30 research outputs found

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

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    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

    Workshop on Strategies for Calibration and Validation of Global Change Measurements

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    The Committee on Environment and Natural Resources (CENR) Task Force on Observations and Data Management hosted a Global Change Calibration/Validation Workshop on May 10-12, 1995, in Arlington, Virginia. This Workshop was convened by Robert Schiffer of NASA Headquarters in Washington, D.C., for the CENR Secretariat with a view toward assessing and documenting lessons learned in the calibration and validation of large-scale, long-term data sets in land, ocean, and atmospheric research programs. The National Aeronautics and Space Administration (NASA)/Goddard Space Flight Center (GSFC) hosted the meeting on behalf of the Committee on Earth Observation Satellites (CEOS)/Working Group on Calibration/walidation, the Global Change Observing System (GCOS), and the U. S. CENR. A meeting of experts from the international scientific community was brought together to develop recommendations for calibration and validation of global change data sets taken from instrument series and across generations of instruments and technologies. Forty-nine scientists from nine countries participated. The U. S., Canada, United Kingdom, France, Germany, Japan, Switzerland, Russia, and Kenya were represented

    Overview of Intercalibration of Satellite Instruments

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    Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d’unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stabilitymonitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration

    Overview of Intercalibration of Satellite Instruments

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    Intercalibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be interoperable, the instruments must be cross-calibrated. To meet the stringent needs of such applications, instruments must provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d’unités traceable calibration and validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stabilitymonitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Intercalibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Intercalibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated intercalibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of postlaunch radiometric calibration of remote sensing satellite instruments through intercalibration

    Ozone profile retrievals from the Ozone Monitoring Instrument

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    Ozone profiles from the surface to about 60 km are retrieved from Ozone Monitoring Instrument (OMI) ultraviolet radiances using the optimal estimation technique. OMI provides daily ozone profiles for the entire sunlit portion of the earth at a horizontal resolution of 13 km×48 km for the nadir position. The retrieved profiles have sufficient accuracy in the troposphere to see ozone perturbations caused by convection, biomass burning and anthropogenic pollution, and to track their spatiotemporal transport. However, to achieve such accuracy it has been necessary to calibrate OMI radiances carefully (using two days of Aura/Microwave Limb Sounder data taken in the tropics). The retrieved profiles contain ~6–7 degrees of freedom for signal, with 5–7 in the stratosphere and 0–1.5 in the troposphere. Vertical resolution varies from 7–11 km in the stratosphere to 10–14 km in the troposphere. Retrieval precisions range from 1% in the middle stratosphere to 10% in the lower stratosphere and troposphere. Solution errors (i.e., root sum square of precisions and smoothing errors) vary from 1–6% in the middle stratosphere to 6–35% in the troposphere, and are dominated by smoothing errors. Total, stratospheric, and tropospheric ozone columns can be retrieved with solution errors typically in the few Dobson unit range at solar zenith angles less than 80°

    Feasibility Study for an Aquatic Ecosystem Earth Observing System Version 1.2.

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    International audienceMany Earth observing sensors have been designed, built and launched with primary objectives of either terrestrial or ocean remote sensing applications. Often the data from these sensors are also used for freshwater, estuarine and coastal water quality observations, bathymetry and benthic mapping. However, such land and ocean specific sensors are not designed for these complex aquatic environments and consequently are not likely to perform as well as a dedicated sensor would. As a CEOS action, CSIRO and DLR have taken the lead on a feasibility assessment to determine the benefits and technological difficulties of designing an Earth observing satellite mission focused on the biogeochemistry of inland, estuarine, deltaic and near coastal waters as well as mapping macrophytes, macro-algae, sea grasses and coral reefs. These environments need higher spatial resolution than current and planned ocean colour sensors offer and need higher spectral resolution than current and planned land Earth observing sensors offer (with the exception of several R&D type imaging spectrometry satellite missions). The results indicate that a dedicated sensor of (non-oceanic) aquatic ecosystems could be a multispectral sensor with ~26 bands in the 380-780 nm wavelength range for retrieving the aquatic ecosystem variables as well as another 15 spectral bands between 360-380 nm and 780-1400 nm for removing atmospheric and air-water interface effects. These requirements are very close to defining an imaging spectrometer with spectral bands between 360 and 1000 nm (suitable for Si based detectors), possibly augmented by a SWIR imaging spectrometer. In that case the spectral bands would ideally have 5 nm spacing and Full Width Half Maximum (FWHM), although it may be necessary to go to 8 nm wide spectral bands (between 380 to 780nm where the fine spectral features occur -mainly due to photosynthetic or accessory pigments) to obtain enough signal to noise. The spatial resolution of such a global mapping mission would be between ~17 and ~33 m enabling imaging of the vast majority of water bodies (lakes, reservoirs, lagoons, estuaries etc.) larger than 0.2 ha and ~25% of river reaches globally (at ~17 m resolution) whilst maintaining sufficient radiometric resolution

    Quantitative cloud analysis using meteorological satellites = [Kwantitatieve analyse van wolken met meteorologische satellieten]

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    This thesis is about observations of clouds from satellite and ground based instruments. The aim is to reconstruct the three dimensional cloud distributions. This information is used both in climate research and operational meteorological applications. In climate research, cloud observations provide a reference to atmospheric models, which enables optimization of cloud parameterizations. For operational meteorologists clouds are symptoms of atmospheric conditions. Cloud observations therefore are helpful in understanding the current weather (nowcasting) and improve the estimate of how of the atmospheric conditions will evolve (forecasting).In order to obtain cloud field characteristics, analysis environments were developed for the interpretation of meteorological satellite measurements in terms of cloud properties. A large effort was put in the evaluation of the results with synoptic observations and measurements from two measurement campaigns. As a result this thesis comprises three major research topics: Meteosat analysis, AVHRR analysis and combined analysis of ground and satellite observations.Meteosat analysisA new cloud detection scheme was developed that includes the use of the surface temperature fields of a Numerical Weather Prediction (NWP) model as a threshold value to distinguish cloudy and cloud free areas. It is shown that also for cloud free conditions, the equivalent black body temperature as measured from satellite is different from the model surface temperature. An innovative part of the scheme is the quantification of this temperature difference, which is used to improve the skill of the cloud detection method. The improvement of the detection efficiency was quantified over land and ocean for 1997 on a 3 hourly basis in a semi-operational setting. As the method optimizes the use of the infrared information it is relatively insensitive to changes of insolation conditions with time of day, location, or season.AVHRR analysisThe NWP model surface temperatures are also used in the AVHRR analysis environment. For the interpretation of the 0.6ÎĽm channel reflectivities, extensive radiative transfer calculations were done with the Doubling-Adding KNMI (DAK) radiative transfer code. The results were put in Look-up tables (LUT). The LUTs are used to obtain the following cloud field properties: cloud cover fraction, cloud top temperature, optical thickness and liquid water path. In order to assess the quality, the retrieved properties were compared to measurements from two campaigns: the Tropospheric Budget Experiment, TEBEX, and the Clouds and Radiation intensive measurement campaigns, CLARA. The comparison shows that the retrieval algorithms yield results that agree with independent ground based measurements for the cases studied.Combined analysis of satellite and ground observationsCombined analysis of satellite and ground based observations from the TEBEX and CLARA data sets yields information on the quality of the satellite retrieval, but also on the merits of the ground based remote sensing instruments. The study shows that both observational sets have strong points, but a combination is preferred to obtain a good definition of the cloud field. In all comparisons the problem of collocation occurs. The ground based instruments measure continuous in time at one location, while satellites measure a spatial distribution at one moment in time. When comparing ground and satellite derived cloud products it is always questionable which part of the time series corresponds to which part of the spatial distribution. This correlation is studied by comparing variance spectra of time series and spatial distributions of liquid water path derived from microwave radiometer and AVHRR data respectively. It is shown that for two cases with different scaling properties the variance spectrum is similar for a part of the time-series and for a part of the AVHRR image.This thesis contributes to quantitative use of meteorological satellite data in meteorology and climate research. Furthermore, it advances combined analysis of space born and ground based remote sensing measurements of clouds for routine applications.</p

    Satellite Ocean Colour: Current Status and Future Perspective

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    Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and interannual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided
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