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Single point eddy covariance measurements of the Earth’s surface energy budget frequently identify an imbalance between available energy and turbulent heat fluxes. While this imbalance lacks a definitive explanation, it is nevertheless a persistent finding from single-site measurements; one with implications for atmospheric and ecosystem models. This has led to a push for intensive field campaigns with temporally and spatially distributed sensors to help identify the causes of energy balance non-closure. Here we present results from the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19)—an observational experiment designed to investigate how the Earth’s surface energy budget responds to scales of surface spatial heterogeneity over a forest ecosystem in northern Wisconsin. The campaign was conducted from June–October 2019, measuring eddy covariance (EC) surface energy fluxes using an array of 20 towers and a low-flying aircraft. Across the domain, energy balance residuals were found to be highest during the afternoon, coinciding with the period of surface heterogeneity-driven mesoscale motions. The magnitude of the residual varied across different sites in relation to the vegetation characteristics of each site. Both vegetation height and height variability showed positive relationships with the residual magnitude. During the seasonal transition from latent heat-dominated summer to sensible heat-dominated fall the magnitude of the energy balance residual steadily decreased, but the energy balance ratio remained constant at 0.8. This was due to the different components of the energy balance equation shifting proportionally, suggesting a common cause of non-closure across the two seasons. Additionally, we tested the effectiveness of measuring energy balance using spatial EC. Spatial EC, whereby the covariance is calculated based on deviations from spatial means, has been proposed as a potential way to reduce energy balance residuals by incorporating contributions from mesoscale motions better than single-site, temporal EC. Here we tested several variations of spatial EC with the CHEESEHEAD19 dataset but found little to no improvement to energy balance closure, which we attribute in part to the challenging measurement requirements of spatial EC. 

The lake breeze circulation along Lake Michigan is associated with high tropospheric ozone concentrations at shoreline locations. The 2021 Wisconsin's Dynamic Influence of Shoreline Circulation on Ozone (WiscoDISCO-21) campaign involved atmospheric measurements over Chiwaukee Prairie State Natural Area in Southeastern Wisconsin from May 21–26, 2021. Three different platforms, two uncrewed aerial systems (UAS) and a Doppler lidar instrument, were used to collect data on this campaign, supplemented by a ground-based Wisconsin DNR maintained regulatory monitor at the site. A Purdue University M210 multirotor copter, and the University of Colorado RAAVEN fixed-wing aircraft were flown in coordination. Using data from the ground station, RAAVEN and onsite lidar, lake breezes were detected on several days of the campaign. The longest sustained lake breezes during the campaign were detected on May 22, 2021, from 17:00–21:38 UTC and on May 24, 2021, from 14:24–22:51 UTC. The presence of the lake breezes correlated with detected temperature inversions measured from the RAAVEN and high ozone events measured from the M210. Lake breezes were investigated with their relationship to vertical profiles measured on the UAS, ozone concentrations, and marine boundary layer height observed with Doppler lidar to demonstrate a multi-layered lower atmosphere. A buoyant internal boundary layer was observed over land from 40–100 m AGL below highest ozone concentrations. Marine layer extent was investigated through minimum buoyancy and Richardson number analysis, showing limited vertical mixing at altitudes up to 200 m AGL, below easterly lake breeze circulation patterns extending upward to 400 m AGL in the late day. 

Abstract. The observing system design of multidisciplinary fieldmeasurements involves a variety of considerations on logistics, safety, andscience objectives. Typically, this is done based on investigator intuitionand designs of prior field measurements. However, there is potential forconsiderable increases in efficiency, safety, and scientific success byintegrating numerical simulations in the design process. Here, we present anovel numerical simulation–environmental response function (NS–ERF)approach to observing system simulation experiments that aidssurface–atmosphere synthesis at the interface of mesoscale and microscalemeteorology. In a case study we demonstrate application of the NS–ERFapproach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balanceStudy Enabled by a High-density Extensive Array of Detectors 2019(CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered theplacement of 20 eddy covariance flux towers, operations for 72 h oflow-altitude flux aircraft measurements, and integration of various remotesensing data products. A 2 h high-resolution large eddy simulationcreated a cloud-free virtual atmosphere for surface and meteorologicalconditions characteristic of the field campaign domain and period. Toexplore two specific design hypotheses we super-sampled this virtualatmosphere as observed by 13 different yet simultaneous observing systemdesigns consisting of virtual ground, airborne, and satellite observations.We then analyzed these virtual observations through ERFs to yield an optimalaircraft flight strategy for augmenting a stratified random flux towernetwork in combination with satellite retrievals. We demonstrate how the novel NS–ERF approach doubled CHEESEHEAD19'spotential to explore energy balance closure and spatial patterning scienceobjectives while substantially simplifying logistics. Owing to its modularextensibility, NS–ERF lends itself to optimizing observing system designs alsofor natural climate solutions, emission inventory validation, urban airquality, industry leak detection, and multi-species applications, among otheruse cases. 

Abstract Climate change is intensifying the hydrologic cycle and altering ecosystem function, including water flux to the atmosphere through evapotranspiration (ET). ET is made up of evaporation (E) via non‐stomatal surfaces, and transpiration (T) through plant stomata which are impacted by global changes in different ways. E and T are difficult to measure independently at the ecosystem scale, especially across multiple sites that represent different land use and land management strategies. To address this gap in understanding, we applied flux variance similarity (FVS) to quantify how E and T differ across 13 different ecosystems measured using eddy covariance in a 10 × 10 km area from the CHEESEHEAD19 experiment in northern Wisconsin, USA. The study sites included eight forests with a large deciduous broadleaf component, three evergreen needleleaf forests, and two wetlands. Average T/ET for the study period averaged nearly 52% in forested sites and 45% in wetlands, with larger values after excluding periods following rain events when evaporation from canopy interception may be expected. A dominance analysis revealed that environmental variables explained on average 69% of the variance of half‐hourly T, which decreased from summer to autumn. Deciduous and evergreen forests showed similar E trajectories over time despite differences in vegetation phenology, and vapor pressure deficit explained some 13% of the variance E in wetlands but only 5% or less in forests. Retrieval of E and T within a dense network of flux towers lends confidence that FVS is a promising approach for comparing ecosystem hydrology across multiple sites to improve our process‐based understanding of ecosystem water fluxes. 

Abstract. The Arctic marine environment plays an important role inthe global carbon cycle. However, there remain large uncertainties in howsea ice affects air–sea fluxes of carbon dioxide (CO₂), partially dueto disagreement between the two main methods (enclosure and eddy covariance)for measuring CO₂ flux ( $F_{\mathrm{CO}{}_2}$). The enclosure method has appearedto produce more credible $F_{\mathrm{CO}{}_2}$ than eddy covariance (EC), but is notsuited for collecting long-term, ecosystem-scale flux datasets in suchremote regions. Here we describe the design and performance of an EC systemto measure $F_{\mathrm{CO}{}_2}$ over landfast sea ice that addresses the shortcomingsof previous EC systems. The system was installed on a 10m tower onQikirtaarjuk Island – a small rock outcrop in Dease Strait located roughly35km west of Cambridge Bay, Nunavut, in the Canadian Arctic Archipelago. Thesystem incorporates recent developments in the field of air–sea gasexchange by measuring atmospheric CO₂ using a closed-path infrared gasanalyzer (IRGA) with a dried sample airstream, thus avoiding the known watervapor issues associated with using open-path IRGAs in low-flux environments.A description of the methods and the results from 4 months of continuousflux measurements from May through August 2017 are presented, highlightingthe winter to summer transition from ice cover to open water. We show thatthe dried, closed-path EC system greatly reduces the magnitude of measured $F_{\mathrm{CO}{}_2}$ compared to simultaneous open-path EC measurements, and for thefirst time reconciles EC and enclosure flux measurements over sea ice. Thisnovel EC installation is capable of operating year-round on solar and windpower, and therefore promises to deliver new insights into the magnitude ofCO₂ fluxes and their driving processes through the annual sea icecycle. 

Abstract Structurally complex forests optimize resources to assimilate carbon more effectively, leading to higher productivity. Information obtained from Light Detection and Ranging (LiDAR)‐derived canopy structural complexity (CSC) metrics across spatial scales serves as a powerful indicator of ecosystem‐scale functions such as gross primary productivity (GPP). However, our understanding of mechanistic links between forest structure and function, and the impact of disturbance on the relationship, is limited. Here, we paired eddy covariance measurements of carbon and water fluxes from nine forested sites within the 10 × 10 km CHEESEHEAD19 study domain in Northern Wisconsin, USA with drone LiDAR measurements of CSC to establish which CSC metrics were strong drivers of GPP, and tested potential mediators of the relationship. Mechanistic relationships were inspected at five resolutions (0.25, 2, 10, 25, and 50 m) to determine whether relationships persisted with scale. Vertical heterogeneity metrics were the most influential in predicting productivity for forests with a significant degree of heterogeneity in management, forest type, and species composition. CSC metrics included in the structure‐function relationship as well as driver strength was dependent on metric calculation resolution. The relationship was mediated by light use efficiency (LUE) and water use efficiency (WUE), with WUE being a stronger mediator and driver of GPP. These findings allow us to improve representation in ecosystem models of how CSC impacts light and water‐sensitive processes, and ultimately GPP. Improved models enhance our capacity to accurately simulate forest responses to management, furthering our ability to assess climate mitigation strategies. 

Abstract A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.