Observed dependence of the water vapor and clear-sky greenhouse effect on sea surface temperature: comparison with climate warming experiments

1995 ◽  
Vol 11 (5) ◽  
pp. 307-320 ◽  
Author(s):  
Sandrine Bony ◽  
Jean-Philippe Duvel ◽  
Hervé Le Trent
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Warming ◽  
Greenhouse Effect ◽  
Sea Surface ◽  
Clear Sky

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 Variability of vertical structure of precipitation with sea surface temperature over the Arabian Sea and the Bay of Bengal as inferred by TRMM PR measurements

2018 ◽  
Author(s):  
Kadiri Saikranthi ◽  
Basivi Radhakrishna ◽  
Thota Narayana Rao ◽  
Sreedharan Krishnakumari Satheesh
Keyword(s):  
Water Vapor ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Bay Of Bengal ◽  
Arabian Sea ◽  
Vertical Structure ◽  
Tropical Rainfall Measuring Mission ◽  
Sea Surface ◽  
Cloud Formation ◽  
Freezing Level

Abstract. Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) 2A25 reflectivity profiles data during the period 1998–2013 are used to study the differences in the vertical structure of precipitation and its variation with sea surface temperature (SST) over the Arabian Sea (AS) and the Bay of Bengal (BOB). Even though the AS and the BOB are parts of the Indian Ocean, they exhibit distinct features in vertical structure of precipitation and its variation with SST. The variation of reflectivity and precipitation echo top occurrence with SST is remarkable over the AS but trivial over the BOB. The median reflectivity increases with SST at all heights below 10 km altitude, but the increase is prominent below the freezing level height over the AS. On the other hand, irrespective of altitude, reflectivity profiles are same at all SSTs over the BOB. To understand these differences, variation of aerosols, cloud and water vapor with SST is studied over these seas. At SSTs less than 27 °C, the observed high aerosol optical depth (AOD) and low total column water vapor (TCWV) over the AS results in small Cloud effective radius (CER) values and low reflectivity. As SST increases AOD decreases and TCWV increases, which result in large CER and high reflectivity. Over the BOB the change in AOD, TCWV and CER with SST is marginal. Thus, the observed variations in reflectivity profiles seem to be present from the cloud formation stage itself over both the seas.

scholarly journals Improving Satellite-Derived Sea Surface Temperature Accuracies Using Water Vapor Profile Data

2011 ◽  
Vol 28 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Ian J. Barton
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Sea Surface ◽  
Radiative Transfer Model ◽  
Clear Correlation ◽  
Transfer Model ◽  
The Difference

Abstract Analyses based on atmospheric infrared radiative transfer simulations and collocated ship and satellite data are used to investigate whether knowledge of vertical atmospheric water vapor distributions can improve the accuracy of sea surface temperature (SST) estimates from satellite data. Initially, a simulated set of satellite brightness temperatures generated by a radiative transfer model with a large maritime radiosonde database was obtained. Simple linear SST algorithms are derived from this dataset, and these are then reapplied to the data to give simulated SST estimates and errors. The concept of water vapor weights is introduced in which a weight is a measure of the layer contribution to the difference between the surface temperature and that measured by the satellite. The weight of each atmospheric layer is defined as the layer water vapor amount multiplied by the difference between the SST and the midlayer temperature. Satellite-derived SST errors are then plotted against the difference in the sum of weights above an altitude of 2.5 km and that below. For the simple two-channel (with typical wavelengths of 11 and 12 μm) analysis, a clear correlation between the weights differences and the SST errors is found. A second group of analyses using ship-released radiosondes and satellite data also show a correlation between the SST errors and the weights differences. The analyses suggest that, for an SST derived using a simple two-channel algorithm, the accuracy may be improved if account is taken of the vertical distribution of water vapor above the ocean surface. For SST estimates derived using algorithms that include data from a 3.7-μm channel, there is no such correlation found.

scholarly journals Mechanisms of Summertime Subtropical Southern Indian Ocean Sea Surface Temperature Variability: On the Importance of Humidity Anomalies and the Meridional Advection of Water Vapor*

2007 ◽  
Vol 20 (19) ◽  
pp. 4835-4852 ◽  
Author(s):  
A. M. Chiodi ◽  
D. E. Harrison
Keyword(s):  
Heat Flux ◽  
Water Vapor ◽  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Latent Heat Flux ◽  
Sea Surface ◽  
Sst Variability ◽  
Flux Variability ◽  
Meridional Advection

Abstract It is well known that some austral summertime subtropical Indian Ocean sea surface temperature (SST) variability correlates with rainfall over certain regions of Africa that depend on rainfall for their economic well-being. Recent studies have determined that this SST variability is at least partially driven by latent heat flux variability, but the mechanism has not been fully described. Here, the mechanism that drives this SST variability is reexamined using analyses of operational air–sea fluxes, ocean mixed layer modeling, and simple atmospheric boundary layer physics. The SST variability of interest is confirmed to be mainly driven by latent heat flux variability, which is shown, for the first time, to be mainly caused by near-surface humidity variability. This humidity variability is then shown to be fundamentally driven by the anomalous meridional advection of water vapor. The meridional wind anomalies of interest are subsequently found to occur when the subtropical atmospheric anticyclone is preferentially located toward one of the sides (east/west) of the basin.

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