Extreme High Wind Research Articles

Effects and Interaction of Meteorological Factors on Pulmonary Tuberculosis in Urumqi, China, 2013-2019.

BackgroundMost existing studies have only investigated the delayed effect of meteorological factors on pulmonary tuberculosis (PTB). However, the effect of extreme climate and the interaction between meteorological factors on PTB has been rarely investigated.MethodsNewly diagonsed PTB cases and meteorological factors in Urumqi in each week between 2013 and 2019 were collected. The lag-exposure-response relationship between meteorological factors and PTB was analyzed using the distributed lag non-linear model (DLNM). The generalized additive model (GAM) was used to visualize the interaction between meteorological factors. Stratified analysis was used to explore the impact of meteorological factors on PTB in different stratification and RERI, AP and SI were used to quantitatively evaluate the interaction between meteorological factors.ResultsA total of 16,793 newly diagnosed PTB cases were documented in Urumqi, China from 2013 to 2019. The median (interquartile range) temperature, relative humidity, wind speed, and PTB cases were measured as 11.3°C (−5.0–20.5), 57.7% (50.7–64.2), 4.1m/s (3.4–4.7), and 47 (37–56), respectively. The effects of temperature, relative humidity and wind speed on PTB were non-linear, which were found with the “N”-shaped, “L”-shaped, “N”-shaped distribution, respectively. With the median meteorological factor as a reference, extreme low temperature was found to have a protective effect on PTB. However, extreme high temperature, extreme high relative humidity, and extreme high wind speed were found to increase the risk of PTB and peaked at 31.8°C, 83.2%, and 7.6 m/s respectively. According to the existing monitoring data, no obvious interaction between meteorological factors was found, but low temperature and low humidity (RR = 1.149, 95%CI: 1.003–1.315), low temperature and low wind speed (RR = 1.273, 95%CI: 1.146–1.415) were more likely to cause the high incidence of PTB.ConclusionTemperature, relative humidity and wind speed were found to play vital roles in PTB incidence with delayed and non-linear effects. Extreme high temperature, extreme high relative humidity, and extreme high wind speed could increase the risk of PTB. Moreover, low temperature and low humidity, low temperature and low wind speed may increase the incidence of PTB.

Interactions between extreme climate and urban morphology: Investigating the evolution of extreme wind speeds from mesoscale to microscale

This paper investigates the interactions between urban morphology indicators and extreme weather variables. In this regard, variations of wind speed and air temperature at the urban microscale are studied for three urban morphologies by means of numerical simulations. Each urban model contains ninety-nine calculation points at different locations and heights to assess the variations during two 24-h cycles of extreme low and high wind speeds by introducing a microscale indicator. According to the results, transforming from mesoscale to microscale can considerably dampen the magnitude of wind speed (up to 66%) and amplify the air temperature (up to 39%). Moreover, the urban morphology parameters (layout geometry, final height and urban density) can change the average magnitude of wind speed (up to 23%) and air temperature (up to 16%) at microscale. For extreme low wind speeds (0.16–1.14 m/s), strong correlations exist between the mesoscale and microscale magnitude of wind speed and air temperature, while there is no significant correlation for extreme high wind speeds (12.2–14 m/s). For extreme low wind speeds, stronger buoyancy effects are observed at the urban canopies. An easy-to-setup approach is proposed to count for microscale conditions during extreme low wind speeds in urban climate studies.

The Long Term Variations of Tropical Cyclone Activity in the South China Sea and the Vicinity of Hong Kong

ABSTRACT This study examines the long-term variations of tropical cyclone (TC) frequency and intensity in the South China Sea (SCS) and the vicinity of Hong Kong from 1961 to 2010 based on the best track data of four main weather agencies in the western North Pacific, namely the Hong Kong Observatory, China Meteorological Administration, Regional Specialized Meteorological Center Tokyo and Joint Typhoon Warning Center of the United States. To account for the discrepancy in the best track data between agencies, the maximum sustained wind speeds are standardized to the 10-minute average before data analysis. Moreover, a sensitivity assessment based on three different data scenarios is also conducted to study the uncertainty in trend analysis due to the discrepancy in the datasets from various agencies. the results show that, likely modulated by the El Nino Southern Oscillation and the Pacific Decadal Oscillation, there exist strong inter-annual and inter-decadal variations in the TC frequency in the SCS and the vicinity of Hong Kong. For the long-term trend, all dataset/scenario combinations depict a decrease in the TC frequency in the SCS and the vicinity of Hong Kong during the study period, but the trend is not statistically significant at 5% level for most of the datasets. As for the TC intensity, the discrepancy between weather agencies remains very substantial even when the difference in the wind speed averaging period is accounted for. The large differences in the available datasets do not allow for a reliable detection of the long-term trend of the TC intensity in the SCS. The study of the TC impacts on Hong Kong reveals that there is no significant trend on the TC-induced extreme rainfall in Hong Kong. The extreme high winds associated with TCs within 500 km range of Hong Kong have no significant trend at Waglan Island (offshore island) while those of the urban station at Kai Tak have a significant decreasing trend.

Impacts of Storm-Track Variations on Wintertime Extreme Weather Events over the Continental United States

Extratropical cyclones are responsible for many of the high-impact weather events over the United States, including extreme cold, extreme high wind, and extreme heavy precipitation. In this study, impacts from the variations of the cyclone (or storm-track) activity on these extreme events are examined through composites based on map-averaged cyclone activity. Increased cyclone activity enhances the frequency of extreme cold and high wind events over much of the United States, and impacts extreme precipitation around the Ohio River valley. These impacts are largely due to a changing of the tail of the distribution rather than a shifting of the mean. To systematically study these impacts, three singular value decomposition (SVD) analyses have been conducted, each one between the cyclone activity and one kind of extreme event frequency. All three SVD leading modes represent a pattern of overall increase or decrease of storm tracks over the United States. The average of the time series of these leading modes is highly correlated with the observed map-averaged storm track and strongly associated with the Pacific–North America (PNA) pattern and El Niño–Southern Oscillation (ENSO). However, composites based on either the PNA pattern or ENSO do not show as strong impacts as the map-averaged storm track. A second common SVD mode is found that correlates weakly with the North Pacific mode and is likely to be largely due to internal variability. Finally, the potential impacts of projected storm-track change on the frequency of extreme events are examined, indicating that the projected storm-track decrease over North America may give rise to some reduction in the frequency of extreme events.

Extreme Weather and Climate Change in the American Mind, April 2013

This report is based on findings from a nationally representative survey – Climate Change in the American Mind – conducted by the Yale Project on Climate Change Communication and the George Mason University Center for Climate Change Communication. Interview dates: April 8 - 15, 2013. Interviews: 1,045 Adults (18+) Total average margin of error: +/- 3 percentage points at the 95% confidence level; regional margins of error are +/- 7 percentage points for the Northeast and West; +/- 6 percentage points for the Midwest; and +/- 5 percentage points for the South.Key findings include:• About six in ten Americans (58%) say “global warming is affecting weather in the United States.”• Many Americans believe global warming made recent extreme weather and climatic events “more severe,” specifically: 2012 as the warmest year on record in the United States (50%); the ongoing drought in the Midwest and the Great Plains (49%); Superstorm Sandy (46%); and Superstorm Nemo (42%).• About two out of three Americans say weather in the U.S. has been worse over the past several years, up 12 percentage points since Spring 2012. By contrast, fewer Americans say weather has been getting better over the past several years – only one in ten (11%), down 16 points compared to a year ago.• Many Americans (51%) also say weather in their local area has been worse over the past several years.• Overall, 85 percent of Americans report that they experienced one or more types of extremeweather in the past year, most often citing extreme high winds (60%) and extreme heat (51%).• Of those Americans who experienced extreme weather events in the past year, many (37%) say they were significantly harmed. Moreover, the number who have been harmed appears to be growing (up 5 percentage points since Fall 2012 and 4 points since Spring 2012). For example, about one in five Americans today say they suffered a moderate or great deal of harm from extreme high winds (18%, up 8 points since Fall 2012) or extreme cold weather (10%, up 5 points). More also say they were harmed by a hurricane (6%, up 3 points).• Most Americans (80%) have close friends or family members (not living with them) who experienced extreme weather events in the past year, including extreme high winds (47%), an extreme heat wave (46%), an extreme snowstorm (39%), extreme cold temperatures (39%), an extreme rainstorm (37%), or a drought (35%).• Over half of Americans (54%) believe it is “very” or “somewhat likely” that extreme weather will cause a natural disaster in their community in the coming year.• Americans who experienced an extreme weather event are most likely to have communicated about it person-to-person – either in person (89%) or on the phone (84%) – although some used social media, such as writing about the experience on Facebook (23%) or sharing a photo of the event or its aftermath using Facebook, Tumblr, or Instagram (19%).

QuikSCAT geophysical model function for tropical cyclones and application to Hurricane Floyd

The QuikSCAT radar measurements of several tropical cyclones in 1999 have been studied to develop the geophysical model function (GMF) of Ku-band radar /spl sigma//sub 0/ values (normalized radar cross section) for extreme high wind conditions. To account for the effects of precipitation, the authors analyze the co-located rain rates from the Special Sensor Microwave/Imager (SSM/I) and propose the rain rate as a parameter of the GMF. The analysis indicates the deficiency of the NSCAT2 GMF developed for the NASA scatterometer, which overestimates the ocean /spl sigma//sub 0/ for tropical cyclones and ignores the influence of rain. It is suggested that the QuikSCAT /spl sigma//sub 0/ is sensitive to the wind speed of up to about 40-50 m s/sup -1/. The authors introduce modifications to the NSCAT2 GMF and apply the modified GMF to the QuikSCAT observations of Hurricane Floyd. The QuikSCAT wind estimates for Hurricane Floyd in 1999 was improved with the maximum wind speed reaching above 60 m s/sup -1/. The authors perform an error analysis by comparing the QuikSCAT winds with the analyses fields from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD). The reasonable agreement between the improved QuikSCAT winds and the HRD analyses supports the applications of scatterometer wind retrievals for hurricanes.

On the fitting of low mean windspeed data to the Weibull distribution

Information on the frequency of occurrence of mean windspeeds between certain limits is required for a range of applications. These cover all possible windspeed values, from extreme high winds, for wind loading applications, through moderate winds for wind energy or building ventilation applications down to low windspeeds for use in risk assessments, where, although all windspeeds are relevant, these low values dominate the risk from accidental releases. The fitting of wind data to statistical distributions has previously been focused primarily on the moderate windspeed range, partly because of the applications considered, but also because of the paucity of high windspeed data, and the poor quality of most of the available low windspeed data. This paper uses good quality data, obtained from sonic or lightweight cup anemometers, to demonstrate the applicability of the Weibull distribution over the complete windspeed range.