Search Results

You are looking at 1 - 4 of 4 items for :

  • Author or Editor: Anthony Arguez x
  • Journal of Applied Meteorology and Climatology x
  • Refine by Access: All Content x
Clear All Modify Search
Rocky Bilotta, Jesse E. Bell, Ethan Shepherd, and Anthony Arguez

Abstract

The air-freezing index (AFI) is a common metric for determining the freezing severity of the winter season and estimating frost depth for midlatitude regions, which is useful for determining the depth of shallow foundation construction. AFI values represent the seasonal magnitude and duration of below-freezing air temperature. Departures of the daily mean temperature above or below 0°C (32°F) are accumulated over each August–July cold season; the seasonal AFI value is defined as the difference between the highest and lowest extrema points. Return periods are computed using generalized extreme value distribution analysis. This research replaces the methodology used by the National Oceanic and Atmospheric Administration to calculate AFI return periods for the 1951–80 time period, applying the new methodology to the 1981–2010 climate normals period. Seasonal AFI values and return period values were calculated for 5600 stations across the coterminous United States (CONUS), and the results were validated using U.S. Climate Reference Network temperature data. Return period values are typically 14%–18% lower across CONUS during 1981–2010 versus a recomputation of 1951–80 return periods with the new methodology. For the 100-yr (2 yr) return periods, about 59% (83%) of stations show a decrease of more than 10% in the more recent period, whereas 21% (2%) show an increase of more than 10%, indicating a net reduction in winter severity that is consistent with observed climate change.

Full access
Imke Durre, Michael F. Squires, Russell S. Vose, Xungang Yin, Anthony Arguez, and Scott Applequist

Abstract

The 1981–2010 “U.S. Climate Normals” released by the National Oceanic and Atmospheric Administration’s (NOAA) National Climatic Data Center include a suite of monthly, seasonal, and annual statistics that are based on precipitation, snowfall, and snow-depth measurements. This paper describes the procedures used to calculate the average totals, frequencies of occurrence, and percentiles that constitute these normals. All parameters were calculated from a single, state-of-the-art dataset of daily observations, taking care to produce normals that were as representative as possible of the full 1981–2010 period, even when the underlying data records were incomplete. In the resulting product, average precipitation totals are available at approximately 9300 stations across the United States and parts of the Caribbean Sea and Pacific Ocean islands. Snowfall and snow-depth statistics are provided for approximately 5300 of those stations, as compared with several hundred stations in the 1971–2000 normals. The 1981–2010 statistics exhibit the familiar climatological patterns across the contiguous United States. When compared with the same calculations for 1971–2000, the later period is characterized by a smaller number of days with snow on the ground and less total annual snowfall across much of the contiguous United States; wetter conditions over much of the Great Plains, Midwest, and northern California; and drier conditions over much of the Southeast and Pacific Northwest. These differences are a reflection of the removal of the 1970s and the addition of the 2000s to the 30-yr-normals period as part of this latest revision of the normals.

Full access
Anthony Arguez, Anand Inamdar, Michael A. Palecki, Carl J. Schreck, and Alisa H. Young

Abstract

Climate normals are traditionally calculated every decade as the average values over a period of time, often 30 years. Such an approach assumes a stationary climate, with several alternatives recently introduced to account for monotonic climate change. However, these methods fail to account for interannual climate variability [e.g., El Niño–Southern Oscillation (ENSO)] that systematically alters the background state of the climate similar to climate change. These effects and their uncertainties are well established, but they are not reflected in any readily available climate normals datasets. A new high-resolution set of normals is derived for the contiguous United States that accounts for ENSO and uses the optimal climate normal (OCN)—a 10-yr (15 yr) running average for temperature (precipitation)—to account for climate change. Anomalies are calculated by subtracting the running means and then compositing into 5 ENSO phase and intensity categories: Strong La Niña, Weak La Niña, Neutral, Weak El Niño, and Strong El Niño. Seasonal composites are produced for each of the five phases. The ENSO normals are the sum of these composites with the OCN for a given month. The result is five sets of normals, one for each phase, which users may consult with respect to anticipated ENSO outcomes. While well-established ENSO patterns are found in most cases, a distinct east–west temperature anomaly pattern emerges for Weak El Niño events. This new product can assist stakeholders in planning for a broad array of possible ENSO impacts in a changing climate.

Full access
Daniel M. Gilford, Shawn R. Smith, Melissa L. Griffin, and Anthony Arguez

Abstract

The daily temperature range (DTR; daily maximum temperature minus daily minimum temperature) at 290 southeastern U.S. stations is examined with respect to the warm and cold phases of the El Niño–Southern Oscillation (ENSO) for the period of 1948–2009. A comparison of El Niño and La Niña DTR distributions during 3-month seasons is conducted using various metrics. Histograms show each station’s particular distribution. To compare directly the normalized distributions of El Niño and La Niña, a new metric (herein called conditional ratio) is produced and results are evaluated for significance at 95% confidence with a bootstrapping technique. Results show that during 3-month winter, spring, and autumn seasons DTRs above 29°F (16.1°C) are significantly more frequent during La Niña events and that DTRs below 15°F (8.3°C) are significantly more frequent during El Niño events. It is hypothesized that these results are associated spatially with cloud cover and storm tracks during each season and ENSO phase. Relationships between DTRs and ENSO-related relative humidity are examined. These results are pertinent to the cattle industry in the Southeast, allowing ranchers to plan for and mitigate threats posed by periods of low DTRs associated with the predicted phase of ENSO.

Full access