Stochastic weather generator for diurnal temperature range

High daily temperatures in the Mediterranean and Europe have been documented in observation and modeling studies. Long-term temperature data, from 1988 to 2017, from a suburban station and an urban station in Nicosia, Cyprus have been analyzed, and the diurnal temperature range (DTR) trend was investigated. The seasonal Mann–Kendall test revealed a decreasing DTR trend of −0.24 °C/decade at the urban station and −0.36 °C/decade at the suburban station, which were attributed to an increase in the daily minimum temperature. Variations in precipitation, longwave radiation, ultraviolet-A (UVA), ultraviolet-B (UVB), cloud cover, water vapor, and urbanization were used to assess their possible relationship with regional DTR. The clustering of daytime and night-time data showed a strong relationship between the DTR and observed cloud cover, net longwave radiation, and precipitation. Clouds associated with smaller shortwave and net longwave radiation reduce the DTR by decreasing the surface solar radiation, while atmospheric absolute humidity denotes an increased daytime surface evaporative cooling and higher absorption of the short and longwave radiation. The intra-cluster variation could be reduced, and the inter-cluster variance increased by the addition of other meteorological parameters and anthropogenic sources that affect DTR in order to develop a quantitative basis for assessing DTR variations.

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The Association Between Diurnal Temperature Range and Clinic Visits for Upper Respiratory Tract Infection Among College Students in Wuhan, China

10.21203/rs.3.rs-483728/v1 ◽

2021 ◽

Author(s):

Faxue Zhang ◽

Chuangxin Wu ◽

Miaoxuan Zhang ◽

Han Zhang ◽

Huan Feng ◽

...

Keyword(s):

College Students ◽

Tract Infection ◽

Respiratory Tract ◽

Respiratory Tract Infection ◽

Diurnal Temperature Range ◽

Upper Respiratory Tract ◽

Diurnal Temperature ◽

Temperature Range ◽

Outpatient Visits ◽

Upper Respiratory

Abstract The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature in the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for upper respiratory tract infection (URTI) among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were provided by the Hospital of Wuhan University from January 1, 2016 to November 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 ℃ increased in DTR was associated with 0.89% (95%CI: 0.40, 1.38) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.83% (95%CI: 0.81, 2.86)], and in females [1.44% (95%CI: 0.51, 2.38)] at lag 0–6 days. DTR had more adverse health impact in the warm season than that in the cold season. Public health departments should consider the negative effect of DTR to formulate more effective preventive and control measures for protecting vulnerable people.

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Deep learning models' comparable assessment and uncertainty analysis for diurnal temperature range (DTR) predictions over indian urban cities

Results in Engineering ◽

10.1016/j.rineng.2021.100326 ◽

2021 ◽

pp. 100326

Author(s):

Sovan Sankalp ◽

Bibhuti Bhusan Sahoo ◽

Sanat Nalini Sahoo

Keyword(s):

Deep Learning ◽

Uncertainty Analysis ◽

Diurnal Temperature Range ◽

Learning Models ◽

Diurnal Temperature ◽

Temperature Range

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Association between meteorological factors and audiogram configurations in patients with sudden sensorineural hearing loss: a cross-sectional study

BMJ Open ◽

10.1136/bmjopen-2020-045768 ◽

2021 ◽

Vol 11 (12) ◽

pp. e045768

Author(s):

Jilei Zhang ◽

Shangwei Ji ◽

Xin Ma ◽

Lisheng Yu ◽

Yuanyuan Jing

Keyword(s):

Hearing Loss ◽

Relative Humidity ◽

Sensorineural Hearing Loss ◽

Diurnal Temperature Range ◽

Meteorological Factors ◽

Sudden Sensorineural Hearing Loss ◽

Sensorineural Hearing ◽

Secondary Outcome ◽

Diurnal Temperature ◽

Temperature Range

ObjectiveWe aimed to determine the association between meteorological factors and sudden sensorineural hearing loss (SSNHL) audiogram configurations.DesignRetrospective review of medical records from 1 October 2007 to 31 December 2018.SettingA tertiary hospital.Participants510 patients with SSNHL who had data on the exact date of SSNHL onset and underwent audiological evaluation within 14 days were included.Primary and secondary outcome measuresDaily values of meteorological factors, including maximum and minimum temperature, mean temperature and its day-to-day change, diurnal temperature range, atmospheric pressure, mean and maximum wind speed and relative humidity, and seasonal distributions.ResultsAmong the 510 patients (259 women (50.8%); mean (SD) age, 46.4 (15.5) years), 108 (21.2%) displayed ascending patterns, 143 (28.0%) displayed descending patterns, 129 (25.3%) displayed flat patterns and 130 (25.5%) displayed profound patterns of audiograms. The diurnal temperature range on the day of SSNHL onset in patients with profound patterns was significantly higher than that in patient with ascending (mean difference (MD), 2.2°C; 95% CI, 0.7°C to 3.7°C; p=0.001) and descending (MD, 1.5°C; 95% CI, 0.1°C to 2.9°C; p=0.031) patterns. The relative humidity was the highest on the day of SSNHL onset in patients with ascending patterns and showed a significant difference compared with that in patients with profound patterns (MD, 8.0%; 95% CI, 0.7% to 15.3%; p=0.026). Seasonal distribution did not differ among patients with different audiogram configurations.ConclusionsProfound audiogram patterns correlated with high diurnal temperature range, while ascending audiogram patterns correlated with high relative humidity in patients with SSNHL. No correlation was observed between seasons and audiogram configurations.

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