100,000 observations an hour. In August 2016, The Weather Channel app, with over 50 million downloads, began collecting upwards of 3 million observations an hour from a mere 3% of their user-base. By mid-2017, 30 billion pressures will be retrieved every month from the Weather Channel app. If infrastructure and data quality challenges can be met, these observations could revolutionize numerical weather prediction (NWP) by providing unprecedented observational coverage and density. 1.2) Background and Literature Review As of January 2017, over 170 smartphones are capable of measuring surface pressure. Surface pressure is arguably the most valuable observed surface variable due to its ability to provide information on all scales of motion ranging from convectively induced cold pools to mid-latitude cyclones. Surface pressure atmospheric structure aloft above the planetary boundary layer (PBL), surface temperature, moisture, and wind. Unlike other surface measurements, surface pressure is less affected by error as the distribution of surface pressure is typically more spatially homogeneous than other surface parameters. Measurements of pressure exhibit fewer exposure problems and are less sensitive to the placement of instrumentation than measurements of other surface variables. For these reasons, among others, a number of a studies during the last decade have examined the impact of surface observations, and in particular surface pressure, on numerical simulations and forecasts across a variety of atmospheric scales. At the planetary scale, Whitaker et al. (2004) showed that assimilating surface pressure at a relatively sparse collection of locations could produce realistic lower and middle tropospheric analyss with 500 hPa errors similar to present 2.5 day forecast errors. Compo et al. (2006) assimilated surface pressure observations using ensemble techniques and found surface pressure observations alone could reproduce the entire upper tropospheric circulation, even during the
100,000 observations an hour. In August 2016, The Weather Channel app, with over 50 million downloads, began collecting upwards of 3 million observations an hour from a mere 3% of their user-base. By mid-2017, 30 billion pressures will be retrieved every month from the Weather Channel app. If infrastructure and data quality challenges can be met, these observations could revolutionize numerical weather prediction (NWP) by providing unprecedented observational coverage and density. 1.2) Background and Literature Review As of January 2017, over 170 smartphones are capable of measuring surface pressure. Surface pressure is arguably the most valuable observed surface variable due to its ability to provide information on all scales of motion ranging from convectively induced cold pools to mid-latitude cyclones. Surface pressure atmospheric structure aloft above the planetary boundary layer (PBL), surface temperature, moisture, and wind. Unlike other surface measurements, surface pressure is less affected by error as the distribution of surface pressure is typically more spatially homogeneous than other surface parameters. Measurements of pressure exhibit fewer exposure problems and are less sensitive to the placement of instrumentation than measurements of other surface variables. For these reasons, among others, a number of a studies during the last decade have examined the impact of surface observations, and in particular surface pressure, on numerical simulations and forecasts across a variety of atmospheric scales. At the planetary scale, Whitaker et al. (2004) showed that assimilating surface pressure at a relatively sparse collection of locations could produce realistic lower and middle tropospheric analyss with 500 hPa errors similar to present 2.5 day forecast errors. Compo et al. (2006) assimilated surface pressure observations using ensemble techniques and found surface pressure observations alone could reproduce the entire upper tropospheric circulation, even during the