On a Stochastic Model for Moisture Budget in an Eulerian Atmospheric Column

1997 ◽  
Vol 8 (5) ◽  
pp. 425-440 ◽  
Author(s):  
Mark Freidlin ◽  
Harry Pavlopoulos
2021 ◽  
Author(s):  
Kerry H Cook ◽  
Edward K. Vizy

Abstract The processes that determine the seasonality of precipitation in the Congo Basin are examined using the atmospheric column moisture budget. Studying the fundamental determinants of Congo Basin precipitation seasonality supports process-based studies of variations on all time scales, including those associated with greenhouse gas-induced global warming. Precipitation distributions produced by the ERA5 reanalysis provide sufficient accuracy for this analysis, which requires a consistent dataset to relate the atmospheric dynamics and moisture distribution to the precipitation field. The Northern and Southern Hemisphere regions of the Congo Basin are examined separately to avoid the misconception that Congo Basin rainfall is primarily bimodal. While evapotranspiration is indispensable for providing moisture to the atmospheric column to support precipitation in the Congo Basin, its seasonal variations are small and it does not drive precipitation seasonality. During the equinoctial seasons, precipitation is primarily supported by meridional wind convergence in the moist environment in the 800 hPa to 500 hPa layer where moist air flows into the equatorial trough. Boreal fall rains are stronger than boreal spring rains in both hemispheres because low-level moisture divergence develops in boreal spring in association with the developing Saharan thermal low. The moisture convergence term also dominates the moisture budget during the summer season in both hemispheres, with meridional convergence in the 850-600 hPa layer as cross-equatorial flow interacts with the cyclonic flow about the Angola and Sahara thermal lows. Winter precipitation is low because of dry air advection from the winter hemisphere subtropical highs over the continent.


1964 ◽  
Vol 9 (7) ◽  
pp. 273-276
Author(s):  
ANATOL RAPOPORT
Keyword(s):  

1996 ◽  
Vol 6 (4) ◽  
pp. 445-453 ◽  
Author(s):  
Roberta Donato
Keyword(s):  

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.


2011 ◽  
Vol 131 (2) ◽  
pp. 303-310
Author(s):  
Ji-Sun Shin ◽  
Cheng-You Cui ◽  
Tae-Hong Lee ◽  
Hee-hyol Lee

2008 ◽  
Vol 11 (6) ◽  
pp. 507-524
Author(s):  
Don Kulasiri ◽  
Sean Richards

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