Statistical Classification of Self‐Organized Snow Surfaces
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Statistical Classification of Self‐Organized Snow Surfaces

Filetype[PDF-1.06 MB]


Details You May Also Like

Details:

  • Journal Title:
    Geophysical Research Letters
  • Personal Author:
  • NOAA Program & Office:
    CIRES (Cooperative Institute for Research in Environmental Sciences)
  • Description:
    Wind‐swept snow self‐organizes into bedforms. These bedforms affect local and global energy fluxes but have not been incorporated into Earth system models because the conditions governing their development are not well understood. To address this difficulty, we created statistical classifiers, drawn from 736 hr of time‐lapse footage in the Colorado Front Range, that predict bedform presence as a function of wind speed and time since snowfall. These classifiers provide the first quantitative predictions of bedform and sastrugi presence in varying weather conditions. We find that the likelihood that a snow surface is covered by bedforms increases with time since snowfall and with wind speed and that the likelihood that a surface is covered by sastrugi increases with time and with the highest wind speeds. Our observations will be useful to Earth system modelers and represent a new step toward understanding self‐organized processes that ornament 8% of the surface of the planet.
  • Keywords:
  • Source:
    Geophysical Research Letters 45(13):6532-6541, 2018
  • DOI:
  • Document Type:
    Journal Article
  • Rights Information:
    Other
  • Compliance:
    Submitted
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files

More +

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.26