Search Results

You are looking at 1 - 8 of 8 items for

  • Author or Editor: Thomas A. Herring x
  • Refine by Access: All Content x
Clear All Modify Search
Thomas C. Peterson, Peter A. Stott, and Stephanie Herring

Attribution of extreme events shortly after their occurrence stretches the current state-of-theart of climate change assessment. To help foster the growth of this science, this article illustrates some approaches to answering questions about the role of human factors, and the relative role of different natural factors, for six specific extreme weather or climate events of 2011.

Not every event is linked to climate change. The rainfall associated with the devastating Thailand floods can be explained by climate variability. But long-term warming played a part in the others. While La Niña contributed to the failure of the rains in the Horn of Africa, an increased frequency of such droughts there was linked to warming in the Western Pacific– Indian Ocean warm pool. Europe's record warm temperatures would probably not have been as unusual if the high temperatures had been caused only by the atmospheric flow regime without any long-term warming.

Calculating how the odds of a particular extreme event have changed provides a means of quantifying the influence of climate change on the event. The heatwave that affected Texas has become distinctly more likely than 40 years ago. In the same vein, the likelihood of very warm November temperatures in the UK has increased substantially since the 1960s.

Comparing climate model simulations with and without human factors shows that the cold UK winter of 2010/2011 has become about half as likely as a result of human influence on climate, illustrating that some extreme events are becoming less likely due to climate change.

Full access
Stephanie C. Herring, Martin P. Hoerling, Thomas C. Peterson, and Peter A. Stott
Full access
Stephanie C. Herring, Martin P. Hoerling, James P. Kossin, Thomas C. Peterson, and Peter A. Stott
Full access
Stephanie C. Herring, Martin P. Hoerling, James P. Kossin, Thomas C. Peterson, and Peter A. Stott

Editors note: For easy download the posted pdf of the Explaining Extreme Events of 2014 is a very low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download.

Full access
Stephanie C. Herring, Martin P. Hoerling, James P. Kossin, Thomas C. Peterson, and Peter A. Stott
Full access
Thomas C. Peterson, Martin P. Hoerling, Peter A. Stott, and Stephanie C. Herring
Full access
Michael Bevis, Steven Businger, Steven Chiswell, Thomas A. Herring, Richard A. Anthes, Christian Rocken, and Randolph H. Ware

Abstract

Emerging networks of Global Positioning System (GPS) receivers can be used in the remote sensing of atmospheric water vapor. The time-varying zenith wet delay observed at each GPS receiver in a network can be transformed into an estimate of the precipitable water overlying that receiver. This transformation is achieved by multiplying the zenith wet delay by a factor whose magnitude is a function of certain constants related to the refractivity of moist air and of the weighted mean temperature of the atmosphere. The mean temperature varies in space and time and must be estimated a priori in order to transform an observed zenith wet delay into an estimate of precipitable water. We show that the relative error introduced during this transformation closely approximates the relative error in the predicted mean temperature. Numerical weather models can be used to predict the mean temperature with an rms relative error of less than 1%.

Full access
Jingping Duan, Michael Bevis, Peng Fang, Yehuda Bock, Steven Chiswell, Steven Businger, Christian Rocken, Frederick Solheim, Terasa van Hove, Randolph Ware, Simon McClusky, Thomas A. Herring, and Robert W. King

Abstract

A simple approach to estimating vertically integrated atmospheric water vapor, or precipitable water, from Global Positioning System (GPS) radio signals collected by a regional network of ground-based geodetic GPS receiver is illustrated and validated. Standard space geodetic methods are used to estimate the zenith delay caused by the neutral atmosphere, and surface pressure measurements are used to compute the hydrostatic (or “dry”) component of this delay. The zenith hydrostatic delay is subtracted from the zenith neutral delay to determine the zenith wet delay, which is then transformed into an estimate of precipitable water. By incorporating a few remote global tracking stations (and thus long baselines) into the geodetic analysis of a regional GPS network, it is possible to resolve the absolute (not merely the relative) value of the zenith neutral delay at each station in the augmented network. This approach eliminates any need for external comparisons with water vapor radiometer observations and delivers a pure GPS solution for precipitable water. Since the neutral delay is decomposed into its hydrostatic and wet components after the geodetic inversion, the geodetic analysis is not complicated by the fact that some GPS stations are equipped with barometers and some are not. This approach is taken to reduce observations collected in the field experiment GPS/STORM and recover precipitable water with an rms error of 1.0–1.5 mm.

Full access