Dr. Simona Seastrand will speak at the 98th Annual AMS Conference in Austin, TX (7 –11 January, 2018). Her presentation will highlight results from PEMDAS’ recent Air-Land-Sea campaign, an experimental study designed to investigate the impact of assimilating in-situ measures of pressure, temperature, and humidity from the PEMDAS designed Airborne Sensing and Prediction System (ASAPS) into a regional weather model. PEMDAS Chief Scientist, Dr. Mike Gauthier will also be in attendance.
In addition, Dr. Seastrand will speak at the 17th Annual AMS Student Conference, held the weekend prior to the AMS Annual Meeting. The AMS Student Conference serves over 700 graduate and undergraduate students annually. The theme of the 17th Annual AMS Student Conference is “Revamping the Conversation: How Communication Fuels our Profession” and is focused on inspiring attendees to direct their learning experience to tools that are necessary for a successful career. Dr. Seastrand was invited to speak due to her extensive technical expertise in modeling.
Assessing the Impact of Mobile, Multi-Source, Observations on Forecast Accuracy
Seastrand, S. R., Gauthier, M. L., Lockhart, M. G. and D. J. Brees
Data from mobile, particularly airborne, sensors have been shown to be extremely impactful relative to increasing the fidelity of NWP model output (Barwell et al. 1985, Kruus 1986, Baeda et al. 1987, Benjamin et al. 1991, Smith and Benjamin 1994, Graham et al. 2000, Schwartz et al. 2000, Zapotocny et al. 2000, Zhang et al. 2016). However, most aircraft sensing platforms do not have a mechanism for recording moisture; sensing platforms that do have a means of measuring moisture often are not assimilated into numerical weather prediction models (Moninger et al. 2003, Hoover et al. 2017). An experimental study was designed to investigate the impact of assimilating in-situ measures of pressure, temperature and humidity into the Weather Research and Forecast (WRF) model using data collected during the PEMDAS Air-Land-Sea (ALS) field campaign. The PEMDAS designed Airborne Sensing and Prediction System (ASAPS) provided high-frequency (1Hz), in-situ, data-linked measures of pressure, temperature, and humidity across each of the three sources. Observations were assimilated into a regional NWP model with performance assessed relative to representative control runs using NCAR’s Model Evaluation Tools verification package. Notable improvements for many parameters, including temperature and composite reflectivity are attributed to the inclusion of these high-frequency in-situ observations.
Reference: Seastrand, S. R., Gauthier, M. L., Lockhart, M. G. and D. J. Brees, 2018. Assessing the Impact of Mobile, Multi-Source, Observations on Forecast Accuracy. 22nd Conf. on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface, P2.616.
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