33788 – Spatial, Temporal and Depth Distribution of Snow Properties in the Crater Lake Snowpack

Investigator’s Annual Reports (IAR’s) for Crater Lake National Park

Spatial, Temporal and Depth Distribution of Snow Properties in the Crater Lake Snowpack

 

Report Number: 33788

Permit Number: CRLA-2005-SCI-0001

Current Status: Checked in

Date Received: Dec 28, 2005

Reporting Year: 2005

Principal Investigator: Ms Lora Koenig, University of Washington, Department of Earth and Space Sciences, Seattle, WA

Additional investigator(s): Julia C. Jarvis

Park-assigned Study Id. # CRLA-00004

Permit Expiration Date: Jun 30, 2005

Permit Start Date: Jan 01, 2005

Study Starting Date: Jan 01, 2005

Study Ending Date: Jun 30, 2005

Study Status: Completed

Activity Type: Research

Subject/Discipline: Glaciers

Objectives: There are three main purposes of this study:

a) to investigate the changes of snow’s thermal conductivity with depth

b) to create a highly spatially sampled snow grain size dataset

c) to create an in-situ dataset that can be used with a variety of space-borne sensors

d) to determine the temporal variability of nitrate (NO3-) isotopes in snow at Crater Lake

e) to test field methods for later use in Antarctica

General Purpose:

Remote sensing of snow properties is the future of snow science. Satellites have the ability to determine spatially distributed snow properties on a daily basis in inhospitable areas (Dozier and Painter, 2004). However there is a dearth of in-situ measurements collected specifically for satellite ground tracks. This research will begin to fill in this void of information by collecting a spatial and depth distributed ground dataset for sensor calibration. This dataset will include depth dependant information on thermal conductivity and snow grain size. This depth component is important for satellite sensors, such as passive microwave sensors, that record emission some distance into the snow. The deep snow pack at Crater Lake National Park is an ideal location for studying changes in snow parameters with depth.