Longwave Channels Research Articles

Hybrid solar irradiance nowcasting and forecasting with the SCOPE method and convolutional neural networks

We use a full year (2018) of GOES-R satellite data to produce 5-minute resolved information on cloud coverage for 7 Surface Radiation Budget Network (SURFRAD). The remote sensing images are then processed using the Spectral Cloud Optical Property Estimation (SCOPE) method in conjunction with Convolution Neural Networks (CNNs) for nowcasts and 1-hour ahead forecasts. We propose and compare two CNN based models for GHI now-casting with a 1-hour forecast horizon and a time resolution that processes data every 5 minutes: one enhanced with the SCOPE method for cloud estimation and another without it. The inclusion of SCOPE-derived information significantly improves model performance, yielding an average RMSE of 44.7 versus 68.9 W/m2 for the model without SCOPE information. The present work underscores the efficacy of even basic CNNs in interpreting satellite imagery combined with atmospheric models of the atmosphere to estimate ground irradiance accurately. The hybrid SCOPE-CNN model outperforms the basic CNN model that relies solely on 10 longwave channels, indicating the relevance of SCOPE’s physical features in enhancing predictions across various solar micro-climates. Further advancements using Convolutional Long Short-Time Memory (ConvLSTM) schemes lead to the development of a SCOPE-CNN-ConvLSTM model, showcasing significant enhancements over smart persistence across all conditions.

The Evaluation of FY-3E Hyperspectral Infrared Atmospheric Sounder-II Long-Wave Temperature Sounding Channels

Prior to assimilating hyperspectral infrared data on the FengYun (FY) satellite in the numerical weather prediction (NWP) system, it is necessary to identify the quality and bias characteristics of these data, especially as China’s first early-morning-orbit satellite data. Using the numerical model CMA-GFS (China Meteorological Administration Global Forecast System) and the observation of FY-3E HIRAS-II (Hyperspectral Infrared Atmospheric Sounder-II), the differences between observed and simulated brightness temperatures (O-Bs) are comprehensively analyzed, with a focus on evaluating the long-wave (LW) temperature sounding channels of HIRAS-II observation in the clear sky. The results show that the O-Bs in the LW channels are between ±1.0 K, except for the CO2 absorption line peak at 667 cm−1. Only a tiny variation in O-Bs, with relative consistency, could be observed during the day, the line of dawn and dusk, and night. The difference in the standard deviations of O-Bs in the three cases is less than 0.1 K. The O-Bs of two typical channels (channels 14 and 47) in the stratosphere have disturbances at individual times, whereas the O-Bs are much more stable in time series in the tropospheric channels. The O-Bs in different channels show the characteristics of changing with the latitude, but the bias and standard deviations of O-Bs during the ascending and descending stages are not much different, except for the bias of channel 47 in low latitude. The optimal ranking of Fields of View (FOVs) in assimilation is derived from a priori analysis of O-Bs. The results demonstrate that FOV4 and FOV5 are the best in a Field of Regard (FOR) compared to all LW channels of HIRAS-II in constructions of their O-Bs and magnitude of O-B standard deviations, and they can be used as the preferred FOVs for assimilation. While the O-Bs in FOV1 and FOV2 are slightly larger, the O-Bs’ characteristics also meet the assimilation requirements and can be used as assimilation FOVs in HIRAS-II LW channels after FOV4 and FOV5 lose their efficacy.

Extending the HIRS Data Record with IASI Measurements

The High-Resolution Infrared Radiation Sounder (HIRS) on the NOAA and the MetOp satellite series have provided global sounding measurements since the late 1970s, spanning over 40 years. These measurements have been useful in climate change detection, numerical weather prediction, and development of long-term climate data records of profiles of atmospheric temperature and humidity, cloud climatology, upper tropospheric water vapor, outgoing longwave radiation, etc. However, the HIRS instrument is being replaced by the new generation of sounders such as the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) on recently launched satellites. In order to continue and extend the HIRS record, we use IASI measurements to simulate and derive HIRS-like data for the 12 HIRS longwave channels. The MetOp satellite operated by EUMETSAT carries both the HIRS and the hyper-spectral IASI instrument with accurate spectral and radiometric calibration, providing a great opportunity to consistently calibrate the measurements. The IASI radiances are convolved with the HIRS spectral response functions to produce IASI-simulated HIRS (IHIRS) for the longwave channels. In the present work, IHIRS data are collocated and compared with HIRS observed radiances on the same satellite to develop a calibration table for each of the ascending/descending orbits and cloudy and clear categories. The resulting inter-instrument calibrated IHIRS data was found to agree with HIRS brightness temperatures within 0.05 K for all longwave channels.

Advantage of Regional Algorithms for the Chlorophyll-a Concentration Retrieval from In Situ Optical Measurements in the Kara Sea

The data of the sea reflectance coefficient were obtained during the cruise of the R/V “Akademik Ioffe” (10 August–8 September 2021) in the Kara Sea beyond the Arctic Circle. A total of 28 measurements of sea reflectance were performed in different conditions ranging from estuarine zones to open ocean. In addition, at 10 stations, water samples were taken, and chlorophyll-a concentrations were determined using the fluorometric method. In situ reflectance data were compared to satellite data (MODIS Aqua/Terra, Sentinel OLCI 3A/B, VIIRS SNPP) obtained within 24 h before and after the measurement. It was shown that, in general, an overestimation of remote sensing reflectance is observed in short-wave channels (412, 443, 469 nm for MODIS; 410, 412.5, 442.5 for OLCI) and underestimation in long-wave channels (708.75, 753.75 nm for OLCI). The obtained in situ chlorophyll-a concentrations were compared with the results of standard models (GIOP, OC2, OC3, OC4), and regional algorithms (semi-analytical MHI, empirical K17) were applied to the in situ and remotely sensed reflectances. In the cases of GIOP and OC4, unrealistic concentrations of chlorophyll-a were obtained. Regional algorithms developed earlier, specifically for the Kara Sea, showed good correlation (0.6 and 0.76) with in situ measurements. Despite the approximately 20% overestimation of chlorophyll-a by both regional algorithms, they can be used to obtain chlorophyll-a concentrations in the Kara Sea in a concentration range of <1 mg/m3.

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.

Using GOES ABI Split-Window Radiances to Retrieve Daytime Low-Level Water Vapor for Convective Forecasting

A clear sky, daytime retrieval of low-level precipitable water vapor based on the single-layer approximation to the radiative transfer equation applied to three longwave window channels is described. The algorithm, which simultaneously retrieves skin temperature and air temperature as well, has the advantage of using satellite radiances only—no ancillary information is needed. Application of the method to Geostationary Operational Environmental Satellite (GOES)-16 Advanced Baseline Imager (ABI) radiance observations at 10.3, 11.2 and 12.3 µm demonstrates its utility in monitoring the location of low-level water vapor in the warm season, pre-convective atmosphere over the United States.

Behavioural thresholds of blue tit colour vision and the effect of background chromatic complexity

Vision is a vital attribute to foraging, navigation, mate selection and social signalling in animals, which often have a very different colour perception in comparison to humans. For understanding how animal colour perception works, vision models provide the smallest colour difference that animals of a given species are assumed to detect. To determine the just-noticeable-difference, or JND, vision models use Weber fractions that set discrimination thresholds of a stimulus compared to its background. However, although vision models are widely used, they rely on assumptions of Weber fractions since the exact fractions are unknown for most species. Here, we test; i) which Weber fractions in long-, middle- and shortwave (i.e. L, M, S) colour channels best describe the blue tit (Cyanistes caeruleus) colour discrimination, ii) how changes in hue of saturated colours and iii) chromatic background noise impair search behaviour in blue tits. We show that the behaviourally verified Weber fractions on achromatic backgrounds were L: 0.05, M: 0.03 and S: 0.03, indicating a high colour sensitivity. In contrast, on saturated chromatic backgrounds, the correct Weber fractions were considerably higher for L: 0.20, M: 0.17 and S: 0.15, indicating a less detailed colour perception. Chromatic complexity of backgrounds affected the longwave channel, while middle- and shortwave channels were mostly unaffected. We caution that using a vision model whereby colour discrimination is determined in achromatic viewing conditions, as they often are, can lead to misleading interpretations of biological interactions in natural – colourful – environments.

Determination Of Efficient Modes Of Optical Radiation Exposure For Control Of Human Circadian Activity

The article describes the stages of transformation of the direct and diffused components of solar radiation in the short-wave and long-wave spectral channels of the human circadian activity control path. The method of determination of the dependences of irradiance on Solar altitude angle as well as the values of radiant exposure in the circadian region of the optical spectre required for efficient control of human circadian activity. An example of utilisation of the developed method is provided. Correspondence between the results of calculations based onthe proposed method and the results of independent experimental studies is demonstrated. The developed method allows us to formulate major light-engineering requirements to characteristics of emitting installations controlling human circadian activity, preventing and eliminating its deregulations.

On the Methods for Recalibrating Geostationary Longwave Channels Using Polar Orbiting Infrared Sounders

This study presents a common recalibration method that has been applied to geostationary imagers’ infrared (IR) and water vapour (WV) channel measurements, referred to as the multi-sensor infrared channel calibration (MSICC) method. The method relies on data of the Infrared Atmospheric Sounding Interferometer (IASI), Atmospheric Infrared Sounder (AIRS), and High-Resolution Infrared Radiation Sounder (HIRS/2) on polar orbiting satellites. The geostationary imagers considered here are VISSR/JAMI/IMAGER on JMA’s GMS/MTSAT series and MVIRI/SEVIRI on EUMETSAT’s METEOSAT series. IASI hyperspectral measurements are used to determine spectral band adjustment factors (SBAF) that account for spectral differences between the geostationary and polar orbiting satellite measurements. A new approach to handle the spectral gaps of AIRS measurements using IASI spectra is developed and demonstrated. Our method of recalibration can be directly applied to the lowest level of geostationary measurements available, i.e., digital counts, to obtain recalibrated radiances. These radiances are compared against GSICS-corrected radiances and are validated against SEVIRI radiances, both during overlapping periods. Significant reduction in biases have been observed for both IR and WV channels, 4% and 10%, respectively compared to the operational radiances.

Thermal field of the southern taiga landscape of the Russian plain

The technology of allocation of order parameters (invariants) of the spatial structure of the thermal field of the southern taiga landscape (Central Forest Nature Reserve) obtained on the basis of the analysis of the time series of measurements in the long-wave channel of Landsat satellites from 1986 to 2017 and reflecting its stationary state is considered. It is shown that the heat flux is measured by the satellite not directly from the forest crowns, but from the ground layer of the atmosphere, the state of which is determined by the parameters of the landscape. It is found that the invariant component of the spatiotemporal variation of the thermal field is displayed by two order parameters: the first mainly reflects the temperature of winter months, the second – of summer. The contribution of relief and vegetation to the determination of invariants and the autochthonous components of the thermal field determined by the transition zones between the landscape elements contrasting in thermal radiation are revealed. It is shown that the thermal field measured by the satellite reflects the heat flux from the ground layer of the atmosphere, which is in direct interaction with the landscape cover.

Alternate Mapping Correlated k-Distribution Method for Infrared Radiative Transfer Forward Simulation

The alternate mapping correlated k-distribution (AMCKD) method is studied and applied to satellite simulations. To evaluate the accuracy of AMCKD, the simulated brightness temperatures at the top of the atmosphere are compared with line-by-line radiative transfer model (LBLRTM) or the observed data which are from Advanced Himawari Imager (AHI) on board the Himawari-8, as well as Medium Resolution Spectral Imager (MERSI) on board the Fengyun-3D. The result of AMCKD is also compared with the algorithm of Radiative Transfer for the Television Observation Satellite Operational Vertical Sounder (RTTOV). Under the standard atmospheric profiles, the absolute errors of AMCKD in all longwave channels of AHI and MERSI are bounded by 0.44K compared to the benchmark results of LBLRTM, which are more accurate than those of RTTOV. In the most cases, the error of AMCKD is smaller than the NEDT at ST, while the error of RTTOV is larger than the instrument noise equivalent temperature (NEDT) at scene temperature (ST). Under real atmospheric profile conditions, the errors of AMCKD increase, because the input data from ERA-Interim reanalysis dataause bias in the satellite remote sensing results. In the most considered cases, the accuracy of AMCKD is higher than RTTOV, while the efficiency of AMCKD is slightly slower than RTTOV.

Using the Himawari-8 AHI Multi-Channel to Improve the Calculation Accuracy of Outgoing Longwave Radiation at the Top of the Atmosphere

In this study, Himawari-8 Advanced Himawari Imager (AHI) longwave channel data that is sensitive to clouds and absorption gas were used to improve the accuracy of the algorithm used to calculate outgoing longwave radiation (OLR) at the top of the atmosphere. A radiative transfer model with a variety of atmospheric conditions was run using Garand vertical profile data as input data. The results of the simulation showed that changes in AHI channels 8, 12, 15, and 16, which were used to calculate OLR, were sensitive to changes in cloud characteristics (cloud optical thickness and cloud height) and absorption gases (water vapor, O3, CO2, aerosol optical thickness) in the atmosphere. When compared to long-term analysis OLR data from 2017, as recorded by the Cloud and Earth’s Radiant Energy System (CERES), the OLR calculated in this study had an annual mean bias of 2.28 Wm−2 and a root mean square error (RMSE) of 11.03 Wm−2. The new calculation method mitigated the problem of overestimations in OLR in mostly cloudy and overcast regions and underestimated OLR in cloud-free desert regions. It is also an improvement over the result from the existing OLR calculation algorithm, which uses window and water vapor channels.

Modeling of Nonlocal Thermodynamic Equilibrium Effects in the Classical and Principal Component‐Based Version of the RTTOV Fast Radiative Transfer Model

AbstractThe direct assimilation in 4D‐Var of principal component (PC) scores derived from Infrared Atmospheric Sounding Interferometer (IASI) spectra has recently been demonstrated. To maximize the exploitation of the IASI instrument, a future step is to consider the extension of the PC approach to the extraction of information from the 4.3‐μm CO2‐absorbing region. Shortwave IASI channels are currently underused compared to similar longwave channels because of day‐night variations in data usability due to departures from local thermodynamic equilibrium (LTE). In this paper, we document the introduction of non‐LTE (NLTE) effects in the PC‐based version of the radiative transfer for TIROS operational vertical sounder (RTTOV) fast radiative transfer model (PC‐RTTOV). The inclusion of NLTE effects in PC‐RTTOV has required the development of a parameterized scheme that allows the fast computation of a NLTE correction to LTE radiances. The fast NLTE model is general enough to be applied to any sensor and can be utilized to add a fast and accurate NLTE correction to polychromatic LTE spectra computed by any general radiative transfer model, including RTTOV, which now incorporates the fast NLTE model developed in this study. The accuracy of the NLTE correction is such that daytime and nighttime radiances can be simulated to almost the same degree of accuracy. The comparison with IASI observations shows that the fast NLTE model presented here performs significantly better than the fast NLTE model incorporated in the previous version of RTTOV and also that improvements have to be made to the simulation of NLTE effects at winter high latitudes.

Combining CrIS double CO2 bands for detecting clouds located in different layers of the atmosphere

AbstractDetection of clouds within certain vertical layers of the atmosphere from satellite infrared instruments is challenging, especially of those optically thin clouds due to their small thermal contrasts to the background. This study develops a new method for cloud detection by using the Cross‐track Infrared Sounder (CrIS) hyperspectral radiances at shortwave (~4.3 µm) and longwave (~15 µm) CO2 bands. Specifically, CrIS longwave channels are first paired with shortwave channels based on weighting function altitudes and sensitivity to clouds. A linear relationship of brightness temperatures between each paired channel is then derived for predicting the shortwave channel from the longwave channel in clear‐sky conditions. A cloud emission and scattering index (CESI) can finally be defined as the difference of the paired shortwave channel between the clear‐sky, regression model predicted and the observed brightness temperatures. Spatial distributions of such derived CESI for several paired channels in the troposphere are examined for a winter storm that occurred in the eastern part of the United States during 22–24 January 2016. It is shown that the CESI values over the storm regions with optically thin cirrus, fog, and supercooled water clouds are positively larger than those over optically thick opaque ice and overshooting clouds or in clear‐sky conditions. Of particular interest is that an area of fog and water clouds over Gulf of Mexico, which are indicated by the Visible Infrared Imaging Radiometer Suite day and night band observations, is identified by the CESI. The global distribution of CESIs derived from CrIS double CO2 bands with weighting functions peak around 321 hPa agrees well with the distribution of ice cloud optical thickness from the Atmospheric Infrared Sounder version 6 cloud product data set in both daytime and nighttime.

Low Crosstalk Three-Color Infrared Detector by Controlling the Minority Carriers Type of InAs/GaSb Superlattices for Middle-Long and Very-Long Wavelength**Supported by the National Basic Research Program of China under Grant Nos 2014CB643903, 2013CB932904, 2012CB932701 and 2011CB922201, the National Special Funds for the Development of Major Research Equipment and Instruments of China under Grant No 2012YQ140005, the Strategic Priority Research Program (B)

We report a type-II InAs/GaSb superlattice three-color infrared detector for mid-wave (MW), long-wave (LW), and very long-wave (VLW) detections. The detector structure consists of three contacts of NIPIN architecture for MW and LW detections, and hetero-junction NIP architecture for VLW detection. It is found that the spectral crosstalks can be significantly reduced by controlling the minority carriers transport via doping beryllium in the two active regions of NIPIN section. The crosstalk detection at MW, LW, and VLW signals are achieved by selecting the bias voltages on the device. At 77K, the cutoff wavelengths of the three-color detection are 5.3 μm (at 0 mV), 14 μm (at 300 mV) and 19 μm (at −20 mV) with the detectivities of 4.6×1011 cm·Hz1/2 W−1, 2.3 × 1010 cm·Hz1/2W−1, and 1.0×1010 cm·Hz1/2W−1 for MW, LW and VLW. The crosstalks of the MW channel, LW channel, and VLW channel are almost 0, 0.25, and 0.6, respectively.

Preliminary assessment of the Advanced Himawari Imager (AHI) measurement onboard Himawari-8 geostationary satellite

The Japan Himawari-8 geostationary satellite was successfully launched into the geosynchronous orbit around 140°E on 17 October 2014. The Advanced Himawari Imager (AHI) onboard the Himawari-8 has its channels 7–16 covering from the short- to the thermal-infrared bands, of which observations can be assimilated into a data assimilation system to improve the atmospheric analysis. Before conducting any AHI data assimilation experiments, it is the first and critical step to correctly quantify AHI bias and error variance, since these two variables are required in a data assimilation system. This study investigates the bias and the error variance of the AHI infrared measurements under clear-sky conditions by using a numerical weather prediction model and a radiative transfer model. Overall, AHI observations agree favourably with the model simulations. It is noted that channels 7–14 has a cold bias of approximately 1.0 K while the cold bias reaches around 2.0 ~ 3.0 K for the longwave Channel 15 and Channel 16. The sums of the observation and model error are about 1.5 K for three water vapour channels 8, 9, 10, and approximately 1.0 K for the remaining channels. The dependence of the bias on the scene temperature and scan angle is further investigated. It shows that a warm bias is negatively correlated with the scene temperature when the scene temperature is low for those surface-sensitive channels. Besides, linear regression tests between the bias and the sensor zenith angle shows that the fitting coefficient is less than 0.015 K/degree for all ten channels, indicating no obvious scan-angle-dependent bias.

Comparisons of Two Cloud-Detection Schemes for Infrared Radiance Observations

AbstractThe cloud-detection procedure developed by McNally and Watts (MW03) was added to the Weather Research and Forecasting Data Assimilation System. To provide some guidelines for setting up cloud-detection schemes, this study compares the MW03 scheme to the Multivariate and Minimum Residual (MMR) scheme for both simulated and real Advanced Infrared Sounder (AIRS) radiances. Results show that there is a high level of consistency between the results from simulated and real AIRS data. As expected, both cloud-detection schemes perform well in finding the cloud-contaminated channels based on the channels' peak levels. The clouddetection results from MW03 are sensitive to the prescribed brightness temperature innovation threshold and brightness temperature gradient threshold. When increasing the brightness temperature innovation threshold for MW03 to roughly eight times the default threshold, the two cloud-detection schemes produce consistent data rejection distributions overall for high channels. MMR gener...

Point response function of the Clouds and Earth Radiant Energy System scanning radiometer

An overview of work related to the point response function (PRF) of the Clouds and Earth Radiant Energy System (CERES) scanning radiometer is presented. The aspects of the CERES design that affect the PRF are described, and then the design of the PRF is explained. The PRF was designed by shaping the field of view so as to minimize the blur plus alias errors of the radiance field reconstructed from the CERES measurements. The design is conducted in the Fourier domain. The PRF can then be computed by transforming the resulting transfer function to the physical domain. Alternatively, the PRF can be computed in the physical plane. The PRF of each model of the CERES instrument has been tested in the Radiation Calibration Facility by use of a PRF source and compared well with prediction. CERES instruments are aboard the Terra, Aqua, and Suomi-NPP spacecraft. In orbit, lunar observations are used to validate the PRF. These results showed nominal performance except for the longwave window channel of flight model 2, for which a region of anomalously high sensitivity was found.

Comparisons of Two Cloud-Detection Schemes for Infrared Radiance Observations

The cloud-detection procedure developed by McNally and Watts(MW03) was added to the Weather Research and Forecasting Data Assimilation System. To provide some guidelines for setting up cloud-detection schemes, this study compares the MW03 scheme to the Multivariate and Minimum Residual(MMR) scheme for both simulated and real Advanced Infrared Sounder(AIRS) radiances. Results show that there is a high level of consistency between the results from simulated and real AIRS data. As expected, both cloud-detection schemes perform well in finding the cloud-contaminated channels based on the channels' peak levels. The clouddetection results from MW03 are sensitive to the prescribed brightness temperature innovation threshold and brightness temperature gradient threshold. When increasing the brightness temperature innovation threshold for MW03 to roughly eight times the default threshold, the two cloud-detection schemes produce consistent data rejection distributions overall for high channels. MMR generally retains more data for long-wave channels. For both cloud-detection schemes, there is a high level of consistency between the cloud-free pixels and the visible/near-IR(Vis/NIR) cloud mask.

Intersatellite Differences of HIRS Longwave Channels Between NOAA-14 and NOAA-15 and Between NOAA-17 and METOP-A

Intersatellite differences of the High-Resolution Infrared Radiation Sounder (HIRS) longwave channels (channels 1-12) between National Oceanic and Atmospheric Administration 14 (NOAA-14) and NOAA-15 and between NOAA-17 and METOP-A are examined. Two sets of colocated data are incorporated in the examination. One data set is obtained during periods when equator crossing times of two satellites are very close to each other, and the data set is referred to as global simultaneous nadir overpass observation (SNO). The other data set is based on multiyear polar SNOs. The examination shows that intersatellite differences (ISDs) of temperature-sounding channels from lower stratosphere to lower troposphere, i.e., channels 3-7, are correlated with their corresponding lapse rate factors. Many of the channels also vary with respect to channel brightness temperatures; however, for the upper tropospheric temperature channel (channel 4), the patterns of ISDs from low latitudes and high latitudes are very different due to the fact that the latitudinal variation of brightness temperature does not necessarily follow the latitudinal variation of the temperature lapse rate. The differences between observations in low latitudes and high latitudes form “fork” patterns in scatter plots of ISDs with respect to brightness temperatures. A comparison of ISDs derived from short-term global SNOs and those derived from multiyear polar SNOs reveals the advantage and the limitation of the two data sets. The multiyear polar SNO generally provides larger observation ranges of brightness temperatures in channels 1-4. The global SNO extends the brightness temperature observations to the warm sides for channels 5-12 and captures the occurrences of larger ISDs for most longwave channels.