Abstract
Measurements from the South Dakota School of Mines and Technology T-28 hail-penetrating aircraft are analyzed using recently developed data processing techniques with the goals of identifying where the large hail is found relative to vertical motion and improving the detection of hail microphysical properties from radar. Hail particle size distributions (PSD) and environmental conditions (temperature, relative humidity, liquid water content, air vertical velocity) were digitally collected by the T28 between 1995 and 2003 and synthesized by Detwiler et al. (2012). The PSD were forward-modeled by Cecchini et al. (2022) to simulate the radar reflectivity of the PSD at multiple radar wavelengths.
The T-28 penetrated temperatures primarily between 0 and ā10 Ā°C. The largest hailstones were sampled near the updraft/downdraft interface. Liquid water contents were highest in the updraft cores, whereas total (liquid + frozen) water contents were highest near the updraft/downdraft interface. The fitted properties of the PSD, intercept and slope, are directly related to each other, but do not show any dependence on the region of the hailstorm where sampled. The PSD measurements and the radar reflectivity calculations at multiple radar wavelengths facilitated the development of relationships between the PSD bulk propertiesāhail kinetic energy and kinetic energy fluxāand the radar reflectivity. Rather than using the oft-assumed sphericity and solid ice physical properties, actual measurements of hail properties are used in the analysis. Results from the maximum estimated size of hail (MESH) and vertical integrated liquid water (VIL) algorithms are evaluated based on this analysis.
Abstract
Measurements from the South Dakota School of Mines and Technology T-28 hail-penetrating aircraft are analyzed using recently developed data processing techniques with the goals of identifying where the large hail is found relative to vertical motion and improving the detection of hail microphysical properties from radar. Hail particle size distributions (PSD) and environmental conditions (temperature, relative humidity, liquid water content, air vertical velocity) were digitally collected by the T28 between 1995 and 2003 and synthesized by Detwiler et al. (2012). The PSD were forward-modeled by Cecchini et al. (2022) to simulate the radar reflectivity of the PSD at multiple radar wavelengths.
The T-28 penetrated temperatures primarily between 0 and ā10 Ā°C. The largest hailstones were sampled near the updraft/downdraft interface. Liquid water contents were highest in the updraft cores, whereas total (liquid + frozen) water contents were highest near the updraft/downdraft interface. The fitted properties of the PSD, intercept and slope, are directly related to each other, but do not show any dependence on the region of the hailstorm where sampled. The PSD measurements and the radar reflectivity calculations at multiple radar wavelengths facilitated the development of relationships between the PSD bulk propertiesāhail kinetic energy and kinetic energy fluxāand the radar reflectivity. Rather than using the oft-assumed sphericity and solid ice physical properties, actual measurements of hail properties are used in the analysis. Results from the maximum estimated size of hail (MESH) and vertical integrated liquid water (VIL) algorithms are evaluated based on this analysis.
Abstract
Arctic communities are experienced with severe weather, but impacts can still be serious, particularly when the intensity or persistence of hazardous conditions is extreme. Such was the case for the community of Clyde River (Kangiqtugaapik), Nunavut, Canada, which experienced 33 blizzard days during winter 2021/22ālikely the most at Clyde River since at least 1978/79. Blizzard conditions resulted from unusually frequent high winds rather than excessive snowfall. The most severe stretch included eight blizzard days over an 11-day period, with top wind gusts of 98 km hā1. Winds caused severe drifting, covering homes and blocking streets. Broken heavy equipment, including snow-clearing machines, compounded the impacts, leaving homes without essential services like water delivery and sewage pump-out for days. Residents reported the storms and resulting impacts as some of the worst in memory. The drifting and volume of snow, combined with the lack of available resources to manage it, obliged the community to declare a state of emergency. Projections of increased Arctic precipitation and extreme weather events points to the need for communities to have proper resources and supports, including preparedness and adaptation and mitigation strategies, so they can be better equipped to handle storm and blizzard impacts such as those experienced at Clyde River in the winter of 2021/22. Additional steps that can be implemented to better support and prepare communities include investing in preparedness planning, expanded and enhanced weather information and services, community land-based programming to transfer Inuit knowledge and skills, assessing the usefulness of current forecasts, and new approaches to community planning.
Significance Statement
In this study, we consider the winter of 2021/22, during which the community of Clyde River (Kangiqtugaapik), Nunavut experienced 33 days with blizzard conditionsāmore than any other year since at least 1978/79. Blizzards are characterized by strong winds and blowing snow. Low visibility impedes travel, and drifting snow blocks roads and can bury equipment and buildings. In this case, broken snow-clearing equipment and other infrastructure challenges also hampered the communityās ability to respond, and residents went days without essential services. Several studies suggest that extreme winds will become more common in the Baffin Bay region in the future. This study demonstrates the need for proper resourcing of communities for preparedness, response, and adaptation strategies, especially with the possibility of extreme winter weather becoming more common.
Abstract
Arctic communities are experienced with severe weather, but impacts can still be serious, particularly when the intensity or persistence of hazardous conditions is extreme. Such was the case for the community of Clyde River (Kangiqtugaapik), Nunavut, Canada, which experienced 33 blizzard days during winter 2021/22ālikely the most at Clyde River since at least 1978/79. Blizzard conditions resulted from unusually frequent high winds rather than excessive snowfall. The most severe stretch included eight blizzard days over an 11-day period, with top wind gusts of 98 km hā1. Winds caused severe drifting, covering homes and blocking streets. Broken heavy equipment, including snow-clearing machines, compounded the impacts, leaving homes without essential services like water delivery and sewage pump-out for days. Residents reported the storms and resulting impacts as some of the worst in memory. The drifting and volume of snow, combined with the lack of available resources to manage it, obliged the community to declare a state of emergency. Projections of increased Arctic precipitation and extreme weather events points to the need for communities to have proper resources and supports, including preparedness and adaptation and mitigation strategies, so they can be better equipped to handle storm and blizzard impacts such as those experienced at Clyde River in the winter of 2021/22. Additional steps that can be implemented to better support and prepare communities include investing in preparedness planning, expanded and enhanced weather information and services, community land-based programming to transfer Inuit knowledge and skills, assessing the usefulness of current forecasts, and new approaches to community planning.
Significance Statement
In this study, we consider the winter of 2021/22, during which the community of Clyde River (Kangiqtugaapik), Nunavut experienced 33 days with blizzard conditionsāmore than any other year since at least 1978/79. Blizzards are characterized by strong winds and blowing snow. Low visibility impedes travel, and drifting snow blocks roads and can bury equipment and buildings. In this case, broken snow-clearing equipment and other infrastructure challenges also hampered the communityās ability to respond, and residents went days without essential services. Several studies suggest that extreme winds will become more common in the Baffin Bay region in the future. This study demonstrates the need for proper resourcing of communities for preparedness, response, and adaptation strategies, especially with the possibility of extreme winter weather becoming more common.
Abstract
Groundwater and climate interact in a two-way manner. Precipitation ultimately controls groundwater recharge and, conversely, groundwater may influence climate through evapotranspiration. Yet very few global climate models or Earth system models actually simulate groundwater flows. And while the expected impacts of climate change on groundwater resources are the subject of a growing concern, global-scale groundwaterāclimate feedbacks have received very little attention so far. Here we show that the integration of unconfined aquifers in a global climate model can regionally affect the climate change signal on temperatures and precipitation. We assess the impact of groundwater under preindustrial and 4xCO2 conditions (after climate stabilization). In both cases, we find that groundwater has a cooling and a wetting effect in certain regions of the world. In eastern Europe, both these impacts are stronger in the warmer climate (4xCO2 forcing) where the presence of groundwater reduces the frequency of summer heatwaves by 40%, compared to a 15% reduction in the preindustrial world. This work constitutes one of the very first global assessments of the potential feedbacks of groundwater on climate change. Our results support the idea that groundwater should be represented in global climate models and Earth system models, as it does indeed play an active role in the climate system.
Abstract
Groundwater and climate interact in a two-way manner. Precipitation ultimately controls groundwater recharge and, conversely, groundwater may influence climate through evapotranspiration. Yet very few global climate models or Earth system models actually simulate groundwater flows. And while the expected impacts of climate change on groundwater resources are the subject of a growing concern, global-scale groundwaterāclimate feedbacks have received very little attention so far. Here we show that the integration of unconfined aquifers in a global climate model can regionally affect the climate change signal on temperatures and precipitation. We assess the impact of groundwater under preindustrial and 4xCO2 conditions (after climate stabilization). In both cases, we find that groundwater has a cooling and a wetting effect in certain regions of the world. In eastern Europe, both these impacts are stronger in the warmer climate (4xCO2 forcing) where the presence of groundwater reduces the frequency of summer heatwaves by 40%, compared to a 15% reduction in the preindustrial world. This work constitutes one of the very first global assessments of the potential feedbacks of groundwater on climate change. Our results support the idea that groundwater should be represented in global climate models and Earth system models, as it does indeed play an active role in the climate system.
Abstract
Point predictions of hydroclimatic processes through nonlinear modeling tools are associated with uncertainty. The main goal of this research was to construct prediction intervals (PIs) for nonlinear artificial neural network (ANN)-based models of evaporation and the standardized precipitation index (SPI). These are two critical indicators for climate for four stations in Iran (i.e., Tabriz, Urmia, Ardabil, and Ahvaz) to qualify their predicted uncertainty values (UVs). We used classical techniques of bootstrap (BS), mean variance estimation (MVE), and Delta, as well as an optimization-based method of lower upper bound estimation (LUBE), to construct and compare the PIs. The wavelet-based denoising method was also adopted to denoise input data, enhancing the modeling performance. The obtained results indicate the ability of the BS and LUBE methods to estimate the uncertainty bound. The Delta method mostly failed to find the desired coverage due to its narrow PIs. On the other hand, the MVE method, due to its wide bound, did not convey valuable information about uncertainty. According to the obtained results, denoising the input vector could enhance the PI quality in the modeling of the SPI by up to 76%. It was more prominent than reducing the UV for evaporation models, which was observed the most at the Ardabil station, up to 30%. The inherently more random nature of drought than the evaporation process was interpreted as the cause of this reaction. From the results, Urmia station seems the riskiest regarding drought ventures.
Significance Statement
The point predictions of evaporation and precipitation (in the form of SPI) are subject to uncertainty. The best way is to provide an area with the highest contingency as a prediction interval. The reduction in the width of such an interval leads to increased confidence in explaining and predicting these processes. We investigated different methods and found that by utilizing the optimization-based method for denoised inputs, uncertainty values of the output were conveyed better. Additionally, we concluded that the more random the process, the greater its uncertainty. A primary sense of the drought risk was made from the uncertainty perspective.
Abstract
Point predictions of hydroclimatic processes through nonlinear modeling tools are associated with uncertainty. The main goal of this research was to construct prediction intervals (PIs) for nonlinear artificial neural network (ANN)-based models of evaporation and the standardized precipitation index (SPI). These are two critical indicators for climate for four stations in Iran (i.e., Tabriz, Urmia, Ardabil, and Ahvaz) to qualify their predicted uncertainty values (UVs). We used classical techniques of bootstrap (BS), mean variance estimation (MVE), and Delta, as well as an optimization-based method of lower upper bound estimation (LUBE), to construct and compare the PIs. The wavelet-based denoising method was also adopted to denoise input data, enhancing the modeling performance. The obtained results indicate the ability of the BS and LUBE methods to estimate the uncertainty bound. The Delta method mostly failed to find the desired coverage due to its narrow PIs. On the other hand, the MVE method, due to its wide bound, did not convey valuable information about uncertainty. According to the obtained results, denoising the input vector could enhance the PI quality in the modeling of the SPI by up to 76%. It was more prominent than reducing the UV for evaporation models, which was observed the most at the Ardabil station, up to 30%. The inherently more random nature of drought than the evaporation process was interpreted as the cause of this reaction. From the results, Urmia station seems the riskiest regarding drought ventures.
Significance Statement
The point predictions of evaporation and precipitation (in the form of SPI) are subject to uncertainty. The best way is to provide an area with the highest contingency as a prediction interval. The reduction in the width of such an interval leads to increased confidence in explaining and predicting these processes. We investigated different methods and found that by utilizing the optimization-based method for denoised inputs, uncertainty values of the output were conveyed better. Additionally, we concluded that the more random the process, the greater its uncertainty. A primary sense of the drought risk was made from the uncertainty perspective.
Abstract
It has been well known that the preceding winter ENSO affects the atmospheric convection over the tropical western North Pacific (WNP) in summer, which has important impacts on Asian climate. However, more than half of the interannual variance in tropical WNP convection cannot be explained by the ENSO. This study separates the WNP convection into two components: independent of and dependent on the preceding winter ENSO, and compares the anomalies associated with these two components. The linear regression results indicate that the independent convection suppression corresponds to significant cyclonic anomalies over East Asia in both the lower and upper troposphere, and correspondingly a southward displacement of upper-tropospheric East Asian westerly jet. By contrast, these circulation anomalies are weakened for the dependent convection suppression, which is more closely related to the lower-tropospheric cyclonic anomalies over the Indian Ocean. Accordingly, the independent and dependent components exert distinct impacts on rainfall and temperature in Asia. Specifically, the independent suppression corresponds to more significantly enhanced rainfall in the subtropical East Asia compared with the dependent one. Moreover, there are colder surface air temperatures in the mid-latitude East Asia for the independent suppression and warmer temperatures in South and Southeast Asia for the dependent suppression. Further analyses suggest that the circulation and climate anomalies for the independent component are mainly contributed by July and August, while those for the dependent component become weak from June to August. These results can be helpful for a better understanding of summer Asian climate variability and predictability.
Abstract
It has been well known that the preceding winter ENSO affects the atmospheric convection over the tropical western North Pacific (WNP) in summer, which has important impacts on Asian climate. However, more than half of the interannual variance in tropical WNP convection cannot be explained by the ENSO. This study separates the WNP convection into two components: independent of and dependent on the preceding winter ENSO, and compares the anomalies associated with these two components. The linear regression results indicate that the independent convection suppression corresponds to significant cyclonic anomalies over East Asia in both the lower and upper troposphere, and correspondingly a southward displacement of upper-tropospheric East Asian westerly jet. By contrast, these circulation anomalies are weakened for the dependent convection suppression, which is more closely related to the lower-tropospheric cyclonic anomalies over the Indian Ocean. Accordingly, the independent and dependent components exert distinct impacts on rainfall and temperature in Asia. Specifically, the independent suppression corresponds to more significantly enhanced rainfall in the subtropical East Asia compared with the dependent one. Moreover, there are colder surface air temperatures in the mid-latitude East Asia for the independent suppression and warmer temperatures in South and Southeast Asia for the dependent suppression. Further analyses suggest that the circulation and climate anomalies for the independent component are mainly contributed by July and August, while those for the dependent component become weak from June to August. These results can be helpful for a better understanding of summer Asian climate variability and predictability.
Abstract
Broadcast meteorologists are essential in the communication of National Weather Service (NWS) warnings to the public. Therefore, it is imperative to include them in a user-centered approach for the design and implementation of new warning products. Forecasting a Continuum of Environmental Threats (FACETs) will modernize the way meteorologists forecast and communicate NWS warning information to the general public using rapidly updating probabilistic hazard information (PHI). Storm-scale PHI consists of probabilistic forecasts for severe wind/hail, tornadoes, and lightning hazards. Hence, NWS warnings would have the capacity to be supplemented by a quantitative or qualitative likelihood of hazard occurrence. The researchers conducting this study wanted to know what broadcast meteorologists thought about the inclusion of this likelihood information and how it could impact their decision-making and communication process. Using a nationwide survey, this team of researchers first asked broadcast meteorologists about their current practices for severe weather coverage using NWS watches and warnings. Next, broadcast meteorologists were introduced to multiple iterations of PHI prototypes and queried for their input. Findings indicated that broadcast meteorologists already face a complex decision-making and communication process under todayās warning paradigm. In addition, respondents were split on whether to explicitly communicate probabilities with their viewers. Respondentsā choices were also somewhat inconclusive regarding nomenclature, definitions of PHI and representations of PHI with warning polygons. These results suggest that PHI should feature user-driven, customizable options to fulfill broadcast meteorologistsā needs and that the iterative nature of the research-and-development process of PHI should continue.
Significance Statement
Broadcast meteorologists are vital communicators of dangerous weather to the public, leading researchers to study them more closely. Using a nationwide survey, this team of researchers wanted to know how broadcast meteorologists talk about tornadoes, large hail, and high winds to their viewers under todayās system of National Weather Service warnings. Survey findings indicated that broadcast meteorologists face a complex decision-making process when communicating dangerous weather. Any effort to modernize the current warning system, such as including hazard probability, should consider this complex process. Modernization should complement the role of broadcast meteorologists to ultimately serve the public and user-driven options should be a key component of any probabilistic information that is included in a future National Weather Service warning system.
Abstract
Broadcast meteorologists are essential in the communication of National Weather Service (NWS) warnings to the public. Therefore, it is imperative to include them in a user-centered approach for the design and implementation of new warning products. Forecasting a Continuum of Environmental Threats (FACETs) will modernize the way meteorologists forecast and communicate NWS warning information to the general public using rapidly updating probabilistic hazard information (PHI). Storm-scale PHI consists of probabilistic forecasts for severe wind/hail, tornadoes, and lightning hazards. Hence, NWS warnings would have the capacity to be supplemented by a quantitative or qualitative likelihood of hazard occurrence. The researchers conducting this study wanted to know what broadcast meteorologists thought about the inclusion of this likelihood information and how it could impact their decision-making and communication process. Using a nationwide survey, this team of researchers first asked broadcast meteorologists about their current practices for severe weather coverage using NWS watches and warnings. Next, broadcast meteorologists were introduced to multiple iterations of PHI prototypes and queried for their input. Findings indicated that broadcast meteorologists already face a complex decision-making and communication process under todayās warning paradigm. In addition, respondents were split on whether to explicitly communicate probabilities with their viewers. Respondentsā choices were also somewhat inconclusive regarding nomenclature, definitions of PHI and representations of PHI with warning polygons. These results suggest that PHI should feature user-driven, customizable options to fulfill broadcast meteorologistsā needs and that the iterative nature of the research-and-development process of PHI should continue.
Significance Statement
Broadcast meteorologists are vital communicators of dangerous weather to the public, leading researchers to study them more closely. Using a nationwide survey, this team of researchers wanted to know how broadcast meteorologists talk about tornadoes, large hail, and high winds to their viewers under todayās system of National Weather Service warnings. Survey findings indicated that broadcast meteorologists face a complex decision-making process when communicating dangerous weather. Any effort to modernize the current warning system, such as including hazard probability, should consider this complex process. Modernization should complement the role of broadcast meteorologists to ultimately serve the public and user-driven options should be a key component of any probabilistic information that is included in a future National Weather Service warning system.
Abstract
High resolution airborne cloud Doppler radars such as the W-Band Wyoming Cloud Radar (WCR) have, since the 1990s, investigated cloud microphysical, kinematic, and precipitation structures down to 30-m resolution. These measurements revolutionized our understanding of fine-scale cloud structure and the scales at which cloud processes occur. Airborne cloud Doppler radars may also resolve cloud turbulent eddy structure directly at 10-meter scales. To date, cloud turbulence has been examined as variances (Schwartz et al. 2019) and dissipation rates (Strauss et al. 2015) at coarser resolution than individual pulse volumes. The present work advances the potential of near-vertical pulse pair Doppler spectrum width as a metric for turbulent air motion. Doppler spectrum width has long been used to investigate turbulent motions from ground-based remote sensors. However, complexities of airborne Doppler radar and spectral broadening resulting from platform and hydrometeor motions have limited airborne radar spectrum width measurements to qualitative interpretation only. Here we present the first quantitative validation of spectrum width from an airborne cloud radar. Echoes with signal-to-noise ratio greater than 10 dB yield spectrum width values that strongly correlate with retrieved mean Doppler variance for a range of non-convective cloud conditions. Further, Doppler spectrum width within turbulent regions of cloud also shows good agreement with in-situ eddy dissipation rate (EDR) and gust probe variance. However, the use of pulse pair estimated spectrum width as a metric for turbulent air motion intensity is only suitable for turbulent air motions more energetic than the magnitude of spectral broadening, estimated to be < 0.4 m sā1 for the WCR in these cases.
Abstract
High resolution airborne cloud Doppler radars such as the W-Band Wyoming Cloud Radar (WCR) have, since the 1990s, investigated cloud microphysical, kinematic, and precipitation structures down to 30-m resolution. These measurements revolutionized our understanding of fine-scale cloud structure and the scales at which cloud processes occur. Airborne cloud Doppler radars may also resolve cloud turbulent eddy structure directly at 10-meter scales. To date, cloud turbulence has been examined as variances (Schwartz et al. 2019) and dissipation rates (Strauss et al. 2015) at coarser resolution than individual pulse volumes. The present work advances the potential of near-vertical pulse pair Doppler spectrum width as a metric for turbulent air motion. Doppler spectrum width has long been used to investigate turbulent motions from ground-based remote sensors. However, complexities of airborne Doppler radar and spectral broadening resulting from platform and hydrometeor motions have limited airborne radar spectrum width measurements to qualitative interpretation only. Here we present the first quantitative validation of spectrum width from an airborne cloud radar. Echoes with signal-to-noise ratio greater than 10 dB yield spectrum width values that strongly correlate with retrieved mean Doppler variance for a range of non-convective cloud conditions. Further, Doppler spectrum width within turbulent regions of cloud also shows good agreement with in-situ eddy dissipation rate (EDR) and gust probe variance. However, the use of pulse pair estimated spectrum width as a metric for turbulent air motion intensity is only suitable for turbulent air motions more energetic than the magnitude of spectral broadening, estimated to be < 0.4 m sā1 for the WCR in these cases.
Evaluation of Ocean Currents Observed from Autonomous Surface VehiclesAbstract
The development of autonomous surface vehicles, such as the Boeing Liquid Robotics Wave Glider, has revolutionized our ability to collect surface oceanālower atmosphere observations, a crucial step toward developing better physical understanding of upper-ocean and airāsea interaction processes. However, due to the wave-following nature of these vehicles, they experience rapid shifting, rolling, and pitching under the action of surface waves, making motion compensation of observations of ocean currents particularly challenging. We present an evaluation of the accuracy of Wave Gliderābased ADCP measurements by comparing them with coincident and collocated observations collected from a bottom-mounted ADCP over the course of a week-long experiment. A novel motion compensation method, tailored to wave-following surface vehicles, is presented and compared with standard approaches. We show that the use of an additional position and attitude sensor (GPS/IMU) significantly improves the accuracy of the observed currents.
Abstract
The development of autonomous surface vehicles, such as the Boeing Liquid Robotics Wave Glider, has revolutionized our ability to collect surface oceanālower atmosphere observations, a crucial step toward developing better physical understanding of upper-ocean and airāsea interaction processes. However, due to the wave-following nature of these vehicles, they experience rapid shifting, rolling, and pitching under the action of surface waves, making motion compensation of observations of ocean currents particularly challenging. We present an evaluation of the accuracy of Wave Gliderābased ADCP measurements by comparing them with coincident and collocated observations collected from a bottom-mounted ADCP over the course of a week-long experiment. A novel motion compensation method, tailored to wave-following surface vehicles, is presented and compared with standard approaches. We show that the use of an additional position and attitude sensor (GPS/IMU) significantly improves the accuracy of the observed currents.
Abstract
The frequent occurrence of extreme cold waves under climate change has attracted widespread attention. Based on the Japanese 55-year Reanalysis daily dataset from 1958 to 2021, we use a newly developed dynamic metric, the local finite-amplitude wave activity (LWA), to explore the precursory signals, outburst conditions, and key dynamic features of extreme cold waves over eastern China from the perspective of synoptic climatology. The statistical results show that approximately 40% of extreme cold waves have the following features. First, the formation of significant positive LWA anomalies over the BalkhashāBaikal region is an evident precursory signal, which is accompanied by significant cold surface air temperature anomalies that accumulate over mid- and high-latitude Eurasia. Second, the appearance of extreme positive LWA anomalies over the region east of Lake Baikal (ELB) is necessary for subsequent outbursts of extreme cold waves. These extreme positive LWA anomalies indicate the meridionally enhanced planetary trough over East Asia and advection of the accumulated cold air masses southeastward to eastern China. Third, the evident positive change in the LWA anomalies over the ELB is mainly attributable to the convergence of the zonal LWA flux due to the zonal wind in the eddy-free state and Stokes drift flux over the eastern area of the ELB and the convergence of the meridional eddy heat flux over the western area. This study demonstrates that the LWA could be used as a simple and feasible metric for monitoring and forecasting extreme cold waves.
Significance Statement
Enhanced waviness in circulation usually occurs before and during the outburst of extreme cold waves over eastern China. With a state-of-the-art diagnostic tool, the local finite-amplitude wave activity (LWA), the present study reveals both precursory signals and outburst conditions of these extreme cold events from the perspective of synoptic climatology. This study not only deepens our understanding of the dynamic process for extreme cold events over eastern China but also offers a method for monitoring and forecasting those extreme events. Our work also provides a method for studying other extreme climate events that are closely related to large-amplitude circulation waviness over the middle and high latitudes.
Abstract
The frequent occurrence of extreme cold waves under climate change has attracted widespread attention. Based on the Japanese 55-year Reanalysis daily dataset from 1958 to 2021, we use a newly developed dynamic metric, the local finite-amplitude wave activity (LWA), to explore the precursory signals, outburst conditions, and key dynamic features of extreme cold waves over eastern China from the perspective of synoptic climatology. The statistical results show that approximately 40% of extreme cold waves have the following features. First, the formation of significant positive LWA anomalies over the BalkhashāBaikal region is an evident precursory signal, which is accompanied by significant cold surface air temperature anomalies that accumulate over mid- and high-latitude Eurasia. Second, the appearance of extreme positive LWA anomalies over the region east of Lake Baikal (ELB) is necessary for subsequent outbursts of extreme cold waves. These extreme positive LWA anomalies indicate the meridionally enhanced planetary trough over East Asia and advection of the accumulated cold air masses southeastward to eastern China. Third, the evident positive change in the LWA anomalies over the ELB is mainly attributable to the convergence of the zonal LWA flux due to the zonal wind in the eddy-free state and Stokes drift flux over the eastern area of the ELB and the convergence of the meridional eddy heat flux over the western area. This study demonstrates that the LWA could be used as a simple and feasible metric for monitoring and forecasting extreme cold waves.
Significance Statement
Enhanced waviness in circulation usually occurs before and during the outburst of extreme cold waves over eastern China. With a state-of-the-art diagnostic tool, the local finite-amplitude wave activity (LWA), the present study reveals both precursory signals and outburst conditions of these extreme cold events from the perspective of synoptic climatology. This study not only deepens our understanding of the dynamic process for extreme cold events over eastern China but also offers a method for monitoring and forecasting those extreme events. Our work also provides a method for studying other extreme climate events that are closely related to large-amplitude circulation waviness over the middle and high latitudes.
Abstract
Severe floods and droughts, including their back-to-back occurrences (weather whiplash), have been increasing in frequency and severity around the world. Improved understanding of systematic changes in hydrological extremes is essential for preparation and adaptation. In this study, we identified and quantified extreme wet and dry events globally by applying a clustering algorithm to terrestrial water storage (TWS) data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (FO). The most intense events, ranked using an intensity metric, often reflect impacts of large-scale oceanic oscillations such as the EL NiƱo Southern Oscillation and consequences of climate change. Severity of both wet and dry events, represented by standardized TWS anomalies, increased significantly in most cases, likely associated with intensification of wet and dry weather regimes in a warmer world, and consequently, exhibited strongest correlation with global temperature. In the Dry climate, the number of wet events decreased while the number of dry events increased significantly, suggesting a drying trend that may be attributed to climate variability and possible increases in irrigation and reliance on groundwater. In the Continental climate where temperature has risen faster than global average, dry events increased significantly. Characteristics of extreme events often showed strong correlations with global temperature, especially when averaged over all climates. These results suggest changes in hydrological extremes and underscore the importance of quantifying total water storage changes when studying hydrological extremes. Extending the GRACE/FO record, which spans 2002-present, is essential to continuously tracking changes in TWS and hydrological extremes.
Abstract
Severe floods and droughts, including their back-to-back occurrences (weather whiplash), have been increasing in frequency and severity around the world. Improved understanding of systematic changes in hydrological extremes is essential for preparation and adaptation. In this study, we identified and quantified extreme wet and dry events globally by applying a clustering algorithm to terrestrial water storage (TWS) data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (FO). The most intense events, ranked using an intensity metric, often reflect impacts of large-scale oceanic oscillations such as the EL NiƱo Southern Oscillation and consequences of climate change. Severity of both wet and dry events, represented by standardized TWS anomalies, increased significantly in most cases, likely associated with intensification of wet and dry weather regimes in a warmer world, and consequently, exhibited strongest correlation with global temperature. In the Dry climate, the number of wet events decreased while the number of dry events increased significantly, suggesting a drying trend that may be attributed to climate variability and possible increases in irrigation and reliance on groundwater. In the Continental climate where temperature has risen faster than global average, dry events increased significantly. Characteristics of extreme events often showed strong correlations with global temperature, especially when averaged over all climates. These results suggest changes in hydrological extremes and underscore the importance of quantifying total water storage changes when studying hydrological extremes. Extending the GRACE/FO record, which spans 2002-present, is essential to continuously tracking changes in TWS and hydrological extremes.
