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Jieshun Zhu Bohua Huang Magdalena A. Balmaseda James L. Kinter III Peitao Peng Zeng-Zhen Hu Lawrence Marx 《Climate Dynamics》2013,41(9-10):2785-2795
Currently, ensemble seasonal forecasts using a single model with multiple perturbed initial conditions generally suffer from an “overconfidence” problem, i.e., the ensemble evolves such that the spread among members is small, compared to the magnitude of the mean error. This has motivated the use of a multi-model ensemble (MME), a technique that aims at sampling the structural uncertainty in the forecasting system. Here we investigate how the structural uncertainty in the ocean initial conditions impacts the reliability in seasonal forecasts, by using a new ensemble generation method to be referred to as the multiple-ocean analysis ensemble (MAE) initialization. In the MAE method, multiple ocean analyses are used to build an ensemble of ocean initial states, thus sampling structural uncertainties in oceanic initial conditions (OIC) originating from errors in the ocean model, the forcing flux, and the measurements, especially in areas and times of insufficient observations, as well as from the dependence on data assimilation methods. The merit of MAE initialization is demonstrated by the improved El Niño and the Southern Oscillation (ENSO) forecasting reliability. In particular, compared with the atmospheric perturbation or lagged ensemble approaches, the MAE initialization more effectively enhances ensemble dispersion in ENSO forecasting. A quantitative probabilistic measure of reliability also indicates that the MAE method performs better in forecasting all three (warm, neutral and cold) categories of ENSO events. In addition to improving seasonal forecasts, the MAE strategy may be used to identify the characteristics of the current structural uncertainty and as guidance for improving the observational network and assimilation strategy. Moreover, although the MAE method is not expected to totally correct the overconfidence of seasonal forecasts, our results demonstrate that OIC uncertainty is one of the major sources of forecast overconfidence, and suggest that the MAE is an essential component of an MME system. 相似文献
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A multivariate analysis of the upper ocean thermal structure is used to examine the recent long-term changes and decadal variability in the upper ocean heat content as represented by model-based ocean reanalyses and a model-independent objective analysis. The three variables used are the mean temperature above the 14°C isotherm, its depth and a fixed depth mean temperature (250?m mean temperature). The mean temperature above the 14°C isotherm is a convenient, albeit simple, way to isolate thermodynamical changes by filtering out dynamical changes related to thermocline vertical displacements. The global upper ocean observations and reanalyses exhibit very similar warming trends (0.045°C per decade) over the period 1965–2005, superimposed with marked decadal variability in the 1970s and 1980s. The spatial patterns of the regression between indices (representative of anthropogenic changes and known modes of internal decadal variability), and the three variables associated with the ocean heat content are used as fingerprint to separate out the different contributions. The choice of variables provides information about the local heat absorption, vertical distribution and horizontal redistribution of heat, this latter being suggestive of changes in ocean circulation. The discrepancy between the objective analysis and the reanalyses, as well as the spread among the different reanalyses, are used as a simple estimate of ocean state uncertainties. Two robust findings result from this analysis: (1) the signature of anthropogenic changes is qualitatively different from those of the internal decadal variability associated to the Pacific Interdecadal Oscillation and the Atlantic Meridional Oscillation, and (2) the anthropogenic changes in ocean heat content do not only consist of local heat absorption, but are likely related with changes in the ocean circulation, with a clear shallowing of the tropical thermocline in the Pacific and Indian oceans. 相似文献
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Timothy N. Stockdale David L. T. Anderson Magdalena A. Balmaseda Francisco Doblas-Reyes Laura Ferranti Kristian Mogensen Timothy N. Palmer Franco Molteni Frederic Vitart 《Climate Dynamics》2011,37(3-4):455-471
The latest operational version of the ECMWF seasonal forecasting system is described. It shows noticeably improved skill for sea surface temperature (SST) prediction compared with previous versions, particularly with respect to El Nino related variability. Substantial skill is shown for lead times up to 1?year, although at this range the spread in the ensemble forecast implies a loss of predictability large enough to account for most of the forecast error variance, suggesting only moderate scope for improving long range El Nino forecasts. At shorter ranges, particularly 3?C6?months, skill is still substantially below the model-estimated predictability limit. SST forecast skill is higher for more recent periods than earlier ones. Analysis shows that although various factors can affect scores in particular periods, the improvement from 1994 onwards seems to be robust, and is most plausibly due to improvements in the observing system made at that time. The improvement in forecast skill is most evident for 3-month forecasts starting in February, where predictions of NINO3.4 SST from 1994 to present have been almost without fault. It is argued that in situations where the impact of model error is small, the value of improved observational data can be seen most clearly. Significant skill is also shown in the equatorial Indian Ocean, although predictive skill in parts of the tropical Atlantic are relatively poor. SST forecast errors can be especially high in the Southern Ocean. 相似文献
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An ensemble estimation of the variability of upper-ocean heat content over the tropical Atlantic Ocean with multi-ocean reanalysis products 总被引：2，自引：2，他引：0
Current ocean reanalysis systems contain considerable uncertainty in estimating the subsurface oceanic state, especially in the tropical Atlantic Ocean. Given this level of uncertainty, it is important to develop useful strategies to identify realistic low-frequency signals optimally from these analyses. In this paper, we present an “ensemble” method to estimate the variability of upper-ocean heat content (HC) in the tropical Atlantic based on multiple-ocean reanalysis products. Six state-of-the-art global ocean reanalaysis products, all of which are widely used in the climate research community, are examined in terms of their HC variability from 1979 to 2007. The conventional empirical orthogonal function (EOF) analysis of the HC anomalies from each individual analysis indicates that their leading modes show significant qualitative differences among analyses, especially for the first modes, although some common characteristics are discernable. Then, the simple arithmetic average (or ensemble mean) is applied to produce an ensemble dataset, i.e., the EM analysis. The leading EOF modes of the EM analysis show quantitatively consistent spatial–temporal patterns with those derived from an alternative EOF technique that maximizes signal-to-noise ratio of the six analyses, which suggests that the ensemble mean generates HC fields with the noise reduced to an acceptable level. The quality of the EM analysis is further validated against AVISO altimetry sea level anomaly (SLA) data and PIRATA mooring station data. A regression analysis with the AVISO SLA data proved that the leading modes in the EM analysis are realistic. It also demonstrated that some reanalysis products might contain higher level of intrinsic noise than others. A quantitative correlation analysis indicates that the HC fields are more realistic in the EM analysis than in individual products, especially over the equatorial regions, with signals contributed from all ensemble members. A direct comparison with the HC anomalies derived from in situ temperature measurements showed that the EM analysis generally gets realistic HC variability at the five chosen PIRATA mooring stations. Overall, these results demonstrate that the EM analysis is a promising alternative for studying physical processes and possibly for initializing climate predictions. 相似文献
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Predictability of the mid-latitude Atlantic meridional overturning circulation in a multi-model system 总被引：1，自引：1，他引：0
Holger Pohlmann Doug M. Smith Magdalena A. Balmaseda Noel S. Keenlyside Simona Masina Daniela Matei Wolfgang A. Müller Philippe Rogel 《Climate Dynamics》2013,41(3-4):775-785
Assessing the skill of the Atlantic meridional overturning circulation (AMOC) in decadal hindcasts (i.e. retrospective predictions) is hampered by a lack of observations for verification. Models are therefore needed to reconstruct the historical AMOC variability. Here we show that ten recent oceanic syntheses provide a common signal of AMOC variability at 45°N, with an increase from the 1960s to the mid-1990s and a decrease thereafter although they disagree on the exact magnitude. This signal correlates with observed key processes such as the North Atlantic Oscillation, sub-polar gyre strength, Atlantic sea surface temperature dipole, and Labrador Sea convection that are thought to be related to the AMOC. Furthermore, we find potential predictability of the mid-latitude AMOC for the first 3–6 year means when we validate decadal hindcasts for the past 50 years against the multi-model signal. However, this predictability is not found in models driven only by external radiative changes, demonstrating the need for initialization of decadal climate predictions. 相似文献
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Toyoda Takahiro Fujii Yosuke Kuragano Tsurane Kosugi Naohiro Sasano Daisuke Kamachi Masafumi Ishikawa Yoichi Masuda Shuhei Sato Kanako Awaji Toshiyuki Hernandez Fabrice Ferry Nicolas Guinehut Stéphanie Martin Matthew Andrew Peterson K. Good Simon A. Valdivieso Maria Haines Keith Storto Andrea Masina Simona Köhl Armin Yin Yonghong Shi Li Alves Oscar Smith Gregory Chang You-Soon Vernieres Guillaume Wang Xiaochun Forget Gael Heimbach Patrick Wang Ou Fukumori Ichiro Lee Tong Zuo Hao Balmaseda Magdalena 《Climate Dynamics》2017,49(3):891-907
Climate Dynamics - The interannual-decadal variability of the wintertime mixed layer depths (MLDs) over the North Pacific is investigated from an empirical orthogonal function (EOF) analysis of an... 相似文献
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Tong Lee Toshiyuki Awaji Magdalena Balmaseda Nicolas Ferry Yosuke Fujii Ichiro Fukumori Benjamin Giese Patrick Heimbach Armin Köhl Simona Masina Elisabeth Remy Anthony Rosati Michael Schodlok Detlef Stammer Anthony Weaver 《Dynamics of Atmospheres and Oceans》2010
Monthly averaged total volume transport of the Indonesian throughflow (ITF) estimated by 14 global ocean data assimilation (ODA) products that are decade to multi-decade long are compared among themselves and with observations from the INSTANT Program (2004–2006). The main goals of the comparisons are to examine the consistency and evaluate the skill of different ODA products in simulating ITF transport. The ensemble averaged, time-mean value of ODA estimates is 13.6 Sv (1 Sv = 106 m3/s) for the common 1993–2001 period and 13.9 Sv for the 2004–2006 INSTANT Program period. These values are close to the 15-Sv estimate derived from INSTANT observations. All but one ODA time-mean estimate fall within the range of uncertainty of the INSTANT estimate. In terms of temporal variability, the scatter among different ODA estimates averaged over time is 1.7 Sv, which is substantially smaller than the magnitude of the temporal variability simulated by the ODA systems. Therefore, the overall “signal-to-noise” ratio for the ensemble estimates is larger than one. The best consistency among the products occurs on seasonal-to-interannual time scales, with generally stronger (weaker) ITF during boreal summer (winter) and during La Nina (El Nino) events. The scatter among different products for seasonal-to-interannual time scales is approximately 1 Sv. Despite the good consistency, systematic difference is found between most ODA products and the INSTANT observations. All but the highest-resolution (18 km) ODA product show a dominant annual cycle while the INSTANT estimate and the 18-km product exhibit a strong semi-annual signal. The coarse resolution is an important factor that limits the level of agreement between ODA and INSTANT estimates. Decadal signals with periods of 10–15 years are seen. The most conspicuous and consistent decadal change is a relatively sharp increase in ITF transport during 1993–2000 associated with the strengthening tropical Pacific trade wind. Most products do not show a weakening ITF after the mid-1970s’ associated with the weakened Pacific trade wind. The scatter of ODA estimates is smaller after than before 1980, reflecting the impact of the enhanced observations after the 1980s. To assess the representativeness of using the average over a three-year period (e.g., the span of the INSTANT Program) to describe longer-term mean, we investigate the temporal variations of the three-year low-pass ODA estimates. The average variation is about 3.6 Sv, which is largely due to the increase of ITF transport from 1993 to 2000. However, the three-year average during the 2004–2006 INSTANT Program period is within 0.5 Sv of the long-term mean for the past few decades. 相似文献
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