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.

In the tropics, convective activity organizes at a range of spatial scales. This organization is affected by external forcing such as land-sea contrast, sea surface temperature (SST) gradients, and synoptic equatorial waves. The organization of convective activities has been intensively studied using an idealized framework of radiative-convective equilibrium (RCE) experiments (Wing et al., 2017). In these simulations, convective activity spontaneously organized into a single cell, even though there was no inhomogeneous external forcing or rotation. In earlier works involving two-dimensional x-z plane RCE experiments, convective activity was generally concentrated at one location with a wavenumber-one structure (

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<p>We conducted radiative convective equilibrium (RCE) experiments with varying domain size and sea surface temperature (SST) using the global cloud-system-resolving model NICAM (Satoh et al. 2014) to investigate the dependence of the maximum horizontal scale of the convective cluster on SST.</p><p>Convective self-aggregation in RCE simulations are widely studied, where convections spontaneously organize into a humid convective cluster even in the absence of inhomogeneities in boundary conditions and forcing. Previous studies show that convective self-organization does not occur when the domain size is too small, and that convective region become single-connected regions within a certain domain size, whereas when the domain size is large enough, multiple convective clusters are generated. In a previous study, although the maximum horizontal scale of the convective cluster was estimated to be about 4000 km, but the domain size of the simulation was smaller than the Earth surface, so it is not certain whether the preferable size of the convective aggregation exists over the realistic domain of the Earth. Moreover, it is now well understood how the horizontal size of the aggregation depends on SST; this aspect is relevant to understanding of the climate sensitivity.</p><p>The experiments were conducted with the NICAM simulations with switching off convective parameterization over a non-rotating spherical domain over the area of the region by varying the radius (the Earth radius R, R/2, R/4, R/8, and R/16). The horizontal uniform constant SST was changed as 295, 300, and 305K. The results show that there was a single convective cluster at a radius of R/4 or less, while there were multiple convective clusters at a radius of R/2 or more. The threshold for the transition between multiple convective clusters and a single convective cluster is found to be between R/4 and R/2. Physical variables such as vertical profiles of temperature and humidity gradually changes as the radius becomes larger, and converged at the radius R/2. For the SST dependency, the result robustly indicates that the maximum horizontal scale of the convection cluster is not monotonic with SST and it was largest for SST 300K.</p><p>As the domain size increases, the domain average moistens, and the boundary layer wind speed increases. Because the diabatic radiative cooling is constrained by the temperature and humidity structure, the surface evaporation and thus the surface wind speed must also be constrained with an upper limit; this is why the maximum horizontal scale exists and there are multiple convective clusters for the domain size larger than R/2. We also found that the moist static energy transport from the convective region decreases as the domain becomes larger, as pointed out by Patrizio and Randall (2019). The horizontal scale dependence of the convective cluster is related to two factors: the effect of the horizontal pressure difference in the boundary layer and the circulation structure of free troposphere. The energy budget analysis also explains the SST dependence of the maximum horizontal scale of the convective clusters.</p>

Abstract. Pre-launch simulated satellite data are useful to develop retrieval algorithms and to facilitate the rapid release of retrieval products after launch. Here we introduce the Japanese Aerospace Exploration Agency's (JAXA) EarthCARE synthetic data based on simulations using a 3.5 km horizontal-mesh global storm-resolving model. Global aerosol transport simulation results are added for aerosol retrieval developers. Synthetic data were produced corresponding to the four EarthCARE instrument sensors, namely a 94 GHz cloud-profiling radar (CPR), a 355 nm atmospheric lidar (ATLID), a seven-channel multispectral imager (MSI), and a broadband radiometer (BBR). JAXA EarthCARE synthetic data include a standard product with data for two orbits and a research product with shorter frames and more detailed instrument settings. In the research products, random errors in the CPR are considered based on the observation window, and noise in ATLID signals are added using a noise simulator. We consider the spectral misalignment effect of the visible and near-infrared MSI channels based on response functions depending on the angle from the nadir. We introduce plans for updating the JAXA EarthCARE synthetic data using large eddy simulation model data and the implementation of a three-dimensional radiation model. The JAXA EarthCARE synthetic data are available publicly.

We describe a collaborative analysis study involving numerical models and observation data for the Tokyo metropolitan area called the ULTra-sIte for Measuring Atmosphere of Tokyo Metropolitan Environment (ULTIMATE) project. It evaluates cloud microphysics schemes of numerical models using extensive observation data for the Tokyo area. We have access to various remote sensing and in situ data for the Tokyo area for operational and research purposes, particularly by enhancing observations for ground validation of the EarthCARE satellite, which is set to launch in 2023. This study focuses on using the dual-polarization Doppler weather radar, operated by the Japan Meteorological Agency. In terms of numerical models, we use and compare multi-models with single-moment (SM) and double-moment (DM) cloud microphysics schemes; the global non-hydrostatic model, Non-hydrostatic ICosahedral Atmospheric Model (NICAM) and the two regional models with A System based on a Unified Concept for Atmosphere (ASUCA) and Scalable Computing for Advanced Library and Environment (SCALE) are used. In particular, because NICAM can be used as both a global and a regional model, we can immediately test the improved scheme on a global scale for its effect on climatology and the evaluation of climate sensitivity. This paper introduces the methodology for evaluating numerical models by the dual-polarization radar using the observation simulator and compares numerical model results with observations. In particular, we evaluate the simulated rain in the lower level near the ground and the large ice particles just above the melting level. The simulation with NICAM-DM reproduces the comparable polarimetric radar characteristics of rain as the observation. However, the simulations with NICAM-SM and ASUCA-SM show larger raindrop sizes in stronger rain areas compared to the observation. For the larger ice particles just above the melting level around 4 km, NICAM-DM and ASUCA-SM overestimate particle sizes of graupel or snow, while NICAM-SM has a similar size of the ice particles. In future studies, we will use the present results to improve the cloud microphysics scheme, which will be tested on a global model.

We describe a collaborative analysis study involving numerical models and observation data for the Tokyo metropolitan area, called the ULTIMATE (ULTra-sIte for Measuring Atmosphere of Tokyo Metropolitan Environment) project. It evaluates cloud microphysics schemes of numerical models using extensive observation data for the Tokyo area. We have access to a variety of remote sensing and in-situ data for the Tokyo area for operational and research purposes, particularly by enhancing observations for ground validation of the EarthCARE satellite, which is set to launch in 2023. This study focuses on using the dual-polarization Doppler weather radar, operated by the Japan Meteorological Agency. In terms of numerical models, we use and compare multi-models with various cloud microphysics schemes, including a global non-hydrostatic model, NICAM (Non-hydrostatic Icosahedral Atmospheric Model), and the regional model of the Japan Meteorological Agency, ASUCA (A System based on a Unified Concept for Atmosphere), together with a regional model, SCALE (Scalable Computing for Advanced Library and Environment) developed by RIKEN. In particular, because NICAM can be used as both a global and a regional model, we can immediately test the improved scheme on a global scale for its effect on climatology and the evaluation of climate sensitivity.This paper introduces the methodology for evaluating numerical models by the dual-polarization radar using the observation simulator and compares numerical model results with observations. We found discrepancies in the signals of rain and graupel between the observation and the simulations. In future studies, we will use the present results to improve the cloud microphysics scheme, which will be tested on a global model.

Abstract. Pre-launch simulated data to be obtained from new sensors on a satellite is useful to develop retrieval algorithms and aid the rapid release of retrieval products after launch. Here we introduce Japanese Aerospace Exploration Agencies (JAXA) EarthCARE synthetic data based on simulations using a 3.5 km horizontal-mesh global storm-resolving model. Global aerosol transport simulation results are added for aerosol retrieval developers. Synthetic data were produced for four types of EarthCARE sensor: a 94 GHz cloud-profiling radar (CPR), a 355 nm atmospheric lidar (ATLID), a seven-channel multispectral imager (MSI), and a broadband radiometer (BBR). JAXA EarthCARE synthetic data include a standard product with data for two orbits and a research product with shorter frames and more detailed instrument settings. In the research products, random errors in the CPR are considered based on the observation window, and noise in ATLID signals are added using a noise simulator. We consider the spectral misalignment effect of the visible and near-infrared MSI channels based on response functions depending on the angle from nadir. We discuss plans for updating JAXA EarthCARE synthetic data using a large eddy simulation and implementation of a three-dimensional radiation model.