Anthony Arguez

Possible artifacts of data biases in the recent global surface warming hiatus

Walking back talk of the end of warming Previous analyses of global temperature trends during the first decade of the 21st century seemed to indicate that warming had stalled. This allowed critics of the idea of global warming to claim that concern about climate change was misplaced. Karl et al. now show that temperatures did not plateau as thought and that the supposed warming “hiatus” is just an artifact of earlier analyses. Warming has continued at a pace similar to that of the last half of the 20th century, and the slowdown was just an illusion. Science, this issue p. 1469 Updated global surface temperature data do not support the notion of a global warming “hiatus.” Much study has been devoted to the possible causes of an apparent decrease in the upward trend of global surface temperatures since 1998, a phenomenon that has been dubbed the global warming “hiatus.” Here, we present an updated global surface temperature analysis that reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century. These results do not support the notion of a “slowdown” in the increase of global surface temperature.

The Definition of the Standard WMO Climate Normal: The Key to Deriving Alternative Climate Normals

©2011 American Meteorological Society T he World Meteorological Organization (WMO) and its predecessor, the International Meteorological Organization (IMO), have been coordinating the publication of global climate normals at the monthly scale for about 75 years. Member nations of the IMO/WMO were first mandated to compute climate normals for their respective countries for the 1901–30 period, and are required to update these climate normals every 30 years, resulting in the 1931–60 normals and the 1961–90 normals. Since 1956, the WMO has recommended that each member country recompute their 30-year climate normals every 10 years. Although some member countries do not update their climate normals every decade, for ease of comprehension we hereafter refer to the recommended decadally updated 30-year average as the standard WMO climate normal. Given substantial evidence (e.g., Solomon et al. 2007; Milly et al. 2008) indicating that the stationarity of climate statistics can no longer be (and never should have been) taken for granted, the justification for using a 30-yr normal for describing current and future climate conditions has increasingly been called into question (e.g., the 2007 Journal of Applied Meteorology and Climatology article by Livezey et al., hereafter referred to as L07). The key problem is that climate normals are calculated retrospectively, but are often utilized prospectively. Specifically, climate normals are calculated using data from a recent 30-yr The Definition of the Standard WMO Climate Normal The Key to Deriving Alternative Climate normals

NOAA's 1981–2010 U.S. Climate Normals: An Overview

The National Oceanic and Atmospheric Administration (NOAA) released the 1981–2010 U.S. Climate Normals in July 2011, representing the latest decadal installment of this long-standing product line. Climatic averages (and other statistics) of temperature, precipitation, snowfall, and numerous derived quantities were calculated for ~9,800 stations operated by the U.S. National Weather Service (NWS). They include estimated normals, or “quasi normals,” for approximately 2,000 active short-record stations such as those in the U.S. Climate Reference Network. The 1981–2010 installment features several new products and methodological enhancements: 1) state-of-the-art temperature homogenization at the monthly scale, 2) extensive utilization of quality-controlled daily climate data, 3) new statistical approaches for calculating daily temperature normals and heating and cooling degree days, and 4) a comprehensive suite of precipitation, snowfall, and snow depth statistics. This paper provides a general overview of th...

NOAA’s 1981–2010 U.S. Climate Normals: Monthly Precipitation, Snowfall, and Snow Depth

AbstractThe 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. T...

Calculation and Evaluation of an Air-Freezing Index for the 1981–2010 Climate Normals Period in the Coterminous United States

AbstractThe 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 validat...

1981–2010 U.S. Hourly Normals

The 1981–2010 U.S. Climate Normals released by the National Oceanic and Atmospheric Administrations (NOAA) National Climatic Data Center (NCDC) include a suite of descriptive statistics based on hourly observations. For each hour and day of the year, statistics of temperature, dew point, mean sea level pressure, wind, clouds, heat index, wind chill, and heating and cooling degree hours are provided as 30-year averages, frequencies of occurrence, and percentiles. These hourly normals are available for 262 locations, primarily major airports, from across the United States and its Pacific territories. We encourage use of these products specifically for examination of the diurnal cycle of a particular variable, and how that change may shift over the annual cycle.

A Harmonic Approach for Calculating Daily Temperature Normals Constrained by Homogenized Monthly Temperature Normals

AbstractNOAA released the new 1981–2010 climate normals in July 2011. These included monthly and daily normals of minimum and maximum temperature. Monthly normals were computed from monthly temperature values that were corrected for biases (i.e., homogenized) due to changes in observing practices over the course of the normals period (station moves, changes in observation time, and changes in instrumentation). Daily temperature observations, however, are not homogenized, which could lead to inconsistencies between the daily and monthly normals. This study offers a constrained harmonic technique that forces the daily temperature normals to be consistent with the monthly temperature normals. This approach replaces the cubic spline interpolation of monthly temperature normals that was used to compute earlier versions of NOAAs daily temperature normals. It effectively passes the homogenization applied at the monthly scale down to the daily scale, resulting in a smooth annual cycle devoid of day-to-day sampli...

On the Estimation of Daily Climatological Temperature Variance

AbstractThe climatological daily variance of temperature is sometimes estimated from observed temperatures within a centered window of dates. This method overestimates the true variance of daily temperature when the rate of seasonal temperature change is large, because the seasonal change within the date window introduces additional variance. The contribution of the seasonal change may be removed by performing the variance calculation using daily temperature anomalies, leading to a bias-free estimate of variance.The difference between the variance estimation methods is illustrated using both idealized simulations of temperature variability and observed historical temperature data. The simulation results confirm that removing the climatological temperature cycle eliminates bias in the variance estimates. For several U.S. midlatitude locations, the difference in estimated standard deviation of daily mean temperature is on the order of a few percent near the seasonal peaks in climatological temperature chang...

Southeastern U.S. Daily Temperature Ranges Associated with the El Niño–Southern Oscillation

AbstractThe 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 Nino–Southern Oscillation (ENSO) for the period of 1948–2009. A comparison of El Nino and La Nina 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 Nino and La Nina, 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 Nina events and that DTRs below 15°F (8.3°C) are significantly more frequent during El Nino events. It is hypothesized that these results are associated spatially with cloud cover and storm tracks during each season and ENSO phase....