Percentile Threshold Research Articles

More frequent, persistent, and deadly heat waves in the 21st century over the Eastern Mediterranean

Heat waves are extreme events characterized by sweltering weather over an extended period. Skillful projections of heat waves and their impacts on human mortality can help develop appropriate adaptation strategies. Here, we provide nuanced projections of heat wave characteristics and their effect on human mortality over the Eastern Mediterranean based on ERA5 reanalysis and CORDEX ensemble simulations. Heat waves were identified according to the 90th percentile threshold of the Climatic Stress Index (CSI), specifically tailored for the summer conditions in this region.We provide evidence that heat waves in the region are projected to occur seven times more often and last three times longer by the end of the 21st century (RCP8.5). We find that heat waves will become more persistent in a warmer world. Finally, we offer a conservative estimate of excess mortality in Israel based on a simple linear model. The projected changes in heat stress intensity and frequency may result in ~330 excess deaths per summer at the end of the 21st century (RCP8.5) compared to the historical baseline of ~30 heat-related deaths, particularly pronounced in the elderly (65+ years).We conclude that heat waves increasingly threaten society in the vulnerable Eastern Mediterranean. We also emphasize that true interdisciplinary regional collaborations are required to achieve adequate public health adaptation to extreme weather events in a changing climate.

Bivariate Analysis of Extreme Precipitation Using Copula Functions in Arid and Semi-Arid Regions

This study analyzed extreme precipitation events, using daily rainfall data for 1966–2015. A Mann–Kendall trend test was used to evaluate trends in extreme precipitation, copula functions were applied to compute the joint return periods of extreme events, and univariate and bivariate distributions were used to determine risk. The results showed that the decrease in consecutive wet days (CWD) was significant in the west and the northwest of Iran, while the consecutive dry days (CDD) index was increasing therein. The precipitation on more than the 90th percentile (P90) very wet days and annual number of days with precipitation less than the 90th percentile threshold (D90) indices followed similar patterns, with no significant trend in most parts of Iran, but at several stations in the north, west, and northwest, their decline was extreme. Furthermore, the increase of D10 (annual number of days with precipitation less than the 90th percentile threshold) and P10 (total precipitation of D10 of a year) was extreme in the wet regions of Iran, including the north, west, and northwest areas, and also part of the center. More than 50 percent of Iran experienced a low risk level, with a return period of extreme events (CWD, CDD) of more than 27.5 years, and the joint return periods of (D10, D90), (P10, P90), and (D10, P10) pairs were less than 100 years in most regions of Iran. Due to the increasing number of dry days in the north, west, and northwest of Iran, the drought risk increased. Based on the changes in extreme precipitation indices in recent years, the findings of this study will be useful for copula-based frequency analysis under a changing environment at regional and global scales.

Regime shift increase in East Asia's summer extreme hot day frequency across the late 1990s

AbstractHere we analysed the long‐term change in extreme hot days (EHDs) in East Asia during boreal summer (June–July–August) since 1979, where EHDs was defined as days exceeding or equalling the 90th percentile threshold of the climatological (1991–2020) daily and . EHDs frequency occurrence in East Asia during summer showed not only an increasing trend but also a distinct regime shift increase since the late 1990s. Based on this regime shift, we divided these years into two periods, P1 (1979–1998) and P2 (1999–2021), and found that different physical processes operated for each period's EHDs variability. P2's EHDs was related to the stationary wave originating from both the North Atlantic Ocean and the Indo‐Pacific warm pool, but these influences did not appear in P1. To investigate whether the observed regime shift increase was caused by natural variability or greenhouse gas concentration increases, we conducted a CO2 quadrupling experiment as well as a present‐day experiment with a fixed CO2 concentration using the Community Earth System Model with 28 ensemble members. We demonstrated that the regime shift increase of East Asian EHDs occurrences was due to increasing greenhouse gas concentrations. We further discussed the influence of Arctic sea ice reduction due to global warming on EHDs occurrences in East Asia.

Age-specific reference values for low psoas muscle index at the L3 vertebra level in healthy populations: A multicenter study.

The progressive and generalized loss of skeletal muscle mass, strength and physical function is defined as sarcopenia. Sarcopenia is closely related to the prognosis of patients. Accurate diagnosis and adequate management of sarcopenia are crucial. The psoas muscle mass index taken at the third lumbar vertebra (L3-PMI, cm2/m2) is one of the established methods for evaluating skeletal muscle mass. However, the cutoff values of L3-PMI for diagnosis of sarcopenia are not yet to be clarified in Asian populations. We attempted to establish reference values for low L3-PMI that would be suitable for defining sarcopenia in the Northern Chinese population. This was a retrospective, multicenter cross-sectional study. A search of abdominal CT imaging reports was conducted in four representative cities in northern China. Transverse CT images were measured using the analysis software Slice-O-Matic. Low psoas muscle index was defined as the 5th percentile or mean-2SD of the study group. 1,787 healthy individuals in the study were grouped by age. The sex and number of people in each group were similar. L3-PMI had a negative linear correlation with age, and a strong correlation with the skeletal muscle index taken at the third lumbar vertebrae (L3-SMI, cm2/m2). The L3-PMI reference values in males were 5.41 cm2/m2 for 20-29 years, 4.71 cm2/m2 for 30-39 years, 4.65 cm2/m2 for 40-49 years, 4.10 cm2/m2 for 50-59 years and 3.68 cm2/m2 for over 60 years by using 5th percentile threshold. Similarly, the reference values in females were 3.32, 3.40, 3.18, 2.91, and 2.62 cm2/m2. When using mean-2SD as the reference, the values for each age group were 4.57, 4.16, 4.03, 3.37, and 2.87 cm2/m2 for males and 2.79, 2.70, 2.50, 2.30, and 2.26 cm2/m2 for females, respectively. We defined the reference values of age-specific low skeletal muscle mass when simply evaluated by L3-PMI. Further studies about the association of sarcopenia using these reference values with certain clinical outcomes or diseases are needed.

Projection of compound wind and precipitation extremes in China based on Phase 6 of the Coupled Model Intercomparison Project models

AbstractExtreme precipitation and extreme wind may lead to catastrophic impacts on ecosystems, infrastructure, human dwellings and settlements. The concurrence of the two extremes, compound wind and precipitation extremes (CWPEs), may cause even larger impacts than the univariate counterparts. Under global warming with increased weather and climate extremes, there is a necessity to explore projected changes of CWPEs in the future. Based on daily precipitation and surface wind speed from observations (CN05.1) and simulations of Phase 6 of the Coupled Model Intercomparison Project (CMIP6) models, we assess changes of CWPEs in the mainland of China in the future. By defining CWPEs based on the 98th percentile threshold in summer seasons (June–July–August [JJA]) in historical periods (1995–2014), we first explore the model performance in simulating precipitation, wind speed and CWPEs in China during JJA in historical periods. We then compute the projected changes of CWPEs in the near‐term (2021–2040), mid‐term (2041–2060) and long‐term (2081–2100) periods under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 scenarios. The occurrence of CWPEs is projected to increase in three future periods, particularly in the south and east China. Though a slight increase of CWPEs is shown under SSP1‐2.6 and SSP2‐4.5, the projected changes of CWPEs under SSP5‐8.5 show a dramatic increase (around 46%) in the long‐term period. Our assessment of projected changes in CWPEs can provide useful information to cope with the impact of CWPEs in China under climate change.

Plasma glial fibrillary acidic protein as a moderator along the Alzheimer’s disease biomarker cascade

AbstractBackgroundAstrocyte reactivity may contribute to pathogenic relationships between β‐amyloid (A), phosphorylated tau (T), neurodegeneration (N), and cognition (memory). We examined whether severity of astrocyte reactivity, characterized by plasma glial fibrillary acidic protein (GFAP), moderates relationships along the A/T/N and memory cascade in non‐demented adults.MethodPlasma phosphorylated tau181 (P‐tau181) and GFAP concentrations (Quanterix Simoa) were measured in cognitively unimpaired (CU) individuals and patients with mild cognitive impairment (MCI). Analyses were conducted on overlapping sample subsets (aged 52‐92) with florbetapir Aβ‐PET (112 CU [80 Aβ‐, 32 Aβ+; SUVR>1.11], 29 MCI [all Aβ+]), structural MRI (139 CU, 39 MCI), and memory testing (168 CU, 45 MCI). Linear regression tested statistical moderation of plasma GFAP on the association of Aβ‐PET (A) with plasma P‐tau181 (T), and on associations of plasma P‐tau181 with hippocampal volume (N) and composite memory z‐scores (cognition). To probe moderation effects, region of significance analyses identified percentile thresholds along the plasma GFAP distribution at which statistically significant A/T/N and cognition associations emerged. Covariates included age, sex, APOE genotype, education (cognitive analysis), and intracranial volume (MRI analysis).ResultPlasma GFAP significantly moderated the relationship between Aβ‐PET and plasma P‐tau181 (β=0.23, p=.003) and the relationship between plasma P‐tau181 and memory (β=‐0.18, p=.027). Region of significance analyses detected significantly higher plasma P‐tau181 concentrations in Aβ+ (vs. Aβ‐) only above the 17th percentile of plasma GFAP, whereas the significant relationship between higher plasma P‐tau181 and worse memory was only detected above the 73rd percentile of plasma GFAP. Plasma GFAP did not moderate the relationship between plasma P‐tau181 and hippocampal volume (p=.648); however, both plasma P‐tau181 (β=‐0.20, p=.004) and GFAP (β=‐0.16, p=.035) independently related to smaller hippocampal volume.ConclusionAdverse associations along the A/T/N and memory cascade only emerged with increasing plasma GFAP concentrations, with a higher GFAP threshold needed to detect plasma P‐tau181‐related memory associations than Aβ‐related elevations in plasma P‐tau181. These adverse associations were absent at low GFAP levels, suggesting less severe astrocyte reactivity may buffer against AD pathological changes. As a non‐invasive marker of astrocyte reactivity, incorporating plasma GFAP into AD biomarker models may enhance characterization of AD risk and resilience.

Spatial connections in extreme precipitation events obtained from NWP forecasts: A complex network approach

Understanding the spatial variability of extreme precipitation events (EPEs) has always been a challenging task, with climate change further complicating the issue. Many studies have looked into the spatiotemporal characteristics of EPEs and the possibility of them being connected. Most of these studies are based on observation data products which inform about the events after they have occurred. Various Quantitative Precipitation Forecasts (QPFs) obtained from the Numerical Weather Prediction (NWP) models such as those of the European Centre for Medium-range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), National Centre for Medium-Range Weather Forecasting (NCMRWF), and UK Met Office (UKMO) are available which inform about the precipitation events before they have occurred. In this study, we inter-evaluate four gridded (deterministic) QPFs over the Ganga River basin of India for their ability to detect the spatial connections among EPEs during the monsoon months, i.e., June, July, August and September (JJAS). Several experimental runs are performed in multiple time periods (13, 6 and 4 years) at various percentile thresholds (85th, 90th and 95th percentile) at two spatial resolutions of 25 and 50-km. Moreover, we also evaluate the forecast patterns of the QPF obtained from the national agency of India, i.e., NCMRWF and analyse its performance with respect to the other three selected QPFs from international agencies. For the observation/reference dataset, the gridded Indian Meteorological Department (IMD) dataset is selected. We first use the deterministic and dichotomous error statistics to evaluate the performance of NWP forecasts. Further, we employ the theory of complex networks to create networks of extreme precipitation at each grid. With this work, we aim to answer (a) can the theory of complex networks be a feasible tool for evaluating the performance of NWP forecasts in detecting extreme precipitation behaviour; (b) does the change in temporal length of the NWP forecasts influence the spatial structure of extreme precipitation as observed before, and (c) can a global NWP model, larger in length, be used as a potential substitute to the NCMRWF model. The ECMWF model performs well with respect to IMD as the average CC for TP_13 is 0.42 while they are 0.31 and 0.34 for TP_6 and TP_4, respectively. Also, we find that ECMWF can be a suitable substitute for the NCMRWF model. The identification of a substitute precipitation forecast, larger in temporal length, can be beneficial as input in hydrological models for streamflow forecasting and estimating parameters for bias correction of precipitation, among others.

Identifying Nursing Homes With Diverse Racial and Ethnic Resident Compositions: The Importance of Group Heterogeneity and Geographic Context.

Racial/ethnic composition of nursing home (NH) plays a particularly important role in NH quality. A key methodological issue is defining when an NH serves a low versus high proportion of racially/ethnically diverse residents. Using the Minimum Data Set from 2015 merged with Certification and Survey Provider Enhanced Reports, we calculated the racial/ethnic composition of U.S.-based NHs for Black or Hispanic residents specifically, and a general Black, Indigenous, and People of Color (BIPOC) grouping for long-stay residents. We examined different definitions of having a high racial/ethnic composition by varying percentile thresholds of composition, state-specific and national thresholds, and restricting composition to BIPOC residents as well as only Black and Hispanic residents. NHs with a high racial/ethnic composition have different facility characteristics than the average NH. Based on this, we make suggestions for how to identify NHs with diverse racial/ethnic resident compositions.

Average treatment effect of facility hepatopancreatobiliary malignancy case volume on survival of patients with nonoperatively managed hepatobiliary malignancies

BackgroundSurgical volume-outcome relationships have been described for a variety of procedures. There is scant literature on total institutional volume and outcomes in patients who are nonoperatively managed. We examined the average treatment effect of total hepatopancreatobiliary malignancy case volume on survival outcomes of patients with nonresected hepatobiliary malignancies. MethodsWe identified patients with hepatopancreatobiliary malignancies [pancreatic adenocarcinoma, pancreatic neuroendocrine neoplasms, hepatocellular carcinoma, biliary tract cancers] within the National Cancer Database (2004–2018). We determined percentile thresholds based on the total annual hepatopancreatobiliary malignancy case volume. We then identified nonoperatively managed patients with hepatocellular carcinoma or biliary tract cancers. We used inverse probability-weighted Cox regression to estimate the effect of facility volume on overall survival. ResultsWe identified 710,988 patients with hepatopancreatobiliary malignancies. Total annual hepatopancreatobiliary malignancy case volume of 32, 71, and 177 cases/year corresponded to the 25th, 50th, and 75th percentiles. A total of 96,420 with hepatocellular carcinoma and 52,627 patients with biliary tract cancers were managed nonoperatively. In patients with hepatocellular carcinoma or biliary tract cancer, treatment at ≥25th, ≥50th, and ≥75th percentile facilities was associated with improved median, 1-, 2-, and 3-year overall survival compared with treatment at lower-percentile facilities. On inverse probability–weighted Cox analysis, treatment at higher-percentile facilities resulted in a lower hazard of death. Consistent findings were observed in patients with early or intermediate/advanced hepatocellular carcinoma or metastatic biliary tract cancers. ConclusionPatients with nonoperatively managed hepatocellular carcinoma or biliary tract cancer who receive treatment at higher-volume facilities have improved survival outcomes. These data suggest regionalization of care for patients with hepatocellular carcinoma or biliary tract cancer to high-volume centers may improve survival.

Ambulatory hypertension diagnosed by 24-h mean ambulatory versus day and night ambulatory blood pressure thresholds in children: a cross-sectional study

BackgroundThe agreement between the commonly used ambulatory blood pressure (ABP) thresholds to diagnose ambulatory hypertension in children (patient’s 24-h mean ABP classified by 24-h 95th ABP percentile threshold, American Heart Association [AHA] threshold, or patient’s day and night mean ABP classified by day-night 95th ABP percentile thresholds) is not known. We evaluated the agreement among 24-h ABP threshold, AHA threshold, and day-night ABP thresholds to diagnose ambulatory hypertension, white coat hypertension (WCH) and masked hypertension (MH).MethodsIn a cross-sectional study design, we analyzed ABP recordings from 450 participants with suspected hypertension from a tertiary care outpatient hypertension clinic. The American Academy of Pediatrics thresholds were used to diagnose office hypertension.ResultsThe 24-h ABP threshold and day-night ABP thresholds classified 19% ABP (95% confidence interval [CI], 0.15–0.23) differently into ambulatory normotension/hypertension (kappa [κ], 0.58; 95% CI, 0.51–0.66). Ambulatory hypertension diagnosed by 24-h ABP threshold in 27% participants (95% CI, 0.22–0.32) was significantly lower than that by day-night ABP thresholds in 44% participants (95% CI, 0.37–0.50; P < 0.001). The AHA threshold had a stronger agreement with 24-h ABP threshold than with day-night ABP thresholds for classifying ABP into ambulatory normotension/hypertension (k 0.94, 95% CI 0.91–0.98 vs. k 0.59, 95% CI 0.52–0.66). The diagnosis of ambulatory hypertension by the AHA threshold (26%; 95% CI, 0.21–0.31) was closer to that by 24-h ABP threshold (27%, P = 0.73) than by day-night ABP thresholds (44%, P < 0.001). Similar agreement pattern persisted among these ABP thresholds for diagnosing WCH and MH.ConclusionsThe 24-h ABP threshold classifies a lower proportion of ABP as ambulatory hypertension than day-night ABP thresholds. The AHA threshold exhibits a stronger agreement with 24-h ABP than with day-night ABP thresholds for diagnosing ambulatory hypertension, WCH and MH. Our findings are relevant for a consistent interpretation of hypertension by these ABP thresholds in clinical practice.

Response of extreme precipitation to climatic warming in the Weihe river basin, China and its mechanism

Abstract As global warming continues, extreme precipitation events occur frequently in inland areas, seriously affecting human security and the ecological environment. Spatiotemporal evolution of extreme precipitation as well as response of extreme precipitation to climatic warming and its mechanism were investigated by considering the Weihe river basin in a monsoon transition zone of China as a research object. The results indicate that while the annual average temperature of the Weihe river basin increased with fluctuations from 1966 to 2017, except for the consecutive dry days (CDD) and simple daily intensity index that increased slightly, the other extreme precipitation indices (consecutive wet days, R25, and Rx5day) tended to decrease. Moreover, except for the CDD, the other four indices gradually increased from the northwest to the southeast, showing a similar trend to the temperature. The relationship between the 95th percentile threshold and temperature (hereinafter referred to as the P 95d–T relationship) in the Weihe river basin demonstrates the hook structure and its strength in terms of response is mainly dominated by the super-Clausius–Clapeyron (C–C) and C–C scaling. Furthermore, the peak temperature rises gradually from the northwest to the southeast. The results can provide important reference for the prediction of climate change and future studies of disaster risk in the Weihe river basin.

The Effects of Co-Exposure to Extremes Heat and Particulate Air Pollution on Mortality in California

Background: Extremes of heat and particulate air pollution threaten human health and are becoming more frequent due to climate change. Understanding the health impacts of the co-exposure to extreme heat and air pollution is urgent. Methods: Death certificate data for California from January 1, 2014, to December 31, 2019 were used to identify all-cause, cardiovascular, and respiratory mortality. A case-crossover study with time-stratified matching and conditional logistic regression was used to estimate the mortality association with acute co-exposures to extreme heat and PM2.5. Several percentile-based threshold values (i.e., 90th, 95th, 97th, and 99th) were used to define a day as an extreme exposure day. For each case day (date of death) and its control days, daily average PM2.5, maximum and minimum temperature were assigned based on decedent’s residence census tract. Age-stratified analyses were also conducted. Results: This study included 1.5 million all-cause, 0.5 million cardiovascular, and 0.14 million respiratory deaths. Based on a 99th percentile threshold, all-cause mortality risk increased 6.1% (95%confidence interval,CI: 4.1, 8.1) on extreme maximum temperature only days and 5.0% (95%CI: 3.0, 8.0) on extreme PM2.5 only days, compared to non-extreme days. Risk increased 21.0% (95%CI: 6.6, 37.3) on days with exposure to both extreme maximum temperature and PM2.5. Increased risk of cardiovascular and respiratory mortality on extreme co-exposure days were 29.9% (95%CI: 3.3, 63.3) and 38.0% (95%CI: -12.5, 117.7), respectively, and were more than the sum of individual effects of extreme temperature and PM2.5 only. A similar pattern was observed for co-exposure to extreme PM2.5 and minimum temperature; effect estimates were larger among those over age 75 years. Conclusion: Short-term exposure to extreme heat and air pollution alone were individually associated with increased risk of mortality, but their co-exposure had larger effects beyond the sum of their individual effects. Keywords: extreme co-exposure, heat, air pollution, mortality

Future land use and climate change escalate connectivity loss for Himalayan brown bears

AbstractClimate and land use change are among the main drivers affecting virtually all species on earth. There were extensive studies projecting impacts of climate and land use changes on habitat loss and fragmentation but few on connectivity loss, and those that investigated connectivity did not disentangle the combined effects between climate change and land use change. This study uses the Himalayan brown bear (Ursus arctos isabellinus) as a case study to illustrate an approach for disentangling the effects of climate change and human land use on population connectivity in the future. First, we assessed the current spatial pattern of population connectivity by simulating cumulative resistant kernels and factorial least‐cost paths with empirical field data. Then, we simulated the changes in connectivity due to future climate change under alternative emission scenarios (RCP 2.6 and RCP 8.5) in mid (2041–2060) and late (2061–2080) 21st century, which served as baseline scenarios of future connectivity. Finally, we estimated the changes in future connectivity due to human land use changes by adding a low and a high human land use activity scenario to the baseline climate change scenarios in our simulations. Alarmingly, all high emission scenarios, with or without human land use change, were projected to result in &gt;99% reduction in current core areas of connectivity by the end of 21st century at 50th percentile threshold or above. This study demonstrates a spatially explicit scenario modeling approach to examine the interplay between future climate change and human land use on species connectivity. Our results suggest that regional land use regulations may be insufficient to conserve connectivity for HBB if nothing is done to reduce climate change at a global scale.

Obsessive-Compulsive Disorder (OCD) Types and Social Media: Are Social Media Important and Impactful for OCD People?

Social media (SM) are the new standard for social interaction and people with OCD use such platforms like everyone else. However, the research on these individuals provides limited, sporadic, and difficult-to-generalize data outside of social-media evidence for one specific context concerning how SM is experienced by people with OCD. Our cross-sectional study involved 660 participants (71.4% females, 28.6% males) with 22% of the sample surpassing the 90° percentile threshold to be identified as high-level OCD-symptomatic individuals. Our work highlighted that roughly all OCD types are affected by social media in terms of mood and that these individuals appeared to give SM more importance than non-OCD individuals. The evidence presented, although very narrow, can be conceived as the first building blocks to encourage future research considering how individuals with OCD experience social media, since they appear to be affected more by them compared to non-OCD individuals.

The impact of climate change on the distribution of rare and endangered tree Firmiana kwangsiensis using the Maxent modeling.

The upsurge in anthropogenic climate change has accelerated the habitat loss and fragmentation of wild animals and plants. The rare and endangered plants are important biodiversity elements. However, the lack of comprehensive and reliable information on the spatial distribution of these organisms has hampered holistic and efficient conservation management measures. We explored the consequences of climate change on the geographical distribution of Firmiana kwangsiensis (Malvaceae), an endangered species, to provide a reference for conservation, introduction, and cultivation of this species in new ecological zones. Modeling of the potential distribution of F. kwangsiensis under the current and two future climate scenarios in maximum entropy was performed based on 30 occurrence records and 27 environmental variables of the plant. We found that precipitation‐associated and temperature‐associated variables limited the potentially suitable habitats for F. kwangsiensis. Our model predicted 259,504 km2 of F. kwangsiensis habitat based on 25 percentile thresholds. However, the high suitable habitat for F. kwangsiensis is only about 41,027 km2. F. kwangsiensis is most distributed in Guangxi's protected areas. However, the existing reserves are only 2.7% of the total suitable habitat and 4.2% of the high suitable habitat for the plant, lower than the average protection area in Guangxi (7.2%). This means the current protected areas network is insufficient, underlining the need for alternative conservation mechanisms to protect the plant habitat. Our findings will help identify additional F. kwangsiensis localities and potential habitats and inform the development and implementation of conservation, management, and cultivation practices of such rare tree species.

A Simple Approach to the Identification of Guideline-Based Coronary Artery Calcium Score Percentiles (From the Multi-Ethnic Study of Atherosclerosis)

Absolute coronary artery calcium (CAC) scores and CAC percentiles can identify different patient groups, which could be confusing in clinical practice. We aimed to create a simple "rule of thumb" for identifying the American College of Cardiology/American Heart Association endorsed 75th CAC percentile based on age, gender, and the absolute CAC score. Using the Multi-Ethnic Study of Atherosclerosis, we calculated the age and gender-specific percent likelihood that a guideline-based absolute CAC score group (1 to 100, 100 to 300, &gt;300) will place a patient above the 75th percentile. Also, we derived gender-specific age cutoffs by which 95% of participants with any (&gt;0), moderate (≥100), or severe (≥300) CAC score would be over the 75th percentile. We repeated the analysis using the 90th percentile threshold and also conducted sensitivity analyses stratified by race. Any CAC &gt;0 places 95% of women younger than 60 years and over 90% of men younger than 50 years over the 75th percentile. Moderate absolute CAC scores (&gt;100) place nearly all men &lt;60 years and all women &lt;70 years over the 75th percentile. Confirmatory analysis for age cutoffs was consistent with primary analysis, with cutoffs of 48 years for men and 59 years for women indicating a 95% likelihood that any CAC would place patients over the 75th percentile. In conclusion, our study provides a simple rule of thumb (men &lt;50 years and women &lt;60 years with any CAC, men &lt;60 years and women &lt;70 years with CAC &gt;100) for identifying CAC &gt;75th percentile that might be readily adopted in clinical practice.

A study on the impact of extreme weather on the poverty vulnerability of farming households—evidence from six counties in the hubei and yunnan provinces of china

By using micro-farm household survey data from six counties in the Hubei and Yunnan provinces, warm days, heavy precipitation, and consecutive dry days were selected as extreme weather measures, and the RClimDex software was used to empirically examine the impacts of extreme weather on farm household poverty vulnerability by setting percentile thresholds to measure extreme weather indicators in each district and county in 2017. Based on the improved Department for International Development sustainable livelihoods analysis framework, the entropy value method was used to synthesize the variables in the farm household sustainable livelihood capacity to examine their mediating effects. The results were as follows: 1) Extreme weather significantly affected farm household poverty vulnerability. Warm days were significantly and negatively related to farmers’ poverty vulnerability, while total heavy precipitation and consecutive dry days were significantly and positively related to farmers’ poverty vulnerability. 2) The impacts of extreme weather on farmers with different vulnerability characteristics varied. 3) The sustainable livelihood capacity of farm households played a partially mediating role in the process of extreme weather indicators of persistent drought index affecting the poverty vulnerability of farm households. 4) As compared to rural households engaged in non-agricultural industries, agricultural production and operation-based farming households were more vulnerable to shocks from extreme weather. Accordingly, we recommended that to improve farmers’ climate resilience, differentiated policies should be adopted according to local conditions; climate-sensitive vulnerable groups should be identified; agricultural insurance coverage should be expanded; farmers should be guided into entrepreneurship; and equalization of public services should be equalized so as to avoid farmers becoming impoverished due to extreme weather.

Self-Organized Criticality of Precipitation in the Rainy Season in East China

Based on daily precipitation data from 1960 to 2017 in the rainy season in east China, to a given percentile threshold of one observation station, the time that precipitation spends below threshold is defined as quiet time τ. The probability density functions τ in different thresholds follow power-law distributions with exponent β of approximately 1.2 in the day, pentad and ten-day period time scales, respectively. The probability density functions τ in different regions follow the same rules, too. Compared with sandpile model, Γ function describing the collapse behavior can effectively scale the quiet time distribution of precipitation events. These results confirm the assumption that for observation station data and low-resolution precipitation data, even in China, affected by complex weather and climate systems, precipitation is still a real world example of self-organized criticality in synoptic. Moreover, exponent β of the probability density function τ, mean quiet time τ¯q and hazard function Hq of quiet times can give sensitive regions of precipitation events in China. Usual intensity precipitation events (UPEs) easily occur and cluster mainly in the middle Yangtze River basin, east of the Sichuan Province and north of the Gansu Province. Extreme intensity precipitation events (EPEs) more easily occur in northern China in the rainy season. UPEs in the Hubei Province and the Hunan Province are more likely to occur in the future. EPEs in the eastern Sichuan Province, the Guizhou Province, the Guangxi Province and Northeast China are more likely to occur.

Response of the water footprint of maize production to high temperatures in the Huang-Huai-Hai region of China.

Water footprint (WF) can comprehensively evaluate agricultural water use efficiency under high-temperature weather. Based on the historical meteorological data in the Huang-Huai-Hai (3H) region of China, this study used the percentile threshold method to analyze the distribution of high-temperature events and set three types of meteorological scenarios, namely the actual temperature scenario (S1), the high temperatures in the ear stage scenario (S2), and the high temperatures in the flowering-maturity stage scenario (S3). The growing degree day (GDD) mode and calendar day (CD) mode in the AquaCrop model were used to simulate the yield per unit area (Yunit ) of maize under different temperature scenarios and then the crop evapotranspiration (ETc ) and production WF during maize growth period were calculated. The occurrence frequency of extreme high-temperature event in ear stage in the 3H region was lower than that in the flowering-maturity stage. There were significant differences in the WF of maize between S1 and S2 and between S1 and S3 in GDD mode, and significant differences in Yunit , ETc , and WF of maize under three temperature scenarios in the CD mode. High temperature events occur in maize growth period, especially in the flowering-maturity stage, will increase the WF of maize. Measures such as changing the planting structure, changing the sowing date of maize and cultivating heat-resistant maize varieties could be taken to reduce the negative impacts of high-temperature weather. © 2022 Society of Chemical Industry.

Impact of thresholds on nonstationary frequency analyses of peak over threshold extreme rainfall series in Pearl River Basin, China

Nonstationary frequency analysis of peak over threshold (POT) extreme rainfall series is crucial in hydrology. Most previous studies on the nonstationary frequency analyses of POT extreme rainfall series used only a single threshold, ignoring the differences in the statistical characteristics of POT extreme rainfall series extracted with different thresholds. This study investigated the impact of thresholds on the nonstationary frequency analyses of POT extreme rainfall series using a three-step method. First, the non-stationarities in POT extreme rainfall series extracted with different thresholds were assessed using the Iterative Mann-Kendall test and the Mood test. Second, the nonstationary POT extreme rainfall series were modeled using the generalized Pareto distribution (GPD) with the scale parameter to be linked with physical covariates. Third, the uncertainty in the parameters and return level of the optimal model for the POT extreme rainfall series were evaluated using the Markov chain Monte Carlo method. This method was applied to the daily rainfall at 48 stations in the Pearl River Basin (PRB) from 1979 to 2020. By comparing the optimal models of POT extreme rainfall series extracted with different percentile thresholds, we can draw the following conclusions. (1) As the threshold increases from the 90th percentile to the 99.7th percentile, the percentage of nonstationary POT extreme rainfall series gradually decreases from 92% to 13%, with most stations with a significant increasing trend changing to most stations with a significant decreasing trend, especially when the threshold is greater than the 98th percentile. (2) The uncertainty in the scale parameter, shape parameter, and return level increases as the threshold increases, and increases significantly when the threshold is greater than the 98th percentile, especially for the scale and shape parameters. (3) The 98th percentile is suggested as the optimal threshold for the PRB; (4) For the 98th percentile threshold, the total column water vapor in the convective indices is the most significant covariate for the entire PRB.