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Shang-Ping Xie

Abstract

Over a large zonal extent of the central and eastern Pacific, the intertropical convergence zone (ITCZ) is located to the north of the equator. Collocated with this ITCZ is a zonal band of warm sea surface, where the highest sea surface temperatures (SST) along a meridian are found. A one-dimensional coupled ocean–atmosphere model that neglects zonal variations is used to investigate this problem of latitudinal asymmetry in the tropical climate. The equatorially symmetric model solution is found to be unstable to infinitesimal disturbances and equatorial asymmetries develop spontaneously. A linear instability that is stationary in space and antisymmetric about the equator is responsible for the unstable transition of the model from the symmetric state. The destabilizing mechanism involves a positive feedback between the scalar wind speed and SST through surface evaporation, which is illustrated with a simple low-order model that contains only two SST grid points, one in each hemisphere.

The existence of the equatorially antisymmetric instability indicates that in a zonally uniform setting, a latitudinally asymmetric climate with a single ITCZ off the equator could emerge on a symmetric planet.

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Yuqing Wang
,
Haiming Xu
, and
Shang-Ping Xie

Abstract

The sensitivity of a regional climate model to physical parameterizations and model resolution is investigated in terms of its simulation of boundary layer stratocumulus (SCu) clouds over the southeast Pacific. Specifically, the physical schemes being tested include shallow cumulus convection, subgrid vertical mixing, cloud droplet number concentration (CDNC), and drizzle.

As described in Part I, the model with standard settings captures the major features of the boundary layer in the region, including a well-mixed marine boundary layer, a capping temperature inversion, SCu clouds, and the boundary layer regime transition from the well-mixed layer near the coast of South America to a decoupled cloud layer over warmer water to the west. Turning off the shallow cumulus parameterization results in a dramatic increase in the simulated SCu clouds while the boundary layer structure becomes unrealistic, losing the decoupled regime over warm water. With reduced penetrative mixing at the top of shallow cumuli, the simulated SCu clouds are somewhat increased while the boundary layer structure remained largely unchanged. Reducing the CDNC increases the size of cloud droplets and reduces the cloud albedo but has little effect on the vertical structure of the boundary layer and clouds. Allowing more drizzle decreases boundary layer clouds considerably. It is also shown that the simulated depth of the boundary layer and its decoupling is highly sensitive to the model horizontal and vertical resolutions. Insufficient horizontal or vertical resolutions produce a temperature inversion and cloud layer too close to the sea surface, a typical problem for global general circulation models.

Implications of these results for global and regional modeling of boundary layer clouds and the areas that need more attention in future model development are discussed.

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Xiangzhou Song
,
Xuehan Xie
,
Yunwei Yan
, and
Shang-Ping Xie

Abstract

Based on data collected from 14 buoys in the Gulf Stream, this study examines how hourly air–sea turbulent heat fluxes vary on sub-daily timescales under different boundary layer stability conditions. The annual mean magnitudes of the sub-daily variations in latent and sensible heat fluxes at all stations are 40 and 15 W·m−2, respectively. Under near-neutral conditions, hourly fluctuations in air–sea humidity and temperature differences are the major drivers of sub-daily variations in latent and sensible heat fluxes, respectively. When the boundary layer is stable, on the other hand, wind anomalies play a dominant role in shaping the sub-daily variations in latent and sensible heat fluxes. In the context of a convectively unstable boundary layer, wind anomalies exert a strong controlling influence on sub-daily variations in latent heat fluxes, whereas sub-daily variations in sensible heat fluxes are equally determined by air–sea temperature difference and wind anomalies. The relative contributions by all physical quantities that affect sub-daily variations in turbulent heat fluxes are further documented. For near-neutral and unstable boundary layers, the sub-daily contributions are О(2) and О(1) W·m−2 for latent and sensible heat fluxes, respectively, and they are less than О(1) W·m−2 for turbulent heat fluxes under stable conditions.

Open access
Yuqing Wang
,
Shang-Ping Xie
,
Haiming Xu
, and
Bin Wang

Abstract

A regional climate model is used to simulate boundary layer stratocumulus (Sc) clouds over the southeast Pacific off South America during August–October 1999 and to study their dynamical, radiative, and microphysical properties and their interaction with large-scale dynamic fields. Part I evaluates the model performance against satellite observations and examines physical processes important for maintaining the temperature inversion and Sc clouds in the simulation.

The model captures major features of the marine boundary layer in the region, including a well-mixed marine boundary layer, a capping temperature inversion, Sc clouds, and the diurnal cycle. The Sc clouds develop in the lower half of and below the temperature inversion layer that increases its height westward off the Pacific coast of South America. The strength of the capping inversion is determined not only by large-scale subsidence and local sea surface temperature (SST), but also by cloud–radiation feedback. A heat budget analysis indicates that upward longwave radiation strongly cools the upper part of the cloud layer and strengthens the temperature inversion. This cloud-top cooling further induces a local enhancement of subsidence in and below the inversion layer, resulting in a dynamical warming that strengthens the temperature stratification above the clouds.

While of secondary importance on the mean, solar radiation drives a pronounced diurnal cycle in the model boundary layer. Consistent with observations, boundary layer clouds thicken after sunset and cloud liquid water content reaches a maximum at 0600 local time just before the sunrise.

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Liu Yang
,
Jing-Wu Liu
,
Shang-Ping Xie
, and
Samuel S. P. Shen

Abstract

Over the midlatitude northwest Pacific Ocean, summer fog frequents the Kuroshio–Oyashio front as a result of the warm advection by the prevailing southerly to southwesterly winds, and stratus clouds are prevalent downstream of the fog regime in the subpolar northwest Pacific. The present study tracks a boundary layer air column along a typical northeastward trajectory along which fog on the sea surface temperature (SST) front makes its transition to stratus clouds. A turbulence-closure large-eddy simulation model can capture the evolution of the air column forced by the time-varying SST along the trajectory. Results show that the surface cooling effects across the SST front and the longwave radiative cooling (LRC) at the cloud top dominate the evolution of the boundary layer and the related turbulent processes. The sharp SST decrease across the SST front cools the surface layer, leading to condensation through shear-induced turbulence. Once the fog forms, the LRC at the fog top cools the boundary layer strongly through thermal turbulent mixing. The buoyancy-induced turbulence near the fog top entrains the warm and dry air from the free atmosphere into the boundary layer, reducing surface humidity and ultimately lifting the cloud base away from the sea surface to form stratus clouds. Sensitivity simulations also suggest that neither the latent heat flux from ocean nor and the diurnal solar variation is essential for the summer fog-to-stratus transition over the northwestern Pacific.

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Qian Wang
,
Su-Ping Zhang
,
Shang-Ping Xie
,
Joel R. Norris
,
Jian-Xiang Sun
, and
Yu-Xi Jiang

Abstract

A research vessel sailing across a warm eddy in the Kuroshio Extension on 13 April 2016 captured an abrupt development of stratocumulus under synoptic high pressure. Shipboard observations and results from regional atmospheric model simulations indicate that increased surface heat flux over the ocean eddy lowered surface pressure and thereby accelerated southeasterly winds. The southeasterly winds transported moisture toward the low pressure and enhanced the air–sea interface heat flux, which in turn deepened the low pressure and promoted low-level convergence and rising motion over the warm eddy. The lifting condensation level lowered and the top of the marine atmospheric boundary layer (MABL) rose, thereby aiding the development of the stratocumulus. Further experiments showed that 6°C sea surface temperature anomalies associated with the 400-km-diameter warm eddy accounted for 80% of the total ascending motion and 95% of total cloud water mixing ratio in the marine atmospheric boundary layer during the development of stratocumulus. The synthesis of in situ soundings and modeling contributes to understanding of the mechanism by which the MABL and marine stratocumulus respond to ocean eddies.

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William E. Chapman
,
Luca Delle Monache
,
Stefano Alessandrini
,
Aneesh C. Subramanian
,
F. Martin Ralph
,
Shang-Ping Xie
,
Sebastian Lerch
, and
Negin Hayatbini

Abstract

Deep-learning (DL) postprocessing methods are examined to obtain reliable and accurate probabilistic forecasts from single-member numerical weather predictions of integrated vapor transport (IVT). Using a 34-yr reforecast, based on the Center for Western Weather and Water Extremes West-WRF mesoscale model of North American West Coast IVT, the dynamically/statistically derived 0–120-h probabilistic forecasts for IVT under atmospheric river (AR) conditions are tested. These predictions are compared with the Global Ensemble Forecast System (GEFS) dynamic model and the GEFS calibrated with a neural network. In addition, the DL methods are tested against an established, but more rigid, statistical–dynamical ensemble method (the analog ensemble). The findings show, using continuous ranked probability skill score and Brier skill score as verification metrics, that the DL methods compete with or outperform the calibrated GEFS system at lead times from 0 to 48 h and again from 72 to 120 h for AR vapor transport events. In addition, the DL methods generate reliable and skillful probabilistic forecasts. The implications of varying the length of the training dataset are examined, and the results show that the DL methods learn relatively quickly and ∼10 years of hindcast data are required to compete with the GEFS ensemble.

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