Impacts of Observation Errors on Hurricane Forecasts When Assimilating Hyperspectral Infrared Sounder Radiances in Partially Cloudy Skies

Abstract

Hyperspectral infrared (IR) sounders provide high vertical resolution atmospheric sounding information that can improve the forecast accuracy of numerical weather prediction (NWP) models. Due to the challenges of assimilating cloudy radiances, NWP centers usually assimilate only radiances that are not affected by clouds. An imager based cloud‐clearing technique provides an alternative and effective way to remove the cloud effects from a partially cloudy field‐of‐view and derive the equivalent clear sky radiances or the cloud‐cleared radiances (CCRs) for assimilation in NWP. Since the observation error is amplified in the cloud‐clearing, or noise amplification process, it is necessary to inflate the observation errors appropriately in order to achieve the optimal value‐added impact from assimilating CCRs. The estimation of observation error inflation is established and discussed. Hurricane Harvey (2017) and Hurricane Maria (2017) are used to simulate and understand the impacts of observation error inflation on the assimilation of Cross‐track Infrared Sounder CCRs for hurricane forecast improvement. Both the precipitation location and intensity forecasts are improved when assimilating CCRs with an inflated observation error for Hurricane Harvey (2017). Assimilating CCRs with an inflated observation error adjusts the temperature and geopotential height fields and further affects the hurricane structures to improve the hurricane track forecasts, thereby demonstrating the importance of using hyperspectral IR measurements in partially cloudy skies for simulating the hurricane structure and improving its forecast. This method can be applied to other imager/sounder combined observations for improving sounder radiance assimilation in cloudy skies and has potential for operational applications.

An Analysis Study of FORMOSAT-7/COSMIC-2 Radio Occultation Data in the Troposphere

“…The sound profiles contain more than 100 pressure levels from surface to the 0.005 hPa, with uncertainties of about 1 K and 20% in temperature and moisture mixing ratio in the troposphere from the NUCAPS Algorithm Theoretical Basis Document (ATBD). These data have been supported for both operational applications and research studies (e.g., [21][22][23]).…”

Added-value of GEO-hyperspectral Infrared Radiances for Local Severe Storm Forecasts Using the Hybrid OSSE Method

“…The observations from these imagers can monitor rapidly changing weather systems, especially local severe storms (LSS), which have relatively short lifetimes but can cause severe damage with large hail, heavy precipitation, and strong winds. The development and movement of cloud and moisture fields within weather systems can be better understood through the use of advanced imager data (Ma et al, 2017;Kazumori, 2018;Lee et al, 2018;Schmit et al 2019;Wang et al, 2019). However, there are only a few absorption bands for NWP applications and those bands that are included are spectrally wide, containing limited vertical information.…”

Evaluation of Environmental Moisture from NWP Models with Measurements from Advanced Geostationary Satellite Imager—A Case Study

“…DTC transitioned the operational GSI system into a community system, which can be used in the public domain for study, research or other purposes. WRF/GSI together now is widely used in the research community [16,[29][30][31][32][33][34][35].…”