Affiliation:
1. University of Washington, Seattle, Washington
Abstract
Predicting when and where individual convective storms will develop remains an elusive challenge. Previous studies have suggested that surface observations can capture convective-scale features relevant to the convective initiation (CI) process, and new surface observing platforms such as crowdsourcing could significantly increase surface observation density in the near future. Here, a series of observing system simulation experiments (OSSEs) are performed to determine the required density of surface observations necessary to constrain storm-scale forecasts of CI. Ensemble simulations of an environment where CI occurs are cycled hourly using the CM1 model while assimilating synthetic surface observations at varying densities. Skillful and reliable storm-scale forecasts of CI are produced when surface observations of at least 4-km—and particularly with 1-km—density are assimilated, but only for forecasts initiated within 1 h of CI. Time scales of forecast improvement in surface variables suggest that hourly cycling is at the upper limit for CI forecast improvement. In addition, the structure of the assimilation increments, ensemble calibration in these experiments, and challenges of convective-scale assimilation are discussed.
Funder
National Oceanic and Atmospheric Administration
Publisher
American Meteorological Society
Cited by
11 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献