Thunderstorm climatology and lightning location applications in northern Europe

Thunderstorm is a dangerous electrical phenomena in the atmosphere. Thundercloud is formed when thermal energy is transported rapidly upwards in convective updraughts. Electrification occurs in the collisions of cloud particles in the strong updraught. When the amount of charge in the cloud is large enough, electrical breakdown, better known as a flash, occurs. Lightning location is nowadays an essential tool for the detection of severe weather. Located flashes indicate in real time the movement of hazardous areas and the intensity of lightning activity. Also, an estimate for the flash peak current can be determined. The observations can be used in damage surveys. The most simple way to represent lightning data is to plot the locations on a map, but the data can be processed in more complex end-products and exploited in data fusion. Lightning data serves as an important tool also in the research of lightning-related phenomena, such as Transient Luminous Events. Most of the global thunderstorms occur in areas with plenty of heat, moisture and tropospheric instability, for example in the tropical land areas. In higher latitudes like in Finland, the thunderstorm season is practically restricted to the summer season. Particular feature of the high-latitude climatology is the large annual variation, which regards also thunderstorms. Knowing the performance of any measuring device is important because it affects the accuracy of the end-products. In lightning location systems, the detection efficiency means the ratio between located and actually occurred flashes. Because in practice it is impossible to know the true number of actually occurred flashes, the detection efficiency has to be esimated with theoretical methods.

The Madden-Julian Oscillation : observation, modeling, and theory

The Madden-Julian Oscillation (MJO) is a pattern of intense rainfall and associated planetary-scale circulations in the tropical atmosphere, with a recurrence interval of 30-90 days. Although the MJO was first discovered 40 years ago, it is still a challenge to simulate the MJO in general circulation models (GCMs), and even with simple models it is difficult to agree on the basic mechanisms. This deficiency is mainly due to our poor understanding of moist convection—deep cumulus clouds and thunderstorms, which occur at scales that are smaller than the resolution elements of the GCMs. Moist convection is the most important mechanism for transporting energy from the ocean to the atmosphere. Success in simulating the MJO will improve our understanding of moist convection and thereby improve weather and climate forecasting.

We address this fundamental subject by analyzing observational datasets, constructing a hierarchy of numerical models, and developing theories. Parameters of the models are taken from observation, and the simulated MJO fits the data without further adjustments. The major findings include: 1) the MJO may be an ensemble of convection events linked together by small-scale high-frequency inertia-gravity waves; 2) the eastward propagation of the MJO is determined by the difference between the eastward and westward phase speeds of the waves; 3) the planetary scale of the MJO is the length over which temperature anomalies can be effectively smoothed by gravity waves; 4) the strength of the MJO increases with the typical strength of convection, which increases in a warming climate; 5) the horizontal scale of the MJO increases with the spatial frequency of convection; and 6) triggered convection, where potential energy accumulates until a threshold is reached, is important in simulating the MJO. Our findings challenge previous paradigms, which consider the MJO as a large-scale mode, and point to ways for improving the climate models.

The top ten California floods of the 20th century

The purpose of this paper is to summarize the biggest northern California floods of the 20th century. Flooding in California can occur from different causes. At least three types of floods occur: 1. Winter general floods, which cover a large area. 2. Spring and early summer snowmelt floods unique to the higher-elevation central and southern Sierra Nevada, which occur about once in 10 years on the average. 3. Local floods from strong thunderstorms, with intense rain over a relatively small area. These originate in moist tropical or subtropical air and include the flash floods of the desert and other areas of southern California when remnants of eastern Pacific hurricanes get carried into the state.

Dependence of severe storm occurrence on circulation types in Poland

The paper investigates the relationships between the occurrence of thunderstorms with heavy precipitation (> 30 mm) and atmospheric circulation types. The study covers the period 1951–1998 and is based on a matching span of records of thunderstorm occurrence and daily precipitation totals at 47 weather stations in Poland. A catalogue of circulation types by Osuchowska-Klein, data on frequency of fronts over south-eastern Poland by Niedźwiedź and weather maps were used. In Poland, days with a thunderstorm and more than 30 mm of precipitation are extremely rare and occur mainly in summer. Their recurrence period amounts to about two to four years, with the exception of mountain areas (southern Poland) where they occur nearly every year. The heaviest precipitation on a day with thunderstorm, 166.1 mm, was recorded at a high-mountain station on Mt. Kasprowy Wierch. Apart from this station the highest precipitation was 141.0 mm and only eight stations had at least one record of more than 100 mm. Four regions characterised by different circulation types most favourable for the occurrence of thunderstorms with heavy precipitation were identified. In all of them southerly advection was most favourable for the occurrence of the phenomena studied (Sc, SEc, Sa/c), but that effect was especially prominent in the south-western region. Most of the days with thunderstorm and heavy precipitation coincided with the passing of an atmospheric front over Poland (53.8–81.9% days depending on the station). Days with air-mass thunderstorm and heavy precipitation were rare and mostly occurred in areas of variable topography.

Acute Asthma Epidemics, Weather and Pollen in England, 1987-1994

Recent epidemics of acute asthma have caused speculation that, if their causes were known, early warnings might be feasible. In particular, some epidemics seemed to be associated with thunderstorms. We wondered what risk factors predicting epidemics could be identified. Daily asthma admissions counts during 1987-1994, for two age groups (0-14 yrs and > or = 15 yrs), were measured using the Hospital Episodes System (HES). Epidemics were defined as combinations of date, age group and English Regional Health Authority (RHA) with exceptionally high asthma admission counts compared to the predictions of a log-linear autoregression model. They were compared with control days 1 week before and afterwards, regarding seven meteorological variables and 5 day average pollen counts for four species. Fifty six asthma epidemics were identified. The mean density of sferics (lightning flashes), temperature and rainfall on epidemic days were greater than those on control days. High sferics densities were overrepresented in epidemics. Simultaneously high sferics and grass pollen further increased the probability of an epidemic, but only to 15% (95% confidence interval 2-45%). Two thirds of epidemics were not preceded by thunderstorms. Thunderstorms and high grass pollen levels precede asthma epidemics more often than expected by chance. However, most epidemics are not associated with thunderstorms or unusual weather conditions, and most thunderstorms, even following high grass pollen levels, do not precede epidemics. An early warning system based on the indicators examined here would, therefore, detect few epidemics and generate an unacceptably high rate of false alarms.

Studies on the Vertical Structure of Horizontal Wind Variability in the Surface Boundary Layer Over Sriharikota

The present study on the vertical structure of horizontal wind variability in the surface boundary layer over Sriharikota. Based on clock wind speed and direction measuring meteorological tower facility from seven levels in the 100 m layer. The study on wind variability and elliptical approximation of wind hodographs investigated for this tropical coastal station established that Sriharikota is of meso-scale weather entity. Wind variability ratio increases from lower levels to upper levels. In South West monsoon months the station is of high ratio values and it gets affected with meso-scale weather features like thunderstorms. Average total shears are observed greater values than scalar shears. Scalar shears are high in the lowest shear levels compared to upper levels. Semi diurnal types of oscillation in average total shears are found in south west monsoon months. During cyclonic storm passage it is observed that there can be significant difference in mean wind speed from 10 m to 100 m level, but it is not so for peak wind speeds. The variations in wind variability ratio in different months is clearly depicted its strong link to define meso-scale or synoptic –scale forcing domination for this station. Meso-scale forcing is characterized by diurnal wind variability and synoptic- scale forcing by interdiurnal wind variability.

Environmental Influences on the Frequency and Intensity of North Indian Ocean Tropical Cyclones

Tropical cyclones genesis, movement and intensification are highly dependent on its environment both oceanic and atmospheric. This thesis has made a detailed study on the environmental factors related to tropical cyclones of North Indian Ocean basin. This ocean basin has produced only 6% of the global tropical cyclones annually but it has caused maximum loss of human life associated with the strong winds, heavy rain and particularly storm surges that accompany severe cyclones as they strike the heavily populated coastal areas. Atmospheric factors studied in the thesis are the moisture content of the atmosphere, instability of the atmosphere that produces thunderstorms which are the main source of energy for the tropical cyclone, vertical wind shear to which cyclones are highly sensitive and the Sub-Tropical westerly Jetsteram and its Asian high speed center. The oceanic parameters studied are sea surface temperature and heat storage in the top layer of the ocean. A major portion of the thesis has dealt with the three temporal variabilities of tropical cyclone frequency namely intra-seasonal (mainly the influence of Madden Julian Oscillation), inter- annual (the relation with El Nino Southern Oscillation) and decadal variabilities. Regarding decadal variability, a prominent four decade oscillation in the frequency of both tropical cyclones and monsoon depressions unique to the Indian Ocean basin has been brought out. The thesis consists of 9 chapters.

A Comparative Study of Convective Parameterization Schemes in WRF-NMM Model

Severe local storms, including tornadoes, damaging hail and wind gusts, frequently occur over the eastern and northeastern states of India during the pre-monsoon season (March-May). Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. In this paper, sensitivity experiments are conducted with the WRF-NMM model to test the impact of convective parameterization schemes on simulating severe thunderstorms that occurred over Kolkata on 20 May 2006 and 21 May 2007 and validated the model results with observation. In addition, a simulation without convective parameterization scheme was performed for each case to determine if the model could simulate the convection explicitly. A statistical analysis based on mean absolute error, root mean square error and correlation coefficient is performed for comparisons between the simulated and observed data with different convective schemes. This study shows that the prediction of thunderstorm affected parameters is sensitive to convective schemes. The Grell-Devenyi cloud ensemble convective scheme is well simulated the thunderstorm activities in terms of time, intensity and the region of occurrence of the events as compared to other convective schemes and also explicit scheme

An overview of Earth's global electric circuit and atmospheric conductivity

The Earth’s global atmospheric electric circuit depends on the upper and lower atmospheric boundaries formed by the ionosphere and the planetary surface. Thunderstorms and electrified rain clouds drive a DC current (∼1 kA) around the circuit, with the current carried by molecular cluster ions; lightning phenomena drive the AC global circuit. The Earth’s near-surface conductivity ranges from 10−7 S m−1 (for poorly conducting rocks) to 10−2 S m−1 (for clay or wet limestone), with a mean value of 3.2 S m−1 for the ocean. Air conductivity inside a thundercloud, and in fair weather regions, depends on location (especially geomagnetic latitude), aerosol pollution and height, and varies from ∼10−14 S m−1 just above the surface to 10−7 S m−1 in the ionosphere at ∼80 km altitude. Ionospheric conductivity is a tensor quantity due to the geomagnetic field, and is determined by parameters such as electron density and electron–neutral particle collision frequency. In the current source regions, point discharge (coronal) currents play an important role below electrified clouds; the solar wind-magnetosphere dynamo and the unipolar dynamo due to the terrestrial rotating dipole moment also apply atmospheric potential differences. Detailed measurements made near the Earth’s surface show that Ohm’s law relates the vertical electric field and current density to air conductivity. Stratospheric balloon measurements launched from Antarctica confirm that the downward current density is ∼1 pA m−2 under fair weather conditions. Fortuitously, a Solar Energetic Particle (SEP) event arrived at Earth during one such balloon flight, changing the observed atmospheric conductivity and electric fields markedly. Recent modelling considers lightning discharge effects on the ionosphere’s electric potential (∼+250 kV with respect to the Earth’s surface) and hence on the fair weather potential gradient (typically ∼130 V m−1 close to the Earth’s surface. We conclude that cloud-to-ground (CG) lightning discharges make only a small contribution to the ionospheric potential, and that sprites (namely, upward lightning above energetic thunderstorms) only affect the global circuit in a miniscule way. We also investigate the effects of mesoscale convective systems on the global circuit.

Observed atmospheric electricity effect on clouds

The atmosphere's fair weather electric field is a permanent feature, arising from the combination of distant thunderstorms, Earth's conducting surface, a charged ionosphere and cosmic ray ionization. Despite its ubiquity, no fair weather electricity effect on clouds has been hitherto demonstrated. Here we report surface measurements of radiation emitted and scattered by extensive thin continental cloud, which, after ~2 min delay, shows changes closely following the fair weather electric field. For typical fluctuations in the fair weather electric field, changes of about 10% are subsequently induced in the diffuse short-wave radiation. These observations are consistent with enhanced production of large cloud droplets from charging at layer cloud edges.

An overview of Earth’s global electric circuit and atmospheric conductivity

The Earth’s global atmospheric electric circuit depends on the upper and lower atmospheric boundaries formed by the ionosphere and the planetary surface. Thunderstorms and electrified rain clouds drive a DC current (∼1 kA) around the circuit, with the current carried by molecular cluster ions; lightning phenomena drive the AC global circuit. The Earth’s near-surface conductivity ranges from 10−7 S m−1 (for poorly conducting rocks) to 10−2 S m−1 (for clay or wet limestone), with a mean value of 3.2 S m−1 for the ocean. Air conductivity inside a thundercloud, and in fair weather regions, depends on location (especially geomagnetic latitude), aerosol pollution and height, and varies from ∼10−14 S m−1 just above the surface to 10−7 S m−1 in the ionosphere at ∼80 km altitude. Ionospheric conductivity is a tensor quantity due to the geomagnetic field, and is determined by parameters such as electron density and electron–neutral particle collision frequency. In the current source regions, point discharge (coronal) currents play an important role below electrified clouds; the solar wind-magnetosphere dynamo and the unipolar dynamo due to the terrestrial rotating dipole moment also apply atmospheric potential differences. Detailed measurements made near the Earth’s surface show that Ohm’s law relates the vertical electric field and current density to air conductivity. Stratospheric balloon measurements launched from Antarctica confirm that the downward current density is ∼1 pA m−2 under fair weather conditions. Fortuitously, a Solar Energetic Particle (SEP) event arrived at Earth during one such balloon flight, changing the observed atmospheric conductivity and electric fields markedly. Recent modelling considers lightning discharge effects on the ionosphere’s electric potential (∼+250 kV with respect to the Earth’s surface) and hence on the fair weather potential gradient (typically ∼130 V m−1 close to the Earth’s surface. We conclude that cloud-to-ground (CG) lightning discharges make only a small contribution to the ionospheric potential, and that sprites (namely, upward lightning above energetic thunderstorms) only affect the global circuit in a miniscule way. We also investigate the effects of mesoscale convective systems on the global circuit.

Variability in surface atmospheric electric field measurements

An electrical current of the order one picoamp per metre squared flows vertically in the Earth's atmosphere, between the ionosphere at approximately 50km altitude and the surface. This current is generated by global thunderstorm activity and is modulated by galactic cosmic rays and atmospheric aerosol. In fair weather conditions, this current cause a vertical atmospheric electric field, commonly measured as a potential gradient. For circumstances other than fair weather conditions, the potential gradient varies, from small steady enhancements in fog to large fluctuations in thunderstorms. The atmospheric potential gradient is continuously monitored at the Reading University Atmospheric Observatory. An account of the variability of the potential gradient on a variety of time scales will be presented.

Retrieval of global atmospheric electrical activity at a polluted urban site

The atmospheric electrical Potential Gradient (PG) arises from global thunderstorm activity, but surface measurements of the atmospheric Potential Gradient (PG) are influenced by global thunderstorms and local aerosol concentration changes. The local aerosol change can be monitored independently, and in some cases the concentration changes are closely related to PG changes. For these circumstances, a general theory to remove the local aerosol influence on PG measurements has been developed. Continuous measurements of PG and aerosol mass concentration were made during 24–31 Dec, 2005 within an urban environment at Reading, UK. The average diurnal variation of PG showed a double diurnal cycle, with maxima in the early morning and evening hours. The aerosol concentration has similar double maxima. Removing the aerosol using from the PG and aerosol correlation returns a single diurnal cycle, suggestive of the more global PG diurnal cycle.

Lightning-induced intensification of the ionospheric sporadic E layer

A connection between thunderstorms and the ionosphere has been hypothesized since the mid-1920s(1). Several mechanisms have been proposed to explain this connection(2-7), and evidence from modelling(8) as well as various types of measurements(9-14) demonstrate that lightning can interact with the lower ionosphere. It has been proposed, on the basis of a few observed events(15), that the ionospheric 'sporadic E' layer - transient, localized patches of relatively high electron density in the mid-ionosphere E layer, which significantly affect radio-wave propagation - can be modulated by thunderstorms, but a more formal statistical analysis is still needed. Here we identify a statistically significant intensification and descent in altitude of the mid-latitude sporadic E layer directly above thunderstorms. Because no ionospheric response to low-pressure systems without lightning is detected, we conclude that this localized intensification of the sporadic E layer can be attributed to lightning. We suggest that the co-location of lightning and ionospheric enhancement can be explained by either vertically propagating gravity waves that transfer energy from the site of lightning into the ionosphere, or vertical electrical discharge, or by a combination of these two mechanisms.

Ensemble prediction for nowcasting with a convection-permitting model—I: description of the system and the impact of radar-derived surface precipitation rates

A key strategy to improve the skill of quantitative predictions of precipitation, as well as hazardous weather such as severe thunderstorms and flash floods is to exploit the use of observations of convective activity (e.g. from radar). In this paper, a convection-permitting ensemble prediction system (EPS) aimed at addressing the problems of forecasting localized weather events with relatively short predictability time scale and based on a 1.5 km grid-length version of the Met Office Unified Model is presented. Particular attention is given to the impact of using predicted observations of radar-derived precipitation intensity in the ensemble transform Kalman filter (ETKF) used within the EPS. Our initial results based on the use of a 24-member ensemble of forecasts for two summer case studies show that the convective-scale EPS produces fairly reliable forecasts of temperature, horizontal winds and relative humidity at 1 h lead time, as evident from the inspection of rank histograms. On the other hand, the rank histograms seem also to show that the EPS generates too much spread for forecasts of (i) surface pressure and (ii) surface precipitation intensity. These may indicate that for (i) the value of surface pressure observation error standard deviation used to generate surface pressure rank histograms is too large and for (ii) may be the result of non-Gaussian precipitation observation errors. However, further investigations are needed to better understand these findings. Finally, the inclusion of predicted observations of precipitation from radar in the 24-member EPS considered in this paper does not seem to improve the 1-h lead time forecast skill.