Possible Impacts of the Arctic Oscillation on the Interdecadal Variation of Summer Monsoon Rainfall in East Asia

The influences of the wintertime AO (Arctic Oscillation) on the interdecadal variation of summer monsoon rainfall in East Asia were examined. An interdecadal abrupt change was found by the end of the 1970s in the variation of the AO index and the leading principal component time series of the summer rainfall in East Asia, The rainfall anomaly changed from below normal to above normal in central China, the southern part of northeastern China and the Korean peninsula around 1978. However,the opposite interdecadal variation was found in the rainfall anomaly in North China and South China.The interdecadal variation of summer rainfall is associated with the weakening of the East Asia summer monsoon circulation. It is indicated that the interdecadal variation of the AO exerts an influence on the weakening of the monsoon circulation. The recent trend in the AO toward its high-index polarity during the past two decades plays important roles in the land-sea contrast anomalies and wintertime precipitation anomaly. The mid- and high-latitude regions of the Asian continent are warming, while the low-latitude regions are cooling in winter and spring along with the AO entering its high-index polarity after the late 1970s. In the meantime, the precipitation over the Tibetan Plateau and South China is excessive, implying an increase of soil moisture. The cooling tendency of the land in the southern part of Asia will persist until summer because of the memory of soil moisture. So the warming of the Asian continent is relatively slow in summer. Moreover, the Indian Ocean and Pacific Ocean which are located southward and eastward of the Asian land, are warming from winter to summer. This suggests that the contrast between the land and sea is decreased in summer. The interdecadal decrease of the land-sea heat contrast finally leads to the weakening of the East Asia summer monsoon circulation.     

Numerical Simulation of Wind and Temperature Fields over Beijing Area in Summer

1. IntroductionThe basic role of urban-rural boundary layer re-search is to study all kinds of physical process changesin the atmosphere boundary layer over urban and itssurrounding areas. Urban heat island (UHI) is a well-known feature of urban-rural climate. Attempts toincrease the understanding of the causes of the UHIand other urban-rural boundary layer phenomena haveused observational, theoretical and modelling methodssince long before. Seaman (1989) used a hydrostaticmodel, with real …     

On the applicability of KirchofPs law and the principle of heat balance in thermal infrared remote sensing:A non-isothermal system

This paper proposes a basic equation of thermal radiation interaction between surface objects on the basis of the principle of heat balance in the interface. The solution of this equation takes account of the contribution of sensible heat flux and latent heat flux more completely, compared with traditional solution for surface cooling and heating processes. By the aid of the experimental data conducted in the Xiaotangshan experimental site, Beijing, both the non-applicability of Kirchoff's law and the measurability of surface emissivity in a non-isothermal system have been highlighted. Two methods called ventilation and time-delay compensations have been proposed to reduce the error induced by change of surface temperatures of non-isothermal objects during the measurement of emissivity. Based on the solution of the basic equation, this paper has analyzed and pointed out the misunderstanding in comprehension and application of Kirchoff's law published in literature.     

Changes in the spatial scale of Beijing UHI and urban development

The seasonal and interannual variations of Beijing urban heat island (UHI) are investigated in this paper using the temperature data from 1960 to 2000 at 20 meteorological stations in the Beijing region, and then the relationship between the intensity and spatial scale of UHI and Beijing urbanization indices is analyzed and discussed. Main conclusions are the followings. First, Beijing UHI shows obvious seasonal variations, and it is strongest in winter, next in spring and autumn, and least in summer. The seasonal variation of the UHI mainly occurs in the urban area. The UHI intensity at the center of Beijing is more than 0.8℃ in winter, and only 0.5℃ in summer. Second, the intensity of Beijing HUI exhibits a clear interannual warming trend with its mean growth rate (MGR) being 0.3088℃/10 a. The MGR of HUI is largest in winter, next in spring and autumn, and least in summer, and the urban temperature increase makes a major contribution to the growth of HUI intensity. Third, since the Reform and Opening, the urbanization indices have grown several ten times or even one hundred times, the intensity of HUI has increased dramatically, and its spatial scale also expanded distinctively along with the expansion of urban architectural complexes. Fourth, the interannual variation of urbanization indices is very similar with that of HUI intensity, and their linear correlation coefficients are significant at a more than 0.001 confidence level.     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Pixel‐oriented land use classification in energy balance modelling

Mass and energy transfer between soil, vegetation and atmosphere is the process that allows to maintain an adequate energy and water balance in the earth–atmosphere system. However, the evaluation of the energy balance components, such as the net radiation and the sensible and latent heat fluxes, is characterized by significant uncertainties related to both the dynamic nature of heat transfer processes and surfaces heterogeneity. Therefore, a detailed land use classification and an accurate evaluation of vegetation spatial distribution are required for an accurate estimation of these variables. For this purpose, in the present article, a pixel‐oriented supervised classification was applied to obtain land use maps of the Basilicata region in Southern Italy by processing three Landsat TM and ETM+ satellite images. An accuracy analysis based on the overall accuracy index and the agreement Khat of Cohen coefficient showed a good performance of the applied classification methodology and a good quality of the obtained maps. Subsequently, these maps were used in the application of a simplified two‐source energy balance model for estimating the actual evapotranspiration at a regional scale. The comparison between the simulations made by applying the simplified two‐source energy balance model and the measurements of evapotranspiration at a lysimetric station located in the study area showed the applicability and the validity of the proposed methodology. Copyright © 2012 John Wiley & Sons, Ltd.     

Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Modeling deepwater seabed steady-state thermal fields around buried pipeline including trenching and backfill effects

Deepwater pipelines are designed to transport mixtures of oil and gas, and their associated impurities at wellhead temperatures that can be in excess of 149 °C (∼300 °F or 422 K) while the external temperature maybe in the range of 5 °C (∼41 °F or 278 K). Depending on the circumstances these pipelines may be buried for physical protection or for additional thermal insulation using robotic trenching equipment. This results in a complex cut and backfill geometry in the seafloor in addition to altering the thermal properties of the backfill. A two-dimensional boundary element model was developed specifically to address to investigate the local steady-state thermal field in the near field of the pipeline. The model allows one to account for the complex geometries in the near field associated with this burial technique, site-specific multi-layered soil conditions and the seawater adjacent to the seafloor. A parametric study was preformed to evaluate effects of the thermal power loss, burial depth, pipe diameter and soil thermal conductivity on the thermal field in the near field of a buried pipeline. The numerical examples illustrate the influence of the backfill thermal property on the temperature at the pipe wall, that the pipe diameter controls the required output thermal power needed to maintain the desired pipe wall temperature, and the importance of pipeline burial depth on seabed temperature distribution above the pipeline.     

Improved spatial delineation of streambed properties and water fluxes using distributed temperature sensing

A new method was developed for analysing and delineating streambed water fluxes, flow conditions and hydraulic properties using coiled fibre‐optic distributed temperature sensing or closely spaced discrete temperature sensors. This method allows for a thorough treatment of the spatial information embedded in temperature data by creating a matrix visualization of all possible sensor pairs. Application of the method to a 5‐day field dataset reveals the complexity of shallow streambed thermal regimes. To understand how velocity estimates are affected by violations of assumptions of one‐dimensional, saturated, homogeneous flow and to aid in the interpretation of field observations, the method was also applied to temperature data generated by numerical models of common field conditions: horizontal layering, presence of lateral flow and variable streambed saturation. The results show that each condition creates a distinct signature visible in the triangular matrices. The matrices are used to perform a comparison of the behaviour of one‐dimensional analytical heat‐tracing models. The results show that the amplitude ratio‐based method of velocity calculation leads to the most reliable estimates. The minimum sensor spacing required to obtain reliable velocity estimates with discrete sensors is also investigated using field data. The developed method will aid future heat‐tracing studies by providing a technique for visualizing and comparing results from fibre‐optic distributed temperature sensing installations and testing the robustness of analytical heat‐tracing models. Copyright © 2016 John Wiley & Sons, Ltd.