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Mojib Latif and Nicholas E. Graham

Abstract

The time history of upper-ocean temperatures in the tropical Pacific has been used as a predictor in a statistical prediction scheme to forecast SST anomalies in this region. The temperature variations were taken from the output of an oceanic general circulation model that was forced by observed winds for the period 1961 to 1985. Since such model data are presently used as initial conditions in prediction experiments with coupled ocean–atmosphere models, it is of particular interest to investigate up to what lead time tropical Pacific SST is predictable without the coupling of an atmosphere model to the ocean model.

We compared our results with those obtained by the persistence forecast and with those obtained by using the wind stresses themselves as predictors in a statistical forecast model. It is shown that using the upper ocean temperatures from the ocean model forced by observed winds gives significantly better skills at lead times of 6 to 12 months compared to persistence and to the pure wind-stress model. Off-equatorial heat content anomalies at 5°N are shown to contribute significantly to the predictability at these lead times, while those at 12°N do not.

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Nicholas E. Graham and Konstantine P. Georgakakos

Abstract

Numerical simulation techniques and idealized reservoir management models are used to assess the utility of climate information for the effective management of a single multiobjective reservoir. Reservoir management considers meeting release and reservoir volume targets and minimizing wasteful spillage. The influence of reservoir size and inflow variability parameters on the management benefits is examined. The effects of climate and demand (release target) change on the management policies and performance are also quantified for various change scenarios. Inflow forecasts emulate ensembles of dynamical forecasts for a hypothetical climate system with somewhat predictable low-frequency variability. The analysis considers the impacts of forecast skill. The mathematical problem is cast in a dimensionless time and volume framework to allow generalization. The present work complements existing research results for specific applications and expands earlier analytical results for simpler management situations in an effort to draw general conclusions for the present-day reservoir management problem under uncertainty. The findings support the following conclusions: (i) reliable inflow forecasts are beneficial for reservoir management under most situations if adaptive management is employed; (ii) tolerance to forecasts of lower reliability tends to be higher for larger reservoirs; (iii) reliable inflow forecasts are most useful for a midrange of reservoir capacities; (iv) demand changes are more detrimental to reservoir management performance than inflow change effects of similar magnitude; (v) adaptive management is effective for mitigating climatic change effects and may even help to mitigate demand change effects.

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Nicholas E. Graham and Henry F. Diaz

Using NCEP–NCAR reanalysis and in situ data, evidence of important changes in the winter (December–March) cyclone climatology of the North Pacific Ocean over the past 50 years is found. The frequency and intensity of extreme cyclones has increased markedly, with associated upward trends in extreme surface winds between 25° and 40°N and major changes in cyclone-related circulation patterns in the Gulf of Alaska. Related increases in extreme wave heights are inferred from wave measurements and wave-model hindcast results. The more vigorous cyclone activity has apparently resulted from increasing upper-tropospheric winds and vertical wind shear over the central North Pacific. Such changes, which create an environment more favorable for cyclone formation and intensification, may be related to the observed modulation of El Niño–related teleconnections at decadal and longer timescales. It is intriguing that this trend has been relatively steady rather than the sudden or stepwise shifts documented for other aspects of North Pacific climate change. Increasing sea surface temperatures in the western tropical Pacific are suggested as a plausible cause of the observed changes, though other underlying mechanisms may also contribute.

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Nicholas E. Graham and Warren B. White

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No abstract available.

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Nicholas E. Graham and Warren B. White

Abstract

Coupled models of the Pacific ocean–atmosphere system have been shown to produce oscillations in the model coupled system that resemble the observed El Niño–Southern Oscillation (ENSO) cycle in many respects. The tendency for the coupled models to oscillate is due to delayed negative feedback resulting from the reflection of Rossby wave activity from the western boundary. In the real ocean the reflection process is difficult to observe. Furthermore, among other potential complications affecting the generation and propagation baroclinic waves, the real western boundary is ragged with unknown reflective characteristics rather than the efficiently reflecting boundaries found in the oceanic components of the simple coupled models that produce ENSO-like oscillations. Thus, the validity of the delayed negative feedback–coupled oscillator concept remains open to question.

We present the results of experiments with two coupled models, one simple and one more complex, in which realistic western equatorial boundary data were prescribed. The working hypothesis for these experiments is that, if western boundary reflections play the role envisioned under the coupled oscillator scenario in the real world, then the models should produce correctly timed ENSO activity. The results of these experiments strongly support this hypothesis and are consistent with the systematic role of western boundary reflections in the ENSO cycle and the validity of the delayed negative feedback/coupled oscillator concept.

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Mark L. Morrissey and Nicholas E. Graham

Analysis of recently compiled tropical Pacific rain gauge measurements shows a trend toward increased precipitation in the central tropical Pacific during the period 1971–90. Previous studies of precipitation trends in this region have used satellite data and shipboard measurements, which have been demonstrated to contain a variety of known and unknown biases that could artificially produce a trend. Using rain gauge data, an independent and direct measure of the precipitation trends in the Pacific corroborates previous results based on satellite measurements, estimates of oceanic evaporation from shipboard meteorological observations, and results from numerical models. Furthermore, the result is consistent with suggestions that an enhancement of the tropical hydrologic cycle has been responsible for the increases in globally averaged tropospheric temperatures during the past two decades.

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Simon J. Mason and Nicholas E. Graham

Abstract

The relative operating characteristic (ROC) curve is a highly flexible method for representing the quality of dichotomous, categorical, continuous, and probabilistic forecasts. The method is based on ratios that measure the proportions of events and nonevents for which warnings were provided. These ratios provide estimates of the probabilities that an event will be forewarned and that an incorrect warning will be provided for a nonevent. Some guidelines for interpreting the ROC curve are provided. While the ROC curve is of direct interest to the user, the warning is provided in advance of the outcome and so there is additional value in knowing the probability of an event occurring contingent upon a warning being provided or not provided. An alternative method to the ROC curve is proposed that represents forecast quality when expressed in terms of probabilities of events occurring contingent upon the warnings provided. The ratios used provide estimates of the probability of an event occurring given the forecast that is issued. Some problems in constructing the curve in a manner that is directly analogous to that for the ROC curve are highlighted, and so an alternative approach is proposed. In the context of probabilistic forecasts, the ROC curve provides a means of identifying the forecast probability at which forecast value is optimized. In the context of continuous variables, the proposed relative operating levels curve indicates the exceedence threshold for defining an event at which forecast skill is optimized, and can enable the forecast user to estimate the probabilities of events other than that defined by the forecaster.

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Konstantine P. Georgakakos and Nicholas E. Graham

Abstract

This paper examines the conditions for which beneficial use of forecast uncertainty may be made for improved reservoir release decisions. It highlights the parametric dependencies of the effects of uncertainty in seasonal inflow volumes on the optimal release and objective function of a single reservoir operated to meet a single volume target at the end of the season under volume and release constraints. The duration of the “season” may be one or several months long. The analysis invokes the application of Kuhn–Tucker theory, and it shows that the presence of uncertainty introduces complex dependence of the optimal release and objective function on the reservoir parameters and uncertain inflow forcing. The seasonal inflow volume uncertainty is represented by a bounded symmetric beta distribution with a given mean, which is considered to be unbiased, and a half-range QR. The authors find that the use of predicted inflow uncertainty is particularly beneficial during operation with a volume target that is either near reservoir capacity or near zero reservoir volume, with the optimal release being directly dependent on QR in these situations. This positive finding is moderated by the additional finding that errors in the estimation of predicted QR can result in significant operation losses (larger deviations from the target volume) that are due to suboptimal release decisions. Furthermore, the presence of binding release constraints leads to loss of optimal release and objective function benefits due to the seasonal inflow uncertainty predictions, suggesting less rigid release policies for improved operations under uncertain forecasts. It is also shown that the reservoir capacity values for which optimal reservoir operations are most sensitive to seasonal inflow uncertainty predictions are found to be at most 5 times the uncertainty range of the predicted seasonal inflow volume and to be at least as large as the uncertainty range of predicted inflow volumes. Suggestions for continued research in this area are offered.

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Duane E. Waliser, Nicholas E. Graham, and Catherine Gautier

Abstract

Currently, there are two long-term satellite-derived datasets most are frequently used as indices for tropical deep convection. These are the Outgoing Longwave Radiation (OLR) and Highly Reflective Cloud (HRC) datasets. Although both of these datasets have demonstrated their value, no direct comparison of these datasets has been conducted, to determine how well they agree when used to estimate tropical convection, nor has there been much work toward comparing these long-record datasets with more recently developed convection datasets. This information is vital since the inhomogeneous sampling of the in situ rainfall record makes it inadequate for many studies concerning tropical convection and the more modern datasets have not achieved a climatologically useful record length for all studies. The goal of this paper is to compare these two datasets in order to quantify their strengths and weaknesses. This information will provide guidance in choosing the most appropriate dataset(s) for subsequent studies, interpreting the results from those studies, and extending more modern convection datasets backward.

Comparisons are done in terms of their climatological and frequency-dependent characteristics, their consistency in identifying deep tropical convection, and their relationships to local sea surface temperature (SST). Additionally, use is made of the more modern, shorter-terrain International Satellite Cloud Climatology Project stage C2 dataset as a means of further comparison and validation. The results of this study reveal some important differences between the HRC and OLR in terms of their temporal and spatial scales of variability, their relationships to other geophysical fields, and the logistics of their use. Further, they suggest that for many applications the HRC more accurately represents the characteristics of cloud cluster-scale tropical convection. This is especially true in cases where 1) characterization of the spatial scales or frequency-dependent variability of convection is important, 2) the relationships between deep convection and SST or water vapor are being considered, and 3) the domain of interest is large enough to contain spatial inhomogeneities, such as land-sea contrasts or inhomogeneous SST and moisture fields.

One new and important finding of this study is that both the OLR-SST and HRC-SST relationships show that SSTs in excess of about 29.5°C tend to occur only under conditions of diminished convection. Thus, the maximum convective activity does not occur over the warmest (>29.5°C) water; rather, the warmest water occurs under “clear,” less-convective skies. Further, our results empirically demonstrate that in a highly convective regime the maximum equilibrium SST that can be supported is about 29.5°C. These results are further evidence that convective-cloud complexes provide a systematic and climatologically important cooling effect on the surface temperature.

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Arthur J. Miller, Tim P. Barnett, and Nicholas E. Graham

Abstract

Tropical Pacific SST hindcasts are examined in the Zebiak and Cane (Lamont), Latif (MPIZ), Oberhuber (OPYC), and GFDL ocean models, each forced by the same wind-stress fields over the 1970–85 time interval. Skill scores reveal that, although all the models exhibit significant skill, the regions where the skill is maximized differ from model to model. The simplest model (Lamont) has maximum skills in the eastern basin near the boundary while the three GCMs have maxima in central Pacific regions. We also examine, via canonical correlation analysis (CCA), the heat budgets of the surface layers of the Lamont, MPIZ, and OPYC models. We find that although similar spatial relationships exist for the mechanisms that excite SST anomalies (i.e., zonal advection, meridional advection, and vertical advection/mixing), the balance of the strength of them terms is different for each model. Vertical advection tends to control the large-scale structure of SST in the Lamont model, meridional advection provides the dominant large-scale forcing for SST anomalies in the MPIZ model, and all three terms are important in the region of developing SST in the OPYC model. CCA reconstructions of the El Niño events of 1972–73 and 1982–83 reveal that the Lamont model does not exhibit any clear eastward propagation of SST; the MPIZ model propagates SST anomalies eastward for both the 1972–73 and 1982–83 El Niño events while the OPYC model propagates SST eastward for the 1982–83 El Niño and develops SST in place for the 1972–73 El Niño.

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