Ying K.,Beijing Normal University |
Zheng X.,Beijing Normal University |
Quan X.-W.,University of Colorado at Boulder |
International Journal of Climatology | Year: 2013
An effort is made to identify the 'more predictable' signals in seasonal precipitation in the Eastern Yangtze-Huaihe River Valley of China based on the observations recorded for the period of 1951-2004 at a network of 23 stations in this region. A recently developed methodology for decomposing the interannual variance of seasonal mean climate fields is applied to precipitation time series at the stations. This allows the total interannual variance to be separated into the variance of a slow component, or predictable signal, and the variance of a more noisier component of rainfall associated with intraseasonal variability. The potential predictability (signal-to-total ratio) is generally moderate in this region and is lower during winter from January to March (JFM) and higher in summer from May to July (MJJ) and autumn from November to January (NDJ). Empirical orthogonal function (EOF) analysis is then applied to the predictable-, intraseasonal- and total-covariance matrices, respectively. Leading EOF modes of the total component more often resemble the EOF modes of the intraseasonal component when the potential predictability is lower and vice versa. Temporal variation of the leading modes in the predictable components is more closely linked to the interannual variability of Eastern Pacific sea surface temperature (SST) in early summer (MJJ), North Atlantic SST in late summer (JAS) and El Niño/Southern oscillation in late autumn (NDJ). The rainfall SST connections found in these seasons persist throughout the entire 54-year period. The predictable rainfall modes also have apparent linkages to the intensity and position of the Western Pacific subtropical high during the early summer and late autumn with more rainfall occurring in the region when the height pattern is more intensive and extends further west. During the late summer, the predictable rainfall variability is accompanied by a large variation of tropospheric advection from north of the region, indicating the impact of an anomalous atmospheric circulation associated with the variation of summer North Atlantic Oscillation. © 2013 Royal Meteorological Society.
Martin M.,UK Met Office |
Dash P.,National Oceanic and Atmospheric Administration |
Dash P.,Cooperative Institute for Research in the Atmospheres CIRA |
Ignatov A.,National Oceanic and Atmospheric Administration |
And 12 more authors.
Deep-Sea Research Part II: Topical Studies in Oceanography | Year: 2012
Many sea surface temperature (SST) gap-free gridded analysis (Level 4, or L4) fields are produced by various groups in different countries. The Group for High Resolution SST (GHRSST) is an international collaboration body which has formed the inter-comparison technical advisory group (IC-TAG), to advise SST producers and users on the relative performance of these SST fields. This two-part paper describes two of the three major systems developed under GHRSST coordination towards this goal. Part one (this paper) describes the GHRSST Multi-Product Ensemble (GMPE) system, which runs on a daily basis at the UK Met Office, taking various L4 analyses as inputs, transferring them onto a common grid, and producing an ensemble median and standard deviation. The various analysis systems contributing to the GHRSST inter-comparisons are discussed, highlighting areas of commonality between the systems as well as those parts of the systems where there is less agreement on the appropriate algorithmic or parametric choices. The characteristics of the contributing L4 analyses are demonstrated by comparing them to near-surface Argo profile temperature data, which provide an independent measurement of SST and have been shown to provide a good estimate of foundation SST (the SST free of diurnal warming). The feature resolution characteristics of the L4 analyses are demonstrated by calculating horizontal gradients of the SST fields (on their original grid). The accuracy and resolution of the GMPE median are compared with those of the input analyses using the same metrics, showing that the GMPE median is more accurate than any of the contributing analyses with a standard deviation error of 0.40. K globally with respect to near-surface Argo data. For use in climate applications such as trend analysis or assimilation into climate models, it is important to have a good measure of uncertainty, so the suitability of the GMPE standard deviation as a measure of uncertainty is explored. This assessment shows that, over large spatial and temporal scales, the spread in the ensemble does have a strong relationship with the error in the median, although it underestimates the error by about one third. © 2012 .
Izumo T.,University of Tokyo |
Izumo T.,University Pierre and Marie Curie |
Lengaigne M.,University Pierre and Marie Curie |
Vialard J.,University Pierre and Marie Curie |
And 6 more authors.
Climate Dynamics | Year: 2014
The Indian Ocean Dipole (IOD) can affect the El Niño-Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981-2009). The present paper explores the interdecadal robustness of this result over the 1872-2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD-ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean. © 2013 Springer-Verlag Berlin Heidelberg.
Zhang C.,University of Miami |
Gottschalck J.,College Park |
Maloney E.D.,Colorado State University |
Moncrieff M.W.,NCAR |
And 4 more authors.
Geophysical Research Letters | Year: 2013
The Madden-Julian oscillation poses great challenges to our understanding and prediction of tropical convection and the large-scale circulation. Several internationally coordinated activities were recently formed to meet the challenges from the perspectives of numerical simulations, prediction, diagnostics, and virtual and actual field campaigns. This article provides a brief description of these activities and their connections, with the motivation in part to encourage the next generation of physical scientists to help solve the grand challenging problem of the Madden-Julian oscillation. Key Points Several unprecedented international studies of the MJO are underway They provide opportunities to further our understanding of the MJO Advanced prediction skill of the MJO will have tremendous societal benefits. ©2013 American Geophysical Union. All Rights Reserved.
Tripathi O.P.,University of Reading |
Baldwin M.,University of Exeter |
Charlton-Perez A.,University of Reading |
Charron M.,Environment Canada |
And 12 more authors.
Quarterly Journal of the Royal Meteorological Society | Year: 2015
Extreme variability of the winter- and spring-time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond 5 days and into the sub-seasonal range (0-30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecast skill by 5-7% in the extratropics on sub-seasonal time-scales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context. © 2014 The Authors.
Collins M.,University of Exeter |
Collins M.,UK Met Office |
An S.-I.,Yonsei University |
Cai W.,CSIRO |
And 12 more authors.
Nature Geoscience | Year: 2010
The El Nĩo-Southern Oscillation (ENSO) is a naturally occurring fluctuation that originates in the tropical Pacific region and affects ecosystems, agriculture, freshwater supplies, hurricanes and other severe weather events worldwide. Under the influence of global warming, the mean climate of the Pacific region will probably undergo significant changes. The tropical easterly trade winds are expected to weaken; surface ocean temperatures are expected to warm fastest near the equator and more slowly farther away; the equatorial thermocline that marks the transition between the wind-mixed upper ocean and deeper layers is expected to shoal; and the temperature gradients across the thermocline are expected to become steeper. Year-to-year ENSO variability is controlled by a delicate balance of amplifying and damping feedbacks, and one or more of the physical processes that are responsible for determining the characteristics of ENSO will probably be modified by climate change. Therefore, despite considerable progress in our understanding of the impact of climate change on many of the processes that contribute to El Nĩo variability, it is not yet possible to say whether ENSO activity will be enhanced or damped, or if the frequency of events will change. © 2010 Macmillan Publishers Limited. All rights reserved.
Langford S.,CAWCR |
Monthly Weather Review | Year: 2013
Seasonal rainfall predictions for Australia from the Predictive Ocean Atmosphere Model for Australia (POAMA), version P15b, coupled model seasonal forecast system, which has been run operationally at the Australian Bureau of Meteorology since 2002, are overconfident (too low spread) and only moderately reliable even when forecast accuracy is highest in the austral spring season. The lack of reliability is a major impediment to operational uptake of the coupled model forecasts. Considerable progress has been made to reduce reliability errors with the new version of POAMA2, which makes use of a larger ensemble from three different versions of the model. Although POAMA2 can be considered to be multimodel, its individual models and forecasts are similar as a result of using the same perturbed initial conditions and the same model lineage. Reliability of thePOAMA2 forecasts, although improved, remains relatively low. Hence, the authors explore the additional benefit that can be attained using more independent models available in the European Union Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project. Although forecast skill and reliability of seasonal predictions of Australian rainfall are similar for POAMA2 and the ENSEMBLES models, forming a multimodel ensemble using POAMA2 and the ENSEMBLES models is shown to markedly improve reliability of Australian seasonal rainfall forecasts. The benefit of including POAMA2 into this multimodel ensemble is due to the additional information and skill of the independent model, and not just due to an increase in the number of ensemble members. The increased reliability, as well as improved accuracy, of regional rainfall forecasts from this multimodel ensemble system suggests it could be a useful operational prediction system. © 2013 American Meteorological Society.
Oke P.R.,CSIRO |
Brassington G.B.,CAWCR |
Cummings J.,U.S. Navy |
Martin M.,UK Met Office |
Hernandez F.,Mercator Ocean
Journal of Operational Oceanography | Year: 2012
This paper compares the performance of operational short-range ocean forecast systems developed under the Global Ocean Data Assimilation Experiment (GODAE) - an international effort to demonstrate the feasibility of operational ocean forecasting. 'Best estimates' from four different operational forecast systems (either analyses, hindcasts, or nowcasts) are inter-compared for the Tasman and Coral Seas, off eastern Australia. Systems considered include those developed in Australia, France, the USA, and the UK. Each system is compared to observations of along-track sea-level anomaly, sea-surface temperature, near-surface velocity, and sub-surface temperature and salinity. All have their strengths and weaknesses, and each system out-performs all others in one aspect or another. With few exceptions, all systems demonstrate signal-to-noise ratios greater than one for all variables. Due to the Australian focus, in addition to the best estimates from the operational systems, operational forecasts and a delayed-mode reanalysis are also inter-compared using the Australian system. The Australian system generally performs the best for sea-level anomaly; the French system is best for near-surface velocities; the USA system generally performs the best for sea-surface temperature; and the UK system is best for sub-surface temperature and salinity. These findings provide useful indicators of deficiencies in each system and clear metrics by which future developments should be assessed. Based on these results and other practical considerations the adoption of multimodel consensus forecasting, using all available forecasts from all systems, is promoted as the most robust approach for the user community. Such developments are being pursued under GODAE OceanView - the successor to GODAE. The results show the success of GODAE in demonstrating the feasibility of operational oceanography.
Kitsios V.,CSIRO |
Frederiksen J.S.,CSIRO |
Proceedings of the 18th Australasian Fluid Mechanics Conference, AFMC 2012 | Year: 2012
Stochastic and deterministic subgrid-scale parameterisations are developed for the large eddy simulation (LES) of oceanic flows. Parameterisations are developed for a flow representative of the Antarctic Circumpolar Current (ACC), generated using a spectral quasi-geostrophic code. The subgrid eddy viscosity coefficients are calculated using the approach of , whereby a high resolution reference direct numerical simulation (DNS) is truncated back to the LES truncation wavenumber TR. Two subgrid parameterisations are produced: isotropic, in which the coefficients are only dependent on the total wavenumber (n); and anisotropic, in which the coefficients are also dependent on zonal wavenumbers (m). These LES variants reproduce the kinetic energy spectra of the DNS at various resolutions. Scaling laws are determined representing the isotropic profiles, which make the parameterisations more generally applicable, as they remove the need for a higher resolution reference simulation.
Feng M.,CSIRO |
Feng M.,Western Australian Marine Science Institution |
Hendon H.H.,CAWCR |
Xie S.-P.,University of California at San Diego |
And 6 more authors.
Geophysical Research Letters | Year: 2015
Ningaloo Niño refers to the episodic occurrence of anomalously warm ocean conditions along the subtropical coast of Western Australia (WA). Ningaloo Niño typically develops in austral spring, peaks in summer, and decays in autumn, and it often occurs in conjunction with La Niña conditions in the Pacific which promote poleward transport of warm tropical waters by the Leeuwin Current. Since the late 1990s, there has been a marked increase in the occurrence of Ningaloo Niño, which is likely related to the recent swing to the negative phase of the Interdecadal Pacific Oscillation (IPO) and enhanced El Niño-Southern Oscillation variance since 1970s. The swing to the negative IPO sustains positive heat content anomalies and initiates more frequent cyclonic wind anomalies off the WA coast so favoring enhanced poleward heat transport by the Leeuwin Current. The anthropogenically forced global warming has made it easier for natural variability to drive extreme ocean temperatures in the region. Key Points There has been an increased frequency of Ningaloo Niño since late 1990s Negative IPO sustains positive heat content anomalies and strong Leeuwin Current Global warming and natural variability together drive extreme ocean temperatures ©2014. American Geophysical Union. All Rights Reserved.