scholarly journals Evaluating sub-seasonal heatwave reforecasts of the ECMWF over Europe

2021 ◽  
Author(s):  
Natalia Korhonen ◽  
Otto Hyvärinen ◽  
Matti Kämäräinen ◽  
Kirsti Jylhä

<p>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).</p><p>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 90<sup>th</sup> 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…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.</p><p>The work presented here is part of the research project HEATCLIM (Heat and health in the changing climate) funded by the Academy of Finland.</p>

2018 ◽  
Vol 146 (4) ◽  
pp. 1063-1075 ◽  
Author(s):  
Alexey Yu. Karpechko

The skill of the Arctic stratospheric retrospective ensemble forecasts (hindcasts) of the European Centre for Medium-Range Weather Forecasts extended-range system is analyzed with a focus on the predictability of the major sudden stratospheric warmings (SSWs) during the period 1993–2016. Thirteen SSWs took place during this period. It is found that forecasts initialized 10–15 days before the SSWs show worse skill in the stratosphere than forecasts initialized during normal conditions in terms of root-mean-square errors but not in terms of anomaly correlation. Using the spread of ensemble members to estimate forecasted SSW probability, it is shown that some SSWs can be predicted with high (>0.9) probability at lead times of 12–13 days if a difference of 3 days between actual and forecasted SSW is allowed. Focusing on SSWs with significant impacts on the tropospheric circulation, on average, the forecasted SSW probability is found to increase from nearly 0 at 1-month lead time to 0.3 at day 13 before SSW, and then rapidly increases to nearly 1 at day 7. The period between days 8 and 12 is when most of the SSWs are predicted, with a probability of 0.5–0.9, which is considerably larger than the observed SSW occurrence frequency. Therefore, this period can be thought of as an estimate of the SSW predictability limit in this system. Indications that the predictability limit for some SSWs may be longer than 2 weeks are also found; however, this result is inconclusive and more studies are needed to understand when and why such long predictability is possible.


2018 ◽  
Vol 39 (4) ◽  
pp. 2422-2437 ◽  
Author(s):  
Daniel Fenner ◽  
Achim Holtmann ◽  
Alexander Krug ◽  
Dieter Scherer

2018 ◽  
Vol 176 ◽  
pp. 02008
Author(s):  
Erland Källén

The ADM/Aeolus wind lidar mission will provide a global coverage of atmospheric wind profiles. Atmospheric wind observations are required for initiating weather forecast models and for predicting and monitoring long term climate change. Improved knowledge of the global wind field is widely recognised as fundamental to advancing the understanding and prediction of weather and climate. In particular over tropical areas there is a need for better wind data leading to improved medium range (3-10 days) weather forecasts over the whole globe.


2020 ◽  
Vol 35 (2) ◽  
pp. 367-377
Author(s):  
Hyun-Ju Lee ◽  
Woo-Seop Lee ◽  
Jong Ahn Chun ◽  
Hwa Woon Lee

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.


Author(s):  
Hojjatollah Yazdanpanah ◽  
Josef Eitzinger ◽  
Marina Baldi

Purpose The purpose of this paper is to assess the spatial and temporal variations of extreme hot days (H*) and heat wave frequencies across Iran. Design/methodology/approach The authors used daily maximum temperature (Tmax) data of 27 synoptic stations in Iran. These data were standardized using the mean and the standard deviation of each day of the year. An extreme hot day was defined when the Z score of daily maximum temperature of that day was equal or more than a given threshold fixed at 1.7, while a heat wave event was considered to occur when the Z score exceeds the threshold for at least three continuous days. According to these criteria, the annual frequency of extreme hot days and the number of heat waves were determined for all stations. Findings The trend analysis of H* shows a positive trend during the past two decades in Iran, with the maximum number of H* (110 cases) observed in 2010. A significant trend of the number of heat waves per year was also detected during 1991-2013 in all the stations. Overall, results indicate that Iran has experienced heat waves in recent years more often than its long-term average. There will be more frequent and intense hot days and heat waves across Iran until 2050, due to estimated increase of mean air temperature between 0.5-1.1 and 0.8-1.6 degree centigrade for Rcp2.6 and Rcp8.8 scenarios, respectively. Originality/value The trend analysis of hot days and heat wave frequencies is a particularly original aspect of this paper. It is very important for policy- and decision-makers especially in agriculture and health sectors of Iran to make some adaptation strategies for future frequent and intense hot days over Iran.


2015 ◽  
Vol 124 (3-4) ◽  
pp. 679-689 ◽  
Author(s):  
Matilde Rusticucci ◽  
Jan Kyselý ◽  
Gustavo Almeira ◽  
Ondřej Lhotka
Keyword(s):  

2021 ◽  
Vol 7 ◽  
Author(s):  
Lillian R. Aoki ◽  
Karen J. McGlathery ◽  
Patricia L. Wiberg ◽  
Matthew P. J. Oreska ◽  
Amelie C. Berger ◽  
...  

Worldwide, seagrass meadows accumulate significant stocks of organic carbon (C), known as “blue” carbon, which can remain buried for decades to centuries. However, when seagrass meadows are disturbed, these C stocks may be remineralized, leading to significant CO2 emissions. Increasing ocean temperatures, and increasing frequency and severity of heat waves, threaten seagrass meadows and their sediment blue C. To date, no study has directly measured the impact of seagrass declines from high temperatures on sediment C stocks. Here, we use a long-term record of sediment C stocks from a 7-km2, restored eelgrass (Zostera marina) meadow to show that seagrass dieback following a single marine heat wave (MHW) led to significant losses of sediment C. Patterns of sediment C loss and re-accumulation lagged patterns of seagrass recovery. Sediment C losses were concentrated within the central area of the meadow, where sites experienced extreme shoot density declines of 90% during the MHW and net losses of 20% of sediment C over the following 3 years. However, this effect was not uniform; outer meadow sites showed little evidence of shoot declines during the MHW and had net increases of 60% of sediment C over the following 3 years. Overall, sites with higher seagrass recovery maintained 1.7x as much C compared to sites with lower recovery. Our study demonstrates that while seagrass blue C is vulnerable to MHWs, localization of seagrass loss can prevent meadow-wide C losses. Long-term (decadal and beyond) stability of seagrass blue C depends on seagrass resilience to short-term disturbance events.


2021 ◽  
Author(s):  
Xiaolu Ling ◽  
Ying Huang ◽  
Weidong Guo ◽  
Yixin Wang ◽  
Chaorong Chen ◽  
...  

Abstract. Soil moisture (SM) plays a critical role in the water and energy cycles of the earth system; consequently, a long-term SM product with high quality is urgently needed. In this study, five SM products, including one microwave remote sensing product [European Space Agency's Climate Change Initiative (ESA CCI)] and four reanalysis datasets [European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERAI), National Centers for Environmental Prediction (NCEP), the Twentieth Century Reanalysis Project from National Oceanic and Atmospheric Administration (NOAA) and the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5)], are systematically evaluated using in situ measurements during 1981–2013 in four climate regions at different timescales over mainland China. The results show that ESA CCI is closest to the observations in terms of both the spatial distributions and magnitude of the monthly SM. All reanalysis products tend to overestimate soil moisture in all regions but have higher correlations than the remote sensing product except in Northwest China. The largest inconsistency is found in southern Northeast China, with a relative RMSE value larger than 0.1. However, none of the products can well reproduce the trends of interannual anomalies. The largest relative bias of 44.6 % is found for the ERAI SM product under severe drought conditions, and the lowest relative biases of 4.7 % and 9.5 % are found for the ESA CCI SM product under severe drought conditions and the NCEP SM product under normal conditions, respectively. As decomposing mean square errors in all the products suggests that the bias terms are the dominant contribution, the ESA CCI SM product is a good option for long-term hydrometeorological applications in mainland China. ERA5 is also a promising product, which is attributed to the incorporation of more observations. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.


Author(s):  
Krzysztof Bartoszek ◽  
Alicja Węgrzyn

Abstract The occurrence of hot weather in the Lublin-Felin and Czesławice in relation to atmospheric circulation (1966−2010). The paper describes the occurrence of hot (tmax 25.1−30.0°C) and very hot days (tmax >30°C) in Lublin-Felin and Czesławice in the years 1966−2010. The analysis covers the long-term variability of such days, and duration of heat waves. Their circulation conditions were also determined, with indication of circulation types during which the probability of occurrence of hot and very hot days was the highest. In the study area, hot days occurred from April to September, and very hot days from May to August, with the highest frequency in July in both cases. In the period from 1991 to 2010, a considerably higher number of cases of very hot days were recorded than in the 1970s and 1980s. Moreover, they occurred in increasingly long sequences, contributing to more frequent occurrence of unfavourable thermal and humid conditions during the growing season of plants. The highest probability of occurrence of hot and very hot days was determined for circulation types with airflow from the southern sector, and the lowest from the northern sector. Should the upward trend in the frequency of very hot days continue, the risk of the effect of such unfavourable thermal conditions on the health and well-being of tourists and patients of the health resort in Nałęczów will also increase


2020 ◽  
Author(s):  
Assaf Hochman ◽  
Sebastian Scher ◽  
Julian Quinting ◽  
Joaquim G. Pinto ◽  
Gabriele Messori

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.


Sign in / Sign up

Export Citation Format

Share Document