Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research

An Overview of NPP VIIRS Pre-Launch and On-Orbit Calibration and Characterization

NPP Visible Infrared Imaging Radiometer Suite (VIIRS) test program at the instrument and observatory level is complete and has provided an extensive amount of high quality data to enable the assessment of sensor performance

CLARREO: Reference Inter-Calibration on Orbit With Reflected Solar Spectrometer

The CLARREO approach for reference intercalibration is based on obtaining coincident highly accurate spectral reflectance and reflected radiance measurements, and establish an on-orbit reference for existing Earth viewing reflected solar radiation sensors: CERES and VIIRS on JPSS satellites, AVHRR and follow-on imagers on MetOp, and imagers on GEO platforms. The mission goal is to be able to provide CLARREO RS reference observations that are matched in space, time, and viewing angles with measurements from the aforementioned instruments, with sampling sufficient to overcome the random error sources from imperfect data matching and instrument noise. The intercalibration method is to monitor over time changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, spectral degradation, and sensitivity to polarization of optics

PACE Technical Report Series, Volume 4: Cloud Retrievals in the PACE Mission: PACE Science Team Consensus Document

Earth is a complex dynamical system exhibiting continuous change in its atmosphere, ocean,and surface elements. Nearly all (99.97%) of the energy driving these systems is linked to the Sun. Measurements of reflected sunlight contain a unique signature of wavelength-specific scattering and absorption interactions occurring between incoming solar energy and atmospheric (molecules, aerosols,clouds) and surface features Clouds can affect significantly both shortwave and long wave radiation, depending on altitude/vertical structure, thermodynamic phase, and optical properties. Low, warm, and optically thick clouds predominantly have a cooling effect, while high, cold, optically thin clouds can cause warming by absorbing warmer radiation emitted from the surface and lower atmosphere.When the net difference between outgoing and incoming solar radiation is matched by the net infrared radiation emitted to space, the Earth's climate is in radiative balance. While radiative forcing components (GHGs, aerosols - direct and indirect) contribute to a net radiative imbalance, climate sensitivity is ultimately determined by the contribution of various system feed backs. The role of cloud feedback in a warming climate is currently the largest inter-model uncertainty in climate sensitivity and therefore in climate prediction [Bony and Dufresne 2005]. A comprehensive understanding of current cloud propertiesand dynamic/microphysical processes requires a global perspective from satellites

Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument

NASA’s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) satellite mission is scheduled to launch in 2022, with the Ocean Color Instrument (OCI) on board. For the first time reflected sunlight from the Earth across a broad spectrum from the ultraviolet (UV: 350 nm) to the short wave infrared (SWIR: 2260 nm) will be measured from a single instrument at 1 km spatial resolution. While seven discrete bands will represent the SWIR, the spectrum from 350 to 890 nm will be continuously covered with a spectral resolution of 5 nm. OCI will thus combine in a single instrument (and at an enhanced spatial resolution for the UV) the heritage capabilities of the Moderate resolution Imaging Spectroradiometer (MODIS) and the Ozone Monitoring Instrument (OMI), while covering the oxygen A-band (O2A). Designed for ocean color and ocean biology retrievals, OCI also enables continuation of heritage satellite aerosol products and the development of new aerosol characterization from space. In particular the combination of MODIS and OMI characteristics allows deriving aerosol height, absorption and optical depth along with a measure of particle size distribution. This is achieved by using the traditional MODIS visible-to-SWIR wavelengths to constrain spectral aerosol optical depth and particle size. Extrapolating this information to the UV channels allows retrieval of aerosol absorption and layer height. A more direct method to derive aerosol layer height makes use of O2A absorption methods, despite the relative coarseness of the nominal 5 nm spectral resolution of OCI. Altogether the PACE mission with OCI will be an unprecedented opportunity for aerosol characterization that will continue climate data records from the past decades and propel aerosol science forward toward new opportunities

Requirements for an Advanced Ocean Radiometer

This document suggests requirements for an advanced ocean radiometer, such as e.g. the ACE (Aerosol/Cloud/Ecosystem) ocean radiometer. The ACE ocean biology mission objectives have been defined in the ACE Ocean Biology white paper. The general requirements presented therein were chosen as the basis for the requirements provided in this document, which have been transformed into specific, testable requirements. The overall accuracy goal for the advanced ocean radiometer is that the total radiometric uncertainties are 0.5% or smaller for all bands. Specific mission requirements of SeaWiFS, MODIS, and VIIRS were often used as a model for the requirements presented here, which are in most cases more demanding than the heritage requirements. Experience with on-orbit performance and calibration (from SeaWiFS and MODIS) and prelaunch testing (from SeaWiFS, MODIS, and VIIRS) were important considerations when formulating the requirements. This document describes requirements in terms of the science data products, with a focus on qualities that can be verified by prelaunch radiometric characterization. It is expected that a more comprehensive requirements document will be developed during mission formulatio

Satellite Ocean Color Sensor Design Concepts and Performance Requirements

In late 1978, the National Aeronautics and Space Administration (NASA) launched the Nimbus-7 satellite with the Coastal Zone Color Scanner (CZCS) and several other sensors, all of which provided major advances in Earth remote sensing. The inspiration for the CZCS is usually attributed to an article in Science by Clarke et al. who demonstrated that large changes in open ocean spectral reflectance are correlated to chlorophyll-a concentrations. Chlorophyll-a is the primary photosynthetic pigment in green plants (marine and terrestrial) and is used in estimating primary production, i.e., the amount of carbon fixed into organic matter during photosynthesis. Thus, accurate estimates of global and regional primary production are key to studies of the earth's carbon cycle. Because the investigators used an airborne radiometer, they were able to demonstrate the increased radiance contribution of the atmosphere with altitude that would be a major issue for spaceborne measurements. Since 1978, there has been much progress in satellite ocean color remote sensing such that the technique is well established and is used for climate change science and routine operational environmental monitoring. Also, the science objectives and accompanying methodologies have expanded and evolved through a succession of global missions, e.g., the Ocean Color and Temperature Sensor (OCTS), the Seaviewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Medium Resolution Imaging Spectrometer (MERIS), and the Global Imager (GLI). With each advance in science objectives, new and more stringent requirements for sensor capabilities (e.g., spectral coverage) and performance (e.g., signal-to-noise ratio, SNR) are established. The CZCS had four bands for chlorophyll and aerosol corrections. The Ocean Color Imager (OCI) recommended for the NASA Pre-Aerosol, Cloud, and Ocean Ecosystems (PACE) mission includes 5 nanometers hyperspectral coverage from 350 to 800 nanometers with three additional discrete near infrared (NIR) and shortwave infrared (SWIR) ocean aerosol correction bands. Also, to avoid drift in sensor sensitivity from being interpreted as environmental change, climate change research requires rigorous monitoring of sensor stability. For SeaWiFS, monthly lunar imaging accurately tracked stability at an accuracy of approximately 0.1% that allowed the data to be used for climate studies [2]. It is now acknowledged by the international community that future missions and sensor designs need to accommodate lunar calibrations. An overview of ocean color remote sensing and a review of the progress made in ocean color remote sensing and the variety of research applications derived from global satellite ocean color data are provided. The purpose of this chapter is to discuss the design options for ocean color satellite radiometers, performance and testing criteria, and sensor components (optics, detectors, electronics, etc.) that must be integrated into an instrument concept. These ultimately dictate the quality and quantity of data that can be delivered as a trade against mission cost. Historically, science and sensor technology have advanced in a "leap-frog" manner in that sensor design requirements for a mission are defined many years before a sensor is launched and by the end of the mission, perhaps 15-20 years later, science applications and requirements are well beyond the capabilities of the sensor. Section 3 provides a summary of historical mission science objectives and sensor requirements. This progression is expected to continue in the future as long as sensor costs can be constrained to affordable levels and still allow the incorporation of new technologies without incurring unacceptable risk to mission success. The IOCCG Report Number 13 discusses future ocean biology mission Level-1 requirements in depth

Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the onorbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed

Estimating Optically-Thin Cirrus Cloud Induced Cold Bias On Infrared Radiometric Satellite Sea Surface Temperature Retrieval In The Tropics

Passive longwave infrared radiometric satellite-based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically-thin cirrus (OTC) clouds (cloud optical depth \u3c 0.3; COD). Level 2 split-window SST retrievals over tropical oceans (30 S - 30 N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, mounted on the independent NASA CALIPSO satellite. OTC are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level-2 data, representing over 99% of all contaminating cirrus found. This results in cold-biased SST retrievals using either split- (MODIS, AVHRR and VIIRS) or triple-window (AVHRR and VIIRS only) retrieval methods. SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5 km thick OTC cloud placed incrementally from 10.0 - 18.0 km above mean sea level for cloud optical depths (COD) between 0.0 - 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud top height and COD (assuming them consistent across each platform) integrated within each corresponding modeled cold bias matrix. Split-window relative OTC cold biases, for any single observation, range from 0.40 - 0.49 C for the three sensors, with an absolute (bulk mean) bias between 0.10 - 0.13 C. Triple-window retrievals are more resilient, ranging from 0.03 - 0.04 C relative and 0.11 - 0.16 C absolute. Cold biases are constant across the Pacific and Indian Ocean domains. Absolute bias is smaller over the Atlantic, but relative bias is larger due to different cloud properties indicating that this issue persists globally

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

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