Regional Reanalysis over the Beaufort and Chukchi Seas
Abstract
Potential future oil development in the Beaufort and Chukchi Seas is accompanied by the threat of oil spills. In the event of a spill, time is of the essence in directing mitigation, cleanup, and recovery efforts, and thus improving the predictability of oil spill transport is of great importance. As the surface wind field is the primary factor in driving ocean currents, and thus the dispersal of any accompanying oil, accurate modeling of the surface winds is essential in enhancing the prediction of oil spill transport. As such, a study of the mesoscale meteorology of the Beaufort/Chukchi region has been conducted in an effort to ensure the accurate simulation of near-surface winds, which will thereby lead to improved prediction of oil spill dispersal. The final product of this effort is a long-term, high-quality, high-resolution reanalysis of the region's mesoscale meteorology that will be used to drive oil spill transport models. The Beaufort/Chukchi region represents a highly complex geographical environment. It comprises highly varying topography, ranging from the sharp peaks of the Brooks Range to the broad flatlands of the North Slope, and is characterized by a constantly changing sea ice presence in the ocean. The atmospheric environment is equally complex, with extremes of cold and wind a fixture of the region's climatology. Together, these present a great challenge to the accurate modeling of the Beaufort/Chukchi regional meteorology, and correspondingly of the associated surface winds. In addition, due to its remote nature, observations are sparse throughout the area, further complicating efforts to accurately initialize and simulate atmospheric conditions in the region, and making it all the more important to fully utilize any available observations through data assimilation. In this study, the Weather Research and Forecasting (WRF) model and its variational data assimilation system were used to conduct numerical simulations of the region's mesoscale meteorology at a grid spacing of 10 km while assimilating in situ and satellite data sources in order to produce an hourly reanalysis over a 31-year period (1979-2009). The final reanalysis demonstrates significant improvements in representing surface conditions, particularly surface winds, relative to those given in ERA-Interim, the forcing dataset used to drive the current simulation. In addition, the length of the modeled period, coupled with the high spatial and temporal resolution of the reanalysis, offers researchers the opportunity to investigate in great detail the climatology of a region undergoing rapid transformation in response to global climate change.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFM.A41I0090K
- Keywords:
-
- 3309 ATMOSPHERIC PROCESSES / Climatology;
- 3315 ATMOSPHERIC PROCESSES / Data assimilation;
- 3349 ATMOSPHERIC PROCESSES / Polar meteorology;
- 3355 ATMOSPHERIC PROCESSES / Regional modeling