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International Journal of Remote Sensing Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tres20 Assessment of MetOp-A Advanced Very High Resolution Radiometer (AVHRR) short-wave infrared channel measurements using Infrared Atmospheric Sounding Interferometer (IASI) observations and line-by-line radiative transfer model simulations M. K. Rama Varma Raja a , Xiangqian Wu b & Fangfang Yu c a NPP OMPS Science Operations Center, NASA Goddard Space Flight Center, Science Systems and Applications, Lanham, MD, 20706, USA b Sensor Physics Branch, NOAA/NESDIS/STAR, Camp Springs, MD, 20746-4304, USA c Sensor Physics Branch, ERT Systems, Inc.@NOAA/NESDIS/STAR, Camp Springs, MD, 20746-4304, USA Available online: 24 Feb 2012

To cite this article: M. K. Rama Varma Raja, Xiangqian Wu & Fangfang Yu (2012): Assessment of MetOp-A Advanced Very High Resolution Radiometer (AVHRR) short-wave infrared channel measurements using Infrared Atmospheric Sounding Interferometer (IASI) observations and line- by-line radiative transfer model simulations, International Journal of Remote Sensing, 33:16, 5240-5250 To link to this article: http://dx.doi.org/10.1080/01431161.2012.656766

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Assessment of MetOp-A Advanced Very High Resolution Radiometer (AVHRR) short-wave infrared channel measurements using Infrared Atmospheric Sounding Interferometer (IASI) observations and line-by-line radiative transfer model simulations

M. K. RAMA VARMA RAJA∗†, XIANGQIAN WU‡ and FANGFANG YU§ †NPP OMPS Science Operations Center, NASA Goddard Space Flight Center, Science Systems and Applications, Lanham, MD 20706, USA ‡Sensor Physics Branch, NOAA/NESDIS/STAR, Camp Springs, MD 20746-4304, USA §Sensor Physics Branch, ERT Systems, Inc.@NOAA/NESDIS/STAR, Camp Springs, MD 20746-4304, USA

(Received 27 June 2011; in ﬁnal form 1 January 2012)

MetOp-A satellite-based hyper-spectral Infrared Atmospheric Sounding Interferometer (IASI) observations are used to evaluate the accuracy of the broadband short-wave infrared (SWIR) atmospheric window channel (channel 3B) centred at 3.74 µm of the Advanced Very High Resolution Radiometer (AVHRR) carried on the same platform. To complement the partial spectral coverage of IASI, line-by-line radiative transfer model (LBLRTM)-simulated IASI spectra are used. The comparisons result in signiﬁcant negative AVHRR minus IASI bias in radiance (∼–0.04 mW m–2 sr–1 cm–1) with scene temperature dependency in which the absolute value of the bias linearly increases with increasing temperature. It is demonstrated that the negative bias and the scene temperature dependency of the bias are the results of signiﬁcant absorption in the portion of AVHRR spectral band not seen by IASI, leading to the conclusion that MetOp-A AVHRR channel 3B is not purely an ‘atmospheric window’ channel.

1. Introduction Space-based observations of the Earth’s atmosphere, land surface and ocean are becoming key ingredients of operational weather forecasting, climate monitoring and

Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 research. For observations from Earth observation sensors to be used as climate data records (CDRs), the continuity and quality of observations must be ensured to be optimal. The long-term data sets of spectrally resolved Earth radiances from Advanced Very High Resolution Radiometers (AVHRRs) ﬂown since 1970 are potential CDRs provided they meet the stringent accuracy-level requirements. For example, for temperature CDRs the required accuracy is about 0.1 K year–1 (Ohring et al. 2005, Mittaz et al. 2009). In this context, to realize the potential use of AVHRR-based long-term infrared radiance data sets as CDRs at ﬁrst the measurement uncertainties, in particular the calibration uncertainties, need to be investigated, characterized and resolved. In addition, it is important to understand the consistencies and inconsistencies

*Corresponding author. Email: ramavarmaraja.mundakkara-kovilakom@nasa.gov

International Journal of Remote Sensing ISSN 0143-1161 print/ISSN 1366-5901 online © 2012 Taylor & Francis http://www.tandf.co.uk/journals http://dx.doi.org/10.1080/01431161.2012.656766 Comparison of AVHRR channel 3B and IASI 5241

between corresponding infrared spectral bands of different space-based instruments to create links between various successive multispectral instruments for long-term climate change detection. The hyper-spectral measurements of radiance from the Infrared Atmospheric Sounding Interferometer (IASI) are known to be superiorly calibrated and IASI has been used as an on-orbit reference radiometer for studies linked to space- based infrared measurements of Earth radiances (Wang and Cao 2008, Wang et al. 2010). Thus, with their demonstrated capability and accuracy used as a reference standard, IASI hyper-spectral measurements offer a unique opportunity to evaluate and characterize the uncertainties of spectrally overlapping broadband radiometric measurements. The AVHRR 3.74 µm channel (channel 3B) is known to be an ‘atmospheric window channel’, and the data from this channel are used for a variety of purposes such as cloud detection, ﬁre pixel detection, snow/ice differentiation, measuring surface thermal emissivity, sea surface temperature estimation and night-time land surface temperature estimation (Reynolds and Smith 1993, Ellrod 1995, 2006, Qin and Karnieli 1999, Li et al. 2001, Trischenko et al. 2002, Heidinger et al. 2004, Sun et al. 2004, Dash and Ignatov 2008, Liu et al. 2009). Most of the products derived from measurements in AVHRR channel 3B crucially rely on its ‘atmospheric window’ nature. For example, Liu et al. (2009) states that ‘AVHRR channel 3B centered at 3.7 µm is the most transparent IR band of AVHRR and it is instrumental for SST retrievals and radiance assimilation at night’. Thus, the atmospheric window nature of this AVHRR channel needs to be ensured for optimal accuracy for the derived products. The recent advances in hyper-spectral radiance measurements make it possible to perform such an evaluation. In this study, an attempt is made to evaluate the uncertainties in the measurements of the AVHRR 3.74 µm channel on MetOp-A using hyper-spectral measurements from IASI on the same platform. In a previous study, Wang and Cao (2008) evalu- ated the MetOp-A AVHRR channels 4 (centred at 11 µm) and 5 (centred at 12 µm) using hyper-spectral measurements from IASI. However, channel 3B measurements were not investigated by Wang and Cao (2008) because of the limitation imposed by the partial spectral coverage of IASI over this AVHRR band. In this study, to complement the IASI observations for complete spectral coverage, line-by-line radiative transfer model (LBLRTM)-simulated IASI spectra are used. The combination of the incomplete nature of the IASI spectral coverage, the high-resolution nature of the IASI measurements and the complementary LBLRTM-generated IASI spectra provides Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 a unique opportunity to investigate from a space-based perspective the within-band radiative inﬂuences on AVHRR channel 3B observations. This study combines IASI hyper-spectral observations with LBLRTM model simulations of IASI spectra to investigate the within-band effects on MetOp-A AVHRR channel 3B observations.

2. The data, instruments, LBLRTM model and method of analysis The following sections describe, respectively, the data sets used, the instruments, the radiative transfer model and the methodology adopted for the analysis.

2.1 Data sets used One day’s worth of IASI data (∼480 granules) are selected from each month in the year 2009, and these approximately represent the median observations in the corresponding 5242 M. K. R. V. Raja et al.

320 1.0

300 0.8 280

(K) 0.6 b

T 260 0.4

IASI 240 0.2 220

200 0.0 response function Spectral 2000 2500 3000 3500 Wave number (cm–1)

Figure 1. A typical example of line-by-line radiative transfer model (LBLRTM)-simulated IASI brightness temperature spectra versus wave numbers for the covered portion of the AVHRR channel 3B band (black) and for the AVHRR band portion with no IASI coverage (magenta). The spectral response function (SRF) of AVHRR channel 3B is plotted in blue and the green vertical indicates the cut-off wave number for IASI observations.

month. The days selected are 16 January, 14 February, 16 March, 15 April, 16 May, 15 June, 16 July, 16 August, 15 September, 16 October, 15 November and 16 December. In addition to the level 1C data, simulated IASI spectral data corresponding to the entire bandwidth of AVHRR channel 3B are used in this study. The requirement for LBLRTM-simulated data originates from the incomplete spectral coverage of IASI as mentioned in the previous section and illustrated clearly in ﬁgure 1. In ﬁgure 1, the LBLRTM-simulated IASI brightness temperature spectra versus wave numbers are plotted in black and magenta demarcated by a green vertical line. The blue-coloured curve represents the MetOp-A AVHRR channel 3B spectral response function versus wave number. The IASI spectra in black towards the left of the green vertical line indicate the IASI observational spectral coverage over the MetOp-A AVHRR band and the magenta-coloured spectra represent the portion not covered by the IASI observations. It can be noted that the AVHRR channel 3B band starts at 4.499 µm (2222.72 cm–1) and extends up to 2.98 µm (3355.70 cm–1) while IASI coverage is for the portion 4.499–3.62 µm (2760 cm–1).

Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 2.2 IASI instrument The IASI instrument designed by the Centre National d’Etudes Spatiales (CNES) is a high-resolution spectral sounder based on a Fourier transform spectrometer (Phillips and Schlussel 2005, Clerbaux et al. 2007) and makes measurements, on board the MetOp-A satellite in a Sun-synchronous polar orbit at ∼819 km altitude, of IR radiation from Earth in the wavelength region 3.6–15 µm (645–2760 cm–1). The orbit of MetOp-A has an equator crossing time of 9:30 a.m. in the descending node. The IASI instrument has a swath width of 2200 km and observes an area of 50 km × 50 km at nadir. It follows a step stare scanning pattern with a scan angle range of ± 47.85◦ covered in 30 steps. Each IASI ﬁeld-of-view (FOV) is sampled by a matrix of 2 × 2 1.25◦ circular pixels, each having a 12 km footprint diameter at the nadir view. It must be noted that the data sets used in this study are the level 1C IASI radiance product data, which are apodized, resampled and calibrated radiance spectra. Comparison of AVHRR channel 3B and IASI 5243

2.3 AVHRR instrument The AVHRR is a broadband filter imaging radiometer instrument providing observations of Earth’s radiation in a number of channels ranging from visible to infrared since 1978 from low Earth orbiting (polar orbiting) satellites (Rao 1987, Cracknell 1997, Mittaz et al. 2009). Thus, AVHRR data are among the long-term space-based data of Earth’s radiation, making them potential climate record data sets for monitoring global climate change. In addition, the operational AVHRR measurements have been regularly used to monitor weather, land surface and ocean parameters. The AVHRR instrument on board the MetOp-A satellite is the latest AVHRR/3 design in which there are six spectral channels covering a range of wavelengths from visible through infrared. Channel 1 is centred at the visible wavelength of 0.63 µm, channel 2 is centred at the near-infrared (NIR) wavelength of 0.86 µm, channel 3A is centred at the NIR wavelength of 1.61 µm, channel 3B is centred at the short-wave infrared (SWIR) wavelength of 3.74 µm, channel 4 is centred at the long-wave infrared wavelength of 11 µm and channel 5 is centred at the long-wave infrared window of 12 µm. The AVHRR/3 instrument is a cross track scanning radiometer with a horizontal swath width of 2000 km. The AVHRR measurement has a horizontal spatial resolution of ∼1 km at the nadir view. The noise specification limit for AVHRR/3 infrared channels beyond which the measurements are considered noisy is 0.12 K (the noise- equivalent delta temperature value at a nominal brightness temperature of 300 K), which is far more relaxed than the CDR accuracy requirement. For further specific details about the AVHRR instrument see Rao (1987) and Cracknell (1997).

2.4 Line-by-line radiative transfer model The radiative transfer model used to generate IASI spectra in this study is the LBLRTM version 11.1. The LBLRTM is a line-by-line model that covers the entire spectral range from microwave to ultraviolet (Clough et al. 2005). It is known to be an accurate, efﬁcient and highly ﬂexible model for computation of spectral transmittance and radiance and is a widely used model for radiative transfer applications. This model derives its heritage from the Fast Atmospheric Signature Code (FASCODE) model and incorporates several attributes to generate highly accurate spectral radiances with approximately 0.5% accuracy (Turner et al. 2004, Clough et al. 2005). Detailed descriptions of LBLRTM attributes and examples of LBLRTM model validation can be found in Clough et al. (2005) and references therein. Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 2.5 The methodology The level 1C data have 120 IASI footprints per scan line taken in 30 stare steps. These data sets have IASI radiance values corresponding to 8461 channels. For each of the IASI FOVs, there exist corresponding collocated, coincident and FOV-averaged AVHRR channel radiances. The IASI FOV (∼12 km) is relatively larger than that of AV H R R ( ∼1 km). Therefore, it becomes necessary to consider the inhomogeneous scenes possible within the IASI FOV, before the FOV-averaged AVHRR radiances are constructed. For this reason, the AVHRR scenes within the IASI FOV are segregated into seven different classes and each class is assigned a unique weight for averaging (Phillips and Schlussel 2005). By multiplying the class-based radiances with corresponding weights and adding them together, the averaged AVHRR radiances within the IASI FOV can be constructed. Following a similar procedure, standard deviation 5244 M. K. R. V. Raja et al.

corresponding to class-based average radiances could be converted to standard deviation of FOV-averaged AVHRR radiances. Since the spectral resolutions of AVHRR and IASI are signiﬁcantly different, they are not directly comparable. The technique of spectral convolution is employed to simulate the band-averaged AVHRR radiances using IASI spectral data provided at ﬁne spectral resolution. Following the spectral convolution, the AVHRR radiance Ra can be written as

ν2 Ri(νi)ϕa(νi)dν ν R (ν ) = 1 ,(1) a c ν2 ϕa(νi)dν

ν1

where Ra is the simulated AVHRR radiance using IASI hyper-spectral observations corresponding to the AVHRR channel 3B at 3.74 µm, νc is the central wave number of AVHRR channel 3B, Ri is the IASI hyper-spectral radiance corresponding to wave number νi, φa is the AVHRR spectral response function interpolated to the IASI wave number, ν1 is the lower limit wave number of the AVHRR channel 3B and ν2 is the upper limit wave number which due to the incomplete spectral coverage inherent with the IASI observations coincides with its cut-off wave number inside the AVHRR spectral band. The simulated AVHRR radiances are supposed to retain the high-quality nature of IASI spectral data and are spectrally compatible for comparison with the coincident AVHRR observations. The result of equation (1) is the band-averaged radiance at the centre wave number νc for the bandwidth |ν2 − ν1|. From equation (1) it is clear that one of the limitations imposed by the incomplete spectral coverage of AVHRR channel 3B by IASI is the possible shift in representative central wave number νc, which becomes crucial for conversion of radiances into corresponding brightness temperatures. However, the simulated partial AVHRR radiances, while possibly representing a νc other than 3.74 µm, are still useful for investigations related to within-band spectral-radiative properties of AVHRR channel 3B because the parameters νc, ν1 and ν2 are all within the original AVHRR bandwidth. For these reasons, the analysis presented in this study is all with respect to radiance parameter instead of brightness temperature parameter. Using IASI level 1C data for selected days in each month of the year 2009 and following equation (1), simulated band-averaged AVHRR channel 3B radiances were generated for the AVHRRbandwidth covered by IASI. In ﬁgure 2(a) a typical example Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 of such simulated AVHRR channel 3B radiances using IASI observations with incomplete spectral coverage over the AVHRR channel 3B bandwidth versus the observed AVHRR channel 3B radiances is given. The example corresponds to observations on 15 November 2009. Figure 2(a) shows wide scatters indicating the necessity for quality control (QC) of the data. The chosen QC criteria for the coincident pairs used for further analysis are described in section 3.

3. Quality control criteria used for selecting the coincident pairs The QC criterion applied in the study is with respect to the scene homogeneity and the same as Wang and Cao (2008) except that in this study the scene homogeneity criterion is applied with respect to channel 3B. The inhomogeneous scenes lead to a variety of uncertainties such as the instrument line shape (ILS), in particular for IASI, Comparison of AVHRR channel 3B and IASI 5245

(a)(b) 6 2.0 ) 1.0 Bias = –0.0282840 –1 SD = 0.165563 cm N = 628753 –1 4 y x sr 0.8 = 0.883857 + –0.00205741

–2 r = 0.721591 1.5 (K) Sigma slope = 0.00106938 b T 2 Sigma intercept = 0.000318055 0.6 0 1.0

0.4 –2 Standard deviaton (K) 0.5 (AVHRR–IASI) ch3B (AVHRR–IASI) 0.2 –4

0.0 –6 0.0 AVHRR channel (mW m 3B radiance AVHRR 0.0 0.2 0.4 0.6 0.8 1.0 0.00 0.05 0.10 0.15 0.20 IASI channel 3B radiance (mW m–2 sr–1 cm–1) Standard deviaton of AVHRR radiance/ mean AVHRR radiance

Figure 2. (a) Typical example of AVHRR channel 3B radiances versus AVHRR SRF- convolved IASI radiances and (b) the (AVHRR – IASI) brightness temperature bias versus the scene homogeneity factor (SHF; black) and the standard deviation of AVHRR brightness temperatures versus SHF (magenta). In (a), legend ‘SD’ indicates standard deviation and ‘r’ indicates coefﬁcient of correlation. The green vertical line in (b) indicates the cut-off SHF chosen forthisstudy.

and spatial collocation uncertainties. Therefore, it is important to choose only those coincident pairs of AVHRR and IASI that are taken over homogeneous scenes for investigations. Following Wang and Cao (2008), the scene homogeneity factor (SHF) is deﬁned as follows:

Standard deviation of radiance SHF = .(2) Average radiance

The numerator in equation (2) is the standard deviation of radiance in the IASI FOV provided by collocated AVHRR measurements and the denominator is the corresponding averaged AVHRR radiance. Figure 2(b) shows AVHRR channel 3B specific brightness temperature bias as a function of SHF. As shown in this figure, an SHF value of 0.03 is chosen as a cut-off above which all the coincident pairs of AVHRR– Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 IASI in channel 3B are neglected from the analysis. It is clear from figure 3 that the standard deviations of brightness temperature are all much less than 1 K for the selected channel-specific cut-off values. The scatter plot in figure 3 demonstrates the effectiveness of SHF criteria in remov- ing the unwanted outliers. The spread of scatter in figure 3 is relatively smaller and devoid of outliers. In addition, the negative AVHRR minus IASI bias is more clearly evident in figure 3 than in figure 2(a) indicating the effectiveness of the SHF-based QC criterion in bringing out the subtle features of the data more prominently. These high-quality coincident pairs over presumably uniform scenes with minimized uncertainties can be utilized for investigating the inherent instrument or calibration-related uncertainties. It is acknowledged that the main limitation of the QC is that it depends only on AVHRR measurements while discarding any possible issues with IASI measurements. 5246 M. K. R. V. Raja et al. )

–1 1.0 Bias = –0.0428694 cm SD = 0.0236146 –1 N = 235680 sr y x –2 0.8 = 0.884883 + –0.00231703 r = 0.999961 Sigma slope = 1.65084e-05 0.6 Sigma intercept = 6.72533e-06

0.4

0.2

0.0 AVHRR channel (mW m 3B radiance AVHRR 0.0 0.2 0.4 0.6 0.8 1.0 IASI channel 3B radiance (mW m–2 sr–1 cm–1)

Figure 3. The AVHRR channel 3B radiances versus the AVHRR SRF-convoluted IASI radiances after applying the scene homogeneity factor-based quality control. This example corresponds to the quality controlled subset of data presented in ﬁgure 2(a).

However, for the goals of investigations with respect to this study equation (2) is deemed sufﬁcient.

4. Results and discussion It is clear from figure 3 that the AVHRR minus IASI bias is significantly negative (∼–0.04 mW m–2 sr–1 cm–1). If one does the comparison in brightness temperature space assuming a central wave number of 3.74 µm, this negative bias is nearly –2.8 K. The significant negative AVHRR minus IASI bias, in spite of the incomplete spectral coverage over AVHRR bandwidth by IASI, can only be explained by the absorption or scattering or both experienced at the portion of the AVHRR channel 3B band not seen by IASI. Such an explanation would question the ‘atmospheric window’ nature of MetOp-A AVHRR channel 3B. To further investigate the possible causes of the negative bias, IASI spectra were simulated using LBLRTM over the entire bandwidth of AVHRR channel 3B as shown Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 in figure 1. The simulated IASI spectra for four different atmospheric conditions were separately created and analysed. The four different atmospheric conditions considered in this study are tropical clear atmospheric conditions and tropical cloudy atmospheric conditions with cloud tops, respectively, at 700, 500 and 200 mb pressure levels. Subsequently, following equation (1), simulated AVHRRradiances corresponding to the entire AVHRR SWIR channel bandwidth centred at 3.74 µm are generated from LBLRTM-simulated IASI spectra. For convenience, these simulated AVHRR radiances are called AVHRRCOMPLETE and there are four of them corresponding to different atmospheric conditions mentioned above. In a similar way, simulated AVHRR radiances for only the IASI-covered portion of the AVHRR bandwidth are constructed using LBLRTM-simulated spectra and are called AVHRRINCOMPLETE. The AVHRRCOMPLETE minus the AVHRRINCOMPLETE bias versus the corresponding scene radiances for the four cases are plotted in figure 4(a). It can be noted in Comparison of AVHRR channel 3B and IASI 5247

(a)(b) ) –1 0.10 0.10 cm Bias = –0.0371250 Bias = –0.0428694 –1 SD = 0.0396547 SD = 0.0236146 sr N –2 = 4 N = 235680 y x = –0.126969 + –0.000888165 y x 0.05 0.05 = –0.115134 + –0.00231041 ) –1 Tropical profile with 200 mb cloud top cm –1 Tropical profile with 500 mb cloud top 0.00 sr 0.00 –2 Tropical profile with 700 mb cloud top (mW m –0.05 –0.05 Tropical clear profile (AVHRR-IASI) channel 3B radiance

–0.10 –0.10 0.0 0.2 0.4 0.6 0.8 1.0

AVHRR–IASI channel 3B radiance (mW m 0.0 0.2 0.4 0.6 0.8 1.0 –2 –1 –1 IASI channel 3B radiance (mW m–2 sr–1 cm–1) IASI channel 3B radiance (mW m sr cm )

Figure 4. (a) Idealized AVHRR minus IASI radiance bias in channel 3B versus the corresponding IASI channel 3B radiance constructed from line-by-line model simulations for four different atmospheric conditions such as tropical clear atmosphere, tropical cloudy atmosphere with cloud top height at 700 mb, tropical cloudy atmosphere with cloud top height at 500 mb and tropical cloudy atmosphere with cloud top at 200 mb. (b) Observed AVHRR minus IASI channel 3B radiance bias versus AVHRR SRF-convolved IASI channel 3B radiance.

figure 4(a) that the bias values are negative and that the absolute values of the bias linearly increase with increasing scene radiances. Plotted in figure 4(b) are the observed AVHRR minus IASI biases versus the corresponding IASI radiances on the night of 15 November 2009. Because MetOp-A AVHRR channel 3B operates only during the night, the effect of solar contamination can be excluded from consideration. The observed negative bias values with linear dependence on scene radiances are strikingly similar to the hypothetical cases presented in figure 4(a). In figure 4(a), the tropical clear profile represents the deepest atmospheric column and the tropical cloudy profile with cloud top height at the 200 mb pressure level represents the shortest atmospheric column experienced by the target emitted radiances before they are detected by sensor. Analogously, in figure 4(b), the warmest radiances most likely correspond to clear conditions with Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 the deepest atmospheric column, and the coldest scenes are possibly cloudy scenes with a shorter atmospheric column. The striking similarities of the bias values and their dependencies between figures 4(a)and4(b) clearly suggest that the radiant energy absorption by the atmospheric trace gas constituents in the spectral portion of the AVHRR channel 3B band not seen by IASI is the main reason for the observed negative AVHRR minus IASI bias and its linear dependency on the target emitted radiance. It must be noted that the portion of the AVHRR spectral band not seen by IASI is towards higher wave number regions from ∼3.3 to 2.98 µm (3030–3356 cm–1). The study by Liu et al. (2009) has shown that a number of trace gases such as car- bon dioxide (CO2), water vapour (H2O) and ozone (O3) could contribute towards absorption of infrared energy in the band between 2200 and 3200 cm–1. Thus, the MetOp-A AVHRR band portion between 3030 and 3200 cm–1 which is not seen by IASI can be considered to be contributing significantly towards the absorption. 5248 M. K. R. V. Raja et al.

(a)(b) 0.10 0.10 Bias = –0.0505158 Bias = –0.0416357 SD = 0.0354474 SD = 0.0226592 N = 17659 0.05 0.05 N = 224339 y = –0.0859812x + –0.00530237 y = –0.115468x + –0.00214458 ) ) –1 –1 0.00 0.00 cm cm –1 –1 sr sr

–0.05 –2 –0.05 –2 (mW m

(mW m –0.10 –0.10 (AVHRR-IASI) channel 3B radiance (AVHRR-IASI)

(AVHRR–IASI) channel 3B radiance (AVHRR–IASI) –0.15 –0.15

–0.20 –0.20 0.0 0.5 1.0 1.5 2.0 2.5 0.0 0.5 1.0 1.5 2.0 2.5 IASI channel 3B radiance (mW m–2 sr–1 cm–1) IASI channel 3B radiance (mW m–2 sr–1 cm–1)

Figure 5. (a) Observed AVHRR minus IASI radiance bias in channel 3B versus corresponding AVHRR SRF-convolved IASI channel 3B radiance during daytime on 23 November 2009. The daytime observations on two orbits of MetOp-A were materialized through National Oceanic and Atmospheric Administration (NOAA)–European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) collaboration and coordination. (b)Sameasin(a)but for night-time observations. The red lines in both panels indicate the best linear ﬁt.

While Liu et al. (2009) mainly investigated the out-of-band response by the National Oceanic and Atmospheric Administration (NOAA)-16 AVHRR, this study brings out the significant within-band absorption experienced by MetOp-A AVHRR channel 3B. A detailed quantitative examination of individual atmospheric trace gas contribution towards absorption of infrared energy in the entire portion of MetOp-A AVHRR channel 3B band not seen by IASI is interesting but considered beyond the scope of this study. To further confirm that the routine MetOp-A AVHRR channel 3B observations taken typically during night-time are not adversely affected by solar contamination, a comparison of AVHRR minus IASI biases versus the corresponding scene IASI radiances, respectively, for daytime and night-time is presented in figure 5(a)and5(b). These cases correspond to 23 November 2009 when the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) enabled daytime MetOp- A AVHRR channel 3B observations over two orbits. While the adverse impact of solar Downloaded by [M. K. Rama Varma Raja] at 11:09 27 February 2012 contamination on AVHRR channel 3B measurements is clearly evident in figure 5(a), with increased spread of scatter and slightly enhanced negative bias, the features of night-time biases in figure 5(b) are nearly similar to those presented in figure 4(b). The linear dependence of the bias on scene radiances is clearly evident for daytime observations too. A comparison of figures 5(a)and5(b) makes it clear that routine MetOp-A AVHRR channel 3B observations which typically happen in night are not solar contaminated and the conclusions drawn in this study are not adversely influenced.

5. Conclusions A comparison between AVHRR channel 3B observed radiances and coincident IASI radiances that are convolved with the AVHRR spectral response function showed Comparison of AVHRR channel 3B and IASI 5249

a signiﬁcant negative AVHRR minus IASI bias. Because of the fact that the spectrally convolved IASI radiances cover only a portion of the AVHRR spectral band from 4.49 to 3.7 µm, even though the actual AVHRR bandwidth is 4.49–2.98 µm, the underestimation of AVHRR radiances can only be explained based on the possible absorption of energy in the portion not seen by IASI. Thus, it is demonstrated through observations that MetOp-A AVHRR channel 3B experiences signiﬁcant within-band absorption, which is further supported by the results of investigations using LBLRTM. The near similarity between results from the observations and those from the LBLRTM simulations in terms of the bias sign, the bias magnitude and the scene radiance dependency of the bias clearly indicates that the absorption taking place in the portion of the MetOp-A AVHRR channel 3B band not seen by the IASI is the root cause of the observed negative bias and scene dependency of the bias. Irrespective of day or night, the biases and the associated behaviours are nearly similar except that there is a slightly enhanced negative bias during daytime, pointing towards the possibility of solar contamination in both AVHRR and IASI observations during daytime. Also, there is a larger spread during daytime indicating the solar contamination in the measurements. This study thus reveals that MetOp-A AVHRR channel 3B is not a ‘true atmospheric window’. The algorithms for deriving products using this AVHRR channel should take this factor into account for optimal accuracy in the derived products.

Acknowledgements The authors are grateful to Dr Michael Weinreb of NOAA/NESDIS/SOCC for helpful discussions during the course of the work. M. K. Rama Varma Raja also gratefully acknowledges the helpful discussions during the course of the reported work with Dr Changyong Cao (NOAA/NESDIS/STAR), Dr Likun Wang (Dell Services Federal Government@NOAA/NESDIS/STAR) and Dr Ruiyue Chen (I.M. Systems Group, Inc.@NOAA/NESDIS/STAR). M. K. Rama Varma Raja gratefully acknowledges the support received from I.M. Systems Group, Inc., during the course of this work. This work was funded by the NOAA/NESDIS/STAR cal/val project and the NOAA Science Data Stewardship project through the interagency agreement IA1-1016. The contents are solely the opinions of the authors and do not consti- tute a statement of policy, decision or position on behalf of the NOAA or the US Government.

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