scholarly journals The Diurnal Cycle of Clouds and Precipitation at the ARM SGP Site: An Atmospheric State-Based Analysis and Error Decomposition of a Multiscale Modeling Framework Simulation

2017 ◽  
Vol 122 (24) ◽  
pp. 13,387-13,403 ◽  
Author(s):  
Wei Zhao ◽  
Roger Marchand ◽  
Qiang Fu
Keyword(s):  
Multiscale Modeling ◽  
Diurnal Cycle ◽  
Modeling Framework ◽  
Atmospheric State ◽  
Multiscale Modeling Framework ◽  
Error Decomposition

scholarly journals Robust Nocturnal and Early Morning Summer Rainfall Peaks over Continental East Asia in a Global Multiscale Modeling Framework

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 53 ◽  
Author(s):  
Yi Zhang ◽  
Haoming Chen ◽  
Dan Wang
Keyword(s):  
East Asia ◽  
Multiscale Modeling ◽  
Diurnal Cycle ◽  
Summer Rainfall ◽  
Early Morning ◽  
Atmospheric Modeling ◽  
The Tibetan Plateau ◽  
Moderate Increase ◽  
Modeling Framework ◽  
Multiscale Modeling Framework

The diurnal cycle of convection and precipitation is an important atmospheric feature. It also poses a great challenge to global numerical atmospheric modeling. Over continental East Asia, most global models cannot well capture the nocturnal and early morning peaks of summer rainfall. This problem may lead to dry biases and limit the modeling skills. This study investigates this problem using a global multiscale modeling framework (Super-Parameterized CAM5; SPCAM5). The nocturnal and early morning peaks, which are almost absent in CAM5 and a coarser-resolution SPCAM5, can be successfully captured by SPCAM5 with a moderate increase in the horizontal resolution. On the lee side of the Tibetan Plateau, SPCAM5 generates robust eastward propagating rainfall signals, which correspond to the moving convective systems, as revealed by the heating and drying profiles. Over the eastern plain of China, the early morning peaks become more evident, corresponding to a stratiform-type heating structure in the midlevel. A sensitivity experiment with altered grid-scale forcing also suggests the important preconditioning role of the vertical moisture advection in regulating the early morning peaks. These results highlight the added value of representing multiscale processes to the successful simulation of the diurnal cycle over continental East Asia.

Evaluation of the Simulated Interannual and Subseasonal Variability in an AMIP-Style Simulation Using the CSU Multiscale Modeling Framework

2008 ◽  
Vol 21 (3) ◽  
pp. 413-431 ◽  
Author(s):  
Marat Khairoutdinov ◽  
Charlotte DeMott ◽  
David Randall
Keyword(s):  
Multiscale Modeling ◽  
Vertical Velocity ◽  
Diurnal Cycle ◽  
Modeling Framework ◽  
Subseasonal Variability ◽  
Cloud Water Content ◽  
Velocity Variance ◽  
Stratocumulus Clouds ◽  
Cloud Effect ◽  
Multiscale Modeling Framework

Abstract The Colorado State University (CSU) Multiscale Modeling Framework (MMF) is a new type of general circulation model (GCM) that replaces the conventional parameterizations of convection, clouds, and boundary layer with a cloud-resolving model (CRM) embedded into each grid column. The MMF has been used to perform a 19-yr-long Atmospheric Model Intercomparison Project–style simulation using the 1985–2004 sea surface temperature (SST) and sea ice distributions as prescribed boundary conditions. Particular focus has been given to the simulation of the interannual and subseasonal variability. The annual mean climatology is generally well simulated. Prominent biases include excessive precipitation associated with the Indian and Asian monsoon seasons, precipitation deficits west of the Maritime Continent and over Amazonia, shortwave cloud effect biases west of the subtropical continents due to insufficient stratocumulus clouds, and longwave cloud effect biases due to overestimation of high cloud amounts, especially in the tropics. The geographical pattern of the seasonal cycle of precipitation is well reproduced, although the seasonal variance is considerably overestimated mostly because of the excessive monsoon precipitation mentioned above. The MMF does a good job of reproducing the interannual variability in terms of the spatial structure and magnitude of major anomalies associated with El Niño–Southern Oscillation (ENSO). The subseasonal variability of tropical climate associated with the Madden–Julian oscillation (MJO) and equatorially trapped waves are particular strengths of the simulation. The wavenumber–frequency power spectra of the simulated outgoing longwave radiation (OLR), precipitation rate, and zonal wind at 200 and 850 mb for time scales in the range of 2–96 days compare very well to the spectra derived from observations, and show a robust MJO and Kelvin and Rossby waves with phase speeds similar to those observed. The geographical patterns of the MJO and Kelvin wave–filtered OLR variance for summer and winter seasons are well simulated; however, the variances tend to be overestimated by as much as 50%. The observed seasonal and interannual variations of the strength of the MJO are also well reproduced. The physical realism of the simulated marine stratocumulus clouds is demonstrated by an analysis of the composite diurnal cycle of cloud water content, longwave (IR) cooling, vertical velocity variance, rainfall, and subcloud vertical velocity skewness. The relationships between vertical velocity variance, IR cooling, and negative skewness all suggest that, despite the coarse numerical grid of the CRM, the simulated clouds behave in a manner consistent with the understanding of the stratocumulus dynamics. In the stratocumulus-to-cumulus transition zone, the diurnal cycle of the inversion layer as simulated by the MMF also bears a remarkable resemblance to in situ observations. It is demonstrated that in spite of the coarse spacing of the CRM grid used in the current version of MMF, the bulk of vertical transport of water in the MMF is carried out by the circulations explicitly represented on the CRM grid rather than by the CRM’s subgrid-scale parameterization.

Evaluation of Hydrometeor Occurrence Profiles in the Multiscale Modeling Framework Climate Model Using Atmospheric Classification

2009 ◽  
Vol 22 (17) ◽  
pp. 4557-4573 ◽  
Author(s):  
Roger Marchand ◽  
Nathaniel Beagley ◽  
Thomas P. Ackerman
Keyword(s):  
Multiscale Modeling ◽  
Great Plains ◽  
Large Scale ◽  
Climate Model ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Modeling Framework ◽  
Neural Network Approach ◽  
Atmospheric State ◽  
Multiscale Modeling Framework

Abstract Vertical profiles of hydrometeor occurrence from the multiscale modeling framework (MMF) climate model are compared with profiles observed by a vertically pointing millimeter wavelength cloud radar (located in the U.S. southern Great Plains) as a function of the large-scale atmospheric state. The atmospheric state is determined by classifying (or clustering) the large-scale (synoptic) fields produced by the MMF and a numerical weather prediction model using a neural network approach. The comparison shows that for cold-frontal and post-cold-frontal conditions the MMF produces profiles of hydrometeor occurrence that compare favorably with radar observations, while for warm-frontal conditions the model tends to produce hydrometeor fractions that are too large with too much cloud (nonprecipitating hydrometeors) above 7 km and too much precipitating hydrometeor coverage below 7 km. It is also found that the MMF has difficulty capturing the formation of low clouds and that, for all atmospheric states that occur during June, July, and August, the MMF produces too much high and thin cloud, especially above 10 km.

scholarly journals Mean Structure and Diurnal Cycle of Southeast Atlantic Boundary Layer Clouds: Insights from Satellite Observations and Multiscale Modeling Framework Simulations

2014 ◽  
Vol 28 (1) ◽  
pp. 324-341 ◽  
Author(s):  
David Painemal ◽  
Kuan-Man Xu ◽  
Anning Cheng ◽  
Patrick Minnis ◽  
Rabindra Palikonda
Keyword(s):  
Boundary Layer ◽  
Multiscale Modeling ◽  
Diurnal Cycle ◽  
Cloud Cover ◽  
Satellite Observations ◽  
Modeling Framework ◽  
Boundary Layer Clouds ◽  
Mean Structure ◽  
The Mean ◽  
Multiscale Modeling Framework

Abstract The mean structure and diurnal cycle of southeast (SE) Atlantic boundary layer clouds are described with satellite observations and multiscale modeling framework (MMF) simulations during austral spring (September–November). Hourly resolution cloud fraction (CF) and cloud-top height (HT) are retrieved from Meteosat-9 radiances using modified Clouds and the Earth’s Radiant Energy System (CERES) Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms, whereas liquid water path (LWP) is from the University of Wisconsin microwave satellite climatology. The MMF simulations use a 2D cloud-resolving model (CRM) that contains an advanced third-order turbulence closure to explicitly simulate cloud physical processes in every grid column of a general circulation model. The model accurately reproduces the marine stratocumulus spatial extent and cloud cover. The mean cloud cover spatial variability in the model is primarily explained by the boundary layer decoupling strength, whereas a boundary layer shoaling accounts for a coastal decrease in CF. Moreover, the core of the stratocumulus cloud deck is concomitant with the location of the strongest temperature inversion. Although the model reproduces the observed westward boundary layer deepening and the spatial variability of LWP, it overestimates LWP by 50%. Diurnal cycles of HT, CF, and LWP from satellites and the model have the same phase, with maxima during the early morning and minima near 1500 local solar time, which suggests that the diurnal cycle is driven primarily by solar heating. Comparisons with the SE Pacific cloud deck indicate that the observed amplitude of the diurnal cycle is modest over the SE Atlantic, with a shallower boundary layer as well. The model qualitatively reproduces these interregime differences.

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