NDVI variation and its relation to climate in Canadian ecozones

Parks Canada began the Northern Satellite Monitoring Program in 1997, with the objective of tracking large‐scale vegetation variation in Canadian ecosystems and helping land managers to develop appropriate management practices in response to climate change. Under this program, a sequence of 10‐day composite Advanced Very High Resolution Radiometer (AVHRR)‐derived Normalized Difference Vegetation Index (NDVI) data from 1985 to 2007 was examined to study seasonal and inter‐annual relationships between vegetation and climate data over Canadian ecosystems using statistical and wavelet analysis. Statistical analysis showed that temperature was the principal driver for seasonal variability in greenness, explaining more than 70 percent of seasonal variation in vegetation for most Canadian ecozones. In comparison with temperature, the relationships between NDVI and precipitation were weaker but still significant. Maximum annual NDVI showed increasing trends in Canadian ecozones during the study period, although increasing rates were spatially heterogeneous. Wavelet analysis confirmed that inter‐annual variation in NDVI was different at two ecozones in Canada. NDVI variation in the Northern Arctic was significant at scales of 3–4 years from 1997 to 2001, which was associated with temperature and precipitation variation. Comparatively, NDVI variation in the Boreal Shield was significant at scales of 5–8 years from 1991 to 1999, but did not correspond with climate variation.     

Has it become warmer in Alberta? Mapping temperature changes for the period 1950–2010 across Alberta,Canada

When a Canada‐wide daily climate time series, covering the period 1950–2010, became available, an opportunity arose to analyze the time series for trends of a variety of temperature indices. The 6,833 climate grid cells covering Alberta, each with an area of 10 km by 10 km, allowed the detailed mapping of 30 temperature indices across the province. From each time series, an annual series was computed, which then enabled trend analyses using the non‐parametric Mann‐Kendall and Sen Slope tests. New maps could be created at an unprecedented spatial resolution, and an associated website was developed to access all trends and changes between 1950 and 2010 for all grid cells at albertaclimaterecords.com . The confidence levels of some temperature trends exceed 99%, while others are below 80%. In Alberta's south, annual average temperatures have increased by 1°C to 2°C since the 1950s, but in Alberta's north the increase is 2°C to 4°C. The growing season has lengthened by between one and five weeks since the 1950s, while the number of frost days has declined. The most significant trends observed were increases in mean annual and winter temperatures, and declines in the number of days below ?20°C and heating degree days.     

ANALYSIS and PREDICTION OF ABNORMALLY COLD SPELLS IN SOUTHERN SASKATCHEWAN

The risk of departures of daily minimum temperatures at some prescribed level below the daily average can be estimated by the use of a combined deterministic/stochastic model. From a regional perspective the coefficients and parameters of the model are point observations containing information pertaining to both regional trends and local environmental conditions. Trend surface analyses, using latitude, longitude, and elevation, provide a means of identifying the relative importance of regional and local effects on cold spell risks. The derived surfaces indicate that the deterministic components filter out the regional characteristics and that the parameters of the stochastic model are more sensitive to local changes in elevation. The efficacy of the technique is illustrated by the prediction of cold spell risks at six test sites. Le risque d'écarts des températures journalières mini-males par rapport à un niveau prédéterminé se situant en-dessous de la moyenne journalière peut se mesurer au moyen d'un modèle à la fois déterministe et stochas-tique. Au plan régional, les coefficients et les paramètres du modèle sont des observ ations ponctuelles qui renfer-ment des informations se rapportant à la fois à des tendances régionales et à des conditions locales de I'envi-ronnement. Les analyses de tendance en surface, au moyen de latitude, longitude et altitude, constitutent une façon d'identifier l'importance relative des effets ré-gionaux et locaux sur les risques de vagues de froid. Les surfaces qui en dérivent révèlent que les composantes déterministes font ressortir les particolarités régionales et que les paramètres du modèle stochastique sont davan-tage sensibles aux changements locaux d'élévation. Des prévisions du risque de vague de froid, testées en six endroits, montrent I'efficacité de la technique.     

Longitudinal differences and inter-annual variations of zonal wind in the tropical stratosphere and troposphere

A quantitative assessment has been made of the longitude-dependent differences and the interannual variations of the zonal wind components in the equatorial stratosphere and troposphere, from the analysis of rocket and balloon data for 1979 and 1980 for three stations near ±8.5° latitude (Ascension Island at 14.4°W, Thumba at 76.9°E and Kwajalein at 67.7°E) and two stations near 21.5° latitude (Barking Sands at 159.6°W and Balasore at 86.9°E). The longitude-dependent differences are found to be about 10–20 m s⁻¹ (amounting to 50–200% in some cases) for the semi-annual oscillation (SAO) and the annual oscillation (AO) amplitudes, depending upon the altitude and latitude. Inter-annual variations of about 10 m s⁻¹ also exist in both oscillations. The phase of the SAO exhibits an almost 180° shift at Kwajalein compared to that at the other two stations near 8.5°, while the phase of the AO is independent of longitude, in the stratosphere.The amplitude and phase of the quasi-biennial oscillation (QBO) are found to be almost independent of longitude in the 18–38 km range, but above 40 km height the QBO amplitude and phase have different values in different longitude sectors for the three stations near ±8.5° latitude. The mean zonal wind shows no change from 1979 to 1980, but in the troposphere at 8.5° latitude strong easterlies prevail in the Indian zone, in contrast to the westerlies at the Atlantic and Pacific stations.     

Application of Artificial Neural Networks in Climatology: A Case Study of Sunspot Prediction and Solar Climate Trends

Global temperature trends on time scales of years to centuries have recently been shown to be related to volcanic aerosols, carbon dioxide levels, and solar activity. The most visible and well-studied indicators of solar variability are dark areas or “sunspots” on the surface of the Sun, with sunspot numbers directly related to the level of solar activity. Prediction of sunspot numbers in advance of the actual event has proven problematic with most methods failing due to nonlinearities in solar activity. An approach using the generation of a feedforward neural network may resolve some of the difficulties inherent in currently utilized statistical and precursor approaches since feedforward networks offer a useful and practical method of approximating nonlinear relations and their derivatives without knowing the actual underlying nonlinear function. In this paper, we show some preliminary findings in using feedforward neural networks for the prediction of peak sunspot cycle amplitude and discuss the climatic implications of the findings.     

Long-term tropospheric and lower stratospheric ozone variations from ozonesonde observations

An analysis is presented of the long-term mean pressure latitude seasonal distribution of tropospheric and lower stratospheric ozone for the four seasons covering, in part, over 20 years of ozonesonde data. The observed patterns show minimum ozone mixing ratios in the equatorial and tropical troposphere except in regions where net photochemical production is dominant. In the middle and upper troposphere, and low stratosphere to 50 mb, ozone increases from the tropics to subpolar latitudes of both hemispheres. In mid stratosphere, the ozone mixing ratio is a maximum over the tropics. The observed vertical ozone gradient is small in the troposphere but increases rapidly above the tropopause. The seasonal variation at a typical mid latitude station (Hohenpeissenberg) shows a summer maximum in the low to middle troposphere, shifting to a winter-spring maximum in the upper troposphere and lower stratosphere and spring -summer maximum at 10 mb. The amplitude of the annual variation increases from a minimum in the tropics to a maximum in polar regions. Also, the amplitude increases with height at all latitudes up to about 30 mb where the phase of the annual variation changes abruptly. The phase of the annual variation is during spring in the boundary layer, summer in mid troposphere, and spring in the upper troposphere and lower stratosphere. The annual long-term ozone trends are significantly positive at about + 1.2% yr in mid troposphere (500 mb) and significantly negative at about − 0.6% yr¹ in the lower stratosphere(50mb)     

Extreme weather events in northeastern New Brunswick (Canada) for the period 1950–2012: Comparison of newspaper archive and weather station data

In the context of global warming, changes in extreme weather and climate events are expected, particularly those associated with changes in temperature and precipitation regimes and those that will affect coastal areas. The main objectives of this study were to establish the number of extreme events that have occurred in northeastern New Brunswick, Canada in recent history, and to determine whether their occurrence has increased. By using archived regional newspapers and data from three meteorological stations in a national network, the frequency of extreme events in the study area was established for the time period 1950–2012. Of the 282 extreme weather events recorded in the newspaper archives, 70% were also identified in the meteorological time series analysis. The discrepancy might be explained by the synergistic effect of co‐occurring non‐extreme events, and increased vulnerability over time, resulting from more people and infrastructure being located in coastal hazard zones. The Mann Kendall and Pettitt statistical tests were used to identify trends and the presence of break points in the weather data time series. Results indicate a statistically significant increase in average temperatures and in the number of extreme events, such as extreme hot days, as well as an increase in total annual and extreme precipitation. A significant decrease in the number of frost‐free days and extreme cold days was also found, in addition to a decline in the number of dry days.     

The application of quicklook NOAA AVHRR satellite imagery in Northern Scandinavia for synoptic weather analyses

The suitability of imagery from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA series of satellites for the synoptic classification of circulation trends in the European Arctic is assessed with reference to data from three climate stations. Simplified synoptic cyclonic classifications are derived from the satellite imagery and tested against climate data. Five classes of frontal system are derived from the tracking of systems over the UK‐Scandinavia‐Baltic region using 1460 satellite images over two years. An index based on the qualitative interpretation of satellite imagery was related to the reference data. The tracking of the systems in the imagery also facilitates a comparison of travel times across the region and the frequency of occurrence. Frontal systems that remain largely stationary over the Baltic were found to correlate best with precipitation at the reference sites. The paper thus investigates the use of AVHRR imagery for the categorisation of weather patterns towards deriving quantitative relationships between circulation classes and weather elements (such as temperature and precipitation) where, for example, climate data are sparse or where skills required for the interpretation of Height Potential Fields are lacking.     

Monitoring the Near‐surface Urban Heat Island in Beijing,China by Satellite Remote Sensing

Urban heat island (UHI) effect is an important impact factor of the regional climate and ecological environment. How to observe and analyse the spatial distribution of UHI has become an important issue of urban environmental research. In this paper, the near‐surface air temperature of Beijing was derived based on the Landsat/TM satellite imagery on 26 July 2011 to study the near‐surface UHI. A statistical model at 195‐m window size was established to estimate the air temperature, using land surface temperature, normalized difference vegetation index, altitude, and surface albedo as independent variables. The mean absolute error (MAE) of the model was 0.87°C, and the R² was 0.66, indicating that the method can be used to effectively estimate the air temperature. The air temperature distribution obtained from remote sensing revealed that the UHI effect in Beijing was very significant and showed a concentrated pattern. The heat island intensity was stronger in the southern part than in the northern part of the city. In addition, the relationship between the air temperature and impervious surfaces was analysed. The air temperature increased with increasing impervious surface coverage, and the rate of change depended on the impervious surface coverage. When the impervious surface coverage was below 40 per cent, the temperature increased rapidly with increasing impervious surface coverage, and when the impervious surface coverage was above 40 per cent, the temperature increased slowly. This study provides a new approach to monitor near‐surface UHI and reveals its relationship with impervious surface, providing a scientific reference for urban planning and environmental assessment.     

中国南方十一座旅游名城避寒疗养气候旅游资源评估

文章对人体健康与气候环境作了分析,阐明寒冷气候与呼吸道系统、心血管系统、消化道系统疾病发病率、死亡率的对应关系。运用生理气候舒适度指数,对中国南方11座旅游名城的避寒气候作了横向分析比较,得出中国最佳避寒疗养地的区域格局,为开展中国冬季避寒疗养旅游提供了发展基础。     

Reducing Errors in Rainfall Estimates through Rain Gauge Location

Facility location models are examined as a framework for generating rain gauge networks designed to reduce errors in mean areal precipitation (MAP) estimation. Errors in estimating MAP may be divided into two types: (i) capture error, not observing a storm which occurs in a gauged area, and (ii) extrapolation error, using a rain gauge measurement to represent a heterogeneous area. In this paper, five rain gauge location models are developed to minimize these errors. The models include adaptations of the maximal covering location problem, the p-median model, and three models derived from multicriteria cluster analysis. The models are tested using precipitation data from an experimental watershed maintained by the U.S. Department of Agriculture in Arizona. Analysis of the results reveals, for the particular watershed, that (1) in sparse networks, location of rain gauges can play a larger role than number of rain gauges in reducing errors in MAP estimates; (2) models based on mean hydrologic data provide nearly as good networks as models based on spatially correlated data; and (3) models yielding the best networks for estimating precipitation for flood predictions are different from the models providing the best precipitation estimates for low flow forecasts.     

Trends and triggers: Climate,climate change and civil conflict in Sub-Saharan Africa

The conventional discourse relating climate change to conflict focuses on long term trends in temperature and precipitation that define ecosystems and their subsequent impact on access to renewable resources. Because these changes occur over long time periods they may not capture the proximate factors that trigger conflict. We estimate the impact of both long term trends in climate and short term climatic triggers on civil conflict onset in Sub-Saharan Africa. We find that both operationalizations have a significant impact. Climates more suitable for Eurasian agriculture are associated with a decreased likelihood of conflict, while freshwater resources per capita are positively associated with the likelihood of conflict. Moreover, positive changes in rainfall are associated with a decreased likelihood of conflict in the following year. We also assess the outlook for the future by analyzing simulated changes in precipitation means and variability over the period 2000–2099. We find few statistically significant, positive trends in our measure of interannual variability, suggesting that it is unlikely to be affected dramatically by expected changes in climate.     

The Potential of Tree Rings in Eucalyptus pauciflora for Climatological and Hydrological Reconstruction

We investigate the causes of variability in a tree‐ring chronology comprising data from Eucalyptus pauciflora Sieb. Ex. Spreng. at the alpine treeline on the Kosciuszko Plateau in New South Wales, Australia. Following verification of crossdating in a subset of the available data, we found that ring width correlates significantly with net radiation, precipitation and mean minimum and maximum air temperature during the preceding winter and spring of the growing season. Our results for spring are consistent with the impact of climate on tree growth in alpine woodlands reported in previous studies. Analyses of snow‐depth data revealed negative correlations with ring width throughout winter and spring. Our results indicate that low temperature and high precipitation during winter negatively affect the growth of E. pauciflora by prolonging spring snow cover. Ring width also correlates significantly with an index of soil dryness and flow in rivers with their headwaters in the Kosciuszko plateau. Given the apparent sensitivity of our chronology to climate and snow conditions, our results suggest that tree‐ring chronologies comprising data from E. pauciflora at the alpine treeline have potential for climatological and hydrological reconstruction in southeast Australia.     

Ground-based microwave radiometry to determine stratospheric and mesospheric ozone profiles

From April 1984 to April 1985 a microwave radiometer was operated at Bern (Switzerland, latitude 47°N) measuring the thermal emission of the rotational ozone transition at 142.2 GHz to determine stratospheric and mesospheric ozone abundances in the range ~25–~75 km altitude. From a total of 334 retrieved day-time profiles, monthly mean ozone partial pressures for Umkehr layers 6–10 were calculated. On this basis ozone variations compare favorably with Umkehr data from the nearby Arosa (Switzerland, 150 km east of Bern) station and with a monthly zonal mean model compiled from satellite data by Keating and Young. From the microwave data an annual mean ozone distribution was determined. The method retrieves somewhat larger ozone volume mixing ratios between 25 and 30 km altitude. For the rest of the measurement range of the sensor there is good agreement with 20 year annual mean ozone values from Arosa, with the Krueger and Minzner profile and with the respective annual mean data given by Keating and Young. The microwave ozone sensor can easily be adapted for operational use, where it can supplement and expand the measurement range of the traditional Umkehr network.     

A Hybrid Framework for Space–Time Modeling of Environmental Data. 环境数据时空建模的混合框架

The space–time autoregressive integrated moving average (STARIMA) model family provides useful tools for modeling space–time processes that exhibit stationarity (or near stationarity) in space and time. However, a more general method for routine use and efficient computation is needed to model the nonlinearities and nonstationarities of environmental space–time series. This article presents a hybrid framework combining machine learning and statistical methods to address this issue. It uses an artificial neural network (ANN) to extract global deterministic (nonlinear) space–time trends and a STARIMA model to extract local stochastic space–time variations in data. A four‐stage procedure is proposed for analyzing and modeling space–time series. The proposed framework and procedures are applied to forecast annual average temperature at 137 national meteorological stations in China. The results demonstrate that the hybrid framework achieves better forecasting accuracy than the STARIMA model alone. This finding suggests that the combination of machine learning and statistical methods provides a very powerful tool for analyzing and modeling space–time series of environmental data that have strong spatial nonlinear and nonstationary components.     

Local sustainable development: a knowledge base for adaptation planning

Towards the end of the century, Serbia will face a dramatic increase in annual temperature between 2°C and 6°C and decrease in annual accumulated precipitation up to 12%. Recent 2014 floods in Serbia, with more than 30 victims, and more than 30,000 displaced people, with overall damage close to €1.5 billion, reflected those trends and the likely risks that region will face due the changing climate. Those risks may influence the development process at the local level. This paper assesses the existing priority measures in local sustainable development strategies and re-interprets their characteristics using a methodological framework for the definition of adaptation measures. It offers a new understanding of the ongoing local sustainable development approach in the potentially most vulnerable municipalities in Serbia. The study focused on following properties of developmental measures: cost-effectiveness, structural characteristics, target realm, spatial determination, time frame, climate responsiveness, and sector and budget allocation of development measures at the local level. The results of the analysis suggest that the initiation of adaptation planning should consider the improvement of the methodological framework – the introduction of inter-sectoral and cross-sectoral planning practice, cost–benefit analysis, the involvement of individual actors in planning and dynamic planning approaches.     

Mesopause temperatures and integrated band brightnesses calculated from airglow OH emissions recorded at Maynooth (53.2°N, 6.4°W) during 1993

Spectra of the hydroxyl emissions in the wavelength range 1.0–1.6 μm, which originate at mesopause altitudes, have been obtained, using a Fourier transform spectrometer at Maynooth (53.2°N, 6.4°W), on all suitable nights during the period January–December 1993. Rotational temperatures and integrated band brightnesses have been calculated from the spectra of the OH(3, 1) and (4, 2) vibration-rotation bands. The mean annual temperatures calculated over all measurements were T(3, 1)=200±19 K and T(4, 2)=206±19 K, where the uncertainty represents the standard deviation on the measurements. Harmonic analysis of the nightly averaged temperature values revealed an amplitude of 27 ± 1 K and a phase of 95 ± 2 days in the annual variation of the (3, l) band at our latitude. The semiannual component was found to have an amplitude of 7 ± 1 K and a phase of −51 ± 9 days for this band. Results for the (4, 2) band were identical in both amplitude and phase for the annual component, while the semiannual component gave an amplitude of 8 ± 1 K and a phase of − 43 ± 7 days. These results are compared with data recorded by the SME satellite, and with the predictions of the MSISE-90 model for a station at 53° latitude. Temperatures predicted by the MSISE-90 model for Maynooth are consistently below the values obtained in this study by 15–20 K. Excellent agreement is observed between the absolute value of temperature, in the case of the SME satellite, and in the amplitude and phase of the annual variation predicted by MSISE-90. The phase of the semiannual component observed in our data deviates somewhat from the −99 ± 1 days predicted by MSISE-90.The annual mean brightness of the OH (3, 1) band was found to be 75 ± 18 kR, while that of the (4, 2) band was 106±26 kR. Diurnal variations generally showed a steady decrease from dusk to dawn, apart from a brief period in June and July. Monthly average values of band brightness have been calculated for each band and are compared with the predictions of a recent photochemical model (Le Texier et al., 1987). The model shows some elements of agreement with our observations, particularly a pair of maxima near the equinoxes, but it does not predict the broad winter maximum observed in both bands at this latitude.     

VARIABILITY OF THE CHARACTERISTICS OF WEATHER AND CLIMATE OF THE CENTRAL ECONOMIC REGION

Basic climatic elements and factors of climate formation in the Central Economic Region are assessed with a view toward improving methods of short-term forecasting. More specifically, analysis of the spatial variation of radiation, evaporation, and turbulent heat transfer, patterns of the most economically significant climatic elements; and trends in temperature and precipitation relative to long-term means sets the stage for a discussion of problems in forecasting the length of the heating season and in predicting precipitation anomalies one year into the future (translated by Andrew R. Bond).     

Agent-Based Simulation of Holocene Monsoon Precipitation Patterns and Hunter-Gatherer Population Dynamics in Semi-arid Environments

Based on archaeological evidence from Kutch-Saurashtra (N Gujarat, NW India), we use agent-based modelling (ABM) to explore the persistence of hunter-gatherer (HG) groups in semi-arid environments in the mid and late Holocene. Agents interact within a realistic semi-arid environment dominated by the monsoon. Precipitation trends are modelled from instrumental records (1871–2008) calibrated with existing models for the Asian monsoon in the Holocene (c. 12 ka–present). Experiments aim at exploring dependencies between population dynamics and climate-driven environmental change (in terms of resource availability) for precipitation patterns at the local, regional and continental scales. Resources are distributed across a simplified ground model. Average yearly precipitation (AYP, i.e. mean) and variance in yearly precipitation (VYP, i.e. standard deviation) are the main parameters affecting resource availability in the simulations. We assess the effects of environmental change on HG populations at different timescales: (1) patterns of seasonal (inter-annual) resource availability, (2) effects of changes in mean precipitation trends over the long (Pleistocene–Holocene) and the mid (Holocene, millennial) periods, and (3) effects of intra-annual precipitation variability, i.e. changes in standard deviation from mean precipitation trends over the short period (annual to decadal). Simulations show that (1) strong seasonality is coherent with the persistence of HG populations in India, independently of the geographical scale of the precipitation models, (2) changes in AYP over the mid period (Holocene) are not sufficient to explain the disappearance of HG populations in Kutch-Saurashtra (K-S) 4 ka and (3) precipitation variability (VYP) over the short period (annual to decadal) is the main parameter affecting population performance and overall ecosystem dynamics. To date, sufficiently refined palaeoclimatic records do not exist for the study area, but higher VYP values 4 ka do not exclude the possibility that other factors may have driven the disappearance of HG populations in Kutch-Saurashtra.     

Beyond Alternative: Exploring the Potential for Autonomous Food Spaces

Abstract: Much attention has been given in recent years to the rise of alternative food networks However, the very concept of “alternative” has come under increasing scrutiny, as theorists grapple with what is meant by alternative and whether the concept adequately captures the key components of such a diverse range of networks and communities. Drawing on poststructuralist political economy, I propose the concept of autonomous food spaces as one possible lens for approaches food‐provisioning activities that situate food within the broader context of non‐capitalist communities seeking to build relationships of mutual aid and non‐market exchanges. I use the examples of a radical collective kitchen, Food Not Bombs, and a community‐supported agriculture operation, Vegetables Unplugged, to explore the potential for autonomous food spaces as part of a broader “politics of possibilities” beyond capitalism.