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J. Fasullo and P. J. Webster

Abstract

Using the NCEP–NCAR reanalysis for the 1950–2000 period, differences in the atmospheric hydrological cycle between the extremes of ENSO (i.e., La Niña minus El Niño) are examined. Zonal vertically integrated moisture transport (VIMT) across 100°E accounts for about half of the variability in net moisture convergence in the north Indian Ocean region between ENSO extremes when all ENSO events are considered. Changes in VIMT across 100°E are associated with large changes in the strength of the Pacific Ocean trade wind regime during ENSO. The bulk of the remaining VIMT anomalies are from the Arabian Sea and appear to be associated with sea level pressure variations in the northern and western parts of the Indian Ocean Basin. This initial analysis, therefore, suggests that the interaction between the monsoon and ENSO may be more complex than the direct modulation of VIMT by the Pacific Ocean trade winds alone.

The analysis is refined further by comparing the differences of the Indian and Pacific Ocean hydrological cycles between ENSO extremes when they occur concurrently with anomalous monsoons [ENSO–anomalous monsoon years (EAM)], and when the monsoon is normal [ENSO–normal monsoon years (ENM)]. For both EAM and ENM years, similar differences exist in VIMT across 100°E between ENSO extremes. However, major differences are noted in VIMT anomalies from the west and south into the north Indian Ocean region. Thus, the principal difference in moisture convergence in the north Indian Ocean between EAM and ENM years is associated primarily with VIMT anomalies in the western Indian Ocean region and not those in the eastern Indian or Pacific Oceans.

To test the hypothesis that Pacific Ocean SST anomalies occurring prior to the monsoon may be important in influencing the eventual nature of the monsoon, the analysis is extended backward to the spring period. While May SST differences in the Niño-3 region between ENSO extremes are found to be similar for both EAM and ENM years, VIMT differences in both the Indian Ocean and the central and western Pacific Oceans are significantly larger during EAM years than ENM years. May SST differences in the central subtropical Pacific Ocean are also significantly larger during EAM than ENM years. These results show that the anomalous SST gradient between the eastern equatorial and the central subtropical Pacific Ocean prior to the monsoon onset, together with its associated VIMTs anomalies, may be important factors in determining the degree of connection between monsoon and ENSO. In addition, the circulation in the Indian Ocean prior to and during the monsoon onset shares a strong association with the eventual intensity of the monsoon–ENSO coupling.

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J. Fasullo and P. J. Webster

Abstract

A diagnostic criterion that retrospectively assesses the onset and withdrawal dates of the Indian monsoon is derived from variability in the large-scale hydrologic cycle. The method is proposed as an improved means with which to understand interannual variability in the monsoon transitions as compared to criteria that rely heavily on rainfall variability over limited spatial domains (e.g., individual Indian districts). The hydrologic cycle is chosen as a key physical basis for monitoring the monsoon due to the essential roles played by zonal and meridional gradients in water vapor, clouds, and rainfall in driving the large-scale monsoon circulation. Moreover, as rainfall is greater than evaporation in wet monsoonal areas, lateral transports of water vapor are required for the existence of monsoonal rains. To diagnose onset and withdrawal, vertically integrated moisture transport (VIMT) is therefore used instead of rainfall, which over the large scale is often poorly measured and modeled. In contrast to rainfall, VIMT is generally well modeled and observed, and its variability, particularly over the Arabian Sea, is substantial during both monsoon onset and withdrawal. An index, named the hydrologic onset and withdrawal index (HOWI), is thus formed from those regions where VIMT variability is pronounced at the beginning and end of the monsoon season. The HOWI offers several advantages as the index is based on fields that are better modeled and measured than rainfall, and the index is indicative of the transition in the large-scale monsoon circulation rather than being highly sensitive to synoptic variability and the spatial complexity of the monsoon transitions. The HOWI is shown to be both robust to bogus monsoon onsets and reflective of the timing, rather than the spatial character, of the transitions.

Analysis of interannual variability in monsoon onset and withdrawal dates based on the HOWI reveals robust associations that are weak and insignificant when assessed using other onset criteria. For example, the associations between total June–July–August–September (JJAS) rainfall and both monsoon onset and withdrawal are weak (correlations are weaker than −0.11) when onset dates from the Indian Meteorological Department (IMD) or other objective methods are considered. However, the HOWI criterion shows strong correlations between total JJAS rainfall and both onset (0.30) and withdrawal (−0.49). Thus, the length of the monsoon season is shown to be strongly related to its overall strength. In addition, while the correlation between IMD onset date and Niño-3 SST is insignificant, the correlation based on HOWI is 0.41. The associations between HOWI and both ENSO and the overall monsoon season exceed significance at the 99% confidence level. Moreover, the associations are shown to be robust to the scale of the region selected in compiling the HOWI. It is speculated that the influence of synoptic variability and the spatially variable nature of the monsoon transitions mask, in part, the existence of the climate associations that are revealed by the HOWI.

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P. A. Agudelo, J. A. Curry, C. D. Hoyos, and P. J. Webster

Abstract

Intraseasonal oscillations (ISOs) are important large-amplitude and large-scale elements of the tropical Indo-Pacific climate with time scales in the 20–60-day period range, during which time they modulate higher-frequency tropical weather. Despite their importance, the ISO is poorly simulated and predicted by numerical models. A joint diagnostic and modeling study of the ISO is conducted, concentrating on the period between the suppressed and active (referred to as the “transition”) period that is hypothesized to be the defining stage for the development of the intraseasonal mode and the component that is most poorly simulated.

The diagnostic study uses data from the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). It is found that during the transition period, the ocean and the atmosphere undergo gradual but large-scale and high-amplitude changes, especially the moistening of the lower troposphere caused jointly by the anomalously warm sea surface temperature arising from minimal cloud and low winds during the suppressed phase and the large-scale subsidence that inhibits the formation of locally deep convection. Using a cloud classification scheme based on microwave and infrared satellite data, it is observed that midtop (cloud with a top in the middle troposphere) nonprecipitating clouds are a direct response of the low-level moisture buildup.

To investigate the sensitivity of ISO simulations to the transitional phase, the European Centre for Medium-Range Weather Forecasts (ECMWF) coupled ocean–atmosphere climate model is used. The ECMWF was run serially in predictive ensemble mode (five members) for 30-day periods starting from 1 December 1992 to 30 January 1993, encompassing the ISO occurring in late December. Predictability of the active convective period of the ISO is poor when initialized before the transitional phases of the ISO. However, when initialized with the correct lower-tropospheric moisture field, predictability increases substantially, although the model convective parameterization appears to trigger convection too quickly without allowing an adequate buildup of convective available potential energy during the transition period.

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X. W. Quan, P. J. Webster, A. M. Moore, and H. R. Chang

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.

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Johannes Loschnigg, Gerald A. Meehl, Peter J. Webster, Julie M. Arblaster, and Gilbert P. Compo

Abstract

The interaction of the Indian Ocean dynamics and the tropospheric biennial oscillation (TBO) is analyzed in the 300-yr control run of the National Center for Atmospheric Research (NCAR) Climate System Model (CSM). Sea surface temperature (SST) anomalies and equatorial ocean dynamics in the Indian Ocean are associated with the TBO and interannual variability of Asian–Australian monsoons in observations. The air–sea interactions involved in these processes in the coupled ocean–atmosphere model are analyzed, so as to diagnose the causes of the SST anomalies and their role in the development of a biennial cycle in the Indian–Pacific Ocean region.

By using singular value decomposition (SVD) analysis, it is found that the model reproduces the dominant mechanisms that are involved in the development of the TBO's influence on the south Asian monsoon: large-scale forcing from the tropical Pacific and regional forcing associated with both the meridional temperature gradient between the Asian continent and the Indian Ocean, as well as Indian Ocean SST anomalies. Using cumulative anomaly pattern correlation, the strength of each of these processes in affecting the interannual variability of both Asian and Australian monsoon rainfall is assessed.

In analyzing the role of the Indian Ocean dynamics in the TBO, it is found that the Indian Ocean zonal mode (IOZM) is an inherent feature of the Asian summer monsoon and the TBO. The IOZM is thus a part of the biennial nature of the Indian–Pacific Ocean region. The coupled ocean–atmosphere dynamics and cross-equatorial heat transport contribute to the interannual variability and biennial nature of the ENSO–monsoon system, by affecting the heat content of the Indian Ocean and resulting SST anomalies over multiple seasons, which is a key factor in the TBO.

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A. P. Sokolov, P. H. Stone, C. E. Forest, R. Prinn, M. C. Sarofim, M. Webster, S. Paltsev, C. A. Schlosser, D. Kicklighter, S. Dutkiewicz, J. Reilly, C. Wang, B. Felzer, J. M. Melillo, and H. D. Jacoby
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A. P. Sokolov, P. H. Stone, C. E. Forest, R. Prinn, M. C. Sarofim, M. Webster, S. Paltsev, C. A. Schlosser, D. Kicklighter, S. Dutkiewicz, J. Reilly, C. Wang, B. Felzer, J. M. Melillo, and H. D. Jacoby

Abstract

The Massachusetts Institute of Technology (MIT) Integrated Global System Model is used to make probabilistic projections of climate change from 1861 to 2100. Since the model’s first projections were published in 2003, substantial improvements have been made to the model, and improved estimates of the probability distributions of uncertain input parameters have become available. The new projections are considerably warmer than the 2003 projections; for example, the median surface warming in 2091–2100 is 5.1°C compared to 2.4°C in the earlier study. Many changes contribute to the stronger warming; among the more important ones are taking into account the cooling in the second half of the twentieth century due to volcanic eruptions for input parameter estimation and a more sophisticated method for projecting gross domestic product (GDP) growth, which eliminated many low-emission scenarios.

However, if recently published data, suggesting stronger twentieth-century ocean warming, are used to determine the input climate parameters, the median projected warming at the end of the twenty-first century is only 4.1°C. Nevertheless, all ensembles of the simulations discussed here produce a much smaller probability of warming less than 2.4°C than implied by the lower bound of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) projected likely range for the A1FI scenario, which has forcing very similar to the median projection in this study. The probability distribution for the surface warming produced by this analysis is more symmetric than the distribution assumed by the IPCC because of a different feedback between the climate and the carbon cycle, resulting from the inclusion in this model of the carbon–nitrogen interaction in the terrestrial ecosystem.

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Rachel A. Stratton, Catherine A. Senior, Simon B. Vosper, Sonja S. Folwell, Ian A. Boutle, Paul D. Earnshaw, Elizabeth Kendon, Adrian P. Lock, Andrew Malcolm, James Manners, Cyril J. Morcrette, Christopher Short, Alison J. Stirling, Christopher M. Taylor, Simon Tucker, Stuart Webster, and Jonathan M. Wilkinson

Abstract

A convection-permitting multiyear regional climate simulation using the Met Office Unified Model has been run for the first time on an Africa-wide domain. The model has been run as part of the Future Climate for Africa (FCFA) Improving Model Processes for African Climate (IMPALA) project, and its configuration, domain, and forcing data are described here in detail. The model [Pan-African Convection-Permitting Regional Climate Simulation with the Met Office UM (CP4-Africa)] uses a 4.5-km horizontal grid spacing at the equator and is run without a convection parameterization, nested within a global atmospheric model driven by observations at the sea surface, which does include a convection scheme. An additional regional simulation, with identical resolution and physical parameterizations to the global model, but with the domain, land surface, and aerosol climatologies of CP4-Africa, has been run to aid in the understanding of the differences between the CP4-Africa and global model, in particular to isolate the impact of the convection parameterization and resolution. The effect of enforcing moisture conservation in CP4-Africa is described and its impact on reducing extreme precipitation values is assessed. Preliminary results from the first five years of the CP4-Africa simulation show substantial improvements in JJA average rainfall compared to the parameterized convection models, with most notably a reduction in the persistent dry bias in West Africa, giving an indication of the benefits to be gained from running a convection-permitting simulation over the whole African continent.

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