Task 3 – Atmospheric temperatures derived from IASI data

Temperature profiles can be obtained from IASI radiances using CO2 absorption bands at 15 µm (645-800 cm-1) and 4.3 µm (2250-2400 cm-1). Weighting functions from atmospheric radiative transfer models provide information regarding which radiance channel is sensitive to which altitudes. 

Assessment of the stability of the radiance record

Since 2007, the processing of IASI data done by the EUropean organisation for the exploitation of METeorological SATellites (EUMETSAT) has improved, but due to IASI’s huge data flow, the whole dataset has not yet been reprocessed backwards. In 2019, EUMETSAT reprocessed IASI radiances with the latest version of the processing algorithm. We compared IASI operational radiances with the reprocessed ones to assess their homogeneity. In brightness temperatures, the differences between the two datasets range from 0.02 K at 700 cm-1 to 0.1 K at 2200 cm-1. Two updates in 2010 and 2013 had the largest impact on the evolution of radiances, see Figure 3.1.

Figure 3.1. Evolution of the differences Rreproc – Roper as a function of the Field of Regard (FoR) in the Amazon rainforest (AMA), Western Europe (EUR), the Indian Ocean (OCE) and Greenland (GRO) at 700, 1200, 1700 and 2200 cm-1. The differences are shown as percentage of the reprocessed L1C. Grey pixels correspond to no data with the right FoR. The vertical dashed lines correspond to L1 processing updates. Note that the colorbar limits are different for each wavenumber.

Assessment of the stability of the temperature record

For temperatures, we compared IASI-A and B with ERA5 reanalysis temperatures. We found differences of ~5-10 K at the surface and between 1 and 5 K in the atmosphere (Figure 3.2). These differences decrease abruptly after the release of the IASI L2 processor version 6 in 2014.These results suggest that it is not recommended to use the IASI inhomogeneous temperature products for trend analysis, both for temperature and trace gas trends.

Figure 3.2. Differences between IASI-A and ERA5 (in dark colors), and IASI-B and ERA5 (in lighter colors) for surface temperature at the poles, mid latitudes and the equator. Differences in the Northern Hemisphere are plotted in red/orange and differences in the Southern Hemisphere are plotted in blue. The vertical dashed lines correspond to L2 updates. Note that the y-axis limits for each latitude band are different.

Computation of a new temperature record

In order to compute a new homogeneous temperature record, we used a artificial neural network (ANN). The ANN was trained with IASI radiances as input and ERA5 atmospheric temperatures at 11 pressure levels as output. The retrieved temperatures were compared with ERA5 and ARSA for validation. We found a good agreement between the three datasets between 750 and 7 hPa, where IASI is most sensitive to temperature (differences up to 1 K). At 2 hPa, the IASI sensitivity decreases and the differences reach 2 K. Figure 3.3 show the differences between the ANN product and ERA5 at the 11 pressure levels.


We used this new temperature time series to compute linear trends over the period 2008-2020 (figure 3.4.). We found that there is a general warming of the troposphere that is more important at the poles and mid-latitudes (0.5 K/decade at mid-latitudes, 1 K/decade at the North Pole). The stratosphere is globally cooling on average, except at the South Pole as a result of the ozone layer recovery and a sudden stratospheric warming in 2019. The cooling is most pronounced in the equatorial upper stratosphere (−1 K/decade).

Figure 3.4. Zonal temperature trends for the period 2008–2020 computed with the outputs of the ANN. Grey areas correspond to trends that are not statistically significant.


Bouillon M., S. Safieddine, J. Hadji-Lazaro, S. Whitburn, L. Clarisse, M. Doutriaux-Boucher, D. Coppens, T. August, E. Jacquette and C. Clerbaux: Ten-year assessment of IASI radiances and temperatures, Remote Sensing, 12(15), 2393; https://doi.org/10.3390/rs12152393, 2020.

Bouillon, M., Safieddine, S., Whitburn, S., Clarisse, L., Aires, F., Pellet, V., Lezeaux, O., Scott, N. A., Doutriaux-Boucher, M., and Clerbaux, C.: Time evolution of temperature profiles retrieved from 13 years of infrared atmospheric sounding interferometer (IASI) data using an artificial neural network, Atmos. Meas. Tech., 15, 1779–1793, https://doi.org/10.5194/amt-15-1779-2022, 2022.

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