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Nicholas E. Graham
,
Tim P. Barnett
,
Robert M. Chervin
,
Michael E. Schlesinger
, and
Ulrich Schlese

Abstract

Many of the processes that have important effects on both the climatological distribution and interannual variability of sea surface temperatures (SSTs) in the tropical oceans are greatly affected by the surface wind field. For this reason accurate simulation of the surface wind is a key factor governing the success of coupled tropical ocean-atmosphere models. This paper presents the results of two analyses that investigate the quality of wind fields produced by three general circulation models (GCMs) over the tropical Indian and Pacific oceans.

The first analysis concerns the annual cycles of the tropical wind fields simulated by versions of the GCM at the Oregon State University (OSU), European Centre for Medium Range Forecasts (ECMWF), and National Center for Atmospheric Research (NCAR). These models have similar horizontal resolutions but vary widely in vertical resolution. The results show that although there are substantial differences in model performance, apparently related to differences in vertical resolution, there are also clear similarities in their behavior. Each GCM did best in major trade wind regions and somewhat poorly in convectively active areas with light winds. This finding suggests that the formulations governing the interactions between persistent convection and the circulation may limit model performance.

A second analysis examines the response of the NCAR GCM, in terms of tropical Pacific wind stress, to prescribed SST anomalies over the period 1961–1972. It was found that the model response to SST anomalies associated with the El Niño/Southern Oscillation(ENSO) was distinct and in some respects resembled that of the real atmosphere. However, there were important discrepancies in the spatial configuration of the GCM field and in the amplitude of response of the GCM to the SST anomalies. An analysis of these discrepancies suggests that while the trapped equatorial Kelvin wave response of an ocean model coupled to this GCM would be qualitatively correct, differences in the GCM and observed forcing fields would result in large errors away from the equator. Tests with the Florida State University model of the tropical Pacific, to be reported in a later paper, support this conclusion.

Taken together, these findings suggest that while GCMs are capable of reproducing correctly many features of the tropical surface wind fields, discrepancies remain with respect to both the annual cycle and the response to the anomalous SST patterns associated with ENSO. These discrepancies appear to be related, at least in part, to interactions between organized convection and the circulation. To what degree these differences would affect the oceanic component of a coupled model is currently under study.

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Nicholas E. Graham
,
Tim P. Barnett
,
Robert Wilde
,
Michael Ponater
, and
Silke Schubert

Abstract

Three numerical experiments have been conducted to explore the relative roles of midlatitude and tropical SSTs in producing atmospheric variability. In these experiments, anomalous observed SSTs were prescribed in 1) the tropical oceans only, 2) the midlatitude oceans only, and 3) globally. These simulations were conducted with the same atmospheric model and covered the period 1970–88. Although each simulation reproduced some aspects of the observed circulation variability, the results from the two experiments including tropical SSTs performed best by most measure particularly in showing temporal signals that agreed with those seen in the observations. The results indicate that the response of the observed atmospheric circulation to North Pacific SST anomalies is much smaller and much less systematic than the response to tropical SSTs. It is suggested that the apparent links between North Pacific SSTs and the observed winter circulation am due primarily to the effects on oceanic forcing by the recurrent patterns of atmospheric variability remotely forced by changes in tropical SSTs. The results are consistent with the idea that the major shift in the winter circulation during the mid-1970s was forced by changes in tropical SSTS.

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Alexander Gershunov
,
Tim P. Barnett
,
Daniel R. Cayan
,
Tony Tubbs
, and
Lisa Goddard

Abstract

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical–statistical and full-dynamical approaches have been used to forecast El Niño–Southern Oscillation (ENSO)–related total precipitation, daily precipitation frequency, and average intensity anomalies during the January–March season. For El Niño winters, the hybrid approach emerges as the best performer, while La Niña forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Niña and El Niño winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available records is possible now for ENSO-extreme years.

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Nathalie Voisin
,
Alan F. Hamlet
,
L. Phil Graham
,
David W. Pierce
,
Tim P. Barnett
, and
Dennis P. Lettenmaier

Abstract

The benefits of potential electric power transfers between the Pacific Northwest (PNW) and California (CA) are evaluated using a linked set of hydrologic, reservoir, and power demand simulation models for the Columbia River and the Sacramento–San Joaquin reservoir systems. The models provide a framework for evaluating climate-related variations and long-range predictability of regional electric power demand, hydropower production, and the benefits of potential electric power transfers between the PNW and CA. The period of analysis is 1917–2002. The study results show that hydropower production and regional electric power demands in the PNW and CA are out of phase seasonally but that hydropower productions in the PNW and CA have strongly covaried on an annual basis in recent decades. Winter electric power demand and spring and annual hydropower production in the PNW are related to both El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO) through variations in winter climate. Summer power demand in CA is related primarily to variations in the PDO in spring. Hydropower production in CA, despite recent covariation with the PNW, is not strongly related to ENSO variability overall. Primarily because of strong variations in supply in the PNW, potential hydropower transfers between the PNW and CA in spring and summer are shown to be correlated to ENSO and PDO, and the conditional probability distributions of these transfers are therefore predictable with long lead times. Such electric power transfers are estimated to have potential average annual benefits of $136 and $79 million for CA and the PNW, respectively, at the year-2000 regional demand level. These benefits are on average 11%–27% larger during cold ENSO/PDO events and are 16%–30% lower during warm ENSO/PDO events. Power transfers from the PNW to CA and hydropower production in CA are comparable in magnitude, on average.

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David W. Pierce
,
Tim P. Barnett
,
Krishna M. AchutaRao
,
Peter J. Gleckler
,
Jonathan M. Gregory
, and
Warren M. Washington

Abstract

Observations show the oceans have warmed over the past 40 yr, with appreciable regional variation and more warming at the surface than at depth. Comparing the observations with results from two coupled ocean–atmosphere climate models [the Parallel Climate Model version 1 (PCM) and the Hadley Centre Coupled Climate Model version 3 (HadCM3)] that include anthropogenic forcing shows remarkable agreement between the observed and model-estimated warming. In this comparison the models were sampled at the same locations as gridded yearly observed data. In the top 100 m of the water column the warming is well separated from natural variability, including both variability arising from internal instabilities of the coupled ocean–atmosphere climate system and that arising from volcanism and solar fluctuations. Between 125 and 200 m the agreement is not significant, but then increases again below this level, and remains significant down to 600 m. Analysis of PCM’s heat budget indicates that the warming is driven by an increase in net surface heat flux that reaches 0.7 W m−2 by the 1990s; the downward longwave flux increases by 3.7 W m−2, which is not fully compensated by an increase in the upward longwave flux of 2.2 W m−2. Latent and net solar heat fluxes each decrease by about 0.6 W m−2. The changes in the individual longwave components are distinguishable from the preindustrial mean by the 1920s, but due to cancellation of components, changes in the net surface heat flux do not become well separated from zero until the 1960s. Changes in advection can also play an important role in local ocean warming due to anthropogenic forcing, depending on the location. The observed sampling of ocean temperature is highly variable in space and time, but sufficient to detect the anthropogenic warming signal in all basins, at least in the surface layers, by the 1980s.

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Nicholas E. Graham
,
Tim P. Barnett
,
Vijay G. Panchang
,
Ole M. Smedstad
,
James J. O'Brien
, and
Robert M. Chervin

Abstract

An experiment in which surface wind stress data from the National Center for Atmospheric Research global circulation model (GCM) was used to drive a simple model of the tropical Pacific is described. First, a 15-year integration of the GCM was conducted, forcing the model with observed sea surface temperatures (SSTs) for the period 1958–72 (the FORCED case). A parallel integration was conducted using long-term monthly mean SSTs (the CONTROL case). All other boundary forcing in both GCM simulations was identical. Surface wind stress date from each GCM integration were then used to drive the Florida State University 1½ layer, reduced gravity model of the tropical Pacific. A separate integration of the ocean model was conducted using observed wind stress for the period 1961–72 (the OBSTRESS case).

The goal of this research was to evaluate the response of a sophisticated GCM to tropical Pacific SST variability in terms of the surface wind stress field, and to investigate the sensitivity of a simple wind-driven ocean model to differences between the simulated and observed wind stress data. These are important issues bearing on the potential for accurate modeling of the coupled ocean-atmosphere system over the tropical Pacific. In this paper the results from the ocean model simulations and observations are compared in terms of interannual variability. An earlier paper describes the response of the GCM tropical Pacific surface wind stress field to prescribed SSTs.

The results show that the GCM response to prescribed SSTs produced wind stress anomaly patterns over the tropical Pacific that qualitatively resemble those observed in association with extremes of the El Niño activity, particularly in the central equatorial ocean. These wind stress anomalies produced upper-layer thickness anomalies in the eastern ocean that bore some resembalance to those found in observations and the results of the OBSTRESS integration; i.e., simulated El Niños did occur. In general, however, the El Niño signal in the FORCED case was considerably lower in magnitude and was less organized than in the OBSTRESS simulation. Further, the episode-to-episode changes in magnitude did not agree well with those in the OBSTRESS integration. These results reflect not only important differences between the spatial character of the response of the observed and GCM surface wind stress fields to El Niño SST anomalies, but also the fact that the overall coupling between the GCM atmosphere and the tropical Pacific SST field is not as strong as observed in the real ocean–atmosphere system.

A second interesting result was that quasi-periodic oceanic variability in some ways resembling that associated with El Niñc variability in the OBSTRESS and FORCED experiments was clearly evident in the CONTROL case. Considerations of the response of the model ocean to temporally random atmospheric forcing with large spatial scales shows that such organized low frequency variability may arise from the excitation of preferred resonant frequencies defined by the Rossby wave dispersion relation. This finding may have implications concerning the maintenance and character of the El Niño activity.

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Céline Bonfils
,
Benjamin D. Santer
,
David W. Pierce
,
Hugo G. Hidalgo
,
Govindasamy Bala
,
Tapash Das
,
Tim P. Barnett
,
Daniel R. Cayan
,
Charles Doutriaux
,
Andrew W. Wood
,
Art Mirin
, and
Toru Nozawa

Abstract

Large changes in the hydrology of the western United States have been observed since the mid-twentieth century. These include a reduction in the amount of precipitation arriving as snow, a decline in snowpack at low and midelevations, and a shift toward earlier arrival of both snowmelt and the centroid (center of mass) of streamflows. To project future water supply reliability, it is crucial to obtain a better understanding of the underlying cause or causes for these changes. A regional warming is often posited as the cause of these changes without formal testing of different competitive explanations for the warming. In this study, a rigorous detection and attribution analysis is performed to determine the causes of the late winter/early spring changes in hydrologically relevant temperature variables over mountain ranges of the western United States. Natural internal climate variability, as estimated from two long control climate model simulations, is insufficient to explain the rapid increase in daily minimum and maximum temperatures, the sharp decline in frost days, and the rise in degree-days above 0°C (a simple proxy for temperature-driven snowmelt). These observed changes are also inconsistent with the model-predicted responses to variability in solar irradiance and volcanic activity. The observations are consistent with climate simulations that include the combined effects of anthropogenic greenhouse gases and aerosols. It is found that, for each temperature variable considered, an anthropogenic signal is identifiable in observational fields. The results are robust to uncertainties in model-estimated fingerprints and natural variability noise, to the choice of statistical downscaling method, and to various processing options in the detection and attribution method.

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David W. Pierce
,
Tim P. Barnett
,
Hugo G. Hidalgo
,
Tapash Das
,
Céline Bonfils
,
Benjamin D. Santer
,
Govindasamy Bala
,
Michael D. Dettinger
,
Daniel R. Cayan
,
Art Mirin
,
Andrew W. Wood
, and
Toru Nozawa

Abstract

Observations show snowpack has declined across much of the western United States over the period 1950–99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D–A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean–atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D–A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols.

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Anthony G. Barnston
,
Huug M. van den Dool
,
Stephen E. Zebiak
,
Tim P. Barnett
,
Ming Ji
,
David R. Rodenhuis
,
Mark A. Cane
,
Ants Leetmaa
,
Nicholas E. Graham
,
Chester R. Ropelewski
,
Vernon E. Kousky
,
Edward A. O'Lenic
, and
Robert E. Livezey

The National Weather Service intends to begin routinely issuing long-lead forecasts of 3-month mean U. S. temperature and precipitation by the beginning of 1995. The ability to produce useful forecasts for certain seasons and regions at projection times of up to 1 yr is attributed to advances in data observing and processing, computer capability, and physical understanding—particularly, for tropical ocean-atmosphere phenomena. Because much of the skill of the forecasts comes from anomalies of tropical SST related to ENSO, we highlight here long-lead forecasts of the tropical Pacific SST itself, which have higher skill than the U.S forecasts that are made largely on their basis.

The performance of five ENSO prediction systems is examined: Two are dynamical [the Cane-Zebiak simple coupled model of Lamont-Doherty Earth Observatory and the nonsimple coupled model of the National Centers for Environmental Prediction (NCEP)]; one is a hybrid coupled model (the Scripps Institution for Oceanography-Max Planck Institute for Meteorology system with a full ocean general circulation model and a statistical atmosphere); and two are statistical (canonical correlation analysis and constructed analogs, used at the Climate Prediction Center of NCEP). With increasing physical understanding, dynamically based forecasts have the potential to become more skillful than purely statistical ones. Currently, however, the two approaches deliver roughly equally skillful forecasts, and the simplest model performs about as well as the more comprehensive models. At a lead time of 6 months (defined here as the time between the end of the latest observed period and the beginning of the predict and period), the SST forecasts have an overall correlation skill in the 0.60s for 1982–93, which easily outperforms persistence and is regarded as useful. Skill for extra-tropical surface climate is this high only in limited regions for certain seasons. Both types of forecasts are not much better than local higher-order autoregressive controls. However, continual progress is being made in understanding relations among global oceanic and atmospheric climate-scale anomaly fields.

It is important that more real-time forecasts be made before we rush to judgement. Performance in the real-time setting is the ultimate test of the utility of a long-lead forecast. The National Weather Service's plan to implement new operational long-lead seasonal forecast products demonstrates its effectiveness in identifying and transferring “cutting edge” technologies from theory to applications. This could not have been accomplished without close ties with, and the active cooperation of, the academic and research communities.

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