Northeast Colorado Extreme Rains Interpreted in a Climate Change Context

The probability for an extreme five-day September rainfall event over northeast Colorado, as was observed in early September 2013, has likely decreased due to climate change

Anatomy of an Extreme Event

© Copyright 2013 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act September 2010 Page 2 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (https://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] record-setting 2011 Texas drought/heat wave is examined to identify physical processes, underlying causes, and predictability. October 2010–September 2011 was Texas’s driest 12-month period on record. While the summer 2011 heat wave magnitude (2.9°C above the 1981–2010 mean) was larger than the previous record, events of similar or larger magnitude appear in preindustrial control runs of climate models. The principal factor contributing to the heat wave magnitude was a severe rainfall deficit during antecedent and concurrent seasons related to anomalous sea surface temperatures (SSTs) that included a La Niña event. Virtually all the precipitation deficits appear to be due to natural variability. About 0.6°C warming relative to the 1981–2010 mean is estimated to be attributable to human-induced climate change, with warming observed mainly in the past decade. Quantitative attribution of the overall human-induced contribution since preindustrial times is complicated by the lack of a detected century-scale temperature trend over Texas. Multiple factors altered the probability of climate extremes over Texas in 2011. Observed SST conditions increased the frequency of severe rainfall deficit events from 9% to 34% relative to 1981–2010, while anthropogenic forcing did not appreciably alter their frequency. Human-induced climate change increased the probability of a new temperature record from 3% during the 1981–2010 reference period to 6% in 2011, while the 2011 SSTs increased the probability from 4% to 23%. Forecasts initialized in May 2011 demonstrate predictive skill in anticipating much of the SST-enhanced risk for an extreme summer drought/heat wave over Texas

Preconditions for extreme wet winters over the contiguous United States

We identify physical factors leading to extreme wet winters over the contiguous U.S. and examine whether preconditions operated during winter 2019 (December 2018 to February 2019) when record precipitation occurred that led to billion-dollar flood disasters along the Missouri and Mississippi Rivers. Models and observations are used to determine the effect of slow-varying forcing that may lead to practical forecast skill for extreme wet winters. Atmospheric models indicate that sea surface temperatures during strong eastern Pacific El Niño events like 1983 and 1998 can drive extreme wet winters over the contiguous U.S. These strong El Niños shift the distribution of contiguous U.S. precipitation to wetter conditions with a mean wetting of 1.5–2.0 standard deviations of the interannual variability. The shift to wetter conditions leads to a fivefold increase in the probability of wet winters of the magnitude observed in 2019. On longer timescales, observations indicate contiguous U.S. winter precipitation has increased over the last century. Analysis of historical coupled model simulations indicate anthropogenically-forced shifts to wetter conditions over the last century of 0.2–0.4 standard deviations of the interannual variability. While increasing the risk of extreme wet winters like 2019, this effect is a limited source of predictability during any particular winter. Concerning 2019 specifically, preconditioning factors of the risk for extreme contiguous U.S. winter wetness were weak or absent and offered little practical early warning. The ongoing central Pacific El Niño that winter did not significantly alter the risk of the wetness, and thus the extreme 2019 conditions are judged not to have been a seasonal forecast of opportunity

Drivers of 2016 record Arctic warmth assessed using climate simulations subjected to Factual and Counterfactual forcing

A suite of historical atmospheric model simulations is described that uses a hierarchy of global boundary forcings designed to inform research on the detection and attribution of weather and climate-related extremes. In addition to experiments forced by actual variations in sea surface temperature, sea ice concentration, and atmospheric chemical composition (so-called Factual experiments); additional (Counterfactual) experiments are conducted in which the boundary forcings are adjusted by removing estimates of long-term climate change. A third suite of experiments are identical to the Factual runs except that sea ice concentrations are set to climatological conditions (Clim-Polar experiments). These were used to investigate the cause for extremely warm Arctic surface temperature during 2016.Much of the magnitude of surface temperature anomalies averaged poleward of 65°N in 2016 (3.2 ± 0.6 °C above a 1980–89 reference) is shown to have been forced by observed global boundary conditions. The Factual experiments reveal that at least three quarters of the magnitude of 2016 annual mean Arctic warmth was forced, with considerable sensitivity to assumptions of sea ice thickness change. Results also indicate that 30–40% of the overall forced Arctic warming signal in 2016 originated from drivers outside of the Arctic. Despite such remote effects, the experiments reveal that the extreme magnitude of the 2016 Arctic warmth could not have occurred without consideration of the Arctic sea ice loss. We find a near-zero probability for Arctic surface temperature to be as warm as occurred in 2016 under late-19th century boundary conditions, and also under 2016 boundary conditions that do not include the depleted Arctic sea ice. Results from the atmospheric model experiments are reconciled with coupled climate model simulations which lead to a conclusion that about 60% of the 2016 Arctic warmth was likely attributable to human-induced climate change. Keywords: Arctic, Climate, Extreme, Model, Attributio

Aegean Tree-Ring Signature Years Explained

As a long master tree -ring chronology for the region around the Aegean approaches completion, timbers from monuments and archaeological sites as far as 2,000 km apart, and as far back as 7000 BC, are being dated. The patterns used in this dating are characterized by signature years, in which trees at the majority of the sites have smaller or broader rings than in the previous year. We show that the signature years are consistently associated with specific, persistent, circulation anomalies that control the access of precipitation- bearing systems to the region in springtime. This explains the feasibility of dating wooden objects from widely dispersed sites, and opens the possibility of reconstructing aspects of the climate in which the wood grew.This item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. It was digitized from a physical copy provided by the Laboratory of Tree-Ring Research at The University of Arizona. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at [email protected]

Appendix B. Creation of an independent, non-autocorrelated, evaluation data set.

Creation of an independent, non-autocorrelated, evaluation data set

Appendix A. Fossil records documenting late Pleistocene Joshua tree distribution and Holocene migration rates.

Fossil records documenting late Pleistocene Joshua tree distribution and Holocene migration rates

Online rainfall atlas of Hawai\u27i

The Rainfall Atlas of Hawai\u27i is a set of digital maps of the spatial patterns of 1978-2007 mean monthly and annual rainfall for the major Hawaiian Islands. For every map of mean rainfall, a corresponding map of uncertainty is also provided. Access to the rainfall maps, data, and related information is available via the Rainfall Atlas of Hawai\u27i website. The monthly rainfall database compiled for the new Rainfall Atlas of Hawai\u27i includes 1,067 stations, with 517,017 station-months of data over the period 1874-2007. For the purposes of the Rainfall Atlas, with a base period of 1978�2007, and ongoing analysis of temporal rainfall trends, gap filling was done for as many stations as possible for the period 1920�2007. Hawai\u27i\u27s rainfall pattern is spectacularly diverse Annual means range from 204 mm near the summit of Mauna Kea to 10,271 mm near Big Bog on the windward slope of Haleakala, Maui. This pattern is explained by the main controls on Hawai\u27i\u27s rainfall. The maps comprising the new Rainfall Atlas of Hawai\u27i give an up-to-date picture of normal rainfall amounts and patterns