A topoclimatic classification to map spring frost risk for six deciduous tree fruit varieties

Abstract

A topoclimatic classification was developed to map the frequency of damaging spring radiation frosts to six deciduous fruit varieties at a scale of 1:25,000. The methodology utilizes night‐time temperatures from climatological stations operated by the Atmospheric Environment Service (aes) ofEnvironment Canada, as well as night‐time temperatures from a temporary network of standard climate stations and mobile temperature surveys. Maps of the deviation of minimum temperature from the local aes climate station, and of spring frost risk for each fruit variety are produced.     

Climate change,weather variability and corn yield at a higher latitude locale: Southwestern Quebec

Climate change has led to increased temperatures, and simulation models suggest that this should affect crop production in important agricultural regions of the world. Nations at higher latitudes, such as Canada, will be most affected. We studied the relationship between climate variability (temperature and precipitation) and corn yield trends over a period of 33 years for the Monteregie region of south-western Quebec using historical yield and climate records and statistical models. Growing season mean temperature has increased in Monterregie, mainly due to increased September temperature. Precipitation did not show any clear trend over the 33 year period. Yield increased about 118 kg ha⁻¹ year⁻¹ from 1973 to 2005 (under normal weather conditions) due mainly to changes in technology (genetics and management). Two climate variables were strongly associated with corn yield variability: July temperature and May precipitation. These two variables explain more than a half of yield variability associated with climate. In conclusion, July temperatures below normal and May precipitation above normal have negative effects on corn yield, and the growing seasons have warmed, largely due to increases in the September temperature.     

What spatial resolution do we need for a route-based road weather decision support system?

Since their implementation, road weather information systems have mostly relied on point measurements from outstations to initiate and verify daily forecasts. Initially, spatial extrapolation was achieved by thermal mapping, but this is gradually being replaced by route-based forecasting techniques. Both techniques are similar in the sense that they use a point measurement, often taken from an outstation, to provide a spatial forecast of road surface temperatures around the road network at varying resolutions. A substantial research effort has been undertaken to understand and model the complex environmental conditions and mechanisms responsible for the variation in road surface temperatures around the road network. In particular, the interaction of varying geographical parameters around the road network (e.g. altitude, land use, road construction, topography, etc.) has been used to develop local climatological models and route-based forecasting products. By considering the needs of winter maintenance engineers, this paper reviews the current state of the art and takes a critical look at the embedding of forecast products into decision support systems. This is achieved by considering a case study of how road surface temperature and condition vary across the width of a road profile, instead of just lengthways along a road. It is shown that temperature and condition both vary significantly across the profile, which immediately raises questions about the validity of current surveying and modelling practices. This has implications for both the resolution of route-based forecasting products as well as user confidence in automated decision support systems.     

An examination of internally generated variability in long climate simulations

General circulation model experiments designed to estimate the magnitude and structure of internally generated variability and to help understand the mechanisms underlying this variability are described. The experiments consist of three multi-century integrations of a rhomboidal 15, 9 level, version of the Center for Ocean-Land-Atmosphere Studies atmospheric general circulation model: a run with fixed sea surface temperatures and equinox solar radiation, a run with seasonally varying climatological sea surface temperatures and seasonally varying solar forcing, and a run with seasonally varying solar forcing in which the state of the ocean is predicted by a 3° by 3°, 16 vertical level, nearly global domain version of the Geophysical Fluid Dynamics Laboratory Modular Ocean Model. No flux correction is used in the coupled model integration. Selected surface fields of the three runs are compared to each other as well as to the observed climate. Statistical properties of variability on interannual time scales are compared between the runs. Evidence is presented that climate time scale variability in the simulations is produced by random weather time scale forcing due to the integrating effect of elements of the system with long memories. The importance of ocean variability for land climate variability is demonstrated and attributed to both the memory effect and coupled atmosphere-ocean instability.     

Variation in road surface temperature due to topography and wind

Summary The present study involves a discussion of nocturnal temperature variation due to topography and prevailing wind speed. It is part of the ongoing project Applied climatology for increased traffic safety and road maintenance, which aims at a development of a local climatological model applicable to winter road conditions. The temperature recordings which are used are from sensors in the Swedish Road Weather Information System in the county of Skaraborg.During clear and calm nights, local air temperature differences have been related to different topographical environments. The main factors resulting in large temperature differences are the effect of wind shelter, stagnation or production of cold air, and of cold air advection.Variation in air temperatures during clear and windy nights has also been studied. At wind speeds higher than 4–5 m/s, the temperature variation is low. With decreasing wind speed the variation in temperature increases, but only for sensor sites which have some wind shelter by topography or vegetation.The air temperature variation which develops during clear nights affects the road surface temperature. In this paper, the connection between road surface temperature differences and air temperature variation is discussed. A linear relationship between the two variables exists.With 5 Figures     

沪宁高速公路路面温度变化特征及统计模型

使用2006年7月-2007年6月沪宁高速公路沿线梅村和仙人山站附近的逐分钟路面温度、气温、湿度、风向、风速、降水气象资料, 分析了梅村和仙人山不同季节和不同天气状况下路面温度的日变化特征。结果表明:不同季节路面温度和气温具有明显的日变化;日出至日落时段,路面温度与气温有较大差异。在此基础上,应用逐步回归方法建立了梅村和仙人山最高和最低路面温度统计模型, 得出最低路面温度模型模拟结果与实况的变化趋势接近,误差绝对值不超过2℃, 具有很好的实际应用价值; 而最高路面温度模型在一定程度上模拟结果偏差较大,实际应用中需进行适当修订。     

Summer Extreme Temperatures over East China during 1984-2004 Simulated by LASG/IAP Regional Climate Model CREM

The authors examine extreme summer temperatures over East China during 1984-2004 using a regional climate model named CREM(the Climate version of Regional Eta-coordinate Model),which was developed by LASG/IAP.The results show that the main features of the extreme summer temperatures over East China are reproduced well by CREM,and the skill for the minimum temperature is higher than that for the maximum temperature,especially along the Yangtze-Huai River Valley(YHV).The simulated extreme temperatures are lower than those of observation,especially for the maximum temperature.The bias of extreme temperatures is consistent with the cold bias of the climatological mean summer surface air temperature.The skill of the model in simulating the interannual variability of extreme temperatures increases from north to south.The simulated interannual variation of the minimum temperature is more reasonable than the maximum temperature.The underestimation of net solar radiation at the surface leads to a cold bias of the climatological mean temperature.Furthermore,the model underestimates the light and moderate rain,while overestimates heavy rain.It causes the simulated minimum temperature more reasonable than the maximum temperature.     

People as sensors: Mass media and local temperature influence climate change discussion on Twitter

This study examined whether people living in the US connect their sensory experiences with local temperature to climate change and whether mass media influences the process. We used the volume of Twitter messages containing words “climate change” and “global warming” as the indicator of attention that public pays to the issue. Specifically, the goals were: (1) to investigate whether people immediately notice substantial local weather anomalies such as deviations from long-term mean temperatures and connect them to climate change by contributing to climate change discourse on Twitter and (2) to examine the role of mass media in this process. Over 2 million tweets were collected for a two-year period (2012–2013) and were assigned to 157 urban areas in the continental US. The rate of tweeting on climate change was regressed on the time variables, number of climate change publications in the mass media, and a number of temperature variables. The analysis was conducted at the two levels of aggregation – national and local. The high significance of the mass media and temperature variables in the majority of regression models suggests that both the weather and mass media coverage control public interest to the topic. However, no convincing evidence was found that the media acts as a mediator in the relationship between local weather and climate change discourse. Overall, the findings confirmed that the public recognize extreme temperature anomalies and connect these anomalies to climate change.     

Sensitivity of Ceres-Maize Yields to Statistical Structure of Daily Weather Series

To study impacts of climate variations on cropproduction, the growth models are used to simulateyields in present vs. changed climate conditions.Met&Roll is a four-variate (precipitation amount,solar radiation, minimum and maximum temperatures) stochasticweather generator used to supply synthetic dailyweather series for the crop growth model CERES-Maize.Three groups of experiments were conducted in thisstudy: (1) Validation of Met&Roll reveals some discrepanciesin the statistical structure of synthetic weatherseries, e.g., (i) the frequency of occurrence of longdry spells, extreme values of daily precipitationamount and variability of monthly means areunderestimated by the generator; (ii) correlations andlag-1 correlations among weather characteristicsexhibit a significant annual cycle not assumed by themodel. On the whole, the best fit of the observed andsynthetic weather series is experienced in summermonths. (2) The Wilcoxon test was employed to comparedistributions of maize yields simulated with use ofobserved vs. synthetic weather series. As nostatistically significant differences were detected,it is assumed that the generator imperfections inreproducing the statistical structure of weatherseries negligibly affect the model yields. (3) Thesensitivity of model yields to selectedcharacteristics of the daily weather series wasexamined. Emphasis was placed on the characteristicsnot addressed by typical GCM-based climate changescenarios: daily amplitude of temperature, persistenceof the weather series, shape of the distribution ofdaily precipitation amount, and frequency ofoccurrence of wet days. The results indicate that someof these characteristics may significantly affect cropyields and should therefore be considered in thedevelopment of climate change scenarios.     

Regional water temperature characteristics of lakes subjected to climate change

A deterministic, validated, one-dimensional, unsteady-state lake water quality model was linked to a daily weather data base to simulate daily water temperature profiles in lakes over a period of twenty-five (1955–79) years. Twenty seven classes of lakes which are characteristic for the north-central U.S. were investigated. Output from a global climate model (GISS) was used to modify the weather data base to account for a doubling of atmospheric CO₂. The simulations predict that, after climate change, epilimnetic temperatures will be higher but increase less than air temperature, hypolimnetic temperatures in seasonally stratified dimictic lakes will be largely unchanged or even lower than at present, evaporative water loss will be increased by as much as 300 mm for the season, onset of stratification will occur earlier and overturn later in the season, and overall lake stability will become greater in spring and summer.     

Objective method for classifying air masses: an application to the analysis of Buenos Aires’ (Argentina) urban heat island intensity

Summary ?During recent years, numerous studies have examined the Buenos Aires urban climate, but the relationship between large-scale weather conditions and the Buenos Aires urban heat island (UHI) intensity has not been studied. The goal of this paper is to apply an objective synoptic climatological method to identify homogeneous air masses or weather types affecting Buenos Aires during winter, and to relate the results to the UHI intensity. A K-means clustering method was used to define six different air masses considering the 03:00, 09:00, 15:00 and 21:00 LT surface observations of dry bulb temperature, dew point, cloud cover, atmospheric pressure and wind direction and velocity at Ezeiza, the most rural meteorological station of the Buenos Aires metropolitan area (Fig. 1). Results show that the mean UHI intensity is at its maximum (2.8 °C) a few hours before sunrise when conditions are dominated by cold air masses associated with cold-core anticyclones, weak winds and low cloud cover. Inverse heat islands are found during the afternoon for all air masses indicating that surface processes are not dominant at that time. The relatively infrequent and warmest air mass is the only one that presents a mean negative urban-rural temperature difference (−0.1 °C) during the afternoon with the smallest diurnal cycle of the UHI intensity probably due to the prevailing high humidity and cloudy sky conditions. The paper provides an insight into the Buenos Aires urban–rural temperature difference under a variety of winter weather types and results could be useful to improve local daily temperature forecasts for the metropolitan area of Buenos Aires on the basis of the routine forecasts of weather types. Received October 24, 2001; revised June 12, 2002; accepted October 10, 2002     

How do weather characteristics change in a warming climate?

The possible change in the characteristics of weather in the future should be considered as important as the mean climate change because the increasing risk of extremes is related to the variability on daily time scales. The weather characteristics can be represented by the climatological mean interdiurnal (day-to-day) variability (MIDV). This paper first assessed the phase five of the Coupled Model Intercomparison Project coupled climate models’ capability to represent MIDV for the surface maximum and minimum temperature, surface wind speed and precipitation under the present climate condition. Based on the assessment, we selected three best models for projecting future change. We found that the future changes in MIDV are characterized by: (a) a marked reduction in surface maximum and minimum temperature over high latitudes during the cold season; (b) a stronger reduction in the surface minimum temperature than in the maximum temperature; (c) a reduction in surface wind speed over large parts of lands in Northern Hemisphere (NH) during NH spring; (d) a noticeable increase in precipitation in NH mid-high latitudes in NH spring and winter, and in particular over East Asia throughout most of the year.     

冬季影响北疆高速公路行车安全的气象要素特征分析

利用1961—2007年长达47a高速、高等级公路沿线气象站的资料,重点研究北疆高速、高等级公路沿线冬季影响车辆安全行驶的气象要素的气候特征,分析该路段降雪、积雪、结冰、冻雨等气象要素的时间和空间分布,并依据气候分布特点从气候的角度将北疆高速、高等级公路沿线路段按降雪、积雪、结冰、冻雨等对行车安全影响程度划分为极易打滑路段、较易打滑路段、易打滑路段和不易打滑路段,为公路管理部门提供科学的、合理的防御和减少冬季交通事故的理论依据。     

A Model to Interpolate Monthly Mean Climatological Data at Bavarian Forest Climate Stations

Summary  Six methods were used to interpolate the monthly mean climatological data from German climate stations to three Bavarian forest climate stations. The observed forest climatological data at the Bavarian forest climate stations were used as the reference data to which the interpolated data were compared. The results show that, for monthly mean daily maximum temperature at valley and plain forest climate stations, each of the six interpolation methods can give accurate estimates. For monthly mean daily maximum temperature, minimum temperature, air temperature and water vapor pressure at mountain forest climate stations, topographically aided interpolation can give the most accurate estimates. Barnes interpolation combined with empirical transfer functions can give accurate estimates forall climate variables at the plain and valley forest climate stations, and it can also give accurate estimates for monthly mean wind speed and monthly precipitation at the mountain forest climate station. The empirical transfer functions are very important for estimating the forest climatological data. These transfer functions will be used for reconstruction of long-term forest climatological data in Bavaria. Received September 9, 1998 Revised May 21, 1999     

Vulnerability and adaptation assessments of agriculturalcrops under climate change in the Southeastern USA

Summary  It is expected that a change in climatic conditions due to global warming will directly impact agricultural production. Most climate change studies have been applied at very large scales, in which regions were represented by only one or two weather stations, which were mainly located at airports of major cities. The objective of this study was to determine the potential impact of climate change at a local level, taking into account weather data recorded at remote locations. Daily weather data for a 30-year period were obtained for more than 500 sites, representing the southeastern region of the USA. Climate change scenarios, using transient and equilibrium global circulation models (GCM), were defined, created and applied to the daily historical weather data. The modified temperature, precipitation and solar radiation databases corresponding to each of the climate change scenarios were used to run the CERES v.3.5 simulation model for maize and winter wheat and the CROPGRO v.3.5 model for soybean and peanut. The GCM scenarios projected a shorter duration of the crop-growing season. Under the current level of CO₂, the GCM scenarios projected a decrease of crop yields in the 2020s. When the direct effects of CO₂ were assumed in the study, the scenarios resulted in an increase in soybean and peanut yield. Under equilibrium , the GCM climate change scenarios projected a decrease of maize and winter wheat yield. The indirect effects of climate change also tended to decrease soybean and peanut yield. However, when the direct effects of CO₂ were included, most of the scenarios resulted in an increase in legume yields. Possible changes in sowing data, hybrids and cultivar selection, and fertilization were considered as adaptation options to mitigate the potential negative impact of potential warming. Received July 20, 1999/Revised April 18, 2000     

Relationships between Synoptic Climatology and Atmospheric Pollution at 4 US Cities

Summary  An evaluation of the impacts of weather on pollution, specifically, ozone and total suspended particulates concentration for Summer, is examined in four cities in the U.S.: Birmingham, Cleveland, Philadelphia, and Seattle. These cities were selected because of their different climate regimes and their generally good pollutant and meteorological datasets. This paper uses a synoptic climatological approach, which combines a number of atmospheric factors, to better identify the relationships between atmospheric pollution and climatological conditions. Synoptic events represent holistic units of atmospheric conditions which commonly occur at a given locale, and possess specific weather and pollution characteristics. A number of weather variables, including temperature, are used in the development of a synoptic index, which can be used to identify synoptic events associated with specific pollution episodes. Results from the analysis illustrate that there is a substantial difference in pollution loads under different synoptic patterns, and that the cities do have substantially different relationships. Information from this study could be used to assist in the analysis of the differential impacts of weather and pollution upon human morbidity. Specific information as to the linkages between the synoptic weather patterns, pollution concentrations, and human health could be used in the development of weather/health watch-warning systems to alert the public that a synoptic episode is imminent. Received September 18, 1998     

Very high resolution rainfall patterns measured by TRMM precipitation radar: seasonal and diurnal cycles

The TRMM Precipitation Radar is used to construct a high resolution (0.05°?×?0.05°) climatology of rainfall over the latitude band extending to about 36° North and South. This study describes climatological patterns of rainfall frequency and intensity at high spatial resolution, with special focus on the seasonal and diurnal cycles in the frequency of rainfall events. We use this Tropics-wide dataset to highlight small-scale precipitation features that are too fine to be captured by the most widely used satellite-based rainfall datasets. The results shed light on the roles of changes in the wind direction, the land-sea thermal contrast, small-scale variations in sea surface temperature, and orography in shaping the seasonal and diurnal cycles of rainfall. In some regions of the tropics, diurnally locked local circulations are largely responsible for sharp gradients in the spatial distribution of seasonal mean precipitation. In other regions, we show that climatological rainfall frequency changes very sharply at coastlines, even though rainfall in these regions is expected to be controlled by relatively large scale weather systems.     

冬季高速公路路桥温度变化规律及能量平衡分析

利用2009年10月-2010年3月湖北省武英高速凤凰关水库自动气象站逐时路、桥面温度和常规气象资料,分析了冬季典型天空状况（晴空、阴天）和天气过程（雾、降雨、降雪）中气温、路面温度和桥面温度的变化规律。结果表明,夜间桥面温度与气温接近,比路面温度低2℃,桥面0℃以下的低温维持时间为路面维持时间的2倍左右。利用下垫面能量平衡模型,分别计算冬季夜间晴空和阴天时路、桥面辐射能量收支变化情况,分析了夜间路面和桥面温度变化差异的原因,并对桥面比路面更易结冰的现象给出了理论解释。     

冬季扬溧高速路桥面的低温差异性特征研究

利用江苏扬溧高速公路润扬大桥段2012—2015年交通气象监测站逐分钟监测资料和同期邻近气象观测站逐时气象观测资料,开展了冬季路桥面温度的差异性特征及成因分析研究,结果表明:(1)冬季相同天气条件下,不同类型下垫面的夜间温度分布表现为“桥面温度＜路面温度＜地面温度”;同一路段上,桥面与相邻路面的温度差值最大可达-5.7 ℃,出现最大差值的时间比达到最低温度的时间早近1 h。(2)冬季不同天气条件下夜间路桥面温度变化规律相似,晴天变幅最大、阴天和雨天居中、雪天最小;桥面温度一般比路面温度提前2 h降至0 ℃以下,桥面维持低温时间比路面长3 h,低温维持阶段桥面温度低于路面温度约2 ℃。(3)冬季夜间雪天桥面平均降温速率最小,较其他三类天气条件下小一个量级;同一天气条件下桥面的平均降温速率明显高于路面。(4)冬季夜间晴天条件下,桥面热通量最大(-55.6 W/m2),阴天和雨天次之,雪天最小(约为晴天的1/2);四种天气条件下夜间桥面与路面的热通量差值都近似为-10 W/m2,桥面热通量的变幅更大;与桥面相比,夜间路面还受到路基的热补偿作用,这种作用强于空气对路面的潜热输送和流体运动热交换,所以桥面温度低于路面温度。这也是冬季夜间桥面更容易、更早出现结冰现象的根本原因。      

Future heat vulnerability in California, Part I: projecting future weather types and heat events

Excessive heat significantly impacts the health of Californians during irregular but intense heat events. Through the 21st century, a significant increase in impact is likely, as the state experiences a changing climate as well as an aging population. To assess this impact, future heat-related mortality estimates were derived for nine metropolitan areas in the state for the remainder of the century. Here in Part I, changes in oppressive weather days and consecutive-day events are projected for future years by a synoptic climatological method. First, historical surface weather types are related to circulation patterns at 500mb and 700mb, and temperature patterns at 850mb. GCM output is then utilized to classify future circulation patterns via discriminant function analysis, and multinomial logistic regression is used to derive future surface weather type at each of six stations in California. Five different climate model-scenarios are examined. Results show a significant increase in heat events over the 21st century, with oppressive weather types potentially more than doubling in frequency, and with heat events of 2?weeks or longer becoming up to ten times more common at coastal locations.