Convective Index Research Articles

Impacts of forced and internal climate variability on changes in convective environments over the eastern United States

Hazards from convective weather pose a serious threat to the contiguous United States (CONUS) every year. Previous studies have examined how future projected changes in climate might impact the frequency and intensity of convective weather using simulations with both convection-permitting regional models and coarser-grid climate and Earth system models. We build on this existing literature by utilizing a large-ensemble of historical and future Earth system model simulations to investigate the time evolution of the forced responses in large-scale convective environments and how those responses might be modulated by the rich spectrum of internal climate variability. Specifically, daily data from an ensemble of 50 simulations with the most recent version of the Community Earth System Model was used to examine changes in the convective environment over the eastern CONUS during March-June from 1870 to 2100. Results indicate that anthropogenically forced changes include increases in convective available potential energy and atmospheric stability (convective inhibition) throughout this century, while tropospheric vertical wind shear is projected to decrease across much of the CONUS. Internal climate variability on decadal and longer time scales can either significantly enhance or suppress these forced changes. The time evolution of two-dimensional histograms of convective indices suggests that future springtime convective environments over the eastern CONUS may, on average, be supportive of relatively less frequent and shorter-lived, but deeper and more intense convection.

Stretching/shrinking impact on the transient heat transfer in a radial moving porous fin of a longitudinal trapezoidal structure

The prime goal of the current pagination is to scrutinize the transient thermal response in a radial porous moving fin of a longitudinal trapezoidal structure. The solution of the constructed problem is heeded by a pdepe solver in Matlab, which works on the centered-finite difference technique. Darcy’s model is utilized to investigate porous nature. A stretching/shrinking mechanism has been incorporated to improve the fin efficiency. Stretching reduces efficiency, whereas shrinking improves fin efficiency indicating major benefits of fin design consideration. The relevant temperature results are shown visually and discussed quantitatively in detail to evaluate the competence of the suggested fin. With a rise in the Peclet number, temperature distribution decreases. A similar nature is noted with respect to the power index of convective heat transfer coefficient, convection and radiation parameters, porous parameter, stretching/shrinking parameter, and thermal conductivity gradient with temperature. The graphical outcomes also show that the fin temperature amplifies with the ambient temperature parameter. Also, it is noticed that thermal distribution is a decreasing function of the power index of the convective heat transfer coefficient such that there is a decrease of 1.64% in temperature distribution as the power index increases. To support the validity of the solutions, a comparison was made with notable results from the existing literature for the specific case of this study. The novelty of the work is to study highly nonlinear boundary value problems and such nonlinearities are more relevant in the system that describes the thermal processing of materials. It is also noted that initial transient heat transfer vanishes quickly under steady-state conditions when the material is exposed to the ambient temperature.

Shallow and deep learning of extreme rainfall events from convective atmospheres

Abstract. Our subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify daily ERA5 fields of convective indices according to CatRaRE, using an array of 13 statistical methods, consisting of 4 conventional (“shallow”) and 9 more recent deep machine learning (DL) algorithms; the classifiers are then applied to corresponding fields of simulated present and future atmospheres from the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. The inherent uncertainty of the DL results from the stochastic nature of their optimization is addressed by employing an ensemble approach using 20 runs for each network. The shallow random forest method performs best with an equitable threat score (ETS) around 0.52, followed by the DL networks ALL-CNN and ResNet with an ETS near 0.48. Their success can be understood as a result of conceptual simplicity and parametric parsimony, which obviously best fits the relatively simple classification task. It is found that, on summer days, CatRaRE-convective atmospheres over Germany occur with a probability of about 0.5. This probability is projected to increase, regardless of method, both in ERA5-reanalyzed and CORDEX-simulated atmospheres: for the historical period we find a centennial increase of about 0.2 and for the future period one of slightly below 0.1.

Adverse impact of terrain steepness on thermally driven initiation of orographic convection

Abstract. Diurnal mountain winds precondition the environment for deep moist convection through horizontal and vertical transport of heat and moisture. They also play a key role in convection initiation, especially in strongly inhibited environments, by lifting air parcels above the level of free convection. Despite its relevance, the impact of these thermally driven circulations on convection initiation has yet to be examined systematically. Using idealized large-eddy simulations (Δx=50 m) with the Weather Research and Forecasting (WRF) model, we study the effect of cross-valley circulations on convection initiation under synoptically undisturbed and convectively inhibited conditions, considering quasi-2D mountain ranges of different heights and widths. In particular, we contrast convection initiation over relatively steep mountains (20 % average slope) and less steep ones (10 %). One distinctive finding is that, under identical environmental conditions, relatively steep mountain ranges lead to a delayed onset and lower intensity of deep moist convection, although they cause stronger thermal updrafts at ridge tops. The temporal evolution of convective indices, such as convective inhibition and convective available potential energy, shows that destabilization over the steeper mountains is slower, presumably due to lower low-level moisture. Analysis of the ridgetop moisture budget reveals the competing effects of moisture advection by the mean thermally driven circulation and turbulent moisture transport. In general, at mountaintops, the divergence of the turbulent moisture flux offsets the convergence of the advective moisture flux almost entirely. Due to the stronger ridgetop updraft, the mean advective moistening over the steeper mountains is higher; nevertheless, the total moistening is lower and the width of the updraft zone is narrower on average. Thus, buoyant updrafts over the steeper mountains are more strongly affected by the turbulent entrainment of environmental air, which depletes their moisture and cloud water content and makes them less effective at initiating deep convection. Saturated updrafts over less steep mountains, on the other hand, gain more moisture from the vapor flux at cloud base, leading to significantly higher moisture accumulation. The lower entrainment rates in these simulations are revealed by the fact that equivalent potential temperature in the cloud decreases less strongly with height than over steeper terrain. The precipitation efficiency, a measure of how much of the condensed water eventually precipitates, is considerably larger over the less steep mountains, also due to lower total condensation compared with the steeper simulations. The relationship between mountain size and precipitation amount depends on the thermodynamic profile. It is nearly linear in cases with low initial convective inhibition but more complex otherwise. The weaker convection over steeper mountains is a robust finding, valid over a range of background environmental stability and mountain sizes.

Application of a Three-Dimensional Wind Field from a Phased-Array Weather Radar Network in Severe Convection Weather

In 2019–2020, an array weather radar (AWR) network consisting of seven X-band phased-array radars (PARs), with a detection spatial resolution of 30 m and a temporal resolution of 30 s, was built in the city of Foshan in China’s Guangdong Province. The detection time deviation in the same space is within 5 s. Through variational data assimilation, the three-dimensional wind field inside the storm can be obtained. This study selected instances of hail, thunderstorms, strong winds, and short-duration heavy precipitation in 2020 to conduct a detailed analysis. The results show the following: (1) The fine detection ability enables phased-array radars to detect the complete evolution process of convective storms, including development, strengthening, and weakening, providing a useful reference for judging the future variation trends of convective storms. (2) Through evolutionary analysis of the three-dimensional wind field, the dynamic mechanisms of storm strengthening and weakening could be obtained, which could serve as a reference to predict the development of storms. The gust wind index and convection index calculated based on the three-dimensional wind field could provide advanced warning for nowcasting. When the gust wind index was greater than 263, the probability of gale-force wind (above 17.0 m/s) was determined to be high. Moreover, the warning could be provided 10–20 min in advance. A convection index greater than 35 and the presence of concentrated contour lines were found to be conducive to the strengthening and formation of a convection, and the warning could be provided 20 min in advance. These results show that the application of PAR can provide important technical support for nowcasting severe convective weather.

Modelling hail hazard over Italy with ERA5 large-scale variables

Hail is a meteorological phenomenon with adverse impacts that affects multiple socio-economic sectors such as agriculture, renewable energy, and insurance. Nevertheless, the understanding of the favourable environmental conditions for hail formation and the models’ inadequacy to represent these phenomena have been limited by the scarce temporal and spatial coverage of hail observations. This is a major concern for the mitigation of hail-related risk in sensitive regions such as Italy, which is one of the more hail-prone areas in Europe. In this work, we present a hail model that has been developed to describe the hail hazard over Italy. This model relies on several ERA5 large-scale meteorological variables and convective indices that are combined following the statistical method described in Prein and Holland (2018). The identification of the best set of variables to be used as predictors in the hail model has been performed by a systematic machine learning procedure based on a genetic algorithm. The hail model estimates the hail probability over Italy in the 1979–2020 period, on the ERA5 spatial grid resolution (∼ 30 km). The output of the hail model has been used to characterize the seasonality and long-term variability of hail events in Italy. Furthermore, the categorical verification of the hail probability over the Friuli Venezia Giulia region has revealed that the hail model is able to effectively estimate the hail occurrences in specific Italian regions.

A Study of Important Atmospheric Convective Indices and Their Impacts on Aviation

Studies of the environmental impact on aircraft operations always create great interest, for both the scientific and non-scientific fraternities. It has now been fairly understood that climate changes (sea level rise, enormous increase of surface temperatures, and heat waves) have significant impacts on the aviation sector while a proper knowledge of the impacts of convective activities on the aviation sector has not yet been well known. This research presents the general mechanism of a few important atmospheric indices including, convective available potential energy (CAPE), convective inhibition (CIN), and lifted index (LI) by using radiosonde (a balloon-borne instrument). Initially, convective indices over two Indian stations (coastal and inland) are presented in terms of monthly and seasonal variations. The observed trends are discussed based on the available literature. The impacts of the atmospheric indices on the aviation industry and the feasible solutions if an airplane is caught in a severe thunderstorm are discussed.

Changes in the vegetation and water cycle of the Ecuadorian páramo during the last 5000 years

We analyzed changes in the long-term vegetation cover and in fire activity over the past 5000 years in the Ecuadorian páramo using a sediment core from Papallacta (Ecuador). The chronology is constrained by three tephra layers and 32 AMS 14C ages, and 168 samples yielded a high-resolution record of environmental changes. We estimated the upslope wind convectivity as the ratio between pollen transported from the Andean cloud forest and Poaceae pollen to distinguish changes in atmospheric moisture from changes in soil moisture. The record showed that the two sources of moisture, either from year-round adiabatic cloud dripping linked to SASM activity or to ENSO variability at decadal-scale, influenced vegetation-cover changes. Between 5000 and 2450 cal yr BP, both soil moisture and biomass burning were higher than after 2450 cal yr BP. The shift between the two states matches the zonal increase in summer insolation that drove the ITCZ to its southernmost position. Our results underline resilience to volcanic activity, the importance of the upslope convective dripping with the lowest convective index observed at ~4500 cal yr BP, the anomalous last century with the highest convective activity and the driest soil conditions recorded in the last 5000 years, the recent increase in fire activity and the link between soil moisture and the position of the ITCZ.

Impact of thresholds on nonstationary frequency analyses of peak over threshold extreme rainfall series in Pearl River Basin, China

Nonstationary frequency analysis of peak over threshold (POT) extreme rainfall series is crucial in hydrology. Most previous studies on the nonstationary frequency analyses of POT extreme rainfall series used only a single threshold, ignoring the differences in the statistical characteristics of POT extreme rainfall series extracted with different thresholds. This study investigated the impact of thresholds on the nonstationary frequency analyses of POT extreme rainfall series using a three-step method. First, the non-stationarities in POT extreme rainfall series extracted with different thresholds were assessed using the Iterative Mann-Kendall test and the Mood test. Second, the nonstationary POT extreme rainfall series were modeled using the generalized Pareto distribution (GPD) with the scale parameter to be linked with physical covariates. Third, the uncertainty in the parameters and return level of the optimal model for the POT extreme rainfall series were evaluated using the Markov chain Monte Carlo method. This method was applied to the daily rainfall at 48 stations in the Pearl River Basin (PRB) from 1979 to 2020. By comparing the optimal models of POT extreme rainfall series extracted with different percentile thresholds, we can draw the following conclusions. (1) As the threshold increases from the 90th percentile to the 99.7th percentile, the percentage of nonstationary POT extreme rainfall series gradually decreases from 92% to 13%, with most stations with a significant increasing trend changing to most stations with a significant decreasing trend, especially when the threshold is greater than the 98th percentile. (2) The uncertainty in the scale parameter, shape parameter, and return level increases as the threshold increases, and increases significantly when the threshold is greater than the 98th percentile, especially for the scale and shape parameters. (3) The 98th percentile is suggested as the optimal threshold for the PRB; (4) For the 98th percentile threshold, the total column water vapor in the convective indices is the most significant covariate for the entire PRB.

Climatology and Formation Environments of Severe Convective Windstorms and Tornadoes in the Perm Region (Russia) in 1984–2020

Severe convective windstorms and tornadoes regularly hit the territory of Russia causing substantial damage and fatalities. An analysis of the climatology and formation environments of these events is essential for risk assessments, forecast improvements and identifying of links with the observed climate change. In this paper, we present an analysis of severe convective windstorms, i.e., squalls and tornadoes reported between 1984 and 2020 in the Perm region (northeast of European Russia), where a local maximum in the frequency of such events was previously found. The analysed database consists of 165 events and includes 100 squalls (convective windstorms), 59 tornadoes, and six cases with both tornadoes and squalls. We used various information to compile the database including weather station reports, damage surveys, media reports, previously presented databases, and satellite images for windthrow. We found that the satellite images of damaged forests are the main data source on tornadoes, but their role is substantially lower for windstorm events due to the larger spatial and temporal scale of such events. Synoptic-scale environments and associated values of convective indices were determined for each event with a known date and time. Similarities and differences for the formation conditions of tornadoes and windstorms were revealed. Both squalls and tornadoes occur mostly on rapidly moving cold fronts or on waving quasi-stationary fronts, associated with low-pressure systems. Analyses of 72-h air parcel backward trajectories shows that the Caspian and Aral Seas are important sources of near-surface moisture for the formation of both squalls and tornadoes. Most of these events are formed within high CAPE and high shear environments, but tornadic storms are generally characterised by a higher wind shear and helicity. We also differentiated convective storms that caused forest damage and those did not. We found the composite parameter WMAXSHEAR is the best discriminator between these two groups. In general, storm events causing windthrow mainly occur under conditions more favourable for deep well-organised convection. Thus, forest damage can be considered as an indicator of the storm severity in the Perm region and in adjacent regions with forest-covered area exceeding 50%.

Evaluation of convective parameters derived from pressure level and native ERA5 data and different resolution WRF climate simulations over Central Europe

The mean climatological distribution of convective environmental parameters from the ERA5 reanalysis and WRF regional climate simulations is evaluated using radiosonde observations. The investigation area covers parts of Central and Eastern Europe. Severe weather proxies are calculated from daily 1200 UTC sounding measurements and collocated ERA5 and WRF pseudo-profiles in the 1985–2010 period. The pressure level and the native ERA5 reanalysis, and two WRF runs with grid spacings of 50 and 10 km are verified. ERA5 represents convective parameters remarkably well with correlation coefficients higher than 0.9 for multiple variables and mean errors close to zero for precipitable water and mid-tropospheric lapse rate. Monthly mean mixed-layer CAPE biases are reduced in the full hybrid-sigma ERA5 dataset by 20–30 J/kg compared to its pressure level version. The WRF model can reproduce the annual cycle of thunderstorm predictors but with considerably lower correlations and higher errors than ERA5. Surface elevation differences between the stations and the corresponding grid points in the 50-km WRF run lead to biases and false error compensations in the convective indices. The 10-km grid spacing is sufficient to avoid such discrepancies. The evaluation of convection-related parameters contributes to a better understanding of regional climate model behavior. For example, a strong suppression of convective activity might explain precipitation underestimation in summer. A decreasing correlation of WRF-derived wind shear away from the western domain boundaries indicates a deterioration of the large-scale circulation as the constraining effect of the driving reanalysis weakens.

Simulating the storm environment responsible for Nepal's first observed tornado

A high-resolution numerical forecast model was used to simulate the meteorological conditions leading up to the March 31st, 2019 severe weather event that produced Nepal's first-ever observed tornado. The sparse meteorologic observations in the region capturing the storm environment limit the ability to anticipate another similar situation should the particular set of conditions present themselves again. This study presents a multifaced view of the storm environment through 1) a synoptic perspective provided by the Global Data Assimilation System (GDAS) reanalysis dataset and 2) a trio of progressively higher resolution one-way nested simulations (12 km–4km–1km) driven by GDAS boundary conditions to more closely examine the storm-scale environment. GDAS data and numerical simulations revealed moderately strong instability throughout the region with CAPE values between 1000 and 2000 J kg−1 K−1 and lifted index values between −4 and −7. Vertical wind profiles featuring little directional shear and moderate velocity shear yielded shear-based convective indices that suggested slight potential for rotating supercell thunderstorms. Within this environment, the 1-km simulation produced strong, rotating convection in nearly the same location and at nearly the same time as the observed tornadic storm. Lastly, an assessment of the limited number of observed historical tornadic events in the region showed that with amply convective available potential energy, the 2019 Nepal tornado environment stood out for the limited vertical directional wind shear present.

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the atmosphere boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement Southern Great Plains site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential-absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to obtain a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near the boundary-layer top. We also explore how differences in retrievals may affect results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval shows some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

Numerical Analysis of the Flow Effect of the Menger-Type Artificial Reefs with Different Void Space Complexity Indices

Based on fractal theory, a regular fractal is used to construct symmetrical reef models (e.g., cube and triangle reef models) with different fractal levels (n = 1, 2, 3). Using the concept of fractal dimension, we can better understand the spatial effectiveness of artificial reefs. The void space complexity index is defined to quantify the complexity of the internal spatial distribution of artificial reefs models under different levels. The computational fluid dynamics (CFD) flow simulation approach was used to investigate the effects of void space complexity on the flow field performances of the symmetrical artificial reef models. The upwelling convection index (Hupwelling/HAR, Vupwelling/VAR), wake recirculating index (Lwake/LAR, Vwake/VAR) and non-dimensionalized velocity ratio range were used to evaluate the efficiency of the flow field effect inside or around artificial reefs. The surface area and spatial complexity index of artificial reefs increase with increasing fractal level. The numerical simulation data shows that the Menger-type artificial reef models with a higher spatial complexity index have better flow field performances in the upwelling and wake regions. Compared to the traditional artificial reef models, the upwelling convection index (Vupwelling/VAR) and recirculating index (Vwake/VAR) of n = 3 fractal cube artificial reef increase by 37.5% and 46.8%, respectively. The efficiency indices of the upwelling region and wake region around the fractal triangle artificial reef model are 2–3 times those of the fractal cube artificial reef model when the fractal level is 3.

Warunki synoptyczne sprzyjające rozwojowi burz nocnych w Polsce = Synoptic conditions favouring the development of nocturnal thunderstorms in Poland

This article presents research into the meteorological conditions underpinning the development of night thunderstorms in Poland. The main objective was thus to identify the synoptic situations favouring nocturnal thunderstorms, as well as to determine which convection indices are of greatest relevance to forecasts of this type of thunderstorm. The research detailed here was carried out by analysing cloud-to-ground lightning flashes registered in Poland in the years 2002‑2018 via the PERUN system. ERA 5 reanalysis was used to obtain relevant atmospheric parameters and convection indices. In addition, synoptic analysis was carried out for specified thunderstorms, with their dominant structure also determined. No fewer than 1.5 million cloud-to-ground lightning flashes were analysed for the purposes of this study. These data making it clear that the development of nocturnal thunderstorms is favoured primarily in conditions of a waving front, cold front or wind convergence line. In all cases, the jet stream in the upper troposphere emerged as an additional factor increasing the development and activity of nocturnal thunderstorms.

УСЛОВИЯ ВОЗНИКНОВЕНИЯ СИЛЬНЫХ ШКВАЛОВ И СМЕРЧЕЙ, ВЫЗЫВАЮЩИХ КРУПНЫЕ ВЕТРОВАЛЫ В ЛЕСНОЙ ЗОНЕ ЕВРОПЕЙСКОЙ ЧАСТИ РОССИИ И УРАЛА

The environments of 53 severe squalls and tornadoes that caused large-scale windthrows in the forest zone of European Russia and the Ural in 1989–2019 are analyzed. The CFSR and ERA-5 reanalyses and sounding data were used to estimate characteristics of the environments including convective instability indices. It was found that the substantial temperature gradient on the atmospheric front (9.6C/500 km on average) and the jet stream presence in the lower or middle troposphere oriented along the frontal zone are important factors to estimate environments of the formation of severe squalls and tornadoes. In most cases, squalls and tornadoes require a combination of high precipitable water content (40 mm on average), moderate or high convective instability (CAPE >1000 J/kg), and moderate or strong wind shear. High precipitable water content and strong convective instability are important for the formation of squalls, while low-level wind shear plays a principal role for the tornado generation.

Comparison of Heavy Rainfall Events Originated from Different Directions of Beijing City

Strong rainfall events originated from the northeast (NE) and southwest (SW) directions of the plain area of Beijing City (BJP) over 8 recent warm seasons (May-September of 2009–2016) were analyzed by using hourly merged rainfall, satellite brightness temperature, and the fifth-generation ECMWF reanalysis (ERA5) data. Such heavy regional rainfall events (RREs) with different origins present quite different features in both the precipitation itself and its corresponding circulations. The heavy RREs originated from the SW occur more frequently in the flood season of North China (July and August), and the peak time of rainfall occurrences is in the early morning. They are linked with stronger large-scale circulation forcing, compared with the NE-originated events. Meanwhile, the ratio of heavy rainfall to the total rainfall in SW-originated events, the mean spatial coverage of rainfall, and associated convective index, are also larger, for the SW events. The heavy RREs from the NE occur more frequently in June and July (before the traditional flood season), with a more apparent afternoon peak. They exhibit stronger convective features, with higher maximum convective index values, but the large-scale forcing is weaker at the hour of onset. These features of the RREs from different directions of Beijing City and associated precursor circulation signals help better forecast RREs over the BJP.

Estimation of steady water flux density in a porous medium by Fourier analysis of temperature variations in a cyclic heat pulse system

We tested a novel theoretical model that determines the steady water flux density in a porous medium from Fourier analysis of temperature variations induced by a cyclic heat pulse system. The model depends on the thermal diffusivity of the medium and on the relative spatial variation of the amplitude and phase of the first order sinusoidal component of the heat wave. The model was tested by using a hydraulic column made of a PVC pipe filled with sawdust. The sensor consisted of two hypodermic needles spaced 7 mm apart. One needle contained a heater and a thermocouple while the other contained only a thermocouple. Different combinations of heating and cooling cycles were tested. The flow was controlled by pressure head and volumetrically measured at the outlet of the tube. The experimental results supported the theoretical model. In particular, the convective index defined in terms of the variations of amplitude and phase of the first component of the heat wave was linearly related to the measured flux density, as predicted. The model was independent of the different combinations of heating and cooling cycles. The estimated water flux density was strongly related to the measured flux density (R2>0.99), having the same slope for the different combinations. The first results of this new approach of cyclic heat pulse system are very promising and suggest further studies and field applications.

Inter-Comparison of AIRS Temperature and Relative Humidity Profiles with AMMA and DACCIWA Radiosonde Observations over West Africa

The vertical profiles of temperature and water vapour from the Atmospheric InfraRed Sounder (AIRS) have been validated across various regions of the globe as an effort to provide a substitute for radiosonde observations. However, there is a paucity of inter-comparisons over West Africa where local convective processes dominate and radiosonde observations (RAOBs) are limited. This study validates AIRS temperature and relative humidity profiles for selected radiosonde stations in West Africa. Radiosonde data were obtained from the AMMA and DACCIWA campaigns which spanned 2006–2008 and June–July 2016 respectively and offered a period of prolonged radiosonde observations in West Africa. AIRS performance was evaluated with the bias and root mean square difference (RMSD) at seven RAOB stations which were grouped into coastal and inland. Evaluation was performed on diurnal and seasonal timescales, cloud screening conditions and derived thunderstorm instability indices. At all timescales, the temperature RMSD was higher than the AIRS accuracy mission goal of ±1 K. Relative humidity RMSD was satisfactory with deviations <20% and <50% for both lower and upper troposphere respectively. AIRS retrieval of water vapour under cloudy and cloud-free conditions had no significant difference whereas cloud-free temperature was found to be more accurate. The seasonal evolution of some thunderstorm convective indices were also found to be comparable for AIRS and RAOB. The ability of AIRS to capture the evolution of these indices imply it will be a useful dataset for the African Science for Weather Information and Forecasting Techniques (SWIFT) high impact weather studies.

Application of random forest algorithm in hail forecasting over Shandong Peninsula

To improve the accuracy of hail forecasting, this study applies the random forest (RF) algorithm in hail identification and prediction in Shandong Peninsula. Hail observation data of 41 meteorological stations in Shandong Peninsula from 1998 to 2013 are used. The hail forecasting model with a 0–6 h range based on the RF algorithm is constructed using the convection index and related physical quantities calculated by the reanalysis data of the European Centre for Medium-Range Weather Forecasts during the same period. The model is built by undersampling within the RF algorithm (balanced RF), and the cross-validation is adopted to select the optimal forecast probability. The cross-validation exhibits high simulation accuracy, stable fitting effect, and small average generalization error. The performance of the balanced RF is tested by the independent data samples from 2014 to 2018, which shows excellent results. A trial report on the weather process on 13 June 2018 shows that the model is effective in identifying hail-fall areas and capable of forecasting all hail stations and the occurrence time of hail disasters. The RF algorithm focuses on thermal factors. The physical meaning of the selected factors is clear and consistent with the subjective prediction. The thresholds of the thermal factors, such as the lifted index, Showalter stability index, and total index, can be utilized as a reference for hailstorm prediction over Shandong Peninsula.