Effects of CO2 Changes on Hyperspectral Infrared Radiances and Its Implications on Atmospheric Temperature Profile Retrieval and Data Assimilation in NWP

Di Di,Wenguang Bai,Peng Zhang,Yunheng Xue,Jun Li

doi:10.3390/rs12152401

Abstract

Although atmospheric CO2 is a trace gas, it has seasonal variations and has increased over the last decade. Its seasonal variation and increase have substantial radiative effects on hyperspectral infrared (IR) radiance calculations in both longwave (LW) and shortwave (SW) CO2 absorption spectral regions that are widely used for weather and climate applications. The effects depend on the spectral coverage and spectral resolution. The radiative effect caused by the increase of CO2 has been calculated to be greater than 0.5 K within 5 years, whereas a radiative effect of 0.1–0.5 K is introduced by the seasonal variation in some CO2 absorption spectral regions. It is important to take into account the increasing trend and seasonal variation of CO2 in retrieving the atmospheric temperature profile from hyperspectral IR radiances and in the radiance assimilation in numerical weather prediction (NWP) models. The simulation further indicates that it is very difficult to separate atmospheric temperature and CO2 information from hyperspectral IR sounder radiances because the atmospheric temperature signal is much stronger than that of CO2 in the CO2 absorption IR spectral regions.

Highlights

Radiance measurements from high spectral resolution infrared (IR) sounders in polar orbit such as the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), the Cross-track Infrared Sounder (CrIS), and the Hyperspectral Infrared Atmospheric Sounder (HIRAS) have been widely used in weather analysis, nowcasting, forecasting, numerical weather prediction (NWP), and environmental and climate applications [1]
Our studies indicate that CO2 changes have had a substantial effect on simulations for hyperspectral IR radiances in both longwave (LW) and shortwave (SW) CO2 absorption IR spectral regions
This influence cannot be ignored in the atmospheric temperature profile retrieval and data assimilation (DA)

Summary

Introduction

Radiance measurements from high spectral resolution (or hyperspectral) infrared (IR) sounders in polar orbit such as the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), the Cross-track Infrared Sounder (CrIS), and the Hyperspectral Infrared Atmospheric Sounder (HIRAS) have been widely used in weather analysis, nowcasting, forecasting, numerical weather prediction (NWP), and environmental and climate applications [1]. Assimilation of radiances with an observation operator (or the radiative transfer model-RTM) assumes that the CO2 is fixed in the three-dimensional or four-dimensional variational (3DVAR, 4DVAR)-based data assimilation (DA) systems Another application is real-time or near real-time (NRT) weather monitoring, situation awareness and nowcasting using atmospheric temperature and moisture profiles retrieved from hyperspectral IR sounders [4,5,6]. Ota and Imasu [17] used the Maximum a Posteriori (MAP) algorithm to derive the upper troposphere CO2 concentration from the Interferometric Monitor for Greenhouse gases (IMG) by including the temperature information from the ECMWF (European Centre for Medium-Range Weather Forecasts) analysis Because this method relies on retrieved product or meteorological analysis, the uncertainty in atmospheric temperature significantly impacts the precision of the retrieved CO2. TThhee qquueessttiioonn ooff sseeppaarraattiinngg aattmmoosspphheerriicc tteemmppeerraattuurree aanndd CCOO22iissaaddddrreesssseeddaannddddiissccuusssseedd

Results

Consideration of CO2 Changes in Radiance Assimilation in NWP Models

Conclusions