Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19

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 exami...

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Veröffentlicht in:Bulletin of the American Meteorological Society 2021-02, Vol.102 (2), p.E421-E445
Hauptverfasser: Butterworth, Brian J., Desai, Ankur R., Metzger, Stefan, Townsend, Philip A., Schwartz, Mark D., Petty, Grant W., Mauder, Matthias, Vogelmann, Hannes, Andresen, Christian G., Augustine, Travis J., Bertram, Timothy H., Brown, William O. J., Buban, Michael, Cleary, Patricia, Durden, David J., Florian, Christopher R., Iglinski, Trevor J., Kruger, Eric L., Lantz, Kathleen, Lee, Temple R., Meyers, Tilden P., Mineau, James K., Olson, Erik R., Oncley, Steven P., Paleri, Sreenath, Pertzborn, Rosalyn A., Pettersen, Claire, Plummer, David M., Riihimaki, Laura D., Guzman, Eliceo Ruiz, Sedlar, Joseph, Smith, Elizabeth N., Speidel, Johannes, Stoy, Paul C., Sühring, Matthias, Thom, Jonathan E., Turner, David D., Vermeuel, Michael P., Wagner, Timothy J., Wang, Zhien, Wanner, Luise, White, Loren D., Wilczak, James M., Wright, Daniel B., Zheng, Ting
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container_end_page E445
container_issue 2
container_start_page E421
container_title Bulletin of the American Meteorological Society
container_volume 102
creator Butterworth, Brian J.
Desai, Ankur R.
Metzger, Stefan
Townsend, Philip A.
Schwartz, Mark D.
Petty, Grant W.
Mauder, Matthias
Vogelmann, Hannes
Andresen, Christian G.
Augustine, Travis J.
Bertram, Timothy H.
Brown, William O. J.
Buban, Michael
Cleary, Patricia
Durden, David J.
Florian, Christopher R.
Iglinski, Trevor J.
Kruger, Eric L.
Lantz, Kathleen
Lee, Temple R.
Meyers, Tilden P.
Mineau, James K.
Olson, Erik R.
Oncley, Steven P.
Paleri, Sreenath
Pertzborn, Rosalyn A.
Pettersen, Claire
Plummer, David M.
Riihimaki, Laura D.
Guzman, Eliceo Ruiz
Sedlar, Joseph
Smith, Elizabeth N.
Speidel, Johannes
Stoy, Paul C.
Sühring, Matthias
Thom, Jonathan E.
Turner, David D.
Vermeuel, Michael P.
Wagner, Timothy J.
Wang, Zhien
Wanner, Luise
White, Loren D.
Wilczak, James M.
Wright, Daniel B.
Zheng, Ting
description 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.
doi_str_mv 10.1175/BAMS-D-19-0346.1
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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.</description><subject>Airborne instruments</subject><subject>Airborne sensing</subject><subject>Analytical methods</subject><subject>Atmospheric boundary layer</subject><subject>Atmospheric models</subject><subject>Atmospheric processes</subject><subject>Boreal ecosystems</subject><subject>Boundary layers</subject><subject>Canopies</subject><subject>Canopy</subject><subject>Climate models</subject><subject>Connecting</subject><subject>Covariance</subject><subject>Data comparison</subject><subject>Density</subject><subject>Detectors</subject><subject>Eddy covariance</subject><subject>Energy</subject><subject>Energy balance</subject><subject>Experiments</subject><subject>Fluxes</subject><subject>Forest ecosystems</subject><subject>Heterogeneity</subject><subject>Hypotheses</subject><subject>Infrared interferometers</subject><subject>Infrared radiometers</subject><subject>Instrumentation</subject><subject>Large eddy simulation</subject><subject>Large eddy simulations</subject><subject>Lidar</subject><subject>Microwave imagery</subject><subject>Microwave radiometers</subject><subject>National forests</subject><subject>Ocean circulation</subject><subject>Oceanic eddies</subject><subject>Patchiness</subject><subject>Radar</subject><subject>Radiometers</subject><subject>Radiosondes</subject><subject>Scaling</subject><subject>Spatial heterogeneity</subject><subject>Spectroscopy</subject><subject>Surface energy</subject><subject>Surface properties</subject><subject>Towers</subject><subject>Vegetation</subject><subject>Vortices</subject><subject>Water vapor</subject><subject>Water vapour</subject><subject>Weather</subject><issn>0003-0007</issn><issn>1520-0477</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNo9kMFOwzAMhiMEEmNw54JUiXNH3CRNeyxdoZOGkBico7R1RyeWjKQ77MY78IY8Ca2GuNiy_f2_pZ-Qa6AzACnu7rOnVTgPIQ0p4_EMTsgERERDyqU8JRNKKQuHIs_JhfebcWQJTMhLbo3Buu_MOlhq0_x8fWf91vrdOzoMFqZHp4erNT7obbDau1bXGJQ47O0aDXb9IehMkJdFsSrKIptDeknOWv3h8eqvT8nbQ_Gal-Hy-XGRZ8uwZkz0oW4SSuNYat5UTcWAc94KCRG2tAEJEilLG05lJTBpZYJtEjU8QZZoUcWYCjYlt0ffnbOfe_S92ti9M8NLFQkAiKM0GSl6pGpnvXfYqp3rttodFFA1JqfG5NRcQarG5BQMkpujZON76_75SEZUQgrsFymyanA</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Butterworth, Brian J.</creator><creator>Desai, Ankur R.</creator><creator>Metzger, Stefan</creator><creator>Townsend, Philip A.</creator><creator>Schwartz, Mark D.</creator><creator>Petty, Grant W.</creator><creator>Mauder, Matthias</creator><creator>Vogelmann, Hannes</creator><creator>Andresen, Christian G.</creator><creator>Augustine, Travis J.</creator><creator>Bertram, Timothy H.</creator><creator>Brown, William O. 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J. ; Buban, Michael ; Cleary, Patricia ; Durden, David J. ; Florian, Christopher R. ; Iglinski, Trevor J. ; Kruger, Eric L. ; Lantz, Kathleen ; Lee, Temple R. ; Meyers, Tilden P. ; Mineau, James K. ; Olson, Erik R. ; Oncley, Steven P. ; Paleri, Sreenath ; Pertzborn, Rosalyn A. ; Pettersen, Claire ; Plummer, David M. ; Riihimaki, Laura D. ; Guzman, Eliceo Ruiz ; Sedlar, Joseph ; Smith, Elizabeth N. ; Speidel, Johannes ; Stoy, Paul C. ; Sühring, Matthias ; Thom, Jonathan E. ; Turner, David D. ; Vermeuel, Michael P. ; Wagner, Timothy J. ; Wang, Zhien ; Wanner, Luise ; White, Loren D. ; Wilczak, James M. ; Wright, Daniel B. ; Zheng, Ting</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c335t-ad800667a4dbdb31444f5712ef0d1717e039d407b5e8f78ef82d48e38a5b6e953</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Airborne instruments</topic><topic>Airborne sensing</topic><topic>Analytical methods</topic><topic>Atmospheric boundary layer</topic><topic>Atmospheric models</topic><topic>Atmospheric processes</topic><topic>Boreal ecosystems</topic><topic>Boundary layers</topic><topic>Canopies</topic><topic>Canopy</topic><topic>Climate models</topic><topic>Connecting</topic><topic>Covariance</topic><topic>Data comparison</topic><topic>Density</topic><topic>Detectors</topic><topic>Eddy covariance</topic><topic>Energy</topic><topic>Energy balance</topic><topic>Experiments</topic><topic>Fluxes</topic><topic>Forest ecosystems</topic><topic>Heterogeneity</topic><topic>Hypotheses</topic><topic>Infrared interferometers</topic><topic>Infrared radiometers</topic><topic>Instrumentation</topic><topic>Large eddy simulation</topic><topic>Large eddy simulations</topic><topic>Lidar</topic><topic>Microwave imagery</topic><topic>Microwave radiometers</topic><topic>National forests</topic><topic>Ocean circulation</topic><topic>Oceanic eddies</topic><topic>Patchiness</topic><topic>Radar</topic><topic>Radiometers</topic><topic>Radiosondes</topic><topic>Scaling</topic><topic>Spatial heterogeneity</topic><topic>Spectroscopy</topic><topic>Surface energy</topic><topic>Surface properties</topic><topic>Towers</topic><topic>Vegetation</topic><topic>Vortices</topic><topic>Water vapor</topic><topic>Water vapour</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Butterworth, Brian J.</creatorcontrib><creatorcontrib>Desai, Ankur R.</creatorcontrib><creatorcontrib>Metzger, Stefan</creatorcontrib><creatorcontrib>Townsend, Philip A.</creatorcontrib><creatorcontrib>Schwartz, Mark D.</creatorcontrib><creatorcontrib>Petty, Grant W.</creatorcontrib><creatorcontrib>Mauder, Matthias</creatorcontrib><creatorcontrib>Vogelmann, Hannes</creatorcontrib><creatorcontrib>Andresen, Christian G.</creatorcontrib><creatorcontrib>Augustine, Travis J.</creatorcontrib><creatorcontrib>Bertram, Timothy H.</creatorcontrib><creatorcontrib>Brown, William O. 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J.</au><au>Buban, Michael</au><au>Cleary, Patricia</au><au>Durden, David J.</au><au>Florian, Christopher R.</au><au>Iglinski, Trevor J.</au><au>Kruger, Eric L.</au><au>Lantz, Kathleen</au><au>Lee, Temple R.</au><au>Meyers, Tilden P.</au><au>Mineau, James K.</au><au>Olson, Erik R.</au><au>Oncley, Steven P.</au><au>Paleri, Sreenath</au><au>Pertzborn, Rosalyn A.</au><au>Pettersen, Claire</au><au>Plummer, David M.</au><au>Riihimaki, Laura D.</au><au>Guzman, Eliceo Ruiz</au><au>Sedlar, Joseph</au><au>Smith, Elizabeth N.</au><au>Speidel, Johannes</au><au>Stoy, Paul C.</au><au>Sühring, Matthias</au><au>Thom, Jonathan E.</au><au>Turner, David D.</au><au>Vermeuel, Michael P.</au><au>Wagner, Timothy J.</au><au>Wang, Zhien</au><au>Wanner, Luise</au><au>White, Loren D.</au><au>Wilczak, James M.</au><au>Wright, Daniel B.</au><au>Zheng, Ting</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19</atitle><jtitle>Bulletin of the American Meteorological Society</jtitle><date>2021-02-01</date><risdate>2021</risdate><volume>102</volume><issue>2</issue><spage>E421</spage><epage>E445</epage><pages>E421-E445</pages><issn>0003-0007</issn><eissn>1520-0477</eissn><abstract>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.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/BAMS-D-19-0346.1</doi><oa>free_for_read</oa></addata></record>
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subjects Airborne instruments
Airborne sensing
Analytical methods
Atmospheric boundary layer
Atmospheric models
Atmospheric processes
Boreal ecosystems
Boundary layers
Canopies
Canopy
Climate models
Connecting
Covariance
Data comparison
Density
Detectors
Eddy covariance
Energy
Energy balance
Experiments
Fluxes
Forest ecosystems
Heterogeneity
Hypotheses
Infrared interferometers
Infrared radiometers
Instrumentation
Large eddy simulation
Large eddy simulations
Lidar
Microwave imagery
Microwave radiometers
National forests
Ocean circulation
Oceanic eddies
Patchiness
Radar
Radiometers
Radiosondes
Scaling
Spatial heterogeneity
Spectroscopy
Surface energy
Surface properties
Towers
Vegetation
Vortices
Water vapor
Water vapour
Weather
title Connecting Land–Atmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19
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