Future Projections of the Large-Scale Meteorology Associated with California Heat Waves in CMIP5 Models

Abstract Large-scale synoptic circulations have a profound effect on western U.S. summer weather and climate. Heat waves, water availability, the distribution of monsoonal moisture, fire-weather conditions, and other phenomena are impacted by the position and amplitude of large-scale synoptic circulations. Furthermore, regional weather is modulated by the interactions of the large-scale flow with terrain and land–water contrasts. It is therefore crucial to understand projected changes in large-scale circulations and their variability under anthropogenic global warming. Although recent research has examined changes in the jet stream, storm tracks, and synoptic disturbances over the Northern Hemisphere under global warming, most papers have focused on the cold season. In contrast, this work analyzes the projected trends in the spatial distribution and amplitude of large-scale synoptic disturbances over the western United States and eastern Pacific during July and August. It is shown that CMIP5 models project weaker mean midtropospheric gradients in geopotential height as well as attenuated temporal variability in geopotential height, temperature, vorticity, vertical motion, and sea level pressure over this region. Most models suggest reduced frequency of troughs and increased frequency of ridges over the western United States. These changes in the variability of synoptic disturbances have substantial implications for future regional weather and climate.

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Co-occurrence of extreme ozone and heat waves in two cities from Morocco

Satellite Oceanography and Meteorology ◽

10.18063/som.v3i3.733 ◽

2018 ◽

Vol 3 (3) ◽

Cited By ~ 4

Author(s):

Kenza KHOMSI 1,2 ◽

Houda NAJMI 2 ◽

Zineb SOUHAILI 1

Keyword(s):

Climate Change ◽

Surface Temperature ◽

Extreme Events ◽

Global Climate Change ◽

Large Scale ◽

Heat Waves ◽

Global Climate ◽

Meteorological Factor ◽

Two Cities ◽

Change Context

Temperature is the first meteorological factor to be directly involved in leading ozone (O3) extreme events. Generally, upward temperatures increase the probability of having exceedance in ozone adopted thresholds. In the global climate change context more frequent and/or persistent heat waves and extreme ozone (O3) episodes are likely to occur during in coming decades and a key question is about the coincidence and co-occurrence of these extremes. In this paper, using 7 years of surface temperature and air quality observations over two cities from Morocco (Casablanca and Marrakech) and implementing a percentile thresholding approach, we show that the extremes in temperature and ozone (O3) cluster together in many cases and that the outbreak of ozone events generally match the first or second days of heat waves. This co-occurrence of extreme episodes is highly impacted by humidity and may be overlapping large-scale episodes.

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A novel method to identify subseasonal clustering episodes of extreme precipitation events and their contribution to large accumulations

10.5194/egusphere-egu21-836 ◽

2021 ◽

Author(s):

Jérôme Kopp ◽

Pauline Rivoire ◽

S. Mubashshir Ali ◽

Yannick Barton ◽

Olivia Martius

Keyword(s):

Time Scales ◽

Extreme Precipitation ◽

Large Scale ◽

Time Window ◽

Heat Waves ◽

Reanalysis Data ◽

Data Set ◽

Temporal Clustering ◽

Extreme Precipitation Events ◽

Precipitation Events

<p>Temporal clustering of extreme precipitation events on subseasonal time scales is a type of compound event, which can cause large precipitation accumulations and lead to floods. We present a novel count-based procedure to identify subseasonal clustering of extreme precipitation events. Furthermore, we introduce two metrics to characterise the frequency of subseasonal clustering episodes and their relevance for large precipitation accumulations. The advantage of this approach is that it does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this methodology to the ERA5 reanalysis data set, we identify regions where subseasonal clustering of annual high precipitation percentiles occurs frequently and contributes substantially to large precipitation accumulations. Those regions are the east and northeast of the Asian continent (north of Yellow Sea, in the Chinese provinces of Hebei, Jilin and Liaoning; North and South Korea; Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southeast of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the subseasonal time window (here 2 &#8211; 4 weeks). The procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different time scales (e.g. for drought years). <span>For a complementary study on the subseasonal clustering of European extreme precipitation events and its relationship to large-scale atmospheric drivers, please refer to Barton et al.</span></p>

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Evaluation of the Antarctic Circumpolar Wave Simulated by CMIP5 and CMIP6 Models

Atmosphere ◽

10.3390/atmos11090931 ◽

2020 ◽

Vol 11 (9) ◽

pp. 931

Author(s):

Zhichao Lu ◽

Tianbao Zhao ◽

Weican Zhou

Keyword(s):

Large Scale ◽

Global Climate ◽

Coupled Model ◽

Cmip5 Models ◽

Weather Forecasts ◽

Antarctic Circumpolar Wave ◽

Sst Variability ◽

The Antarctic ◽

Chemistry Module ◽

Better Than

As a coupled large-scale oceanic and atmospheric pattern in the Southern Ocean, the Antarctic circumpolar wave (ACW) has substantial impacts on the global climate. In this study, using the European Centre for Medium-Range Weather Forecasts ERA5 dataset and historical experiment outputs from 24 models of the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5/CMIP6) spanning the 1980s and 1990s, the simulation capability of models for sea-level pressure (SLP) and sea surface temperature (SST) variability of the ACW is evaluated. It is shown that most models can capture well the 50-month period of the ACW. However, many simulations show a weak amplitude, but with various phase differences. Selected models can simulate SLP better than SST, and CMIP6 models generally perform better than the CMIP5 models. The best model for SLP simulation is the CanESM5 model from CMIP6, whereas the best model for SST simulation is the ACCESS1.3 model from CMIP5. It seems that the SST simulation benefits from the inclusion of both a carbon cycle process and a chemistry module, while the SLP simulation benefits from only the chemistry module. When both SLP and SST are taken into consideration, the CanESM5 model performs the best among all the selected models.

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Probabilistic Heat Wave Forecast Based on a Large-Scale Circulation Pattern Using the TIGGE Data

Weather and Forecasting ◽

10.1175/waf-d-19-0188.1 ◽

2020 ◽

Vol 35 (2) ◽

pp. 367-377

Author(s):

Hyun-Ju Lee ◽

Woo-Seop Lee ◽

Jong Ahn Chun ◽

Hwa Woon Lee

Keyword(s):

South Korea ◽

Heat Wave ◽

Large Scale ◽

Heat Waves ◽

Ensemble Prediction ◽

Multimodel Ensemble ◽

Large Scale Circulation ◽

Circulation Patterns ◽

Wave Forecast ◽

Prediction Systems

Abstract Forecasting extreme events is important for having more time to prepare and mitigate high-impact events because those are expected to become more frequent, intense, and persistent around the globe in the future under the warming atmosphere. This study evaluates the probabilistic predictability of the heat wave index (HWI) associated with large-scale circulation patterns for predicting heat waves over South Korea. The HWI, reflecting heat waves over South Korea, was defined as the vorticity difference at 200 hPa between the South China Sea and northeast Asia. The forecast of up to 15 days from five ensemble prediction systems and the multimodel ensemble has been used to predict the probabilistic HWI during the summers of 2011–15. The ensemble prediction systems consist of different five operational centers, and the forecast skill of the probability of heat waves occurrence was assessed using the Brier skill score (BSS), relative operating characteristics (ROC), and reliability diagram. It was found that the multimodel ensemble is capable of better predicting the large-scale circulation patterns leading to heat waves over South Korea than any other single ensemble system through all forecast lead times. We concluded that the probabilistic forecast of the HWI has promise as a tool to take appropriate and timely actions to minimize the loss of lives and properties from imminent heat waves.

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Detection of Intraseasonal Large-Scale Heat Waves: Characteristics and Historical Trends during the Sahelian Spring

Journal of Climate ◽

10.1175/jcli-d-17-0244.1 ◽

2017 ◽

Vol 31 (1) ◽

pp. 61-80 ◽

Cited By ~ 12

Author(s):

J. Barbier ◽

F. Guichard ◽

D. Bouniol ◽

F. Couvreux ◽

R. Roehrig

Keyword(s):

Large Scale ◽

Heat Waves ◽

Heat Index ◽

Daily Maximum ◽

Historical Trends ◽

Climatic Trend ◽

Climatic Trends ◽

Spatiotemporal Scales ◽

Time Of Year ◽

Very High

Abstract In the Sahel very high temperatures prevail in spring, but little is known about heat waves in this region at that time of year. This study documents Sahelian heat waves with a new methodology that allows selecting heat waves at specific spatiotemporal scales and can be used in other parts of the world. It is applied separately to daily maximum and minimum temperatures, as they lead to the identification of distinct events. Synoptic–intraseasonal Sahelian heat waves are characterized from March to July over the period 1950–2012 with the Berkeley Earth Surface Temperature (BEST) gridded dataset. Morphological and temperature-related characteristics of the selected heat waves are presented. From March to July, the further into the season, the shorter and the less frequent the heat waves become. From 1950 to 2012, these synoptic–intraseasonal heat waves do not tend to be more frequent; however, they become warmer, and this trend follows the Sahelian climatic trend. Compared to other commonly used indices, the present index tends to select heat waves with more uniform intensities. This comparison of indices also underlined the importance of the heat index definition on the estimated climatic heat wave trends in a changing climate. Finally, heat waves were identified with data from three meteorological reanalyses: ERA-Interim, MERRA, and NCEP-2. The spreads in temperature variabilities, seasonal cycles, and trends among reanalyses lead to differences in the characteristics, interannual variability, and climatic trends of heat waves, with fewer departures from BEST for ERA-Interim.

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