MC3E
Midlatitude Continental Convective Clouds Experiment (MC3E)
22 April 2011 - 6 June 2011
Lead Scientist: Michael Jensen
Observatory: sgp, sgp
Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earth’s climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes. To this end, the Midlatitude Continental Convective Cloud Experiment (MC3E), a joint field program involving NASA Global Precipitation Measurement Program and ARM investigators, was conducted in south-central Oklahoma during the April to May 2011 period. The experiment leveraged from the unprecedented observing infrastructure available in the central United States, combined with an extensive sounding array. Our goal was to provide the most complete characterization of convective cloud systems and their environment that had ever been obtained, providing constraints for model cumulus parameterizations that had never before been available. Several different components of convective processes tangible to the convective parameterization problem were targeted, such as pre-convective environment and convective initiation, updraft/downdraft dynamics, condensate transport and detrainment, precipitation and cloud microphysics, influence on the environment and radiation, and a detailed description of the large-scale forcing. This intensive observation period used a new multi-scale observing strategy with the participation of a network of distributed sensors (both passive and active). The approach was to document in 3D not only precipitation, but also clouds, winds, and moisture in an attempt to provide a holistic view of convective clouds and their feedback with the environment. A goal was to measure cloud and precipitation transitions and environmental quantities that are important for convective parameterization in large-scale models and cloud-resolving model simulations. With unprecedented observing capabilities comes a greater responsibility to develop synthesis data products suitable for model studies and evaluation. Thus, special emphasis was given to the development of a systematic dialogue with the ASR modeling group for the development of such 3D data products.
This experiment seeks to use a multi-scale, multi-frequency, multi-platform observational strategy to provide unprecedented detail in characterizing convection and its environment, providing constraints for model cumulus parameterizations and spaceborne measurements of precipitation over land that have never before been available. The key goals are to:
- Advance the understanding of the different components of convective simulation and microphysical parameterization
- Improve the fidelity of rainfall estimates over land
Co-Investigators
Anthony Del Genio |
Scott Giangrande |
Pavlos Kollias |
Timeline
- Child Campaign
Related Publications
2024
O'Brien JR, M Grover, R Jackson, ZS Sherman, SM Collis, A Theisen, BA Raut, M Tuftedal, and D Feldman. 2024. Colorado State University (CSU) X-Band Precipitation Radar Plan Position Indicator Data Processed with Corrected Moments in Antenna Coordinates (CMAC) Value-Added Product Report. Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-TR-313. 10.2172/2483333.
Sherman Z, M Grover, R Jackson, S Collis, J O’Brien, C Homeyer, R Chase, TJ Lang, D Stechman, A Sockol, K Muehlbauer, J Thielen, A Theisen, S Gardner, and DB Michelson. 2024. "Effective Visualization of Radar Data for Users Impacted by Color Vision Deficiency." Bulletin of the American Meteorological Society, 105, 10.1175/BAMS-D-23-0056.1.
Research Highlight
2023
Dolan B, S Saleeby, S Rutledge, S van den Heever, and K Van Valkenburg. 2023. "A statistical framework for evaluating rain microphysics in model simulations and disdrometer observations." Journal of Geophysical Research: Atmospheres, 128(18), e2023JD038902, 10.1029/2023JD038902.
Gupta A, A Deshmukh, D Waman, S Patade, A Jadav, V Phillips, A Bansemer, J Martins, and F Gonçalves. 2023. "The microphysics of the warm-rain and ice crystal processes of precipitation in simulated continental convective storms." Communications Earth & Environment, 4(1), 226, 10.1038/s43247-023-00884-5.
Waman D, A Deshmukh, A Jadav, S Patade, M Gautam, V Phillips, A Bansemer, and J Jakobsson. 2023. "Effects from time dependence of ice nucleus activity for contrasting cloud types." Journal of the Atmospheric Sciences, 80(8), 10.1175/JAS-D-22-0187.1.
2022
Waman D, S Patade, A Jadav, A Deshmukh, A Gupta, V Phillips, A Bansemer, and P DeMott. 2022. "Dependencies of Four Mechanisms of Secondary Ice Production on Cloud-Top Temperature in a Continental Convective Storm." Journal of the Atmospheric Sciences, 79(12), 10.1175/JAS-D-21-0278.1.
Saleeby S, B Dolan, J Bukowski, K Van Valkenburg, S van den Heever, and S Rutledge. 2022. "Assessing Raindrop Breakup Parameterizations Using Disdrometer Observations." Journal of the Atmospheric Sciences, 79(11), 10.1175/JAS-D-21-0335.1.
Research Highlight
Collis SM, JJ Helmus, ZS Sherman, and RC Jackson. 2022. Corrected Moments in Antenna Coordinates (CMAC) X-SAPR Technical Report. Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-TR-283. 10.2172/1898601.
Wang J and M Zhang. 2022. "The Impact of Constrained Data Assimilation on the Forecasts of Three Convection Systems During the ARM MC3E Field Campaign." Monthly Weather Review, , 10.1175/MWR-D-22-0144.1. ONLINE.
Patade S, D Waman, A Deshmukh, A Gupta, A Jadav, V Phillips, A Bansemer, J Carlin, and A Ryzhkov. 2022. "The influence of multiple groups of biological ice nucleating particles on microphysical properties of mixed-phase clouds observed during MC3E." Atmospheric Chemistry and Physics, 22(18), 10.5194/acp-22-12055-2022.
View All Related Publications
Campaign Data Sets
IOP Participant | Data Source Name | Final Data |
---|---|---|
Mary Jane Bartholomew | Video Disdrometer | Order Data |
Jennifer Comstock | High Volume Precip Spectrometer | Order Data |
Jennifer Comstock | High Volume Precip Spectrometer | Order Data |
Xiquan Dong | Cloud Aerosol Precip Spectrometer(CAPS)/Cloud Imaging Probe (CIP) | Order Data |
Xiquan Dong | S-band radar (NEXRAD) | Order Data |
Michael Jensen | Convective Available Potential Energy (CAPE) | Order Data |
Michael Jensen | Microwave Radiometer | Order Data |
Michael Jensen | Radiosonde Data | Order Data |
Mathew Schwaller | GPM Ground Validation Autonomous Parsivel Unit (APU) MC3E | Order Data |
Mathew Schwaller | GPM Ground Validation Two-Dimensional Video Disdrometer (2DVD) MC3E | Order Data |
Jason Tomlinson | Ultra High Sensitivity Aerosol Spectrometer- G1 Aircraft | Order Data |
Jason Tomlinson | Ultra High Sensitivity Aerosol Spectrometer- G1 Aircraft | Order Data |
David Turner | AERI Retrieved Thermodynamic Profiles and Cloud Properties | Order Data |
Christopher Williams | 449 MHz Profiler | Order Data |
Christopher Williams | S-band Radar | Order Data |
Christopher Williams | Surface Meteorology- T0 Site | Order Data |
Christopher Williams | Vertical Air Motion | Order Data |
Christopher Williams | laser disdrometer | Order Data |
Shaocheng Xie | Single Column Model Forcing | Order Data |