The mean evolution and variability of the Asian summer monsoon: Comparison of ECMWF and NCEP-NCAR reanalyses

The behavior of the Asian summer monsoon is documented and compared using the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA) and the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) Reanalysis. In terms of seasonal mean climatologies the results suggest that, in several respects, the ERA is superior to the NCEP-NCAR Reanalysis. The overall better simulation of the precipitation and hence the diabatic heating field over the monsoon domain in ERA means that the analyzed circulation is probably nearer reality. In terms of interannual variability, inconsistencies in the definition of weak and strong monsoon years based on typical monsoon indices such as All-India Rainfall (AIR) anomalies and the large-scale wind shear based dynamical monsoon index (DMI) still exist. Two dominant modes of interannual variability have been identified that together explain nearly 50% of the variance. Individually, they have many features in common with the composite flow patterns associated with weak and strong monsoons, when defined in terms of regional AIR anomalies and the large-scale DMI. The reanalyses also show a common dominant mode of intraseasonal variability that describes the latitudinal displacement of the tropical convergence zone from its oceanic-to-continental regime and essentially captures the low-frequency active/break cycles of the monsoon. The relationship between interannual and intraseasonal variability has been investigated by considering the probability density function (PDF) of the principal component of the dominant intraseasonal mode. Based on the DMI, there is an indication that in years with a weaker monsoon circulation, the PDF is skewed toward negative values (i,e., break conditions). Similarly, the PDFs for El Nino and La Nina years suggest that El Nino predisposes the system to more break spells, although the sample size may limit the statistical significance of the results.

Toward an integrated seasonal forecasting system for South America

This study proposes an objective integrated seasonal forecasting system for producing well-calibrated probabilistic rainfall forecasts for South America. The proposed system has two components: ( i) an empirical model that uses Pacific and Atlantic sea surface temperature anomalies as predictors for rainfall and ( ii) a multimodel system composed of three European coupled ocean - atmosphere models. Three-month lead austral summer rainfall predictions produced by the components of the system are integrated ( i. e., combined and calibrated) using a Bayesian forecast assimilation procedure. The skill of empirical, coupled multimodel, and integrated forecasts obtained with forecast assimilation is assessed and compared. The simple coupled multimodel ensemble has a comparable level of skill to that obtained using a simplified empirical approach. As for most regions of the globe, seasonal forecast skill for South America is low. However, when empirical and coupled multimodel predictions are combined and calibrated using forecast assimilation, more skillful integrated forecasts are obtained than with either empirical or coupled multimodel predictions alone. Both the reliability and resolution of the forecasts have been improved by forecast assimilation in several regions of South America. The Tropics and the area of southern Brazil, Uruguay, Paraguay, and northern Argentina have been found to be the two most predictable regions of South America during the austral summer. Skillful rainfall forecasts are generally only possible during El Nino or La Nina years rather than in neutral years.

Influence of the seasonal cycle on the termination of El Nino events in a coupled general circulation model

In this study, the mechanisms leading to the El Nino peak and demise are explored through a coupled general circulation model ensemble approach evaluated against observations. The results here suggest that the timing of the peak and demise for intense El Nino events is highly predictable as the evolution of the coupled system is strongly driven by a southward shift of the intense equatorial Pacific westerly anomalies during boreal winter. In fact, this systematic late-year shift drives an intense eastern Pacific thermocline shallowing, constraining a rapid El Nino demise in the following months. This wind shift results from a southward displacement in winter of the central Pacific warmest SSTs in response to the seasonal evolution of solar insolation. In contrast, the intensity of this seasonal feedback mechanism and its impact on the coupled system are significantly weaker in moderate El Nino events, resulting in a less pronounced thermocline shallowing. This shallowing transfers the coupled system into an unstable state in spring but is not sufficient to systematically constrain the equatorial Pacific evolution toward a rapid El Nino termination. However, for some moderate events, the occurrence of intense easterly wind anomalies in the eastern Pacific during that period initiate a rapid surge of cold SSTs leading to La Nina conditions. In other cases, weaker trade winds combined with a slightly deeper thermocline allow the coupled system to maintain a broad warm phase evolving through the entire spring and summer and a delayed El Nino demise, an evolution that is similar to the prolonged 1986/87 El Nino event. La Nina events also show a similar tendency to peak in boreal winter, with characteristics and mechanisms mainly symmetric to those described for moderate El Nino cases.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

Climate predictability experiments with a general circulation model

The atmospheric response to the evolution of the global sea surface temperatures from 1979 to 1992 is studied using the Max-Planck-Institut 19 level atmospheric general circulation model, ECHAM3 at T 42 resolution. Five separate 14-year integrations are performed and results are presented for each individual realization and for the ensemble-averaged response. The results are compared to a 30-year control integration using a climate monthly mean state of the sea surface temperatures and to analysis data. It is found that the ECHAM3 model, by and large, does reproduce the observed response pattern to El Nin˜o and La Nin˜a. During the El Nin˜ o events, the subtropical jet streams in both hemispheres are intensified and displaced equatorward, and there is a tendency towards weak upper easterlies over the equator. The Southern Oscillation is a very stable feature of the integrations and is accurately reproduced in all experiments. The inter-annual variability at middle- and high-latitudes, on the other hand, is strongly dominated by chaotic dynamics, and the tropical SST forcing only modulates the atmospheric circulation. The potential predictability of the model is investigated for six different regions. Signal to noise ratio is large in most parts of the tropical belt, of medium strength in the western hemisphere and generally small over the European area. The ENSO signal is most pronounced during the boreal spring. A particularly strong signal in the precipitation field in the extratropics during spring can be found over the southern United States. Western Canada is normally warmer during the warm ENSO phase, while northern Europe is warmer than normal during the ENSO cold phase. The reason is advection of warm air due to a more intense Pacific low than normal during the warm ENSO phase and a more intense Icelandic low than normal during the cold ENSO phase, respectively.

ENSO impact on Kelvin waves and associated tropical convection

The impact of El Nino–Southern Oscillation (ENSO) on atmospheric Kelvin waves and associated tropical convection is investigated using the ECMWF Re-Analysis, NOAA outgoing longwave radiation (OLR), and the analysis technique introduced in a previous study. It is found that the phase of ENSO has a substantial impact on Kelvin waves and associated convection over the equatorial central-eastern Pacific. El Nino (La Nina) events enhance (suppress) variability of the upper-tropospheric Kelvin wave and the associated convection there, both in extended boreal winter and summer. The mechanism of the impact is through changes in the ENSO-related thermal conditions and the ambient flow. In El Nino years, because of SST increase in the equatorial central-eastern Pacific, variability of eastward-moving convection, which is mainly associated with Kelvin waves, intensifies in the region. In addition, owing to the weakening of the equatorial eastern Pacific westerly duct in the upper troposphere in El Nino years, Kelvin waves amplify there. In La Nina years, the opposite occurs. However, the stronger westerly duct in La Nina winters allows more NH extratropical Rossby wave activity to propagate equatorward and force Kelvin waves around 200 hPa, partially offsetting the in situ weakening effect of the stronger westerlies on the waves. In general, in El Nino years Kelvin waves are more convectively and vertically coupled and propagate more upward into the lower stratosphere over the central-eastern Pacific. The ENSO impact in other regions is not clear, although in winter over the eastern Indian and western Pacific Oceans Kelvin waves and their associated convection are slightly weaker in El Nino than in La Nina years.