CAPSULE SUMMARY A regional-scale observational experiment designed to address how the atmospheric boundary layer responds to spatial heterogeneity in surface energy fluxes.

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model-data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon-Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world's highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

<p align="justify"><span lang="en-US">A new</span><span lang="en-US">ly</span> <span lang="en-US">available</span><span lang="en-US"> Raman</span> <span lang="en-US">l</span><span lang="en-US">idar (Purple Pulse Lidar Systems) for vertical profil</span><span lang="en-US">ing</span><span lang="en-US"> of atmospheric water vapor, temperature and aerosols was </span><span lang="en-US">evaluated</span><span lang="en-US"> during the </span><span lang="en-US">TEAMx pre-campaign</span><span lang="en-US"> (TEAMx-PC22)</span><span lang="en-US"> in</span> <span lang="en-US">s</span><span lang="en-US">ummer 2022 in the Inn </span><span lang="en-US">V</span><span lang="en-US">alley (Austria).</span><span lang="en-US"> TEAMx </span><span lang="en-US">(</span><em><span lang="en-US">Multi-scale </span></em><strong><span lang="en-US">t</span></strong><em><span lang="en-US">ransport and </span></em><strong><span lang="en-US">e</span></strong><em><span lang="en-US">xchange processes in the </span></em><strong><span lang="en-US">a</span></strong><em><span lang="en-US">tmosphere over </span></em><strong><span lang="en-US">m</span></strong><em><span lang="en-US">ountains – programme and e</span></em><strong><span lang="en-US">x</span></strong><em><span lang="en-US">periment) </span></em><span lang="en-US">is a</span><span lang="en-US">n</span><span lang="en-US"> international research program addressing exchange processes in the atmosphere over mountains</span><span lang="en-US"> and their parametrization in numerical weather models and climate models</span><span lang="en-US">.</span> <span lang="en-US">Prior to the</span> <span lang="en-US">multi disciplinary </span><span lang="en-US"> measurement campaign</span><span lang="en-US">,</span> <span lang="en-US">planned </span><span lang="en-US">in 2024/2025, the pre-campaign 2022 was rather </span><span lang="en-US"> performed</span><span lang="en-US"> for testing </span><span lang="en-US">(new)</span><span lang="en-US"> instruments and measurement sites and finding synergies between </span><span lang="en-US">certain devices</span><span lang="en-US">.</span></p> <p align="justify"><span lang="en-US">Th</span><span lang="en-US">e</span> <span lang="en-US">Raman </span><span lang="en-US">lidar system is capable of profiling water vapor and temperature throughout the </span><span lang="en-US">entire </span><span lang="en-US">planetary boundary layer (typically 3 km to 4 km </span><span lang="en-US">agl</span><span lang="en-US">.</span><span lang="en-US"> on summer days) </span><span lang="en-US">continuously</span><span lang="en-US"> with a basic temporal resolution of 10 s and a reasonable vertical resolution of 30 m to 100 m. Depending on conditions and temporal averaging, water vapor profiles could </span><span lang="en-US">even </span><span lang="en-US">be obtained up to ~7.5</span> <span lang="en-US">km </span><span lang="en-US">agl</span><span lang="en-US">.</span><span lang="en-US"> during nighttime. The </span><span lang="en-US">l</span><span lang="en-US">idar</span> <span lang="en-US">s</span><span lang="en-US">ystem was located at the University of Innsbruck (downtown). It was operated side by side with a vertical</span><span lang="en-US">ly</span> <span lang="en-US">star</span><span lang="en-US">ing</span> <span lang="en-US">Doppler wind lidar and a nearby (50 m) scanning Doppler wind lidar on the rooftop of the university building, </span><span lang="en-US">which provide vertical profiles of the vertical wind component at </span><span lang="en-US">a </span><span lang="en-US">1-</span><span lang="en-US">s</span> <span lang="en-US">interval</span><span lang="en-US"> and vertical profiles of the three-dimensional wind vector at </span><span lang="en-US">a </span><span lang="en-US">10-min interval, respectively</span><span lang="en-US">. During th</span><span lang="en-US">e</span> <span lang="en-US">measurement</span><span lang="en-US"> period (Aug 2022 to Sep 2022), operational radiosondes were laun</span><span lang="en-US">c</span><span lang="en-US">hed </span><span lang="en-US">in close proximity, </span><span lang="en-US">at Innsbruck </span><span lang="en-US">A</span><span lang="en-US">irport, roughly 3 km to the west </span><span lang="en-US">of the </span><span lang="en-US">l</span><span lang="en-US">idar site</span><span lang="en-US">. In addition to </span><span lang="en-US">t</span><span lang="en-US">he daily ascent at 2 UTC, radiosondes were launched at </span><span lang="en-US">about </span><span lang="en-US">8, 14 and 20 UTC on selected days </span><span lang="en-US">with </span><span lang="en-US">potentially complex meteorological conditions</span><span lang="en-US">. We present a first assessment of the Raman lidar measurements </span><span lang="en-US">through</span><span lang="en-US"> compari</span><span lang="en-US">sons</span><span lang="en-US"> with the radiosonde data. Together with data from the wind lidars, we also present an interpretation for significant meteorological situations and events, such as </span><span lang="en-US">f</span><span lang="en-US">oe</span><span lang="en-US">hn, a passing front, a thunderstorm and the formation of a convective boundary layer during a warm period.</span></p>

<p>Precise knowledge about the prevailing aerosol content in the atmosphere is very important for several reasons, as aerosols are involved in multiple important processes that not only have a direct impact on air quality, but also influence cloud formation and the earth's radiation budget. Besides that, continuous aerosol observations provide valuable information on atmospheric transport dynamics.<br />Aerosol backscatter coefficient measurements with elastic backscatter lidars are conducted since multiple decades [1], while the implemented retrieval algorithms predominantly refer to the seminal publications by Klett 1985, Fernald 1984 and Sasano 1985 [2,3,4]. The respective inversion algorithm is often simply called the 'Klett inversion', being a main reason why this algorithm is most often adapted. While more sophisticated aerosol lidars (e.g. Raman lidars, HSRL, ...) have been developed since, simple elastic backscatter lidar measurements are still very frequently conducted as they are technically easy to implement, often as a byproduct. In most cases, the corresponding retrieval algorithms still refer to the 'Klett inversion'.<br />Unfortunately, the inversion algorithm by Klett 1985 is afflicted by a sign error. In his publication, the sign error is hidden within a substitute, making it very hard to be recognized, representing a major pitfall. A comprehensive literature review revealed, that large parts of the aerosol lidar community are aware of this problem and have tacitly corrected it or, to a much smaller amount, even referred to an erratum which was published by Kaestner in 1986 [5].<br />However, at the same time and up to this date, a considerable error propagation can be found in literature as well, using and referring to the incorrect algorithm with the sign error included.<br />Therefore, we want to renew the awareness towards this sign error and show a corrected and slightly improved Klett inversion algorithm. In addition, we present the overall implication resulting from the uncorrected inversion algorithm by using exemplary case studies. Depending on the lidar location and prevailing atmospheric conditions, potential errors reach from marginal to major, often preventing error detection solely based on the magnitude of the calculated results. Simple a posteriori corrections are not possible, as the error magnitude depends on multiple factors.</p> <p>[1] T. Trickl, H. Giehl, H. Jäger, and H. Vogelmann. 35 yr of stratospheric aerosol measurements at Garmisch-Partenkirchen: From Fuego to Eyjafjalla-   jökull, and beyond. Atmospheric Chemistry and Physics, 13(10):5205–5225, 2013.<br />[2] James D. Klett. Lidar inversion with variable backscatter/extinction ratios. Appl. Opt., 24(11):1638–1643, June 1985.<br />[3] Frederick G. Fernald. Analysis of atmospheric lidar observations: Some comments. Appl. Opt., 1984.<br />[4] Yasuhiro Sasano, Edward V. Browell, and Syed Ismail. Error caused by using a constant extinction/backscattering ratio in the lidar solution. Appl. Opt., 24(22):3929–3932, November 1985.<br />[5] Martina Kaestner. Lidar inversion with variable backscatter/extinction ratios: Comment. Applied Optics, 25(6):833–835, March 1986.</p>