scholarly journals Convective Transition Statistics over Tropical Oceans for Climate Model Diagnostics: GCM Evaluation

2020 ◽  
Vol 77 (1) ◽  
pp. 379-403 ◽  
Author(s):  
Yi-Hung Kuo ◽  
J. David Neelin ◽  
Chih-Chieh Chen ◽  
Wei-Ting Chen ◽  
Leo J. Donner ◽  
...  

Abstract To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.

2020 ◽  
Vol 13 (2) ◽  
pp. 673-684
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho

Abstract. We revisit the concept of the cloud vertical structure (CVS) classes we have previously employed to classify the planet's cloudiness (Oreopoulos et al., 2017). The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an atmospheric global climate model, specifically a version of NASA's GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Such classes can be defined in GEOS-5 thanks to a subcolumn cloud generator paired with the model's radiative transfer algorithm, and their associated radiative effects can be evaluated against observations. We find that the model produces 50 % more clear skies than observations in relative terms and produces isolated high clouds that are slightly less frequent than in observations, but optically thicker, yielding excessive planetary and surface cooling. Low clouds are also brighter than in observations, but underestimates of the frequency of occurrence (by ∼20 % in relative terms) help restore radiative agreement with observations. Overall the model better reproduces the longwave radiative effects of the various CVS classes because cloud vertical location is substantially constrained in the CVS framework.


2019 ◽  
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
Nayeong Cho

Abstract. We revisit Cloud Vertical Structure (CVS) classes we have previously employed to classify the planet’s cloudiness. The CVS classification reflects simple combinations of simultaneous cloud occurrence in the three standard layers traditionally used to separate low, middle, and high clouds and was applied to a dataset derived from active lidar and cloud radar observations. This classification is now introduced in an Atmospheric Global Climate Model (AGCM), specifically NASA’s GEOS-5, in order to evaluate the realism of its cloudiness and of the radiative effects associated with the various CVS classes. Determination of CVS and associated radiation in the model is possible thanks to the implementation of a subcolumn cloud generator which is paired with the model’s radiative transfer algorithm. We assess GEOS-5 cloudiness in terms of the statistics and geographical distributions of the CVS classes, as well as features of their associated Cloud Radiative Effect (CRE). We decompose the model’s CVS-specific CRE errors into component errors stemming from biases in the frequency of occurrence of the CVSs, and biases in their internal radiative characteristics. Our framework sheds additional light into the verisimilitude of cloudiness in large scale models and can be used to complement cloud evaluations that take advantage of satellite simulator implementations.


2018 ◽  
Author(s):  
Toni Mitovski ◽  
Jason N. S. Cole ◽  
Norman A. McFarlane ◽  
Knut von Salzen ◽  
Guang J. Zhang

Abstract. Changes in the large-scale environment during convective precipitation events in the Tropical Western Pacific simulated by version 4.3 of the Canadian Atmospheric Model (CanAM4.3) is compared against those simulated by version 5.0 of the super parameterized Community Atmosphere Model (spCAM5). This is done by compositing sub-hourly output of convective rainfall, convective available potential energy (CAPE), CAPE generation due to large-scale forcing in the free troposphere (dCAPELSFT), and near surface vertical velocity (ω) over the time period May–July 1997. Compared to spCAM5, CanAM4.3 tends to produce more frequent light convective precipitation ( 2 mm h−1). In spCAM5 5 % of convective precipitation events lasted less than 1.5 h and 75 % lasted between 1.5 and 3.0 h while in CanAM4.3 80 % of the events lasted less than 1.5 h. Convective precipitation in spCAM5 is found to be a function of dCAPELSFT and the large-scale near surface ω with variations in ω slightly leading variations in convective precipitation. Convective precipitation in CanAM4.3 does not have the same dependency and instead is found to be a function of CAPE.


2018 ◽  
Vol 76 (1) ◽  
pp. 11-26 ◽  
Author(s):  
Christina Klasa ◽  
Marco Arpagaus ◽  
André Walser ◽  
Heini Wernli

Abstract Dynamical processes determining the time evolution of difference kinetic energy (DKE) in a limited-area domain are investigated with the convection-permitting ensemble model COSMO-E for a forecasting period of 4 days. DKE is quantified by means of ensemble variance of the irrotational and nondivergent horizontal wind. For three case studies characterized by contrasting predictability levels of precipitation, it is shown that DKE of the irrotational wind strongly increases during periods of solar-forced moist convective activity and decreases when the latter ceases. The response of DKE of the nondivergent wind is also clearly related to the convective activity, but delayed by a few hours, pointing to interactions between both wind components. Apart from the impact of moist convection, DKE of the nondivergent wind is primarily governed by large-scale advection, imposed at the lateral domain boundaries of the limited-area ensemble. This forcing may also sustain or increase DKE of the irrotational wind when moist convection is absent. Consequently, the large-scale flow and diurnal solar forcing, associated with higher spatiotemporal predictability, determines the overall evolution of the limited-area ensemble variance of the horizontal wind, which increases in the presence of moist convective activity or strong synoptic-scale forcing, and stagnates or decreases otherwise, rendering forecasts of convection-permitting ensembles valuable beyond the very short forecast range.


2011 ◽  
Vol 24 (13) ◽  
pp. 3520-3544 ◽  
Author(s):  
Stephen M. Griffies ◽  
Michael Winton ◽  
Leo J. Donner ◽  
Larry W. Horowitz ◽  
Stephanie M. Downes ◽  
...  

Abstract This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.


2019 ◽  
Vol 12 (5) ◽  
pp. 2107-2117 ◽  
Author(s):  
Toni Mitovski ◽  
Jason N. S. Cole ◽  
Norman A. McFarlane ◽  
Knut von Salzen ◽  
Guang J. Zhang

Abstract. Changes in the large-scale environment during convective precipitation events in the tropical western Pacific simulated by version 4.3 of the Canadian Atmospheric Model (CanAM4.3) are compared against those simulated by version 5.0 of the super-parameterized Community Atmosphere Model (spCAM5). This is done by compositing sub-hourly output of convective rainfall, convective available potential energy (CAPE), CAPE generation due to large-scale forcing in the free troposphere (dCAPELSFT) and near-surface vertical velocity (ω) over the time period May–July 1997. Compared to spCAM5, CanAM4.3 tends to produce more frequent light convective precipitation (<0.2 mm h−1) and underestimates the frequency of extreme convective precipitation (>2 mm h−1). In spCAM5, 5 % of convective precipitation events lasted less than 1.5 h and 75 % lasted between 1.5 and 3.0 h, while in CanAM4.3 80 % of the events lasted less than 1.5 h. Convective precipitation in spCAM5 is found to be a function of dCAPELSFT and the large-scale near-surface ω with variations in ω slightly leading variations in convective precipitation. Convective precipitation in CanAM4.3 does not have the same dependency and instead is found to be a function of CAPE.


2015 ◽  
Vol 28 (8) ◽  
pp. 3275-3288 ◽  
Author(s):  
Gábor Drótos ◽  
Tamás Bódai ◽  
Tamás Tél

Abstract The authors argue that the concept of snapshot attractors and of their natural probability distributions are the only available tools by means of which mathematically sound statements can be made about averages, variances, etc., for a given time instant in a changing climate. A basic advantage of the snapshot approach, which relies on the use of an ensemble, is that the natural distribution and thus any statistics based on it are independent of the particular ensemble used, provided it is initiated in the past earlier than a convergence time. To illustrate these concepts, a tutorial presentation is given within the framework of a low-order model in which the temperature contrast parameter over a hemisphere decreases linearly in time. Furthermore, the averages and variances obtained from the snapshot attractor approach are demonstrated to strongly differ from the traditional 30-yr temporal averages and variances taken along single realizations. The authors also claim that internal variability can be quantified by the natural distribution since it characterizes the chaotic motion represented by the snapshot attractor. This experience suggests that snapshot-attractor-based calculations might be appropriate to be evaluated in any large-scale climate model, and that the application of 30-yr temporal averages taken along single realizations should be complemented with this more appealing tool for the characterization of climate changes, which seems to be practically feasible with moderate ensemble sizes.


2009 ◽  
Vol 22 (20) ◽  
pp. 5401-5420 ◽  
Author(s):  
Scott J. Weaver ◽  
Siegfried Schubert ◽  
Hailan Wang

Abstract Sea surface temperature (SST) linkages to central U.S. low-level circulation and precipitation variability are investigated from the perspective of the Great Plains low-level jet (GPLLJ) and recurring modes of SST variability. The observed and simulated links are first examined via GPLLJ index regressions to precipitation, SST, and large-scale circulation fields in the NCEP–NCAR and North American Regional Reanalysis (NARR) reanalyses, and NASA’s Seasonal-to-Interannual Prediction Project (NSIPP1) and Community Climate Model, version 3 (CCM3) ensemble mean Atmospheric Model Intercomparison Project (AMIP) simulations for the 1949–2002 (1979–2002 for NARR) period. Characteristics of the low-level circulation and its related precipitation are further examined in the U.S. Climate Variability and Predictability (CLIVAR) Drought Working Group idealized climate model simulations (NSIPP1 and CCM3) forced with varying polarities of recurring modes of SST variability. It is found that the observed and simulated correlations of the GPLLJ index to Atlantic and Pacific SST, large-scale atmospheric circulation, and Great Plains precipitation variability for 1949–2002 are robust during the July–September (JAS) season and show connections to a distinct global-scale SST variability pattern, one similar to that used in forcing the NSIPP1 and CCM3 idealized simulations, and a subtropical Atlantic-based sea level pressure (SLP) anomaly with a maximum over the Gulf of Mexico. The idealized simulations demonstrate that a warm Pacific and/or a cold Atlantic are influential over regional hydroclimate features including the monthly preference for maximum GPLLJ and precipitation in the seasonal cycle. Furthermore, it appears that the regional expression of globally derived SST variability is important for generating an anomalous atmospheric low-level response of consequence to the GPLLJ, especially when the SST anomaly is positioned over a regional maximum in climatological SST, and in this case the Western Hemisphere warm pool.


2020 ◽  
Vol 77 (4) ◽  
pp. 1415-1428 ◽  
Author(s):  
Tsung-Lin Hsieh ◽  
Stephen T. Garner ◽  
Isaac M. Held

Abstract Simulations of baroclinic cyclones often cannot resolve moist convection but resort to convective parameterization. An exception is the hypohydrostatic rescaling, which in principle can be used to better represent convection with no increase in computational cost. The rescaling is studied in the context of a quasi-steady, convectively active, baroclinic cyclone. This is a novel framework with advantages due to the unambiguous time-mean structure. The rescaling is evaluated against high-resolution solutions up to a 5-km grid spacing. A theoretical scaling combining convective-scale dynamics and synoptic-scale energy balance is derived and verified by the simulations. It predicts the insensitivity of the large-scale flow to resolution finer than 40 km and to moderate rescaling, and a weak bias in the cyclone intensity under very large rescaling. The theory yields a threshold for the rescaling factor that avoids large-scale biases. Below the threshold, the rescaling can be used to control resolution errors at the convective scale, such as the distribution of extreme precipitation rates.


2018 ◽  
Vol 11 (1) ◽  
pp. 453-466
Author(s):  
Aurélien Quiquet ◽  
Didier M. Roche ◽  
Christophe Dumas ◽  
Didier Paillard

Abstract. This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km  ×  40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.


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