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The gradient flux technique, which measures the gas transfer velocity (k), and new observational techniques that probe turbulence in the aqueous surface boundary layers were conducted over a tidal cycle in the Plum Island Sound, Massachusetts. Efforts were aimed at testing new methods in an estuarine system and to determine if turbulence created by tidal velocity can be responsible for the short-term variability ink. Measurements were made during a low wind day, at a site with tidal excursions of 2.7 m and a range in tidal velocity of nearly 1 m s−1. Estimates ofk using the gradient flux technique were made simultaneously with the Controlled Flux Technique (CFT), infrared imagery, and high-resolution turbulence measurements, which measure the surface renewal rate, turbulent scales, and the turbulent dissipation rate, respectively. All measurements were conducted from a small mobile catamaran that minimizes air- and water-side flow distortions. Infrared imagery showed considerable variability in the turbulent scales that affect air-water gas exchange. These measurements were consistent with variation in the surface renewal rate (range 0.02 to 2 s−1), the turbulent dissipation rate (range 10−7 to 10−5 W kg−1), andk (range 2.2 to 12.0 cm hr−1). During this low wind day, all variables were shown to correlate with tidal speed. Taken collectively our results indicate the promise of these methods for determining short-term variability in gas transfer and near surface turbulence in estuaries and demonstrate that turbulent transport associated with tidal velocity is a potentially important factor with respect to gas exchange in coastal systems.  相似文献   
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The atmosphere and the ocean are subject to many dynamical instabilities, which limit the time during which their behaviour can be deterministically forecasted. At longer timescales, the atmosphere can be predicted at best using statistical methods, as a response to external forcing linked to sea- and land-surface anomalies. Climate being defined as the mean of atmospheric states, it appears that it can be predicted up to a few months in advance, which is the characteristic time of the so-called slow components of the climate system. Forecasting can sometimes be extended to longer time ranges, especially when the coupled ocean–atmosphere system exhibits internal variability modes, with characteristic times of a few years. Seasonal climate forecasting is most often based upon Monte-Carlo simulations, where the various realisations correspond to slightly different initial conditions. The present sate-of-the-art in Europe (ECMWF) and/or in the USA (IRI) allows to forecast such major phenomena, as El Niño, up to six months in advance. Finally, some parameters may exhibit predictability at still longer time-ranges (inter-annual to decadal), but only for certain regions. The example of electricity production is used to underline the potentially large economical benefit of seasonal climate forecasting. To cite this article: J.-C. André et al., C. R. Geoscience 334 (2002) 1115–1127.

Résumé

L'atmosphère et l'océan sont le siège d'instabilités dynamiques, qui limitent la durée pendant laquelle il est possible d'en prévoir l'évolution de façon déterministe. Au-delà, l'atmosphère n'est plus prévisible, au mieux, que de façon statistique, en fonction du forçage externe qu'exerce(nt) sur elle l'océan et/ou la surface des continents. Le climat (au sens d'une moyenne des états atmosphériques) se révèle ainsi prévisible jusqu'à des échéances temporelles de quelques mois, échelle de temps caractéristique des composantes dites « lentes » du système climatique. La prévision peut s'étendre à des échéances parfois plus longues, dans le cas où le système couplé océan–atmosphère posséderait des modes de variabilité temporelle de périodes caractéristiques de quelques années. La prévision climatique saisonnière est très souvent construite à partir de simulations de type Monte-Carlo, avec des ensembles de réalisations utilisant des conditions initiales légèrement différentes. Dans l'état actuel de ces prévisions, qu'elles soient réalisées en Europe (CEPMMT) ou aux États-Unis (IRI), il est possible de prévoir environ six mois à l'avance un certain nombre de phénomènes climatiques, en particulier ceux liés aux épisodes dits « El Niño », pour lesquels l'amplitude des variations est suffisamment importante. Il existe, par ailleurs, une prévisibilité à encore plus longue échéance (inter-annuelle à décennale), mais seulement pour certains paramètres et certaines régions. L'exemple de la production d'électricité montre l'importance économique potentielle très grande de la prévision climatique saisonnière. Pour citer cet article : J.-C. André et al., C. R. Geoscience 334 (2002) 1115–1127.  相似文献   
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Crétat  Julien  Braconnot  Pascale  Terray  Pascal  Marti  Olivier  Falasca  Fabrizio 《Climate Dynamics》2020,55(9-10):2761-2784

The low-frequency evolution of Indian rainfall mean-state and associated interannual-to-decadal variability is discussed for the last 6000 years from a multi-configuration ensemble of fully coupled global transient simulations. This period is marked by a shift of Indian Summer Monsoon Rainfall (ISMR) distribution towards drier conditions, including extremes, and a contraction of the rainy season. The drying is larger in simulations with higher horizontal resolution of the atmosphere and revised land surface hydrology. Vegetation–climate interactions and the way runoff is routed to ocean modulate the timing of the monsoon onset but have negligible effects on the evolution of seasonal rainfall amounts in our modeling framework in which carbon cycling is always active. This drying trend is accompanied by changes in ISMR interannual-to-decadal variability decreasing over north and south India but increasing over central India (20°–25° N). The ISMR interannual-to-decadal variability is decomposed into six physically consistent regimes using a clustering technique to further characterize its changes and associated teleconnections. From 6 to 3.8 kyr bp, the century-to-century modulations in the frequency of occurrence associated to the regimes are asynchronous between the simulations. Orbitally-driven trends can only be detected for two regimes over the whole 6–0 kyr bp period. These two regimes reflect increased influence of ENSO on both ISMR and Indian Ocean Dipole as the inter-hemispheric energy gradient weakens. Severe long-term droughts are also shown to be a combination of long-term drying and internally generated low-frequency modulations of the interannual-to-decadal variability.

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In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.  相似文献   
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The SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled models. The model also exhibits reasonable skill in simulating coherent northward propagating monsoon intraseasonal anomalies including SST and precipitation, which are generally consistent with observed ISV characteristics. Results from the observations and the model establish the existence of spatial variability in the atmospheric convective response to SST anomalies, over the Asian monsoon domain on intraseasonal timescales. The response is fast over the Arabian Sea, where precipitation lags SST by ~5 days; whereas it is slow over the Bay of Bengal and South China Sea, with a lag of ~12 days. The intraseasonal SST anomalies result in a similar atmospheric response across the basins, which consists of a destabilization of the bottom of the atmospheric column, as observed from the equivalent potential temperature anomalies near the surface. However, the presence of a relatively strong surface convergence over the Arabian Sea, due to the presence of a strong zonal gradient in SST, which accelerates the upward motion of the moist air, results in a relatively faster response in terms of the local precipitation anomalies over the Arabian Sea than over the Bay of Bengal and South China Sea. With respect to the observations, the ocean–atmosphere coupling is well simulated in the model, though with an overestimation of the intraseasonal SST anomalies, leading to an exaggerated SST-precipitation relationship. A detailed examination points to a systematic bias in the thickness of the mixed layer of the ocean model, which needs to be rectified. A too shallow (deep) mixed layer enhances (suppress) the amplitude of the intraseasonal SST anomalies, thereby amplifying (lessening) the ISV and the active-break phases of the monsoon in the model.  相似文献   
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This study examines the feasibility of using a variable resolution global general circulation model (GCM), with telescopic zooming and enhanced resolution (~35 km) over South Asia, to better understand regional aspects of the South Asian monsoon rainfall distribution and the interactions between monsoon circulation and precipitation. For this purpose, two sets of ten member realizations are produced with and without zooming using the LMDZ (Laboratoire Meteorologie Dynamique and Z stands for zoom) GCM. The simulations without zoom correspond to a uniform 1° × 1° grid with the same total number of grid points as in the zoom version. So the grid of the zoomed simulations is finer inside the region of interest but coarser outside. The use of these finer and coarser resolution ensemble members allows us to examine the impact of resolution on the overall quality of the simulated regional monsoon fields. It is found that the monsoon simulation with high-resolution zooming greatly improves the representation of the southwesterly monsoon flow and the heavy precipitation along the narrow orography of the Western Ghats, the northeastern mountain slopes and northern Bay of Bengal (BOB). A realistic Monsoon Trough (MT) is also noticed in the zoomed simulation, together with remarkable improvements in representing the associated precipitation and circulation features, as well as the large-scale organization of meso-scale convective systems over the MT region. Additionally, a more reasonable simulation of the monsoon synoptic disturbances (lows and disturbances) along the MT is noted in the high-resolution zoomed simulation. On the other hand, the no-zoom version has limitations in capturing the depressions and their movement, so that the MT zone is relatively dry in this case. Overall, the results from this work demonstrate the usefulness of the high-resolution variable resolution LMDZ model in realistically capturing the interactions among the monsoon large-scale dynamics, the synoptic systems and the meso-scale convective systems, which are essential elements of the South Asian monsoon system.  相似文献   
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