A copula-based assessment of renewable energy droughts across Europe

Meeting carbon-reduction targets will require thorough consideration of climate variability and climate change due to the increasing share of climate-sensitive renewable energy sources (RES). One of the main concerns arises from situations of low renewable production and high demand, which can hinder the power system. We analysed energy droughts, defined as periods of low energy production (wind plus solar generation) or high residual load (demand minus production), in terms of two main properties: duration and severity. We estimated the joint return periods associated with energy droughts of residual load and power production. We showed that moderate winter energy droughts of both low renewable production and high residual load occur every half a year, while summer events occur every 3.6 and 2.4 years (on average). As expected, the occurrence of energy droughts tends to decrease with the degree of the severity of the energy drought, and moderate and extreme energy droughts showed longer return period for most countries. In general, we found a large variability across Europe in summer, with some countries (e.g. Italy) being more sensitive to energy droughts. Our results highlight the relevance of sharing RES during prolonged periods of low production and high demand.

Drought Occurrence Probability Analysis Using Multivariate Standardized Drought Index and Copula Function Under Climate Change

This study aims to investigate the effect of climate change on the probability of drought occurrence in central Iran. To this end, a new drought index called Multivariate Standardized Drought Index (MSDI) was developed, which is composed of the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Soil Moisture Index (SSI). The required data included precipitation, temperature (from CRU TS), and soil moisture (from the ESA CCA SM product) on a monthly time scale for the 1980–2016 period. Moreover, future climate data were downloaded from CMIP6 models under the latest SSPs-RCPs emission scenarios (SSP1-2.6 and SSP5-8.5) for the 2020–2056 period. Based on the NRMSE, Sn, and NS evaluation criteria, the Galambos and Clayton functions were selected to derive copula-based joint distribution functions in both periods. The results showed that more severe droughts and longer will occur in the future compared to the historical period and in particular under the SSP5-8.5 scenario. From the derived joint return period, a drought event with defined severity or duration will happen in a shorter return period as compared with the historical period. In other words, joint return period indicated a higher probability of drought occurrence in the future period. Moreover, the joint return period analysis revealed that the return period of mild droughts will remain the same, while it decresed over extreme droughts in the future.

SESR-based Identification of Flash Drought and Multivariate Drought Risk Probability Assessment in the Pearl River Basin, China

Flash drought (FD) is characterized by the rapid onset and development of drought conditions. It usually occurs during the growing seasons, causing more severe impacts on agriculture and society than the slowly-evolving droughts. Based on the Standard Evaporative Stress Ratio (SESR), this study presents an assessment of the spatio-temporal variability of the joint return periods of FD characteristics in the Pearl River basin (PRB), southern China. Three FD characteristics (i.e., duration D, intensity I, peak P) are extracted at each 0.25o×0.25o grid point over the PRB by the Runs theory. Four marginal distribution functions (Gamma, Exponential, Generalized Extreme Value and Lognormal) are used to fit FD characteristics, while three Archimedean Copula functions (Clayton, Frank and Gumbel) are used for generating the joint distributions of various paired FD characteristics. The results indicate that Lognormal is the best-fitted marginal distribution function of FD characteristics in most parts of PRB, while Frank and Clayton are the best-fitted Copula of the joint PDFs of three pairs of FD characteristics in most parts of PRB. During 1953–2013, the FD events are more frequent in eastern PRB (> 40 events) than western PRB (<10 events), and larger FD characteristics (D and I) are also found in eastern PRB than western PRB. The return period of each FD characteristic is smaller in eastern PRB than western PRB, leading to smaller joint return periods of three paired FD characteristics (D-I, D-P, P-I) in eastern PRB than western PRB. Overall, our results suggest that the risk of FD is gradually increased from the west to the east of the PRB.

A maximum entropy copula-based frequency analysis method for assessing bivariate drought risk: a case study of the Kaidu River Basin

In this study, a maximum entropy copula-based frequency analysis (MECFA) method is developed through integrating maximum entropy, copulas and frequency analysis into a general framework. The advantages of MECFA are that the marginal modeling requires no assumption and joint distribution preserves the dependence structure of drought variables. MECFA is applied to assessing bivariate drought frequency in the Kaidu River Basin, China. Results indicate that the Kaidu River Basin experienced 28 drought events during 1958–2011, and drought inter-arrival time is 10.8 months. The average duration is 6.2 months (severity 4.6), and the most severe drought event lasts for 35 months (severity 41.2) that occurred from June 1977 to March 1980. Results also disclose that hydrological drought index (HDI) 1 is suitable for drought frequency analysis in target year of return periods of 5 and 10, HDI 3, HDI 6 and HDI 12 are fit for the target year of return periods of 20, 50 and 100. The joint return period can be used as the upper bound of the target return period, and the joint return period that either duration or severity reaches the drought threshold can be used as the lower bound of the target return period.

Global compound floods from precipitation and storm surge: Hazards and the roles of cyclones

During simultaneous or successive occurrences of precipitation and storm surges, the interplay of the two types of extremes can exacerbate the impact to a greater extent than either of them in isolation. The compound flood hazards from precipitation and storm surges vary across regions of the world because of the various weather conditions. By analyzing in-situ observations of precipitation and storm surges across the globe, we found that the return periods of compound floods with marginal values exceeding the 98.5th percentile (i.e., equivalent to a joint return period of 12 years if the marginal variables are independent) are < 2 years in most areas, while those in northern Europe are > 8 years due to weaker dependence. Our quantitative assessment shows that cyclones (i.e., tropical cyclones (TCs) and extratropical cyclones (ETCs)) are the major triggers of compound floods. More than 80% of compound floods in East Asia and > 50% of those in the Gulf of Mexico and northern Australia are associated with TCs, while in northern Europe and the higher latitude coast of North America, ETCs contribute to the majority of compound floods (i.e., 80%). Weather patterns characterized by deep low pressure, cyclonic wind, and abundant precipitable water content are conducive to the occurrence of compound floods. Extreme precipitation and extreme storm surges over Europe tend to occur in different months, which explains the relatively lower probability of compound floods in Europe. The comprehensive hazard assessment of global compound floods in this study serves as an important reference for flood risk management in coastal regions across the globe.

Copula based Assessment of Climate Extremes across India: Past and Future

&lt;p&gt;Climate change significantly influences the global hydrological cycle and consequently affects climatic extremes. The present study is focussed upon varying patterns of climate extremes using observed daily precipitation (1989-2019), daily temperature from Global Meteorological Forcing Dataset (GMFD) (1985-2016) and simulated daily meteorological forcing data (2025-2055 and 2065-2095) of 21 GCMs attained from the statistically downscaled dataset, NEX-GDDP (NASA Earth Exchange Global Daily Downscaled Projections) under RCP4.5 and RCP8.5 scenario across India. The copula method was employed to estimate the joint return period based on different climate extreme indices. Here, we found that R20, R95p and CWD attain an increasing trend and CDD mostly shows a decreasing trend in major segments of country in future. Based upon the 10-year joint return periods (1989-2019), it is found that parts of north-western, north-eastern, southern, western region and Western Ghats are highly prone towards floods and a large portion of the country is susceptible to co-occurrence of floods and droughts. Moreover, the study shows that many regions with less vulnerability towards precipitation extremes would become more vulnerable in future. Furthermore, TXx, TNx, TX90p, TN90p, TNn and TXn are found to be significantly increasing in future except increasing during 2065-2095 under RCP4.5 predominantly across the country. And, TX10p and TN10p follows a significantly decreasing trend in future across the except exhibiting a decreasing trend during 2065-2095 under RCP4.5, throughout the country. With the projected increase in hot days/nights, the frequency of concurrence of extreme number of hot days (TX90p) and nights (TN90p) within a year would increase in the future across the country. The present study provides useful information on the regional distribution of climate extremes and how they might change in the future. This information can further contribute to facilitate an effective planning strategy to improve resilience towards climate extremes.&lt;/p&gt;

Swell wave progression in the English Channel: implications for coastal monitoring

Energetic swell waves, particularly when they coincide with high water levels, can present significant coastal hazards. To better understand and predict these risks, analysis of the sea levels and waves that generate these events and the resulting coastal impacts is essential. Two energetic swell events, neither of which were predicted by modelled flood forecasts, occurred in quick succession in the English Channel. The first event, on 30 January 2021, produced moderate significant wave heights at or just below the 0.25 year return period along the southwest English coast, but combined with significant swell caused overtopping at East Beach in West Bay and at Chesil Beach. The second event, on 1 February 2021, generated the highest wave energy periods measured at many locations along the southern English coastline and, at high water, caused waves to run up over the promenades at Poole Bay and Christchurch Bay and caused overtopping at Hayling Island. Both events are described in detail, and their spatial footprints are mapped through a joint return period analysis using a copula function. It is found that typical joint return period analysis of water level and significant wave height underestimates potential impacts, while a joint consideration of water level and wave power (P) describes the 31 January event better and a joint consideration of water level and energy period (Te) best describes the 1 February event. Therefore, it is recommended that Te and P are adopted for coastal monitoring purposes, and that future studies further explore the use of both parameters for swell monitoring.

Multivariate Assessment of Low-Flow Hazards via Copulas: The Case Study of the Çoruh Basin (Turkey)

Bivariate modeling and hazard assessment of low flows are performed exploiting copulas. 7-day low flows observed, respectively, in the upper, middle and lower parts of the Çoruh basin (Turkey) are examined, considering three pairs of certified stations located in different sub-basins. A thorough statistical analysis indicates that the GEV distribution can be used to model the marginal behavior of the low-flow. The joint distributions at each part are modeled via a dozen of copula families. As a result, the Husler–Reiss copula adequately fits the joint low flows in the upper part, while the t-Student copula turns out to best fit the other parts. In order to assess the low-flow hazard, these copulas are then used to compute joint return periods and failure probabilities under a critical bivariate “AND” hazard scenario. The results indicate that the middle and lower parts of the Çoruh basin are likely to experience the largest drought hazards. As a novelty, the statistical tools used allow to objectively quantify drought threatening in a thorough multivariate perspective, which involves distributional analysis, frequency analysis (return periods) and hazard analysis (failure probabilities).

Analysis and Application of Drought Characteristics Based on Theory of Runs and Copulas in Yunnan, Southwest China

Drought is a complex natural disaster phenomenon. It is of great significance to analyze the occurrence and development of drought events for drought prevention. In this study, two drought characteristic variables (the drought duration and severity) were extracted by using the Theory of Runs based on four drought indexes (i.e., the percentage of precipitation anomaly, the standardized precipitation index, the standardized precipitation evapotranspiration index and the improved comprehensive meteorological drought index). The joint distribution model of drought characteristic variables was built based on four types of Archimedean copulas. The joint cumulative probability and the joint return period of drought events were analyzed and the relationship between the drought characteristics and the actual crop drought reduction area was also studied. The results showed that: (1) The area of the slight drought and the extreme drought were both the zonal increasing distribution from northeast to southwest in Yunnan Province from 1960 to 2015. The area of the high frequency middle drought was mainly distributed in Huize and Zhanyi in Northeast Yunnan, Kunming in Central Yunnan and some areas of Southwest Yunnan, whereas the severe drought was mainly occurred in Deqin, Gongshan and Zhongdian in Northwest Yunnan; (2) The drought duration and severity were fitted the Weibull and Gamma distribution, respectively and the Frank copula function was the optimal joint distribution function. The Drought events were mostly short duration and high severity, long duration and low severity and short duration and low severity. The joint cumulative probability and joint return period were increased with the increase of drought duration and severity; (3) The error range between the theoretical return period and the actual was 0.1–0.4 a. The year of the agricultural disaster can be accurately reflected by the combined return period in Yunnan Province. The research can provide guidelines for the agricultural management in the drought area.