Micro2Macro: Origins of Climate Change Uncertainty Workshop

Microphysical cloud and aerosol processes are a leading source of uncertainty in climate projections due to their effects on cloud macrophysical properties. Most of our uncertainty in historical anthropogenic radiative forcing is due to uncertainty in anthropogenic aerosol indirect forcing. This contributes to substantial uncertainty in the degree of climate sensitivity that can be inferred from the historical record of surface air temperature, and thus causes uncertainty in future climate projections. Similarly, global climate feedback uncertainty is mostly due to uncertainty in cloud feedback. Ultimately, clouds, precipitation, convection, and aerosols are dependent on microscale processes responding to large-scale environmental changes. The choices we make representing microscale processes with climate model parameterizations also result in substantial feedback and forcing uncertainty in simulations. Next-generation, km-resolution global models will remain challenged to represent such microphysical processes through parameterizations. We urgently need observational and modeling frameworks that target robust quantification and reduction of microphysical uncertainty and how it translates into uncertainty in predictions of macrophysical cloud properties and climate change.

Objectives

The Micro2Macro workshop will develop the foundation of a new framework to confront and evaluate climate models using observations to improve our process-based understanding and strategically reduce climate projection uncertainty. Workshop themes will include:

• Identifying key structural model differences that cause cascading uncertainties from microphysical processes to macrophysical cloud properties and climate change
• Evaluating the scale mismatch between in-situ observations, remotely sensed microphysical properties, and macrophysical climate properties
• Quantifying and constraining the effects of microphysical process uncertainty on climate projection uncertainty
• Investigating connections between modeling and observations of aerosol, clouds and precipitation across the globe

Our framework will evaluate multiple microphysical to macrophysical couplings including, but not limited to, a) marine (especially biogenic) aerosol emission control of pre-industrial aerosol loading, and the potential to affect future climate; b) ice formation processes and their impacts on precipitation; c) the microphysical reasons marine cloud feedback dominates overall cloud feedback; d) the way microphysical processes impact the marine atmosphere and ocean to alter cloud regimes and evolution.

Target Participants 

Attendance is open to all with a target workshop size of 50-80 participants. Participation is sought from throughout the atmospheric sciences, including those with expertise in: aerosol, cloud and precipitation microphysics; radiative transfer; cloud dynamics; ground-based, airborne and remote-sensing observations; aerosol, cloud, and climate modeling and feedback analysis; and machine learning. Attendees across career stages and identities (e.g., gender, race, ethnicity, orientation) are welcome. Applications for limited travel support are available through registration for students, early-career scientists (within 10 years of the last degree), and scientists from under-represented communities, and these participants will be encouraged to participate in leadership roles such as facilitating workshop discussions.

Location

Laramie is a small college town in the central Rocky Mountains, full of outdoor activities with a lively cultural scene. A group excursion to the Medicine Bow-Routt National Forest is planned after the workshop.

Workshop Format

The 2.5 day workshop will include plenary sessions with invited and contributed talks, poster sessions, and breakout group discussions. Emphasis will be placed on identifying and refining analysis frameworks that may be a mix of established and novel approaches. Micro2Marco will be a hybrid workshop, with in-person and virtual participation options. 

Sessions

• What's Wrong with Microphysics in Climate Models? This session focuses on the microphysical properties that climate models struggle to simulate and the consequences of those struggles for cloud macrophysics, global radiative fluxes and circulation, and other quantities that impact climate projections. It also focuses on the reasons why these microphysics parameterizations struggle

• Can We Even Observe Microphysics? This session focuses on summarizing the current capabilities and limitations of observational techniques for the characterization of microphysical properties and processes in the surface-atmosphere system toward the validation and uncertainty evaluation in climate model representations of microphysics. The focused measurement techniques include but are not limited to experimental laboratory measurements, airborne/ ground-based in-situ measurements, and remote sensing from any platform

• How are Observations Being Used to Improve Models? This session focuses on surveying existing and emerging frameworks and best-practices for utilizing observational data to address and reduce uncertainty in climate model representations of microphysics. This session will explore how structural deficiencies in models, such as missing or inadequately represented microphysical processes, can be identified and addressed by integrating more realistic process representations or by employing machine learning techniques to reduce computational costs and improve model skill. Contributions that both quantify parametric uncertainties and offer innovative solutions to tackle these modeling challenges are highly encouraged

• Developing Better Protocols for Process Observations and Model Constraints. Due to the complexity of the process interactions in the atmosphere and the operational and technical challenges of field campaign deployments, laboratory experiments, and remote sensing networks, there is a need to develop improved protocols and design processes for observations that can move the needle on critical uncertain processes in climate models. Contributions discussing existing or proposed approaches to integrate atmospheric models (of any scale) into the design of experiments, field campaigns, and observational networks are especially encouraged

Outcomes

The workshop will produce a US CLIVAR report highlighting the state of the science, gaps, and recommended next steps including scoping of frameworks for the following purposes:

• Evaluation of model microphysics: This deliverable will seek the development and standardization of model evaluation procedures and data sets to facilitate comparison between in situ observations, remote sensing, and climate models
• Quantification of microphysical remote sensing retrieval uncertainty: This deliverable will develop suggestions for a probabilistic framework to evaluate remote sensing retrievals of microphysical properties that allow a characterization of uncertainty globally, beyond the relatively small set of direct observations
• Identification of laboratory and field observation measurement gaps: This deliverable will identify gaps in current lab, in situ, and ground-based observational capabilities, that are priorities for reducing microphysical process uncertainties, including recommending future field campaigns and identifying needs for enhanced analysis of previous campaigns
• Application of impactful, traceable, and interpretable uses of machine learning and artificial intelligence to enhance the use of observations to better inform microphysics parameterizations in models

Scientific Organizing Committee

Daniel McCoy, University of Wyoming (Co-chair)
Rob Wood, University of Washington (Co-chair)
Susannah Burrows, DOE PNNL
Ann Fridlind, NASA GISS
Adele Igel, University of California, Davis
Coty Jen, Carnegie Mellon University
Leighton Regayre, University of Leeds / UK Met Office 
Masanori Saito, University of Wyoming 
Duncan Watson-Parris, University of California San Diego

Program Organizing Committee

Alyssa Cannistraci, US CLIVAR
Mike Patterson, US CLIVAR
Jessica Martinez, UCAR CPAESS

Workshop Sponsors