FWCAO Table of ContentsAll ConferencesAcronymsMain MenuSEARCH...entire CD...this documentHelpAuthor IndexP2.1 CAN U.S. WEST COAST CLIMATE BE FORCAST? Steve LaDochy*, Jeffrey N. Brown and Mattias Selke California State University, Los Angeles William C. Patzert, JPL NASA 1. Introduction The tropical Pacific Ocean influences local, regional and global climates. Its variability can be used to anticipate changes in the atmosphere on an inter- and intra-annual time scale (Zhang et al. 1997; Livezey et al. 1997). The ENSO signals show prominence in seasonal and interannual temperature and precipitation records throughout North America (Ropelewski and Halpert 1986). Stronger relationships show interdecadal variability. Castro et al. (2001) show how Pacific SSTs influence the North American Monsoon. They show that ENSO effects are strong when in phase with the PDO, but weak when out of phase. That is, that ENSO related teleconnection patterns with climate anomalies are more consistent when El Nino occurs during the positive phase of PDO and La Nina occurs during the PDO negative phase (Gershunov and Barnett 1998). In their study of the strength of ENSO teleconnections with western U.S. precipitation, McCabe and Dettinger (1999) also found that positive PDO periods tended to weaken the teleconnection relationships. Updated standardized values for the PDO index are derived as the leading PC of monthly SST anomalies in the North Pacific Ocean, poleward of 20N. The monthly mean global average SST anomalies are removed to separate this pattern of variability from any “global warming” signal that may be present in the data (Zhang et al. 1997; Mantua et al. 1997). Pacific decadal SST variability has also been linked to U.S. droughts, floods and streamflow amounts (Nigram et al. 1999; Cole and Overpeck 2002; Pizarro and Lall 2002; Gray et al. 2003). Pacific teleconnection patterns, as shown by the PNA (Pacific North American Index) have been shown to even disrupt the Atlantic Multidecadal Oscillation signal in winter Mississippi Valley stream flow (Rodgers and Coleman 2003). * Corresponding author address: Steve LaDochy, Dept. of Geography, Calif. State Univ., Los Angeles, CA 90032; e-mail: [email protected]. West coast climate is influenced directly by its watery neighbor. The strongest atmospheric influence of the PDO shows up in the strength of the Aleutian low (Mantua et al., 1997). Sea Level Pressure (SLP) changes in the Pacific are linked to changes in surface winds, and hence SSTs, upper ocean temperature and heat content, mixed layer depth and thermocline depth (Schwing et al. 2002; Miller et al. 1994). These then are related to changes in climate along the west coast of the Americas (Montecinos and Purca 2003). The strong correlations between short term through decadal Pacific oceanic and atmospheric conditions with North American climate makes it possible to attempt long range forecasting for the U.S. west coast. This paper looks at the feasibility in long-range prediction of temperatures and precipitation along the U.S. west coast by utilizing the strong relationships between Pacific oceanic and atmospheric indices with coastal climates. 2. Data and Methodology In order to forecast long-range west coast climatic conditions, the authors look at Pacific Ocean SSTs and atmospheric circulation patterns, both in the tropics and extratropical latitudes and see how they have explained temperature and precipitation variabilities in the past. Pacific oceanic and atmospheric data, along with west coast climatic data, were provided by the online Climate Diagnostics Center (CDC) Correlations web pages (see http://www.cdc.noaa.gov/USclimate/Correlation/). We chose monthly values of relevant Pacific oceanic and atmospheric indices for 1948-2002 for most analyses, along with 1895-2002 monthly records for some climatic data and ENSO events. Temperature and precipitation data is included for West coast climate divisions of California, Oregon and Washington (Fig. 1). Each of the Pacific indices was correlated with temperature and precipitation to show strength of relationships, seasonally and annually. Since the rainy season is mainly during the coolerseasons, and the Water Year (July 1-June 30) differs from calendar year, correlation with annual precipitation was done using Water Year totals. Indices showing the strongest influences were evaluated at progressing leads of 1 to 12 months, to show the best temporal relationships with regional temperatures and precipitation. To estimate the magnitudes of anomalies for temperatures and precipitation, divisional temperature and precipitation anomalies were calculated from the 1895-2000 record for El Nino and La Nina years during positive and negative phases of the PDO. Based on the 1948-2003 NCEP reanalyses maps of atmospheric circulation, we also derived composites for SLP, 500 mb geopotential heights, and 250 mb windspeeds, for high and low values of PDO, SOI, NP and WPI. 3. Results Coastal temperatures. PDO dominates the influences on California temperatures, annually and seasonally. Table 1 (see appendix) shows that PDO accounts for about 50% of interannual temperature variability for the 3 coastal climate divisions. Figure 2 indicates that the PDO-temperature relationship is consistently strong throughout the western U.S. The relationship remains highly significant with leads of up to 2 seasons. Coastal Oregon and Washington show similar, though slightly lower correlations for the same leads. The PDO also explains seasonal temperature variability, although not as well as with interannual values. California summer temperatures are explained best among the seasons (Fig. 3), while winter temperatures are the least explained by PDO. The relationships remain highly significant for up to 2 seasons lead times (Fig. 4). For coastal Oregon and Washington, PDO values up to 1 season explain spring temperatures the best, Fig. 1 Study area showing the west coast climatic divisions. Fig. 2 Correlations by climatic divisions between Nov. – Oct. PDO values and annual (Jan-Dec.) temperatures.Fig. 3 Correlations by climatic divisions between Feb.-Apr. PDO values and summer (June-Aug.) temperatures.followed by winter, fall and summer temperatures. All relationships are highly significant at .001 or better. Besides PDO, the NP Index also explains coastal temperature variability well. This is not