The use of hyperspectral sounding information to monitor atmospheric tendencies leading to severe local storms

Abstract

Operational space-based hyperspectral sounders like the Atmospheric Infrared Sounder, the Infrared Atmospheric Sounding Interferometer, and the Cross-track Infrared Sounder on polar-orbiting satellites provide radiance measurements from which profiles of atmospheric temperature and moisture can be retrieved. These retrieval products are provided on a global scale with the spatial and temporal resolution needed to complement traditional profile data sources like radiosondes and model fields. The goal of this paper is to demonstrate how existing efforts in real-time weather and environmental monitoring can benefit from this new generation of satellite hyperspectral data products. We investigate how retrievals from all four operational sounders can be used in time series to monitor the preconvective environment leading up to the outbreak of a severe local storm. Our results suggest the potential benefit of independent, consistent, and high-quality hyperspectral profile information to real-time monitoring applications.

Impact of Moisture Information From Advanced Himawari Imager Measurements on Heavy Precipitation Forecasts in a Regional NWP Model

“…Information about moisture distribution and transportation in the preconvection environment is very important for nowcasting and forecasting severe weather events (Lee et al, 2017;Li et al, 2008Li et al, , 2011Li et al, , 2012Sieglaff et al, 2009;Weisz et al, 2015). The Advanced Baseline Imager (ABI) onboard the U.S. next generation of Geostationary Operational Environmental Satellite (GOES-R series; Schmit et al, 2005Schmit et al, , 2008Schmit et al, , 2017, the Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8/-9 (Bessho et al, 2016), and the Advanced Geosynchronous Radiation Imager (AGRI) onboard the Chinese FengYun-4 series (Yang et al, 2017) provide high temporal (30 s to 15 min) and spatial (2 km for ABI and AHI and 4 km for AGRI; Table 1) resolution moisture information useful for weather monitoring and forecasting.…”

Satellite-Based Atmospheric Infrared Sounder Development and Applications

“…Overcoming the downside of channel subselection remains a challenge; studies underway include reverting to assimilation of sounding retrievals from advanced IR sounders, which have much higher vertical resolution than those from the low-spectral-resolution IR sounders, or using reconstructed radiances (computed from principal component scores). For example, in order to achieve consistency in vertical resolution between retrievals and model background, a method for correcting satellite profile retrievals for vertical-resolution-dependent biases has been formulated (Smith et al 2015) for retrieval assimilation. Migliorini (2012) also pointed out that there is equivalence between radiance and retrieval assimilation under certain circumstances, and assimilation of transformed retrievals may be particularly advantageous for instruments with a very high number of channels.…”

“…Furthermore, the hyperspectral IR sounder 12-15-µm spectral region is particularly sensitive to cloud-top height (CTH) and effective cloud cover, and the 9-µm band contains information on cloud optical thickness and particle size (Li et al 2004(Li et al , 2005b; these hyperspectral measurements have become the basis for joint retrievals of atmospheric and cloud parameters (Smith et al 2012). Li et al (2004Li et al ( , 2005b) used a 1DVAR approach with AIRS data to retrieve CTP, ECA, effective particle radius, and optical depth, with the latter two comparing favorably with the results from satellite-and groundbased active remote sensing instruments (Wu et al 2005;Weisz et al 2007). They also pointed out that AIRS cloud products have more abundant spectral features than MODIS cloud products, and the two can be complementary.…”

“…Optimally the CTPs derived from advanced sounder data (e.g., from AIRS, IASI, and CrIS) are within 300-m precision, the cloud-top temperatures around 2 K, and the cloud coverages around 10% (August et al 2012); but these numbers are cloud-state dependent (Eyre 1989). However, there are also some limitations; AIRS cloud microphysical parameters lack precision in thick clouds [cloud optical thickness (COT) > 10] and especially thin clouds (COT < 0.1) since IR observations have the largest sensitivity to the variations in clouds when the optical depth is between 0.4 and 4 Li et al 2005b;Weisz et al 2007).…”

An efficient radiative transfer model for hyperspectral IR radiance simulation and applications under cloudy‐sky conditions

“…HIRTM has been successfully utilized for many applications, such as extracting products of atmospheric profiles and cloud properties Zhou et al, 2007;Smith et al, 2012;Weisz et al, 2007Weisz et al, , 2013Wu et al, 2005], real-time applications of those products in weather analysis Weisz et al, 2007], nowcasting and forecasting Weisz et al, 2015], and climate research . In addition, HIRTM can be used for future observing system simulation [Greenwald et al, 2016], evaluating NWP model forecasts by converting the forecasts to the simulated brightness temperatures (BTs) and comparing with BT observations [Jiang, 2016], as well as for evaluating microphysical schemes in a NWP model [Cintineo et al, 2014].…”