Increasing Model Resolution Research Articles

Small Sensitivity of the Simulated Climate of Tidally Locked Aquaplanets to Model Resolution

Abstract Tidally locked terrestrial planets around low-mass stars are the prime targets of finding potentially habitable exoplanets. Several atmospheric general circulation models have been employed to simulate their possible climates; however, model intercomparisons showed that there are large differences in the results of the models even when they are forced with the same boundary conditions. In this paper, we examine whether model resolution contributes to the differences. Using the atmospheric general circulation model ExoCAM coupled to a 50 m slab ocean, we examine three different horizontal resolutions (440 km × 550 km, 210 km × 280 km, and 50 km × 70 km in latitude and longitude) and three different vertical resolutions (26, 51, and 74 levels) under the same dynamical core and the same schemes of radiation, convection, and clouds. Among the experiments, the differences are within 5 K in global-mean surface temperature and within 0.007 in planetary albedo. These differences are from cloud feedback, water vapor feedback, and the decreasing trend of relative humidity with increasing resolution. Relatively small-scale downdrafts between upwelling columns over the substellar region are better resolved and the mixing between dry and wet air parcels and between anvil clouds and their environment are enhanced as the resolution is increased. These reduce atmospheric relative humidity and high-level cloud fraction, causing a lower clear-sky greenhouse effect, a weaker cloud longwave radiation effect, and subsequently a cooler climate with increasing model resolution. Overall, the sensitivity of the simulated climate of tidally locked aquaplanets to model resolution is small.

Eddy Kinetic Energy in the Arctic Ocean From a Global Simulation With a 1‐km Arctic

AbstractSimulating Arctic Ocean mesoscale eddies in ocean circulation models presents a great challenge because of their small size. This study employs an unstructured‐mesh ocean‐sea ice model to conduct a decadal‐scale global simulation with a 1‐km Arctic. It provides a basinwide overview of Arctic eddy energetics. Increasing model resolution from 4 to 1 km increases Arctic eddy kinetic energy (EKE) and total kinetic energy (TKE) by about 40% and 15%, respectively. EKE is the highest along main currents over topography slopes, where strong conversion from available potential energy to EKE takes place. It is high in halocline with a maximum typically centered in the depth range of 70–110 m, and in the Atlantic Water layer of the Eurasian Basin as well. The seasonal variability of EKE along the continental slopes of southern Canada and eastern Eurasian basins is similar, stronger in fall and weaker in spring.

Fourth-Order Conservative Transport on Overset Grids Using Multi-Moment Constrained Finite Volume Scheme for Oceanic Modeling

With an increase in model resolution, compact high-order numerical advection scheme can improve its effectiveness and competitiveness in oceanic modeling due to its high accuracy and scalability on massive-processor computers. To provide high-quality numerical ocean simulation on overset grids, we tried a novel formulation of the fourth-order multi-moment constrained finite volume scheme to simulate continuous and discontinuous problems in the Cartesian coordinate. Utilizing some degrees of freedom over each cell and derivatives at the cell center, we obtained a two-dimensional (2D) cubic polynomial from which point values on the extended overlap can achieve fourth-order accuracy. However, this interpolation causes a lack of conservation because the flux between the regions are no longer equal; thus, a flux correction is implemented to ensure conservation. A couple of numerical experiments are presented to evaluate the numerical scheme, which confirms its approximately fourth-order accuracy in conservative transportation on overset grid. The test cases reveal that the scheme is effective to suppress numerical oscillation in discontinuous problems, which may be powerful for salinity advection computing with a sharp gradient.

The vertical structure and spatial variability of lower-tropospheric water vapor and clouds in the trades

Abstract. Horizontal and vertical variability of water vapor is omnipresent in the tropics, but its interaction with cloudiness poses challenges for weather and climate models. In this study we compare airborne lidar measurements from a summer and a winter field campaign in the tropical Atlantic with high-resolution simulations to analyze the water vapor distributions in the trade wind regime, its covariation with cloudiness, and their representation in simulations. Across model grid spacing from 300 m to 2.5 km, the simulations show good skill in reproducing the water vapor distribution in the trades as measured by the lidar. An exception to this is a pronounced moist model bias at the top of the shallow cumulus layer in the dry winter season which is accompanied by a humidity gradient that is too weak at the inversion near the cloud top. The model's underestimation of water vapor variability in the cloud and subcloud layer occurs in both seasons but is less pronounced than the moist model bias at the inversion. Despite the model's insensitivity to resolution from hecto- to kilometer scale for the distribution of water vapor, cloud fraction decreases strongly with increasing model resolution and is not converged at hectometer grid spacing. The observed cloud deepening with increasing water vapor path is captured well across model resolution, but the concurrent transition from cloud-free to low cloud fraction is better represented at hectometer resolution. In particular, in the wet summer season the simulations with kilometer-scale resolution overestimate the observed cloud fraction near the inversion but lack condensate near the observed cloud base. This illustrates how a model's ability to properly capture the water vapor distribution does not necessarily translate into an adequate representation of shallow cumulus clouds that live at the tail of the water vapor distribution.

Reproducibility of Surface Wind and Tracer Transport Simulations over Complex Terrain Using 5-, 3-, and 1-km-Grid Models

AbstractThe reproducibility of surface wind and tracer transport simulations from high-resolution weather and transport models was studied over complex terrain in wintertime in Japan. The horizontal grid spacing was varied (5-, 3-, and 1-km grids), and radioactive cesium (Cs-137) from the Fukushima nuclear power plant was used as a tracer. Fukushima has complex terrain, such as mountains and valleys. The model results were validated by observations collected from the national networks of the automated meteorological data acquisition system and the hourly air pollution sampling system. The reproducibility depended on the model resolution, topographic complexity, and synoptic weather conditions. Higher model resolution led to higher reproducibility of surface winds, especially in mountainous areas when the Siberian winter monsoon was disturbed. In contrast, the model improvement was negligible or nonexistent over plain/coastal areas when the synoptic field was steady. The statistical scores of the tracer transport simulations often deteriorated as a result of small errors in the plume locations. However, the higher-resolution models advantageously performed better transport simulations in the mountainous areas because of the lower numerical diffusion and higher reproducibility of the mass flux. The reproducibility of the tracer distribution in the valley of the Fukushima mountainous region was dramatically improved with increasing model resolution. In the range of mesoscale model resolutions (commonly 1–10 km), it was concluded that a higher-resolution model is definitely recommended for tracer transport simulations over mountainous terrain.

Characteristics of Model Tropical Cyclone Climatology and the Large-Scale Environment

AbstractHere we explore the relationship between the global climatological characteristics of tropical cyclones (TCs) in climate models and the modeled large-scale environment across a large number of models. We consider the climatology of TCs in 30 climate models with a wide range of horizontal resolutions. We examine if there is a systematic relationship between the climatological diagnostics for the TC activity [number of tropical cyclones (NTC) and accumulated cyclone energy (ACE)] by hemisphere in the models and the environmental fields usually associated with TC activity, when examined across a large number of models. For low-resolution models, there is no association between a conducive environment and TC activity, when integrated over space (tropical hemisphere) and time (all years of the simulation). As the model resolution increases, for a couple of variables, in particular vertical wind shear, there is a statistically significant relationship in between the models’ TC characteristics and the environmental characteristics, but in most cases the relationship is either nonexistent or the opposite of what is expected based on observations. It is important to stress that these results do not imply that there is no relationship between individual models’ environmental fields and their TC activity by basin with respect to intraseasonal or interannual variability or due to climate change. However, it is clear that when examined across many models, the models’ mean state does not have a consistent relationship with the models’ mean TC activity. Therefore, other processes associated with the model physics, dynamical core, and resolution determine the climatological TC activity in climate models.

Impact of Ocean–Atmosphere Current Feedback on Ocean Mesoscale Activity: Regional Variations and Sensitivity to Model Resolution

AbstractOcean mesoscale eddies are characterized by rotating-like and meandering currents that imprint the low-level atmosphere. Such a current feedback (CFB) has been shown to induce a sink of energy from the ocean to the atmosphere, and consequently to damp the eddy kinetic energy (EKE), with an apparent regional disparity. In a context of increasing model resolution, the importance of this feedback and its dependence on oceanic and atmospheric model resolution arise. Using a hierarchy of quasi-global coupled models with spatial resolutions varying from 1/4° to 1/12°, the present study shows that the CFB induces a negative wind work at scales ranging from 100 to 1000 km, and a subsequent damping of the mesoscale activity by ~30% on average, independently of the model resolution. Regional variations of this damping range from ~20% in very rich eddying regions to ~40% in poor eddying regions. This regional modulation is associated with a different balance between the sink of energy by eddy wind work and the source of EKE by ocean intrinsic instabilities. The efficiency of the CFB is also shown to be a function of the surface wind magnitude: the larger the wind, the larger the sink of energy. The CFB impact is thus related to both wind and EKE. Its correct representation requires both an ocean model that resolves the mesoscale field adequately and an atmospheric model resolution that matches the ocean effective resolution and allows a realistic representation of wind patterns. These results are crucial for including adequately mesoscale ocean–atmosphere interactions in coupled general circulation models and have strong implications in climate research.

Importance of Spatial Resolution in Global Groundwater Modeling.

Global-scale gradient-based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady-state hydraulic heads simulated by two versions of the global groundwater model G3 M, at spatial resolutions of 5 arc-minutes (9 km) and 30 arc-seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low-resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global-scale groundwater models will not improve the simulation of the global freshwater system.

Simulating and Evaluating Atmospheric River‐Induced Precipitation Extremes Along the U.S. Pacific Coast: Case Studies From 1980–2017

AbstractAtmospheric rivers (ARs) are responsible for a majority of extreme precipitation and flood events along the U.S. West Coast. To better understand the present‐day characteristics of AR‐related precipitation extremes, a selection of nine most intense historical AR events during 1980–2017 is simulated using a dynamical downscaling modeling framework based on the Weather Research and Forecasting Model. We find that the chosen framework and Weather Research and Forecasting Model configuration reproduces both large‐scale atmospheric features—including parent synoptic‐scale cyclones—as well as the filamentary corridors of integrated vapor transport associated with the ARs themselves. The accuracy of simulated extreme precipitation maxima, relative to in situ and interpolated gridded observations, improves notably with increasing model resolution, with improvements as large as 40–60% for fine scale (3 km) relative to coarse‐scale (27 km) simulations. A separate set of simulations using smoothed topography suggests that much of these gains stem from the improved representation of complex terrain. Additionally, using the 12 December 1995 storm in Northern California as an example, we demonstrate that only the highest‐resolution simulations resolve important fine‐scale features—such as localized orographically forced vertical motion and powerful near hurricane‐force boundary layer winds. Given the demonstrated ability of a targeted dynamical downscaling framework to capture both local extreme precipitation and key fine‐scale characteristics of the most intense ARs in the historical record, we argue that such a configuration may be highly conducive to understanding AR‐related extremes and associated changes in a warming climate.

Joint inversion of surface and borehole magnetic data: A level-set approach

The need to improve the depth resolution of the magnetic susceptibility model recovered from surface magnetic data is a well-known challenge, and it becomes increasingly important as exploration moves to regions under cover and at great depths. Incorporating borehole magnetic data can be an effective means to achieve increased model resolution at depth. The recently developed level-set method for magnetic inversion provides a novel means for constructing the geometric shape of causative bodies and opens a new avenue for the joint inversion of surface and borehole magnetic data for the purpose of achieving improved depth resolution. We have developed an extension of the algorithm to the joint inversion and find that the level-set algorithm can resolve the configuration and spatial separation of complex magnetic sources using the information in the magnetic data from sparse boreholes. We further examine the use of borehole intersection information in estimating the crucially important susceptibility values within the context of level-set inversion and find that the susceptibility value can also be used as a probing parameter to assess the uncertainty in the spatial extent of the causative bodies. We determine that the modified level-set inversion leads to an effective means to image and delineate magnetic causative bodies with complex structure by combining the information from surface magnetic data, borehole magnetic data, and sparse drillhole intersection data.

Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution

Abstract. In this study the latest version of the MiKlip decadal hindcast system is analyzed, and the effect of an increased horizontal and vertical resolution on the prediction skill of the extratropical winter circulation is assessed. Four different metrics – the storm track, blocking, cyclone and windstorm frequencies – are analyzed in the North Atlantic and European region. The model bias and the deterministic decadal hindcast skill are evaluated in ensembles of five members in a lower-resolution version (LR, atm: T63L47, ocean: 1.5∘ L40) and a higher-resolution version (HR, atm: T127L95, ocean: 0.4∘ L40) of the MiKlip system based on the Max Planck Institute Earth System model (MPI-ESM). The skill is assessed for the lead winters 2–5 in terms of the anomaly correlation of the quantities' winter averages using initializations between 1978 and 2012. The deterministic predictions are considered skillful if the anomaly correlation is positive and statistically significant. While the LR version shows common shortcomings of lower-resolution climate models, e.g., a storm track that is too zonal and southward displaced as well as a negative bias of blocking frequencies over the eastern North Atlantic and Europe, the HR version counteracts these biases. Cyclones, i.e., their frequencies and characteristics like strength and lifetime, are particularly better represented in HR. As a result, a chain of significantly improved decadal prediction skill between all four metrics is found with the increase in the spatial resolution. While the skill of the storm track is significantly improved primarily over the main source region of synoptic activity – the North Atlantic Current – the other extratropical quantities experience a significant improvement primarily downstream thereof, i.e., in regions where the synoptic systems typically intensify. Thus, the skill of the cyclone frequencies is significantly improved over the central North Atlantic and northern Europe, the skill of the blocking frequencies is significantly improved over the Mediterranean, Scandinavia and eastern Europe, and the skill of the windstorms is significantly improved over Newfoundland and central Europe. Not only is the skill improved with the increase in resolution, but the HR system itself also exhibits significant skill over large areas of the North Atlantic and European sector for all four circulation metrics. These results are particularly promising regarding the high socioeconomic impact of European winter windstorms and blocking situations.

Modeling Arctic Boundary Layer Cloud Streets at Grey-zone Resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds, we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiagvik (formerly Barrow), Alaska, on 2 May 2013 and were observed by MODIS (the Moderate Resolution Imaging Spectroradiometer). The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain. We investigated the model-simulated mesoscale environment, horizontal and vertical cloud structures, boundary layer stability, and cloud properties, all of which were subsequently used to interpret the observed roll-cloud case. Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer. The clouds were stratiform-like in the mesoscale domain, but as the model resolution increased, roll-like structures, aligned along the wind field, appeared with ever smaller wavelengths. A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing. With fixed model grid spacing at 0.333 km, changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment, a stronger vertical water vapor gradient below the cloud layers, and the wavelengths of the rolls decreased slightly. In this study, only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Atmospheric Predictability: Revisiting the Inherent Finite-Time Barrier

Abstract The accepted idea that there exists an inherent finite-time barrier in deterministically predicting atmospheric flows originates from Edward N. Lorenz’s 1969 work based on two-dimensional (2D) turbulence. Yet, known analytic results on the 2D Navier–Stokes (N-S) equations suggest that one can skillfully predict the 2D N-S system indefinitely far ahead should the initial-condition error become sufficiently small, thereby presenting a potential conflict with Lorenz’s theory. Aided by numerical simulations, the present work reexamines Lorenz’s model and reviews both sides of the argument, paying particular attention to the roles played by the slope of the kinetic energy spectrum. It is found that when this slope is shallower than −3, the Lipschitz continuity of analytic solutions (with respect to initial conditions) breaks down as the model resolution increases, unless the viscous range of the real system is resolved—which remains practically impossible. This breakdown leads to the inherent finite-time limit. If, on the other hand, the spectral slope is steeper than −3, then the breakdown does not occur. In this way, the apparent contradiction between the analytic results and Lorenz’s theory is reconciled.

Advancing global storm surge modelling using the new ERA5 climate reanalysis

This study examines the implications of recent advances in global climate modelling for simulating storm surges. Following the ERA-Interim (0.75° × 0.75°) global climate reanalysis, in 2018 the European Centre for Medium-range Weather Forecasts released its successor, the ERA5 (0.25° × 0.25°) reanalysis. Using the Global Tide and Surge Model, we analyse eight historical storm surge events driven by tropical—and extra-tropical cyclones. For these events we extract wind fields from the two reanalysis datasets and compare these against satellite-based wind field observations from the Advanced SCATterometer. The root mean squared errors in tropical cyclone wind speed reduce by 58% in ERA5, compared to ERA-Interim, indicating that the mean sea-level pressure and corresponding strong 10-m winds in tropical cyclones greatly improved from ERA-Interim to ERA5. For four of the eight historical events we validate the modelled storm surge heights with tide gauge observations. For Hurricane Irma, the modelled surge height increases from 0.88 m with ERA-Interim to 2.68 m with ERA5, compared to an observed surge height of 2.64 m. We also examine how future advances in climate modelling can potentially further improve global storm surge modelling by comparing the results for ERA-Interim and ERA5 against the operational Integrated Forecasting System (0.125° × 0.125°). We find that a further increase in model resolution results in a better representation of the wind fields and associated storm surges, especially for small size tropical cyclones. Overall, our results show that recent advances in global climate modelling have the potential to increase the accuracy of early-warning systems and coastal flood hazard assessments at the global scale.

The impact of horizontal atmospheric resolution in modelling air–sea heat fluxes

AbstractClimate modes as simulated by global climate models are often found to be considerably weaker than are observed. One possibility is that coarse‐resolution climate models do not capture turbulent air–sea fluxes sufficiently. Ensemble experiments with the same atmospheric configuration of the Met Office Hadley Centre climate model, forced with observed sea‐surface temperatures (SST) and at three different horizontal model resolutions (approximately 130, 60 and 25 km), are used to test the sensitivity of air–sea surface heat and moisture fluxes. We find that, although global mean budgets at the three resolutions are very similar, substantial differences appear in regional air–sea flux patterns. Increased model resolution consistently enhances zonal‐mean air–sea fluxes in the mid–high latitudes while suppressing heat fluxes in the low latitudes and weakening the Hadley Circulation. In the North Atlantic, annual mean surface heat fluxes into the atmosphere along the Gulf Stream/North Atlantic Current and over the sub‐polar gyre can increase by up to 10 W/m2 when atmospheric model resolution increases from 130 to 60 km. In the Pacific, increased model resolution tends to weaken the Walker Circulation with increased heat fluxes from the east but markedly reduced fluxes from the western Pacific, leading to significantly improved precipitation over the tropical western Pacific and the Maritime Continent. Changes in air–sea heat fluxes come about mainly as a result of changed near‐surface ventilation. Generally, increasing resolution strengthens surface winds and reduces specific humidity in the mid–high latitudes while weakening surface winds over the Tropics and subtropics.

Enhanced large-scale atmospheric flow interaction with ice sheets at high model resolution

Abstract The development in supercomputing power allows running full-complexity Earth System Models (ESM) at increasingly higher spatial resolutions on a global scale. We show here a recent example where increased model resolution leads to a fundamentally different large-scale fluid dynamical adjustment of the mean wind pattern to the presence of an ice sheet over Europe compared to a coarse resolution simulation. While the higher resolution allows for a more realistic representation of atmospheric flow interaction with complex topographic features, the interpretation and prediction of the model results with a stronger bottom-up mechanical and thermal forcing on the atmosphere becomes increasingly difficult to be studied within a fully coupled model. We emphasize that interdisciplinary approaches should be pursued where the experience from engineering approaches of studying flow around objects and the influence of boundary-layer processes can help to disentangle the complexity within ESM. Ultimately, such engineering approaches will add a more fundamental theoretical understanding and prediction of expected flow interactions and will help to design full-complexity atmospheric model experiments accordingly.

Resolving Sahelian thunderstorms improves mid-latitude weather forecasts

The summertime West African Sahel has the worldwide highest degree of thunderstorm organisation into long-lived, several hundred-kilometre elongated, fast propagating systems that contribute 90% to the annual rainfall. All current global weather prediction and climate models represent thunderstorms using simplified parameterisation schemes which deteriorates the modelled distribution of rainfall from individual storms and the entire West African monsoon circulation. It is unclear how this misrepresentation of Sahelian convection affects forecasts globally. Our study is the first to demonstrate how a computationally feasible increase of model resolution over West Africa – allowing to avoid convection parameterisation – yields a better representation of organised convection in the Sahel and of moisture within the monsoon system, ultimately improving 5–8-day tropical and mid-latitude weather forecasts. We advocate an operational use of a modelling strategy similar to the one presented here for a cost-effective improvement of global weather prediction and potentially even (sub-)seasonal and climate simulations.

Simulating Canadian Arctic Climate at Convection-Permitting Resolution

Inadequate representation and parameterization of sub-grid scale features and processes are one of the main sources for uncertainties in regional climate change projections, particularly for the Arctic regions where the climate change signal is amplified. Increasing model resolution to a couple of kilometers will be helpful in resolving some of these challenges, for example to better simulate convection and refined land heterogeneity and thus land–atmosphere interactions. A set of multi-year simulations has been carried out for the Canadian Arctic domain at 12 km and 3 km resolutions using limited-area version of the global environmental multi-scale (GEM) model. The model is integrated for five years driven by the fifth generation of the European Centre for medium-range weather forecast reanalysis (ERA-5) at the lateral boundaries. The aim of this study is to investigate the role of horizontal model resolution on the simulated surface climate variables. Results indicate that although some aspects of the seasonal mean values are deteriorated at times, substantial improvements are noted in the higher resolution simulation. The representation of extreme precipitation events during summer and the simulation of winter temperature are better captured in the convection-permitting simulation. Moreover, the observed temperature–extreme precipitation scaling is realistically reproduced by the higher resolution simulation. These results advocate for the use of convective-permitting resolution models for simulating future climate projections over the Arctic to support climate impact assessment studies such as those related to engineering applications and where high spatial and temporal resolution are beneficial.

Recent Progress in Numerical Atmospheric Modeling in China

This review summarizes the scientific and technical progress in atmospheric modeling in China since 2011, including the dynamical core, model physics, data assimilation, ensemble forecasting, and model evaluation strategies. In terms of the dynamical core, important efforts have been made in the improvement of the existing model formulations and in exploring new modeling approaches that can better adapt to massively parallel computers and global multiscale modeling. With regard to model physics, various achievements in physical representations have been made, especially a trend toward scale-aware parameterization for accommodating the increase of model resolution. In the field of data assimilation, a 4D-Var system has been developed and is operationally used by the National Meteorological Center of China, and its performance is promising. Furthermore, ensemble forecasting has played a more important role in operational forecast systems and progressed in many fundamental techniques. Model evaluation strategies, including key performance metrics and standardized experimental protocols, have been proposed and widely applied to better understand the strengths and weaknesses of the systems, offering key routes for model improvement. The paper concludes with a concise summary of the status quo and a brief outlook in terms of future development.

Precipitation Characteristics in the Community Atmosphere Model and Their Dependence on Model Physics and Resolution

AbstractPrecipitation amount (A), frequency (F), intensity (I), and duration (D) are important properties of precipitation, but their estimates are sensitive to data resolution. This study investigates this resolution dependence, and the influences of different model physics, by analyzing simulations by the Community Atmospheric Model (CAM) version 4 (CAM4) and version 5 (CAM5) with varying grid sizes from ~0.25 to 2.0°. Results show that both CAM4 and CAM5 greatly overestimate F and D but underestimate I at all resolutions, despite realistic A. These biases partly result from too much parameterized (convective) precipitation with high F and D but low I. Different cloud microphysics schemes contribute to the precipitation differences between CAM4 and CAM5. The A, F, I, and D of convective and nonconvective precipitation react differently to grid‐size decreases, leading to the large decreases in F and D but increases in the I for total precipitation as model resolution increases. This resolution dependence results from the increased probability of precipitation over a larger area (area aggregation effect, which is smaller than in observations) and the varying performance of model physics under changing resolution (model adjustment effect), which roughly enhances the aggregation‐induced dependence. Finer grid sizes not only increase resolved precipitation, which has higher intensity and thus improves overall precipitation intensity in CAM, but also reduce the area aggregation effect. Thus, the long‐standing drizzling problem in climate models may be mitigated by increasing model resolution and modifying model physics to suppress parameterized convective precipitation and enhance resolved nonconvective precipitation.