Implications of whole-disc DSCOVR EPIC spectral observations for estimating Earth's spectral reflectivity based on low-earth-orbiting and geostationary observations

Earth’s reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)’s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)’s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth’s reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth’s reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth’s reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between −0.7% and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between −10% and 23%.The NASA/GSFC DSCOVR project is funded by NASA Earth Science Division. W. Song, G. Yan, and X. Mu were also supported by the key program of National Natural Science Foundation of China (NSFC; Grant No. 41331171). This research was conducted and completed during a 13-month research stay of the lead author in the Department of Earth and Environment, Boston University as a joint Ph.D. student, which was supported by the Chinese Scholarship Council (201606040098). DSCOVR EPIC L1B data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. The authors would like to thank the editor who handled this paper and the two anonymous reviewers for providing helpful and constructive comments and suggestions that significantly helped us improve the quality of this paper. (NASA Earth Science Division; 41331171 - key program of National Natural Science Foundation of China (NSFC); 201606040098 - Chinese Scholarship Council)Accepted manuscrip

Earth observations from DSCOVR EPIC instrument

The National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. There are two National Aeronautics and Space Administration (NASA) Earth-observing instruments on board: the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). The purpose of this paper is to describe various capabilities of the DSCOVR EPIC instrument. EPIC views the entire sunlit Earth from sunrise to sunset at the backscattering direction (scattering angles between 168.5° and 175.5°) with 10 narrowband filters: 317, 325, 340, 388, 443, 552, 680, 688, 764, and 779 nm. We discuss a number of preprocessing steps necessary for EPIC calibration including the geolocation algorithm and the radiometric calibration for each wavelength channel in terms of EPIC counts per second for conversion to reflectance units. The principal EPIC products are total ozone (O3) amount, scene reflectivity, erythemal irradiance, ultraviolet (UV) aerosol properties, sulfur dioxide (SO2) for volcanic eruptions, surface spectral reflectance, vegetation properties, and cloud products including cloud height. Finally, we describe the observation of horizontally oriented ice crystals in clouds and the unexpected use of the O2 B-band absorption for vegetation properties.The NASA GSFC DSCOVR project is funded by NASA Earth Science Division. We gratefully acknowledge the work by S. Taylor and B. Fisher for help with the SO2 retrievals and Marshall Sutton, Carl Hostetter, and the EPIC NISTAR project for help with EPIC data. We also would like to thank the EPIC Cloud Algorithm team, especially Dr. Gala Wind, for the contribution to the EPIC cloud products. (NASA Earth Science Division)Accepted manuscrip

Using Deep Space Climate Observatory Measurements to Study the Earth as An Exoplanet

Even though it was not designed as an exoplanetary research mission, the Deep Space Climate Observatory (DSCOVR) has been opportunistically used for a novel experiment, in which Earth serves as a proxy exoplanet. More than two years of DSCOVR Earth images were employed to produce time series of multi-wavelength, single-point light sources, in order to extract information on planetary rotation, cloud patterns, surface type, and orbit around the Sun. In what follows, we assume that these properties of the Earth are unknown, and instead attempt to derive them from first principles. These conclusions are then compared with known data about our planet. We also used the DSCOVR data to simulate phase angle changes, as well as the minimum data collection rate needed to determine the rotation period of an exoplanet. This innovative method of using the time evolution of a multi-wavelength, reflected single-point light source, can be deployed for retrieving a range of intrinsic properties of an exoplanet around a distant star

Estimation of Earth's reflectivity from low orbit satellite data

PresentationFirst author draf

Calibration of the DSCOVR EPIC Visible and NIR Channels Using MODIS Terra and Aqua Data and EPIC Lunar Observations

The unique position of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange 1 point makes an important addition to the data from currently operating low orbit Earth observing instruments. EPIC instrument does not have an onboard calibration facility. One approach to its calibration is to compare EPIC observations to the measurements from polar orbiting radiometers. Moderate Resolution Imaging Spectroradiometer (MODIS) is a natural choice for such comparison due to its well-established calibration record and wide use in remote sensing. We use MODIS Aqua and Terra L1B 1km reflectances to infer calibration coefficients for four EPIC visible and NIR channels: 443 nm, 551 nm, 680 nm and 780 nm. MODIS and EPIC measurements made between June 2015 and June 2016 are employed for comparison. We first identify favorable MODIS pixels with scattering angle matching temporarily collocated EPIC observations. Each EPIC pixel is then spatially collocated to a subset of the favorable MODIS pixels within 25 km radius. Standard deviation of the selected MODIS pixels as well as of the adjacent EPIC pixels is used to find the most homogeneous scenes. These scenes are then used to determine calibration coefficients using a linear regression between EPIC counts/sec and reflectances in the close MODIS spectral channels. We present thus inferred EPIC calibration coefficients and discuss sources of uncertainties. The Lunar EPIC observations are used to calibrate EPIC O2 absorbing channels (688 nm and 764 nm) assuming that there is a small difference between moon reflectances separated by approx.10 nm in wavelength provided the calibration factors of the red (680 nm) and near-IR (780 nm) are known from comparison between EPIC and MODIS

Development of Multi-Sensor Global Cloud and Radiance Composites for Earth Radiation Budget Monitoring from DSCOVR

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). Radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers have to be co-located with EPIC pixels to provide scene identification in order to select anisotropic directional models needed to calculate shortwave and longwave fluxes. A new algorithm is proposed for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-kilometer resolution. An aggregated rating is employed to incorporate several factors and to select the best observation at the time nearest to the EPIC measurement. Spatial accuracy is improved using inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into EPIC-view domain by convolving composite pixels with the EPIC point spread function (PSF) defined with a half-pixel accuracy. PSF-weighted average radiances and cloud properties are computed separately for each cloud phase. The algorithm has demonstrated contiguous global coverage for any requested time of day with a temporal lag of under 2 hours in over 95 percent of the globe

Using Deep Space Climate Observatory Measurements to Study the Earth as an Exoplanet

Even though it was not designed as an exoplanetary research mission, the Deep Space Climate Observatory (DSCOVR) has been opportunistically used for a novel experiment in which Earth serves as a proxy exoplanet. More than 2 yr of DSCOVR Earth images were employed to produce time series of multiwavelength, single-point light sources in order to extract information on planetary rotation, cloud patterns, surface type, and orbit around the Sun. In what follows, we assume that these properties of the Earth are unknown and instead attempt to derive them from first principles. These conclusions are then compared with known data about our planet. We also used the DSCOVR data to simulate phase-angle changes, as well as the minimum data collection rate needed to determine the rotation period of an exoplanet. This innovative method of using the time evolution of a multiwavelength, reflected single-point light source can be deployed for retrieving a range of intrinsic properties of an exoplanet around a distant star

Capability of Sentinel-2 data for estimating maximum evapotranspiration and irrigation requirements for tomato crop in Central Italy

Abstract The occurrence of water shortages ascribed to projected climate change, especially in the Mediterranean region, fosters the interest in remote sensing (RS) applications to optimize water use in agriculture. Remote sensing evapotranspiration and water demand estimation over large cultivated areas were used to manage irrigation to minimize losses during the crop growing cycle. The research aimed to explore the potential of the MultiSpectral Instrument (MSI) sensor on board Sentinel-2A to estimate crop parameters, mainly surface albedo (α) and Leaf Area Index (LAI) that influence the dynamics of potential evapotranspiration (ETp) and Irrigation Water Requirements (IWR) of processing tomato crop (Solanum lycopersicum L.). Maximum tomato ETp was calculated according to the FAO Penman-Monteith equation (FAO-56 PM) using appropriate values of canopy parameters derived by processing Sentinel-2A data in combination with daily weather information. For comparison, we used the actual crop evapotranspiration (ETa) derived from the soil water balance (SWB) module in the Environmental Policy Integrated Climate (EPIC) model and calibrated with in-situ Root Zone Soil Moisture (RZSM). The experiment was set up in a privately-owned farm located in the Tarquinia irrigation district (Central Italy) during two growing seasons, within the framework of the EU Project FATIMA (FArming Tools for external nutrient Inputs and water Management). The results showed that canopy growth, maximum evapotranspiration (ETp) and IWR were accurately inferred from satellite observations following seasonal rainfall and air temperature patterns. The net estimated IWR from satellite observations for the two-growing seasons was about 272 and 338 mm in 2016 and 2017, respectively. Such estimated requirement was lower compared with the actual amount supplied by the farmer with sprinkler and drip micro-irrigation system in both growing seasons resulting in 364 (276 mm drip micro-irrigation, and 88 mm sprinkler) and 662 (574 mm drip micro-irrigation, and 88 mm sprinkler) mm, respectively. Our findings indicated the suitability of Sentinel-2A to predict tomato water demand at field level, providing useful information for optimizing the irrigation over extended farmland

Advances in Measuring the Apparent Optical Properties (AOPs) of Optically Complex Waters

This report documents new technology used to measure the apparent optical properties (AOPs) of optically complex waters. The principal objective is to be prepared for the launch of next-generation ocean color satellites with the most capable commercial off-the-shelf (COTS) instrumentation. An enhanced COTS radiometer was the starting point for designing and testing the new sensors. The follow-on steps were to apply the lessons learned towards a new in-water profiler based on a kite-shaped backplane for mounting the light sensors. The next level of sophistication involved evaluating new radiometers emerging from a development activity based on so-called microradiometers. The exploitation of microradiometers resulted in an in-water profiling system, which includes a sensor networking capability to control ancillary sensors like a shadowband or global positioning system (GPS) device. A principal advantage of microradiometers is their flexibility in producing, interconnecting, and maintaining instruments. The full problem set for collecting sea-truth data--whether in coastal waters or the open ocean-- involves other aspects of data collection that were improved for instruments measuring both AOPs and inherent optical properties (IOPs), if the uncertainty budget is to be minimized. New capabilities associated with deploying solar references were developed as well as a compact solution for recovering in-water instrument systems from small boats