Utility of Dense Pressure Observations for Improving Mesoscale Analyses and Forecasts

Abstract

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.

Crowdsourcing for climate and atmospheric sciences: current status and future potential

“…Madaus et al . () recently found that assimilating additional pressure tendency data from privately owned weather stations reduced forecast error for mesoscale phenomena, offering potential for other crowdsourced data such as dense barometric readings from smart phones for the real‐time tracking of storms. Therefore extreme weather phenomena that exhibit significant pressure and wind variations (e.g.…”

Central and Eastern U.S. Surface Pressure Variations Derived from the USArray Network

“…Surface pressure is also more readily assimilated into research and operational models (Whitaker et al 2004;Dirren et al 2007;Wheatley and Stensrud 2010). As discussed by Madaus et al (2014), assimilating densely spaced surface pressure observations shows promise for improving future mesoscale analyses and forecasts.…”

Surface Pressure Observations from Smartphones: A Potential Revolution for High-Resolution Weather Prediction?

“…As shown by Madaus et al (2014) the assimilation of dense pressure observations can shift fronts in a realistic way that substantially improves short-term wind forecasts. One major problem is forecasting the initiation of severe convection, with models being initialized before any precipitation or radar echo is apparent.…”

“…Since it makes little sense to assimilate pressure observations in regions where models lack sufficient resolution to duplicate observed pressure features, pressure observations in such areas should be rejected when model and actual terrain are substantially different (Madaus et al 2014). GPS elevations are available, but can have modest errors (typically ±10 m, roughly equivalent to a 1-hPa pressure error, the typical error variance used in most operational data assimilation systems; see http:// gpsinformation.net/main/altitude.htm for a discussion on the vertical errors in GPS-based elevation).…”

“…Initial research on the impacts of networks of surface pressure observations on mesoscale prediction (e.g., Wheatley and Stensrud 2010;Madaus et al 2014) suggest that ensemble-based mesoscale data assimilation may offer 7. If private sector firms or other organizations can develop the infrastructure to "harvest" and share these pressure observations in real time, there could be a substantial improvements in the quality of the initializations of high-resolution numerical weather prediction models and their subsequent forecasts for a wide range of important weather features such as severe convection.…”