Matthew D. Shupe, Ph.D. - US grants

This research will increase the fundamental understanding of both temporal and spatial variability of Arctic clouds. Knowledge of Arctic cloud properties is important for understanding the overall energy balance of the Arctic, and how Arctic climate interacts with the global climate system. There have been many short-term field experiments to study Arctic clouds at specific locations, but there is a lack of knowledge regarding the temporal and spatial variability of cloud properties across the Arctic. The longest record of data exists at the North Slope of Alaska ARM site, but this is only at a single location. New data are now available from other ground-based sites that complement the measurements in Alaska and broaden our understanding of Arctic clouds. This group will combine these ground-based measurements at various sites with satellite observations to make a network of cloud observations across the Arctic.

Arctic clouds will be one of the important indicators signifying if, and when, the Arctic system is moving to a new climatic state. The work of data integration and analysis of Arctic cloud observations will yield a significant contribution to the legacy of infrastructure and data that will result from the IPY.

The proposed work specifically addresses the following four questions:
What are the macrophysical and microphysical properties of clouds at various locations in the Arctic? A comprehensive suite of macro- and micro-physical cloud property retrieval algorithms will be applied to Arctic cloud measurements from various surface sites. The derived products will provide a baseline of Arctic cloud properties upon which to identify and understand future change, and to validate models.

How do Arctic cloud properties vary both temporally and spatially? Multi-year records of cloud observations from Barrow, Alaska and Eureka, Canada will be used to investigate inter-annual cloud variability. Additionally, time periods of overlapping measurements at the different stations are expected to provide important insight into the spatial dependence of cloud properties.

How do the spatial and temporal variability of Arctic cloud properties depend upon regional "forcing" parameters? Using ancillary data at each surface site, differences or similarities in cloud properties, and their variability, will be associated with regional meteorological properties that contribute to the forcing of cloud formation to explain the observed variability.

Do satellite retrievals yield similar cloud properties and variability to the coincident surface-based measurements? Cloud properties derived from the surface measurements will be related to retrievals from satellite instruments. Based on this information, the satellite measurements will then be used to expand the analysis to other regions of the Arctic, in particular the locations of possible future or newly coordinated surface sites, such as Tiksi, Russia and NyAlesund, Norway.

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

This award supports a field campaign that will expand the Arctic Observing Network (AON) by adding cloud, atmosphere, and precipitation measurements, and associated higher-order data products, to Summit, Greenland, at the top of the Greenland Ice Sheet. The proposed instrument suite consists of a cloud radar, two microwave radiometers, an Atmospheric Emitted Radiance Interferometer, an X-band precipitation sensor, a ceilometer, a micropulse lidar, and a twice-daily radiosonde program. Measurements from this advanced suite of instruments, combined with some ongoing measurements at Summit, will be input for a number of algorithms to produce climatically useful geophysical data products to support GIS-specific and Arctic-wide research. Data products will include: (1) Atmospheric State - temperature and moisture profiles through the troposphere and lower stratosphere; (2) Cloud Macrophysics - cloud occurrence, vertical boundaries, and temperatures; (3) Cloud Microphysics - cloud phase, water content, optical depth, and particle size; (4) Precipitation - precipitation type and rate; and (5) Cloud Radiative Forcing - impact of clouds on the surface radiation balance. Together these products will augment similar data sets that are produced at other locations across the Arctic. It is anticipated and intended that these data sets will be widely used by the broader scientific community to understand the climates of the Greenland Ice Sheet and the broader Arctic Basin and to validate satellite retrievals and model simulations over Greenland. The "Broader Impacts" of this award are numerous. The proposed observations will contribute to the goals of the Study of Arctic Environmental Change (SEARCH). They will be the first of their kind on the Greenland Ice Sheet and will expand the existing, although modest, network of such measurements across the Arctic. Uncertainty in polar cloud properties is a major deficiency in current models of polar climate; the proposed observations of cloud macro- and micro-physics will provide some of the necessary constraints for improving model cloud algorithms. This project will provide important field work and data processing experience for graduate students at the University of Wisconsin, University of Colorado and University of Idaho. In addition, data and experiences from the field program will be integrated into undergraduate coursework at the University of Idaho and summer workshops at the University of Wisconsin.

This project will focus on in situ and remote sensing measurements of wintertime clouds over the Park Range of the Rocky Mountains in northern Colorado. These clouds are generally mixed-phase; the combination of ice, liquid and water vapor presents challenges both to measurements and modeling, and consequently, to understanding their impact on atmospheric radiation and on precipitation. The Colorado Airborne Multi-Phase Cloud Study (CAMPS) will use the Wyoming King Air research aircraft instrumented with both remote (cloud radar and cloud lidar) and in situ sensors (cloud and particle probes, total water hygrometer) to elucidate the vertical and horizontal structure of cold mixed-phase clouds.

Intellectual Merit:

The data gathered during CAMPS will include information about macro- and microphysical parameters of mixed-phase clouds obtained by both in situ and remote-sensing methods. These data will be analyzed to address a number of important questions about the structure, properties and impacts of mixed-phase clouds. Specific goals include:

1. To assess the vertical and horizontal structure and spatial and temporal variation of cloud properties (particle size distribution, ice and liquid water content, particle habit) in liquid, mixed-phase and precipitating clouds at a mid-latitude continental site with complex terrain during winter.

2. To assess the impact of topography and associated variations in vertical forcing on cloud generation and cloud properties.

3. To develop a data set that provides the information necessary for improving the representation of mixed-phase clouds in cloud-resolving and climate models.

4. To provide correlative data for validation of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program mobile facility and the National Aeronautics and Space Administration A-Train satellite-borne remote sensors.

5. To provide observational confirmation of the redistribution of snowfall associated with riming inhibition due to enhanced CCN.


Broader Impacts:

Ultimately, by enhancing the community's understanding of cloud-scale processes, the data from CAMPS will be the basis for improvements in the representation of clouds in global climate models. This will lead to more accurate calculations of current and future climate. In addition the CAMPS project will contribute to both formal and informal education at a number of levels. At least one graduate student from each of the participating universities will be involved with the field work and/or data analysis related to this project. The investigators will include undergraduates from their institutions in flight-planning and/or meteorology exercises related to CAMPS when possible. Formal educational opportunities for elementary school students will be coordinated by the Storm Peak Laboratory staff, including visits to the laboratory and aircraft and classroom exercises. Outreach activities will include signage at the Steamboat Springs Ski Resort, an interactive display at the gondola building and coordination with the 2011 Steamboat Weather Summit.

The Arctic lower troposphere represents a sensitive balance between surface, atmospheric boundary layer, and cloud processes, forming a cloud-ABL-surface (CAS) system. Changes to a component in this system will produce physical responses in the other components, culminating in the net system response to the change. In order to accurately simulate the net CAS contributions and responses to a component change, such as to the predicted change from primarily multi-year sea-ice to first-year sea-ice, the process interactions between the CAS components must be well understood and quantitatively represented in coupled climate models. Unfortunately, the understanding of various key processes and their interactions is very nascent, leading to poor representations in current global or regional climate models. Hence, significant uncertainties exist in modeled parameters such as cloud fraction, ice water path, and liquid water path, resulting in surface cloud radiative forcing that varies by 40 W m-2 among models and modeled surface turbulent heat fluxes that have poor correlations with observations. Even basic surface parameters, such as albedo, are often not physically represented and provide a source of significant errors to the CAS system.
This proposal focuses on understanding the complex processes and interactions in the Arctic CAS system using existing observations and process models and on improving key parameterizations in these process models. A broad range of existing in-situ and remotely sensed observational data will be used in the analyses. The process modeling will be done with multiple-resolution configurations of the Weather and Research Forecasting Model (WRF). Observational analyses and model evaluations will be conducted using process-oriented diagnostics -- diagnostics that reveal physical relationships directly relevant to a process and/or parameterization. Through informal collaboration with the National Center for Atmospheric Research (NCAR), preliminary evaluations of the ability of a state-of-the-art global climate model (GCM), the Community Climate System Model (CCSM), to faithfully represent these process interactions will also be performed, providing initial insight as to whether key processes and relationships found in observations and process models are also represented in CCSM.

The project will utilize results from several Arctic measurement sites, including long-term observations at Barrow, Alaska, and shorter-term observations from Summit, Greenland, and two measurement campaigns over the Arctic Ocean to improve upon previous estimates of Arctic aerosol-cloud interactions. To do this a critical first step will involve understanding the conditions under which surface aerosol conditions, as generally used in the compilation of statistical datasets addressing this issue, are comparable to those at cloud level. Using a variety of techniques, the distinction between surface-coupled and decoupled cloud states will focus evaluation of aerosol-cloud interactions on appropriate cases, reducing statistical contamination. From these cases, a statistical evaluation will be performed to reveal co-variation between key cloud (e.g. liquid water path, ice water path) and aerosol (e.g. concentration, size, hygroscopicity) properties. Combined with surface radiation measurements and idealized radiative transfer simulations, the results from this evaluation will provide an improved estimate of the net radiative impact of aerosols on Arctic clouds. Additionally, it will provide an overview of the seasonal evolution and surface-state dependence of these relationships. Outreach plans include several visits to Arctic regions, with a focus on the North Slope of Alaska and Greenland. The primary aim of these visits is to disseminate information relevant to the proposed research to seminar audiences consisting of local people (including underrepresented native people), primary school students, and local officials. A secondary aim of these visits is to give Arctic researchers (particularly early career researchers) who have never had a chance to visit the Arctic themselves an opportunity to see firsthand the region on which their efforts focus. This project will also support two early career scientists at the University of Colorado.

In 2010, the observatory at Summit, Greenland, in the center of the Greenland Ice Sheet (GIS), was expanded to include a comprehensive suite of cloud-atmosphere observing instruments including microwave and infrared spectrometers, cloud radar, depolarization lidar, ceilometer, precipitation sensor, sodar, and a twice-daily radiosonde program. This observing effort was termed ICECAPS (Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit). A continuation of this project is proposed here, with moderate enhancements to include atmospheric aerosol observations. Measurements from this expanded instrument suite will be used to derive critical baseline atmospheric data products including:
* Atmospheric State - tropospheric temperature, moisture, and wind profiles
* Aerosols - concentration of total particles and cloud condensation nuclei
* Cloud Macrophysics - occurrence, vertical boundaries, temperature
* Cloud Microphysics - phase, water content, and characteristic particle size
* Precipitation - type and rate
Together these products, when combined with similar ongoing measurements at Summit, can be used to study processes that impact the surface energy budget and precipitation at the site, as well as addressing questions related to atmospheric stability, cloud phase composition, the persistence of stratiform clouds, and aerosol-cloud interactions. It is further anticipated that these observations will continue to be used by a broad cross-section of the scientific community to promote understanding of GIS and Arctic climate, validate satellite observations, and evaluate model simulations. Graduate students play significant roles in most aspects of this project, gaining valuable experience with polar field work, operating instruments, and processing data. In addition, this research team has developed a unique education and outreach plan to work with students from local schools using simple, proxy instrumentation to help develop their understanding of atmospheric principles and observations, and to enhance the scientific curriculum in their schools via a wide range of outreach activities.

Funds are provided to characterize the interactions among the atmospheric state, cloud properties, radiation, and precipitation at Summit, Greenland. The objective is to investigate a number of important cloud-related processes, how these interact with the Arctic climate system, and their impact on the surface energy and mass budgets. Specific foci will include:
1) Low-cloud persistence mechanisms that lead to long-lived Arctic stratiform clouds, which interact strongly with the atmospheric structure and surface energy budget;
2) Cloud-phase partitioning, which determines the cloud microphysical composition and, ultimately, the effects that clouds have on atmospheric radiation and the hydrologic cycle; and
3) Precipitation partitioning, in order to understand the different modes of precipitation at Summit and how these impact the total surface accumulation.
To address these topics, this project will utilize detailed observations from a suite of ground-based remote sensors deployed at Summit as part of the NSF/AON-funded ICECAPS project in combination with data from satellite-borne active remote sensors. High-resolution numerical modeling will also be used to investigate many of the fine-scale cloud processes and their mesoscale influences. These studies over the Greenland Ice Sheet will also be considered within the context of similar measurements and model studies made at other Arctic locations in order to understand these important processes over Summit and, in a more general sense, across the Arctic.

Atmospheric water vapor, clouds, and precipitation greatly affect the surface energy and cryospheric mass balances in the Arctic, and are responsible for much of the variability in these balances. It is thought that recent rapid melting of Arctic sea ice may be driven, in part, by changes in cloud cover and radiation. Cloud-related processes and feedbacks are known to be one of the greatest sources of uncertainty in global climate models, and these shortcomings have been clearly identified in model simulations over the Arctic. Thus, the results of this project should improve our understanding of Arctic cloud processes and their inclusion in climate models, which, in turn, will improve predictability.

As broader impacts of this research, the project will provide important data analysis and integration experience for four new graduate students at the participating universities. In addition, data and results from this study will be integrated into undergraduate coursework and summer workshops for high school students and teachers.

A better understanding of Arctic cloud and aerosol properties, structure and formation is essential to understand the specific response of the Arctic in the context of global climate change. A lack of coherent high vertical and temporal resolution observations of cloud particles, aerosols moisture advection (i.e. water vapor) and thermodynamics, creates large uncertainties in current model estimates of cloud properties and inhibits our understanding of cloud radiative and precipitation impacts on the surface. As a result, current weather and climate models poorly parameterize clouds over the Arctic and more specifically over the Greenland Ice Sheet (GIS). A reduction in this uncertainty is particularly important above the GIS, where clouds act as sinks and sources to the ice mass balance by modulating the surface radiation budget and available precipitable water. To gain the understanding necessary to reduce this uncertainty, a new autonomous multi-wavelength, polarized Raman lidar is proposed for development and deployment at the NSFʼs observatory in Summit, Greenland. The new lidar observations will employ multiple wavelengths and polarizations to observe elastic and inelastic scattering from the Arctic atmosphere enabling regular retrieval of temperature, water vapor and extinction profiles. This combination of observational capability will create a coherent dataset of high-resolution thermodynamic, cloud and aerosol observations through the Arctic troposphere and lower stratosphere above Summit. Broadly, this addition to the NSF Observatory at Summit, Greenland as part of the larger Arctic Observing Network fits well within the Study of Environmental Arctic Change (SEARCH) implementation plan. Thus, this instrument will significantly enhance Arctic observing infrastructure and advance observations and understanding of change in the Arctic. The proposed instrumentation and observations are the first of their kind on the GIS and will expand the existing, although modest, network of such measurements across the Arctic. This project will also provide a unique experience and educational opportunity through the combination of fieldwork and subsequent data processing for graduate students at the University of Colorado.

Energy fluxes to the sea ice, and the processes that control them in time and space, comprise some of the largest uncertainties in current models of the central Arctic system and are likely changing as the sea ice thins. This project will make observations to provide the type of information that model developers need for representing emergent Arctic processes. These observations will be the first set of comprehensive, coupled atmosphere-ice-ocean energy and momentum flux measurements collected within a well-defined network. They will enable a process-based understanding of ice thermodynamics and dynamics via synergistic use of a coupled model. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition is a tremendous opportunity to leverage large US and international investments

MOSAiC is motivated by the changing Arctic system and declining sea ice, and their significant implications for the global climate system and numerous stakeholders. The initiative seeks to address leading deficiencies in model representation of coupled, atmosphere-ice-ocean processes in the Arctic system through intensive, year-round observations from a drifting station in the central Arctic and coordinated multi-scale modeling. This project will examine the detailed interplay of sea-ice thermodynamic and dynamic processes and how they control the state of the ice over a full year. This project will entail an observational array of five nodes installed at approximately 15 km separation in the central Arctic sea ice, each of which has systems to measure continuously the states of the upper ocean and lower atmosphere, the heat and momentum fluxes from the ocean and atmosphere to the ice, and the ice thermodynamic state and mass balance. A network of position buoys will be used to measure ice movement and deformation across the observing domain. Regional, coupled-system model simulations will provide the means to synthesize observational information towards process understanding. Together these tools will be used to build comprehensive sea ice energy, upper ocean heat, and sea-ice momentum budgets, examine how these co-vary in space and time over all seasons, and develop temporally-evolving process relationships among multiple key parameters. They will use the detailed observations and coupled regional model to examine how energy transfer processes (thermodynamics) are influenced by sea-ice deformation (dynamics) on sub-seasonal to seasonal time scales, and they will assess sea-ice predictability related to dynamic and thermodynamic process relationships, using a full year of quasi-operational, 10-day sea-ice forecasts.

Improved predictive models are an important means for addressing major societal needs related to Arctic change and declining sea ice. The project will provide an observational and process-based foundation for model development that has been called for by model developers and international experts. Moreover, it will offer insight into the sources of sea ice predictability, which will help to constrain future research pathways for improved sea ice models. The observations will enable a wide array of coupled system research that reaches well beyond the proposed project to impact research on other aspects of the Arctic physical, biological, and biogeochemical systems. Moreover, this project will support development towards autonomous ocean and atmospheric flux measurements that will help fill critical gaps in the Arctic observing network. Educational content developed around the project's research themes will support student learning on the physics of the Arctic system and enable broader scientific outreach efforts.