An Object-Based Approach for Quantification of GCM Biases of the Simulation of Orographic Precipitation. Part I: Idealized Simulations

2014 ◽  
Vol 27 (24) ◽  
pp. 9139-9154 ◽  
Author(s):  
M. Soner Yorgun ◽  
Richard B. Rood
Keyword(s):  
General Circulation ◽  
Evaluation Method ◽  
Model Simulation ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Dynamical Core ◽  
Community Atmosphere Model ◽  
Object Based ◽  
Intercomparison Project

Abstract An object-based evaluation method to quantify biases of general circulation models (GCMs) is introduced using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Idealized experiments with different topography are designed to reproduce the spatial characteristics of precipitation biases that were present in Atmospheric Model Intercomparison Project simulations using the CAM finite volume (FV) and CAM Eulerian spectral dynamical cores. Precipitation features are identified as “objects” to understand the causes of the differences between CAM FV and CAM Eulerian spectral dynamical cores. Three different mechanisms of precipitation were simulated in idealized experiments: stable upslope ascent, local surface fluxes, and resolved downstream waves. The results indicated stronger sensitivity of the CAM Eulerian spectral dynamical core to resolution. The application of spectral filtering to topography is shown to have a large effect on the CAM Eulerian spectral model simulation. The removal of filtering improved the results when the scales of the topography were resolvable. However, it reduced the simulation capability of the CAM Eulerian spectral dynamical core because of Gibbs oscillations, leading to unusable results. A clear perspective about models biases is provided from the quantitative evaluation of objects extracted from these simulations and will be further discussed in part II of this study.

scholarly journals GCM Simulations of the Climate in the Central United States

2005 ◽  
Vol 18 (7) ◽  
pp. 1016-1031 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
Xin-Zhong Liang
Keyword(s):  
United States ◽  
General Circulation ◽  
Coupled Model ◽  
Scalar Fields ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Model Intercomparison ◽  
Central United States ◽  
Intercomparison Project ◽  
Precipitation Changes

Abstract A diagnostic analysis of relationships between central U.S. climate characteristics and various flow and scalar fields was used to evaluate nine global coupled ocean–atmosphere general circulation models (CGCMs) participating in the Coupled Model Intercomparison Project (CMIP). To facilitate identification of physical mechanisms causing biases, data from 21 models participating in the Atmospheric Model Intercomparison Project (AMIP) were also used for certain key analyses. Most models reproduce basic features of the circulation, temperature, and precipitation patterns in the central United States, although no model exhibits small differences from the observationally based data for all characteristics in all seasons. Model ensemble means generally produce better agreement with the observationally based data than any single model. A fall precipitation deficiency, found in all AMIP and CMIP models except the third-generation Hadley Centre CGCM (HadCM3), appears to be related in part to slight biases in the flow on the western flank of the Atlantic subtropical ridge. In the model mean, the ridge at 850 hPa is displaced slightly to the north and to the west, resulting in weaker southerly flow into the central United States. The CMIP doubled-CO2 transient runs show warming (1°–5°C) for all models and seasons and variable precipitation changes over the central United States. Temperature (precipitation) changes are larger (mostly less) than the variations that are observed in the twentieth century and the model variations in the control simulations.

scholarly journals Automatic tuning of the Community Atmospheric Model CAM5.3 by using short-term hindcasts with an improved downhill simplex optimization method

2018 ◽  
Author(s):  
Tao Zhang ◽  
Minghua Zhang ◽  
Yanluan Lin ◽  
Wei Xue ◽  
Wuyin Lin ◽  
...  
Keyword(s):  
General Circulation ◽  
Model Simulation ◽  
Computational Cost ◽  
Model Performance ◽  
Optimization Procedure ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Automatic Tuning ◽  
Short Term ◽  
Cloud Forcing

Abstract. Traditional trial-and-error tuning of uncertain parameters in global atmospheric General Circulation Models (GCM) is time consuming and subjective. This study explores the feasibility of automatic optimization of GCM parameters for fast physics by using short-term hindcasts. An automatic workflow is described and applied to the Community Atmospheric Model (CAM5) to optimize several parameters in its cloud and convective parameterizations. We show that the auto-optimization leads to 10 % reduction of the overall bias in CAM5, which is already a well calibrated model, based on a pre-defined metric that includes precipitation, temperature, humidity, and longwave/shortwave cloud forcing. The computational cost of the entire optimization procedure is about equivalent to about a single 12-year atmospheric model simulation. The tuning reduces the large underestimation in the CAM5 longwave cloud forcing by decreasing the threshold relative humidity and the sedimentation velocity of ice crystals in the cloud schemes; it reduces the overestimation of precipitation by increasing the adjustment time in the convection scheme. The physical processes behind the tuned model performance for each targeted field are discussed. Limitations of the automatic tuning are described, including the slight deterioration in some targeted fields that reflect the structural errors of the model. It is pointed out that automatic tuning can be a viable supplement to process-oriented model evaluations and improvement.

scholarly journals Automatic tuning of the Community Atmospheric Model (CAM5) by using short-term hindcasts with an improved downhill simplex optimization method

2018 ◽  
Vol 11 (12) ◽  
pp. 5189-5201 ◽  
Author(s):  
Tao Zhang ◽  
Minghua Zhang ◽  
Wuyin Lin ◽  
Yanluan Lin ◽  
Wei Xue ◽  
...  
Keyword(s):  
General Circulation ◽  
Model Simulation ◽  
Computational Cost ◽  
Model Performance ◽  
Optimization Procedure ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Automatic Tuning ◽  
Short Term ◽  
Cloud Forcing

Abstract. Traditional trial-and-error tuning of uncertain parameters in global atmospheric general circulation models (GCMs) is time consuming and subjective. This study explores the feasibility of automatic optimization of GCM parameters for fast physics by using short-term hindcasts. An automatic workflow is described and applied to the Community Atmospheric Model (CAM5) to optimize several parameters in its cloud and convective parameterizations. We show that the auto-optimization leads to 10 % reduction of the overall bias in CAM5, which is already a well-calibrated model, based on a predefined metric that includes precipitation, temperature, humidity, and longwave/shortwave cloud forcing. The computational cost of the entire optimization procedure is about equivalent to a single 12-year atmospheric model simulation. The tuning reduces the large underestimation in the CAM5 longwave cloud forcing by decreasing the threshold relative humidity and the sedimentation velocity of ice crystals in the cloud schemes; it reduces the overestimation of precipitation by increasing the adjustment time in the convection scheme. The physical processes behind the tuned model performance for each targeted field are discussed. Limitations of the automatic tuning are described, including the slight deterioration in some targeted fields that reflect the structural errors of the model. It is pointed out that automatic tuning can be a viable supplement to process-oriented model evaluations and improvement.

scholarly journals Tropical Biases in CMIP5 Multimodel Ensemble: The Excessive Equatorial Pacific Cold Tongue and Double ITCZ Problems*

2014 ◽  
Vol 27 (4) ◽  
pp. 1765-1780 ◽  
Author(s):  
Gen Li ◽  
Shang-Ping Xie
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Equatorial Pacific ◽  
Cold Tongue ◽  
Model Intercomparison ◽  
Tropical Ocean ◽  
Easterly Wind ◽  
Double Itcz ◽  
Intercomparison Project

Abstract Errors of coupled general circulation models (CGCMs) limit their utility for climate prediction and projection. Origins of and feedback for tropical biases are investigated in the historical climate simulations of 18 CGCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), together with the available Atmospheric Model Intercomparison Project (AMIP) simulations. Based on an intermodel empirical orthogonal function (EOF) analysis of tropical Pacific precipitation, the excessive equatorial Pacific cold tongue and double intertropical convergence zone (ITCZ) stand out as the most prominent errors of the current generation of CGCMs. The comparison of CMIP–AMIP pairs enables us to identify whether a given type of errors originates from atmospheric models. The equatorial Pacific cold tongue bias is associated with deficient precipitation and surface easterly wind biases in the western half of the basin in CGCMs, but these errors are absent in atmosphere-only models, indicating that the errors arise from the interaction with the ocean via Bjerknes feedback. For the double ITCZ problem, excessive precipitation south of the equator correlates well with excessive downward solar radiation in the Southern Hemisphere (SH) midlatitudes, an error traced back to atmospheric model simulations of cloud during austral spring and summer. This extratropical forcing of the ITCZ displacements is mediated by tropical ocean–atmosphere interaction and is consistent with recent studies of ocean–atmospheric energy transport balance.

scholarly journals An ensemble of AMIP simulations with prescribed land surface temperatures

2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
Global Climate ◽  
General Circulation Models ◽  
Solar Constant ◽  
Surface Temperatures ◽  
Co2 Concentrations ◽  
Land Surface Temperatures ◽  
Intercomparison Project

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.

Evaluation of the tail of the probability distribution of daily and sub-daily precipitation in CMIP6 models

2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen
Keyword(s):  
General Circulation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Coupled Model ◽  
Lower Troposphere ◽  
General Circulation Models ◽  
Intercomparison Project ◽  
Cloud Tops ◽  
The Tropics ◽  
Fraction Models

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.

Impact of circulation on tropical cloud feedbacks in cloud resolving models 

2021 ◽  
Author(s):  
Anna Mackie ◽  
Michael P. Byrne
Keyword(s):  
General Circulation ◽  
Deep Convection ◽  
General Circulation Models ◽  
Static Stability ◽  
Cloud Feedback ◽  
Dynamic Component ◽  
Intercomparison Project ◽  
Channel Configuration ◽  
Open Question ◽  
Long Channel

<div> <p>Uncertainty in the response of clouds to warming remains a significant barrier to reducing the range in projected climate sensitivity. A key question is to what extent cloud feedbacks can be attributed to changes in circulation, such as the strengthening or weakening of ascent or changes in the areas of convecting vs subsiding air. Previous research has shown that, in general circulation models (GCMs), the ‘dynamic’ component of the cloud feedback – that which is due to changes in circulation rather than changes in the thermodynamic properties of clouds (Bony et al., 2006) – is generally small (Byrne and Schneider, 2018). An open question, however, is whether this extends to models at cloud resolving resolutions that explicitly simulate deep convection.  </p> </div><div> <p>Here, we utilize simulations from the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP, Wing et al., 2018, 2020) to quantify the impact of circulation on tropical cloud feedbacks. RCE is a simple idealisation of the tropical atmosphere and we focus on simulations in a long channel configuration with uniform sea surface temperatures of 295, 300 and 305K. The dynamic component of the total cloud feedback is substantial for this suite of cloud resolving models (CRMs), and is driven by circulation changes and nonlinearity in the climatological relationship between clouds and circulation. The large spread in dynamic component across models is linked to the extent to which convection strengthens and narrows with warming. This strengthening/narrowing of convective regions is further linked to changes in clear-sky radiative cooling and mid-tropospheric static stability in subsiding regions. </p> </div><div> <p> </p> </div>

scholarly journals The importance of considering sub-grid cloud variability when using satellite observations to evaluate the cloud and precipitation simulations in climate models

2018 ◽  
Vol 11 (8) ◽  
pp. 3147-3158 ◽  
Author(s):  
Hua Song ◽  
Zhibo Zhang ◽  
Po-Lun Ma ◽  
Steven Ghan ◽  
Minghuai Wang
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Satellite Observations ◽  
Community Atmosphere Model ◽  
Cloud Resolving Model ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Indispensable Tool ◽  
Probability Of Precipitation

Abstract. Satellite cloud observations have become an indispensable tool for evaluating general circulation models (GCMs). To facilitate the satellite and GCM comparisons, the CFMIP (Cloud Feedback Model Inter-comparison Project) Observation Simulator Package (COSP) has been developed and is now increasingly used in GCM evaluations. Real-world clouds and precipitation can have significant sub-grid variations, which, however, are often ignored or oversimplified in the COSP simulation. In this study, we use COSP cloud simulations from the Super-Parameterized Community Atmosphere Model (SPCAM5) and satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and CloudSat to demonstrate the importance of considering the sub-grid variability of cloud and precipitation when using the COSP to evaluate GCM simulations. We carry out two sensitivity tests: SPCAM5 COSP and SPCAM5-Homogeneous COSP. In the SPCAM5 COSP run, the sub-grid cloud and precipitation properties from the embedded cloud-resolving model (CRM) of SPCAM5 are used to drive the COSP simulation, while in the SPCAM5-Homogeneous COSP run only grid-mean cloud and precipitation properties (i.e., no sub-grid variations) are given to the COSP. We find that the warm rain signatures in the SPCAM5 COSP run agree with the MODIS and CloudSat observations quite well. In contrast, the SPCAM5-Homogeneous COSP run which ignores the sub-grid cloud variations substantially overestimates the radar reflectivity and probability of precipitation compared to the satellite observations, as well as the results from the SPCAM5 COSP run. The significant differences between the two COSP runs demonstrate that it is important to take into account the sub-grid variations of cloud and precipitation when using COSP to evaluate the GCM to avoid confusing and misleading results.

scholarly journals Diagnostic study of errors in the simulation of tropical continental precipitation in general circulation models

2003 ◽  
Vol 21 (5) ◽  
pp. 1197-1207 ◽  
Author(s):  
J. Srinivasan
Keyword(s):  
Water Vapour ◽  
General Circulation ◽  
Nonlinear Function ◽  
General Circulation Models ◽  
Atmospheric Model ◽  
Large Error ◽  
Tropical Meteorology ◽  
Diagnostic Model ◽  
Diagnostic Study ◽  
Integrated Water Vapour

Abstract. A simple diagnostic model has been used to identify the parameters that induce large errors in the simulation of tropical precipitation in atmospheric General Circulation models (GCM). The GCM that have been considered are those developed by the National Center for Environmental Prediction (NCEP), the National Center for Atmospheric Research (NCAR) and the Japanese Meteorological Agency (JMA). These models participated in the phase II of the Atmospheric Model Inter-comparison Project (AMIP II) and simulated the climate for the period 1979 to 1995. The root mean-square error in the simulation of precipitation in tropical continents was larger in NCEP and NCAR simulations than in the JMA simulation. The large error in the simulation of precipitation in NCEP was due to errors in the vertical profile of water vapour. The large error in precipitation in NCAR in North Africa was due to an error in net radiation (at the top of the atmosphere). The simple diagnostic model predicts that the moisture converge is a nonlinear function of integrated water vapour. The large error in the interannual variance of rainfall in NCEP over India has been shown to be due to this nonlinearity.Key words. Meteorology and atmospheric dynamics (precipitation; tropical meteorology; convective processes)

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