote Sensing

Praveena Krishnan served as the Guest Editor of a recently completed special issue of Remote Sensing titled, “Understanding Biosphere-Atmosphere Interactions with Remote Sensing” along with Shusen Wang of Canada Centre for Remote Sensing, Natural Resources, Canada.
Editorial: Krishnan P, Wang S. Editorial for the Special Issue “Understanding Biosphere–Atmosphere Interactions with Remote Sensing”. Remote Sensing. 2023; 15(2):332. https://doi.org/10.3390/rs15020332

Published: New Parameterizations of Turbulence Statistics for the Atmospheric Surface Layer by Temple Lee and Tilden Meyers in Monthly Weather Review.

Abstract: Recent work has shown that bulk-Richardson (Rib) parameterizations for friction velocity, sensible heat flux, and latent heat flux have similar, and in some instances better, performance than long-standing parameterizations from Monin–Obukhov similarity theory (MOST). In this work, we expanded upon new Rib parameterizations and developed parameterizations of turbulence statistics, i.e., standard deviations in the 30-min u (horizontal), υ (meridional), and w (vertical) wind components (i.e., σu, συ, and σw, respectively), which allowed us to derive Rib-based parameterizations of turbulent kinetic energy (e), and standard deviations in the 30-min temperature and moisture measurements (σθ and σq, respectively). We used datasets from three 10-m micrometeorological towers installed during the Land Atmosphere Feedback Experiment (LAFE) conducted in Oklahoma from 1 to 31 August 2017 and evaluated the new parameterizations by comparing them against parameterizations from MOST. We used the LAFE datasets and fully independent datasets obtained from two micrometeorological towers installed in Alabama between February 2016 and April 2017 to evaluate the performance of the parameterizations. Based on the slope of the relationship between the observed and parameterized turbulence statistics (mb) and the coefficient of correlation (r), we found that the Rib relationships generally performed better than MOST at parameterizing συ, σw, σθ, and σq, and the Rib relationships performed better at low wind speeds than at high wind speeds. These results, coupled with recent developments of Rib parameterizations for surface-layer momentum, heat, and moisture fluxes, provide further evidence to consider using Rib-based parameterizations in weather forecasting models.

Significance Statement: Deficiencies in Monin–Obukhov similarity theory (MOST) are well known, yet MOST forms the basis in weather forecasting models for describing heat, moisture, and momentum transfer between the land surface and atmosphere. We expanded upon previous work suggesting a MOST alternative called the bulk-Richardson approach. We used data collected from meteorological towers installed in Oklahoma and compared the bulk-Richardson approach with MOST. We evaluated these two approaches using data from meteorological towers installed in Oklahoma and Alabama and found that, overall, the bulk-Richardson approach performed better than MOST in determining the 30-min variability in temperature, moisture, and wind. This result provides additional motivation to use a bulk-Richardson approach in weather forecasting models because doing so will likely yield improved forecasts.

Lee, Temple R., and Tilden P. Meyers. “New Parameterizations of Turbulence Statistics for the Atmospheric Surface Layer,” Monthly Weather Review 151, 1 (2023): 85-103, accessed Jan 11, 2023, https://doi.org/10.1175/MWR-D-22-0071.1