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This paper analyses over 10,000 quality‐controlled pilot reports of low‐level wind shear ('wind shear') at the Hong Kong International Airport (HKIA; ICAO code: VHHH) between 2001 and 2019. HKIA is well known for its susceptibility to wind shear, which is a potential hazard for aircraft during landing and take‐off. Wind shear at HKIA exhibits strong seasonality with double peaks in the middle of the spring and summer months. There is a strong diurnal cycle in report numbers, peaking towards the afternoon, as modulated by air traffic at HKIA. On average, there are 115 days per year with wind shear reported, with possible power law distribution in the number of days with different number of reports. By comparing the background wind distribution during those minutes with pilot reports against the climatological distribution, wind shear is observed to be, on average, favoured under higher wind speeds (≥6 m s−1) and reduced under lower speeds with shifted frequency peak and heavier tail, although statistical behaviour can differ significantly across individual runway corridors. Preferred background wind directions for wind shear occurrence highlight the role of terrain influence upstream of HKIA. While positive shear (65.6%) is more often reported than negative shear (34.4%), both types of wind shear events appear to follow an exponential distribution in shear magnitude, with similar rates of decay. This is by far the largest statistical study of low‐level wind shear at an airport. Results can serve as an important local reference in addition to being a useful example for airports around the world. [ABSTRACT FROM AUTHOR]

The Met Office Global Hazard Map (GHM) summarizes the risk of high‐impact weather across the globe over the coming week using global ensemble forecast data. In addition to gridded daily probability forecasts, a symbol and polygon‐based summary layer gives an at‐a‐glance view of likely high‐impact weather for the week ahead. To evaluate the performance of the GHM, two complementary approaches were used. The first is an objective precipitation verification approach comparing the daily gridded precipitation forecasts with global precipitation observations. The second, and the main focus of this paper is a new, semi‐automated evaluation approach that assesses the ability of the multi‐model ensemble precipitation summary layer to highlight events that cause community impacts, as recorded in an impact database. The verification against observed precipitation confirms there is good skill in the precipitation forecasts and that the multi‐model ensemble provides the best guidance to take forward into the summary layer. The verification against impacts indicates there is a good spatial relationship between the GHM precipitation forecasts and heavy rainfall impacts across the globe. Hit rates for all impact severities range from 40 to 60% for days 1–3 and taper off to lower hit rates at the longer lead times (10–20% for days 6–7). High‐impact events are captured marginally less well than the low‐, medium‐ and disastrous‐impact event categories and this paper illustrates a number of approaches that could positively alter the profile of the hit‐rate curve. The Met Office Global Hazard Map (GHM) summarizes the risk of high‐impact weather across the globe over the coming week using global‐ensemble forecast data. A new, semi‐automated evaluation approach that assesses the ability of the multi‐model ensemble precipitation summary layers to highlight events that cause community impacts, as recorded in an impact database, is described. Hit rates for all impact severities range from 40 to 60% for days 1–3 and taper off to lower hit rates at the longer lead times (10–20% for days 6–7). [ABSTRACT FROM AUTHOR]

Air temperature conditions affect various aspects of human life through diverse pathways, such as health, agriculture, labour productivity, infrastructure and building constructions, economic production, and so on. To address better efforts at resolving this issue, decision‐making tools need to be developed to identify and prioritize areas where appropriate actions are required. The present paper identifies vulnerable areas in Morocco with a focus on three different aspects: high temperatures, low temperatures and daily temperature amplitude. Maps were created using the National Oceanic and Atmospheric Administration (NOAA)‐developed Climate Forecast System Reanalysis (CFSR) 30 year‐long daily maximum and minimum temperature data set. Several indicators as well as vulnerability indexes were defined and calculated. Maps showing the spatial distribution of these indicators were created. The results show that 78% of Morocco is considered to be non‐vulnerable areas to areas with low vulnerability; and 19% is characterized by moderate vulnerability to the effects of temperature. The remaining areas are characterized by high to extreme vulnerability: the most vulnerable areas are located in the provinces of Figuig, Jerada and Boulemane in the eastern part of the country, as well as in the provinces of Khouribga, Fquih Ben Saleh and Settat in the central part. This implies, for example, that national‐level planners in the agriculture and transport/infrastructure sectors in the central part need to take into account temperature vulnerabilities as they develop sector strategies and plans. [ABSTRACT FROM AUTHOR]

ABSTRACT This study describes the development and deployment of a new climate data management system aimed at improving climate data management and associated climate services in Pacific island countries and East Timor. The system is called Climate Data for the Environment ( CliDE). Installed locally, it provides each country with a central relational database and web-based user interface that includes customizable key entry forms, quality control tools, station maintenance forms, meteorological and climate reports, and data file extracts. It has been deployed as free and open source software in 15 countries (East Timor, Papua New Guinea, Solomon Islands, Vanuatu, Palau, Federated States of Micronesia, Nauru, Marshall Islands, Kiribati, Tuvalu, Fiji, Tonga, Samoa, Niue and Cook Islands). In developing CliDE, the project team sought to develop a database capable of providing a robust method of managing an individual country's meteorological observations from networks typically consisting of several to hundreds of stations. In many Pacific countries significant data remain only in paper form; therefore, a key consideration was in providing a secure and efficient means for digitizing paper records. As CliDE has developed, it has become the central hub of a multitude of climate and meteorological services of benefit to small national meteorological services, such as statistical reports, graphical analyses, data extractions, climate summaries, and products that can provide input to public works planning, agriculture and health sectors. It has helped improve significantly the work flow, data integrity and consistency beyond previous practices in the western Pacific. [ABSTRACT FROM AUTHOR]

ABSTRACT Evaluation is important for improving climate prediction systems and establishing the credibility of their predictions of the future. This paper shows how the choices that must be made about how to evaluate predictions affect the outcome and ultimately our view of the prediction system's quality. The aim of evaluation is to measure selected attributes of the predictions, but some attributes are susceptible to having their apparent performance artificially inflated by the presence of climate trends, thus rendering past performance an unreliable indicator of future performance. We describe a class of performance measures that are immune to such spurious skill. The way in which an ensemble prediction is interpreted also has strong implications for the apparent performance, so we give recommendations about how evaluation should be tailored to different interpretations. Finally, we explore the role of the timescale of the predictand in evaluation and suggest ways to describe the relationship between timescale and performance. The ideas in this paper are illustrated using decadal temperature hindcasts from the CMIP5 archive. © 2013 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

ABSTRACT The amount of sunshine weighs heavily in our perception of the weather. It is largely determined by cloud cover, especially that at the low-to-medium level. Therefore, when reviewing the Hong Kong Observatory's weather symbol forecasting product, verification on the low-to-medium cloud field is carried out against the synoptic observations at the Hong Kong International Airport. Several metrics are used to examine the different aspects of the forecasts, and consideration is given to the non-Gaussian nature of the reported cloud amount for a fairer assessment. Based on the data from January to mid-August 2015, the median of the forecasts from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System is found to outperform the other model forecasts, particularly when the performance is examined by forecast day. This paper presents these results and also discusses the potential of using the field in deriving site-specific weather symbol forecasts. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, an objective identification technique for regional extreme events (OITREE) is used to identify regional drought events (RDEs) in southern China based on the daily precipitation dataset of 342 stations from 1961 to 2012. Generally RDEs in southern China occur over an entire year, with high frequencies from January to April and peak frequencies in February and March. The spatial distributions of frequency and intensity of RDEs are consistent, with high frequencies of more than 60 and the annual average number of drought days being more than 30 in most regions of southern China east of 105 ° E. The trend distributions of the frequency and intensity of RDEs in southern China are similar, with increasing trends in most western regions and decreasing trends in most eastern regions. The decreasing trends of RDEs in most eastern regions were mainly affected by the weakening of East Asia summer moonsoon (EASM) from the 1960s to the 1990s, which resulted in the summer main rain belts in eastern China moving from North China to southern China and caused the precipitation increasing in eastern regions of southern China from the 1960s to the 1990s. While the increasing trends of RDEs in most western regions were not only affected by the EASM, but also associated with the weakening of the India-Burma Trough (IBT) that caused less wet air transport to Southwest China and the decrease of precipitation in western regions of southern China. [ABSTRACT FROM AUTHOR]

ABSTRACT The investigation of weather forecast errors has focussed mainly on assessing the physical causes in numerical weather forecasting, such as errors in the initial state and model deficiencies. The framework and context of this paper are different. A 30 year time series (1979-2011) of 1 and 2 day human forecasts of temperature in Finland were used to investigate the statistical and climatological characteristics of maximum and minimum temperature forecast errors. Error dependence on different flow types and weather regimes was also analysed. The error statistics indicate that the forecast root-mean-square error has halved, and the forecast hit rate within a 2.5 °C error threshold has increased from 70% to 85-90% during the 30 year period. Large forecast errors of >5 °C are presently very rare, and they are mostly seen as positive biases in extreme cold temperatures and inversions. Otherwise, the forecasts nowadays are mostly unbiased with only small negative biases associated with Foehn events. Forecast error extremes were found during winter, with a secondary peak in spring and under high pressure periods in non-westerly and especially northeasterly airflows, dry air mass and relatively weak winds. The summertime maximum temperature errors are typically associated with opposite weather situations that occur most typically with cyclonic circulations, moist air masses and strong winds. [ABSTRACT FROM AUTHOR]

ABSTRACT The Extreme Forecast Index ( EFI) compares a medium range ensemble forecast ( ENS) to climatology to establish the severity of an event. In this paper, the large-scale influence of the design and configuration of this climatology on the climate distribution and the EFI is examined. The design factors considered are ensemble size (how many ensemble members), sampling frequency (how often per week), lead-time dependency (from which lead time to draw the climatology), and the sampling length (number of years). The results show that most of the climate configurations with sample size above 50-100 give a relatively good representation of the climate distribution between the 10th and 90th percentiles. For more extreme percentiles (for 1-10% and 90-99%) some care is needed to select the best configuration, whereas the extreme tails of the distribution cannot be well represented by any of the investigated configurations (up to a 14 year, daily, 50 member climate), for which a bigger sample would be needed. Results show that the hindcast length is clearly the superior sampling factor in general, better than the sampling frequency and the ensemble size. In addition, the ensemble size has only very limited contribution to the non-extreme climate percentiles and the EFI, especially at short range. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, the role of eddy feedback in the formation and excitation of the NAO ( North Atlantic Oscillation) is examined in a linear barotropic model with an empirical closure for synoptic eddy and low-frequency flow ( SELF) feedback. The EOF-space based model captures the linear dynamics of the barotropic model linearized with respect to climatological mean flow very accurately with relative low-order truncations. The parameterized empirical linear low-dimension SELF-feedback operator also depicts the relation between eddy-induced streamfunction tendencies and the large-scale circulation to a reasonable degree. Singular vector analysis ( SVD) is performed on the linear low-dimension dynamic operator with SELF-feedback to exam the leading low-frequency mode of the system. It is shown that the leading SVD mode (the left vector) of the linear low-dimension dynamic operator with smallest SVD value resembles the observed NAO pattern. The role of eddy feedback in the excitation and maintenance of NAO is then further examined by relating the effective external forcing patterns to the right vector of the leading SVD mode of the linear dynamic operator. It is shown that local dipolar external forcing at middle latitudes over North Atlantic is effective in exciting the NAO-like anomaly pattern, whereas the effectiveness of the external forcing over different areas sensitively depends on the eddy feedback. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, precipitation outputs from retrospective seasonal forecasts made by nine General Circulation Models ( GCMs) are used to investigate historical Indian summer monsoon seasonal rainfall variability and predictability over India. The observed data is taken from the India Meteorological Department whereas GCMs are obtained from the International Research Institute for Climate and Society, Columbia University, the National Center for Environmental Prediction, and the Japan Agency for Marine Earth Science and Technology. The study focusses on June- September precipitation hindcasts initialized from the 1 May. First, the mean climatology, variance of interannual variability ( IAV), and long-term trends for the nine GCMs were evaluated. Then Empirical Orthogonal Function ( EOF) is used to extract major climate modes and spectral analyses method is used to investigate the temporal properties of the leading principal components. It is found that the models are able to reproduce the climatology and IAV to varying degrees. The EOF and spectral analyses of models hindcast reveal that these models are capable of predicting the observed precipitation variability to some extent. In order to study the remote response, the correlation co-efficient between model predicted rainfall and sea surface temperature ( SST) have been calculated. The results suggest that the models show exaggerated remote response to ENSO SST forcing and the Indian Ocean Dipole Mode index has less predictive skill compared to ENSO. The correlation values between the model predicted Monsoon Hadley Index ( MHI) and observed MHI reveals that only a few of them could exhibit large scale circulation features well. [ABSTRACT FROM AUTHOR]

Cold air drainage is a characteristic of hilly or mountainous terrain and can have significant impact on agricultural or horticultural activities. This paper considers a range of synoptic and topographic factors that could affect the phenomenon of cold air drainage, through an exploration of its characteristics in the Peak District of central England, showing that cold air drainage events can occur at any time of the year, with summer events being even more frequent than those usually noticed in winter. The occurrence of such events is related to the local topography, and particularly the correspondence to hollows and local valleys on the scale of 0.5-1 km, rather than on the scale of the principal drainage routes in the region. In contrast to some previous studies, synoptic and local weather conditions were not found to be strong indicators of cold air drainage events. It is also shown that under suitable conditions cold air drainage can overcome the effects of the urban heat island. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Extreme weather events can have severe consequences for the local environment and population. Projected future changes in climate (e.g. UKCP09) indicate that North West England is likely to experience an increasing frequency and intensity of meteorological extremes, leading to flooding, heat waves and storms. Consequently, it is important that the region enhances its preparedness for such events. This paper explores the possibility of developing quantifiable climate risk indices for the case study area of Greater Manchester, using a combination of archival research and statistical analysis of past climate data. For extremes which are the function of a single meteorological variable (e.g. heat waves, pluvial flooding and heavy snowfall) the thresholds proved to be reliable and skillful. Days with maximum daily temperature greater than or equal to 29.2 °C, daily snowfall amount greater than or equal to 6 cm or maximum gust speed greater than or equal to 60 knots are found to be indicative of weather-related impacts which have in the past affected human health/well-being, have caused damage to the urban infrastructure or have severely disrupted services. Extreme events which are the result of a more complex interaction between variables (e.g. drought, freezing conditions) were less well captured by applying the thresholds associated with a single variable in isolation. Such critical threshold indices can be used in conjunction with future projections of climate change to establish weather-related risk for the future. This risk-based approach can subsequently be integrated to climate change adaptation strategies and development planning to ensure future preparedness. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Five years of UK Met Office global model analyses from 1 January 2004 to 31 December 2008 have been used to generate a global hail climatology at 1° latitude by 1° longitude resolution. Hail has been diagnosed from model vertical profiles of temperature and humidity using a simple algorithm based on a paper by Fawbush and Miller (). Results have been compared with published observational climatologies on both a global and regional basis. The model diagnoses compare favourably with the observed data with both orographic and seasonal signals. However, there are differences, and possible reasons for these are discussed. These include limitations of the simple algorithm, the difficulty of observing hail in sparsely populated areas and the problem of population growth influencing the number of hail reports. Copyright © 2011 Royal Meteorological Society and Crown Copyright [ABSTRACT FROM AUTHOR]

This study evaluates the predictive performance of the North American Multi-model Ensemble (NMME) over Central Africa (CA) using the historical rainfall data. The African Rainfall Climatology Version 2 (ARC2) is used as a substitute for reference observational data to examine the capability of 11 NMME and their NMME ensemble mean (MME) in simulating rainfall. Using the Kling- Gupta efficiency (KGE), Taylor skill score (TSS), and Heidke skill score, the predictive evaluation of the models is performed from lead 0 to lead 5 of each season. The results show that the NMME models satisfactorily reproduce the bimodal and unimodal structure of rainfall in CA at the lead 0 level of different seasons: December–February (DJF), March–May (MAM), June–August (JJA), and September–November (SON). The pattern correlation coefficient (PCC) shows values of NMME and MME greater than ~0.69 and TSS > 0.60 for all four seasons. The MME presents a maximum in DJF 0.~96 between 0 and 1 month lead time. With the same time scale, just over 85% of the NMME have a KGE between 0 and 0.42. It follows that as the forecast lead time increases, the PCC and TSS of each model become small, with PCC 0:~12 in JJA and DJF, TSS<0.21 in JJA at lead 5. The NMME models exhibit an important rainfall bias and the calculated scores show the quality of the forecast decreases with increasing lead time; this may justify a constraint on the models to keep the good quality of the long-term seasonal forecast in CA. [ABSTRACT FROM AUTHOR]

The last decade has seen a considerable increase in the amount and availability of remotely sensed data. This paper reviews the satellites, sensors and studies relevant to land surface temperature measurements in the context of meteorology and climatology. The focus is on using the thermal infrared part of the electromagnetic spectrum for useful measurements of land surface temperature, which can be beneficial for a number of uses, for example urban heat island measurements. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The propagation of radio electric waves emitted from ground-based meteorological instruments is determined through stratification of the atmosphere. In super-refractive cases characterized by strong temperature inversions or strong vertical moisture gradients, the radar beam can be deflected towards the ground (trapping). This phenomenon often results in spurious returned echoes and misinterpretation of radar images such as erroneous precipitation, wind, and temperature detection. In this study, a 5-year Central and West Africa (CWA) climatology of the frequency of super-refractive and trapping-layer base height has been produced using refractivity computations from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses at a 40-km horizontal resolution and 60 levels in the vertical direction. The aim of this climatology is to improve the understanding on how frequent such anomalous propagations conditions are, which is a prerequisite for fully benefiting from radar data information for the multiple purposes of model validation, precipitation analysis, and data assimilation. First, the main climatological features are summarized for the whole CWA: Sahara and inlands seldom experience super-refraction, whereas coastal areas are strongly affected, especially in regions where the temperature inversion and the trade winds are intense lying near the surface. Over land, seasonal averages of super-refraction frequencies reach 80% (40%) over moist areas year-round but remain below 40% (15%) in most other regions. Seasonal statistics exhibit a pronounced diurnal cycle of super-refraction occurrences, with averaged frequencies peaking at 60% in summer late afternoon over the areas located on the Atlantic Ocean border but inlands region are less affected with super-refractive cases by midday. [ABSTRACT FROM AUTHOR]

In this study we evaluate the reliability of the Regional Climate Model (RegCM4.6) by performing several sensitivity tests at 50 km horizontal resolution using 10 convection schemes or combination of convection schemes. Emphasis on model output is made for the September-October--November 2017-2019 seasonal period. Part of the Central African region, five sub-regions, was identified. The simulated temperatures are compared to the daily climatology of near-surface temperature of the European Centre for Medium-Range Weather Forecasts Reanalysis fifthgeneration and the National Center for Environmental Prediction datasets, while the simulated precipitations are compared to the precipitation of the Global Precipitation Climatology Project and Climate Hazards Group Infrared Precipitation with Stations datasets. In most analyses, the Grell scheme with Arakawa--Schubert closure assumption tends to have the best index of agreement but its spatial distribution shows underestimation of rainfall. Generally, the Emanuel convection scheme is more suitable to represent rainfall and temperature over Central Africa. Compared to our previous study (Komkoua Mbienda et al., International Journal of Climatology, 2017, 37, 328-342), the present study shows that we have to pay attention to the choice of convective scheme when using any version of RegCM4 released for climate study over Central Africa. This choice is strictly related to the RegCM version released, the study years and the season. It is important to note, however, that the results presented are a preliminary study of the response to the selected convection schemes. The analysis uses a limited sample of climate model simulation (three model years for each convection scheme). Follow-up work, featuring longer duration climate simulations and a full assessment of statistical significance, is therefore required to confirm the robustness of the analysis presented. [ABSTRACT FROM AUTHOR]

This study was conducted to assess drought trend, frequency and extremity during 1966-2012 over widely different climatic regimes in Iran. Two drought indicators, i.e. the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI), were employed to characterize the droughts at 3, 6, 12 and 24 month time scales. In addition, the Mann--Kendall test was used for trend analysis. There was a declining (drying) trend in the SPI and SPEI at 76% and 85% or more, respectively, of the investigated sites. The SPIs were not well correlated with the SPEIs over the hyper-arid/arid regions, demonstrating the significance of reference evapotranspiration (ET0) inclusion for drought identification over these water-limited areas. Furthermore, the SPEI appears not to be calculated reliably using temperature-based ET0 equations and also when wind speed data are missing at hyper-arid/arid sites. More frequent droughts were detected during 1998-2012, which can be attributed to more recurrent La Niña events in this period. Seasonally, a greater increment in drought frequency at 3 and 6 month time scales was found in the March-April-May period. The most extended droughts and the most intensive dry months were also captured over 1998-2012 for most locations. In the majority of cases, it seems that the 1998-2001, 2007-2009 and 2010-2012 La Niña events caused long and severe droughts. The drought frequency increment and the most extreme drought incidences seem to have adversely impacted the agricultural sector over the studied areas. Consequently, there is a need for adaptation to negate the influences of frequent intensive dry episodes in Iran. [ABSTRACT FROM AUTHOR]

Changes in precipitation patterns as a result of increased atmospheric water vapour in a warming environment over the Indian region have been reported in the past few decades. However, these studies have not focused much on exploring the changes in atmospheric water vapour in a changing climate. The present study focuses on examining the variability of integrated precipitable water (IPW) over the Indian region derived from the Modern Era Retrospective‐Analysis for Research and Application (MERRA 2) model in a warming environment. The results suggest that the IPW has increased significantly in recent decades. Changes in the IPW are consistent with changes in regional warming over India. The results also point out an increase of about 4.98% ± 1.26% in the IPW for a 1°C increase in regional warming. The variability of IPW has been examined in a warming climate. An increase in regional temperature shows coherent variation with IPW. A decadal increase of about 1.69% has been reported in the IPW. [ABSTRACT FROM AUTHOR]

The present study analyses the impacts of past and future climate change on extreme weather events for southern parts of Canada from 1981 to 2100. A set of precipitation and temperature‐based indices were computed using the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) multi‐model ensemble projections at 8 km resolution over the 21st Century for two representative concentration pathway (RCP) scenarios: RCP4.5 and RCP8.5. The results show that this region is expected to experience stronger warming and a higher increase in precipitation extremes in future. Generally, projected changes in minimum temperature will be greater than changes in maximum temperature, as shown by respective indices. A decrease in frost days and an increase in warm nights will be expected. By 2100 there will be no cool nights and cool days. Daily minimum and maximum temperatures will increase by 12 and 7°C, respectively, under the RCP8.5 scenario, when compared with the reference period 1981–2000. The highest warming in minimum temperature and decrease in cool nights and days will occur in Ontario and Quebec provinces close to the Great Lakes and Hudson Bay. The highest warming in maximum temperature will occur in the southern parts of Alberta and Saskatchewan. Annual total precipitation is expected to increase by about 16% and the occurrence of heavy precipitation events by five days. The highest increase in annual total precipitation will occur in the northern parts of Ontario and Quebec and in western British Columbia. [ABSTRACT FROM AUTHOR]

Reliable and affordable telecommunications are an integral part of service‐based economies, but the nature of the associated physical infrastructure leads to considerable exposure to weather. With unique access to observational records of the UK fixed‐line telecommunications infrastructure, an end‐to‐end demonstration of how extended range forecasts can be used to improve the management of weather risk is presented, assessing forecast value on both short‐term "operational" (weeks) and long‐term "planning" timeframes (months/years). A robust long‐term weather‐related fault‐rate climatology is first constructed at weekly resolution, based on the ERA‐Interim reanalysis. A clear dependence of winter fault rates on large‐scale atmospheric circulation indices is demonstrated. The European Centre for Medium‐Range Weather Forecasts (ECMWF) sub‐seasonal forecast system is subsequently shown to produce skilful forecast of winter weekly fault rates at lead times of three to four weeks ahead (i.e. days 14–20 and 21–28). Forecast skill at a given lead time is, however, a necessary rather than a sufficient condition for improved risk management. It is shown that practical decision‐making leads to dependencies across multiple forecasts times that cannot be modelled using traditional "cost‐loss matrix" methods as errors in previous forecasts influence the value of subsequent forecasts. A parsimonious model representing operational decision‐making for fault repair scheduling is therefore constructed to show that fault‐rate forecast skill does improve both short‐ and long‐term management outcomes (in this case meeting performance targets more often in the short term, or reducing the resources required to achieve these targets in the long term). Consequently, it is argued that new methods are needed for forecast skill assessment in complex decision environments. [ABSTRACT FROM AUTHOR]

This study uses the Offset Elliptical Normal (OEN) mixture model to parameterize the seasonal–diurnal wind climate of Rome, Italy, for engineering design purposes, and also to reveal the physical meteorology of this "mixed" wind climate. The joint probability density function (PDF) of the wind vectors in the zonal–meridional plane are represented by a mixture of disjoint bivariate‐Normal ellipses. Each OEN ellipse is tentatively attributed to a physical wind mechanism: sea/land breezes; transient coastal jets; katabatic flows; the migrating atmospheric tide; and (non‐diurnal) geostrophic winds. The model enables a fuzzy probability of each wind mechanism to be assigned to each observation, allowing the progression of the various diurnal cycles to be tracked through time. This seasonal–diurnal parametric model is directly applicable to wind energy resource estimation, pollution studies, pedestrian comfort, and heating and ventilation design. The model is also an essential starting point in methods to simulate realistic time series of wind speed and direction. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented which focuses on new weather monitoring techniques and how they can be used to measure parameters of weather and climate in the troposphere.

An objective verification system for the Met Office's 5‐day thunderstorm and cumulonimbus (CB) risk forecasts is described. The forecasts are designed specifically to forecast the impact of CB on aviation in the London Terminal Manoeuvring Area, known as the London TMA, and are produced by meteorologists at the Met Office. Challenges faced in developing the verification system resulting from the subjective nature of the forecasts themselves and the limitations of the data (from the UK Air Navigation Service Provider [UK ANSP]) available to assess the true impact on aviation are discussed. The forecasts include the likelihood of medium impact events as well as the likelihood of high impact events resulting from thunderstorms. A unique approach has been taken to verifying these forecasts which has involved working closely with the primary user, the UK ANSP. An objective verification system has been developed to assess the forecast accuracy across all lead times for high and medium impact events. This system provides the tools necessary for routine, year‐on‐year evaluation of the forecast performance. Verification of impact‐based forecasts is challenging and using traditional weather observations to verify the forecasts is not possible. The verification system developed to assess the performance of the Met Office's thunderstorm risk forecasts takes a unique approach to identifying observed medium impact and high impact convective events using data provided by the UK Air Navigation Service Provider to verify the 5‐day forecasts. Results from the 2014 and 2015 seasons of operation indicate that forecast performance is good. [ABSTRACT FROM AUTHOR]

ABSTRACT Growing interest in traditional knowledge ( TK), particularly in relation to the prediction of weather or climate extremes, raises issues concerning the appropriate storage and management of the information collected. The Traditional Knowledge Database ( TK Database) for the storage and use of TK associated with weather and climate prediction in the Pacific was designed with the following principles in mind: (1) preservation of the knowledge, maintaining cultural context wherever possible; (2) respect for intellectual property and cultural sensitivities around data sharing and use; (3) appropriate system design, accounting for ongoing costs of system maintenance and often intermittent Internet access; and (4) moving beyond data preservation to ensure continued use and growth of the TK. The TK Database was successfully deployed to four countries in the south Pacific and is regularly used by their national meteorological services, and partner organizations, both to preserve TK related to weather and climate and as a tool to assist in monitoring the TK indicators. As the first database of its kind, the TK Database fills a critical gap in the appropriate storage and application of TK and provides an important foundation for future developments. [ABSTRACT FROM AUTHOR]

ABSTRACT The rainfall prediction accuracy of seven state-of-the-art operational models during landfall ( LF) of tropical cyclones formed in the North Indian Ocean was assessed. The rainfall predicted by these models 1-3 days (24-72 h) before the LF day of tropical cyclones was compared with TRMM_3B42 rainfall data. Cyclone induced rainfall occurs along its track; thus rainfall within 600 km along the cyclone track was used for comparison. The error in cyclone track prediction affects the rainfall prediction. This has been taken care of by shifting the rainfall distribution over the cyclone best track positions provided by the India Meteorological Department. The validation statistics for the rainfall prediction accuracy of the models were computed by combining the forecasts generated by these seven models during LF of nine cyclones formed in the North Indian Ocean during 2010-2013. The skill of the models was analysed using different rainfall validation measures/statistics. Based on these validation statistics it was found that, of the seven global models, the models from four centres, namely the National Center for Environment Prediction, the European Centre for Medium-range Weather Forecasts, the UK Meteorological Office and the Canadian Meteorological Centre, performed closer to the observations. However, there was no single model which was able to exhibit all the features of the observed rainfall. [ABSTRACT FROM AUTHOR]

ABSTRACT A detailed observational study of squall line thunderstorms, a particular form of mesoscale convective systems arranged in a line that repeatedly affected Salento Peninsula (southern Apulia, Italy) throughout 2015, is presented and discussed. Specifically, three relevant events that occurred in January, at the end of September and in October are described, combining thermodynamic and synoptic analysis with radar imagery delivered by the cutting-edge polarimetric Doppler radar recently installed in Torchiarolo, in the central part of Salento Peninsula. Reported observational information reveals that, regardless of the season of the year, convergence along an approaching cold front represents the common initiating mechanism leading to the formation of linear convective systems. Furthermore, high resolution Doppler data provided by Torchiarolo radar allows better detection and prompt recognition of severe weather signatures, such as bow echoes and cyclonic mesovortices, commonly associated with squall line thunderstorms. Therefore, the present study clearly confirms the key role of the new advanced weather radar installed in Torchiarolo which thus represents a powerful tool giving researchers and forecasters valuable information about kinematic and microphysical properties of severe weather systems crossing Apulia region, especially Salento Peninsula. [ABSTRACT FROM AUTHOR]

ABSTRACT Accurate forecasts of fog and visibility are important for many applications; while prolonged fog can adversely affect many crops, even a short duration of dense fog can lead to disruption of air and highway traffic. The genesis and dynamics of fog are a result of many processes; accurate forecasting of fog thus continues to be a challenge. A forecast model of the occurrence of fog, measured in terms of visibility, is presented. The model is formulated as an analogue model; thus the merit of the model is primarily based on its validation against observation. Two forecasts using two sets of meteorological fields are considered: one as the benchmark forecasts with visibility calculated from observed meteorological fields and the other based on meteorological forecasts from an atmospheric mesoscale model ( Weather Research and Forecasting). While the benchmark (perfect) forecasts from observed meteorological fields provide the potential skill of the model, the mesoscale forecasts provide an assessment of realizable skill in an operational setting. The validation was carried out against hourly visibility data recorded at Indira Gandhi International Airport over Delhi during the winter months ( December and January) for the period 2009-2012. Error statistics show that the analogue fog model can capture a significant part of the observed variability of fog. The forecasts have more success in forecasting intense (visibility < 500 m) and persistent (duration > 4 h) fog events. The model provides a useful forecasting tool, as shown by measures such as average error, number of false warnings and the number of misses. [ABSTRACT FROM AUTHOR]

ABSTRACT This study examines the simulation of the catastrophic precipitating event that occurred on 14-16 May 2014 over the western Balkans, using two regional models, the Eta model and the Weather Research and Forecasting Non-hydrostatic Mesoscale Model ( WRF-NMM). This case was an extreme precipitation event with very large precipitation totals exceeding 200 mm in 72 h. The Eta model was run in two variants, switched to use the eta co-ordinate with sloping steps and switched to use the sigma co-ordinate. The aim of this study was to analyse the ability of the regional model to forecast heavy precipitation successfully as well as the impact of the vertical co-ordinate on the forecasting of extreme precipitation events based on realistic model simulation. Experiments show the ability of regional models to reproduce extreme accumulations for 2 days of heavy precipitation with bias adjusted equitable threat score ranging from 0.3 to 0.5 for precipitation greater than the analysed threshold values (25-55 mm day−1), whereby the Eta model exhibits a slight advantage over the WRF-NMM and the run of the Eta model switched to the eta co-ordinate has the smallest frequency bias. For larger observed accumulations exceeding 50 mm day−1 all forecasts tend to be more biased. The root mean square precipitation difference varies insignificantly between the three forecasts. The results of the experiment indicate that, in the case of the extreme precipitation considered in this study, scores of the forecasts of the Eta model for 10 m wind speed and 2 m temperature show a small dependence on the vertical co-ordinate and in favour of the run with the eta co-ordinate. [ABSTRACT FROM AUTHOR]

ABSTRACT While seasonal outlooks have been operational for many years, until recently the extended-range timescale referred to as subseasonal-to-seasonal ( S2S) has received little attention. S2S prediction fills the gap between short-range weather prediction and long-range seasonal outlooks. Decisions in a range of sectors are made in this extended-range lead time; therefore, there is a strong demand for this new generation of forecasts. International efforts are under way to identify key sources of predictability, improve forecast skill and operationalize aspects of S2S forecasts; however, challenges remain in advancing this new frontier. If S2S predictions are to be used effectively, it is important that, along with science advances, an effort is made to develop, communicate and apply these forecasts appropriately. In this study, the emerging operational S2S forecasts are presented to the wider weather and climate applications community by undertaking the first comprehensive review of sectoral applications of S2S predictions, including public health, disaster preparedness, water management, energy and agriculture. The value of applications-relevant S2S predictions is explored, and the opportunities and challenges facing their uptake are highlighted. It is shown how social sciences can be integrated with S2S development, from communication to decision-making and valuation of forecasts, to enhance the benefits of 'climate services' approaches for extended-range forecasting. While S2S forecasting is at a relatively early stage of development, it is concluded that it presents a significant new window of opportunity that can be explored for application-ready capabilities that could allow many sectors the opportunity to systematically plan on a new time horizon. [ABSTRACT FROM AUTHOR]

ABSTRACT The goal of the present study was to exploit the volumetric data from the Wideumont weather radar to estimate the occurrence and severity of hail over a period of 10 years (2003-2012). The radar is located in the southeastern part of Belgium and its domain covers Belgium, Luxembourg and some parts of Germany, France and The Netherlands. Two hail detection algorithms were used for detecting hail falls in the volumetric radar data. The algorithms provide an empirical estimation of the probability of hail ( POH) and the probability of severe hail ( POSH). The study shows that post-processing of probabilities by means of the advection correction significantly influences the statistical results about hail occurrence. The advection correction is very effective in reducing the 'fishbone effect' due to a temporal sampling of the radar data that is too low, which has an impact on the geographical distribution of the hail fall frequencies over the study domain. The post-processed POH and POSH datasets are verified against hail reports at the ground. The statistics obtained show that the diurnal cycle of hail falls has a pronounced peak in the 1500-1600 UTC (local solar time + 1 h) time interval with 28% of all hail events occurring in July and 30% of severe hail events occurring in May. Nevertheless, severe hail events have a low occurrence in absolute terms and longer time series of observations are required to obtain a more reliable severe hail climatology. [ABSTRACT FROM AUTHOR]

ABSTRACT The advanced algorithm for the tracking of objects ( AALTO) constructs tracks from objects, such as thunderstorms or mesocyclones, detected by multiple weather radars at irregular time intervals. It is important to have high accuracy in tracking thunderstorms to generate skilful forecasts and high-quality climatologies and, fundamentally, to ensure that any derived product from tracks captures only that particular storm, and in its entirety. AALTO incorporates many of the best practices of existing tracking algorithms and techniques employed by meteorologists in constructing tracks. AALTO differs from existing algorithms designed to track meteorological phenomena that manifest in radar data in the following ways: (1) AALTO is designed to track objects from multiple radars, enabling analysis over a larger domain than if a single radar was used; (2) improved tracking is realized through improved initial motion estimates and directional thresholding and (3) AALTO looks both at the track history and at the subsequent possible positions along a track when constructing the best possible tracks, mimicking the approach that would be taken by a human meteorologist. Verification was done using metrics that were objectively determined to distinguish between good and degraded tracks; a description of the approach to determine the appropriate metrics is presented. An overview of the AALTO tracking procedure and an example case are presented in this study. [ABSTRACT FROM AUTHOR]

An increasing number of significant and violent tornado events in the United States have been documented and mapped at extremely high resolution by government, research and private entities using remotely sensed and post-event damage surveys; however, these assessments often generate inconsistent spatial measures of tornado strength, even for the same event. This investigation assembles a portfolio of contemporary tornado events that contain spatially comprehensive damage and/or wind velocity information from a diverse set of sources. Thereafter, the relationship between land-use/cover and tornado intensity is examined in order to quantify spatial measures of damage indicator bias in post-event tornado damage surveys. A climatology of both significant and violent tornado intensity assessments is then created, promoting the generation of synthetic, or model, paths with observationally constrained damage length and width metrics by the Enhanced Fujita scale magnitude. Results from the climatology and collection of synthetic paths are compared to previous observed, empirical and theoretical assessments, revealing differences in the spatial scale of the overall tornado footprint, as well as percentage contribution of swaths by Enhanced Fujita scale magnitude. The range of synthetic paths produced may be used to assess potential tornado damages to the population, the built environment and insurance portfolios. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to compare the forecasting skill of two nowcasting schemes, the Multi-scale Tracking Radar Echoes by Cross-correlation (MTREC) in current usage and the newly developed Multi-scale Tracking and Forecasting Radar Echoes (MTaFRE) used by the State Key Laboratory of Severe Weather (LaSW) of the Chinese Academy of Meteorological Science (CAMS), with the Eulerian Persistence Model (EPM) scheme as a benchmark, and the state-of-the-art Watershed-Clustering Nowcasting (WCN) scheme, which is part of the Warning Decision Support System-Integrated Information (WDSS-II) developed at the University of Oklahoma and the National Severe Storms Laboratory (NSSL). The inter-comparison considers six heavy-rain events and one month of radar data observed by radar networks of the Chinese Meteorological Administration (CMA) located in the Jianghuai River Basin. Four sets of forecast fields up to the next 180 min with an interval of 15 min were generated by the four nowcasting algorithms, and the forecast performances were evaluated as a function of lead time. At an individual event level, the results show that no single model outperforms all others consistently in cross-skill categories at all lead-time intervals of the six events. Overall, EPM performs worse than the three Lagrangian persistent models (LPMs). The MTREC scheme performs slightly worse than the WCN scheme used in WDSS-II, and the MTaFRE scheme is most comparable to the WCN scheme. More importantly, this study confirms that the MTaFRE shows an improvement over its predecessor MTREC by using multi-scale moving mean windows effectively for different lead times. [ABSTRACT FROM AUTHOR]

Streamflow droughts are characterized by reduced runoff and can cause significant damage to nature and society. Forecasts of stream flow droughts could improve risk management and preparedness. How the quality of the meteorological forcing of a hydrological model affects the hydrological response during stream flow droughts was explored in case studies of two Swiss rivers: the Thur, which is mainly rain-fed and the Landquart, which is dominantly snow-fed. A fully distributed version of the PREcipitation-Runoff-EVA potranspiration HRU model (PREVAH) was used with input from: (1) meteorological observations, (2) reforecast from the probabilistic numerical weather prediction model Limited-area Ensemble Prediction System developed and run by the COnsortium for Small-scale MOdelling (COSMO-LEPS) and (3) COSMO-LEPS reforecasts that are calibrated with the bias correction method quantile mapping. The meteorological input variables such as precipitation, air temperature, wind speed, relative humidity, global radiation and sunshine duration are required to initialize PREVAH. Different combinations of the input variables, for example observed precipitation with the other variables from COSMO-LEPS, were used to assess the sensitivity of each input variable to the performance of the low-flow simulation (1981-2000). Stream flow droughts are defined by indices of duration, severity and magnitude, by applying a seasonally varying threshold. Simulations for low-flow and stream flow drought performed better when meteorological observations or calibrated COSMO-LEPS reforecasts were used as forcing instead of the COSMO-LEPS reforecast. It was sufficient to replace precipitation with observations or calibrated COSMO-LEPS values and keep the other variables from COSMO-LEPS to improve the low-flow simulations. Depending on the catchment characteristics, better quality of temperature and relative humidity may also be relevant. [ABSTRACT FROM AUTHOR]

The present study assesses the medium-range probabilistic forecast issued using an improved version of the Centre for Weather Forecasting and Climate Studies (CPTEC) Ensemble Prediction System (EPS). This version includes improvements made to the method used to select the fastest growing modes (the empirical orthogonal functions (EOF)-based method), and the bias correction. Results demonstrate that this improved CPTEC EPS surpasses the skills of the current operational version. An assessment was conducted using the framework of the THORPEX Interactive Grand Global Ensemble (TIGGE), comparing three configurations of the CPTEC EPS to the EPS from the National Centre for Environment Prediction (NCEP) and the Korean Meteorological Agency (KMA). The score adopted for metrics was the continuous ranked probability score (CRPS), calculated for absolute temperature at the 850 hPa level (T850), and sea level pressure (SLP). The best improvements were found for T850 over the Northern and Southern Hemispheres, with a general increase of 9 days in the useful forecast horizon. SLP augments are more modest, with useful performance extension of 2 days in the Northern Hemisphere and 3 days in the Southern Hemisphere. All the EPSs over the Southern Hemisphere showed a general decrease in performance when compared with their respective counterparts in the Northern Hemisphere, both for T850 and SLP. Over the Tropics, SLP is better predicted than T850 by most EPSs, but the NCEP EPS presents the best performance over this region with similar scores for the two variables. [ABSTRACT FROM AUTHOR]

ABSTRACT This study is based on climatological records (1979-2008) of cold outbreak ( friagem) events that occurred in the southern Amazon region during the austral winter months (May to September). The friagem events were identified with an objective method that used climatological data from the surface station of the Department of Airspace Control ( DCEA) in Vilhena city, including the minimum temperature ( Tmin), the pressure reduced to mean sea level ( Pmsl) and the decrease in Tmin ( DTmin). The purpose of this study was to investigate the association between atmospheric circulation and friagem events using Climate Forecast System Reanalysis ( CFSR) and a composite method. One hundred and forty-four friagem events were identified with the proposed methodology. These events produced large changes in weather conditions in Amazonia, including an abrupt decrease in air temperature, an increase in the amount of dry air, and an increase in surface pressure. The main atmospheric features associated with friagem events are an intensification of high post-frontal surface pressure that is caused by the intensification of a ridge at middle and high levels when air approaches the Andes and strong southerly winds at the surface that carry cold, dry air to tropical latitudes. [ABSTRACT FROM AUTHOR]

ABSTRACT Accurate predictions of severe weather events are important for the society, economy, and environment in regions affected by such events. In the present study, the development and testing of a suite of prototype ensemble-based early warning products for severe weather events, which are now routinely available at , are reported. The early warning products are based on operational medium-range ensemble forecasts from four of the leading global numerical weather centres: the European Centre for Medium-Range Weather Forecasts, the Japan Meteorological Agency, the UK Meteorological Office, and the National Centers for Environmental Prediction in USA. In these products, the forecast probability of the occurrence of severe weather events, including heavy rainfall, strong surface winds, and high/low surface temperatures, is defined based on each model's climatological probabilistic density function. Several case studies have demonstrated the ability of the products to successfully predict severe events, including the Russian heatwave in 2010, the 2010 Pakistan floods, and Hurricane Sandy in 2012. The construction of a grand ensemble by combining four single-centre ensembles can improve the probabilistic skills of forecasts of severe events, up to a lead time of +360 h. The improvements in forecast skills are more pronounced for severe surface temperature and precipitation. The grand ensemble provides more reliable forecasts than single-centre ensembles, particularly with respect to strong wind speeds and severe temperature, aiding the advance detection of severe weather events to help mitigate the associated catastrophic damage, especially in developing countries. [ABSTRACT FROM AUTHOR]

Rain gauge observations show that when averaged over a large number of cases of frontal systems passing over the UK, strong orographic rain enhancement occurs on the lee slopes of the first hills encountered by the southwesterly flow in the warm sector. The operational forecasts using 1.5 km grid spacing produced realistic looking mean rainfall patterns over the Lake District and Wales, with an area-averaged rain accumulation error of less than 2%. Model-level rain rates increase with decreasing altitude consistent with the seeder-feeder mechanism. Increasing the horizontal grid spacing in the operational weather forecast model decreases the amount of rain produced over the hills, thereby reducing forecast accuracy. The area-averaged rain accumulations are 11-24% smaller than observed at 12 km grid spacing and 33-48% smaller than observed at 40 km grid spacing. In additional simulations of the 15 January 2011 case over the Lake District at 1.5 km grid spacing, replacing the orography with that used by the 12 and 40 km models reduced the area-averaged rain accumulations by 10 and 23% respectively. These changes were due to reduced cloud water and ice mixing ratios over the lower hills resulting in slower increases in rain rate with decreasing altitude. It is demonstrated that neglecting the horizontal advection of falling rain drops results in too much rain falling on the windward slope and not enough falling on the lee slopes. Copyright © 2012 British Crown Copyright, the Met Office. Published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Empirical conditional probabilities of extreme monthly precipitation averaged over three regions of the southern part of the La Plata basin were calculated as a function of three atmospheric indices: two of them represent low level moisture convergence and the third is related to the mid tropospheric circulation over southern South America. The first region includes southern Paraguay, northeastern Argentina, north of Uruguay and the western sector of southern Brazil, the second region stretches over part of southern Brazil, while the third region, surrounding the Plata Estuary extends over western Uruguay and eastern Argentina between 37 ° S and 32 ° S. Regional monthly precipitation was considered extreme when it exceeded its mean value plus one standard deviation. Conditional empirical probabilities of Months with Extreme Precipitation ( MEP) are more than twice and even four times higher than climatic probabilities when they are calculated under the restriction that the atmospheric indices were beyond certain extreme thresholds empirically defined. Combined conditional probability is even higher when the values of two or the three indices over their respective thresholds take place at the same time, but these cases are less frequent. The index that renders higher conditional probabilities is the one that accounts for the low level moisture convergence in a region that is basically to the west and outside of the three regions. This reflects the fact that most of the mesoconvective systems, which originate to the west of these regions and then move eastwards, produce heavy precipitation that lead to monthly accumulated extremes. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT Forest fires are the most crucial natural threat to forests and wooded areas. They destroy many more trees than all other natural catastrophes such as parasite attacks, insects, extreme weather events and others. Forest fires, especially in summer and dry autumn/spring periods, are frequent in the Mediterranean basin and represent growing environmental and ecological problems. The aim of this investigation is to determine a climatic pattern of fire-meteorology over the Mediterranean basin via the frequency analysis of the forest fires weather index ( FFWI) of Haines. The FFWI values were obtained by using the hourly data derived from reanalysis fields available from the National Centers for Environmental Prediction/ National Center for Atmospheric Research ( NCEP/ NCAR) for the period 1980-2010. High frequency values of FFWI, taken to be a sign of moderate-level risk of forest fires, were obtained on the forests, scrubs, succulents and wooded areas in several countries facing the sea including Greece, Italy, Turkey, Syria, Lebanon, Cyprus, Macedonia, Albania, Serbia, Slovenia, France, Portugal, Spain, Morocco and Tunisia, almost all of which are characterized by dry summer, subtropical Mediterranean climates. As expected, the highest-level risk values are found in the arid desert climate regions: the desert areas of the Sahara and Libya in North Africa and the semi-arid steppe climate regions of the Middle East, as well as the semi-arid environments near the Caspian Sea basin. Copyright © 2013 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT Between January and May 2011, southern China suffered perhaps the most severe drought since 1954. This investigation was carried out based on OLR ( Outgoing Long-wave Radiation) data derived from NOAA/ AVHRR satellite observations, precipitation records at 753 meteorological stations in China and NCEP reanalysis data during 1990 and 2011. This was done by first calculating the January to May climate averages of all required atmospheric parameters during 1990 and 2011, and then calculating the January to May 2011 anomalies (the difference between the parameter value in January to May 2011 and its climate average), with the goal to understand the dynamic and thermal mechanisms behind the 2011 5 month drought. Results show that during the drought: (1) the large-scale circulations were abnormal with a strengthened Mongolian High, a weakened subtropical high and abnormal northerly winds prevailing over southern China and the South China Sea; (2) the air was drier due to the anomalous deep dry-cold air column at middle and lower levels over southern China (linked to the northerly wind from the Mongolian anticyclone and the northwesterly wind from the Yellow Sea cyclone); (3) the abnormal air temperature structure, i.e. warm at higher levels (due to the abnormal South Asian High) and cold at middle and lower levels (due to the anomalous deep dry-cold air column over southern China), and (4) a formation of an abnormal mesoscale circulation structure, with the cyclonic convergence at the mid-level low (due to the Yellow Sea cyclone), the anticyclonic divergence at the low-level small high (due to the Mongolian anticyclone) and the resulting abnormal vertical downward movement over southern China. All these factors contributed significantly to the January to May 2011 drought over southern China. [ABSTRACT FROM AUTHOR]

ABSTRACT This study focuses on the spatial distribution of heavy precipitation events that occurred in Romania over 30 years, between 1 January 1980 and 31 December 2009. It is the first such study carried out for this country, using this particular data set and methodology, whereby a Relational Database Management System was used to store data on precipitation and to filter subsets of interest out of the main dataset. Increasing trends have been found in the time series of the maximum annual precipitation amounts recorded in 24 h, and in that of the annual number of events; an increasing trend, from one decade to another, was also found in the latter dataset. Peculiarities of spatial distributions over the three decades are highlighted, such as the virtual confinement of extreme precipitation events to areas outside of the Carpathian Mountains arch in Romania and on mountain sides oriented towards the outside of it. [ABSTRACT FROM AUTHOR]

The propagation of electromagnetic waves emitted from ground-based meteorological radar is determined using high-resolution radiosonde data. In this work, a detailed analysis of surface ducts has been undertaken to determine the anomalous propagation days on the coastal site of Douala in Cameroon (4 °N, 9.7 °E) over the Gulf of Guinea. The median duct strength shows that the strongest ducts are seen in the rainy season and that the surface duct occurs more frequently during the day than at night. The duct strength seasonal variability shows a value over Douala of about − 7.2 M-units for 1200 UTC and − 4.5 M-units for 0000 UTC in January, whereas in July the duct strengths are stronger during the day (−12.8 M-units at 1200 UTC) than at night (−9.8 M-units at 0000 UTC). The Cloudsat data products for Douala and neighbouring areas during the days of 26 January 2009 at 233525 UTC and 5 July 2009 at 233552 UTC were also analysed in association with the statistical discussion. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

ABSTRACT An evaluation of the performance of the Stable Equitable Error in Probability Space ( SEEPS) and the Symmetric Extremal Dependence Index ( SEDI) as monitoring metrics for 6 h precipitation forecasts from regional NWP is presented. These scores provide complementary assessments of forecast performance. SEEPS quantifies general performance in the prediction of dry weather and precipitation amount. SEDI focuses on higher threshold events. By using the climatological distribution of precipitation at each location to define thresholds, both scores assess the locally important aspects of the forecast. Both scores can also be aggregated over climatologically diverse regions to obtain an area-mean performance measure. From the perspective of forecast system development, an important aspect of both scores is their resistance to hedging. Each score is calculated for forecasts coming from two model systems, one a 12 km regional configuration of the Met Office Unified Model ( MetUM), the other is the independent European Centre for Medium-range Weather Forecasts ( ECMWF) global model; here interpolated to a 25 km grid. Results suggest that SEEPS can be meaningfully applied to 6 h accumulations. Diurnal variations in SEEPS highlight timing errors in the development of convection. A decomposition in the contributions to SEEPS highlights the over-prediction of drizzle near midday, and difficulties to predict convection during the evening. SEDI results suggest that performance trends in 90% percentile events are detectable over a 3 year period. However, results do suggest that higher model resolution improves the skill and frequency bias for higher percentile events. Copyright © 2013 Royal Meteorological Society and British Crown copyright, the Met Office [ABSTRACT FROM AUTHOR]

Daily weather patterns over the North Atlantic are classified into relevant types: typical weather patterns that may characterize the range of climate impacts from aviation in this region, for both summer and winter. The motivation is to provide a set of weather types to facilitate an investigation of climate-optimal aircraft routing of trans-Atlantic flights (minimizing the climate impact on a flight-by-flight basis). Using the New York to London route as an example, the time-optimal route times are shown to vary by over 60 min, to take advantage of strong tailwinds or avoid headwinds, and for eastbound routes latitude correlates well with the latitude of the jet stream. The weather patterns are classified by their similarity to the North Atlantic Oscillation and East Atlantic teleconnection patterns. For winter, five types are defined; in summer, when there is less variation in jet latitude, only three types are defined. The types can be characterized by the jet strength and position, and therefore the location of the time-optimal routes varies by type. Simple proxies for the climate impact of carbon dioxide, ozone, water vapour and contrails are defined, which depend on parameters such as the route time, latitude and season, the time spent flying in the stratosphere, and the distance over which the air is supersaturated with respect to ice. These proxies are then shown to vary between weather types and between eastbound and westbound routes. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Drought has significantly affected environmental and socio-economic conditions in Iran. In this study three drought indices were used for monitoring drought intensity and duration in the Kashafrood basin (northeast Iran). The standardized precipitation Index (SPI), Precipitation Index Percent of Normal (PNPI) and Agricultural Rainfall Index (ARI) were calculated for the base period (1990-1961). All these indices were used to assess future drought events in the Kashafrood basin under climate change attributed to low and high greenhouse gas emission scenarios (SRES B2 and A2, respectively) for three periods (2010-2039, 2040-2069 and 2070-2100). Projected changes in precipitation, temperature and potential evaporation were simulated by statistical downscaling of HadCM3 outputs. The main results showed: (1) slight increase in precipitation means, around 2.2-5.4% under the A2 scenario and 6.8 and 8.6% under the B2 scenario: (2) slight increase in maximum temperature, around 4.6-5.6 °C for the A2 scenario and 4.25 and 4.6 °C under the B2 scenario; (3) slight increase in minimum temperature, around 1.6-1.9 °C under the A2 scenario and 1 and 2.23 °C under the B2 scenario, and, (4) higher drought frequency associated with global warming was demonstrated by all indices under both scenarios. Such an increase in drought frequency would have major implications for natural resource management, water security planning, water demand management strategies and drought relief payments. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a relationship between rainfall and surface water (runoff) in South Crete, Greece. This application was carried out on five sub-basins in the Messara valley, with a total surface of 1125 km2. Three factors were taken into account: the climate regime including precipitation and air temperature, the geological nature of the ground and the surface area of the basin. The development of the rainfall-discharge model consisted of three steps. Firstly, the actual evapotranspiration ( Er) was computed. Secondly, the storage capacity of each hydrogeological unit in every catchment area was geologically estimated and, lastly, the rainfall-runoff model was developed using the water balance equation and the above mentioned relationship of Er. The amount of variance in runoff between the sub-basins explained by those three factors was 92%. Decreases in mean annual precipitation by 17 and 15% for east and west Messara, respectively, predicted by the regional climate model REMO resulted in even more drastic mean runoff reductions by 29 and 32% at the respective sides of the valley. Furthermore, the coefficient of variation of runoff increased by more than 15% in the east side of the valley but dropped by only 1.5% in the west. The proposed rainfall-discharge relationship is a useful tool for hydrological management and evaluation of water resources under the present-day and future climate conditions in Messara valley in Crete. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

From 1961 to 2008, the overall frequency of dust storms in northern China has shown an unquestionable reduction. However, the Hunshdak Sandy Lands of northern China display an increasing frequency in dust storm activities, especially during the period 2001 to 2008. In an attempt to explore the cause of this increase, a comprehensive investigation was conducted by examining the climate variables, the average normalized difference vegetation index (NDVI) and the local inhabitant migrations. The climate variables include local precipitation, temperature, aridity, evaporation, relative humidity, soil moisture and wind speed. Moreover, by analyzing the 2001-2008 average anomaly charts (relative to the 30 year climatology of 1971-2000) of the upper air and surface conditions, an advantageous atmospheric circulation background for drought development over the Hunshdak was confirmed. Meanwhile, a multivariable step-regression model was employed to distinguish the significant variables of the climate elements mentioned before. The model output suggests that aridity is the leading factor impacting the Hunshdak dust storm frequency. During 2001 to 2008, the lack of local precipitation, higher temperature and strong evaporation deteriorated the local surface condition to below that before 2000, which is verified by the reduction of vegetation cover (NDVI), soil moisture and relative humidity. Furthermore, compared to the 30 year climatology of the wind speed observed during dust storm occurrence time, the mean velocity of 2001-2008 was reduced by 3.0 m s−1, indicating that even with relatively weaker winds, dust storms still occurred primarily due to the degeneration of surface conditions around the Hunshdak. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]