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Seasonality in SST-Forced Atmospheric Short-Term Climate Predictability

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  • 1 Program in Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado
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Abstract

The seasonal dependence of atmospheric short-term climate (i.e., seasonal to interannual) predictability is studied. This is accomplished by analyzing the output from ensemble integrations of the European Centre for Medium-Range Weather Forecasts model. The integrations use the observed evolution of sea surface temperature (SST) as prescribed boundary forcing. Forced by the interannual variation of SST, the short-term climate predictability of the atmospheric circulation is geographically and seasonally dependent. In general, the predictability is larger in the Tropics than the extratropics and is greater in the Pacific–Atlantic Ocean sector compared to the Indian Ocean–Asian monsoon region. Predictability is also higher in the winter hemisphere than in the summer hemisphere. On average, the weakest predictability in the Northern Hemisphere occurs during the northern autumn. However, it is noted that the 1982/83 strong El Niño event produced stronger atmospheric predictability than the 1988/89 strong La Niña event during the northern spring, and the predictability pattern is reversed during the northern autumn.

Predictability is further partitioned into its internal and external components. The external component is defined as the interannual variation of ensemble average, and the internal component is the sample-to-sample variance. The temporal and spatial structure in the external variability accounts for most of the structure in the SST-forced atmospheric predictability. However, there are regions in the Tropics, such as over the monsoon region, where the external and internal variabilities show roughly the same magnitude. Overall, internal variability is largest in the extratropics. Specifically, the internal variability is larger in the northern extratropics during the northern autumn and larger in the southern extratropics during the northern spring. In contrast, the external variability is smaller (larger) in the northern extratropics during the northern autumn (spring).

It is concluded that major features of the SST-forced atmospheric predictability are determined by the external variability in the Tropics. In the extratropics, the predictability is determined by seasonal variations in both internal and external variabilities. The weakest predictability that occurs in the northern extratropics during the northern autumn is the result of a conjunction of a local increase in internal variability and a decrease in external variability at the same time.

Furthermore, the external variability is controlled by seasonality in the forcing over the tropical Pacific Ocean, which is largely determined by the following two mechanisms: 1) the annual cycle–ENSO interaction over the tropical Pacific Ocean and 2) nonlinear effects of hydrological processes associated with the annual cycle–ENSO interaction. Also, it is interesting that the annual cycle–ENSO interaction can be summarized into a conceptual model that shows some analogy to the quark model in nuclear physics.

Corresponding author address: Dr. Xiao-Wei Quan, NOAA–CIRES CDC, R/E/CD1, 325 Broadway, Boulder, CO 80305. Email: quan.xiaowei@noaa.gov

Abstract

The seasonal dependence of atmospheric short-term climate (i.e., seasonal to interannual) predictability is studied. This is accomplished by analyzing the output from ensemble integrations of the European Centre for Medium-Range Weather Forecasts model. The integrations use the observed evolution of sea surface temperature (SST) as prescribed boundary forcing. Forced by the interannual variation of SST, the short-term climate predictability of the atmospheric circulation is geographically and seasonally dependent. In general, the predictability is larger in the Tropics than the extratropics and is greater in the Pacific–Atlantic Ocean sector compared to the Indian Ocean–Asian monsoon region. Predictability is also higher in the winter hemisphere than in the summer hemisphere. On average, the weakest predictability in the Northern Hemisphere occurs during the northern autumn. However, it is noted that the 1982/83 strong El Niño event produced stronger atmospheric predictability than the 1988/89 strong La Niña event during the northern spring, and the predictability pattern is reversed during the northern autumn.

Predictability is further partitioned into its internal and external components. The external component is defined as the interannual variation of ensemble average, and the internal component is the sample-to-sample variance. The temporal and spatial structure in the external variability accounts for most of the structure in the SST-forced atmospheric predictability. However, there are regions in the Tropics, such as over the monsoon region, where the external and internal variabilities show roughly the same magnitude. Overall, internal variability is largest in the extratropics. Specifically, the internal variability is larger in the northern extratropics during the northern autumn and larger in the southern extratropics during the northern spring. In contrast, the external variability is smaller (larger) in the northern extratropics during the northern autumn (spring).

It is concluded that major features of the SST-forced atmospheric predictability are determined by the external variability in the Tropics. In the extratropics, the predictability is determined by seasonal variations in both internal and external variabilities. The weakest predictability that occurs in the northern extratropics during the northern autumn is the result of a conjunction of a local increase in internal variability and a decrease in external variability at the same time.

Furthermore, the external variability is controlled by seasonality in the forcing over the tropical Pacific Ocean, which is largely determined by the following two mechanisms: 1) the annual cycle–ENSO interaction over the tropical Pacific Ocean and 2) nonlinear effects of hydrological processes associated with the annual cycle–ENSO interaction. Also, it is interesting that the annual cycle–ENSO interaction can be summarized into a conceptual model that shows some analogy to the quark model in nuclear physics.

Corresponding author address: Dr. Xiao-Wei Quan, NOAA–CIRES CDC, R/E/CD1, 325 Broadway, Boulder, CO 80305. Email: quan.xiaowei@noaa.gov

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