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Jean Philippe Duvel, Rémy Roca, and Jérôme Vialard

Abstract

In situ and satellite observations reveal that the tropical intraseasonal oscillation is occasionally associated with large variations in sea surface temperature (SST). The purpose of this paper is to find the physical origin of such strong SST perturbations (up to 3 K) over the Indian Ocean by examining two intraseasonal events in January and March 1999. Analysis of SST data from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and from drifting buoys reveals that these two intraseasonal events deeply modify the SST field between the equator and 10°S, while the surface flux perturbation extends over a wide area of the tropical Indian Ocean. Forced ocean general circulation model (OGCM) simulations are successful in reproducing the spatial patterns of this intraseasonal SST variability albeit with a weaker amplitude. The weaker amplitude given by the OGCM is partly related to the absence of warm-layer formation in the model. The model simulation reveals that the background oceanic subsurface structure explains the observed latitudinal distribution of the SST perturbations. For the Indian Ocean, the Ekman pumping (reinforced in 1999 due to La Niña conditions) gives a thermocline close to the surface between 5° and 10°S that inhibits the deepening of the mixed layer during strong wind episodes and thus gives a mixed layer temperature more reactive to surface forcing. Other factors like the Ekman dynamics associated with the wind burst and the precipitation perturbation south of the equator also contribute toward preventing the deepening of the mixed layer. For these regions, as is found over the western Pacific, the intraseasonal variability of the SST is mainly driven by the surface fluxes perturbation, and not by advection or exchanges with the subsurface. As a consequence, the phasing and the magnitude of convective and large-scale dynamical perturbations of the surface fluxes, which are regionally dependent, are also determinant factors for the local amplitude of the SST perturbation. Finally, results show a relation at interannual time scales between the thermocline structure and the mixed layer depth south of the equator that may have consequences on interannual changes in the intraseasonal activity over the Indian Ocean.

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Carsten Standfuss, Michel Viollier, Robert S. Kandel, and Jean Philippe Duvel

Abstract

A regional (2.5° × 2.5° resolved) diurnal (hourly) albedo climatology for low and midlatitudes is derived for each month from the 5⅓-yr narrow-field-of-view data record obtained from the Earth Radiation Budget Satellite (ERBS). It is used in a quasi-operational diurnal interpolation/extrapolation procedure (DIEP) to calculate regional monthly means of the reflected shortwave radiation flux (RSR) from instantaneous albedo observations. This climatological approach (CDIEP) replaces the questionable assumption of diurnally constant cloud conditions made in the conventional DIEP by assuming a diurnal variation of cloudiness corresponding to the mean long-term diurnal variation of the planetary albedo. Validation of CDIEP, using the three-satellite Earth Radiation Budget Experiment (ERBE) data for December of 1986, indicates that on regional scales monthly time sampling errors for single satellite products are generally reduced but not completely removed in comparison with the currently applied diurnal model (EDIEP). On a global scale, rms errors are reduced by 16% and 28% for ERBE NOAA-10 and NOAA-9 monthly mean RSR, respectively. The efficiency of CDIEP is satisfactory by accounting for coherent diurnal variations of cloudiness, if present, and by reproducing the results obtained by EDIEP elsewhere.

Applying CDIEP to the full-year record of ScaRaB-Meteor ERB measurements enables the analysis of its impact with regard to the varying local observation time of each month. The standard deviation between regional monthly means of the RSR calculated by CDIEP and EDIEP varies between less than 2 W m−2 and about 4 W m−2 for high-noon and near-terminator time sampling conditions, respectively. On regional scales, time sampling errors with a 3½-month period, induced by the orbit’s precession, can be reduced, in particular for marine areas characterized by persistent stratocumulus, where the amplitude often exceeds 10 W m−2.

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Prince K. Xavier, Jean-Philippe Duvel, and Francisco J. Doblas-Reyes

Abstract

The intraseasonal variability (ISV) of the Asian summer monsoon represented in seven coupled general circulation models (CGCMs) as part of the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) project is analyzed and evaluated against observations. The focus is on the spatial and seasonal variations of ISV of outgoing longwave radiation (OLR). The large-scale organization of convection, the propagation characteristics, and the air–sea coupling related to the monsoon ISV are also evaluated. A multivariate local mode analysis (LMA) reveals that most models produce less organized convection and ISV events of shorter duration than observed. Compared to the real atmosphere, these simulated patterns of perturbations are poorly reproducible from one event to the other. Most models simulate too weak sea surface temperature (SST) perturbations and systematic phase quadrature between OLR, surface winds, and SST—indicative of a slab-ocean-like response of the SST to surface flux perturbations. The relatively coarse vertical resolution of the different ocean GCMs (OGCMs) limits their ability to represent intraseasonal processes, such as diurnal warm layer formation, which are important for realistic simulation of the SST perturbations at intraseasonal time scales. Models with the same atmospheric GCM (AGCM) and different OGCMs tend to have similar biases of the simulated ISV, indicating the dominant role of atmospheric models in fixing the nature of the intraseasonal variability. It is, therefore, implied that improvements in the representation of ISV in coupled models have to fundamentally arise from fixing problems in the large-scale organization of convection in AGCMs.

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Jean Philippe Duvel, Sophie Bouffiès-Cloché, and Michel Viollier

Abstract

The error resulting from the use of a visible channel to estimate shortwave (SW) (0.2–4 μm) fluxes reflected by the earth is analyzed. First, the authors compute regression coefficients between visible (0.55–0.65 μm) and SW radiance measurements made by the ScaRaB (Scanner for Radiation Budget) instrument aboard the Meteor-3/7 satellite between March 1994 and February 1995. These regression coefficients are computed from the 10 months of available ScaRaB measurements in different classes of geotypes and different classes of solar and viewing angles. The regression is applied to the visible radiance measurements to simulate the SW measurements in the operational processing of ScaRaB.

For instantaneous fluxes, the visible-to-SW conversion gives a standard deviation of the error smaller than 8%. By comparison, the standard deviation of the instantaneous flux error coming from the angular sampling and the bidirectional reflectance uncertainty is estimated to be about 10%. For monthly mean values the standard deviation of the error is smaller than 4% and is comparable to the expected temporal sampling error made by two polar orbiting satellites. In addition, using ScaRaB visible data with these regression coefficients and with the ScaRaB processing gives a bias smaller than 2% for either instantaneous or monthly mean fluxes. However, calibration and processing problems certainly remain important practical issues for the determination of the earth planetary albedo using only narrowband radiometers.

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Sara Shamekh, Caroline Muller, Jean-Philippe Duvel, and Fabio D’Andrea

Abstract

We investigate the role of a warm sea surface temperature (SST) anomaly (hot spot of typically 3 to 5 K) on the aggregation of convection using cloud-resolving simulations in a nonrotating framework. It is well known that SST gradients can spatially organize convection. Even with uniform SST, the spontaneous self-aggregation of convection is possible above a critical SST (here 295 K), arising mainly from radiative feedbacks. We investigate how a circular hot spot helps organize convection, and how self-aggregation feedbacks modulate this organization. The hot spot significantly accelerates aggregation, particularly for warmer/larger hot spots, and extends the range of SSTs for which aggregation occurs; however, at cold SST (290 K) the aggregated cluster disaggregates if we remove the hot spot. A large convective instability over the hot spot leads to stronger convection and generates a large-scale circulation which forces the subsidence drying outside the hot spot. Indeed, convection over the hot spot brings the atmosphere toward a warmer temperature. The warmer temperatures are imprinted over the whole domain by gravity waves and subsidence warming. The initial transient warming and concomitant subsidence drying suppress convection outside the hot spot, thus driving the aggregation. The hot-spot-induced large-scale circulation can enforce the aggregation even without radiative feedbacks for hot spots sufficiently large/warm. The strength of the large-scale circulation, which defines the speed of aggregation, is a function of the hot spot fractional area. At equilibrium, once the aggregation is well established, the moist convective region with upward midtropospheric motion, centered over the hot spot, has an area surprisingly independent of the hot spot size.

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Prince K. Xavier, Jean-Philippe Duvel, Pascale Braconnot, and Francisco J. Doblas-Reyes

Abstract

The intraseasonal variability (ISV) is an intermittent phenomenon with variable perturbation patterns. To assess the robustness of the simulated ISV in climate models, it is thus interesting to consider the distribution of perturbation patterns rather than only one average pattern. To inspect this distribution, the authors first introduce a distance that measures the similarity between two patterns. The reproducibility (realism) of the simulated intraseasonal patterns is then defined as the distribution of distances between each pattern and the average simulated (observed) pattern. A good reproducibility is required to analyze the physical source of the simulated disturbances. The realism distribution is required to estimate the proportion of simulated events that have a perturbation pattern similar to observed patterns. The median value of this realism distribution is introduced as an ISV metric. The reproducibility and realism distributions are used to evaluate boreal summer ISV of precipitations over the Indian Ocean for 19 phase 3 of the Coupled Model Intercomparison Project (CMIP3) models. The 19 models are classified in increasing ISV metric order. In agreement with previous studies, the four best ISV metrics are obtained for models having a convective closure totally or partly based on the moisture convergence. Models with high metric values (poorly realistic) tend to give (i) poorly reproducible intraseasonal patterns, (ii) rainfall perturbations poorly organized at large scales, (iii) small day-to-day variability with overly red temporal spectra, and (iv) less accurate summer monsoon rainfall distribution. This confirms that the ISV is an important link in the seamless system that connects weather and climate.

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