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Spatially explicit quantification on design storms are essential for flood risk assessment and planning. Since the limited temporal data availability from weather radar data, design storms are usually estimated on the basis of rainfall records of a few precipitation stations having a substantially long time coverage. To achieve a regional picture these station based estimates are spatially interpolated, incorporating a large source of uncertainty due to the typical low station density, in particular for short event durations. In this study we present a method to estimate spatially explicit design storms with a return period of up to 100 years on the basis of statistically extended weather radar precipitation estimates based on the ideas of regional frequency analyses and subsequent bias correction. Associated uncertainties are quantified using an ensemble-sampling approach and event-based bootstrapping. With the resulting dataset, we compile spatially explicit design storms for various return periods and event durations for the federal state of Baden Württemberg, Germany. We compare our findings with two reference datasets based on interpolated station estimates. We find that the transition in the spatial patterns of the design storms from a rather random short duration events, 15 minute) to a more structured, orographically influenced pattern (long duration events, 24 hours) seems to be much more realistic in the weather radar based product. However, the absolute magnitude of the design storms, although bias-corrected, is still generally lower in the weather radar product, which should be addressed in future studies in more detail.

Wildfire changes the hydrologic and geomorphic response of watersheds, resulting in a cascade of increased hazards for sediment-laden floods, shallow landslides, and debris flows. This phenomenon has long been studied in regions where landscape evolution is driven by repeated fire-flood sequences such as Southern California. However, comparing mass movement hazards across multiple regions presents a challenge because most landslide inventories are limited to local or regional spatial scales. This study seeks to identify unique triggering characteristics of post-fire landslides through a comparison of the precipitation characteristics preceding landslides at both burned and unburned locations spanning six global regions. Regional inter-comparison was facilitated by selecting landslide events from the NASA Global Landslide Catalog (GLC), and then establishing fire and precipitation histories for each site using MODIS global burned area and CHIRPS precipitation data. In addition, since the GLC did not contain a sufficient percentage of burned locations in any part of Europe, a parallel analysis incorporates nationally maintained landslide inventories from several European countries. Analysis of normalized seven-day accumulated precipitation for sites across all regions shows that post-wildfire landslides are preceded by less precipitation than landslides without antecedent wildfire events. This supports the hypothesis that fire increases the rainfall-driven landslide hazards. A regional examination of landslide susceptibility using normalized triggering storm volumes as a proxy indicator reveals a distinct sensitivity to fire across several regions of the western US. However, in other regions wildfire appears to have a limited or even opposite impact on landslide susceptibility. Unburned locations also tend to see a sharper ramp-up of precipitation leading up to the date of the landslide relative to burned sites in regions of the Western US. In other regions the storm timing is similar or, a in Central America, even longer in burned locations. The landslide-triggering storms of post-fire landslides also exhibit different seasonality from other rainfall-triggered landslides, with a variety of seasonal shifts ranging from approximately six months in the Pacific Northwest of the US to one week in the Himalayas. These results suggest that the apparent inconsistency in the impact of wildfire on landslide hazards may be due to a combination of two factors: interactions between fire and precipitation seasonality and variability in soils and vegetation. For example, in the Intermountain West of the US and Southeast Asia landslides are preceded by a thirty-day or longer dry period while in all other regions there is no difference in the precipitation prior to the triggering storm event, which suggests different landslide mechanisms such as dry ravel, which rely on low rather than high soil moisture levels, may be a factor. Overall, this work offers an exploration of regional differences in the characteristics of rainfall-triggered landslides over a broad spatial scale encompassing a variety of climates, terrains, and ecoregions.

Flooding causes serious impacts on the old town of Venice, its residents, and its cultural heritage. Despite this existence-defining condition, limited scientific knowledge on flood risk of the old town of Venice is available to support decisions to mitigate existing and future flood impacts. Therefore, this study proposes a risk assessment framework to provide a methodical and flexible instrument for decision-making for flood risk management in Venice. We first use a state-of-the-art hydrodynamic urban model to identify the hazard characteristics inside the city of Venice. Exposure, vulnerability, and corresponding damage are then modeled by a multi-parametric, micro-scale damage model which is adapted to the specific context of Venice with its dense urban structure and high risk awareness. Furthermore, a set of individual protection scenarios are implemented to account for possible variability in flood preparedness of the residents. This developed risk assessment framework was tested for the flood event of 12 November 2019 and proved able to reproduce flood characteristics and resulting damage well. A scenario analysis based on a meteorological event like 12 November 2019 was conducted to derive flood damage estimates for the year 2060 for a set of sea level rise scenarios in combination with a (partially) functioning storm surge barrier, the Modulo Sperimentale Elettromeccanico (MOSE). The analysis suggests that a functioning MOSE barrier could prevent flood damage for the considered storm event and sea level scenarios almost entirely. A partially closed MOSE barrier (open Lido inlet) could reduce the damage by up to 34 % for optimistic sea level rise prognoses. However, damage could be 10 % to 600 % higher in 2060 compared to 2019 for a partial closure of the storm surge barrier, depending on different levels of individual protection.

Due to the influence of the monsoon, river runoff in most of China’s river basins is mainly concentrated in the flood season. The distribution is extremely uneven during the year and between the year. It needs to be fully utilized by the reservoir to bring serious challenges to the daily management. Therefore, analyzing the seasonal variation of storm floods, scientifically and rationally staging the flood season can not only give full play to the comprehensive benefits of the reservoir, but also be an inevitable requirement for coordinating reservoir flood control and power generation. Aiming at the several commonly used methods of flood season staging, the case study is carried out, and the applicable conditions are analyzed. Based on these, three new staging methods are proposed. Among them, the improved change point analysis method adopts the linear and nonlinear joint fitting, which improves the commonly used mean value calculation method. In theory, the non-uniformity and seasonality of the reservoir water are more carefully considered, and the flood season is considered to some extent. The distribution law and continuity of floods along the time course; the projection method has a similar theoretical system with the vector statistical method based on the annual maximum sampling method, both of which are based on the intensity of the points, the difference is the point of the latter is projected on the circumference, the partitioning result is selected by manual experience, and the human influence factor is large. The new method is to project the point on the straight line, and quantitatively gives the partitioning method, and is also applicable to the maximum flow of different sequences. The case of the same time, the dynamic clustering method divides the sample set into several subsets according to the similarity between samples, and has the advantage that the calculation amount is small and the genus of the sample can be changed compared with the system clustering method. The research results can provide reference for the reasonable adjustment of the reservoir flood season.

Rainfall microphysical characteristics including raindrop fall speed, axis ratio, and canting angle were measured through field observations by using a high-speed optical disdrometer (HOD) during and after tornadic severe storm passage. High and low wind and turbulence characteristics were observed during and after passage, respectively, which provided an opportunity to compare the effects of the different wind and turbulence characteristics on raindrop characteristics. During passage, 9.4% of the raindrops larger than 1.0 mm in volume equivalent diameter (D) were identified as subterminal, whereas only 0.5% of the raindrops of the same size were detected as subterminal after passage. Contrary to findings in literature, we could not find any distinct superterminal fall speed behavior for raindrops with D < 1.0 mm during or after passage. For raindrops with D > 2.0 mm, deviations of the axis ratio distribution from the predicted distribution for the equilibrium raindrops were observed, and the deviations during passage were larger than those after passage. The deviations of the axis ratio distributions from the predicted distributions for the equilibrium raindrops were also observed for midsized (1.0 < D < 2.0 mm) raindrops; however, these deviations during and after passage were of similar magnitude. The canting angle distribution for raindrops with D > 2.0 mm was found to have the mean value of approximately 0° both during and after passage and the standard deviation values of 24.7° during passage and 13.6° after passage. This study shows the clear influence of wind on various rainfall microphysical characteristics and documents the observed value ranges of these characteristics under strong wind that are of importance for a number of rainfall applications, including radar rainfall retrievals and rainfall modeling.

Commercial microwave links (CMLs) can be used as opportunistic and unconventional rainfall sensors by converting the received signal level into path-averaged rainfall intensity. As the reliable reconstruction of the spatial distribution of rainfall is still a challenging issue in meteorology and hydrology, there is a widespread interest in integrating the precipitation estimates gathered by the ubiquitous CMLs with the conventional rainfall sensors, i.e. rain gauges (RGs) and weather radars. Here, we investigate the potential of a dense CML network for the estimation of river discharges via a semi-distributed hydrological model. The analysis is conducted in a peri-urban catchment, Lambro, located in northern Italy and covered by 50 links. A two-level comparison is made between CML- and RG-based outcomes, relying on 12 storm/flood events. First, rainfall data are spatially interpolated and assessed in a set of significant points of the catchment area. Rainfall depth values obtained from CMLs are definitively comparable with direct RG measurements, except for the spells of persistent light rain, probably due to the limited sensitivity of CMLs caused by the coarse quantization step of raw power data. Moreover, it is shown that, when changing the type of rainfall input, a new calibration of model parameters is required. In fact, after the recalibration of model parameters, CML-driven model performance is comparable with RG-driven performance, confirming that the exploitation of a CML network may be a great support to hydrological modelling in areas lacking a well-designed and dense traditional monitoring system.

To forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition,” i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. Storm-following nests are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Project, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC–TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multistorm nesting approach to improve the simulation of TC–TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multistorm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multistorm approach demonstrated TC intensity forecast improvements, including more realistic TC–TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System.

Accurate estimation of the potential “upper limit” for extreme precipitation is critical for dam safety and water resources management, as dam failures pose significant risks to life and property. Methods used to estimate the theoretical upper limit of precipitation are often outdated and in need of updating. The rarity of extreme events means that old storms with limited observational data are often used to define the upper bound of precipitation. Observations of many important old storms are limited in spatial and temporal coverage, and sometimes of dubious quality. This reduces confidence in flood hazard assessments used in dam safety evaluations and leads to unknown or uncertain societal risk. This paper describes a method for generating and applying ensembles of high-resolution, state-of-the-art numerical model simulations of historical past extreme precipitation events to meet contemporary stakeholder needs. The method was designed as part of a research-to-application-focused partnership project to update state dam safety rules in Colorado and New Mexico. The results demonstrated multiple stakeholder and user benefits that were applied directly into storm analyses utilized for extreme rainfall estimation, and diagnostics were developed and ultimately used to update Colorado state dam safety rules, officially passed in January 2020. We discuss how what started as a prototype research foray to meet a specific user need may ultimately inform wider adoption of numerical simulations for water resources risk assessment, and how the historical event downscaling method performed offers near-term, implementable improvements to current dam safety flood risk estimates that can better serve society today.

Methods of rainstorm disaster risk monitoring based on retrieved satellite rainfall data are studied. Due to significant regional differences in global rainstorm disasters, they are not only affected by geographical location, topography, and rivers, but also by climate events. It is necessary to study disaster-causing factors, hazard-formative environments, and hazard-affected incidents of rainstorm disasters based on the climate distribution characteristics of precipitation and rainstorm disasters worldwide. According to a global flood disaster data-set from the last 20 years, the top four flood disaster causes (accounting for 96.8% in total) related to precipitation, from most to least influential, are heavy rain (accounting for 61.6%), brief torrential rain (16.7%), monsoonal rain (9.4%), and tropical cyclone/storm rain (9.1%). The dynamic global rainstorm disaster threshold is established using global climate data on 3319 rainstorm-induced floods and rainfall retrieved by satellites in the last 20 years. Taking the 7-day accumulated rainfall, 3-hour and 12-hour maximum rainfall, 24-hour rainfall, rainstorm threshold, and others as the main parameters, a rainstorm intensity index is established. The calculation method and global map of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are formed based on the terrain, river datasets, the population, and economic datasets. Finally, a satellite remote sensing rainstorm disaster risk monitoring model is established including these three factors (rainstorm intensity index, hazard-formative environment factor, and hazard-affected body factor). The results show that the model can well describe the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020.

This paper examines if wind might be an additional energy source for solar powered, crewed Mars missions during dusty days. Wind data from Viking Lander 2 is analyzed from a wind engineering point of view, as it is done on Earth, to evaluate wind turbine sites. It is assumed that wind energy will not be the primary energy source used on a crewed Mars mission but an additional option during times of global dust storms, when solar power is suffering from an increase of atmospheric optical depth, which is seen as one of the largest drawbacks of solar arrays. In order to evaluate if wind energy might be a reliable energy source during dust storms, when the energy yield of solar cells is reduced, it will be investigated whether wind strength has a positive correlation with increased atmospheric optical depth. This is, in case wind speed is generally capable of providing a significant amount of power, a further requirement if wind turbines should compensate the power loss of solar arrays during increased atmospheric optical depth. For a first estimate of the amount of wind turbines needed to maintain energy output during a storm a case study is done which regards power production during the 1977b global dust storm.

Lasting updrafts are necessary to produce severe hail; conventional wisdom suggests that extremely large hailstones require updrafts of commensurate strength. Because updraft strength is largely controlled by convective available potential energy (CAPE), one would expect environments with larger CAPE to be conducive to storms producing larger hail. By systematically varying CAPE in a horizontally homogeneous initial environment, we simulate hail production in high-shear, high-instability supercell storms using Cloud Model 1 and a detailed 3D hail growth trajectory model. Our results suggest that CAPE modulates the updraft’s strength, width, and horizontal wind field, as well as the liquid water content along hailstones’ trajectories, all of which have a significant impact on final hail sizes. In particular, hail sizes are maximized for intermediate CAPE values in the range we examined. Results show a non-monotonic relationship between the hailstones’ residence time and CAPE due to changes to the updraft wind field. The ratio of updraft area to southerly wind speed within the updraft serves as a proxy for residence time. Storms in environments with large CAPE may produce smaller hail because the in-updraft horizontal wind speeds become too great, and hailstones are prematurely ejected out of the optimal growth region. Liquid water content (LWC) along favorable hailstone pathways also exhibits peak values for intermediate CAPE values, owing to the horizontal displacement across the midlevel updraft of moist inflow air from differing source levels. In other words, larger CAPE does not equal larger hail, and storm-structural nuances must be examined.

Validation of synthetic storm technique (SST) has been done for prediction of attenuation due to rain over a hilly, high-rainfall, tropical location, Shillong (25°N, 91°E), India. In this letter, considering one year of rain attenuation and rain rate data shows that SST predicted attenuation overestimates while comparing the available experimental result. Storm speed has been found to have no significant effect on the attenuation prediction by SST. Second-order rain attenuation prediction, i.e., prediction of fade slope, has also been studied. Fade slope is found to have been overestimated by SST for all categories of rain events at 20.2- and 30.3-GHz frequency. Exceedance plot of fade duration by SST shows an overestimation for higher frequency and underestimation for lower frequency.

This paper studies the response of the ionospheric parameters critical frequency (foF2), their height (hmF2), and Total Electron Content (TEC) at mid, low, and near-equatorial latitudes of the South American sector during the intense geomagnetic storm of 26 August 2018. The ionospheric response at the beginning of the main phase was different depending on latitude (in general, there were decreases in foF2 at near-equatorial and low latitudes and small increases at mid-latitudes). During the recovery, positive storm effects in foF2 and TEC were observed almost all day on 26 August 2018 overall the stations along all the latitudes and also on 27 August. The initial effects were possibly caused by a weak prompt penetration electric field while the enhanced ratio of thermosphere neutral composition i.e. [O]/[N2] was considered as the main cause for the positive storm effects during the recovery phase.

This study aims to retrieve cloud top height (CTH)--excluding cirrus--using passive microwave radiometer observations combined with humidity and temperature profiles. A machine-learning-based approach, combining neural network and gradient boosting methods, is used with Cloud Profiling Radar observations as input. The subsequently derived microwave CTH predictions show a mean average error of 2.1 km and a correlation index of 0.8. The algorithm is used to retrieve the CTH during Hurricane Maria and during a mid-latitude autumn storm. This new algorithm will allow to provide estimates of CTH, at world scale, for a 20-year period.

The problem of disturbances in the parameters of the F2 layer and upper ionosphere during the days preceding onset of a magnetic storm is known already for many decades. Many publications have been dedicated to analysis of these disturbances both in the critical frequency and height of the F2 layer and in the total electron content. The majority of researchers have drawn a conclusion that such disturbances are observed prior almost to every storm, positive events (an excess of the values in the prestorm period over the corresponding values on a geomagnetically quiet day) prevailing. Moreover, some authors claimed that the aforementioned disturbances could be considered as precursors of the coming magnetic storm. A concept of the so-called Q-disturbances, according to which the disturbances during the prestorm days are not related to the coming storm but are a result of several processes (meteorological influence on the ionosphere, changes in the magnetosphere-ionosphere interaction) which sometimes cause deviations of ionospheric parameters is an alternative to the precursor concept. Arguments are presented in favor of the precursor concept. These arguments are, first of all, based on the existence of a dependence of parameters of the prestorm disturbances on parameters of the coming storm. The dependencies on the magnetic storm intensity, local time of the storm onset SO, and time from the disturbance to SO present the strongest arguments against the Q-disturbance concept. Numerous examples of these dependencies are presented. The recent publications with new experimental data on the foF2 and TEC behavior in the prestorm period are discussed. Arguments in favor of the prestorm concept presented in these publications are briefly considered.

Absorption level by riometer was estimated at high-latitudes during four moderate magnetic storms that occurred in 2018 and were similar by several features. The data of riometer absorption at 30 MHz was obtained from Sodankyla Geophysical Observatory in Finland (67.36°N, 26.63°E). Particle precipitations were estimated by POES satellite data. According to our results, the character of development of the magnetic disturbance and the similarity/difference of Space Weather parameter variations (IMF magnitude, solar wind parameters, Dst variation) did not played the leading role in the absorption peak value. The absorption level in the auroral oval during the considered similar moderate magnetic disturbances depended on the combination of factors: simultaneous electron bursts of particular energies, the number of precipitating particles in these bursts and the moment of the storm at which such precipitation bursts occurred. The highest absorption was caused by the large electron precipitations with energies of >40 keV and >130 keV that occurred just after the maximal storm development at the very beginning of the recovery phase of the storm.

Offshore wind turbines (OWTs) must withstand harsh environmental loads over their 20- to 30-year design life. Fragility analysis investigates the probability of damage over a range of hazard intensities and is integral to a performance-based engineering approach. The focus of this paper is on monopiles, which are widely used to support OWTs in water depths up to around 40m. The paper presents a fragility analysis of monopiles in extreme storms in terms of geotechnical performance, measured by permanent rotation of the foundation. Geotechnical fragility has so far not been comprehensively addressed due to the challenge of predicting soil behaviour under cyclic loading and estimating the probability of extreme responses. On the latter, the paper develops efficient Karhunen-Loeve representations of wind and wave loading that can be combined with inexpensive probabilistic methods to compute fragility. The framework was demonstrated using a representative scenario of a 5MW OWT installed in clay. Non-linear foundation response was captured by a dynamic 3D finite element model. Fragility curves were generated using subset simulation for storms with return periods (RPs) from 1 to 100 years. Fragility during extreme storms (with 50- and 100-year RPs) was significantly higher than storms with RPs of 10 years or less.

Vertical wind profiles of selected tropical cyclones over the South China Sea are studied for the first time using dropsonde measurements by a fixed-wing aircraft of the Hong Kong Government. They are studied in a number of aspects which have not been conducted before for storms over the South China Sea. First the strengthening and weakening of the tropical cyclones are analyzed based on the radial wind profiles, namely, inflow and outflow, particularly over the atmospheric boundary layer. Second, the vertical wind profiles are fitted using the commonly considered wind profile models reported in the literature. This would have significant contributions to wind engineering applications in the region. Finally, the performance of a mesoscale meteorological data in the analysis and nowcast of the vertical profiles of tropical cyclones are studied (the model has not assimilated the dropsonde data in the analysis). The results are unique for tropical cyclones over South China Sea and would serve as useful reference for the studies of tropical cyclones in this ocean basin.

Recent numerical modeling studies demonstrate that dry tropical cyclones can be stably sustained via a supply of surface sensible heat flux. This raises questions of whether surface sensible heat flux (SHX) and latent heat flux (LHX) have the same effect on the intensity evolution of tropical cyclones. An estimation of equivalent potential temperature budget in the boundary layer shows that LHX leads to larger increase in equivalent potential temperature than SHX even when they possess the same magnitude. By formulating these two kinds of surface heat fluxes with the same mathematical framework, the simulated intensifications of moist and dry tropical cyclones are compared, with the former driven exclusively by LHX and the latter by SHX. Results show significantly larger intensification rates for the tropical cyclone driven by LHX than that by SHX, revealing low effectiveness of SHX in the intensification of tropical cyclones. The diabatic heating in the moist tropical cyclone occurs accompanying the convection, while it is merely pronounced near the surface in the dry tropical cyclone and is decoupled from the dry convection. A new surface pressure tendency equation is proposed, without incorporating the implicit pressure tendency term on the right-hand side. The budget analysis indicates that the SHX is less effective than LHX in lowering surface central pressure and therefore in tropical cyclone intensification. A series of sensitivity experiments suggest that the threshold of energy input required for spinning up a tropical cyclone is lower in the form of LHX than that of SHX.

Precipitation downscaling, which is similar to the mechanism of single-image super-resolution (SR), aims to improve the spatial resolution of rain maps. It is of great practical value and theoretical significance. This letter presents a new deep precipitation downscaling (DPD) method, named auxiliary guided spatial distortion (AGSD) network, motivated by SR techniques. Specifically, an auxiliary guided module (AGM), which takes multiple meteorological elements (e.g., temperature, relative humidity, and wind) as input, is proposed for getting more accurate rain map features. Meanwhile, a simple but effective spatial distortion module (SDM) is proposed. Benefitting from SDM, the DPD model can rectify the rain map via terrain correlation. Furthermore, to improve the model performance among various rain intensity (including small rain, moderate rain, heavy rain, and storm), a threat score-driven pseudo threat-score (PTS) loss is presented. Experimental results compared with state-of-the-art methods demonstrate the superiority of the proposed method.

The present study investigates the effect of increasing sea surface temperatures (SSTs) on tropical cyclone (TC) frequency using the high-resolution Australian Community Climate and Earth-System Simulator (ACCESS) model. We examine environmental conditions leading to changes in TC frequency in aqua-planet global climate model simulations with globally uniform sea surface temperatures (SSTs). Two different TC tracking schemes are used. The Commonwealth Scientific and Industrial Research Organization (CSIRO) scheme (a resolution-dependent scheme) detects TCs that resemble observed storms, while the Okubo–Weiss zeta parameter (OWZP) tracking scheme (a resolution-independent scheme) detects the locations within “marsupial pouches” that are favorable for TC formation. Both schemes indicate a decrease in the global mean TC frequency with increased saturation deficit and static stability of the atmosphere. The OWZP scheme shows a poleward shift in the genesis locations with rising temperatures, due to lower vertical wind shear. We also observe an overall decrease in the formation of tropical depressions (TDs) with increased temperatures, both for those that develop into TCs and non-developing cases. The environmental variations at the time of TD genesis between the developing and the non-developing tropical depressions identify the Okubo–Weiss (OW) parameter and omega (vertical mass flux) as significant influencing variables. Initial vortices with lower vorticity or with weaker upward mass flux do not develop into TCs due to environments with higher saturation deficit and stronger static stability of the atmosphere. The latitudinal variations in the large-scale environmental conditions account for the latitudinal differences in the TC frequency in the OWZP scheme.

Asian dust storms have long been a major environmental concern in China, affecting the lives of about one billion people. However, it is unclear whether the mechanisms responsible for Asian dust storms during the Holocene varied on different timescales, and thus it is unclear whether there was a shift from a natural forcing to an anthropogenic forcing of dust storms. We reconstructed a high-resolution Holocene record of dust storms from the sediments of an undisturbed alpine lake on the Chinese Loess Plateau. We found that Asian dust storm activity generally increased during the Holocene, with the largest fluctuations occurring during the past 2000 years. The increase in dust storm activity was in contrast to the decrease in East Asian winter monsoon (EAWM) intensity during the Holocene, indicating that the EAWM played a limited role in modulating dust storms. By contrast, the increase in dust storms corresponded to a decrease in East Asian summer monsoon (EASM) precipitation. This demonstrates that EASM precipitation was the dominant control of dust storm activity on a millennial timescale, because decreased EASM precipitation expanded the desert area and thus increased the dust storm activity. The increasing intensity of human activity in the region since the Bronze Age resulted in an acceleration of dust storm activity against the background of decreased EASM precipitation. As human disturbance continued to intensify, beginning at least at ~2 cal ka BP, increased dust storms were closely linked to increasing human populations in the dust source regions, and there is a strong temporal coherence between increased dust storms and higher EASM precipitation. This was completely different from when natural processes are dominant. During that period, fewer dust storms occurred during periods of a strengthened EASM. Therefore, there was a shift from a natural forcing to an anthropogenic forcing of dust storms on a multi-decadal to centennial timescale, and was a mode in which “human activity overtook the EASM as the dominant control of the Earth surface system”.

Mesoscale convective systems (MCSs) supply a substantial portion of warm-season rainfall to the Great Plains of North America, and they are responsible for severe weather and flooding across the central United States. However, little is known about past behaviour and long-term drivers of these systems, limiting our ability to predict future extreme weather patterns in this region. Here, we generate a 20,000-year-long multiproxy record of storm intensity and hydroclimate variability from central Texas in the southern Great Plains and use transient climate model simulations to diagnose the dynamics of reconstructed changes in the climate of this region. We find that southern Great Plains storm intensity responded dynamically to external forcings associated with glacial boundary conditions and orbital forcing via changes in seasonal land surface warming. Springtime land surface warming steepens the zonal pressure gradient, producing an intensified southerly Great Plains low-level jet, enhancing southerly moisture transport and increasing springtime MCS intensity. Climate models predict a strengthening of the low-level jet in response to future warming, which our study suggests will lead to enhanced MCS activity and an increase in extreme weather across the Great Plains. Shifts in the seasonal timing of land surface warming set the severity of storm systems in the southern Great Plains since the last glacial, according to a hydroclimate proxy record from Texas and palaeoclimate modelling.

Salt marshes are important coastal habitats and provide ecosystem services to surrounding communities. They are, however, threatened by accelerating sea-level rise and sediment deprivation due to human activity within upstream catchments, which result in their drowning and a reduction in their extent. Rising seas are also leading to an expansion of coastal flooding protection infrastructures, which might also represent another serious if poorly understood threat to salt marshes due to effects on the resuspension and accumulation of sediment during storms. Here, we use observations from the Venice Lagoon (Italy), a back-barrier system with no fluvial sediment input recently protected by storm-surge barriers, to show that most of the salt-marsh sedimentation (more than 70% in this case) occurs due to sediment reworking during storm surges. We also prove that the large, yet episodic storm-driven sediment supply is seriously reduced by operations of storm-surge barriers, revealing a critical competition between the objectives of protection against coastal flooding and preservation of natural ecosystems. Without complementary interventions and management policies that reduce barrier activations, the survival of coastal wetlands is even more uncertain. Sediment supply to the Venice Lagoon is substantially reduced by flood barriers inhibiting storm-related sediment reworking and transport, according to observations through multiple storm events before and after barrier installation.

Knutson et al. (BAMS 101:E303–E322, 2020) combined results from many studies to produce distributions of how tropical cyclone frequency and average intensity may change in the future. These distributions can be applied to risk models by using them to simulate multiple realisations of possible changes in future storm climate. Ideally the simulations would be performed to maintain consistency between the changes in frequency and average intensity, but it is not obvious how to do that, or whether it is even possible. Considering North Atlantic cyclones, we test three methods for simulating from Knutson et al. and find two that are consistent and one that is not. Using the best of the methods we find that there are no future scenarios in which weak storms increase in frequency while very intense storms decrease in frequency. We then apply changes in frequency and average intensity to a risk model for annual maximum intensity. After integrating over the uncertainty, we find that on a conditional basis all storms become more intense under climate change, and that the annual probability of the most intense storms increases by 19%. Annual maximum intensity decreases at intermediate levels of intensity as a result of the non-linear propagation of uncertainty. We also show that the changes in risk implied by the Knutson et al. results cannot be well approximated if the propagation of uncertainty is ignored. Future work should involve updating these results with tropical cyclone projections from the latest high-resolution climate models.

This work studies the characteristics of thunderstorms that cause lightning-caused wildfires in Catalonia, north-east Iberian Peninsula, using lightning and weather radar data. Although thunderstorms produce ~57 000 cloud-to-ground (CG) flashes yearly in Catalonia, only 1 in 1000 end up as a flaming wildfire. Characterisation of thunderstorms that ignite wildland fires can help fire weather forecasters identify regions of increased ignition potential. Lightning data and radar products like maximum reflectivity, echo tops heights and equivalent liquid content were obtained over a 7-year period. Characteristics of thunderstorms that ignite wildfires are examined including storm motion, duration, morphology and intensity. It was found that most probable ignition candidates are lightning associated with cellular thunderstorms and non-linear systems. Radar reflectivity values for lightning that ignites wildfires were found to be below average, these morphological types favouring the occurrence of lightning outside regions of high reflectivity, where precipitation reaching the ground is low or non-existent. Thunderstorms that ignite wildfires are typically of low intensity, with a CG flash rate below average. Most ignitions occur during the maturity phase when the CG flash rate is the highest. A better scientific understanding of the thunderstorms that cause lightning wildfires will help improve early firefighting response.

The Dooars region of West Bengal in India is a major tea producing region that contributes around 25% of the national tea yield. Changes in weather patterns along with the increased frequency of drought, storms, flood, etc. are likely to affect the tea industry adversely as tea production is reliant on the climate of the tea-growing region. In spite of the tea industry being the primary contributor of the Dooars economy, to date, the impact of climatic variables on tea yield in Dooars region remains unexplored. Here, we have developed a panel dataset that includes monthly data of the tea gardens of Dooars region over a 10-year period and statistically analysed the effects of climatic variables including temperature, precipitation, drought intensity, magnitude of warm-wet condition and precipitation intensity on tea yield. Overall, our seasonal analysis suggested that higher temperature during summer and monsoon seasons affected tea yield. Contrastingly, higher temperature during winter months and summer and winter rainfall were found to be beneficial for the increase in tea yield. An excessive and sporadic rainfall and a combination of hotter and wetter weather condition during monsoon months had a detrimental effect on tea yield. Finally, projections using climate models under different emission scenario predicted reduction of monsoon production under extreme carbon emission. The analyses and predictions of our study will be beneficial for tea garden managers of Dooars region in particular and northern India in general in adopting strategies to prevent the tea plantations from being affected due to climate change.

Occasionally, a winter storm will dispense its fury from coast to coast. However, most often, a storm is captivating due to some unusual regional circumstance that has to do with its magnitude, loc...

Mangroves have been recognized as soft structures that provide coastline protection. The capability of dampening waves helps minimize destruction from catastrophic events including erosive wave attacks, torrential storms, and tsunamis. Mangroves act as the first line of coastal defense in natural tragedies such as during the Super Typhoon Haiyan 2013 and Indian Ocean Tsunami 2004, whereby the leeward mangrove area encountered less damage than the unprotected area. This has further brought the attention of researchers to study the attenuation performance of these coastal vegetations. Based on an extensive literature review, this paper discusses the attenuation mechanism of mangroves, the factors influencing the dissipation performance, studies on mangrove dissipation via different approaches, the dissipation efficiency, mangrove conservation and rehabilitation efforts in Malaysia and implementation of mangrove as coastal bio-shield in other countries. The study highlights that mangrove parameters (such as species, width, density etc.) and wave parameters (such as wave period and incident wave height) are among the contributing factors in mangroves-induced wave attenuation, with different efficiency rates performed by different mangroves and waves parameters. Towards that end, several improvements are proposed for future research such as to incorporate all influencing dissipation factors with specific analysis for each species of mangroves, to perform validation on the studied mangroves attenuation capacity in different settings and circumstances, as well as to address the extent of protection by the rehabilitated mangroves. A systematic and effective management strategy incorporating ecological, forestry, and coastal engineering knowledge should be considered to ensure a sustainable mangroves ecosystem and promising coastline protection by mangroves. Doi: 10.28991/cej-2021-03091772 Full Text: PDF

Sand and Dust storms are considered a major natural disaster that cause many damages to society and environment in Iraq and surrounded deserted regions. Two spring sand/dust storms on May in two different years were synoptically analyzed. These sand/dust storms were compared in terms of dust surface concentration from NMMB/BSC-Dust model, sea level pressure, surface wind vector, satellite vegetation index and stations rainfall. The findings of this sand/dust storms comparison indicate that Iraq in spring may be affected by two types of wind one dust storm initiated by Shamal which have long occurred in this region and caused frequent dust storms in spring and second by Al-Khamsian. Dust storm in 2012 is massive than sand/dust storm in 2018 where the highest dust surface concentration is reached to (7700 μg/m3) in 22 May 2012 and about (3100 μg/m3) in 11 May 2018. Increase in vegetation cover over Iraq in 2018 was about 23% more than in 2012. Rainfall level in season (2017-2018) was higher than in rainfall season (2011-2012) in Iraqi dust sources regions. Low pressure gradient, less strong wind, rise in rainfall level and enhancement in vegetation cover are contributed to decrease the storm concentration of 2018 roughly by half.

The Nigerian Total Electron Content (NIGTEC) is a regional neural network-based model developed by the Nigerian Centre for Atmospheric Research to predict the Total Electron Content (TEC) at any location over Nigeria. The addition of the disturbance storm time (Dst) index as one of NIGTEC's input layer neurons raises a question of its accuracy during geomagnetic storms. In this paper, the capability of NIGTEC in predicting the variability of TEC during geomagnetic storms has been assessed. TEC data predicted by NIGTEC is compared with those derived from Global Navigation Satellite System (GNSS) over Lagos (6.5oN, 3.4oE) and Toro (10.1oN, 9.12oE) during the intense storms in March 2012 and 2013. The model's predictive capability is evaluated in terms of Root Mean Square Error (RMSE). NIGTEC reproduced a fairly good storm time morphology in VTEC driven by the prompt penetration electric field and the increase in thermospheric O/N2. Nevertheless, it failed to predict the increase in TEC after the intense sudden impulse of 60 nT on 8 March 2012. And it could not capture the changes in VTEC driven by the storm time equatorward neutral wind especially during 18:00–24:00 UT. Consequently, the RMSEs were higher during this time window, and the highest RMSE value was obtained during the most intense storm in March 2012.

This study aims to investigate the effectiveness of the low impact development (LID) practices on sustainable urban flood storm water management. We applied three LID techniques, i.e. green roof, permeable pavements and bioretention cells, on a highly urbanized watershed in Istanbul, Turkey. The EPA-SWMM was used as a hydrologic-hydraulic model and the model calibration was performed by the well-known Parameter ESTimation (PEST) tool. The rainfall-runoff events occurred between 2012 and 2020. A sensitivity analysis on the parameter selection was applied to reduce the computational cost. The Nash-Sutcliffe efficiency coefficient (NSE) was used as the objective function and it was calculated as 0.809 in the model calibration. The simulations were conducted for six different return periods of a storm event, i.e. 2, 5, 10, 25, 50 and 100 years, in which the synthetic storm event hyetographs were produced by means of the alternating block method. The results revealed that the combination of green roof and permeable pavements have the major impact on both the peak flood reduction and runoff volume reduction compared to the single LIDs. The maximum runoff reduction percentage was obtained as 56.02% for a 10 years return period of a storm event in the combination scenario. HIGHLIGHTS The PEST software is used for the auto-calibration of US EPA-SWMM and the calibration results are statistically significant.; The green roof application has more impact on both the peak discharge reduction and the volume reduction than both the permeable pavements and bioretention cells in the highly urbanized Ayamama watershed.; The combination of green roof and permeable pavements has substantial effect on flood mitigation.

Dust storms are common over north-west parts of India during the pre-monsoon season. The main objective of this study is to assess the movement of dust over Indian region during a dust event using the dust aerosol optical depth (AOD) forecast from an operational numerical weather prediction model. Observed values of visibility, wind speed are used to identify the dust events over a point location. In addition, satellite observations for the days prior to, during and after dust events are utilized to ascertain the dust event. The performance of operational NCMRWF Unified Model (NCUM) is analyzed in predicting the values of dust AOD during dust events over north west parts of India. Predicted values of dust AOD are compared with observations available from satellite and ground based network of Aerosol Observation Network (Aeronet). The dust event of 25th May, 2016 observed at Jaipur and Lucknow is well captured by NCUM up to Day-3 forecast. The comparison of predicted dust AOD at point locations Jaipur and Kanpur reveals that NCUM is capable in predicting the high values of AODs during dust event.

High-impact weather events, such as thunderstorms and dust storms, are aspects of a changing climate that are likely to have an adverse effect on society. A number of such severe weather events struck Delhi and adjoining areas during the months of April, May and June of the year 2018. Three events observed during May-June have been analyzed using observations from C-Band Polarimetric Doppler Weather Radar (DWR) and ground based Global Navigational Satellite (GNSS) receiving system installed at Mausam Bhawan, New Delhi. Here, an attempt has been made to study the data regarding these unusual events from DWR observations especially of polarimetric nature and cross verify it with the data obtained from GNSS receiving system. Reflectivity of more than 60 dbZ was observed in all the events by the DWR system except on 9 June when a squall line formed with maximum reflectivity around 54 dBZ and the wind velocity increased upto 120 knots on the same date on few occasions and generally varied between 45-60 knots during the period of the storms. The height of these storms varied between 12 kms and 13.6 kms except on 9 June when the storm height was observed to be more than 15 kms by the DWR. Though the maximum reflectivity was a bit less on 9th June but the vertical extent of the clouds was greater and therefore the estimated value of IPWV from GNSS had a maximum of 67 mm as compared to the values in the range of 40 to 45 mm for other storm events. Apart from the single-pol DWR observations, the dual-pol products presented a more comprehensive ingredients of the storms in respect of the size, shape and variety of the hydrometeors and also their non-meteorological nature. The information regarding the concentration of hydrometeors has also been a positive point while analyzing through the eyes of a dual-pol radar. These multiple thunderstorms have been discussed to bring out some of their important features and a good amount of agreement has been observed between the data obtained from dual-pol DWR system and GNSS.

Murray-Darling Freshwater Research CentreMDFRC item.This paper assesses the capacity of a small (450 m2) constructed wetland in Victoria, Australia, to decrease nutrient loads generated by both background flows and storm events within the period March 1993 to January 1995. Under Australian conditions the effectiveness of wetlands in controlling diffuse pollution is influenced by extreme hydrological events which often carry a large proportion of the annual load from the catchment. The wetland retained a varying proportion of the nitrogen and phosphorus load over a range of hydrological events and seasonal conditions. The wetland also acted as a source of these nutrients on occasions. An annual nutrient budget was calculated for the period February 1994 to January 1995 by measuring all loads between and during storm events entering and leaving the wetland. The wetland ‘retained' 10 kg N yr−1 (23 g N m−2 yr−1) of nitrogen and 1.24 kg P yr−1 (2.80 g P m−2 yr−1) of phosphorus, representing 11 and 17%, respectively of the incoming nutrient loads for the budget period.Storm event size influenced the impact of the wetland on the nutrient loads generated in these events. Increasing event volumes generally resulted in decreased nutrient interception. The results of this study indicate that for significant load reduction to occur the scale of the wetland should be such that there is sufficient residence time to enable wetland processes to operate. Small strategically located wetlands high up in catchments which will have a cumulative impact on runoff generated in large storm events are likely to be more effective in intercepting nutrient loads than larger downstream structures.

Tropical Cyclone (TC) is one of the most devastating and deadly weather phenomena and causes loss of life and property. The Bay of Bengal (BoB) is a potentially energetic region for the development of cyclonic storms, accounting about 6% of the global annual total number of cyclonic storms. Accurate prediction of these storms is essential to avoid loss of lives and damage to properties. In this regard, the reduction of errors associated with the track and intensity forecast of the TCs is an important aspect to disseminate more reliable information to the disaster management. The present study examined the performance of Advanced Research Weather Research and Forecasting (WRF-ARW) model for the simulation of track and intensity of TCs over BoB during 1999-2013. The numerical simulations were carried out for 38-cyclones (during 1999-2013) using different microphysical parameterization (MP), cumulus parameterization (CP) and planetary boundary layer (PBL) schemes of the WRF-ARW model. The total 1133 simulations were performed by using 11 combinations with four MPs [Lin et al. (LIN), Ferrier (new Eta) (FERR), WSM 6-class Scheme graupel scheme (WSM6) and Thompson (THOMP)], four CPs [Kain-Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell-Devenyi (GD) and New Grell Scheme (NG)] and three PBLs (Yonsei University scheme (YSU), Mellor-Yamada-Janjic (Eta) TKE (MYJ) and Asymmetrical Convective Model version 2 (ACM2)] to identify the best logical combination of these schemes to predict the track and intensity of TCs over BoB. The best combination of CP and PBL schemes were more influenced the simulations of intensity and track of the cyclones compared to the MP schemes. Further, the simulations were conducted for intense storms with different initial conditions and suggested that the combination of KF + LIN + YSU provided better simulations of the storms for 72h over the BoB and also observed the decreased track error from 1999 to 2013 cyclones. This clearly indicated that the improvement in the initial conditions and parameterization schemes of the WRF-ARW model. This study is very useful for the cyclone warning centers, disaster management centers, real-time governance system and researchers to provide better management for coastal community during the cyclone events.

Within the North Indian Ocean basin, tropical cyclone (TC) activity over the Bay of Bengal (BoB) is substantially greater than over the Arabian Sea (AS). The authors attempt to quantify the roles of specific environmental factors in order to understand the reasons for this difference between the two basins. Environmental variables are considered in the basin as a whole and in the immediate times and places at which cyclognesis and storm intensification occur. The results for the two sub-basins are compared to determine which environmental variables differed significantly between the sub-basins. A tropical cyclone genesis index (TCGI) is also examined to determine whether the AS-BoB difference can be explained in terms of the environment using this index. Though the overall level of activity in both is under-predicted by the index by about a factor of two, the index shows a relative diffrence between the basins that is approximately consistent with that in observations. Based on that partial success, climatologies of the individual factors that comprise the index are examined to determine which ones are most important in the AS-BoB diffrence. Column relative humidity and vertical wind shear emerge as the most likely candidates. A closer examination suggests that column relative humidity is the more important factor and thus that the AS has fewer cyclones than the BoB primarily because it has a drier lower troposphere.

Understanding Rapid Intensification (RI) is crucial for improving the Tropical Cyclone (TC) intensity forecast skill and TC induced disaster preparedness. The physical processes that lead to RI are not well studied over the North Indian Ocean (NIO) region. Two TC cases, i.e., Titli (exhibited RI) and Phethai (not exhibited RI) from the 2018 post-monsoon season are considered to understand the environmental conditions responsible for making RI happen. The Hurricane Weather Research and Forecasting (HWRF) model produced simulations for Titli and Phethai are analyzed to understand the intensification changes. The purpose of this study is to investigate the environmental and storm structure characteristics that led to the RI of TC Titli when compared to TC Phethai. The Phethai and Titli simulations are initially validated against the best estimations by India Meteorological Department (IMD) and compared in terms of the environmental vertical wind shear as this parameter is often negatively correlated with TC intensification. Area averages of the deep-layer and mid-layer vertical wind shear over the TC environment suggest that shear did not affect the intensification of the Titli simulation. Initially, Titli contained higher magnitudes of relative humidity throughout the troposphere within the storm’s circulation. This steered to a higher upward mass flux in the troposphere and rapid intensification of relative vorticity (circulation) in the middle troposphere prior to any significant change ensued at the surface. After a deep vortex was established, the mass flux (and lower-tropospheric convergence) continued to rise, leading to RI. These results offer a basis for future research to understand better and forecast the development of RI.

In this study, the varying trends of dust storm frequency in a typical oasis located at the South edge of Taklimakan desert, China were analyzed by using time series analysis and regression models. The LUCC (land use/cover change) data, NDVI (Normalized Difference Vegetation Index) remote sensing data, meteorological data and dust storm frequency data for the period of 2004-2018 were collected from local station and ERDAS (Earth Resources Data Analysis System) software, the multivariate relationships between human activities, natural factor and dust storm frequencies were analyzed by using Principal Component Analysis (PCA). Results indicated that the annual dust storm frequency in the study period increased with fluctuation. The monthly dust storm frequency shows higher values between the months of March and June, which accounts for 72.3% of the annual dust storm frequency. Precipitation and wind speed are two meteorological factors which can impact the dust storm formation and its frequency. The correlation between dust storm frequency and temperature was insignificant. Moreover, human activities indirectly affected the dynamics of dust storms by changing the vegetation cover and direct dust emissions. Furthermore, multivariate analysis highlighted a clear relationship among dust storm frequency, meteorological factors and NDVI. The high loadings of dust storm frequency, precipitation, wind speed and NDVI on a PC indicated that increase in precipitation and NDVI will decline dust storm frequency, whereas higher wind speed will enhance dust storm frequency. The findings of this study could be useful to understand the possible causes of dust storms, which can provide the basis for controlling the dust storm source region and also mitigation of the negative effects dust storm on the environment.

The Gulf Stream and Kuroshio regions feature strong sea surface temperature (SST) gradients that influence cyclone development and the storm track. Previous studies showed that smoothing the SSTs in either the North Atlantic or North Pacific yields a reduction in cyclone activity, surface heat fluxes, and precipitation, as well as a southward shift of the storm track and the upper-level jet. To what extent these changes are attributable to changes in individual cyclone behaviour, however, remains unclear. Comparing simulations with realistic and smoothed SSTs in the atmospheric general circulation model AFES, we find that the intensification of individual cyclones in the Gulf Stream or Kuroshio region is only marginally affected by reducing the SST gradient. In contrast, we observe considerable changes in the climatological mean state as well as a reduced cyclone activity in the North Atlantic and North Pacific storm tracks that are shifted equatorward in both basins. The upper-level jet in the Atlantic also shifts equatorward, while the jet in the Pacific strengthens in its climatological position and extends further east. Surface heat fluxes, specific humidity, and precipitation also respond strongly to the smoothing of the SST, with a considerable decrease in their mean values on the warm side of the SST front. This decrease is more pronounced in the Gulf Stream than in the Kuroshio region, due to the larger decrease in SST along the Gulf Stream SST front. Considering the differences of the different variables occurring within/outside of a 750 km radius of any cyclone over their entire lifetime, we find that cyclones play only a secondary role in explaining the differences in the mean state between the smoothed and realistic SST experiments.

Idealized supercell storms are simulated with two aerosol-aware bulk microphysics schemes (BMSs), the Thompson and the Chen-Liu-Reisner (CLR), using the Weather Research and Forecast (WRF) model. The objective of this study is to investigate the parameterizations of aerosol effects on cloud and precipitation characteristics and assess the necessity of introducing aerosols into a weather prediction model at fine grid resolution. The results show that aerosols play a decisive role in the composition of clouds in terms of the mixing ratios and number concentrations of liquid and ice hydrometeors in an intense supercell storm. The storm consists of a large amount of cloud water and snow in the polluted environment, but a large amount of rainwater and graupel instead in the clean environment. The total precipitation and rain intensity are suppressed in the CLR scheme more than in the Thompson scheme in the first three hours of storm simulations. The critical processes explaining the differences are the auto-conversion rate in the warm-rain process at the beginning of storm intensification and the low-level cooling induced by large ice hydrometeors. The cloud condensation nuclei (CCN) activation and auto-conversion processes of the two schemes exhibit considerable differences, indicating the inherent uncertainty of the parameterized aerosol effects among different BMSs. Beyond the aerosol effects, the fall speed characteristics of graupel in the two schemes play an important role in the storm dynamics and precipitation via low-level cooling. The rapid intensification of storms simulated with the Thompson scheme is attributed to the production of hail-like graupel.

In July 2007 an intense summer storm resulted in significant activation of the sediment system in the Thinhope Burn, UK. Catchment- and reach-scale morphodynamic modelling is used to investigate the geomorphic work undertaken by Thinhope Burn; comparing this with the more subdued responses shown by its neighbours. Total sediment efflux for Thinhope Burn over the 10 yr period 1998-2007 was 18, 801 m3 four times that of the larger Knar Burn catchment and fifty-four times that of the smaller Glendue Burn catchment. For a discharge of 60 m3s-1, equivalent to the July 2007 Thinhope flood, sediment efflux was 575 m3, 76 m3, and 67 m3 for Thinhope, Glendue and Knar Burns respectively. It is clear that Thinhope Burn undertook significantly more geomorphic work compared to its neighbours. Analysis of the population of shear stress for reach-scale simulations on Thinhope Burn highlighted that the final three simulations (flood peaks of 60, 90, 236 m3s-1) all produced very similar distributions, with no marked increase in the modal shear stress (∼250 Nm-2). This possibly suggests that flows >60 m3s-1 are not able to exert significantly greater energy on the channel boundary, indicating that flows in the region of 60 m3s-1 attain ‘peak’ geomorphic work. It is argued that factors such as strength resistance of the key sediment sources (e.g. paleoberms perched on terraces), structural resistance to flood waves imposed by valley form resistance, location sensitivity and transmission resistance, may all offer explanations for increased geomorphic effectiveness compared with its neighbours. With the expectation of greater rainfall totals in the winter and more extreme summer events in upland areas of the UK, it is clear that attention needs to focus upon the implications of this upon the morphological stability of these areas not least to aid future sustainable flood risk management.

Typhoon Haiyan (2013) and Typhoon Hagupit (2014) are examples of two tropical cyclones (TCs) where, despite similarities in the track and intensity, the predictability of the TCs differed greatly. Both TCs made landfall over the Philippines having followed a similar track across the Pacific and both reached intensities in excess of 60 ms-1. Operational global ensemble forecasts showed large uncertainty in the track of Hagupit, whereas the ensemble spread for Haiyan was considerably less. Using the Met Office's Unified Model, 5-day global ensemble forecasts were produced for both storms. Consistent with the operational forecasts produced at the time of the storms, the spread of tracks is greater in the forecasts produced for Hagupit than Haiyan. Haiyan was located on the southern periphery of the subtropical high and embedded in a strong easterly flow. In contrast, the position of Hagupit between two anticyclones earlier in the forecast is key to the subsequent motion of the storm and determining if Hagupit will make landfall over the Philippines or turn to the north. Upper level winds contribute the most to the depth-averaged steering flow. Statistically significant differences in the strength of the upper level anticyclone to the east of the storm, the strength and position of the upper level ridge downstream of the storm and the location of a detached PV streamer appear between two groups of ensemble members - those which turn to the north and those which make landfall. Positional differences of the TC in different ensemble members earlier in the forecasts, particularly in the east to west direction, are correlated to larger north-east to south-west position differences later in the forecast. Ensemble sensitivity analysis suggests that this initial east-west positional variance is linked to the upper level geopotential height directly south of the storm. Accurately representing both the steering flow of Hagupit and the position of Hagupit is vital for an accurate forecast.

This study analyzes some characteristic features associated with the Mars year 34 (2018) global dust storm (GD18) using the retrievals of Mars Climate Sounder (MCS) and Mars Color Imager (MARCI) onboard Mars Reconnaissance Orbiter (MRO). According to the MRO MARCI's weather report and Mars daily global maps, the GD18 resulted from a large precursor dust storm in the broader Acidalia region at LS ~ 186° and developed into a global scale storm at LS ~ 194°. Dust lifting is reported to continue until LS ~ 207° in MARCI images, and the MCS-derived column dust opacity peaks around LS 208°. However, the middle atmospheric dust loading only peaks around LS 211°, i.e., 3–4° LS after the surface dust lifting maximum. High-altitude dust maximum is evident after LS ~ 190°, a few degrees of LS after the large precursor Acidalia dust storm. These delays probably indicate a vertical mixing timescale similar to that for a regional scale storm, indicating a common mechanism irrespective of the spatial scale of a dust storm. During GD18, the diurnal tide is strongly amplified at high altitudes, away from the tropics (especially over SH), and the vertical extent of clouds is significantly reduced. These changes are consistent with the time scale of the evolving vertical distribution of dust observed by MCS.

We present a feasibility study for an object-based method to characterise thunderstorm properties in simulation data from convection-permitting weather models. An existing thunderstorm tracker, the Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) algorithm, was applied to thunderstorms simulated by the Advanced Research Weather Research and Forecasting (AR-WRF) weather model at convection-permitting resolution for a domain centred on Switzerland. Three WRF microphysics parameterisations were tested. The results are compared to independent radar-based observations of thunderstorms derived using the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm. TRT was specifically designed to track thunderstorms over the complex Alpine topography of Switzerland. The object-based approach produces statistics on the simulated thunderstorms that can be compared to object-based observation data. The results indicate that the simulations underestimated the occurrence of severe and very large hail compared to the observations. Other properties, including the number of storm cells per day, geographical storm hotspots, thunderstorm diurnal cycles, and storm movement directions and velocities, provide a reasonable match to the observations, which shows the feasibility of the technique for characterisation of simulated thunderstorms over complex terrain.

Accurate information on the thermal structures of tropical cyclones (TCs) is essential for monitoring and forecasting their intensity and location. In this study, a scene-dependent 1-D variation (SD1DVAR) algorithm is developed to retrieve atmospheric temperature and moisture profiles under all-weather conditions. In SD1DVAR, the background and observation error matrix varies according to the scattering intensity. Especially, the observation error matrix increases in precipitating atmospheres due to a larger uncertainty in the forward operator. With the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) satellite, SD1DVAR can retrieve better thermal structures in the storm life cycle than NOAA Microwave Integrated Retrieval System (MIRS). Comparing with the aircraft dropsonde observations, the temperature and humidity errors from SD1DVAR are about 3 K and 20%, respectively, whereas those from MIRS are around 4 K–5 K and 30%, respectively. SD1DVAR is also applied for Microwave Temperature Sounder (MWTS) and Microwave Humidity Sounder (MWHS) onboard FengYun-3D (FY-3D) satellite. The MWTS and MWHS data sets are first combined into a single Comprehensive MicroWave Suite (CMWS) data stream and then used to retrieve the hurricane thermal structures. It is shown that the hurricane structure from CMWS is very similar to that from ATMS. However, due to the availability of 118-GHz measurements from the CMWS, the hurricane temperature vertical structure is better resolved, and the humidity error is also reduced by about 5%.