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During 2013, multiple tornadoes occurred across Australia, leading to 147 injuries and considerable damage. This prompted speculation as to the frequency of these events in Australia, and whether 2013 constituted a record year. Leveraging media reports, public accounts, and the Bureau of Meteorology observational record, 69 tornadoes were identified for the year in comparison to the official count of 37 events. This identified set and the existing historical record were used to establish that, in terms of spatial distribution, 2013 was not abnormal relative to the existing climatology, but numerically exceeded any year in the bureau’s record. Evaluation of the environments in which these tornadoes formed illustrated that these conditions included tornado environments found elsewhere globally, but generally had a stronger dependence on shear magnitude than direction, and lower lifting condensation levels. Relative to local environment climatology, 2013 was also not anomalous. These results illustrate a range of tornadoes associated with cool season, tropical cyclone, east coast low, supercell tornado, and low shear/storm merger environments. Using this baseline, the spatial climatology from 1980 to 2019 as derived from the nonconditional frequency of favorable significant tornado parameter environments for the year is used to highlight that observations are likely an underestimation. Applying the results, discussion is made of the need to expand observing practices, climatology, forecasting guidelines for operational prediction, and improve the warning system. This highlights a need to ensure that the general public is appropriately informed of the tornado hazard in Australia, and provide them with the understanding to respond accordingly.

Hailstorms are dangerous and costly phenomena that are expected to change in response to a warming climate. In this Review, we summarize current knowledge of climate change effects on hailstorms. As a result of anthropogenic warming, it is generally anticipated that low-level moisture and convective instability will increase, raising hailstorm likelihood and enabling the formation of larger hailstones; the melting height will rise, enhancing hail melt and increasing the average size of surviving hailstones; and vertical wind shear will decrease overall, with limited influence on the overall hailstorm activity, owing to a predominance of other factors. Given geographic differences and offsetting interactions in these projected environmental changes, there is spatial heterogeneity in hailstorm responses. Observations and modelling lead to the general expectation that hailstorm frequency will increase in Australia and Europe, but decrease in East Asia and North America, while hail severity will increase in most regions. However, these projected changes show marked spatial and temporal variability. Owing to a dearth of long-term observations, as well as incomplete process understanding and limited convection-permitting modelling studies, current and future climate change effects on hailstorms remain highly uncertain. Future studies should focus on detailed processes and account for non-stationarities in proxy relationships. Hailstorms are dangerous phenomena that are expected to change in response to a warming climate. This Review summarizes current knowledge of climate change effects on hailstorms, details the uncertainties and highlights future research directions.

Long-term trends in the historical frequency of environments supportive of atmospheric convection are unclear, and only partially follow the expectations of a warming climate. This uncertainty is driven by the lack of unequivocal changes in the ingredients for severe thunderstorms (i.e., conditional instability, sufficient low-level moisture, initiation mechanism, and vertical wind shear). ERA5 hybrid-sigma data allow for superior characterization of thermodynamic parameters including convective inhibition, which is very sensitive to the number of levels in the lower troposphere. Using hourly data we demonstrate that long-term decreases in instability and stronger convective inhibition cause a decline in the frequency of thunderstorm environments over the southern United States, particularly during summer. Conversely, increasingly favorable conditions for tornadoes are observed during winter across the Southeast. Over Europe, a pronounced multidecadal increase in low-level moisture has provided positive trends in thunderstorm environments over the south, central, and north, with decreases over the east due to strengthening convective inhibition. Modest increases in vertical wind shear and storm-relative helicity have been observed over northwestern Europe and the Great Plains. Both continents exhibit negative trends in the fraction of environments with likely convective initiation. This suggests that despite increasing instability, thunderstorms in a warming climate may be less likely to develop due to stronger convective inhibition and lower relative humidity. Decreases in convective initiation and resulting precipitation may have long-term implications for agriculture, water availability, and the frequency of severe weather such as large hail and tornadoes. Our results also indicate that trends observed over the United States cannot be assumed to be representative of other continents.

As lightning-detection records lengthen and the efficiency of severe weather reporting increases, more accurate climatologies of convective hazards can be constructed. In this study we aggregate flashes from the National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) with severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data on a common grid of 0.25° and 1-h steps. Each year approximately 75–200 thunderstorm hours occur over the southwestern, central, and eastern United States, with a peak over Florida (200–250 h). The activity over the majority of Europe ranges from 15 to 100 h, with peaks over Italy and mountains (Pyrenees, Alps, Carpathians, Dinaric Alps; 100–150 h). The highest convective activity over continental Europe occurs during summer and over the Mediterranean during autumn. The United States peak for tornadoes and large hail reports is in spring, preceding the maximum of lightning and severe wind reports by 1–2 months. Convective hazards occur typically in the late afternoon, with the exception of the Midwest and Great Plains, where mesoscale convective systems shift the peak lightning threat to the night. The severe wind threat is delayed by 1–2 h compared to hail and tornadoes. The fraction of nocturnal lightning over land ranges from 15% to 30% with the lowest values observed over Florida and mountains (~10%). Wintertime lightning shares the highest fraction of severe weather. Compared to Europe, extreme events are considerably more frequent over the United States, with maximum activity over the Great Plains. However, the threat over Europe should not be underestimated, as severe weather outbreaks with damaging winds, very large hail, and significant tornadoes occasionally occur over densely populated areas.

In this study we investigate convective environments and their corresponding climatological features over Europe and the United States. For this purpose, National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) data, ERA5 hybrid-sigma levels, and severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data were combined on a common grid of 0.25° and 1-h steps over the period 1979–2018. The severity of convective hazards increases with increasing instability and wind shear (WMAXSHEAR), but climatological aspects of these features differ over both domains. Environments over the United States are characterized by higher moisture, CAPE, CIN, wind shear, and midtropospheric lapse rates. Conversely, 0–3-km CAPE and low-level lapse rates are higher over Europe. From the climatological perspective severe thunderstorm environments (hours) are around 3–4 times more frequent over the United States with peaks across the Great Plains, Midwest, and Southeast. Over Europe severe environments are the most common over the south with local maxima in northern Italy. Despite having lower CAPE (tail distribution of 3000–4000 J kg−1 compared to 6000–8000 J kg−1 over the United States), thunderstorms over Europe have a higher probability for convective initiation given a favorable environment. Conversely, the lowest probability for initiation is observed over the Great Plains, but, once a thunderstorm develops, the probability that it will become severe is much higher compared to Europe. Prime conditions for severe thunderstorms over the United States are between April and June, typically from 1200 to 2200 central standard time (CST), while across Europe favorable environments are observed from June to August, usually between 1400 and 2100 UTC.

The tornado outbreak of 21–23 January 2017 caused 20 fatalities, more than 200 injuries, and over a billion dollars in damage in the Southeast United States. The event occurred concurrently with a record-breaking warm Gulf of Mexico (GoM) basin. This article explores the influence that warm GoM sea surface temperatures (SSTs) had on the tornado outbreak. Backward trajectory analysis, combined with a Lagrangian-based moisture-attribution algorithm, reveals that the tornado outbreak’s moisture predominantly originated from the southeast GoM and the northwest Caribbean Sea. We used the WRF Model to generate a control simulation of the event and explore the response to perturbed SSTs. With the aid of a tornadic storm proxy derived from updraft helicity, we show that the 21–23 January 2017 tornado outbreak exhibits sensitivity to upstream SSTs during the first day of the event. Warmer SSTs across remote moisture sources and adjacent waters increase tornado frequency, in contrast to cooler SSTs, which reduce tornado activity. Upstream SST sensitivity is reduced once convection is ongoing and modifying local moisture and instability availability. Our results highlight the importance of air–sea interactions before airmass advection toward the continental United States. The complex and nonlinear nature of the relationship between upstream SSTs and local precursor environments is also discussed.

Large-scale weather patterns favorable for tornado occurrence have been understood for many decades. Yet prediction of tornadoes, especially at extended lead periods of more than a few days, remains an arduous task, partly due to the space and time scales involved. Recent research has shown that tropical convection, sea surface temperatures, and the Earth-relative atmospheric angular momentum can induce jet stream configurations that may increase or decrease the probability of tornado frequency across the United States. Applying this recent theoretical work in practice, on 1 March 2015, the authors began the Extended-Range Tornado Activity Forecast (ERTAF) project, with the following goals: 1) to have a map room–style discussion of the anticipated atmospheric state in the 2–3-week lead window; 2) to predict categorical level of tornado activity in that lead window; and 3) to learn from the forecasts through experience by identifying strengths and weaknesses in the methods, as well as identifying any potential scientific knowledge gaps. Over the last five years, the authors have shown skill in predicting U.S. tornado activity two to three weeks in advance during boreal spring. Unsurprisingly, skill is shown to be greater for forecasts spanning week 2 versus week 3. This manuscript documents these forecasting efforts, provides verification statistics, and shares the challenges and lessons learned from predicting tornado activity on the subseasonal time scale.

Hail size records are analyzed at 2254 stations in China and a hail size climatology is developed based on gridded hail observations for the period 1960–2015. It is found that the annual percentiles of hail size records changed sharply and national-wide after 1980, therefore two periods, 1960–79 and 1980–2015, are studied. There are some similarities between the two periods in terms of the characteristics of hail size such as the spatial distribution patterns of mean annual maximum hail size and occurrence week of annual maximum hail size. The 1980–2015 period had higher observation density than the 1960–79 period, but showed smaller mean annual maximum hail size, especially in northern China. In the majority of grid boxes, the annual maximum hail size experienced a decreasing trend during the 1980–2015 period. A Gumbel extreme value model is fitted to each grid box to estimate the return periods of maximum hail size. The scale and location parameter of the fitted Gumbel distributions are higher in eastern China than in western China, thereby reflecting a greater likelihood of large hail in eastern China. In southern China, the maximum hail size exceeds 127 mm for a 10-yr return period, whereas in northern China maximum hail size exceeds this threshold for a 50-yr return period. The Gumbel model is found to potentially underestimate the maximum hail size for certain return periods, but provides a more informed picture of the spatial distribution of extreme hail size and the regional differences.

The response of severe convective storms to a warming climate is poorly understood outside of a few well studied regions. Here, projections from seven global climate models from the CMIP6 archive, for both historical and future scenarios, are used to explore the global response in variables that describe favorability of conditions for the development of severe storms. The variables include convective available potential energy (CAPE), convection inhibition (CIN), 0–6 km vertical wind shear (S06), storm relative helicity (SRH), and covariate indices (i.e., severe weather proxies) that combine them. To better quantify uncertainty, understand variable sensitivity to increasing temperature, and present results independent from a specific scenario, we consider changes in convective variables as a function of global average temperature increase across each ensemble member. Increases to favorable convective environments show an overall frequency increases on the order of 5%–20% per °C of global temperature increase, but are not regionally uniform, with higher latitudes, particularly in the Northern Hemisphere, showing much larger relative changes. The driving mechanism of these changes is a strong increase in CAPE that is not offset by factors that either resist convection (CIN), or modify the likelihood of storm organization (S06, SRH). Severe weather proxies are not the same as severe weather events. Hence, their projected increases will not necessarily translate to severe weather occurrences, but they allow us to quantify how increases in global temperature will affect the occurrence of conditions favorable to severe weather.

Meteotsunamis are both a well-known and poorly understood phenomenon. In particular, the influence of and disturbance by meteotsunami on coastal wetlands is largely unknown. This paper documents tw...

Tornadic thunderstorms rely on the availability of sufficient low-level moisture, but the source regions of that moisture have not been explicitly demarcated. Using the NOAA Air Resources Laboratory HYSPLIT model and a Lagrangian-based diagnostic, moisture attribution was conducted to identify the moisture source regions of tornadic convection. This study reveals a seasonal cycle in the origins and advection patterns of water vapor contributing to winter and spring tornado-producing storms (1981–2017). The Gulf of Mexico is shown to be the predominant source of moisture during both winter and spring, making up more than 50% of all contributions. During winter, substantial moisture contributions for tornadic convection also emanate from the western Caribbean Sea (>19%) and North Atlantic Ocean (>12%). During late spring, land areas (e.g., soil and vegetation) of the contiguous United States (CONUS) play a more influential role (>24%). Moisture attribution was also conducted for nontornadic cases and tornado outbreaks. Findings show that moisture sources of nontornadic events are more proximal to the CONUS than moisture sources of tornado outbreaks. Oceanic influences on the water vapor content of air parcels were also explored to determine if they can increase the likelihood of an air mass attaining moisture that will eventually contribute to severe thunderstorms. Warmer sea surface temperatures were generally found to enhance evaporative fluxes of overlying air parcels. The influence of atmospheric features on synoptic-scale moisture advection was also analyzed; stronger extratropical cyclones and Great Plains low-level jet occurrences lead to increased meridional moisture flux.

The climatology of (severe) thunderstorm days is investigated on a pan-European scale for the period of 1979–2017. For this purpose, sounding measurements, surface observations, lightning data from ZEUS (a European-wide lightning detection system) and European Cooperation for Lightning Detection (EUCLID), ERA-Interim, and severe weather reports are compared and their respective strengths and weaknesses are discussed. The research focuses on the annual cycles in thunderstorm activity and their spatial variability. According to all datasets thunderstorms are the most frequent in the central Mediterranean, the Alps, the Balkan Peninsula, and the Carpathians. Proxies for severe thunderstorm environments show similar patterns, but severe weather reports instead have their highest frequency over central Europe. Annual peak thunderstorm activity is in July and August over northern, eastern, and central Europe, contrasting with peaks in May and June over western and southeastern Europe. The Mediterranean, driven by the warm waters, has predominant activity in the fall (western part) and winter (eastern part) while the nearby Iberian Peninsula and eastern Turkey have peaks in April and May. Trend analysis of the mean annual number of days with thunderstorms since 1979 indicates an increase over the Alps and central, southeastern, and eastern Europe with a decrease over the southwest. Multiannual changes refer also to changes in the pattern of the annual cycle. Comparison of different data sources revealed that although lightning data provide the most objective sampling of thunderstorm activity, short operating periods and areas devoid of sensors limit their utility. In contrast, reanalysis complements these disadvantages to provide a longer climatology, but is prone to errors related to modeling thunderstorm occurrence and the numerical simulation itself.

Aridland springs maintain groundwater-dependent habitats for aquatic and terrestrial species. San Solomon Spring (Texas, USA) is part of a regional karst spring complex in the Chihuahuan Desert that supports several species of federal and state conservation interest. However, drought, climatic variability, and groundwater abstraction threaten discharge and water quality. In the surrounding Delaware Basin, expansion in unconventional oil and gas development using hydraulic fracturing may increase demands on aquifers that also provide flows to the springs. A critical knowledge gap limiting habitat conservation and sustainable groundwater abstraction is that the flow system is not well understood. While the source of most spring discharge is from a Pleistocene-recharged regional flow system, evidence suggests that a modern local flow component provides fresh water influx. However, the exact sources, mechanisms, and timing of localized recharge are unknown. To address these questions, this study combined long-term in-situ spring water quality monitoring (specific conductance, turbidity, and temperature) data with weather station-corrected 4 km gridded precipitation data to quantify the lag response at San Solomon Springs to mesoscale storm events and to delineate potential local recharge zones. Between April 2011 and March 2012, 26 event-flow responses were documented, with an average lag of 43 days between storm event and spring response. Response time varied depending on storm magnitude, spatial extent, and antecedent soil moisture conditions. Cross-correlation analysis of spatially distributed precipitation indicated zones of potential local recharge in the mountain block/mountain front zones and alluvial channels issuing from the Davis Mountains. Some local flow paths appear to cross known watershed boundaries, suggesting that groundwater abstraction in sensitive capture zones should be managed carefully to maintain spring flows and conserve habitats.

Globally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

Assessments of spatiotemporal severe hailfall characteristics using hail reports are plagued by serious limitations in report databases, including biases in reported sizes, occurrence time, and location. Multiple studies have used Next Generation Weather Radar (NEXRAD) network observations or environmental hail proxies from reanalyses. Previous work has specifically utilized the single-polarization radar parameter maximum expected size of hail (MESH). In addition to previous work being temporally limited, updates are needed to include recent improvements that have been made to MESH. This study aims to quantify severe hailfall characteristics during a 23-yr period, markedly longer than previous studies, using both radar observations and reanalysis data. First, the improved MESH configuration is applied to the full archive of gridded hourly radar observations known as GridRad (1995–2017). Next, environmental constraints from the Modern-Era Retrospective Analysis for Research and Applications, version 2, are applied to the MESH distributions to produce a corrected hailfall climatology that accounts for the reduced likelihood of hail reaching the ground. Spatial, diurnal, and seasonal patterns show that in contrast to the report climatology indicating one high-frequency hail maximum centered on the Great Plains, the MESH-only method characterizes two regions: the Great Plains and the Gulf Coast. The environmentally filtered MESH climatology reveals improved agreement between report characteristics (frequency, location, and timing) and the recently improved MESH calculation methods, and it reveals an overall increase in diagnosed hail days and westward broadening in the spatial maximum in the Great Plains than that seen in reports.

The moisture origins and associated physical mechanisms for tornadoes of various climatic regions of the United States were investigated. The NOAA Air Resources Laboratory HYSPLIT model and a moisture attribution algorithm were used in conjunction with statistical analyses to explore these relationships on a climate scale (1981–2017). It was found that moisture sources of United States tornadic convection exhibit distinctive regionality. For example, moisture contributions to east coast tornadoes primarily emanate from the Atlantic Ocean as opposed to the Gulf of Mexico. Moisture sources of a class of non-significant severe thunderstorms also show regionality based on the location of storm occurrence with latitudinal differences to that of tornadic storms. Moisture increases for tornadic and non-significant severe storms were shown to be closely related to the respective air parcel's temperature, with underlying sea surface temperatures playing a less important role. Long-term trends of moisture uptake and horizontal advection were also explored using the Mann-Kendall test and linear regressions. Both statistical analyses demonstrate that the magnitude of advective fluxes and the rate of moisture increases have been rising since the 1980s, which can increase the complexity of forecasting downstream convection. The potential ramifications of these trends on storm development and prediction are discussed to conclude the article.

El Niño–Southern Oscillation (ENSO) and the Gulf of Mexico (GoM) influence winter tornado variability and significant tornado (EF2+, where EF is the enhanced Fujita scale) environments. Increases occur in the probability of a significant tornado environment from the southern Great Plains to the Midwest during La Niña, and across the southern contiguous United States (CONUS) during El Niño. Winter significant tornado environments are absent across Florida, Georgia, and the coastal Carolinas during moderate-to-strong La Niña events. Jet stream modulation by ENSO contributes to higher tornado totals during El Niño in December and La Niña in January, especially when simultaneous with a warm GoM. ENSO-neutral phases yield fewer and weaker tornadoes, but proximity to warm GoM climate features can enhance the probability of a significant tornado environment. ENSO intensity matters; stronger ENSO phases generate increases in tornado frequency and the probability of a significant tornado environment, but are characterized by large variance, in which very strong El Niño and La Niña events can produce unfavorable tornado climatological states. This study suggests that it is a feasible undertaking to expand spring seasonal and subseasonal tornado prediction efforts to encompass the winter season, which is of importance given the notable threat posed by winter tornadoes. Significant tornadoes account for 95% of tornado fatalities and winter tornadoes are rated significant more frequently than during other seasons.

Climate Forecast System, version 2, predictions of monthly U.S. severe thunderstorm activity are analyzed for the period 1982–2016. Forecasts are based on a tornado environmental index and a hail environmental index, which are functions of monthly averaged storm relative helicity (SRH), convective precipitation (cPrcp), and convective available potential energy (CAPE). Overall, forecast indices reproduce well the annual cycle of tornado and hail events. Forecast index biases are mostly negative and caused by environment values that are low east of the Rockies, although forecast CAPE is higher than the reanalysis values over the High Plains. Skill is diagnosed spatially for the indices and their constituents separately. SRH is more skillfully forecast than cPrcp and CAPE, especially during December–June. The spatial patterns of forecast skill for CAPE and cPrcp are similar, with higher skill for CAPE and less spatial coherence for cPrcp. The indices are forecast with substantially less skill than the environmental parameters. Numbers of tornado and hail events are forecast with modest but statistically significant skill in some NOAA regions and months of the year. Skill tends to be relatively higher for hail events and in climatologically active seasons and regions. Much of the monthly skill appears to be derived from the first 2 weeks of the forecast. El Niño–Southern Oscillation (ENSO) modulates forecasts and, to a lesser extent, forecast skill, during March–May, with more activity and higher skill during cool ENSO conditions.

Convective surface winds in the contiguous United States are classified as severe at 50 kt (58 mi h−1, or 26 m s−1), whether measured or estimated. In 2006, NCDC (now NCEI) Storm Data, from which analyzed data are directly derived, began explicit categorization of such reports as measured gusts (MGs) or estimated gusts (EGs). Because of the documented tendency of human observers to overestimate winds, the quality and reliability of EGs (especially in comparison with MGs) has been challenged, mostly for nonconvective winds and controlled-testing situations, but only speculatively for bulk convective data. For the 10-yr period of 2006–15, 150 423 filtered convective-wind gust magnitudes are compared and analyzed, including 15 183 MGs and 135 240 EGs, both nationally and by state. Nonmeteorological artifacts include marked geographic discontinuities and pronounced “spikes” of an order of magnitude in which EG values (in both miles per hour and knots) end in the digits 0 or 5. Sources such as NWS employees, storm chasers, and the general public overestimate EGs, whereas trained spotters are relatively accurate. Analysis of the ratio of EG to MG and their sources also reveals an apparent warning-verification-influence bias in the climatological distribution of wind gusts imparted by EG reliance in the Southeast. Results from prior wind-tunnel testing of human subjects are applied to 1) illustrate the difference between measured and perceived winds for the database and 2) show the impact on the severe-wind dataset if EGs were bias-corrected for the human overestimation factor.

A 10-yr geostationary (GEO) overshooting cloud-top (OT) detection database using Multifunction Transport Satellite (MTSAT) Japanese Advanced Meteorological Imager (JAMI) observations has been developed over the Australian region. GEO satellite imagers collect spatially and temporally detailed observations of deep convection, providing insight into the development and evolution of hazardous storms, particularly where surface observations of hazardous storms and deep convection are sparse and ground-based radar or lightning sensor networks are limited. Hazardous storms often produce one or more OTs that indicate the location of strong updrafts where weather hazards are typically concentrated, which can cause substantial impacts on the ground such as hail, damaging winds, tornadoes, and lightning and to aviation such as turbulence and in-flight icing. The 10-yr OT database produced using an automated OT detection algorithm is demonstrated for analysis of storm frequency, diurnally, spatially, and seasonally relative to known features such as the Australian monsoon, expected regions of hazardous storms along the southeastern coastal regions of southern Queensland and New South Wales, and the preferential extratropical cyclone track along the Indian Ocean and southern Australian coast. A filter based on atmospheric instability, deep-layer wind shear, and freezing level was used to identify OTs that could have produced hail. The filtered OT database is used to generate a hail frequency estimate that identifies a region extending from north of Brisbane to Sydney and the Goldfields–Esperance region of eastern Western Australia as the most hail-prone regions.

The spatial distribution of return intervals for U.S. hail size is explored within the framework of extreme value theory using observations from the period 1979–2013. The center of the continent has experienced hail in excess of 5 in. (127 mm) during the past 30 yr, whereas hail in excess of 1 in. (25 mm) is more common in other regions, including the West Coast. Observed hail sizes show heavy quantization toward fixed-diameter reference objects and are influenced by spatial and temporal biases similar to those noted for hail occurrence. Recorded hail diameters have been growing in recent decades because of improved reporting. These data limitations motivate exploration of extreme value distributions to represent the return periods for various hail diameters. The parameters of a Gumbel distribution are fit to dithered observed annual maxima on a national 1° × 1° grid at locations with sufficient records. Gridded and kernel-smoothed return sizes and quantiles up to the 200-yr return period are determined for the fitted Gumbel distribution. These results are used to illustrate return levels for hail greater than a given size for at least one location within each 1° × 1° grid box for the United States.

Extended Logistic Regression is used to predict March-May severe convective storm (SCS) activity based on the preceding December-February (DJF) ENSO state. The spatially-resolved probabilistic forecasts are verified against U.S. tornado counts, hail events and two environmental indices for severe convection. The cross-validated skill is positive for roughly a quarter of the U.S. Overall, indices are predicted with more skill than are storm reports, and hail events are predicted with more skill than tornado counts. Skill is higher in the cool phase of ENSO (La Nina-like) when overall SCS activity is higher. SCS forecasts based on the predicted DJF ENSO state from coupled dynamical models initialized in October of the previous year extend the lead-time with only a modest reduction in skill compared to forecasts based on the observed DJF ENSO state.

Oceanic fronts are dynamically active regions of the global ocean that support upwelling and downwelling with significant implications for phytoplankton production and export. However (on time scales (Formula presented.) the inertial time scale), the vertical velocity is 10–10 times weaker than the horizontal velocity and is difficult to observe directly. Using intensive field observations in conjunction with a process study ocean model, we examine vertical motion and its effect on phytoplankton fluxes at multiple spatial horizontal scales in an oligotrophic region in the Western Mediterranean Sea. The mesoscale ageostrophic vertical velocity (∼10 m/day) inferred from our observations shapes the large-scale phytoplankton distribution but does not explain the narrow (1–10 km wide) features of high chlorophyll content extending 40–60 m downward from the deep chlorophyll maximum. Using modeling, we show that downwelling submesoscale features concentrate 80% of the downward vertical flux of phytoplankton within just 15% of the horizontal area. These submesoscale spatial structures serve as conduits between the surface mixed layer and pycnocline and can contribute to exporting carbon from the sunlit surface layers to the ocean interior., The AlborEx experiment was conducted in the framework of PERSEUS EU‐funded project (Grant 287600) and was led by the Spanish National Research Council (CSIC) and involved other national and international partners: Balearic Islands Coastal Observing and Forecasting System (SOCIB, Spain); Consiglio Nazionale delle Ricerche (CNR, Italy); Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS, Italy); and Woods Hole Oceanographic Institution (WHOI, ONR Grant N00014‐16‐1‐3130). Glider operations were partially funded by JERICO FP7 project. Part of this work has been carried out as part of the Copernicus Marine Environment Monitoring Service (CMEMS) MedSUB project. CMEMS is implemented by Mercator Ocean in the framework of a delegation agreement with the European Union. S. R. and A. P. acknowledge support from WHOI Subcontract A101339.

The driving factors that influence the spatial and annual variability of thunderstorms across Europe are still poorly understood. Due to a lack of long‐term, reliable and consistent information about the occurrence of convective storms, a weather type classification has been developed that estimates thunderstorm probability from a combination of appropriate meteorological quantities on the mesoscale. Based on this approach, the temporal and spatial variability of convection‐favouring environments is investigated between 1958 and 2014 using a high‐resolution reanalysis dataset. To identify potential drivers for convective days, typical upper‐level flow patterns were deduced using a multivariate approach. Our results suggest a strong link between local‐scale thunderstorm activity and large‐scale flow and air mass properties, such as stability, moisture, or vertical lifting. For example, while all over central Europe the most prominent pattern is given by a southwesterly flow type over the respective area, distinct regional discrepancies regarding further favourable flow types are observed. The crucial role of large‐scale flow is further studied by assessing the relation between Northern Hemisphere teleconnection patterns and widespread convective activity. It is found that positive phases of the East Atlantic or Scandinavian patterns go along with a significant enhancement of convection‐favouring conditions in several European regions, which can be explained by anomalies in the large‐scale temperature and flow fields. Sea‐surface temperature over the Bay of Biscay likewise impacts the convective environment, with the largest positive effect over the western part of the study area.

The supply of nitrate to surface waters plays a crucial role in maintaining marine life. Physical processes at the mesoscale (~10-100?km) and smaller have been advocated to provide a major fraction of the global supply. Whilst observational studies have focussed on well-defined features, such as isolated eddies, the vertical circulation and nutrient supply in a typical 100-200?km square of ocean will involve a turbulent spectrum of interacting, evolving and decaying features. A crucial step in closing the ocean nitrogen budget is to be able to rank the importance of mesoscale fluxes against other sources of nitrate for surface waters for a representative area of open ocean. While this has been done using models, the vital observational equivalent is still lacking.To illustrate the difficulties that prevent us from putting a global estimate on the significance of the mesoscale observationally, we use data from a cruise in the Iceland Basin where vertical velocity and nitrate observations were made simultaneously at the same high spatial resolution. Local mesoscale nitrate flux is found to be an order of magnitude greater than that due to small-scale vertical mixing and exceeds coincident nitrate uptake rates and estimates of nitrate supply due to winter convection. However, a non-zero net vertical velocity for the region introduces a significant bias in regional estimates of the mesoscale vertical nitrate transport. The need for synopticity means that a more accurate estimate can not be simply found by using a larger survey area. It is argued that time-series, rather than spatial surveys, may be the best means to quantify the contribution of mesoscale processes to the nitrate budget of the surface ocean.

The complex patterns observed in marine phytoplankton distributions arise from the interplay of biological and physical processes, but the nature of the balance remains uncertain centuries after the first observations. Previous observations have shown a consistent trend of decreasing variability with decreasing length-scale. Influenced by similar scaling found for the properties of the water that the phytoplankton inhabit, ‘universal' theories have been proposed that simultaneously explain the variability seen from meters to hundreds of kilometers. However, data on the distribution of phytoplankton alone has proved insufficient to differentiate between the many causal mechanisms that have been suggested. Here we present novel observations from a cruise in the North Atlantic in which fluorescence (proxy for phytoplankton), nitrate and temperature were measured simultaneously at scales from 10 m to 100 km for the first time in the open ocean. These show a change in spectra between the small scale (10–100 m) and the mesoscale (10–100 km) which is different for the three tracers. We discuss these observations in relation to the current theories for phytoplankton patchiness.

Rainfall intensity displays relationships with atmospheric conditions such as surface temperature, and these relationships have implications for how the intensity of rainfall varies with climate. Here, hourly gauge measurements of rainfall over the contiguous United States (CONUS) are related to atmospheric variables taken from the North American Regional Reanalysis for the period 1979–2012. This analysis extends previous work relating the rainfall process to the environment by including a wider range of variables in univariate and bivariate quantile regressions. Known covariate relationships are used to quantify the regional contributions of different weather regimes to rainfall occurrence and to identify preferential atmospheric states for rainfall occurrence. The efficiency of different sets of regressors is evaluated, and the results show that both moisture availability and vertical instability should be taken into account, with CAPE in combination with specific humidity or dewpoint temperature being the most powerful regressors. Different regions and seasons behave differently, pointing to the challenges of constructing global or CONUS-wide models for representing the rainfall process. In particular, the relationships between environment and rainfall in the west of the United States are different from other regions, reflecting nonlocal rainfall processes. Most of the coastal and eastern United States display relatively low regional variability in the relationships between rainfall and environment.

The response of severe thunderstorms to a changing climate is a rapidly growing area of research. Severe thunderstorms are one of the largest contributors to global losses in excess of USD $10 billion per year in terms of property and agriculture, as well as dozens of fatalities. Phenomena associated with severe thunderstorms such as large hail (greater than 2 cm), damaging winds (greater than 90 kmh−1), and tornadoes pose a global threat, and have been documented on every continent except Antarctica. Limitations of observational records for assessing past trends have driven a variety of approaches to not only characterize the past occurrence but provide a baseline against which future projections can be interpreted. These proxy methods have included using environments or conditions favorable to the development of thunderstorms and directly simulating storm updrafts using dynamic downscaling. Both methodologies have demonstrated pronounced changes to the frequency of days producing severe thunderstorms. Major impacts of a strongly warmed climate include a general increase in the length of the season in both the fall and spring associated with increased thermal instability and increased frequency of severe days by the late 21st century. While earlier studies noted changes to vertical wind shear decreasing frequency, recent studies have illustrated that this change appears not to coincide with days which are unstable. Questions remain as to whether the likelihood of storm initiation decreases, whether all storms which now produce severe weather will maintain their physical structure in a warmer world, and how these changes to storm frequency and or intensity may manifest for each of the threats posed by tornadoes, hail, and damaging winds. Expansion of the existing understanding globally is identified as an area of needed future research, together with meaningful consideration of both the influence of climate variability and indirect implications of anthropogenic modification of the physical environment.

The El Nino/Southern Oscillation modulates global weather and climate. Analyses of large-scale environmental indices show that it also affects the frequency of tornado and hail events in the central United States, which may help with predictability.

An empirical model relating monthly hail occurrence to the large-scale environment has been developed and tested for the United States (U.S.). Monthly hail occurrence for each 1°×1° grid box is defined as the number of hail events that occur there during a month; a hail event consists of a 3 h period with at least one report of hail larger than 1 in. The model is derived using climatological annual cycle data only. Environmental variables are taken from the North American Regional Reanalysis (NARR; 1979–2012). The model includes four environmental variables convective precipitation, convective available potential energy, storm relative helicity, and mean surface to 90 hPa specific humidity. The model differs in its choice of variables and their relative weighting from existing severe weather indices. The model realistically matches the annual cycle of hail occurrence both regionally and for the contiguous U.S. (CONUS). The modeled spatial distribution is also consistent with the observed hail climatology. However, the westward shift of maximum hail frequency during the summer months is delayed in the model relative to observations, and the model has a lower frequency of hail just east of the Rocky Mountains compared to observations. Year-to-year variability provides an independent test of the model. On monthly and annual time scales, the model reproduces observed hail frequencies. Overall model trends are small compared to observed changes, suggesting that further analysis is necessary to differentiate between physical and nonphysical trends. The empirical hail model provides a new tool for exploration of connections between large-scale climate and severe weather.

The influence of a warming climate on the occurrence of severe thunderstorms over Australia is, as yet, poorly understood. Based on methods used in the development of a climatology of observed severe thunderstorm environments over the continent, two climate models [Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6) and the Cubic-Conformal Atmospheric Model (CCAM)] have been used to produce simulated climatologies of ingredients and environments favorable to severe thunderstorms for the late twentieth century (1980–2000). A novel evaluation of these model climatologies against data from both the ECMWF Interim Re-Analysis (ERA-Interim) and reports of severe thunderstorms from observers is used to analyze the capability of the models to represent convective environments in the current climate. This evaluation examines the representation of thunderstorm-favorable environments in terms of their frequency, seasonal cycle, and spatial distribution, while presenting a framework for future evaluations of climate model convective parameters. Both models showed the capability to explain at least 75% of the spatial variance in both vertical wind shear and convective available potential energy (CAPE). CSIRO Mk3.6 struggled to either represent the diurnal cycle over a large portion of the continent or resolve the annual cycle, while in contrast CCAM showed a tendency to underestimate CAPE and 0–6-km bulk magnitude vertical wind shear (S06). While spatial resolution likely contributes to rendering of features such as coastal moisture and significant topography, the distribution of severe thunderstorm environments is found to have greater sensitivity to model biases. This highlights the need for a consistent approach to evaluating convective parameters and severe thunderstorm environments in present-day climate: an example of which is presented here.

The influence of a warming climate on the occurrence of severe thunderstorm environments in Australia was explored using two global climate models: Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6), and the Cubic-Conformal Atmospheric Model (CCAM). These models have previously been evaluated and found to be capable of reproducing a useful climatology for the twentieth-century period (1980–2000). Analyzing the changes between the historical period and high warming climate scenarios for the period 2079–99 has allowed estimation of the potential convective future for the continent. Based on these simulations, significant increases to the frequency of severe thunderstorm environments will likely occur for northern and eastern Australia in a warmed climate. This change is a response to increasing convective available potential energy from higher continental moisture, particularly in proximity to warm sea surface temperatures. Despite decreases to the frequency of environments with high vertical wind shear, it appears unlikely that this will offset increases to thermodynamic energy. The change is most pronounced during the peak of the convective season, increasing its length and the frequency of severe thunderstorm environments therein, particularly over the eastern parts of the continent. The implications of this potential increase are significant, with the overall frequency of potential severe thunderstorm days per year likely to rise over the major population centers of the east coast by 14% for Brisbane, 22% for Melbourne, and 30% for Sydney. The limitations of this approach are then discussed in the context of ways to increase the confidence of predictions of future severe convection.

In previous work the authors demonstrated an empirical relation, in the form of an index, between U.S. monthly tornado activity and monthly averaged environmental parameters. Here a detailed comparison is made between the index and reported tornado activity. The index is a function of two environmental parameters taken from the North American Regional Reanalysis: convective precipitation (cPrcp) and storm relative helicity (SRH). Additional environmental parameters are considered for inclusion in the index, among them convective available potential energy, but their inclusion does not significantly improve the overall climatological performance of the index. The aggregate climatological dependence of reported monthly U.S. tornado numbers on cPrcp and SRH is well described by the index, although it fails to capture nonsupercell and cool season tornadoes. The contributions of the two environmental parameters to the index annual cycle and spatial distribution are examined with the seasonality of cPrcp (maximum during summer) relative to SRH (maximum in winter) accounting for the index peak value in May. The spatial distribution of SRH establishes the central U.S. “tornado alley” of the index, while the spatial distribution of cPrcp enhances index values in the South and Southeast and suppresses them west of the Rockies and over elevation. At the scale of the NOAA climate regions, the largest deficiency of the index climatology occurs over the central region where the index peak in spring is too low and where the late summer drop-off in the reported number of tornadoes is poorly captured. This index deficiency is related to its sensitivity to SRH, and increasing the index sensitivity to SRH improves the representation of the annual cycle in this region. The ability of the index to represent the interannual variability of the monthly number of U.S. tornadoes can be ascribed during most times of the year to interannual variations of cPrcp rather than of SRH. However, both factors are important during the peak spring period. The index shows some skill in representing the interannual variability of monthly tornado numbers at the scale of NOAA climate regions.

Severe thunderstorms present a significant threat to property and life in Australia during the warm season (September to April). However, these relatively infrequent events are poorly understood in terms of frequency and occurrence for much of the continent due to a lack of in-situ observations. With the spectre of a changing climate, there is an increasing need to understand thunderstorms and their impact on Australia, both in the past and for the future. To facilitate this, the relationship between severe thunderstorms and their associated environments is used as a probabilistic proxy for direct observations. To establish these conditions, a proximity climatology of environments was developed for observed severe thunderstorms in Australia during the period 2003–2010 using the ERA-Interim reanalysis. Proximity soundings from the reanalysis for observed severe thunderstorms were used to develop covariate discriminants that identify the increased probability of an environment to produce severe thunderstorms. The covariates use a combination of ingredients describing instability (mixed-layer convective available potential energy) and potential for organized severe convection (deep-layer wind shear). These discriminants have been extrapolated to produce a climatology of environments favourable to the development of severe thunderstorms over the period 1979–2011 from this reanalysis. The inter-annual variations in both the spatial and temporal distribution of convective environments over Australia were analysed, with particular focus on the influence of El Nino-Southern Oscillation (ENSO) on the occurrence of severe thunderstorm environments. These results suggest that while ENSO has a substantial impact on the spatial distribution of severe thunderstorm environments over the continent, the link to frequency is more uncertain.

Different features of the Gulf of Mexico (GOM), such as the Loop Current and warm-core rings, are found to influence monthly-to-seasonal severe weather occurrence in different regions of the United States (U.S.). The warmer (cooler) the GOM sea surface temperatures, the more (less) hail and tornadoes occur during March–May over the southern U.S. This pattern is reflected physically in boundary layer specific humidity and mixed-layer convective available potential energy, two large-scale atmospheric conditions favorable for severe weather occurrence. This relationship is complicated by interactions between the GOM and El Nino–Southern Oscillation (ENSO) but persists when analyzing ENSO neutral conditions. This suggests that the GOM can influence hail and tornado occurrence and provides another source of regional predictability for seasonal severe weather.

There is widespread speculation as to whether hailstorms are getting more intense or frequent as the global climate warms. Now research suggests a potential increase in both the mean hail size and frequency of larger hail events over North America.

A global climatology for rapid cyclone intensification has been produced from the second NCEP reanalysis (NCEP2), the 25-yr Japanese Reanalysis (JRA-25), and the ECMWF reanalyses over the period 1979–2008. An improved (combined) criterion for identifying explosive cyclones has been developed based on preexisting definitions, offering a more balanced, normalized climatological distribution. The combined definition was found to significantly alter the population of explosive cyclones, with a reduction in “artificial” systems, which are found to compose 20% of the population determined by earlier definitions. Seasonally, winter was found to be the dominant formative period in both hemispheres, with a lower degree of interseasonal variability in the Southern Hemisphere (SH). Considered over the period 1979–2008, little change is observed in the frequency of systems outside of natural interannual variability in either hemisphere. Significant statistical differences have been found between reanalyses in the SH, while in contrast the Northern Hemisphere (NH) was characterized by strong positive correlations between reanalyses in almost all examined cases. Spatially, explosive cyclones are distributed into several distinct regions, with two regions in the northwest Pacific and the North Atlantic in the NH and three main regions in the SH. High-resolution and modern reanalysis data were also found to increase the climatology population of rapidly intensifying systems. This indicates that the reanalyses have apparently undergone increasing improvements in consistency over time, particularly in the SH.

Initial results from a deployment of the SUV-6 ultraviolet spectrophotometer, integrated with the SeaSoar towed vehicle, are presented. The innovative, combined system measures nitrate concentration at high spatial resolution (4 m vertically, 5 km horizontally), high sensitivity (0.2 μM), and concomitantly with temperature, salinity, and dissolved oxygen. The authors demonstrate that this approach constitutes a powerful new tool for quantifying the role of mesoscale and submesoscale vertical nutrient fluxes to the euphotic zone, using measurements from a high-resolution survey of an eddy dipole in the Iceland Basin during the summer of 2007.

Numerous observations demonstrate that considerable spatial variability exists in components of the marine planktonic ecosystem at the mesoscale and submesoscale (100?km -1?km). The causes and consequences of physical processes at these scales (‘eddy advection’) influencing biogeochemistry have received much attention. Less studied, the non-linear nature of most ecological and biogeochemical interactions means that such spatial variability has consequences for regional estimates of processes including primary production and grazing, independent of the physical processes. This effect has been termed ‘eddy reactions’. Models remain our most powerful tools for extrapolating hypotheses for biogeochemistry to global scales and to permit future projections. The spatial resolution of most climate and global biogeochemical models means that processes at the mesoscale and submesoscale are poorly resolved. Modelling work has previously suggested that the neglected ‘eddy reactions’ may be almost as large as the mean field estimates in some cases. This study seeks to quantify the relative size of eddy and mean reactions observationally, using in situ and satellite data. For primary production, grazing and zooplankton mortality the eddy reactions are between 7% and 15% of the mean reactions. These should be regarded as preliminary estimates to encourage further observational estimates, and not taken as a justification for ignoring eddy reactions. Compared to modelling estimates, there are inconsistencies in the relative magnitude of eddy reactions and in correlations which are a major control on their magnitude. One possibility is that models exhibit much stronger spatial correlations than are found in reality, effectively amplifying the magnitude of eddy reactions.

During the North Atlantic spring bloom, a seasonal phytoplankton community succession takes place from diatoms to non-siliceous phytoplankton. Diatoms rely on silica to form their frustules and are out-competed by other species when silica becomes depleted. Diatoms are also expected to contribute significantly to export production in the North Atlantic. We suggest that a lower boundary to export production can be estimated as the component of total production that occurs between the start of the spring bloom and the time when silica becomes depleted. This method has been tested in the Irminger Basin, located between Greenland and Iceland, in the North Atlantic. A technique to estimate silica concentration from satellite-derived sea surface temperature and chlorophyll a concentration has been developed and used to determine silica concentration at high spatial and temporal resolution. This facilitates an estimation of the timing of silica depletion and thus the timing of the transition from a phytoplankton community dominated by diatoms to dominance by non-siliceous species. The timing of the initiation of the bloom, defined as a pronounced and sustained increase in biomass, is estimated from a Sea-viewing Wide Field-of-View Sensor (SeaWiFS)-derived chlorophyll a concentration. A lower-boundary estimate of export production is made and, additionally, estimates of the contribution to export production by diatoms and non-diatoms are made by considering silica-to-nitrate drawdown ratios. We estimate export production in this region to be ~60 gC m–2 yr–1, of which diatoms account for ~65%.

Recent data from an autonomous ocean glider in the Ibiza Channel (Western Mediterranean Sea) show variations in the transport volumes of water over timescales of days-weeks, as large as those previously only identifiable as seasonal or eddy driven. High frequency variation in transports of water masses has critical implications for ocean forecasting. Three potential modes of transport are proposed, which have the potential to simplify the previously observed complex pattern of flows. Restricted choke points between ocean basins are critical locations to monitor water transport variability; the Ibiza Channel is one such choke point, where variation in the transports of water masses are known to affect the spawning grounds of commercially important fish stocks. © 2012. American Geophysical Union. All Rights Reserved., This research was partially funded by the European Commission Projects, MyOcean, PERSEUS, and JERICO.

Diatoms are unicellular or chain-forming phytoplankton that use silicon (Si) in cell wall construction. Their survival during periods of apparent nutrient exhaustion enhances carbon sequestration in frontal regions of the northern North Atlantic. These regions may therefore have a more important role in the 'biological pump' than they have previously been attributed1, but how this is achieved is unknown. Diatom growth depends on silicate availability, in addition to nitrate and phosphate2, 3, but northern Atlantic waters are richer in nitrate than silicate4. Following the spring stratification, diatoms are the first phytoplankton to bloom2, 5. Once silicate is exhausted, diatom blooms subside in a major export event6, 7. Here we show that, with nitrate still available for new production, the diatom bloom is prolonged where there is a periodic supply of new silicate: specifically, diatoms thrive by 'mining' deep-water silicate brought to the surface by an unstable ocean front. The mechanism we present here is not limited to silicate fertilization; similar mechanisms could support nitrate-, phosphate- or iron-limited frontal regions in oceans elsewhere.

[1] Inverse relationships between sea surface temperature and concentrations of the major inorganic nutrients have recently been exploited to estimate new production from remotely sensed data. In situ surface data collected in the Irminger Basin during four successive seasons in 2001/2 allow a robust examination of the conceptual processes behind temperature-nitrate relationships. The data confirm a simple model of the seasonal variation in the temperature-nitrate relationship. A strong inverse correlation between temperature and nitrate is found in both winter data sets, but no correlation is seen in spring or summer. Furthermore, the slope of the temperature-nitrate regression is found to be different for the two winter data sets. The results have implications for using temperature-nitrate relationships to derive new production estimates at high latitudes from satellite sea surface temperature measurements. However, the data allow a simple, lower-bound estimate of the region's new production to be made by exploiting Argo float data.

Phytoplankton size structure is acknowledged as a fundamental property determining energy flow through 'microbial' or 'herbivore' pathways1. The balance between these two pathways determines the ability of the ecosystem to recycle carbon within the upper layer or to export it to the ocean interior1. Small cells are usually characteristic of oligotrophic, stratified ocean waters, in which regenerated ammonium is the only available form of inorganic nitrogen and recycling dominates. Large cells seem to characterize phytoplankton in which inputs of nitrate enter the euphotic layer and exported production is higher2-4. But the size structure of phytoplankton may depend more directly on hydrodynamical forces than on the source of available nitrogen5-7. Here we present an empirical model that relates the magnitude of mesoscale vertical motion to the slope of the size-abundance spectrum8-10 of phytoplankton in a frontal ecosystem. Our model indicates that the relative proportion of large cells increases with the magnitude of the upward velocity. This suggests that mesoscale vertical motion - a ubiquitous feature of eddies and unstable fronts - controls directly the size structure of phytoplankton in the ocean., This work was supported by the MAST III programme of the European Commision and the CICYT-CYTMAR programme (Spain).