scholarly journals Interactions among Cloud, Water Vapor, Radiation, and Large-Scale Circulation in the Tropical Climate. Part II: Sensitivity to Spatial Gradients of Sea Surface Temperature

2003 ◽  
Vol 16 (10) ◽  
pp. 1441-1455 ◽  
Author(s):  
Kristin Larson ◽  
Dennis L. Hartmann
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Sea Surface ◽  
Large Scale Circulation ◽  
High Cloud ◽  
Low Clouds ◽  
The Mean ◽  
Sst Gradient

Abstract The responses of the large-scale circulation, clouds, and water vapor to an imposed sea surface temperature (SST) gradient are investigated. Simulations compare reasonably to averaged observations over the Pacific, considering the simplifications applied to the model. The model responses to sinusoidal SST patterns have distinct circulations in the upper and lower troposphere. The upper circulation is sensitive to the heating from deep convection over the warmest SST. Stronger SST gradients are associated with stronger longwave cooling above stratus clouds in the subsidence region, stronger lower-tropospheric large-scale circulation, a reduction of the rain area, and larger area coverage of low clouds. A similar SST gradient with a warmer mean temperature produces slightly weaker lower-tropospheric circulation, and slightly reduced low cloud coverage. The outgoing longwave radiation (OLR) is not sensitive to the mean SST or the range of the imposed sinusoidal SST gradient. The positive feedbacks of water vapor and decreasing high cloud OLR compensate for the increase in longwave emission with increasing mean temperature in these simulations. As the SST gradient is increased keeping the mean SST constant, the positive high cloud feedback is still active, but the air temperature increases in proportion to the maximum SST in the domain, increasing the clear-sky OLR value and keeping the average OLR constant. The net absorbed shortwave radiation (SWI) is found to be extremely sensitive to the SST gradient. The stronger lower-tropospheric large-scale circulation produces a higher water content in the high and low clouds, increasing the absolute magnitude of the shortwave cloud forcing. A 25% increase in the maximum zonal mass flux of the lower circulation of the 300-K mean, 4-K SST range simulation leads to a 7.4 W m−2 decrease in SWI. Increasing the mean SST creates a positive feedback in these simulations because of the decrease in the lower-tropospheric large-scale circulation and the resultant decrease in cloud optical depth.

scholarly journals The Atmospheric Response to Weak Sea Surface Temperature Fronts*

2015 ◽  
Vol 72 (9) ◽  
pp. 3356-3377 ◽  
Author(s):  
Niklas Schneider ◽  
Bo Qiu
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Atmospheric Boundary Layer ◽  
Sea Surface Temperature ◽  
Wind Stress ◽  
Large Scale ◽  
Sea Surface ◽  
Coupling Coefficients ◽  
Wind Stress Curl ◽  
Sst Gradient

Abstract The response of the atmospheric boundary layer to fronts of sea surface temperature (SST) is characterized by correlations between wind stress divergence and the downwind component of the SST gradient and between the wind stress curl and the crosswind component of the SST gradient. The associated regression (or coupling) coefficients for the wind stress divergence are consistently larger than those for the wind stress curl. To explore the underlying physics, the authors introduce a linearized model of the atmospheric boundary layer response to SST-induced modulations of boundary layer hydrostatic pressure and vertical mixing in the presence of advection by a background Ekman spiral. Model solutions are a strong function of the SST scale and background advection and recover observed characteristics. The coupling coefficients for wind stress divergence and curl are governed by distinct physics. Wind stress divergence results from either large-scale winds crossing the front or from a thermally direct, cross-frontal circulation. Wind stress curl, expected to be largest when winds are parallel to SST fronts, is reduced through geostrophic spindown and thereby yields weaker coupling coefficients.

scholarly journals Interactions among Cloud, Water Vapor, Radiation, and Large-Scale Circulation in the Tropical Climate. Part I: Sensitivity to Uniform Sea Surface Temperature Changes

2003 ◽  
Vol 16 (10) ◽  
pp. 1425-1440 ◽  
Author(s):  
Kristin Larson ◽  
Dennis L. Hartmann
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Radiative Forcing ◽  
Cloud Amount ◽  
Sea Surface ◽  
Lapse Rate ◽  
High Cloud ◽  
Clear Sky

Abstract The responses of tropical clouds and water vapor to SST variations are investigated with simple numerical experiments. The fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model is used with doubly periodic boundary conditions and a uniform constant sea surface temperature (SST). The SST is varied and the equilibrium statistics of cloud properties, water vapor, and circulation at different temperatures are compared. The top of the atmosphere (TOA) radiative fluxes have the same sensitivities to SST as in observations averaged from 20°N to 20°S over the Pacific, suggesting that the model sensitivities are realistic. As the SST increases, the temperature profile approximately follows a moist-adiabatic lapse rate. The rain rate and cloud ice amounts increase with SST. The average relative humidity profile stays approximately constant, but the upper-tropospheric relative humidity increases slightly with SST. The clear-sky mean temperature and water vapor feedbacks have similar magnitudes to each other and opposite signs. The net clear-sky feedback is thus about equal to the lapse rate feedback, which is about −2 W m−2 K−1. The clear-sky outgoing longwave radiation (OLR) thus increases with SST, but the high cloud-top temperature is almost constant with SST, and the high cloud amount increases with SST. The result of these three effects is an increase of cloud longwave forcing with SST and a mean OLR that is almost independent of SST. The high cloud albedo remains almost constant with increasing SST, but the increase in high cloud area causes a negative shortwave cloud radiative forcing feedback, which partly cancels the longwave cloud feedback. The net radiation decreases slightly with SST, giving a small net negative feedback, implying a stable, but very sensitive climate.

Correcting infrared satellite estimates of sea surface temperature for atmospheric water vapor attenuation

1994 ◽  
Vol 99 (C3) ◽  
pp. 5219 ◽  
Author(s):  
William J. Emery ◽  
Yunyue Yu ◽  
Gary A. Wick ◽  
Peter Schluessel ◽  
Richard W. Reynolds
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Atmospheric Water Vapor ◽  
Atmospheric Water

scholarly journals Statistical Downscaling Forecasts for Winter Monsoon Precipitation in Malaysia Using Multimodel Output Variables

2010 ◽  
Vol 23 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Liew Juneng ◽  
Fredolin T. Tangang ◽  
Hongwen Kang ◽  
Woo-Jin Lee ◽  
Yap Kok Seng
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Winter Season ◽  
Peninsular Malaysia ◽  
Sea Surface ◽  
Asia Pacific ◽  
Forecast Data ◽  
Multimodel Ensembles

Abstract This paper compares the skills of four different forecasting approaches in predicting the 1-month lead time of the Malaysian winter season precipitation. Two of the approaches are based on statistical downscaling techniques of multimodel ensembles (MME). The third one is the ensemble of raw GCM forecast without any downscaling, whereas the fourth approach, which provides a baseline comparison, is a purely statistical forecast based solely on the preceding sea surface temperature anomaly. The first multimodel statistical downscaling method was developed by the Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) team, whereas the second is based on the canonical correlation analysis (CCA) technique using the same predictor variables. For the multimodel downscaling ensemble, eight variables from seven operational GCMs are used as predictors with the hindcast forecast data spanning a period of 21 yr from 1983/84 to 2003/04. The raw GCM forecast ensemble tends to have higher skills than the baseline skills of the purely statistical forecast that relates the dominant modes of observed sea surface temperature variability to precipitation. However, the downscaled MME forecasts have higher skills than the raw GCM products. In particular, the model developed by APCC showed significant improvement over the peninsular Malaysia region. This is attributed to the model’s ability to capture regional and large-scale predictor signatures from which the additional skills originated. Overall, the results showed that the appropriate downscaling technique and ensemble of various GCM forecasts could result in some skill enhancement, particularly over peninsular Malaysia, where other models tend to have lower or no skills.

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