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1
. "Jeugd(zorg)onderzoek: trends of trendy?" Kind en adolescent 16, no. 1 (March 1995): 37–38. http://dx.doi.org/10.1007/bf03060575.
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. "Jeugd(zorg)onderzoek: trends of trendy?" Kind en adolescent 21, no. 1 (March 2000): 36–37. http://dx.doi.org/10.1007/bf03060756.
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KOBAYASHI, Ichiro. "Verbalization of Trend Information － Verbalizing Trends －." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 22, no. 5 (2010): 562–68. http://dx.doi.org/10.3156/jsoft.22.5_562.
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Baart, Fedor, Mark van Koningsveld, and M. J. F. Stive. "Trends in Sea-Level Trend Analysis." Journal of Coastal Research 280 (March 2012): 311–15. http://dx.doi.org/10.2112/jcoastres-11a-00024.1.
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Xie, Ping, Yuxi Zhao, Yan-Fang Sang, Haiting Gu, Ziyi Wu, and Vijay P. Singh. "Gradation of the significance level of trends in precipitation over China." Hydrology Research 49, no. 6 (June 12, 2018): 1890–901. http://dx.doi.org/10.2166/nh.2018.187.
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Abstract How to accurately detect and estimate the significance level of trends in hydroclimate time series is a challenge. Building on correlation analysis, we propose an approach for evaluating and grading the significance level of trend in a series, and apply it to evaluate the changes in annual precipitation in China. The approach involved first formulating the relationship between the correlation coefficient and trend's slope. Four correlation coefficient thresholds are then determined by considering the influence of significance levels and data length, and the significance of trends is graded as five levels: no, weak, moderate, strong and dramatic. A larger correlation coefficient reflects a larger slope of trend and its higher significance level. Results of Monte-Carlo experiments indicated that the correlation coefficient-based approach not only reflects the magnitude of a trend, but also considers the influence of dispersion degree and mean value of the original series. Compared with the Mann–Kendall test used commonly, the proposed approach gave more accurate and specific gradation of the significance level of trends in annual precipitation over China. We find that the precipitation trends over China are not uniform, and the effects of global climate change on precipitation are not strong and limited to some regions.
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Ziegler, John, and Michael Gertz. "Who Is behind a Trend? Temporal Analysis of Interactions among Trend Participants on Twitter." Proceedings of the International AAAI Conference on Web and Social Media 17 (June 2, 2023): 960–69. http://dx.doi.org/10.1609/icwsm.v17i1.22203.
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Trends are a fundamental component of today's fast-evolving media landscape. Still, a lot of questions about who participates in such trends remain unanswered. Are trends driven by individual actors, or do interactions between actors reveal community structures? If so, do those structures change during the life cycle of a trend or between topically similar trends? In short: Who is behind a trend? This paper contributes to a better understanding of these questions and, in general, actor networks underlying trends on social media. As a case study, we leverage a large Twitter dataset from the EURO2020 soccer competition to detect and analyze topical trends. Our novel Gaussian fitting method allows separating trend life cycles into up- and down-trend components, as well as determining the duration of trends. An event-based evaluation proves good performance results. Given separate trend stages and topically similar trends at different points in time, we conduct a temporal analysis of the actor networks during trends. Our findings not only reveal a large overlap of participants between successive trends but also indicate large variations within a trend life cycle. Furthermore, actor networks seem to be centred around a small number of dominant users and communities. Those users also show large stability across similar trends over time. In contrast, temporally stable community structures are neither found within nor across topically similar trends.
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Rogers, Meghan L., and William Alex Pridemore. "Do National Homicide Rates Follow Supranational Trends?" Journal of Research in Crime and Delinquency 55, no. 6 (July 8, 2018): 691–727. http://dx.doi.org/10.1177/0022427818785210.
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Objectives: We explored supranational trends in national homicide rates. We searched for a global trend, regional trends, and trends specific to other theoretically relevant groups of nations. We also tested two common metanarratives—modernization and conflict—as potential explanations for any global trend present in homicide rates. Method: We obtained annual homicide victimization rates for 94 nations between 1979 and 2013. We examined year-to-year differences, squared semipartial correlation coefficients to search for supranational trends, and pooled cross-sectional mixed models to test potential explanations of any global trend. Results: There was a very weak global homicide trend. We found strong regional trends in Eastern Europe and in Northern Europe, a weak trend for South and Central America, and no trend for Asia. Both wealthy and nonwealthy nations exhibited weak trends. Transitional nations shared a strong homicide trend. Modernization and conflict theories fared poorly as explanations for the weak global trend. Conclusions: The presence or absence of supranational homicide trends holds significant implications for theory. A weak global trend is evidence against widely held metanarratives such as the modernization, civilizing, and conflict perspectives. Strong subregional homicide trends in Eastern Europe and Northern Europe demand further exploration and should shift popular attention away from Western Europe. The lack of a homicide trend in developed or developing nations and the presence of a strong trend among transitional nations are curious features requiring further consideration.
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Kolodnyi, Anatolii M. "Familiarity: Origins, trends, trends." Ukrainian Religious Studies, no. 1 (March 31, 1996): 41–43. http://dx.doi.org/10.32420/1996.1.15.
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Familiarity creates its own specific continuum of spiritual life in Ukraine, becomes a notable phenomenon in the field of Ukrainian national revival. With this phrase, we identified a group of related phenomena in the spiritual life of present-day Ukraine, based on the idea of a revival in one form or another of pre-Christian religion, which is considered by the organizers of the Homeland Movement as the authentic worldview of Ukrainians. It is impossible to call each of the currents of native religion a neo-religious denomination, because, first, some of them, by virtue of their belief-conceptions of monotheistic religions, do not accept such an assessment of themselves; and secondly, some of these trends are still not religiously determined, but exist at the level of some educational institutions, they appear in the form of peculiar clubs of interest; Thirdly, a number of them functions in a very limited religious space, consisting only of several communities and a relatively small number of followers.
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SATO, Fumika. "Research Trends: New Trend of Men's Studies." Japanese Sociological Review 61, no. 2 (2010): 186–95. http://dx.doi.org/10.4057/jsr.61.186.
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Sutton, Stuart A. "Trends, Trend Projections, and Crystal Ball Gazing." Journal of Education for Library and Information Science 42, no. 3 (2001): 241. http://dx.doi.org/10.2307/40324015.
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Kim, Young-Ki, and Seong-Taek Park. "Patent Litigation Research Trends and Trend Analysis." Journal of Computational and Theoretical Nanoscience 18, no. 5 (May 1, 2021): 1485–89. http://dx.doi.org/10.1166/jctn.2021.9609.
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The purpose of this study is to provide useful points to companies by performing an analysis about patent litigation (dispute) trends that is recently coming to the fore as an important issue and also the solution measures. In this study, network analysis method will be used. For this, data was collected from dissertation database and Twitter, and data preprocessing was conducted before performing the analysis. The data analysis was performed by applying a data analysis tool called R and a network analysis tool. First of all, the analysis results of Twitter showed that patent and dispute, Nokia, litigation and patent, coronavirus, legal, and developments appeared as important factors because of the high weight value compared to other factors. The analysis results of Scopus showed that patent and litigation, infringement, system, payment, and settlement appeared as important factors because of the high weight value compared to other factors. The results of this study can provide a practical guideline to the researchers that intend to carry out research about patent dispute and also to the persons in charge of company that need prior knowledge about patent dispute.
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Diantari, Ni Kadek Yuni. "TREND CYCLE ANALYSIS ON FAST FASHION PRODUCTS." Journal of Aesthetics, Design, and Art Management 1, no. 1 (October 20, 2021): 24–33. http://dx.doi.org/10.58982/jadam.v1i1.101.
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Purpose: trend cycles need to be understood to know the developments and changes in trends infast fashion as well as consumer considerations in consuming fast fashion products.Research methods: Trend changes in such a short time need to be analyzed further through trendstages, trend cycles, and trend differentiation that occurs in fast fashion. To analyze the trend in fastfashion products, a qualitative descriptive method was conducted in which the research processconsisted of collecting and compiling data, analyzing and interpreting phenomena.Findings: Trends provide trends in fast fashion products such as colors, styles, themes, motifs,and cuts/silhouettes. In general, fashion trends generally only recognize two seasons, includingspring/summer (spring/summer) and autumn/cold (fall and winter). Fast fashion has 52 trends in ayear or about once a week. In fast fashion, trend changes are influenced by the stages of the fashioncycle, fashion flows, trend differentiation, and trend adopters.Implications: Fast fashion is a design, manufacturing and marketing method that focuses onproducing large quantities of clothing quickly and at affordable prices. Fast fashion products arealways influenced by trends.
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Nickl, Markus. "Trends bei Anleitungen." Sprache im Beruf 5, no. 2 (2022): 226–36. http://dx.doi.org/10.25162/sprib-2022-0012.
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Li, Gen, Baohua Ren, Jianqiu Zheng, and Chengyun Yang. "Trend Singular Value Decomposition Analysis and Its Application to the Global Ocean Surface Latent Heat Flux and SST Anomalies." Journal of Climate 24, no. 12 (June 15, 2011): 2931–48. http://dx.doi.org/10.1175/2010jcli3743.1.
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Abstract Given the complexity of trends in the actual climate system, distinguishing between different trends and different trend modes is important for climate research. This study introduces a new method called “trend singular value decomposition (TSVD) analysis,” which is designed for systematically extracting coupled trend modes, albeit small, by performing an eigenanalysis of the inverse-rank covariance matrix between two fields. Applications to simple time series models and annual mean surface latent heat flux (LHF) and SST data for 1958–2006 are presented and discussed. Results show that the TSVD analysis can capture different coherent trends into different leading modes. The first TSVD mode between the global LHF and SST anomalies, similar to the first conventional SVD mode, generally represents a large-scale increasing LHF trend induced by a warming SST trend; whereas, interestingly, unlike the second SVD mode that is mainly associated with the familiar ENSO, the second TSVD mode is mainly associated with the Pacific decadal oscillation (PDO). TSVD analysis casts the (global) long-term and (Pacific) decadal trends into the leading two modes, respectively. Compared to SVD analysis, the advantages of the TSVD analysis in detecting coupled low-frequency modes are even more evident in the tropical Pacific (TP), where the coherent trend signals (i.e., the long-term trends and the decadal trends) are smaller than the ENSO-related signals. Thus, TSVD analysis performs better than SVD analysis when focusing on trends rather than on maximum covariance patterns, particularly on relatively small coherent trend patterns, such as the coupled long-term trends and decadal trends in the TP.
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Howe, David. "Adoption Trends and Counter Trends." Adoption & Fostering 11, no. 1 (April 1987): 44–46. http://dx.doi.org/10.1177/030857598701100113.
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Dietmüller, Simone, Hella Garny, Roland Eichinger, and William T. Ball. "Analysis of recent lower-stratospheric ozone trends in chemistry climate models." Atmospheric Chemistry and Physics 21, no. 9 (May 5, 2021): 6811–37. http://dx.doi.org/10.5194/acp-21-6811-2021.
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Abstract. Recent observations show a significant decrease in lower-stratospheric (LS) ozone concentrations in tropical and mid-latitude regions since 1998. By analysing 31 chemistry climate model (CCM) simulations performed for the Chemistry Climate Model Initiative (CCMI; Morgenstern et al., 2017), we find a large spread in the 1998–2018 trend patterns between different CCMs and between different realizations performed with the same CCM. The latter in particular indicates that natural variability strongly influences LS ozone trends. However none of the model simulations reproduce the observed ozone trend structure of coherent negative trends in the LS. In contrast to the observations, most models show an LS trend pattern with negative trends in the tropics (20∘ S–20∘ N) and positive trends in the northern mid-latitudes (30–50∘ N) or vice versa. To investigate the influence of natural variability on recent LS ozone trends, we analyse the sensitivity of observational trends and the models' trend probability distributions for varying periods with start dates from 1995 to 2001 and end dates from 2013 to 2019. Generally, modelled and observed LS trends remain robust for these different periods; however observational data show a change towards weaker mid-latitude trends for certain periods, likely forced by natural variability. Moreover we show that in the tropics the observed trends agree well with the models' trend distribution, whereas in the mid-latitudes the observational trend is typically an extreme value of the models' distribution. We further investigate the LS ozone trends for extended periods reaching into the future and find that all models develop a positive ozone trend at mid-latitudes, and the trends converge to constant values by the period that spans 1998–2060. Inter-model correlations between ozone trends and transport-circulation trends confirm the dominant role of greenhouse gas (GHG)-driven tropical upwelling enhancement on the tropical LS ozone decrease. Mid-latitude ozone, on the other hand, appears to be influenced by multiple competing factors: an enhancement in the shallow branch decreases ozone, while an enhancement in the deep branch increases ozone, and, furthermore, mixing plays a role here too. Sensitivity simulations with fixed forcing of GHGs or ozone-depleting substances (ODSs) reveal that the GHG-driven increase in circulation strength does not lead to a net trend in LS mid-latitude column ozone. Rather, the positive ozone trends simulated consistently in the models in this region emerge from the decline in ODSs, i.e. the ozone recovery. Therefore, we hypothesize that next to the influence of natural variability, the disagreement of modelled and observed LS mid-latitude ozone trends could indicate a mismatch in the relative role of the response of ozone to ODS versus GHG forcing in the models.
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Naaman, Mor, Hila Becker, and Luis Gravano. "Hip and trendy: Characterizing emerging trends on Twitter." Journal of the American Society for Information Science and Technology 62, no. 5 (March 7, 2011): 902–18. http://dx.doi.org/10.1002/asi.21489.
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Alashan, Sadık. "Can innovative trend analysis identify trend change points?" Brilliant Engineering 1, no. 3 (February 21, 2020): 6–15. http://dx.doi.org/10.36937/ben.2020.003.002.
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Trends in temperature series are the main cause of climate change. Because solar energy directs hydro-meteorological events and increasing variations in this resource change the balance between events such as evaporation, wind, and rainfall. There are many methods for calculating trends in a time series such as Mann-Kendall, Sen's slope estimator, Spearman's rho, linear regression and the new Sen innovative trend analysis (ITA). In addition, Mann-Kendall's variant, the sequential Mann Kendall, has been developed to identify trend change points; however, it is sensitive to related data as specified by some researchers. Şen_ITA is a new trend detection method and does not require independent and normally distributed time series, but has never been used to detect trend change points. In the literature, multiple, half-time and multi-durations ITA methods are used to calculate partial trends in a time series without identifying trend change points. In this study, trend change points are detected using the Şen_ITA method and named ITA_TCP. This approach may allow researchers to identify trend change points in a time series. Diyarbakır (Turkey) is selected as a study area, and ITA_TCP has detected trends and trends change points in monthly average temperatures. Although ITA detects only a significant upward trend in August, given the 95% statistical significance level, ITA_TCP shows three upward trends in June, July and August, and a decreasing trend in September. Critical trend slope values are obtained using the bootstrap method, which does not require the normal distribution assumption.
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Alashan, Sadık. "Can innovative trend analysis identify trend change points?" Brilliant Engineering 1, no. 3 (February 21, 2020): 6–15. http://dx.doi.org/10.36937/ben.2020.003.02.
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Trends in temperature series are the main cause of climate change. Because solar energy directs hydro-meteorological events and increasing variations in this resource change the balance between events such as evaporation, wind, and rainfall. There are many methods for calculating trends in a time series such as Mann-Kendall, Sen's slope estimator, Spearman's rho, linear regression and the new Sen innovative trend analysis (ITA). In addition, Mann-Kendall's variant, the sequential Mann Kendall, has been developed to identify trend change points; however, it is sensitive to related data as specified by some researchers. Şen_ITA is a new trend detection method and does not require independent and normally distributed time series, but has never been used to detect trend change points. In the literature, multiple, half-time and multi-durations ITA methods are used to calculate partial trends in a time series without identifying trend change points. In this study, trend change points are detected using the Şen_ITA method and named ITA_TCP. This approach may allow researchers to identify trend change points in a time series. Diyarbakır (Turkey) is selected as a study area, and ITA_TCP has detected trends and trends change points in monthly average temperatures. Although ITA detects only a significant upward trend in August, given the 95% statistical significance level, ITA_TCP shows three upward trends in June, July and August, and a decreasing trend in September. Critical trend slope values are obtained using the bootstrap method, which does not require the normal distribution assumption.
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Manaster, Andrew, Christopher W. O’Dell, and Gregory Elsaesser. "Evaluation of Cloud Liquid Water Path Trends Using a Multidecadal Record of Passive Microwave Observations." Journal of Climate 30, no. 15 (August 2017): 5871–84. http://dx.doi.org/10.1175/jcli-d-16-0399.1.
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In this study, observed cloud liquid water path (LWP) trends from the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) dataset (1988–2014) are compared to trends computed from the temporally coincident records of 16 global climate models (GCMs) participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). For many regions, observed trend magnitudes are several times larger than the corresponding model mean trend magnitudes. Muted model mean trends are thought to be the result of cancellation effects arising from differing interannual variability characteristics and differences in model physics–dynamics. In most regions, the majority of modeled trends were statistically consistent with the observed trends. This was thought to be because of large estimated errors in both the observations and the models due to interannual variability. Over the southern oceans (south of 40°S latitude), general agreement between the observed trend and virtually all GCM trends is also found (about 1–2 g m−2 decade−1). Observed trends are also compared to those from the Atmospheric Model Intercomparison Project (AMIP). Like the CMIP5 models, the majority of modeled AMIP trends were statistically consistent with the observed trends. It was also found that, in regions where the AMIP model mean time series better captures observed interannual variability, it tends to better capture the magnitude of the observed trends.
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Vorobyova, Anastasiya, Nataliya Kovalʹova, Oleksandr Yurchenko, and Volodymyr Kovalʹov. "FITNESS TRENDS 2020." Sports Bulletin of the Dnieper 1 (2020): 230–37. http://dx.doi.org/10.32540/2071-1476-2019-1-230.
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Introduction. The fitness industry is one of the fastest growing spheres with quick-paced fashion on different kinds of fitness. Fitness centers or clubs, as well as fitness trainers, to stay competitive should know about new tendencies and even predict them. To help them researchers from different countries are conducting surveys to find fitness trends for the next year. In 2019 more regions join to research. Material and methods. The research is based on the analysis of sources of literature and experts’ thoughts. In the worldwide survey took part 3037 specialists from more than 40 countries; in the European – 1001 specialists from 40 countries. Experts' opinions on the development of the fitness industry have been analyzed in Ukraine. Results. Comparison of the worldwide and European trends-2020 made it possible to find as similar tendencies (16 positions from 20), as well as differences between these regions. However, ranking of top-20 trends in every region is absolutely different. For example, wearable technology – the trend, which is on the first place of worldwide survey, but on the 18th place in Europe. As in Ukraine no such studies have been conducted, the analysis of experts' opinions has allowed us to identify the main trends in the development of the fitness industry. In Ukraine, only 2.9% of the population is involved in fitness, and therefore there are significant prospects for the industry. Experts agree that fitness in small cities should be developed. Conclusions. Comparison of world and European fitness trends suggests that mentally Ukraine is closer to European trends, but the forecasts of Ukrainian fitness experts differ significantly from both world and European ones, so there is a need for a national survey to determine Ukraine's fitness trends. Keywords: fitness, trend, development, perspective, world trends, national trends, European trends.
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Osinowo, Adekunle, Xiaopei Lin, Dongliang Zhao, and Zhifeng Wang. "Long-Term Variability of Extreme Significant Wave Height in the South China Sea." Advances in Meteorology 2016 (2016): 1–21. http://dx.doi.org/10.1155/2016/2419353.
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This paper describes long-term spatiotemporal trends in extreme significant wave height (SWH) in the South China Sea (SCS) based on 30-year wave hindcast. High-resolution reanalysis wind field data sets are employed to drive a spectral wave model WAVEWATCH III™ (WW3). The wave hindcast information is validated using altimeter wave information (Topex/Poseidon). The model performance is satisfactory. Subsequently, the trends in yearly/seasonal/monthly mean extreme SWH are analyzed. Results showed that trends greater than 0.05 m yr−1are distributed over a large part of the central SCS. During winter, strong positive trends (0.07–0.08 m yr−1) are found in the extreme northeast SCS. Significant trends greater than 0.01 m yr−1are distributed over most parts of the central SCS in spring. In summer, significant increasing trends (0.01–0.05 m yr−1) are distributed over most regions below latitude 16°N. During autumn, strong positive trends between 0.02 and 0.08 m yr−1are found in small regions above latitude 12°N. Increasing positive trends are found to be generally significant in the central SCS in December, February, March, and July. Furthermore, temporal trend analysis showed that the extreme SWH exhibits a significant increasing trend of 0.011 m yr−1. The extreme SWH exhibits the strongest increasing trend of 0.03 m yr−1in winter and showed a decreasing trend of −0.0098 m yr−1in autumn.
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Rinke, A., B. Segger, S. Crewell, M. Maturilli, T. Naakka, T. Nygård, T. Vihma, et al. "Trends of Vertically Integrated Water Vapor over the Arctic during 1979–2016: Consistent Moistening All Over?" Journal of Climate 32, no. 18 (August 21, 2019): 6097–116. http://dx.doi.org/10.1175/jcli-d-19-0092.1.
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Abstract Arctic trends of integrated water vapor were analyzed based on four reanalyses and radiosonde data over 1979–2016. Averaged over the region north of 70°N, the Arctic experiences a robust moistening trend that is smallest in March (0.07 ± 0.06 mm decade−1) and largest in August (0.33 ± 0.18 mm decade−1), according to the reanalyses’ median and over the 38 years. While the absolute trends are largest in summer, the relative ones are largest in winter. Superimposed on the trend is a pronounced interannual variability. Analyzing overlapping 30-yr subsets of the entire period, the maximum trend has shifted toward autumn (September–October), which is related to an accelerated trend over the Barents and Kara Seas. The spatial trend patterns suggest that the Arctic has become wetter overall, but the trends and their statistical significance vary depending on the region and season, and drying even occurs over a few regions. Although the reanalyses are consistent in their spatiotemporal trend patterns, they substantially disagree on the trend magnitudes. The summer and the Nordic and Barents Seas, the central Arctic Ocean, and north-central Siberia are the season and regions of greatest differences among the reanalyses. We discussed various factors that contribute to the differences, in particular, varying sea level pressure trends, which lead to regional differences in moisture transport, evaporation trends, and differences in data assimilation. The trends from the reanalyses show a close agreement with the radiosonde data in terms of spatiotemporal patterns. However, the scarce and nonuniform distribution of the stations hampers the assessment of central Arctic trends.
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Rathnayake, Upaka. "Comparison of Statistical Methods to Graphical Methods in Rainfall Trend Analysis: Case Studies from Tropical Catchments." Advances in Meteorology 2019 (September 2, 2019): 1–10. http://dx.doi.org/10.1155/2019/8603586.
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Time series analyses for climatic factors are important in climate predictions. Rainfall is being one of the most important climatic factors in today’s concern for future predictions; thus, many researchers analyze the data series for identifying potential rainfall trends. The literature shows several methods in identifying rainfall trends. However, statistical trend analysis using Mann–Kendall equation and graphical trend analysis are the two widely used and simplest tests in trend analysis. Nevertheless, there are few studies in comparing various methods in the trend analysis to suggest the simplest methods in analyzing rainfall trends. Therefore, this paper presents a comparison analysis of statistical and graphical trend analysis techniques for two tropical catchments in Sri Lanka. Results reveal that, in general, both trend analysis techniques produce comparable results in identifying rainfall trends for different time steps including annual, seasonal, and monthly rainfalls.
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Cetron, Marvin J., Owen Davies, Fred DeMicco, and Mohan Song. "Shaping the future of hospitality and travel: trends in energy, environmental, and labor force and work." International Hospitality Review 34, no. 2 (July 16, 2020): 129–52. http://dx.doi.org/10.1108/ihr-03-2020-0007.
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PurposeThe purpose of this study is to continue to forecast trends in the hospitality and travel industry with practical implications.Design/methodology/approachThis study is the updated version of our previous list of trends. The new edition updates the previous report on the implications for the hospitality industry of major trends now shaping the future. We focus mainly on energy, environmental and labor force and work trends and discuss sub-trends under each trend. We then implicate how the trends affect the Hospitality and Travel industry.FindingsWe shared implications under each sub-trends.Originality/valueThe value of this article is to analyze the impact of the environment on the Hospitality and Travel industry from a macro perspective. For each trend, we implicate an estimate for future trends. We hope this article sheds light on the prediction of the Hospitality and Travel industry.
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Vogel, R. M., A. Rosner, and P. H. Kirshen. "Brief communication "Likelihood of societal preparedness for global change"." Natural Hazards and Earth System Sciences Discussions 1, no. 1 (January 28, 2013): 1–13. http://dx.doi.org/10.5194/nhessd-1-1-2013.
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Abstract. Anthropogenic influences on earth system processes are now pervasive, resulting in trends in river discharge, pollution levels, ocean levels, precipitation, temperature, wind, landslides, bird and plant populations and a myriad of other important natural hazards relating to earth system state variables. Thousands of trend detection studies have been published which report the statistical significance of observed trends. Unfortunately, such studies only concentrate on the null hypothesis of "no trend". Little or no attention is given to the power of such statistical trend tests, which would quantify the likelihood that we might ignore a trend if it really existed. The probability of missing the trend if it exists, known as the type II error, informs us about the likelihood of whether or not society is prepared to accommodate and respond to such trends. We describe how the power or probability of detecting a trend if it exists, depends critically on our ability to develop improved multivariate deterministic and statistical methods for predicting future trends in earth system processes. Several other research and policy implications for improving our understanding of trend detection and our societal response to those trends are discussed.
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Vogel, R. M., A. Rosner, and P. H. Kirshen. "Brief Communication: Likelihood of societal preparedness for global change: trend detection." Natural Hazards and Earth System Sciences 13, no. 7 (July 11, 2013): 1773–78. http://dx.doi.org/10.5194/nhess-13-1773-2013.
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Abstract. Anthropogenic influences on earth system processes are now pervasive, resulting in trends in river discharge, pollution levels, ocean levels, precipitation, temperature, wind, landslides, bird and plant populations and a myriad of other important natural hazards relating to earth system state variables. Thousands of trend detection studies have been published which report the statistical significance of observed trends. Unfortunately, such studies only concentrate on the null hypothesis of "no trend". Little or no attention is given to the power of such statistical trend tests, which would quantify the likelihood that we might ignore a trend if it really existed. The probability of missing the trend, if it exists, known as the type II error, informs us about the likelihood of whether or not society is prepared to accommodate and respond to such trends. We describe how the power or probability of detecting a trend if it exists, depends critically on our ability to develop improved multivariate deterministic and statistical methods for predicting future trends in earth system processes. Several other research and policy implications for improving our understanding of trend detection and our societal response to those trends are discussed.
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Ishola, Bunmi. "Lit Trends: Diversifying Bookshelves: From Trend to Norm." World Literature Today 94, no. 4 (2020): 9. http://dx.doi.org/10.1353/wlt.2020.0222.
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Ishola. "Lit Trends: Diversifying Bookshelves: From Trend to Norm." World Literature Today 94, no. 4 (2020): 9. http://dx.doi.org/10.7588/worllitetoda.94.4.0009.
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Rech, Jörg. "Discovering trends in software engineering with google trend." ACM SIGSOFT Software Engineering Notes 32, no. 2 (March 2007): 1–2. http://dx.doi.org/10.1145/1234741.1234765.
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Agar, Michael, and Heather Schacht Reisinger. "Using Trend Theory to Explain Heroin Use Trends." Journal of Psychoactive Drugs 33, no. 3 (September 2001): 203–11. http://dx.doi.org/10.1080/02791072.2001.10400567.
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Li, Geng, Zhankun Wang, and Binbin Wang. "Multidecade Trends of Sea Surface Temperature, Chlorophyll-a Concentration, and Ocean Eddies in the Gulf of Mexico." Remote Sensing 14, no. 15 (August 5, 2022): 3754. http://dx.doi.org/10.3390/rs14153754.
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This study characterizes the spatial patterns of the overall and monthly trends in sea surface temperature (SST) and chlorophyll-a (Chl-a) of the Gulf of Mexico (GoM) to investigate the seasonal variations in oceanic climate trends. We also investigate the trends in mesoscale eddies using three parameters to identify ocean-eddy-related energetic features in their area, strength, and intensity. Multidecadal remote-sensing-based observations of monthly SST, Chl-a, and sea surface height are used to detect trends at both basin and grid scales. Prominent warming trends are found in most regions of the GoM in all months, with the largest trends in the northern GoM. Winter cooling trends are also detected along the Texas and Florida coast. The overall summer warming trend (~0.22 °C/decade) is larger than the winter trend (~0.05 °C/decade), suggesting seasonal variations of increase in SST with warming. Chl-a trends and variations are confined on the continental shelf and slope in the northern GoM. The largest increase trends are found near the Mississippi River Delta. No obvious Chl-a trend is detected in the deepwater of the GoM, consistent with previous studies. Small but significant changes are found in eddy characteristics, indicating the eddy activities might be slowly affected by climate change in the GoM. The detailed monthly trends at per-grid scale are valuable for regional resource management, environmental protection, and policy making in the GoM.
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Carson, Mark, and D. E. Harrison. "Is the Upper Ocean Warming? Comparisons of 50-Year Trends from Different Analyses*." Journal of Climate 21, no. 10 (May 15, 2008): 2259–68. http://dx.doi.org/10.1175/2007jcli2002.1.
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Abstract There is great interest in World Ocean temperature trends, yet the historical global ocean database has very uneven coverage in space and time. Previous work on 50-yr upper ocean temperature trends from the NOAA ocean data archive is extended here. Trends at depths from 50 to 1000 m are examined, based on observations gridded over larger regions than in the earlier study. Despite the use of larger grid boxes, most of the ocean does not have significant 50-yr trends at the 90% confidence level (CL). In fact only 30% of the ocean at 50 m has 90% CL trends, and the percentage decreases significantly with increasing depth. As noted in the previous study, there is much spatial structure in 50-yr trends, with areas of strong warming and strong cooling. These trend results are compared with trends calculated from data interpolated to standard levels and from a highly horizontally interpolated version of the dataset that has been used in previous heat content trend studies. The regional trend results can differ substantially, even in the areas with statistically significant trends. Trends based on the more interpolated analyses show more warming. Together with major temporal and spatial sampling limitations, the previously described strong interdecadal and spatial variability of trends makes it very difficult to formally estimate uncertainty in World Ocean averages, but these results suggest that upper ocean heat content integrals and integral trends may be substantially more uncertain than has yet been acknowledged. Further exploration of uncertainties is needed.
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Huang, Shih-Han, Khalid Mahmud, and Chia-Jeng Chen. "Meaningful Trend in Climate Time Series: A Discussion Based On Linear and Smoothing Techniques for Drought Analysis in Taiwan." Atmosphere 13, no. 3 (March 9, 2022): 444. http://dx.doi.org/10.3390/atmos13030444.
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Finding significant trends in hydroclimate time series has been deemed an essential task in numerous studies. Despite the existence of various trend detection methods, statistical significance is mostly examined for linear trends and related to the meaningfulness of the found trends. We wish to draw attention to a more general definition of meaningful trends by cross-referencing not only linear but also smoothing techniques. We apply linear regression (LR) and two smoothing techniques based on regularized minimal-energy tensor-product B-splines (RMTB) to the trend detection of standardized precipitation index (SPI) series over Taiwan. LR and both RMTB-based methods identify an overall upward (wetting) trend in the SPI series across the time scales in Taiwan from 1960 to 2019. However, if dividing the entire time series into the earlier (1960–1989) and later (1990–2019) sub-series, we find that some downward (drying) trends at varied time scales migrate from southcentral–southwestern to eastern regions. Among these significant trends, we have more confidence in the recent drying trend over eastern Taiwan since all the methods show trend patterns in highest similarity. We also argue that LR should be used with great caution, unless linearity in data series and independence and normality in residuals can be assured.
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Blancher, Peter J., R. Dean Phoenix, Debra S. Badzinski, Michael D. Cadman, Tara L. Crewe, Constance M. Downes, Don Fillman, et al. "Population trend status of Ontario’s forest birds." Forestry Chronicle 85, no. 2 (March 1, 2009): 184–201. http://dx.doi.org/10.5558/tfc85184-2.
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Recent population trends of Ontario’s forest birds were assessed by integrating results across 8 bird surveys to provide an estimate of trend status for all of Ontario, and for 2 forested regions of Ontario separately. Surveys with mid- and longterm trends were relied on most extensively in this assessment. Comparison of the first and second Breeding Bird Atlases was especially important for estimating trends in northern forests, but overall reliability of status assessments in the north was considered poor due to limited coverage and significant potential for bias. Trends of most forest birds were stable or positive at the Ontario-wide scale, with trends at least as positive as forest birds elsewhere in North America, and showing more positive trends overall than birds of agricultural landscapes. Nevertheless, individual species trends ranged from large declines to large increases, and several forest birds have been added to Species at Risk lists largely because of population declines. There were few differences in trend status among forest birds grouped by habitat association or migratory guild, although all 5 aerial insectivore species have declined. Better monitoring coverage of the boreal will be needed if improved reliability of trends is desired in the near future. Key words: Ontario, forest birds, boreal forest, population trend, bird surveys, monitoring reliability
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Halil Ibrahim Burgan. "The Short-Term and Seasonal Trend Detection of Sediment Discharges in Turkish Rivers." Rocznik Ochrona Środowiska 24 (2022): 214–30. http://dx.doi.org/10.54740/ros.2022.016.
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Hydrometeorological variables are tested by trend methods to be able to detect trends in river basins. Mann-Kendall, Spearman’s rho tests are widely used as traditional trend methods. Besides that, some new trend tests are applied to hydrometeorological variables as Innovative Trend Analysis (ITA). Sediment discharge observations are more difficult than other hydrometeorological variables. In general, sediment data are observed in monthly time scale. Therefore, there are very limited studies on sediment data, especially in Turkey. In this study, Innovative Trend Analysis (ITA), Mann-Kendall, Correlated Mann-Kendall and Seasonal Mann-Kendall trend analyses are applied to sediment discharges in Turkish river basins. According to Mann-Kendall, Correlated Mann-Kendall and Seasonal Mann Kendall results, positive trends have detected only 8, 2 and 20 gauging stations, respectively. Then, 30 positive and 15 negative trends by ITA methodology. The trend slopes calculated from ITA methodology are categorized because some positive and negative of trends are weak. The applied trend methods are evaluated together considering climate properties of hydrological regions in Turkey. Increasing trends on sediment data are detected from the rivers from Mediterranean region of Turkey. The results of the study would help to manage water resources as well as sustainable development in the Turkish river basins.
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Manikandan, M., M. Nagarajan, and N. Anandaraj. "Evaluation of Historic Trends for Monthly, Seasonal, and Annual Rainfall Series of Tenkasi, Tamil Nadu, India." International Journal of Environment and Climate Change 14, no. 2 (February 17, 2024): 590–600. http://dx.doi.org/10.9734/ijecc/2024/v14i23974.
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Analyzing the variability and trends of rainfall plays a major role in water resource planning and management. Changes in rainfall patterns significantly influence the water availability in the irrigation structures and agronomical practices of crops. This study aimed to investigate the trends and estimate the magnitudes of monthly, seasonal, and annual rainfall series in Tenkasi, Tamil Nadu, India, using 49 years of rainfall data from 1971 to 2019. Sen’s Innovative trend analysis (ITA) method, Mann-Kendall (MK), and Simple Linear Regression (SLR) test were applied to assess the trends at 5 and 10 % significance levels. Trend magnitudes were estimated by Sen’s slope estimator (SSE) and SLR method. Changes in rainfall magnitude with mean values in percentage were estimated for all three slope estimation methods. The results revealed that the ITA method detected more significant trends of rainfall series over other methods. Significant downward trends were exhibited by October and north east monsoon (NEM) rainfall series had a trend magnitude of -0.43 mm/year and -0.04 mm/year. The percentage change in magnitude of the trend from mean values for October and the NEM series was -11.5% and -0.39%. Sub-trends within the October and NEM rainfall series showed that the low rainfall sub-series exhibited no trend, medium and high rainfall sub-series showed a downward trend. This study concluded that, in comparison to traditional trend analysis methods, the ITA method demonstrated a more rigorous investigation of trends. The significant decrease in rainfall during the NEM necessitates greater attention to water resources planning and management, serving as valuable scientific information for both crop planning and water resource management.
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McClure, Crystal D., and Daniel A. Jaffe. "US particulate matter air quality improves except in wildfire-prone areas." Proceedings of the National Academy of Sciences 115, no. 31 (July 16, 2018): 7901–6. http://dx.doi.org/10.1073/pnas.1804353115.
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Using data from rural monitoring sites across the contiguous United States, we evaluated fine particulate matter (PM2.5) trends for 1988–2016. We calculate trends in the policy-relevant 98th quantile of PM2.5 using Quantile Regression. We use Kriging and Gaussian Geostatistical Simulations to interpolate trends between observed data points. Overall, we found positive trends in 98th quantile PM2.5 at sites within the Northwest United States (average 0.21 ± 0.12 µg·m−3·y−1; ±95% confidence interval). This was in contrast with sites throughout the rest of country, which showed a negative trend in 98th quantile PM2.5, likely due to reductions in anthropogenic emissions (average −0.66 ± 0.10 µg·m−3·y−1). The positive trend in 98th quantile PM2.5 is due to wildfire activity and was supported by positive trends in total carbon and no trend in sulfate across the Northwest. We also evaluated daily moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) for 2002–2017 throughout the United States to compare with ground-based trends. For both Interagency Monitoring of Protected Visual Environments (IMPROVE) PM2.5 and MODIS AOD datasets, we found positive 98th quantile trends in the Northwest (1.77 ± 0.68% and 2.12 ± 0.81% per year, respectively) through 2016. The trend in Northwest AOD is even greater if data for the high-fire year of 2017 are included. These results indicate a decrease in PM2.5 over most of the country but a positive trend in the 98th quantile PM2.5 across the Northwest due to wildfires.
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Forootan, Elham. "Analysis of trends of hydrologic and climatic variables." Soil and Water Research 14, No. 3 (May 27, 2019): 163–71. http://dx.doi.org/10.17221/154/2018-swr.
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Assessing trends of hydrologic variables related to both hydrologic processes facilitates accurate water resources forecasting, especially in arid and semiarid regions with high evaporation and low rainfall volume. In this study, spatial and temporal trends of six hydrologic and climatic variables, viz. rainfall, evaporation, streamflow discharge, temperature, wind speed and relative humidity and also the ratio of annual potential evaporation to precipitation (E/P) were analysed at a monthly and annual scale. Moreover, the relationship of relative humidity, temperature, rainfall and wind speed trends with evaporation trend was investigated. Results of the study revealed the absence of significant temporal trend in precipitation, temperature and wind velocity for the majority of months, and the presence of upward trends in relative humidity and evaporation values as well as downward trend in streamflow discharge in some months. At an annual scale increasing evaporation and decreasing stream flow discharge trends were observed at most stations, which means that the region will be confronted with more severe drought conditions in future. Also, the result of Spearman’s rank coefficient revealed that the temporal evaporation trend is not related to wind speed, temperature, relative humidity and rainfall trend. Moreover, the spatial trend of climatic and hydrologic variables indicated the similarity of evaporation and relative humidity trend as well as wind speed and rainfall trend.
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Soni, Pramod. "The Impact of Data Uncertainty on Identifying Precipitation Trends in India." MAUSAM 75, no. 3 (June 28, 2024): 895–904. http://dx.doi.org/10.54302/mausam.v75i3.6300.
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The study investigates the effect of missing data, variability, and measurement errors on precipitation data in India, as well as the potential errors in trend analysis that result from neglecting these factors. Daily rainfall data and RSTN (ratio of station grids) for the entire country from 1951 to 2015 were obtained from APHRODITE and used both simple and weighted linear regression to estimate trends. The findings of the simple linear regression indicated that on an annual scale, roughly 1489 grids (31% significant at the 95% confidence level) displayed positive trends, whereas 3150 grids (57% significant at the 95% confidence level) exhibited negative trends. In contrast, using the WLR method, a total of 2274 grids displayed positive trends, and 2365 grids showed negative trends, with approximately 25-30% of the grids having significant trends at an annual timescale. Overall, approximately 86% of positive trends and 68% of negative trends remained unchanged when using the WLR method instead of the LR method, respectively. However, approximately 23-26% of significant positive trends and about 46% of significant negative trends in the LR method were converted to non-significant trends in the WLR method. Moreover, only approximately 0.5% of positive significant trends and 2-3% of negative significant trends reversed to significant negative and positive trends, respectively. The study emphasizes the importance of considering missing records and data variability over time to obtain accurate trend analysis.
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Knowles, Noah. "Trends in Snow Cover and Related Quantities at Weather Stations in the Conterminous United States." Journal of Climate 28, no. 19 (September 29, 2015): 7518–28. http://dx.doi.org/10.1175/jcli-d-15-0051.1.
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Abstract Trend tests, linear regression, and canonical correlation analysis were used to quantify changes in National Weather Service Cooperative Observer (COOP) snow depth data and derived quantities, precipitation, snowfall, and temperature over the study period 1950–2010. Despite widespread warming, historical trends in snowfall and snow depth are generally mixed owing to competing influences of trends in precipitation. Trends toward later snow-cover onset in the western half of the conterminous United States and earlier onset in the eastern half and a widespread trend toward earlier final meltoff of snow cover combined to produce trends toward shorter snow seasons in the eastern half of the United States and in the west and longer snow seasons in the Great Plains and southern Rockies. The annual total number of days with snow cover exhibited a widespread decline. Monthly trend patterns show the dominant influence of temperature trends on occurrence of snow cover in the warmer snow-season months and a combination of temperature and precipitation trends in the colder months. A canonical correlation analysis indicated that most trends presented here took hold in the 1970s, consistent with the temporal pattern of global warming during the study period.
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Dræge, Anders. "Geo-consistent depth trends: Honoring geology in siliciclastic rock-physics depth trends." Leading Edge 38, no. 5 (May 2019): 379–84. http://dx.doi.org/10.1190/tle38050379.1.
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A new method for modeling rock-physics depth trends called “geo-consistent depth trend modeling” is presented. No new rock-physics models are developed in this work, but existing models are put together in a new workflow. The workflow integrates rock-physics modeling with petrologic porosity models that account for burial, pressure, and temperature history. The new approach honors geologic trends, patterns, and cyclicity in the rocks. Examples based on well data are given to show how depositional trends can influence seismic response and depth trends. Geo-consistent depth trends are compared with the standard method for rock-physics depth trends, and differences are discussed. Geo-consistent depth trends can contribute to increased understanding of the subsurface and give input to risking of targets in exploration.
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Rasul, Azad, Sa’ad Ibrahim, Ajoke R. Onojeghuo, and Heiko Balzter. "A Trend Analysis of Leaf Area Index and Land Surface Temperature and Their Relationship from Global to Local Scale." Land 9, no. 10 (October 12, 2020): 388. http://dx.doi.org/10.3390/land9100388.
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Although the way in which vegetation phenology mediates the feedback of vegetation to climate systems is now well understood, the magnitude of these changes is still unknown. A thorough understanding of how the recent shift in phenology may impact on, for example, land surface temperature (LST) is important. To address this knowledge gap, it is important to quantify these impacts and identify patterns from the global to the regional scale. This study examines the trend and linear regression modeling of the leaf area index (LAI) and LST derived from the moderate resolution imaging spectroradiometer (MODIS) data, specifically to assess their spatial distribution and changing trends at the continental and regional scales. The change detection analysis of interannual variability in the global LAI and LST between two periods (2003–2010 and 2011–2018) demonstrates more positive LAI trends than negative, while for LST most changes were not significant. The relationships between LAI and LST were assessed across the continents to ascertain the response of vegetation to changes in LST. The regression between LAI and LST was negative in Australia (R2 = 0.487 ***), positive but minimal in Africa (R2 = 0.001), positive in North America (R2 = 0.641 ***), negative in Central America (R2 = 0.119), positive in South America (R2 = 0.253 *) and positive in Europe (R2 = 0.740 ***). Medium temperatures enhance photosynthesis and lengthen the growing season in Europe. We also found a significant greening trend in China (trendp = 0.16 ***) and India (trendp = 0.13 ***). The relationships between LAI and LST in these most prominent greening countries of the world are R2 = 0.06 and R2 = 0.25 for China and India, respectively. Our deductions here are twofold—(1) In China, an insignificant association appeared between greening trend and temperature. (2) In India, the significant greening trend may be a factor in lowering temperatures. Therefore, temperature may stabilize if the greening trend continues. We attribute the trends in both countries to the different land use management and climate mitigation policies adopted by these countries.
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Franzke, Christian. "Nonlinear Trends, Long-Range Dependence, and Climate Noise Properties of Surface Temperature." Journal of Climate 25, no. 12 (June 15, 2012): 4172–83. http://dx.doi.org/10.1175/jcli-d-11-00293.1.
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Abstract This study investigates the significance of trends of four temperature time series—Central England Temperature (CET), Stockholm, Faraday-Vernadsky, and Alert. First the robustness and accuracy of various trend detection methods are examined: ordinary least squares, robust and generalized linear model regression, Ensemble Empirical Mode Decomposition (EEMD), and wavelets. It is found in tests with surrogate data that these trend detection methods are robust for nonlinear trends, superposed autocorrelated fluctuations, and non-Gaussian fluctuations. An analysis of the four temperature time series reveals evidence of long-range dependence (LRD) and nonlinear warming trends. The significance of these trends is tested against climate noise. Three different methods are used to generate climate noise: (i) a short-range-dependent autoregressive process of first order [AR(1)], (ii) an LRD model, and (iii) phase scrambling. It is found that the ability to distinguish the observed warming trend from stochastic trends depends on the model representing the background climate variability. Strong evidence is found of a significant warming trend at Faraday-Vernadsky that cannot be explained by any of the three null models. The authors find moderate evidence of warming trends for the Stockholm and CET time series that are significant against AR(1) and phase scrambling but not the LRD model. This suggests that the degree of significance of climate trends depends on the null model used to represent intrinsic climate variability. This study highlights that in statistical trend tests, more than just one simple null model of intrinsic climate variability should be used. This allows one to better gauge the degree of confidence to have in the significance of trends.
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Kumar, Sourabh, and Saurabh Sharma. "Equine Hydrotherapy: Recent Trends." Journal of Cardiovascular Medicine and Surgery 2, no. 2 (2016): 45–48. http://dx.doi.org/10.21088/jcms.2454.7123.2216.1.
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ȘTEFAN, Carmen. "TRENDS IN PILOTS TRAINING." Review of the Air Force Academy 15, no. 3 (December 14, 2017): 119–24. http://dx.doi.org/10.19062/1842-9238.2017.15.3.14.
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Rajalakshmi, S. "Crime Trends among Youth." International Journal of Research in Arts and Science 2, no. 2 (April 30, 2016): 07–10. http://dx.doi.org/10.9756/ijras.8123.
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Bhatia, Rinky. "Servitization: A Global Trends." Global Journal For Research Analysis 3, no. 1 (June 15, 2012): 48–49. http://dx.doi.org/10.15373/22778160/january2014/35.
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Edyvean, Robert GJ. "Market Trends in Biofuel." Open Access Journal of Agricultural Research 8, no. 3 (2023): 1–6. http://dx.doi.org/10.23880/oajar-16000311.
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Biofuels, (ethanol and biodiesel primarily derived from corn, sugarcane and vegetable oils) are a growing area of renewable energy. For example, in the transport sector ethanol can be used in suitable internal combustion engines or blended with petrol while biodiesel can be used in diesel vehicles with little engine alteration. This study looked at biofuel supply and demand in a number of countries as it recovers from the 2019-2022 COVID-19 pandemic and found that demand fluctuated over this period since external factors which influence oil prices, have a greater effect on the smaller, and mostly newer, biofuel industry. Such fluctuations would happen with any major shift in energy resources but have been exacerbated by the pandemic and recent conflicts. While governments must evaluate the role of biofuels in energy security, food security and GHG objectives in a changing political and financial environment, there are countries where they can play a significant role in the energy supply. How Governments might look longer term to pave the way to a “new normal” energy base is discussed.
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Qi, Li, and Yuqing Wang. "Changes in the Observed Trends in Extreme Temperatures over China around 1990." Journal of Climate 25, no. 15 (August 1, 2012): 5208–22. http://dx.doi.org/10.1175/jcli-d-11-00437.1.
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Abstract Based on the daily temperature data from weather stations in China, linear trends of the seasonal mean and extreme temperatures in summer and winter are analyzed and compared for the periods of 1960–89 and 1990–2009. The results show prominent changes in those trends since the early 1990s, in particular in winter—a signal of climate shift as previously identified. The changes, however, are found to be strongly region dependent. In summer, both seasonal mean and extreme temperatures show a considerable cooling trend in central China and a warming trend in north and south China before 1990. After 1990 all temperature indices show significant warming trends throughout China with the largest trend up to 4.47°C (10 yr)−1 in north China. In winter in north China, with the most prominent warming trend during 1960–89, there is a significant cooling trend in both the seasonal mean temperature and the cold temperature indices after 1990. The warming trends over the Tibetan Plateau are substantially enhanced since 1990. All indices for the diurnal temperature range (DTR) show consistent decreasing trends in both summer and winter throughout China before 1990 while they turn to increasing trends in northeast China in summer and over the Tibetan Plateau in winter after 1990. The annual temperature range displays a decreasing trend throughout China before 1990 while it is dominated by an increasing trend after 1990 except over the Tibetan Plateau and in a narrow band along the Yangtze River. Possible mechanisms for the observed trend changes are discussed.