A New View of Heat Wave Dynamics and Predictability over the Eastern Mediterranean

Abstract. Skillful forecasts of extreme weather events have a major socio-economic relevance. Here, we compare two complementary approaches to diagnose the predictability of extreme weather: recent developments in dynamical systems theory and numerical ensemble weather forecasts. The former allows us to define atmospheric configurations in terms of their persistence and local dimension, which inform on how the atmosphere evolves to and from a given state of interest. These metrics may be used as proxies for the intrinsic predictability of the atmosphere, which depends exclusively on the atmosphere’s properties. Ensemble weather forecasts inform on the practical predictability of the atmosphere, which primarily depends on the performance of the numerical model used. We focus on heat waves affecting the Eastern Mediterranean. These are identified using the Climatic Stress Index (CSI), which was explicitly developed for the summer weather conditions in this region and differentiates between heat waves (upper decile) and cool days (lower decile). Significant differences are found between the two groups from both the dynamical systems and the numerical weather prediction perspectives. Specifically, heat waves show relatively stable flow characteristics (high intrinsic predictability), but comparatively low practical predictability (large model spread/error). For 500 hPa geopotential height fields, the intrinsic predictability of heat waves is lowest at the event’s onset and decay. We relate these results to the physical processes governing Eastern Mediterranean summer heat waves: adiabatic descent of the air parcels over the region and the geographical origin of the air parcels over land prior to the onset of a heat wave. A detailed analysis of the mid-August 2010 record-breaking heat wave provides further insights into the range of different regional atmospheric configurations conducive to heat waves. We conclude that the dynamical systems approach can be a useful complement to conventional numerical forecasts for understanding the dynamics of Eastern Mediterranean heat waves.

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A new view of heat wave dynamics and predictability over the eastern Mediterranean

Earth System Dynamics ◽

10.5194/esd-12-133-2021 ◽

2021 ◽

Vol 12 (1) ◽

pp. 133-149

Author(s):

Assaf Hochman ◽

Sebastian Scher ◽

Julian Quinting ◽

Joaquim G. Pinto ◽

Gabriele Messori

Keyword(s):

Dynamical Systems ◽

Heat Wave ◽

Heat Waves ◽

Eastern Mediterranean ◽

Weather Prediction ◽

Extreme Weather ◽

Extreme Weather Events ◽

Stress Index ◽

Weather Forecasts ◽

Ensemble Weather Forecasts

Abstract. Skillful forecasts of extreme weather events have a major socioeconomic relevance. Here, we compare two complementary approaches to diagnose the predictability of extreme weather: recent developments in dynamical systems theory and numerical ensemble weather forecasts. The former allows us to define atmospheric configurations in terms of their persistence and local dimension, which provides information on how the atmosphere evolves to and from a given state of interest. These metrics may be used as proxies for the intrinsic predictability of the atmosphere, which only depends on the atmosphere's properties. Ensemble weather forecasts provide information on the practical predictability of the atmosphere, which partly depends on the performance of the numerical model used. We focus on heat waves affecting the eastern Mediterranean. These are identified using the climatic stress index (CSI), which was explicitly developed for the summer weather conditions in this region and differentiates between heat waves (upper decile) and cool days (lower decile). Significant differences are found between the two groups from both the dynamical systems and the numerical weather prediction perspectives. Specifically, heat waves show relatively stable flow characteristics (high intrinsic predictability) but comparatively low practical predictability (large model spread and error). For 500 hPa geopotential height fields, the intrinsic predictability of heat waves is lowest at the event's onset and decay. We relate these results to the physical processes governing eastern Mediterranean summer heat waves: adiabatic descent of the air parcels over the region and the geographical origin of the air parcels over land prior to the onset of a heat wave. A detailed analysis of the mid-August 2010 record-breaking heat wave provides further insights into the range of different regional atmospheric configurations conducive to heat waves. We conclude that the dynamical systems approach can be a useful complement to conventional numerical forecasts for understanding the dynamics and predictability of eastern Mediterranean heat waves.

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Extreme Weather Impacts on Inland Waterways Transport of Yangtze River

Atmosphere ◽

10.3390/atmos10030133 ◽

2019 ◽

Vol 10 (3) ◽

pp. 133 ◽

Cited By ~ 2

Author(s):

Lijun Liu ◽

Yuanqiao Wen ◽

Youjia Liang ◽

Fan Zhang ◽

Tiantian Yang

Keyword(s):

Heat Wave ◽

Yangtze River ◽

Heat Waves ◽

Extreme Weather ◽

Extreme Weather Events ◽

The Yangtze River ◽

Climate Zone ◽

Inland Waterways ◽

Weather Events ◽

The Impact

The impact of extreme weather events on the navigation environment in the inland waterways of the Yangtze River is an interdisciplinary hotspot in subjects of maritime traffic safety and maritime meteorology, and it is also a difficult point for the implementation of decision-making and management by maritime and meteorological departments in China. The objective of this study is to review the variation trends and distribution patterns in the periods of adverse and extreme weather events that are expected to impact on inland waterways transport (IWT) on the Yangtze River. The frequency of severe weather events, together with the changes in their spatial extension and intensity, is analyzed based on the ERA-Interim datasets (1979–2017) and the GHCNDEX dataset (1979–2017), as well as the research progresses and important events (2004–2016) affecting the navigation environment. The impacts of extreme weather events on IWT accidents and phenomena of extreme weather (e.g., thunderstorms, lightning, hail, and tornadoes) that affect the navigation environment are also analyzed and discussed. The results show that: (1) the sections located in the plain climate zone is affected by extreme weather in every season, especially strong winds and heat waves; (2) the sections located in the hilly mountain climate zone is affected particularly by spring extreme phenomena, especially heat waves; (3) the sections located in the Sichuan Basin climate zone is dominated by the extreme weather phenomena in autumn, except cold waves; (4) the occurrence frequency of potential flood risk events is relatively high under rainstorm conditions and wind gusts almost affect the navigation environment of the Jiangsu and Shanghai sections in every year; (5) the heat wave indices (TXx, TR, and WSDI) tend to increase and the temperature of the coldest day of the year gradually increases; (6) the high occurrences of IWT accidents need to be emphasized by relevant departments, caused by extreme weather during the dry season; and (7) the trends and the degree of attention of extreme weather events affecting IWT are ranked as: heat wave > heavy rainfall > wind gust > cold spell > storm. Understanding the seasonal and annual frequency of occurrence of extreme weather events has reference significance for regional management of the Yangtze River.

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A New Avenue of Research for Improving the Predictability of Weather Extremes - The Eastern Mediterranen as a Case Study

10.5194/egusphere-egu2020-2864 ◽

2020 ◽

Author(s):

Assaf Hochman ◽

Pinhas Alpert ◽

Hadas Saaroni ◽

Tzvi Harpaz ◽

Joaquim G. Pinto ◽

...

Keyword(s):

Dynamical Systems ◽

Systems Approach ◽

Eastern Mediterranean ◽

Extreme Weather ◽

Extreme Weather Events ◽

Weather Extremes ◽

Systems Perspective ◽

Weather Events ◽

The Mediterranean

Extreme weather events have long been considered challenging to predict. It is likely that global warming will trigger extreme weather in many regions of the globe and especially over the Mediterranean &#180;hot spot&#180;. Therefore, extreme weather events have been selected as one of the grand challenges of the World Climate Research Program.The intrinsic predictability of a weather system, or any dynamical system, depends on its persistence and its active number of degrees of freedom. Recent developments in dynamical systems theory allow to compute these metrics for atmospheric configurations (1). In most of the mid-latitudes, synoptic scale patterns exert a strong control on regional weather, thus, stimulating a broad interest, especially in weather forecasting. Recently, we have integrated the dynamical systems approach with a synoptic classification algorithm over the Eastern Mediterranean (2).&#160; It was shown that the dynamical systems perspective provides an extremely informative tool for evaluating the predictability of synoptic patterns and especially of weather extremes.The novel perspective, which leverages a dynamical systems approach to investigate the predictability of extreme weather events, outlines a new avenue of research that may be fruitfully applied at operational weather and climate forecasting services in the Mediterranean Region and around the globe.References<ol><li>Faranda D, Messori G, Yiou P. 2017. Dynamical Proxies of North Atlantic Predictability and Extremes. Scientific Reports 7, 412782017b. DOI: 10.1038/srep4127</li> <li>Hochman A, Alpert P, Harpaz T, Saaroni H, Messori G. 2019. A New Dynamical Systems Perspective on Atmospheric Predictability; Eastern Mediterranean Weather Regimes as a Case Study. Science Advances 5. DOI: 10.1126/sciadv.aau0936</li> </ol>

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Reliability Framework for Characterizing Heat Wave and Cold Spell Events

10.21203/rs.3.rs-684055/v1 ◽

2021 ◽

Author(s):

Sanaz Moghim ◽

Mohammad Sina Jahangir

Keyword(s):

Heat Wave ◽

Heat Waves ◽

Probability Distributions ◽

Extreme Temperature ◽

Extreme Weather ◽

Extreme Weather Events ◽

Average Intensity ◽

Cold Spell ◽

Weather Events ◽

Two Cities

Abstract Extreme weather events such as heat waves and cold spells affect people’s lives. This study uses a probabilistic framework to evaluate heat waves and cold spells in different regions (Tehran in Iran and Vancouver in Canada). Average daily temperatures of meteorological stations of the two cities from 1995 to 2016 are used to identify four main indicators including intensity, average intensity, duration, and the rate of the occurrence. In addition, average intensities of the events are obtained from the MODIS Land Surface Temperature (LST) in each pixel of the two cities. To include possible uncertainties, the predictive probability distributions of the intensity and duration are derived using a Bayesian scheme and Monte-Carlo Markov Chain (MCMC) method. The probability distributions of the indicators show that the most extreme temperature (lowest temperature) occurs during the cold spell. Results indicate that although Tehran is more probable to experience heat waves than Vancouver, both cities are more likely to be affected by the cold spell than the heat wave. The developed approach can be used to characterize other extreme weather events in any location.

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Dynamics and predictability of cold spells over the Eastern Mediterranean

Climate Dynamics ◽

10.1007/s00382-020-05465-2 ◽

2020 ◽

Author(s):

Assaf Hochman ◽

Sebastian Scher ◽

Julian Quinting ◽

Joaquim G. Pinto ◽

Gabriele Messori

Keyword(s):

Dynamical Systems ◽

Systems Approach ◽

Eastern Mediterranean ◽

Absolute Error ◽

Extreme Weather ◽

Extreme Weather Events ◽

Future Research ◽

Weather Extremes ◽

Weather System ◽

Weather Events

Abstract The accurate prediction of extreme weather events is an important and challenging task, and has typically relied on numerical simulations of the atmosphere. Here, we combine insights from numerical forecasts with recent developments in dynamical systems theory, which describe atmospheric states in terms of their persistence (θ−1) and local dimension (d), and inform on how the atmosphere evolves to and from a given state of interest. These metrics are intuitively linked to the intrinsic predictability of the atmosphere: a highly persistent, low-dimensional state will be more predictable than a low-persistence, high-dimensional one. We argue that θ−1 and d, derived from reanalysis sea level pressure (SLP) and geopotential height (Z500) fields, can provide complementary predictive information for mid-latitude extreme weather events. Specifically, signatures of regional extreme weather events might be reflected in the dynamical systems metrics, even when the actual extreme is not well-simulated in numerical forecasting systems. We focus on cold spells in the Eastern Mediterranean, and particularly those associated with snow cover in Jerusalem. These rare events are systematically associated with Cyprus Lows, which are the dominant rain-bearing weather system in the region. In our analysis, we compare the ‘cold spell Cyprus Lows’ to other ‘regular’ Cyprus Low days. Significant differences are found between cold spells and ‘regular’ Cyprus Lows from a dynamical systems perspective. When considering SLP, the intrinsic predictability of cold spells is lowest hours before the onset of snow. We find that the cyclone’s location, depth and magnitude of air-sea fluxes play an important role in determining its intrinsic predictability. The dynamical systems metrics computed on Z500 display a different temporal evolution to their SLP counterparts, highlighting the different characteristics of the atmospheric flow at the different levels. We conclude that the dynamical systems approach, although sometimes challenging to interpret, can complement conventional numerical forecasts and forecast skill measures, such as model spread and absolute error. This methodology outlines an important avenue for future research, which can potentially be fruitfully applied to other regions and other types of weather extremes.

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Probability and deterministic amount of precipitation on the multi-model ensemble

10.5194/egusphere-egu2020-6242 ◽

2020 ◽

Author(s):

Juwon Kim ◽

Hae-Jin Kong ◽

Hyuncheol Shin

Keyword(s):

Data Assimilation ◽

Weather Prediction ◽

Extreme Weather ◽

Extreme Weather Events ◽

Ensemble Prediction ◽

Prediction System ◽

Model Ensemble ◽

Post Processing ◽

Weather Forecasts ◽

The Impact

Multi-model ensemble using statistical post-processing is one of the methods to provide the impact of uncertainties of the Numerical Weather Prediction (NWP) models, with low cost and better accuracy for extreme weather forecasts. Extreme weather events such as heat/cold waves, windstorms, and heavy rainfall result in severe damage in human life and properties. However, the performance of the NWP models, particularly, heavy rain forecast is still low due to the intermittent and non-Gaussian properties. The light rain tends to be overestimated and the strong rain tends to be underestimated averagely on the NWP models. Thus the multi-model ensemble using statistical post-processing is activated to correct the discrepancies between the observation and the model intensity of precipitation. The aim of this study is to provide the improvement of precipitation forecasts in probabilistic and deterministic aspects using a multi-model ensemble method with more weights on the less error and without any bias correction. Six types of models, namely, Local Data assimilation and Prediction System (LDPS), Local ENsemble System (LENS), Global Data assimilation and Prediction System (GDPS), Ensemble Prediction System-Global (EPSG) of Korea Meteorological Administration (KMA), the single and ensemble models of European Centre for Medium-Range Weather Forecasts (ECMWF), are used to blend. The preliminary results of the multi-model ensemble show similar results to the ECMWF ensemble mean in deterministic for 3-hourly accumulated precipitation over the East Asia and the middle of the performance among individual models in probabilistic over the South Korea. More details of the methodology, results, and improvements will be discussed in the presentation.

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ESD Reviews: Extreme Weather and Societal Impacts in the Eastern Mediterranean

10.5194/esd-2021-55 ◽

2021 ◽

Author(s):

Assaf Hochman ◽

Francesco Marra ◽

Gabriele Messori ◽

Joaquim G. Pinto ◽

Shira Raveh-Rubin ◽

...

Keyword(s):

High Pressure ◽

Red Sea ◽

Heat Waves ◽

Eastern Mediterranean ◽

Heavy Precipitation ◽

Extreme Weather ◽

Extreme Weather Events ◽

Weather Events ◽

Societal Impacts ◽

Wind Storms

Abstract. Gaining a holistic understanding of extreme weather, from its physical drivers to its impacts on society and ecosystems, is key to supporting future risk reduction and preparedness measures. Here, we provide an overview of the state-of-the-art, knowledge gaps and key open questions in the study of extreme weather events over the vulnerable eastern Mediterranean. This region is situated in a transition zone between subtropical and mid-latitude climates. Extreme weather is mainly governed by the large-scale atmospheric circulation and its interaction with regional synoptic systems, i.e., Cyprus Lows, Red Sea Troughs, Persian Troughs, ‘Sharav’ Lows, and high-pressure systems. Complex orographic features further play an important role in the generation of extreme weather. Most extreme weather events, including heavy precipitation, cold spells, floods and wind storms, are associated with a Cyprus Low or Active Red Sea Trough, whereas heat waves are related with either the Persian Trough and Sub-Tropical High-pressure systems in summer, or the ‘Sharav’ Low during spring time. Heat waves and droughts are projected to significantly increase in both frequency and intensity. In future decades, changes in heavy precipitation frequency and intensity may vary in sign and magnitude depending on the scale, severity and region of interest. There are still relatively large uncertainties concerning the physical understanding and the projected changes of cold spells, wind storms and compound events, as these types of events received comparatively little attention in the literature. We further identify knowledge gaps that relate to the societal impacts of extreme weather. These gaps mainly relate to the effects extreme weather may have on mortality, morbidity and infrastructure in the eastern Mediterranean. Research is currently limited in this context, and we call to strengthen the database of analyzed case-studies. We trust that this can only be suitably accomplished by inter-disciplinary and international regional collaborations, in spite of political unrest.

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Impacts of compound extreme weather events on ozone in the present and future

10.5194/acp-2018-231 ◽

2018 ◽

Author(s):

Junxi Zhang ◽

Yang Gao ◽

Kun Luo ◽

L. Ruby Leung ◽

Yang Zhang ◽

...

Keyword(s):

Extreme Events ◽

Heat Waves ◽

Extreme Weather ◽

Extreme Weather Events ◽

Low Wind Speed ◽

Weather Events ◽

The Us ◽

The Future ◽

Compound Events ◽

Ozone Episodes

Abstract. The Weather Research and Forecasting model with Chemistry (WRF/Chem) was used to study the effect of extreme weather events on ozone in US for historical (2001–2010) and future (2046–2055) periods under RCP8.5 scenario. During extreme weather events, including heat waves, atmospheric stagnation, and their compound events, ozone concentration is much higher compared to non-extreme events period. A striking enhancement of effect during compound events is revealed when heat wave and stagnation occur simultaneously and both high temperature and low wind speed promote the production of high ozone concentrations. In regions with high emissions, compound extreme events can shift the high-end tails of the probability density functions (PDFs) of ozone to even higher values to generate extreme ozone episodes. In regions with low emissions, extreme events can still increase high ozone frequency but the high-end tails of the PDFs are constrained by the low emissions. Despite large anthropogenic emission reduction projected for the future, compound events increase ozone more than the single events by 10 % to 13 %, comparable to the present, and high ozone episodes are not eliminated. Using the CMIP5 multi-model ensemble, the frequency of compound events is found to increase more dominantly compared to the increased frequency of single events in the future over the US, Europe, and China. High ozone episodes will likely continue in the future due to increases in both frequency and intensity of extreme events, despite reductions in anthropogenic emissions of its precursors. However, the latter could reduce or eliminate extreme ozone episodes, so improving projections of compound events and their impacts on extreme ozone may better constrain future projections of extreme ozone episodes that have detrimental effects on human health.

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Evaluating sub-seasonal heatwave reforecasts of the ECMWF over Europe

10.5194/ems2021-146 ◽

2021 ◽

Author(s):

Natalia Korhonen ◽

Otto Hyvärinen ◽

Matti Kämäräinen ◽

Kirsti Jylhä

Keyword(s):

Heat Wave ◽

Heat Waves ◽

Lead Times ◽

Weather Forecasts ◽

Wave Forecast ◽

Extended Range ◽

Hot Days ◽

Medium Range ◽

Summer Temperatures

Severe heatwaves have harmful impacts on ecosystems and society. Early warning of heat waves help with decreasing their harmful impact. Previous research shows that the Extended Range Forecasts (ERF) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have over Europe a somewhat higher reforecast skill for extreme hot summer temperatures than for long-term mean temperatures. Also it has been shown that the reforecast skill of the ERFs of the ECMWF was strongly increased by the most severe heat waves (the European heatwave 2003 and the Russian heatwave 2010).Our aim is to be able to estimate the skill of a heat wave forecast at the time the forecast is given. For that we investigated the spatial and temporal reforecast skill of the ERFs of the ECMWF to forecast hot days (here defined as a day on which the 5 days running mean surface temperature is above its summer 90th percentile) in the continental Europe in summers 2000-2019. We used the ECMWF 2-meter temperature reforecasts and verified them against the ERA5 reanalysis. The skill of the hot day reforecasts was estimated by the symmetric extremal dependence index (SEDI) which considers both hit rates and false alarm rates of the hot day forecasts. Further, we investigated the skill of the heatwave reforecasts based on at which time steps of the forecast the hot days were forecasted. We found that on the mesoscale (horizontal scale of ~500 km) the ERFs of the ECMWF were most skillful in predicting the life cycle of a heat wave (lasting up to 25 days) about a week before its start and during its course. That is, on the mesoscale those reforecasts, in which hot day(s) were forecasted to occur during the first 7&#8230;11 days, were more skillful on lead times up to 25 days than the rest of the heat wave forecasts. This finding is valuable information, e.g., in the energy and health sectors while preparing for a coming heat wave.The work presented here is part of the research project HEATCLIM (Heat and health in the changing climate) funded by the Academy of Finland.

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Is there a Need to Integrate Human Thermal Models with Weather Forecasts to Predict Thermal Stress?

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16224586 ◽

2019 ◽

Vol 16 (22) ◽

pp. 4586 ◽

Cited By ~ 3

Author(s):

Petersson ◽

Kuklane ◽

Gao

Keyword(s):

Thermal Stress ◽

Cold Stress ◽

Extreme Weather ◽

Data Availability ◽

Extreme Weather Events ◽

Weather Data ◽

Stress Index ◽

Thermal Models ◽

Weather Events ◽

Heat And Cold Stress

More and more people will experience thermal stress in the future as the global temperature is increasing at an alarming rate and the risk for extreme weather events is growing. The increased exposure to extreme weather events poses a challenge for societies around the world. This literature review investigates the feasibility of making advanced human thermal models in connection with meteorological data publicly available for more versatile practices and a wider population. By providing society and individuals with personalized heat and cold stress warnings, coping advice and educational purposes, the risks of thermal stress can effectively be reduced. One interesting approach is to use weather station data as input for the wet bulb globe temperature heat stress index, human heat balance models, and wind chill index to assess heat and cold stress. This review explores the advantages and challenges of this approach for the ongoing EU project ClimApp where more advanced models may provide society with warnings on an individual basis for different thermal environments such as tropical heat or polar cold. The biggest challenges identified are properly assessing mean radiant temperature, microclimate weather data availability, integration and continuity of different thermal models, and further model validation for vulnerable groups.

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