Climatological Approach Research Articles

Thermodynamic and Dynamic Components of Winter Temperature Changes in Western Canada, 1950–2020

Abstract Most of the globe has experienced significant warming trends that have been attributed to anthropogenic climate change. However, these rates of warming are also influenced by short-term climate fluctuations driven by atmospheric circulation dynamics, resulting in inconsistent trend magnitudes in both time and space. This research evaluated winter (December–February) temperature trends over 1950–2020 at 91 climate stations across British Columbia (BC), Alberta (AB), and Saskatchewan (SK), Canada, and determined the components attributed to thermodynamic and dynamic (atmospheric circulation) factors. A synoptic climatological approach was used to classify atmospheric circulation patterns in the midtroposphere, relate those patterns to surface temperature, and evaluate changes in frequency. Moderate to high temperature increases over 71 years were found for most of the region, averaging 3.1°C in southern SK to 4.1°C in central-northern AB, and a maximum of 5.8°C in northern BC. Low to moderate increases were found for southern BC, averaging 1.2°C. Changes in atmospheric circulation accounted for 29% and 31% of observed temperature changes in central-northern BC and AB, respectively. Dynamic factors were a moderate driver in southern AB (18%) and central-northern SK (13%), and low in southern SK (5%). Negative dynamic contributions in southern BC (−6%), suggest that atmospheric circulation changes counteracted thermodynamically driven temperature changes. Results were consistent with trend analyses, indicating this method is well suited for trend detection and identification of thermodynamic and dynamic drivers. Results of this research improve our understanding of the magnitude of winter temperature changes critical for informing adaptation and climate-related policy decisions. Significance Statement Winter temperatures are strongly influenced by atmospheric circulation patterns, which move warm or cold air masses over large distances. We wanted to understand how changes in atmospheric circulation affect observed changes in winter temperatures in three provinces in western Canada. This also helps us to understand how much temperature change is due to anthropogenic (e.g., caused by greenhouse gases and land cover changes) and naturally occurring changes to Earth’s energy balance. Our results highlight the importance of understanding variability when selecting a time series for trend analyses or climate baselines for modeling studies. This study also helps to inform climate-related policies, decision-making, and adaptation strategies.

Global Observations of Tropospheric Bromine Monoxide (BrO) Columns From TROPOMI

AbstractBromine monoxide (BrO) plays an important role in tropospheric chemistry. The state‐of‐the‐science TROPOspheric Monitoring Instrument (TROPOMI) offers the potential to monitor atmospheric composition with a fine spatial resolution of up to 5.5 × 3.5 km2. We present here the retrieval of tropospheric BrO columns from TROPOMI. We implement a stratospheric correction scheme using a climatological approach based on the latest GEOS‐Chem High Performance chemical transport model, and improve the tropospheric air mass factor calculation with TROPOMI surface albedo data accounting for the geometrical dependency. Our product presents a good level of consistency in comparison with measurements from ground‐based zenith‐sky differential optical absorption spectroscopy (r = 0.67), aircrafts (r = 0.46), and satellites (similar spatial distributions of BrO columns). Furthermore, our retrieval captures BrO enhancements in the polar springtime with values up to 7.8 × 1013 molecules cm−2 and identifies small‐scale emission sources such as volcanoes and salt marshes. Based on TROPOMI data, we probe a blowing snow aerosol bromine mechanism in which the snow salinity is reduced to better match simulation and observation. Our TROPOMI tropospheric BrO product contributes high‐resolution global information to studies investigating atmospheric bromine chemistry.

Climatological approaches of irrigation scheduling for growing tomato crop under drip irrigation in sub-tropical region of Punjab

A field experiment was conducted at Lovely Professional University, Phagwara, Punjab for two years (2022 and 2023) to study the response of tomato crop to drip irrigation scheduling based on climatological approach viz. Penman-Monteith, Blaney-Criddle and pan evaporation. Result revealed that, the all treatments of irrigation scheduling were found feasible for optimizing tomato yield (30.8 to 44.6 t ha-1), water saving (27 to 50.7%) and water use efficiency (1.31 to 1.61 t ha-1-cm) under drip irrigation over soil moisture depletion approach. In selected region the average daily ET0 (4.4 to 9 mm day-1) and ETC (2.5 to 10.8 mm day-1) varies with different growth stages and results varying crop water demand of tomato. This water demand can successfully meet out by applying water at 100 % ET0 based on Penman-Monteith method with significant crop yield (44.6 t ha-1) and water use efficiency (1.33 t ha-1-cm). Correlation analysis indicated that, in case of other regions where the availability of weather parameters will be limited for irrigation scheduling, the farmer could irrigate their tomato crop at 90% ET0 based on daily pan evaporation method under drip irrigation. In selected region, the Blaney-Criddle method was found ineffective and shows under and overestimated values of daily ETo during mid stage and late stage which gives more water saving (up to 51%) but reduces significant tomato yield over Pan Evaporation method.

Seasonal climate models for national wheat yield forecasts in Brazil

National wheat yield depends on climate conditions and usually remains unknown until harvest. In-season knowledge can be provided by wheat yield forecast systems, supporting the decision-making of farmers, food traders, or policymakers. In this study, we improved a previously developed statistical wheat yield model to forecast trend-corrected wheat yield in Brazil with monthly temperature and precipitation data from seasonal climate models (SCM) from the last three months before harvest. We chose SCM from the European Center for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environmental Prediction (NCEP), and the UK-based Met-Office (UKMO). A multi-model ensembles (MME) approach from the three individual models as well as a climatology (CLIMATE) approach were also tested. Wheat yield forecasts were issued at the beginning of each month from planting in April to harvest in November. Each month, features from future months are forecasted by SCM, and past features are supplemented with observations from weather stations. Our approach shows a 12% RMSE in forecasting yield early in the season, from April to June. Forecasts start to improve from July onwards, with shorter lead times and including observed features from September onwards. At the beginning of October, about two months before harvest is completed, wheat yield can be forecasted with 7.6%, 7.9%, 7.9%, 9.1%, and 9.3% RMSE using climate data from UKMO, ECMWF, MME, NCEP, and CLIMATE respectively. Seasonal climate models can be useful tools to forecast national wheat yield, even shortly before harvest to prepare for possible food shortages. Our approach could be applied to other staple crops and regions.

Investigating surface UHI using local climate zones (LCZs), the case study of Cairo’s River Islands

The spatial configuration of the built environment influences the thermal behaviour at the local level and may generate the urban heat island (UHI) phenomenon. This impact has been investigated through several physical and climatological approaches. In this respect, the local climate zones (LCZs) scheme is recently adopted to facilitate the spatial study and understanding of UHIs. This research investigates the formation of surface UHIs in the case of the Nile River Islands, Cairo. It adopts the classification scheme of LCZs for selecting and comparing samples and conducting analyses of the distribution of land surface temperature (LST) for the area of interest. The adopted workflow aims at defining the homogenous zones of LCZs by three main steps: (i) the classification of LCZs based on supervised pixel-based classification of geospatial data, using the web-based tool of LCZ Generator, (ii) the detection of UHIs through the estimation of LST, and (iii) spatial statistical tests of Global Moran’s Index and Hotspot analysis for studying the significance of LST distribution within the study area. The adopted workflow successfully assists in estimating the LST and mapping UHI, and it contributes to the understanding of the physical and thermal characteristics of the selected urban areas. The analyses of outputs show reliable results with the recent studies of spatial relations between LCZs and LST.

A climatology-based wind speed map for NBR 6123

abstract: Updating the basic wind speed map of NBR 6123 –-Wind loading on buildings – is one of the duties of the committee responsible for the revision of this code. Traditionally such maps are elaborated by means of extreme value wind speed data collected at meteorological stations, use of statistical methods for data characterization, and application of mathematical regression to elaborate the territorial maps. However, the spatial distribution of the atmospheric phenomena responsible for strong winds cannot be disregarded. This work presents a proposal for a new wind speed map for NBR 6123 combining a climatological approach and wind speed data recently compiled from hundreds of meteorological stations. A climatological wind map was first produced considering the phenomena which cause strong winds, and used as a basis to draw the isopleths of the basic wind speed map, considering the measured wind speed data. The resulting map shows basic wind speeds ranging from 30 to 48m/s.

Application of climatological approach to determine the temperature of radiation fogs formation

The effectiveness of a radiation fog forecast is determined by the accuracy of a forecast for two values – temperature of fog formation and minimum air temperature. The accuracy of the first measurement significantly depends on a degree of adaptability of a forecast method to specific factors affecting the formation of fogs – orthography, local circulations, seasons, time of day, temperature-humidity stratification in the boundary layer of the atmosphere, etc. Taking into account each of them in a specific point will dictate its characteristics, whereas use of non-adapted fog forecasting methods will reduce their effectiveness.
 The article suggests an approach that makes it possible to carry out a comparative analysis of the prognostic value of the fog formation temperature and its average value pertaining to a specific point, season and time of day.
 In order to implement the studied approach the research considered a daily-annual repeatability of fogs at Kyiv station over 2012-2020. Based on this an average temperature of fog formation for each combination of month and time of day was determined according to actual observation data and, for the purpose of comparison, according to the Sanders method that uses data from radio sounding of the atmosphere as its baseline. The results of the analysis of the structure of the fog repeatability distribution allowed approximation of the daily-annual distribution of fog formation temperature via polynomial functions and a harmonic two-dimensional oscillator. Based on the selected efficiency criterion it was determined, via sequential selection, that the polynomial approximation of the data indicating the actual temperature of fog formation during the year is the most effective method. Obtaining an analytical form of the probability distribution function of daily and annual values of the fog formation temperature allows us to plot graphs of its daily variability for any month of the year. Such result makes it possible to control emissions of forecast values of fog formation temperature for a specific point, season and time of day, which will increase the effectiveness of the existing ways of making the forecasts in question.

Coriander Seed Quality and Vigour Assessment as Affected by Bioregulators and Varied Irrigation Regimes Based on Climatological Approach

The evaluation of seed quality parameters in coriander (Coriandrum sativum L.) under different irrigation regimes based on climatological approach and varied compositions of stress mitigating chemicals was carried out in the Laboratory of Seed Technology Research Unit, Department of Plant Breeding and Genetics, College of Agriculture, JNKVV Jabalpur (M.P.). The investigation consisted of four Irrigation regimes ie IW/CPE 0.6, 0.8, 1.0 and 1.2 and stress mitigating chemicals (Salicylic acid, thiourea and KNO3) with different concentrations. The experiment was laid out in Completely Randomized Design with three replicates during Rabi season (2020-21 and 2021-22). Marked influence of applied irrigation regime was exhibited by the seed lot collected from plots with IW/CPE ratio 0.8. The maximum standard germination of 82.89% was recorded in seeds from the plants which were grown in sufficient moisture content comprising of IW/CPE 1.2. Exogenous application of salicylic acid improved the seed germination parameters. The highest concentration was most effective in each treatment. Salicylic acid @ 150 ppm expressed better results. The results depicted higher test weight with 17.80g, higher plumule length of 15.75cm, radical length of 5.61 cm, seedling height of 21.36 cm, maximum magnitude 1841.64 and 28.33 of seed vigour index I & II respectively for Jawahar Dhaniya-10 was registered when the seeds harvested from plots with treatment combination of IW/CPE 0.8 along with foliar spray of salicylic acid @ 150ppm (I2C2). Higher content of 89.57% total solids was expressed under interaction of IW/CPE 0.6 with exogenous application of thiourea @ 500ppm (I1C3). Hence it can be concluded that treatment combination of IW/CPE 0.8 along with foliar spray of salicylic acid @ 150ppm (I2C2) ascertained better seed germination and quality attributes.

Study on Soil Moisture Depletion Pattern of Wheat Under Different IW/CPE Ratio

Wheat is one of the most important cereal crops and staple food of nearly 35 percent of the world population. In climatologically approaches, irrigation is scheduled on IW/CPE ratio. In IW/CPE approach, known amount of irrigation water is applied when cumulative pan evaporation reaches predetermined level. The experiment was conducted in randomized block design with irrigation scheduling on climatological approach i.e. on IW/CPE ratios of IW/CPE=0.6, IW/CPE=0.8, IW/CPE=1.0, IW/CPE=1.2 and control treatment with six irrigations at critical growth stages of wheat. Seasonal water requirement of wheat was found to be highest (570 mm) under irrigation scheduling at control treatment (I 4). Favorable soil moisture was maintained in the irrigation scheduling treatment of IW/CPE=1.2 (I 4) throughout the growing period and it was always maintained in allowable depletion regime. However, soil moisture was inadequate in irrigation scheduling at IW/CPE=0.6 (I 1). Highest water use efficiency was recorded in treatment I2 which may due to lowest water use, followed by I 3, I 4, I 1 and I 5.

Tropospheric O3 Model from Climatological Approaches in the Colombian Andes

We identified two climatological parameters that are key to modeling the behavior of tropospheric ozone (O3) produced in the urban area of a heavily polluted city in the Colombian Andes. These parameters are the relative humidity (RH) and total radiation intensity (I). In topographically constrained areas, the production of tropospheric O3, as a by-product during photo-oxidation of carbon monoxide (CO) and nitrogen oxides (NO and NO2) has received much attention over the last decades. Models used to describe O3 dynamics are based on computationally demanding techniques that require lots of input data, however. This study proposes a simple approach for describing O3. To that end, it evaluates fifteen empirical models based on the combination of four linear regressions: O3 against RH, temperature (T), wind speed (U), and I. Each model is driven by the analyzed climatological parameters over the period from 2012 to 2018 and further run using either daily or monthly averaged data. The best fitting model for monthly averaged data outperformed that for daily averaged data in both mathematical simplicity and accuracy; however, the differences between these models remained <0.4 percent. The results suggest that the O3 produced increases with I and decreases with RH.

Developing automated methods to estimate spectrally resolved direct normal irradiance for solar energy applications

We describe four schemes designed to estimate spectrally resolved direct normal irradiance (DNI) for multi-junction concentrator photovoltaic systems applications. The schemes have increasing levels of complexity in terms of aerosol and circumsolar irradiance (CSI) treatment, ranging from a climatological aerosol classification with no account of CSI, to an approach which includes explicit aerosol typing and type dependent CSI contribution. When tested against ground-based broadband and spectral measurements at five sites spanning a range of aerosol conditions, the most sophisticated scheme yields an average bias of +0.068%, well within photometer calibration uncertainties. The average spread of error is 2.5%. These statistics are markedly better than the climatological approach, which carries an average bias of −1.76% and a spread of 4%. They also improve on an intermediate approach which uses Angström exponents to estimate the spectral variation in aerosol optical depth across the solar energy relevant wavelength domain. This approach results in systematic under and over-estimations of DNI at short and long wavelengths respectively. Incorporating spectral CSI particularly benefits sites which experience a significant amount of coarse aerosol. All approaches we describe use freely available reanalyses and software tools, and can be easily applied to alternative aerosol measurements, including those from satellite.

Influence of Deficit Irrigation on Biometric Parameters of Capsicum Crop under Polyhouse Conditions

The influence of different deficit irrigations on capsicum crop biometric parameters and fruit yield were assessed in an experiment the variety ‘Indra’ was tested using completely randomized block design with three deficit irrigations (0.50, 0.75 and 1.0 ETC) and 5 replications in polyhouse and 1.0 ETC in open field conditions. The biometric parameters namely plant height, number of leaves, number of branches, number of days to flowering; number of days to harvesting, number of fruits per plant, individual fruit weight and fruit yield are measured. From the results, observed that, average of plant height (91.23 cm), number of leaves (91.3), number of branches (6.9), number of days to flowering (32.7), number of days to harvest (71), fruit number per plant (7), individual fruit weight (75.99 g) and yield (6466.66 t ha-1) parameters found higher in 1.0 ETC (T1), but in case of water productivity (12.4 kg ha-1 mm-1) in the treatment (T2) 0.75 ETC showed superiority. From the results, it is determined that by adopting the 0.75 ETC (T2) we can save the water up to 25%.&#x0D; Aims: The objective of this study is to evaluate the influence of deficit irrigation in biometric parameters of capsicum.&#x0D; Study Design: Completely randomized block design.&#x0D; Place and Duration of Study: Experiment conducted during January to May 2018 at Agriculture farm, College of Agricultural Engineering, Madakasira located in Rayalaseema region.&#x0D; Methodology: Physical and chemical properties of field were found by using standard methods. The experiment was arranged using CRD design with three levels of irrigation and five replications. Fertigation was done with 250:150:150 kg/ha recommended doses of N:P:K to capsicum crop. Based on climatological approach (evapotranspiration basis) the quantity of water applied. All the recommended cultural practices selection of cultivars, nursery raising, land preparation, laying drip lines, fumigation, fertilizer application, transplanting, pruning, training and plant protection measures are removing affected plant parts, flowers, fruits and for thrips and aphids management are dicofol (2 ml/L) and imidacloprid (0.5 ml/l) standardized for polyhouse were followed time to time to ensure a healthy crop stand. Crop water requirement was determined by using AquaCrop model. The parameters viz., plant height, number of leaves per plant and number of branches per plant were recorded at 30, 60, 90, 120 days after transplanting and at harvest. The collected data of different parameters during the course of research were analysed as per the completely randomized design (CRD) by applying the technique of analysis of variance procedure.&#x0D; Results: Among all the treatments, Irrigation with 100% Crop Evapotranspiration (1.0 ETc) (T1) registered the highest plant height, number of leaves, number of branches, number of days required to harvesting, number of days required to flowering, fruit number, average fruit weight and fruit yield, followed by 0.75 ETc (T2), 0.5 ETc (T3) and open field conditions. This might be due to good soil moisture distribution in drip irrigation compared to the open field. From the observed parameters it is exhibited that drip irrigation 0.75 ETC recorded as the higher water productivity (12.4 kg ha-1 mm-1) followed by drip irrigation scheduled at 1.0 ETC (11.49 kg ha-1 mm-1), 0.5 ETC (11.07 kg ha-1 mm-1) and open field (1.38 kg ha-1 mm-1) recorded very less.&#x0D; Conclusion: By adopting T2 (0.75 ETC) irrigation treatment we can save the water up to 25%, by using saved water additional quantity of vegetables can be produced.

Climatological conditions of the Black Sea‐effect snowfall events in Istanbul, Turkey

AbstractA climatological analysis and overlying synoptic conditions of Black Sea‐effect snowfall events were investigated for Istanbul, Turkey, during the 1971–2006 winter (DJF) periods. Using the synoptic climatological approach, the Lamb Weather Type (LWT) method was applied to NCEP/NCAR daily mean sea level pressure data. Basically, northwesterly (NW), northerly (N), and northeasterly (NE) circulation types (CTs), which blow from the Black Sea (BS), were thought to be important for sea‐effect snowfall events to occur. Wind speeds and flows at 850‐hPa, directional shear, and temperature difference between sea surface and 850‐hPa level (SST‐T850) thresholds were applied to these three CTs in order to find suitable snowfall cases originating from the Black‐Sea. The results showed that 4, 14, and 111 snowfall episodes occurred during NW, N, and NE circulation types over Istanbul with the 2.8, 4.1, and 3.5 cm daily mean snow cover depths (DMSCD), respectively. In particular, it was found that interaction between a surface high located over continental Europe and a low pressure located over the central Black Sea, and a relatively warm sea surface temperature (SST), and cold temperature anomaly at the low level of the atmosphere (SST‐T850 &gt; 17°C) are a favourable environment for the development of intense Black Sea‐effect snowstorms (DMSCD &gt; 10 cm) sourced by NE cases. A statistically significant positive relation between snow cover depths and SST‐Tmax (daily maximum temperature) under NE cases (r = 0.28, p &lt; .05) indicated that we observe intense daily snow accumulation when land‐sea temperature contrast increases (&gt;7°C) in the region.

Performance of potato variety Kufri Megha under different irrigation scheduling and date of planting at North Eastern Indian mid hills

Aim: To assess the performance of winter potato (Solanum tuberosum L.) variety Kufri Megha, under real time based irrigation scheduling, i.e., ratio of depth of irrigation water to cumulative pan evaporation in mid hills of Meghalaya during winter season of 2016-17. Methodology: A field trial with three different irrigation scheduling as main-treatments, viz., IW: CPE- 0.75 (I1), IW: CPE- 1.00 (I2) and IW: CPE- 1.25 (I3), four different dates of planting, viz., 1st November (D1), 11th November (D2), 21st November (D3) and 1st December (D4) was laid out and replicated thrice. Irrigation was provided with a micro sprinkler irrigation system and was laid out in split plot design. Results: The plants planted on 11th November and irrigation scheduled at IW: CPE-1.25 recorded higher values for plant height (cm), number of branches per plant, leaf area index, dry matter accumulation per plant, net assimilation ratio, crop growth rate, relative growth rate, tuber yield (t ha-1), haulm yield (t ha-1), harvest index (%), water use efficiency and benefit cost ratio over other treatments. Interpretation: It can be recommended that by following climatological approach of cumulative pan evaporation for irrigation scheduling in potato using micro sprinkler method of irrigation, the crop water requirement could be met during lean period to avoid moisture stress in plants coupled with planting at the right climatic conditions.

Climate drivers provide valuable insights into late season prediction of Australian wheat yield

Foresight of grain yields prior to harvest would be empowering for many stakeholders along the supply chain from farmers through to bulk handlers, banks and insurance companies. Estimating Australian grain production ahead of harvest is difficult for many reasons including the highly variable year to year rainfall. The rainfall in the final months prior to harvest, can be crucial to final harvest totals. Here we explore the importance of rainfall from September 1, which broadly corresponds to the close of the top-dressing fertilizer application window, for the remaining cropping season in determining final yield. This is assessed via sensitivity analysis of water-limited wheat potential yield totals from historical climate in the APSIM crop model. At locations where the rainfall influences wheat yield, we compare three methods to forecast wheat yields that differ based on the climate data input: 1) climatology approach, which uses 30 years of observed climate data, 2) analogue climatology, which uses information from climate drivers (El-Niño Southern Oscillation and Indian Ocean Dipole) to create analogue years; and 3) dynamical climate forecasts from a general circulation model (ACCESS-S). We find that potential yields strongly depend on in-season plant available water (PAW) where years with high PAW are unaffected by the late season rainfall. Predicting the potential yield from analogue climatology (climate drivers) had the greatest skill, with smallest Root Mean Squared Error of 0.45 t/ha. This approach ranked first for 42% of the study locations compared to the climatology and ACCESS-S forecasting methods. This knowledge can help inform decision makers about the need to incorporate seasonal climate forecasts and the most appropriate climate forecasting method.

Measuring the Risk of Supply and Demand Imbalance at the Monthly to Seasonal Scale in France

Transmission system operator (TSOs) need to project the system state at the seasonal scale to evaluate the risk of supply-demand imbalance for the season to come. Seasonal planning of the electricity system is currently mainly adressed using climatological approach to handle variability of consumption and production. Our study addresses the need for quantitative measures of the risk of supply-demand imbalance, exploring the use of sub-seasonal to seasonal forecasts which have hitherto not been exploited for this purpose. In this study, the risk of supply-demand imbalance is defined using exclusively the wind energy production and the consumption peak at 7 pm. To forecast the risks of supply-demand imbalance at monthly to seasonal time horizons, a statistical model is developed to reconstruct the joint probability of consumption and production. It is based on a the conditional probability of production and consumption with respect to indexes obtained from a linear regression of principal components of large-scale atmospheric predictors. By integrating the joint probability of consumption and production over different areas, we define two kind of risk measures: one quantifies the probablity of deviating from the climatological means, while the other, which is the value at risk at 95% confidence level (VaR95) of the difference between consumption and production, quantifies extreme risks of imbalance. In the first case, the reconstructed risk accurately reproduces the actual risk with over 0.80 correlation in time, and a hit rate around 70–80%. In the second case, we find a mean absolute error (MAE) between the reconstructed and real extreme risk of 2.5 to 2.8 GW, a coefficient of variation of the root mean square error (CV-RMSE) of 3.8% to 4.2% of the mean actual VaR95 and a correlation of 0.69 and 0.66 for winter and fall, respectively. By applying our model to ensemble forecasts performed with a numerical weather prediction model, we show that forecasted risk measures up to 1 month horizon can outperform the climatology often used as the reference forecast (time correlation with actual risk ranging between 0.54 and 0.82). At seasonal time horizon (3 months), our forecasts seem to tend to the climatology.

Horsemen of the Apocalypse? Turkish Alterity in Chronicles from the Latin East, 1099-1127

This article examines the image of the Turks in narratives written in the Latin East following the expedition widely known as the First Crusade (1096-99). The Turks did not feature in biblical or (late) antique ethnographic sources, to which Western authors turned when they wanted to know more about peoples in the Middle East. As “new people” they had to be assigned a place in the greater scheme of things. Narratives written shortly after the crusade and up to Walter the Chancellor (post-1119) tended to characterize the Turks as a barbarian people coming from the northern parts of the world. This image is likely connected to seventh- and eighth-century apocalyptic prophecies asserting that the End of Days would be preceded by an invasion of peoples from the North. These prophecies contributed to a more general idea that the peoples from the Eurasian steppes were cruel barbarians-an image that had its roots in antique ethnography in turn. Despite eschatological overtones in some chronicles, the Turks are nowhere directly associated with the Apocalypse. Fulcher of Chartres (ca. 1059-ca. 1127) recast the Turks as an Eastern people, still operating in the eschatological context of the First Crusade, but in a different way. His reorientation of the Turks must be seen in light of a renewed interest in climate theory-the ancient idea that geographic location shapes character. The article shows how each author’s individual background informed his choice to take a more ethnographic, individual, or climatological approach to Turkish alterity.

Synoptic climatological approach associated with three recent summer heatwaves in the Canadian Arctic

Abstract The observed unusually high temperatures in the Arctic during recent decades can be related to the Arctic sea ice declines in summer 2007, 2012 and 2016. Arctic dipole formation has been associated with all three heatwaves of 2007, 2012 and 2016 in the Canadian Arctic. Here, the differences in weather patterns are investigated and compared with normal climatological mean (1981–2010) structures. This study examines the high-resolution datasets from the North American Regional Reanalysis model. During the study periods, the north of Alaska has been affected by the low-pressure tongue. The maximum difference between Greenland high-pressure centre and Alaska low-pressure tongue for the summers of 2012, 2016 and 2007 are 8 hPa, 7 hPa and 6 hPa, respectively, corresponding and matching to the maximum summer surface Canadian Arctic temperature records. During anomalous summer heatwaves, low-level wind, temperatures, total clouds (%) and downward radiation flux at the surface are dramatically changed. This study shows the surface albedo has been reduced over most parts of the Canadian Arctic Ocean during the mentioned heatwaves (∼5–40%), with a higher change (specifically in the eastern Canadian Arctic region) during summer 2012 in comparison with summer 2016 and summer 2007, agreeing with the maximum surface temperature and sea ice decline records.

Identifying patterns of airborne pollen distribution using a synoptic climatology approach

Understanding the mechanisms of pollen release and dispersion in the atmosphere is of high importance, not only for getting an insight on the patterns of movement of these biological particles that are necessary for plants' reproduction, but also because exposure to airborne pollen is a major concern for respiratory allergies worldwide. In this work, a synoptic circulation-to-environment classification method was adopted to elucidate the relationship between distinct atmospheric patterns and pollen levels for the 11 most abundant but also allergenic taxa in Thessaloniki, Greece, for the 15-year period 1987–2001. It was found that the NW1 depressional weather type is associated with the “low winter pollen season” and high levels of pollen from Carpinus spp., Corylus spp., Cupressaceae, Platanus spp., Pinaceae, Quercus spp. and Urticaceae. In contrast, the SW1 cyclonic type is linked to the “high spring-summer pollen season” and high levels of pollen from Oleaceae and Urticaceae. On the other hand, anticyclonic weather is associated with the “summer-autumn pollen season” and high levels of Poaceae and Chenopodiaceae pollen in the atmosphere. Regional transport of Alnus pollen is linked to a strong high-pressure system centered over Italy, giving light NE winds over northern Greece. These findings shed light to the synoptic climatology of airborne pollen in Thessaloniki and could feed early-warning systems for alerting vulnerable groups of the allergic population.

Weather patterns and all-cause mortality in England, UK.

Cold- and heat-related mortality poses significant public health concerns worldwide. Although there are numerous studies dealing with the association between extreme ambient temperature and mortality, only a small number adopt a synoptic climatological approach in order to understand the nature of weather systems that precipitate increases in cold- or heat-related mortality. In this paper, the Lamb Weather Type synoptic classification is used to examine the relationship between daily mortality and weather patterns across nine regions of England. Analysis results revealed that the population in England is more susceptible to cold weather. Furthermore, it was found that the Easterly weather types are the most hazardous for public health all-year-long; however, during the cold period, the results are more evident and spatially homogenous. Nevertheless, it is noteworthy that the most dangerous weather conditions are not always associated with extreme (high or low) temperatures, a finding which points to the complexity of weather-related health effects and highlights the importance of a synoptic climatological approach in elucidating the relationship between temperature and mortality.