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  • 1
    Publication Date: 2017-06-28
    Print ISSN: 0094-8276
    Electronic ISSN: 1944-8007
    Topics: Geosciences , Physics
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  • 2
    Publication Date: 2016-10-21
    Description: Recent studies have highlighted the role of subsurface ocean dynamics in modulating eastern Pacific (EPac) hurricane activity on interannual time scales. In particular, the well-known El Niño–Southern Oscillation (ENSO) recharge–discharge mechanism has been suggested to provide a good understanding of the year-to-year variability of hurricane activity in this region. This paper investigates the influence of equatorial subsurface subannual and intraseasonal oceanic variability on tropical cyclone (TC) activity in the EPac. That is to say, it examines previously unexplored time scales, shorter than interannual, in an attempt to explain the variability not related to ENSO. Using ocean reanalysis products and TC best-track archive, the role of subannual and intraseasonal equatorial Kelvin waves (EKW) in modulating hurricane intensity in the EPac is examined. It is shown first that these planetary waves have a clear control on the subannual and intraseasonal variability of thermocline depth in the EPac cyclone-active region. This is found to affect ocean subsurface temperature, which in turn fuels hurricane intensification with a marked seasonal-phase locking. This mechanism of TC fueling, which explains up to 30% of the variability of TC activity unrelated to ENSO (around 15%–20% of the total variability), is embedded in the large-scale equatorial dynamics and therefore offers some predictability with lead time up to 3–4 months at seasonal and subseasonal time scales.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 3
    Publication Date: 2017-08-30
    Description: A set of ensemble seasonal reforecasts for 1958–2014 is conducted using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2. In comparison with other current reforecasts, this dataset extends the seasonal reforecasts to the 1960s–70s. Direct comparison of the predictability of the ENSO events occurring during the 1960s–70s with the more widely studied ENSO events since then demonstrates the seasonal forecast system’s capability in different phases of multidecadal variability and degrees of global climate change. A major concern for a long reforecast is whether the seasonal reforecasts before 1979 provide useful skill when observations, particularly of the ocean, were sparser. This study demonstrates that, although the reforecasts have lower skill in predicting SST anomalies in the North Pacific and North Atlantic before 1979, the prediction skill of the onset and development of ENSO events in 1958–78 is comparable to that for 1979–2014. In particular, the ENSO predictions initialized in April during 1958–78 show higher skill in the summer. However, the skill of the earlier predictions declines faster in the ENSO decaying phase, because the reforecasts initialized after boreal summer persistently predict lingering wind and SST anomalies over the eastern equatorial Pacific during such events. Reforecasts initialized in boreal fall overestimate the peak SST anomalies of strong El Niño events since the 1980s. Both phenomena imply that the model’s air–sea feedback is overly active in the eastern Pacific before ENSO event termination. Whether these differences are due to changes in the observing system or are associated with flow-dependent predictability remains an open question.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 4
    Publication Date: 2020-06-01
    Description: Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
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  • 5
    Publication Date: 2015-10-01
    Description: Forty years ago, Klaus Wyrtki of the University of Hawaii launched an “El Niño Watch” expedition to the eastern equatorial Pacific to document oceanographic changes that were expected to develop during the onset of an El Niño event in early 1975. He and his colleagues used a very simple atmospheric pressure index to predict the event and convinced the National Science Foundation and Office of Naval Research to support an expedition to the eastern Pacific on relatively short notice. An anomalous warming was detected during the first half of the expedition, but it quickly dissipated. Given the state of the art in El Niño research at the time, Wyrtki and colleagues could offer no explanation for why the initial warming failed to amplify, nor could they connect what they observed to what was happening in other parts of the basin prior to and during the expedition. With the benefit of hindsight, the authors provide a basin-scale context for what the expedition observed, elucidate the dynamical processes that gave rise to the abbreviated warming that was detected, and present retrospective forecasts of the event using modern coupled ocean–atmosphere dynamical model prediction systems. Reviewing this history highlights how early pioneers in El Niño research, despite the obstacles they faced, were able to make significant progress through bold initiatives that advanced the frontiers of our knowledge. It is also evident that, even though the scientific community today has a much deeper understanding of climate variability, more advanced observational capabilities, and sophisticated seasonal forecasting tools, skillful predictions of El Niño and its cold counterpart La Niña remain a major challenge.
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
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  • 6
    Publication Date: 2014-04-23
    Description: Climate change from increased greenhouse gases arises from a global energy imbalance at the top of the atmosphere (TOA). TOA measurements of radiation from space can track changes over time but lack absolute accuracy. An inventory of energy storage changes shows that over 90% of the imbalance is manifested as a rise in ocean heat content (OHC). Data from the Ocean Reanalysis System, version 4 (ORAS4), and other OHC-estimated rates of change are used to compare with model-based estimates of TOA energy imbalance [from the Community Climate System Model, version 4 (CCSM4)] and with TOA satellite measurements for the year 2000 onward. Most ocean-only OHC analyses extend to only 700-m depth, have large discrepancies among the rates of change of OHC, and do not resolve interannual variability adequately to capture ENSO and volcanic eruption effects, all aspects that are improved with assimilation of multivariate data. ORAS4 rates of change of OHC quantitatively agree with the radiative forcing estimates of impacts of the three major volcanic eruptions since 1960 (Mt. Agung, 1963; El Chichón, 1982; and Mt. Pinatubo, 1991). The natural variability of the energy imbalance is substantial from month to month, associated with cloud and weather variations, and interannually mainly associated with ENSO, while the sun affects 15% of the climate change signal on decadal time scales. All estimates (OHC and TOA) show that over the past decade the energy imbalance ranges between about 0.5 and 1 W m−2. By using the full-depth ocean, there is a better overall accounting for energy, but discrepancies remain at interannual time scales between OHC- and TOA-based estimates, notably in 2008/09.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 7
    Publication Date: 2005-08-15
    Description: The European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts since 1997 with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification. Seasonal predictability is to a large extent due to the El Niño–Southern Oscillation (ENSO) climate oscillations. ENSO predictions of the ECMWF models are compared with those of statistical models, some of which are used operationally. The relative skill depends strongly on the season. The dynamical models are better at forecasting the onset of El Niño or La Niña in boreal spring to summer. The statistical models are comparable at predicting the evolution of an event in boreal fall and winter.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 8
    Publication Date: 2006-12-01
    Description: Variations in tropical Atlantic SST are an important factor in seasonal forecasts in the region and beyond. An analysis is given of the capabilities of the latest generation of coupled GCM seasonal forecast systems to predict tropical Atlantic SST anomalies. Skill above that of persistence is demonstrated in both the northern tropical and equatorial Atlantic, but not farther south. The inability of the coupled models to correctly represent the mean seasonal cycle is a major problem in attempts to forecast equatorial SST anomalies in the boreal summer. Even when forced with observed SST, atmosphere models have significant failings in this area. The quality of ocean initial conditions for coupled model forecasts is also a cause for concern, and the adequacy of the near-equatorial ocean observing system is in doubt. A multimodel approach improves forecast skill only modestly, and large errors remain in the southern tropical Atlantic. There is still much scope for improving forecasts of tropical Atlantic SST.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 9
    Publication Date: 2012-04-28
    Description: Ocean heat content (HC) is one of the key indicators of climate variability and also provides ocean memory critical for seasonal and decadal predictions. The availability of multiple operational ocean analyses (ORAs) now routinely produced around the world is an opportunity for estimation of uncertainties in HC analysis and development of ensemble-based operational HC climate indices. In this context, the spread across the ORAs is used to quantify uncertainties in HC analysis and the ensemble mean of ORAs to identify, and to monitor, climate signals. Toward this goal, this study analyzed 10 ORAs, two objective analyses based on in situ data only, and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability, and long-term trend of HC in the upper 300 m (HC300) from 1980 to 2009 are compared. The spread across HC300 analyses generally decreased with time and reached a minimum in the early 2000s when the Argo data became available. There was a good correspondence between the increase of data counts and reduction of the spread. The agreement of HC300 anomalies among different ORAs, measured by the signal-to-noise ratio (S/N), is generally high in the tropical Pacific, tropical Indian Ocean, North Pacific, and North Atlantic but low in the tropical Atlantic and extratropical southern oceans where observations are very sparse. A set of climate indices was derived as HC300 anomalies averaged over the areas where the covariability between SST and HC300 represents the major climate modes such as ENSO, Indian Ocean dipole, Atlantic Niño, Pacific decadal oscillation, and Atlantic multidecadal oscillation.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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  • 10
    Publication Date: 2005-08-15
    Description: Since 1997, the European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts with ensembles of a coupled ocean–atmosphere model, System-1 (S1). In January 2002, a new version, System-2 (S2), was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 yr of hindcasts and forecasts are now available for verification. The main cause of seasonal predictability is El Niño and La Niña perturbing the average weather in many regions and seasons throughout the world. As a baseline to compare the dynamical models with, a set of simple statistical models (STAT) is constructed. These are based on persistence and a lagged regression with the first few EOFs of SST from 1901 to 1986 wherever the correlations are significant. The first EOF corresponds to ENSO, and the second corresponds to decadal ENSO. The temperature model uses one EOF, the sea level pressure (SLP) model uses five EOFs, and the precipitation model uses two EOFs but excludes persistence. As the number of verification data points is very low (15), the simplest measure of skill is used: the correlation coefficient of the ensemble mean. To further reduce the sampling uncertainties, we restrict ourselves to areas and seasons of known ENSO teleconnections. The dynamical ECMWF models show better skill in 2-m temperature forecasts over sea and the tropical land areas than STAT, but the modeled ENSO teleconnection pattern to North America is shifted relative to observations, leading to little pointwise skill. Precipitation forecasts of the ECMWF models are very good, better than those of the statistical model, in southeast Asia, the equatorial Pacific, and the Americas in December–February. In March–May the skill is lower. Overall, S1 (S2) shows better skill than STAT at lead time of 2 months in 29 (32) out of 40 regions and seasons of known ENSO teleconnections.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
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