Compound Events Research Articles

Managing compound events in the COVID-19 era: A critical analysis of gaps, measures taken, and challenges

Since the beginning of 2020, the focus has predominantly been on the prevention and control of the COVID-19 pandemic. However, the 'new normal' has drastically altered responses to other hazards, underscoring the need to prepare and plan for complex, multi-risk scenarios. Nevertheless, there's limited literature on disaster preparedness and response for compound hazard scenarios, particularly pandemic-natural hazard hybrids. The few studies that have explored concurrent hazards during the COVID-19 pandemic have largely focused on developed, high-income countries. Yet, compound events can exacerbate pre-existing socio-economic vulnerabilities in developing countries, straining systems and causing disproportionate impacts. This study addresses this lacuna by examining (1) emergency preparedness and response measures for Sri Lanka's Southwest and Northeast monsoons during the COVID-19 pandemic, and (2) the feasibility of current Disaster Risk Reduction (DRR) strategies for managing compound pandemic-natural hazard events in Sri Lanka. The research involves a desk-based policy analysis of disaster and health policies, key informant interviews with 26 officials, and focus group discussions with Public Health Inspectors from Ratnapura, Jaffna, Matara, and Gampaha. Findings indicate that while significant steps were taken, including impact scenario analyses, stakeholder meetings, and revised response measures, challenges such as resource constraints and limited capacity persisted. This study further demonstrates that the country's existing DRR strategies are characterised by gaps that may hinder capacities to effectively manage compound hazards. The findings of this study therefore encourage the implementation of structural changes and anticipatory action that adequately account for the complexity of risk supported by cross-sectoral collaboration. The study particularly highlights the importance of proactive scenario-based planning, developing composite risk matrices that account for multiple dimensions of vulnerability, fostering cross-sectoral and cross-level collaboration, and adapting existing early warning systems to effectively manage compound hazard scenarios.

The ocean losing its breath under the heatwaves

The world’s oceans are under threat from the prevalence of heatwaves caused by climate change. Despite this, there is a lack of understanding regarding their impact on seawater oxygen levels - a crucial element in sustaining biological survival. Here, we find that heatwaves can trigger low-oxygen extreme events, thereby amplifying the signal of deoxygenation. By utilizing in situ observations and state-of-the-art climate model simulations, we provide a global assessment of the relationship between the two types of extreme events in the surface ocean (0–10 m). Our results show compelling evidence of a remarkable surge in the co-occurrence of marine heatwaves and low-oxygen extreme events. Hotspots of these concurrent stressors are identified in the study, indicating that this intensification is more pronounced in high-biomass regions than in those with relatively low biomass. The rise in the compound events is primarily attributable to long-term warming primarily induced by anthropogenic forcing, in tandem with natural internal variability modulating their spatial distribution. Our findings suggest the ocean is losing its breath under the influence of heatwaves, potentially experiencing more severe damage than previously anticipated.

Increased stress from compound drought and heat events on vegetation

Compound drought and heat events (CDHEs), which are frequently occurring compound extreme climate events, have garnered considerable attention because of their detrimental effects on ecosystems. However, the intricacies of the spatial and temporal distributions of different durations of compound events, along with the variability in vegetation responses remain unclear. Here, we delineated the CDHEs based on meteorological observation data and investigated the spatial and temporal characteristics of CDHEs from 1993 to 2020 using the Theil-Sen trend test and Mann–Kendall nonparametric test. Furthermore, we utilized sliding correlation analysis to evaluate the impacts of CDHEs on vegetation among different climatic regions and ecosystems. Our findings indicate significant increasing trends in both the frequency and persistence of CDHEs from 1993 to 2020. The average trend of CDHEs frequency across different duration periods amounted to 13.80 %/decade. The fractional contribution of CDHEs lasting more than three days exhibited a significant increase, with an average trend of 2.00 %/decade. We also observed that vegetation is most significantly affected by compound events lasting 5–9 days. During the study period, the geographical extent of vegetation significantly impacted by CDHEs expanded by 0.89 %, correlation strength increased by 0.02, and lag time decreased by 0.25 months. These insights highlight the growing impact of CDHEs on vegetation under climate change, improving our understanding of vegetation responses to these compound events.

The application of the analysis framework for compound extreme event dependencies in China

AbstractThe escalation of compound extreme events has resulted in noteworthy economic and property losses. Recognizing the intricate interconnections among these events has become imperative. To tackle this challenge, we have formulated a comprehensive framework for the systematic analysis of their dependencies. This framework consists of three steps. (1) Define extreme events using Mahalanobis distance thresholds. (2) Represent dependencies among multiple extreme events through a point process‐based method. (3) Verify dependencies with residual tail coefficients, determining the final dependency structure. Applying this framework to assess the extreme dependence of precipitation on wind speed and temperature in China, revealed four distinct dependency structures. In northern, Jianghuai, and southern China, precipitation heavily relies on wind speed, while temperatures maintain relative independence. In northeastern and northwestern China, precipitation exhibits relative independence, yet a notable dependence exists between temperatures and wind speed. In southwestern China, precipitation strongly depends on temperature, while wind speed remains relatively independent. The Qinghai–Tibet Plateau region displays a significant dependence relationship among precipitation, wind speed, and temperature, with weaker dependence between extreme wind speed and temperature. This framework is instrumental for analyzing dependencies among extreme values in compound events.

Atmospheric preconditions investigation of wet-cold compound events in Greece between 1980 and 2004

Atmospheric preconditions investigation of wet-cold compound events in Greece between 1980 and 2004

Projection of Compound Wind and Precipitation Extreme Events in the Iberian Peninsula Based on CMIP6

This study aims to investigate the potential changes in the co-occurrence of strong precipitation and wind events over the Iberian Peninsula using simulations from the Coupled Model Intercomparison Project (CMIP) Phase 6 under two scenarios (SSP2 − 4.5 and SSP5 − 8.5). Projected changes indicate a significant regional variability during all seasons. In winter, the western regions are projected to experience an increase in compound events as the century progresses under both scenarios, with a significantly larger area being affected by the end of the century. In spring, summer, and autumn, a general decline in the occurrence of these events is anticipated throughout the century, accompanied by a reduction in the area affected by them. However, in the northwesternmost area (Galicia), an increase in the occurrence of compound events is expected during the spring towards the end of the century, particularly under the SSP5-8.5 scenario.

Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble

Abstract. ​​​​​​​Severe floods with extreme return periods of 100 years and beyond have been observed in several large rivers in Bavaria in the last 3 decades. Flood protection structures are typically designed based on a 100-year event, relying on statistical extrapolations of relatively short observation time series while ignoring potential temporal non-stationarity. However, future precipitation projections indicate an increase in the frequency and intensity of extreme rainfall events, as well as a shift in seasonality. This study aims to examine the impact of climate change on the 100-year flood (HF100) events of 98 hydrometric gauges within hydrological Bavaria. A hydrological climate change impact (CCI) modeling chain consisting of a regional Single Model Initial-condition Large Ensemble (SMILE) and a single hydrological model was created. The 50 equally probable members of the Canadian Regional Climate Model version 5 large ensemble (CRCM5-LE) were used to drive the hydrological model WaSiM (Water balance Simulation Model) to create a hydro-SMILE. As a result, a database of 1500 model years (50 members × 30 years) per investigated time period was established for extreme value analysis (EVA) to illustrate the benefit of the hydro-SMILE approach for a robust estimation of HF100 based on annual maxima (AM) and to examine the CCI on the frequency and magnitude of HF100 in different discharge regimes under a strong-emission scenario (RCP8.5). The results demonstrate that the hydro-SMILE approach provides a clear advantage for a robust estimation of HF100 using the empirical probability of 1500 AM compared to its estimation using the generalized extreme value (GEV) distribution of 1000 samples of typically available time series sizes of 30, 100, and 200 years. Thereby, by applying the hydro-SMILE framework, the uncertainty from statistical estimation can be reduced. The study highlights the added value of using hydrological SMILEs to project future flood return levels. The CCI of HF100 varies for different flow regimes, with snowmelt-driven catchments experiencing severe increases in frequency and magnitude, leading to unseen extremes that impact the distribution. Pluvial regimes show a lower intensification or even decline. The dynamics of HF100 driving mechanisms depict a decline in snowmelt-driven events in favor of rainfall-driven events, an increase in events driven by convective rainfall, and almost no change in the ratio between single-driver and compound events towards the end of the century.

Dynamic evolution characteristics and hazard assessment of compound drought/waterlogging and low temperature events for maize

Hazard assessment is fundamental in the field of disaster risk management. With the increase in global warming, compound water and temperature events have become more frequent. Current research lacks risk assessments of low temperatures and their compound events, necessitating relevant hazard assessment work to improve the accuracy and diversity of maize disaster prevention and mitigation strategies. This study comparatively analyzed the dynamic evolution characteristics and hazards of compound drought/waterlogging and low temperature events (CDLEs and CWLEs) for maize in the Songliao Plain during different growth periods from 1981 to 2020. First, composite drought/waterlogging and low temperature magnitude indices (CDLMI and CWLMI) were constructed to quantify the intensity of CDLEs and CWLEs by fitting non-exceedance probabilities. Next, static and dynamic hazard assessment models were developed by fitting probability density and cumulative probability density curves to CDLMI and CWLMI. The results showed that the correlations between SPRI and LTI across different decades were mainly negative during the three growth periods. The hazard ratings for both CDLEs and CWLEs were relatively high in the northern part of the study area, consistent with the higher occurrence, duration, and severity of both CDLEs and CWLEs at higher latitudes. Relative to 2001–2010, the center of gravity of hazard shifted southward for CDLEs and northward for CWLEs in 2011–2020. The mean duration, frequency, and hazard were generally higher for CWLEs, but CDLEs were associated with more severe maize yield reductions. This study provides new insights into compound disaster risk assessment, and the research methodology can be generalized to other agricultural growing areas to promote sustainable development of agricultural systems and food security.

Attribution of the unprecedented summer 2022 compound marine and terrestrial heatwave in the Northwest Pacific

In boreal summer (July–August) 2022, an unprecedented marine heatwave (MHW) occurred in the northwest Pacific Ocean (NWP), while a record-breaking terrestrial heatwave (THW) hit the Yangtze River Basin (YRB). The temperature anomalies caused by this compound MHW-THW event exceeded climatology by 2.5 standard deviations (SDs), breaking the historical record for nearly 100 years, with severe impacts on the ecosystems and social economy. To investigate the underlying causes, we explored the potential roles of anthropogenic forcing, atmospheric circulation, and ‘triple-dip’ La Niña on this compound event using the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulations. Results indicate that the 2022-like compound MHW-THW event was extremely unlikely to happen without anthropogenic warming, and that such extreme heatwaves were governed by the climatic mean temperature rather than changes in temperature variability. Notably, the anticyclone circulation patterns and associated high-pressure systems (i.e. western North Pacific subtropical high (WNPSH) and South Asian high (SAH)) increase the probability of a 2022-like MHW-THW event by 3.7 times. However, the La Niña phase has no significant effect on the occurrence probability of such events. We further estimate that the 2022-like MHW-THW event will become 7.5 and 11.4 times more likely under the SSP3-7.0 scenario by the middle and end of the 21st century, respectively. This study demonstrates the contribution of anthropogenic climate change and natural variability to the occurrence of compound MHW-THW events and highlights the urgent need to build mitigation strategies for compound MHW-THW events.

Heat, humidity and health impacts: how causal diagrams can help tell the complex story

The global health burden associated with exposure to heat is a grave concern and is projected to further increase under climate change. While physiological studies have demonstrated the role of humidity alongside temperature in exacerbating heat stress for humans, epidemiological findings remain conflicted. Understanding the intricate relationships between heat, humidity, and health outcomes is crucial to inform adaptation and drive increased global climate change mitigation efforts. This article introduces ‘directed acyclic graphs’ (DAGs) as causal models to elucidate the analytical complexity in observational epidemiological studies that focus on humid-heat-related health impacts. DAGs are employed to delineate implicit assumptions often overlooked in such studies, depicting humidity as a confounder, mediator, or an effect modifier. We also discuss complexities arising from using composite indices, such as wet-bulb temperature. DAGs representing the health impacts associated with wet-bulb temperature help to understand the limitations in separating the individual effect of humidity from the perceived effect of wet-bulb temperature on health. General examples for regression models corresponding to each of the causal assumptions are also discussed. Our goal is not to prioritize one causal model but to discuss the causal models suitable for representing humid-heat health impacts and highlight the implications of selecting one model over another. We anticipate that the article will pave the way for future quantitative studies on the topic and motivate researchers to explicitly characterize the assumptions underlying their models with DAGs, facilitating accurate interpretations of the findings. This methodology is applicable to similarly complex compound events.

Severe compound events of low wind and cold temperature for the British power system

AbstractBritain's power system has shifted towards a major contribution from wind energy. However, wind is highly variable, and exceptionally low wind events can simultaneously occur with cold conditions, which increase demand. These conditions can pose a threat for the security of energy supply. Here we use bias‐corrected wind supply data and the estimated temperature‐related part of demand to analyse events of potential weather‐related energy shortfall based on the historic meteorological record. We conduct sensitivity studies with varying scenarios of Britain's total wind energy capacity and the temperature sensitivity of national demand. These scenarios are estimates for present‐day conditions as well as potential future changes of the power system. We apply a new methodology to estimate the potential severity of an event for the power system, and analyse the atmospheric conditions associated with the most severe events. We find that events of potentially severe shortfall are relatively rare and short‐lived, and often occur with an atmospheric pattern broadly resembling a negative North Atlantic Oscillation. This broad tendency emerges from a wide range of individual daily weather patterns that cause cold and still conditions. With an increase in wind capacity, it is likely that severe events will become rarer, although the most severe days of the record are relatively insensitive to changes in wind supply and temperature sensitivity of demand under our assumptions.

Climatic Challenges in the Growth Cycle of Winter Wheat in the Huang-Huai-Hai Plain: New Perspectives on High-Temperature–Drought and Low-Temperature–Drought Compound Events

Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random forest models, and copula methods to analyze the spatial and temporal distribution of these events and their impact on winter wheat in the Huang-Huai-Hai Plain from 1982 to 2020. High-temperature–drought events increased in frequency and expanded from north to south, with about 40% of observation stations recording such events from 2001 to 2020. In contrast, low-temperature–drought events decreased in frequency, affecting up to 80% of stations, but with lower frequency than high-temperature–drought events. Sensitivity analyses show winter wheat is most responsive to maximum and minimum temperature changes, with significant correlations to drought and temperature extremes. Copula analysis indicates temperature extremes and drought severity are crucial in determining compound event probability and return periods. High-temperature–drought events are likely under high temperatures and mild drought, while low-temperature–drought events are more common under low temperatures and mild drought. These findings highlight the need for effective agricultural adaptation strategies to mitigate future climate change impacts.

Compound climate change risk analysis for port infrastructures

Ports serve as essential nodes for coastal and maritime transportation and are key sources of income and economic activity in coastal zones. This significance, combined with their location in coastal areas, which are prone to climate-driven impacts, makes them highly susceptible to climate change effects. In this work, a climate change risk assessment methodology for port infrastructures that is focused on compound events analysis is presented. This approach is based on a spatial high-resolution probabilistic framework that enables the evaluation of port performance evolution under the effects of climate change. This assessment draws from a multimodel characterization of the evolution of several climate drivers for different emission scenarios and time horizons. It accounts for multiple port infrastructure risks and considers the compound effects of climate drivers and the interdependencies of infrastructures as complex systems. Performance indicators are developed for the physical assets and services at port locations on a highly granular scale, thus allowing port managers and planners to allocate reserves and develop adaptation plans that reduce climate change risks in the operations of maritime transportation nodes based on port performance forecasts. The methodology is implemented in two case studies set in the northern coast of Spain, demonstrating its applicability and replicability among several locations and scales.

Lightning-induced fire regime in Portugal based on satellite-derived and in situ data

Fire databases typically contain information regarding the location, timing, and duration of fire occurrences, as well as the cause (natural or human-induced). These databases allow for the analysis and understanding of the circumstances surrounding the ignition and propagation of wildfires, being highly relevant when addressing fire suppression and management plans, or for improvement of prevention policies. In Portugal, a large number of fires in the official database have unknown causes, which limits the understanding about the relevance of each fire cause, in particular the role of lightning on the ignition of fires over the country. The objective of this paper is twofold: first, we investigated the spatial-temporal variability of lightning-induced fires from 2003 to 2020. Then, we evaluate the feasibility of using remote sensing data as a surrogate for identifying fire causes, through validation with the fire database. Our results revealed that lightning-ignited fires represent an even smaller fraction of all fire events than mentioned in the latest official report about fire causes in the country, accounting for only 1 % of the fire occurrences and 4.6 % of the total burned area in the 18-year period under analysis. The months of June to September comprise 91 % of all lightning fires, which occur more frequently in the northern, remote regions of the country and at relatively high altitudes. Moreover, lightning ignitions originate fires larger than the global average and contributed significantly to the total area burned during the extreme 2003 and 2017 fire seasons. Its importance in these extreme years suggests that lightning can trigger large fires when in conjunction with compound events such as droughts and heatwaves. When compared with in-situ databases, the application of remote sensing data reproduced the seasonality of lightning-ignited fires, but failed to account for the contribution of smaller fires, which represent the majority of occurrences in the Portuguese fire database. Finally, we discuss the implications of our findings for the improved assessment of fire risks, causes, and impacts in Portugal.

Compound events of heatwave and dust storm in the Taklamakan Desert

Compound events of heatwave and dust storm in the Taklamakan Desert

Compound droughts under climate change in Switzerland

Abstract. The co-occurrence of meteorological, agricultural, and hydrological droughts (multivariate compound droughts) in Switzerland during growing season is problematic due to limitations in water abstractions from rivers during low-flow periods, while at the same time the need for irrigation is high. We analyse compound droughts for 52 catchments in Switzerland during the extended summer season (May–October) using the transient climate and hydrological scenarios for Switzerland (CH2018 and Hydro-CH2018) for both a scenario with mitigation (representative concentration pathway 2.6 (RCP2.6), 8 model chains) and a scenario without mitigation (RCP8.5, 20 model chains). In the RCP8.5 scenario the number of compound drought days is projected to significantly increase by mid-century across all greater regions of Switzerland. The increased frequency is mainly a result of more frequent events (significant) rather than longer event durations (non-significant). Models generally agree on the sign of change. By 2085, compound drought events are projected to occur in median once per catchment per extended summer season north of the Alps and every 1–2 years south of the Alps. Further, the increases in compound drought days mainly occur between May–October, leading to a shift in the main agricultural production season and a more pronounced seasonality with the highest occurrence probabilities between mid-July and the beginning of October. Coupled to the increase in days and events, significantly more catchments are projected to be affected by compound droughts at the same time. In the RCP2.6 (mitigation) scenario, the increase in the number of compound drought days and events is not significant by the end of the 21st century. In comparison with RCP8.5, the number of compound drought days is reduced by 50 %–55 % north of the Alps and by up to 75 % south of the Alps by the end of the century. This emphasizes the need for coordinated adaptation in combination with mitigation measures taken at an early stage.

Assessing the potential of compound extreme storm surge and precipitation along China's coastline

The occurrence of extreme storm surges and precipitation simultaneously or successively can lead to compound flooding. The interaction between extreme storm surges and precipitation holds significant implications for understanding the potential contributing to compound flood risk in coastal areas. This study examines the likelihood of joint occurrence for compound extreme storm surges and precipitation along the China's coastline using observations and model data sets based on tail dependence. We assess the complete characteristics of the tail dependence from observations at the spatio-temporal scale. Subsequently, we perform a principal component analysis to classify the compound flood into 6 synoptic patterns based on the mean sea level pressure data in two typical points (Xiamen and Shijiusuo). We analyze the structure dependence of both observed and simulated surge data and compare the dependence between the historical and the future tail dependence. The result shows that the Yellow Sea and East China Sea exhibit higher dependence compared to the Bohai Sea and South China Sea. The southeastern sea of China has more significant seasonal variation in dependence relative to the northern sea of China. The result indicates that the dominant weather type in Xiamen is associated with low sea pressure and high land pressure, while the type in Shijiusuo is located at the southern edge of a low-pressure center. Projected probabilities of future compound events (2015–2050) have shown substantial increases of 23.9%, 25.38%, 58.21%, and 119.47% over the current period (1979–2014), according to climate models CMCC-CM2-VHR4, GFDL-CMC192-SST, ECEarth3P-HR, and HadGEM3-GC31-HM, respectively. These findings emphasize the correlation between extreme precipitation and storm surges, contributing to a deeper understanding of the compound flood and promoting disaster prevention and control.

The Beast from the East and drought of summer 2018: an example of compound event impacts upon Ireland's agricultural sector

AbstractThe most noticeable and damaging manifestation of human‐induced climate change is the increasing likelihood of certain extreme weather events. As defined in the IPCC sixth assessment report, compound extremes can lead to extreme impacts that are much larger than the sum of the impacts due to the occurrence of individual extremes alone. Of these compound weather events, events occurring in close succession have received the least attention to date. In this paper, we explore such a case study of successive events affecting the agricultural sector in Ireland arising from the winter storm of 2018, dubbed the ‘Beast from the East’, followed by the drought of summer 2018 which combined yielded a substantial reduction in agricultural productivity over 2018.

The compound impact of rainfall, river flow and sea level on a watercourse through a coastal city: Methodology in making

Due to climate change, future weather conditions will become more extreme. During recent years, several severe damages have been caused by heavy rainfalls in combination with riverine events. Even though the effects of compound events are known to be influential for flood hazard, the method for investigating these types of events is a novel area of expertise. In this study, a methodology was developed to investigate a watercourse, acting as a part of a stormwater drainage system in an urban coastal area, in a hydrodynamic model to find areas prone to flooding. The method was applied for Ståstorpsån in Trelleborg, Sweden. The model was a unified model for seasonal variability and compound events with scenarios developed based on series of data representing normal values of the boundary conditions rainfall, river flow and sea level. The result was analysed graphically and statistically as a flood hazard. The data used was based on data collected during the past 10 years for rain and sea level and 16 years of simulated river flow. The constructed rain events from gauge data all had a return time of less than 10 years. Therefore, the chosen events are considered to represent normal levels. For Trelleborg, the results from the hydrodynamic model indicate that compound events will increase the flood hazard with anincreasing time horizon. The visual analysis converges with earlier flood events, and hotspots are generally seen around bridges and culverts. For the studied area, there is a large seasonal variation in the flood hazard and with climate change, all seasons will cause more severe flood hazards. The effects experienced during a summer event, which is the most severe event today, are to be expected for all seasons in 2100. The effect seen during summer eventsis a combination of all three drivers. However, rain intensity is likely to be more influential for normal events. When a certain threshold value for sea level is reached, sea level becomes the most influential driver, overtaking the other drivers in importance.

Projected changes in heat, extreme precipitation, and their spatially compound events over China’s coastal lands and seas through a high-resolution climate models ensemble

China’s coastal lands and seas are highly susceptible to the changing environment due to their dense population and frequent economic activities. These areas experience more significant impacts from climate change-induced extreme events than elsewhere. The most noticeable effects of climate change are extreme high temperatures and extreme precipitation. We employ an ensemble of RCMs (Regional Climate Models) to investigate and project changes in temperature, precipitation, and Compound Heat-Precipitation Extreme events (CHPEs) over selected China’s coastal lands and seas for both historical (1985–2004) and future periods (2080–2099). The multi-model ensemble projects that daily temperature extremes will increase by 2.9 °C to 5.4 °C across China’s coastal lands and seas, with land areas showing a higher temperature increase than marine areas. Extreme precipitation shows a high geographical heterogeneity with a 2.8–3.9 mm d−1 reduction over the 15–25°N marine areas while a 2.2–5.4 mm d−1 increment over the 25°N-35°N land areas. We use the Clausius–Clapeyron relationship to reveal that the peak of daily extreme precipitation will increase by 2–7 mm d−1 and the temperature at which extreme precipitation peaks will increase by 2 °C to 6 °C by warming. The land area of 25–30°N has the highest peak precipitation increase of 9.87 mm d−1 and a peak temperature increase of 6 °C. As precipitation extremes intensify with daily temperature extremes increase, CHPEs are projected to occur more frequently over both land and marine areas. Compared with the historical period, the frequency of CHPEs will increase by 40.9%-161.2% over marine areas, and by 36.2%-163.6% over land areas in the future. The 15–20°N area has the highest frequency increase of CHPE events, and the 25–30°N area has the largest difference in frequency increase under two different scenarios. It indicated that the 25–30°N area will be more easily affected by climate change.