The Coupled Model Predictability of the Western North Pacific Summer Monsoon with Different Leading Times

Leading time length is an important issue for modeling seasonal forecasts. In this study, a comparison of the interannual predictability of the Western North Pacific (WNP) summer monsoon between different leading months was performed by using one-, four-, and sevenmonth lead retrospective forecasts (hindcasts) of four coupled models from Ensembles-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) for the period of 1960 2005. It is found that the WNP summer anomalies, including lower-tropospheric circulation and precipitation anomalies, can be well predicted for all these leading months. The accuracy of the four-month lead prediction is only slightly weaker than that of the one-month lead prediction, although the skill decreases with the increase of leading months.     

Predictability of the East Asian winter monsoon indices by the coupled models of ENSEMBLES

The seasonal predictability of various East Asian winter monsoon （EAWM） indices was investigated in this study based on the retrospective forecasts of the five state-of-the-art coupled models from ENSEMBLES for a 46-year period of 19612006.It was found that the ENSEMBLES models predict five out of the 21 EAWM indices well,with temporal correlation coefficients ranging from 0.54 to 0.61.These five indices are defined by the averaged lower-tropospheric winds over the low latitudes （south of 30°N）.Further analyses indicated that the predictability of these five indices originates from their intimate relationship with ENSO.A cross-validated prediction,which took the preceding （November） observed Nifo3.4 index as a predictor,gives a prediction skill almost identical to that shown by the model.On the other hand,the models present rather low predictability for the other indices and for surface air temperature in East Asia.In addition,the models fail to reproduce the relationship between the indices of different categories,implying that they cannot capture the tropicalextratropical interaction related to EAWM variability.Together,these results suggest that reliable prediction of the EAWM indices and East Asian air temperature remains a challenge.     

Climate change impacts on bedload transport in alpine drainage basins with hydropower exploitation

Sediment transport is known to have a significant impact on hydropower infrastructures and changes in sediment transport rates are important for sediment management measures and hydroelectricity production. In this study, we present how climate change may affect bedload transport in 66 high alpine catchments used by hydropower companies in the Valais, Switzerland. Future sediment yield is estimated with a runoff‐based sediment transport model for the two future 30 year time periods 2021–2050 and 2070–2099. The analysis is integrated into a modelling chain in which error‐corrected and downscaled climate scenarios generated in the framework of the ENSEMBLES project are coupled to the hydrological model PREVAH, glacier retreat and bedload transport. To calibrate the sediment transport model, we used the observed sediment volumes in water intakes and reservoirs if such data were available. The results obtained show on average a decrease of sediment yield due to the reduced runoff generation during summer, especially for the scenario period 2070–2099. A shift of the seasonal sediment transport regime with a current maximum during July and August to earlier months in the year is predicted. Projections of future sediment yield rely on the accuracy of the individual modeling chain elements. The different sources of uncertainty are discussed qualitatively. Copyright © 2015 John Wiley & Sons, Ltd.     

Seasonality and magnitude of floods in Switzerland under future climate change

The flood seasonality of catchments in Switzerland is likely to change under climate change because of anticipated alterations of precipitation as well as snow accumulation and melt. Information on this change is crucial for flood protection policies, for example, or regional flood frequency analysis. We analysed projected changes in mean annual and maximum floods of a 22‐year period for 189 catchments in Switzerland and two scenario periods in the 21st century based on an ensemble of climate scenarios. The flood seasonality was analysed with directional statistics that allow assessing both changes in the mean date a flood occurs as well as changes in the strength of the seasonality. We found that the simulated change in flood seasonality is a function of the change in flow regime type. If snow accumulation and melt is important in a catchment during the control period, then the anticipated change in flood seasonality is most pronounced. Decreasing summer precipitation in the scenarios additionally affects the flood seasonality (mean date of flood occurrence) and leads to a decreasing strength of seasonality, that is a higher temporal variability in most cases. The magnitudes of mean annual floods and more clearly of maximum floods (in a 22‐year period) are expected to increase in the future because of changes in flood‐generating processes and scaled extreme precipitation. Southern alpine catchments show a different signal, though: the simulated mean annual floods decrease in the far future, that is at the end of the 21st century. Copyright © 2013 John Wiley & Sons, Ltd.     

Runoff evolution in the Swiss Alps: projections for selected high‐alpine catchments based on ENSEMBLES scenarios

The Alps are often referred to as the ‘water tower of Europe’. In Switzerland, many branches of the economy, especially the hydropower industry, are closely linked to and dependent on the availability of water. Assessing the impact of climate change on streamflow runoff is, thus, of great interest. Major efforts have already been made in this respect, but the analyses often focus on individual catchments and are difficult to intercompare. In this article, we analysed nine high‐alpine catchments spread over the Swiss Alps, selected for their relevance to a wide range of morphological characteristics. Runoff projections were carried out until the end of the current century by applying the Glacier Evolution Runoff Model (GERM) and climate scenarios generated in the framework of the ENSEMBLES project. We focused on assessing the uncertainty induced by the unknown climate evolution and provided general, statistically based statements, which should be useful as a ‘rule of thumb’ for analyses addressing questions related to water management. Catchments with a high degree of glacierization will undergo the largest changes. General statements about absolute variations in discharge are unreliable, but an overall pattern, with an initial phase of increased annual discharge, followed by a phase with decreasing discharge, is recognizable for all catchments with a significant degree of glacierization. In these catchments, a transition from glacial and glacio‐nival regime types to nival will occur. The timing of maximal annual runoff is projected to occur before 2050 in all basins. The time of year with maximal daily discharges is expected to occur earlier at a rate of 4·4 ± 1·7 days per decade. Compared to its present level, the contribution of snow‐ and icemelt to annual discharge is projected to drop by 15 to 25% until the year 2100. Copyright © 2011 John Wiley & Sons, Ltd.     

Seasonal Prediction Assessment of the South Asian Summer Monsoon: ENSEMBLES versus DEMETER

The seasonal forecasting skill with respect to the South Asian summer monsoon(SASM) was compared between the European Commission FP7 project(ENSEMBLES) and the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction project(DEMETER). The Webster-Yang index(WYI) was chosen to represent the intensity of the SASM. First, the authors compared the ability to forecast the zonal wind at 850 h Pa(U850) and 200 h Pa(U200) between ENSEMBLES and DEMETER models. The results indicated that the models from the European Centre for Medium-Range Weather Forecasts, International Organization(ECMWF) and UK Met Office(UKMO) in ENSEMBLES possess greater skill in seasonally forecasting the JJA(June, July, and August) U850, U200, and U850 minus U200 than in DEMETER. Compared to in DEMETER, the JJA U200 and U850 minus U200 forecasting skill was greater for the model from MétéoFrance(MF) in ENSEMBLES over most of the SASM region. The three coupled models(ECMWF, MF, and UKMO), especially the UKMO model in ENSEMBLES, all demonstrated improved skill in their seasonal forecasts compared to in DEMETER with respect to the interannual variability of the SASM. The three ENSEMBLES models also showed better ability in forecasting the sea surface temperature anomalies(SSTAs) over the eastern equatorial Pacific and North Indian Ocean, and more accurately reproduced the large-scale atmospheric circulation and precipitation over northern India, which are related to the SASM. It seems that the couple between the atmospheric system and external forcing of ENSMBLES over Indian Ocean and Pacific is better than that of DEMETER.     

Assessment of the Capability of ENSEMBLES Hindcasts in Predicting Spring Climate in China

Using the hindcasts provided by the Ensemble-Based Predictions of Climate Changes and Their Impacts(ENSEMBLES) project for the period of 1980–2005, the forecast capability of spring climate in China is assessed mainly from the aspects of precipitation, 2-m air temperature, and atmospheric circulations. The ENSEMBELS can reproduce the climatology and dominant empirical orthogonal function(EOF) modes of precipitation and 2-m air temperature, with some differences arising from different initialization months. The multi-model ensemble(MME) forecast of interannual variability is of good performance in some regions such as eastern China with February initialization.The spatial patterns of the MME interannual and inter-member spreads for precipitation and 2-m air temperature are consistent with those of the observed interannual spread, indicating that internal dynamic processes have major impacts on the interannual anomaly of spring climate in China. We have identified two coupled modes between intermember anomalies of the 850-hPa vorticity in spring and sea surface temperature(SST) both in spring and at a lead of 2 months, of which the first mode shows a significant impact on the spring climate in China, with an anomalous anticyclone located over Northwest Pacific and positive precipitation and southwesterly anomalies in eastern China.Our results also suggest that the SST at a lead of two months may be a predictor for the spring climate in eastern China. A better representation of the ocean–atmosphere interaction over the tropical Pacific, Northwest Pacific, and Indian Ocean can improve the forecast skill of the spring climate in eastern China.     

Predictability of winter rainfall in South China as demonstrated by the coupled models of ENSEMBLES

Winter rainfall over South China shows strong interannual variability,which accounts for about half of the total winter rainfall over South China.This study investigated the predictability of winter （December-January-February; DJF） rainfall over South China using the retrospective forecasts of five state-of-the-art coupled models included in the ENSEMBLES project for the period 1961-2006.It was found that the ENSEMBLES models predicted the interannual variation of rainfall over South China well,with the correlation coefficient between the observed/station-averaged rainfall and predicted/areaaveraged rainfall being 0.46.In particular,above-normal South China rainfall was better predicted,and the correlation coefficient between the predicted and observed anomalies was 0.64 for these wetter winters.In addition,the models captured well the main features of SST and atmospheric circulation anomalies related to South China rainfall variation in the observation.It was further found that South China rainfall,when predicted according to predicted DJF Nifio3.4 index and the ENSO-South China rainfall relationship,shows a prediction skill almost as high as that directly predicted,indicating that ENSO is the source for the predictability of South China rainfall.