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Gershunov, A, Michaelsen J, Gautier C.  1998.  Large-scale coupling between the tropical greenhouse effect and latent heat flux via atmospheric dynamics. Journal of Geophysical Research-Atmospheres. 103:6017-6031.   10.1029/97jd03520   AbstractWebsite

The clear-sky greenhouse effect (GE) is determined primarily by the amount and vertical distribution of water vapor in the atmospheric column. GE hampers surface radiative cooling and is maintained through surface evaporative cooling. This paper examines the intimate space-time relationships between the patterns of radiative heating of the atmosphere and sui-face evaporative cooling. We use data derived from satellite and in situ observations to show that tropical maritime GE is decoupled in space and time from latent heat flux (LHF), its source of water vapor. Large scale transport of atmospheric water vapor responsible for the observed relationships between GE and LHF is discussed. The spatial patterns of average GE and LHF are imbedded in the Walker and Hadley circulations and reinforce these circulations with strong evaporative cooling in the subtropical highs and greenhouse warning in the equatorial trough zones. Throughout tropical areas characterized by strong seasonality, the seasonal cycles of GE and LHF are out of phase. Much of the moisture that feeds GE in these off equatorial regions is advected by the Hadley circulation from tropical moisture Source regions of the opposite hemisphere. An out-of-phase relationship between GE and LHF also turns up on El Nino-Southern Oscillation timescales, most notably in the central tropical Pacific. The "super" greenhouse effect (SGE), a situation when GE absorption increases more than colocated surface longwave emission, is a seasonal feature of extensive tropical off-equatorial areas where it is maintained by moisture convergence and convection. On interannual timescales, the same dynamical processes appear to assert the SGE in the central equatorial Pacific. GE and LHF regimes are also described for the equatorial cold tongue and warm pool regions.

Westerling, AL, Gershunov A, Cayan DR, Barnett TP.  2002.  Long lead statistical forecasts of area burned in western US wildfires by ecosystem province. International Journal of Wildland Fire. 11:257-266.   10.1071/wf02009   AbstractWebsite

A statistical forecast methodology exploits large-scale patterns in monthly U.S. Climatological Division Palmer Drought Severity Index (PDSI) values over a wide region and several seasons to predict area burned in western US. wildfires by ecosystem province a season in advance. The forecast model, which is based on canonical correlations, indicates that a few characteristic patterns determine predicted wildfire season area burned. Strong negative associations between anomalous soil moisture (inferred from PDSI) immediately prior to the fire season and area burned dominate in most higher elevation forested provinces, while strong positive associations between anomalous soil moisture a year prior to the fire season and area burned dominate in desert and shrub and grassland provinces. In much of the western US., above- and below-normal fire season forecasts were successful 57% of the time or better, as compared with a 33% skill for a random guess, and with a low probability of being surprised by a fire season at the opposite extreme of that forecast.

Gershunov, A, Schneider N, Barnett T.  2001.  Low-frequency modulation of the ENSO-Indian monsoon rainfall relationship: Signal or noise? Journal of Climate. 14:2486-2492.   10.1175/1520-0442(2001)014<2486:lfmote>;2   AbstractWebsite

Running correlations between pairs of stochastic time series are typically characterized by low-frequency evolution. This simple result of sampling variability holds for climate time series but is not often recognized for being merely noise. As an example, this paper discusses the historical connection between El Nino-Southern Oscillation (ENSO) and average Indian rainfall (AIR). Decades of strong correlation (similar to -0.8) alternate with decades of insignificant correlation, and it is shown that this decadal modulation could be due solely to stochastic processes. In fact, the specific relationship between ENSO and AIR is significantly less variable on decadal timescales than should be expected from sampling variability alone.