High-Resolution Infrared Radiation Sounder Channels Research Articles

Spectral Recalibration of NOAA HIRS Longwave CO2 Channels toward a 40+ Year Time Series for Climate Studies

The High-Resolution Infrared Radiation Sounder (HIRS) on NOAA and MetOp A/B satellites has been observing the Earth continuously for over four decades, providing essential data for operational numerical weather prediction, retrieval of atmospheric vertical profile, and total column information on atmospheric temperature, moisture, water vapor, ozone, cloud climatology, and other geophysical parameters globally. Although the HIRS data meets the needs of the short-term weather forecast, there are inconsistencies when the long-term decadal time series is used for time series analysis. The discrepancies are caused by several factors, including spectral response differences between the HIRS models on the satellites and spectral response uncertainties and other calibration issues. Previous studies have demonstrated that significant improvements can be achieved by recalibrating some of the HIRS longwave CO2 channels (Channels 4, 5, 6, and 7), which has helped make the time series more consistent. The current study aims to extend the previous study to the remaining longwave infrared sounding channels, including Channels 1, 2, 3, and 8, using a similar approach. Similar to previous findings, the spectral shift of the HIRS bands has helped improve the consistency in the time series from NOAA-06 to MetOp-A and B for these channels. We also found that HIRS channels on MetOp-B also have bias relative to Infrared Atmospheric Sounding Interferometer (IASI) on the same satellite, especially Channel 4, and a spectral shift significantly reduced the bias. To bridge the observation gap in time series in the mid-1980s between NOAA-07 and NOAA-09, the global mean method has been used since no transfer radiometers between them was available for this period, and the spectral response function corrections, therefore, can be applied to the earliest satellites (NOAA-06) for these channels. The recalibration parameters have been provided to other scientists at the University of Wisconsin for improving the time series in their long-term studies using historical HIRS data and are now made available to the science community.

Error Correlations in High-Resolution Infrared Radiation Sounder (HIRS) Radiances

The High-resolution Infrared Radiation Sounder (HIRS) has been flown on 17 polar-orbiting satellites between the late 1970s and the present day. HIRS applications require accurate characterisation of uncertainties and inter-channel error correlations, which has so far been lacking. Here, we calculate error correlation matrices by accumulating count deviations for sequential sets of calibration measurements, and then correlating deviations between channels (for a fixed view) or views (for a fixed channel). The inter-channel error covariance is usually assumed to be diagonal, but we show that large error correlations, both positive and negative, exist between channels and between views close in time. We show that correlated error exists for all HIRS and that the degree of correlation varies markedly on both short and long timescales. Error correlations in excess of 0.5 are not unusual. Correlations between calibration observations taken sequentially in time arise from periodic error affecting both calibration and Earth counts. A Fourier spectral analysis shows that, for some HIRS instruments, this instrumental effect dominates at some or all spatial frequencies. These findings are significant for application of HIRS data in various applications, and related information will be made available as part of an upcoming Fundamental Climate Data Record covering all HIRS channels and satellites.

HIRS channel 12 brightness temperature dataset and its correlations with major climate indices

Abstract. A new version of the High-Resolution Infrared Radiation Sounder (HIRS) upper tropospheric water vapor channel (channel 12) brightness temperature dataset is developed using intersatellite calibrated data. In this dataset, only those pixels affected by upper tropospheric clouds are discarded. Compared to the previous version that was based on column-clear-sky data, the new version has much better daily spatial coverage. The HIRS observation patterns are compared to microwave sounder measurements. The differences between the two types of sounders vary with respect to brightness temperature with larger differences for higher (dry) values. Correlations between the HIRS upper tropospheric water vapor channel brightness temperatures and several major climate indices show strong signals during cold seasons. The selected climate indices track climate variation signals covering regions from the tropics to the poles. Qualitatively, moist signals are correlated with troughs and ascending branches of the circulation, while dry signals occur with ridges and descent. These correlations show the potential of using the upper tropospheric water vapor channel brightness temperature dataset together with a suite of many atmospheric variables to monitor regional climate changes and locate global teleconnection patterns.

Climate Model–Simulated Diurnal Cycles in HIRS Clear-Sky Brightness Temperatures

Abstract Clear-sky brightness temperature measurements from the High-Resolution Infrared Radiation Sounder (HIRS) are simulated with two climate models via a radiative transfer code. The models are sampled along the HIRS orbit paths to derive diurnal climatologies of simulated brightness temperature analogous to an existing climatology based on HIRS observations. Simulated and observed climatologies are compared to assess model performance and the robustness of the observed climatology. Over land, there is good agreement between simulations and observations, with particularly high consistency for the tropospheric temperature channels. Diurnal cycles in the middle- and upper-tropospheric water vapor channels are weak in both simulations and observations, but the simulated diurnal brightness temperature ranges are smaller than are observed with different phase and there are also intermodel differences. Over sea, the absence of diurnal variability in the models’ sea surface temperatures causes an underestimate of the small diurnal cycles measured in the troposphere. The simulated and observed climatologies imply similar diurnal sampling biases in the HIRS record for the tropospheric temperature channels, but for the upper-tropospheric water vapor channel, differences in the contributions of the 24- and 12-hourly diurnal harmonics lead to differences in the implied bias. Comparison of diurnal cycles derived from HIRS-like and full model sampling suggests that the HIRS measurements are sufficient to fully constrain the diurnal behavior. Overall, the results suggest that recent climate models well represent the major processes driving the diurnal behavior of clear-sky brightness temperature in the HIRS channels. This encourages further studies of observed and simulated climate trends over the HIRS era.

Mineral aerosol contamination of TIROS Operational Vertical Sounder (TOVS) temperature and moisture retrievals

Since mineral aerosols absorb significant amounts of infrared radiation, they may contribute to errors in the retrievals of atmospheric and surface parameters from the TIROS Operational Vertical Sounder (TOVS) High‐Resolution Infrared Radiation Sounder (HIRS) if the atmosphere is assumed clear. TOVS is an operational sounder on NOAA polar satellites. To see if observed brightness temperatures are reduced by mineral aerosol, we analyzed results from the Data Assimilation Office (DAO) Finite Volume Data Assimilation System (fvDAS). Every 6 hours the assimilated temperature and moisture profiles are used as a first guess in the DAO interactive cloud‐clearing TOVS retrieval system. The observed minus the forecast (O–F) brightness temperature, which is a measure of the accuracy of the first guess and radiative transfer parameters, becomes more negative with increasing dust concentrations. Dust concentrations are from the Goddard Ozone Chemistry Aerosol Radiation Transport (GOCART) model. Since there was no account of dust during this fvDAS run, the dependence of O–F on the estimated atmospheric dust concentrations from GOCART indicates that the dust is affecting the TOVS brightness temperatures. HIRS channels that are sensitive to the surface temperature, lower tropospheric temperature, and moisture are subject to a 0.5 K or more reduction in the brightness temperature during heavy dust loading conditions. The radiative transfer module used in the TOVS retrieval system was modified to account for dust assuming a composition of illite, and the fvDAS run was repeated. Accounting for dust absorption in the retrieval system yields warmer surface temperatures (0.4 K) and warmer lower tropospheric temperatures in regions of moderate dust loading over the tropical Atlantic.

Climatological features of the global tropical subsidence region based on satellite observations

Consisting of subtropical highs and tropical buffer zone, the global tropical subsidence region is the subsidence branches of Hadley cell. Walker circulation and monsoon circulation which are important components of the global general circulation. This region is closely connected with Asian monsoon. Based on long-term satellite observations of OLR (Outgoing Longwave Radiation) and HIRS-Tbl2 (the bright temperature from High-resolution Infra-red Radiation Sounder Channel 12 (6.7 Μm)), the climatological features over the global tropical subsidence region are studied in this paper and the main findings are as follows:

An Assessment of the Differential Inversion Method for Remote Sounding of Temperatures

Abstract We have explored the applicability of the differential inversion (DI) method to temperature retrievals in both clear and cloudy atmospheres using red satellite data. The main theme of the DI is that the local Planck intensity can be exactly expressed by a linear combination of the derivatives of radiances in the logarithmic pressure coordinate. The inversion coefficients are obtained by fitting the weighting function to a generalized form. The higher-order derivatives of radiances are determined from polynomial fittings. The satellite dataset used in this work contains collocated brightness temperatures and radiosonde data that have been collected during the period of Baseline Upper Atmospheric Network (BUAN) experiments. These data include both cloudy and clear cases. A multispectral cloud-removal method using the principle of the N* method has been developed. This method uses radiances of High-Resolution Infrared Radiation Sounder channels 6, 7, and 8 to estimate clear radiances of these channe...