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Improving Severe Weather Forecasting: Hyperspectral IR Data and Low-level Inversions Justin M. Sieglaff Cooperative Institute for Meteorological Satellite.

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Presentation on theme: "Improving Severe Weather Forecasting: Hyperspectral IR Data and Low-level Inversions Justin M. Sieglaff Cooperative Institute for Meteorological Satellite."— Presentation transcript:

1 Improving Severe Weather Forecasting: Hyperspectral IR Data and Low-level Inversions Justin M. Sieglaff Cooperative Institute for Meteorological Satellite Studies (CIMSS) Department of Atmospheric and Oceanic Sciences University of Wisconsin - Madison Timothy J. Schmit NOAA/NESDIS, SaTellite Applications and Research (STAR) Advanced Satellite Products Branch (ASPB) Steven A. Ackerman Cooperative Institute for Meteorological Satellite Studies (CIMSS) Department of Atmospheric and Oceanic Sciences University of Wisconsin - Madison Thanks also to… Wayne Feltz, CIMSS Bob Rabin, NSSL/CIMSS Jun Li, CIMSS Jinglong Li, CIMSS Michael Morgan, UW Jim Nelson, CIMSS Gene Brusky, NWSFO GRB Future Work Research Motivation Goal: Determine how hyperspectral IR data can be used to detect lower tropospheric inversions and use this information to increase probability of detection AND decrease false alarm rate of severe weather events TAMDAR aircraft can provide high vertical resolution profile data; these profiles greatly aid in short term convection forecasts TAMDAR profiles limited spatially to regional airports and temporally to hours when flights operate; hyperspectral IR data can be used to provide high vertical resolution atmospheric soundings with increased spatial and temporal coverage over aircraft data TAMDAR/Hyperspectral IR data can in part be used to improve short term convection forecasts, especially when numerical models do not accurately capture state of the atmosphere Hyperspectral data such as AIRS/HES can improve capabilities over broadband data, like the current GOES sounder Excerpt from watch number 425: “…CAP IS WEAKENING RAPIDLY WITH HEATING ACROSS CENTRAL WI WITH MLCAPE APPROACHING 1000 J/KG. RUC MODEL SOUNDINGS ACROSS CENTRAL WI HAVE BEEN SHOWING STEEP LOW/MID LEVEL LAPSE RATES NEARING 8C/KM INDICATING AN INCREASING THREAT FOR DAMAGING WINDS AND HAIL. …” June 07, 2005 Case Study Future work includes using higher resolution AIRS forward model for radiances Development of methodology for detecting and monitoring lower tropospheric inversions in simulated and observed radiances, however this is complicated by need for retrieved skin temperature Below is simulated spectra for the same profile, but varied skin temperature Differences between ‘window regions’ and ‘absorption features’ (circled) have different sign depending on skin temperature Methodology will need to account for differences imparted by skin temperature, as well as moisture profile GOES-12 B8 294.4K GOES-12 B7 291.7K GOES-12 B6 286.9 K October 04, 2002 Retrieval Observed AIRS spectra for CART site, observed temperature and moisture profiles, and retrieved temperature and moisture profiles CIMSS/AIRS experimental retrieval (hyperspectral) detects inversion near 850 hPa, while current GOES sounder (broadband) fails to capture inversion 2002 10 04 1945 UTC AIRS Granule 872 cm -1 (11.5 µm) CART SITE Calculated and AIRS observed spectra for KCWA ~1900UTC (Note: AIRS observation is for nearby clear AIRS pixel due to clouds over KCWA) Note agreement between calculations and AIRS observation – confident in simulated datasets However, TAMDAR (green) shows the temperature inversion near 900 hPa, while the RUC (blue) inaccurately dissipated the inversion MCS dissipated as it entered WW #425 and watch was eventually cancelled KCWA 2005 06 07 1850 UTC AIRS Granule 872 cm -1 (11.5 µm) Select References The Utility of TAMDAR Regional Aircraft Sounding Data in Short-term Convective Forecasting, Eugene S. Brusky, NOAA/NWS, Green Bay, WI; and P. Kurimski, 10th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), February 2006 AirDat System for Ensuring TAMDAR Data Quality, Alan K. Anderson, 10th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS), February 2006 AIRS Subpixel Cloud Characterization Using MODIS Cloud Products, Jun Li, Et. Al., Journal of Applied Meteorology, August 2004 Hyperspectral (HES) ΔT for this simulation is larger than HES/PORD NEDT (black line) Brightness temperature difference for two simulated TBB spectra for the inversion noted in the June 7, 2005 case


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