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Regional features of pollen R-values in China

Science China Earth Sciences 2024年第1期67卷 295-308页

作者： Jie XIA Jian NI College of Life Sciences Zhejiang Normal UniversityJinhua 321004China Jinhua Mountain Observation and Research Station for Subtropical Forest Ecosystems Jinhua 321004China

Establishing a quantitative relationship between modern pollen and vegetation remains a pivotal but intricate pursuit within the field of Quaternary palynology.The R-value,a well-established and traditional metric characterized by its simplicity and direct applicability,serves to calibrate the nonlinear disparities between surface pollen and modern vegetation.This study entails the construction of a comprehensive pollen R-value dataset for China derived from R-values published between 1987 and 2021.The dataset,compiled after rigorous screening,calibration,and standardization processes,encompasses 898 modern pollen sampling sites and 2115 pollen R-value data entries,encapsulating 152 pollen taxa spanning 65 families and 113 genera.Synthesizing the extracted R-values yielded the following insights:(1)A macrospatial analysis validates previously established knowledge at a site-specific scale.Evidently,pollen R-value variations across China are statistically significant.Approximately two-thirds of pollen taxa exhibit underrepresentation(e.g.,Taxodiaceae,Corylus,Nitraria,Tamarix,Cyperaceae,Poaceae,and Fabaceae),while the remaining one-third display overrepresentation(e.g.,Pinus,Picea,Betula,Ephedra,Chenopodiaceae,and Artemisia).The degree of underrepresentation surpasses that of overrepresentation,and the representation patterns of Castanea,Quercus,Polygonaceae,and Asteraceae are contingent upon vegetation types.(2)Pollen R-values follow distinct spatial distribution patterns within China.In the woody vegetation region of eastern China,R-values progressively decline from north to south,correlating with rising temperatures and precipitation.Conversely,in herbaceous vegetation regions of northern and western China,R-values decrease from east to west and from northeast to southwest,corresponding to increased aridity.Nevertheless,pollen R-values manifest variation contingent on pollen taxa,vegetation types,and climatic regions,even differing for the same taxa across varying vegetation types and climatic conditions.This hi

关键词： Pollen R-value Modern pollen-vegetation relationship Regional pattern variability Paleovegetation reconstruction

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Application of Predictive Model for Efficient Cassava (Manihot esculenta Crantz) Yield in the Face of Climate variability in Enugu State, Nigeria

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American Journal of Climate Change 2024年第2期13卷 361-389页

作者： Emeka Bright Ogbuene Tonia Nkiru Nwobodo Obianuju Gertrude Aloh Achoru Fred Emeka Josiah C. Ogbuka Vivian Amarachi Ozorme Andrew M. Oroke Obiageli Jacinta Okolo Anwara Obianuju Amara E. S. Enemuo Centre for Environmental Management and Control (CEMAC) University of Nigeria Nsukka Nigeria Department of Geography University of Nigeria Nsukka Nigeria Department of Geography and Meteorology Enugu State University of Science and Technology (ESUT) Enugu Nigeria School of Civil Engineering Newcastle University Newcastle upon Tyne UK

Climate variability as occasioned by conditions such as extreme rainfall and temperature, rainfall cessation, and irregular temperatures has considerable impact on crop yield and food security. This study develops a predictive model for cassava yield (Manihot esculenta Crantz) amidst climate variability in rainfed zone of Enugu State, Nigeria. This study utilized data of climate variables and tonnage of cassava yield spanning from 1971 to 2012;as well as information from a questionnaire and focus group discussion from farmers across two seasons in 2023 respectively. Regression analysis was employed to develop the predictive model equation for seasonal climate variability and cassava yield. The rainfall and temperature anomalies, decadal change in trend of cassava yield and opinion of farmers on changes in rainfall season were also computed in the study. The result shows the following relationship between cassava and all the climatic variables: R2 = 0.939;P = 0.00514;Cassava and key climatic variables: R2 = 0.560;P = 0.007. The result implies that seasonal rainfall, temperature, relative humidity, sunshine hours and radiation parameters are key climatic variables in cassava production. This is supported by computed rainfall and temperature anomalies which range from −478.5 to 517.8 mm as well as −1.2˚C to 2.3˚C over the years. The questionnaire and focus group identified that farmers experienced at one time or another, late onset of rain, early onset of rain or rainfall cessation over the years. The farmers are not particularly sure of rainfall and temperature characteristics at any point in time. The implication of the result of this study is that rainfall and temperature parameters determine the farming season and quantity of productivity. Hence, there is urgent need to address the situation through effective and quality weather forecasting network which will help stem food insecurity in the study area and Nigeria at large. The study made recommendations such as a comprehensive early warning system on climate va

关键词： Climate variability Cassava (Manihot esculenta Crantz) Predictive Model Yield

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Characteristics of Extreme Rainfall Events over Uganda during September to November Rainfall Season

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Journal of Geoscience and Environment Protection 2024年第3期12卷 131-152页

作者： Donnata Alupot Guirong Tan Kokou Romaric Posset Peter Natiko Key Laboratory of Meteorological Disaster Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD) Nanjing University of Information Science and Technology Nanjing China Climate Change Department Pan African University Institute for Water and Energy Sciences (Including Climate Change) C/O Univer-sité Abou Bekr Belkaid Tlemcen Campus Chetouane Tlemcen Algeria Directorate of Weather Forecasting Uganda National Meteorological Authority Port Bell Road Kampala Uganda

Understanding the characteristics of extreme rainfall is crucial for effective flood management planning, as it enables the incorporation of insights from past extreme rainfall patterns and their spatiotemporal distribution. This work investigated the changes in the frequency and pattern of extreme rainfall over Uganda, using daily datasets sourced from Climate Hazard Group InfraRed Precipitation with Station (CHIRPS-v2) for the period 1981 to 2022. The study utilized the extreme weather Indices provided by the Expert Team on Climate Change Detection and Indices (ETCCDI). Attention was directed towards September to November (SON) rainfall season with precise analysis of four indices (Rx1day, Rx5day, R95p, and R99p). The Sequential Mann-Kendall (SQMK) non-parametric test was applied to identify abrupt changes in SON extreme rainfall trends. Results showed that October consistently recorded the highest count of extreme rainfall days across all four indices. The long-term analysis revealed fluctuations in extreme rainfall events across years, with certain periods exhibiting heightened intensity. The analysis portrayed a shift in the decadal variations and region-specific distribution of extreme rainfall, with Eastern Uganda and areas around Lake Victoria standing out compared to other regions. The findings further revealed an increase in extreme rainfall for all indices in the recent decade (2011-2022) with 2019/2020 standing out as the extreme years of SON for the study period. While trendlines suggested a slight increase in intense daily rainfall events, the SQMK tests revealed statistical significance in the trend of prolonged periods of intense daily rainfall. This study contributes to the understanding of the spatiotemporal variability and trends of extreme rainfall events over Uganda during the SON season, which is crucial for the assessment of climate change impacts and adaptation strategies. It provides valuable information for seasonal extreme rainfall forecasting, development of early warning systems, floo

关键词： CHIRPS variability Region-Specific Early Warning Climate Change

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variability of microphysical characteristics in the “21·7” Henan extremely heavy rainfall event

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Science China Earth Sciences 2022年第10期65卷 1861-1878页

作者： Gang CHEN Kun ZHAO Yinghui LU Yuanyuan ZHENG Ming XUE Zhe-Min TAN Xin XU Hao HUANG Haonan CHEN Fen XU Ji YANG Shushi ZHANG Xueqi FAN Key Laboratory of Transportation Meteorology of China Meteorological Administration Nanjing Joint Institute for Atmospheric SciencesNanjing 210041China Key Laboratory for Mesoscale Severe Weather/MOE and School of Atmospheric Science Nanjing UniversityNanjing 210023China State Key Laboratory of Severe Weather and Joint Center for Atmospheric Radar Research of CMA/NJU Chinese Academy of Meteorological SciencesBeijing 100081China Center for Analysis and Prediction of Storms and School of Meteorology University of OklahomaNormanOklahoma 73072USA Colorado State University Fort CollinsCO 80523USA

In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometers and two polarimetric radars.The broad distributions of specific drop size distribution(DSD) parameters are identified in heavy rainfall from the disdrometer observations, indicating obvious microphysical variability on the surface. A K-means clustering algorithm is adopted to objectively classify the disdrometer datasets into separate groups, and distinct DSD characteristics are found among these heavy rainfall groups. Combined with the supporting microphysical structures obtained through radar observations, comprehensive microphysical features of the DSD groups are derived. An extreme rainfall group is dominantly formed in the deep convection over the plain regions, where the high number of concentrations and large mean sizes of surface raindrops are underpinned by both active ice-phase processes and efficient warm-rain collision-coalescence processes in the vertical direction. Convection located near orographic regions is characterized by restricted ice-phase processes and high coalescence efficiency of liquid hydrometeors, causing the dominant DSD group to comprise negligible large raindrops. Multiple DSD groups can coexist within certain precipitation episodes at the disdrometer stations, indicating the potential microphysical variability during the passage of convective system on the plain regions.

关键词： The“21·7”Henan EHR event Microphysical characteristics variability Disdrometer Polarimetric radar

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Quantifying spatiotemporal variability in occupant exposure to an indoor airborne contaminant with an uncertain source location

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Building Simulation 2023年第6期16卷 889-913页

作者： John E.Castellini Jr Cary A.Faulkner Wangda Zuo Michael D.Sohn Department of Mechanical Engineering University of Colorado BoulderUCB 427BoulderCO80309USA Department Architectural Engineering The Pennsylvania State UniversityUniversity ParkPA16802USA National Renewable Energy National Laboratory GoldenCO80401USA Energy Analysis and Environmental Impacts Division Lawrence Berkeley National Laboratory1 Cyclotron RoadBerkeleyCA94720USA

Well-mixed zone models are often employed to compute indoor air quality and occupant exposures.While effective,a potential downside to assuming instantaneous,perfect mixing is underpredicting exposures to high intermittent concentrations within a room.When such cases are of concern,more spatially resolved models,like computational-fluid dynamics methods,are used for some or all of the zones.But,these models have higher computational costs and require more input information.A preferred compromise would be to continue with a multi-zone modeling approach for all rooms,but with a better assessment of the spatial variability within a room.To do so,we present a quantitative method for estimating a room’s spatiotemporal variability,based on influential room parameters.Our proposed method disaggregates variability into the variability in a room’s average concentration,and the spatial variability within the room relative to that average.This enables a detailed assessment of how variability in particular room parameters impacts the uncertain occupant exposures.To demonstrate the utility of this method,we simulate contaminant dispersion for a variety of possible source locations.We compute breathing-zone exposure during the releasing(source is active)and decaying(source is removed)periods.Using CFD methods,we found after a 30 minutes release the average standard deviation in the spatial distribution of exposure was approximately 28%of the source average exposure,whereas variability in the different average exposures was lower,only 10%of the total average.We also find that although uncertainty in the source location leads to variability in the average magnitude of transient exposure,it does not have a particularly large influence on the spatial distribution during the decaying period,or on the average contaminant removal rate.By systematically characterizing a room’s average concentration,its variability,and the spatial variability within the room important insights can be gained as to how much uncertainty is introduced into

关键词： uncertainty variability airborne contaminant spatiotemporal variability well-mixed heterogeneity

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Charting Normative Brain variability Across the Human Lifespan

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Neuroscience Bulletin 2023年第2期39卷 362-364页

作者： Yongbin Wei Han Zhang Yong Liu School of Artifcial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China

Introduction Since De Montbeillard characterized the first curve of his son's height in the late 18th century,growth charts have become increasingly essential for pediatricians to describe group-level variability and monitor the over-development of individual-level growth[1].Growth charts can provide a standardized statistical reference to estimate deviations in a child's physiological measurements(e.g.,height and weight).

关键词： charts height variability

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Analysis of the relationship between blood pressure variability and subtle cognitive decline in older adults

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World Journal of Psychiatry 2023年第11期13卷 872-883页

作者： Hui-Feng Guo Yi Wu Jie Li Feng-Feng Pan Department of Gerontology Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200233China Prenatal Diagnosis Center International Peace Maternity&Child Health HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai 200030China

BACKGROUND Blood pressure variability(BPV)has been shown to be related to mild cognitive impairment and Alzheimer's disease in a number of studies.However,the relationship between BPV and subtle cognitive decline(SCD)has received minimal attention in this field of research to date and has rarely been reported.AIM To examine whether SCD is independently associated with changes in BPV in older adults.METHODS Participants were selected based on having participated in cognitive function evaluation and ambulatory blood pressure measurement at the Shanghai Sixth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine between June 2020 and August 2022.The participants included 182 individuals with SCD as the experimental group and 237 with normal cognitive function as the control group.The basic data,laboratory examinations,scale tests,and ambulatory blood pressure test results of the two groups were analyzed retrospectively,and the relationship between SCD and BPV was subsequently evaluated.RESULTS Significant differences were observed between the two groups of participants(P<0.05)in terms of age,education level,prevalence rate of diabetes,fasting blood glucose level,24-h systolic blood pressure standard deviation and coefficient of variation,24-h diastolic blood pressure standard deviation and coefficient of variation.The scale monitoring results showed significant differences in the scores for memory,attention,and visual space between the experimental and control groups.Logistic regression analysis indicated that age,education level,blood sugar level,and BPV were factors influencing cognitive decline.Linear regression analysis showed that there was an independent correlation between blood pressure variation and SCD,even after adjusting for related factors.Each of the above differences was still significant.CONCLUSION This study suggests that increased BPV is associated with SCD.

关键词： Blood pressure variability Elderly Subtle cognitive decline relationship

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Lipoprotein(a)variability is associated with mean follow-up Creactive protein in patients with coronary artery disease following percutaneous coronary intervention

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World Journal of Clinical Cases 2022年第35期10卷 12909-12919页

作者： Si-Si Zhang Wen-Yi Hu Yi-Jing Li Juan Yu Shang Sang Zakareya M Alsalman Da-Qi Xie Department of Cardiology Ningbo Ninth HospitalNingbo 315300Zhejiang ProvinceChina

BACKGROUND Increased lipoprotein(a)[lp(a)]has proinflammatory effects,which increase the risk of coronary artery disease.However,the association between lp(a)variability and follow-up C-reactive protein(CRP)level in patients undergoing percutaneous coronary intervention(PCI)has not been investigated.AIM To explore the association between lp(a)variability and mean CRP levels within the 1st year post-PCI.METHODS Results of lp(a)and CRP measurements from at least three follow-up visits of patients who had received PCI were retrospectively analyzed.Standard deviation(SD),coefficient of variation(CV),and variability independent of the mean(VIM)are presented for the variability for lp(a)and linear regression analysis was conducted to correlate lp(a)variability and mean follow-up CRP level.The relationship of lp(a)variability and inflammation status was analyzed by restricted cubic spline analysis.Finally,exploratory analysis was performed to test the consistency of results in different populations.RESULTS A total of 2712 patients were enrolled.Patients with higher variability of lp(a)had a higher level of mean follow-up CRP(Pvariability was positively correlated with the mean follow-up CRP(SD:β=0.023,Pvariability correlated with mean follow-up CRP level and high variability could be considered an independent risk factor for increased post-PCI CRP level.

关键词： Lipoprotein(a) variability C-reactive protein Coronary artery disease Percutaneous coronary intervention

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An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones

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Tropical Cyclone Research and Review 2023年第3期12卷 216-239页

作者： Suzana J.Camargo Hiroyuki Murakami Nadia Bloemendaal Savin S.Chand Medha S.Deshpande Christian Dominguez-Sarmiento Juan Jesús Gonz´alez-Alem´an Thomas R.Knutson I.-I.Lin Il-Ju Moon Christina M.Patricola Kevin A.Reed Malcolm J.Roberts Enrico Scoccimarro Chi Yung(Francis)Tam Elizabeth J.Wallace Liguang Wu Yohei Yamada Wei Zhang Haikun Zhao Lamont-Doherty Earth Observatory Columbia UniversityPalisadesNYUSA National Oceanographic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory PrincetonNJUSA University Corporation for Atmospheric Research BoulderCOUSA Vrije University Amsterdam AmsterdamNetherlands Federation University Australia BallaratVictoriaAustralia Indian Institute of Tropical Meteorology Ministry of Earth SciencesPuneIndia Instituto de Ciencias de la Atmosfera y Cambio Clim´atico Universidad Nacional Autonoma de Mexico(UNAM)Mexico CityMexico Spanish State Meteorological Agency(AEMet) MadridSpain National Taiwan University TaiwanChina Jeju National University JejuRepublic of Korea Iowa State University AmesIAUSA Stony Brook University Stony BrookNYUSA Met Office ExeterUnited Kingdom Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici BolognaItaly The Chinese University of Hong Kong Hong KongChina Old Dominion University NorfolkVAUSA Fudan University ShanghaiChina Japan Agency for Marine-Earth Science and Technology YokohamaJapan Utah State University LoganUTUSA Nanjing University of Information Science and Technology NanjingChina

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones(IWTC-9)in 2018,improving our understanding of the effect of climate change on tropical cyclones(TCs)and associated hazards and risks.These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change.New modeling and observational studies suggested the potential influence of anthropogenic climate forcings,including greenhouse gases and aerosols,on global and regional TC activity at the decadal and century time scales.However,there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic,and the limitations of observed TC records.The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models.A new paradigm,TC seeds,has been proposed,and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency.New studies also highlighted the importance of large-scale environmental fields on TC activity,such as snow cover and air-sea interactions.Future projections on TC translation speed and medicanes are new additional focus topics in our report.Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.

关键词： tropical climate variability

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Mathematical Insight into Moderate Inversion Gate Delay variability for Ultradeep Submicron Digital Circuit Design

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Journal of Harbin Institute of Technology(New Series) 2023年第4期30卷 68-75页

作者： Shruti Kalra Department of Electronics and Communication Engineering Jaypee Institute of Information TechnologyNoida 201307India

Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.

关键词： moderate inversion ultradeep submicron predictive technology model variability log skew normal distribution

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