A new set of reflectance calibration coefficients has been derived for channel 1 (0.63 m) and channel 2 (0.86 m) of the Advanced Very High Resolution Radiometer (AVHRR) flown on the National Oceanic and Atmospheric Administration (NOAA) and European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar orbiting meteorological satellites. This paper uses several approaches that are radiometrically tied to the observations from National Aeronautics and Space Administration's (NASA's) Moderate Resolution Imaging Spectroradiometer (MODIS) imager to make the first consistent set of AVHRR reflectance calibration coefficients for every AVHRR that has ever flown. Our results indicate that the calibration coefficients presented here provide an accuracy of approximately 2% for channel 1 and 3% for channel 2 relative to that from the MODIS sensor.

The Advanced Very High Resolution Radiometer (AVHRR) visible and near-infrared channels must be calibrated after launch to maintain the accuracy of data derived from these channels for quantitative utilizations. The postlaunch calibration of these channels can only be carried out vicariously. The National Oceanic and Atmospheric Administration (NOAA) - National Environmental Satellite, Data, an Information Service (NESDIS) has been using the Libyan Desert as reference for operational calibration of AVHRR visible and near-infrared channels since 1995. A previous algorithm was successful correcting for the long-term instrument degradation in recalibration but had difficulty updating instrument calibration in near-real-time operation. This paper describes the operational calibration algorithm implemented since 2003, which overcomes the existing shortcomings by reducing target contamination and accounting for the effects of target bidirectional reflectance distribution function. Application of the algorithm shortens the latency of postlaunch calibration from 3 to 4 years for NOAA-14 and NOAA-16 to less than 2 years for NOAA-17 and to a few months for later satellites. Compared with the previous algorithm, the current algorithm enhances the calibration precision from 1.7% to 0.9% for channel 1.

The absolute accuracy of the thermal infrared (IR) radiances and brightness temperatures derived from the Advanced Very High Resolution Radiometer (AVHRR) is still unknown, with major sources of error not yet fully understood. This is despite the fact that data from the AVHRR IR channels are widely used in deriving important atmospheric and surface parameters as well as in weather prediction, climate modeling, and other environmental studies. Central to the problem are possible errors introduced by the calibration test procedures and methodologies that can range up to approximately 0.5 K, much larger than the instrument electronic and detector noise characteristics. Further, there are known issues with the current calibration including a large mismatch of up to 0.7 K between the measured physical temperature of the internal calibration target (ICT) and its radiometric temperature estimated by using the AVHRR-observed counts. In an effort to improve this, a new approach to the calibration has been adopted that is dependent on physical instrument parameters. It is shown that this new calibration method can explain the ICT temperature mismatch as a combination of an incorrect assumption that the AVHRR was kept at a constant temperature during testing combined with the effect of scattered radiation from the test chamber and other sources. This new calibration also reduces the total biases and errors that exist when using the current operational calibration on the prelaunch data. Comparing the external calibration target temperatures to the temperatures derived using the AVHRR measurements, this new calibration can reduce an up to 0.7-K bias seen currently to an essentially zero bias with a scatter of less than 0.05 K in the SST regime. This marks an improvement of up to an order of magnitude in accuracy over the current operational calibration.

The long-term trend of aerosol optical thickness (AOT) over the global oceans has been studied by using a nearly 25-year aerosol record from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere extended (PATMOS-x) data set. Both global and regional analyses have been performed to derive the AOT tendencies for monthly, seasonal, and annual mean AOT values at AVHRR 0.63 mu m channel (or Channel-1). A linear decadal change of -0.01 is obtained for globally and monthly averaged aerosol optical thickness, tau(1), of AVHRR Channel-1. This negative tendency is even more evident for globally and annually averaged tau(1) and the magnitude can be up to -0.03/decade. Seasonal patterns in the AOT regional long-term trend are evident. In general, negative tendencies are observed for seasonally averaged tau(1) in regions influenced by emissions from industrialized countries and the magnitude can be up to -0.10/decade. Positive tendencies are observed in regions influenced by emissions from fast developing countries and the magnitude can be up to +0.04/decade. For regions heavily influenced by Saharan desert particles, a negative trend with a maximum magnitude of -0.03/decade is detected. However, over regions influenced by smoke from biomass burning, positive tendencies with a maximum magnitude of +0.04/decade are observed. Sensitivity analyses have also been performed to study the effects of radiance calibration, aerosol retrieval algorithm, and spatial resolution of input retrieval radiances on the global aerosol long-term tendencies.

The long-term trend of aerosol optical thickness (AOT) over the global oceans has been studied by using a nearly 25-year aerosol record from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere (PATMOS) climate data. Both global and regional analyses have been performed to derive the AOT tendencies for monthly, seasonal, and annual mean AOT values at AVHRR 0.63mum channel (or Channel-1). A linear decadal change of -0.01 is obtained for globally and monthly averaged aerosol optical thicknesses of AVHRR Channel-1. Sensitivity analyses have also been performed to study the effects of radiance calibration and aerosol retrieval algorithm on the global aerosol long-term tendencies.

Warming climates have been widely recognized to advance spring vegetation phenology. However, the delayed responses of vegetation phenology to rising temperature and their mechanisms are poorly understood. Using satellite and climate data from 1982 to 2005, we reveal a latitude transition zone of greenup onset in vegetation communities that has diversely responded to warming temperature in North America. From 40°N northwards, a winter chilling requirement for vegetation dormancy release is far exceeded and the decrease in chilling days by warming winter temperature has little impact on thermal‐time requirements for greenup onset. Thus, warming spring temperature has constantly advanced greenup onset by 0.32 days/year. However, from 40°N southward, the shortened winter chilling days are insufficient for fulfilling vegetation chilling requirement, so that the thermal‐time requirement for greenup onset during spring increases gradually. Consequently, vegetation greenup onset changes progressively from an early trend (north region) to a later trend (south region) along the latitude transition zone from 40–31°N, where the switch occurs around 35°N. The greenup onset is delayed by 0.15 days/year below 31°N.

The measurements from microwave sounding unit (MSU) on board different NOAA polar‐orbiting satellites have been extensively used for detecting atmospheric temperature trend during the last several decades. However, temperature trends derived from these measurements are under significant debate, mostly caused by calibration errors. This study recalibrates the MSU channel 2 observations at level 0 using the postlaunch simultaneous nadir overpass (SNO) matchups and then provides a well‐merged new MSU 1b data set for climate studies. The calibration algorithm consists of a dominant linear response of the MSU raw counts to the Earth‐view radiance plus a smaller quadratic term. Uncertainties are represented by a constant offset and errors in the coefficient for the nonlinear quadratic term. A SNO matchup data set for nadir pixels with criteria of simultaneity of less than 100 s and within a ground distance of 111 km is generated for all overlaps of NOAA satellites. The simultaneous nature of these matchups eliminates the impact of orbital drifts on the calibration. A radiance error model for the SNO pairs is developed and then used to determine the offsets and nonlinear coefficients through regressions of the SNO matchups. It is found that the SNO matchups can accurately determine the differences of the offsets as well as the nonlinear coefficients between satellite pairs, thus providing a strong constraint to link calibration coefficients of different satellites together. However, SNO matchups alone cannot determine the absolute values of the coefficients because there is a high degree of colinearity between satellite SNO observations. Absolute values of calibration coefficients are obtained through sensitivity experiments, in which the percentage of variance in the brightness temperature difference time series that can be explained by the warm target temperatures of overlapping satellites is a function of the calibration coefficient. By minimizing these percentages of variance for overlapping observations, a new set of calibration coefficients is obtained from the SNO regressions. These new coefficients are significantly different from the prelaunch calibration values, but they result in bias‐free SNO matchups and near‐zero contaminations by the warm target temperatures in terms of the calibrated brightness temperature. Applying the new calibration coefficients to the Level 0 MSU observations, a well‐merged MSU pentad data set is generated for climate trend studies. To avoid errors caused by small SNO samplings between NOAA 10 and 9, observations only from and after NOAA 10 are used. In addition, only ocean averages are investigated so that diurnal cycle effect can be ignored. The global ocean‐averaged intersatellite biases for the pentad data set are between 0.05 and 0.1 K, which is an order of magnitude smaller than that obtained when using the unadjusted calibration algorithm. The ocean‐only anomaly trend for the combined MSU channel 2 brightness temperature is found to be 0.198 K decade−1 during 1987–2003.

Lone-term satellite observations, such as Advanced Very High Resolution Radiometer (AVHRR), provide an irreplaceable means in monitoring Earth system through a series of satellites. However, to be able to detect the signal related to climate change, one of the critical requirements is the consistency and stability of calibration among the satellites. Applying Simultaneous Nadir Overpass (SNOs) method (Cao et al., 2002)., we fully accessed instrument-related consistency of AVHRR measurements covering all channels (from visible to IR) and time period from 1978 to 2003. It is seen that the inter-satellite biases in visible channels (channel 1 and 2) show larger inconsistency among satellites especially between NOAA-14 and NOAA-12. The inconsistency is shown as both the large bias and trend in the biases, mostly due to the lack of onboard calibration. Comparatively, the biases in IR channels, i.e., channel 4 and 5 are generally smaller, there are within ± 1 k. However, the difference in the magnitude of the biases among satellites and the dependence of biases on the scene temperature may affect the quality of long term trend derived from such dataset. Analyses of bias root causes indicate that the effect from the difference in Spectral Response Function may not be large enough to account for the observed biases.

Intersatellite radiance comparisons for the 19 infrared channels of the High-Resolution Infrared Radiation Sounders (HIRS) on board NOAA-15, -16, and -17 are performed with simultaneous nadir observations at the orbital intersections of the satellites in the polar regions, where each pair of the HIRS views the same earth target within a few seconds. Analysis of such datasets from 2000 to 2003 reveals unambiguous intersatellite radiance differences as well as calibration anomalies.The results show that in general, the intersatellite relative biases are less than 0.5 K for most HIRS channels. The large biases in different channels differ in both magnitude and sign, and are likely to be caused by the differences and measurement uncertainties in the HIRS spectral response functions. The seasonal bias variation in the stratosphere channels is found to be highly correlated with the lapse rate factor approximated by the channel radiance differences. The method presented in this study works particularly well for channels sensing the stratosphere because of the relative spatial uniformity and stability of the stratosphere, for which the intercalibration accuracy and precision are mostly limited by the instrument noise. This method is simple and robust, and the results are highly repeatable and unambiguous. Intersatellite radiance calibration with this method is very useful for the on-orbit verification and monitoring of instrument performance, and is potentially useful for constructing long-term time series for climate studies.

The solar reflectance bands (SRB) of the Advanced Very High Resolution Radiometers (AVHRR) flown onboard NOAA satellites are often referred to as non-calibrated in-flight. In contrast, the Earth emission bands (EEB) are calibrated using two reference points, deep space and the internal calibration target. In the SRBs, measurements of space count (SC) are also available, however, historically they are not used to specify the calibration offset ("zero count", ZC), which does not even appear in the calibration equation. A regression calibration formulation is used instead, equivalent to setting the ZC to a constant, whose value is specified from pre-launch measurements. Our analyses supported by a review of the instrument design and a wealth of historical SC information show that the SC varies in-flight and it differs from its pre-launch value. We therefore suggest that (1) the AVHRR calibration equation in the SRBs be re-formulated to explicitly use the ZC, consistently with the EEBs, and (2) the value of ZC be specified from the onboard measurements of SC. This study emphasizes the importance of clear discrimination between the SC (which is a measured quantity and therefore takes on a range of values, characterized by the empirical probability density function, PDF), from the ZC (which is a parameter in the calibration equation, i.e. a number whose value needs to be estimated from the measured SC as a mean, median or other statistic of the measured PDF). The ZC-formulation of the calibration equation is physically solid, and it minimizes human-induced calibration errors resulting from the use of a regression formulation with an un-constrained intercept. Specifying the calibration offset improves radiances, most notably at the low end of radiometric scale, and subsequently provides for more accurate vicarious determinations of the calibration slope (inverse gain). These calibration improvements are important for the products derived from the AVHRR low-radiances, such as aerosol over ocean, and particularly critical when generating their long-term climate data records.

The solar reflectance bands (SRB; centered at lambda(1) = 0.63, lambda(2) = 0.83, and lambda(3A) = 1.61 mum) of the Advanced Very High Resolution Radiometers (AVHRR) flown on board NOAA satellites are often referred to as noncalibrated in-flight. In contrast, the Earth emission bands (EEBs; centered at lambda(3B) = 3.7, lambda(4) = 11, and lambda(5) = 12 mum) are calibrated using two reference points: deep space and the internal calibration targets. In the SRBs, measurements of space count (SC) are also available;, however, historically they are not used to specify the calibration offset [zero count (ZC)], which does not even appear in the calibration equation. A regression calibration formulation is used instead, equivalent to setting the ZC to a constant, whose value is specified from prelaunch measurements.The analyses below, supported by a review of the instrument design and a wealth of historical SC information, show that the SC varies in-flight and differs from its prelaunch value. It is therefore suggested that 1) the AVHRR calibration equation in the SRBs be reformulated to explicitly use the ZC, consistently with the EEBs; and 2) the value of ZC be specified from the onboard measurements of SC. The ZC formulation of the calibration equation is physically solid, and it minimizes human-induced calibration errors resulting from the use of a regression formulation with an unconstrained intercept. Specifying the calibration offset improves radiances, most notably at the low end of radiometric scale, and subsequently provides for more accurate vicarious determinations of the calibration slope (gain). These calibration improvements are important for the products derived from the AVHRR low radiances, such as aerosol over ocean, and are particularly critical when generating their long-term climate data records (CDRs).

The quality of satellite radiances is essential for direct radiance assimilation in numerical weather prediction, for retrievals of various geophysical parameters, and for climate monitoring and reanalysis. It is also a measure of the success of the engineering and science efforts of our operational satellite program. However, past effort in postlaunch calibration/validation was a piecemeal approach, focusing on onboard calibration of individual instruments, with much less attention paid to the quality of radiance data of earth observations. Many instrument artifacts could remain undiscovered in the earth observation data until major impacts are found by users. The lack of on-orbit calibration standard and methodology for radiance verification also aggravated the problem. We believe that in order to meet the challenge of the increasing demand for better satellite data quality, an integrated approach for calibration/validation should be used, which includes several core components. This integrated system will bring together all operational satellite radiometers and make the radiances highly traceable among a constellation of global satellites in both polar and geostationary orbits. In this paper we introduce our efforts and progress in developing this integrated system and plans for supporting the calibration/validation and long-term monitoring of POES, MetOP, and NPOESS radiometers.

The Microwave Sounding Units (MSU) aboard the NOAA series of polar orbiting satellites has been used by three groups to monitor the very small trend in the global tropospheric temperature over the 25‐year satellite record. To obtain a homogeneous data set, each group made different calibration corrections of the MSUs in the form of fixed biases, and in some cases temperature‐dependent adjustments, to each of the nine satellite instruments using data during the overlap periods. Up until now, however, the adjustments are empirically based. To improve the accuracy as well as our understanding of the error sources, this paper develops an alternate, physical approach for intercalibrating the MSU instruments. The paper develops a calibration model for the MSU instrument that includes the errors in the cold space and warm target measurements, as well as the nonlinear factor. Corrections for these calibration errors are estimated using a least squares minimization where the predictors are the differences between all 12 overlapping satellite measurements at low and high latitudes. After applying the calibration corrections, the zonally averaged differences between satellite instruments are no larger than 0.03 K, independent of latitude. It is also found that the tropospheric temperature trend derived from MSU measurements is nearly the same as the surface trend. Furthermore, it now appears that much of the earlier inconsistency between the satellite and surface measurements arises from errors in the MSU calibration correction procedure, which can artificially suppress the temperature trend.

The orbit drift of National Oceanic & Atmospheric Administration (NOAA)-14 towards the terminator has caused the deterioration of the radiometric calibration of the Advanced Very High Resolution Radiometer (AVHRR) 3.7 mum channel at night. This deterioration is a result of solar contamination of the radiometric calibration system when the sun strikes the instrument from the spacecraft horizon. The long-term trend and seasonal variation of the contamination are analysed in this study based on trending data from 1995 to 2000. The calibration bias is evaluated and its effect on the sea surface temperature retrievals is quantified. The solar contamination in late 2000 affected as much as 25% of an orbit of data, compared to an average of 7% in 1995. The NOAA/NESDIS operational calibration algorithm partially corrects for the bias but residual effects can still contribute bias on the order of 0.5 K in scene brightness temperature.

Time series of desert sites are used to derive a post-launch calibration of the visible (ch1—0.63 µm) and near-infrared (ch2—0.86 µm) channels on the NOAA-12 AVHRR. This work extends the techniques that have been applied to NOAA satellites in afternoon orbits to a satellite in a morning orbit. An analysis of the bidirectional reflectance distribution function effects apparent in the data was used to limit the time period used to analyse the calibration slope of ch1 and ch2. Three desert sites were used to compute the relative degradation rates of the calibration slope of ch1 and ch2. Measurements from NOAA-9 over the Libyan Desert and from aircraft flights over White Sands, New Mexico were used to produce an absolute calibration. The resulting absolute calibrations for ch1 and ch2 agree with previous results to within 2%. The degradation results indicated that the calibration slope decreases by 3.14% per year for ch1 and 3.19% per year for ch2.

A series of 10 advanced very high resolution radiometers (AVHRRs) flown on National Oceanic and Atmospheric Administration (NOAA)'s polar‐orbiting satellites for over 20 years has provided data suitable for many quantitative remote sensing applications. To be useful for geophysical research, each radiometer must be accurately calibrated, which poses problems in the AVHRR reflectance channels because they have no onboard calibration. Previous studies have shown that values of the reflectance channel calibrations, accurately measured during preflight, change abruptly immediately after launch and then change slowly during the satellite's lifetime. The presence of the dual‐gain reflectance channels on the current series of AVHRRs also complicates the application of previous calibration techniques. A technique is presented here for calibrating the AVHRR dual‐gain reflectance channels using Moderate Resolution Imaging Spectrometer (MODIS) data. This method employs selective criteria to reproduce a laboratory type calibration where instrument counts observed by AVHRR are matched to reflectances measured by MODIS on a pixel by pixel basis for coincident and co‐located scenes. Unlike AVHRR, MODIS employs onboard calibration of its reflectance channels. The goal here was to explore the utility of using MODIS to calibrate the new dual‐gain reflectance channels of the AVHRR. The AVHRRs in the NOAA‐KLM series of spacecraft employ a dual‐gain approach to increase the sensitivity to dark scenes. Traditional methods using radiometrically stable targets to calibrate the reflectance channels of AVHRR typically do not provide data for both gain settings. The data from two scenes that met the over‐pass criteria are analyzed. The regression of the MODIS reflectances versus the AVHRR counts for these scenes were able to produce calibration slopes and intercepts in both the low and high gain regions. The reflectance differences using the MODIS‐derived calibration compared to preflight calibration are well within the expected behavior of the AVHRR during its first year in orbit. Comparison with reference ch1 and ch2 reflectance values from NOAA 9 for a Libyan Desert Target were within 5% of those using the MODIS‐derived calibration. While the determination of the absolute accuracy this approach needs further study, it clearly offers the potential for calibration of the AVHRR dual‐gain reflectance channels.

Solar impingement on the advanced very high resolution radiometers (AVHRRs) near the terminator can contaminate the onboard radiometric calibration system and degrade AVHRR data. The solar contamination causes disagreement between the sensor‐measured radiometric output of the onboard blackbody versus its bulk temperature measured by the platinum resistance thermometers. Despite the sun shield installed on the latest AVHRR unit, solar contamination can still contribute errors of more than 0.5 K in the 3.7 μm channel and 0.25 K in the long‐wave infrared channels. The timescale and spectral characteristics of the contamination are analyzed to find the possible causes. In addition, stray light in Earth scenes is found whenever the radiometric calibration is contaminated. These effects occur as the spacecraft moves out of the shadow of the Earth at spacecraft sunrise. The intensity of the effects varies by orbit and season and is related to the solar zenith and azimuth angles at the spacecraft.