An empirical model for the statistics of sea surface diurnal warming

A statistical model is derived relating the diurnal variation of sea surface temperature (SST) to the net surface heat flux and surface wind speed from a numerical weather prediction (NWP) model. The model is derived using fluxes and winds from the European Centre for Medium-Range Weather Forecastin...

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Main Authors: M. J. Filipiak, C. J. Merchant, H. Kettle, P. Le Borgne
Format: Article
Language:English
Published: Copernicus Publications 2012-03-01
Series:Ocean Science
Online Access:http://www.ocean-sci.net/8/197/2012/os-8-197-2012.pdf
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spelling doaj-79b38e210030491686f0275298dee2aa2020-11-25T01:35:03ZengCopernicus PublicationsOcean Science1812-07841812-07922012-03-018219720910.5194/os-8-197-2012An empirical model for the statistics of sea surface diurnal warmingM. J. FilipiakC. J. MerchantH. KettleP. Le BorgneA statistical model is derived relating the diurnal variation of sea surface temperature (SST) to the net surface heat flux and surface wind speed from a numerical weather prediction (NWP) model. The model is derived using fluxes and winds from the European Centre for Medium-Range Weather Forecasting (ECMWF) NWP model and SSTs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In the model, diurnal warming has a linear dependence on the net surface heat flux integrated since (approximately) dawn and an inverse quadratic dependence on the maximum of the surface wind speed in the same period. The model coefficients are found by matching, for a given integrated heat flux, the frequency distributions of the maximum wind speed and the observed warming. Diurnal cooling, where it occurs, is modelled as proportional to the integrated heat flux divided by the heat capacity of the seasonal mixed layer. The model reproduces the statistics (mean, standard deviation, and 95-percentile) of the diurnal variation of SST seen by SEVIRI and reproduces the geographical pattern of mean warming seen by the Advanced Microwave Scanning Radiometer (AMSR-E). We use the functional dependencies in the statistical model to test the behaviour of two physical model of diurnal warming that display contrasting systematic errors.http://www.ocean-sci.net/8/197/2012/os-8-197-2012.pdf
collection DOAJ
language English
format Article
sources DOAJ
author M. J. Filipiak
C. J. Merchant
H. Kettle
P. Le Borgne
spellingShingle M. J. Filipiak
C. J. Merchant
H. Kettle
P. Le Borgne
An empirical model for the statistics of sea surface diurnal warming
Ocean Science
author_facet M. J. Filipiak
C. J. Merchant
H. Kettle
P. Le Borgne
author_sort M. J. Filipiak
title An empirical model for the statistics of sea surface diurnal warming
title_short An empirical model for the statistics of sea surface diurnal warming
title_full An empirical model for the statistics of sea surface diurnal warming
title_fullStr An empirical model for the statistics of sea surface diurnal warming
title_full_unstemmed An empirical model for the statistics of sea surface diurnal warming
title_sort empirical model for the statistics of sea surface diurnal warming
publisher Copernicus Publications
series Ocean Science
issn 1812-0784
1812-0792
publishDate 2012-03-01
description A statistical model is derived relating the diurnal variation of sea surface temperature (SST) to the net surface heat flux and surface wind speed from a numerical weather prediction (NWP) model. The model is derived using fluxes and winds from the European Centre for Medium-Range Weather Forecasting (ECMWF) NWP model and SSTs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In the model, diurnal warming has a linear dependence on the net surface heat flux integrated since (approximately) dawn and an inverse quadratic dependence on the maximum of the surface wind speed in the same period. The model coefficients are found by matching, for a given integrated heat flux, the frequency distributions of the maximum wind speed and the observed warming. Diurnal cooling, where it occurs, is modelled as proportional to the integrated heat flux divided by the heat capacity of the seasonal mixed layer. The model reproduces the statistics (mean, standard deviation, and 95-percentile) of the diurnal variation of SST seen by SEVIRI and reproduces the geographical pattern of mean warming seen by the Advanced Microwave Scanning Radiometer (AMSR-E). We use the functional dependencies in the statistical model to test the behaviour of two physical model of diurnal warming that display contrasting systematic errors.
url http://www.ocean-sci.net/8/197/2012/os-8-197-2012.pdf
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