Local regression models for spatial interpolation of urban heat island—an example from Wroc?aw, SW Poland

Geographically weighted regression algorithm (GWR) has been applied to derive the spatial structure of urban heat island (UHI) in the city of Wroc?aw, SW Poland. Seven UHI cases, measured during various meteorological conditions and characteristic of different seasons, were selected for analysis. GWR results were compared with global regression models (MLR), using various statistical procedures including corrected Akaike Information Criterion, determination coefficient, analysis of variance, and Moran’s I index. It was found that GWR is better suited for spatial modeling of UHI than MLR models, as it takes into account non-stationarity of the spatial process. However, Monte Carlo and F3 tests for spatial stationarity of the independent variables suggest that for several spatial predictors a mixed GWR–MLR approach is recommended. Both local and global models were extended by the interpolation of regression residuals and used for spatial interpolation of the UHI structure. The interpolation results were evaluated with the cross-validation approach. It was found that the incorporation of the spatially interpolated residuals leads to significant improvement of the interpolation results for both GWR and MLR approaches. Because GWR is better justified in terms of statistical specification, the combined GWR?+?interpolated regression residuals (GWR residual kriging; GWRK) approach is recommended for spatial modeling of UHI, instead of widely applied MLR models.     

Statistical modelling of the main features of the <Emphasis Type="Italic">Artemisia</Emphasis> pollen season in Wrocław,Poland, during the 2002–2011 time period

The aim of this article is to present statistical forecasting models concerning the dynamics of Artemisia pollen seasons in Wroc?aw, including the start and end, the date of maximum pollen concentration and seasonal pollen index (SPI). For statistical evaluation, use was made of aerobiological and meteorological data from the last 10 years (2002–2011). Based on this data, agroclimatic indicators, i.e. crop heat units (CHUs), were determined for various averaging periods. The beginning of the Artemisia pollen season in the studied time period, on average, took place on 23 June. Its length usually varied between 26 and 45 days, and maximum daily concentrations occurred between 31 July and 18 August. It was found that the beginning of the pollen season depends, above all, on the values of CHUs and photothermal unit (PTU) (p?<?0.05) in the period from March to June, for various thermal thresholds. The date of maximum daily concentration correlates with sunshine duration, PTU and air temperature for June and July (p?<?0.05). On the other hand, SPI is connected with thermal variables, i.e. average, maximum and minimum air temperatures and CHUs and heliothermal unit (HTU) for July (p?<?0.05) and the beginning of spring. Based on the correlation analysis and the chosen variables, regression models for the beginning date of Artemisia pollen season and SPI were prepared, which were then verified by using leave-one-out cross-validation. A better fit between modelled and actual values was found for the analysis concerning the season start date than for the SPI.     

Spatial and temporal variability of precipitation indices during 1961–2010 in Hunan Province,central south China

Based on daily precipitation records at 75 meteorological stations in Hunan Province, central south China, the spatial and temporal variability of precipitation indices is analyzed during 1961–2010. For precipitation extremes, most of precipitation indices suggest that both the amount and the intensity of extreme precipitation are increasing, especially the mean precipitation amount on a wet day, showing a significant positive trend. Meanwhile, both of the monthly rainfall heterogeneity and the contribution of the days with the greatest rainfall show an upward trend. When it comes to rainfall erosivity, most of this province is characterized by high values of annual rainfall erosivity. Although the directions of trends in annual rainfall erosivity at most stations are upward, only 6 of the 75 stations have significant trends. Furthermore, the spatial and temporal variation of dryness/wetness has been assessed by the standardized precipitation index (SPI). The principal component analysis (PCA) was applied to the SPI series computed on 24-month time scales. The results demonstrated a noticeable spatial variability with three subregions characterized by different trends: a remarkable wet tendency prevails in the central and southern areas, while the northern areas are dominated by a remarkable dry tendency.     

Characteristics,and similarities and differences of climate change in major high mountains in the world-comprehensive interpretation of IPCC AR6 WGI report and SROCC北大核心CSCD

IPCC SROCC和AR6对高山区气候变化的评估表明,近期全球山地增暖速率提高,1980年代以来亚洲高山区增暖速率明显高于全球平均和其他高山区同期水平。各山地增暖普遍具有海拔依赖性,但机制复杂且区域差异大,除落基山脉未来气温增幅随海拔降低外,其余山地均随海拔有不同程度的升高。全球山地年降水在过去几十年没有明显趋势;预计未来北半球许多山地年降水将增加5%~20%,但极端降水变化的区域和季节差异较大,其中青藏高原喜马拉雅山脉极端降水频次和强度都将增大。山地年最大雪水当量的减少在固-液态降水转化的海拔高度带更强,未来山地降雪和积雪变化不仅与排放情景有关,而且与海拔高度密切相关。2010—2019年全球山地冰川物质亏损较有观测记录以来的任何一个10年都多,亚洲高山区虽然冰川物质亏损速率较小,但每年亏损的冰量在全球四大高山区中仅次于安第斯山脉南段。预计山地冰川将持续退缩数十年或数百年,未来亚洲高山区冰川退缩对海平面上升的贡献将居全球四大高山区之首。山地多年冻土温度升高、厚度减薄,预计未来多年冻土将加速退化,即使在低温室气体排放情景下,21世纪末青藏高原多年冻土面积预计也将减少13.4%~27.7%。从评估的完整性和信度水平来看,山地观测和研究仍存在巨大差距。     

A decision‐analytic study of the joint value of seasonal precipitation and temperature forecasts in a choice‐of‐crop problem

Abstract

A static decision‐analytic method is used to investigate the economic value of bivariate ‐ precipitation and temperature ‐ seasonal forecasts of the form currently issued by the U.S. National Weather Service. This method is applied to a corn versus spring wheat choice‐of‐crop decision‐making problem by considering a transect of four counties across the northwestern margin of the North American corn belt. Numerical results indicate that seasonal forecasts of current quality can be of appreciable value (≥$1/ha) for some locations when the optimal action chosen on the basis of climatological information is only marginally preferred to another action. Increases in forecast value follow from hypothetical increases in the quality of both the precipitation and temperature components of the forecasts in the spring wheat region, whereas forecast value increases primarily as a function of the quality of the precipitation forecasts alone in the corn belt region. The results are very sensitive to absolute and relative crop prices.     

Climate change affecting temperature and aridity zones: a case study in Eastern Inner Mongolia, China from 1960–2008

Recent climate change is substantially affecting the spatial pattern of geographical zones, and the temporal and spatial inconsistency of climatic warming and drying patterns contributes to the complexity of the shifting of temperature and aridity zones. Eastern Inner Mongolia, China, located in the interface region of different biomes and ecogeographic zones, has experienced dramatic drying and warming over the past several decades. In this study, the annual accumulated temperature above 10 °C (AAT10) and the aridity index, two key indicators in geographical regionalization, are used to assess warming and drying processes and track the movements of temperature and aridity zones from 1960 to 2008. The results show a significant warming at the regional level from 1960 to 2008 with an AAT10 increase rate of 7.89 °C·d/year (p?<?0.001) in Eastern Inner Mongolia, while the drying trend was not significant during this period. Spatial heterogeneity of warming and drying distributions was also evident. Analysis of warming and drying via piecewise regression revealed two separate, specific trends between the first 31 years (1960–1990) and the subsequent 18 years (1991–2008). Generally, mild warming and very slight wetting occurred prior to 1990, while after 1991 both warming and drying were significant and enhanced. Continuous warming drove a northward shift of temperature zones from the 1960s to 2000s, while aridity zones displayed enhanced temporal and spatial variability. Climate change effects on temperature and aridity zones imply that the patterns of cropping systems, macro-ecosystems, and human land use modes are potentially undergoing migration and modification due to climate change.     

Energy use, climate change and folk psychology: Does sustainability have a chance? Results from a qualitative study in five European countries

Citizens’ support for policies that aim to curb carbon emissions and energy use is often seen as informed by their values, attitudes and perceptions of the environmental problem in question. We argue that we also need to understand how people conceptualise policies and the governance approaches underpinning them to be able to judge the likely acceptance of policy change.In this study, we draw on qualitative interviews (n = 202) from five European countries to explore citizens’ views on governance approaches to stimulate behavioural change in the field of resource use, including regulations, price changes, collective action, technological change and education.We found that many of our interviewees referred to generalised characteristics of humankind and contemporary society to back up their arguments for or against specific governance approaches. In particular, many interviewees concurred that people in general were so self-centred, driven by habit and money- and consumption-oriented that only strict regulations, drastic price changes and technological innovation could possibly achieve widespread behavioural change. As a consequence, such ‘folk psychologies’ can have substantial impact not only on public acceptance, but also on the success of policy measures that aim to reduce citizens’ resource use.     

Traditional ecological knowledge and community resilience to environmental extremes: A case study in Doñana,SW Spain

Research in the last decade has emphasised the potential contribution of traditional ecological knowledge to cope with challenges from global environmental change. This research examines the role of traditional ecological knowledge and shared systems of beliefs in building long-term social–ecological resilience to environmental extremes. Data were collected from 13 villages of the Doñana region, southwestern Spain, through interviews, focus groups, and systematic reviews of historical archives. First, we assess adaptive practices to cope with environmental change. Then, we use historical records of religious ceremonies (1577–1956) to reconstruct collective responses to environmental extremes. Our results (1) show how environmental extremes could induce social and economic crises through declines in ecosystem services and (2) identify practices to cope with recurrent disturbance and institutional devices developed in response to environmental extremes. We conclude that traditional ecological knowledge and shared systems of beliefs can facilitate collective responses to crises and contribute to the maintenance of long-term resilience of social–ecological systems.     

Seasonal temperature and precipitation variability during the last 60?years in a Mediterranean climate area of Northeastern Spain: a multivariate analysis

This paper presents the analysis of mean daily temperature and precipitation from 1950 to 2010 in an area with Mediterranean climate of NE Spain including some coastal areas near Barcelona and the Penedès and Camp de Tarragona Depressions located between the Coastal Mountain Range and the Mediterranean Sea. Their variability, with especial attention to the frequency of extreme events, was analysed by using 18 indexes: seven for temperature and 11 for precipitation were analysed for four meteorological observatories. A multivariate analysis was performed in order to analyse the temperature and precipitation trends. During the analysed period, an increase in mean annual maximum temperature was observed in all observatories ranging between 1.5 and 2.2°C associated with an increase in the number of days with high extreme temperatures. Minimum temperature only increased significantly in the coast observatories (about 1.4°C). By seasons, temperature trends were greater at Vilafranca del Penedès and Barcelona observatories and lower at Reus airport. Maximum spring temperature increased between 1.5 and 2.5°C, summer temperature increased between 1.6 and 2.5°C and autumn temperature increased by up to 2.2°C. Precipitation presented a high variability from year to year, without significant trends. The most significant results were related to the dry conditions observed in spring 2000s, the wet conditions recorded in summer 2000s and 1980s and the longer dry periods in autumn 2000s. The increase of temperatures determined the increase of evapotranspiration, and due to the higher irregular distribution, water deficits for crop development were recorded. An advance of phenological dates and a reduction of grape yield are associated to climate trends.     

Observed variability and trends in extreme temperature indices and rice–wheat productivity over two districts of Bihar, India—a case study

The purpose of this paper is to analyze the trends and variability in extreme temperature indices and its impact on rice–wheat productivity over two districts of Bihar, India, which is part of the middle Indo-Gangetic Basin. Mann–Kendall non-parametric test was employed for detection of trend and Sen slope was determined to quantify the magnitude of such trends. We have analyzed 10 extreme temperature indices for monthly and seasonally. The influence of extreme temperature indices on rice–wheat productivity was determined using correlation analysis. As far as Patna is concerned, if the number of cool days during September ≥10, the rice productivity will increase due to the availability of sufficient duration to fill up the grain. However, higher warm days during all the months except June will affect the productivity. A significant negative correlation was noticed between maximum value of minimum temperature during September and rice productivity. Highly significant positive correlation was noticed between number of cool days during September with rice productivity while it was highly significant negative correlation in the case of number of warm days during the same month. As far as Samastipur is concerned, a negative correlation was noticed between wheat productivity and maximum value of maximum temperature (TXx) during February, but not statistically significant. The higher temperature may affect the kernel weight and thereby yield. It is seen that a critical value of TXx ≥29.2 °C will be harmful to wheat crop during February. A significant positive correlation of number of cool nights with wheat productivity also supports the above relationship. The critical values of extreme temperature indices during rice and wheat growing months provide an indicator to assess the vulnerability of rice–wheat productivity to temperature for Patna and Samastipur districts and there is a need to prepare an adaptive strategy and also develop thermo-insensitive rice–wheat high yielding varieties suitable for this region to sustain rice–wheat productivity under projected climate change situation.     

The heat wave of June 2007 in Athens,Greece – Part 2: Modeling study and sensitivity experiments

In the frame of this paper a heat wave that resulted in record high temperatures in Athens Greece is analysed. Namely the analysis focuses in the ability of three widely used planetary boundary layer parameterisations to reproduce the heat wave temperatures. The simulations were performed with the Pennsylvania State University – National Center for Atmospheric Research MM5 model that is also used for operational weather forecasting at the National Observatory of Athens since 2002. The 2-m temperature at a grid increment of 1-km over the highly complex terrain of the Athens Area is statistically verified against the available surface station observations. The results of the analysis showed that the two nonlocal schemes, namely Blackadar and MRF succeeded much better than the local scheme ETA to reproduce the heat wave 2-m temperature although they considerably underestimated the maximum observed temperatures. In addition, it was found that the model grid points characterised by “urban” land-use provided better statistical verification results, with reduced cold bias. Further, in order to study the role of the initial skin temperature conditions on the 2-m temperature forecasts, satellite observed skin temperatures have been used to initialise the high resolution simulations. This sensitivity test showed that when using the satellite observed skin temperature in the model initial conditions, the simulation of the 2-m temperature is positively affected during the early stages of the simulation while later on the model physical parameterisations are decisive for the time evolution of temperature.     

Role of a meso-γ vortex in Meiyu torrential rainfall over the Hangzhou Bay,China: An observational study

A mesoscale torrential rainfall event that occurred over eastern China in June 2013 is analyzed by using observational data. The results show that a mesoscale convergence line and a weak convective cloud line formed over the northern part of the Hangzhou Bay during the onset of the torrential rainfall event. A meso-vortex appeared over the confluence point of northeasterly flow associated with the Yellow-Sea high, easterly flow from rainfall area, and southeasterly flow from the Hangzhou Bay. The meso-vortex with a horizontal scale of 10–20 km lasted for about 1 h for stable surface circulations. The analysis of radar retrieval reveals that the meso-vortex in the boundary layer occurred at the south of strong radar echo. The formation of the meso-vortex turned to enhance convergence and cyclonic vorticity in the lower troposphere, which strengthened updrafts that are tilted into convective clouds and caused torrential rainfall. Thus, the occurrence of the meso-vortex in boundary layer is one of the mechanisms that are responsible for the enhancement of convective development.     

Well-being and environmental change in the arctic: a synthesis of selected research from Canada’s International Polar Year program

The social and cultural dimensions of arctic environmental change were explored through Canada??s International Polar Year (IPY) research program. Drawing on concepts of vulnerability, resilience and human security, we discuss preliminary results of 15 IPY research projects (of 52) which dealt with the effects and responses of northern communities to issues of ecological variability, natural resource development and climate change. This paper attempts to determine whether the preliminary results of these projects have contributed to the IPY program goal of building knowledge about well-being in the arctic. The projects were diverse in focus and approach but together offer a valuable pan-northern perspective on many themes including land and resource use, food security, poverty and best practices of northern engagement. Case study research using self-reported measures suggests individual views of their own well-being differ from regional and territorial standardized statistics on quality of life. A large body of work was developed around changes in land and resource use. A decline in land and resource use in some areas and consequent concerns for food security, are directly linked to the effects of climate change, particularly in coastal areas where melting sea ice, erratic weather events and changes in the stability of landscapes (e.g., erosion, slumping) are leading to increased risks for land users. Natural resource development, while creating some new economic opportunities, may be compounding rather than offsetting such stresses of environmental change for vulnerable populations. While the IPY program has contributed to our understanding of some aspects of well-being in the arctic, many other issues of social, economic, cultural and political significance, including those unrelated to environmental change, remain poorly understood.     

Combined tree-ring width and ��13C to reconstruct snowpack depth: a pilot study in the Gongga Mountain, west China

Tree-ring width (TRW) and stable carbon isotope (??¹³C) in tree-ring cellulose of subalpine fir (Abies fabri) were used to develop high-resolution climate proxy data to indicate snow-depth variations in the Gongga Mountain, west China. Tree radial growth- and ??¹³C-climate response analyses demonstrated that the TRW and ??¹³C at the timberline (3,400?m.a.s.l.) are mainly influenced by temperature and precipitation of previous growth seasons and current summer (June to August) under cold and humid conditions. Considering the analogous control factors on both tree growth and carbon isotope discrimination (??¹³C) and snow accumulation, the negative and significant relationships between tree-ring parameters (TRW and ??¹³C) and mean monthly snowpack depth were found. Herein, by combining two tree-ring parameters, a primary snow-depth reconstruction (previous October to current May) over the reliable period A.D. 1880?C2004 was estimated. The reconstruction explains 58.0% of the variance in the instrumental record, and in particular captures the longer-term fluctuations successfully. Except the period with extreme higher snowpack depth around 1990, the snowpack depth seems to fluctuate in a normal way. The reconstruction agrees with the nearby snowpack depth record in Kangding and the mean observed snowpack-depth variations of the stations on the Tibetan Plateau, particularly at long-term scales. The snowpack depth in low-frequency fluctuations, during the past century, agrees quite well with the Eastern India precipitation covering the period of previous October?Ccurrent May. Our results suggest that combing tree-ring width and ??¹³C in certain subalpine tree species growing on the Tibetan Plateau may be an effective way for reconstructing regional snowpack variations.     

Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes,multilayer perceptron neural networks,and functional trees methods

The objective of this study is to make a comparison of the prediction performance of three techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural Nets), and Naïve Bayes (NB) for landslide susceptibility assessment at the Uttarakhand Area (India). Firstly, a landslide inventory map with 430 landslide locations in the study area was constructed from various sources. Landslide locations were then randomly split into two parts (i) 70 % landslide locations being used for training models (ii) 30 % landslide locations being employed for validation process. Secondly, a total of eleven landslide conditioning factors including slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to lineaments, distance to rivers, and rainfall were used in the analysis to elucidate the spatial relationship between these factors and landslide occurrences. Feature selection of Linear Support Vector Machine (LSVM) algorithm was employed to assess the prediction capability of these conditioning factors on landslide models. Subsequently, the NB, MLP Neural Nets, and FT models were constructed using training dataset. Finally, success rate and predictive rate curves were employed to validate and compare the predictive capability of three used models. Overall, all the three models performed very well for landslide susceptibility assessment. Out of these models, the MLP Neural Nets and the FT models had almost the same predictive capability whereas the MLP Neural Nets (AUC = 0.850) was slightly better than the FT model (AUC = 0.849). The NB model (AUC = 0.838) had the lowest predictive capability compared to other models. Landslide susceptibility maps were final developed using these three models. These maps would be helpful to planners and engineers for the development activities and land-use planning.     

Correction to: Observational Investigation of the Statistical Properties of Surface-Layer Turbulence in a Suburban Area of São Paulo,Brazil: Objective Analysis of Scaling-Parameter Accuracy and Uncertainties

Boundary-Layer Meteorology -     

Continuous 1064/532 nm Lidar Measurements (CORALNet-UBC) in Vancouver,British Columbia: Selected Results from a Year of Operation

CORALNet-UBC was installed in April 2008 as a “proof of concept” and the first facility in a proposed cross-Canada network of similar lidars. Despite its location on the wet West Coast of Canada, data recovery ranged from a low of 45% of the total time in December, when heavy snowfall interrupted operations, to a high of 90% in July. The facility has been a spectacular success in terms of its operational characteristics (as measured by data recovery), the range of phenomena observed and the research that it has spawned. Examples are provided of the types of phenomena observed since its initial deployment. These include observations of boundary layer structure, cloud signatures, forest fire plumes and evidence of singular long-range pollutant and volcanic transport events. Observations from CORALNet-UBC complement data from other aerosol measurement initiatives in the region and provide a rich source of information that is relevant to researchers, operational forecasters and air quality managers. Future research will be directed at elucidating the processes and phenomena revealed by the instrument as well as developing new products that exploit the real-time forecasting and public advisory potential of the facility.     

Observational Investigation of the Statistical Properties of Surface-Layer Turbulence in a Suburban Area of São Paulo,Brazil: Objective Analysis of Scaling-Parameter Accuracy and Uncertainties

Boundary-Layer Meteorology - Statistical properties of turbulence, specifically variances of velocity components, temperature, water vapor, and carbon dioxide densities, are observationally...     

Lost in the mix: will the technologies of carbon dioxide capture and storage provide us with a breathing space as we strive to make the transition from fossil fuels to renewables?

This paper explores concepts of carbon lock-in arising from the technologies of CO₂ capture and storage (CCS). We examine the argument that CCS reduces carbon lock-in and the calls for a CCS ‘mandate’ and emission performance standards. We analyse the pros- and cons- of a low-carbon fossil fuel lock-in, arguing that lock-in per se is not the problem; it is rather the depth of lock-in which creates problems because deeper lock-in reduces flexibility and increases the ‘error cost’ (i.e. the cost of a decision which turns out to be based on incorrect understanding) and should be avoided. A set of technical and institutional indicators for measuring the flexibility of different technologies is then presented and applied to three technologies: a landfill gas power generator, a conventional nuclear power plant and a CCS plant under development in California. We conclude that these indicators are a useful way forward in assessing individual projects and that public authorities and other stakeholders might wish to employ some version of these indicators in their deliberations on the role of CCS.