Clouds and the Earth&amp;rsquo;s Radiant Energy System (CERES) Data Products for Climate Research

Kato, Seiji; Loeb, Norman G.; Rutan, David A.

doi:10.2151/jmsj.2015-048

Cited by 14 publications

(8 citation statements)

References 106 publications

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“…We are able to compare satellite data products such as DARDAR directly with the GSRM output in a statistical sense. Unfortunately, satellite sampling of microphysical properties is difficult and local radiative fluxes (and heating) can only be determined by model construction using satellite constraints (see, e.g., KATO et al., 2015). In situ aircraft measurements taken when satellite data is also available can provide meaningful comparisons of model microphysics and radiation simultaneously, but such aircraft measurements are limited (see Bucci et al., 2020, for a recent effort to make such measurements).…”

Section: Summary and Discussionmentioning

confidence: 99%

Tropical Cirrus in Global Storm‐Resolving Models: 2. Cirrus Life Cycle and Top‐of‐Atmosphere Radiative Fluxes

Turbeville

Nugent

Ackerman

et al. 2022

Earth and Space Science

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High clouds in the tropics have been difficult to reproduce in global climate models (GCMs) because of their complex microphysics and radiative properties (e.g., Del Genio, 2012;Stephens, 2005). Proper representation of the properties of tropical cirrus, especially cloud amount and hydrometeor distribution, is a key issue for improving GCMs (e.g., Inoue et al., 2010;Stephens, 2005;Zelinka et al., 2012). GCMs generally have a low spatial resolution, which is unable to explicitly represent convection and the subsequent tropical cloud life cycle. Diverse convective and ice microphysical parameterizations lead to large differences between GCMs in the ice cloud population (Del Genio, 2012). This is the second of two papers comparing the formation and properties of tropical cirrus in relation to deep convection in several high-resolution global storm-resolving models (GSRMs). Nugent et al. (2022) (hereafter Part I) focuses on deep convection and its role as a source of ice and vapor for cirrus formation. Here, we compare the simulated ice cloud populations with satellite observations, interpreting them in terms of an aggregate cirrus life cycle.As noted in Part I, GSRMs are attractive for modeling tropical cirrus. Unlike conventional climate models with horizontal grid spacings of 25-200 km, GSRMs have sub-5 km grid spacing that enables them to explicitly simulate deep convection and its detrainment of ice into the upper troposphere and better represent the mesoscale

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Section: Summary and Discussionmentioning

confidence: 99%

Tropical Cirrus in Global Storm‐Resolving Models: 2. Cirrus Life Cycle and Top‐of‐Atmosphere Radiative Fluxes

Turbeville

Nugent

Ackerman

et al. 2022

Earth and Space Science

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“…The CERES project as a successor to Earth Radiation Budget Experiment (ERBE) has been providing radiative flux components from 2000 to till date [6,43,122]. CERES program focused on measuring outgoing longwave radiation (OLR) radiances and reflected solar radiances to an accuracy of 1% and 2%, respectively.…”

Section: Ceres/modis (Cm)mentioning

confidence: 99%

“…The ERBE [5,6] program provided significant information about the energetics and the effects of clouds in modulating the energy balance [31,82]. The CERES project conceived as a successor to ERBE to compile a data record for the investigation of interannual variations of climate [31,43,122]. In the present study, we have used daily averaged CM observed Geostationary enhanced, temporally interpolated surface radiative fluxes for all-sky conditions (version 3) data of Q S and Q L .…”

Section: Ceres/modis (Cm)mentioning

confidence: 99%

Evaluation of surface shortwave and longwave downwelling radiations over the global tropical oceans

Thandlam

Rahaman

2019

SN Appl. Sci.

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In the present study, daily downwelling shortwave (Q S ) and longwave radiation (Q L ) data from one satellite and two hybrid products have been evaluated using Global Tropical Moored Buoy Array during 2001-2009 in the tropical oceans. Daily satellite data are used from the Clouds and Earth's Radiant Energy System (CERES) program. Data are obtained using Moderate Resolution Imaging Spectroradiometer (MODIS) (CM) aboard the Terra and Aqua satellites. Coordinated Ocean Research Experiments (CORE-II) and Tropical Flux data (TropFlux) are the other two hybrid products used in this study.The analysis shows that majority of Q S observations as well as derived products lie in 200-300 Wm −2 range in all the three tropical oceans. Both Q S and Q L in all products overestimated the majority of the observations. Yet, they underestimated the lower (0-100 Wm −2 ) values in Q S and higher (300-440 Wm −2 ) values in Q L . Majority of the Q L observations lie within 390-420 Wm −2 range, and CM slightly overestimated this observed distribution in the Pacific and the Atlantic Oceans. But, majority of the observations in the Indian Ocean lie within 420-450 Wm −2 range. This implies that the tropical Indian Ocean receives 30 Wm −2 more energy as compared to the tropical Pacific and the Atlantic in the form of downwelling longwave radiation. Daily observed Q S shows dominant seasonal cycle over the central, the eastern Pacific and the eastern Atlantic. On the other hand, the western Pacific, the central Atlantic and the Indian Oceans show intraseasonal variations. All products show this variation with high root-mean-square error (RMSE) values (Q S and Q L ) over the Indian Ocean than in the Pacific and the Atlantic Oceans. Downwelling radiation from CORE-II shows highest RMSE (for both Q S and Q L ) with least correlation coefficient (CC), and TropFlux has lowest RMSE and highest CC among all products in all three tropical oceans. CM has intermediate values of standard deviation, CC and RMSE. These results are not seasonally dependent, since the seasonal statistics are consistent with seasonal changes. Assuming that the SST is only driven by the downwelling shortwave and longwave fluxes, the errors associated with monthly SST can be as large as 0.2-0.3 (0.1-0.2) °C associated with errors in Q S (Q L ). Both Q S and Q L in CORE-II have lower spatial variability as compared to other datasets. Q L in the tropical oceans shows seasonal spatial variability determined by intertropical convergence zone positions. This variability does not change significantly over the Pacific and the Atlantic Oceans. The summer and winter monsoon patterns in the Indian Ocean guide the Q L variability. Opposite to Q S , higher Q L values have lower variability.Thus, this study aims at finding better radiation dataset to use in the numerical models and deduce that satellite data could be an alternative to existing reanalysis products.

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“…Used are the global surface flux data for total sky condition of Clouds with the Earth's Radiant Energy System SYN1deg‐day which are described as “The Synoptic Radiative Fluxes and Clouds (SYN1deg‐Day)” products that contain a day of space and time averaged Clouds with the Earth's Radiant Energy System geostationary enhanced temporally interpolated data (Kato et al, ). The 1° regional fluxes are daily averages from the Synoptic Radiative Fluxes and Clouds (SYN1deg‐1Hour) product.…”

Section: Datamentioning

confidence: 99%

Evaluating Surface Radiation Fluxes Observed From Satellites in the Southeastern Pacific Ocean

Pinker

Zhang

Weller

et al. 2018

Geophysical Research Letters

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This study is focused on evaluation of current satellite and reanalysis estimates of surface radiative fluxes in a climatically important region. It uses unique observations from the STRATUS Ocean Reference Station buoy in a region of persistent marine stratus clouds 1,500 km off northern Chile during 2000–2012. The study shows that current satellite estimates are in better agreement with buoy observations than model outputs at a daily time scale and that satellite data depict well the observed annual cycle in both shortwave and longwave surface radiative fluxes. Also, buoy and satellite estimates do not show any significant trend over the period of overlap or any interannual variability. This verifies the stability and reliability of the satellite data and should make them useful to examine El Niño–Southern Oscillation variability influences on surface radiative fluxes at the STRATUS site for longer periods for which satellite record is available.

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Clouds and the Earth’s Radiant Energy System (CERES) Data Products for Climate Research

Cited by 14 publications

References 106 publications

Tropical Cirrus in Global Storm‐Resolving Models: 2. Cirrus Life Cycle and Top‐of‐Atmosphere Radiative Fluxes

Tropical Cirrus in Global Storm‐Resolving Models: 2. Cirrus Life Cycle and Top‐of‐Atmosphere Radiative Fluxes

Evaluation of surface shortwave and longwave downwelling radiations over the global tropical oceans

Evaluating Surface Radiation Fluxes Observed From Satellites in the Southeastern Pacific Ocean

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