Abstract

The Atmospheric Infrared Sounder (AIRS) provides twice-daily global observations of brightness temperature, which can be used to retrieve the total column ozone with high spatial and temporal resolution. In order to apply the AIRS ozone data to numerical prediction of tropical cyclones, a four-dimensional variational (4DVAR) assimilation scheme on selected model levels is adopted and implemented in the mesoscale non-hydrostatic model MM5. Based on the correlation between total column ozone and potential vorticity (PV), the observation operator of each level is established and five levels with highest correlation coefficients are selected for the 4DVAR assimilation of the AIRS total column ozone observations. The results from the numerical experiments using the proposed assimilation scheme for Hurricane Earl show that the ozone data assimilation affects the PV distributions with more mesoscale information at high levels first and then influences those at middle and low levels through the so-called asymmetric penetration of PV anomalies. With the AIRS ozone data being assimilated, the warm core of Hurricane Earl is intensified, resulting in the improvement of other fields near the hurricane center. The track prediction is improved mainly due to adjustment of the steering flows in the assimilation experiment.

Highlights

  • Due to imperfect parameterization of the air-sea interaction and convection, and a lack of observations over the ocean, the large-scale environmental fields and initial conditions of a tropical cyclone (TC) cannot be accurately described in a numerical weather prediction (NWP) model

  • Satellite data assimilations are divided into two categories: indirect assimilation of atmospheric temperature and moisture data retrieved from satellite observations in an NWP model, and direct assimilation through a radiative transfer model, linking satellite observations and model variables to obtain temperature and moisture variables close to the actual state of the atmosphere (Xue, 2009)

  • In order to assess the impact of incorporating Atmospheric Infrared Sounder (AIRS) ozone data into the initial field in simulating Hurricane Earl, Fig. 5 shows potential vorticity (PV) at 400 hPa, the zonal cross-section of PV through the hurricane center from the control experiment of Earl0118, and PV increments from ozone experiment of Earl0118 at 1800 UTC 1 September 2010

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Summary

Introduction

Due to imperfect parameterization of the air-sea interaction and convection, and a lack of observations over the ocean, the large-scale environmental fields and initial conditions of a tropical cyclone (TC) cannot be accurately described in a numerical weather prediction (NWP) model. Wu and Zou (2008) subsequently assimilated TOMS ozone data into an NWP model to better describe the large-scale environment of Hurricane Erin (2001), based on the relationship between total ozone and mean PV. This study aims to examine if it is possible to improve the prediction of TC track and intensity by assimilating the AIRS ozone data into the initial fields of a mesoscale NWP model. For this purpose, application of a four-dimensional variational (4DVAR) assimilation scheme on selected model levels is developed to assimilate AIRS ozone data and to verify the assimilation effects on numerical prediction of Hurricane Earl (2010). This study focuses on the period when Earl regained its peak intensity prior to its landfall from 1800 UTC 1 to 1800 UTC 4 September 2010

Numerical model
AIRS ozone data and quality control
Assimilation scheme
TC track
TC intensity
Batch experiments
Potential vorticity increments
Warm core
Steering flows
Summary
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