Weather Types Research Articles

Asymmetric warming rates between warm and cold weather regimes in Europe

AbstractIn Europe, the increase in temperatures caused by climate change has been particularly fast in the cold season. Although the magnitude of this change is relatively well known, less research has been done on how the increase of temperatures is manifested in different large‐scale weather types, called weather regimes. For example, one could expect that the weather patterns in which air is flowing from the rapidly‐warming Arctic would have warmed faster than other weather patterns in recent decades. Here we show that such an asymmetric warming actually occurs in the four Euro‐Atlantic weather regimes. In northern Europe, the weather regime which is typically associated with cold airmasses from the Arctic (NAO–) has warmed about 25% faster than the cold‐season days on average, and about 60% faster than the regime where the air flows from the North Atlantic (NAO+). Consequently, the weather regime that on average brings the coldest weather is warming the fastest in a large part of northern Europe. In contrast, the weather regime that typically brings the warmest weather has warmed the slowest, especially in the continental Europe. Our results provide a new perspective on the reported decrease of sub‐seasonal temperature variability.

Association between circulation weather types and hospital admissions due to COPD in Changchun, a city in Northeast China

Association between circulation weather types and hospital admissions due to COPD in Changchun, a city in Northeast China

A Comparison of Different Station Data on Revealing the Characteristics of Extreme Hourly Precipitation Over Complex Terrain: The Case of Zhejiang, China

AbstractBoth long‐term but small number of national stations and short‐term but large number of regional stations have been frequently used to study the extreme hourly precipitation (EXHP) in China. However, few studies focus on the differences of the two for revealing the features of EXHP. In this study, the characteristics of EXHP in Zhejiang Province are investigated using three rainfall data sets at three threshold criteria. The comparison between different data sets shows that increasing the station density can better reflect the climatic spatial distribution of EXHP thresholds if long‐term data is absent. The majority of EXHP can be classified into four weather types: the southwesterly wind type (30.7%–48.5%), the trough type (12.2%–23.6%), the tropical cyclone (TC) type (11.4%–17.5%) and the easterly wind type (4.9%–17.9%). The selection of stations is more sensitive to the proportions of the four weather types than the statistical years and threshold criteria. The monthly and diurnal variations of EXHP, as well as their differences revealed by the three data sets, are varied by weather type. Only using national stations cannot distinguish the spatial differences between the TC type and the easterly wind type, and there is an underestimation for southwesterly wind type and trough type in the mountainous area of southwest Zhejiang. The statistical year and station height are the main reasons for the differences in the duration of EXHP events calculated by different data sets, with the TC type having the largest effect and the southwesterly wind type the smallest.

Sources of contamination in sediments of retention tanks and the influence of precipitation type on the size of pollution load

Densification of cities and urban population contributes to increased runoff and suspended solids and alteration of the urban water cycle. Nowadays, Blue-Green Infrastructure is promoted to increase a city’s resilience to floods; however, stormwater drainage systems, supported with retention tanks are still important in protecting urban areas against floods. Sediment accumulation in stormwater infrastructure relates to an issue of pollutants such as heavy metals, nutrients etc. Research on the origin of the pollutants associated with the suspension and ultimately sediment accumulated in sewage can bring new insights about processes in urban catchment areas. This is the first study, which is focused on the analysis of stable carbon and nitrogen isotopes in bottom sediments collected from municipal retention tanks to verify the origin of the deposited pollutants immediately after pluvial floods. The research was additionally extended with water quality analyzes immediately after three types of weather: a dry period, typical precipitation (< 30 mm) and torrential rainfalls (2 events with daily precipitation over 30 mm which caused pluvial flooding of the city area). Analyses of sediments indicated that the main source of carbon and nitrogen in the bottom of the retention tanks had been brought with stormwater runoff from the city area. Organic nitrogen fertilizers appeared to be the main source of nitrogen, while the sources of organic carbon were mixed: C3 land plants, wood, and oil. Additionally, it was found that torrential rainfall caused a 23-fold increase of N-NO3 concentration, a sevenfold increase of P-PO4 concentration, and an over fivefold increase of concentration of organic matter, in comparison to typical precipitation.

The climate change impact on greenhouse gas emissions (CO2 and N2O) from soils at agroecosystems

Formulation of the problem. Soils are a significant source of greenhouse gases (GHGs), the release of which into the atmosphere forms the global warming potential. Mathematical models describing greenhouse gas emissions make it possible to assess the impact of climate change on the GHG emissions on a regional scale, and study how land-use changes affect these emissions. The study is aimed at assessment of potential changes in CO2 and N2O emissions from soils at agroecosystems under the influence of temperature regime changes and increasing aridity in the context of global climate change. Materials and methods. Numerical experiments with a comprehensive model of GHG emissions from the soils at the winter wheat agroecosystem were performed by means of RCP4.5 climate change scenario. The study is based on the materials of agrometeorological observations at the hydrometeorological station of Bilovodsk (Eastern Ukraine) for the period of 1991-2020 and the climate change scenario RCP4.5 for the period of 2021-2050. Results. Classification of crop vegetation conditions allowed us to reduce the diversity of their regimes to certain weather types, characterizing the common conditions of crop formation in spring and summer, due to which the so-called ‘dry’ and ‘humid’ years were distinguished. The tendencies of change in air temperature and rainfall during vegetation of winter wheat in years different on humidity have been established. The increase in air temperature from the beginning of the growing season was gradual, while maintaining a stable correlation: a ten-day average long-term temperature was more than a temperature of the ‘dry’ year which was more than a temperature of the ‘humid’ year. The intensity of greenhouse gas emissions is defined by the type of humidification in the growing season. In the ‘dry’ years at the beginning of the vegetation season, CO2 emissions will make up 0.044-0.079 tons of С-CO2 ha-1 per a ten-day period, which is higher than the average long-term values and almost twice as high as in the ‘humid’ years. In the spring at the beginning of the growing season, as a rule, the level of moisture content in the arable soil layer is quite high, which leads to the formation of anaerobic conditions. They, in turn, determine the level of N2O emissions. Increasing aridity reduces the level of N2O fluxes. For ‘dry’ years, at the expense of a fairly high level of spring moisture of the arable layer at the beginning of the growing season, the level of N2O emissions was quite high (0.061-0.089 kg of N-N2O ha-1 per a ten-day period). Subsequently its level decreased significantly. In general, total greenhouse gas emissions in terms of CO2 equivalent will decrease by 6.2% in ‘dry’ years and by 32.3% in ‘humid’ years. Conclusions. Based on numerical experiments with the model of greenhouse gas emissions from soils at the winter wheat agroecosystem, the general patterns of vegetation-related variation of CO2 and N2O emissions are identified. The main patterns feature consists in increasing CO2 emissions during spring-summer vegetation of winter wheat from the beginning of a growing season to the wax ripeness phase and in decreasing N2O emissions from the beginning of the winter wheat growing season until its ending. Their peculiarities are defined by the years’ different humid conditions.

Two-Stage Grid-Connected Frequency Regulation Control Strategy Based on Photovoltaic Power Prediction

The large number of photovoltaics connected to the distribution network via power electronic converters squeezes the functional space of traditional synchronous generators in the power system and reduces the inertia of the network itself. However, due to the random and fluctuating nature of PV power generation, different types of meteorological conditions can also affect the inertia support capability of PV output power. Therefore, this paper proposes a frequency regulation control strategy based on the dynamic characteristics of the grid-side DC capacitor. Firstly, the control strategy of the grid-side inverter is improved and the mechanism of the frequency dynamic response model under PV penetration is analysed. Secondly, data from different weather types are correlated and analysed to predict PV power, and wireless sensor technology is used to introduce the data signals into the control link. Finally, a simulation model of a two-stage PV power generation system is developed and the fast-response capability of the system under different control parameters when the load is increased or decreased is analysed. The results show that under the proposed frequency regulation strategy, the larger the regulation coefficient and virtual inertia time constant, the greater the virtual inertia provided by the PV power generation, which improves the stability of the distribution network.

Optimal Dispatch of Distribution Networks Based on Energy Storage Systems and Integrated Demand Response in Lightning Climates

Lightning weather is a type of strong convective weather that is an important factor in causing faults in the operation of the distribution network, which can lead to widespread power outages. The application of PV and energy storage systems further mitigates the losses caused by lightning-struck outages. In the paper, firstly, the uncertainty model of lightning strike probability and contact line power loss is established based on the irradiation intensity and the expected value of power losses is calculated using sequence operation theory. Secondly, considering the cost of load loss, an optimal dispatching model of the distribution network based on opportunity-bound planning is constructed to minimize system operation costs, and the impact of different operation strategies on power loss in the lightning context is explored in depth. The proposed method allows for a trade-off between the economy and the reliability of the distribution network in the lightning context by setting suitable confidence levels. Finally, the model is solved using the CPLEX solver, and the accuracy of the proposed model and dispatching strategy is verified by an improved IEEE33 system example.

Scenario-based multi-objective optimization strategy for rural PV-battery systems

Increasing the proportion of photovoltaic (PV) electricity in power systems is effective for achieving carbon neutrality. However, PV electricity is unstable and random, and direct connection to the grid reduces power quality and jeopardizes grid security. Herein, a scenario-based optimized sizing and management strategy for a rural PV-battery system is proposed for a village in Central China. The goal of this power system is not only to meet its own electricity demand without other energy supplies, but also to smoothly feed electricity into the grid. In this study, the possibility of applying the optimization strategies and evaluation methods of power plants in the design of rural power systems is explored. The PV power model, battery charging and discharging model, and farmer's energy use model are established respectively, and the constraints are combined with the nodal power balance principle, and then solved by simulated annealing algorithm with economy and grid interaction smoothness as the objective function. For optimal component sizing, this study considered various scenarios with different types of farmers, seasons, and weather to ensure that the performance of the objective function can be satisfied at any time throughout the year. This study proposed the objective function and evaluation index for smooth interaction with the grid for the first time. The simulation results showed that the required PV and battery capacities differed depending on farmer type, owing to different seasonal electrical loads and weather conditions. Compared to traditional PV-battery systems, the proposed system improves the smoothness of interaction with the grid by 87 %, while reducing transformer expansion pressure by approximately 50 kW. Therefore, based on rational capacity selection and optimization strategies, it is possible for a rural power system to become a virtual power plant.

Changes in extreme precipitation in Taiwan's Mei‐yu season

AbstractHigh‐resolution Taiwan Climate Change Projection Information and Adaptation Knowledge Platform (TCCIP) gridded precipitation data are used to characterize days in the Mei‐yu season with the most extreme precipitation (EP). These “EP days” are grouped into weather types based on the presence of features such as tropical cyclones (TCs) and atmospheric rivers (ARs), then analyzed from the perspective of weather type frequency and synoptic changes. During the 1979–2019 period, EP days associated with ARs were associated with significant increasing trends in season‐total precipitation. These AR‐related precipitation increases are due to four events in 2005, 2006, 2012, and 2017 which had long duration and unusually intense precipitation, and which were anomalous even within the longer 1960–2019 time period. Meanwhile, TC‐related EP days contribute less precipitation than they did in the 1980s due to decreased frequency of TCs on EP days and in the Mei‐yu season climatology. Over the 1979–2019 period, the AR‐related and TC‐related trends combine to produce EP increases in western Taiwan and decreases in eastern Taiwan. Mei‐yu season southwesterly integrated vapor transport (IVT), wind speed, and specific humidity have all increased in association with these extreme events. Low‐level winds appear to the primary factor influencing the IVT increase, with increased moisture also contributing. The wind trends are consistent with climatological pressure increases south of Taiwan and decreases over the East Asian landmass, which facilitate a strengthened circulation in a corridor extending from the southern China coastline over Taiwan during this season.

Human thermo-physiological comfort assessment in Lisbon by local climate zones on very hot summer days

Extreme heat is a current and future issue on urban areas, with negative impacts on health and quality of life (increasing morbidity and mortality rates). This paper analyses day (12:00–15:00 h) and nighttime (00:00–03:00 h) thermo-physiological comfort (TC) conditions by Local Climate Zones (LCZ) in Lisbon during a particular Local Weather Type (LWT), very hot summer days. For this, 13 different microscale sample areas were chosen covering urban and non-urban land cover classes (LCZs 1–3, 4–6, 8, 9, A and B). Universal Thermal Climate Index (UTCI) and Mean Radiant Temperature (MRT) were modeled on SkyHelios software for 163 days between 2008 and 2014. Results show that during the day all urban LCZ samples depict the same average TC conditions (average UTCI of 34°C—strong heat stress) and densely wooded areas are 2°C cooler (average UTCI of 32°C—moderate heat stress). However, compact areas (LCZs 1–3) with low sky view factor and some vegetation (street trees) display lower percentages of area with higher thermo-physiological discomfort (TD) levels (83% with strong heat stress against 98% in LCZs 8 and 9 and 100% in LCZs 4–6). When considering the hottest days (air temperatures equal or above 35°C—75th percentile), the moderate heat stress class disappears in all samples and the very strong heat stress class appears only on urban areas, occupying between 12% and 16% on LCZs 1–3, 10%–22% on LCZs 4–6, 16%–22% on LCZs 8 and 9 on LCZ 9. During the nighttime period all samples show no thermal stress, favoring nocturnal physiological recovery. TC conditions in Lisbon are strongly influenced by solar radiation and wind, which explains the need to increase the shading area, preferably by trees, and to promote and preserve ventilation paths.

Weathering Intensity Response to Climate Change on Decadal Scales: A Record of Rb/Sr Ratios from Chaonaqiu Lake Sediments, Western Chinese Loess Plateau

The Rb/Sr ratio of lake sediments has been widely adopted as an indicator of weathering intensity in studies of past climate change, but the geochemical significance of this ratio varies with timescale. Here, we present Rb/Sr data for the past 300 years for sediments collected from Chaonaqiu Lake in the Liupan Mountains of the western Chinese Loess Plateau as a decadal-scale record of weathering intensity. To validate the application of this weathering proxy, we correlated the record with those of other major elements, rock-forming minerals, and paleoclimatic proxies. We found that Rb/Sr ratios are influenced mainly by Sr activity within the lake catchment (where Sr is likely sourced from albite). In addition, higher (lower) Rb/Sr ratios of bulk sediments from Chaonaqiu Lake are correlated with lower (higher) fractions of terrigenous detritus (SiO2, Ti, K2O, Al2O3, and Na2O). These indicate that the Rb/Sr ratios of bulk sediments in Chaonaqiu Lake are closely linked to terrigenous detritus input on decadal scales and also correlate well with TOC (a precipitation indicator) and other high-resolution paleoclimate records (e.g., tree rings and drought/flood index) in neighboring regions, with higher (lower) Rb/Sr ratios corresponding to more (less) precipitation. Lake bulk sediment Rb/Sr ratios are dominated by the input of terrigenous detritus over decadal timescales. Our data show that physical and chemical weathering in the Chaonaqiu Lake watershed have opposing influences on Rb/Sr ratios of bulk sediment, competing to dominate these ratios of lake sediments over different timescales, with ratios reflecting the relative importance of the two types of weathering.

Assessment of Winter Urban Heat Island in Ljubljana, Slovenia

Although the urban heat island (UHI) phenomenon is more commonly studied in summer, its influence is also important in winter. In this study, the authors focused on the winter UHI in Ljubljana (Slovenia) and its impact on the urban population, as well as in comparison with a UHI study from 2000. Through a combination of mobile and stationary temperature measurements in different parts of the city, the winter intensity of the UHI in Ljubljana was studied in a dense spatial network of measurements. It was found that the intensity of the winter UHI in Ljubljana decreases as winters become warmer and less snowy. The results showed that the winter UHI in Ljubljana intensifies during the night and reaches the greatest intensity at sunrise. During the winter radiation type of weather, the warmest part of Ljubljana reaches an intensity of 3.5 °C in the evening. In total, 22% of the urban area is in the evening UHI intensity range of 2–4 °C, and 65% of the urban population lives in this range. In the morning, the UHI in Ljubljana has a maximum intensity of 5 °C. The area of &gt;4 °C UHI intensity covers 7% of the urban area, and 28% of the total urban population lives in this area. Higher temperatures in urban centers in winter lead to a longer growing season, fewer snow cover days, lower energy consumption and cold stress, and lower mortality from cold-related diseases compared to the colder periphery.

Short–term global solar radiation forecasting based on an improved method for sunshine duration prediction and public weather forecasts

Accurate forecasting of daily global solar radiation (Rs) is important for photovoltaic power and other sectors. Numerical models coupled with public weather forecasts information is a feasible method to predict short–term daily Rs. Here, we propose a novel sunshine duration converting method (n_new) based on forecasted air temperature and weather types data, which we validated using measurements from 86 radiation stations. A widely-used, generalized sunshine–based Rs model (Rs_n) was then coupled with the n_new method (Rs_n new) for forecasting daily Rs. This was further compared to Rs_n incorporated with the common sunshine duration converting method (n_com) using only weather types data (Rs_n com) and a recently developed generalized temperature–based model (Rs_T). The results indicated that the n_new method produced better estimates than the n_com method, as indicated by increased mean correlation coefficient (R; 13.0%–24.5%) and index of agreement (dIA; 2.9%–9.5%) and decreased mean root mean squared error (RMSE; 12.8%–14.8%) for the 1–7 days lead time over 86 sites. The Rs_n new model improved the accuracy for 98% of sites when compared to the Rs_n com model, with mean values of R and dIA increasing by 7.7%–11.0% and 2.1%–4.8% and that of RMSE decreasing by 9.7%–12.5% for the 1–7 days lead time. The results suggest that the Rs_n new model is advantageous in short–term forecasts. The Rs_n new model ranked first for 52.3%–74.4% of sites for the 1–7 days lead time, followed by the Rs_T model (25.6%–47.7%). Moreover, there was generally a better performance for the Rs_n new model to forecast daily Rs at a longer lead time. Therefore, the Rs_n new model using weather forecasts information is highly recommended to forecast short–term daily Rs.

Influence of weather regime and local geomagnetic activity on the occurrence of epileptic seizures

Epilepsy is a common neurologic disease and presents a major public health problem. Patients with epilepsy have unexpected occurrence of seizures with many triggered by existing triggering factors such as alcohol, stress etc. Other potential triggers include certain weather or atmospheric parameters and local geomagnetic activity. We have analyzed the impact of atmospheric parameters grouped in 6 grouped weather types or weather regimes and the local geomagnetic activity through the K – index. In the prospective study, we analyzed a total of 431 seizures over a 17-month period. In the results obtained, we found that the most severely common weather regime grouped type of weather was radiation and then precipitation regime. It was also found that grouped weather types of weather regimes had more impact on generalized than focal epileptic seizures. Local geomagnetic activity had no direct effect on the occurrence of epileptic seizures. Those results confirm the thesis how the impact of certain external factors is complex and that the further study is required in that respect.

Load forecasting of district heating system based on improved FB-Prophet model

Accurate load forecasting of the district heating network (DHN) is essential to guarantee effective energy production, distribution, and rational utilization. An improved Facebook-Prophet (FB-Prophet) model with additional positional encoding layers has been developed to forecast the DHN heat consumption. The accuracy of univariate and multivariate FB-Prophet models is evaluated; this paper also evaluates the optimum training dataset length. To explore the performance of the improved FB-Prophet model in heating load forecasting tasks, another seven machine learning models, namely FB-Prophet, DeepVAR, long-short term memory, extreme gradient boosting, multilayer perceptron, recurrent neural network, and support vector regression are used for comparison. The historical heating load, outside temperature, relative humidity, speed of wind, direction of wind, and weather type of a DHN in Serbia are utilized to extensively investigate the effectiveness of the improved FB-Prophet model. The prediction outcomes of all the models are thoroughly analyzed. The results indicate that the improved FB-Prophet model can generate the most precise and consistent predictions and it showed better results for sparse DHN data. The prediction curve is fitted to the trend of hourly DHN consumption change, which can play an effective guiding function in the distribution of heat.

Weather Types and Their Influence on PM10 and O3 Urban Concentrations in the Cergy-Pontoise Conurbation

Abstract Daily atmospheric concentrations of the pollutants PM10 and O3 vary according to weather types. This study aims to identify the weather patterns associated with PM10 and O3 pollution episodes from 2009 to 2020. Episodes characterized by exceedance of World Health Organization standards were identified, and their duration and persistence were studied. The results show that air pollution days are associated with three atmospheric patterns for PM10 and four for O3. The dominant weather pattern corresponds to an anticyclonic situation in central and Eastern Europe with a ridge of high pressure over France at the surface and 500-hPa geopotential height. For PM10, the persistent high-concentration sequences were found to be associated with a thermal inversion constraining the vertical dispersion of pollutants. For O3, the four weather types responsible for ozone pollution all have a higher occurrence in summer. The highest percentage (46% of days) is associated with the presence of a ground-level barometric marsh (an area of the atmosphere between two weather systems where the pressure varies slightly but is slightly low) and a ridge at 500 hPa (weather type T1). Similarly, thermal inversions and thermal winds cause pollution to persist beyond 8 consecutive days. Significance Statement Air quality is not only influenced by ground-level emissions, but also by complex meteorological processes that can contribute to pollutant accumulations. The importance of this research is that the prediction of these processes helps to prevent the development of extreme concentrations near the surface. The results of this study provide a better understanding of how characteristic weather patterns in the Cergy-Pontoise conurbation impact PM10 and O3 pollutant levels. These impacts are expressed by the intensity and frequency of pollution episodes.

Exploring injury severity of Non-Motor vehicle riders involving in traffic accidents using the generalized ordered logit model

This study aims to explore potential factors that affect non-motor vehicles (NMV) riders’ injury severity in accidents with motor vehicles (MV). Factors including human characteristics, vehicles, road features and environmental conditions were investigated. Police-reported crash data from the period of 2007 to 2017 in Xi’an, China were used to develop the generalized ordered logit models. Model results revealed that NMV riders’ injury severity was significantly influenced by rider’s Hukou, type of NMV, type of roadside protection, road structure, linearity, weather, accident time, light condition and visibility level. Besides, factors involving NMV rider’s age, compulsory third party insurance, type of MV, season, road type will increase their risk of suffering from serious/fatal injuries. Research findings are beneficial in helping policymakers to develop measures to improve NMV riders’ safety in China, such as isolating NMV and MV, educating drivers especially those from rural areas, and improving road and environment conditions.

Media against the Fire, or How to Secure the Forest for the Trees

May 01 2023 Media against the Fire, or How to Secure the Forest for the Trees Kapp Singer Kapp Singer Kapp Singer is a writer from California. He is interested in infrastructure and its representations, capitalism, and the climate crisis. His work has appeared in venues such as Pidgin and Bloomberg CityLab. He is pursuing a B. A. in architecture at Yale, graduating in May 2023, and his favorite type of weather is fog. Search for other works by this author on: This Site Google Scholar Author and Article Information Kapp Singer Kapp Singer is a writer from California. He is interested in infrastructure and its representations, capitalism, and the climate crisis. His work has appeared in venues such as Pidgin and Bloomberg CityLab. He is pursuing a B. A. in architecture at Yale, graduating in May 2023, and his favorite type of weather is fog. Online ISSN: 2572-7338 Print ISSN: 1091-711X © 2023 Kapp Singer2023Kapp Singer Thresholds (2023) (51): 96–109. https://doi.org/10.1162/thld_a_00778 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn MailTo Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Kapp Singer; Media against the Fire, or How to Secure the Forest for the Trees. Thresholds 2023; (51): 96–109. doi: https://doi.org/10.1162/thld_a_00778 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThresholds Search Advanced Search This content is only available as a PDF. © 2023 Kapp Singer2023Kapp Singer Article PDF first page preview Close Modal You do not currently have access to this content.

Inclement Weather and Risk of Missing Scheduled Hemodialysis Appointments among Patients with Kidney Failure.

Nonadherence to hemodialysis appointments could potentially result in health complications that can influence morbidity and mortality. We examined the association between different types of inclement weather and hemodialysis appointment adherence. We analyzed health records of 60,135 patients with kidney failure who received in-center hemodialysis treatment at Fresenius Kidney Care clinics across the Northeastern US counties during 2001-2019. County-level daily meteorological data on rainfall, hurricane and tropical storm events, snowfall, snow depth, and wind speed were extracted using National Oceanic and Atmosphere Agency data sources. A time-stratified case-crossover study design with conditional Poisson regression was used to estimate the effect of inclement weather exposures within the Northeastern US region. We applied a distributed lag nonlinear model framework to evaluate the delayed effect of inclement weather for up to 1 week. We observed positive associations between inclement weather and missed appointment (rainfall, hurricane and tropical storm, snowfall, snow depth, and wind advisory) when compared with noninclement weather days. The risk of missed appointments was most pronounced during the day of inclement weather (lag 0) for rainfall (incidence rate ratio [RR], 1.03 per 10-mm rainfall; 95% confidence interval [CI], 1.02 to 1.03) and snowfall (RR, 1.02; 95% CI, 1.01 to 1.02). Over 7 days (lag 0-6), hurricane and tropical storm exposures were associated with a 55% higher risk of missed appointments (RR, 1.55; 95% CI, 1.22 to 1.98). Similarly, 7-day cumulative exposure to sustained wind advisories was associated with 29% higher risk (RR, 1.29; 95% CI, 1.25 to 1.31), while wind gusts advisories showed a 34% higher risk (RR, 1.34; 95% CI, 1.29 to 1.39) of missed appointment. Inclement weather was associated with higher risk of missed hemodialysis appointments within the Northeastern United States. Furthermore, the association between inclement weather and missed hemodialysis appointments persisted for several days, depending on the inclement weather type.

Mapping the urban climate to address summer comfort management in French urban planning documents

In France, the integration of climate and energy issues in the spatial planning tools of local authorities is compulsory for cities with more than 20000 inhabitants. Through the example of Toulouse Metropole, the interdisciplinary work here presented make use of the available geographic and climatic data to perform spatial microclimatic diagnostics and its translation into recommendations to address thermal summer comfort. Analysis maps and strategic maps for daytime and night time are presented for thermal and aeraulic analysis taking advantage of available numerical simulations at 250x250 m, one year of duration and local weather type classifications. A three years long collaboration with the local authority and the urban agency allowed the co-construction of the cartographic protocol and the publication of an Atlas as well as a set of guidelines. Collaboration with a network of French cartographers allowed original propositions on graphic semiology as visual organization, the choice of urban and geographical information to be combined with the climatic information or a proposition of a new UTCI colorimetric spectrum.