Browsing by Author "Gershunov, A"

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    A method for prediction of California air surface temperature
    (EOS, Transactions, American Geophysical Union, 2004) Alfaro, E; Gershunov, A; Cayan, D; Steinemann, A; Pierce, D; Barnett, T
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    Prediction of Summer Maximum and Minimum Temperature over the Central and Western United States: The Roles of Soil Moisture and Sea Surface Temperature
    (Journal of Climate, 2006) Alfaro, E; Gershunov, A; Cayan, D
    A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.
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    Relationships between the Irrigation-Pumping Electrical Loads and the Local Climate in Climate Division 9, Idaho
    (Journal of Applied Meteorology, 2005) Alfaro, E; Pierce, D; Steinemann, A; Gershunov, A
    The electrical load from irrigation pumps is an important part of the overall electricity demand in many agricultural areas of the U.S. west. The date the pumps turn on and the total electrical load they present over the summer varies from year to year, partly because of climate fluctuations. Predicting this variability would be useful to electricity producers that supply the region. This work presents a contingency analysis and linear regression scheme for forecasting summertime irrigation pump loads in southeastern Idaho. The basis of the predictability is the persistence of spring soil moisture conditions into summer, and the effect it has on summer temperatures. There is a strong contemporaneous relationship between soil moisture and temperature in the summer and total summer pump electrical loads so that a reasonable prediction of summer pump electrical loads based on spring soil moisture conditions can be obtained in the region. If one assumes that decision makers will take appropriate actions based on the forecast output, the net economic benefit of forecast information is approximately $2.5 million per year, making this prediction problem an important seasonal summer forecasting issue with significant economic implications.