Impacts of Urbanization and Station-relocation on Surface Air Temperature Series in Anhui Province, China

Since the 1990s, many meteorological stations in China have passively “entered” cities, which has led to frequent relocation and discontinuity in observational records at many stations. To study the impacts of urbanization on surface air temperature series, 52 meteorological stations in Anhui Province were chosen based firstly on a homogeneity test of the time series, and then their surrounding underlying surfaces during different decades were identified utilizing Landsat Multispectral Scanner images from the 1970s, Landsat Thematic Mapper images from 1980s and 1990s, and Enhanced Thematic Mapper images after 2000, to determine whether or not the station “entered” city, and then these stations were categorized into three groups: urban, suburban, and rural using Landsat-measured land use/land cover (LULC) around the station. Finally, variations in annual mean air temperature (T _mean), maximum air temperature (T _max), and minimum air temperature (T _min) were analyzed in urban-type stations and compared to their surrounding rural-type stations. The results showed that, in Anhui Province over the past two decades, many rural stations experienced urbanization and changed into urban or suburban locations. This process is referred as the “city-entering” phenomena of stations. Consequently, many of the latest stations were relocated and moved to currently rural and suburban areas, which significantly influenced the continuity of observational records and the homogeneity of long-term trends. Based on homogeneous data series, the averaged annual T _mean, T _max, and T _min over Anhui Province increased at a rate of 0.407, 0.383 and 0.432 °C decade^?1 from 1970 to 2008. The strongest effect of urbanization on annual T _mean, T _max, and T _min trends occurred at urban stations, with corresponding contributions of 35.824, 14.286, and 45.161 % to total warming, respectively. This work provides convincing evidences that (1) urban expansion has important impacts on the evaluation of regional climate change, (2) high spatial resolution images of Landsat are very useful for selecting reference climate stations for evaluating the potential urban bias in the surface air temperature data in certain regions of the continents, and (3) meteorological observation adjustments of station-relocation-induced inhomogeneities are essential for the study of regional or global climate change.     

Regional climate change and local urbanization effects on weather variables in Southeast China

This paper presents the analyses of regional climate change features and the local urbanization effects on different weather variables over Southeast China. The weather variables considered are: daily mean (T_m), minimum (T_min), and maximum (T_max) near surface air temperature, diurnal temperature range (DTR), relative humidity (RH), and precipitation (P). With analysis of two datasets (a station dataset for the period from 1960 to 2005 that is mainly used and a grid dataset for the period 1960–2000), this study reveals that the trends in the variations of these weather variables can be separated into two periods, before and after 1984. Before 1984, there were no significant urbanization effects, and T_min, RH, and P steadily increased but T_max decreased, resulting in a considerable decrease in DTR and a slight decrease in T_m. After 1984, T_min and T_max increased considerably, and the urbanization influence on T_min, but not T_max, is observable. The urbanization effect causes an extra increasing trend in T_min with a rate of about 0.6°C/decade and, accordingly, extra decreasing trends in DTR and RH. The analysis of the seasonal trends reveals that the urbanization influence results in a near-uniform increase of T_min for all four seasons and a strong decrease of RH in summer and autumn. Moreover, there is no significant change in P at the annual scale and an increasing rate of 11.8%/decade in summer. With the urbanization influence, a considerable increase in P is noticeable at the annual scale; specifically, the increasing rates of 18.6%/decade in summer and 13.5%/decade in autumn are observed.     

Trends in extreme temperature indices in the Poyang Lake Basin,China

Based on daily maximum and minimum temperature records at 78 meteorological stations in the Basin of China’s largest fresh water lake (Poyang Lake Basin), the temporal and spatial variability of 11 extreme temperature indices are investigated for the period 1959–2010. The analysis indicates that the annual mean of daily minimum temperature (T_min) has increased significantly, while no significant trends were observed in the annual mean of daily maximum temperature (T_max), resulting in a significant decrease in the diurnal temperature range. Trends and percentages of stations with significant trends in T_min-related indices are generally stronger and higher than those in T_max-related indices; however, no significant trends can be found in T_max-related indices (TXMean, TX90p, TXx and TX10p) at both seasonal and annual time scale. Low correlations with Global-SST ENSO index are also detected in T_max-related indices. Significant positive relationships can be found in T_min-related indices (TNMean, TNx, TNn and TN90p), however, the most significant negative coefficient was also found in cold nights (TN10p) with the Global-SST ENSO index. Singular value decomposition (SVD) correlating extreme temperatures over the Poyang Lake Basin and the North Pacific SST indicates the East China Sea, Western Pacific and Bering Sea to be stronger linked with T_min than T_max with the first mode (SVD-1) explaining 90 and 94 % of annual T_max and T_min respectively.     

Regional recharge assessment in the crystalline bedrock aquifer of the Kenogami Uplands,Canada

Abstract

Estimates of trends of climatic changes at basin and state scales are required for developing adaptation strategies related to planning, development and management of water resources. In the present study, seasonal and annual trends of changes in maximum temperature (T _max), minimum temperature (T _min), mean temperature (T _mean), temperature range (T _range), highest maximum temperature (H _max) and lowest minimum temperature (L _min) have been examined at the basin scale. The longest available records over the last century, for 43 stations covering nine river basins in northwest and central India, were used in the analysis. Of the nine river basins studied, seven showed a warming trend, whereas two showed a cooling trend. The Narmada and Sabarmati river basins experienced the maximum warming and cooling, respectively. The majority of basins in the study area show increasing trend in T _range, H _max and L _min. Seasonal analysis of different variables shows that the greatest changes in T _max and T _mean were observed in the post-monsoon season, while T _min experienced the greatest change in the monsoon season. This analysis provides scenarios of temperature changes which may be used for sensitivity analysis of water availability for different basins, and accordingly in planning and implementation of adaptation strategies.     

Woody buffer effects on water temperature: The role of spatial configuration and daily temperature fluctuations

Water temperature is a key driver for riverine biota and strongly depends on shading by woody riparian vegetation in summer. While the general effects of shading on daily maximum water temperature T_max are well understood, knowledge gaps on the role of the spatial configuration still exist. In this study, the effect of riparian buffer length, width, and canopy cover (percentage of buffer area covered by woody vegetation) on T_max was investigated during summer baseflow using data measured in seven small lowland streams in western Germany (wetted width 0.8–3.7 m). The effect of buffer length on T_max differed between downstream cooling and heating: T_max approached cooler equilibrium conditions after a distance of 0.4 km (~45 min travel-time) downstream of a sharp increase in canopy cover. In contrast, T_max continued to rise downstream of a sharp decrease in canopy cover along the whole 1.6 km stream length investigated. The effect of woody vegetation on T_max depended on buffer width, with changes in canopy cover in a 10 m wide buffer being a better predictor for changes in T_max compared to a 30 m buffer. The effect of woody vegetation on T_max was linearly related to canopy cover but also depended on daily temperature range T_range, which itself was governed by cloudiness, upstream canopy cover, and season. The derived empirical relationship indicated that T_max was reduced by −4.6°C and increased by +2.7°C downstream of a change from unshaded to fully shaded conditions and vice versa. This maximum effect was predicted for a 10 m wide buffer at sunny days in early summer, in streams with large diel fluctuations (large T_range). Therefore, even narrow woody riparian buffers may substantially reduce the increase in T_max due to climate change, especially in small shallow headwater streams with low baseflow discharge and large daily temperature fluctuations.     

The effect of climate change on extreme waves in front of the Dutch coast

Coastal safety may be influenced by climate change, as changes in wave conditions (height, period, direction) may increase the vulnerability of dunes and other coastal defences. Dune erosion depends on mean water level, storm surge height and wave conditions. In this paper, we investigate the change in wave conditions in the North Sea in a changing climate. Until now, the effect of climate change on annual maximum wave conditions has been investigated, while events with higher return periods are actually most damaging for the coast (e.g. severe dune erosion). Here, we use the 17-member Ensemble SimulationS of Extreme weather under Non-linear Climate changeE (ESSENCE) change of climate change simulations, to analyse A1b-induced changes in the mean wave climate, the annual maxima and wave conditions with return periods of up to 1:10,000?years in front of the Dutch coast. The mean wave climate is not projected to differ between 1961–1990 and 2071–2100, with both wave height (H _s) and wave period (T _m) remaining unaltered. In the annual maximum conditions, a decrease is projected; especially, the annual T _m maximum decreases significantly by 0.3 to 0.6?s over the whole study area. Furthermore, we find that the direction of the annual maximum wave conditions shifts from north and north-west to west and south-west for both H _s and T _m. This is induced by a similar shift in the direction of the extreme wind speeds. Despite the decrease in annual maximum conditions, the return H _s and T _m are not projected to change significantly as a result of climate change in front of the Dutch coast for the period 2071–2100 relative to 1961–1990.     

Performance evaluation of satellite-based approaches for the estimation of daily air temperature and reference evapotranspiration

Different satellite-based radiation (Makkink) and temperature (Hargreaves-Samani, Penman-Monteith temperature, PMT) reference evapotranspiration (ET_o) models were compared with the FAO56-PM method over the Cauvery basin, India. Maximum air temperature (T_max) required in the ET_o models was estimated using the temperature–vegetation index (TVX) and an advanced statistical approach (ASA), and evaluated with observed T_max obtained from automatic weather stations. Minimum air temperature (T_min) was estimated using ASA. Land surface temperature was employed in the ET_o models in place of air temperature (T_a) to check the potency of its applicability. The results suggest that the PMT model with T_a as input performed better than the other ET_o models, with correlation coefficient (r), averaged root mean square error (RMSE) and mean bias error (MBE) of 0.77, 0.80 mm d^?1 and ?0.69 for all land cover classes. The ASA yielded better T_max and T_min values (r and RMSE of 0.87 and 2.17°C, and 0.87 and 2.27°C, respectively).     

Trends in rainfall and temperature in the Peruvian Amazon–Andes basin over the last 40 years (1965–2007)

The hydroclimatology of the Peruvian Amazon–Andes basin (PAB) which surface corresponding to 7% of the Amazon basin is still poorly documented. We propose here an extended and original analysis of the temporal evolution of monthly rainfall, mean temperature (T_mean), maximum temperature (T_max) and minimum temperature (T_min) time series over two PABs (Huallaga and Ucayali) over the last 40 years. This analysis is based on a new and more complete database that includes 77 weather stations over the 1965–2007 period, and we focus our attention on both annual and seasonal meteorological time series. A positive significant trend in mean temperature of 0.09 °C per decade is detected over the region with similar values in the Andes and rainforest when considering average data. However, a high percentage of stations with significant T_mean positive trends are located over the Andes region. Finally, changes in the mean values occurred earlier in T_max (during the 1970s) than in T_min (during the 1980s). In the PAB, there is neither trend nor mean change in rainfall during the 1965–2007 period. However, annual, summer and autumn rainfall in the southern Andes presents an important interannual variability that is associated with the sea surface temperature in the tropical Atlantic Ocean while there are limited relationships between rainfall and El Niño‐Southern Oscillation (ENSO) events. On the contrary, the interannual temperature variability is mainly related to ENSO events. Copyright © 2012 John Wiley & Sons, Ltd.     

Comparison of transfer functions in statistical downscaling models for daily temperature and precipitation over Canada

This study compares three linear models and one non-linear model, specifically multiple linear regression (MLR) with ordinary least squares (OLS) estimates, robust regression, ridge regression, and artificial neural networks (ANNs), to identify an appropriate transfer function in statistical downscaling (SD) models for the daily maximum and minimum temperatures (T_max and T_min) and daily precipitation occurrence and amounts (P_occ and P_amount). This comparison was made over twenty-five observation sites located in five different Canadian provinces (British Columbia, Saskatchewan, Manitoba, Ontario, and Québec). Reanalysis data were employed as atmospheric predictor variables of SD models. Predictors of linear transfer functions and ANN were selected by linear correlations coefficient and mutual information, respectively. For each downscaled case, annual and monthly models were developed and analysed. The monthly MLR, annual ANN, annual ANN, and annual MLR yielded the best performance for T_max, T_min, P_occ and P_amont according to the modified Akaike information criterion (AICu). A monthly MLR is recommended for the transfer functions of the four predictands because it can provide a better performance for the T_max and as good performance as the annual MLR for the T_min, P_occ, and P_amount. Furthermore, a monthly MLR can provide a slightly better performance than an annual MLR for extreme events. An annual MLR approach is also equivalently recommended for the transfer functions of the four predictands because it showed as good a performance as monthly MLR in spite of its mathematical simplicity. Robust and ridge regressions are not recommended because the data used in this study are not greatly affected by outlier data and multicollinearity problems. An annual ANN is recommended only for the T_min, based on the best performance among the models in terms of both the RMSE and AICu.     

The importance of ocean temperature to global biogeochemistry

Variations in the mean temperature of the ocean, on time scales from millennial to millions of years, in the past and projected for the future, are large enough to impact the geochemistry of the carbon, oxygen, and methane geochemical systems. In each system, the time scale of the temperature perturbation is key. On time frames of 1-100 ky, atmospheric CO₂ is controlled by the ocean. CO₂ temperature-dependent solubility and greenhouse forcing combine to create an amplifying feedback with ocean temperature; the CaCO₃ cycle increases this effect somewhat on time scales longer than ∼5-10 ky. The CO₂/T feedback can be seen in the climate record from Vostok, and a model including the temperature feedback predicts that 10% of the fossil fuel CO₂ will reside in the atmosphere for longer than 100 ky. Timing is important for oxygen, as well; the atmosphere controls the ocean on short time scales, but ocean anoxia controls atmospheric pO₂ on million-year time scales and longer. Warming the ocean to Cretaceous temperatures might eventually increase pO₂ by approximately 25%, in the absence of other perturbations. The response of methane clathrate to climate change in the coming century will probably be small, but on longer time scales of 1-10 ky, there may be a positive feedback with ocean temperature, amplifying the long-term climate impact of anthropogenic CO₂ release.     

Contribution of climatic and technological factors to crop yield: empirical evidence from late paddy rice in Hunan Province,China

Climatic and technological factors are two remarkable aspects that are thought to contribute to crop yield change. However, the most significant factors and their contribution rate remain debatable. Selecting Hunan Province, which is one of the largest paddy rice producing regions in China as the research area, the marginal contributions of climatic and technological factors to late paddy yield change are estimated using a county-level panel data regression model with explicit consideration of technological variables during 2000–2011. The results indicate that the mean daily temperature and adoption rate of hybrid rice have significant positive impacts on late paddy rice yield. During the research period, 1 °C temperature increase will cause 7.220 t/km² increase in late paddy rice yield, and 1 % increase in the adoption rate of hybrid rice will cause 0.212 t/km² increase. Climatic factors, especially their annual variability, exhibit a stronger overall linkage to changes in late paddy rice yield in the study area compared with the technological factors. Climatic factors accounted for 67.645 and 74.585 % of the trend and variability in late paddy rice yield, respectively. The results of this study can provide valuable information for stakeholders to adjust the input on late paddy rice production and better adapt to the effect of climate change.     

Uncertainty analysis of downscaling methods in assessing the influence of climate change on hydrology

Five downscaling techniques, namely the statistical downscaling model, the automated statistical downscaling method, the change factor (CF) method, the advanced CF method, the Weather generator (LarsWG5) method, are applied to the upstream basin of the Huaihe River. Changes in regional climate scenarios and hydrology variables are compared in future periods to investigate the uncertainty associated with the downscaling techniques. Paired-sample T test is applied to evaluation the significant of the difference of the means between the observed data and the downscaled data in the future. The Xinanjiang rainfall–runoff model is employed to simulate the rainfall–runoff relation. The results demonstrate that the downscaling techniques utilized herein predict an increased tendency in the future. The increases range of maximum temperature (T_max) is between 3.7 and 4.7 °C until the time period of 2070–2099 (2080s). While, the increases range of minimum temperature (T_min) is between 2.8 and 4.9 °C until 2080s. The research presented herein determined that there is an increase predicted for the peaks over threshold (discussed in the paper) and a decrease predicted for the peaks below the threshold (discussed in the paper) in the future, which illustrates that the temperature would rise gradually in the future. Precipitation changes are not as obvious as temperatures changes and tend to be influence by the season. Most downscaling techniques predict increases, and others indict decreases. The annual mean precipitation range changes between 3.2 and 53.3 %, and moreover, these changes vary from season to season.     

Solar activity dependence of electron and ion temperatures using SROSS C2 RPA data and comparison with IRI model

Electron and ion temperature (T_e and T_i) data observed using RPA on board SROSS C2 satellite are investigated for the variation with local time, season, latitude (0–30°N geographic) over a half of a solar cycle (1995–2000). The nighttime T_e (∼1000 K) is independent of the season and the solar flux whereas T_i exhibits positive correlation with the solar activity during all three seasons. In the early morning hours during summer, T_e is higher by ∼500 K than other seasons in all three levels of solar activity. During winter and equinox in the early morning hours, T_e and T_i are higher during low solar activity, showing a negative correlation with solar flux. During daytime, the T_i increases with the solar flux in winter and summer solstice, but is independent in equinox. IRI underestimates T_e and T_i during the morning period by 50–75% in the equatorial and near-equatorial stations during all levels of solar activities.     

Climate and hydrological changes in the Ob River Basin during 1936–2017

Changes in the hydrological regimes of Arctic rivers could affect the thermohaline circulation of the Arctic Ocean. In this study, we analysed spatiotemporal variations in temperature and precipitation in the Ob River Basin regions during 1936–2017 based on data from the Global Precipitation Climatology Center. Changes in discharge and response to climate change were examined based on monthly observed data during the same period. It is indicated the Ob River Basin experienced significant overall rapid warming and wetting (increased precipitation) in the study period, with average rates of 0.20°C (10 year⁻¹) and 5.3 mm (10 year⁻¹), respectively. The annual spatial variations of temperature and precipitation showed different scales in different regions. The discharge in spring and winter significantly increased at a rate of 384.1 and 173.1 m³/s (10 year⁻¹), respectively. Hydrograph separation indicated infiltration and supported that deep flow paths increased the contribution of groundwater to base flow. Meanwhile, the variation of the ratio of Q_max/Q_min suggested that the basin storage and the mechanism of discharge generation have significantly changed. The hydrological processes were influenced by changes of permafrost in a certain in the Ob River Basin. An increase in the recession coefficient (RC) implies that the permafrost degradation in the basin due to climate warming affected hydrological processes in winter. Permafrost degradation affected the Q_max/Q_min more significantly in the warm season than RC due to the enhanced infiltration that converted more surface water into groundwater in the cold season. The impact of precipitation on discharge, including surface flow and base flow, was more significant than temperature at the annual and seasonal scales in the Ob River Basin. The base flow was more obviously influenced by temperature than surface flow. The results of this study are significant for analyses of the basin water budget and freshwater input to the Arctic Ocean.     

Petrogenesis of the concealed Daqiling intrusion in Guangxi and its tectonic significance: Constraints from geochemistry,zircon U-Pb dating and Nd-Hf isotopic compositions

The samples from the hidden Daqiling muscovite monzonite granite, which has recently been recognized within the Limu Sn-polymetallic ore field, have been analyzed for zircon U-Pb ages and whole rock geochemical and Nd-Hf isotopic compositions to discuss its genesis, source, and tectonic setting. LA-ICP-MS zircon U-Pb dating indicates that the granite crystallized in the late Indosinian (224.8±1.6 Ma). The granite is enriched in SiO₂ and K₂O and low in CaO and Na₂O. It is strongly peraluminous with the A/CNK values of 1.09–1.20 and 1.4 vol%–2.7 vol% normal corundum. Chondrite-normalized REE patterns show slightly right-dipping shape with strongly negative Eu anomalies (δEu =0.08–0.17). All samples show enrichment of LILEs (Cs, Rb and K) and HFSEs (U, Pb, Ce and Hf), but have relatively low contents of Ba, Sr and Ti. The zircon saturation temperatures (T _zr) are from 711 to 740°C, which are slightly lower than the average value of typical S-type granite (764°C). The granite has negative ? _Nd(t) and ? _Hf(t) values, which change from ?9.1 to ?10.1 with the peak values of ?9.2 to ?9.0 and from ?3.7 to ?12.6 with the peak values of ?6 to ?5, respectively. The T _DM ^C (Nd) and T _DM ^C (Hf) values are 1.74–1.82 Ga with the peak values of 1.73–1.75 Ga and 1.49–2.04 Ga with the peak values of 1.5–1.6 Ga, respectively. These characteristics reveal that the source region of the granite is dominantly late Paleoproterozoic to early Mesoproterozoic crustal materials. Seven inherited magmatic zircons are dated at the age of 248.6±4.3 Ma, which suggests the existence of the early Indosinian granite in Limu area. These zircons have the ? _Hf(t) values of ?6.7–?2.3, similar to those of the Daqiling granite, implying the involvement of the early Indosinian granite during the formation of the Daqiling granite. Inherited zircon of 945±11 Ma has the ? _Hf(t) and T _DM(Hf) values of 8.7 and 1.14 Ga, respectively, compatible with those of the Neoproterozoic arc magmatic rocks in the eastern Jiangnan orogenic belt. Therefore we inferred that Neoproterozoic arc magma might have been involved in the formation of the Daqiling granite, and that the Neoproterozoic arc magma belt and continent-arc collision belt between the Yangtze and Cathaysia Blocks might have extended westsouthward to Limu region. It is proposed that the underplating of mantle materials triggered by crustal extension and thinning resulted in partial melting of crustal materials to form the Daqiling granite in the late Indosinian under post-collisional tectonic setting.     

Magnetic field variations in the umbra of single sunspots during their passage across the solar disk

Temporal variations of the maximum (B _max) and average (〈B〉) magnetic inductions, minimum (α _min) and average (〈α〉) inclination angles of the field lines to the radial direction from the center of the Sun, and areas of the sunspot umbra S in the umbra of single sunspots during their passage across the solar disk are investigated. The variation of the properties of single sunspots has been considered at different stages of their existence, i.e., during formation, the “quiet” period, and the disappearance stage. It has been found that, for the majority of the selected single sunspots, there is a positive correlation between B _max and S and between 〈B〉 and S defined at different times during the passage of sunspots across the solar disk. It is shown in this case that the nature of the dependence between the parameters α _min and B _max, α _min and S, as well as between 〈α〉 and 〈B〉, 〈α〉 and S, can vary from sunspot to sunspot, but for many sunspots the inclination angle of the field lines decreases on average with the growth of the sunspot umbra area and the field strength.     

New Approach to the Characterization of M max and of the Tail of the Distribution of Earthquake Magnitudes

We develop a new method for the statistical estimation of the tail of the distribution of earthquake sizes recorded in the Harvard catalog of seismic moments converted to m _W -magnitudes (1977–2004 and 1977–2006). For this, we suggest a new parametric model for the distribution of main-shock magnitudes, which is composed of two branches, the pure Gutenberg-Richter distribution up to an upper magnitude threshold m ₁, followed by another branch with a maximum upper magnitude bound M _max, which we refer to as the two-branch model. We find that the number of main events in the catalog (N = 3975 for 1977–2004 and N = 4193 for 1977–2006) is insufficient for a direct estimation of the parameters of this model, due to the inherent instability of the estimation problem. This problem is likely to be the same for any other two-branch model. This inherent limitation can be explained by the fact that only a small fraction of the empirical data populates the second branch. We then show that using the set of maximum magnitudes (the set of T-maxima) in windows of duration T days provides a significant improvement, in particular (i) by minimizing the negative impact of time-clustering of foreshock/main shock/aftershock sequences in the estimation of the tail of magnitude distribution, and (ii) by providing via a simulation method reliable estimates of the biases in the Moment estimation procedure (which turns out to be more efficient than the Maximum Likelihood estimation). We propose a method for the determination of the optimal choice of the T value minimizing the mean-squares-error of the estimation of the form parameter of the GEV distribution approximating the sample distribution of T-maxima, which yields T _optimal = 500 days. We have estimated the following quantiles of the distribution of T-maxima for the whole period 1977–2006: Q _16%(M _max) = 9.3, Q _50%(M _max) = 9.7 and Q _84%(M _max) = 10.3. Finally, we suggest two more stable statistical characteristics of the tail of the distribution of earthquake magnitudes: The quantile Q _T (q) of a high probability level q for the T-maxima, and the probability of exceedance of a high threshold magnitude ρ _T (m*)  = P{m _k  ≥ m*}. We obtained the following sample estimates for the global Harvard catalog and The comparison between our estimates for the two periods 1977–2004 and 1977–2006, where the latter period included the great Sumatra earthquake 24.12.2004, m _W  = 9.0 confirms the instability of the estimation of the parameter M _max and the stability of Q _T (q) and ρ _T (m*) = P{m _k  ≥ m*}.     

A multimodel comparison for assessing water temperatures under changing climate conditions via the equilibrium temperature concept: case study of the Middle Loire River,France

This paper investigates three categories of models that are derived from the equilibrium temperature concept to estimate water temperatures in the Loire River in France and the sensitivity to changes in hydrology and climate. We test the models' individual performances for simulating water temperatures and assess the variability of the thermal responses under the extreme changing climate scenarios that are projected for 2081–2100. We attempt to identify the most reliable models for studying the impact of climate change on river temperature (T_w). Six models are based on a linear relationship between air temperatures (T_a) and equilibrium temperatures (T_e), six depend on a logistic relationship, and six rely on the closure of heat budgets. For each category, three approaches that account for the river's thermal exchange coefficient are tested. In addition to air temperatures, an index of day length is incorporated to compute equilibrium temperatures. Each model is analysed in terms of its ability to simulate the seasonal patterns of river temperatures and heat peaks. We found that including the day length as a covariate in regression‐based approaches improves the performance in comparison with classical approaches that use only T_a. Moreover, the regression‐based models that rely on the logistic relationship between T_e and T_a exhibit root mean square errors comparable (0.90 °C) with those obtained with a classical five‐term heat budget model (0.82 °C), despite a small number of required forcing variables. In contrast, the regressive models that are based on a linear relationship T_e = f(T_a) fail to simulate the heat peaks and are not advisable for climate change studies. The regression‐based approaches that are based on a logistic relationship and the heat balance approaches generate notably similar responses to the projected climate changes scenarios. This similarity suggests that sophisticated thermal models are not preferable to cruder ones, which are less time‐consuming and require fewer input data. Copyright © 2012 John Wiley & Sons, Ltd.     

Notable shifting in the responses of vegetation activity to climate change in China

The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (P_NDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive P_NDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.     

Scaling of ground motions and its implications to plan-asymmetric structures

Ground motions are often scaled to certain convenient target spectra in the response assessment of structures. While uniform hazard spectrum (UHS) is more widely used, conditional mean spectrum (CMS) is recently proposed as a more desirable target for scaling of real accelerograms. In this backdrop, the present study spectrally scales, using wavelets, a set of near-field and far-field ground motions to both the targets, viz., UHS and CMS. Relevance of a set of useful ground motion characteristics, viz., the peak ground acceleration-to-peak velocity ratio (a_max/v_max), predominant period (T_p), Arias intensity (I_a), Housner intensity (I_H), cumulative absolute velocity (CAV) and significant duration (T_d^⁎), is reviewed. Influence of ground motion scaling is discussed in terms of possible changes of such identified parameters. Seismic demand of horizontally irregular structures is assessed under both scaled and seed records recognizing strength dependent stiffness. Threshold of the scale factor, shown to have well-correlated with the change of ground motion characteristics, may be as high as ~10 to adequately estimate torsion-induced amplification in asymmetric system without any bias.