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of how the radiative impacts vary with cloud type and cloud properties. Previous studies have presented comprehensive multiyear climatological descriptions of surface radiation measurements, cloud properties, and cloud radiative effects (CRE) from ground-based measurements at midlatitude ( Dong et al. 2005 , 2006 ; Liu et al. 2011 ) and Arctic sites ( Dong et al. 2010 ); no corresponding study of the tropical region using long-term ground-based measurements exists, however. The tropical western
of how the radiative impacts vary with cloud type and cloud properties. Previous studies have presented comprehensive multiyear climatological descriptions of surface radiation measurements, cloud properties, and cloud radiative effects (CRE) from ground-based measurements at midlatitude ( Dong et al. 2005 , 2006 ; Liu et al. 2011 ) and Arctic sites ( Dong et al. 2010 ); no corresponding study of the tropical region using long-term ground-based measurements exists, however. The tropical western
surface temperature change between two states). But given that the radiative effects of clouds are highly nonlinear, the traditional radiative kernel method is not suitable. Instead, cloud feedback has been obtained as a residual or estimated from changes in cloud radiative effect, while accounting for cloud masking effects, whereby clear-sky responses are diminished by the presence of clouds ( Soden et al. 2008 ). A novel technique for directly calculating cloud feedbacks was introduced by Zelinka
surface temperature change between two states). But given that the radiative effects of clouds are highly nonlinear, the traditional radiative kernel method is not suitable. Instead, cloud feedback has been obtained as a residual or estimated from changes in cloud radiative effect, while accounting for cloud masking effects, whereby clear-sky responses are diminished by the presence of clouds ( Soden et al. 2008 ). A novel technique for directly calculating cloud feedbacks was introduced by Zelinka
magnitude of the 3D effect (the difference in radiative fluxes between radiation calculations including and neglecting 3D transport) is dependent on the ratio of the area of cloud side to the total cloud cover. Therefore, cumulus clouds are of particular importance when considering 3D radiative effects: although when present they have a cloud cover of only around 0.25, cumulus regimes cover huge stretches of the tropical oceans. The myriad of ways that radiation can interact with a complex cloud field
magnitude of the 3D effect (the difference in radiative fluxes between radiation calculations including and neglecting 3D transport) is dependent on the ratio of the area of cloud side to the total cloud cover. Therefore, cumulus clouds are of particular importance when considering 3D radiative effects: although when present they have a cloud cover of only around 0.25, cumulus regimes cover huge stretches of the tropical oceans. The myriad of ways that radiation can interact with a complex cloud field
convection–radiation interaction and MJO development remain unexplained. In this study, we will examine and identify the processes and feedbacks arising from the cloud radiative effects and contributing to the development of MJO (leaving the propagation of MJO signal in a separate study). We show these processes and feedbacks using the observed MJO events that were recorded during the field campaign of DYNAMO/CINDY2011 ( Yoneyama et al. 2013 ). To identify these processes and feedbacks, we use a
convection–radiation interaction and MJO development remain unexplained. In this study, we will examine and identify the processes and feedbacks arising from the cloud radiative effects and contributing to the development of MJO (leaving the propagation of MJO signal in a separate study). We show these processes and feedbacks using the observed MJO events that were recorded during the field campaign of DYNAMO/CINDY2011 ( Yoneyama et al. 2013 ). To identify these processes and feedbacks, we use a
1. Introduction On average, clouds of various types cover roughly two-thirds of Earth’s surface, and cloud radiative effects (CRE) play a significant role in moderating Earth’s energy balance (e.g., Arking 1991 ; Mace et al. 2009 ; Stubenrauch et al. 2013 ). Reflection, scattering, and absorption of solar radiation by clouds reduces the global mean top-of-atmosphere (TOA) shortwave (SW) radiative flux by −46.6 W m −2 and enhances the mean longwave (LW) radiative flux by +29.5 W m −2
1. Introduction On average, clouds of various types cover roughly two-thirds of Earth’s surface, and cloud radiative effects (CRE) play a significant role in moderating Earth’s energy balance (e.g., Arking 1991 ; Mace et al. 2009 ; Stubenrauch et al. 2013 ). Reflection, scattering, and absorption of solar radiation by clouds reduces the global mean top-of-atmosphere (TOA) shortwave (SW) radiative flux by −46.6 W m −2 and enhances the mean longwave (LW) radiative flux by +29.5 W m −2
resolution, and Barker et al. (2015 , 2016) , who calculate the ICA bias using 2D cloud fields retrieved from CloudSat and CALIPSO . Here we discuss the magnitude of the bias that results from neglecting the 3D cloud radiative effects by making the ICA. We use large-eddy simulations (LES) to generate 3D cloud fields representing three canonical cloud regimes: shallow cumulus convection, stratocumulus, and deep convection. These cloud regimes are representative of the clouds typically found in the
resolution, and Barker et al. (2015 , 2016) , who calculate the ICA bias using 2D cloud fields retrieved from CloudSat and CALIPSO . Here we discuss the magnitude of the bias that results from neglecting the 3D cloud radiative effects by making the ICA. We use large-eddy simulations (LES) to generate 3D cloud fields representing three canonical cloud regimes: shallow cumulus convection, stratocumulus, and deep convection. These cloud regimes are representative of the clouds typically found in the
change? The impacts of aerosols on monsoons are well studied, with suggestions that anthropogenic aerosols may weaken and dry the South and East Asian monsoons ( Bollasina et al. 2011 ; Dong et al. 2019 ). But aside from aerosols, the extent to which the radiative effects of CO 2 , clouds, and water vapor are important for monsoons is unclear. In this study the radiation-locking method is used to isolate the effects of CO 2 forcing and “moist-radiative feedbacks” associated with clouds and water
change? The impacts of aerosols on monsoons are well studied, with suggestions that anthropogenic aerosols may weaken and dry the South and East Asian monsoons ( Bollasina et al. 2011 ; Dong et al. 2019 ). But aside from aerosols, the extent to which the radiative effects of CO 2 , clouds, and water vapor are important for monsoons is unclear. In this study the radiation-locking method is used to isolate the effects of CO 2 forcing and “moist-radiative feedbacks” associated with clouds and water
. 2019 ). Despite large differences in LWP and cloud amount, climate models show good agreement in cloud radiative effects ( Lauer and Hamilton 2013 ), suggesting that some amount of model tuning is used to achieve the constrained radiative fluxes. The tendency for GCMs to produce low clouds that are underestimated in amount and overly reflective has been well documented. The “too few, too bright” problem was coined by Nam et al. (2012) , who showed that models predict overly bright low clouds, even
. 2019 ). Despite large differences in LWP and cloud amount, climate models show good agreement in cloud radiative effects ( Lauer and Hamilton 2013 ), suggesting that some amount of model tuning is used to achieve the constrained radiative fluxes. The tendency for GCMs to produce low clouds that are underestimated in amount and overly reflective has been well documented. The “too few, too bright” problem was coined by Nam et al. (2012) , who showed that models predict overly bright low clouds, even
regions surrounding a cyclone. Allan and Soden (2007) showed that the variability of tropical precipitation in many models is also much more limited than observed. Wielicki et al. (2002) reported that the observed top-of-the-atmosphere (TOA) radiative energy budget in the tropics is more variable than represented by models. The restricted range of modeled variability may explain why models struggle to simulate the radiative effects of clouds and has motivated several studies focusing on
regions surrounding a cyclone. Allan and Soden (2007) showed that the variability of tropical precipitation in many models is also much more limited than observed. Wielicki et al. (2002) reported that the observed top-of-the-atmosphere (TOA) radiative energy budget in the tropics is more variable than represented by models. The restricted range of modeled variability may explain why models struggle to simulate the radiative effects of clouds and has motivated several studies focusing on
; Stephens et al. 1990 ; Khvorostyanov and Sassen 2002 ). However, a wide spectrum of ice clouds exist in nature, including optically thick or low-level ice clouds in addition to high and optically thin cirrus. Investigation of the radiative effects across the whole ice cloud spectrum has been lacking, largely because of insufficient global and vertically resolved observations of ice clouds. Previous studies on ice cloud radiative effects have focused either on certain types of ice clouds such as thin
; Stephens et al. 1990 ; Khvorostyanov and Sassen 2002 ). However, a wide spectrum of ice clouds exist in nature, including optically thick or low-level ice clouds in addition to high and optically thin cirrus. Investigation of the radiative effects across the whole ice cloud spectrum has been lacking, largely because of insufficient global and vertically resolved observations of ice clouds. Previous studies on ice cloud radiative effects have focused either on certain types of ice clouds such as thin
