scholarly journals CAM6 simulation of mean and extreme precipitation over Asia: sensitivity to upgraded physical parameterizations and higher horizontal resolution

2019 ◽  
Vol 12 (8) ◽  
pp. 3773-3793 ◽  
Author(s):  
Lei Lin ◽  
Andrew Gettelman ◽  
Yangyang Xu ◽  
Chenglai Wu ◽  
Zhili Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Southern China ◽  
Northern China ◽  
Precipitation Variability ◽  
Horizontal Resolution ◽  
Model Version ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Physical Parameterizations

Abstract. The Community Atmosphere Model version 6 (CAM6), released in 2018 as part of the Community Earth System Model version 2 (CESM2), is a major upgrade over the previous CAM5 that has been used in numerous global and regional climate studies. Since CESM2–CAM6 will participate in the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6) and is likely to be adopted in many future studies, its simulation fidelity needs to be thoroughly examined. Here we evaluate the performance of a developmental version of the Community Atmosphere Model with parameterizations that will be used in version 6 (CAM6α), with a default 1∘ horizontal resolution (0.9∘×1.25∘, CAM6α-1∘) and a high-resolution configuration (approximately 0.25∘, CAM6α-0.25∘), against various observational and reanalysis datasets of precipitation over Asia. CAM6α performance is compared with CAM5 at default 1∘ horizontal resolution (CAM5-1∘) and a high-resolution configuration at 0.25∘ (CAM5-0.25∘). With the prognostic treatment of precipitation processes and the new microphysics module, CAM6α is able to better simulate climatological mean and extreme precipitation over Asia, better capture the heaviest precipitation events, better reproduce the diurnal cycle of precipitation rates over most of Asia, and better simulate the probability density distributions of daily precipitation over Tibet, Korea, Japan and northern China. Higher horizontal resolution in CAM6α improves the simulation of mean and extreme precipitation over northern China, but the performance degrades over the Maritime Continent. Moisture budget diagnosis suggests that the physical processes leading to model improvement are different over different regions. Both upgraded physical parameterizations and higher horizontal resolution affect the simulated precipitation response to the internal variability of the climate system (e.g., Asian monsoon variability, El Niño–Southern Oscillation – ENSO, Pacific Decadal Oscillation – PDO), but the effects vary across different regions. For example, higher horizontal resolution degrades the model performance in simulating precipitation variability over southern China associated with the East Asian summer monsoon. In contrast, precipitation variability associated with ENSO improves with upgraded physical parameterizations and higher horizontal resolution. CAM6α-0.25∘ and CAM6α-1∘ show an opposite response to the PDO over southern China. Basically, the response to increases in horizontal resolution is dependent on the CAM version.

scholarly journals CAM6 simulation of mean and extreme precipitation over Asia: Sensitivity to upgraded physical parameterizations and higher horizontal resolution

2019 ◽  
Author(s):  
Lei Lin ◽  
Andrew Gettelman ◽  
Yangyang Xu ◽  
Chenglai Wu ◽  
Zhili Wang ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Southern China ◽  
Northern China ◽  
Precipitation Variability ◽  
Horizontal Resolution ◽  
Modeling Framework ◽  
Model Version ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Physical Parameterizations

Abstract. The Community Atmosphere Model version 6 (CAM6) released in 2018, as part of the Community Earth System Model version 2 (CESM2) modeling framework, is a major upgrade over the previous CAM5 that has been used in numerous global and regional climate studies in the past six years. Since CESM2/CAM6 will participate in the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6) and is likely to be adopted in many future studies, its simulation fidelity needs to be thoroughly examined. Here we evaluate the performance of a developmental version of the Community Atmosphere Model with parameterizations that will be used in CMIP6 (CAM6α) with the default 1º horizontal resolution (0.9º × 1.25º, CAM6α-1º) and a higher resolution simulation (approximately 0.25º, CAM6α-0.25º), against various precipitation observational datasets over Asia. The CAM6α performance is also compared with CAM5 with the default 1º horizontal resolution (CAM5-1º). With the prognostic treatment of precipitation processes (which is missing in CAM5) and the new microphysics module, CAM6 is able to better simulate climatological mean and extreme precipitation over Asia, to better capture the heaviest precipitation events, to reproduce the diurnal cycle of precipitation rates over most of Asia, and to better simulate the probability density distributions of daily precipitation over Tibet, Korea, Japan and Northern China. Higher horizontal resolution in CAM6α improves simulations of mean and extreme precipitation over mountainous Sichuan and Northern China, but the performance degrades over the Maritime continent. Further diagnosis on moisture budget suggests that the physical processes leading to model improvement are different over different regions. Both upgraded physical parameterizations and higher horizontal resolution affect the precipitation response to internal variability of ocean and atmosphere (e.g. Asian monsoon index, ENSO, PDO), but the effects vary across different regions. Higher horizontal resolution degrades the model performance in simulating precipitation variability associated with the East Asian summer monsoon in the middle and lower reaches of the Yangtze River in China. The precipitation variability associated with ENSO gets better with upgraded physical parameterizations and higher horizontal resolution. Higher horizontal resolution, however, induces an opposite response to PDO in CAM6 over Southern China.

scholarly journals Global Radiative–Convective Equilibrium in the Community Atmosphere Model, Version 5

2015 ◽  
Vol 72 (5) ◽  
pp. 2183-2197 ◽  
Author(s):  
Kevin A. Reed ◽  
Brian Medeiros ◽  
Julio T. Bacmeister ◽  
Peter H. Lauritzen
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
General Circulation Models ◽  
Tropical Climate ◽  
Horizontal Resolution ◽  
Grid Spacing ◽  
Model Version ◽  
Extreme Precipitation Events ◽  
Community Atmosphere Model ◽  
Atmosphere Model

Abstract In the continued effort to understand the climate system and improve its representation in atmospheric general circulation models (AGCMs), it is crucial to develop reduced-complexity frameworks to evaluate these models. This is especially true as the AGCM community advances toward high horizontal resolutions (i.e., grid spacing less than 50 km), which will require interpreting and improving the performance of many model components. A simplified global radiative–convective equilibrium (RCE) configuration is proposed to explore the implication of horizontal resolution on equilibrium climate. RCE is the statistical equilibrium in which the radiative cooling of the atmosphere is balanced by heating due to convection. In this work, the Community Atmosphere Model, version 5 (CAM5), is configured in RCE to better understand tropical climate and extremes. The RCE setup consists of an ocean-covered Earth with diurnally varying, spatially uniform insolation and no rotation effects. CAM5 is run at two horizontal resolutions: a standard resolution of approximately 100-km grid spacing and a high resolution of approximately 25-km spacing. Surface temperature effects are considered by comparing simulations using fixed, uniform sea surface temperature with simulations using an interactive slab-ocean model. The various CAM5 configurations provide useful insights into the simulation of tropical climate as well as the model’s ability to simulate extreme precipitation events. In particular, the manner in which convection organizes is shown to be dependent on model resolution and the surface configuration (including surface temperature), as evident by differences in cloud structure, circulation, and precipitation intensity.

scholarly journals Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations

2016 ◽  
Vol 121 (8) ◽  
pp. 4162-4176 ◽  
Author(s):  
Jennifer E. Kay ◽  
Line Bourdages ◽  
Nathaniel B. Miller ◽  
Ariel Morrison ◽  
Vineel Yettella ◽  
...  
Keyword(s):  
Model Version ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Lidar Observations

scholarly journals Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations

2017 ◽  
Vol 17 (7) ◽  
pp. 4731-4749 ◽  
Author(s):  
Chenglai Wu ◽  
Xiaohong Liu ◽  
Minghui Diao ◽  
Kai Zhang ◽  
Andrew Gettelman ◽  
...  
Keyword(s):  
Nucleation And Growth ◽  
Ice Nucleation ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Model Version ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Community Atmosphere Model ◽  
Atmosphere Model ◽  
Ice Water

Abstract. In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ −40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.

scholarly journals An Explanation for the Sensitivity of the Mean State of the Community Atmosphere Model to Horizontal Resolution on Aquaplanets

2017 ◽  
Vol 30 (13) ◽  
pp. 4781-4797 ◽  
Author(s):  
Adam R. Herrington ◽  
Kevin A. Reed
Keyword(s):  
Moisture Transport ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Horizontal Resolution ◽  
Hadley Cell ◽  
Community Atmosphere Model ◽  
The Mean ◽  
Atmosphere Model ◽  
Mean State

The sensitivity of the mean state of the Community Atmosphere Model to horizontal resolutions typical of present-day general circulation models is investigated in an aquaplanet configuration. Nonconvergence of the mean state is characterized by a progressive drying of the atmosphere and large reductions in cloud coverage with increasing resolution. Analyses of energy and moisture budgets indicate that these trends are balanced by variations in moisture transport by the resolved circulation, and a reduction in activity of the convection scheme. In contrast, the large-scale precipitation rate increases with resolution, which is approximately balanced by greater advection of dry static energy associated with more active resolved vertical motion in the ascent region of the Hadley cell. An explanation for the sensitivity of the mean state to horizontal resolution is proposed, based on linear Boussinesq theory. The authors hypothesize that an increase in horizontal resolution in the model leads to a reduction in horizontal scale of the diabatic forcing arising from the column physics, facilitating finescale flow and faster resolved convective updrafts within the dynamical core, and steering the coupled system toward a new mean state. This hypothesis attempts to explain the underlying mechanism driving the variations in moisture transport observed in the simulations.

scholarly journals The importance of model resolution on simulated precipitation in Europe – from global to regional model

2020 ◽  
Author(s):  
Gustav Strandberg ◽  
Petter Lind
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Model Resolution ◽  
Simulated Precipitation ◽  
The Difference ◽  
Model Ensembles ◽  
High Resolution Models

Abstract. Precipitation, and especially extreme precipitation, is a key climate variable as it effects large parts of society. It is difficult to simulate in a climate model because of its large variability in time and space. This study investigates the importance of model resolution on the simulated precipitation in Europe for a wide range of climate model ensembles: from global climate models (GCM) at horizontal resolution of around 300 km to regional climate models (RCM) at horizontal resolution of 12.5 km. The aim is to investigate the differences between models and model ensembles, but also to evaluate their performance compared to gridded observations from E-OBS. Model resolution has a clear effect on precipitation. Generally, extreme precipitation is more intense and more frequent in high-resolution models compared to low-resolution models. Models of low resolution tend to underestimate intense precipitation. This is improved in high-resolution simulations, but there is a risk that high resolution models overestimate precipitation. This effect is seen in all ensembles, and GCMs and RCMs of similar resolution give similar results. The number of precipitation days, which is more governed by large-scale atmospheric flow, is not dependent on model resolution, while the number of days with heavy precipitation is. The difference between different models is often larger than between the low- and high-resolution versions of the same model, which makes it difficult to quantify the improvement. In this sense the quality of an ensemble is depending more on the models it consists of rather than the average resolution of the ensemble. Furthermore, the difference in simulated precipitation between an RCM and the driving GCM depend more on the choice of RCM and less on the down-scaling itself; as different RCMs driven by the same GCM may give different results. The results presented here are in line with previous similar studies but this is the first time an analysis like this is done across such relatively large model ensembles of different resolutions, and with a method studying all parts of the precipitation distribution.

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