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- Author or Editor: Jon A. Skindlov x
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Abstract
Mesoscale model gridpoint temperature data from simulations in the southwestern United States during the summer of 1990 are compared with both observations and statistical guidance from large-scale models over a 32-day period. Although the raw model temperature data at the lowest sigma level typically are much lower than observed, when the mean temperature bias is removed, the model values of high temperature compare favorably with both observations and operational statistical guidance products. A simple 7-day running mean bias calculation that could be used in an operational environment is tested and also found to produce good results. These comparisons suggest that the ability of mesoscale model gridpoint data to produce useful and accurate forecast products through the use of very simple bias corrections should be explored fully as mesoscale model data become routinely available.
Abstract
Mesoscale model gridpoint temperature data from simulations in the southwestern United States during the summer of 1990 are compared with both observations and statistical guidance from large-scale models over a 32-day period. Although the raw model temperature data at the lowest sigma level typically are much lower than observed, when the mean temperature bias is removed, the model values of high temperature compare favorably with both observations and operational statistical guidance products. A simple 7-day running mean bias calculation that could be used in an operational environment is tested and also found to produce good results. These comparisons suggest that the ability of mesoscale model gridpoint data to produce useful and accurate forecast products through the use of very simple bias corrections should be explored fully as mesoscale model data become routinely available.
Abstract
The selection of the proper clustering procedure to use in the development of an objective synoptic methodology may have far-reaching implications on the composition of the final “homogeneous” groupings. The goal of this study is to evaluate three common clustering techniques (Ward's, average linkage, and centroid) to determine which yields the most meaningful synoptic classification. The three clustering procedures were applied to a temporal synoptic index which classified days in Mobile, Alabama into meteorologically homogeneous units. The final meteorological groupings differed widely among the three pressures. Ward's tended to produce groups with relatively similar numbers of days. Thus, many extreme weather days were grouped with less extreme days, and the final meteorological units did not duplicate reality with great precision. The centroid procedure produced one very large group and many single-day groups, yielding unsatisfactory results. The average linkage procedure, which minimizes within-cluster variance, produced the most realistic synoptic groupings and properly combined extreme weather days into distinct meteorological units.
Abstract
The selection of the proper clustering procedure to use in the development of an objective synoptic methodology may have far-reaching implications on the composition of the final “homogeneous” groupings. The goal of this study is to evaluate three common clustering techniques (Ward's, average linkage, and centroid) to determine which yields the most meaningful synoptic classification. The three clustering procedures were applied to a temporal synoptic index which classified days in Mobile, Alabama into meteorologically homogeneous units. The final meteorological groupings differed widely among the three pressures. Ward's tended to produce groups with relatively similar numbers of days. Thus, many extreme weather days were grouped with less extreme days, and the final meteorological units did not duplicate reality with great precision. The centroid procedure produced one very large group and many single-day groups, yielding unsatisfactory results. The average linkage procedure, which minimizes within-cluster variance, produced the most realistic synoptic groupings and properly combined extreme weather days into distinct meteorological units.
Abstract
Over the past few decades, heat-island related temperature increases in Phoenix, Arizona have been similar to the temperature increases predicted in a number of greenhouse simulation experiments. In this investigation, we use the Phoenix climate record to assess how increasing summertime mean temperatures are related to changes in the extreme maximum and minimum temperatures. Generally, rising mean temperatures are associated with substantial changes in the occurrence of extreme minimum temperatures (e.g., fewer days of extreme low minimum temperatures and more days of extreme high minimum temperatures). However, while the rising mean temperatures strongly influence the occurrence of moderately high maximum temperatures, they are weakly associated with the occurrence of extreme maximum temperatures. The results suggest that considerable caution should be used in predicting the occurrence of extreme temperatures from projected increases in mean temperature levels.
Abstract
Over the past few decades, heat-island related temperature increases in Phoenix, Arizona have been similar to the temperature increases predicted in a number of greenhouse simulation experiments. In this investigation, we use the Phoenix climate record to assess how increasing summertime mean temperatures are related to changes in the extreme maximum and minimum temperatures. Generally, rising mean temperatures are associated with substantial changes in the occurrence of extreme minimum temperatures (e.g., fewer days of extreme low minimum temperatures and more days of extreme high minimum temperatures). However, while the rising mean temperatures strongly influence the occurrence of moderately high maximum temperatures, they are weakly associated with the occurrence of extreme maximum temperatures. The results suggest that considerable caution should be used in predicting the occurrence of extreme temperatures from projected increases in mean temperature levels.
Abstract
Areal extents of monthly and seasonal North American snow cover were correlated with precipitation totals, precipitation frequency, and severe weather associated with the North American monsoon. Significant relationships were found to exist between monsoon variables and snow-cover extent over western North America.
Synoptic composites of the summertime atmosphere revealed that during years of low snow-cover extent, 500-mb heights were higher across much of the United States and 850-mb specific humidity values were increased over the desert southwest compared with high snow-cover extent years. Seemingly, displacement of the 500-mb ridge across the United States displaces the Four Corners high, which in turn affects the strength of low-level moisture advection into the southwestern United States.
In beginning to assess the possibility of anticipating the strength of the North American monsoon using winter and spring snow-cover extent, data for anomalously large and small snow-cover years (50% of the data record) were input into stepwise multiple regressions. Using the limited data record, results showed that winter and spring snow-cover variables explained significant portions of the variance in precipitation totals (83%), precipitation frequency (95%), hail (81%), wind (82%), and total severe weather (98%) for the monsoon region. The results lead to optimism regarding the development of seasonal forecasting algorithms that are centered upon the use of winter and spring snow-cover extent to assess the potential intensity of the subsequent North American monsoon season. Accurate prediction of general monsoon intensity several months in advance would be invaluable to many different aspects of life in southwestern North America.
Abstract
Areal extents of monthly and seasonal North American snow cover were correlated with precipitation totals, precipitation frequency, and severe weather associated with the North American monsoon. Significant relationships were found to exist between monsoon variables and snow-cover extent over western North America.
Synoptic composites of the summertime atmosphere revealed that during years of low snow-cover extent, 500-mb heights were higher across much of the United States and 850-mb specific humidity values were increased over the desert southwest compared with high snow-cover extent years. Seemingly, displacement of the 500-mb ridge across the United States displaces the Four Corners high, which in turn affects the strength of low-level moisture advection into the southwestern United States.
In beginning to assess the possibility of anticipating the strength of the North American monsoon using winter and spring snow-cover extent, data for anomalously large and small snow-cover years (50% of the data record) were input into stepwise multiple regressions. Using the limited data record, results showed that winter and spring snow-cover variables explained significant portions of the variance in precipitation totals (83%), precipitation frequency (95%), hail (81%), wind (82%), and total severe weather (98%) for the monsoon region. The results lead to optimism regarding the development of seasonal forecasting algorithms that are centered upon the use of winter and spring snow-cover extent to assess the potential intensity of the subsequent North American monsoon season. Accurate prediction of general monsoon intensity several months in advance would be invaluable to many different aspects of life in southwestern North America.
