52 research outputs found

    Enhancements to the Open Access Spectral Band Adjustment Factor Online Calculation Tool for Visible Channels

    Get PDF
    With close to 40 years of satellite observations, from which, cloud, land-use, and aerosol parameters can be measured, inter-consistent calibrations are needed to normalize retrievals across satellite records. Various visible-sensor inter-calibration techniques have been developed that utilize radiometrically stable Earth targets, e.g., deep convective clouds and desert/polar ice pseudo-invariant calibration sites. Other equally effective, direct techniques for intercalibration between satellite imagers are simultaneous nadir overpass comparisons and ray-matched radiance pairs. Combining independent calibration results from such varied techniques yields robust calibration coefficients, and is a form of self-validation. One potential source of significant error when cross-calibrating satellite sensors, however, are the often small but substantial spectral discrepancies between comparable bands, which must be accounted for. As such, visible calibration methods rely on a Spectral Band Adjustment Factor (SBAF) to account for the spectral-response function- induced radiance differences between analogous imagers. The SBAF is unique to each calibration method as it is a function of the Earth-reflected spectra. In recent years, NASA Langley pioneered the use of SCIAMACHY-, GOME-2-, and Hyperion-retrieved Earth spectra to compute SBAFs. By carefully selecting hyperspectral footprints that best represent the conditions inherent to an inter-calibration technique, the uncertainty in the SBAF is greatly reduced. NASA Langley initially provided the Global Space-based Inter-calibration System processing and research centers with online SBAF tools, with which users select conditions to best match their calibration criteria. This article highlights expanded SBAF tool capabilities for visible wavelengths, with emphasis on the use of the spectral range filtering for the purpose of separating scene conditions for the channel that the SBAF is needed based on the reflectance values of other bands. In other words, spectral filtering will enable better scene-type selection for bands where scene determination is difficult without information from other channels, which should prove valuable to users in the calibration community

    The Characterization of Deep Convective Cloud Albedo as a Calibration Target Using MODIS Reflectances

    Get PDF
    There are over 25 years of historical satellite data available to climate analysis. The historical satellite data needs to be well calibrated, especially in the visible, where there is no onboard calibration on operational satellites. The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard black-bodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined. Although DCC clouds are nearly Lambertion, the angular distribution of reflectances will be sampled and compared with theoretical models. Both Aqua and Terra MODIS DCC angular models will be compared for consistency. Normalizing angular geostationary DCC reflectances, which were calibrated against MODIS, with SCIAMACHY spectral reflectances and comparing them to MODIS DCC reflectances will inspect the usage of DCC albedos as an absolute calibration target

    Climate Quality Broadband and Narrowband Solar Reflected Radiance Calibration Between Sensors in Orbit

    Get PDF
    vAs the potential impacts of global climate change become more clear [1], the need to determine the accuracy of climate prediction over decade-to-century time scales has become an urgent and critical challenge. The most critical tests of climate model predictions will occur using observations of decadal changes in climate forcing, response, and feedback variables. Many of these key climate variables are observed by remotely sensing the global distribution of reflected solar spectral and broadband radiance. These "reflected solar" variables include aerosols, clouds, radiative fluxes, snow, ice, vegetation, ocean color, and land cover. Achieving sufficient satellite instrument accuracy, stability, and overlap to rigorously observe decadal change signals has proven very difficult in most cases and has not yet been achieved in others [2]. One of the earliest efforts to make climate quality observations was for Earth Radiation Budget: Nimbus 6/7 in the late 1970s, ERBE in the 1980s/90s, and CERES in 2000s are examples of the most complete global records. The recent CERES data products have carried out the most extensive intercomparisons because if the need to merge data from up to 11 instruments (CERES, MODIS, geostationary imagers) on 7 spacecraft (Terra, Aqua, and 5 geostationary) for any given month. In order to achieve climate calibration for cloud feedbacks, the radiative effect of clear-sky, all-sky, and cloud radiative effect must all be made with very high stability and accuracy. For shortwave solar reflected flux, even the 1% CERES broadband absolute accuracy (1-sigma confidence bound) is not sufficient to allow gaps in the radiation record for decadal climate change. Typical absolute accuracy for the best narrowband sensors like SeaWiFS, MISR, and MODIS range from 2 to 4% (1-sigma). IPCC greenhouse gas radiative forcing is approx. 0.6 W/sq m per decade or 0.6% of the global mean shortwave reflected flux, so that a 50% cloud feedback would change the global reflected flux by approx. 0.3 W/sq m or 0.3% per decade in broadband SW calibration change. Recent results comparing CERES reflected flux changes with MODIS, MISR, and SeaWiFS narrowband changes concluded that only SeaWiFS and CERES were approaching sufficient stability in calibration for decadal climate change [3]. Results using deep convective clouds in the optically thick limit as a stability target may prove very effective for improving past data sets like ISCCP. Results for intercalibration of geostationary imagers to CERES using an entire month of regional nearly coincident data demonstrates new approaches to constraining the calibration of current geostationary imagers. The new Decadal Survey Mission CLARREO is examining future approaches to a "NIST-in-Orbit" approach of very high absolute accuracy reference radiometers that cover the full solar and infrared spectrum at high spectral resolution but at low spatial resolution. Sampling studies have shown that a precessing CLARREO mission could calibrate other geo and leo reflected solar radiation and thermal infrared sensors

    The Calibration of AVHRR Visible Dual Gain using Meteosat-8 for NOAA-16 to 18

    Get PDF
    The NOAA AVHRR program has given the remote sensing community over 25 years of imager radiances to retrieve global cloud, vegetation, and aerosol properties. This dataset can be used for long-term climate research, if the AVHRR instrument is well calibrated. Unfortunately, the AVHRR instrument does not have onboard visible calibration and does degrade over time. Vicarious post-launch calibration is necessary to obtain cloud properties that are not biased over time. The recent AVHRR-3 instrument has a dual gain in the visible channels in order to achieve greater radiance resolution in the clear-sky. This has made vicarious calibration of the AVHRR-3 more difficult to unravel. Reference satellite radiances from well-calibrated instruments, usually equipped with solar diffusers, such as MODIS, have been used to successfully vicariously calibrate other visible instruments. Transfer of calibration from one satellite to another using co-angled, collocated, coincident radiances has been well validated. Terra or Aqua MODIS and AVHRR comparisons can only be performed over the poles during summer. However, geostationary satellites offer a transfer medium that captures both parts of the dual gain. This AVHRR-3 calibration strategy uses, calibrated with MODIS, Meteosat-8 radiances simultaneously to determine the dual gains using 50km regions. The dual gain coefficients will be compared with the nominal coefficients. Results will be shown for all visible channels for NOAA-17

    Assessment of the Visible Channel Calibrations of the TRMM VIRS and MODIS on Aqua and Terra

    Get PDF
    Several recent research satellites carry self-calibrating multispectral imagers that can be used for calibrating operational imagers lacking complete self-calibrating capabilities. In particular, the visible (VIS, 0.65 m) channels on operational meteorological satellites are generally calibrated before launch, but require vicarious calibration techniques to monitor the gains and offsets once they are in orbit. To ensure that the self-calibrating instruments are performing as expected, this paper examines the consistencies between the VIS channel (channel 1) reflectances of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites and the Version 5a and 6 reflectances of the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission using a variety of techniques. These include comparisons of Terra and Aqua VIS radiances with coincident broadband shortwave radiances from the well-calibrated Clouds and the Earth s Radiant Energy System (CERES), time series of deep convective cloud (DCC) albedos, and ray-matching intercalibrations between each of the three satellites. Time series of matched Terra and VIRS data, Aqua and VIRS data, and DCC reflected fluxes reveal that an older version (Version 5a, ending in early 2004) of the VIRS calibration produced a highly stable record, while the latest version (Version 6) appears to overestimate the sensor gain change by approx.1%/y as the result of a manually induced gain adjustment. Comparisons with the CERES shortwave radiances unearthed a sudden change in the Terra MODIS calibration that caused a 1.17% decrease in the gain on 19 November 2003 that can be easily reversed. After correction for these manual adjustments, the trends in the VIRS and Terra channels are no greater than 0.1%/y. Although the results were more ambiguous, no statistically significant trends were found in the Aqua MODIS channel-1 gain. The Aqua radiances are 1% greater, on average, than their Terra counterparts, and after normalization are 4.6% greater than VIRS radiances, in agreement with theoretical calculations. The discrepancy between the two MODIS instruments should be taken into account to ensure consistency between parameters derived from them. With the adjustments, any of the three instruments can serve as references for calibrating other satellites. Monitoring of the calibrations continues in near-real-time and the results are available via the world wide web

    Variability in Global Top-of-Atmosphere Shortwave Radiation Between 2000 and 2005

    Get PDF
    Measurements from various instruments and analysis techniques are used to directly compare changes in Earth-atmosphere shortwave (SW) top-of-atmosphere (TOA) radiation between 2000 and 2005. Included in the comparison are estimates of TOA reflectance variability from published ground-based Earthshine observations and from new satellite-based CERES, MODIS and ISCCP results. The ground-based Earthshine data show an order-of-magnitude more variability in annual mean SW TOA flux than either CERES or ISCCP, while ISCCP and CERES SW TOA flux variability is consistent to 40%. Most of the variability in CERES TOA flux is shown to be dominated by variations global cloud fraction, as observed using coincident CERES and MODIS data. Idealized Earthshine simulations of TOA SW radiation variability for a lunar-based observer show far less variability than the ground-based Earthshine observations, but are still a factor of 4-5 times more variable than global CERES SW TOA flux results. Furthermore, while CERES global albedos exhibit a well-defined seasonal cycle each year, the seasonal cycle in the lunar Earthshine reflectance simulations is highly variable and out-of-phase from one year to the next. Radiative transfer model (RTM) approaches that use imager cloud and aerosol retrievals reproduce most of the change in SW TOA radiation observed in broadband CERES data. However, assumptions used to represent the spectral properties of the atmosphere, clouds, aerosols and surface in the RTM calculations can introduce significant uncertainties in annual mean changes in regional and global SW TOA flux

    Calibrating Historical IR Sensors Using GEO, and AVHRR Infrared Tropical Mean Calibration Models

    Get PDF
    Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth's radiant energy. Therefore, by making historical satellite calibrations consistent with those of today's imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 biasdifference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby establish a climate-quality IR data record

    Validation of Improved Broadband Shortwave and Longwave Fluxes Derived From GOES

    Get PDF
    Broadband (BB) shortwave (SW) and longwave (LW) fluxes at TOA (Top of Atmosphere) are crucial parameters in the study of climate and can be monitored over large portions of the Earth's surface using satellites. The VISST (Visible Infrared Solar Split-Window Technique) satellite retrieval algorithm facilitates derivation of these parameters from the Geostationery Operational Environmental Satellites (GOES). However, only narrowband (NB) fluxes are available from GOES, so this derivation requires use of narrowband-to-broadband (NB-BB) conversion coefficients. The accuracy of these coefficients affects the validity of the derived broadband (BB) fluxes. Most recently, NB-BB fits were re-derived using the NB fluxes from VISST/GOES data with BB fluxes observed by the CERES (Clouds and the Earth's Radiant Energy Budget) instrument aboard Terra, a sun-synchronous polar-orbiting satellite that crosses the equator at 10:30 LT. Subsequent comparison with ARM's (Atmospheric Radiation Measurement) BBHRP (Broadband Heating Rate Profile) BB fluxes revealed that while the derived broadband fluxes agreed well with CERES near the Terra overpass times, the accuracy of both LW and SW fluxes decreased farther away from the overpass times. Terra's orbit hampers the ability of the NB-BB fits to capture diurnal variability. To account for this in the LW, seasonal NB-BB fits are derived separately for day and night. Information from hourly SW BB fluxes from the Meteosat-8 Geostationary Earth Radiation Budget (GERB) is employed to include samples over the complete solar zenith angle (SZA) range sampled by Terra. The BB fluxes derived from these improved NB-BB fits are compared to BB fluxes computed with a radiative transfer model

    Results from the Deep-Convective Clouds (DCC) Based Response Versus Scan-Angle (RVS) Characterization for the MODIS Reflective Solar Bands

    Get PDF
    The Terra and Aqua MODIS scan mirror reflectance is a function of the angle of incidence (AOI) and was characterized prior to launch by the instrument vendor. The relative change of the prelaunch response versus scan-angle (RVS) is tracked and linearly scaled on-orbit using observations at two AOIs of 11.2deg and 50.2deg corresponding to the moon view and solar diffuser, respectively. As the missions continue to operate well beyond their design life of 6 years, the assumption of linear scaling between the two AOIs is known to be inadequate in accurately characterizing the RVS, particularly at short wavelengths. Consequently, an enhanced approach of supplementing the on-board measurements with response trends from desert pseudo-invariant calibration sites (PICS) was formulated in MODIS Collection 6 (C6). An underlying assumption for the continued effectiveness of this approach is the long-term (multi-year) and short-term (month-to-month) stability of the PICS. Previous work has shown that the deep convective clouds (DCC) can also be used to monitor the on-orbit RVS performance with less trend uncertainties than desert sites. In this paper, the raw sensor response to the DCC is used to characterize the on-orbit RVS on a band and mirror side basis. These DCC-based RVS results are compared with the C6 PICS-based RVS, showing an agreement within 2% observed in most cases. The pros and cons of using a DCC-based RVS approach are also discussed in this paper. Although this reaffirms the efficacy of the C6 PICS-based RVS, the DCC-based RVS approach presents itself as an effective alternative for future considerations. Potential applications of this approach to other instruments such as SNPP and JPSS VIIRS are also discussed

    Surface irradiances consistent with CERES-derived top-of-atmosphere shortwave and longwave irradiances

    Get PDF
    Author Posting. © American Meteorological Society, 2013. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 26 (2013): 2719–2740, doi:10.1175/JCLI-D-12-00436.1.The estimate of surface irradiance on a global scale is possible through radiative transfer calculations using satellite-retrieved surface, cloud, and aerosol properties as input. Computed top-of-atmosphere (TOA) irradiances, however, do not necessarily agree with observation-based values, for example, from the Clouds and the Earth’s Radiant Energy System (CERES). This paper presents a method to determine surface irradiances using observational constraints of TOA irradiance from CERES. A Lagrange multiplier procedure is used to objectively adjust inputs based on their uncertainties such that the computed TOA irradiance is consistent with CERES-derived irradiance to within the uncertainty. These input adjustments are then used to determine surface irradiance adjustments. Observations by the Atmospheric Infrared Sounder (AIRS), Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) that are a part of the NASA A-Train constellation provide the uncertainty estimates. A comparison with surface observations from a number of sites shows that the bias [root-mean-square (RMS) difference] between computed and observed monthly mean irradiances calculated with 10 years of data is 4.7 (13.3) W m−2 for downward shortwave and −2.5 (7.1) W m−2 for downward longwave irradiances over ocean and −1.7 (7.8) W m−2 for downward shortwave and −1.0 (7.6) W m−2 for downward longwave irradiances over land. The bias and RMS error for the downward longwave and shortwave irradiances over ocean are decreased from those without constraint. Similarly, the bias and RMS error for downward longwave over land improves, although the constraint does not improve downward shortwave over land. This study demonstrates how synergetic use of multiple instruments (CERES, MODIS, CALIPSO, CloudSat, AIRS, and geostationary satellites) improves the accuracy of surface irradiance computations.The work was supported by theNASACERES and, in part, Energy Water Cycle Study (NEWS) projects.2013-11-0
    • …
    corecore