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To explore the interactions among column processes in the Community Atmosphere Model (CAM), the single‐column version of CAM (SCAM) is integrated for 1000 days in radiative‐convective equilibrium (RCE) with tropical values of boundary conditions, spanning a parameter or configuration space of model physics versions (v5 vs. v6), vertical resolution (standard and 60 levels), sea surface temperature (SST), and some interpretation‐driven experiments. The simulated time‐mean climate is reasonable, near observations and RCE of a cyclic cloud‐resolving model. Updraft detrainment in the deep convection scheme produces distinctive grid‐scale structures in humidity and cloud, which also interact with radiative transfer processes. These grid artifacts average out in multi‐column RCE results reported elsewhere, illustrating the nuts‐and‐bolts interpretability that SCAM adds to the hierarchy of model configurations. Multi‐day oscillations of precipitation arise from descent of warm convection‐capping layers starting near the tropopause, eventually reset by a burst of convective deepening. Experiments reveal how these oscillations depend critically on an internal parameter that controls the number of neutral buoyancy levels allowed for determining cloud top and computing dilute convective available potential energy in the deep convection scheme, and merely modified a little by disabling cloud‐base radiation (heating of cloud base). This strong dependence of transient behavior in 1D on this parameter will be tested in the second part of this work, in which SCAM is coupled to a parameterized dynamics of two‐dimensional, linearized gravity wave, and in the 3D simulations in future study. Plain Language Summary: Atmospheric climate models are so complicated, with so many interacting processes, that their behaviors are hard to interpret and thus flaws are hard to fix. This study tries to address that difficulty by isolating the algorithms representing vertical physical processes within an air column (turbulence, clouds, and radiation), without allowing any wind to move and smear the features caused by those interacting processes. Two versions of a popular open‐source community model are compared in this one‐dimensional single‐column framework, along with modified versions. Results suggest some ways that the model can be understood and perhaps improved, but those hypotheses need to be tested in more complicated versions of the model, accounting for winds and a spherical planet and eventually all the other complications of Earth. Key Points: Radiative‐convective equilibrium occurs in the Single Column Atmospheric ModelThe simulated climate states feature grid artifacts of humidity and cloud that are contributed from deep convective updraft detrainmentMulti‐day oscillations occur spontaneously, and are modulated by number of neutral buoyancy levels allowed for determining final cloud top [ABSTRACT FROM AUTHOR]

This paper describes a new intermediate global atmosphere model in which synoptic and planetary dynamics including the advection of water vapor are explicit in 10 layers, the time-mean flow is centered near a realistic state through the use of carefully calibrated time-independent 3-D forcings, and temporal anomalies of convective tendencies of heat and moisture in each column are represented as a linear matrix acting on the anomalous temperature and moisture profiles. Currently, this matrix is Kuang's [2010] linear response function (LRF) of a cyclic convection-permitting model (CCPM) in equilibrium with specified atmospheric cooling (i.e., without radiation or WISHE interactions, so it conserves column moist static energy exactly). The goal of this effort is to cleanly test the role of convection's free-tropospheric moisture sensitivity in tropical waves, without incurring large changes of mean climate that confuse the interpretation of experiments with entrainment parameters in the convection schemes of full-physics GCMs. When the sensitivity to free-tropospheric moisture is multiplied by a factor ranging from 0 to 2, the model's variability ranges from: (1) moderately strong convectively coupled Kelvin waves with speeds near 20 m s-1; to (0) similar but much weaker waves; to (2) similar but stronger and slightly faster waves as the water vapor field plays an increasingly important role. Longitudinal structure in the model's time-mean tropical flow is not fully realistic, and does change significantly with matrix-coupled variability, but further work on editing the anomaly physics matrix and calibrating the mean state could improve this class of models. [ABSTRACT FROM AUTHOR]

Characteristics of, and fundamental differences between, the radiative‐convective equilibrium (RCE) climate states following the Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) protocols in the Community Atmosphere Model version 5 (CAM5) and version 6 (CAM6) are presented. This paper explores the characteristics of clouds, moisture, precipitation and circulation in the RCE state, as well as the tropical response to surface warming, in CAM5 and CAM6 with different parameterizations. Overall, CAM5 simulates higher precipitation rates that result in larger global average precipitation, despite lower outgoing longwave radiation compared to CAM6. Differences in the structure of clouds, particularly the amount and vertical location of cloud liquid, exist between the CAM versions and can, in part, be related to distinct representations of shallow convection and boundary layer processes. Both CAM5 and CAM6 simulate similar peaks in cloud fraction, relative humidity, and cloud ice, linked to the usage of a similar deep convection parameterization. These anvil clouds rise and decrease in extent in response to surface warming. More generally, extreme precipitation, aggregation of convection, and climate sensitivity increase with warming in both CAM5 and CAM6. This analysis provides a benchmark for future studies that explore clouds, convection, and climate in CAM with the RCEMIP protocols now available in the Community Earth System Model. These results are discussed within the context of realistic climate simulations using CAM5 and CAM6, highlighting the usefulness of a hierarchical modeling approach to understanding model and parameterization sensitivities to inform model development efforts. Plain Language Summary: Clouds, circulations and rainfall in the tropics play an important role in Earth's climate. However, global climate models differ in their representation of these features, contributing to uncertainty in future climate projections. One useful tool to better understand model differences and inform efforts to improve models is to analyze idealized configurations. We explore two different numerical representations of an idealized atmosphere relevant to tropical regions to determine the impact on the characteristics of clouds, rainfall and circulations as well as the tropical atmospheric response to warming. We show that our idealized models mirror differences in the low‐cloud structure in the deep tropics of more realistic models. This work also finds similarities between the two numerical representations, such as a decrease in the spatial extent of high altitude clouds with warming. As the surface is warmed, both versions also show increases in the clustering of clouds, the likelihood of extreme precipitation rates, and an estimate of how much warming would occur in response to a doubling of carbon dioxide. Key Points: A new radiative‐convective equilibrium (RCE) configuration is added to the official release of Community Earth System Model (CESM) to facilitate the use of Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) in the CESM hierarchyThe Community Atmosphere Model version 5 and Community Atmosphere Model version 6 (CAM6) RCEMIP climate states and variation across SST experiments are documented in the context of the CESM hierarchyDiffering parameterizations lead to a reduction of low‐level clouds in CAM6, consistent with differences in more realistic simulations [ABSTRACT FROM AUTHOR]

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations. Plain Language Summary: This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The data set of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We do not find a conclusive result for how cloud clustering changes as the climate warms. Key Points: Temperature, humidity, and clouds in radiative‐convective equilibrium vary substantially across modelsModels agree that self‐aggregation dries the atmosphere and reduces high cloudinessThere is no consistency in how self‐aggregation depends on warming [ABSTRACT FROM AUTHOR]

To understand the relationship between rain intensity and brightness temperature, Cloud Top Brightness Temperature (CTBT) derived from INSAT three hourly IR radiances having a resolution of 0.25 × 0.25 deg. is compared with corresponding TRMM PR Rain Rate (TPRR) for the Indian Summer Monsoon periods of 2007 and 2008. BT value ranges corresponding to events of various intensities of rain in the four major raining sub regions identified in Indian subcontinent and surrounding ocean are compared. The sub regions identified are (1) Head Bay of Bengal, (2) Central Indian land region, (3) Eastern Arabians Sea and West coast of India and (4) South West Indian Ocean. BT values are grouped into classes of 10°K bin width between 270 and 180°K. Number of occurrence of three classes of rain (light - >4.5 mm, moderate - 4.5–9 mm and heavy 9.0 mm and above cumulative for 3 h) belonging in each BT classes is calculated. It is observed that the three classes of rainfall have distinct characteristic BT ranges. This rain category - BT range relation has geographical (spatial) variability. This could be due to the variation in types of clouds prevalent in the sub regions considered. The present study improves the understanding of the structure and spatial variability of cloudiness and rainfall in and around Indian region during monsoon season. [ABSTRACT FROM AUTHOR]