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Abstract The multidimensional impacts of climate change necessitate participation of large scale organizations in the management of vulnerability to climate change. Operating at multiple levels of governance, these organizations help manage the deleterious effects of changing climate for different sectors of human-environment systems. How they frame vulnerability, what influences their framings, why are their framings aligned or misaligned: while these are critical questions for managing vulnerability, they are often overlooked in the literature. By 'framing' we mean how actors understand and evaluate key factors of vulnerability. Through a case study in Bangladesh, we analyze how vulnerability is framed by the leading organizations across five sectors and three levels of governance. Drawing from key-informant interviews, we developed a spatial multi-criteria decision analysis (MCDA) approach and identified vulnerability hotspots. With few variations, our study reveals that the framings of vulnerability are mostly aligned across scale irrespective at which stakeholders are operating. Collectively, proximity to river/sea along with poverty, schooling, cropping intensity, soil salinity, and availability of multipurpose disaster shelters are identified as key determinants of vulnerability by all organizations. They prioritize infrastructural and agricultural development as basis for vulnerability management. We argue that similarity of the understanding of vulnerability across scale would facilitate adaptation decision-making process. However, less focus on socio-economic criteria can undermine the success of adaptation initiatives. While the findings of this study can assist the decision-makers of Bangladesh in coastal vulnerability management, the methodological approach should be useful to assess coastal vulnerability in other parts of the world as well. Highlights • Coastal vulnerability framings by the multilevel organizations involved in climate change management are often overlooked. • Diagnostic framing approach was adopted to analyze coastal vulnerability at multiple levels of governance in Banglades. • We developed a spatial multi-criteria decision analysis approach for the analysis. • Vulnerability framings are mostly aligned, irrespective of scale at which stakeholders are operating. • Governing organizations mostly emphasize on infrastructural and agricultural criteria. [ABSTRACT FROM AUTHOR]

The effect of urbanization on local climate is quantified by numerical simulations for five desert cities that represent a wide range of urban size, climate zone, and composition of land cover. Land-use land cover maps generated from Landsat data for 1985 and 2010, chosen as the start and end of a period of rapid urbanization, are used to constrain the surface boundary conditions for the numerical model. In this manner, this study focuses on the particular aspect of the effect of land-use changes on local climate. Within this scope, the results reveal a pattern of the climatic effect of desert urbanization with nighttime warming and weaker, but significant daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detailed land cover types in the surrounding areas. The pattern is identified in both winter and summer. Exceptions to this pattern are found in a small number of cases when the noisiness of local circulation, specifically monsoon and land-sea breeze, overwhelms the climatic signal induced by land-use changes. The inter-cities’ differences in the temperature response to land-use change are also discussed. [ABSTRACT FROM AUTHOR]

Understanding the impacts of land cover pattern on the heat island effect is essential for sustainable urban development. Conventional model fitting methods have restricted ability to produce accurate estimates of the land cover-temperature association due to the lack of procedures to address two important issues: spatial dependence in proximal spatial units and high correlations among predictor variables. In this study, we seek to develop an effective framework called spatially filtered ridge regression (SFRR) to estimate the variations in the quantity and distribution of land surface temperature (LST) in response to various land cover patterns. The SFRR effectively integrates spatial autoregressive models and ridge regression, and it achieves reliable parameter estimates with substantially reduced mean square errors. We show this by comparing the performance of the SFRR to other widely adopted models using Monte Carlo simulation followed by an empirical study over central Phoenix. Results highlight the great potential of the SFRR in producing accurate statistical estimates, providing a positive step toward informed and unbiased decision-making across a wide variety of disciplines. (Code and data to reproduce the results in the case study are available at: .) [ABSTRACT FROM AUTHOR]

We quantified the spatio-temporal patterns of land cover/land use (LCLU) change to document and evaluate the daytime surface urban heat island (SUHI) for five hot subtropical desert cities (Beer Sheva, Israel; Hotan, China; Jodhpur, India; Kharga, Egypt; and Las Vegas, NV, USA). Sequential Landsat images were acquired and classified into the USGS 24-category Land Use Categories using object-based image analysis with an overall accuracy of 80% to 95.5%. We estimated the land surface temperature (LST) of all available Landsat data from June to August for years 1990, 2000, and 2010 and computed the urban-rural difference in the average LST and Normalized Difference Vegetation Index (NDVI) for each city. Leveraging non-parametric statistical analysis, we also investigated the impacts of city size and population on the urban-rural difference in the summer daytime LST and NDVI. Urban expansion is observed for all five cities, but the urbanization pattern varies widely from city to city. A negative SUHI effect or an oasis effect exists for all the cities across all three years, and the amplitude of the oasis effect tends to increase as the urban-rural NDVI difference increases. A strong oasis effect is observed for Hotan and Kharga with evidently larger NDVI difference than the other cities. Larger cities tend to have a weaker cooling effect while a negative association is identified between NDVI difference and population. Understanding the daytime oasis effect of desert cities is vital for sustainable urban planning and the design of adaptive management, providing valuable guidelines to foster smart desert cities in an era of climate variability, uncertainty, and change. [ABSTRACT FROM AUTHOR]

Changes in land use and land cover alter the local energy balance and contribute to distinct urban climates. This paper presents a local-scale above-canopy study of intra-urban land cover mixes in two cities to analyse the relative effects of surface morphology and local climate on the surface energy balance (SEB). The study is conducted for urban areas in Phoenix, Arizona, and Portland, Oregon, cities with distinct climates but similarly warm and dry summers. A Local-Scale Urban Meteorological Parameterization Scheme (LUMPS) is used to analyse the relative contributions of local weather extremes and land cover variations on the urban energy balance. The partitioning of net all-wave radiation into turbulent sensible and latent heat fluxes as well as heat storage is investigated for a typical dry summer month and two extreme weather scenarios in the two cities. Results of sensitivity analyses show that incoming solar radiation is an important driver of the SEB in LUMPS and should be considered in the generation of climate scenarios. The relationship between individual land cover fractions and SEB fluxes is not clear because of interrelated effects of surface characteristics in the land cover mix. Daytime Bowen ratios vary inversely with vegetation fraction between and within cities for all weather scenarios. Impervious surface cover is positively correlated to the available energy that is partitioned into sensible heat. Cumulative evapotranspiration (ET) is similar for average weather conditions across medium wet sites in Phoenix and Portland but varies more in Portland than in Phoenix under extreme weather conditions. Results suggest that land cover manipulation could offset influences of weather extremes on ET in Portland to a certain degree but not in Phoenix. These findings highlight the importance of spatial and climatic context in the urban design process to mitigate the effects of urbanization. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

• Vegetation phenology in protected area is significantly different from that in unprotected area. • The start of the carbon uptake season in unprotected area advanced more quickly. • Spring phenological sensitivity in protected area is much higher than that in unprotected area. Land surface phenology (LSP) and its trend are important for understanding the vegetation–climate relationship. However, whether LSP and LSP trends for different forest communities vary with the intensity of forest disturbance and the main cause of the change is still unclear. In this study, LSP indicators and their temperature sensitivity (Ts) were obtained for coniferous (Larch Coniferous forests (LC) and Spruce Fir Korean Pine forests (SFKP)), mixed (Broadleaf Korean Pine forests (BKP) and Spruce Fir Broadleaf forests (SFB)), and broadleaf (Aspen White Birch forests (AWB) and White Birch forests (WB)) communities in protected (Fenglin National Natural Reserve, FNNR) and unprotected (Lilin Experimental Forest Farm, LEFF) areas in Northeastern China from remote sensing and climate data. Statistical comparisons of the LSP, LSP trends, and Ts were conducted for various forest communities in both FNNR and LEFF. The results show that the values of mean start of the season (SOS) and mean end of the season (EOS) in FNNR were significantly different from those in LEFF, and the SOS, EOS, and the length of season (LOS) trends for various forest communities in FNNR were significantly different from those in LEFF, except for the SFB. In broadleaf forests, both the mean LOS and LOS trends for various forest communities were significantly higher in FNNR. However, significantly higher LOS but lower LOS trends in FNNR were identified for coniferous and mixed forests. In addition, the SOS Ts for various forest communities in FNNR were significantly higher than those in LEFF, and the Ts for broadleaf forests in FNNR were significantly lower than that in other forest communities. The results of this study suggest that the carbon uptake periods of most temperate forest communities are apparently enhanced by the high spring phenological Ts in protected areas, which provides important insights into future carbon sequestration potential and forest management strategies for temperate forests in Northeastern China. [ABSTRACT FROM AUTHOR]