A step forward toward effectively using hyperspectral IR sounding information in NWP

Abstract

Citation: Li, J., and W. Han: A step forward toward effectively using hyperspectral IR sounding information in NWP. Adv. Atmos. Sci., 34(11), 1263-1264, https://doi.org/ 10.1007/s00376-017-7167-2.Satellite-based atmospheric sounding measurements with high spectral resolution or from hyperspectral infrared (IR) sounders are important global observations for improving weather forecasts through assimilating them into operational numerical weather prediction (NWP) systems. Advanced IR sounders, such as the Atmospheric Infrared Sounder (AIRS) (Chahine et al., 2006) onboard Aqua, the Infrared Atmospheric Sounding Interferometer (IASI) (Hilton et al., 2012) onboard Metop-A and -B, and the Crosstrack Infrared Sounder (CrIS) (Gambacorta et al., 2014) onboard SNPP (Suomi National Polar-orbiting Partnership), together with microwave sounders, have become the most important providers of observations for operational centers (Le Marshall et al., 2005, 2006a, 2006bCardinali, 2009). These advanced IR and microwave sounders have provided the largest impact on forecast skill amongst all satellite observations (Joo et al., 2013;Cucurull and Anthes, 2014). Although advanced IR sounders have played a critical role in NWP systems, only a few hundred of the channels are selected in for assimilation, instead of all available channels, due partly to the large amount of data. For example, AIRS has 2372 channels, IASI has 8461 channels, and CrIS has 1305 channels, but in each case only a subset of channels are assimilated in the NWP systems at the major operational centers.Methodologies have been developed for selecting a subset of channels for NWP assimilation. For example, Li and Huang (1994) developed an approach based on a stepwise regression for AIRS channel selection; Collard (2007) selected channels for assimilation based on information content analysis along with some additional criteria; Rabier et al. (2002) studied channel selection based on the Jacobian matrix and iterative method for sequentially selecting channels with the largest information content; Ventress and Dudhia (2014) modified the standard algorithm to allow spectrally correlated errors to be properly modelled, and quantified, * Corresponding author: Jun LI Email: Jun.Li@ssec.wisc.edu within the channel selection process; and Migliorini (ECMWF technical Memo no. 727, 2014) studied the optimal flow-dependent selection of channels in the presence of cloud. These methodologies are very useful for selecting a subset of channels presenting optimal information for radiance assimilation, especially when hyperspectral advanced sounder data are available from geostationary orbit; for example, the Geostationary Interferometric Infrared Sounder onboard the FengYun-4 series (Yang et al., 2017). In general, these methodologies are based on information content analysis, in which the linearization is used in the channel selection process. One limitation of information content analysis is the linear approach for selecting absorption channels that have high nonlinearity (e.g., the r...

Enhancing the Fast Radiative Transfer Model for FengYun‐4 GIIRS by Using Local Training Profiles

“…No doubt that the local coefficients will perform better on the BT simulation in general, although for some specific channels with central wavenumber around 1,700 to 1,800 cm −1 , the performance of local coefficients is slightly degraded. The comprehensive performances on BT simulation for each channel can be used together with other criteria in channel selection (J. Li & Han, ), for example, to keep those channels with BT simulation accuracy less dependent on the RTM training profiles and the atmospheric conditions.…”

“…The comprehensive performances on BT simulation for each channel can be used together with other criteria in channel selection (J. Li & Han, 2017), for example, to keep those channels with BT simulation accuracy less dependent on the RTM training profiles and the atmospheric conditions.…”

Characteristics of Satellite Sampling Errors in Total Precipitable Water from SSMIS, HIRS, and COSMIC Observations

“…Because in addition to differences in sampling errors, there are also some other differences in real satellite data, like channel to channel coregistration, detector noises, time inhomogeneity caused by orbit drifting, retrieval algorithm, cloud detecting scheme, calibration, intercalibration in radiance level, and so on (Kidder & Jones, ; Mears et al, ; Schröder et al, ). Therefore, more sophisticated methodologies, such as the work of combining infrared and microwave measurements in Li et al (), imaging and sounding (Li et al, ; Li & Han, ), and so on, should be developed and used to fuse the multisource data for a consistent water vapor climate data record.…”

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

“…Satellite data has been proven for their positive impact on NWP based forecasts [33,36,37]. To better understand the influence of satellite data such as the Cross-track Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS) observations from JPSS using Suomi NPP on the moisture forecast, the BT and BTD between the model calculations from WRF (with GTS data only)/WRF (GTS and JPSS data) and AHI observations for three WV absorption bands at 1800 UTC on 5 July 2015 are shown in Figures 8-10.…”