ARL Weekly News – June 10, 2024
| Upcoming Events |
ARL 75th Anniversary Open House
ARL continues its 75th Anniversary celebrations with an Open House event hosted at the Special Operations and Research Division in Idaho Falls, ID on June 26. Attendees will have the chance to talk to the scientists, engineers, and technicians building weather stations, collected measurements and conducting the research. Stations set around the grounds will demonstrate the ways we gather data.
ASMD scientists Prepare for Two Field Campaigns in Colorado and Utah in Summer 2024
The Air Quality and Greenhouse gas measurement team at ASMD are preparing for two upcoming field campaigns: Airborne Methane Mass Balance Emissions in Colorado and Utah Summer Ozone Study in Salt Lake City, UT, as the first year study of the Airborne and Remote sensing Methane and Air Pollutant Surveys (AiRMAPS). The team will be deploying a suite of instruments on a NOAA Twin Otter aircraft to measure in situ greenhouse gases and air pollutants. The NOAA Air Resources Car (NOAA’s ARC) will also be deployed in both campaigns to make mobile measurements on the ground. The primary objective is to provide comprehensive and quantitative top-down emissions data for methane, other greenhouse gases, and major air pollutants from the Denver-Julesburg oil & gas production basin and Salt Lake City.
| Recent Events |
Strengthening ties with Texas Tech
Temple Lee traveled to Lubbock, Texas from June 12-15 to serve on the committee for two M.S. students’ thesis defenses in the atmospheric science department at Texas Tech University. The two students successfully defended their theses, one of which focused on the advection of urban heat islands, and the second examined the characteristics of boundary layer thermodynamics across frontal boundaries. In addition, Temple met with several professors and students in the atmospheric science department to strengthen research collaborations between ARL and Texas Tech.
| Publications |
World Meteorological Organization report co-author
Beiming Tang is a co-author on a World Meteorological Organization (WMO) report that was published on June 13.
Title: Integration low-cost sensor systems and networks to Enhance air quality applications
Summary: Low-cost air quality sensor systems (LCS) are emerging technologies for policy-relevant air quality analysis, including pollution levels, source identification, and forecasting. This report discusses LCS use in networks and alongside other data sources for comprehensive air quality applications, complementing other WMO publications on LCS operating principles, calibration, performance assessment, and data communication.
The LCS’s utility lies in their ability to provide new insights into air quality that existing data sources may not offer. While LCS data must be verified, their integration with other data sources can enhance understanding and management of air quality. In areas without reference-grade monitors, LCS can identify factors affecting local air quality and guide future monitoring efforts. Combining LCS data with satellite and other air quality systems can improve data reliability and establish corroborating evidence for observed trends. LCS can extend the spatial coverage of existing monitoring networks, offering localized insights and supporting effective air quality management policies. Co-locating LCS with reference-grade monitors helps quantify measurement uncertainties and apply LCS data appropriately for forecasting, source impact analysis, and community engagement.
Accepted Paper
Decadal increases in carbon uptake offset by respiratory losses across northern permafrost ecosystems, by See et al. (with John Kochendorfer included among many coauthors), was accepted for publication in Nature Climate Change.
Abstract: Tundra and boreal ecosystems encompass the northern circumpolar permafrost region, and are experiencing rapid environmental change with important implications for the global carbon (C) budget. We analyzed multi-decadal time series containing 349 annual estimates of carbon dioxide (CO2) flux across 70 permafrost and non-permafrost ecosystems, and 672 estimates of summer CO2 flux across 181 ecosystems. We find an increase in the annual CO2 sink across non-permafrost ecosystems, but not permafrost ecosystems, despite similar increases in summer uptake. Thus, recent non-growing season CO2 losses have significantly impacted the CO2 balance of permafrost ecosystems. Further, analysis of interannual variability reveals warmer summers amplify the C cycle (increase productivity and respiration) at putatively nitrogen-limited sites, and at sites less reliant on summer precipitation for water use. Our findings suggest that water and nutrient availability will be important predictors of the C cycle response of these ecosystems to future warming.
Accepted Paper
Hung, W.-T., P. Campbell, Z. Moon, R. Saylor, J. Kochendorfer, T.R. Lee, & W. Massman (2024): Evaluation of an In-Canopy Wind and Wind Adjustment Factor Model for Wildfire Spread Applications Across Scales. J. of Advances in Modeling Earth Systems. Accepted.
Abstract: The representation of vegetative sub-canopy wind is critical in numerical weather prediction (NWP) models for the determination of the air-surface exchange processes of heat, momentum, and trace gases. Because of the relationship between wind speed and fire behaviors, the influence of the canopy on near-surface wind speed is critical for prognostic fire spread models used in regional NWP models. In practice, the wind speed at the midflame point of fires (midflame wind speed) is used to determine the rate of fire spread. However, the wind speeds from most in-situ measurements and NWP models are taken at some reference height above the canopy and fire flames. Hence, this study develops a modular and computationally-efficient one-dimensional model set composed of a canopy wind model and a wind adjustment factor (WAF) model for NWP applications across scales. The model set uses prescribed foliage shape functions to represent the vertical vegetation profile and its impacts on the three-dimensional structure of horizontal wind speeds. Results from the canopy wind model well agree with ground-based observations with average mean absolute bias, root mean square error and determination coefficients around 0.18 m s-1, 0.40 m s-1and 0.90, respectively. The WAF model provides midflame wind speeds by estimating the WAF based on canopy, fire and flame characteristics. Various user-definable options provide flexibility to adapt to variations in canopy characteristics and additional complexities associated with wildfires. The model set is expected to improve NWP models by providing an improved representation of the sub-grid wind flows at any spatial scale.