Abstract
Abstract. The 3-D fields of temperature (T) and specific humidity (q) retrieved by instruments such as the Atmospheric Infrared Sounder (AIRS) are predictive
of convection, but convection often triggers during the multi-hour gaps between satellite overpasses. Here we fill the hours after AIRS overpasses
by treating AIRS retrievals as air parcels which are moved adiabatically along numerical weather prediction (NWP) wind trajectories. The approach is
tested in a simulation experiment that samples 3-D European Reanalysis-5 (ERA5) T and q following the real-world AIRS time–space sampling from
March–November 2019 over much of the continental US. Our time-resolved product is named ERA5-FCST, in correspondence to the AIRS forecast product
we are using it to test, named AIRS-FCST. ERA5-FCST errors may arise since processes such as radiative heating and NWP sub-grid convection are
ignored. For bulk atmospheric layers, ERA5-FCST captures 59 %–94 % of local hourly variation in T and q. We then consider the
relationship between convective available potential energy (CAPE), convective inhibition (CIN), and ERA5 precipitation. The
1∘ latitude–longitude ERA5-FCST grid cells in our highest CAPE and lowest CIN bins are more than 50 times as likely to develop heavy
precipitation (> 4 mm hr−1), compared with the baseline probability from randomly selecting a location. This is a substantial
improvement compared with using the original CAPE and CIN values at overpass time. The results support the development of similar FCST products for
operational atmospheric sounders to provide time-resolved thermodynamics in rapidly changing pre-convective atmospheres.
Funder
Science Mission Directorate
Reference66 articles.
1. Agee, E. and Childs, S.:
Adjustments in Tornado Counts, F-Scale Intensity, and Path Width for Assessing Significant Tornado Destruction, J. Appl. Meteorol. Clim., 53, 1494–1505, https://doi.org/10.1175/JAMC-D-13-0235.1, 2014..
2. AIRS project: Aqua/AIRS L2 Support Retrieval (AIRS-only) V7.0, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/APJ6EEN0PD0Z, 2019.
3. Ali, H. and Mishra, V.:
Contributions of Dynamic and Thermodynamic Scaling in Subdaily Precipitation Extremes in India, Geophys. Res. Lett., 45, 2352–2361, https://doi.org/10.1002/2018GL077065, 2018.
4. Barthel, F. and Neumayer, E.:
A trend analysis of normalized insured damage from natural disasters, Climatic Change, 113, 215–237, https://doi.org/10.1007/s10584-011-0331-2, 2012.
5. Bechtold, P., Semane, N., Lopez, P., Chaboureau, J.-P., Beljaars, A., and Bormann, N.:
Representing Equilibrium and Nonequilibrium Convection in Large-Scale Models, J. Atmos. Sci., 71, 734–753, https://doi.org/10.1175/JAS-D-13-0163.1, 2014.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献