DOES INCREASING HORIZONTAL RESOLUTION PRODUCE MORE SKILLFUL FORECASTS?

DOES INCREASING HORIZONTAL RESOLUTION PRODUCE MORE SKILLFUL FORECASTS? This paper examines the impacts of increasing horizontal resolution on the performance of mesoscale numerical weather prediction models. A review of previous studies suggests that decreasing grid spacing to approximately 10 km or less generally produces more realistic mesoscale structures, with particular benefits for orographically and diurnally driven flows. There have been only a few long-term objective verification studies of high-resolution forecasts, and these studies suggest, perhaps deceptively, that there are diminishing returns as horizontal grid spacing decreases below approximately 10 km.A multiyear objective verification of the University of Washington MM5 real-time forecasting system compares the realism of predicted surface parameters at 36-, 12-, and 4-km grid spacing over western Washington state for periods up to 48 h. Traditional verification statistics (such as mean absolute, bias, and root-mean-square error) are calculated by interpolating model forecasts to the observation sites. For precipitation, it is shown that model skill over western Washington improves as grid spacing decreases from 36 to 12 km. Verification scores generally degrade as resolution is increased from 12 to 4 km as overprediction develops over the windward slopes and the crests of terrain. However, for heavy precipitation amounts on windward slopes, the transition from 12 to 4 km does appear to enhance forecast accuracy. Temperature and wind statistics indicate noticeably improved skill as horizontal resolution decreases from 36 to 12 km, while only minor increases in skill are evident as grid spacing decreases to 4 km. In contrast, verification of sea level pressure suggests little improvement as resolution is increased.The benefits of resolution are not uniform over the 4-km domain. For all parameters, the region downwind of a major barrierthe Olympic Mountainsenjoys the largest enhancement of forecast skill as resolution is increased from 36 to 12 km, with noticeable, but lesser, improvements as grid spacing decreases to 4 km. Filtering the verification times to consider only periods with relatively good synoptic-scale forecasts provides only modest forecast improvement.A case study illustrates that decreasing grid spacing to 4 km produces more realistic mesoscale structures and amplitudes, a fact that is not revealed by traditional verification approaches because a small timing error existed. The paper ends by examining the benefits of resolution, some pitfalls associated with traditional verification approaches, and suggests future directions for numerical weather prediction and mesoscale verification. It is argued that higher resolution might be more beneficial than simple skill scores and that new mesoscale verification approaches must be crafted. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bulletin of the American Meteorological Society American Meteorological Society

DOES INCREASING HORIZONTAL RESOLUTION PRODUCE MORE SKILLFUL FORECASTS?

Loading next page...
 
/lp/ams/does-increasing-horizontal-resolution-produce-more-skillful-forecasts-80mcwwgi14
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0477
D.O.I.
10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2
Publisher site
See Article on Publisher Site

Abstract

This paper examines the impacts of increasing horizontal resolution on the performance of mesoscale numerical weather prediction models. A review of previous studies suggests that decreasing grid spacing to approximately 10 km or less generally produces more realistic mesoscale structures, with particular benefits for orographically and diurnally driven flows. There have been only a few long-term objective verification studies of high-resolution forecasts, and these studies suggest, perhaps deceptively, that there are diminishing returns as horizontal grid spacing decreases below approximately 10 km.A multiyear objective verification of the University of Washington MM5 real-time forecasting system compares the realism of predicted surface parameters at 36-, 12-, and 4-km grid spacing over western Washington state for periods up to 48 h. Traditional verification statistics (such as mean absolute, bias, and root-mean-square error) are calculated by interpolating model forecasts to the observation sites. For precipitation, it is shown that model skill over western Washington improves as grid spacing decreases from 36 to 12 km. Verification scores generally degrade as resolution is increased from 12 to 4 km as overprediction develops over the windward slopes and the crests of terrain. However, for heavy precipitation amounts on windward slopes, the transition from 12 to 4 km does appear to enhance forecast accuracy. Temperature and wind statistics indicate noticeably improved skill as horizontal resolution decreases from 36 to 12 km, while only minor increases in skill are evident as grid spacing decreases to 4 km. In contrast, verification of sea level pressure suggests little improvement as resolution is increased.The benefits of resolution are not uniform over the 4-km domain. For all parameters, the region downwind of a major barrierthe Olympic Mountainsenjoys the largest enhancement of forecast skill as resolution is increased from 36 to 12 km, with noticeable, but lesser, improvements as grid spacing decreases to 4 km. Filtering the verification times to consider only periods with relatively good synoptic-scale forecasts provides only modest forecast improvement.A case study illustrates that decreasing grid spacing to 4 km produces more realistic mesoscale structures and amplitudes, a fact that is not revealed by traditional verification approaches because a small timing error existed. The paper ends by examining the benefits of resolution, some pitfalls associated with traditional verification approaches, and suggests future directions for numerical weather prediction and mesoscale verification. It is argued that higher resolution might be more beneficial than simple skill scores and that new mesoscale verification approaches must be crafted.

Journal

Bulletin of the American Meteorological SocietyAmerican Meteorological Society

Published: Mar 28, 2002

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • No expiration
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches

$49/month

Start Free Trial

14-day Free Trial

Best Deal — 39% off

Annual Plan

  • All the features of the Professional Plan, but for 39% off!
  • Billed annually
  • No expiration
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

$588

$360/year

billed annually
Start Free Trial

14-day Free Trial