ALBERT

Description: Cloud processes play a central role in the dynamics of the tropical atmosphere, but for many years the shortcomings of cloud parameterizations have limited our ability to simulate and understand important tropical weather systems such as the Madden–Julian oscillation. Since about 2001, “superparameterization” has emerged as a new path forward, complementing but not replacing studies based on conventional parameterizations. This chapter provides an overview of work with superparameterization, including a discussion of the method itself and a summary of key results.

Description: Eastward propagating Madden-Julian oscillation (MJO) events that develop in the Indian Ocean from November to April are separated into events whose convective anomalies do and do not propagate across the Maritime Continent (MC). Propagating (P) events are divided into strong (sP) and weak (wP) subsets based on the initial amplitudes of their convective anomalies. Eastward decaying (ED) MJO events have initial amplitudes similar to those of wP events. Roughly half of all MJO events encounter westward propagating transient dry precursor (TDP) signals over the MC. These TDPs, which are external to the MJO circulation system, overwhelm the weak, eastward propagating moist anomaly in ED events, leading to MJO termination. In wP events, the MJO moist anomaly is stronger than the TDP dry anomaly, and the MJO propagates beyond the MC. ED MJO events that do not encounter TDPs decay because of insufficient moistening in the southern MC region. The background states of TDP- and non-TDP-affected MJO events resemble La Niña and El Niño conditions, respectively. The regional regulation of TDP activity and background moisture gradients by El Niño–Southern Oscillation can both be understood in terms of the zonal shift and the meridional expansion or contraction of Warm Pool moisture in response to El Niño–Southern Oscillation sea surface temperature anomalies. Our results demonstrate that modulation of TDPs by the background state moisture can affect the MJO in a manner that reinforces its propagation or decay via the interaction of MJO circulation anomalies and background moisture gradients. ©2018. American Geophysical Union. All Rights Reserved.

Description: The oceanic feedback to the atmospheric boreal summer intraseasonal oscillation (BSISO) is examined by diagnosing the sea surface temperature (SST) modification of surface fluxes and moist static energy on intraseasonal scales. SST variability affects intraseasonal surface latent heat (LH) and sensible heat (SH) fluxes, through its influence on air‐sea moisture and temperature gradients (∆q and ∆T, respectively). According to bulk formula decomposition, LH is mainly determined by wind‐driven flux perturbations, while SH is more sensitive to thermodynamic flux perturbations. SST fluctuations tend to increase the thermodynamic flux perturbations over active BSISO regions, but this is largely offset by the wind‐driven flux perturbations. Enhanced surface fluxes induced by intraseasonal SST anomalies are located ahead (north) of the convective center over both the Indian Ocean and the western Pacific, favoring BSISO northward propagation. Analysis of budgets of column‐integrated moist static energy (⟨m⟩) and its time rate of change (∂⟨m⟩/∂t) shows that SST‐modulated surface fluxes can influence the development and propagation of the BSISO, respectively. LH and SH variability induced by intraseasonal SSTs maintain 1–2% of ⟨m⟩ day−1 over the equatorial western Indian Ocean, Arabian Sea, and Bay of Bengal but damp about 1% of ⟨m⟩ day−1 over the western North Pacific. The contribution of intraseasonal SST variability to ∂⟨m⟩/∂t can reach 12–20% over active BSISO regions. These results suggest that SST variability is conducive, but perhaps not essential, for the propagation of convection during the BSISO life cycle.

Description: 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.

Description: Implied ocean heat transport (To) based on net surface energy budgets is computed for two versions of the Community Atmospheric Model (CAM, version 3.0) general circulation model (GCM). The first version is the standard CAM with parameterized convection. The second is the multiscale modeling framework (MMF), in which parameterized convection is replaced with a two-dimensional cloud-resolving model in each GCM grid column. Although global-mean net surface energy totals are similar for both models, differences in the geographic distributions of the component errors lead to distinctly different To for each model, with CAM’s To generally agreeing with observationally based To estimates, and the MMF’s To producing northward transport at all latitudes north of ∼50°S. Analysis of component error sources in the To calculation identifies needed improvements in the MMF. Net surface shortwave radiation and latent heat fluxes over the oceans are the primary causes of To errors in the MMF. Surface shortwave radiation biases in the MMF are associated with liquid and/or ice water content biases in tropical and extratropical convection and a deficit of marine stratocumulus clouds. It is expected that tropical ice water contents in the MMF can be made more realistic via improvements to the cloud microphysics parameterization. MMF marine stratocumulus clouds are overly sensitive to low-level relative humidity and form only with nearly saturated conditions and a shallow boundary layer. Latent heat flux errors in the MMF are amplifications of those found in the CAM and are concentrated in the trade wind regime and the Asian monsoon region and the adjacent western Pacific Ocean. Potential improvements to To are estimated by replacing either simulated net surface shortwave or latent heat fluxes with those from observations and recomputing To. When observed shortwave fluxes are used, both CAM and MMF produce greatly improved To curves for both hemispheres. When To is computed using observed latent heat fluxes, CAM To degrades slightly and MMF To improves, especially in the sign of Southern Hemisphere transport.

Description: Precipitation variability is analyzed in two versions of the Community Atmospheric Model (CAM), the standard model, CAM, and a “multiscale modeling framework” (MMF), in which the cumulus parameterization has been replaced with a cloud-resolving model. Probability distribution functions (PDFs) of daily mean rainfall in three geographic locations [the Amazon Basin and western Pacific in December–February (DJF) and the North American Great Plains in June–August (JJA)] indicate that the CAM produces too much light–moderate rainfall (10 ∼ 20 mm day−1), and not enough heavy rainfall, compared to observations. The MMF underestimates rain contributions from the lightest rainfall rates but correctly simulates more intense rainfall events. These differences are not always apparent in seasonal mean rainfall totals. Analysis of 3–6-hourly rainfall and sounding data in the same locations reveals that the CAM produces moderately intense rainfall as soon as the boundary layer energizes. Precipitation is also concurrent with tropospheric relative humidity and lifted parcel buoyancy increases. In contrast, the MMF and observations are characterized by a lag of several hours between boundary layer energy buildup and precipitation, and a gradual increase in the depth of low-level relative humidity maximum prior to rainfall. The environmental entrainment rate selection in the CAM cumulus parameterization influences CAM precipitation timing and intensity, and may contribute to the midlevel dry bias in that model. The resulting low-intensity rainfall in the CAM leads to rainfall–canopy vegetation interactions that are different from those simulated by the MMF. The authors present evidence suggesting that this interaction may artificially inflate North American Great Plains summertime rainfall totals in the CAM.

Description: Mechanisms for the northward propagation (NP) of the boreal summer intraseasonal oscillation (BSISO) and associated Asian summer monsoon (ASM) are investigated using data from the interim ECMWF Re-Analysis (ERA-Interim, herein called ERAI) and the superparameterized Community Climate System Model (SP-CCSM). Analyzed mechanisms are 1) destabilization of the lower troposphere by sea surface temperature anomalies, 2) boundary layer moisture advection, and boundary layer convergence associated with 3) SST gradients and 4) barotropic vorticity anomalies. Mechanism indices are regressed onto filtered OLR anomaly time series to study their relationships to the intraseasonal oscillation (ISO) and to equatorial Rossby (ER) waves. Northward propagation in ERAI and SP-CCSM is promoted by several mechanisms, but is dominated by boundary layer moisture advection and the barotropic vorticity effect. SST-linked mechanisms are of secondary importance but are nonnegligible. The magnitudes of NP mechanisms vary from the Indian Ocean to the west Pacific Ocean, implying that NP is accomplished by different mechanisms across the study area. SP-CCSM correctly simulates observed NP mechanisms over most of the ASM domain except in the Arabian Sea during the early stages of the monsoon life cycle. Reduced NP in the Arabian Sea arises from weaker-than-observed easterly shear, reducing the effectiveness of the barotropic vorticity mechanism. The ability of SP-CCSM to correctly simulate NP mechanisms in other regions results from the model’s ability to simulate reasonable mean wind and moisture fields, a realistic spectrum of variability, and the capability of convection to respond to boundary layer changes induced by large-scale NP mechanisms.