Advances in Geostationary-Derived Longwave Fluxes for the CERES Synoptic (SYN1deg) Product

Doelling, David R.; Sun, Moguo; Nguyen, L.; Nordeen, Michele L.; Haney, Conor O.; Keyes, D. F.; Mlynczak, Pamela E.

doi:10.1175/jtech-d-15-0147.1

Cited by 175 publications

(132 citation statements)

References 33 publications

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“…in detail. Future studies will require a recalculation LUT that reflects the characteristics of the surface and clouds and should be periodically corrected by long-term observed broadband radiation [5,66].…”

Section: Discussionmentioning

confidence: 99%

Retrieval of Reflected Shortwave Radiation at the Top of the Atmosphere Using Himawari-8/AHI Data

et al. 2018

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This study developed a retrieval algorithm for reflected shortwave radiation at the top of the atmosphere (RSR). This algorithm is based on Himawari-8/AHI (Advanced Himawari Imager) whose sensor characteristics and observation area are similar to the next-generation Geostationary Korea Multi-Purpose Satellite/Advanced Meteorological Imager (GK-2A/AMI). This algorithm converts the radiance into reflectance for six shortwave channels and retrieves the RSR with a regression coefficient look-up-table according to geometry of the solar-viewing (solar zenith angle, viewing zenith angle, and relative azimuth angle) and atmospheric conditions (surface type and absence/presence of clouds), and removed sun glint with high uncertainty. The regression coefficients were calculated using numerical experiments from the radiative transfer model (SBDART), and ridge regression for broadband albedo at the top of the atmosphere (TOA albedo) and narrowband reflectance considering anisotropy. The retrieved RSR were validated using Terra, Aqua, and S-NPP/CERES data on the 15th day of every month from July 2015 to February 2017. The coefficient of determination (R 2 ) between AHI and CERES for scene analysis was higher than 0.867 and the Bias and root mean square error (RMSE) were −21.34-5.52 and 51.74-59.28 Wm −2 . The R 2 , Bias, and RMSE for the all cases were 0.903, −2.34, and 52.12 Wm −2 , respectively.

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Section: Discussionmentioning

confidence: 99%

Retrieval of Reflected Shortwave Radiation at the Top of the Atmosphere Using Himawari-8/AHI Data

et al. 2018

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“…Observations 2.1.1. CERES The Clouds and the Earth's Radiant Energy System (CERES) Ed4a SYN1deg data set contains TOA radiative fluxes, surface radiative fluxes, and cloud fraction retrievals extending from July 2002 to present (with a 6-month processing lag) at 1°× 1°spatial resolution and 1-hourly temporal resolution (Doelling et al, 2013(Doelling et al, , 2016Loeb et al, 2009;Minnis et al, 2011;Wielicki et al, 1996).…”

Section: Datamentioning

confidence: 99%

Sensitivity of the Amazonian Convective Diurnal Cycle to Its Environment in Observations and Reanalysis

2018

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Atmospheric model parameterizations of tropical deep convection struggle to reproduce the observed diurnal variability of convection in the Amazon leading to climatological biases in the energy budget and water cycle. To identify the physical process contributions to these biases, we analyze the relationships between the convective diurnal cycle and atmosphere state variables relevant to convection in the Amazon using satellite observations and reanalysis data sets for wet and dry seasons between 2002 and 2016 and two Green Ocean Amazon periods. The analysis first stratifies the diurnal cycle into convective and nonconvective days using a daily maximum rain rate threshold of 0.5 mm/hr. Second, the population of days is constrained by requiring reanalysis and observations to agree on the occurrence of convective rain rates, controlling for frequency‐dependent biases in convection. The model‐generated precipitation phase in Modern‐Era Retrospective Analysis for Research and Applications‐2 is closer to observations than ERA during 2002–2016, which exhibits a systematic noontime bias and exaggerated diurnal amplitude. Despite the systematic noontime precipitation bias, ERA produces better agreement with Green Ocean Amazon observations due to the frequent midmorning arrival of the coastal front acting to shift the observed diurnal cycle closer to noon. Model disagreement between middle‐tropospheric vertical velocity is largest overnight during the dissipation stage of convection, acting to sustain biases through radiative effects. Specifically, the slower dissipation of convection in Modern‐Era Retrospective Analysis for Research and Applications‐2 acts to reduce morning surface fluxes and increase convective inhibition, whereas enhanced nocturnal midtropospheric subsidence and higher boundary layer humidity in ERA reduce morning convective inhibition leading to an earlier initiation of afternoon deep convection.

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“…Global EOR observations, such as those from the Clouds and the Earth's Radiant Energy System (CERES) instrument (Wielicki et al, 1996), provide complete coverage but are not used in this study mainly due to their lack of diurnal sampling from low-Earth sun-synchronous orbits. Substantial efforts have been applied to interpolate between the diurnal gaps in CERES sampling 120 (Doelling et al, 2013;2016) but these products do not match the high temporal resolution of the model data required for thorough investigations of the diurnal cycle. Observations from the Scanner for Radiation Budget (ScaRaB) instrument are capable of capturing long-term averaged diurnal variability due to the drifting orbit of the Megha-Tropiques satellite (Viollier and Raberanto, 2010), but are limited to the inner tropics due to the very low-inclination of the orbit and are therefore also not appropriate.…”

Section: Supporting Satellite Datasetsmentioning

confidence: 99%

Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model

Gristey¹,

Gurney²,

Morcrette³

et al. 2018

Preprint

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Abstract.A globally-complete, high-temporal resolution and multiple-variable approach is employed to analyse the diurnal cycle of Earth's outgoing energy flows. This is made possible via the use of Met Office model output for September 2010 that is assessed alongside regional satellite observations throughout. Principal component analysis applied to the longwave component of modelled outgoing radiation reveals dominant diurnal patterns related to land surface heating and convective cloud development, respectively explaining 68.5 % and 16.0 % of the variance at the global scale. The total variance explained 15 by these first two patterns is markedly less than previous regional estimates from observations, and this analysis suggests that around half of the difference relates to the lack of global coverage in the observations. The first pattern is strongly and simultaneously coupled to the land surface temperature diurnal variations. The second pattern is strongly coupled to the cloud water content and height diurnal variations, but lags the cloud variations by several hours. We suggest that the mechanism controlling the delay is a moistening of the upper troposphere due to the evaporation of anvil cloud. The shortwave component 20 of modelled outgoing radiation, analysed in terms of albedo, exhibits a very dominant pattern explaining 88.4 % of the variance that is related to the angle of incoming solar radiation, and a second pattern explaining 6.7 % of the variance that is related to compensating effects from convective cloud development and marine stratocumulus cloud dissipation. Similar patterns are found to exist in regional satellite observations. The first pattern is controlled by changes in surface and cloud albedo, and Rayleigh and aerosol scattering. The second pattern is strongly coupled to the diurnal variations in both cloud water content 25 and height in convective regions but only cloud water content in marine stratocumulus regions, with substantially shorter lag times compared with the longwave counterpart. This indicates that the shortwave radiation response to diurnal cloud development and dissipation is more rapid, which is found to be robust in the regional satellite observations. These global, diurnal radiation patterns and their coupling with other geophysical variables demonstrate the process level understanding that can be gained using this approach and highlight a need for global, diurnal observing systems for Earth outgoing radiation in 30 the future.Atmos. Chem. Phys. Discuss., https://doi

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Advances in Geostationary-Derived Longwave Fluxes for the CERES Synoptic (SYN1deg) Product

Cited by 175 publications

References 33 publications

Retrieval of Reflected Shortwave Radiation at the Top of the Atmosphere Using Himawari-8/AHI Data

Retrieval of Reflected Shortwave Radiation at the Top of the Atmosphere Using Himawari-8/AHI Data

Sensitivity of the Amazonian Convective Diurnal Cycle to Its Environment in Observations and Reanalysis

Insights into the diurnal cycle of global Earth outgoing radiation using a numerical weather prediction model

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