De Bruin och Hartogensis har föreslagit en ny metod för att beräkna impulsflödet och det sensibla värmeflödet vid stabila förhållanden. Metoden bygger på att de normaliserade standardavvikelserna är approximativt konstanta för den horisontella vinden och temperaturen. Beräkningarna görs endast utifrån medelvinden och temperaturen och dess standardavvikelser. Den här metoden testas i den här studien med datamaterial från Labans kvarnar på Gotland i Östersjön och Östergarnsholm som ligger 4 km utanför Gotland. Labans kvarnar representerar flöden över land och Östergarnsholm flöden över hav. Konstanterna som De Bruin och Hartogensis använde är följande: Cu=2.5 och CT=2.3, vilket gav en mycket liten spridning i deras beräkningar av flöden. Datamaterialet de använde sig av var från Kansas, USA, över en plan grässlätt. Olika statistiska mått har här testats för att erhålla värden på konstanterna. Medel-, median- och typvärde för de normaliserade standardavvikelserna för respektive kvantitet har beräknats. För landförhållanden i den här studien fås lite högre värden på konstanterna, Cu=2.6 och CT=2.6, än vad De Bruin och Hartogensis erhöll.  Vid beräkningar av flöden över hav delas vindriktningen upp i två intervall. Vindriktningen som ligger mellan 220o - 300o representerar vindar som blåser ifrån Gotland och vindriktningar som ligger mellan 80o - 220o representerar vindar från öppet hav. För öppna havsförhållanden fås konstanter som har ett lägre värde vid beräkning av impulsflödet, Cu=2.2 , än de värde som De Bruin och Hartogensis fick. För vindar som blåser ifrån Gotland erhålls konstanten till:Cu=3.0. Konstanter för beräkning av värmeflödet är svårare att bestämma och ger inte alls lika bra resultat över hav som för impulsflödet. Bestämningar av värmeflöde är mycket mer komplicerade än för impulsflöde. Delvis på grund av att det behövs två konstanter, men det beror också på att temperaturstrukturen i det marina gränsskiktet inte följer Monin-Obukhovs similaritetsteori.Framsidans foto / De Bruin and Hartogensis have proposed a new method to determine momentum flux and sensible heat flux at stable conditions. When using this method the assumption is made that the standard deviations for the longitudinal wind component and temperature are approximately constant. Only the mean wind and the temperature and the standard deviations are necessary for the calculations. The method has been analyzed in this study with data from Labans kvarnar sited on Gotland in the Baltic Sea and Östergarnsholm which is situated 4 km outside Gotland. Labans kvarnar represents fluxes over land and Östergarnsholm represents fluxes over sea. The constants that De Bruin and Hartogensis found are the following:Cu=2.5 for wind speed and CT=2.3  for temperature, which shows very little scatter in the calculations of the fluxes. The data they used where measured in Kansas over a very flat grassland site. Different statistics measurements have been tested to receive values of the constants. In search of constants the mean value, median value and the modal value for respectively quantity have been calculated. For land conditions the values of the constants are a little bit higher, Cu=2.6 and CT=2.6, than the values De Bruin and Hartogensis received. When calculating the fluxes over ocean the wind direction is divided in to two intervals. The wind direction between 220o - 300o represents winds from Gotland and wind direction between  80o - 220o represents winds from open sea. For the open sea conditions the constants calculated for the momentum flux in this study are a little bit lower, Cu=2.2, than the value De Bruin and Hartogensis found. For winds from Gotland the constant for momentum flux was found to be: Cu=3.0. When calculating the sensible heat flux the constants are very difficult to find and do not give as good result as for the momentum flux over sea. The conditions for the sensible heat are much more complicated than it is for momentum flux. Firstly two constants are needed and secondly the temperature structure in the marine boundary layer does not follow Monin-Obukhov similarity theory.

La température de surface de l'océan (SST) est depuis l'avènement des satellites, l'une des variables océaniques la mieux observée. Les modèles réalistes de circulation générale océanique ne la prennent pourtant pas en compte explicitement dans leur fonction de forçage. Dans cette dernière, seules interviennent les variables atmosphériques à proximité de la surface (température, humidité, vitesse du vent, radiations descendantes et précipitations) connues pour être entachées d'incertitudes importantes dès lors qu'on considère l'objectif d'étudier la variabilité à long terme de l'océan et son rôle climatique. La SST est alors classiquement utilisée en assimilation de données pour contraindre l'état du modèle vers une solution en accord avec les observations mais sans corriger la fonction de forçage. Cette approche présente cependant les inconvénients de l'incohérence existant potentiellement entre la solution « forcée » et « assimilée ». On se propose dans cette thèse de développer dans un contexte réaliste une méthode d'assimilation de données de SST observée pour corriger les paramètres de forçage atmosphérique sans correction de l'état océanique. Le jeu de forçage faisant l'objet de ces corrections est composé des variables atmosphériques issues de la réanalyse ERAinterim entre 1989 et 2007. On utilise pour l'estimation de paramètres une méthode séquentielle basée sur le filtre de Kalman, où le vecteur d'état est augmenté des variables de forçage dont la distribution de probabilité a priori est évaluée via des expériences d'ensemble. On évalue ainsi des corrections de forçage mensuelles applicables dans un modèle libre pour la période 1989-2007 en assimilant la SST issue de la base de données de Hurrel (Hurrel, 2008), ainsi qu'une climatologie de salinité de surface (Levitus, 1994). Cette étude démontre la faisabilité d'une telle démarche dans un contexte réaliste, ainsi que l'amélioration de la représentation des flux océan-atmosphère par l'exploitation d'observations de la surface de l'océan. / Sea surface temperature (SST) is more accurately observed from space than near-surface atmospheric variables and air-sea fluxes. But ocean general circulation models for operational forecasting or simulations of the recent ocean variability use, as surface boundary conditions, bulk formulae which do not directly involve the observed SST. In brief, models do not use explicitly in their forcing one of the best observed ocean surface variable, except when assimilated to correct the model state. This classical approach presents however some inconsistency between the “assimilated” solution of the model and the “forced” one. The objective of this research is to develop in a realistic context a new assimilation scheme based on statistical methods that will use SST satellite observations to constrain (within observation-based air-sea flux uncertainties) the surface forcing function (surface atmospheric input variables) of ocean circulation simulations. The idea is to estimate a set of corrections for the atmospheric input data from ERAinterim reanalysis that cover the period from 1989 to 2007. We use a sequential method based on the SEEK filter, with an ensemble experiment to evaluate parameters uncertainties. The control vector is extended to correct forcing parameters (air temperature, air humidity, downward longwave and shortwave radiations, precipitation, wind velocity). Over experiments of one month duration, we assimilate observed monthly SST products (Hurrel, 2008) and SSS seasonal climatology (Levitus, 1994) data, to obtain monthly parameters corrections that we can use in a free run model This study shows that we can thus produce in a realistic case, on a global scale, and over a large time period, an optimal flux correction set that improves the forcing function of an ocean model using sea surface observations.

Around Sri Lanka and to the south of India sea surface temperatures (SST) are cooler compared to the surrounding region during summer monsoon. This region where SSTs are relatively cooler is known as the cold pool. Owing to its possible impact on monsoon variability, some studies have been carried out to understand the evolution of cold pool SST during this period. These studies suggest, coastal upwelling along southern coast of Sri Lanka and eastward advection of cooler water contributes to the decrease in SST during summer monsoon. However, the processes leading to the formation of cold pool, still, remain unknown. In this study, we have investigated the mechanism responsible for the formation and maintenance of southern Bay of Bengal (BOB) cold pool using high resolution satellite data, model simulations and in-situ observations for the year 2009. Our study reveals formation of cold pool is dominated by atmospheric processes, whereas oceanic processes dominate its maintenance. Cooling of SSTs during premonsoon and onset phase acts as a prerequisites for the formation of cold pool, which are linked to the reduction in Net Heat flux (NHFX) during theses periods. The changes in NHFX during premonsoon and onset phase are dominated by reduction in Short-wave (SW) radiation associated with strong convective activity over cold pool. Convective activity over the cold pool are associated with the northward movement of Maximum Cloud Zone (MCZ) that forms over Equatorial Indian Ocean (EIO) during these periods. SST within the cold pool after the steady increase during February-April months, cools first during premonsoon rain event and then during monsoon onset. Analysis of high resolution satellite data for the period 2003-2009 suggest that, these sequence of events occurs with minor amount of inter-annual variability. Lead-lag correlation also made it clear that SST response in 5 days to the corresponding variation in atmospheric processes. SST within the cold pool shows several intraseasonal cooling events during the summer mon-soon. Considering that rainfall above the cold pool is very low during the summer monsoon, these cooling events occurring within the summer should be necessary for maintaining the cold pool. The seasonal evolution of SST shows that it continues to decrease till the end of the summer monsoon. In-situ data collected during CTCZ field program in 2009, at two time series locations (TSL) and model simulations were used to determine the processes responsible for such cooling events. To estimate the contribution from advection to the observed SST tendency at fixed location, a measurement stratergy called ‘opertaion advection’ was used in this study. This stratergy involves measurement of oceanographic parameters along four edges from TSL directod along North, South, East and West for estimation of horizontal temperature gradients. Our results from SST cooling events captured by CTD at two fixed locations suggests that horizontal advection and entrainment dominate the SST evolution. Model temperature equation evaluated near the TSLs are convinient with the observations and suggest that atmospheric forcing is not responsible for intraseasonal cooling events.