scholarly journals North American Winter Dipole: Observed and Simulated Changes in Circulations

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 793 ◽  
Author(s):  
Yu-Tang Chien ◽  
S.-Y. Simon Wang ◽  
Yoshimitsu Chikamoto ◽  
Steve L. Voelker ◽  
Jonathan D. D. Meyer ◽  
...  
Keyword(s):  
North America ◽  
North American ◽  
Large Scale ◽  
Climate Model ◽  
Model Simulations ◽  
The North ◽  
Weather Events ◽  
The Pacific ◽  
Climate Model Simulations ◽  
Northwestern North America

In recent years, a pair of large-scale circulation patterns consisting of an anomalous ridge over northwestern North America and trough over northeastern North America was found to accompany extreme winter weather events such as the 2013–2015 California drought and eastern U.S. cold outbreaks. Referred to as the North American winter dipole (NAWD), previous studies have found both a marked natural variability and a warming-induced amplification trend in the NAWD. In this study, we utilized multiple global reanalysis datasets and existing climate model simulations to examine the variability of the winter planetary wave patterns over North America and to better understand how it is likely to change in the future. We compared between pre- and post-1980 periods to identify changes to the circulation variations based on empirical analysis. It was found that the leading pattern of the winter planetary waves has changed, from the Pacific–North America (PNA) mode to a spatially shifted mode such as NAWD. Further, the potential influence of global warming on NAWD was examined using multiple climate model simulations.

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

scholarly journals Constraining the temperature history of the past millennium using early instrumental observations

2012 ◽  
Vol 8 (3) ◽  
pp. 1653-1685 ◽  
Author(s):  
P. Brohan ◽  
R. Allan ◽  
E. Freeman ◽  
D. Wheeler ◽  
C. Wilkinson ◽  
...  
Keyword(s):  
Temperature Change ◽  
Large Scale ◽  
Climate Model ◽  
Ice Cores ◽  
East India Company ◽  
Temperature History ◽  
British Library ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Proxy Reconstructions

Abstract. The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations. As the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. One organisation which systematically made observations and collected the results was the English East-India Company (EEIC), and their archives have been preserved in the British Library. Inspection of those archives revealed 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure, and subjective estimates of wind speed and direction, from voyages across the Atlantic and Indian Oceans between 1789 and 1834. Those records have been extracted and digitised, providing 273 000 new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5 °C). This provides a powerful out-of-sample validation for the proxy reconstructions – supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this – such simulations are unlikely to be accurate in this respect.

The Impact of Sea Surface Temperature Biases on North American Precipitation in a High-Resolution Climate Model

2020 ◽  
Vol 33 (6) ◽  
pp. 2427-2447 ◽  
Author(s):  
Nathaniel C. Johnson ◽  
Lakshmi Krishnamurthy ◽  
Andrew T. Wittenberg ◽  
Baoqiang Xiang ◽  
Gabriel A. Vecchi ◽  
...  
Keyword(s):  
North America ◽  
Surface Temperature ◽  
North Atlantic ◽  
North American ◽  
North Pacific ◽  
Climate Model ◽  
Sea Surface ◽  
Tropical Atlantic ◽  
Western North America ◽  
The North

AbstractPositive precipitation biases over western North America have remained a pervasive problem in the current generation of coupled global climate models. These biases are substantially reduced, however, in a version of the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution (FLOR) coupled climate model with systematic sea surface temperature (SST) biases artificially corrected through flux adjustment. This study examines how the SST biases in the Atlantic and Pacific Oceans contribute to the North American precipitation biases. Experiments with the FLOR model in which SST biases are removed in the Atlantic and Pacific are carried out to determine the contribution of SST errors in each basin to precipitation statistics over North America. Tropical and North Pacific SST biases have a strong impact on northern North American precipitation, while tropical Atlantic SST biases have a dominant impact on precipitation biases in southern North America, including the western United States. Most notably, negative SST biases in the tropical Atlantic in boreal winter induce an anomalously strong Aleutian low and a southward bias in the North Pacific storm track. In boreal summer, the negative SST biases induce a strengthened North Atlantic subtropical high and Great Plains low-level jet. Each of these impacts contributes to positive annual mean precipitation biases over western North America. Both North Pacific and North Atlantic SST biases induce SST biases in remote basins through dynamical pathways, so a complete attribution of the effects of SST biases on precipitation must account for both the local and remote impacts.

scholarly journals Intraseasonal and Interannual Variability in North American Storm Tracks and Its Relationship to Equatorial Pacific Variability

2013 ◽  
Vol 141 (10) ◽  
pp. 3610-3625 ◽  
Author(s):  
Kevin M. Grise ◽  
Seok-Woo Son ◽  
John R. Gyakum
Keyword(s):  
North America ◽  
Interannual Variability ◽  
North American ◽  
Southern Oscillation ◽  
Extratropical Cyclones ◽  
The North ◽  
The Pacific ◽  
Cyclone Tracks ◽  
Lagrangian Tracking ◽  
The North Atlantic Oscillation

Abstract Extratropical cyclones play a principal role in wintertime precipitation and severe weather over North America. On average, the greatest number of cyclones track 1) from the lee of the Rocky Mountains eastward across the Great Lakes and 2) over the Gulf Stream along the eastern coastline of North America. However, the cyclone tracks are highly variable within individual winters and between winter seasons. In this study, the authors apply a Lagrangian tracking algorithm to examine variability in extratropical cyclone tracks over North America during winter. A series of methodological criteria is used to isolate cyclone development and decay regions and to account for the elevated topography over western North America. The results confirm the signatures of four climate phenomena in the intraseasonal and interannual variability in North American cyclone tracks: the North Atlantic Oscillation (NAO), the El Niño–Southern Oscillation (ENSO), the Pacific–North American pattern (PNA), and the Madden–Julian oscillation (MJO). Similar signatures are found using Eulerian bandpass-filtered eddy variances. Variability in the number of extratropical cyclones at most locations in North America is linked to fluctuations in Rossby wave trains extending from the central tropical Pacific Ocean. Only over the far northeastern United States and northeastern Canada is cyclone variability strongly linked to the NAO. The results suggest that Pacific sector variability (ENSO, PNA, and MJO) is a key contributor to intraseasonal and interannual variability in the frequency of extratropical cyclones at most locations across North America.

scholarly journals Toward Identifying Subseasonal Forecasts of Opportunity Using North American Weather Regimes

2020 ◽  
Vol 148 (5) ◽  
pp. 1861-1875
Author(s):  
Andrew W. Robertson ◽  
Nicolas Vigaud ◽  
Jing Yuan ◽  
Michael K. Tippett
Keyword(s):  
North American ◽  
El Niño ◽  
Geopotential Height ◽  
Large Scale ◽  
El Nino ◽  
Lead Times ◽  
Seasonal Forecasts ◽  
The North ◽  
The Pacific ◽  
Graphical Tool

Abstract Large-scale atmospheric circulation regime structures are used to diagnose subseasonal forecasts of wintertime geopotential height fields over the North American sector, from the NCEP CFSv2 model. Four large-scale daily circulation regimes derived from reanalysis 500-hPa geopotential height data using K-means clustering are used as a low-dimensional basis for diagnosing the model’s forecasts up to 45 days ahead. On average, hindcast skill in regime space is found to be limited to 10–15 days ahead, in terms of anomaly correlation of 5-day averages of regime counts, over the 1999–2010 period. However, skill up to 30 days ahead is identified in individual winters, and intraseasonal episodes of high skill are identified using a forecast-evolution graphical tool. A striking vacillation between the West Coast and Pacific ridge patterns during December–January 2008/09 is shown to be predicted 20–25 days in advance, illustrating the possibility to identify “forecasts of opportunity” when subseasonal forecast skill is much higher than the average. The forecast-evolution tool also provides insight into the poor seasonal forecasts of California precipitation by operational centers during the 2015/16 El Niño winter. The Pacific trough regime is shown to be greatly overpredicted beyond 1–2 weeks in advance during the 2015/16 winter, with weather-scale features dominating the forecast evolution at shorter lead times. A similar though less extreme situation took place during the weaker El Niño of 2009/10, with the Pacific trough overforecast at S2S lead times.

Do Statistical Pattern Corrections Improve Seasonal Climate Predictions in the North American Multimodel Ensemble Models?

2017 ◽  
Vol 30 (20) ◽  
pp. 8335-8355 ◽  
Author(s):  
Anthony G. Barnston ◽  
Michael K. Tippett
Keyword(s):  
North American ◽  
Large Scale ◽  
Climate Model ◽  
Principal Component ◽  
Eastern Africa ◽  
Multimodel Ensemble ◽  
Anomaly Correlation ◽  
The North ◽  
The Individual ◽  
North American Multimodel Ensemble

Abstract Canonical correlation analysis (CCA)-based statistical corrections are applied to seasonal mean precipitation and temperature hindcasts of the individual models from the North American Multimodel Ensemble project to correct biases in the positions and amplitudes of the predicted large-scale anomaly patterns. Corrections are applied in 15 individual regions and then merged into globally corrected forecasts. The CCA correction dramatically improves the RMS error skill score, demonstrating that model predictions contain correctable systematic biases in mean and amplitude. However, the corrections do not materially improve the anomaly correlation skills of the individual models for most regions, seasons, and lead times, with the exception of October–December precipitation in Indonesia and eastern Africa. Models with lower uncorrected correlation skill tend to benefit more from the correction, suggesting that their lower skills may be due to correctable systematic errors. Unexpectedly, corrections for the globe as a single region tend to improve the anomaly correlation at least as much as the merged corrections to the individual regions for temperature, and more so for precipitation, perhaps due to better noise filtering. The lack of overall improvement in correlation may imply relatively mild errors in large-scale anomaly patterns. Alternatively, there may be such errors, but the period of record is too short to identify them effectively but long enough to find local biases in mean and amplitude. Therefore, statistical correction methods treating individual locations (e.g., multiple regression or principal component regression) may be recommended for today’s coupled climate model forecasts. The findings highlight that the performance of statistical postprocessing can be grossly overestimated without thorough cross validation or evaluation on independent data.

scholarly journals Trends in Downward Solar Radiation at the Surface over North America from Climate Model Projections and Implications for Solar Energy

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Gerardo Andres Saenz ◽  
Huei-Ping Huang
Keyword(s):  
United States ◽  
North America ◽  
Solar Radiation ◽  
Solar Energy ◽  
Climate Model ◽  
Global Climate Model ◽  
The United States ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
The Impact

The projected changes in the downward solar radiation at the surface over North America for late 21st century are deduced from global climate model simulations with greenhouse-gas (GHG) forcing. A robust trend is found in winter over the United States, which exhibits a simple pattern of a decrease of sunlight over Northern USA. and an increase of sunlight over Southern USA. This structure was identified in both the seasonal mean and the mean climatology at different times of the day. It is broadly consistent with the known poleward shift of storm tracks in winter in climate model simulations with GHG forcing. The centennial trend of the downward shortwave radiation at the surface in Northern USA. is on the order of 10% of the climatological value for the January monthly mean, and slightly over 10% at the time when it is midday in the United States. This indicates a nonnegligible influence of the GHG forcing on solar energy in the long term. Nevertheless, when dividing the 10% by a century, in the near term, the impact of the GHG forcing is relatively minor such that the estimate of solar power potential using present-day climatology will remain useful in the coming decades.

scholarly journals Influence of Modes of Climate Variability on Global Temperature Extremes

2008 ◽  
Vol 21 (15) ◽  
pp. 3872-3889 ◽  
Author(s):  
Jesse Kenyon ◽  
Gabriele C. Hegerl
Keyword(s):  
North America ◽  
Climate Variability ◽  
Large Scale ◽  
Southern Oscillation ◽  
Temperature Extremes ◽  
Modes Of Variability ◽  
The North ◽  
The Pacific ◽  
The North Atlantic Oscillation ◽  
Modes Of Climate Variability

Abstract The influence of large-scale modes of climate variability on worldwide summer and winter temperature extremes has been analyzed, namely, that of the El Niño–Southern Oscillation, the North Atlantic Oscillation, and Pacific interdecadal climate variability. Monthly indexes for temperature extremes from worldwide land areas are used describe moderate extremes, such as the number of exceedences of the 90th and 10th climatological percentiles, and more extreme events such as the annual, most extreme temperature. This study examines which extremes show a statistically significant (5%) difference between the positive and negative phases of a circulation regime. Results show that temperature extremes are substantially affected by large-scale circulation patterns, and they show distinct regional patterns of response to modes of climate variability. The effects of the El Niño–Southern Oscillation are seen throughout the world but most clearly around the Pacific Rim and throughout all of North America. Likewise, the influence of Pacific interdecadal variability is strongest in the Northern Hemisphere, especially around the Pacific region and North America, but it extends to the Southern Hemisphere. The North Atlantic Oscillation has a strong continent-wide effect for Eurasia, with a clear but weaker effect over North America. Modes of variability influence the shape of the daily temperature distribution beyond a simple shift, often affecting cold and warm extremes and sometimes daytime and nighttime temperatures differently. Therefore, for reliable attribution of changes in extremes as well as prediction of future changes, changes in modes of variability need to be accounted for.

scholarly journals Increased variability in Greenland Ice Sheet runoff from satellite observations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Thomas Slater ◽  
Andrew Shepherd ◽  
Malcolm McMillan ◽  
Amber Leeson ◽  
Lin Gilbert ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Model Simulations ◽  
Climate Model Simulations

AbstractRunoff from the Greenland Ice Sheet has increased over recent decades affecting global sea level, regional ocean circulation, and coastal marine ecosystems, and it now accounts for most of the contemporary mass imbalance. Estimates of runoff are typically derived from regional climate models because satellite records have been limited to assessments of melting extent. Here, we use CryoSat-2 satellite altimetry to produce direct measurements of Greenland’s runoff variability, based on seasonal changes in the ice sheet’s surface elevation. Between 2011 and 2020, Greenland’s ablation zone thinned on average by 1.4 ± 0.4 m each summer and thickened by 0.9 ± 0.4 m each winter. By adjusting for the steady-state divergence of ice, we estimate that runoff was 357 ± 58 Gt/yr on average – in close agreement with regional climate model simulations (root mean square difference of 47 to 60 Gt/yr). As well as being 21 % higher between 2011 and 2020 than over the preceding three decades, runoff is now also 60 % more variable from year-to-year as a consequence of large-scale fluctuations in atmospheric circulation. Because this variability is not captured in global climate model simulations, our satellite record of runoff should help to refine them and improve confidence in their projections.

scholarly journals A new species of Placiphorella (Polyplacophora: Mopaliidae) from the North American Pacific coast

The Festivus ◽  
2019 ◽  
Vol 51 (2) ◽  
pp. 103-107
Author(s):  
Roger Clark
Keyword(s):  
New Species ◽  
North America ◽  
North American ◽  
Deep Sea ◽  
Pacific Coast ◽  
The North ◽  
The Pacific ◽  
A New Species

A new deep-sea chiton of the genus Placiphorella Dall, 1879, Placiporella laurae n. sp. is described from the Pacific coast of North America. It is compared with its congener Placiphorella pacifica Berry, 1919, from which it differs primarily by having granular valves, lacking false beaks, a papillose girdle, and the characteristics of its girdle spicules

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