Detector Based Calibration of a Portable Imaging Spectrometer for CLARREO Pathfinder Mission

The Climate Absolute Refractivity and Reflectance Observatory (CLARREO) Pathfinder (CPF) mission is being developed to demonstrate SI-traceable retrievals of reflectance at unprecedented accuracies for global satellite observations. An Independent Calibration of the CPF sensor using the Goddard Laser for Absolute Measurement of Radiance (GLAMR) is planned to allow validation of CPF accuracies. GLAMR is a detector-based calibration system relies on a set of NIST-calibrated transfer radiometers to assess the spectral radiance from the GLAMR sphere source to better than 0.3 % (k=2). The current work describes the calibration of the Solar, Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS) that was originally developed as a calibration demonstration system for the CLARREO mission and is now being used to assess the independent calibration being developed for CPF. The methodology for the radiometric calibration of SOLARIS is presented as well as results from the GLAMR-based calibration of SOLARIS. The portability of SOLARIS makes it capable of collecting field measurements of earth scenes and direct solar and lunar irradiance similar to those expected during the on-orbit operation of the CPF sensor. Results of SOLARIS field measurements are presented. The use of SOLARIS in this effort also allows the testing protocols for GLAMR to be improved and the field measurements by SOLARIS build confidence in the error budget for GLAMR calibrations. Results are compared to accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval

Preliminary Error Budget for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements. The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those in the IPCC Report. A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO Project will implement a spaceborne earth observation mission designed to provide rigorous SI traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables, including: 1) Surface temperature and atmospheric temperature profile 2) Atmospheric water vapor profile 3) Far infrared water vapor greenhouse 4) Aerosol properties and anthropogenic aerosol direct radiative forcing 5) Total and spectral solar irradiance 6) Broadband reflected and emitted radiative fluxes 7) Cloud properties 8) Surface albedo There are two methods the CLARREO mission will rely on to achieve these critical decadal change benchmarks: direct and reference inter-calibration. A quantitative analysis of the strengths and weaknesses of the two methods has led to the recommended CLARREO mission approach. The project consists of two satellites launched into 90-degree, precessing orbits separated by 90 degrees. The instrument suite receiver on each spacecraft includes one emitted infrared spectrometer, two reflected solar spectrometers: dividing the spectrum from ultraviolet through near infrared, and one global navigation receiver for radio occultation. The measurements will be acquired for a period of three years minimum, with a five-year lifetime goal, enabling follow-on missions to extend the climate record over the decades needed to understand climate change. The current work concentrates on the reflected solar instrument giving an overview of its design and calibration approach. The calibration description includes the approach to achieving an SI-traceable system on orbit. The calibration overview is followed by a preliminary error budget based on techniques currently in place at the National Institute of Standards and Technology (NIST)

Importance of Calibration/Validation Traceability for Multi-Sensor Imaging Spectrometry Applications

Knowledge of calibration traceability is essential for ensuring the quality of data products relying on multiple sensors and especially true for imaging spectrometers. The current work discusses the expected impact that imaging spectrometers have in ensuring radiometric traceability for both multispectral and hyperspectral products. The Climate Absolute Radiance and Refractivity Observatory Pathfinder mission is used to show the role that high-accuracy imaging spectrometers can play in understanding test sites used for vicarious calibration of sensors. The associated Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer calibration demonstration system is used to illustrate recent advances in laboratory radiometric calibration approaches that will allow both the use of imaging spectrometers as calibration standards as well as to ensure the consistency of the multiple imaging spectrometers expected to be on orbit in the next decade

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earth's Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulationmethods to determinemission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit

Climate Change Observation Accuracy: Requirements and Economic Value

This presentation will summarize a new quantitative approach to determining the required accuracy for climate change observations. Using this metric, most current global satellite observations struggle to meet this accuracy level. CLARREO (Climate Absolute Radiance and Refractivity Observatory) is a new satellite mission designed to resolve this challenge is by achieving advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra. The CLARREO spectrometers can serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, etc). A CLARREO Pathfinder mission for flight on the International Space Station is included in the U.S. President"TM"s fiscal year 2016 budget, with launch in 2019 or 2020. Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A new study has been carried out to quantify the economic benefits of such an advance and concludes that the economic value is ~ $9 Trillion U.S. dollars. The new value includes the cost of carbon emissions reductions

Hyperspectral Observations for Atmospheric Remote Sensing: Instrumentation, Atmospheric Correction, and Spectral Unmixing

Hyperspectral instruments expand the spectral dimension of remote sensing measurements by collecting data in hundreds of contiguous wavelength channels. Spectrally resolved measurements can be used to derive science products for a diverse range of fields such as atmospheric science, geology, oceanography, ecology, climate monitoring, and agricultural science, to name a few. The spectral information collected by hyperspectral instruments enables more accurate retrievals of physical properties and detection of temporal changes. These advantages have led to an increasing number of active and planned hyperspectral instruments. This thesis describes methods for attributing hyperspectral radiation observations to physical sources.We developed, validated and characterized improvements to a hyperspectral instrument, the Solar Spectral Irradiance Monitor (SSIM), built at the University of Colorado Boulder’s Laboratory for Atmospheric and Space Physics. Contributions include the characterization of the optics’ angular response, testing of an optics stabilizing platform and the development and testing of a spectrometer thermal control system. This instrument was then deployed on an aircraft for a field study with the National Ecological Observatory Network (NEON). SSIM measurements of upwelling and downwelling irradiance were used in conjunction with NEON’s Imaging Spectrometer to enable atmospheric correction of imagery collected below cloud layers.We developed a numerical spectral unmixing algorithm, Informed Non-Negative Matrix Factorization (INMF), to separate contributions to hyperspectral imagery from distinct physical sources such as surface reflectance, atmospheric absorption, molecular scattering, and aerosol scattering. INMF was tailored for hyperspectral applications by introducing algorithmic constraints based on the physics of radiative transfer. INMF was tested using imagery collected by the Hyperspectral Imager for the Coastal Ocean (HICO). To validate the method INMF results were compared to model-based atmospheric correction results. We demonstrate possible applications of INMF by presenting the retrieval of two physical properties, aerosol attributed radiance and seafloor depth. The retrievals were evaluated by comparing INMF output to independent retrievals of aerosol properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ seafloor depth measurements from the U.S. Coastal Relief Model. In these comparisons INMF shows promise for retrieving both physical properties, and may be improved with physics-based constraints on the seafloor and aerosol source spectra

Quantifying the Variability of Hyperspectral Earth-reflected Radiation for Climate Studies

An accurate assessment of the Earth\u27s energy budget is essential to understanding how the Earth\u27s climate is changing and what processes and feedbacks are causing those changes. This is difficult to achieve, in part, because reflected solar irradiance, and therefore albedo, is a challenging quantity to measure from space with sufficient accuracy to monitor climate changes. An alternative to irradiance or albedo is directly measured spectral radiance, which provides information about the Earth\u27s atmospheric composition and surface properties that impact albedo variability. We have applied multivariate spectral decomposition techniques, such as principal component analysis (PCA), to quantify the variability of Earth-reflected hyperspectral solar radiance measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) aboard ENVISAT. Using multivariate analysis we explored the potential for directly measured hyperspectral Earth-reflected solar radiance to provide sufficient information to study changes in Earth\u27s climate based on the quantified variability of the data. The spectral signatures of the principal components (PCs) reveal that clouds, water vapor, vegetation, and sea ice are among the physical variables that explain the largest fraction of the SCIAMACHY data variance. The extraction of the spectral, spatial, and temporal variability in reflected shortwave hyperspectral radiance using multivariate analysis provides an alternate and complementary approach to applying inverse methods to space-based observations for climate studies. Observation System Simulation Experiments (OSSEs) have been used to simulate solar radiation measurements during the twenty-first century for the NASA Climate and Absolute Radiance and Refractivity Observatory (CLARREO) hyperspectral shortwave instrument being designed. Comparing the spectral shapes of the OSSE and SCIAMACHY PCs shows that the OSSE has a similar variance distribution to that observed by SCIAMACHY. We developed a quantitative comparison technique to quantify the degree to which the OSSE reproduces the variability within Earth\u27s climate system relative to observations. These comparisons showed that the OSSE spectral variability is close to that observed by SCIAMACHY. In addition, for the first time, the near-decadal temporal variability of observed reflectance measured between 2002 and 2010 was quantified; the variance drivers in the nearly decadal variability of SCIAMACHY measurements exhibited temporal signals of physical variables such as the location of the Intertropical Convergence Zone and the annual cycle of the cryosphere. The intersection also allowed for the direct comparison between the temporal variability of SCIAMACHY and OSSE reflectance at the beginning of the twenty-first century. Finally, we quantified the centennial variability of OSSE output during the twenty-first century, demonstrating that the reflectance spectra simulated from the A2 emission scenario model output exhibited secular trends over the simulation period. Applying the multivariate techniques presented in this thesis to evaluate the OSSE centennial variability enables the development of trend detection methods to further study the temporal variability of reflected solar radiation

Izaña Atmospheric Research Center. Activity Report 2019-2020

Editors: Emilio Cuevas, Celia Milford and Oksana Tarasova.[EN]The Izaña Atmospheric Research Center (IARC), which is part of the State Meteorological Agency of Spain (AEMET), is a site of excellence in atmospheric science. It manages four observatories in Tenerife including the high altitude Izaña Atmospheric Observatory. The Izaña Atmospheric Observatory was inaugurated in 1916 and since that date has carried out uninterrupted meteorological and climatological observations, contributing towards a unique 100-year record in 2016. This reports are a summary of the many activities at the Izaña Atmospheric Research Center to the broader community. The combination of operational activities, research and development in state-of-the-art measurement techniques, calibration and validation and international cooperation encompass the vision of WMO to provide world leadership in expertise and international cooperation in weather, climate, hydrology and related environmental issues.[ES]El Centro de Investigación Atmosférica de Izaña (CIAI), que forma parte de la Agencia Estatal de Meteorología de España (AEMET), representa un centro de excelencia en ciencias atmosféricas. Gestiona cuatro observatorios en Tenerife, incluido el Observatorio de Izaña de gran altitud, inaugurado en 1916 y que desde entonces ha realizado observaciones meteorológicas y climatológicas ininterrumpidas y se ha convertido en una estación centenaria de la OMM. Estos informes resumen las múltiples actividades llevadas a cabo por el Centro de Investigación Atmosférica de Izaña. El liderazgo del Centro en materia de investigación y desarrollo con respecto a las técnicas de medición, calibración y validación de última generación, así como la cooperación internacional, le han otorgado una reputación sobresaliente en lo que se refiere al tiempo, el clima, la hidrología y otros temas ambientales afines

Earth Radiation Budget Research at the NASA Langley Research Center

In the 1970s research studies concentrating on satellite measurements of Earth's radiation budget started at the NASA Langley Research Center. Since that beginning, considerable effort has been devoted to developing measurement techniques, data analysis methods, and time-space sampling strategies to meet the radiation budget science requirements for climate studies. Implementation and success of the Earth Radiation Budget Experiment (ERBE) and the Clouds and the Earth's Radiant Energy System (CERES) was due to the remarkable teamwork of many engineers, scientists, and data analysts. Data from ERBE have provided a new understanding of the effects of clouds, aerosols, and El Nino/La Nina oscillation on the Earth's radiation. CERES spacecraft instruments have extended the time coverage with high quality climate data records for over a decade. Using ERBE and CERES measurements these teams have created information about radiation at the top of the atmosphere, at the surface, and throughout the atmosphere for a better understanding of our climate. They have also generated surface radiation products for designers of solar power plants and buildings and numerous other application

Observation and integrated Earth-system science: a roadmap for 2016–2025

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types of observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016–2025 and some of the issues to be faced. Observations that are organised on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the representations of processes that are already incorporated or through adding new processes or components, are discussed. Some important elements of Earth-system models are considered more fully. Data assimilation is discussed not only because it uses observations and models to generate datasets for monitoring the Earth system and for initiating and evaluating predictions, in particular through reanalysis, but also because of the feedback it provides on the quality of both the observations and the models employed. Inverse methods for surface-flux or model-parameter estimation are also covered. Reviews are given of the way observations and the processed datasets based on them are used for evaluating models, and of the combined use of observations and models for monitoring and interpreting the behaviour of the Earth system and for predicting and projecting its future. A set of concluding discussions covers general developmental needs, requirements for continuity of space-based observing systems, further long-term requirements for observations and other data, technological advances and data challenges, and the importance of enhanced international co-operation