Utility of Dense Pressure Observations for Improving Mesoscale Analyses and Forecasts

被引:30
作者
Madaus, Luke E. [1 ]
Hakim, Gregory J. [1 ]
Mass, Clifford F. [1 ]
机构
[1] Univ Washington, Dept Atmospher Sci, Seattle, WA 98195 USA
基金
美国国家科学基金会;
关键词
ENSEMBLE KALMAN FILTER; DATA ASSIMILATION; HIGH-RESOLUTION; REANALYSIS; PREDICTION; REMOVAL; WEATHER; SYSTEM; ERROR; BIAS;
D O I
10.1175/MWR-D-13-00269.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The use of dense pressure observations is investigated for creating mesoscale ensemble analyses and improving short-term mesoscale forecasts. By exploiting additional observation platforms, the number of pressure observations over the Pacific Northwest region is increased by an order of magnitude over standard airport observations. Quality control and bias correction methods for these observations are discussed, including the use of pressure tendency as an alternative observation type with fewer bias concerns. The enhanced station density provided by these observations contributes to localized adjustments for a variety of mesoscale phenomena. These adjusted analyses yield improved forecasts, including more accurate forecasts of frontal passages and convective bands. Assimilating dense 3-h pressure tendency observations also reduces the error in some forecast surface fields similarly to raw pressure observations, suggesting further investigation into pressure tendency as a mesoscale observation type.
引用
收藏
页码:2398 / 2413
页数:16
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