Cold Index Research Articles

Dynamically-downscaled projections of changes in temperature extremes over China

In this study, likely changes in extreme temperatures (including 16 indices) over China in response to global warming throughout the twenty-first century are investigated through the PRECIS regional climate modeling system. The PRECIS experiment is conducted at a spatial resolution of 25 km and is driven by a perturbed-physics ensemble to reflect spatial variations and model uncertainties. Simulations of present climate (1961–1990) are compared with observations to validate the model performance in reproducing historical climate over China. Results indicate that the PRECIS demonstrates reasonable skills in reproducing the spatial patterns of observed extreme temperatures over the most regions of China, especially in the east. Nevertheless, the PRECIS shows a relatively poor performance in simulating the spatial patterns of extreme temperatures in the western mountainous regions, where its driving GCM exhibits more uncertainties due to lack of insufficient observations and results in more errors in climate downscaling. Future spatio-temporal changes of extreme temperature indices are then analyzed for three successive periods (i.e., 2020s, 2050s and 2080s). The projected changes in extreme temperatures by PRECIS are well consistent with the results of the major global climate models in both spatial and temporal patterns. Furthermore, the PRECIS demonstrates a distinct superiority in providing more detailed spatial information of extreme indices. In general, all extreme indices show similar changes in spatial pattern: large changes are projected in the north while small changes are projected in the south. In contrast, the temporal patterns for all indices vary differently over future periods: the warm indices, such as SU, TR, WSDI, TX90p, TN90p and GSL are likely to increase, while the cold indices, such as ID, FD, CSDI, TX10p and TN10p, are likely to decrease with time in response to global warming. Nevertheless, the magnitudes of changes in all indices tend to decrease gradually with time, indicating the projected warming will begin to slow down in the late of this century. In addition, the projected range of changes for all indices would become larger with time, suggesting more uncertainties would be involved in long-term climate projections.

Assessment of heat and cold wave events over West Africa using three regional climate models

This paper computes heat (cold) waves for four homogeneous temperature regions over West Africa based on excess heat (cold) index and heat (cold) stress. Era Interim daily minimum and maximum temperature data, National Centers for Environmental Prediction-National Center for Atmospheric Research Reanalysis mean daily sea level pressure, 850 hPa winds and 500 hPa geopotential height are used as the surrogate observed data while simulated data are outputs of three Coordinated Regional Climate Downscaling Experiment models (CNRM-ARPEGE, SMHI-RCA and UQAM-CRCM). Heat (cold) wave is calculated for 2001-2008 with respect to 1989-2000 reference period. Findings show that heat wave fluctuates with Intertropical Convergence Zone (ITCZ) from Guinea-Savannah (GS) region in February-March to the Western Sahel between June and August. Frequency of heat waves is fairly stable except in 2007 and 2008 when it increases. The amplitude of heat wave increases from 2001 to 2008, probably due to global warming. With respect to the reanalysis; CNRM-ARPEGE, SMHI-RCA and UQAM-CRCM all simulate comparable spatial and temporal variations in heat waves. However, SMHI generally overestimates the magnitude of heat waves. The models also simulate cold waves similar to the Era Interim except at GS. [...]

Index Storage Mechanism of MongoDB Based on K-center PAM Optimization Algorithm

In MongoDB database, data objects are queried by means of the index. Under the pressure of mass data, all of its index could not be stored in memory, which is bound to affect the system query performance. For this issue, this paper proposes a layered index storage mechanism based on K- center PAM optimization algorithm, clusters hot and cold index through the index of data objects, and uses a layered index storage structure based on Redis cache to reduce times to access disk during data query and improve data query performance. Through experimental comparison with the original index mechanism of MongoDB, this paper verifies that Kcenter PAM optimization index mechanism can enhance the original system query performance.

Monthly Extreme Temperature Trends in CMIP5 Hindcast/Prediction Simulations, 1981–2010 and 2006–35

AbstractA simple index of extreme surface (2 m) monthly temperature was analyzed over the conterminous United States for 13 models from the Coupled Model Intercomparison Project phase 5 (CMIP5) hindcast (1981–2010) and prediction (2006–35) datasets as well as the U.S. climate division dataset, version 2 (nClimDiv), as observations for 1981–2010. Results are analyzed for regions defined in the recent Third U.S. National Climate Assessment. There is good agreement between models and observations for all regions for the annual warm and cold indices except for the warm index in the Northwest. For seasonal values of the temperature index, model simulations generally agree with the sign of the observed seasonal trends in all regions except for the Northwest and a few seasons in the “warming hole” areas of the central and southeastern United States. Most individual ensemble member simulations agree with the sign of the observed trend. However, in all regions and seasons, some simulations, in the range of 10%–40% of all ensemble members, show opposite signs, indicating that even overall skillful projections can have substantial uncertainty. These results indicate that there is potential skill in use of GCMs to provide projections of hot and cold extremes on the 30-yr time scale. However, it is important to note that natural variability is comparable to the forced signal on this time scale and thus introduces uncertainty. Analysis of the future simulations (2006–35) indicates that warm extremes increase rapidly while cold extremes become substantially more rare.

Dynamic changes in temperature extremes and their association with atmospheric circulation patterns in the Songhua River Basin, China

Understanding dynamic changes in climate extremes is important in forecasting extreme climate events and reducing their associated impacts. The objectives of this study were to analyze the spatiotemporal variations in temperature extremes and their association with atmospheric circulation, based on daily maximum (TX) and minimum temperatures (TN) collected from 60 meteorological stations in the Songhua River Basin (SRB) and its surroundings from 1960 to 2014. Following the ETCCDI (Expert Team on Climate Change Detection and Indices), eight extreme temperature indices, including three warm indices, three cold indices and two extreme indices, were chosen to quantify temperature extremes. The Mann-Kendall method and linear trend analysis were used to examine the trends, and Pearson correlation analysis was used to analyze the correlation between the temperature extremes and each atmospheric circulation. The results showed that warm indices, including the number of warm nights, warm days, and summer days, and extreme indices, including minimum TN and maximum TX, showed increasing trends in the SRB from 1960 to 2014. On the other hand, cold indices, including the number of cold nights, cold days and frost days, showed decreasing trends; Warm indices and maximum TX showed significant positive correlations with latitude (P<0.01). The Arctic Oscillation index (AO) displayed significant negative correlations with the cold indices (P<0.01) and positive correlations with the warm indices. The warm indices and extreme indices had positive correlations with the Northern Hemisphere Subtropical High area and intensity indices, while the reverse relationship was found between the cold indices and Northern Hemisphere Subtropical High. The Asia polar vortex area and intensity indices showed negative correlations with warm indices and extreme indices, while they were positively correlated to cold indices. The multivariate ENSO index (MEI) showed no linear correlation with any of the temperature extremes. These findings will provide useful information in forecasting extreme climate events and taking measures to reduce their associated impacts.

Potential effects of land cover change on temperature extremes over Eurasia: current versus historical experiments

ABSTRACTLand use and land cover change (LUCC) is an important external forcing agent of climate change. The comparison of current (2000 A.D.) with historical (1850 A.D.) land cover maps suggests that most of the Eurasian continent has experienced robust and significant LUCC during the past century, especially evident transition from forests to croplands. Therefore, two experiments (control and sensitivity experiments with current and historical land cover maps, respectively) are conducted by using the Community Atmosphere Model Version 5.0 (CAM5.0) coupled with the Community Land Model Version 4.0 (CLM4.0) to investigate the potential effects of LUCC on temperature extremes over Eurasia. Results show significant increases (e.g., 0.2–0.7 °C) in extreme cold indices (e.g., TNn) over central and eastern China, India and mainland Southeast Asia in response to such robust LUCC. Broad and significant decreases (e.g., approximately −1 °C) in extreme warm indices (TXx) are mainly observed in Eastern Europe and western Siberia. Moreover, the effects of LUCC on high and low‐percentile extreme indices of minimum temperature (Tmin) are generally symmetrical, but those for maximum temperature (Tmax) indices are asymmetrical, which are characterized by stronger influences on high‐percentile indices rather than low ones. Further analyses suggest that LUCC‐induced changes in temperature extremes are mostly influenced by shifts in the mean state of Tmin/Tmax. Furthermore, the responses and sensitivities of Tmin/Tmax to LUCC are remarkably distinct among regions. This result mainly occurs because of different LUCC‐induced changes in surface energy components, which depend on the region‐specific climatology of each energy component and the dominant plant functional types.

长江三角洲地区极端气温事件变化特征及其与ENSO的关系

PDF HTML阅读 XML下载 导出引用 引用提醒 长江三角洲地区极端气温事件变化特征及其与ENSO的关系 DOI: 10.5846/stxb201607091409 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41561024）；高校博士学科点专项科研基金项目（20136203110002）；山西省高等学校哲学社会科学研究项目（2015265）。 Correlation analysis of variation of extreme temperature events and El Niño Southern Oscillation(ENSO) in Yangtze River Delta region during 1960-2014 Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:基于1960-2014年65个气象站点逐日最高、最低气温和平均气温资料，分析了长江三角洲地区极端气温事件的变化规律和ENSO事件强度对极端气温指数变化趋势的影响。结果表明：近55年长江三角洲地区夏季日数（SU）、热夜日数（TR）、暖昼日数（TX90）、暖夜日数（TN90）、异常暖昼持续指数（WSDI）、生长期（GSL）均呈增加趋势，其中暖夜日数（TN90）增加幅度最大，增幅为8.55d/10a；极值指数也呈上升趋势，其中月最低气温极小值（TNn）上升幅度最大为（0.53℃/10a）；冰冻日数（ID）、霜冻日数（FD）、冷昼日数（TX10）、冷夜日数（TN10）、异常冷昼持续指数（CSDI）均呈减少趋势，其中冷夜日数（TN10）减少幅度最大（-6.06d/10a）；月平均日较差（DTR）以0.11℃/10a的速率呈下降趋势。空间上，所有站点SU、TXn、TNx呈增加趋势；TR、TX90、TN90、TNn、TXx、WSDI、GSL分别有97%、85%、98%、95%、78%、92%、94%的站点呈增加趋势；所有站点ID、FD、TX10、TN10呈减少趋势；CSDI、DTR分别有87%、77%的站点呈减少趋势。多数极端气温指数与纬度、经度、海拔显著相关。气候变暖突变后，极端暖指数明显增加，极端冷指数明显减少。总体上，厄尔尼诺对极端气温指数的影响大于拉尼娜的影响。 Abstract:Based on daily temperature (maximum, minimum, and average) data of 65 stations, spatial and temporal changes of extreme temperature events and the El Niño Southern Oscillation (ENSO) influence on the extreme temperature threshold over Yangtze River Delta were analyzed for the period 1960-2014. The results showed that in the last 55 years, the extreme temperature indices, i.e. summer days (SU), tropical nights (TR), warm days (TX90), warm nights (TN90), warm spell duration days (WSDI), and growing season length (GSL) have all increased significantly, and TN90 showed an increasing rate of 8.55d per decade. The extremal indices (TXn, TNn, TXx, and TNx) had increasing trends in the Yangtze River Delta region, and TNn showed an increasing rate of 0.53℃ per decade. The ice days (ID), frost days (FD), cold days (TX10), cold nights (TN10), and cold spell duration days (CSDI) have decreased significantly by 0.40 d, 4.03 d, 2.56 d, 6.06 d and 0.33 d per decade, respectively, and TN10 showed a decreasing rate of 6.06 d per decade. DTR has decreased by 0.11℃ per decade. For the spatial distribution of SU, TXn and TNx, all meteorological stations showed increasing trends during 1960-2014. TR, TX90, TN90, TNn, TXx, WSDI, and GSL showed increasing trends at 97%, 85%, 98%, 95%, 78%, 92%, and 94% of meteorological stations, respectively. ID, FD, TX10, and TN10 showed decreasing trends for all stations. For CSDI and DTR, 87% and 77% stations showed decreasing trend. Most extreme temperature indices show good correlation with latitude, longitude, and altitude. After the detected abrupt climate changes, extreme warm indices increased, and extreme cold indices decreased significantly. Overall, the effect of El Nifio on extreme temperature indices was greater than the effect of La Nina. 参考文献 相似文献 引证文献

Temporal and spatial variations in extreme temperatures in the Qilian Mountains-Hexi Corridor over the period 1960-2013

Based on daily maximum and minimum temperatures at 18 meteorological stations in the Qilian Mountains and Hexi Corridor between 1960 and 2013, temporal and spatial variations in extreme temperatures were analysed using linear trends, ten-point moving averages and the Mann-Kendall test. The results are as follows: The trends in the majority of the extreme temperature indices were statistically significant, and the changes in the extreme temperatures were more obvious than the changes in the extreme values. The trends were different for each season, and the changes in rates and intensities in summer and autumn were larger than those in spring and winter. Unlike the cold indices, the magnitudes and trends of the changes in the warm indices were larger and more significant in the Hexi Corridor than in the Qilian Mountains. Abrupt changes were detected in the majority of the extreme temperature indices, and the extreme cold indices usually occurred earlier than the changes in the extreme warm indices. The abrupt changes in the extreme temperatures in winter were the earliest among the four seasons, indicating that these temperature changes were the most sensitive to global climate change. The timing of the abrupt changes in certain indices was consistent throughout the study area, but the changes in the cold indices in the Hexi Corridor occurred approximately four years before those in the Qilian Mountains. Similarly, the changes in the warm indices in the western Hexi Corridor preceded those of the other regions.

Intercomparison of projected changes in climate extremes for South Korea: application of trend preserving statistical downscaling methods to the CMIP5 ensemble

ABSTRACTGlobal climate models (GCMs) provide the fundamental information used to assess potential impacts of future climate change. However, the mismatch in spatial resolution between GCMs and the requirements of regional applications has impeded the use of GCM projections for impact studies at a regional scale. This study applied statistical post‐processing methods that preserve long‐term temporal trends, bias‐correction/spatial disaggregation with detrended quantile mapping (SDDQM) and BCSD with quantile delta mapping (SDQDM), to downscale 20 CMIP5 GCM climate projections for daily precipitation, minimum temperature, and maximum temperature over South Korea. Using the downscaled CMIP5 climate projections, we investigated absolute changes in extreme indices between the reference and three 30‐year future periods. In addition, the biases in change signals from GCM projections for different statistical downscaling methods were compared to evaluate how well long‐term trends in indices are preserved. The results showed that the statistical downscaling methods significantly improved the skill in reproducing extreme indices. For temperature‐related extreme indices, we found strong significant trends while trends for precipitation‐related indices varied depending on the index and climate projection horizon. Specifically, more frequent, longer duration, and more intense hot extremes may occur under the CMIP5 climate projections, while corresponding decreases may occur for extreme cold indices. Prominent upward trends are found in extreme precipitation events. Regarding analysis of the bias in change signals, SDQDM, which explicitly preserves changes in all quantiles of the underlying variables, better preserved long‐term trends in extreme indices simulated by GCMs.

Temperature extremes in the Argentina central region and their monthly relationship with the mean circulation and ENSO phases

ABSTRACTThe aim of this study is to analyse the interannual variability of monthly climatic indices of extreme daily temperature in the central‐north region of Argentina throughout a year and its relationship with the atmospheric circulation. The impact of El Niño‐Southern Oscillation (ENSO) over different temperature indices throughout the year is specially analysed. Globally used indices in the 1970–2010 period are utilized for this purpose. The trends of temperature extremes show warming conditions in several months, especially in October and November. In order to find possible forcings of extreme temperature in the region at monthly scale, the co‐variability with other circulation monthly time series such as changes in the intensity of Southern Hemisphere semi‐permanent anticyclones and the intensity of the subtropical jet were studied. The main finding was a systematic shift of the South Atlantic anticyclone towards the west over the decades in June and August, which might hinder the cold advections over the region surveyed. Moreover, the influence of the variation on the intensity of the subtropical jet over extreme events showed significant positive (negative) correlations between the intensity of the jet and the frequency of cold (warm) indices in a great number of months. Finally, the influence of the ENSO phases on each of the temperature extremes analysed was studied. It was found that under El Niño conditions, minimum temperatures are affected quite evenly throughout the year, fostering the occurrence of warm nights. The impact of the El Niño event on the maximum extreme temperatures, however, shows seasonal differences. Between July and September warm days conditions are fostered, while between November and February the opposite (cold days) can be seen. This results in a decrease in the temperature range in the region surveyed during the summer months under El Niño conditions.

Observed changes of temperature extremes in Serbia over the period 1961 − 2010

The analysis of spatiotemporal changes of temperature extremes in Serbia, based on 18 ETCCDI indices, was performed using daily minimum and maximum temperature observations from 26 meteorological stations over the period 1961–2010. The observation period was divided into two sub-periods (1961–1980 and 1981–2010) according to the results of the sequential Mann–Kendall test. Temporal trends were evaluated by a least-squares linear regression method. The average annual minimum temperature displayed a mixed pattern of increasing, decreasing, and no trends over 1961–1980 and a significant increasing trend over 1981–2010 across the whole country, with a regionally averaged rate of 0.48°C per decade. The average annual maximum temperature showed a decreasing trend during 1961–1980 and a significant increasing trend at all stations during 1981–2010, with a regionally averaged rate of 0.56°C per decade. Hot indices exhibited a general cooling tendency until 1980 and a warming tendency afterwards, with the most pronounced trends in the number of summer and tropical days during the first period and in the frequency of warm days and nights in the second. Cold indices displayed a mostly warming tendency over the entire period, with the most remarkable increase in the lowest annual maximum temperature and the number of ice days during the first period and in the frequency of cool nights during the second. At most stations, the diurnal temperature range showed a decrease until 1980 and no change or a slight increase afterwards. The lengthening of the growing season was much more pronounced in the later period. The computed correlation coefficient between the annual temperature indices and large-scale circulation features revealed that the East Atlantic pattern displayed much stronger association with examined indices than the North Atlantic Oscillation and East Atlantic/West Russia pattern.

Environmental determinants of genetic diversity inCaragana microphylla(Fabaceae) in northern China

The sand-fixing shrub Caragana microphylla (Fabaceae) is extensively used for vegetation restoration in areas of northern China undergoing desertification. Although the understanding of its genetic variation and related determinants is an important component of plant conservation and ecological restoration in the face of a changing global environment, the relationship between genetic diversity in C. microphylla and climatic factors is unknown. In this study, we assessed population genetic variation in C. microphylla along temperature and humidity gradients in northern China using inter-simple sequence repeat (ISSR) markers. In general, high levels of genetic diversity were uncovered in the 13 populations studied. The number of polymorphic loci ranged from 14 to 63 and polymorphism percentages ranged from 8.75 to 39.38%. Observed and effective allele numbers were 1.09–1.40 and 1.06–1.30, respectively. Nei's genetic diversity index (h) was calculated as 0.0340–0.1663 and Shannon's diversity index (I) was 0.0502–0.2403. At the species level, h and I were 0.2579 and 0.3965, respectively. Populations from low hydrothermal level areas, experiencing severe desertification and habitat fragmentation, exhibited the greatest genetic diversity. Genetic diversity in C. microphylla was positively correlated with annual temperature range, cold index, mean annual rainfall and hydrothermal synthesis index, whereas a negative association was found with mean annual temperature. Using redundancy analysis, we found that mean annual rainfall and cold index explained 87.8% of observed genetic variation, suggesting that genetic diversity in C. microphylla depends primarily on these two factors. Our data are relevant to the restoration and management of degraded ecosystems in arid and semiarid regions.

Spatial and Temporal Variations of Extreme Climate Events in Xinjiang, China during 1961-2010

Daily maximum/minimum temperature and precipitation data from 35 weather stations in Xinjiang during 1961-2010 were examined using kriging spatial analysis, linear tendency estimation, and correlation analysis. Temporal trends and spatial distribution patterns of extreme temperature and precipitation in this area were then analyzed using 12 extreme temperature and 7 extreme precipitation indices. The following results were obtained. 1) Over the past 50 years, extreme cold indices, excepting the monthly maximum temperature minimum value and monthly extreme minimum temperature, showed slight decreasing trends. These indices include the maximum number of consecutive frost days, icy days, cold-nighttime days, and cold-daytime days. 2) Extreme warm events generally showed significant increasing trends (P < 0.01), including the indices of summertime days, warm-nighttime days, warm-daytime days, monthly extreme maximum temperature, and monthly minimum temperature maximum value. 3) The spatial distributions of threshold values of extreme warm and cold events showed notable regional differences. A reducing trend of extreme cold events and an increase in extreme warm events has occurred mainly in northern Xinjiang. 4) For the past 50 years, six extreme precipitation indices, aside from consecutive dry days, showed significant increasing trends in Xinjiang (P < 0.05) and notable differences in spatial distribution. The increase in extreme precipitation events was more rapid at northern than at southern sites. Extreme precipitation intensity was greater in mountainous areas, and precipitation frequency increased in the plain region. 5) Factor analysis revealed good correlations among extreme temperature indices, excepting extreme temperature days.

Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960–2013 under global warming

In recent decades, extreme climatic events have been a major issue worldwide. Regional assessments on various climates and geographic regions are needed for understanding uncertainties in extreme events' responses to global warming. The objective of this study was to assess the annual and decadal trends in 12 extreme temperature and 10 extreme precipitation indices in terms of intensity, frequency, and duration over the Loess Plateau during 1960–2013. The results indicated that the regionally averaged trends in temperature extremes were consistent with global warming. The occurrence of warm extremes, including summer days (SU), tropical nights (TR), warm days (TX90), and nights (TN90) and a warm spell duration indicator (WSDI), increased by 2.76 (P<0.01), 1.24 (P<0.01), 2.60 (P=0.0003), 3.41 (P<0.01), and 0.68 (P=0.0041) days/decade during the period of 1960–2013, particularly, sharp increases in these indices occurred in 1985–2000. Over the same period, the occurrence of cold extremes, including frost days (FD), ice days (ID), cold days (TX10) and nights (TN10), and a cold spell duration indicator (CSDI) exhibited decreases of −3.22 (P<0.01), −2.21 (P=0.0028), −2.71 (P=0.0028), −4.31 (P<0.01), and −0.69 (P=0.0951) days/decade, respectively. Moreover, extreme warm events in most regions tended to increase while cold indices tended to decrease in the Loess Plateau, but the trend magnitudes of cold extremes were greater than those of warm extremes. The growing season (GSL) in the Loess Plateau was lengthened at a rate of 3.16days/decade (P<0.01). Diurnal temperature range (DTR) declined at a rate of −0.06°C /decade (P=0.0931). Regarding the precipitation indices, the annual total precipitation (PRCPTOT) showed no obvious trends (P=0.7828). The regionally averaged daily rainfall intensity (SDII) exhibited significant decreases (−0.14mm/day/decade, P=0.0158), whereas consecutive dry days (CDD) significantly increased (1.96days/decade, P=0.0001) during 1960–2013. Most of stations with significant changes in SDII and CDD occurred in central and southeastern Loess Plateau. However, the changes in days of erosive rainfall, heavy rain, rainstorm, maximum 5-day precipitation, and very-wet-day and extremely wet-day precipitation were not significant. Large-scale atmospheric circulation indices, such as the Western Pacific Subtropical High Intensity Index (WPSHII) and Arctic Oscillation (AO), strongly influences warm/cold extremes and contributes significantly to climate changes in the Loess Plateau. The enhanced geopotential height over the Eurasian continent and increase in water vapor divergence in the rainy season have contributed to the changes of the rapid warming and consecutive drying in the Loess Plateau.

Analysis of extreme temperature events in the Qinling Mountains and surrounding area during 1960–2012

In this study, 16 indices of extreme temperature were calculated on the basis of daily maximum and minimum temperature data in the northern and southern regions of the Qinling Mountains (NSQ) using linear trend and correlation analysis and other methods to investigate the temporal variation trend, spatial distribution pattern and correlation of extreme temperature events. The results are as follows. (1) The extreme cold and warm indices exhibited contrasting variation trends over the entire region: the cold indices (TX10, TN10, ID, FD and CSDI) decreased; the warm indices (TX90, TN90, SU, TR and WSDI) increased; the extremal indices (TXn, TNn, TXx and TXn) increased; and the diurnal temperature range (DTR) decreased. (2) The absolute indices, extremal indices and other indices showed a certain latitudinal zonality: ice days (ID) and frost days (FD) decreased from north to south, while summer days (SU), tropical nights (TR), extremal indices (TXn, TNn, TXx and TXn), the cold and warm spell duration indicators (CSDI and WSDI, respectively) and growing season length (GSL) increased from north to south. (3) The correlation analysis results showed that, except for the extremal indices and individual indices, the extreme temperature indices correlated well. (4) The altitude has a large impact on spatial distribution of extreme temperature indices, and the ubiquity of the heat island effect in urban constructed regions also had an impact on amplitude of variation in extreme temperature.

Energy Analysis and Sunshade Strategy Research of Passive Public Buildings

Taking an example of a passive public construction project of building the research and development center in hebei province and based on dynamic analysis of energy consumption principle, this models passive public buildings and simulates energy consumption, it concludes cold index that construction demands in air conditioning season is 5.93W/m2 and 23.75W/m2 in heating season. Where in the condition of sunshade and opening lighting in part of air conditioning room when calculating the difference between the air-conditioning season building energy consumption, it shows that shading effect is more obvious in 13:00~15:00pm,and Saving rate is 0.72%.Experimental study on the above analysis provides reference to Passive public buildings energy-saving operation.

Changes in temperature extremes in the Yangtze River Basin, 1962–2011

Based on daily maximum and minimum temperature observed by the China Meteorological Administration at 115 meteorological stations in the Yangtze River Basin from 1962 to 2011, the methods of linear regression, principal component analysis and correlation analysis are employed to investigate the temporal variability and spatial distribution of temperature extremes. Sixteen indices of extreme temperature are selected. The results are as follows: (1) The occurrence of cold days, cold nights, ice days, frost days and cold spell duration indicator has significantly decreased by −0.84, −2.78, −0.48, −3.29 and −0.67 days per decade, respectively. While the occurrence of warm days, warm nights, summer days, tropical nights, warm spell duration indicator and growing season length shows statistically significant increasing trends at rates of 2.24, 2.86, 2.93, 1.80, 0.83 and 2.30 days per decade, respectively. The tendency rate of the coldest day, coldest night, warmest day, warmest night and diurnal temperature range is 0.33, 0.47, 0.16, 0.19 and −0.07°C per decade, respectively. (2) The magnitudes of changes in cold indices (cold nights, coldest day and coldest night) are obviously greater than those of warm indices (warm nights, warmest day and warmest night). The change ranges of night indices (warm nights and cold nights) are larger than those of day indices (warm days and cold days), which indicates that the change of day and night temperature is asymmetrical. (3) Spatially, the regionally averaged values of cold indices in the upper reaches of the Yangtze River Basin are larger than those in the middle and lower reaches. However, the regionally averaged values of most warm indices (except warm spell duration indicator) and growing season length in the middle and lower reaches are larger than those in the upper reaches. (4) The extreme temperature indices are well correlated with each other except diurnal temperature range.

트위터에서 추출한 감기 증상의 사회적 신호와 영향요인과의 상관분석

소셜 네트워크 서비스의 인기가 증가하면서 현재 이슈가 되는 정보를 추출하거나 증상 등을 추적하는 분석연구가 활발히 진행되고 있다. 특히 트위터에서는 트윗을 통해 이벤트 현상에 대한 반응과 사용자의 개인적인 상태 등이 잘 반영되어 트윗을 센서로 적용한 이벤트 추출이 가능하다. 최근에는 지진과 같은 재난 이벤트뿐만 아니라 사회 전반적으로 관심을 갖고 있는 질환이나 질병에 대한 사회적 신호가 질병의 확산을 조기에 감지하는데 도움을 주고 있다. 논문에서는 감기를 대상 이벤트로 지정하여 트위터로부터 수집한 정보를 감기 신호라는 사회적 신호로 간주하고 분석하였다. 추출된 감기 신호의 신뢰성을 확인하기 위해 감기 확산의 환경적 요인으로 알려진 세 가지 기후 요소와 기상청에서 제공하는 감기 기상지수와의 상관분석을 통해 변수들 사이의 상관관계를 파악한다. With the huge success of Social Network Services, studies on social network analysis to extract the current issues or to track the symptoms of epidemic disease are being carried out actively. On Twitter, tweets reflect people's reaction to an event and users' individual status well, so it is possible to detect an event regarding a tweet as a sensory value. Recently, social signals are used to detect the spread of illness like the flu as well as the occurrence of disaster event like an earthquake in early stages. In this paper, we set up a cold as a target event and regarded tweets as Cold Signals. To evaluate the reliability of Cold Signals, we analyzed correlations between weather factors and the cold index provided by Korea Meteorological Administration.

Arabidopsis LOS5 Gene Enhances Chilling and Salt Stress Tolerance in Cucumber

Low temperature and high salinity are the major abiotic stresses that restrict cucumber growth and production, breeding materials with multiple abiotic resistance are in greatly need. Here we investigated the effect of introducing the LOS5 gene, a key regulator of ABA biosynthesis in Arabidopsis thaliana, under the stress-responsive RD29A promoter into cucumber (Cucumis sativus L. cv. S516). We found that T1RD29A-LOS5 transgenic lines have enhanced tolerance to cold and salt stresses. Specifically, transgenic lines exhibited dwarf phenotypes with reduced leaf number, shorter internode, decreased length of the biggest leaf, fewer female flowers, shorter fruit neck and lower vitamin C (Vc). The increased cold tolerance can be reflected from the significantly decreased cold index, the reduced electrolyte leakage index and the MDA content upon cold treatment as compared to those in the control. This may result from the accumulation of internal ABA, soluble sugars and proline, and the enhanced activities of protective enzymes superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) in the transgenic lines. Under salt treatment, the transgenic lines exhibited increased germination index, vigor index, more lateral roots and increased root fresh weight. Moreover, RD29A-LOS5 transgenic plants displayed quicker responses in salt stress than that in low-temperature stress.

Mudanças climáticas e a produçãode uva no vale do Rio do Peixe-SC

Foram avaliadas as tendências nas séries climáticas e nos índices agroclimáticos para a cultura da videira no Vale do Rio do Peixe-SC. Foram utilizados os dados diários da Estação Meteorológica de Videira do período de 1971 a 2010. As tendências nas séries foram avaliadas pelo teste de Mann-Kendall, e para estimar a magnitude da tendência utilizou-se a declividade mediana, determinada pelo teste de Theil - Sen. Os resultados mostraram tendência de aumento nas séries de temperatura mínima do ar, em escala anual, bem como nas estações do ano. Para a temperatura máxima do ar, houve tendência significativa de aumento na série de temperatura máxima anual e na temperatura máxima no verão e inverno. Também foi observado aumento da frequência de dias quentes e noites quentes. Com relação aos índices agrometeorológicos, foi observada tendência significativa de diminuição do número de geadas, antecipação das datas de brotação, florescimento e colheita, aumento significativo na soma térmica, no índice de Huglin e no índice de frio. Com relação à precipitação, houve tendência significativa de aumento da precipitação total anual e da precipitação no período de crescimento da cultura da videira e do número de dias com chuva igual ou superior a 20 mm.