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NASA NTRS2015

Consistency of CERES Radiances and Fluxes from Aqua and Suomi-NPP

The Clouds and Earth's Radiant Energy System (CERES) instruments on board Terra, Aqua, and Suomi-NPP have been providing data products critical to advancing our understanding of the effects of clouds and aerosols on radiative energy within the Earth-atmosphere system. The CERES instrument consists of a threechannel broadband scanning radiometer. The scanning radiometer measures radiances in shortwave (SW, 0.3-5 micron), window (WN, 8-12 micron), and total (0.3-200 micron) channels. The longwave (LW) component is derived as the difference between total and SW channels. These measured radiances at a given sun-Earthsatellite geometry are converted to outgoing reflected solar and emitted thermal TOA radiative fluxes by using CERES scene-type dependent angular distribution models (ADMs). The CERES instruments must remain radiometrically stable and correctly inter-calibrated to accurately capture changes in Earth"s radiation budget from interannual to decadal timescales. This presentation will focus on comparisons between collocated radiance measurements from CERES instruments on Aqua and on Suomi-NPP. As we do not have a set of ADMs that is constructed specifically for the CERES instrument on Suomi-NPP, CERES Aqua ADMs are used to invert fluxes from radiance measurements on Suomi-NPP. But the CERES Aqua footprint size is smaller than the CERES Suomi-NPP footprint size and the scene identifications provided by MODIS and VIIRS can also be different from each other. Will using Aqua ADMs for Suomi-NPP flux inversion increase the flux uncertainty? We will examine the deseasonalized flux anomaly time series using Aqua data alone and using combined Aqua and Suomi-NPP data. We will also present a simulation study to assess the Suomi-NPP flux uncertainty from using Aqua ADMs for the flux inversion.

Su, Wenying↗

NASA NTRS2015

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

Minnis, Patrick↗

NASA NTRS2015

Evaluating Surface Flux Results from CERES-FLASHFlux

The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed to provide a rapid release version of the Clouds and Earth's Radiant Energy System (CERES) results, which could be made available to the research and applications communities within one week of the satellite observations by exchanging some accuracy for speed of processing. Unlike standard CERES products, FLASHFlux does not maintain a long-term consistent record. Therefore the latest algorithm changes and input data can be incorporated into processing. FLASHFlux released Version3A (January 2013) and Version 3B (August 2014) which include the latest meteorological product from Global Modeling and Assimilation Office (GMAO), GEOS FP-IT (5.9.1), the latest spectral response functions and gains for the CERES instruments, and aerosol climatology based on the latest MATCH data. Version 3B included a slightly updated calibration and some changes to the surface albedo over snow/ice. Typically FLASHFlux does not reprocess earlier versions when a new version is released. The combined record of Time Interpolated Space Averaged (TISA) surface flux results from Versions3A and 3B for July 2012 to October 2015 have been compared to the ground-based measurements. The FLASHFlux results are also compared to two other CERES gridded products, SYN1deg and EBAF surface fluxes.

Wilber, Anne C.↗

NASA NTRS2015

NASA ROVER, Tackling Citizen Science With Grand Challenges and Everyday Problems

ROVER is the Citizen Science arm of the NASA Clouds and the Earth's Radiant Energy System (CERES) Students' Cloud Observations On-Line (S'COOL) Project. Since 2007, participants around the world have been making and reporting ground truth observations of clouds to assist in the validation of the NASA CERES satellite instrument. NASA scientists are very interested in learning how clouds affect our atmosphere, weather, and climate (relating to climate change). It is the clouds, in part, that affect the overall temperature and energy balance of the Earth. The more we know about clouds, the more we will know about our Earth as a system and citizen scientists are an important piece of that puzzle! As a ROVER cloud observer, all participants follow simple online tutorials to collect data on cloud type, height, cover and related conditions. Observations are sent to NASA to be matched to similar information obtained from satellites and sent back to participants for comparison and analysis. The supporting ROVER website houses a searchable database archiving all participant reports and matching satellite data. By involving Citizen Scientists in cloud observations and reporting we can gain a valuable set of data that would have been previously unavailable to science teams due to funding, manpower, and resource limitations or would have taken an unreasonable amount of time to collect. Reports from a wide range of Citizen Scientist locations are helpful to assess the satellite data under different conditions. With nothing more than their eyes and an internet connection participants provide a different perspective and analysis of clouds, adding to a more complete picture of what's happening in the atmosphere in which we live.

Crecelius, Sarah↗

NASA NTRS2015

Radiation Budget Instrument (RBI) for JPSS-2

Radiation Budget Instrument (RBI) will be one of five instruments flying aboard the JPSS-2 spacecraft, a polar-orbiting sun-synchronous satellite in Low Earth Orbit. RBI is a passive remote sensing instrument that will follow the successful legacy of the Clouds and Earth's Radiant Energy System (CERES) instruments to make measurement of Earth's short and longwave radiation budget. The goal of RBI is to provide an independent measurement of the broadband reflected solar radiance and Earth's emitted thermal radiance by using three spectral bands (Shortwave, Longwave, and Total) that will have the same overlapped point spread function (PSF) footprint on Earth. To ensure precise NIST-traceable calibration in space the RBI sensor is designed to use a visible calibration target (VCT), a solar calibration target (SCT), and an infrared calibration target (ICT) containing phase change cells (PCC) to enable on-board temperature calibration. The VCT is a thermally controlled integrating sphere with space grade Spectralon covering the inner surface. Two sides of the sphere will have fiber-coupled laser diodes in the UV to IR wavelength region. An electrical substitution radiometer on the integrating sphere will monitor the long term stability of the sources and the possible degradation of the Spectralon in space. In addition the radiometric calibration operations will use the Spectralon diffusers of the SCT to provide accurate measurements of Solar degradation. All those stable on-orbit references will ensure that calibration stability is maintained over the RBI sensor lifetime. For the preflight calibration the RBI will view five calibration sources - two integrating spheres and three CrIS (Cross-track Infrared Sounder ) -like blackbodies whose outputs will be validated with NIST calibration approach. Thermopile are the selected detectors for the RBI. The sensor has a requirement to perform lunar calibration in addition to solar calibration in space in a way similar to CERES instruments approach. To monitor climate change and to get stable and traceable results, it is critical to assure stable calibration over instrument lifetime.

Georgieva, Elena↗

NASA NTRS2015

On the Relative Stability of CERES Reflected Shortwave and MISR and MODIS Visible Radiance Measurements During the Terra Satellite Mission

Fifteen years of visible, near-infrared, and broadband shortwave radiance measurements from Clouds and the Earth's Radiant Energy System (CERES), Multiangle Imaging Spectroradiometer (MISR), and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board NASA's Terra satellite are analyzed in order to assess their long-term relative stability for climate purposes. A regression-based approach between CERES, MODIS, and MISR (An camera only) reflectances is used to calculate the bias between the different reflectances relative to a reference year. When compared to the CERES shortwave broadband reflectance, relative drift between the MISR narrowbands is within 1%/decade. Compared to the CERES shortwave reflectance, the MODIS narrowband reflectances show a relative drift of less than −1.33%/decade. When compared to MISR, the MODIS reflectances show a relative drift of between −0.36%/decade and −2.66%/decade. We show that the CERES Terra SW measurements are stable over the time period relative to CERES Aqua. Using this as evidence that CERES Terra may be absolutely stable, we suggest that the CERES, MISR, and MODIS instruments meet the radiometric stability goals for climate applications set out in Ohring et al. (2005).

Corbett, J. G.↗

NASA NTRS2015

Next-Generation Angular Distribution Models for Top-of-Atmosphere Radiative Flux Calculation from CERES Instruments: Validation

Radiative fluxes at the top of the atmosphere (TOA) from the Clouds and the Earth's Radiant Energy System (CERES) instrument are fundamental variables for understanding the Earth's energy balance and how it changes with time. TOA radiative fluxes are derived from the CERES radiance measurements using empirical angular distribution models (ADMs). This paper evaluates the accuracy of CERES TOA fluxes using direct integration and flux consistency tests. Direct integration tests show that the overall bias in regional monthly mean TOA shortwave (SW) flux is less than 0.2Wm(exp -2) and the RMSE is less than 1.1Wm(exp -2). The bias and RMSE are very similar between Terra and Aqua. The bias in regional monthly mean TOA LW fluxes is less than 0.5Wm(exp -2) and the RMSE is less than 0.8Wm(exp -)2 for both Terra and Aqua. The accuracy of the TOA instantaneous flux is assessed by performing tests using fluxes inverted from nadir- and oblique-viewing angles using CERES along-track observations and temporally and spatially matched MODIS observations, and using fluxes inverted from multi-angle MISR observations. The averaged TOA instantaneous SW flux uncertainties from these two tests are about 2.3% (1.9Wm(exp -2) over clear ocean, 1.6% (4.5Wm(exp -2) over clear land, and 2.0% (6.0Wm(exp -) over clear snow/ice; and are about 3.3% (9.0Wm(exp -2), 2.7% (8.4Wm(exp -2), and 3.7% (9.9Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA SW flux uncertainties are generally larger for thin broken clouds than for moderate and thick overcast clouds. The TOA instantaneous daytime LW flux uncertainties derived from the CERESMODIS test are 0.5% (1.5Wm(exp -2), 0.8% (2.4Wm(exp -2), and 0.7% (1.3Wm(exp -2) over clear ocean, land, and snow/ice; and are about 1.5% (3.5Wm(exp -2), 1.0% (2.9Wm(exp -2), and 1.1% (2.1Wm(exp -2) over ocean, land, and snow/ice under all-sky conditions. The TOA instantaneous nighttime LW flux uncertainties are about 0.5-1% (<2.0Wm(exp -2) for all surface types. Flux uncertainties caused by errors in scene identification are also assessed by using the collocated CALIPSO, CloudSat, CERES and MODIS data product. Errors in scene identification tend to underestimate TOA SW flux by about 0.6Wm(exp -2) and overestimate TOA daytime (nighttime) LW flux by 0.4 (0.2)Wm(exp -2) when all CERES viewing angles are considered.

Su, W.↗

NASA NTRS2013

Geostationary Enhanced Temporal Interpolation for CERES Flux Products

The Clouds and the Earth's Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth's top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1 deg latitude x 1 deg longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m(sub -2) over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

Doelling, David R.↗

NASA NTRS2016

Construction of a Matched Global Cloud and Radiance Product from LEO/GEO and EPIC Observations to Estimate Daytime Earth Radiation Budget from DSCOVR

With the launch of the Deep Space Climate Observatory (DSCOVR), new estimates of the daytime Earth radiation budget can be computed from a combination of measurements from the two Earth-observing sensors onboard the spacecraft, the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). Although these instruments can provide accurate top-of-atmosphere (TOA) radiance measurements, they lack sufficient resolution to provide details on small-scale surface and cloud properties. Previous studies have shown that these properties have a strong influence on the anisotropy of the radiation at the TOA, and ignoring such effects can result in large TOA-flux errors. To overcome these effects, high-resolution scene identification is needed for accurate Earth radiation budget estimation. Selected radiance and cloud property data measured and derived from several low earth orbit (LEO, including NASA Terra and Aqua MODIS, NOAA AVHRR) and geosynchronous (GEO, including GOES (east and west), METEOSAT, INSAT-3D, MTSAT-2, and HIMAWARI-8) satellite imagers were collected to create hourly 5-km resolution global composites of data necessary to compute angular distribution models (ADM) for reflected shortwave (SW) and longwave (LW) radiation. The satellite data provide an independent source of radiance measurements and scene identification information necessary to construct ADMs that are used to determine the daytime Earth radiation budget. To optimize spatial matching between EPIC measurements and the high-resolution composite cloud properties, LEO/GEO retrievals within the EPIC fields of view (FOV) are convolved to the EPIC point spread function (PSF) in a similar manner to the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product. Examples of the merged LEO/GEO/EPIC product will be presented, describing the chosen radiance and cloud properties and details of how data from the multi-satellite measurements are selected.

Duda, David P.↗

NASA NTRS2017

Direct Radiative Effect of Aerosols Based on PARASOL and OMI Satellite Observations

Accurate portrayal of the aerosol characteristics is crucial to determine aerosol contribution to the Earth's radiation budget. We employ novel satellite retrievals to make a new measurement-based estimate of the shortwave direct radiative effect of aerosols (DREA), both over land and ocean. Global satellite measurements of aerosol optical depth, single-scattering albedo (SSA), and phase function from PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) are used in synergy with OMI (Ozone Monitoring Instrument) SSA. Aerosol information is combined with land-surface bidirectional reflectance distribution function and cloud characteristics from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite products. Eventual gaps in observations are filled with the state-of-the-art global aerosol model ECHAM5-HAM2. It is found that our estimate of DREA is largely insensitive to model choice. Radiative transfer calculations show that DREA at top-of-atmosphere is −4.6 +/- 1.5 W/sq m for cloud-free and −2.1 +/- 0.7 W/sq m for all-sky conditions, during year 2006. These fluxes are consistent with, albeit generally less negative over ocean than, former assessments. Unlike previous studies, our estimate is constrained by retrievals of global coverage SSA, which may justify different DREA values. Remarkable consistency is found in comparison with DREA based on CERES (Clouds and the Earth's Radiant Energy System) and MODIS observations.

Globalsatellite measurements↗

NASA NTRS2017

North Polar Radiative Flux Variability from 2002 Through 2014

NASA's Clouds and the Earth's Radiant Energy System (CERES) project produces the SYN1Deg data product. SYN1deg provides global, 1deg gridded, hourly estimates of Top of Atmosphere (TOA) (CERES observations and calculations) and atmospheric and surface radiative flux (calculations). Examples of 12 year North Polar averages of some variables are shown to the right. Given recent interest in polar science we focus here on TOA and Surface validation of calculated irradiant fluxes. TOA upward longwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining strong through PC 6. Compare SYN1Deg Calculations & Meteorological Teleconnections. TOA reflected shortwave irradiance calculations match the CERES observations well both spatially and temporally with correlations remaining string through PC 7. Comparing SYN1Deg calculations to teleconnection patterns requires expanding the area to 30N for EOF analyses. Correlating the Principal Components of various variables to teleconnection time series indicates which variable is most highly correlated with which teleconnection signal. The tables indicate the Pacific North American Oscillation is most correlated to the OLR EOF 1, and the North American Oscillation is correlated most closely to surface LW flux down EOF 1.

Rutan, David↗

NASA NTRS2016

Evaluation of the Sensitivity of the Amazonian Diurnal Cycle to Convective Intensity in Reanalyses

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics-specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Itterly, Kyle F.↗

NASA NTRS2017

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

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). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.

Khlopenkov, Konstantin V.↗

NASA NTRS2016

Far-Infrared Room-Temperature Focal Plane Modules for Radiation Budget Instrument

This work presents focal plane modules for a Radiation Budget Instrument, a passive remote-sensing instrument that follows the legacy of the Clouds and Earth’s Radiant Energy System (CERES) to measure short and longwave Earth’s radiation budget. The focal plane arrays are micromachined at JPL (Jet Propulsion Laboratory) and integrated into sub-assembly modules to be mounted on the optical telescope of the instrument.

Mariani, Giacomo↗

NASA NTRS2017

CERES S’COOL Project Update: The Evolution and Value of a Long-Running Education Project With a Foundation in NASA Earth Science Missions

In January 1997, the Students’ Cloud Observations On-Line (S’COOL; http://scool.larc.nasa.gov) Project began with NASA scientists visiting rural Gloucester, Virginia to observe clouds with middle school students. In the 19 years since, this educational outreach component of NASA’s Clouds and the Earth’s Radiant Energy System (CERES) mission has collected ~141,000 observations from every continent and ocean basin around the world. Thousands of students and teachers have directly engaged in S’COOL. Beginning in 2008 we invited citizen scientists to participate as well. Over time S’COOL has added more components that engage participants directly with science data analysis, continuing direct ties to CERES research. Whenever possible, the S’COOL team extracts corresponding subsets of CERES data, which are sent to the participant to analyze. Observations can now be matched to images and cloud retrievals from MODIS and measurements from CALIPSO. To date, more than half of S'COOL observation reports correspond to one (or more) CERES overpasses. Comparisons with CERES geostationary satellite cloud retrievals were recently added, making cloud observations at almost any time of day over non-polar regions useful for validation. A thorough analysis of co-located S’COOL and satellite data was conducted during summer 2015. Results show that the S’COOL community provides high quality observations offering useful insights on the strengths and shortcomings of passive cloud remote sensing from space. This reconfirmed the utility of S’COOL observations to the scientific community and provides observers with deeper insight into the challenges associated with validation of space-based cloud property retrievals.

Lin H Chambers↗

NASA NTRS2019

Developing an Aircraft-Based Angular Distribution Model of Solar Reflection from Wildfire Smoke to Aid Satellite-Based Radiative Flux Estimation

This study examines the angular distribution of scattered solar radiation associated with wildfire smoke aerosols observed over boreal forests in Canada during the ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) campaign. First, it estimates smoke radiative parameters (550 nm optical depth of 3.9 and single scattering albedo of 0.90) using quasi-simultaneous multiangular and multispectral airborne measurements by the Cloud Absorption Radiometer (CAR). Next, the paper estimates the broadband top-of-atmosphere radiances that a satellite instrument such as the Clouds and the Earth’s Radiant Energy System (CERES) could have observed, given the narrowband CAR measurements made from an aircraft circling about a kilometer above the smoke layer. This estimation includes both an atmospheric correction that accounts for the atmosphere above the aircraft and a narrowband-to-broadband conversion. The angular distribution of estimated radiances is found to be substantially different than the angular model used in the operational data processing of CERES observations over the same area. This is because the CERES model is a monthly average model that was constructed using observations taken under smoke-free conditions. Finally, a sensitivity analysis shows that the estimated angular distribution remains accurate for a fairly wide range of smoke and underlying surface parameters. Overall, results from this work suggest that airborne CAR measurements can bring some substantial improvements in the accuracy of satellite-based radiative flux estimates.

Varnai, Tamas↗

NASA NTRS2019

Leveraging Thousands of Contrail Observations from GLOBE Citizen Scientists

The GLOBE (Global Learning and Observations to Benefit the Environment) Program is NASA's largest and longest-operating citizen science program contributing Earth observations. Over 800,000 cloud observations have been reported worldwide since YEAR that include reports of short-lived, persistent, and persistent-spreading contrails. While contrails can be challenging to observe with space-borne platforms, humans are adept at spotting contrails from the ground. The NASA GLOBE Clouds team at NASA Langley Research Center in Hampton, Virginia matches cloud observations to multiple satellite platforms for comparison, including: NASA's CERES (Clouds and Earth's Radiant Energy System) instrument onboard Terra and Aqua, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation), and geostationary satellites. A pilot project was started with select students in the United States to track airplanes above 25,000 ft and report airplane type, altitude, and report if a contrail was being or was not being produced. The objective of the pilot project was to establish if this is a scalable approach for building an international observational dataset documenting what types of airplanes are creating what types of contrails (short-lived, persistent, spreading) under what atmospheric conditions. Preliminary results of this pilot project will be presented.

Colón Robles, Marilé↗

NASA NTRS2018

Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product

The Clouds and the Earth’s Radiant Energy System (CERES) project relies on geostationary (GEO) imager derived TOA broadband fluxes and cloud properties to account for the regional diurnal fluctuations between the Terra and Aqua CERES and MODIS measurements. Anchoring the GEO visible calibration to the MODIS reference calibration and stability is critical for consistent fluxes and cloud retrievals across the 16 GEO imagers utilized in the CERES record. The CERES Edition 4A used GEO and MODIS ray-matched radiance pairs over all-sky tropical ocean (ATO-RM) to transfer the MODIS calibration to the GEO imagers. The primary GEO ATO-RM calibration was compared with the deep convective cloud (DCC) ray-matching and invariant desert/DCC target calibration methodologies, which are all tied to the same Aqua-MODIS calibration reference. Results indicate that most GEO record mean calibration method biases are within 1% with respect to ATO-RM. Most calibration method temporal trends were within 0.5% relative to ATO-RM. The monthly gain trend standard errors were mostly within 1% for all methods and GEOs. The close agreement amongst the independent calibration techniques validates all methodologies, and verifies that the coefficients are not artifacts of the methodology but rather adequately represent the true GEO visible imager degradation.

Doelling, David↗