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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 NTRS2016

Shortwave Direct Radiative Effects of Above-Cloud Aerosols Over Global Oceans Derived From 8 Years of CALIOP and MODIS Observations

In this paper, we studied the frequency of occurrence and shortwave direct radiative effects (DREs) of above-cloud aerosols (ACAs) over global oceans using 8 years (2007-2014) of collocated CALIOP and MODIS observations. Similar to previous work, we found high ACA occurrence in four regions: southeastern (SE) Atlantic region, where ACAs are mostly light-absorbing aerosols, i.e., smoke and polluted dust according to CALIOP classification, originating from biomass burning over the African Savanna; tropical northeastern (TNE) Atlantic and the Arabian Sea, where ACAs are predominantly windblown dust from the Sahara and Arabian deserts, respectively; and the northwestern (NW) Pacific, where ACAs are mostly transported smoke and polluted dusts from Asia. From radiative transfer simulations based on CALIOP-MODIS observations and a set of the preselected aerosol optical models, we found the DREs of ACAs at the top of atmosphere (TOA) to be positive (i.e., warming) in the SE Atlantic and NW Pacific regions, but negative (i.e., cooling) in the TNE Atlantic Ocean and the Arabian Sea. The cancellation of positive and negative regional DREs results in a global ocean annual mean diurnally averaged cloudy-sky DRE of 0.015 W m(exp. -2) [range of -0.03 to 0.06 W m (exp. -2)] at TOA. The DREs at surface and within the atmosphere are -0.015 W m(exp. -2) [range of -0.09 to -0.21 W m(exp. -2)], and 0.17 W m(exp. -2) [range of 0.11 to 0.24 W m(exp. -2)], respectively. The regional and seasonal mean DREs are much stronger. For example, in the SE Atlantic region, the JJA (July-August) seasonal mean cloudy-sky DRE is about 0.7 W m(exp. -2) [range of 0.2 to 1.2 W m(exp. -2)] at TOA. All our DRE computations are publicly available. The uncertainty in our DRE computations is mainly caused by the uncertainties in the aerosol optical properties, in particular aerosol absorption, the uncertainties in the CALIOP operational aerosol optical thickness retrieval, and the ignorance of cloud and potential aerosol diurnal cycle. In situ and remotely sensed measurements of ACA from future field campaigns and satellite missions and improved lidar retrieval algorithm, in particular vertical feature masking, would help reduce the uncertainty.

direct radiative effects↗

NASA NTRS2017

Simulation of the Ozone Monitoring Instrument Aerosol Index Using the NASA Goddard Earth Observing System Aerosol Reanalysis Products

We provide an analysis of the commonly used Ozone Monitoring Instrument (OMI) aerosol index (AI) product for qualitative detection of the presence and loading of absorbing aerosols. In our analysis, simulated top-of-atmosphere (TOA) radiances are produced at the OMI footprints from a model atmosphere and aerosol profile provided by the NASA Goddard Earth Observing System (GEOS-5) Modern-Era Retrospective Analysis for Research and Applications aerosol reanalysis (MERRAero). Having established the credibility of the MERRAero simulation of the OMI AI in a previous paper we describe updates in the approach and aerosol optical property assumptions. The OMI TOA radiances are computed in cloud-free conditions from the MERRAero atmospheric state, and the AI is calculated. The simulated TOA radiances are fed to the OMI aerosol retrieval algorithms, and its retrieved AI (OMAERUV AI) is compared to the MERRAero calculated AI. Two main sources of discrepancy are discussed: one pertaining the OMI algorithm assumptions of the surface pressure, which are generally different from what the actual surface pressure of an observation is, and the other related to simplifying assumptions in the molecular atmosphere radiative transfer used in the OMI algorithms. Surface pressure assumptions lead to systematic biases in the OMAERUV AI, particularly over the oceans. Simplifications in the molecular radiative transfer lead to biases particularly in regions of topography intermediate to surface pressures of 600hPa and 1013.25hPa. Generally, the errors in the OMI AI due to these considerations are less than 0.2 in magnitude, though larger errors are possible, particularly over land. We recommend that future versions of the OMI algorithms use surface pressures from readily available atmospheric analyses combined with high-spatial resolution topographic maps and include more surface pressure nodal points in their radiative transfer lookup tables.

remote sensing↗

NASA NTRS2017

Use of A-Train Aerosol Observations to Constrain Direct Aerosol Radiative Effects (DARE) Comparisons with Aerocom Models and Uncertainty Assessments

We describe a technique for combining multiple A-Train aerosol data sets, namely MODIS spectral AOD (aerosol optical depth), OMI AAOD (absorption aerosol optical depth) and CALIOP aerosol backscatter retrievals (hereafter referred to as MOC retrievals) to estimate full spectral sets of aerosol radiative properties, and ultimately to calculate the 3-D distribution of direct aerosol radiative effects (DARE). We present MOC results using almost two years of data collected in 2007 and 2008, and show comparisons of the aerosol radiative property estimates to collocated AERONET retrievals. Use of the MODIS Collection 6 AOD data derived with the dark target and deep blue algorithms has extended the coverage of the MOC retrievals towards higher latitudes. The MOC aerosol retrievals agree better with AERONET in terms of the single scattering albedo (ssa) at 441 nm than ssa calculated from OMI and MODIS data alone, indicating that CALIOP aerosol backscatter data contains information on aerosol absorption. We compare the spatio-temporal distribution of the MOC retrievals and MOC-based calculations of seasonal clear-sky DARE to values derived from four models that participated in the Phase II AeroCom model intercomparison initiative. Overall, the MOC-based calculations of clear-sky DARE at TOA over land are smaller (less negative) than previous model or observational estimates due to the inclusion of more absorbing aerosol retrievals over brighter surfaces, not previously available for observationally-based estimates of DARE. MOC-based DARE estimates at the surface over land and total (land and ocean) DARE estimates at TOA are in between previous model and observational results. Comparisons of seasonal aerosol property to AeroCom Phase II results show generally good agreement best agreement with forcing results at TOA is found with GMI-MerraV3. We discuss sampling issues that affect the comparisons and the major challenges in extending our clear-sky DARE results to all-sky conditions. We present estimates of clear-sky and all-sky DARE and show uncertainties that stem from the assumptions in the spatial extrapolation and accuracy of aerosol and cloud properties, in the diurnal evolution of these properties, and in the radiative transfer calculations.

aerosol↗

NASA NTRS2018

A Geostationary Instrument Simulator for Aerosol Observing System Simulation Experiments

In the near future, there will be several new instruments measuring atmospheric composition from geostationary orbit over North America, East Asia, and Europe. This constellation of satellites will provide high resolution, time resolved measurements of trace gases and aerosols for monitoring air quality and tracking pollution sources. This paper describes a detailed, fast, and accurate (less than 1.0% uncertainty) method for calculating synthetic top of the atmosphere (TOA) radiances from a global simulation with a mesoscale free running model, the GEOS-5 Nature Run, for remote sensing instruments in geostationary orbit that measure in the ultraviolet-visible spectral range (UV-Vis). Generating these synthetic observations is the first step of an Observing System Simulation Experiment (OSSE), a framework for evaluating the impact of a new observation or algorithm. This paper provides details of the model sampling, aerosol and cloud optical properties, surface reflectance modeling, Rayleigh scattering calculations, and a discussion of the uncertainties of the simulated TOA radiance. An application for the simulated TOA radiance observations is demonstrated in the manuscript. Simulated TEMPO (Tropospheric Emissions: Monitoring of Pollution) and GOES-R (Geostationary Operational Environmental Satellites) observations were used to show how observations from the two instruments could be combined to facilitate aerosol type discrimination. The results demonstrate the viability of a detailed instrument simulator for radiance measurements in the UV-Vis that is capable of accurately simulating high resolution, time-resolved measurements with reasonable computational efficiency.

Castellanos, Patricia↗

NASA NTRS2019

Generating Accurate and Consistent Top-Of-Atmosphere Reflectance Products from the New Generation Geostationary Satellite Sensors

GeoNEX is a collaborative project by scientists from NASA, NOAA, JAXA, and other organizations around the world with the purpose of generating a suite of Earth-monitoring products using data streams from the latest geostationary (GEO) sensors including the GOES-16/17 ABI and the Himawari-8/9 AHI. An accurate and consistent top-of-atmosphere (TOA) reflectance product, in particular the bidirectional reflectance factor (BRF), is the starting point in the scientific processing chain. We describe the main considerations and corresponding algorithms in generating the GeoNEX TOA BRF product. First, a special advantage of geostationary data streams is their high temporal resolution (~10 minutes per full-disk scan), providing a key source of information for many downstream products. To fully utilize this high temporal frequency demands a high georegistration accuracy for every acquired image. Our analysis shows that there can be substantial georegistration uncertainties in both GOES and Himawari L1b data which we addressed by implementing a phase-based correction algorithm to remove residual errors. Second, geostationary sensors have distinct illumination-view geometry features in that the solar angle changes for every pixel. Therefore, to accurately derive a BRF requires a solar position algorithm and the estimation of the pixel-wise acquisition time within an uncertainty of 10 seconds. Third, we discuss the measures we adopted to check and correct residual radiometric calibration issues of individual sensors to enable time-series analysis as well as the cross calibration between different satellite sensors (including those from low-Earth orbit). Finally, we also explain the rationale for the choice of the global grid/tile system of the GeoNEX TOA BRF product.

Wang, Weile↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33231-DND

It is well established that clouds have a profound influence on Earth's energy budget and that cloud feedbacks are responsible for much of the uncertainty in climate model projections of global warming in response to radiative forcing by greenhouse gases. While most model evaluation efforts focus on model representation of the observed mean state. For example, the regional mean climatology of key climate variables there is also tremendous value in testing how a model represents observed internal variations of the climate system. Here we use CERES observations during and after the so-called global warming hiatus to evaluate a subset of CMIP6 climate models. The CERES data show a marked 0.83 Wm-2 reduction in global mean reflected SW TOA flux during the three years following the hiatus that results in an increase in net energy into the climate system. The primary driver of the decrease in SW TOA flux is a reduction in low cloud cover over the eastern Pacific Ocean that occurs in response to an unprecedented increase in SSTs in that region following the hiatus. The CMIP6 simulations consist of AMIP-style experiments in which SSTs and sea-ice boundary conditions are constrained by observations. For each model, the AMIP runs were extended through the end of 2017 from the official CMIP6 AMIP end period in 2014. Results show that the models do a good job at capturing the pattern of observed changes in TOA flux observed by CERES, but tend to underestimate the magnitude.

Norman G Loeb↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33601-DND

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 18 years of an accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. CERES provides the climate community the following parameters: coincident instantaneous 1? gridded CERES observed TOA fluxes, computed profile and surface fluxes, as well as MODIS cloud and aerosol retrievals. Clouds and radiation interaction one key factor that dominates climate feedbacks and is also the most difficult problem with large uncertainty. To further advance our understanding of the cloud-radiation interaction, the climate community need data with accurate fluxes and their associated cloud properties for both observational and modelling study. The new CERES FluxByCldTyp data product is produced for this purpose. The flux product combines for the first time CERES measured TOA fluxes along with the associated MODIS cloud properties, which links radiative flux directly to a specific cloud type. This was achieved by computing sub-footprint fluxes for the clear-sky and cloudy portions of the CERES footprint. The spatially distributed cloud properties within the CERES footprint were retrieved from 2-km MODIS pixels, that were stratified by cloud type. The sub-footprint fluxes were estimated from MODIS radiances based on empirically derived narrowband to broadband coefficients. The combined sub-footprint fluxes can then be validated with the observed footprint flux. This presentation will focus on the algorithm development of the flux-by-cloud-type product and its validation.

Moguo Sun↗

NASA NTRSDate not supplied

TPSAS-NF1676L-33753-DND

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 18 years of an accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. CERES provides the climate community the following parameters: coincident instantaneous 1 gridded CERES observed TOA fluxes, computed profile and surface fluxes, as well as MODIS cloud and aerosol retrievals. Clouds and radiation interaction one key factor that dominates climate feedbacks and is also the most difficult problem with large uncertainty. To further advance our understanding of the cloud-radiation interaction, the climate community need data with accurate fluxes and their associated cloud properties for both observational and modelling study. The new CERES FluxByCldTyp data product is produced for this purpose. The flux product combines for the first time CERES measured TOA fluxes along with the associated MODIS cloud properties, which links radiative flux directly to a specific cloud type. This was achieved by computing sub-footprint fluxes for the clear-sky and cloudy portions of the CERES footprint. The spatially distributed cloud properties within the CERES footprint were retrieved from 2-km MODIS pixels, that were stratified by cloud type. The sub-footprint fluxes were estimated from MODIS radiances based on empirically derived narrowband to broadband coefficients. The combined sub-footprint fluxes can then be validated with the observed footprint flux. This presentation will focus on the algorithm development of the flux-by-cloud-type product and its validation. The paper will also discuss CERES FlxbyCldTyp simulator and its application.

Moguo Sun↗

NASA NTRSDate not supplied

TPSAS-NF1676L-35172-DND

The wide field of view instrument on Earth Radiation Budget Experiment (ERBE) Earth Radiation Budget Satellite (ERBS) took measurements from November 1984 through September 1999. It provides top-of-atmosphere (TOA) reflected shortwave and emitted longwave irradiance at a 10 degree by 10 degree spatial resolution. We have recently re-processed ERBS wide field of view data with algorithms similar to those used in the CERES process (Shrestha et al. 2019). We also calibrated ERBS shortwave and longwave irradiance with CERES-derived irradiances. Combining ERBS and CERES data, we analyze the time series of global mean net TOA irradiance from 1985. The change of TOA net radiation over 30 years derived from ERBS and CERES data is larger than the change derived by Allan et al. (2014). The difference in the net irradiance change from two data sets is, however, within the uncertainty of ocean heating rates derived from ocean temperature measurements in 80?s. We also investigate the spatial distribution of changes in reflected shortwave irradiances derived from ERBS and CERES periods. The spatial distribution of reflected shortwave irradiance changes over the tropics and sub-tropical regions derived from our data set is qualitatively consistent with the result of Norris et al. (2016).

Antonio Viudez-Mora↗

NASA NTRSDate not supplied

Overview of SatCORPS Satellite-Derived Cloud and Radiation Retrieval Coverage of ARM Domains

The ARM Climate Research Facility program maintains a number of climatically representative sites, which provide long-term cloud- and climate-monitoring records via ground-based instrumentation. These measurements provide a valuable data record over a localized region, but can be greatly enhanced by use of satellite monitoring. Satellite analyses over larger domains can provide parameters helpful for monitoring climate and evaluating models. The NASA/Langley Cloud group routinely derives such cloud and radiative parameters, from various geostationary and polar-orbiting satellite coverage over ARM sites; the group provides near-realtime analyses covering the 3 ARM fixed sites, as well as the GO-Amazon AMF site. This is accomplished by employing a suite of algorithms including VISST (Visible Infrared Solar Split-Window Technique), SIST (Solar Infrared Split-Window Technique), and SINT (Solar-infrared Infrared Near-Infrared Technique), now collectively called SatCORPS (Satellite Cloud Observations and Radiative Property retrieval System). An overview and catalog of SatCORPS-derived datasets processed for ASR, and available from both the ARM archive and the NASA/Langley Cloud group website, is provided. Specific improvements included in recently added datasets such as GO-Amazon and Azores are highlighted, including an improved cloud-detection mask, as well as improvements in derived Top-of-Atmosphere (TOA) SW albedoes and LW fluxes. New narrowband-to-broadband (NB-BB) fits and corrections for improved TOA fluxes are illustrated, including MTSAT-1/CERES Aqua NB-BB fits for the TWPICE field campaign, as well as new fits covering the Azores region which incorporate GERB TOA fluxes (Geostationery Earth Radiation Budget). Finally, validation of the reprocessed SatCORPS datasets is shown.

M M Khader↗

NASA NTRS2020

CERES Energy Balanced and Filled (EBAF) from Afternoon-Only Satellite Orbits

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) data product uses a diurnal correction methodology to produce a shortwave (SW) top-of-atmosphere (TOA) radiative flux time series that accounts for diurnal cycle changes between CERES observation times while ensuring that the stability of the EBAF record is tied as closely as possible to CERES instrument calibration stability. The current EBAF Ed4.1 data product combines observations from Terra and Aqua after July 2002. However, the Terra satellite will start to drift in Mean Local Time (MLT) in early 2021, and Aqua’s MLT will start to drift in 2022. To ensure the EBAF record remains temporally stable, we explore the feasibility of using only CERES instruments from afternoon satellite orbits with a tight 1330 MLT after July 2002. We test this approach by directly comparing SW TOA fluxes generated after applying diurnal corrections to Aqua-only and to Terra + Aqua for 07/2002–06/2019. We find that global climatological mean SW TOA fluxes for these two cases are within 0.01 W/sq.m and the trend of the difference is < is 0.03 W/sq.m per decade.

Norman G Loeb↗

NASA NTRS2020

Uncertainties in CERES Top-of-Atmosphere Fluxes Caused by Changes in Accompanying Imager

The Clouds and the Earth’s Radiant Energy System (CERES) project provides observations of Earth’s radiation budget using measurements from CERES instruments on board the Terra, Aqua, Suomi National Polar-orbiting Partnership (S-NPP), and NOAA-20 satellites. The CERES top-of-atmosphere (TOA) fluxes are produced by converting radiance measurements using empirical angular distribution models, which are functions of cloud properties that are retrieved from imagers flying with the CERES instruments. As the objective is to create a long-term climate data record, not only calibration consistency of the six CERES instruments needs to be maintained for the entire time period, it is also important to maintain the consistency of other input data sets used to produce this climate data record. In this paper, we address aspects that could potentially affect the CERES TOA flux data quality. Discontinuities in imager calibration can affect cloud retrieval which can lead to erroneous flux trends. When imposing an artificial 0.6 per decade decreasing trend to cloud optical depth, which is similar to the trend difference between CERES Edition 2 and Edition 4 cloud retrievals, the decadal SW flux trend changed from −0.3 5 ± 0.18 Wm −2 to 0.61 ± 0.18 Wm −2 . This indicates that a 13% change in cloud optical depth results in about 1% change in the SW flux. Furthermore, different CERES instruments provide valid fluxes at different viewing zenith angle ranges, and including fluxes derived at the most oblique angels unique to S-NPP (>66 ∘ ) can lead to differences of 0.8 Wm −2 and 0.3 Wm −2 in global monthly mean instantaneous SW flux and LW flux. To ensure continuity, the viewing zenith angle ranges common to all CERES instruments (<66 ∘ ) are used to produce the long-term Earth’s radiation budget climate data record. The consistency of cloud properties retrieved from different imagers also needs to be maintained to ensure the TOA flux consistency.

Wenying Su↗

NASA NTRSDate not supplied

Understanding The Top-Of-Atmosphere Fluxes Difference Between Aerocom Phase III Models And The CERES Product: Clear-Sky Perspective

The Clouds and the Earth’s Radiant Energy System (CERES) project produces a long-term global climate data record (CDR) that can be used to detect decadal changes in the Earth’s radiation budget (ERB) from the surface to the top-of-atmosphere (TOA). The CERES Energy Balanced and Filled (EBAF) product includes monthly mean shortwave (SW), longwave (LW), and net TOA all-sky and clear-sky radiative fluxes over 1-degree latitude by 1-degree longitude regions. The EBAF SW and LW fluxes are adjusted within their uncertainties to be consistent with the heat storage in the Earth-atmosphere system (Johnson et al. 2016). EBAF also provides a gap-free monthly mean clear-sky flux map by inferring clear-sky fluxes from both CERES and MODIS measurements (Loeb et al. 2018). In this study, we compare the TOA clear-sky fluxes from Aerocom phase III output with those from the CERES EBAF products. Flux differences over the ocean are generally smaller than over the land, and the magnitude of the differences shows seasonal and regional dependency. To understand the flux differences, aerosol optical depths (AOD) from the Aerocom models are compared with the satellite retrievals from MODIS and MISR. Over the ocean, the AOD differences and the flux differences show consistent regional features, indicating that the differences between models and observations are robust as the CERES EBAF clear-sky SW fluxes and MODIS/MISR AODs are determined independently. However, very little resemblance is found between the AOD and flux differences over the land. To further understand the cause of the flux differences over the land, we compare the land surface albedo from MODIS with the albedo from the models and find consistency in regional albedo differences and flux differences. Monthly regional radiative kernels of AOD and surface albedo derived using the MERRA-2 reanalysis data (Thorsen et al. 2020) are applied to AOD and surface albedo differences between models and observations. For most of the models, the AOD and surface albedo differences can explain most of the flux differences between models and CERES EBAF. The EOS era satellites have provided 20 years of carefully calibrated and validated observations that are suitable for trend analysis. Both the MODIS AOD and CERES EBAF clear-sky SW flux show decreasing trends over the coastal regions of eastern China and the eastern United States due to the emission control policies enforced in both countries, and an increasing trend off the coast of India. The AOD and clear-sky SW flux trends are less consistent over land, as the surface albedo changes complicate the clear-sky SW flux trend. The AOD and clear-sky SW flux trends from the Oslo model HIST run are also examined. However, none of the aforementioned regional trends are found in the model results.

Wenying Su↗

NASA NTRSDate not supplied

Validation of GOES-17 ABI Reflective Channels Performance: Salar De Uyuni 2018 Field Campaign Results

Validation results from a reflectance-based field campaign at the Salar de Uyuni in Bolivia (September 2018) are presented for GOES-17 and GOES-16 Advanced Baseline Imagers (ABI) reflective channels. The in situ measurements were used to characterize the surface reflectance and the atmosphere in order to constrain a radiative transfer model and predict the reflectance at the top of the atmosphere (TOA), which was then compared to the ABI measurements. The field campaign provides TOA reflectance estimates over several days, allowing assessment of the calibration accuracy and stability of channels 1, 2, 3, 5 and 6 for GOES-17 andGOES-16 ABI. Channel 1 of GOES-17 ABI shows -5.5% bias in comparison to the ground-based predicted TOA. Over 6% bias in GOES-17 B2 was confirmed. A comparison to NOAA-20 VIIRS was also carried on during a near nadir overpass.

validation↗

NASA NTRS2020

Assessments of S-NPP and N20 VIIRS DNB and M bands calibration stability and consistency using a homogeneous ground target

The S-NPP and N20 VIIRS Day-Night band (DNB) and M bands top-of-atmosphere (TOA) radiance and reflectance are calculated and a kernel-driven Bidirectional Reflectance Distribution Function (BRDF) correction model is used to correct the surface and atmosphere combined BRDF influence. Due to degradation in the DNB modulated Relative Spectral Response (RSR), the S-NPP VIIRS observed TOA DNB reflectance indicates a decrease of 1.89% and the SCIAMACHY spectra derived TOA DNB reflectance has a decrease of 1.63% for the past 8.5 years. The N20 VIIRSTOA DNB reflectance decreased 0.50% in the past 2.5 years. The DNB radiance is also compared with the integral of the M bands radiance from M4, M5, and M7. The fitting trends of DNB to the integral of M bands ratios indicate a0.48% decrease for S-NPP VIIRS and 0.14% increase for N20 VIIRS. The N20 VIIRS DNB to integral M bands ratios are closer to 1 than the S-NPP VIIRS data. The BRDF corrected reflectance comparisons show that the N20 VIIRS data is slightly lower than those of S-NPP VIIRS. The averages of the linear fit values of the N20 to S-NPP VIIRS from 2018to 2020 June are -1.97%, -4.99%, -3.36%, and -0.85% for M4, M5, M7, and DNB, respectively. Our results indicate that the S-NPP and N20 VIIRS DNB and M bands calibration have been stable. The cross-sensor differences in DNB and M bands are generally consistent with other independent studies using similar and different approaches.

Libya 4↗

NASA NTRS2021

Cirrus Cloud Top-of-the-Atmosphere Net Daytime Forcing in the Alaskan Subarctic from Ground-Based MPLNET Monitoring

Cirrus cloud daytime top-of-the-atmosphere radiative forcing (TOA CRF) is estimated for a two-year NASA Micro-Pulse Lidar Network (532 nm; MPLNET) dataset collected at Fairbanks, Alaska. Two-year averaged daytime TOA CRF is estimated at between -1.08 and 0.78 W·m-2 (-0.49 to 1.10 W·m-2 in 2017, and -1.67 to 0.47 W·m-2 in 2018). This subarctic study completes a now trilogy of MPLNET ground-based cloud forcing investigations, following midlatitude and tropical studies by Campbell et al. (2016; C16) at Greenbelt, Maryland and Lolli et al. (2017) at Singapore. C16 hypothesize a global meridional daytime TOA CRF gradient that begins positive at the equator (2.20 – 2.59 W·m-2 over land and -0.46 – 0.42 W·m-2 over ocean at Singapore), becomes neutral in the midlatitudes (0.03 – 0.27 W·m-2 over land in Maryland) and turns negative moving poleward. This study does not completely confirm C16, as values are not found as exclusively negative. Evidence in historical reanalysis data suggests that daytime cirrus forcing in and around the subarctic likely once was exclusively negative. Increasing tropopause heights, inducing higher and colder cirrus, have likely increased regional forcing over the last forty years. We hypothesize that subarctic inter-annual cloud variability is likely a considerable influence on global cirrus cloud forcing sensitivity, given the irregularity of polar versus midlatitude synoptic weather intrusions. This study and hypothesis lays basis for an extrapolation of these MPLNET experiments to satellite-based lidar cirrus cloud datasets.

James R Campbell↗

NASA NTRS2021

Less Atmospheric Radiative Heating By Dust Due to the Synergy of Coarser Size and Aspherical Shape

Mineral dust aerosols cool and warm the atmosphere by scattering and absorbing solar (shortwave: SW) and thermal (longwave: LW) radiation. However, significant uncertainties remain in dust radiative effects, largely due to differences in the dust size distribution and spectral optical properties simulated in Earth system models. Dust models typically underestimate the coarse dust load (more than 2.5 µm in diameter) and assume a spherical shape, which leads to an overestimate of the fine dust load (less than 2.5 µm) after the dust emissions in the models are scaled to match observed dust aerosol optical depth at 550 nm (DAOD550). Here, we improve the simulated dust properties with data sets that leverage measurements of size-resolved dust concentration, asphericity factor, and refractive index in a coupled global chemical transport model with a radiative transfer module. After the adjustment of size-resolved dust concentration and spectral optical properties, the global and annual average of DAOD550 from the simulation increases from 0.023 to 0.029 and falls within the range of a semi-observationally based estimate (0.030 ± 0.005). The reduction of fine dust load after the adjustment leads to a reduction of the SW cooling at the top of the atmosphere (TOA). To improve agreement against a semi-observationally based estimate of the radiative effect efficiency at TOA, we find that a less absorptive SW dust refractive index is required for coarser aspherical dust. Thus, only a minor difference is estimated for the net global dust radiative effect at TOA (−0.08 vs. −0.00 W m−2 on a global scale). Conversely, our sensitivity simulations reveal that the surface warming is substantially enhanced near the strong dust source regions (less cooling to −0.23 from −0.60 W m−2 on a global scale). Thus, less atmospheric radiative heating is estimated near the major source regions (less heating to 0.15 from 0.59 W m−2 on a global scale), because of enhanced LW warming at the surface by the synergy of coarser size and aspherical shape.

simulated dust properties↗