Assessing the value of climate assessments: Progress and future directions.

The authors synthesize existing climate research and climate instruments, as well as introduce several frameworks to help educators understand how institutions and researchers have assessed diversity in the college environment. Over 90 instruments were reviewed and examined for their attention to multiple dimensions of the campus climate, diversity initiatives, and outcomes measures that capture students' values, skills, and knowledge for participation in a diverse society. Frameworks presented include a broad definition of the campus climate, a typology of campus initiatives based on an inventory of campus practice, and a typology of representative outcomes that capture cognitive, socio-cognitive, values/attitudes, and preparation for a multicultural society. Campuses that strive to become functional multicultural learning environments can now rely on a body of empirical information to guide practice and critical self-assessment to deepen their commitment to diversity. The authors recommend that campuses integrate their assessment of the climate with the evaluation of student outcomes and campus practice. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Large wood debris recruitment on differing riparian landforms along a Gulf Coastal Plain (USA) stream: a comparison of large floods and average flows

In southeastern Coastal Plain streams, wood debris can be very abundant and is recruited from extensive forested floodplains. Despite importance of wood debris, there have been few opportunities to examine recruitment and redistribution of wood in an undisturbed setting, particularly in the southeastern Coastal Plain. Following extensive flooding in 1994, measurements of individual downed trees (species, dbh, orientation, distance from base‐flow channel and condition) were made across replicated riparian landforms in a Gulf Coastal Plain 5th‐order stream. Annually, the fate of these trees was determined and newly recruited trees were noted. More than 300 downed trees have been recorded. Recruitment varied across landforms with more constrained reaches having greatest mortality. Total tree mortality varied substantially across years. Generally, tree recruitment was greatest in years with substantial floods (1994 and 1998). For each riparian landform type, tree mortality was correlated with the maximum daily flow during the period preceding annual debris surveys. This relationship was particularly strong for sand ridges (r² = 0.942) and low terraces (r² = 0.915), but was significant for floodplains (r² = 0.413). Greatest rates of debris recruitment per maximum daily flow were observed for sand ridges followed by low terraces. Flood characteristics also influenced debris recruitment. The 1994 flood was caused by a tropical storm and resulted in a rapid rise in streamflow. Much of the debris recruited during this flood was from toppled trees and was oriented parallel to the stream channel. In contrast, the 1998 flood was preceded by a wetter than average winter with more gradually rising flows and there was no relationship between riparian landform and debris characteristics. These results indicate that wood recruitment dynamics in Coastal Plain streams are complex. Wood recruitment rates are controlled by cyclical variations in climate interacting with riparian geomorphology. Infrequent high flows appear critical in the maintenance of the instream debris pool. Copyright © 2007 John Wiley & Sons, Ltd.     

Occurrence of standard skies during typical daytime half-days

The current trials to introduce new daylight assessment criteria for future building designs as well as for renewable energy simulations with the trend to implement annual daylight profiles for a specific locale or region need more detail information on the exterior daylight conditions. Bratislava is the only locality in Central Europe where a CIE-IDMP general station is recording 1-min regular daylight measurements since 1994 and 10-year data gathered can be used now to derive models valid for wider regions. In this paper, the analysis of measurements and sky-type occurrence is representing daylight conditions only for this single site. As the meteorological net of observatories register sunshine duration for longer periods worldwide, also this information may serve as the basis for modelling exterior daylight illuminance courses as well as typical sky conditions when no other measurements are available. Furthermore, the new General Sky Standard adopted by CIE in 2003 and by ISO in 2004 gives the possibility to study actual skies occurring under four characteristic daylight situations associated with sunshine duration during typical half-days.     

1960-2020广东汛期降水的时空变异性分析北大核心CSCD

城市内涝等灾害会给人民生命财产和社会经济造成巨大损失,而其主要驱动因子为降水,因此科学、全面认识降水量的分布规律及发展趋势对城市防洪减灾至关重要。本文采用广东26个站点1960—2020的月降水数据,基于空间插值、Mann-Kendall检验、滑动t检验和小波分析等方法,对广东汛期降水的空间变异性、趋势性、突变点与周期性进行分析。研究表明广东按站点月降水量的峰值特征可分为四个降水类型区,各月之间、沿海与内陆降水量年际变化不同步,并阐明了前、后汛期降水高值中心与低值区的空间转移过程。按沿海/内陆-前/后汛期分组分析,对各组降水年际变化判定了趋势和显著性突变点,并识别了各个最强周期尺度下的主周期。     

Temporal variability of indoor dust concentrations of semivolatile organic compounds

The determinants of the temporal variability of indoor dust concentrations of semivolatile organic compounds (SVOCs) remain mostly unexplored. We examined temporal variability of dust concentrations and factors affecting dust concentrations for a wide range of SVOCs. We collected dust samples three times from 29 California homes during a period of 22 months and quantified concentrations of 47 SVOCs in 87 dust samples. We computed intraclass correlation coefficients (ICCs) using three samples collected within the same house. We calculated correlation coefficients (r) between two seasons with similar climate (spring and fall) and between two seasons with opposite climate (summer and winter). Among 26 compounds that were detected in more than 50% of the samples at all three visits, 20 compounds had ICCs above 0.50 and 6 compounds had ICCs below 0.50. For 19 out of 26 compounds, correlation coefficients between spring and fall (r = 0.48-0.98) were higher than those between summer and winter (r = 0.09-0.92), implying seasonal effects on dust concentrations. Our study showed that within-home temporal variability of dust concentrations was small (ICC > 0.50) for most SVOCs, but dust concentrations may vary over time for some SVOCs with seasonal variations in source rates, such as product use.     

气候变化对上海办公建筑能耗的影响分析

评估气候变化对建筑能耗的影响对于建筑节能设计具有重要意义。本文对上海2008—2017年逐时气象数据进行分析,结果表明,相对于标准气象年基准数据,空调度时数(27℃)最大值增加了206%,而采暖度日数(18℃)最小值降低了10%左右。为量化气候变化对建筑能耗的影响范围,以上海一栋采用风冷式多联机的办公建筑为研究对象,利用2008—2017年实测逐时气象数据与标准气象年数据,对比分析空调运行能耗的变化情况。研究结果表明,空调度时数增加的主要原因是7月和8月的高温天气大幅增加,该2个月建筑冷负荷最大增加63%,全年建筑负荷最大增加13%,多联机运行能耗平均增加幅度为16%~26%。     

Impacts of carbon motivated border tax adjustments on competitiveness across regions in China

China is a large developing country with high carbon intensity. It is likely that China will have to face the challenge of CBTA (carbon motivated border tax adjustments) in future. Meanwhile, CBTA would create price gap between CBTA users and target countries, and change the competitiveness of different producers. Under such circumstances, this paper seeks to contribute to the debate on CBTA by focusing on the potential impacts of CBTA on different regions of China from a perspective of competitiveness. We adopt two geographical divides in China (eastern-central-western zones, high-trade-openness to low-trade-openness regions), and simulate the potential impacts across regions through a general equilibrium model. Our simulation results show that CBTA would affect competitiveness of different producers, their comparative advantages, relative trade shares, outputs and emissions. CBTA would induce structure change of the economy, and result in a shift of industrial output toward non-industrial output. There are significant differences in the effects of CBTA among different regions in China. CBTA would result in a relocation of outputs across regions in China. Therefore, CBTA would also have impact on China’s regional development policy.     

CDLSTM: A Novel Model for Climate Change Forecasting

Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle, and municipal purposes. The changing rainfall pattern is an essential aspect of assessing the impact of climate change on water resources planning and management. Climate change affected the entire world, specifically India’s fragile Himalayan mountain region, which has high significance due to being a climatic indicator. The water coming from Himalayan rivers is essential for 1.4 billion people living downstream. Earlier studies either modeled temperature or rainfall for the Himalayan area; however, the combined influence of both in a long-term analysis was not performed utilizing Deep Learning (DL). The present investigation attempted to analyze the time series and correlation of temperature (1796–2013) and rainfall changes (1901–2015) over the Himalayan states in India. The Climate Deep Long Short-Term Memory (CDLSTM) model was developed and optimized to forecast all Himalayan states’ temperature and rainfall values. Facebook’s Prophet (FB-Prophet) model was implemented to forecast and assess the performance of the developed CDLSTM model. The performance of both models was assessed based on various performance metrics and shown significantly higher accuracies and low error rates.