scholarly journals Immediate and Delayed Meteorological Effects on COVID-19 Time-Varying Infectiousness in Tropical Cities

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 513
Author(s):  
Xerxes Seposo ◽  
Chris Fook Sheng Ng ◽  
Lina Madaniyazi
Keyword(s):  
Model Fitting ◽  
Additive Model ◽  
The Philippines ◽  
Air Pressure ◽  
Dew Point ◽  
Outcome Variable ◽  
Climatic Data ◽  
Time Varying ◽  
Rt Pcr ◽  
National Climatic Data Center

The novel coronavirus, which was first reported in Wuhan, China in December 2019, has been spreading globally at an unprecedented rate, leading to the virus being declared a global pandemic by the WHO on 12 March 2020. The clinical disease, COVID-19, associated with the pandemic is caused by the pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Aside from the inherent transmission dynamics, environmental factors were found to be associated with COVID-19. However, most of the evidence documenting the association was from temperate locations. In this study, we examined the association between meteorological factors and the time-varying infectiousness of COVID-19 in the Philippines. We obtained the daily time series from 3 April 2020 to 2 September 2020 of COVID-19 confirmed cases from three major cities in the Philippines, namely Manila, Quezon, and Cebu. Same period city-specific daily average temperature (degrees Celsius; °C), dew point (degrees Celsius; °C), relative humidity (percent; %), air pressure (kilopascal; kPa), windspeed (meters per second; m/s) and visibility (kilometer; km) data were obtained from the National Oceanic and Atmospheric Administration—National Climatic Data Center. City-specific COVID-19-related detection and intervention measures such as reverse transcriptase polymerase chain reaction (RT-PCR) testing and community quarantine measures were extracted from online public resources. We estimated the time-varying reproduction number (Rt) using the serial interval information sourced from the literature. The estimated Rt was used as an outcome variable for model fitting via a generalized additive model, while adjusting for relevant covariates. Results indicated that a same-day and the prior week’s air pressure was positively associated with an increase in Rt by 2.59 (95% CI: 1.25 to 3.94) and 2.26 (95% CI: 1.02 to 3.50), respectively. Same-day RT-PCR was associated with an increase in Rt, while the imposition of community quarantine measures resulted in a decrease in Rt. Our findings suggest that air pressure plays a role in the infectiousness of COVID-19. The determination of the association of air pressure on infectiousness, aside from the testing frequency and community quarantine measures, may aide the current health systems in controlling the COVID-19 infectiousness by integrating such information into an early warning platform.

scholarly journals 1981–2010 U.S. Hourly Normals

2012 ◽  
Vol 93 (11) ◽  
pp. 1637-1640 ◽  
Author(s):  
Scott Applequist ◽  
Anthony Arguez ◽  
Imke Durre ◽  
Michael F. Squires ◽  
Russell S. Vose ◽  
...  
Keyword(s):  
Data Center ◽  
The United States ◽  
Descriptive Statistics ◽  
Dew Point ◽  
Heat Index ◽  
Climatic Data ◽  
Sea Level Pressure ◽  
Wind Chill ◽  
National Climatic Data Center ◽  
Heating And Cooling

The 1981–2010 U.S. Climate Normals released by the National Oceanic and Atmospheric Administration's (NOAA) National Climatic Data Center (NCDC) include a suite of descriptive statistics based on hourly observations. For each hour and day of the year, statistics of temperature, dew point, mean sea level pressure, wind, clouds, heat index, wind chill, and heating and cooling degree hours are provided as 30-year averages, frequencies of occurrence, and percentiles. These hourly normals are available for 262 locations, primarily major airports, from across the United States and its Pacific territories. We encourage use of these products specifically for examination of the diurnal cycle of a particular variable, and how that change may shift over the annual cycle.

scholarly journals Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Serdar Neslihanoglu
Keyword(s):  
State Space Model ◽  
Additive Model ◽  
Market Model ◽  
Time Varying ◽  
Daily Data ◽  
Forecasting Performance ◽  
Modeling And Forecasting ◽  
Crypto Currency ◽  
Beta Risk ◽  
The Relationship

AbstractThis research investigates the appropriateness of the linear specification of the market model for modeling and forecasting the cryptocurrency prices during the pre-COVID-19 and COVID-19 periods. Two extensions are offered to compare the performance of the linear specification of the market model (LMM), which allows for the measurement of the cryptocurrency price beta risk. The first is the generalized additive model, which permits flexibility in the rigid shape of the linearity of the LMM. The second is the time-varying linearity specification of the LMM (Tv-LMM), which is based on the state space model form via the Kalman filter, allowing for the measurement of the time-varying beta risk of the cryptocurrency price. The analysis is performed using daily data from both time periods on the top 10 cryptocurrencies by adjusted market capitalization, using the Crypto Currency Index 30 (CCI30) as a market proxy and 1-day and 7-day forward predictions. Such a comparison of cryptocurrency prices has yet to be undertaken in the literature. The empirical findings favor the Tv-LMM, which outperforms the others in terms of modeling and forecasting performance. This result suggests that the relationship between each cryptocurrency price and the CCI30 index should be locally instead of globally linear, especially during the COVID-19 period.

Parametric study on pressure-based packed bed adsorption system for air dehumidification

2021 ◽  
pp. 095440892110073
Author(s):  
V Sureshkannan ◽  
TV Arjunan ◽  
D Seenivasan ◽  
SP Anbuudayasankar ◽  
M Arulraj
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Flow Rate ◽  
Uptake Rate ◽  
Air Flow ◽  
Packed Bed ◽  
Air Pressure ◽  
Dew Point ◽  
Adsorption System ◽  
Air Flow Rate

Compressed air free from traces of water vapour is vital in many applications in an industrial sector. This study focuses on parametric optimization of a pressure-based packed bed adsorption system for air dehumidification through the Taguchi method and Genetic Algorithm. The effect of operational parameters, namely absolute feed air pressure, feed air linear velocity, and purge air flow rate percent on adsorption uptake rate of molecular sieve 13X-water pair, are studied based on L25 orthogonal array. From the analysis of variance, it has been found that absolute feed air pressure and purge air flow rate percent were the parameters making significant improvement in the adsorption uptake rate. A correlation representing the process was developed using regression analysis. The optimum adsorption conditions were obtained through the Taguchi method and genetic algorithm and verified through the confirmation experiments. This system can be recommended for the industrial and domestic applications that require product air with the dew point temperature below 0°C.

scholarly journals U.S. Climate Reference Network Soil Moisture and Temperature Observations

2013 ◽  
Vol 14 (3) ◽  
pp. 977-988 ◽  
Author(s):  
Jesse E. Bell ◽  
Michael A. Palecki ◽  
C. Bruce Baker ◽  
William G. Collins ◽  
Jay H. Lawrimore ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Performance Studies ◽  
Climate Science ◽  
Reference Network ◽  
Climatic Data ◽  
Soil Sensors ◽  
National Climatic Data Center ◽  
Temperature And Precipitation ◽  
And Performance ◽  
Soil Climate

Abstract The U.S. Climate Reference Network (USCRN) is a network of climate-monitoring stations maintained and operated by the National Oceanic and Atmospheric Administration (NOAA) to provide climate-science-quality measurements of air temperature and precipitation. The stations in the network were designed to be extensible to other missions, and the National Integrated Drought Information System program determined that the USCRN could be augmented to provide observations that are more drought relevant. To increase the network’s capability of monitoring soil processes and drought, soil observations were added to USCRN instrumentation. In 2011, the USCRN team completed at each USCRN station in the conterminous United States the installation of triplicate-configuration soil moisture and soil temperature probes at five standards depths (5, 10, 20, 50, and 100 cm) as prescribed by the World Meteorological Organization; in addition, the project included the installation of a relative humidity sensor at each of the stations. Work is also under way to eventually install soil sensors at the expanding USCRN stations in Alaska. USCRN data are stewarded by the NOAA National Climatic Data Center, and instrument engineering and performance studies, installation, and maintenance are performed by the NOAA Atmospheric Turbulence and Diffusion Division. This article provides a technical description of the USCRN soil observations in the context of U.S. soil-climate–measurement efforts and discusses the advantage of the triple-redundancy approach applied by the USCRN.

scholarly journals The Regional Snowfall Index

2014 ◽  
Vol 95 (12) ◽  
pp. 1835-1848 ◽  
Author(s):  
Michael F. Squires ◽  
Jay H. Lawrimore ◽  
Richard R. Heim ◽  
David A. Robinson ◽  
Mathieu R. Gerbush ◽  
...  
Keyword(s):  
United States ◽  
Data Center ◽  
Historical Perspective ◽  
The United States ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Impact Scale ◽  
Population Information ◽  
Regional Index ◽  
The Impact

This paper describes a new snowfall index that quantifies the impact of snowstorms within six climate regions in the United States. The regional snowfall index (RSI) is based on the spatial extent of snowfall accumulation, the amount of snowfall, and the juxtaposition of these elements with population. Including population information provides a measure of the societal susceptibility for each region. The RSI is an evolution of the Northeast snowfall impact scale (NESIS), which NOAA's National Climatic Data Center began producing operationally in 2006. While NESIS was developed for storms that had a major impact in the Northeast, it includes all snowfall during the lifetime of a storm across the United States and as such can be thought of as a quasi-national index that is calibrated to Northeast snowstorms. By contrast, the RSI is a regional index calibrated to specific regions using only the snow that falls within that region. This paper describes the methodology used to compute the RSI, which requires region-specific parameters and thresholds, and its application within six climate regions in the eastern two-thirds of the nation. The process used to select the region-specific parameters and thresholds is explained. The new index has been calculated for over 580 snowstorms that occurred between 1900 and 2013 providing a century-scale historical perspective for these snowstorms. The RSI is computed for category 1 or greater storms in near–real time, usually a day after the storm has ended.

scholarly journals Identification allergen Cladosporium spores concentration in the ambient of Ahvaz wastewater treatment plant and their relationship with meteorological variables, Ahvaz, Iran

2020 ◽  
Author(s):  
Nastaran Talepour ◽  
Mohammad Sadegh Hassanvand ◽  
Effat Abbasi-Montazeri ◽  
Seyed Mahmoud Latifi ◽  
Neamat Jaafarzadeh Haghighi Fard
Keyword(s):  
Wastewater Treatment ◽  
Wind Speed ◽  
Meteorological Parameters ◽  
Treatment Plant ◽  
Allergic Diseases ◽  
Airborne Fungi ◽  
Air Pressure ◽  
Dew Point ◽  
Uv Index ◽  
Ultraviolet Index

Introduction: Airborne Cladosporium spores in different regions of the world are known as the main cause of allergic diseases. This study aimed to identify the Cladosporium species airborne fungi in Ahvaz wastewater treat- ment plant area and its adjacent places and check the effect of some meteoro- logical parameters on their emissions. Materials and methods: Cladosporium spores were cultured on Sabouraud`s dextrose agar (SDA) medium in both cold and warm seasons. The passive sampling method was performed and after incubation, colonies were counted as CFU/Plate/h. Then, according to the macroscopic and microscopic charac- teristics of the genus, the fungal was studied. The meteorological parameters including temperature, humidity, air pressure, dew point, wind speed, and ultraviolet index were measured. Results: At least, 3358 colonies were counted. 1433 colonies were related  to the Cladosporium species. The amount of Cladosporium in indoor air was 46% of the total Cladosporium. The average of meteorological parameters includes temperature, humidity, air pressure, dew point, wind speed and UV index during the study were 27.8 °C, 32.9%, 548.7 °Kpa, 3.6°, 9.1 km / h and 3.9 respectively. 42.6% of the total number of colonies was related to the Cladosporium species. Cladospiromes had a direct correlation with the dew point, temperature, humidity, air pressure, wind speed, and ultraviolet index (Pvalue<0.05). Primary sludge dewatering has the greatest role in the Cladospo- rium spores emission. Conclusion: Considering the importance of Cladosporium spores in the ap- pearance of allergic diseases, and given that wastewater treatment workers spend most of their time outside, observing health and preventive measures is necessary in this regard.

scholarly journals An Evaluation of the Statistics of Rainfall Extremes in Rain Gauge Observations, and Satellite-Based and Reanalysis Products Using Universal Multifractals

2010 ◽  
Vol 11 (2) ◽  
pp. 388-404 ◽  
Author(s):  
Xiaoming Sun ◽  
Ana P. Barros
Keyword(s):  
Time Series ◽  
Extreme Rainfall ◽  
Global Precipitation Climatology Project ◽  
Rain Gauge ◽  
Climatic Data ◽  
Statistics Of Extremes ◽  
Maximum Rainfall ◽  
Climatic Regions ◽  
National Climatic Data Center ◽  
Rainfall Extremes

Abstract Confidence in the estimation of variations in the frequency of extreme events, and specifically extreme precipitation, in response to climate variability and change is key to the development of adaptation strategies. One challenge to establishing a statistical baseline of rainfall extremes is the disparity among the types of datasets (observations versus model simulations) and their specific spatial and temporal resolutions. In this context, a multifractal framework was applied to three distinct types of rainfall data to assess the statistical differences among time series corresponding to individual rain gauge measurements alone—National Climatic Data Center (NCDC), model-based reanalysis [North America Regional Reanalysis (NARR) grid points], and satellite-based precipitation products [Global Precipitation Climatology Project (GPCP) pixels]—for the western United States (west of 105°W). Multifractal analysis provides general objective metrics that are especially adept at describing the statistics of extremes of time series. This study shows that, as expected, multifractal parameters estimated from the NCDC rain gauge dataset map the geography of known hydrometeorological phenomena in the major climatic regions, including the strong orographic gradients from west to east; whereas the NARR parameters reproduce the spatial patterns of NCDC parameters, but the frequency of large rainfall events, the magnitude of maximum rainfall, and the mean intermittency are underestimated. That is, the statistics of the NARR climatology suggest milder extremes than those derived from rain gauge measurements. The spatial distributions of GPCP parameters closely match the NCDC parameters over arid and semiarid regions (i.e., the Southwest), but there are large discrepancies in all parameters in the midlatitudes above 40°N because of reduced sampling. This study provides an alternative independent backdrop to benchmark the use of reanalysis products and satellite datasets to assess the effect of climate change on extreme rainfall.

TROPICAL CYCLONE WINDS AT LANDFALL: The ASOS–C-MAN Wind Exposure Documentation Project

2004 ◽  
Vol 85 (6) ◽  
pp. 845-852 ◽  
Author(s):  
Mark Powell ◽  
David Bowman ◽  
David Gilhousen ◽  
Shirley Murillo ◽  
Nick Carrasco ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Building Design ◽  
Web Pages ◽  
Climatic Data ◽  
National Climatic Data Center ◽  
Wind Exposure ◽  
Wind Measurements ◽  
Weather Stations ◽  
Aerodynamic Roughness ◽  
American Society

Photographs describing the wind exposure at automatic weather stations susceptible to tropical cyclones are now available on Web pages at the National Climatic Data Center and the National Data Buoy Center. Given the exposure for one of eight wind direction sectors, a user may estimate the aerodynamic roughness and correct mean wind measurements to an open-terrain exposure. The open-terrain exposure is consistent with the tropical cyclone advisories and forecasts issued by the National Weather Service, as well as building design wind load standards published by the American Society of Civil Engineers.

Sign in / Sign up

Export Citation Format

Share Document