scholarly journals Two MODIS Aerosol Products over Ocean on the Terra and Aqua CERES SSF Datasets

2005 ◽  
Vol 62 (4) ◽  
pp. 1008-1031 ◽  
Author(s):  
Alexander Ignatov ◽  
Patrick Minnis ◽  
Norman Loeb ◽  
Bruce Wielicki ◽  
Walter Miller ◽  
...  
Keyword(s):  
Single Channel ◽  
Radiant Energy ◽  
Cloud Amount ◽  
Energy System ◽  
Poor Quality ◽  
Radiation Budget ◽  
Quality Data ◽  
Radiative Fluxes ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

Abstract Understanding the impact of aerosols on the earth’s radiation budget and the long-term climate record requires consistent measurements of aerosol properties and radiative fluxes. The Clouds and the Earth’s Radiant Energy System (CERES) Science Team combines satellite-based retrievals of aerosols, clouds, and radiative fluxes into Single Scanner Footprint (SSF) datasets from the Terra and Aqua satellites. Over ocean, two aerosol products are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) using different sampling and aerosol algorithms. The primary, or M, product is taken from the standard multispectral aerosol product developed by the MODIS aerosol group while a simpler, secondary [Advanced Very High Resolution Radiometer (AVHRR) like], or A, product is derived by the CERES Science Team using a different cloud clearing method and a single-channel aerosol algorithm. Two aerosol optical depths (AOD), τA1 and τA2, are derived from MODIS bands 1 (0.644 μm) and 6 (1.632 μm) resembling the AVHRR/3 channels 1 and 3A, respectively. On Aqua the retrievals are made in band 7 (2.119 μm) because of poor quality data from band 6. The respective Ångström exponents can be derived from the values of τ. The A product serves as a backup for the M product. More importantly, the overlap of these aerosol products is essential for placing the 20+ year heritage AVHRR aerosol record in the context of more advanced aerosol sensors and algorithms such as that used for the M product. This study documents the M and A products, highlighting their CERES SSF specifics. Based on 2 weeks of global Terra data, coincident M and A AODs are found to be strongly correlated in both bands. However, both domains in which the M and A aerosols are available, and the respective τ/α statistics significantly differ because of discrepancies in sampling due to differences in cloud and sun-glint screening. In both aerosol products, correlation is observed between the retrieved aerosol parameters (τ/α) and ambient cloud amount, with the dependence in the M product being more pronounced than in the A product.

scholarly journals Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth’s Radiant Energy System Instrument on the Terra Satellite. Part I: Methodology

2005 ◽  
Vol 22 (4) ◽  
pp. 338-351 ◽  
Author(s):  
Norman G. Loeb ◽  
Seiji Kato ◽  
Konstantin Loukachine ◽  
Natividad Manalo-Smith
Keyword(s):  
Angular Distribution ◽  
Radiant Energy ◽  
Tropical Rainfall Measuring Mission ◽  
Energy System ◽  
Distribution Models ◽  
Radiative Fluxes ◽  
Earth Observing System ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Satellite

Abstract The Clouds and Earth’s Radiant Energy System (CERES) provides coincident global cloud and aerosol properties together with reflected solar, emitted terrestrial longwave, and infrared window radiative fluxes. These data are needed to improve the understanding and modeling of the interaction between clouds, aerosols, and radiation at the top of the atmosphere, surface, and within the atmosphere. This paper describes the approach used to estimate top-of-atmosphere (TOA) radiative fluxes from instantaneous CERES radiance measurements on the Terra satellite. A key component involves the development of empirical angular distribution models (ADMs) that account for the angular dependence of the earth’s radiation field at the TOA. The CERES Terra ADMs are developed using 24 months of CERES radiances, coincident cloud and aerosol retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from the Global Modeling and Assimilation Office (GMAO)’s Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) V4.0.3 product. Scene information for the ADMs is from MODIS retrievals and GEOS DAS V4.0.3 properties over the ocean, land, desert, and snow for both clear and cloudy conditions. Because the CERES Terra ADMs are global, and far more CERES data are available on Terra than were available from CERES on the Tropical Rainfall Measuring Mission (TRMM), the methodology used to define CERES Terra ADMs is different in many respects from that used to develop CERES TRMM ADMs, particularly over snow/sea ice, under cloudy conditions, and for clear scenes over land and desert.

scholarly journals Top-of-Atmosphere Direct Radiative Effect of Aerosols over Global Oceans from Merged CERES and MODIS Observations

2005 ◽  
Vol 18 (17) ◽  
pp. 3506-3526 ◽  
Author(s):  
Norman G. Loeb ◽  
Natividad Manalo-Smith
Keyword(s):  
Information Service ◽  
Radiant Energy ◽  
Energy System ◽  
Surface Fluxes ◽  
Radiative Effect ◽  
Distribution Models ◽  
Radiative Fluxes ◽  
Clear Sky ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Global Oceans

Abstract The direct radiative effect of aerosols (DREA) is defined as the difference between radiative fluxes in the absence and presence of aerosols. In this study, the direct radiative effect of aerosols is estimated for 46 months (March 2000–December 2003) of merged Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra global measurements over ocean. This analysis includes the contribution from clear regions in both clear and partly cloudy CERES footprints. MODIS–CERES narrow-to-broadband regressions are developed to convert clear-sky MODIS narrowband radiances to broadband shortwave (SW) radiances, and CERES clear-sky angular distribution models (ADMs) are used to estimate the corresponding top-of-atmosphere (TOA) radiative fluxes that are needed to determine the DREA. Clear-sky MODIS pixels are identified using two independent cloud masks: (i) the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) algorithm that is used for inferring aerosol properties from MODIS on the CERES Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product (NOAA SSF); and (ii) the standard algorithm that is used by the MODIS aerosol group to produce the MODIS aerosol product (MOD04). Over global oceans, direct radiative cooling by aerosols for clear scenes that are identified from MOD04 is estimated to be 40% larger than for clear scenes from NOAA SSF (5.5 compared to 3.8 W m−2). Regionally, differences are largest in areas that are affected by dust aerosol, such as oceanic regions that are adjacent to the Sahara and Saudi Arabian deserts, and in northern Pacific Ocean regions that are influenced by dust transported from Asia. The net total-sky (clear and cloudy) DREA is negative (cooling) and is estimated to be −2.0 W m−2 from MOD04, and −1.6 W m−2 from NOAA SSF. The DREA is shown to have pronounced seasonal cycles in the Northern Hemisphere and large year-to-year fluctuations near deserts. However, no systematic trend in deseasonalized anomalies of the DREA is observed over the 46-month time series that is considered.

scholarly journals A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products

2013 ◽  
Vol 30 (3) ◽  
pp. 557-568 ◽  
Author(s):  
Alexander Radkevich ◽  
Konstantin Khlopenkov ◽  
David Rutan ◽  
Seiji Kato
Keyword(s):  
Confidence Intervals ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Data Series ◽  
Clear Sky ◽  
Multiple Thresholds ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Snow And Ice

Abstract Identification of clear-sky snow and ice is an important step in the production of cryosphere radiation budget products, which are used in the derivation of long-term data series for climate research. In this paper, a new method of clear-sky snow/ice identification for Moderate Resolution Imaging Spectroradiometer (MODIS) is presented. The algorithm’s goal is to enhance the identification of snow and ice within the Clouds and the Earth’s Radiant Energy System (CERES) data after application of the standard CERES scene identification scheme. The input of the algorithm uses spectral radiances from five MODIS bands and surface skin temperature available in the CERES Single Scanner Footprint (SSF) product. The algorithm produces a cryosphere rating from an aggregated test: a higher rating corresponds to a more certain identification of the clear-sky snow/ice-covered scene. Empirical analysis of regions of interest representing distinctive targets such as snow, ice, ice and water clouds, open waters, and snow-free land selected from a number of MODIS images shows that the cryosphere rating of snow/ice targets falls into 95% confidence intervals lying above the same confidence intervals of all other targets. This enables recognition of clear-sky cryosphere by using a single threshold applied to the rating, which makes this technique different from traditional branching techniques based on multiple thresholds. Limited tests show that the established threshold clearly separates the cryosphere rating values computed for the cryosphere from those computed for noncryosphere scenes, whereas individual tests applied consequently cannot reliably identify the cryosphere for complex scenes.

scholarly journals Geostationary Enhanced Temporal Interpolation for CERES Flux Products

2013 ◽  
Vol 30 (6) ◽  
pp. 1072-1090 ◽  
Author(s):  
David R. Doelling ◽  
Norman G. Loeb ◽  
Dennis F. Keyes ◽  
Michele L. Nordeen ◽  
Daniel Morstad ◽  
...  
Keyword(s):  
Global Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Cloud Properties ◽  
Marine Stratus ◽  
Temporal Interpolation ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Observation Times

Abstract 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° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−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.

scholarly journals Experiments with Cloud Properties: Impact on Surface Radiative Fluxes

2008 ◽  
Vol 25 (6) ◽  
pp. 1034-1040 ◽  
Author(s):  
H. Wang ◽  
R. T. Pinker ◽  
P. Minnis ◽  
M. M. Khaiyer
Keyword(s):  
Optical Properties ◽  
Single Channel ◽  
Winter Season ◽  
Global Scale ◽  
Radiation Budget ◽  
Radiative Fluxes ◽  
Cloud Properties ◽  
Central United States ◽  
Atmospheric Radiation Measurement ◽  
The Impact

Abstract Solar radiation reaching the earth’s surface provides the primary forcing of the climate system, and thus, information on this parameter is needed at a global scale. Several satellite-based estimates of surface radiative fluxes are available, but they differ from each other in many aspects. The focus of this study is to highlight one aspect of such differences, namely, the way satellite-observed radiances are used to derive information on cloud optical properties and the impact this has on derived parameters such as surface radiative fluxes. Frequently, satellite visible radiance in a single channel is used to infer cloud transmission; at times, several spectral channels are utilized to derive cloud optical properties and use these to infer cloud transmission. In this study, an evaluation of these two approaches will be performed in terms of impact on the accuracy in surface radiative fluxes. The University of Maryland Satellite Radiation Budget (UMD/SRB) model is used as a tool to perform such an evaluation over the central United States. The estimated shortwave fluxes are evaluated against ground observations at the Atmospheric Radiation Measurement Program (ARM) Central Facility and at four ARM extended sites. It is shown that the largest differences between these two approaches occur during the winter season when snow is on the ground.

scholarly journals Validation of the CERES Edition-4A Surface-Only Flux Algorithms

2020 ◽  
Vol 59 (2) ◽  
pp. 281-295 ◽  
Author(s):  
David P. Kratz ◽  
Shashi K. Gupta ◽  
Anne C. Wilber ◽  
Victor E. Sothcott
Keyword(s):  
Radiant Energy ◽  
Energy System ◽  
Surface Fluxes ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Random Errors ◽  
High Quality ◽  
Radiative Fluxes ◽  
Accuracy Requirement ◽  
Future Work

AbstractSurface radiative fluxes have been derived with the objective of supplementing top-of-atmosphere (TOA) radiative fluxes being measured under NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project. This has been accomplished by using combinations of CERES TOA measurements, parameterized radiative transfer algorithms, and high-quality meteorological datasets available from reanalysis projects. Current CERES footprint-level products include surface fluxes derived from two shortwave (SW) and three longwave (LW) algorithms designated as SW models A and B and LW models A, B, and C. The SW and LW models A work for clear conditions only; the other models work for both clear and cloudy conditions. The current CERES Edition-4A computed surface fluxes from all models are validated against ground-based flux measurements from high-quality surface networks like the Baseline Surface Radiation Network and NOAA’s Surface Radiation Budget Network (SURFRAD). Validation results as systematic and random errors are provided for all models, separately for five different surface types and combined for all surface types as tables and scatterplots. Validation of surface fluxes is now a part of CERES processing and is used to continually improve the above algorithms. Since both models B work for clear and cloudy conditions alike and meet the accuracy requirement, their results are considered to be the most reliable and most likely to be retained for future work. Both models A have limited use given that they work for clear skies only. Models B will continue to undergo further improvement as more validation results become available.

scholarly journals Top-of-Atmosphere Radiance-to-Flux Conversion in the SW Domain for the ScaRaB-3 Instrument on Megha-Tropiques

2009 ◽  
Vol 26 (10) ◽  
pp. 2161-2171 ◽  
Author(s):  
Michel Viollier ◽  
Carsten Standfuss ◽  
Olivier Chomette ◽  
Arnaud Quesney
Keyword(s):  
Radiant Energy ◽  
Tropical Rainfall Measuring Mission ◽  
Theoretical Models ◽  
Energy System ◽  
Radiation Budget ◽  
Systematic Bias ◽  
Distribution Models ◽  
The Difference ◽  
Input Variables ◽  
The Impact

Abstract The earth radiation budget (ERB) is the difference between the solar absorbed flux and the terrestrial emitted flux. These fluxes are calculated from satellite measurements of outgoing shortwave (SW) and longwave (LW) radiances using empirical or theoretical models of the radiation anisotropy, which are called angular distribution models (ADMs). Owing to multidirectional measurement analyses and synergy with multispectral information at subpixel scale, the ADM developed for the NASA Clouds and the Earth’s Radiant Energy System (CERES) mission is presently the best knowledge and has to be taken into account for future ERB missions, such as the Indian–French Megha-Tropiques mission to be launched in 2010. This mission will carry an ERB instrument called the Scanner for Radiation Budget (ScaRaB). To prepare the algorithms for the ScaRaB ADM retrievals, the artificial neural network (ANN) method described by the CERES team has been adopted and improved by replacing the broadband (BB) radiances by narrowband (NB) radiances from the auxiliary channels of ScaRaB as input variables of the ANN. This article is restricted to the SW domain, the most critical case, and shows that the flux error is reduced by 60% compared to the former ERB Experiment–like model. The rms differences with the CERES fluxes are around 8.4 W m−2. ScaRaB/Megha-Tropiques measurements have a 4 times lower spatial resolution than those of the CERES/Tropical Rainfall Measuring Mission (TRMM). The impact of this spatial degradation has also been explored. There is a small systematic bias of about 1.5 W m−2 (or an absolute albedo error of 0.0015) and the rms differences are less than 3 W m−2; this is not significant compared to the overall error budget. For the radiance-to-flux conversion in the SW domain, the BB and NB ANN methods will be implemented in the ScaRaB/Megha-Tropiques data processing in order to provide SW flux estimates with an accuracy that is as consistent as possible with CERES results.

The Impact of Missing and Error-Prone Auxiliary Information on Sparse-Matrix Sub-Population Parameter Estimates

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 89-99 ◽  
Author(s):  
Leslie Rutkowski ◽  
Yan Zhou
Keyword(s):  
Sparse Matrix ◽  
Small Body ◽  
Auxiliary Information ◽  
Poor Quality ◽  
Quality Data ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Population Parameter ◽  
Conditioning Model ◽  
The Impact

Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient precision. As such, we systematically examine the limitations to current estimation methods used by these programs. Using a simulation study along with empirical results from the 2007 cycle of TIMSS, we show that a combination of missing and misclassified data in the conditioning model induces biases in sub-population achievement estimates, the magnitude and degree to which can be readily explained by data quality. Importantly, estimated biases in sub-population achievement are limited to the conditioning variable with poor-quality data while other sub-population achievement estimates are unaffected. Findings are generally in line with theory on missing and error-prone covariates. The current research adds to a small body of literature that has noted some of the limitations to sub-population estimation.

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

scholarly journals Global maps of aerosol single scattering albedo using combined CERES-MODIS retrieval

2021 ◽  
Author(s):  
Archana Devi ◽  
Sreedharan Krishnakumari Satheesh
Keyword(s):  
Climate Models ◽  
Radiant Energy ◽  
Energy System ◽  
Single Scattering ◽  
Global Scale ◽  
Single Scattering Albedo ◽  
Accurate Information ◽  
Climatic Impact ◽  
Aerosol Absorption ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Single Scattering Albedo (SSA) is a leading contributor to the uncertainty in aerosol radiative impact assessments. Therefore accurate information on aerosol absorption is required on a global scale. In this study, we have applied a multi-satellite algorithm to retrieve SSA using the concept of ‘critical optical depth.’ Global maps of SSA were generated following this approach using spatially and temporally collocated data from Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board Terra and Aqua satellites. The method has been validated using the data from aircraft-based measurements of various field campaigns. The retrieval uncertainty is ±0.03 and depends on both the surface albedo and aerosol absorption. Global mean SSA estimated over land and ocean is 0.93 and 0.97, respectively. Seasonal and spatial distribution of SSA over various regions are also presented. The global maps of SSA, thus derived with improved accuracy, provide important input to climate models for assessing the climatic impact of aerosols on regional and global scales.

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