Search Results

You are looking at 1 - 8 of 8 items for

  • Author or Editor: Andrew W. Ellis x
  • Refine by Access: All Content x
Clear All Modify Search
Andrew W. Ellis
and
Daniel J. Leathers

Abstract

The presence of snow cover has been shown to modify atmospheric conditions through much of the earth’s troposphere due to its radiative effects. Snow cover has garnered much attention in recent decades as a result of concerns associated with potential changes in the global environment that may be intensified by the presence or absence of a snow cover. As a result, a greater emphasis has been placed on the representation of snow cover in weather and climate prediction models. This study investigates the effects of snow albedo and snow depth on the modification of surface air temperatures within cold air masses moving across the U.S. Great Plains in winter.

Through the adaptation of a one-dimensional snowpack model, the thermal characteristics of the core of a cold air mass were derived from the equation governing the heat balance between the surface and the lower atmosphere. The methodology was based on the premise that the core of a cold air mass may be considered homogeneous and not subject to advection of air from outside, thereby isolating the exchange of energy between the surface and the atmosphere as the control on lower-tropospheric temperatures. The adapted model included the synergism of the air mass–snow cover relationship through time, incorporating the natural feedback process.

Simulation of surface air temperatures within four cold air masses over snow cover of different albedo values and depths led to several conclusions. In testing the effects of snow albedo, results indicate 1) mean daytime air temperatures 3°–6°C higher and maximum daytime air temperatures 7°–12°C higher over snow with an albedo equal to 0.50 compared to 0.90, as a consequence of differences in sensible heat flux, and ultimately, absorbed solar radiation, and 2) little thermal inertia and therefore little difference in subsequent nighttime airmass temperatures over snow with an albedo of 0.50 compared to 0.90. In testing the effects of snow depth, results indicate 1) little difference in daytime air temperatures associated with a snow depth of 2.5 cm compared to 15.0 or 30.0 cm, 2) an increase in mean nighttime temperatures of 0.2°–0.7°C over a snow depth of 2.5 cm compared to either of the larger depths, and 3) a masking of the underlying bare soil surfaces by the snow depths of 15.0 and 30.0 cm and virtually no difference in airmass temperatures over the two snow depths.

The potential utility of the results of this study lies in their application as additional guidance for temperature forecasts within wintertime cold air masses over, and downstream from, snow cover across the U.S. Great Plains. Likewise, this study illustrates the importance of the various components of the heat balance between the lower atmosphere and snow cover as based on the physical characteristics of the snowpack, which could prove beneficial in considerations of snow cover in weather and climate models.

Full access
Andrew W. Ellis
and
Daniel J. Leathers

Abstract

Over the past two decades a greater emphasis has been placed on the accuracy of the representation of snow cover–atmosphere interactions in weather and climate prediction models. Much of the attention centered upon snow cover is a result of concerns associated with anthropogenic and natural causes of potential changes in the global environment that may be intensified by the snow cover climatology. As a predictive tool, the importance of the interactions between snow cover and the overlying atmosphere is recognized in areas ranging from daily and seasonal surface air temperature forecasts, to anomalies in large-scale atmospheric circulation patterns. Within this study the effects of snow cover on surface air temperatures within cold air masses moving across the U.S. Great Plains in winter were investigated.

Through the adaptation of a one-dimensional snowpack model, the thermal characteristics of the core of a cold air mass were derived from the equation governing the heat balance between the surface and the lower atmosphere. The methodology was based on the premise that the core of a cold air mass may be considered homogeneous and not subject to advection of air from outside, thereby isolating the exchange of energy between the surface and the atmosphere as the control on lower-atmospheric temperatures. The adapted model included the synergism of the air mass–snow cover relationship through time, incorporating the natural feedback process.

Simulation of surface air temperatures within four cold air masses produced results that include 1) mean daytime temperatures 6°–10°C warmer and maximum daytime temperatures 10°–15°C warmer over bare ground compared to a snow cover, 2) mean nighttime temperatures 1°–2°C warmer over bare ground compared to a snow cover, and 3) attribution of temperature differences primarily to differences in the exchange of sensible heat between the surface and the overlying air mass. Daytime differences in the energy fluxes produced by the different surface conditions were largely the result of surface temperature differences produced by variations in the albedo and the amount of solar radiation absorbed at the surface.

The authors believe that the results of this study can be used as additional guidance for more accurate forecasts of daily maximum and minimum surface air temperatures within wintertime cold air masses over, and possibly downstream from, snow cover across the North American continent. The study documents the importance of the various components of the heat balance between the lower atmosphere and surface in regard to cold airmass modification, and emphasizes the importance of an accurate representation of snow cover in forecast models.

Full access
Paul Miller
,
Andrew W. Ellis
, and
Stephen Keighton

Abstract

This study provides a preliminary, regional assessment of the viability of using spatiotemporal lightning patterns to classify storms into single- versus multi- and supercell storm modes. Total lightning flashes (intracloud and cloud-to-ground flashes) occurring during the afternoon and evening of the period May–August 2012 within an area of the central Appalachian Mountains region were grouped based on their spatial and temporal characteristics using single-linkage clustering. The resulting discrete thunderstorm clusters were characterized in terms of duration, motion, areal extent, and shape. These values were used to formulate four individual attribute scores representing the similarity to the expected values for a typical single-cell thunderstorm. The four scores were then combined into a storm index (SI) using relative weights determined through the analytic hierarchy process (AHP) performed on input from operational forecasters. Of the study days, 89 (72.4%) possessed appreciable lightning, of which 36 (40%) possessed a defined minimum amount of lightning activity required for further analysis. These 36 storm days were divided into two tiers according to the distribution of median daily SI values. The tier containing the 24 storm days (66.7%) with the largest median SI values possessed statistically significant smaller values of 0–6-km wind shear [13.8 knots (kt; 1 kt = 0.51 m s−1)] versus the 12 days in the lower tier of SI values (26.5 kt). This consistency between the total lightning-based classification scheme and increased vertical wind shear associated with lightning-defined multi- and supercells, also evident in synoptic atmospheric composites, lends credibility to the procedure.

Full access
Andrew W. Ellis
and
Jennifer J. Johnson

Abstract

Research over the past several decades has indicated that snowfall has increased dramatically over portions of the past century across those areas of the Great Lakes region of North America that are subject to lake-effect snowfall. Within this study, time series of annual midwinter snowfall within lake-effect areas show evidence of a clear increase in both snowfall and snowfall frequency through a 40-yr period beginning in the early 1930s and ending in the early 1970s. The goal of the work presented here is to determine to what extent the apparent increases in lake-effect snowfall actually modified the winter hydroclimate of the areas.

Simple hydroclimatic analysis of midwinter precipitation to the lee of Lakes Erie and Ontario for the period of significant snowfall increases suggests that the changes were a product of 1) a shift toward more precipitation events that were snowfall rather than rainfall, 2) an associated decrease in midwinter rainfall, 3) an increase in the intensity of individual snowfall events, and 4) an increase in the snowfall/snow water equivalence ratio. The balance was a small increase in total precipitation confined to areas in close proximity to the lakes across northeastern Ohio and western New York, while areas outside the regions generally experienced an overall decrease in midwinter precipitation. While the cause(s) of the snowfall trends remains elusive, the results of the work presented here suggest that no great long-term regional change occurred in the true wintertime seasonal hydroclimate of the lake-effect areas. Rather, much of the touted snowfall increase simply came at the expense of rainfall events to produce only small changes in total precipitation over the time period of significant snowfall increase.

Full access
Gregory B. Goodrich
and
Andrew W. Ellis

Abstract

The winter (December–February) of 2005/06 ranked as the driest in the instrumental record (since 1895) for nearly all regions of Arizona. The city of Phoenix, Arizona, recorded no precipitation during this time period, which was part of a record dry streak of 143 days without measurable precipitation. More important, the Salt and Verde watersheds, which supply the greater Phoenix area with approximately 50% of its water supply, received less than 3% of normal precipitation. Remarkably, this historically dry winter was preceded by the second wettest winter on record in 2004/05, a winter that filled reservoirs statewide and ameliorated a drought that has persisted since 1996 in some parts of the state. This study begins with a brief overview of the historical context of such reversals of extreme seasonal precipitation in Arizona followed by an analysis of the teleconnective impacts. The authors find that while an extreme reversal such as this has only happened once before in Arizona (1904/05 and 1905/06), there is a trend for increasing variability in winter precipitation from one year to the next in Arizona, especially since the 1960s. Large reversals of winter precipitation are followed by large reversals of the opposite sign in the summer monsoon more than 75% of the time. In general, large dry-to-wet reversals are associated with neutral ENSO–to–neutral ENSO conditions or a neutral ENSO–to–El Niño transition, whereas wet-to-dry reversals are associated with an El Niño–to–La Niña transition or, more commonly, with an El Niño–to–neutral ENSO transition. In addition, changes in the sign of the Atlantic multidecadal oscillation, eastern Pacific oscillation, and Pacific–North American (PNA) pattern are all significantly associated with precipitation reversals. During the seven winters when neutral ENSO and strongly positive PNA coexist, large wet-to-dry reversals occur in every case and nearly all rank among the largest such reversals. It is suggested that small reservoirs are more at risk for increasing climatic volatility than are large reservoirs.

Full access
Andrew W. Ellis
and
Daniel J. Leathers

Abstract

Due to their mesoscale nature, forecasting lake-effect snowfall events is very difficult but extremely important to the inhabitants of those regions subject to this type of severe winter weather. Such is the case along the southern and eastern shores of Lakes Erie and Ontario in the northeastern region of the United States. Here a synoptic climatological approach is used to identify the synoptic-scale atmospheric patterns conductive to lake-induced snowfall to the lee of Lakes Erie and Ontario in the states of New York and Pennsylvania from November to March. The approach used in this study allows for a thorough investigation of the characteristics of each lake-effect synoptic type, including the intrannual and interannual variations in frequency and composite atmospheric fields of sea level pressures, 850-mb temperatures and heights, and 500-mb heights. By combining the lake-effect synoptic types with daily snowfall data for 159 stations across New York and Pennsylvania, direct associations are made between each synoptic type and the mean snowfall and snowfall frequency across that region.

Five synoptic types are identified as producing significant lake-effect snowfall in western New York and northwestern Pennsylvania. The large-scale synoptic situation is similar for each lake-effect type; however, each can be clearly distinguished by its wind components, which are important factors in the spatial pattern and intensity of lake-effect snowfall. Variations in the sea level pressure patterns, 850-mb temperatures and heights, 500-mb heights, seasonality, and overlake fetch and strength of flow result in significant differences in the location, magnitude, and frequency of the snowfalls associated with these types. Three of the lake-effect types occur most often in midwinter, while two are most frequent near the beginning and/or end of the snowfall season. Additionally, the interannual frequencies of the midwinter types indicate an upward trend that coincides with evidence of a lake-effect snowfall increase during midseason over the past century.

The authors believe that the differences in the lake-effect synoptic types outlined here can be used as additional guidance for more accurate extended forecasts of lake-effect snowfall in northwestern Pennsylvania and western New York.

Full access
Daniel J. Leathers
,
Andrew W. Ellis
, and
David A. Robinson

Abstract

Daily snow cover and temperature data are collected for a network of 91 stations covering the northeast United States and the association between the two is explored. Observations are examined for the six-month winter season, November–April, for the period 1948/49–1987/88. Daily maximum and minimum temperatures are stratified by 15-day periods and further by the presence or absence of a snow cover. It is found that for snow covers of 2.5 cm or greater, depressions of daily maximum and minimum temperature average approximately 6° and 5°C, respectively. Relatively large variations in the temperature depressions are observed across space, whereas smaller variability is found across the snow cover season.

Temporally, maximum temperature depressions are greater during the early and later portions of the snow cover season and somewhat smaller during the midwinter months. The magnitude of minimum temperature depressions are larger during the midwinter months but decrease in size early and especially late in the snow cover season. The presence of a snow cover decreases the daily temperature range in November, March, and April and has little effect during the intervening months.

Spatially, the magnitude of both maximum and minimum temperature depressions increases away from coastal areas. In the case of maximum temperature depressions, there is also a consistent increase toward the southern portion of the region. For minimum temperature depressions, no large-scale geographic control, except for coastal proximity, dominates the spatial distribution of the depression magnitudes.

Potential geographic “forcing” mechanisms are evaluated. The results indicate that large sensible and, in some cases, latent heat fluxes from the lower atmosphere to the snowpack account for much of the observed temperature depressions.

Full access
Timothy W. Hawkins
,
Andrew W. Ellis
,
Jon A. Skindlov
, and
Dallas Reigle

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.

Full access