Submillimeter-wave and observations of the event on 28 November, 2001

We present a detailed study of a 1B/M6.9 impulsive flare combining high time resolution (1 ms) and instantaneous emission source localization observations at submillimeter frequencies (212 GHz), obtained with the solar submillimeter telescope (SST), and Hα data from the Hα solar telescope for argentina (HASTA). The flare, starting at 16:34 UT, occurred in active region (AR) 9715 (NOAA number) on November 28, 2001, and was followed by an Hα surge. We complement our data with magnetograms from the Michelson Doppler Imager (SOHO/MDI). SST observed a short impulsive burst at 212 GHz, presenting a weak bulk emission (of about 90 sfu) composed of a few shorter duration structures. The integrated Hα and the 212 GHz light curves present a remarkable agreement during the impulsive phase of the event. The delay between both curves stays below 12 s (the time resolution of the Hα telescope). The flare as well as the surge are linked to new flux emergence very close to the main AR bipole. Taking into account the AR magnetic field evolution, we infer that magnetic field reconnection, occurring at low coronal levels, could have been at the origin of the flare; while in the case of surge this would happen at the chromospheric level.     

Experimental study on soil CO2 emission in the alpine grassland ecosystem on Tibetan Plateau

The Tibetan Plateau, the Roof of the World, is the highest plateau with a mean elevation of 4000 m. It is characterized by high levels of solar radiation, low air temperature and low air pressure compared to other regions around the world. The alpine grassland, a typical ecosystem in the Tibetan Plateau, is distributed across regions over the elevation of 4500 m. Few studies for carbon flux in alpine grassland on the Tibetan Plateau were conducted due to rigorous natural conditions. A study of soil respiration under alpine grassland ecosystem on the Tibetan Plateau from October 1999 to October 2001 was conducted at Pangkog County, Tibetan Plateau (31.23°N, 90.01°E, elevation 4800 m). The measurements were taken using a static closed chamber technique, usually every two weeks during the summer and at other times at monthly intervals. The obvious diurnal variation of CO2 emissions from soil with higher emission during daytime and lower emission during nighttime was discovered. Diurnal CO2 flux fluctuated from minimum at 05:00 to maximum at 14:00 in local time. Seasonal CO2 fluxes increased in summer and decreased in winter, representing a great variation of seasonal soil respiration. The mean soil CO2 fluxes in the alpine grassland ecosystem were 21.39 mgCO2 · m-2 · h-1, with an average annual amount of soil respiration of 187.46 gCO2 · m-2 · a-1. Net ecosystem productivity is also estimated, which indicated that the alpine grassland ecosystem is a carbon sink.     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

Localization of mining-induced horizontal fractures along rock layer interfaces in overburden: field measurements and prediction

The locations of mining-induced horizontal fractures along rock interfaces in the overburden of Donetsk Coal Basin were identified using an original experimental device. The device traps methane from horizontal fracture zone (100–fold coal seam thickness) over an active longwall mining excavation. Presence or absence of horizontal fractures along rock layer interfaces is correlated with physical characteristics of the overburden, such as thickness, uniaxial compressive strength of overburden rock layers, location of rock layer interfaces and thickness of extracted coal seams. As a result, a combined criterion based on these physical characteristics is proposed to predict the presence of overburden horizontal fracturing in coal mine operations.     

On Tension Failure of 2-D Rock Specimens and Associated Acoustic Emission

Summary To understand the failure mechanism of quasi-brittle materials like rock under tensile stress, observations on the failure process of granite and marble plate specimens under tension are summarized and presented. Micro- and macro-failure properties of rock plates under uniaxial tension have been characterized by using an acoustic emission technique. Acoustic emission signals associated with micro-fractures are captured to locate the sources. An algorithm based on arrival time difference is developed for this purpose. The results reveal clearly the failure processes of rock which include initiation, nucleation and propagation of micro-fractures when the axial stress is close to the peak strength of rock. It is believed that the difference in heterogeneity between granite and marble specimens leads to different fracture shapes and different behaviors of associated acoustic emissions. Numerical simulation of acoustic emissions for two-dimensional tensile test is also carried out. The simulated characteristics are in good agreement with the experimental results.     

Three dimensional numerical simulation of residential building on shrink–swell soils in response to climatic conditions

Shrink–swell soils can cause distresses in buildings, and every year, the economic loss associated with this problem is huge. This paper presents a comprehensive system for simulating the soil–foundation–building system and its response to daily weather conditions. Weather data include rainfall, solar radiation, air temperature, relative humidity, and wind speed, all of which are readily available from a local weather station or the Internet. These data are used to determine simulation flux boundary conditions. Different methods are proposed to simulate different boundary conditions: bare soil, trees, and vegetation. A coupled hydro‐mechanical stress analysis is used to simulate the volume change of shrink–swell soils due to both mechanical stress and water content variations. Coupled hydro‐mechanical stress‐jointed elements are used to simulate the interaction between the soil and the slab, and general shell elements are used to simulate structural behavior. All the models are combined into one finite element program to predict the entire system's behavior. This paper first described the theory for the simulations. A site in Arlington, Texas, is then selected to demonstrate the application of the proposed system. Simulation results are shown, and a comparison between measured and predicted movements for four footings in Arlington, Texas, over a 2‐year period is presented. Finally, a three‐dimensional simulation is made for a virtual residential building on shrink–swell soils to identify the influence of various factors. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimation of daily stream water temperatures with a Bayesian regression approach

Stream water temperature plays a significant role in aquatic ecosystems where it controls many important biological and physical processes. Reliable estimates of water temperature at the daily time step are critical in managing water resources. We developed a parsimonious piecewise Bayesian model for estimating daily stream water temperatures that account for temporal autocorrelation and both linear and nonlinear relationships with air temperature and discharge. The model was tested at 8 climatically different basins of the USA and at 34 sites within the mountainous Boise River Basin (Idaho, USA). The results show that the proposed model is robust with an average root mean square error of 1.25 °C and Nash–Sutcliffe coefficient of 0.92 over a 2‐year period. Our approach can be used to predict historic daily stream water temperatures in any location using observed daily stream temperature and regional air temperature data.     

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.     

Trends and multi‐annual variability of water temperatures in the river Danube,Serbia

The relationship between air (Ta) and water temperature (Tw) is very important because it shows how the temperature of a water body might respond to future changes in surface Ta. Mean monthly Tw records of three gauging stations (Bezdan, Bogojevo i Veliko Gradi?te) were analysed alongside mean monthly discharge (Q) for the same stations. Additionally, Ta series from two meteorological stations (Sombor and Veliko Gradi?te) were correlated with Tw variations over the period 1950–2012. Locally weighted scatter point smoothing (LOWESS) was used to investigate long‐term trends in the raw data, alongside the Mann–Kendall (MK) trend test. Trend significance was established using Yue–Pilon's pre‐whitening approaches to determine trends in climate data. Also, the rescaled adjusted partial sums (RAPS) method was used to detect dates of possible changes in the time series. Statistically significant warming trends were observed for annual and seasonal minimum and maximum Tw at all investigated sites. The strongest warming was observed at Bogojevo gauging station for seasonal maximum Tw, with +0.05 °C per year on average. RAPS established that the trend began in the 1980s. This behaviour is linked to climate patterns in the North and East Atlantic which determine the amount of heat advected onto mainland Europe. Statistically significant correlations were found for all Tw on an annual basis. Overall, the strongest correlations (p < 0.01) between Tw residuals and the North Atlantic Oscillation (NAO) were recorded for the winter period. These findings suggest possible predictability of Tw over seasonal time‐scales. Copyright © 2016 John Wiley & Sons, Ltd.     

A microscale model for air pollutant dispersion simulation in urban areas: Presentation of the model and performance over a single building

A microscale air pollutant dispersion model system is developed for emergency response purposes. The model includes a diagnostic wind field model to simulate the wind field and a random-walk air pollutant dispersion model to simulate the pollutant concentration through consideration of the influence of urban buildings. Numerical experiments are designed to evaluate the model's performance, using CEDVAL(Compilation of Experimental Data for Validation of Microscale Dispersion Models) wind tunnel experiment data, including wind fields and air pollutant dispersion around a single building. The results show that the wind model can reproduce the vortexes triggered by urban buildings and the dispersion model simulates the pollutant concentration around buildings well. Typically, the simulation errors come from the determination of the key zones around a building or building cluster. This model has the potential for multiple applications; for example, the prediction of air pollutant dispersion and the evaluation of environmental impacts in emergency situations; urban planning scenarios;and the assessment of microscale air quality in urban areas.