CASIE Science - Overview

The Characterization of Arctic Sea Ice Experiment (CASIE) is being conducted to support a larger NASA-funded research effort titled "Sea Ice Roughness as an Indicator of Fundamental Changes in the Arctic Ice Cover: Observations, Monitoring, and Relationships to Environmental Factors." Below, we provide an overview of this project and the specific objectives and plans for CASIE.

1. Project Overview

Recent observations and modeling studies suggest large decreases in Arctic sea-ice thickness in recent years, but uncertainty remains in terms of overall loss of ice mass versus redistribution of mass within the Arctic Basin. "Ridging and rafting" of the ice cover, where ice is piled up due to compression of the ice pack, is one mechanism for such mass redistribution. In general though, the combination of observations and modeling tends to agree that some thinning of the ice cover has occurred. In addition to changes in ice thickness and mass, other related changes in properties are likely if the ice pack is undergoing fundamental changes such as a shift to a largely seasonal sea-ice cover. Ridging characteristics, changes in frequency of rafting versus ridging, the responses of the pack to pressure forces, and momentum exchange between ice, atmosphere and ocean could be expected to vary over time. In turn, changes in these ice topography and related roughness conditions affect dynamic and thermodynamic properties. The degree to which such changes might act as positive or negative feedbacks for ice growth is not known.

Since the macro-scale (meters to tens of meters) roughness characteristics of sea ice are a function of a combination of mechanical interactions and ice growth and melt processes, observations and monitoring of ice roughness will provide new insights into such basic issues as the magnitude and distribution of ice thinning, changes in the nature and amount of ice of different ages, and modifications of the ice cover in ways that might enhance or reduce the effects of rising air temperatures. On a larger scale, sampled via aircraft or satellite, monitoring of the distributions of ridged and rubbled ice would help address questions such as the degree to which changes in Arctic ice mass reflect melting or less growth versus redistribution of mass into regions such as areas north of the Canadian Archipelago.

Our project's research combines the use of a variety of remote sensing methods, including satellite observations and unmanned aircraft systems (UAS), to provide fundamental new insights into ice roughness on the scale of meters to 10's of meters in the context of larger-scale environmental forcings. Our intent is to be able to relate scattering and emission properties to surface roughness and hence to geophysical properties that are difficult or impossible to observe directly. Fine scale and in situ observations are essential to understanding physical processes at work, but it is necessary to know how processes aggregate over the scale of the types of spaceborne observations that we must rely upon for regional and hemispheric-scale monitoring. In keeping with this, the project has three main goals:

  • Determine the degree to which ice-roughness monitoring via remote sensing can detect basic changes in ice conditions such as ice thickness and ice age.
  • Investigate relationships between ice roughness and factors affecting the loss or maintenance of the perennial ice cover.
  • Determine how roughness varies as a function of different kinematic conditions and ice properties.

To address these goals, we are investigating the following key research questions:

  • What are the relationships between radar backscatter, passive microwave emission, and surface roughness characteristics?
  • How does roughness vary over the life cycle of ice and how is this affected by ice formation zone, ice age, and ice thickness?
  • What are the relationships between roughness and kinematic conditions over different length scales?
  • What are the potential applications of roughness observations and monitoring for sea ice modeling?
  • What are the characteristics of fine temporal- and spatial-scale ice motion, in terms of relevance for open water production and simulations?

The approach we are using combines high-resolution aerial observations with satellite data and forward modeling to document the characteristics and evolution of ice roughness over a range of space and time scales. With this information in hand, we can interpret roughness in terms of other ice conditions, improve our understanding of effects on overall ice mass, and develop climate model parameterizations to better simulate sea ice conditions.

2. CASIE

The Characterization of Arctic Sea Ice Experiment (CASIE) mission will contribute to the overall project by providing an unprecedented suite of high-resolution data over a range of sea ice conditions within the Fram Strait region between northern Greenland and Svalbard. These data will include surface topography observations, standard electro-optical (EO) imagery, synthetic aperture radar (SAR) imagery, and surface reflectance and surface temperature measurements.

A key aspect of CASIE is that it will provide these data at finer spatial resolution than previously obtained, over difficult to access locations in the high Arctic. Satellites cannot provide the desired simultaneous combination of sensor types and resolution. Piloted aircraft typically fly too high and too fast to yield the fine-scale sampling rates and mapping patterns required by our project. Also, flights over the areas of interest would require use of large multi-engine aircraft, placing aircraft and crew at risk by flying in dangerous Arctic conditions far from the nearest suitable airfield. For these reasons, the choice was made to use UAS for CASIE.

The NASA SIERRA UAS is the aircraft of choice for our needs. Like other UAS of its class, the SIERRA is able to fly long distances at low altitudes, with high maneuverability and relatively slow flight speed. However, unlike smaller UAS, the SIERRA is particularly well suited for CASIE, since it provides a much larger payload capacity compared to other relatively small UAS, while still offering sufficient flight range, availability, and deployment costs. A combination of sensors can be carried that would be too large and heavy to deploy on a single, smaller UAS. This large payload is critical to meeting our need for sea ice observations acquired simultaneously, using multiple sensors. The need for simultaneous measurements (compared to, for example, carrying out several flights using different instruments) arises from the fact that the ice pack in Fram Strait is highly dynamic, with fast ice drift and potential for ridging and rafting.

The suite of sensors and data systems to be carried onboard the SIERRA during CASIE include:

  • Laser altimeter/surface height profiler (non-scanning) system consisting of two lasers acquiring simultaneous but laterally offset laser tracks, GPS, inertial measurement unit, and payload computer.
  • Imaging synthetic aperture radar with video camera.
  • Two digital cameras.
  • Up- and down-looking broadband shortwave radiation pyranometers.
  • Up- and down-looking shortwave spectrometers.
  • Down-looking temperature sensors (pyrometers).

Flights of the SIERRA will take place from Ny-Alesund, Svalbard. This location was selected because it provides access to ice with a range of thicknesses, age, and ridging characteristics within acceptable flight range of the UAS. The SIERRA will typically fly to the north and northwest, passing over open ocean and the marginal sea ice zone to target the variety of thick, old ice expected to be within the Fram Strait ice outflow region. Once over the desired ice conditions, most of the flight patterns will involve closely spaced, adjacent flight tracks to provide mapping coverage. We also hope to encounter cases where active ice compression is underway, with the goal of observing changes in ridging and rafting over short time periods. After the completion of each mission, data will be downloaded from the aircraft's data systems and analyzed on site as well as uploaded to our project web site.