Academic Librarians in Data Information Literacy Instruction: A Case Study in Meteorology

ERIC Educational Resources Information Center

Frank, Emily P.; Pharo, Nils

2016-01-01

E-science has reshaped meteorology due to the rate data is generated, collected, analyzed, and stored and brought data skills to a new prominence. Data information literacy--the skills needed to understand, use, manage, share, work with, and produce data--reflects the confluence of data skills with information literacy competencies. This research…

How well do meteorological indicators represent agricultural and forest drought across Europe?

NASA Astrophysics Data System (ADS)

Bachmair, S.; Tanguy, M.; Hannaford, J.; Stahl, K.

2018-03-01

Drought monitoring and early warning (M&EW) systems are an important component of agriculture/silviculture drought risk assessment. Many operational information systems rely mostly on meteorological indicators, and a few incorporate vegetation state information. However, the relationships between meteorological drought indicators and agricultural/silvicultural drought impacts vary across Europe. The details of this variability have not been elucidated sufficiently on a continental scale in Europe to inform drought risk management at administrative scales. The objective of this study is to fill this gap and evaluate how useful the variety of meteorological indicators are to assess agricultural/silvicultural drought across Europe. The first part of the analysis systematically linked meteorological drought indicators to remote sensing based vegetation indices (VIs) for Europe at NUTs3 administrative regions scale using correlation analysis for crops and forests. In a second step, a stepwise multiple linear regression model was deployed to identify variables explaining the spatial differences observed. Finally, corn crop yield in Germany was chosen as a case study to verify VIs’ representativeness of agricultural drought impacts. Results show that short accumulation periods of SPI and SPEI are best linked to crop vegetation stress in most cases, which further validates the use of SPI3 in existing operational drought monitors. However, large regional differences in correlations are also revealed. Climate (temperature and precipitation) explained the largest proportion of variance, suggesting that meteorological indices are less informative of agricultural/silvicultural drought in colder/wetter parts of Europe. These findings provide important context for interpreting meteorological indices on widely used national to continental M&EW systems, leading to a better understanding of where/when such M&EW tools can be indicative of likely agricultural stress and impacts.

Monitoring hand, foot and mouth disease by combining search engine query data and meteorological factors.

PubMed

Huang, Da-Cang; Wang, Jin-Feng

2018-01-15

Hand, foot and mouth disease (HFMD) has been recognized as a significant public health threat and poses a tremendous challenge to disease control departments. To date, the relationship between meteorological factors and HFMD has been documented, and public interest of disease has been proven to be trackable from the Internet. However, no study has explored the combination of these two factors in the monitoring of HFMD. Therefore, the main aim of this study was to develop an effective monitoring model of HFMD in Guangzhou, China by utilizing historical HFMD cases, Internet-based search engine query data and meteorological factors. To this end, a case study was conducted in Guangzhou, using a network-based generalized additive model (GAM) including all factors related to HFMD. Three other models were also constructed using some of the variables for comparison. The results suggested that the model showed the best estimating ability when considering all of the related factors. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluating Aerosol Process Modules within the Framework of the Aerosol Modeling Testbed

NASA Astrophysics Data System (ADS)

Fast, J. D.; Velu, V.; Gustafson, W. I.; Chapman, E.; Easter, R. C.; Shrivastava, M.; Singh, B.

2012-12-01

Factors that influence predictions of aerosol direct and indirect forcing, such as aerosol mass, composition, size distribution, hygroscopicity, and optical properties, still contain large uncertainties in both regional and global models. New aerosol treatments are usually implemented into a 3-D atmospheric model and evaluated using a limited number of measurements from a specific case study. Under this modeling paradigm, the performance and computational efficiency of several treatments for a specific aerosol process cannot be adequately quantified because many other processes among various modeling studies (e.g. grid configuration, meteorology, emission rates) are different as well. The scientific community needs to know the advantages and disadvantages of specific aerosol treatments when the meteorology, chemistry, and other aerosol processes are identical in order to reduce the uncertainties associated with aerosols predictions. To address these issues, an Aerosol Modeling Testbed (AMT) has been developed that systematically and objectively evaluates new aerosol treatments for use in regional and global models. The AMT consists of the modular Weather Research and Forecasting (WRF) model, a series testbed cases for which extensive in situ and remote sensing measurements of meteorological, trace gas, and aerosol properties are available, and a suite of tools to evaluate the performance of meteorological, chemical, aerosol process modules. WRF contains various parameterizations of meteorological, chemical, and aerosol processes and includes interactive aerosol-cloud-radiation treatments similar to those employed by climate models. In addition, the physics suite from the Community Atmosphere Model version 5 (CAM5) have also been ported to WRF so that they can be tested at various spatial scales and compared directly with field campaign data and other parameterizations commonly used by the mesoscale modeling community. Data from several campaigns, including the 2006 MILAGRO, 2008 ISDAC, 2008 VOCALS, 2010 CARES, and 2010 CalNex campaigns, have been incorporated into the AMT as testbed cases. Data from operational networks (e.g. air quality, meteorology, satellite) are also included in the testbed cases to supplement the field campaign data. The CARES and CalNex testbed cases are used to demonstrate how the AMT can be used to assess the strengths and weaknesses of simple and complex representations of aerosol processes in relation to computational cost. Anticipated enhancements to the AMT and how this type of testbed can be used by the scientific community to foster collaborations and coordinate aerosol modeling research will also be discussed.

Climatology of meteorological ``bombs'' in the New Zealand region

NASA Astrophysics Data System (ADS)

Leslie, L. M.; Leplastrier, M.; Buckley, B. W.; Qi, L.

2005-06-01

The purpose of this paper is to present a recently developed climatology of explosively developing south eastern Tasman Sea extra-tropical cyclones, or meteorological “bombs”, using a latitude dependent definition for meteorological bombs based on that of Simmonds and Keay (2000a, b), and Lim and Simmonds (2002). These highly transient systems, which have a damaging impact upon New Zealand, are frequently accompanied by destructive winds, flood rains, and coastal storm surges. Two cases are selected from the climatology and briefly described here. The first case study is the major flood and storm force wind event of June 20 to 21, 2002 that affected the Coromandel Peninsula region of the North Island of New Zealand. The second case was a “supercyclone” bomb that developed well to the southwest of New Zealand region during May 29 to 31, 2004, but which could easily have formed in the New Zealand region with catastrophic consequences. It was well-captured by the new high resolution Quikscat scatterometer instrument.

Long-term weather predictability: Ural case study

NASA Astrophysics Data System (ADS)

Kubyshen, Alexander; Shopin, Sergey

2016-04-01

The accuracy of the state-of-the-art long-term meteorological forecast (at the seasonal level) is still low. Here it is presented approach (RAMES method) realizing different forecasting methodology. It provides prediction horizon of up to 19-22 years under equal probabilities of determination of parameters in every analyzed period [1]. Basic statements of the method are the following. 1. Long-term forecast on the basis of numerical modeling of the global meteorological process is principally impossible. Extension of long-term prediction horizon could be obtained only by the revealing and using a periodicity of meteorological situations at one point of observation. 2. Conventional calendar is unsuitable for generalization of meteorological data and revealing of cyclicity of meteorological processes. RAMES method uses natural time intervals: one day, synodic month and one year. It was developed a set of special calendars using these natural periods and the Metonic cycle. 3. Long-term time series of meteorological data is not a uniform universal set, it is a sequence of 28 universal sets appropriately superseding each other in time. The specifics of the method are: 1. Usage of the original research toolkit consisting of - a set of calendars based on the Metonic cycle; - a set of charts (coordinate systems) for the construction of sequence diagrams (of daily variability of a meteorological parameter during the analyzed year; of daily variability of a meteorological parameter using long-term dynamical time series of periods-analogues; of monthly and yearly variability of accumulated value of meteorological parameter). 2. Identification and usage of new virtual meteorological objects having several degrees of generalization appropriately located in the used coordinate systems. 3. All calculations are integrated into the single technological scheme providing comparison and mutual verification of calculation results. During the prolonged testing in the Ural region, it was proved the efficiency of the method for forecasting the following meteorological parameters: ­- air temperature (minimum, maximum, daily mean, diurnal variation, last spring and first autumn freeze); - periods of winds with speeds of >5m/s and the maximal expected wind speed; - precipitation periods and amount of precipitations; -­ relative humidity; - atmospheric pressure. Atmospheric events (thunderstorms, fog) and hydrometeors also occupy the appropriate positions at the sequence diagrams that provides a possibility of long-term forecasting also for these events. Accuracy of forecasts was tested in 2006-2009 years. The difference between the forecasted monthly mean temperature and actual values was <0.5°C in 40.9% of cases, between 0.5°C and 1°C in 18.2% of cases, between 1°C and 1.5°C in 18.2% of cases, <2°C in 86% of cases. The RAMES method provides the toolkit to successfully forecast the weather conditions in advance of several years. 1. A.F. Kubyshen, "RAMES method: revealing the periodicity of meteorological processes and it usage for long-term forecast [Metodika «RAMES»: vyjavlenie periodichnosti meteorologicheskih processov i ee ispol'zovanie dlja dolgosrochnogo prognozirovanija]", in A.E. Fedorov (ed.), Sistema «Planeta Zemlja»: 200 let so dnja rozhdenija Izmaila Ivanovicha Sreznevskogo. 100 let so dnja izdanija ego slovarja drevnerusskogo jazyka. LENAND. Moscow. pp. 305-311. (In Russian)

[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

Application of data mining to the analysis of meteorological data for air quality prediction: A case study in Shenyang

NASA Astrophysics Data System (ADS)

Zhao, Chang; Song, Guojun

2017-08-01

Air pollution is one of the important reasons for restricting the current economic development. PM2.5 which is a vital factor in the measurement of air pollution is defined as a kind of suspended particulate matter with its equivalent diameter less than 25μm, which may enter the alveoli and therefore make a great impact on the human body. Meteorological factors are also one of the main factors affecting the production of PM2.5, therefore, it is essential to establish the model between meteorological factors and PM2.5 for the prediction. Data mining is a promising approach to model PM2.5 change, Shenyang which is one of the most important industrial city in Northeast China with severe air pollutions is set as the case city. Meteorological data (wind direction, wind speed, temperature, humidity, rainfall, etc.) from 2013 to 2015 and PM2.5 concentration data are used for this prediction. As to the requirements of the World Health Organization (WHO), three data mining models, whereby the predictions of PM2.5 are directly generated by the meteorological data. After assessment, the random forest model is appeared to offer better prediction performance than the other two. At last, the accuracy of the generated models are analysed.

Occurrence of human respiratory syncytial virus in summer in Japan.

PubMed

Shobugawa, Y; Takeuchi, T; Hibino, A; Hassan, M R; Yagami, R; Kondo, H; Odagiri, T; Saito, R

2017-01-01

In temperate zones, human respiratory syncytial virus (HRSV) outbreaks typically occur in cold weather, i.e. in late autumn and winter. However, recent outbreaks in Japan have tended to start during summer and autumn. This study examined associations of meteorological conditions with the numbers of HRSV cases reported in summer in Japan. Using data from the HRSV national surveillance system and national meteorological data for summer during the period 2007-2014, we utilized negative binomial logistic regression analysis to identify associations between meteorological conditions and reported cases of HRSV. HRSV cases increased when summer temperatures rose and when relative humidity increased. Consideration of the interaction term temperature × relative humidity enabled us to show synergistic effects of high temperature with HRSV occurrence. In particular, HRSV cases synergistically increased when relative humidity increased while the temperature was ⩾28·2 °C. Seasonal-trend decomposition analysis using the HRSV national surveillance data divided by 11 climate divisions showed that summer HRSV cases occurred in South Japan (Okinawa Island), Kyushu, and Nankai climate divisions, which are located in southwest Japan. Higher temperature and higher relative humidity were necessary conditions for HRSV occurrence in summer in Japan. Paediatricians in temperate zones should be mindful of possible HRSV cases in summer, when suitable conditions are present.

Clinical and epidemiological profiles including meteorological factors of low respiratory tract infection due to human rhinovirus in hospitalized children.

PubMed

Yan, Yongdong; Huang, Li; Wang, Meijuan; Wang, Yuqing; Ji, Wei; Zhu, Canhong; Chen, Zhengrong

2017-03-07

Lower respiratory tract infection (LRTI) is a major cause of morbidity and mortality in children. Human rhinovirus (HRV) is confirmed to be associated with pediatric lower respiratory tract infection. Seasonal and meteorological factors may play a key role in the epidemiology of HRV. The purposes of this study were to investigate the frequency, seasonal distribution, and clinical characteristics of hospitalized children with LRTI caused by HRVs. In addition, associations between incidence of HRVs and meteorological factors in a subtropical region of China were discussed. Hospitalized children <14 years old admitted to the Respiratory Department of the Children's Hospital, which is affiliated to Soochow University, between January 1, 2013 and December 31, 2015, were enrolled in this study. Multi-pathogens were detected in nasopharyngeal aspirate samples. Meanwhile, meteorological factors were recorded. The average incidence of HRVs infection was 11.4% (707/6194) and 240 cases of which were co-infection cases with other pathogens. Children with co-infection presented more frequent fever and tachypnea compared to children infected with HRVs only (both P < 0.05). Among 707 HRV positive children, the mean age was 23.2 months (range 1 to 140 months). Among all respiratory infections, the highest incidence of HRVs cases occurred in children age 13-36 months old (15.1%, 203/1341). Of all 228 HRV cases in 2014, 85 cases (37.3%) were HRV-C positive. HRVs and HRV-C infection occurred throughout the year during the study period, although a higher incidence was observed in summer and autumn seasons. HRVs or HRV-C incidence in hospitalized children with LRTI was associated with the monthly mean temperature (both P < 0.05). HRV was one of the most common viral pathogen detected in hospitalized children with LRTI at the Children's Hospital of Suzhou, China, and had its own seasonal distribution including HRV-C, which was partly caused by temperature.

Causes of death and demographic characteristics of victims of meteorological disasters in Korea from 1990 to 2008

PubMed Central

2011-01-01

Background Meteorological disasters are an important component when considering climate change issues that impact morbidity and mortality rates. However, there are few epidemiological studies assessing the causes and characteristics of deaths from meteorological disasters. The present study aimed to analyze the causes of death associated with meteorological disasters in Korea, as well as demographic and geographic vulnerabilities and their changing trends, to establish effective measures for the adaptation to meteorological disasters. Methods Deaths associated with meteorological disasters were examined from 2,045 cases in Victim Survey Reports prepared by 16 local governments from 1990 to 2008. Specific causes of death were categorized as drowning, structural collapse, electrocution, lightning, fall, collision, landslide, avalanche, deterioration of disease by disaster, and others. Death rates were analyzed according to the meteorological type, specific causes of death, and demographic and geographic characteristics. Results Drowning (60.3%) caused the greatest number of deaths in total, followed by landslide (19.7%) and structural collapse (10.1%). However, the causes of deaths differed between disaster types. The meteorological disaster associated with the greatest number of deaths has changed from flood to typhoon. Factors that raised vulnerability included living in coastal provinces (11.3 times higher than inland metropolitan), male gender (1.9 times higher than female), and older age. Conclusions Epidemiological analyses of the causes of death and vulnerability associated with meteorological disasters can provide the necessary information for establishing future adaptation measures against climate change. A more comprehensive system for assessing disaster epidemiology needs to be established. PMID:21943038

Incidences of Waterborne and Foodborne Diseases After Meteorologic Disasters in South Korea.

PubMed

Na, Wonwoong; Lee, Kyeong Eun; Myung, Hyung-Nam; Jo, Soo-Nam; Jang, Jae-Yeon

Climate change could increase the number of regions affected by meteorologic disasters. Meteorologic disasters can increase the risk of infectious disease outbreaks, including waterborne and foodborne diseases. Although many outbreaks of waterborne diseases after single disasters have been analyzed, there have not been sufficient studies reporting comprehensive analyses of cases occurring during long-term surveillance after multiple disasters, which could provide evidence of whether meteorologic disasters cause infectious disease outbreaks. This study aimed to assess the nationwide short-term changes in waterborne and foodborne disease incidences after a meteorologic disaster. We analyzed cases after all 65 floods and typhoons between 2001 and 2009 using the Korean National Emergency Management Agency's reports. Based on these data, we compared the weekly incidences of Vibrio vulnificus septicemia (VVS), shigellosis, typhoid fever, and paratyphoid fever before, during, and after the disasters, using multivariate Poisson regression models. We also analyzed the interactions between disaster characteristics and the relative risk of each disease. Compared with predisaster incidences, the incidences of VVS and shigellosis were 2.49-fold (95% confidence interval, 1.47-4.22) and 3.10-fold (95% confidence interval, 1.21-7.92) higher, respectively, the second week after the disaster. The incidences of VVS and shigellosis peaked the second week postdisaster and subsequently decreased. The risks of typhoid and paratyphoid fever did not significantly increase throughout the 4 weeks postdisaster. The daily average precipitation interacted with VVS and shigellosis incidences, whereas disaster type only interacted with VVS incidence patterns. The incidences of VVS and shigellosis were associated with meteorologic disasters, and disaster characteristics were associated with the disease incidence patterns postdisaster. These findings provide important comprehensive evidence to develop and support policies for managing and protecting public health after meteorologic disasters. Copyright © 2016 Icahn School of Medicine at Mount Sinai. Published by Elsevier Inc. All rights reserved.

A study of model parameters associated with the urban climate using HCMM data. [analysis of St. Louis, Missouri infrared imagery

NASA Technical Reports Server (NTRS)

1981-01-01

Progress in the study of the intensity of the urban heat island is reported. The intensity of the heat island is commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions. The intensity is considered as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. Twelve case studies were selected and CCT's were ordered. In situ data was obtained from sixteen stations scattered about the city of St. Louis. Upper-air meteorological data were obtained and the water vapor and the temperature data were processed. Atmospheric transmissivities were computed for each of the case studies.

The Application of a Technique for Vector Correlation to Problems in Meteorology and Oceanography.

NASA Astrophysics Data System (ADS)

Breaker, L. C.; Gemmill, W. H.; Crosby, D. S.

1994-11-01

In a recent study, Crosby et al. proposed a definition for vector correlation that has not been commonly used in meteorology or oceanography. This definition has both a firm theoretical basis and a rather complete set of desirable statistical properties. In this study, the authors apply the definition to practical problems arising in meteorology and oceanography. In the first of two case studies, vector correlations were calculated between subsurface currents for five locations along the southeastern shore of Lake Erie. Vector correlations for one sample size were calculated for all current meter combinations, first including the seiche frequency and then with the seiche frequency removed. Removal of the seiche frequency, which was easily detected in the current spectra, had only a small effect on the vector correlations. Under reasonable assumptions, the vector correlations were in most cases statistically significant and revealed considerable fine structure in the vector correlation sequences. In some cases, major variations in vector correlation coincided with changes in surface wind. The vector correlations for the various current meter combinations decreased rapidly with increasing spatial separation. For one current meter combination, canonical correlations were also calculated; the first canonical correlation tended to retain the underlying trend, whereas the second canonical correlation retained the peaks in the vector correlations.In the second case study, vector correlations were calculated between marine surface winds derived from the National Meteorological Center's Global Data Assimilation System and observed winds acquired from the network of National Data Buoy Center buoys that are located off the continental United States and in the Gulf of Alaska. Results of this comparison indicated that 1) there was a significant decrease in correlation between the predicted and observed winds with increasing forecast interval out to 72 h, 2) the technique provides a sensitive indicator for detecting bad buoy reports, and 3) there was no obvious seasonal cycle in the monthly vector correlations for the period of observation.

Evaluating the performance of ENVI-met model in diurnal cycles for different meteorological conditions

NASA Astrophysics Data System (ADS)

Acero, Juan A.; Arrizabalaga, Jon

2018-01-01

Urban areas are known to modify meteorological variables producing important differences in small spatial scales (i.e. microscale). These affect human thermal comfort conditions and the dispersion of pollutants, especially those emitted inside the urban area, which finally influence quality of life and the use of public open spaces. In this study, the diurnal evolution of meteorological variables measured in four urban spaces is compared with the results provided by ENVI-met (v 4.0). Measurements were carried out during 3 days with different meteorological conditions in Bilbao in the north of the Iberian Peninsula. The evaluation of the model accuracy (i.e. the degree to which modelled values approach measured values) was carried out with several quantitative difference metrics. The results for air temperature and humidity show a good agreement of measured and modelled values independently of the regional meteorological conditions. However, in the case of mean radiant temperature and wind speed, relevant differences are encountered highlighting the limitation of the model to estimate these meteorological variables precisely during diurnal cycles, in the considered evaluation conditions (sites and weather).

A study on the uncertainty based on Meteorological fields on Source-receptor Relationships for Total Nitrate in the Northeast Asia

NASA Astrophysics Data System (ADS)

Sunwoo, Y.; Park, J.; Kim, S.; Ma, Y.; Chang, I.

2010-12-01

Northeast Asia hosts more than one third of world population and the emission of pollutants trends to increase rapidly, because of economic growth and the increase of the consumption in high energy intensity. In case of air pollutants, especially, its characteristics of emissions and transportation become issued nationally, in terms of not only environmental aspects, but also long-range transboundary transportation. In meteorological characteristics, westerlies area means what air pollutants that emitted from China can be delivered to South Korea. Therefore, considering meteorological factors can be important to understand air pollution phenomena. In this study, we used MM5(Fifth-Generation Mesoscale Model) and WRF(Weather Research and Forecasting Model) to produce the meteorological fields. We analyzed the feature of physics option in each model and the difference due to characteristic of WRF and MM5. We are trying to analyze the uncertainty of source-receptor relationships for total nitrate according to meteorological fields in the Northeast Asia. We produced the each meteorological fields that apply the same domain, same initial and boundary conditions, the best similar physics option. S-R relationships in terms of amount and fractional number for total nitrate (sum of N from HNO3, nitrate and PAN) were calculated by EMEP method 3.

Impact of inherent meteorology uncertainty on air quality ...

EPA Pesticide Factsheets

It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is important to understand how uncertainties in these inputs affect the simulated concentrations. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. Most studies explore this uncertainty by running different meteorological models or the same model with different physics options and in some cases combinations of different meteorological and air quality models. While these have been shown to be useful techniques in some cases, we present a technique that leverages the initial condition perturbations of a weather forecast ensemble, namely, the Short-Range Ensemble Forecast system to drive the four-dimensional data assimilation in the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model with a key focus being the response of ozone chemistry and transport. Results confirm that a sizable spread in WRF solutions, including common weather variables of temperature, wind, boundary layer depth, clouds, and radiation, can cause a relatively large range of ozone-mixing ratios. Pollutant transport can be altered by hundreds of kilometers over several days. Ozone-mixing ratios of the ensemble can vary as much as 10–20 ppb

Using Earth Observations to Understand and Predict Infectious Diseases

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Kiang, Richard

2015-01-01

This presentation discusses the processes from data collection and processing to analysis involved in unraveling patterns between disease outbreaks and the surrounding environment and meteorological conditions. We used these patterns to estimate when and where disease outbreaks will occur. As a case study, we will present our work on assessing the relationship between meteorological conditions and influenza in Central America. Our work represents the discovery, prescriptive and predictive aspects of data analytics.

Effect of meteorological variables on the incidence of hand, foot, and mouth disease in children: a time-series analysis in Guangzhou, China.

PubMed

Huang, Yong; Deng, Te; Yu, Shicheng; Gu, Jing; Huang, Cunrui; Xiao, Gexin; Hao, Yuantao

2013-03-13

Over the last decade, major outbreaks of hand, foot, and mouth disease (HFMD) have been reported in Asian countries, resulting in thousands of deaths among children. However, less is known regarding the effect of meteorological variables on the incidence of HFMD in children. This study aims at quantifying the relationship between meteorological variables and the incidence of HFMD among children in Guangzhou, China. The association between weekly HFMD cases in children aged <15 years and meteorological variables in Guangzhou from 2008 to 2011 were analyzed using the generalized additive model (GAM) and time-series method, after controlling for long-term trend and seasonality, holiday effects, influenza period and delayed effects. Temperature and relative humidity with one week lag were significantly associated with HFMD infection among children. We found that a 1°C increase in temperature led to an increase of 1.86% (95% CI: 0.92, 2.81%) in the weekly number of cases in the 0-14 years age group. A one percent increase in relative humidity may lead to an increase of 1.42% (95% CI: 0.97, 1.87%) in the weekly number of cases in the 0-14 years age group. This study provides quantitative evidence that the incidence of HFMD in children was associated with high average temperature and high relative humidity. The one-week delay in the effects of temperature and relative humidity on HFMD is consistent with the enterovirus incubation period and the potential time lag between onset of children's sickness and parental awareness and response.

The role of local urban traffic and meteorological conditions in air pollution: A data-based case study in Madrid, Spain

NASA Astrophysics Data System (ADS)

Laña, Ibai; Del Ser, Javier; Padró, Ales; Vélez, Manuel; Casanova-Mateo, Carlos

2016-11-01

Urban air pollution is a matter of growing concern for both public administrations and citizens. Road traffic is one of the main sources of air pollutants, though topography characteristics and meteorological conditions can make pollution levels increase or diminish dramatically. In this context an upsurge of research has been conducted towards functionally linking variables of such domains to measured pollution data, with studies dealing with up to one-hour resolution meteorological data. However, the majority of such reported contributions do not deal with traffic data or, at most, simulate traffic conditions jointly with the consideration of different topographical features. The aim of this study is to further explore this relationship by using high-resolution real traffic data. This paper describes a methodology based on the construction of regression models to predict levels of different pollutants (i.e. CO, NO, NO2, O3 and PM10) based on traffic data and meteorological conditions, from which an estimation of the predictive relevance (importance) of each utilized feature can be estimated by virtue of their particular training procedure. The study was made with one hour resolution meteorological, traffic and pollution historic data in roadside and background locations of the city of Madrid (Spain) captured over 2015. The obtained results reveal that the impact of vehicular emissions on the pollution levels is overshadowed by the effects of stable meteorological conditions of this city.

Improvement of Disease Prediction and Modeling through the Use of Meteorological Ensembles: Human Plague in Uganda

PubMed Central

Moore, Sean M.; Monaghan, Andrew; Griffith, Kevin S.; Apangu, Titus; Mead, Paul S.; Eisen, Rebecca J.

2012-01-01

Climate and weather influence the occurrence, distribution, and incidence of infectious diseases, particularly those caused by vector-borne or zoonotic pathogens. Thus, models based on meteorological data have helped predict when and where human cases are most likely to occur. Such knowledge aids in targeting limited prevention and control resources and may ultimately reduce the burden of diseases. Paradoxically, localities where such models could yield the greatest benefits, such as tropical regions where morbidity and mortality caused by vector-borne diseases is greatest, often lack high-quality in situ local meteorological data. Satellite- and model-based gridded climate datasets can be used to approximate local meteorological conditions in data-sparse regions, however their accuracy varies. Here we investigate how the selection of a particular dataset can influence the outcomes of disease forecasting models. Our model system focuses on plague (Yersinia pestis infection) in the West Nile region of Uganda. The majority of recent human cases have been reported from East Africa and Madagascar, where meteorological observations are sparse and topography yields complex weather patterns. Using an ensemble of meteorological datasets and model-averaging techniques we find that the number of suspected cases in the West Nile region was negatively associated with dry season rainfall (December-February) and positively with rainfall prior to the plague season. We demonstrate that ensembles of available meteorological datasets can be used to quantify climatic uncertainty and minimize its impacts on infectious disease models. These methods are particularly valuable in regions with sparse observational networks and high morbidity and mortality from vector-borne diseases. PMID:23024750

Respiratory viral infections and effects of meteorological parameters and air pollution in adults with respiratory symptoms admitted to the emergency room

PubMed Central

Silva, Denise R; Viana, Vinícius P; Müller, Alice M; Livi, Fernando P; Dalcin, Paulo de Tarso R

2014-01-01

Background Respiratory viral infections (RVIs) are the most common causes of respiratory infections. The prevalence of respiratory viruses in adults is underestimated. Meteorological variations and air pollution are likely to play a role in these infections. Objectives The objectives of this study were to determine the number of emergency visits for influenza-like illness (ILI) and severe acute respiratory infection (SARI) and to evaluate the association between ILI/SARI, RVI prevalence, and meteorological factors/air pollution, in the city of Porto Alegre, Brazil, from November 2008 to October 2010. Methods Eleven thousand nine hundred and fifty-three hospitalizations (adults and children) for respiratory symptoms were correlated with meteorological parameters and air pollutants. In a subset of adults, nasopharyngeal aspirates were collected and analyzed through IFI test. The data were analyzed using time-series analysis. Results Influenza-like illness and SARI were diagnosed in 3698 (30·9%) and 2063 (17·7%) patients, respectively. Thirty-seven (9·0%) samples were positive by IFI and 93 of 410 (22·7%) were IFI and/or PCR positive. In a multivariate logistic regression model, IFI positivity was statistically associated with absolute humidity, use of air conditioning, and presence of mold in home. Sunshine duration was significantly associated with the frequency of ILI cases. For SARI cases, the variables mean temperature, sunshine duration, relative humidity, and mean concentration of pollutants were singnificant. Conclusions At least 22% of infections in adult patients admitted to ER with respiratory complaints were caused by RVI. The correlations among meteorological variables, air pollution, ILI/SARI cases, and respiratory viruses demonstrated the relevance of climate factors as significant underlying contributors to the prevalence of RVI. PMID:24034701

Effect of meteorological variables on Plasmodium vivax and Plasmodium falciparum malaria in outbreak prone districts of Rajasthan, India.

PubMed

Lingala, Mercy A L

Malaria is a public health problem caused by Plasmodium parasite and transmitted by anopheline mosquitoes. Arid and semi-arid regions of western India are prone to malaria outbreaks. Malaria outbreak prone districts viz. Bikaner, Barmer and Jodhpur were selected to study the effect of meteorological variables on Plasmodium vivax and Plasmodium falciparum malaria outbreaks for the period of 2009-2012. The data of monthly malaria cases and meteorological variables was analysed using SPSS 20v. Spearman correlation analysis was conducted to examine the strength of the relationship between meteorological variables, P. vivax and P. falciparum malaria cases. Pearson's correlation analysis was carried out among the meteorological variables to observe the independent effect of each independent variable on the outcome. Results indicate that malaria outbreaks have occurred in Bikaner and Barmer due to continuous rains for more than two months. Rainfall has shown to be an important predictor of malaria outbreaks in Rajasthan. P. vivax is more significantly correlated with rainfall, minimum temperature (P<0.01) and less significantly with relative humidity (P<0.05); whereas P. falciparum is significantly correlated with rainfall, relative humidity (P<0.01) and less significantly with temperature (P<0.05). The determination of the lag period for P. vivax is relative humidity and for P. falciparum is temperature. The lag period between malaria cases and rainfall is shorter for P. vivax than P. falciparum. In conclusion, the knowledge generated is not only useful to take prompt malaria control interventions but also helpful to develop better forecasting model in outbreak prone regions. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Crop evapotranspiration estimation using remote sensing and the existing network of meteorological stations in Cyprus

NASA Astrophysics Data System (ADS)

Papadavid, G.; Hadjimitsis, D.; Michaelides, S.; Nisantzi, A.

2011-05-01

Cyprus is frequently confronted with severe droughts and the need for accurate and systematic data on crop evapotranspiration (ETc) is essential for decision making, regarding water irrigation management and scheduling. The aim of this paper is to highlight how data from meteorological stations in Cyprus can be used for monitoring and determining the country's irrigation demands. This paper shows how daily ETc can be estimated using FAO Penman-Monteith method adapted to satellite data and auxiliary meteorological parameters. This method is widely used in many countries for estimating crop evapotranspiration using auxiliary meteorological data (maximum and minimum temperatures, relative humidity, wind speed) as inputs. Two case studies were selected in order to determine evapotranspiration using meteorological and low resolution satellite data (MODIS - TERRA) and to compare it with the results of the reference method (FAO-56) which estimates the reference evapotranspiration (ETo) by using only meteorological data. The first approach corresponds to the FAO Penman-Monteith method adapted for using both meteorological and remotely sensed data. Furthermore, main automatic meteorological stations in Cyprus were mapped using Geographical Information System (GIS). All the agricultural areas of the island were categorized according to the nearest meteorological station which is considered as "representative" of the area. Thiessen polygons methodology was used for this purpose. The intended goal was to illustrate what can happen to a crop, in terms of water requirements, if meteorological data are retrieved from other than the representative stations. The use of inaccurate data can result in low yields or excessive irrigation which both lead to profit reduction. The results have shown that if inappropriate meteorological data are utilized, then deviations from correct ETc might be obtained, leading to water losses or crop water stress.

Mesoscale Frontogenesis: An Analysis of Two Cold Front Case Studies

DTIC Science & Technology

1993-01-01

marked the boundary of warm air or the "warm sector". Further development of this cyclone model by Bjerknes and Solberg (1922) and Bergeron (1928) provided...represent 25 mn s -1 Relative humidity of greater than 80% indicated by the shaded region in gray. Frontal zones marked with solid black lines. 24 two... Zuckerberg , J.T. Schaefer, and G.E. Rasch, 1986: Forecast problems: The meteorological and operational factors, In: Mesoscale Meteorology and Forecasting

Use of a scenario-neutral approach to identify the key hydro-meteorological attributes that impact runoff from a natural catchment

NASA Astrophysics Data System (ADS)

Guo, Danlu; Westra, Seth; Maier, Holger R.

2017-11-01

Scenario-neutral approaches are being used increasingly for assessing the potential impact of climate change on water resource systems, as these approaches allow the performance of these systems to be evaluated independently of climate change projections. However, practical implementations of these approaches are still scarce, with a key limitation being the difficulty of generating a range of plausible future time series of hydro-meteorological data. In this study we apply a recently developed inverse stochastic generation approach to support the scenario-neutral analysis, and thus identify the key hydro-meteorological variables to which the system is most sensitive. The stochastic generator simulates synthetic hydro-meteorological time series that represent plausible future changes in (1) the average, extremes and seasonal patterns of rainfall; and (2) the average values of temperature (Ta), relative humidity (RH) and wind speed (uz) as variables that drive PET. These hydro-meteorological time series are then fed through a conceptual rainfall-runoff model to simulate the potential changes in runoff as a function of changes in the hydro-meteorological variables, and runoff sensitivity is assessed with both correlation and Sobol' sensitivity analyses. The method was applied to a case study catchment in South Australia, and the results showed that the most important hydro-meteorological attributes for runoff were winter rainfall followed by the annual average rainfall, while the PET-related meteorological variables had comparatively little impact. The high importance of winter rainfall can be related to the winter-dominated nature of both the rainfall and runoff regimes in this catchment. The approach illustrated in this study can greatly enhance our understanding of the key hydro-meteorological attributes and processes that are likely to drive catchment runoff under a changing climate, thus enabling the design of tailored climate impact assessments to specific water resource systems.

Meteorological variables and bacillary dysentery cases in Changsha City, China.

PubMed

Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Zhou, Maigeng; Li, Xiujun; Jiang, Baofa

2014-04-01

This study aimed to investigate the association between meteorological-related risk factors and bacillary dysentery in a subtropical inland Chinese area: Changsha City. The cross-correlation analysis and the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model were used to quantify the relationship between meteorological factors and the incidence of bacillary dysentery. Monthly mean temperature, mean relative humidity, mean air pressure, mean maximum temperature, and mean minimum temperature were significantly correlated with the number of bacillary dysentery cases with a 1-month lagged effect. The ARIMAX models suggested that a 1°C rise in mean temperature, mean maximum temperature, and mean minimum temperature might lead to 14.8%, 12.9%, and 15.5% increases in the incidence of bacillary dysentery disease, respectively. Temperature could be used as a forecast factor for the increase of bacillary dysentery in Changsha. More public health actions should be taken to prevent the increase of bacillary dysentery disease with consideration of local climate conditions, especially temperature.

Meteorological Variables and Bacillary Dysentery Cases in Changsha City, China

PubMed Central

Gao, Lu; Zhang, Ying; Ding, Guoyong; Liu, Qiyong; Zhou, Maigeng; Li, Xiujun; Jiang, Baofa

2014-01-01

This study aimed to investigate the association between meteorological-related risk factors and bacillary dysentery in a subtropical inland Chinese area: Changsha City. The cross-correlation analysis and the Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX) model were used to quantify the relationship between meteorological factors and the incidence of bacillary dysentery. Monthly mean temperature, mean relative humidity, mean air pressure, mean maximum temperature, and mean minimum temperature were significantly correlated with the number of bacillary dysentery cases with a 1-month lagged effect. The ARIMAX models suggested that a 1°C rise in mean temperature, mean maximum temperature, and mean minimum temperature might lead to 14.8%, 12.9%, and 15.5% increases in the incidence of bacillary dysentery disease, respectively. Temperature could be used as a forecast factor for the increase of bacillary dysentery in Changsha. More public health actions should be taken to prevent the increase of bacillary dysentery disease with consideration of local climate conditions, especially temperature. PMID:24591435

Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study.

PubMed

Chien, Lung-Chang; Lin, Ro-Ting; Liao, Yunqi; Sy, Francisco S; Pérez, Adriana

2018-04-17

Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observing possible risk factors, such as weather conditions enhancing mosquito breeding and surviving. This study collected daily meteorological measurements and weekly ZIKV infectious cases among 32 departments of Colombia from January 2015-December 2016. This study applied the distributed lag nonlinear model to estimate the association between the number of ZIKA virus infection and meteorological measurements, controlling for spatial and temporal variations. We examined at most three meteorological factors with 20 lags in weeks in the model. Average humidity, total rainfall, and maximum temperature were more predictable of ZIKV infection outbreaks than other meteorological factors. Our models can detect significantly lagged effects of average humidity, total rainfall, and maximum temperature on outbreaks up to 15, 14, and 20 weeks, respectively. The spatial analysis identified 12 departments with a significant threat of ZIKV, and eight of those high-risk departments were located between the Equator and 6°N. The outbreak prediction also performed well in identified high-risk departments. Our results demonstrate that meteorological factors could be used for predicting ZIKV epidemics. Building an early warning surveillance system is important for preventing ZIKV infection, particularly in endemic areas.

Decreasing reference evapotranspiration in a warming climate - A case of Changjiang (Yangtze) River catchment during 1970-2000

NASA Astrophysics Data System (ADS)

Xu, C. Y.; Gong, L. B.; Tong, J.; Chen, D. L.

2006-07-01

This study deals with temporal trends in the Penman-Monteith reference evapotranspiration estimated from standard meteorological observations, observed pan evaporation, and four related meteorological variables during 1970-2000 in the Yangtze River catchment. Relative contributions of the four meteorological variables to changes in the reference evapotranspiration are quantified. The results show that both the reference evapotranspiration and the pan evaporation have significant. decreasing trends in the upper, the middle as well as in the whole Changjiang (Yangtze) River catchment at the 5% significance level, while the air temperature shows a significant increasing trend. The decreasing trend detected in the reference evapotranspiration can be attributed to the significant decreasing trends in the net radiation and the wind speed.

A numerical model simulation of the regional air pollution meteorology of the greater Chesapeake Bay area - Summer day case study

NASA Technical Reports Server (NTRS)

Segal, M.; Pielke, R. A.; Mcnider, R. T.; Mcdougal, D. S.

1982-01-01

The mesoscale numerical model of the University of Virginia (UVMM), has been applied to the greater Chesapeake Bay area in order to provide a detailed description of the air pollution meteorology during a typical summer day. This model provides state of the art simulations for land-sea thermally induced circulations. The model-predicted results agree favorably with available observed data. The effects of synoptic flow and sea breeze coupling on air pollution meteorological characteristics in this region, are demonstrated by a spatial and temporal presentation of various model predicted fields. A transport analysis based on predicted wind velocities indicated possible recirculation of pollutants back onto the Atlantic coast due to the sea breeze circulation.

Meteorological factors and risk of scrub typhus in Guangzhou, southern China, 2006–2012

PubMed Central

2014-01-01

Background Scrub typhus is becoming the most common vector born disease in Guangzhou, southern China. In this study, we aimed to examine the effect of weather patterns on the incidence of Scrub typhus in the subtropical city of Guangzhou for the period 2006–2012, and assist public health prevention and control measures. Methods Scrub typhus reported cases during the period of 2006–2012 in Guangzhou were obtained from National Notifiable Disease Report System (NNDRS). Simultaneous meteorological data including temperature, relative humidity, atmospheric pressure, sunshine, and rainfall were obtained from the documentation of the Guangzhou Meteorological Bureau. A negative binomial regression was used to identify the relationship between meteorological variables and scrub typhus. Results Annual incidence rates of scrub typhus from 2006 to 2012 were 3.25, 2.67, 3.81, 4.22, 4.41, 5.12, and 9.75 (per 100 000) respectively. Each 1°C rise in temperature corresponded to an increase of 14.98% (95% CI 13.65% to 16.33%) in the monthly number of scrub typhus cases, while a 1 hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 8.03% (95% CI −8.75% to −7.31%). Similarly, a 1 hour rise in sunshine corresponded to an increase of 0.17% or 0.54%, and a 1 millimeter rise in rainfall corresponded to an increase of 0.05% or 0.10%, in the monthly number of scrub typhus cases, depending on the variables considered in the model. Conclusion Our study provided evidence that climatic factors were associated with occurrence of scrub typhus in Guangzhou city, China. Temperature, duration of sunshine, and rainfall were positively associated with scrub typhus incidence, while atmospheric pressure was inversely associated with scrub typhus incidence. These findings should be considered in the prediction of future patterns of scrub typhus transmission. PMID:24620733

Regional Scale Meteorological Analysis and Prediction Using GPS Occultation and EOS Data

NASA Technical Reports Server (NTRS)

Bromwich, David H.; Shum, C. K.; Zhao, Changyin; Kuo, Bill; Rocken, Chris

2004-01-01

The main objective of the research under this award is to improve regional meteorological analysis and prediction for traditionally data limited regions, particularly over the Southern Ocean and Antarctica, using the remote sensing observations from current and upcoming GPS radio occultation missions and the EOS instrument suite. The major components of this project are: 1.Develop and improve the methods for retrieving temperature, moisture, and pressure profiles from GPS radio occultation data and EOS radiometer data. 2. Develop and improve a regional scale data assimilation system (MM5 4DVAR). 3. Perform case studies involving data analysis and numerical modeling to investigate the impact of different data for regional meteorological analysis and the importance of data assimilation for regional meteorological simulation over the Antarctic region. 4. Apply the findings and improvements from the above studies to weather forecasting experiments. 5. In the third year of the award we made significant progress toward the remaining goals of the project. The work included carefully evaluating the performance of an atmospheric mesoscale model, the Polar MM5 in Antarctic applications and improving the upper boundary condition.

An Observational Study of the Relationship between Cloud, Aerosol and Meteorology in Broken Low-Level Cloud Conditions

NASA Technical Reports Server (NTRS)

Loeb, Norman G.; Schuster, Gregory L.

2008-01-01

Global satellite analyses showing strong correlations between aerosol optical depth and 3 cloud cover have stirred much debate recently. While it is tempting to interpret the results as evidence of aerosol enhancement of cloud cover, other factors such as the influence of meteorology on both the aerosol and cloud distributions can also play a role, as both aerosols and clouds depend upon local meteorology. This study uses satellite observations to examine aerosol-cloud relationships for broken low-level cloud regions off the coast of Africa. The analysis approach minimizes the influence of large-scale meteorology by restricting the spatial and temporal domains in which the aerosol and cloud properties are compared. While distributions of several meteorological variables within 5deg 5deg latitude-longitude regions are nearly identical under low and high aerosol optical depth, the corresponding distributions of single-layer low cloud properties and top-of-atmosphere radiative fluxes differ markedly, consistent with earlier studies showing increased cloud cover with aerosol optical depth. Furthermore, fine-mode fraction and Angstrom Exponent are also larger in conditions of higher aerosol optical depth, even though no evidence of systematic latitudinal or longitudinal gradients between the low and high aerosol optical depth populations are observed. When the analysis is repeated for all 5deg 5deg latitude-longitude regions over the global oceans (after removing cases in which significant meteorological differences are found between the low and high aerosol populations), results are qualitatively similar to those off the coast of Africa.

High-resolution urban observation network for user-specific meteorological information service in the Seoul Metropolitan Area, South Korea

NASA Astrophysics Data System (ADS)

Park, Moon-Soo; Park, Sung-Hwa; Chae, Jung-Hoon; Choi, Min-Hyeok; Song, Yunyoung; Kang, Minsoo; Roh, Joon-Woo

2017-04-01

To improve our knowledge of urban meteorology, including those processes applicable to high-resolution meteorological models in the Seoul Metropolitan Area (SMA), the Weather Information Service Engine (WISE) Urban Meteorological Observation System (UMS-Seoul) has been designed and installed. The UMS-Seoul incorporates 14 surface energy balance (EB) systems, 7 surface-based three-dimensional (3-D) meteorological observation systems and applied meteorological (AP) observation systems, and the existing surface-based meteorological observation network. The EB system consists of a radiation balance system, sonic anemometers, infrared CO2/H2O gas analyzers, and many sensors measuring the wind speed and direction, temperature and humidity, precipitation, and air pressure. The EB-produced radiation, meteorological, and turbulence data will be used to quantify the surface EB according to land use and to improve the boundary-layer and surface processes in meteorological models. The 3-D system, composed of a wind lidar, microwave radiometer, aerosol lidar, or ceilometer, produces the cloud height, vertical profiles of backscatter by aerosols, wind speed and direction, temperature, humidity, and liquid water content. It will be used for high-resolution reanalysis data based on observations and for the improvement of the boundary-layer, radiation, and microphysics processes in meteorological models. The AP system includes road weather information, mosquito activity, water quality, and agrometeorological observation instruments. The standardized metadata for networks and stations are documented and renewed periodically to provide a detailed observation environment. The UMS-Seoul data are designed to support real-time acquisition and display and automatically quality check within 10 min from observation. After the quality check, data can be distributed to relevant potential users such as researchers and policy makers. Finally, two case studies demonstrate that the observed data have a great potential to help to understand the boundary-layer structures more deeply, improve the performance of high-resolution meteorological models, and provide useful information customized based on the user demands in the SMA.

A comparative study of the response of modeled non-drizzling stratocumulus to meteorological and aerosol perturbations

NASA Astrophysics Data System (ADS)

Petters, J. L.; Jiang, H.; Feingold, G.; Rossiter, D. L.; Khelif, D.; Sloan, L. C.; Chuang, P. Y.

2013-03-01

The impact of changes in aerosol and cloud droplet concentration (Na and Nd) on the radiative forcing of stratocumulus-topped boundary layers (STBLs) has been widely studied. How these impacts compare to those due to variations in meteorological context has not been investigated in a systematic fashion for non-drizzling overcast stratocumulus. In this study we examine the impact of observed variations in meteorological context and aerosol state on daytime, non-drizzling overcast stratiform evolution, and determine how resulting changes in cloud properties compare. Using large-eddy simulation (LES) we create a model base case of daytime southeast Pacific coastal stratocumulus, spanning a portion of the diurnal cycle (early morning to near noon) and constrained by observations taken during the VOCALS (VAMOS Ocean-Atmosphere-Land Study) field campaign. We perturb aerosol and meteorological properties around this base case to investigate the stratocumulus response. We determine perturbations in the cloud top jumps in potential temperature θ and total water mixing ratio qt from ECMWF Re-analysis Interim data, and use a set of Nd values spanning the observable range. To determine the cloud response to these meteorological and aerosol perturbations, we compute changes in liquid water path (LWP), bulk optical depth (τ) and cloud radiative forcing (CRF). We find that realistic variations in the thermodynamic jump properties can elicit a response in the cloud properties of τ and shortwave (SW) CRF that are on the same order of magnitude as the response found due to realistic changes in aerosol state (i.e Nd). In response to increases in Nd, the cloud layer in the base case thinned due to increases in evaporative cooling and entrainment rate. This cloud thinning somewhat mitigates the increase in τ resulting from increases in Nd. On the other hand, variations in θ and qt jumps did not substantially modify Nd. The cloud layer thickens in response to an increase in the θ jump and thins in response to an increase in the qt jump, both resulting in a τ and SW CRF response comparable to those found from perturbations in Nd. Longwave CRF was not substantially altered by the perturbations we tested. We find that realistic variations in meteorological context can elicit a response in CRF and τ on the same order of magnitude as, and at times larger than, that response found due to realistic changes in aerosol state. We estimate the limits on variability of cloud top jump properties required for accurate observation of aerosol SW radiative impacts on stratocumulus, and find strict constraints: less than 1 K and 1 g kg-1 in the early morning hours, and order 0.1 K and 0.1 g kg-1 close to solar noon. These constraints suggest that accurately observing aerosol radiative impacts in stratocumulus may be challenging as co-variation of meteorological properties may obfuscate aerosol-cloud interactions.

Contribution of ambient ozone to Scots pine defoliation and reduced growth in the Central European forests: a Lithuanian case study.

PubMed

Augustaitis, Algirdas; Bytnerowicz, Andrzej

2008-10-01

The study aimed to explore if changes in crown defoliation and stem growth of Scots pines (Pinus sylvestris L.) could be related to changes in ambient ozone (O(3)) concentration in central Europe. To meet this objective the study was performed in 3 Lithuanian national parks, close to the ICP integrated monitoring stations from which data on meteorology and pollution were provided. Contribution of peak O(3) concentrations to the integrated impact of acidifying compounds and meteorological parameters on pine stem growth was found to be more significant than its contribution to the integrated impact of acidifying compounds and meteorological parameters on pine defoliation. Findings of the study provide statistical evidence that peak concentrations of ambient O(3) can have a negative impact on pine tree crown defoliation and stem growth reduction under field conditions in central and northeastern Europe where the AOT40 values for forests are commonly below their phytotoxic levels.

A Lagrangian particle model to predict the airborne spread of foot-and-mouth disease virus

NASA Astrophysics Data System (ADS)

Mayer, D.; Reiczigel, J.; Rubel, F.

Airborne spread of bioaerosols in the boundary layer over a complex terrain is simulated using a Lagrangian particle model, and applied to modelling the airborne spread of foot-and-mouth disease (FMD) virus. Two case studies are made with study domains located in a hilly region in the northwest of the Styrian capital Graz, the second largest town in Austria. Mountainous terrain as well as inhomogeneous and time varying meteorological conditions prevent from application of so far used Gaussian dispersion models, while the proposed model can handle these realistically. In the model, trajectories of several thousands of particles are computed and the distribution of virus concentration near the ground is calculated. This allows to assess risk of infection areas with respect to animal species of interest, such as cattle, swine or sheep. Meteorological input data like wind field and other variables necessary to compute turbulence were taken from the new pre-operational version of the non-hydrostatic numerical weather prediction model LMK ( Lokal-Modell-Kürzestfrist) running at the German weather service DWD ( Deutscher Wetterdienst). The LMK model provides meteorological parameters with a spatial resolution of about 2.8 km. To account for the spatial resolution of 400 m used by the Lagrangian particle model, the initial wind field is interpolated upon the finer grid by a mass consistent interpolation method. Case studies depict a significant influence of local wind systems on the spread of virus. Higher virus concentrations at the upwind side of the hills and marginal concentrations in the lee are well observable, as well as canalization effects by valleys. The study demonstrates that the Lagrangian particle model is an appropriate tool for risk assessment of airborne spread of virus by taking into account the realistic orographic and meteorological conditions.

[The influence of certain meteorological factors on mortality from complications of arterial hypertension].

PubMed

Afanas'eva, G N; Panova, T N; Dedova, A V; Dzhuvaliakov, P G

2010-01-01

The weather may influence the clinical course of many diseases. The objective of the present study was to evaluate effects of certain meteorological factors on the mortality rate associated with complications of arterial hypertension (cerebral stroke and myocardial infarction) in the city of Astrakhan during the period from 1983 to 2005. The analysis included 17,198 cases of death from cardiovascular disorders (CVD). An original software program was used for the purpose that made it possible to estimate the influence of meteorological factors (air temperature, velocity of wind and precipitation) on the mortality rate among subjects with and without AH. It was shown that mortality due to coronary heart disease (CHD) and cerebrovascular disease positively correlated with the air temperature and amount of precipitation but inversely correlated with the velocity of wind. Correlations between mortality from CVD and meteorological factors among subjects presenting with CHD, cerebrovascular disease, and AH were more pronounced and statistically significant compared with patients of the same groups without AH.

[Correlations between climate change-related infectious diseases and meteorological factors in Korea].

PubMed

Kim, Si Heon; Jang, Jae Yeon

2010-09-01

Infectious diseases are known to be affected by climate change. We investigated if the infectious diseases were related to meteorological factors in Korea. Scrub typhus, hemorrhagic fever with renal syndrome (HFRS), leptospirosis, malaria and Vibrio vulnificus sepsis among the National Notifiable Infectious Diseases were selected as the climate change-related infectious diseases. Temperature, relative humidity and precipitation were used as meteorological factors. The study period was from 2001 through 2008. We examined the seasonality of the diseases and those correlations with meteorological factors. We also analyzed the correlations between the incidences of the diseases during the outbreak periods and monthly meteorological factors in the hyper-endemic regions. All of the investigated diseases showed strong seasonality; malaria and V. vulnificus sepsis were prevalent in summer and scrub typhus, HFRS and leptospirosis were prevalent in the autumn. There were significant correlations between the monthly numbers of cases and all the meteorological factors for malaria and V. vulnificus sepsis, but there were no correlation for the other diseases. However, the incidence of scrub typhus in hyper-endemic region during the outbreak period was positively correlated with temperature and humidity during the summer. The incidences of HFRS and leptospirosis had positive correlations with precipitation in November and temperature and humidity in February, respectively. V. vulnificus sepsis showed positive correlations with precipitation in April/May/July. In Korea, the incidences of the infectious diseases were correlated with meteorological factors, and this implies that the incidences could be influenced by climate change.

How Socio-Environmental Factors Are Associated with Japanese Encephalitis in Shaanxi, China—A Bayesian Spatial Analysis

PubMed Central

Zhang, Shaobai; Hu, Wenbiao; Zhuang, Guihua

2018-01-01

Evidence indicated that socio-environmental factors were associated with occurrence of Japanese encephalitis (JE). This study explored the association of climate and socioeconomic factors with JE (2006–2014) in Shaanxi, China. JE data at the county level in Shaanxi were supplied by Shaanxi Center for Disease Control and Prevention. Population and socioeconomic data were obtained from the China Population Census in 2010 and statistical yearbooks. Meteorological data were acquired from the China Meteorological Administration. A Bayesian conditional autoregressive model was used to examine the association of meteorological and socioeconomic factors with JE. A total of 1197 JE cases were included in this study. Urbanization rate was inversely associated with JE incidence during the whole study period. Meteorological variables were significantly associated with JE incidence between 2012 and 2014. The excessive precipitation at lag of 1–2 months in the north of Shaanxi in June 2013 had an impact on the increase of local JE incidence. The spatial residual variations indicated that the whole study area had more stable risk (0.80–1.19 across all the counties) between 2012 and 2014 than earlier years. Public health interventions need to be implemented to reduce JE incidence, especially in rural areas and after extreme weather. PMID:29584661

Seasonality of Human Leptospirosis in Reunion Island (Indian Ocean) and Its Association with Meteorological Data

PubMed Central

Desvars, Amélie; Jégo, Sylvaine; Chiroleu, Frédéric; Bourhy, Pascale; Cardinale, Eric; Michault, Alain

2011-01-01

Background Leptospirosis is a disease which occurs worldwide but particularly affects tropical areas. Transmission of the disease is dependent on its excretion by reservoir animals and the presence of moist environment which allows the survival of the bacteria. Methods and Findings A retrospective study was undertaken to describe seasonal patterns of human leptospirosis cases reported by the Centre National de Références des Leptospiroses (CNRL, Pasteur Institute, Paris) between 1998 and 2008, to determine if there was an association between the occurrence of diagnosed cases and rainfall, temperature and global solar radiation (GSR). Meteorological data were recorded in the town of Saint-Benoît (Météo France “Beaufonds-Miria” station), located on the windward (East) coast. Time-series analysis was used to identify the variables that best described and predicted the occurrence of cases of leptospirosis on the island. Six hundred and thirteen cases were reported during the 11-year study period, and 359 cases (58.56%) were diagnosed between February and May. A significant correlation was identified between the number of cases in a given month and the associated cumulated rainfall as well as the mean monthly temperature recorded 2 months prior to diagnosis (r = 0.28 and r = 0.23 respectively). The predictive model includes the number of cases of leptospirosis recorded 1 month prior to diagnosis (b = 0.193), the cumulated monthly rainfall recorded 2 months prior to diagnosis (b = 0.145), the average monthly temperature recorded 0 month prior to diagnosis (b = 3.836), and the average monthly GSR recorded 0 month prior to diagnosis (b = −1.293). Conclusions Leptospirosis has a seasonal distribution in Reunion Island. Meteorological data can be used to predict the occurrence of the disease and our statistical model can help to implement seasonal prevention measures. PMID:21655257

Comparison of meteorological forcing (WFDEI, AGRI4CAST) to in-situ observations in a semi arid catchment. The case of Merguellil in Tunisia.

NASA Astrophysics Data System (ADS)

Le Page, Michel; Gosset, Cindy; Oueslati, Ines; Calvez, Roger; Zribi, Mehrez; Lilli Chabaane, Zohra

2015-04-01

Meteorological forcing is essential to hydrological and hydro-geological modeling. In the case of the semi-arid catchment of Merguellil in Tunisia, long term time series are only available in the plain for a SYNOP station. Other meteorological stations have been installed since 2010. Therefore, this study aims at qualifying the reliability of the meteorological forcing necessary for an integrated model conception. We compare the meteorological data from 7 stations (sources: WMO and our own station), inside and around the Merguellil catchment, with daily gridded data at 25*25 km from AGRI4CAST and 50*50km from WFDEI. AGRI4CAST (Biaveti et al, 2008) is an interpolated dataset based on actual weather stations produced by the Joint Research Centre (JRC) for the Monitoring Agricultural Resources Unit (MARS). The WFDEI second version dataset (Weedon et al, 2014) has been generated using the same methodology as the widely used WATCH Forcing Data (WFD) by making use of the ERA-Interim reanalysis data. The studied meteorological variables are Rs, Tmoy, U2, P, RH and ET0, with the scores RMSE, bias and R pearson. Regarding the AGRI4CAST dataset, the scores are established over different periods according to variables based on stepping between the observed and interpolated data. The scores show good correlations between the observed temperatures, but with a spatial variability bound to the stations elevations. The moderate and interpolated radiations also show a good concordance indicating a good reliability. The R pearson score obtained for the values of relative humidity show a good correlation between the observations and the interpolations, however, the short periods of comparisons do not allow obtaining significant information and the RMSE and bias are important. Wind speed has an important negative bias for a majority of stations (positively for only one). Only one station shows concordances between the data. The study of the data indicates that we shall have to adjust the wind speeds and the relative humidity of the air for the implementation of a model. Finally the reference evapotranspiration seems relatively coherent, in spite of the dispersal observed during the meteorological measures, but with biases rather high and RMSE also rather high (> 1.3 mm). After revised the parameter U2 and RH, AGRI4CAST can possibly be corrected by ancillary ground stations. The analysis of the WFDEI dataset is currently under evaluation. (1) Biavetti, I., Karetsos, S., Ceglar, A., Toreti, A., Panagos P. (2014), European meteorological data: contribution to research, development and policy support, Proc. of SPIE Vol. 9229 922907-1 (2) Weedon, G. P., G. Balsamo, N. Bellouin, S. Gomes, M. J. Best, and P. Viterbo (2014), The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50, 7505-7514, doi:10.1002/ 2014WR015638.

Lagrangian transport simulations of volcanic sulfur dioxide emissions: impact of meteorological data products

NASA Astrophysics Data System (ADS)

Hoffmann, Lars; Rößler, Thomas; Griessbach, Sabine; Heng, Yi; Stein, Olaf

2017-04-01

Sulfur dioxide (SO2) emissions from strong volcanic eruptions are an important natural cause for climate variations. We applied our new Lagrangian transport model Massive-Parallel Trajectory Calculations (MPTRAC) to perform simulations for three case studies of volcanic eruption events. The case studies cover the eruptions of Grímsvötn, Iceland, Puyehue-Cordón Caulle, Chile, and Nabro, Eritrea, in May and June 2011. We used SO2 observations of the Atmospheric Infrared Sounder (AIRS/Aqua) and a backward trajectory approach to initialize the simulations. Besides validation of the new model, the main goal of our study was a comparison of simulations with different meteorological data products. We considered three reanalyses (ERA-Interim, MERRA, and NCAR/NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis. Qualitatively, the SO2 distributions from the simulations compare well with the AIRS data, but also with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aerosol observations. Transport deviations and the critical success index (CSI) are analyzed to evaluate the simulations quantitatively. During the first 5 or 10 days after the eruptions we found the best performance for the ECMWF analysis (CSI range of 0.25 - 0.31), followed by ERA-Interim (0.25 - 0.29), MERRA (0.23 - 0.27), and NCAR/NCEP (0.21 - 0.23). High temporal and spatial resolution of the meteorological data does lead to improved performance of Lagrangian transport simulations of volcanic emissions in the upper troposphere and lower stratosphere. Reference: Hoffmann L., Rößler, T., Griessbach, S., Heng, Y., and Stein, O., Lagrangian transport simulations of volcanic sulfur dioxide emissions: impact of meteorological data products, J. Geophys. Res., 121(9), 4651-4673, doi:10.1002/2015JD023749, 2016.

Feedbacks between Air-Quality, Meteorology, and the Forest Environment

NASA Astrophysics Data System (ADS)

Makar, Paul; Akingunola, Ayodeji; Stroud, Craig; Zhang, Junhua; Gong, Wanmin; Moran, Michael; Zheng, Qiong; Brook, Jeffrey; Sills, David

2017-04-01

The outcome of air quality forecasts depend in part on how the local environment surrounding the emissions regions influences chemical reaction rates and transport from those regions to the larger spatial scales. Forested areas alter atmospheric chemistry through reducing photolysis rates and vertical diffusivities within the forest canopy. The emitted pollutants, and their reaction products, are in turn capable of altering meteorology, through the well-known direct and indirect effects of particulate matter on radiative transfer. The combination of these factors was examined using version 2 of the Global Environmental Multiscale - Modelling Air-quality and CHemistry (GEM-MACH) on-line air pollution model. The model configuration used for this study included 12 aerosol size bins, eight aerosol species, homogeneous core Mie scattering, the Milbrandt-Yao two-moment cloud microphysics scheme with cloud condensation nuclei generated from model aerosols using the scheme of Abdul-Razzak and Ghan, and a new parameterization for forest canopy shading and turbulence. The model was nested to 2.5km resolution for a domain encompassing the lower Great Lakes, for simulations of a period in August of 2015 during the Pan American Games, held in Toronto, Canada. Four scenarios were carried out: (1) a "Base Case" scenario (the original model, in which coupling between chemistry and weather is not permitted; instead, the meteorological model's internal climatologies for aerosol optical and cloud condensation properties are used for direct and indirect effect calculations); (2) a "Feedback" scenario (the aerosol properties were derived from the internally simulated chemistry, and coupled to the meteorological model's radiative transfer and cloud formation modules); (3) a "Forest" scenario (canopy shading and turbulence were added to the Base Case); (4) a "Combined" scenario (including both direct and indirect effect coupling between meteorology and chemistry, as well as the forest canopy parameterization). The simulations suggest that the feedbacks between simulated aerosols and meteorology may strengthen the existing lake breeze circulation, modifying the resulting meteorological and air-quality forecasts, while the forest canopy's influence may extend throughout the planetary boundary layer, and may also influence the weather. The simulations will be compared to available observations, in order to determine their relative impact on model performance.

Solar radiation and water vapor pressure to forecast chickenpox epidemics.

PubMed

Hervás, D; Hervás-Masip, J; Nicolau, A; Reina, J; Hervás, J A

2015-03-01

The clear seasonality of varicella infections in temperate regions suggests the influence of meteorologic conditions. However, there are very few data on this association. The aim of this study was to determine the seasonal pattern of varicella infections on the Mediterranean island of Mallorca (Spain), and its association with meteorologic conditions and schooling. Data on the number of cases of varicella were obtained from the Network of Epidemiologic Surveillance, which is composed of primary care physicians who notify varicella cases on a compulsory basis. From 1995 to 2012, varicella cases were correlated to temperature, humidity, rainfall, water vapor pressure, atmospheric pressure, wind speed, and solar radiation using regression and time-series models. The influence of schooling was also analyzed. A total of 68,379 cases of varicella were notified during the study period. Cases occurred all year round, with a peak incidence in June. Varicella cases increased with the decrease in water vapor pressure and/or the increase of solar radiation, 3 and 4 weeks prior to reporting, respectively. An inverse association was also observed between varicella cases and school holidays. Using these variables, the best fitting autoregressive moving average with exogenous variables (ARMAX) model could predict 95 % of varicella cases. In conclusion, varicella in our region had a clear seasonality, which was mainly determined by solar radiation and water vapor pressure.

Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

NASA Astrophysics Data System (ADS)

Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

2015-12-01

Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

Meteorological Influence on the 2009 Influenza A (H1N1) Pandemic in Mainland China.

NASA Astrophysics Data System (ADS)

Zhao, X.; Cai, J.; Feng, D.; Bai, Y.; Xu, B.

2015-12-01

Since May 2009, a novel influenza A (H1N1) pandemic has spread rapidly in mainland China from Mexico. Although there has been substantial analysis of this influenza, reliable work estimating its spatial dynamics and determinants remain scarce. The survival and transmission of this pandemic virus not only depends on its biological properties, but also a correlation with external environmental factors. In this study, we collected daily influenza A (H1N1) cases and corresponding annual meteorological factors in mainland China from May 2009 to April 2010. By analyzing these data at county-level, a similarity index, which considered the spatio-temporal characteristics of the disease, was proposed to evaluate the role and lag time of meteorological factors in the influenza transmission. The results indicated that the influenza spanned a large geographical area, following an overall trend from east to west across the country. The spatio-temporal transmission of the disease was affected by a series of meteorological variables, especially absolute humidity with a 3-week lag. These findings confirmed that the absolute humidity and other meteorological variables contributed to the local occurrence and dispersal of influenza A (H1N1). The impact of meteorological variables and their lag effects could be involved in the improvement of effective strategies to control and prevent disease outbreaks.

The use of random forests in modelling short-term air pollution effects based on traffic and meteorological conditions: A case study in Wrocław.

PubMed

Kamińska, Joanna A

2018-07-01

Random forests, an advanced data mining method, are used here to model the regression relationships between concentrations of the pollutants NO 2 , NO x and PM 2.5 , and nine variables describing meteorological conditions, temporal conditions and traffic flow. The study was based on hourly values of wind speed, wind direction, temperature, air pressure and relative humidity, temporal variables, and finally traffic flow, in the two years 2015 and 2016. An air quality measurement station was selected on a main road, located a short distance (40 m) from a large intersection equipped with a traffic flow measurement system. Nine different time subsets were defined, based among other things on the climatic conditions in Wrocław. An analysis was made of the fit of models created for those subsets, and of the importance of the predictors. Both the fit and the importance of particular predictors were found to be dependent on season. The best fit was obtained for models created for the six-month warm season (April-September) and for the summer season (June-August). The most important explanatory variable in the models of concentrations of nitrogen oxides was traffic flow, while in the case of PM 2.5 the most important were meteorological conditions, in particular temperature, wind speed and wind direction. Temporal variables (except for month in the case of PM 2.5 ) were found to have no significant effect on the concentrations of the studied pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of missing value imputation methods in time series: the case of Turkish meteorological data

NASA Astrophysics Data System (ADS)

Yozgatligil, Ceylan; Aslan, Sipan; Iyigun, Cem; Batmaz, Inci

2013-04-01

This study aims to compare several imputation methods to complete the missing values of spatio-temporal meteorological time series. To this end, six imputation methods are assessed with respect to various criteria including accuracy, robustness, precision, and efficiency for artificially created missing data in monthly total precipitation and mean temperature series obtained from the Turkish State Meteorological Service. Of these methods, simple arithmetic average, normal ratio (NR), and NR weighted with correlations comprise the simple ones, whereas multilayer perceptron type neural network and multiple imputation strategy adopted by Monte Carlo Markov Chain based on expectation-maximization (EM-MCMC) are computationally intensive ones. In addition, we propose a modification on the EM-MCMC method. Besides using a conventional accuracy measure based on squared errors, we also suggest the correlation dimension (CD) technique of nonlinear dynamic time series analysis which takes spatio-temporal dependencies into account for evaluating imputation performances. Depending on the detailed graphical and quantitative analysis, it can be said that although computational methods, particularly EM-MCMC method, are computationally inefficient, they seem favorable for imputation of meteorological time series with respect to different missingness periods considering both measures and both series studied. To conclude, using the EM-MCMC algorithm for imputing missing values before conducting any statistical analyses of meteorological data will definitely decrease the amount of uncertainty and give more robust results. Moreover, the CD measure can be suggested for the performance evaluation of missing data imputation particularly with computational methods since it gives more precise results in meteorological time series.

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China

NASA Astrophysics Data System (ADS)

Duan, Yu; Huang, Xiao-lei; Wang, Yu-jie; Zhang, Jun-qing; Zhang, Qi; Dang, Yue-wen; Wang, Jing

2016-10-01

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 105 population). SARIMAX (1,0,0)(1,0,0)12 model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity ( β = -0.002, p = 0.020), mean temperature ( β = 0.006, p = 0.004), and 1 month lag minimum temperature ( β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR( β) = 0.469, p < 0.001) and in 12 months before (SAR( β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

A note on the correlation between circular and linear variables with an application to wind direction and air temperature data in a Mediterranean climate

NASA Astrophysics Data System (ADS)

Lototzis, M.; Papadopoulos, G. K.; Droulia, F.; Tseliou, A.; Tsiros, I. X.

2018-04-01

There are several cases where a circular variable is associated with a linear one. A typical example is wind direction that is often associated with linear quantities such as air temperature and air humidity. The analysis of a statistical relationship of this kind can be tested by the use of parametric and non-parametric methods, each of which has its own advantages and drawbacks. This work deals with correlation analysis using both the parametric and the non-parametric procedure on a small set of meteorological data of air temperature and wind direction during a summer period in a Mediterranean climate. Correlations were examined between hourly, daily and maximum-prevailing values, under typical and non-typical meteorological conditions. Both tests indicated a strong correlation between mean hourly wind directions and mean hourly air temperature, whereas mean daily wind direction and mean daily air temperature do not seem to be correlated. In some cases, however, the two procedures were found to give quite dissimilar levels of significance on the rejection or not of the null hypothesis of no correlation. The simple statistical analysis presented in this study, appropriately extended in large sets of meteorological data, may be a useful tool for estimating effects of wind on local climate studies.

Intercomparison of the community multiscale air quality model and CALGRID using process analysis.

PubMed

O'Neill, Susan M; Lamb, Brian K

2005-08-01

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

Simulation of Atmospheric Dispersion of Elevated Releases from Point Sources in Mississippi Gulf Coast with Different Meteorological Data

PubMed Central

Yerramilli, Anjaneyulu; Srinivas, Challa Venkata; Dasari, Hari Prasad; Tuluri, Francis; White, Loren D.; Baham, Julius M.; Young, John H.; Hughes, Robert; Patrick, Chuck; Hardy, Mark G.; Swanier, Shelton J.

2009-01-01

Atmospheric dispersion calculations are made using the HYSPLIT Particle Dispersion Model for studying the transport and dispersion of air-borne releases from point elevated sources in the Mississippi Gulf coastal region. Simulations are performed separately with three meteorological data sets having different spatial and temporal resolution for a typical summer period in 1–3 June 2006 representing a weak synoptic condition. The first two data are the NCEP global and regional analyses (FNL, EDAS) while the third is a meso-scale simulation generated using the Weather Research and Forecasting model with nested domains at a fine resolution of 4 km. The meso-scale model results show significant temporal and spatial variations in the meteorological fields as a result of the combined influences of the land-sea breeze circulation, the large scale flow field and diurnal alteration in the mixing depth across the coast. The model predicted SO2 concentrations showed that the trajectory and the concentration distribution varied in the three cases of input data. While calculations with FNL data show an overall higher correlation, there is a significant positive bias during daytime and negative bias during night time. Calculations with EDAS fields are significantly below the observations during both daytime and night time though plume behavior follows the coastal circulation. The diurnal plume behavior and its distribution are better simulated using the mesoscale WRF meteorological fields in the coastal environment suggesting its suitability for pollution dispersion impact assessment in the local scale. Results of different cases of simulation, comparison with observations, correlation and bias in each case are presented. PMID:19440433

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

PubMed

Yan, Long; Wang, Hong; Zhang, Xuan; Li, Ming-Yue; He, Juan

2017-01-01

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model. A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE). Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy. The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

Extreme weather exposure identification for road networks - a comparative assessment of statistical methods

NASA Astrophysics Data System (ADS)

Schlögl, Matthias; Laaha, Gregor

2017-04-01

The assessment of road infrastructure exposure to extreme weather events is of major importance for scientists and practitioners alike. In this study, we compare the different extreme value approaches and fitting methods with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series (PDS) over the standardly used annual maxima series (AMS) in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing PDS) being superior to the block maxima approach (employing AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was visible from neither the square-root criterion nor standardly used graphical diagnosis (mean residual life plot) but rather from a direct comparison of AMS and PDS in combined quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best-suited approach. This will make the analyses more robust, not only in cases where threshold selection and dependency introduces biases to the PDS approach but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend the use of conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of the study directly address road and traffic management but can be transferred to a range of other environmental variables including meteorological and hydrological quantities.

A comparative assessment of statistical methods for extreme weather analysis

NASA Astrophysics Data System (ADS)

Schlögl, Matthias; Laaha, Gregor

2017-04-01

Extreme weather exposure assessment is of major importance for scientists and practitioners alike. We compare different extreme value approaches and fitting methods with respect to their value for assessing extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series over the standardly used annual maxima series in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing partial duration series, PDS) being superior to the block maxima approach (employing annual maxima series, AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was neither visible from the square-root criterion, nor from standardly used graphical diagnosis (mean residual life plot), but from a direct comparison of AMS and PDS in synoptic quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best suited approach. This will make the analyses more robust, in cases where threshold selection and dependency introduces biases to the PDS approach, but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of this study are of relevance for a broad range of environmental variables, including meteorological and hydrological quantities.

The Association Between Heat Waves and Other Meteorological Parameters and Snakebites: Israel National Study.

PubMed

Shashar, Sagi; Yitshak-Sade, Maayan; Sonkin, Roman; Novack, Victor; Jaffe, Eli

2018-06-01

Published annual estimates report a global burden of 2.5 million snakebite cases and >100,000 deaths. In Israel, envenomations are the third most frequent cause of poisonings that are of moderate to major clinical severity. Most studies focus on the clinical descriptions of snakebites in tropical climates, and we sought to investigate the association between snakebite frequency and meteorological parameters. We sought to investigate the seasonality of snakebites and evaluate the association between increasingly common heat waves and other meteorological parameters and snakebite frequency in a semiarid nontropical climate. We obtained data for all medical evacuations (2008-2015) because of snakebites in Israel. Climate data included daily 24-hour average temperature (°C) and relative humidity (%). We used a time-stratified case crossover method, in which a conditional logistic regression was applied to estimate the association, and we also stratified our analysis by season and by region. We identified 1234 snakebite cases over 8 years, of which most (74.2%) occurred in hot seasons and between 6 pm and 9 pm. The risk of snakebite was positively associated with temperature >23°C (odds ratio [OR] 1.24, 95% confidence interval [CI] 1.01-1.53) and inversely with humidity >40% (OR 0.74, 95% CI 0.57-0.97). We also found an association with heat waves both in cold (OR 1.62, 95% CI 1.01-2.60) and hot seasons (OR 1.50, 95% CI 1.18-1.92). In a semiarid nontropical climate, we observed an association between an increase in the number of snakebite cases and higher temperatures and lower humidity. Moreover, heat waves increased the frequency of snakebites in both cold and hot seasons. Copyright © 2018 Elsevier Inc. All rights reserved.

Meteorological, environmental remote sensing and neural network analysis of the epidemiology of malaria transmission in Thailand.

PubMed

Kiang, Richard; Adimi, Farida; Soika, Valerii; Nigro, Joseph; Singhasivanon, Pratap; Sirichaisinthop, Jeeraphat; Leemingsawat, Somjai; Apiwathnasorn, Chamnarn; Looareesuwan, Sornchai

2006-11-01

In many malarious regions malaria transmission roughly coincides with rainy seasons, which provide for more abundant larval habitats. In addition to precipitation, other meteorological and environmental factors may also influence malaria transmission. These factors can be remotely sensed using earth observing environmental satellites and estimated with seasonal climate forecasts. The use of remote sensing usage as an early warning tool for malaria epidemics have been broadly studied in recent years, especially for Africa, where the majority of the world's malaria occurs. Although the Greater Mekong Subregion (GMS), which includes Thailand and the surrounding countries, is an epicenter of multidrug resistant falciparum malaria, the meteorological and environmental factors affecting malaria transmissions in the GMS have not been examined in detail. In this study, the parasitological data used consisted of the monthly malaria epidemiology data at the provincial level compiled by the Thai Ministry of Public Health. Precipitation, temperature, relative humidity, and vegetation index obtained from both climate time series and satellite measurements were used as independent variables to model malaria. We used neural network methods, an artificial-intelligence technique, to model the dependency of malaria transmission on these variables. The average training accuracy of the neural network analysis for three provinces (Kanchanaburi, Mae Hong Son, and Tak) which are among the provinces most endemic for malaria, is 72.8% and the average testing accuracy is 62.9% based on the 1994-1999 data. A more complex neural network architecture resulted in higher training accuracy but also lower testing accuracy. Taking into account of the uncertainty regarding reported malaria cases, we divided the malaria cases into bands (classes) to compute training accuracy. Using the same neural network architecture on the 19 most endemic provinces for years 1994 to 2000, the mean training accuracy weighted by provincial malaria cases was 73%. Prediction of malaria cases for 2001 using neural networks trained for 1994-2000 gave a weighted accuracy of 53%. Because there was a significant decrease (31%) in the number of malaria cases in the 19 provinces from 2000 to 2001, the networks overestimated malaria transmissions. The decrease in transmission was not due to climatic or environmental changes. Thailand is a country with long borders. Migrant populations from the neighboring countries enlarge the human malaria reservoir because these populations have more limited access to health care. This issue also confounds the complexity of modeling malaria based on meteorological and environmental variables alone. In spite of the relatively low resolution of the data and the impact of migrant populations, we have uncovered a reasonably clear dependency of malaria on meteorological and environmental remote sensing variables. When other contextual determinants do not vary significantly, using neural network analysis along with remote sensing variables to predict malaria endemicity should be feasible.

A GIS Procedure to Monitor PWV During Severe Meteorological Events

NASA Astrophysics Data System (ADS)

Ferrando, I.; Federici, B.; Sguerso, D.

2016-12-01

As widely known, the observation of GNSS signal's delay can improve the knowledge of meteorological phenomena. The local Precipitable Water Vapour (PWV), which can be easily derived from Zenith Total Delay (ZTD), Pressure (P) and Temperature (T) (Bevis et al., 1994), is not a satisfactory parameter to evaluate the occurrence of severe meteorological events. Hence, a GIS procedure, called G4M (GNSS for Meteorology), has been conceived to produce 2D PWV maps with high spatial and temporal resolution (1 km and 6 minutes respectively). The input data are GNSS, P and T observations not necessarily co-located coming from existing infrastructures, combined with a simplified physical model, owned by the research group.On spite of the low density and the different configurations of GNSS, P and T networks, the procedure is capable to detect severe meteorological events with reliable results. The procedure has already been applied in a wide and orographically complex area covering approximately the north-west of Italy and the French-Italian border region, to study two severe meteorological events occurred in Genoa (Italy) and other meteorological alert cases. The P, T and PWV 2D maps obtained by the procedure have been compared with the ones coming from meteorological re-analysis models, used as reference to obtain statistics on the goodness of the procedure in representing these fields. Additionally, the spatial variability of PWV was taken into account as indicator for representing potential critical situations; this index seems promising in highlighting remarkable features that precede intense precipitations. The strength and originality of the procedure lie into the employment of existing infrastructures, the independence from meteorological models, the high adaptability to different networks configurations, and the ability to produce high-resolution 2D PWV maps even from sparse input data. In the next future, the procedure could also be set up for near real-time applications.

The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

2015-04-01

Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

A comparison study of the application of data assimilation in the short-term prediction of radiation and precipitation

NASA Astrophysics Data System (ADS)

Ding, Huang; Cui, Fang; Wang, Zhijia; Zhou, Hai; Chen, Weidong

2018-03-01

Based on the meteorological observation of the DG plants in East China, the assimilation effect of the WRF in the summer of 2016 was studied. The results show that, in the case of using data assimilation, the model correctly predicted the occurrence time of precipitation, as well as the variation of the precipitation along with the time were well consistent with the observations, which gives more accurate downward shortwave radiation. The application of data assimilation techniques can provide reliable information to adapt to the high resolution of meso-scale meteorological model. Therefore, it provides the necessary technical support for the development of the distributed power generation.

Evaluation of meteorological and epidemiological characteristics of fatal pulmonary embolism

NASA Astrophysics Data System (ADS)

Törő, Klára; Pongrácz, Rita; Bartholy, Judit; Váradi-T, Aletta; Marcsa, Boglárka; Szilágyi, Brigitta; Lovas, Attila; Dunay, György; Sótonyi, Péter

2016-03-01

The objective of the present study was to identify risk factors among epidemiological factors and meteorological conditions in connection with fatal pulmonary embolism. Information was collected from forensic autopsy records in sudden unexpected death cases where pulmonary embolism was the exact cause of death between 2001 and 2010 in Budapest. Meteorological parameters were detected during the investigated period. Gender, age, manner of death, cause of death, place of death, post-mortem pathomorphological changes and daily meteorological conditions (i.e. daily mean temperature and atmospheric pressure) were examined. We detected that the number of registered pulmonary embolism (No 467, 211 male) follows power law in time regardless of the manner of death. We first described that the number of registered fatal pulmonary embolism up to the nth day can be expressed as Y( n) = α ṡ n β where Y denotes the number of fatal pulmonary embolisms up to the nth day and α > 0 and β > 1 are model parameters. We found that there is a definite link between the cold temperature and the increasing incidence of fatal pulmonary embolism. Cold temperature and the change of air pressure appear to be predisposing factors for fatal pulmonary embolism. Meteorological parameters should have provided additional information about the predisposing factors of thromboembolism.

The short-term association between meteorological factors and mumps in Jining, China.

PubMed

Li, Runzi; Lin, Hualiang; Liang, Yumin; Zhang, Tao; Luo, Cheng; Jiang, Zheng; Xu, Qinqin; Xue, Fuzhong; Liu, Yanxun; Li, Xiujun

2016-10-15

An increasing trend of the incidence of mumps has been observed in a few developing countries in recent years, presenting a major threat to children's health. A few studies have examined the relationship between meteorological factors and mumps with inconsistent findings. The daily data of meteorological variables and mumps from 2009 to 2013 were obtained from Jining, a temperate inland city of China. A generalized additive model was used to quantify the association between meteorological factors and mumps based on the exposure-response relationship. A total of 8520 mumps cases were included in this study. We found a nonlinear relationship of daily mean temperature, sunshine duration and relative humidity with mumps, with an approximately linear association for mean temperature above 4°C (excess risk (ER) for 1°C increase was 2.72%, 95% confidence interval (CI): 2.38%, 3.05% on the current day), for relative humidity above 54%, the ER for 1% increase was -1.86% (95% CI: -2.06%, -1.65%) at lag day 14; and for sunshine duration higher than 5h/d, the ER for per 1h/d increase was12.91% (95% CI: 11.38%, 14.47%) at lag day 1. While we found linear effects for daily wind speed (ER: 2.98%, 95% CI: 2.71%, 3.26% at lag day 13). This study suggests that meteorological factors might be important predictors of incidence of mumps, and should be considered in its control and prevention. Copyright © 2016 Elsevier B.V. All rights reserved.

The Effects of a Blizzard on Urban Air Pollution.

ERIC Educational Resources Information Center

da Silva, Armando; Bein, Frederick L.

1981-01-01

The chronology and effects of a 1978 blizzard on Indianapolis' air pollution levels (ozone, sulfur dioxide, carbon monoxide) are used as a case study for geography classes. Photographs, graphs, and maps are provided as examples of meteorological data collection and interpretation. (AM)

[Assessment of the effect of meteorological factors on the health of a group of patients in the city of Iaşi].

PubMed

Martinescu, Gabriela; Gavăt, Viorica

2012-01-01

Analyzing the meteorological factors influence perception on state of health and evaluation of the awareness of how they act. The study was carried out between 2010-2011 on a sample of 75 patients from of a cabinet of family medicine in the city of Iasi. The lot included randomly selected persons with age between 18-74 years. They answered a questionnaire with 25 items. The questionnaire Included demographic date (age, education, social, financial situation, the belonging religious) and questions on personal perception and evaluation of the influence of climate and weather conditions on individual state of health, degree to promote beneficial climatic factors in maintaining health and quality of life. The istribution of Cases in function of perception implication in meteorological factors in health reveals the following aspects: they showed significantly morecases meteoro-sensibili from urban areas (45.3%) and meteoro dependentecases from rural areas (10.7%) in our group has revealed several casesmeteorosensibile both females (36%) and the male ones (14.7%) Distribution in the study group depending on the class of diseases revealed predominant rheumatic diseases (36%) and heart disease (33.3%), haematological (20%) mental illness (14.7%) digestive (12%),respiratory diseases and neurological (10.7%). Meteorological facts does not represent etiological but the favoring or triggering factors in some pathological conditions. Important weather newsletters in informing and educating patients about the risks of meteorological sesnsibili requires that a necessity for maintaining health andquality of life.

Development of a Method for Selecting Optimum Sites for the Automatic Mountain Meteorology Observation Station (AMOS) to Improve Predictability of Forest Fires in Inaccessible Area

NASA Astrophysics Data System (ADS)

Yoon, S.; Won, M.; Jang, K.; Lim, J.

2016-12-01

As there has been a recent increase in the case of forest fires in North Korea descending southward through the De-Militarized Zone (DMZ), ensuring proper response to such events has been a challenge. Therefore, in order to respond and manage these forest fires appropriately, an improvement in the forest fire predictability through integration of mountain weather information observed at the most optimal site is necessary. This study is a proactive case in which a spatial analysis and an on-site assessment method were developed for selecting an optimum site for a mountain weather observation in national forest. For spatial analysis, the class 1 and 2 forest fire danger areas for the past 10 years, accessibility maximum 100m, Automatic Weather Station (AWS) redundancy within 2.5km, and mountain terrains higher than 200m were analyzed. A final overlay analysis was performed to select the candidates for the field assessment. The sites selected through spatial analysis were quantitatively evaluated based on the optimal meteorological environment, forest and hiking trail accessibility, AWS redundancy, and supply of wireless communication and solar powered electricity. The sites with total score of 70 and higher were accepted as adequate. At the final selected sites, an AMOS was established, and integration of mountain and Korea Meteorological Administration (KMA) weather data improved the forest fire predictability in South Korea by 10%. Given these study results, we expect that establishing an automatic mountain meteorology observation station at the optimal sites in inaccessible area and integrating mountain weather data will improve the predictability of forest fires.

Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

NASA Astrophysics Data System (ADS)

Rodríguez-Rincón, J. P.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

2015-07-01

This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multi-physics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.

Impact of meteorological changes on the incidence of scarlet fever in Hefei City, China.

PubMed

Duan, Yu; Huang, Xiao-Lei; Wang, Yu-Jie; Zhang, Jun-Qing; Zhang, Qi; Dang, Yue-Wen; Wang, Jing

2016-10-01

Studies on scarlet fever with meteorological factors included were few. We aimed to illustrate meteorological factors' effects on monthly incidence of scarlet fever. Cases of scarlet fever were collected from the report of legal infectious disease in Hefei City from 1985 to 2006; the meteorological data were obtained from the weather bureau of Hefei City. Monthly incidence and corresponding meteorological data in these 22 years were used to develop the model. The model of auto regressive integrated moving average with covariates was used in statistical analyses. There was a highest peak from March to June and a small peak from November to January. The incidence of scarlet fever ranges from 0 to 0.71502 (per 10 5 population). SARIMAX (1,0,0)(1,0,0) 12 model was fitted with monthly incidence and meteorological data optimally. It was shown that relative humidity (β = -0.002, p = 0.020), mean temperature (β = 0.006, p = 0.004), and 1 month lag minimum temperature (β = -0.007, p < 0.001) had effect on the incidence of scarlet fever in Hefei. Besides, the incidence in a previous month (AR(β) = 0.469, p < 0.001) and in 12 months before (SAR(β) = 0.255, p < 0.001) was positively associated with the incidence. This study shows that scarlet fever incidence was negatively associated with monthly minimum temperature and relative humidity while was positively associated with mean temperature in Hefei City, China. Besides, the ARIMA model could be useful not only for prediction but also for the analysis of multiple correlations.

Assessment and prediction of short term hospital admissions: the case of Athens, Greece

NASA Astrophysics Data System (ADS)

Kassomenos, P.; Papaloukas, C.; Petrakis, M.; Karakitsios, S.

The contribution of air pollution on hospital admissions due to respiratory and heart diseases is a major issue in the health-environmental perspective. In the present study, an attempt was made to run down the relationships between air pollution levels and meteorological indexes, and corresponding hospital admissions in Athens, Greece. The available data referred to a period of eight years (1992-2000) including the daily number of hospital admissions due to respiratory and heart diseases, hourly mean concentrations of CO, NO 2, SO 2, O 3 and particulates in several monitoring stations, as well as, meteorological data (temperature, relative humidity, wind speed/direction). The relations among the above data were studied through widely used statistical techniques (multivariate stepwise analyses) and Artificial Neural Networks (ANNs). Both techniques revealed that elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg m -3 leads to an increase of 10.2% in the number of admissions), followed by O 3 and the rest of the pollutants (CO, NO 2 and SO 2). Meteorological parameters also play a decisive role in the formation of air pollutant levels affecting public health. Consequently, increased/decreased daily hospital admissions are related to specific types of meteorological conditions that favor/do not favor the accumulation of pollutants in an urban complex. In general, the role of meteorological factors seems to be underestimated by stepwise analyses, while ANNs attribute to them a more important role. Comparison of the two models revealed that ANN adaptation in complicate environmental issues presents improved modeling results compared to a regression technique. Furthermore, the ANN technique provides a reliable model for the prediction of the daily hospital admissions based on air quality data and meteorological indices, undoubtedly useful for regulatory purposes.

Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

2015-01-01

Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

Application of a Gaussian multilayer diffusion model to characterize dispersion of vertical HCl column density in rocket exhaust clouds

NASA Technical Reports Server (NTRS)

Pellett, G. L.; Staton, W. L.

1981-01-01

Solid rocket exhaust cloud dispersion cases, based on seven meteorological regimes for overland advection in the Cape Canaveral, Florida, area, are examined for launch vehicle environmental impacts. They include a space shuttle case and all seven meteorological cases for the Titan 3, which exhausts 60% less HC1. The C(HC1) decays are also compared with recent in cloud peak HC1 data from eight Titan 3 launches. It is stipulated that while good overall agreement provides validation of the model, its limitations are considerable and a dynamics model is needed to handle local convective situations.

A spatiotemporal dengue fever early warning model accounting for nonlinear associations with meteorological factors: a Bayesian maximum entropy approach

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung; Chien, Lung-Chang

2014-05-01

Dengue fever has been identified as one of the most widespread vector-borne diseases in tropical and sub-tropical. In the last decade, dengue is an emerging infectious disease epidemic in Taiwan especially in the southern area where have annually high incidences. For the purpose of disease prevention and control, an early warning system is urgently needed. Previous studies have showed significant relationships between climate variables, in particular, rainfall and temperature, and the temporal epidemic patterns of dengue cases. However, the transmission of the dengue fever is a complex interactive process that mostly understated the composite space-time effects of dengue fever. This study proposes developing a one-week ahead warning system of dengue fever epidemics in the southern Taiwan that considered nonlinear associations between weekly dengue cases and meteorological factors across space and time. The early warning system based on an integration of distributed lag nonlinear model (DLNM) and stochastic Bayesian Maximum Entropy (BME) analysis. The study identified the most significant meteorological measures including weekly minimum temperature and maximum 24-hour rainfall with continuous 15-week lagged time to dengue cases variation under condition of uncertainty. Subsequently, the combination of nonlinear lagged effects of climate variables and space-time dependence function is implemented via a Bayesian framework to predict dengue fever occurrences in the southern Taiwan during 2012. The result shows the early warning system is useful for providing potential outbreak spatio-temporal prediction of dengue fever distribution. In conclusion, the proposed approach can provide a practical disease control tool for environmental regulators seeking more effective strategies for dengue fever prevention.

The role of temperature in reported chickenpox cases from 2000 to 2011 in Japan.

PubMed

Harigane, K; Sumi, A; Mise, K; Kobayashi, N

2015-09-01

Annual periodicities of reported chickenpox cases have been observed in several countries. Of these, Japan has reported a two-peaked, bimodal annual cycle of reported chickenpox cases. This study investigated the possible underlying association of the bimodal cycle observed in the surveillance data of reported chickenpox cases with the meteorological factors of temperature, relative humidity and rainfall. A time-series analysis consisting of the maximum entropy method spectral analysis and the least squares method was applied to the chickenpox data and meteorological data of 47 prefectures in Japan. In all of the power spectral densities for the 47 prefectures, the spectral lines were observed at the frequency positions corresponding to the 1-year and 6-month cycles. The optimum least squares fitting (LSF) curves calculated with the 1-year and 6-month cycles explained the underlying variation of the chickenpox data. The LSF curves reproduced the bimodal and unimodal cycles that were clearly observed in northern and southern Japan, respectively. The data suggest that the second peaks in the bimodal cycles in the reported chickenpox cases in Japan occurred at a temperature of approximately 8·5 °C.

Do local meteorological conditions influence skin irritation caused by transdermal rivastigmine? A retroprospective, pilot study.

PubMed

Segers, Kurt; Cytryn, Ephraim; Surquin, Murielle

2012-06-01

This retrospective study aimed to evaluate the incidence of transdermal rivastigmine treatment withdrawal secondary to adverse skin reactions among the patients from our Memory Clinic. In addition, we tested whether climatic conditions might have an influence on skin irritations leading to eventual treatment disruption. We performed a retrospective review of patients from the Brugmann University Hospital Memory Clinic having started transdermal rivastigmine between June 2008 and December 2010. Local meteorological data were provided by the Royal Meteorological Institute of Belgium. A total of 26.9% of the patients experienced adverse skin reactions at the rivastigmine application site, leading to treatment discontinuation in 19.2% of the cases. Rivastigmine cutaneous tolerability was not found to be related to demographic parameters, Mini Mental Status Examination score, or type of dementia. High temperature and low air humidity during the first month of treatment were found to be associated with a higher incidence of skin reactions and secondary treatment disruption. Transdermal rivastigmine induced a higher incidence of cutaneous adverse events than previously reported in a prospective clinical trial. Moreover, it seems that meteorological conditions favoring skin perspiration (high temperature and low air humidity) during the first month of treatment might have an influence on transdermal rivastigmine skin tolerability.

Infrasonic emissions from local meteorological events: A summary of data taken throughout 1984

NASA Technical Reports Server (NTRS)

Zuckerwar, A. J.

1986-01-01

Records of infrasonic signals, propagating through the Earth's atmosphere in the frequency band 2 to 16 Hz, were gathered on a three microphone array at Langley Research Center throughout the year 1984. Digital processing of these records fulfilled three functions: time delay estimation, based on an adaptive filter; source location, determined from the time delay estimates; and source identification, based on spectral analysis. Meteorological support was provided by significant meteorological advisories, lightning locator plots, and daily reports from the Air Weather Service. The infrasonic data are organized into four characteristic signatures, one of which is believed to contain emissions from local meteorological sources. This class of signature prevailed only on those days when major global meteorological events appeared in or near to eastern United States. Eleven case histories are examined. Practical application of the infrasonic array in a low level wing shear alert system is discussed.

Spatial Variability of Mercury Wet Deposition in Eastern Ohio: Summertime Meteorological Case Study Analysis of Local Source Influences

EPA Science Inventory

Extensive exploration of event precipitation data in the Ohio River Valley indicates that coal combustion emissions play an important role in mercury (Hg) wet deposition. During July-September 2006, an intensive study was undertaken to discern the degree of local source influence...

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study.

PubMed

Escarela, Gabriel

2012-06-01

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.

Dispersion modeling of accidental releases of toxic gases - utility for the fire brigades.

NASA Astrophysics Data System (ADS)

Stenzel, S.; Baumann-Stanzer, K.

2009-09-01

Several air dispersion models are available for prediction and simulation of the hazard areas associated with accidental releases of toxic gases. The most model packages (commercial or free of charge) include a chemical database, an intuitive graphical user interface (GUI) and automated graphical output for effective presentation of results. The models are designed especially for analyzing different accidental toxic release scenarios ("worst-case scenarios”), preparing emergency response plans and optimal countermeasures as well as for real-time risk assessment and management. The research project RETOMOD (reference scenarios calculations for toxic gas releases - model systems and their utility for the fire brigade) was conducted by the Central Institute for Meteorology and Geodynamics (ZAMG) in cooperation with the Viennese fire brigade, OMV Refining & Marketing GmbH and Synex Ries & Greßlehner GmbH. RETOMOD was funded by the KIRAS safety research program of the Austrian Ministry of Transport, Innovation and Technology (www.kiras.at). The main tasks of this project were 1. Sensitivity study and optimization of the meteorological input for modeling of the hazard areas (human exposure) during the accidental toxic releases. 2. Comparison of several model packages (based on reference scenarios) in order to estimate the utility for the fire brigades. For the purpose of our study the following models were tested and compared: ALOHA (Areal Location of Hazardous atmosphere, EPA), MEMPLEX (Keudel av-Technik GmbH), Trace (Safer System), Breeze (Trinity Consulting), SAM (Engineering office Lohmeyer). A set of reference scenarios for Chlorine, Ammoniac, Butane and Petrol were proceed, with the models above, in order to predict and estimate the human exposure during the event. Furthermore, the application of the observation-based analysis and forecasting system INCA, developed in the Central Institute for Meteorology and Geodynamics (ZAMG) in case of toxic release was investigated. INCA (Integrated Nowcasting through Comprehensive Analysis) data are calculated operationally with 1 km horizontal resolution and based on the weather forecast model ALADIN. The meteorological field's analysis with INCA include: Temperature, Humidity, Wind, Precipitation, Cloudiness and Global Radiation. In the frame of the project INCA data were compared with measurements from the meteorological observational network, conducted at traffic-near sites in Vienna. INCA analysis and very short term forecast fields (up to 6 hours) are found to be an advanced possibility to provide on-line meteorological input for the model package used by the fire brigade. Since the input requirements differ from model to model, and the outputs are based on unequal criteria for toxic area and exposure, a high degree of caution in the interpretation of the model results is required - especially in the case of slow wind speeds, stable atmospheric condition, and flow deflection by buildings in the urban area or by complex topography.

Assessment of the relationship between satellite AOD and ground PM₁₀ measurement data considering synoptic meteorological patterns and Lidar data.

PubMed

Zeeshan, Muhammad; Kim Oanh, N T

2014-03-01

Correlation between satellite aerosol optical depth (AOD) and ground monitoring particulate matter (PM) depends on the meteorology that determines PM optical properties, its dispersion, accumulation and vertical distribution. This study presents a novel approach to analyze PM-AOD relationship considering the totality of meteorological factors expressed as synoptic patterns. Meteorological observations at 07:00 Bangkok time from 9 regional meteorological stations, in dry seasons (November-April) of 11 years (2000-2010), were used to categorize governing meteorology over Central Thailand into four categories representing the typical observed synoptic patterns. The MANOVA analysis showed that these patterns were statistically different. PM10 recorded at 22 air quality stations in Bangkok Metropolitan Region were examined which showed the highest levels for the days belonging to pattern 1, followed by pattern 4, both with presence of a high pressure ridge, while the minimum for pattern 2 when thermal lows dominated. Lidar aerosol backscatter profiles recorded at Pimai station were used as indicator of PM vertical distribution that showed similarity within each pattern. R(2) between MODIS and Sun photometer AODs at Pimai was above 0.8. Correlation coefficients (R) between MODIS AOD and corresponding 1h PM10 for clear sky days (cloudiness ≤ 3/10) were examined for each pattern in comparison with lump case. Significant improvements were observed for pattern 1, average R across 22 stations was 0.46 for Terra and 0.38 for Aqua AOD compared to lump case with R of 0.34 and 0.31, respectively. Comparable improvement was also observed for pattern 4. For pattern 2, R values were significantly reduced which may be caused by the deeper mixing layers and varying vertical profiles with overall low values of Lidar backscatter coefficients. Improved R values in pattern 1 and 4, which had highest PM10 in BMR, suggested a better potential of using MODIS AOD for PM10 monitoring with synoptic pattern classification. Copyright © 2013 Elsevier B.V. All rights reserved.

The Long and Short Incubation Periods of Plasmodium vivax Malaria in Korea: The Characteristics and Relating Factors

PubMed Central

Kim, Sun-Ja; Kim, Si-Heon; Jo, Soo-Nam; Gwack, Jin; Youn, Seung-Ki

2013-01-01

Background The cases of Plasmodium vivax malaria in Korea are mixed with long and short incubation periods. This study aims to define clinico-epidemiologic chracteristcs of Plasmodium vivax malaria in Korea. Materials and Methods We selected the civilian cases infected with P. vivax malaria in Korea from the epidemiological investigation data of 2001 to 2010, whose incubation periods could be estimated. The long and short incubation periods were defined by duration of infection and onset time, and the cases were compared by demographic factors and clinical symptom, infection and onset time. The correlation was analyzed between the proportion of cases in the infected region with the long incubation period and meteorological factors along with latitude. Results The length of the mean short and long incubation periods for the cases were 25.5 days and 329.4 days, respectively. The total number of the study subjects was 897, and the number cases of short and long incubation periods was 575 (64.1%) and 322 (35.9%), respectively. The aspect of incubation period showed a significant difference by region of infection; there was a higher proportion of long incubation period infection cases in Gangwon-do than in Gyeonggi-do and Incheon. The proportion of long incubation period cases showed significant correlation with latitude and temperature of August and September of the infected regions. Conclusions Incubation period of P. vivax malaria in Korea showed significant difference by infected region, infection and onset time and the proportion of long incubation period cases showed significant correlation with latitude and meteorological factors of the infected regions. PMID:24265966

The Long and Short Incubation Periods of Plasmodium vivax Malaria in Korea: The Characteristics and Relating Factors.

PubMed

Kim, Sun-Ja; Kim, Si-Heon; Jo, Soo-Nam; Gwack, Jin; Youn, Seung-Ki; Jang, Jae-Yeon

2013-06-01

The cases of Plasmodium vivax malaria in Korea are mixed with long and short incubation periods. This study aims to define clinico-epidemiologic chracteristcs of Plasmodium vivax malaria in Korea. We selected the civilian cases infected with P. vivax malaria in Korea from the epidemiological investigation data of 2001 to 2010, whose incubation periods could be estimated. The long and short incubation periods were defined by duration of infection and onset time, and the cases were compared by demographic factors and clinical symptom, infection and onset time. The correlation was analyzed between the proportion of cases in the infected region with the long incubation period and meteorological factors along with latitude. The length of the mean short and long incubation periods for the cases were 25.5 days and 329.4 days, respectively. The total number of the study subjects was 897, and the number cases of short and long incubation periods was 575 (64.1%) and 322 (35.9%), respectively. The aspect of incubation period showed a significant difference by region of infection; there was a higher proportion of long incubation period infection cases in Gangwon-do than in Gyeonggi-do and Incheon. The proportion of long incubation period cases showed significant correlation with latitude and temperature of August and September of the infected regions. Incubation period of P. vivax malaria in Korea showed significant difference by infected region, infection and onset time and the proportion of long incubation period cases showed significant correlation with latitude and meteorological factors of the infected regions.

Simplified methods for real-time prediction of storm surge uncertainty: The city of Venice case study

NASA Astrophysics Data System (ADS)

Mel, Riccardo; Viero, Daniele Pietro; Carniello, Luca; Defina, Andrea; D'Alpaos, Luigi

2014-09-01

Providing reliable and accurate storm surge forecasts is important for a wide range of problems related to coastal environments. In order to adequately support decision-making processes, it also become increasingly important to be able to estimate the uncertainty associated with the storm surge forecast. The procedure commonly adopted to do this uses the results of a hydrodynamic model forced by a set of different meteorological forecasts; however, this approach requires a considerable, if not prohibitive, computational cost for real-time application. In the present paper we present two simplified methods for estimating the uncertainty affecting storm surge prediction with moderate computational effort. In the first approach we use a computationally fast, statistical tidal model instead of a hydrodynamic numerical model to estimate storm surge uncertainty. The second approach is based on the observation that the uncertainty in the sea level forecast mainly stems from the uncertainty affecting the meteorological fields; this has led to the idea to estimate forecast uncertainty via a linear combination of suitable meteorological variances, directly extracted from the meteorological fields. The proposed methods were applied to estimate the uncertainty in the storm surge forecast in the Venice Lagoon. The results clearly show that the uncertainty estimated through a linear combination of suitable meteorological variances nicely matches the one obtained using the deterministic approach and overcomes some intrinsic limitations in the use of a statistical tidal model.

Modelling the meteorological forest fire niche in heterogeneous pyrologic conditions.

PubMed

De Angelis, Antonella; Ricotta, Carlo; Conedera, Marco; Pezzatti, Gianni Boris

2015-01-01

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition.

Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions

PubMed Central

De Angelis, Antonella; Ricotta, Carlo; Conedera, Marco; Pezzatti, Gianni Boris

2015-01-01

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition. PMID:25679957

Teaching Mesoscale Meteorology in the Age of the Modernized National Weather Service: A Report on the Unidata/COMET Workshop.

NASA Astrophysics Data System (ADS)

Ramamurthy, Mohan K.; Murphy, Charles; Moore, James; Wetzel, Melanie; Knight, David; Ruscher, Paul; Mullen, Steve; Desouza, Russel; Hawk, Denise S.; Fulker, David

1995-12-01

This report summarizes discussions that took place during a Unidata Cooperative Program for Operational Meteorology, Education, and Training (COMET) workshop on Mesoscale Meteorology Instruction in the Age of the Modernized Weather Service. The workshop was held 13-17 June 1994 in Boulder, Colorado, and it was organized by the Unidata Users Committee, with help from Unidata, COMET, and the National Center for Atmospheric Research staff. The principal objective of the workshop was to assess the need for and to initiate those changes at universities that will be required if students are to learn mesoscale and synoptic meteorology more effectively in this era of rapid technological advances. Seventy-one participants took part in the workshop, which included invited lectures, breakout roundtable discussions on focused topics, electronic poster sessions, and a forum for discussing recommendations and findings in a plenary session. Leading scientists and university faculty in the area of synoptic and mesoscale meteorology were invited to share their ideas for integrating data from new observing systems, research and operational weather prediction models, and interactive computer technologies into the classroom. As a result, many useful ideas for incorporating mesoscale datasets and analysis tools into the classroom emerged. Also, recommendations for future coordinated activities to create, catalog, and distribute case study datasets were made by the attendees.

Measurements and Modeling of The Air Pollution and The Meteorology On A Complex Topography Region: Case Study Grenoble 1998/1999

NASA Astrophysics Data System (ADS)

Couach, O.; Balin, I.; Jimenez, R.; Quaglia, P.; Kirchner, F.; Ristori, P.; Simeonov, V.; Clappier, A.; van den Bergh, H.; Calpini, B.

In order to understand, to predict and to elaborate solutions concerning the photo- chemical and meteorological processes, which occur often in the summer time over the Grenoble city and its three surroundings valleys, both modeling and measurement approaches were considered. Two intensive air pollution and meteorological measure- ments campaigns were performed in 1998 and 1999. Ozone (O3) and other pollutants (NOx, CH2O, SO2, etc) as well as wind, temperature, solar radiation and relative hu- midity were intensively measured at surface level combined with 3D measurements range by using: an instrumented aircraft (Metair), two ozone lidars (e.g. EPFL ozone dial lidar) and wind profilers (e.g.Degreane). This poster will focus on the main results of these measurements like the 3D ozone distribution, the mixing height/planetary boundary layer evolution, the meteorological behavior, and the other pollutants evalu- ation. The paper also highlights the use of these measurements as a necessary database for comparison and checking (validation) of the model performances and thus to allow modeling solutions in predicting the air pollution events and thus permitting to build the right abatement strategies.

Winter air pollution and infant bronchiolitis in Paris.

PubMed

Ségala, Claire; Poizeau, David; Mesbah, Mounir; Willems, Sylvie; Maidenberg, Manuel

2008-01-01

Respiratory syncytial virus (RSV) is one of the most common respiratory pathogens in infants and young children. It is not known why some previously healthy infants, when in contact with RSV, develop bronchiolitis whereas others have only mild symptoms. Our study aimed to evaluate the possible association between emergency hospital visits for bronchiolitis and air pollution in the Paris region during four winter seasons. We included children under the age of 3 years who attended emergency room services for bronchiolitis (following standardized definition) during the period 1997-2001. Two series of data from 34 hospitals, the daily number of emergency hospital consultations (n=50857) and the daily number of hospitalizations (n=16588) for bronchiolitis, were analyzed using alternative statistical methods; these were the generalized additive model (GAM) and case-crossover models. After adjustments for public holidays, holidays and meteorological variables the case-crossover model showed that PM10, BS, SO2 and NO2 were positively associated with both consultations and hospitalizations. GAM models, adjusting for long-term trend, seasonality, holiday, public holiday, weekday and meteorological variables, gave similar results for SO2 and PM10. This study shows that air pollution may act as a trigger for the occurrence of acute severe bronchiolitis cases.

SeaWiFS technical report series. Volume 19: Case studies for SeaWiFS calibration and validation, part 2

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Acker, James G. (Editor); Firestone, Elaine R. (Editor); Mcclain, Charles R.; Fraser, Robert S.; Mclean, James T.; Darzi, Michael; Firestone, James K.; Patt, Frederick S.; Schieber, Brian D.

1994-01-01

This document provides brief reports, or case studies, on a number of investigations and data set development activities sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter 1 is a comparison with the atmospheric correction of Coastal Zone Color Scanner (CZCS) data using two independent radiative transfer formulations. Chapter 2 is a study on lunar reflectance at the SeaWiFS wavelengths which was useful in establishing the SeaWiFS lunar gain. Chapter 3 reports the results of the first ground-based solar calibration of the SeaWiFS instrument. The experiment was repeated in the fall of 1993 after the instrument was modified to reduce stray light; the results from the second experiment will be provided in the next case studies volume. Chapter 4 is a laboratory experiment using trap detectors which may be useful tools in the calibration round-robin program. Chapter 5 is the original data format evaluation study conducted in 1992 which outlines the technical criteria used in considering three candidate formats, the hierarchical data format (HDF), the common data format (CDF), and the network CDF (netCDF). Chapter 6 summarizes the meteorological data sets accumulated during the first three years of CZCS operation which are being used for initial testing of the operational SeaWiFS algorithms and systems and would be used during a second global processing of the CZCS data set. Chapter 7 describes how near-real time surface meteorological and total ozone data required for the atmospheric correction algorithm will be retrieved and processed. Finally, Chapter 8 is a comparison of surface wind products from various operational meteorological centers and field observations. Surface winds are used in the atmospheric correction scheme to estimate glint and foam radiances.

Weather features associated with aircraft icing conditions: a case study.

PubMed

Fernández-González, Sergio; Sánchez, José Luis; Gascón, Estíbaliz; López, Laura; García-Ortega, Eduardo; Merino, Andrés

2014-01-01

In the context of aviation weather hazards, the study of aircraft icing is very important because of several accidents attributed to it over recent decades. On February 1, 2012, an unusual meteorological situation caused severe icing of a C-212-200, an aircraft used during winter 2011-2012 to study winter cloud systems in the Guadarrama Mountains of the central Iberian Peninsula. Observations in this case were from a MP-3000A microwave radiometric profiler, which acquired atmospheric temperature and humidity profiles continuously every 2.5 minutes. A Cloud Aerosol and Precipitation Spectrometer (CAPS) was also used to study cloud hydrometeors. Finally, ice nuclei concentration was measured in an isothermal cloud chamber, with the goal of calculating concentrations in the study area. Synoptic and mesoscale meteorological conditions were analysed using the Weather Research and Forecasting (WRF) model. It was demonstrated that topography influenced generation of a mesolow and gravity waves on the lee side of the orographic barrier, in the region where the aircraft experienced icing. Other factors such as moisture, wind direction, temperature, atmospheric stability, and wind shear were decisive in the appearance of icing. This study indicates that icing conditions may arise locally, even when the synoptic situation does not indicate any risk.

Quercus pollen season dynamics in the Iberian peninsula: response to meteorological parameters and possible consequences of climate change.

PubMed

Garcia-Mozo, Herminia; Galan, Carmen; Jato, Victoria; Belmonte, Jordina; de la Guardia, Consuelo; Fernandez, Delia; Gutierrez, Montserrat; Aira, M; Roure, Joan; Ruiz, Luis; Trigo, Mar; Dominguez-Vilches, Eugenio

2006-01-01

The main characteristics of the Quercus pollination season were studied in 14 different localities of the Iberian Peninsula from 1992-2004. Results show that Quercus flowering season has tended to start earlier in recent years, probably due to the increased temperatures in the pre-flowering period, detected at study sites over the second half of the 20th century. A Growing Degree Days forecasting model was used, together with future meteorological data forecast using the Regional Climate Model developed by the Hadley Meteorological Centre, in order to determine the expected advance in the start of Quercus pollination in future years. At each study site, airborne pollen curves presented a similar pattern in all study years, with different peaks over the season attributable in many cases to the presence of several species. High pollen concentrations were recorded, particularly at Mediterranean sites. This study also proposes forecasting models to predict both daily pollen values and annual pollen emission. All models were externally validated using data for 2001 and 2004, with acceptable results. Finally, the impact of the highly-likely climate change on Iberian Quercus pollen concentration values was studied by applying RCM meteorological data for different future years, 2025, 2050, 2075 and 2099. Results indicate that under a doubled CO(2) scenario at the end of the 21st century Quercus pollination season could start on average one month earlier and airborne pollen concentrations will increase by 50 % with respect to current levels, with higher values in Mediterranean inland areas.

Changing teaching techniques and adapting new technologies to improve student learning in an introductory meteorology and climate course

NASA Astrophysics Data System (ADS)

Cutrim, E. M.; Rudge, D.; Kits, K.; Mitchell, J.; Nogueira, R.

2006-06-01

Responding to the call for reform in science education, changes were made in an introductory meteorology and climate course offered at a large public university. These changes were a part of a larger project aimed at deepening and extending a program of science content courses that model effective teaching strategies for prospective middle school science teachers. Therefore, revisions were made to address misconceptions about meteorological phenomena, foster deeper understanding of key concepts, encourage engagement with the text, and promote inquiry-based learning. Techniques introduced include: use of a flash cards, student reflection questionnaires, writing assignments, and interactive discussions on weather and forecast data using computer technology such as Integrated Data Viewer (IDV). The revision process is described in a case study format. Preliminary results (self-reflection by the instructor, surveys of student opinion, and measurements of student achievement), suggest student learning has been positively influenced. This study is supported by three grants: NSF grant No. 0202923, the Unidata Equipment Award, and the Lucia Harrison Endowment Fund.

Relationship of spontaneous pneumothorax cases seen in Eastern Black Sea region with meteorological changes

NASA Astrophysics Data System (ADS)

Yamac, Mustafa Esat; Karapolat, Sami; Turkyilmaz, Atila; Seyis, Kubra Nur; Tekinbas, Celal

2017-08-01

The relationship of climate changes or weather conditions with the incidence of pneumothorax has been explored for many years. We aimed at revealing the effects of meteorological changes on the incidence of pneumothorax in the Eastern Black Sea region where spontaneous pneumothorax cases are seen relatively more frequently. The records of 195 subjects (179 males and 16 females) who had been monitored and treated due to spontaneous pneumothorax between January 2006 and December 2012 at our clinic were reviewed retrospectively, and their relationship was investigated with the meteorological data obtained by going through the database archive records of the 11th Regional Meteorology Directorate for the years between 2006 and 2012. Wind velocity was observed to be less in the days of having spontaneous pneumothorax than in the days of having no spontaneous pneumothorax, and the difference was found statistically significant ( P = 0.026). The people of our region whose active lifestyle is reflected in their working life, social life, and even in their folk dances usually take a rest in the days of slower wind speed. We think that this state of resting leads to an increase in the frequency of spontaneous pneumothorax.

Role of Temperature, Humidity and Rainfall on Influenza Transmission in Guatemala, El Salvador and Panama

NASA Technical Reports Server (NTRS)

Soebiyanto, Radina P.; Bonilla, Luis; Jara, Jorge; McCracken, John; Azziz?-Baumgartner, Eduardo; Widdowson, Marc-Alain; Kiang, Richard

2012-01-01

Worldwide, seasonal influenza causes about 500,000 deaths and 5 million severe illnesses per year. The environmental drivers of influenza transmission are poorly understood especially in the tropics. We aimed to identify meteorological factors for influenza transmission in tropical Central America. We gathered laboratory-confirmed influenza case-counts by week from Guatemala City, San Salvador Department (El Salvador) and Panama Province from 2006 to 2010. The average total cases per year were: 390 (Guatemala), 99 (San Salvador) and 129 (Panama). Meteorological factors including daily air temperature, rainfall, relative and absolute humidity (RH, AH) were obtained from ground stations, NASA satellites and land models. For these factors, we computed weekly averages and their deviation from the 5-yr means. We assessed the relationship between the number of influenza case-counts and the meteorological factors, including effects lagged by 1 to 4 weeks, using Poisson regression for each site. Our results showed influenza in San Salvador would increase by 1 case within a week of every 1 day with RH>75% (Relative Risk (RR)= 1.32, p=.001) and every 1C increase in minimum temperature (RR=1.29, p=.007) but it would decrease by 1 case for every 1mm-above mean weekly rainfall (RR=0.93,p<.001) (model pseudo-R2=0.55). Within 2 weeks, influenza in Panama was increased by 1 case for every 1% increase in RH (RR=1.04, p=.003), and it was increased by 2 cases for every 1C increase of minimum temperature (RR=2.01, p<.001) (model pseudo-R2=0.4). Influenza counts in Guatemala had 1 case increase for every 1C increase in minimum temperature in the previous week (RR=1.21, p<.001), and for every 1mm/day-above normal increase of rainfall rate (RR=1.03, p=.03) (model pseudo-R2=0.54). Our findings that cases increase with temperature and humidity differ from some temperate-zone studies. But they indicate that climate parameters such as humidity and temperature could be predictive of influenza activity and should be incorporated into country-specific influenza transmission models

Delta 2 Explosion Plume Analysis Report

NASA Technical Reports Server (NTRS)

Evans, Randolph J.

2000-01-01

A Delta II rocket exploded seconds after liftoff from Cape Canaveral Air Force Station (CCAFS) on 17 January 1997. The cloud produced by the explosion provided an opportunity to evaluate the models which are used to track potentially toxic dispersing plumes and clouds at CCAFS. The primary goal of this project was to conduct a case study of the dispersing cloud and the models used to predict the dispersion resulting from the explosion. The case study was conducted by comparing mesoscale and dispersion model results with available meteorological and plume observations. This study was funded by KSC under Applied Meteorology Unit (AMU) option hours. The models used in the study are part of the Eastern Range Dispersion Assessment System (ERDAS) and include the Regional Atmospheric Modeling System (RAMS), HYbrid Particle And Concentration Transport (HYPACT), and Rocket Exhaust Effluent Dispersion Model (REEDM). The primary observations used for explosion cloud verification of the study were from the National Weather Service's Weather Surveillance Radar 1988-Doppler (WSR-88D). Radar reflectivity measurements of the resulting cloud provided good estimates of the location and dimensions of the cloud over a four-hour period after the explosion. The results indicated that RAMS and HYPACT models performed reasonably well. Future upgrades to ERDAS are recommended.

Model study of meteorology and photochemical air pollution over un urban area in south-eastern France (ESCOMPTE campaign).

NASA Astrophysics Data System (ADS)

Taghavi, M.; Cautenet, S.

2003-04-01

The ESCOMPTE Campaign has been conducted over Southern France (Provence region including the Marseille, Aix and Toulon cities and the Fos-Berre industrial center) in June and July of 2001. In order to study the redistribution of the pollutants emitted by anthropic and biogenic emissions and their impact on the atmospheric chemistry, we used meso-scale modeling (RAMS model, paralleled version 4.3, coupled on line with chemical modules : MOCA2.2 (Poulet et al, 2002) including 29 gaseous species). The hourly high resolution emissions were obtained from ESCOMPTE database (Ponche et al, 2002). The model was coupled with the dry deposition scheme (Walmsley and Weseley,1996). In this particular case of complex circulation (sea breeze associated with topography), the processes involving peaks of pollution were strongly non linear, and the meso scale modeling coupled on line with chemistry module was an essential step for a realistic redistribution of chemical species. Two nested grids satisfactorily describe the synoptic dynamics and the sea breeze circulations. The ECMWF meteorological fields provide the initial and boundary conditions. Different events characterized by various meteorological situations were simulated. Meteorological fields retrieved by modeling, also Modeled ozone, NOx, CO and SO2 concentrations, were compared with balloons, lidars, aircrafts and surface stations measurements. The chemistry regimes were explained according to the distribution of plumes. The stratified layers were examined.

James Madison and a Shift in Precipitation Seasonality

NASA Astrophysics Data System (ADS)

Druckenbrod, D. L.; Mann, M. E.; Stahle, D. W.; Cleaveland, M. K.; Therrell, M. D.; Shugart, H. H.

2001-12-01

An eighteen-year meteorological diary and tree ring data from James Madison's Montpelier plantation provide a consistent reconstruction of early summer and prior fall rainfall for the 18th Century Virginia piedmont. The Madison meteorological diary suggests a seasonal shift in monthly rainfall towards an earlier wet season relative to 20th Century norms. Furthermore, dendroclimatic reconstructions of early summer and prior fall rainfall reflect this shift in the seasonality of summer rainfall. The most pronounced early summer drought during the Madison diary period is presented as a case study. This 1792 drought occurs during one of the strongest El Niño events on record and is highlighted in the correspondence of James Madison.

Frequency of emergency room visits for childhood asthma in Ottawa, Canada: the role of weather

NASA Astrophysics Data System (ADS)

Villeneuve, Paul J.; Leech, Judy; Bourque, Denis

2005-09-01

The aim of this study was to evaluate associations between meteorological conditions and the number of emergency department visits for asthma in a children's hospital in Ottawa, Canada. A case-crossover study design was used. Hospital emergency department visits for asthma between 1992 and 2000 were identified based on patients' presenting complaints. We obtained hourly measures for the following meteorological variables: wind speed, temperature, atmospheric pressure, relative humidity, and visibility. Particular emphasis was placed on exploring the association between asthma visits and fog, thunderstorms, snow, and liquid and freezing forms of precipitation. In total, there were 18,970 asthma visits among children between 2 and 15 years of age. The number of visits and weather characteristics were grouped into 6 h case and control intervals. The occurrence of fog or liquid precipitation was associated with an increased number of asthma visits, while snow was associated with a reduced number (P<0.05). Stratified analyses by season found no association in any of the four calendar intervals between the number of asthma visits and visibility, change in relative humidity and change in temperature. In contrast, summertime thunderstorm activity was associated with an odds ratio of 1.35 (95% CI=1.02-1.77) relative to summer periods with no activity. Models that incorporate calendar and meteorological data may help emergency departments to more efficiently allocate resources needed to treat children presenting with respiratory distress.

Sabkha Trafficability,

DTIC Science & Technology

1981-01-01

Meteorological Parameters at Meteorological Station 1, 31 May 1980 ........................ 68 $24 Relationship of Jubai. Port Datum to Tide Table Datum. .70 25...around which was a circular weight with two handles. Once assembled, the device was nositioned vertically at the point to be sampled and manually...limited use for sampling very fluid or unconsolidated sand or shell. In the former case, the upper few centimeters of cohesive sediment became embedded

[Anthrax in the canton of Zurich between 1878 and 2005].

PubMed

Brandes Ammann, A; Brandl, H

2007-07-01

Historical records reporting cases of animal anthrax in the canton of Zurich between 1878 and 2005 were analysed on the level of political communities regarding occurrence and number of cases, animals affected, and number of communities affected. Data were correlated with industrial activities (tanning, wool and horse hair processing) in a community and to the prevailing meteorological conditions. A total of 830 cases of animal anthrax has been recorded in 140 of 171 communities. Occurrence correlated with industrial activities in a community such as companies handling potentially contaminated materials (hides, fur, wool, hair, meat, or bone meal). The influence of wool processing companies (P = 0. 004) and tanneries (P = 0. 032) was significant whereas horse hair processing had no effect. However, a statistical relationship between the number of cases reported and meteorological data (rainfall, mean temperature) was not found.

Legionnaires' disease from a cooling tower in a community outbreak in Lidköping, Sweden- epidemiological, environmental and microbiological investigation supported by meteorological modelling.

PubMed

Ulleryd, Peter; Hugosson, Anna; Allestam, Görel; Bernander, Sverker; Claesson, Berndt E B; Eilertz, Ingrid; Hagaeus, Anne-Christine; Hjorth, Martin; Johansson, Agneta; de Jong, Birgitta; Lindqvist, Anna; Nolskog, Peter; Svensson, Nils

2012-11-21

An outbreak of Legionnaires' Disease took place in the Swedish town Lidköping on Lake Vänern in August 2004 and the number of pneumonia cases at the local hospital increased markedly. As soon as the first patients were diagnosed, health care providers were informed and an outbreak investigation was launched. Classical epidemiological investigation, diagnostic tests, environmental analyses, epidemiological typing and meteorological methods. Thirty-two cases were found. The median age was 62 years (range 36 - 88) and 22 (69%) were males. No common indoor exposure was found. Legionella pneumophila serogroup 1 was found at two industries, each with two cooling towers. In one cooling tower exceptionally high concentrations, 1.2 × 109 cfu/L, were found. Smaller amounts were also found in the other tower of the first industry and in one tower of the second plant. Sero- and genotyping of isolated L. pneumophila serogroup 1 from three patients and epidemiologically suspected environmental strains supported the cooling tower with the high concentration as the source. In all, two L. pneumophila strains were isolated from three culture confirmed cases and both these strains were detected in the cooling tower, but one strain in another cooling tower as well. Meteorological modelling demonstrated probable spread from the most suspected cooling tower towards the town centre and the precise location of four cases that were stray visitors to Lidköping. Classical epidemiological, environmental and microbiological investigation of an LD outbreak can be supported by meteorological modelling methods.The broad competence and cooperation capabilities in the investigation team from different authorities were of paramount importance in stopping this outbreak.

Legionnaires’ disease from a cooling tower in a community outbreak in Lidköping, Sweden- epidemiological, environmental and microbiological investigation supported by meteorological modelling

PubMed Central

2012-01-01

Background An outbreak of Legionnaires’ Disease took place in the Swedish town Lidköping on Lake Vänern in August 2004 and the number of pneumonia cases at the local hospital increased markedly. As soon as the first patients were diagnosed, health care providers were informed and an outbreak investigation was launched. Methods Classical epidemiological investigation, diagnostic tests, environmental analyses, epidemiological typing and meteorological methods. Results Thirty-two cases were found. The median age was 62 years (range 36 – 88) and 22 (69%) were males. No common indoor exposure was found. Legionella pneumophila serogroup 1 was found at two industries, each with two cooling towers. In one cooling tower exceptionally high concentrations, 1.2 × 109 cfu/L, were found. Smaller amounts were also found in the other tower of the first industry and in one tower of the second plant. Sero- and genotyping of isolated L. pneumophila serogroup 1 from three patients and epidemiologically suspected environmental strains supported the cooling tower with the high concentration as the source. In all, two L. pneumophila strains were isolated from three culture confirmed cases and both these strains were detected in the cooling tower, but one strain in another cooling tower as well. Meteorological modelling demonstrated probable spread from the most suspected cooling tower towards the town centre and the precise location of four cases that were stray visitors to Lidköping. Conclusions Classical epidemiological, environmental and microbiological investigation of an LD outbreak can be supported by meteorological modelling methods. The broad competence and cooperation capabilities in the investigation team from different authorities were of paramount importance in stopping this outbreak. PMID:23171054

Effects of temperature on flood forecasting: analysis of an operative case study in Alpine basins

NASA Astrophysics Data System (ADS)

Ceppi, A.; Ravazzani, G.; Salandin, A.; Rabuffetti, D.; Montani, A.; Borgonovo, E.; Mancini, M.

2013-04-01

In recent years the interest in the forecast and prevention of natural hazards related to hydro-meteorological events has increased the challenge for numerical weather modelling, in particular for limited area models, to improve the quantitative precipitation forecasts (QPF) for hydrological purposes. After the encouraging results obtained in the MAP D-PHASE Project, we decided to devote further analyses to show recent improvements in the operational use of hydro-meteorological chains, and above all to better investigate the key role played by temperature during snowy precipitation. In this study we present a reanalysis simulation of one meteorological event, which occurred in November 2008 in the Piedmont Region. The attention is focused on the key role of air temperature, which is a crucial feature in determining the partitioning of precipitation in solid and liquid phase, influencing the quantitative discharge forecast (QDF) into the Alpine region. This is linked to the basin ipsographic curve and therefore by the total contributing area related to the snow line of the event. In order to assess hydrological predictions affected by meteorological forcing, a sensitivity analysis of the model output was carried out to evaluate different simulation scenarios, considering the forecast effects which can radically modify the discharge forecast. Results show how in real-time systems hydrological forecasters have to consider also the temperature uncertainty in forecasts in order to better understand the snow dynamics and its effect on runoff during a meteorological warning with a crucial snow line over the basin. The hydrological ensemble forecasts are based on the 16 members of the meteorological ensemble system COSMO-LEPS (developed by ARPA-SIMC) based on the non-hydrostatic model COSMO, while the hydrological model used to generate the runoff simulations is the rainfall-runoff distributed FEST-WB model, developed at Politecnico di Milano.

A Meteorological Supersite for Aviation and Cold Weather Applications

NASA Astrophysics Data System (ADS)

Gultepe, Ismail; Agelin-Chaab, M.; Komar, J.; Elfstrom, G.; Boudala, F.; Zhou, B.

2018-05-01

The goal of this study is to better understand atmospheric boundary layer processes and parameters, and to evaluate physical processes for aviation applications using data from a supersite observing site. Various meteorological sensors, including a weather and environmental unmanned aerial vehicle (WE-UAV), and a fog and snow tower (FSOS) observations are part of the project. The PanAm University of Ontario Institute of Technology (UOIT) Meteorological Supersite (PUMS) observations are being collected from April 2015 to date. The FSOS tower gathers observations related to rain, snow, fog, and visibility, aerosols, solar radiation, and wind and turbulence, as well as surface and sky temperature. The FSOSs are located at three locations at about 450-800 m away from the PUMS supersite. The WE-UAV measurements representing aerosol, wind speed and direction, as well as temperature (T) and relative humidity (RH) are provided during clear weather conditions. Other measurements at the PUMS site include cloud backscattering profiles from CL51 ceilometer, MWR observations of liquid water content (LWC), T, and RH, and Microwave Rain Radar (MRR) reflectivity profile, as well as the present weather type, snow water depth, icing rate, 3D-ultrasonic wind and turbulence, and conventional meteorological observations from compact weather stations, e.g., WXTs. The results based on important weather event studies, representing fog, snow, rain, blowing snow, wind gust, planetary boundary layer (PBL) wind research for UAV, and icing conditions are given. The microphysical parameterizations and analysis processes for each event are provided, but the results should not be generalized for all weather events and be used cautiously. Results suggested that integrated observing systems based on data from a supersite as well as satellite sites can provide better information applicable to aviation meteorology, including PBL weather research, validation of numerical weather model predictions, and remote-sensing retrievals. Overall, the results from the five cases are provided and challenges related to observations applicable to aviation meteorology are discussed.

PREDICTING THE RELATIVE IMPACTS OF URBAN DEVELOPMENT POLICIES AND ON-ROAD VEHICLE TECHNOLOGIES ON AIR QUALITY IN THE UNITED STATES: MODELING AND ANALYSIS OF A CASE STUDY IN AUSTIN, TEXAS

EPA Science Inventory

Urban development results in changes to land use and land cover and, consequently, to biogenic and anthropogenic emissions, meteorological processes, and processes such as dry deposition that influence future predictions of air quality. This study examines the impacts of alter...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jagadeesh, A.

The meteorological stations at which the wind data is available are stationed mostly in cities and towns. At many an observatory the exposure conditions have tended to become progressively unsatisfactory on account of the disturbing effects of urbanisation. To know the effect of urbanisation on windspeeds, wind speed data at five observatories and the wind data available near the Airports is compared in this paper. The data has been taken from Indian Meteorological Department (1930-1960). The monthly wind speed in Km/hr and also the annual average for the meteorological observatory alongwith the nearest Airport are presented in the following tablemore » alongwith increase in percentage in each case.« less

Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds

NASA Astrophysics Data System (ADS)

Bogaard, Thom; Greco, Roberto

2018-01-01

Many shallow landslides and debris flows are precipitation initiated. Therefore, regional landslide hazard assessment is often based on empirically derived precipitation intensity-duration (ID) thresholds and landslide inventories. Generally, two features of precipitation events are plotted and labeled with (shallow) landslide occurrence or non-occurrence. Hereafter, a separation line or zone is drawn, mostly in logarithmic space. The practical background of ID is that often only meteorological information is available when analyzing (non-)occurrence of shallow landslides and, at the same time, it could be that precipitation information is a good proxy for both meteorological trigger and hydrological cause. Although applied in many case studies, this approach suffers from many false positives as well as limited physical process understanding. Some first steps towards a more hydrologically based approach have been proposed in the past, but these efforts received limited follow-up.Therefore, the objective of our paper is to (a) critically analyze the concept of precipitation ID thresholds for shallow landslides and debris flows from a hydro-meteorological point of view and (b) propose a trigger-cause conceptual framework for lumped regional hydro-meteorological hazard assessment based on published examples and associated discussion. We discuss the ID thresholds in relation to return periods of precipitation, soil physics, and slope and catchment water balance. With this paper, we aim to contribute to the development of a stronger conceptual model for regional landslide hazard assessment based on physical process understanding and empirical data.

Remote sensing of rain over the ocean

NASA Technical Reports Server (NTRS)

1978-01-01

Computer models of the microwave emission from the earth's atmosphere were used to study the problem of retrieving meteorological information from the SMMR instrument that will be flown on NIMBUS-G. Methods for retrieving rain rate, wind speed, cloud height, and ocean temperature are described for the case when the satellite is over the ocean.

Final Report for High Latitude Climate Modeling: ARM Takes Us Beyond Case Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russell, Lynn M; Lubin, Dan

2013-06-18

The main thrust of this project was to devise a method by which the majority of North Slope of Alaska (NSA) meteorological and radiometric data, collected on a daily basis, could be used to evaluate and improve global climate model (GCM) simulations and their parameterizations, particularly for cloud microphysics. Although the standard ARM Program sensors for a less complete suite of instruments for cloud and aerosol studies than the instruments on an intensive field program such as the 2008 Indirect and Semi-Direct Aerosol Campaign (ISDAC), the advantage they offer lies in the long time base and large volume of datamore » that covers a wide range of meteorological and climatological conditions. The challenge has been devising a method to interpret the NSA data in a practical way, so that a wide variety of meteorological conditions in all seasons can be examined with climate models. If successful, climate modelers would have a robust alternative to the usual “case study” approach (i.e., from intensive field programs only) for testing and evaluating their parameterizations’ performance. Understanding climate change on regional scales requires a broad scientific consideration of anthropogenic influences that goes beyond greenhouse gas emissions to also include aerosol-induced changes in cloud properties. For instance, it is now clear that on small scales, human-induced aerosol plumes can exert microclimatic radiative and hydrologic forcing that rivals that of greenhouse gas–forced warming. This project has made significant scientific progress by investigating what causes successive versions of climate models continue to exhibit errors in cloud amount, cloud microphysical and radiative properties, precipitation, and radiation balance, as compared with observations and, in particular, in Arctic regions. To find out what is going wrong, we have tested the models' cloud representation over the full range of meteorological conditions found in the Arctic using the ARM North Slope of Alaska (NSA) data.« less

Evaluation of quantitative precipitation forecasts by TIGGE ensembles for south China during the presummer rainy season

NASA Astrophysics Data System (ADS)

Huang, Ling; Luo, Yali

2017-08-01

Based on The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data set, this study evaluates the ability of global ensemble prediction systems (EPSs) from the European Centre for Medium-Range Weather Forecasts (ECMWF), U.S. National Centers for Environmental Prediction, Japan Meteorological Agency (JMA), Korean Meteorological Administration, and China Meteorological Administration (CMA) to predict presummer rainy season (April-June) precipitation in south China. Evaluation of 5 day forecasts in three seasons (2013-2015) demonstrates the higher skill of probability matching forecasts compared to simple ensemble mean forecasts and shows that the deterministic forecast is a close second. The EPSs overestimate light-to-heavy rainfall (0.1 to 30 mm/12 h) and underestimate heavier rainfall (>30 mm/12 h), with JMA being the worst. By analyzing the synoptic situations predicted by the identified more skillful (ECMWF) and less skillful (JMA and CMA) EPSs and the ensemble sensitivity for four representative cases of torrential rainfall, the transport of warm-moist air into south China by the low-level southwesterly flow, upstream of the torrential rainfall regions, is found to be a key synoptic factor that controls the quantitative precipitation forecast. The results also suggest that prediction of locally produced torrential rainfall is more challenging than prediction of more extensively distributed torrential rainfall. A slight improvement in the performance is obtained by shortening the forecast lead time from 30-36 h to 18-24 h to 6-12 h for the cases with large-scale forcing, but not for the locally produced cases.

Municipality Level Simulations of Dengue Fever Incidence in Puerto Rico Using Ground Based and Remotely Sensed Climate Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Morin, Cory

2015-01-01

Dengue fever (DF) is caused by a virus transmitted between humans and Aedes genus mosquitoes through blood feeding. In recent decades incidence of the disease has drastically increased in the tropical Americas, culminating with the Pan American outbreak in 2010 which resulted in 1.7 million reported cases. In Puerto Rico dengue is endemic, however, there is significant inter-annual, intraannual, and spatial variability in case loads. Variability in climate and the environment, herd immunity and virus genetics, and demographic characteristics may all contribute to differing patterns of transmission both spatially and temporally. Knowledge of climate influences on dengue incidence could facilitate development of early warning systems allowing public health workers to implement appropriate transmission intervention strategies. In this study, we simulate dengue incidence in several municipalities in Puerto Rico using population and meteorological data derived from ground based stations and remote sensing instruments. This data was used to drive a process based model of vector population development and virus transmission. Model parameter values for container composition, vector characteristics, and incubation period were chosen by employing a Monte Carlo approach. Multiple simulations were performed for each municipality and the results were compared with reported dengue cases. The best performing simulations were retained and their parameter values and meteorological input were compared between years and municipalities. Parameter values varied by municipality and year illustrating the complexity and sensitivity of the disease system. Local characteristics including the natural and built environment impact transmission dynamics and produce varying responses to meteorological conditions.

A new concept to study the effect of climate change on different flood types

NASA Astrophysics Data System (ADS)

Nissen, Katrin; Nied, Manuela; Pardowitz, Tobias; Ulbrich, Uwe; Merz, Bruno

2014-05-01

Flooding is triggered by the interaction of various processes. Especially important are the hydrological conditions prior to the event (e.g. soil saturation, snow cover) and the meteorological conditions during flood development (e.g. rainfall, temperature). Depending on these (pre-) conditions different flood types may develop such as long-rain floods, short-rain floods, flash floods, snowmelt floods and rain-on-snow floods. A new concept taking these factors into account is introduced and applied to flooding in the Elbe River basin. During the period September 1957 to August 2002, 82 flood events are identified and classified according to their flood type. The hydrological and meteorological conditions at each day during the analysis period are detemined. In case of the hydrological conditions, a soil moisture pattern classification is carried out. Soil moisture is simulated with a rainfall-runoff model driven by atmospheric observations. Days of similar soil moisture patterns are identified by a principle component analysis and a subsequent cluster analysis on the leading principal components. The meteorological conditions are identified by applying a cluster analysis to the geopotential height, temperature and humidity fields of the ERA40 reanalysis data set using the SANDRA cluster algorithm. We are able to identify specific pattern combinations of hydrological pre-conditions and meteorological conditions which favour different flood types. Based on these results it is possible to analyse the effect of climate change on different flood types. As an example we show first results obtained using an ensemble of climate scenario simulations of ECHAM5 MPIOM model, taking only the changes in the meteorological conditions into account. According to the simulations, the frequency of the meteorological patterns favouring long-rain, short-rain and flash floods will not change significantly under future climate conditions. A significant increase is, however, predicted for the amount of precipitation associated with many of the relevant meteorological patterns. The increase varies between 12 and 67% depending on the weather pattern.

Meteorological satellite products support for project COHMEX

NASA Technical Reports Server (NTRS)

Velden, Christopher S.; Goodman, Brian M.; Smith, William L.

1988-01-01

The first year effort focussed on real-time support and satellite data collection during the field phase of COHMEX. Work efforts following the field phase of COHMEX concentrated on post-processing of the real-time data sets, and generation of enhanced, research-quality satellite data sets for selected COHMEX core days. These satellite-derived data sets will augment the special COHMEX conventional data base with high horizontal and temporal resolution information. The data sets will be examined for their usefulness in delineating important elements in the meteorological environment leading to convective activity. In addition, a limited research effort was conducted using the Cooperative Institute for Meteorological Satellite Studies (CIMSS) 4-d data assimilation system in conjunction with evaluating VISSR Atmospheric Sounder (VAS) and His-resolution Interferometer Sounder (HIS) data. The need to address the characteristics of the data types, and the problems they introduce into 4-d assimilation procedures is evident. The HIS instrument was flown aboard an ER-2 aircraft on several occasions during COHMEX. One of the flights was chosen for further study. Processed VAS soundings and COHMEX radiosonde data were also collected for this day. The case study included an evaluation of the HIS and VAS data and an impact study of the data on the assimilation system analysis.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: a case study in endemic districts of Bhutan.

PubMed

Wangdi, Kinley; Singhasivanon, Pratap; Silawan, Tassanee; Lawpoolsri, Saranath; White, Nicholas J; Kaewkungwal, Jaranit

2010-09-03

Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan.

Describing the direct and indirect radiative effects of atmospheric aerosols over Europe by using coupled meteorology-chemistry simulations: a contribution from the AQMEII-Phase II exercise

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Balzarini, Alessandra; Baró, Rocío; Curci, Gabriele; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; Langer, Matthias; Pérez, Juan L.; Pirovano, Guido; San José, Roberto; Tuccella, Paolo; Werhahn, Johannes; Zabkar, Rahela

2014-05-01

The study of the response of the aerosol levels in the atmosphere to a changing climate and how this affects the radiative budget of the Earth (direct, semi-direct and indirect effects) is an essential topic to build confidence on climate science, since these feedbacks involve the largest uncertainties nowadays. Air quality-climate interactions (AQCI) are, therefore, a key, but uncertain contributor to the anthropogenic forcing that remains poorly understood. To build confidence in the AQCI studies, regional-scale integrated meteorology-atmospheric chemistry models (i.e., models with on-line chemistry) that include detailed treatment of aerosol life cycle and aerosol impacts on radiation (direct effects) and clouds (indirect effects) are in demand. In this context, the main objective of this contribution is the study and definition of the uncertainties in the climate-chemistry-aerosol-cloud-radiation system associated to the direct radiative forcing and the indirect effect caused by aerosols over Europe, using an ensemble of fully-coupled meteorology-chemistry model simulations with the WRF-Chem model run under the umbrella of AQMEII-Phase 2 international initiative. Simulations were performed for Europe for the entire year 2010. According to the common simulation strategy, the year was simulated as a sequence of 2-day time slices. For better comparability, the seven groups applied the same grid spacing of 23 km and shared common processing of initial and boundary conditions as well as anthropogenic and fire emissions. With exception of a simulation with different cloud microphysics, identical physics options were chosen while the chemistry options were varied. Two model set-ups will be considered here: one sub-ensemble of simulations not taking into account any aerosol feedbacks (the baseline case) and another sub-ensemble of simulations which differs from the former by the inclusion of aerosol-radiation feedback. The existing differences for meteorological variables (mainly 2-m temperature and precipitation) and air quality levels (mainly ozone an PM10) between both sub-ensembles of WRF-Chem simulations have been characterized. In the case of ozone and PM10, an increase in solar radiation and temperature has generally resulted in an enhanced photochemical activity and therefore a negative feedback (areas with low aerosol concentrations present more than 50 W m-2 higher global radiation for cloudy conditions). However, simulated feedback effects between aerosol concentrations and meteorological variables and on pollutant distributions strongly depend on the model configuration and the meteorological situation. These results will help providing improved science-based foundations to better assess the impacts of climate variability, support the development of effective climate change policies and optimize private decision-making.

A Study Of The Atmospheric Boundary Layer Using Radon And Air Pollutants As Tracers

NASA Astrophysics Data System (ADS)

Kataoka, Toshio; Yunoki, Eiji; Shimizu, Mitsuo; Mori, Tadashige; Tsukamoto, Osamu; Ohashi, Yukitaka, Sahashi, Ken; Maitani, Toshihiko; Miyashita, Koh'ichi; Iwata, Toru; Fujikawa, Yoko; Kudo, Akira; Shaw, Roger H.

Concentrations of radon 222Rn andair pollutants, meteorological parametersnear the surface and vertical profiles of meteorological elements were measured atUchio (Okayama City, Okayama Prefecture, Japan) 12 km north from the coast ofthe Inland Sea of Japan. In the nighttime, the 222Rn concentration increased in the case of weak winds, but did not increase as much in the case of moderate or strong winds, as had been expected. In the daytime, the 222Rn concentrationheld at a slightly higher than average level for the period from sunrise to about 1100 JST. It is considered that this phenomenon is due to a period of morning calm, that is, a transition period from land breeze to sea breeze.NO, which is sensitive to traffic volume,brought information concerning advection.Oxidant concentrations,which reflect the availability of sunlight,acted in the reverse manner to 222Rnconcentrations. Thus, a set of 222Rn and air pollutants could provide useful information regarding the local conditions of the atmospheric boundary layer.

Climate Predictors of the Spatial Distribution of Human Plague Cases in the West Nile Region of Uganda

PubMed Central

MacMillan, Katherine; Monaghan, Andrew J.; Apangu, Titus; Griffith, Kevin S.; Mead, Paul S.; Acayo, Sarah; Acidri, Rogers; Moore, Sean M.; Mpanga, Joseph Tendo; Enscore, Russel E.; Gage, Kenneth L.; Eisen, Rebecca J.

2012-01-01

East Africa has been identified as a region where vector-borne and zoonotic diseases are most likely to emerge or re-emerge and where morbidity and mortality from these diseases is significant. Understanding when and where humans are most likely to be exposed to vector-borne and zoonotic disease agents in this region can aid in targeting limited prevention and control resources. Often, spatial and temporal distributions of vectors and vector-borne disease agents are predictable based on climatic variables. However, because of coarse meteorological observation networks, appropriately scaled and accurate climate data are often lacking for Africa. Here, we use a recently developed 10-year gridded meteorological dataset from the Advanced Weather Research and Forecasting Model to identify climatic variables predictive of the spatial distribution of human plague cases in the West Nile region of Uganda. Our logistic regression model revealed that within high elevation sites (above 1,300 m), plague risk was positively associated with rainfall during the months of February, October, and November and negatively associated with rainfall during the month of June. These findings suggest that areas that receive increased but not continuous rainfall provide ecologically conducive conditions for Yersinia pestis transmission in this region. This study serves as a foundation for similar modeling efforts of other vector-borne and zoonotic disease in regions with sparse observational meteorologic networks. PMID:22403328

Technology and Meteorology. An Action Research Paper.

ERIC Educational Resources Information Center

Taggart, Raymond F.

Meteorology, the science of weather and weather conditions, has traditionally been taught via textbook and rote demonstration. This study was intended to determine to what degree utilizing technology in the study of meteorology improves students' attitudes towards science and to measure to what extent technology in meteorology increases…

Weather Features Associated with Aircraft Icing Conditions: A Case Study

PubMed Central

Fernández-González, Sergio; Sánchez, José Luis; Gascón, Estíbaliz; López, Laura; García-Ortega, Eduardo; Merino, Andrés

2014-01-01

In the context of aviation weather hazards, the study of aircraft icing is very important because of several accidents attributed to it over recent decades. On February 1, 2012, an unusual meteorological situation caused severe icing of a C-212-200, an aircraft used during winter 2011-2012 to study winter cloud systems in the Guadarrama Mountains of the central Iberian Peninsula. Observations in this case were from a MP-3000A microwave radiometric profiler, which acquired atmospheric temperature and humidity profiles continuously every 2.5 minutes. A Cloud Aerosol and Precipitation Spectrometer (CAPS) was also used to study cloud hydrometeors. Finally, ice nuclei concentration was measured in an isothermal cloud chamber, with the goal of calculating concentrations in the study area. Synoptic and mesoscale meteorological conditions were analysed using the Weather Research and Forecasting (WRF) model. It was demonstrated that topography influenced generation of a mesolow and gravity waves on the lee side of the orographic barrier, in the region where the aircraft experienced icing. Other factors such as moisture, wind direction, temperature, atmospheric stability, and wind shear were decisive in the appearance of icing. This study indicates that icing conditions may arise locally, even when the synoptic situation does not indicate any risk. PMID:24701152

Hydrologic Conditions Viewed by the Nimbus Meteorological Satellites

NASA Technical Reports Server (NTRS)

Rabchevsky, G. A.

1971-01-01

The unexploited value of the Nimbus meteorological sensor data relates to the satellites' ability for global, temporal, repetitive and uniform tonal and spatial coverage of the earth's surface. Examples are presented illustrating how synoptic views of large areas increase interpretive capability and enable focusing on large targets of interest. The effect of resolution of the Nimbus imaging systems on these observations is discussed, together with the assessment of the areal and temporal magnitude of changes observed by these systems. Two case studies are presented exemplifying the satellites' ability for repetitive observations enabling phenomena to be monitored under special conditions. One study deals with changes observed in the Antarctic ice conditions utilizing the Nimbus 2 and 3 television picture data. The other study deals with terrestrial changes in the Mississippi River Valley and the Niger River Valley (Africa), observed primarily in the 0.7 to 1.3 micron spectral band.

Analysis of atmospheric ozone measurements made from a B-747 airliner during March 1975

NASA Technical Reports Server (NTRS)

Holdeman, J. D.; Falconer, P. D.

1976-01-01

Measurements of atmospheric ozone in the upper troposphere and lower stratosphere made during March 1975 as part of the NASA Global Atmospheric Sampling Program are reported and analyzed. The interrelationships between the ozone mixing ratio and geographical and meteorological parameters are examined in several case studies. The ozone data correlate well with the difference between the flight altitude and the height of the tropopause, as obtained from National Meteorological Center gridded data. The distribution of ozone mixing ratios with latitude at an altitude of 11 + or - 0.5 km shows a poleward increase and large variability at latitudes greater than 30 deg N in agreement with published mean ozone levels from the North American ozone sonde network.

Pre-seismic anomalies in remotely sensed land surface temperature measurements: The case study of 2003 Boumerdes earthquake

NASA Astrophysics Data System (ADS)

Bellaoui, Mebrouk; Hassini, Abdelatif; Bouchouicha, Kada

2017-05-01

Detection of thermal anomaly prior to earthquake events has been widely confirmed by researchers over the past decade. One of the popular approaches for anomaly detection is the Robust Satellite Approach (RST). In this paper, we use this method on a collection of six years of MODIS satellite data, representing land surface temperature (LST) images to predict 21st May 2003 Boumerdes Algeria earthquake. The thermal anomalies results were compared with the ambient temperature variation measured in three meteorological stations of Algerian National Office of Meteorology (ONM) (DELLYS-AFIR, TIZI-OUZOU, and DAR-EL-BEIDA). The results confirm the importance of RST as an approach highly effective for monitoring the earthquakes.

Machine learning algorithms for meteorological event classification in the coastal area using in-situ data

NASA Astrophysics Data System (ADS)

Sokolov, Anton; Gengembre, Cyril; Dmitriev, Egor; Delbarre, Hervé

2017-04-01

The problem is considered of classification of local atmospheric meteorological events in the coastal area such as sea breezes, fogs and storms. The in-situ meteorological data as wind speed and direction, temperature, humidity and turbulence are used as predictors. Local atmospheric events of 2013-2014 were analysed manually to train classification algorithms in the coastal area of English Channel in Dunkirk (France). Then, ultrasonic anemometer data and LIDAR wind profiler data were used as predictors. A few algorithms were applied to determine meteorological events by local data such as a decision tree, the nearest neighbour classifier, a support vector machine. The comparison of classification algorithms was carried out, the most important predictors for each event type were determined. It was shown that in more than 80 percent of the cases machine learning algorithms detect the meteorological class correctly. We expect that this methodology could be applied also to classify events by climatological in-situ data or by modelling data. It allows estimating frequencies of each event in perspective of climate change.

Numerical simulation of terrain-induced mesoscale circulation in the Chiang Mai area, Thailand

NASA Astrophysics Data System (ADS)

Sathitkunarat, Surachai; Wongwises, Prungchan; Pan-Aram, Rudklao; Zhang, Meigen

2008-11-01

The regional atmospheric modeling system (RAMS) was applied to Chiang Mai province, a mountainous area in Thailand, to study terrain-induced mesoscale circulations. Eight cases in wet and dry seasons under different weather conditions were analyzed to show thermal and dynamic impacts on local circulations. This is the first study of RAMS in Thailand especially investigating the effect of mountainous area on the simulated meteorological data. Analysis of model results indicates that the model can reproduce major features of local circulation and diurnal variations in temperatures. For evaluating the model performance, model results were compared with observed wind speed, wind direction, and temperature monitored at a meteorological tower. Comparison shows that the modeled values are generally in good agreement with observations and that the model captured many of the observed features.

The changing sensitivity of power systems to meteorological drivers: a case study of Great Britain

NASA Astrophysics Data System (ADS)

Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

2018-05-01

The increasing use of intermittent renewable generation (such as wind) is increasing the exposure of national power systems to meteorological variability. This study identifies how the integration of wind power in one particular country (Great Britain, GB) is affecting the overall sensitivity of the power system to weather using three key metrics: total annual energy requirement, peak residual load (from sources other than wind) and wind power curtailment. The present-day level of wind power capacity (approximately 15 GW) is shown to have already changed the power system’s overall sensitivity to weather in terms of the total annual energy requirement, from a temperature- to a wind-dominated regime (which occurred with 6GW of installed wind power capacity). Peak residual load from sources other than wind also shows a similar shift. The associated changes in the synoptic- and large-scale meteorological drivers associated with each metric are identified and discussed. In a period where power systems are changing rapidly, it is therefore argued that past experience of the weather impacts on the GB power system may not be a good guide for the impact on the present or near-future power system.

PREDICTING CLINICALLY DIAGNOSED DYSENTERY INCIDENCE OBTAINED FROM MONTHLY CASE REPORTING BASED ON METEOROLOGICAL VARIABLES IN DALIAN, LIAONING PROVINCE, CHINA, 2005-2011 USING A DEVELOPED MODEL.

PubMed

An, Qingyu; Yao, Wei; Wu, Jun

2015-03-01

This study describes our development of a model to predict the incidence of clinically diagnosed dysentery in Dalian, Liaoning Province, China, using time series analysis. The model was developed using the seasonal autoregressive integrated moving average (SARIMA). Spearman correlation analysis was conducted to explore the relationship between meteorological variables and the incidence of clinically diagnosed dysentery. The meteorological variables which significantly correlated with the incidence of clinically diagnosed dysentery were then used as covariables in the model, which incorporated the monthly incidence of clinically diagnosed dysentery from 2005 to 2010 in Dalian. After model development, a simulation was conducted for the year 2011 and the results of this prediction were compared with the real observed values. The model performed best when the temperature data for the preceding month was used to predict clinically diagnosed dysentery during the following month. The developed model was effective and reliable in predicting the incidence of clinically diagnosed dysentery for most but not all months, and may be a useful tool for dysentery disease control and prevention, but further studies are needed to fine tune the model.

Association between lower air pressure and the onset of ischemic colitis: a case-control study.

PubMed

Kimura, Takefumi; Shinji, Akihiro; Tanaka, Naoki; Koinuma, Masayoshi; Yamaura, Maki; Nagaya, Tadanobu; Joshita, Satoru; Komatsu, Michiharu; Umemura, Takeji; Horiuchi, Akira; Wada, Shuichi; Tanaka, Eiji

2017-09-01

Ischemic colitis (IC) often affects the elderly. Proarteriosclerotic factors, such as hypertension and smoking, and cardiovascular disease are considered major contributors to IC. Although a possible link between certain cerebrocardiovascular disorders and meteorological phenomena has been reported, the relationship between IC onset and weather changes remains uninvestigated. This study examined whether specific meteorological factors were associated with the occurrence of IC. We retrospectively enrolled 303 patients who had been diagnosed with IC between January 2003 and June 2010 at Suwa Red Cross Hospital in Nagano Prefecture, Japan. The meteorological data of the days on which IC patients visited the hospital (IC+ days) were compared with those of the days on which IC patients did not (IC- days). Univariate analysis indicated that IC+ days had significantly lower air pressure (P<0.001), depressed air pressure from the previous day (P<0.001), and fewer daylight hours (P<0.001), as well as higher air temperature (P=0.017), air humidity (P=0.004), wind velocity (P<0.001), and rainfall (P=0.012) compared with IC- days. Multivariate logistic regression analysis of the meteorological data showed that air pressure (odds ratio: 0.935, P<0.001) and change in air pressure from the previous day (odds ratio: 0.934, P<0.001) were related to onset of IC. Lower air pressure and decrease in air pressure from the previous day are possible novel factors associated with the development of IC.

Summarising climate and air quality (ozone) data on self-organising maps: a Sydney case study.

PubMed

Jiang, Ningbo; Betts, Alan; Riley, Matt

2016-02-01

This paper explores the classification and visualisation utility of the self-organising map (SOM) method in the context of New South Wales (NSW), Australia, using gridded NCEP/NCAR geopotential height reanalysis for east Australia, together with multi-site meteorological and air quality data for Sydney from the NSW Office of Environment and Heritage Air Quality Monitoring Network. A twice-daily synoptic classification has been derived for east Australia for the period of 1958-2012. The classification has not only reproduced the typical synoptic patterns previously identified in the literature but also provided an opportunity to visualise the subtle, non-linear change in the eastward-migrating synoptic systems influencing NSW (including Sydney). The summarisation of long-term, multi-site air quality/meteorological data from the Sydney basin on the SOM plane has identified a set of typical air pollution/meteorological spatial patterns in the region. Importantly, the examination of these patterns in relation to synoptic weather types has provided important visual insights into how local and synoptic meteorological conditions interact with each other and affect the variability of air quality in tandem. The study illustrates that while synoptic circulation types are influential, the within-type variability in mesoscale flows plays a critical role in determining local ozone levels in Sydney. These results indicate that the SOM can be a useful tool for assessing the impact of weather and climatic conditions on air quality in the regional airshed. This study further promotes the use of the SOM method in environmental research.

Meteorological Data near Rabbit Ears Pass, Colorado, U.S.A., 1984-2008

USGS Publications Warehouse

Halm, Douglas R.; Beaver, Larry D.; Leavesley, George H.; Reddy, Michael M.

2009-01-01

In 1983, a snowmelt energy budget study was initiated by the U.S. Geological Survey on a small watershed near Rabbit Ears Pass, Colorado, to better understand snowmelt processes. The study included data collection from hydrological and meteorological instrumentation. Interest in long term, high-altitude meteorological sites has increased recently due to the increased awareness of global climate change. The meteorological data collected near Rabbit Ears Pass may aid researchers involved in global climate change studies. Meteorological data from 1984 to 2008 are presented.

Sudden temperature changes in the Sydney Basin: climatology and case studies during the Olympic months of September and October

NASA Astrophysics Data System (ADS)

Buckley, Bruce W.; Leslie, Lance M.

2000-03-01

The accurate prediction of sudden large changes in the maximum temperature from one day to the next remains one of the major challenges for operational forecasters. It is probably the meteorological parameter most commonly verified and used as a measure of the skill of a meteorological service and one that is immediately evident to the general public. Marked temperature changes over a short period of time have widespread social, economic, health and safety effects on the community. The first part of this paper describes a 40-year climatology for Sydney, Australia, of sudden temperature rises and falls, defined as maximum temperature changes of 5°C or more from one day to the next, for the months of September and October. The nature of the forecasting challenge during the period of the Olympic and Paralympic Games to be held in Sydney in the year 2000 will be described as a special application. The international importance of the accurate prediction of all types of significant weather phenomena during this period has been recognized by the World Meteorological Organisation's Commission for Atmospheric Science. The first World Weather Research Program forecast demonstration project is to be established in the Sydney Office of the Bureau of Meteorology over this period in order to test the ability of existing systems to predict such phenomena. The second part of this study investigates two case studies from the Olympic months in which there were both abrupt temperature rises and falls over a 4-day interval. Currently available high resolution numerical weather prediction systems are found to have significant skill several days ahead in predicting a large amount of the detail of these events, provided they are run at an appropriate resolution. The limitations of these systems are also discussed, with areas requiring further development being identified if the desired levels of accuracy of predictions are to be reliably delivered. Differences between the predictability of sudden temperature rises and sudden temperature falls are also explored.

On-line Meteorology-Chemistry/Aerosols Modelling and Integration for Risk Assessment: Case Studies

NASA Astrophysics Data System (ADS)

Bostanbekov, Kairat; Mahura, Alexander; Nuterman, Roman; Nurseitov, Daniyar; Zakarin, Edige; Baklanov, Alexander

2016-04-01

On regional level, and especially in areas with potential diverse sources of industrial pollutants, the risk assessment of impact on environment and population is critically important. During normal operations, the risk is minimal. However, during accidental situations, the risk is increased due to releases of harmful pollutants into different environments such as water, soil, and atmosphere where it is following processes of continuous transformation and transport. In this study, the Enviro-HIRLAM (Environment High Resolution Limited Area Model) was adapted and employed for assessment of scenarios with accidental and continuous emissions of sulphur dioxide (SO2) for selected case studies during January of 2010. The following scenarios were considered: (i) control reference run; (ii) accidental release (due to short-term 1 day fire at oil storage facility) occurred at city of Atyrau (Kazakhstan) near the northern part of the Caspian Sea; and (iii) doubling of original continuous emissions from three locations of metallurgical enterprises on the Kola Peninsula (Russia). The implemented aerosol microphysics module M7 uses 5 types - sulphates, sea salt, dust, black and organic carbon; as well as distributed in 7 size modes. Removal processes of aerosols include gravitational settling and wet deposition. As the Enviro-HIRLAM model is the on-line integrated model, both meteorological and chemical processes are simultaneously modelled at each time step. The modelled spatio-temporal variations for meteorological and chemical patterns are analyzed for both European and Kazakhstan regions domains. The results of evaluation of sulphur dioxide concentration and deposition on main populated cities, selected regions, countries are presented employing GIS tools. As outcome, the results of Enviro-HIRLAM modelling for accidental release near the Caspian Sea are integrated into the RANDOM (Risk Assessment of Nature Detriment due to Oil spill Migration) system.

Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal.

PubMed

Figueiredo, M L; Monteiro, A; Lopes, M; Ferreira, J; Borrego, C

2013-07-01

Despite the increasing concern given to air quality in urban and industrial areas in recent years, particular emphasis on regulation, control, and reduction of air pollutant emissions is still necessary to fully characterize the chain emissions-air quality-exposure-dose-health effects, for specific sources. The Estarreja region was selected as a case study because it has one of the largest chemical industrial complexes in Portugal that has been recently expanded, together with a growing urban area with an interesting location in the Portuguese coastland and crossed by important road traffic and rail national networks. This work presents the first air quality assessment for the region concerning pollutant emissions and meteorological and air quality monitoring data analysis, over the period 2000-2009. This assessment also includes a detailed investigation and characterization of past air pollution episodes for the most problematic pollutants: ozone and PM10. The contribution of different emission sources and meteorological conditions to these episodes is investigated. The stagnant meteorological conditions associated with local emissions, namely industrial activity and road traffic, are the major contributors to the air quality degradation over the study region. A set of measures to improve air quality--regarding ozone and PM10 levels--is proposed as an air quality management strategy for the study region.

Assessing the impact of humidex on HFMD in Guangdong Province and its variability across social-economic status and age groups

NASA Astrophysics Data System (ADS)

Zhang, Wangjian; Du, Zhicheng; Zhang, Dingmei; Yu, Shicheng; Huang, Yong; Hao, Yuantao

2016-01-01

Humidex is a meteorological index that combines the impacts of temperature and humidity, and is directly comparable with dry temperature in degrees Celsius. However, to date, no research has focused on the effect of humidex on hand, foot and mouth disease (HFMD). The current study was designed to address this research need. Case-based HFMD surveillance data and daily meteorological data collected between 2010 and 2012 was obtained from the China CDC and the National Meteorological Information Center, respectively. Distributed lag nonlinear models were applied to assess the impact of humidex on HFMD among children under 15 years oldin Guangdong, and its variability across social-economic status and age groups. We found that relative risk (RR) largely increased with humidex. Lag-specific and cumulative humidex-RR curves for children from the Pearl-River Delta Region as well as older children were more likely to show two-peak distribution patterns. One RR peak occurred at a humidex of between 15 and 20, and the other occurred between 30 and 35. This study provides a comprehensive picture of the impact of humidex on HFMD incidence in Guangdong Province. Results from the present study should be important in the development of area-and-age-targeted control programs.

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula.

PubMed

Hernández-Ceballos, M A; Skjøth, C A; García-Mozo, H; Bolívar, J P; Galán, C

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

NASA Technical Reports Server (NTRS)

Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David

2011-01-01

This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations

Improvement in the accuracy of back trajectories using WRF to identify pollen sources in southern Iberian Peninsula

NASA Astrophysics Data System (ADS)

Hernández-Ceballos, M. A.; Skjøth, C. A.; García-Mozo, H.; Bolívar, J. P.; Galán, C.

2014-12-01

Airborne pollen transport at micro-, meso-gamma and meso-beta scales must be studied by atmospheric models, having special relevance in complex terrain. In these cases, the accuracy of these models is mainly determined by the spatial resolution of the underlying meteorological dataset. This work examines how meteorological datasets determine the results obtained from atmospheric transport models used to describe pollen transport in the atmosphere. We investigate the effect of the spatial resolution when computing backward trajectories with the HYSPLIT model. We have used meteorological datasets from the WRF model with 27, 9 and 3 km resolutions and from the GDAS files with 1 ° resolution. This work allows characterizing atmospheric transport of Olea pollen in a region with complex flows. The results show that the complex terrain affects the trajectories and this effect varies with the different meteorological datasets. Overall, the change from GDAS to WRF-ARW inputs improves the analyses with the HYSPLIT model, thereby increasing the understanding the pollen episode. The results indicate that a spatial resolution of at least 9 km is needed to simulate atmospheric flows that are considerable affected by the relief of the landscape. The results suggest that the appropriate meteorological files should be considered when atmospheric models are used to characterize the atmospheric transport of pollen on micro-, meso-gamma and meso-beta scales. Furthermore, at these scales, the results are believed to be generally applicable for related areas such as the description of atmospheric transport of radionuclides or in the definition of nuclear-radioactivity emergency preparedness.

Meteorology drives ambient air quality in a valley: a case of Sukinda chromite mine, one among the ten most polluted areas in the world.

PubMed

Mishra, Soumya Ranjan; Pradhan, Rudra Pratap; Prusty, B Anjan Kumar; Sahu, Sanjat Kumar

2016-07-01

The ambient air quality (AAQ) assessment was undertaken in Sukinda Valley, the chromite hub of India. The possible correlations of meteorological variables with different air quality parameters (PM10, PM2.5, SO2, NO2 and CO) were examined. Being the fourth most polluted area in the globe, Sukinda Valley has always been under attention of researchers, for hexavalent chromium contamination of water. The monitoring was carried out from December 2013 through May 2014 at six strategic locations in the residential and commercial areas around the mining cluster of Sukinda Valley considering the guidelines of Central Pollution Control Board (CPCB). In addition, meteorological parameters viz., temperature, relative humidity, wind speed, wind direction and rainfall, were also monitored. The air quality data were subjected to a general linear model (GLM) coupled with one-way analysis of variance (ANOVA) test for testing the significant difference in the concentration of various parameters among seasons and stations. Further, a two-tailed Pearson's correlation test helped in understanding the influence of meteorological parameters on dispersion of pollutants in the area. All the monitored air quality parameters varied significantly among the monitoring stations suggesting (i) the distance of sampling location to the mine site and other allied activities, (ii) landscape features and topography and (iii) meteorological parameters to be the forcing functions. The area was highly polluted with particulate matters, and in most of the cases, the PM level exceeded the National Ambient Air Quality Standards (NAAQS). The meteorological parameters seemed to play a major role in the dispersion of pollutants around the mine clusters. The role of wind direction, wind speed and temperature was apparent in dispersion of the particulate matters from their source of generation to the surrounding residential and commercial areas of the mine.

Evaluation of a Mesoscale Atmospheric Dispersion Modeling System with Observations from the 1980 Great Plains Mesoscale Tracer Field Experiment. Part I: Datasets and Meteorological Simulations.

NASA Astrophysics Data System (ADS)

Moran, Michael D.; Pielke, Roger A.

1996-03-01

The Colorado State University mesoscale atmospheric dispersion (MAD) numerical modeling system, which consists of a prognostic mesoscale meteorological model coupled to a mesoscale Lagrangian particle dispersion model, has been used to simulate the transport and diffusion of a perfluorocarbon tracer-gas cloud for one afternoon surface release during the July 1980 Great Plains mesoscale tracer field experiment. Ground-level concentration (GLC) measurements taken along arcs of samplers 100 and 600 km downwind of the release site at Norman, Oklahoma, up to three days after the tracer release were available for comparison. Quantitative measures of a number of significant dispersion characteristics obtained from analysis of the observed tracer cloud's moving GLC `footprint' have been used to evaluate the modeling system's skill in simulating this MAD case.MAD is more dependent upon the spatial and temporal structure of the transport wind field than is short-range atmospheric dispersion. For the Great Plains mesoscale tracer experiment, the observations suggest that the Great Plains nocturnal low-level jet played an important role in transporting and deforming the tracer cloud. A suite of ten two- and three-dimensional numerical meteorological experiments was devised to investigate the relative contributions of topography, other surface inhomogeneities, atmospheric baroclinicity, synoptic-scale flow evolution, and meteorological model initialization time to the structure and evolution of the low-level mesoscale flow field and thus to MAD. Results from the ten mesoscale meteorological simulations are compared in this part of the paper. The predicted wind fields display significant differences, which give rise in turn to significant differences in predicted low-level transport. The presence of an oscillatory ageostrophic component in the observed synoptic low-level winds for this case is shown to complicate initialization of the meteorological model considerably and is the likely cause of directional errors in the predicted mean tracer transport. A companion paper describes the results from the associated dispersion simulations.

HAND-FOOT-AND-MOUTH DISEASE EPIDEMIOLOGICAL STATUS AND RELATIONSHIP WITH METEOROLOGICAL VARIABLES IN GUANGZHOU, SOUTHERN CHINA, 2008-2012

PubMed Central

Li, Tiegang; Yang, Zhicong; Liu, Xiangyi; Kang, Yan; Wang, Ming

2014-01-01

Hand-foot-and-mouth disease (HFMD) is becoming one of the extremely common airborne and contact transmission diseases in Guangzhou, southern China, leading public health authorities to be concerned about its increased incidence. In this study, it was used an ecological study plus the negative binomial regression to identify the epidemic status of HFMD and its relationship with meteorological variables. During 2008-2012, a total of 173,524 HFMD confirmed cases were reported, 12 cases of death, yielding a fatality rate of 0.69 per 10,000. The annual incidence rates from 2008 to 2012 were 60.56, 132.44, 311.40, 402.76, and 468.59 (per 100,000), respectively, showing a rapid increasing trend. Each 1 °C rise in temperature corresponded to an increase of 9.47% (95% CI 9.36% to 9.58%) in the weekly number of HFMD cases, while a one hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 7.53% (95% CI -7.60% to -7.45%). Similarly, each one percent rise in relative humidity corresponded to an increase of 1.48% or 3.3%, and a one meter per hour rise in wind speed corresponded to an increase of 2.18% or 4.57%, in the weekly number of HFMD cases, depending on the variables considered in the model. These findings revealed that epidemic status of HFMD in Guangzhou is characterized by high morbidity but low fatality. Weather factors had a significant influence on the incidence of HFMD. PMID:25351550

Hydro-meteorological functioning of the Eastern Andean Tropical Montane Cloud Forests: Insight from a paired catchment study in the Orinoco river basin highlands

NASA Astrophysics Data System (ADS)

Ramirez, Beatriz; Teuling, Adriaan J.; Ganzeveld, Laurens; Leemans, Rik

2016-04-01

Tropical forests regulate large scale precipitation patterns and catchment-scale streamflow, while tropical mountains influence runoff by orographic effects and snowmelt. Along tropical elevation gradients, these climate/ecosystem/hydrological interactions are specific and heterogeneous. These interactions are poorly understood and represented in hydro-meteorological monitoring networks and regional or global earth system models. A typical case are the South American Tropical Montane Cloud Forests (TMCF), whose water balance is strongly driven by fog persistence. This also depends on local and up wind temperature and moisture, and changes in this balance alter the impacts of changes in land use and climate on hydrology. These TMCFs were until 2010 only investigated up to 350km from the coast. Continental TMCFs are largely ignored. This gap is covered by our study area, which is part of the Orinoco river basin highlands and located on the northern Eastern Andes at an altitudinal range of 1550 to 2300m a.s.l. The upwind part of our study area is dominated by lowland savannahs that are flooded seasonally. Because meteorological stations are absent in our study area, we first describe the spatial and seasonal meteorological variability and analyse the corresponding catchment hydrology. Our hydro-meteorological data set is collected at three gauged neighbouring catchments with contrasting TMCF/grassland cover from June 2013 to May 2014 and includes hourly solar radiation, temperature, relative humidity, wind speed, precipitation, soil moisture and runoff measurements. We compare our results with recent TCMF studies in the eastern Andean highlands in the Amazon basin. The studied elevational range always shows wetter conditions at higher elevations. This indicates a positive relation between elevation and fog or rainfall persistence. Lower elevations are more seasonally variable. Soil moisture data indicate that TMCFs do not use persistently more water than grasslands. Runoff data from our three catchments reflect the interaction between ecosystems and elevation. The less-forested catchment at lower elevations has a more seasonally variable runoff and present the lowest base flows during the dry season. In this season, soil water storage and the wetter conditions at higher elevations are crucial to sustain their base flow. The hydro-meteorological patterns of our study area are similar to those at the eastern Andean TMCF sites, but differences in the elevation of fog and rainfall persistence suggest that specific upwind ecosystem conditions and distance to the coast are important to explain and understand regional seasonal differences.

Forecasting rain events - Meteorological models or collective intelligence?

NASA Astrophysics Data System (ADS)

Arazy, Ofer; Halfon, Noam; Malkinson, Dan

2015-04-01

Collective intelligence is shared (or group) intelligence that emerges from the collective efforts of many individuals. Collective intelligence is the aggregate of individual contributions: from simple collective decision making to more sophisticated aggregations such as in crowdsourcing and peer-production systems. In particular, collective intelligence could be used in making predictions about future events, for example by using prediction markets to forecast election results, stock prices, or the outcomes of sport events. To date, there is little research regarding the use of collective intelligence for prediction of weather forecasting. The objective of this study is to investigate the extent to which collective intelligence could be utilized to accurately predict weather events, and in particular rainfall. Our analyses employ metrics of group intelligence, as well as compare the accuracy of groups' predictions against the predictions of the standard model used by the National Meteorological Services. We report on preliminary results from a study conducted over the 2013-2014 and 2014-2015 winters. We have built a web site that allows people to make predictions on precipitation levels on certain locations. During each competition participants were allowed to enter their precipitation forecasts (i.e. 'bets') at three locations and these locations changed between competitions. A precipitation competition was defined as a 48-96 hour period (depending on the expected weather conditions), bets were open 24-48 hours prior to the competition, and during betting period participants were allowed to change their bets with no limitation. In order to explore the effect of transparency, betting mechanisms varied across study's sites: full transparency (participants able to see each other's bets); partial transparency (participants see the group's average bet); and no transparency (no information of others' bets is made available). Several interesting findings emerged from this study. First, we found evidence for the emergence of collective intelligence, as the group's mean prediction was superior to individuals' predictions (using the metrics of Collective Intelligence Quality and Win Ratio). Second, we found that overall the group's collective intelligence was not very different from the accuracy of the meteorological model (ECMWF): in 6 out of the 12 competition the results were almost indistinguishable (error differences of less than 2 mm); in 4 cases the model clearly outperformed the group; and in 2 cases the group outperformed the model. Third, the design of the bidding mechanism - namely transparency - seems to affect collective intelligence. Fourth, an analysis of individuals' predictions suggests that local knowledge (measured by the distance between home address and the site of competition) and the level of meteorological knowledge (assessed by a short quiz) were not correlated with prediction accuracy. Although, the findings reported here present only preliminary results from a long-term project and while we acknowledge that it is not possible to draw statistically significant conclusions from a study of 12 cases, our findings do reveal some important insights. Our results inform research on collective intelligence and meteorology, as well as have implications for practice (e.g. possibly incorporating collective intelligence into weather forecasting models).

Space-time epidemiology and effect of meteorological parameters on influenza-like illness in Phitsanulok, a northern province in Thailand.

PubMed

Nimbalkar, Prakash Madhav; Tripathi, Nitin Kumar

2016-11-21

Influenza-like illness (ILI) is an acute respiratory disease that remains a public health concern for its ability to circulate globally affecting any age group and gender causing serious illness with mortality risk. Comprehensive assessment of the spatio-temporal dynamics of ILI is a prerequisite for effective risk assessment and application of control measures. Though meteorological parameters, such as rainfall, average relative humidity and temperature, influence ILI and represent crucial information for control of this disease, the relation between the disease and these variables is not clearly understood in tropical climates. The aim of this study was to analyse the epidemiology of ILI cases using integrated methods (space-time analysis, spatial autocorrelation and other correlation statistics). After 2009s H1N1 influenza pandemic, Phitsanulok Province in northern Thailand was strongly affected by ILI for many years. This study is based on ILI cases in villages in this province from 2005 to 2012. We used highly precise weekly incidence records covering eight years, which allowed accurate estimation of the ILI outbreak. Comprehensive methodology was developed to analyse the global and local patterns of the spread of the disease. Significant space-time clusters were detected over the study region during eight different periods. ILI cases showed seasonal clustered patterns with a peak in 2010 (P>0.05-9.999 iterations). Local indicators of spatial association identified hotspots for each year. Statistically, the weather pattern showed a clear influence on ILI cases and it strongly correlated with humidity at a lag of 1 month, while temperature had a weaker correlation.

Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010

NASA Astrophysics Data System (ADS)

Jeon, Wonbae; Choi, Yunsoo; Roy, Anirban; Pan, Shuai; Price, Daniel; Hwang, Mi-Kyoung; Kim, Kyu Rang; Oh, Inbo

2018-02-01

Oak pollen concentrations over the Houston-Galveston-Brazoria (HGB) area in southeastern Texas were modeled and evaluated against in-situ data. We modified the Community Multi-scale Air Quality (CMAQ) model to include oak pollen emission, dispersion, and deposition. The Oak Pollen Emission Model (OPEM) calculated gridded oak pollen emissions, which are based on a parameterized equation considering a plant-specific factor ( C e ), surface characteristics, and meteorology. The simulation period was chosen to be February 21 to April 30 in the spring of 2010, when the observed monthly mean oak pollen concentrations were the highest in six years (2009-2014). The results indicated C e and meteorology played an important role in the calculation of oak pollen emissions. While C e was critical in determining the magnitude of oak pollen emissions, meteorology determined their variability. In particular, the contribution of the meteorology to the variation in oak pollen emissions increased with the oak pollen emission rate. The evaluation results using in-situ surface data revealed that the model underestimated pollen concentrations and was unable to accurately reproduce the peak pollen episodes. The model error was likely due to uncertainty in climatology-based C e used for the estimation of oak pollen emissions and inaccuracy in the wind fields from the Weather Research and Forecast (WRF) model.

[Study on influence of floods on bacillary dysentery incidence in Liaoning province, 2004 -2010].

PubMed

Xu, X; Liu, Z D; Han, D B; Xu, Y Q; Jiang, B F

2016-05-01

To understand the influence of floods on bacillary dysentery in Liaoning province. The monthly surveillance data of bacillary dysentery, floods, meteorological and demographic data in Liaoning from 2004 to 2010 were collected. Panel Poisson regression analysis was conducted to evaluate the influence of floods on the incidence of bacillary dysentery in Liaoning. The mean monthly morbidity of bacillary dysentery was 2.17 per 100 000 during the study period, the bacillary dysentery cases mainly occurred in during July-September. Spearman correlation analysis showed that no lagged effect was detected in the influence of floods on the incidence of bacillary dysentery. After adjusting the influence of meteorological factors, panel data analysis showed that the influence of floods on the incidence of bacillary dysentery existed and the incidence rate ratio was 1.439 4(95%CI: 1.408 1-1.471 4). Floods could significantly increase the risk of bacillary dysentery for population in Liaoning.

Changes in daily pollen concentration based on meteorological data and days after seasonal initiation - a case study for Japanese hop

NASA Astrophysics Data System (ADS)

Choe, H.; Kim, K. R.; Kim, M.; Han, M. J.; Cho, C.; Choi, B. C.

2014-12-01

Pollinosis causes various allergy symptoms such as seasonal rhinitis, asthma, and conjunctivitis (Min, 1991). Japanese hop (Humulus japonicus) is a major allergen in southern Gyonggi-do during the fall seasons (Park, 1998). So that it is needed to forecast the concentration of its pollens.For the germination of Japanese hop, a period of low temperature (<5C) followed by warm (~20C) and humid conditions is needed (Growing and Protecting New Zealand(2010)). The daily concentration of the pollens increases rapidly then decreases a few days afterward. In this study, the changes in daily pollen concentration were analyzed to yield a prediction model.As a result, a regression model was produced to forecast daily pollen concentration. It can be integrated into the daily pollinosis warning system of the Korea Meteorological Administration (KMA) and provide more accurate daily risk information.

Chemical Modeling for Studies of GeoTRACE Capabilities

NASA Technical Reports Server (NTRS)

2005-01-01

Geostationary measurements of tropospheric pollutants with high spatial and temporal resolution will revolutionize the understanding and predictions of the chemically linked global pollutants aerosols and ozone. However, the capabilities of proposed geostationary instruments, particularly GeoTRACE, have not been thoroughly studied with model simulations. Such model simulations are important to answer the questions and allay the concerns that have been expressed in the atmospheric sciences community about the feasibility of such measurements. We proposed a suite of chemical transport model simulations using the EPA Models 3 chemical transport model, which obtains its meteorology from the MM-5 mesoscale model. The model output consists of gridded abundances of chemical pollutants and meteorological parameters every 30-60 minutes for cases that have occurred in the Eastern United States. This output was intended to be used to test the GeoTRACE capability to retrieve the tropospheric columns of these pollutants.

Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China.

PubMed

Zhou, Shui S; Huang, Fang; Wang, Jian J; Zhang, Shao S; Su, Yun P; Tang, Lin H

2010-11-24

Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas. The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence. The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(OR = 1.6, 95%CI (1.042, 2.463), P < 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(P < 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (T(mean)), the average temperature of last two months(T(mean₀₁)) and the average rainfall of current month (R(mean)) and the regression equation was Y = -2.085 + 0.839I₁ + 0.998T(mean₀) - 0.86T(mean₀₁) + 0.16R(mean₀). All the collected mosquitoes were Anopheles sinensis. The vectorial capacity and the basic reproductive rate of An. sinensis in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively. The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of An. sinensis leaded to malaria re-emergence in these areas.

Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China

PubMed Central

2010-01-01

Background Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas. Methods The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence. Results The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(OR = 1.6, 95%CI (1.042, 2.463), P < 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(P < 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (Tmean), the average temperature of last two months(Tmean01) and the average rainfall of current month (Rmean) and the regression equation was Y = -2.085 + 0.839I1 + 0.998Tmean0 - 0.86Tmean01 + 0.16Rmean0. All the collected mosquitoes were Anopheles sinensis. The vectorial capacity and the basic reproductive rate of An. sinensis in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively. Conclusion The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of An. sinensis leaded to malaria re-emergence in these areas. PMID:21092326

Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China

NASA Astrophysics Data System (ADS)

Leung, Danny M.; Tai, Amos P. K.; Mickley, Loretta J.; Moch, Jonathan M.; van Donkelaar, Aaron; Shen, Lu; Martin, Randall V.

2018-05-01

In his study, we use a combination of multivariate statistical methods to understand the relationships of PM2.5 with local meteorology and synoptic weather patterns in different regions of China across various timescales. Using June 2014 to May 2017 daily total PM2.5 observations from ˜ 1500 monitors, all deseasonalized and detrended to focus on synoptic-scale variations, we find strong correlations of daily PM2.5 with all selected meteorological variables (e.g., positive correlation with temperature but negative correlation with sea-level pressure throughout China; positive and negative correlation with relative humidity in northern and southern China, respectively). The spatial patterns suggest that the apparent correlations with individual meteorological variables may arise from common association with synoptic systems. Based on a principal component analysis of 1998-2017 meteorological data to diagnose distinct meteorological modes that dominate synoptic weather in four major regions of China, we find strong correlations of PM2.5 with several synoptic modes that explain 10 to 40 % of daily PM2.5 variability. These modes include monsoonal flows and cold frontal passages in northern and central China associated with the Siberian High, onshore flows in eastern China, and frontal rainstorms in southern China. Using the Beijing-Tianjin-Hebei (BTH) region as a case study, we further find strong interannual correlations of regionally averaged satellite-derived annual mean PM2.5 with annual mean relative humidity (RH; positive) and springtime fluctuation frequency of the Siberian High (negative). We apply the resulting PM2.5-to-climate sensitivities to the Intergovernmental Panel on Climate Change (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections to predict future PM2.5 by the 2050s due to climate change, and find a modest decrease of ˜ 0.5 µg m-3 in annual mean PM2.5 in the BTH region due to more frequent cold frontal ventilation under the RCP8.5 future, representing a small climate benefit, but the RH-induced PM2.5 change is inconclusive due to the large inter-model differences in RH projections.

Temporal downscaling of crop coefficients for winter wheat in the North China Plain: A case study at the Gucheng ecological-meteorological experimental station

USDA-ARS?s Scientific Manuscript database

The crop coefficient (Kc) method is widely used for operational estimation of actual evapotranspiration (ETa) and crop water requirements. The standard method for obtaining Kc is via a lookup table from FAO-56 (Food and Agriculture Organization of the United Nations Irrigation and Drainage Paper No....

Space Shuttle interactive meteorological data system study

NASA Technical Reports Server (NTRS)

Young, J. T.; Fox, R. J.; Benson, J. M.; Rueden, J. P.; Oehlkers, R. A.

1985-01-01

Although focused toward the operational meteorological support review and definition of an operational meteorological interactive data display systems (MIDDS) requirements for the Space Meteorology Support Group at NASA/Johnson Space Center, the total operational meteorological support requirements and a systems concept for the MIDDS network integration of NASA and Air Force elements to support the National Space Transportation System are also addressed.

Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: A case study in endemic districts of Bhutan

PubMed Central

2010-01-01

Background Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. Methods This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. Results It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009 and 67 to 149 cases in 2010, where population in 2009 was 285,375 and the expected population of 2010 to be 289,085. The ARIMAX model of monthly cases and climatic factors showed considerable variations among the different districts. In general, the mean maximum temperature lagged at one month was a strong positive predictor of an increased malaria cases for four districts. The monthly number of cases of the previous month was also a significant predictor in one district, whereas no variable could predict malaria cases for two districts. Conclusions The ARIMA models of time-series analysis were useful in forecasting the number of cases in the endemic areas of Bhutan. There was no consistency in the predictors of malaria cases when using ARIMAX model with selected lag times and climatic predictors. The ARIMA forecasting models could be employed for planning and managing malaria prevention and control programme in Bhutan. PMID:20813066

Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

NASA Astrophysics Data System (ADS)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

2017-11-01

Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias-correction method should be further investigated to remedy this weakness and take more advantage of the ensemble forecasts produced by the climate model. Overall, in this study, bias-corrected ensemble meteorological forecasts appear to be an interesting source of information for hydrological forecasting for lead times up to 1 month. They could also complement ESP for longer lead times.

Association of monthly frequencies of diverse diseases in the calls to the public emergency service of the city of Buenos Aires during 1999-2004 with meteorological variables and seasons.

PubMed

Alexander, P

2013-01-01

This work aims to study associations between monthly averages of meteorological variables and monthly frequencies of diverse diseases in the calls to the public ambulance emergency service of the city of Buenos Aires during the years 1999-2004. Throughout this time period no changes were made in the classification codes of the illnesses. Heart disease, arrhythmia, heart failure, cardiopulmonary arrest, angina pectoris, psychiatric diseases, stroke, transient ischemic attack, syncope and the total number of calls were analyzed against 11 weather variables and the four seasons. All illnesses exhibited some seasonal behavior, except cardiorespiratory arrest and angina pectoris. The largest frequencies of illnesses that exhibited some association with the meteorological variables used to occur in winter, except the psychiatric cases. Heart failure, stroke, psychiatric diseases and the total number of calls showed significant correlations with the 11 meteorological variables considered, and the largest indices (absolute values above 0.6) were found for the former two pathologies. On the other side, cardiorespiratory arrest and angina pectoris revealed no significant correlations and nearly null indices. Variables associated with temperature were the meteorological proxies with the largest correlations against diseases. Pressure and humidity mostly exhibited positive correlations, which is the opposite of variables related to temperature. Contrary to all other diseases, psychiatric pathologies showed a clear predominance of positive correlations. Finally, the association degree of the medical dataset with recurrent patterns was further evaluated through Fourier analysis, to assess the presence of statistically significant behavior. In the Northern Hemisphere high morbidity and mortality rates in December are usually assigned to diverse factors in relation to the holidays, but such an effect is not observed in the present analysis. There seems to be no clearly preferred meteorological proxy among the different types of temperatures used. It is shown that the amount of occurrences depends mainly on season rather on its strength quantified by temperature.

Spatial interpolation of GPS PWV and meteorological variables over the west coast of Peninsular Malaysia during 2013 Klang Valley Flash Flood

NASA Astrophysics Data System (ADS)

Suparta, Wayan; Rahman, Rosnani

2016-02-01

Global Positioning System (GPS) receivers are widely installed throughout the Peninsular Malaysia, but the implementation for monitoring weather hazard system such as flash flood is still not optimal. To increase the benefit for meteorological applications, the GPS system should be installed in collocation with meteorological sensors so the precipitable water vapor (PWV) can be measured. The distribution of PWV is a key element to the Earth's climate for quantitative precipitation improvement as well as flash flood forecasts. The accuracy of this parameter depends on a large extent on the number of GPS receiver installations and meteorological sensors in the targeted area. Due to cost constraints, a spatial interpolation method is proposed to address these issues. In this paper, we investigated spatial distribution of GPS PWV and meteorological variables (surface temperature, relative humidity, and rainfall) by using thin plate spline (tps) and ordinary kriging (Krig) interpolation techniques over the Klang Valley in Peninsular Malaysia (longitude: 99.5°-102.5°E and latitude: 2.0°-6.5°N). Three flash flood cases in September, October, and December 2013 were studied. The analysis was performed using mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) to determine the accuracy and reliability of the interpolation techniques. Results at different phases (pre, onset, and post) that were evaluated showed that tps interpolation technique is more accurate, reliable, and highly correlated in estimating GPS PWV and relative humidity, whereas Krig is more reliable for predicting temperature and rainfall during pre-flash flood events. During the onset of flash flood events, both methods showed good interpolation in estimating all meteorological parameters with high accuracy and reliability. The finding suggests that the proposed method of spatial interpolation techniques are capable of handling limited data sources with high accuracy, which in turn can be used to predict future floods.

Association of monthly frequencies of diverse diseases in the calls to the public emergency service of the city of Buenos Aires during 1999-2004 with meteorological variables and seasons

NASA Astrophysics Data System (ADS)

Alexander, P.

2013-01-01

This work aims to study associations between monthly averages of meteorological variables and monthly frequencies of diverse diseases in the calls to the public ambulance emergency service of the city of Buenos Aires during the years 1999-2004. Throughout this time period no changes were made in the classification codes of the illnesses. Heart disease, arrhythmia, heart failure, cardiopulmonary arrest, angina pectoris, psychiatric diseases, stroke, transient ischemic attack, syncope and the total number of calls were analyzed against 11 weather variables and the four seasons. All illnesses exhibited some seasonal behavior, except cardiorespiratory arrest and angina pectoris. The largest frequencies of illnesses that exhibited some association with the meteorological variables used to occur in winter, except the psychiatric cases. Heart failure, stroke, psychiatric diseases and the total number of calls showed significant correlations with the 11 meteorological variables considered, and the largest indices (absolute values above 0.6) were found for the former two pathologies. On the other side, cardiorespiratory arrest and angina pectoris revealed no significant correlations and nearly null indices. Variables associated with temperature were the meteorological proxies with the largest correlations against diseases. Pressure and humidity mostly exhibited positive correlations, which is the opposite of variables related to temperature. Contrary to all other diseases, psychiatric pathologies showed a clear predominance of positive correlations. Finally, the association degree of the medical dataset with recurrent patterns was further evaluated through Fourier analysis, to assess the presence of statistically significant behavior. In the Northern Hemisphere high morbidity and mortality rates in December are usually assigned to diverse factors in relation to the holidays, but such an effect is not observed in the present analysis. There seems to be no clearly preferred meteorological proxy among the different types of temperatures used. It is shown that the amount of occurrences depends mainly on season rather on its strength quantified by temperature.

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

NASA Technical Reports Server (NTRS)

Koren, Ilan; Feingold, Graham; Remer, Lorraine A.

2010-01-01

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

The influence of the atmospheric boundary layer on nocturnal layers of noctuids and other moths migrating over southern Britain.

PubMed

Wood, Curtis R; Chapman, Jason W; Reynolds, Donald R; Barlow, Janet F; Smith, Alan D; Woiwod, Ian P

2006-03-01

Insects migrating at high altitude over southern Britain have been continuously monitored by automatically operating, vertical-looking radars over a period of several years. During some occasions in the summer months, the migrants were observed to form well-defined layer concentrations, typically at heights of 200-400 m, in the stable night-time atmosphere. Under these conditions, insects are likely to have control over their vertical movements and are selecting flight heights that are favourable for long-range migration. We therefore investigated the factors influencing the formation of these insect layers by comparing radar measurements of the vertical distribution of insect density with meteorological profiles generated by the UK Meteorological Office's (UKMO) Unified Model (UM). Radar-derived measurements of mass and displacement speed, along with data from Rothamsted Insect Survey light traps, provided information on the identity of the migrants. We present here three case studies where noctuid and pyralid moths contributed substantially to the observed layers. The major meteorological factors influencing the layer concentrations appeared to be: (a) the altitude of the warmest air, (b) heights corresponding to temperature preferences or thresholds for sustained migration and (c) on nights when air temperatures are relatively high, wind-speed maxima associated with the nocturnal jet. Back-trajectories indicated that layer duration may have been determined by the distance to the coast. Overall, the unique combination of meteorological data from the UM and insect data from entomological radar described here show considerable promise for systematic studies of high-altitude insect layering.

Meteorological and Aerosol effects on Marine Cloud Microphysical Properties

NASA Astrophysics Data System (ADS)

Sanchez, K. J.; Russell, L. M.; Modini, R. L.; Frossard, A. A.; Ahlm, L.; Roberts, G.; Hawkins, L. N.; Schroder, J. C.; Wang, Z.; Lee, A.; Abbatt, J.; Lin, J.; Nenes, A.; Wonaschuetz, A.; Sorooshian, A.; Noone, K.; Jonsson, H.; Albrecht, B. A.; Desiree, T. S.; Macdonald, A. M.; Seinfeld, J.; Zhao, R.

2015-12-01

Both meteorology and microphysics affect cloud formation and consequently their droplet distributions and shortwave reflectance. The Eastern Pacific Emitted Aerosol Cloud Experiment (EPEACE) and the Stratocumulus Observations of Los-Angeles Emissions Derived Aerosol-Droplets (SOLEDAD) studies provide detailed measurements in 6 case studies of both cloud thermodynamic properties and initial particle number distribution and composition, as well as the resulting cloud drop distribution and composition. This study uses simulations of a detailed chemical and microphysical aerosol-cloud parcel (ACP) model with explicit kinetic drop activation to reproduce the observed cloud droplet distribution and composition. Four of the cases examined had a sub-adiabatic lapse rate, which was shown to have fewer droplets due to decreased maximum supersaturation, lower LWC and higher cloud base height, consistent with previous findings. These detailed case studies provided measured thermodynamics and microphysics that constrained the simulated droplet size distribution sufficiently to match the droplet number within 6% and the size within 19% for 4 of the 6 cases, demonstrating "closure" or consistency of the measured composition with the measured CCN spectra and the inferred and modeled supersaturation. The contribution of organic components to droplet formation shows small effects on the droplet number and size in the 4 marine cases that had background aerosol conditions with varying amounts of coastal, ship or other non-biogenic sources. In contrast, the organic fraction and hygroscopicity increased the droplet number and size in the cases with generated smoke and cargo ship plumes that were freshly emitted and not yet internally mixed with the background particles. The simulation results show organic hygroscopicity causes small effects on cloud reflectivity (<0.7%) with the exception of the cargo ship plume and smoke plume which increased absolute cloud reflectivity fraction by 0.02 and 0.20 respectively. In addition, the ACP model simulations are compared to those from a numerical parameterization of cloud droplet activation that is suitable for GCMs and show droplet concentrations are comparable between the two methods.

Communicating uncertainty in hydrological forecasts: mission impossible?

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

Urban-rural fog differences in Belgrade area, Serbia

NASA Astrophysics Data System (ADS)

Vujović, Dragana; Todorović, Nedeljko

2018-02-01

Urban/rural fog appearance during the last 27 years in the Belgrade region is analysed using hourly meteorological records from two meteorological stations: an urban station at Belgrade-Vračar (BV) and a rural station at Belgrade-Airport (BA). The effects of urban development on fog formation are discussed through analysis of fog frequency trends and comparison with a number of meteorological parameters. The mean annual and the mean annual minimum temperatures were greater at the urban BV station than at the rural BA station. The mean monthly relative humidity and the mean monthly water vapour pressure were greater at the rural than urban station. During the period of research (1988-2014), BA experiences 425 more days with fog than BV, which means that BV experiences fog for 62.68% of foggy days at BA. Trends in the number of days with fog were statistically non-significant. We analysed the fog occurrence during different types of weather. Fog in urban BV occurred more frequently during cyclonal circulation (in 52.75% of cases). In rural BA, the trend was the opposite and fog appeared more frequently during anticyclonic circulation (in 53.58% of cases). Fog at BV occurred most frequently in stable anticyclonic weather with light wind, when a temperature inversion existed (21.86% of cases). Most frequently, fog at BA occurred in the morning and only lasted a short time, followed by clearer skies during the anticyclonic warm and dry weather (22.55% of cases).

Urban air pollution and meteorological factors affect emergency department visits of elderly patients with chronic obstructive pulmonary disease in Taiwan.

PubMed

Ding, Pei-Hsiou; Wang, Gen-Shuh; Guo, Yue-Leon; Chang, Shuenn-Chin; Wan, Gwo-Hwa

2017-05-01

Both air pollution and meteorological factors in metropolitan areas increased emergency department (ED) visits from people with chronic obstructive pulmonary disease (COPD). Few studies investigated the associations between air pollution, meteorological factors, and COPD-related health disorders in Asian countries. This study aimed to investigate the relationship between the environmental factors and COPD-associated ED visits of susceptible elderly population in the largest Taiwanese metropolitan area (Taipei area, including Taipei city and New Taipei city) between 2000 and 2013. Data of air pollutant concentrations (PM 10 , PM 2.5 , O 3 , SO 2 , NO 2 and CO), meteorological factors (daily temperature, relative humidity and air pressure), and daily COPD-associated ED visits were collected from Taiwan Environmental Protection Administration air monitoring stations, Central Weather Bureau stations, and the Taiwan National Health Insurance database in Taipei area. We used a case-crossover study design and conditional logistic regression models with odds ratios (ORs), and 95% confidence intervals (CIs) for evaluating the associations between the environmental factors and COPD-associated ED visits. Analyses showed that PM 2.5 , O 3 , and SO 2 had significantly greater lag effects (the lag was 4 days for PM 2.5 , and 5 days for O 3 and SO 2 ) on COPD-associated ED visits of the elderly population (65-79 years old). In warmer days, a significantly greater effect on elderly COPD-associated ED visits was estimated for PM 2.5 with coexistence of O 3 . Additionally, either O 3 or SO 2 combined with other air pollutants increased the risk of elderly COPD-associated ED visits in the days of high relative humidity and air pressure difference, respectively. This study showed that joint effect of urban air pollution and meteorological factors contributed to the COPD-associated ED visits of the susceptible elderly population in the largest metropolitan area in Taiwan. Government authorities should review existing air pollution policies, and strengthen health education propaganda to ensure the health of the susceptible elderly population. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distributed lag effects and vulnerable groups of floods on bacillary dysentery in Huaihua, China

PubMed Central

Liu, Zhi-Dong; Li, Jing; Zhang, Ying; Ding, Guo-Yong; Xu, Xin; Gao, Lu; Liu, Xue-Na; Liu, Qi-Yong; Jiang, Bao-Fa

2016-01-01

Understanding the potential links between floods and bacillary dysentery in China is important to develop appropriate intervention programs after floods. This study aimed to explore the distributed lag effects of floods on bacillary dysentery and to identify the vulnerable groups in Huaihua, China. Weekly number of bacillary dysentery cases from 2005–2011 were obtained during flood season. Flood data and meteorological data over the same period were obtained from the China Meteorological Data Sharing Service System. To examine the distributed lag effects, a generalized linear mixed model combined with a distributed lag non-linear model were developed to assess the relationship between floods and bacillary dysentery. A total of 3,709 cases of bacillary dysentery were notified over the study period. The effects of floods on bacillary dysentery continued for approximately 3 weeks with a cumulative risk ratio equal to 1.52 (95% CI: 1.08–2.12). The risks of bacillary dysentery were higher in females, farmers and people aged 15–64 years old. This study suggests floods have increased the risk of bacillary dysentery with 3 weeks’ effects, especially for the vulnerable groups identified. Public health programs should be taken to prevent and control a potential risk of bacillary dysentery after floods. PMID:27427387

Distributed lag effects and vulnerable groups of floods on bacillary dysentery in Huaihua, China.

PubMed

Liu, Zhi-Dong; Li, Jing; Zhang, Ying; Ding, Guo-Yong; Xu, Xin; Gao, Lu; Liu, Xue-Na; Liu, Qi-Yong; Jiang, Bao-Fa

2016-07-18

Understanding the potential links between floods and bacillary dysentery in China is important to develop appropriate intervention programs after floods. This study aimed to explore the distributed lag effects of floods on bacillary dysentery and to identify the vulnerable groups in Huaihua, China. Weekly number of bacillary dysentery cases from 2005-2011 were obtained during flood season. Flood data and meteorological data over the same period were obtained from the China Meteorological Data Sharing Service System. To examine the distributed lag effects, a generalized linear mixed model combined with a distributed lag non-linear model were developed to assess the relationship between floods and bacillary dysentery. A total of 3,709 cases of bacillary dysentery were notified over the study period. The effects of floods on bacillary dysentery continued for approximately 3 weeks with a cumulative risk ratio equal to 1.52 (95% CI: 1.08-2.12). The risks of bacillary dysentery were higher in females, farmers and people aged 15-64 years old. This study suggests floods have increased the risk of bacillary dysentery with 3 weeks' effects, especially for the vulnerable groups identified. Public health programs should be taken to prevent and control a potential risk of bacillary dysentery after floods.

Distributed lag effects and vulnerable groups of floods on bacillary dysentery in Huaihua, China

NASA Astrophysics Data System (ADS)

Liu, Zhi-Dong; Li, Jing; Zhang, Ying; Ding, Guo-Yong; Xu, Xin; Gao, Lu; Liu, Xue-Na; Liu, Qi-Yong; Jiang, Bao-Fa

2016-07-01

Understanding the potential links between floods and bacillary dysentery in China is important to develop appropriate intervention programs after floods. This study aimed to explore the distributed lag effects of floods on bacillary dysentery and to identify the vulnerable groups in Huaihua, China. Weekly number of bacillary dysentery cases from 2005-2011 were obtained during flood season. Flood data and meteorological data over the same period were obtained from the China Meteorological Data Sharing Service System. To examine the distributed lag effects, a generalized linear mixed model combined with a distributed lag non-linear model were developed to assess the relationship between floods and bacillary dysentery. A total of 3,709 cases of bacillary dysentery were notified over the study period. The effects of floods on bacillary dysentery continued for approximately 3 weeks with a cumulative risk ratio equal to 1.52 (95% CI: 1.08-2.12). The risks of bacillary dysentery were higher in females, farmers and people aged 15-64 years old. This study suggests floods have increased the risk of bacillary dysentery with 3 weeks’ effects, especially for the vulnerable groups identified. Public health programs should be taken to prevent and control a potential risk of bacillary dysentery after floods.

The use of RPAS in monitoring volume changes, subsidence and gas emissions from a landfill in Veneto Region, North east of Italy.

NASA Astrophysics Data System (ADS)

Busnardo, Enrico; Ravagnan, Riccardo; Castellarin, Nicola; Canella, Claudio; Gandolfo, Luca; Petrillo, Giovanni

2017-04-01

Public opinion consider landfills as a problematic waste disposal system. They are perceived as groundwater and air source of pollution, and unfortunately it is true. For this reason, Regional Environmental Agencies (ARPA) need data in order to figure out the potential pollution near landfills. Remotely Piloted Aircraft Systems (RPAS) with specific sensors, could be a better solution than traditional terrestrial sensors. They provide a better sampling at different altitudes. Therefore, a 3D diffusion gas model could be improved. This study case is about a solid urban waste landfill, located on the Venetian Po Plain in the south of the Veneto Region. The "electronic nose" on the RPAS, needs to be stand still at least 15 seconds while sampling. For this reason, in this study case a multicopter RPAS was used. The result was a 3D concentration map of pollutant gases. The map was related with meteorological data from a Regional meteorological station located near the landfill to identify the gas source. In the end, the study about the olfactory impact was made using the OdiGauss model, developed by the Agricultural and Environmental Sciences Department of Udine University. It was also compared with a simulation carried out with CALWin software.

An investigation of the Sutcliffe development theory

NASA Technical Reports Server (NTRS)

Dushan, J. D.

1973-01-01

Two case studies were used to test the Sutcliffe-Peterssen development theory for both cyclonic and anticyclonic development over the eastern United States. Each term was examined to determine when and where it made a significant contribution to the development process. Results indicate the advection of vorticity at the level of non-divergence exerts the dominant influence for initial cyclone development, and that the thermal terms (advection of thickness, stability, and diabatic influence) become important after development has begun. Anticyclonic development, however, depends primarily on the stability term throughout the life cycle of the anticyclone. Simple procedures for forecasting the development and movement of cyclones and anticyclones are listed. These rules indicate that routine National Meteorological Center analyses may be used to locate areas where the positive advection of 500-mb vorticity, indicative of cyclonic development, coincides with regions of severe weather activity. The development of anticyclones also is predicted easily. Regions of increasing stability, indicating anticyclonic development, may be located by use of National Meteorological Center radar summaries and analyses for 1000-500-mb thickness. A test of these techniques found them to be satisfactory for the case examined.

Power availability at terrestrial receptor sites for laser-power transmission from the satellite power system

NASA Technical Reports Server (NTRS)

Beverly, R. E., III

1982-01-01

A statistical model was developed for relating the temporal transmission parameters of a laser beam from a solar power satellite to observable meteorological data to determine the influence of weather on power reception at the earth-based receiver. Sites within 100 miles of existing high voltage transmission lines were examined and the model was developed for clear-sky and clouded conditions. The cases of total transmission through clouds at certain wavelengths, no transmission, and partial transmission were calculated for the cloud portion of the model. The study covered cirriform, stratiform, cumiliform, and mixed type clouds and the possibility of boring holes through the clouds with the beam. Utilization of weapons-quality beams for hole boring, was found to yield power availability increases of 9-33%, although no beneficial effects could be predicted in regions of persistent cloud cover. An efficiency of 80% was determined as possible if several receptor sites were available within 200-300 miles of each other, thereby allowing changes of reception point in cases of unacceptable meteorological conditions.

Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

NASA Astrophysics Data System (ADS)

Czernecki, Bartosz; Nowosad, Jakub; Jabłońska, Katarzyna

2018-04-01

Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For other phenophases, RMSE are higher and rise up to 9-10 days in the case of the earliest spring phenophases.

Weather conditions influence the number of psychiatric emergency room patients

NASA Astrophysics Data System (ADS)

Brandl, Eva Janina; Lett, Tristram A.; Bakanidze, George; Heinz, Andreas; Bermpohl, Felix; Schouler-Ocak, Meryam

2017-12-01

The specific impact of weather factors on psychiatric disorders has been investigated only in few studies with inconsistent results. We hypothesized that meteorological conditions influence the number of cases presenting in a psychiatric emergency room as a measure of mental health conditions. We analyzed the number of patients consulting the emergency room (ER) of a psychiatric hospital in Berlin, Germany, between January 1, 2008, and December 31, 2014. A total of N = 22,672 cases were treated in the ER over the study period. Meteorological data were obtained from a publicly available data base. Due to collinearity among the meteorological variables, we performed a principal component (PC) analysis. Association of PCs with the daily number of patients was analyzed with autoregressive integrated moving average model. Delayed effects were investigated using Granger causal modeling. Daily number of patients in the ER was significantly higher in spring and summer compared to fall and winter (p < 0.001). Three PCs explained 76.8% percent of the variance with PC1 loading mostly on temperature, PC2 on cloudiness and low pressure, and PC3 on windiness. PC1 and PC2 showed strong association with number of patients in the emergency room (p < 0.010) indicating higher patient numbers on warmer and on cloudy days. Further, PC1, PC2, and PC3 predicted the number of patients presenting in the emergency room for up to 7 days (p < 0.050). A secondary analysis revealed that the effect of temperature on number of patients was mostly due to lower patient numbers on cold days. Although replication of our findings is required, our results suggest that weather influences the number of psychiatric patients consulting the emergency room. In particular, our data indicate lower patient numbers during very cold temperatures.

Weather conditions influence the number of psychiatric emergency room patients

NASA Astrophysics Data System (ADS)

Brandl, Eva Janina; Lett, Tristram A.; Bakanidze, George; Heinz, Andreas; Bermpohl, Felix; Schouler-Ocak, Meryam

2018-05-01

The specific impact of weather factors on psychiatric disorders has been investigated only in few studies with inconsistent results. We hypothesized that meteorological conditions influence the number of cases presenting in a psychiatric emergency room as a measure of mental health conditions. We analyzed the number of patients consulting the emergency room (ER) of a psychiatric hospital in Berlin, Germany, between January 1, 2008, and December 31, 2014. A total of N = 22,672 cases were treated in the ER over the study period. Meteorological data were obtained from a publicly available data base. Due to collinearity among the meteorological variables, we performed a principal component (PC) analysis. Association of PCs with the daily number of patients was analyzed with autoregressive integrated moving average model. Delayed effects were investigated using Granger causal modeling. Daily number of patients in the ER was significantly higher in spring and summer compared to fall and winter ( p < 0.001). Three PCs explained 76.8% percent of the variance with PC1 loading mostly on temperature, PC2 on cloudiness and low pressure, and PC3 on windiness. PC1 and PC2 showed strong association with number of patients in the emergency room ( p < 0.010) indicating higher patient numbers on warmer and on cloudy days. Further, PC1, PC2, and PC3 predicted the number of patients presenting in the emergency room for up to 7 days ( p < 0.050). A secondary analysis revealed that the effect of temperature on number of patients was mostly due to lower patient numbers on cold days. Although replication of our findings is required, our results suggest that weather influences the number of psychiatric patients consulting the emergency room. In particular, our data indicate lower patient numbers during very cold temperatures.

Overview of Dust Model Inter-comparison (DMIP) in East Asia

NASA Astrophysics Data System (ADS)

Uno, I.

2004-12-01

Dust transport modeling plays an important role in understanding the recent increase of Asian Dust episodes and its impact to the regional climate system. Several dust models have been developed in several research institutes and government agencies independently since 1990s. Their numerical results either look very similar or different. Those disagreements are caused by difference in dust modules (concepts and basic mechanisms) and atmospheric models (meteorological and transport models). Therefore common understanding of performance and uncertainty of dust erosion and transport models in the Asian region becomes very important. To have a better understanding of dust model application, we proposed the dust model intercomparison under the international cooperation networks as a part of activity of ADEC (Aeolian Dust Experiment on Climate Impact) project research. Current participants are Kyusyu Univ. (Japan), Meteorological Research Institute (Japan), Hong-Kong City Univ. (China), Korean Meteorological Agency METRI (Korea), US Naval Research Laboratory (USA), Chinese Meteorological Agency (China), Institute of Atmospheric Physics (China), Insular Coastal Dynamics (Malta) and Meteorological Service of Canada (Canada). As a case study episode, we set two huge dust storms occurred in March and April 2002. Results from the dust transport model from all the participants are compiled on the same methods and examined the model characteristics against the ground and airborne measurement data. We will also examine the dust model results from the horizontal distribution at specified levels, vertical profiles, concentration at special check point and emission flux at source region, and show the important parameters for dust modeling. In this paper, we will introduce the general overview of this DMIP activity and several important conclusions from this activity.

Effect of horizontal resolution on meteorology and air-quality prediction with a regional scale model

NASA Astrophysics Data System (ADS)

Varghese, Saji; Langmann, Baerbel; Ceburnis, Darius; O'Dowd, Colin D.

2011-08-01

Horizontal resolution sensitivity can significantly contribute to the uncertainty in predictions of meteorology and air-quality from a regional climate model. In the study presented here, a state-of-the-art regional scale atmospheric climate-chemistry-aerosol model REMOTE is used to understand the influence of spatial model resolutions of 1.0°, 0.5° and 0.25° on predicted meteorological and aerosol parameters for June 2003 for the European domain comprising North-east Atlantic and Western Europe. Model precipitation appears to improve with resolution while wind speed has shown best results for 0.25° resolution for most of the stations compared with ECAD data. Low root mean square error and spatial bias for surface pressure, precipitation and surface temperature show that the model is very reliable. Spatial and temporal variation in black carbon, primary organic carbon, sea-salt and sulphate concentrations and their burden are presented. In most cases, chemical species concentrations at the surface show no particular trend or improvement with increase in resolution. There has been a pronounced influence of horizontal resolution on the vertical distribution pattern of some aerosol species. Some of these effects are due to the improvement in topographical details, flow characteristics and associated vertical and horizontal dynamic processes. The different sink processes have contributed very differently to the various aerosol species in terms of deposition (wet and dry) and sedimentation which are strongly linked to the meteorological processes. Overall, considering the performance of meteorological parameters and chemical species concentrations, a horizontal model resolution of 0.5° is suggested to achieve reasonable results within the limitations of this model.

Assessment of climate change impacts on meteorological and hydrological droughts in the Jucar River Basin

NASA Astrophysics Data System (ADS)

Marcos-Garcia, Patricia; Pulido-Velazquez, Manuel; Lopez-Nicolas, Antonio

2016-04-01

Extreme natural phenomena, and more specifically droughts, constitute a serious environmental, economic and social issue in Southern Mediterranean countries, common in the Mediterranean Spanish basins due to the high temporal and spatial rainfall variability. Drought events are characterized by their complexity, being often difficult to identify and quantify both in time and space, and an universally accepted definition does not even exist. This fact, along with future uncertainty about the duration and intensity of the phenomena on account of climate change, makes necessary increasing the knowledge about the impacts of climate change on droughts in order to design management plans and mitigation strategies. The present abstract aims to evaluate the impact of climate change on both meteorological and hydrological droughts, through the use of a generalization of the Standardized Precipitation Index (SPI). We use the Standardized Flow Index (SFI) to assess the hydrological drought, using flow time series instead of rainfall time series. In the case of the meteorological droughts, the Standardized Precipitation and Evapotranspiration Index (SPEI) has been applied to assess the variability of temperature impacts. In order to characterize climate change impacts on droughts, we have used projections from the CORDEX project (Coordinated Regional Climate Downscaling Experiment). Future rainfall and temperature time series for short (2011-2040) and medium terms (2041-2070) were obtained, applying a quantile mapping method to correct the bias of these time series. Regarding the hydrological drought, the Témez hydrological model has been applied to simulate the impacts of future temperature and rainfall time series on runoff and river discharges. It is a conceptual, lumped and a few parameters hydrological model. Nevertheless, it is necessary to point out the time difference between the meteorological and the hydrological droughts. The case study is the Jucar river basin (Spain), a highly regulated system with a share of 80% of water use for irrigated agriculture. The results show that the climate change would increase the historical drought impacts in the river basin. Acknowledgments The study has been supported by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and European FEDER funds.

Raman Lidar Measurements During the International H2O Project. 2; Instrument Comparisons and Case Studies

NASA Technical Reports Server (NTRS)

Whiteman, D. N.; Demoz, B.; DiGirolamo, P.; Corner, J.; Veselovskii, I.; Evans, K.; Wang, Z.; Sabatino, D.; Schwemmer, G.; Gentry, B.

2005-01-01

The NASA/GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June, 2002 in the midwestern part of the U. S. The SRL system configuration and methods of data analysis were described in part I of this paper. In this second part, comparisons of SRL water vapor measurements and those of chilled mirror radiosonde and LASE airborne water vapor lidar are performed. Two case studies are presented; one for daytime and one for nighttime. The daytime case study is of a convectively driven boundary layer event and is used to characterize the SRL water vapor random error characteristics. The nighttime case study is of a thunderstorm-generated cirrus cloud case that is studied in it s meteorological context. Upper tropospheric humidification due to precipitation from the cirrus cloud is quantified as is the cirrus cloud ice water content and particle depolarization ratio. These detailed cirrus cloud measurements are being used in a cirrus cloud modeling study.

Evaluation of low wind modeling approaches for two tall-stack databases.

PubMed

Paine, Robert; Samani, Olga; Kaplan, Mary; Knipping, Eladio; Kumar, Naresh

2015-11-01

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO2 monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO2 monitors within 10 km of the Dakota Gasification Company's plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO2 monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the over-prediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions. AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the over-prediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.

Teaching Guidelines for the Observance of World Meteorological Day (23 March).

ERIC Educational Resources Information Center

International Understanding at School, 1986

1986-01-01

Discusses the establishment and goals of the World Meteorological Organization and the World Meteorological Day (WMD). Includes teaching objectives for upper elementary and lower secondary school teachers and provides activities which integrate the study of meteorology with language, history, geography, mathematics, science, physical education,…

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin.

PubMed

Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yu, Mingzhao; Yan, Nana; Xing, Qiang

2016-11-04

Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index-FY-2D cloud type sunshine factor-is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration.

A Method to Estimate Sunshine Duration Using Cloud Classification Data from a Geostationary Meteorological Satellite (FY-2D) over the Heihe River Basin

PubMed Central

Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yu, Mingzhao; Yan, Nana; Xing, Qiang

2016-01-01

Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using an interpolation method based on regional-scale meteorological data from field stations. Accurate values in the field are difficult to obtain without ground measurements. In this paper, a satellite-based method to estimate sunshine duration is introduced and applied over the Heihe River Basin. This method is based on hourly cloud classification product data from the FY-2D geostationary meteorological satellite (FY-2D). A new index—FY-2D cloud type sunshine factor—is proposed, and the Shuffled Complex Evolution Algorithm (SCE-UA) was used to calibrate sunshine factors from different coverage types based on ground measurement data from the Heihe River Basin in 2007. The estimated sunshine duration from the proposed new algorithm was validated with ground observation data for 12 months in 2008, and the spatial distribution was compared with the results of an interpolation method over the Heihe River Basin. The study demonstrates that geostationary satellite data can be used to successfully estimate sunshine duration. Potential applications include climate research, energy balance studies, and global estimations of evapotranspiration. PMID:27827935

Forecast of severe fever with thrombocytopenia syndrome incidence with meteorological factors.

PubMed

Sun, Ji-Min; Lu, Liang; Liu, Ke-Ke; Yang, Jun; Wu, Hai-Xia; Liu, Qi-Yong

2018-06-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and some studies reported that SFTS incidence was associated with meteorological factors, while no report on SFTS forecast models was reported up to date. In this study, we constructed and compared three forecast models using autoregressive integrated moving average (ARIMA) model, negative binomial regression model (NBM), and quasi-Poisson generalized additive model (GAM). The dataset from 2011 to 2015 were used for model construction and the dataset in 2016 were used for external validity assessment. All the three models fitted the SFTS cases reasonably well during the training process and forecast process, while the NBM model forecasted better than other two models. Moreover, we demonstrated that temperature and relative humidity played key roles in explaining the temporal dynamics of SFTS occurrence. Our study contributes to better understanding of SFTS dynamics and provides predictive tools for the control and prevention of SFTS. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of meteorological conditions for the Yakima Smoke Intrusion Case Study, 28 September 2009

Treesearch

Miriam Rorig; Robert Solomon; Candace Krull; Janice Peterson; Julia Ruthford; Brian Potter

2013-01-01

On 28 September 2009, the Naches Ranger District on the Okanogan-Wenatchee National Forest in south-central Washington state ignited an 800-ha prescribed fire. Later that afternoon, elevated PM2.5 concentrations and visible smoke were reported in Yakima, Washington, about 40 km east of the burn unit. The U.S. National Weather Service forecast for the day had predicted...

Direct comparison of extinction coefficients derived from Mie-scattering lidar and number concentrations of particles, subjective weather report in Japan

NASA Astrophysics Data System (ADS)

Shimizu, Atsushi; Sugimoto, Nobuo; Matsui, Ichiro; Nishizawa, Tomoaki

2015-03-01

Two components of the lidar extinction coefficient, the dust extinction and the spherical particles extinction, were obtained from observations made by the National Institute for Environmental Studies lidar network in Japan. These two extinctions were compared with the number concentration of particles measured by an optical particle counter, and with subjective weather reports recorded at the nearest meteorological observatories. The dust extinction corresponded well with the number concentration of large particles with diameters as great as 5 μm and during dry conditions with the number concentration of particles larger than 2 μm. The relationship between the spherical particle extinction and the number of small particles was nearly constant under all conditions. Asian dust was sometimes reported by meteorological observatories in the period of lower dust extinction. This indicates contradicting relationship between human-eye based reports and optical characteristics observed by lidars in some cases. The most consistent results between lidar observation and meteorological reports were obtained in dry mist conditions, in which lidars exhibited higher spherical extinction as expected by the definition of the atmospheric phenomenon of dry mist or haze.

Improvement of Advanced Storm-scale Analysis and Prediction System (ASAPS) on Seoul Metropolitan Area, Korea

NASA Astrophysics Data System (ADS)

Park, Jeong-Gyun; Jee, Joon-Bum

2017-04-01

Dangerous weather such as severe rain, heavy snow, drought and heat wave caused by climate change make more damage in the urban area that dense populated and industry areas. Urban areas, unlike the rural area, have big population and transportation, dense the buildings and fuel consumption. Anthropogenic factors such as road energy balance, the flow of air in the urban is unique meteorological phenomena. However several researches are in process about prediction of urban meteorology. ASAPS (Advanced Storm-scale Analysis and Prediction System) predicts a severe weather with very short range (prediction with 6 hour) and high resolution (every hour with time and 1 km with space) on Seoul metropolitan area based on KLAPS (Korea Local Analysis and Prediction System) from KMA (Korea Meteorological Administration). This system configured three parts that make a background field (SUF5), analysis field (SU01) with observation and forecast field with high resolution (SUF1). In this study, we improve a high-resolution ASAPS model and perform a sensitivity test for the rainfall case. The improvement of ASAPS include model domain configuration, high resolution topographic data and data assimilation with WISE observation data.

An Operational Computational Terminal Area PBL Prediction System

NASA Technical Reports Server (NTRS)

Lin, Yuh-Lang; Kaplan, Michael L.

1998-01-01

There are two fundamental goals of this research project which are listed here in terms of priority, i.e., a primary and secondary goal. The first and primary goal is to develop a prognostic system which could satisfy the operational weather prediction requirements of the meteorological subsystem within the Aircraft Vortex Spacing System (AVOSS), i.e., an operational computational Terminal Area PBL Prediction System (TAPPS). The second goal is to perform indepth diagnostic analyses of the meteorological conditions during the special wake vortex deployments at Memphis and Dallas during August 95 and September 97, respectively. These two goals are interdependent because a thorough understanding of the atmospheric dynamical processes which produced the unique meteorology during the Memphis and Dallas deployments will help us design a prognostic system for the planetary boundary layer (PBL) which could be utilized to support the meteorological subsystem within AVOSS. Concerning the primary goal, TAPPS Stage 2 was tested on the Memphis data and is about to be tested on the Dallas case studies. Furthermore benchmark tests have been undertaken to select the appropriate platform to run TAPPS in real time in support of the DFW AVOSS system. In addition, a technique to improve the initial data over the region surrounding Dallas was also tested and modified for potential operational use in TAPPS. The secondary goal involved several sensitivity simulations and comparisons to Memphis observational data sets in an effort to diagnose what specific atmospheric phenomena where occurring which may have impacted the dynamics of atmospheric wake vortices.

Testing the use of standardised indices and GRACE satellite data to estimate the European 2015 groundwater drought in near-real time

NASA Astrophysics Data System (ADS)

Van Loon, Anne F.; Kumar, Rohini; Mishra, Vimal

2017-04-01

In 2015, central and eastern Europe were affected by a severe drought. This event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater situation has been performed. One of the reasons is that real-time groundwater level observations often are not available. In this study, we evaluate two alternative approaches to quantify the 2015 groundwater drought over two regions in southern Germany and eastern Netherlands. The first approach is based on spatially explicit relationships between meteorological conditions and historic groundwater level observations. The second approach uses the Gravity Recovery Climate Experiment (GRACE) terrestrial water storage (TWS) and groundwater anomalies derived from GRACE-TWS and (near-)surface storage simulations by the Global Land Data Assimilation System (GLDAS) models. We combined the monthly groundwater observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardised Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.25° gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in groundwater response time to meteorological input over the region. Based on the estimated optimal accumulation periods and available meteorological time series, we reconstructed the groundwater anomalies up to 2015 and found that in Germany a uniform severe groundwater drought persisted for several months during this year, whereas the Netherlands appeared to have relatively high groundwater levels. The differences between this event and the 2003 European benchmark drought are striking. The 2003 groundwater drought was less uniformly pronounced, both in the Netherlands and Germany. This is because slowly responding wells (the ones with optimal accumulation periods of more than 12 months) still were above average from the wet year of 2002, which experienced severe flooding in central Europe. GRACE-TWS and GRACE-based groundwater anomalies did not capture the spatial variability of the 2003 and 2015 drought events satisfactorily. GRACE-TWS did show that both 2003 and 2015 were relatively dry, but the differences between Germany and the Netherlands in 2015 and the spatially variable groundwater drought pattern in 2003 were not captured. This could be associated with the coarse spatial scale of GRACE. The simulated groundwater anomalies based on GRACE-TWS deviated considerably from the GRACE-TWS signal and from observed groundwater anomalies. The uncertainty in the GRACE-based groundwater anomalies mainly results from uncertainties in the simulation of soil moisture by the different GLDAS models. The GRACE-based groundwater anomalies are therefore not suitable for use in real-time groundwater drought monitoring in our case study regions. The alternative approach based on the spatially variable relationship between meteorological conditions and groundwater levels is more suitable to quantify groundwater drought in near real-time. Compared to the meteorological drought and streamflow drought (described in previous studies), the groundwater drought of 2015 had a more pronounced spatial variability in its response to meteorological conditions, with some areas primarily influenced by short-term meteorological deficits and others influenced by meteorological deficits accumulated over the preceding 2 years or more. In drought management, this information is very useful and our approach to quantify groundwater drought can be used until real-time groundwater observations become readily available.

A study to define meteorological uses and performance requirements for the Synchronous Earth Observatory Satellite

NASA Technical Reports Server (NTRS)

Suomi, V. E.; Krauss, R. J.; Barber, D.; Levanon, N.; Martin, D. W.; Mclellan, D. W.; Sikdar, D. N.; Sromovsky, L. A.; Branch, D.; Heinricy, D.

1973-01-01

The potential meteorological uses of the Synchronous Earth Observatory Satellite (SEOS) were studied for detecting and predicting hazards to life, property, or the quality of the environment. Mesoscale meteorological phenonmena, and the observations requirements for SEOS are discussed along with the sensor parameters.

Meteorology, Emissions, and Grid Resolution: Effects on Discrete and Probabilistic Model Performance

EPA Science Inventory

In this study, we analyze the impacts of perturbations in meteorology and emissions and variations in grid resolution on air quality forecast simulations. The meteorological perturbations con-sidered in this study introduce a typical variability of ~1°C, 250 - 500 m, 1 m/s, and 1...

Flood Warning and Forecasting System in Slovakia

NASA Astrophysics Data System (ADS)

Leskova, Danica

2016-04-01

In 2015, it finished project Flood Warning and Forecasting System (POVAPSYS) as part of the flood protection in Slovakia till 2010. The aim was to build POVAPSYS integrated computerized flood forecasting and warning system. It took a qualitatively higher level of output meteorological and hydrological services in case of floods affecting large territorial units, as well as local flood events. It is further unfolding demands on performance and coordination of meteorological and hydrological services, troubleshooting observation, evaluation of data, fast communication, modeling and forecasting of meteorological and hydrological processes. Integration of all information entering and exiting to and from the project POVAPSYS provides Hydrological Flood Forecasting System (HYPOS). The system provides information on the current hydrometeorological situation and its evolution with the generation of alerts and notifications in case of exceeding predefined thresholds. HYPOS's functioning of the system requires flawless operability in critical situations while minimizing the loss of its key parts. HYPOS is a core part of the project POVAPSYS, it is a comprehensive software solutions based on a modular principle, providing data and processed information including alarms, in real time. In order to achieve full functionality of the system, in proposal, we have put emphasis on reliability, robustness, availability and security.

Meteorological stations as a tool to teach on climate system sciences

NASA Astrophysics Data System (ADS)

Cerdà, Artemi; Bodí, Merche B.; Damián Ruiz-Sinoga, José

2010-05-01

Higher education has been focussed on teaching climate system theory. Meteorology and climatology student rarely visited a meteorological station. However, meteorological stations are the source of information for the climate system studies and they supply the key information for modelling. This paper shows how meteorological station is a key tool to introduce student to the study of climate and meteorology. The research stations of Montesa and El Teularet-Sierra de Enguera are being used for seven years to supply data to the students of Climatology, 1st year of the Degree in Geography at the University of Valencia. The results show that the students that used the raw data set were proud to use original data. Those students got higher qualifications and they choose also in the following year courses on climatology or Physical Geography. Then, the conclusions are that the use of meteorological stations is a positive contribution to the improvement of the knowledge of the students, and his compromise with the science and the environment.

Should we use seasonnal meteorological ensemble forecasts for hydrological forecasting? A case study for nordic watersheds in Canada.

NASA Astrophysics Data System (ADS)

Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert; Guay, Catherine

2017-04-01

Hydro-electricity is a major source of energy for many countries throughout the world, including Canada. Long lead-time streamflow forecasts are all the more valuable as they help decision making and dam management. Different techniques exist for long-term hydrological forecasting. Perhaps the most well-known is 'Extended Streamflow Prediction' (ESP), which considers past meteorological scenarios as possible, often equiprobable, future scenarios. In the ESP framework, those past-observed meteorological scenarios (climatology) are used in turn as the inputs of a chosen hydrological model to produce ensemble forecasts (one member corresponding to each year in the available database). Many hydropower companies, including Hydro-Québec (province of Quebec, Canada) use variants of the above described ESP system operationally for long-term operation planning. The ESP system accounts for the hydrological initial conditions and for the natural variability of the meteorological variables. However, it cannot consider the current initial state of the atmosphere. Climate models can help remedy this drawback. In the context of a changing climate, dynamical forecasts issued from climate models seem to be an interesting avenue to improve upon the ESP method and could help hydropower companies to adapt their management practices to an evolving climate. Long-range forecasts from climate models can also be helpful for water management at locations where records of past meteorological conditions are short or nonexistent. In this study, we compare 7-month hydrological forecasts obtained from climate model outputs to an ESP system. The ESP system mimics the one used operationally at Hydro-Québec. The dynamical climate forecasts are produced by the European Center for Medium range Weather Forecasts (ECMWF) System4. Forecasts quality is assessed using numerical scores such as the Continuous Ranked Probability Score (CRPS) and the Ignorance score and also graphical tools such as the reliability diagram. This study covers 10 nordic watersheds. We show that forecast performance according to the CRPS varies with lead-time but also with the period of the year. The raw forecasts from the ECMWF System4 display important biases for both temperature and precipitation, which need to be corrected. The linear scaling method is used for this purpose and is found effective. Bias correction improves forecasts performance, especially during the summer when the precipitations are over-estimated. According to the CRPS, bias corrected forecasts from System4 show performances comparable to those of the ESP system. However, the Ignorance score, which penalizes the lack of calibration (under-dispersive forecasts in this case) more severely than the CRPS, provides a different outlook for the comparison of the two systems. In fact, according to the Ignorance score, the ESP system outperforms forecasts based on System4 in most cases. This illustrates that the joint use of several metrics is crucial to assess the quality of a forecasts system thoroughly. Globally, ESP provide reliable forecasts which can be over-dispersed whereas bias corrected ECMWF System4 forecasts are sharper but at the risk of missing events.

Diurnal and seasonal variations in surface methane at a tropical coastal station: Role of mesoscale meteorology.

PubMed

Kavitha, M; Nair, Prabha R; Girach, I A; Aneesh, S; Sijikumar, S; Renju, R

2018-08-01

In view of the large uncertainties in the methane (CH 4 ) emission estimates and the large spatial gaps in its measurements, studies on near-surface CH 4 on regional basis become highly relevant. This paper presents the first time observational results of a study on the impacts of mesoscale meteorology on the temporal variations of near-surface CH 4 at a tropical coastal station, in India. It is based on the in-situ measurements conducted during January 2014 to August 2016, using an on-line CH 4 analyzer working on the principle of gas chromatography. The diurnal variation shows a daytime low (1898-1925ppbv) and nighttime high (1936-2022ppbv) extending till early morning hours. These changes are closely associated with the mesoscale circulations, namely Sea Breeze (SB) and Land Breeze (LB), as obtained through the meteorological observations, WRF simulations of the circulations and the diurnal variation of boundary layer height as observed by the Microwave Radiometer Profiler. The diurnal enhancement always coincides with the onset of LB. Several cases of different onset timings of LB were examined and results presented. The CH 4 mixing ratio also exhibits significant seasonal patterns being maximum in winter and minimum in pre-monsoon/monsoon with significant inter-annual variations, which is also reflected in diurnal patterns, and are associated with changing synoptic meteorology. This paper also presents an analysis of in-situ measured near-surface CH 4 , column averaged and upper tropospheric CH 4 retrieved by Atmospheric Infrared Sounder (AIRS) onboard Earth Observing System (EOS)/Aqua which gives insight into the vertical distribution of the CH 4 over the location. An attempt is also made to estimate the instantaneous radiative forcing for the measured CH 4 mixing ratio. Copyright © 2018 Elsevier B.V. All rights reserved.

What are the hydro-meteorological controls on flood characteristics?

NASA Astrophysics Data System (ADS)

Nied, Manuela; Schröter, Kai; Lüdtke, Stefan; Nguyen, Viet Dung; Merz, Bruno

2017-02-01

Flood events can be expressed by a variety of characteristics such as flood magnitude and extent, event duration or incurred loss. Flood estimation and management may benefit from understanding how the different flood characteristics relate to the hydrological catchment conditions preceding the event and to the meteorological conditions throughout the event. In this study, we therefore propose a methodology to investigate the hydro-meteorological controls on different flood characteristics, based on the simulation of the complete flood risk chain from the flood triggering precipitation event, through runoff generation in the catchment, flood routing and possible inundation in the river system and floodplains to flood loss. Conditional cumulative distribution functions and regression tree analysis delineate the seasonal varying flood processes and indicate that the effect of the hydrological pre-conditions, i.e. soil moisture patterns, and of the meteorological conditions, i.e. weather patterns, depends on the considered flood characteristic. The methodology is exemplified for the Elbe catchment. In this catchment, the length of the build-up period, the event duration and the number of gauges undergoing at least a 10-year flood are governed by weather patterns. The affected length and the number of gauges undergoing at least a 2-year flood are however governed by soil moisture patterns. In case of flood severity and loss, the controlling factor is less pronounced. Severity is slightly governed by soil moisture patterns whereas loss is slightly governed by weather patterns. The study highlights that flood magnitude and extent arise from different flood generation processes and concludes that soil moisture patterns as well as weather patterns are not only beneficial to inform on possible flood occurrence but also on the involved flood processes and resulting flood characteristics.

The effect of changes in space shuttle parameters on the NASA/MSFC multilayer diffusion model predictions of surface HCl concentrations

NASA Technical Reports Server (NTRS)

Glasser, M. E.; Rundel, R. D.

1978-01-01

A method for formulating these changes into the model input parameters using a preprocessor program run on a programed data processor was implemented. The results indicate that any changes in the input parameters are small enough to be negligible in comparison to meteorological inputs and the limitations of the model and that such changes will not substantially increase the number of meteorological cases for which the model will predict surface hydrogen chloride concentrations exceeding public safety levels.

Future Projection of Storm Surge at Tokyo Bay under RCP 8.5 Scenario by Meteorological-Ocean-Tide Coupled Model

NASA Astrophysics Data System (ADS)

Iwamoto, T.; Nakamura, R.; Takagawa, T.; Shibayama, T.

2016-12-01

It is clearly valuable to accomplish well-reproduced storm surge model and conduct future projection for disaster prevention. In this study, the reproducibility of Meteorological-Ocean-Tide coupled model was validated by simulating typhoon Roke (2011) storm surge, which was recorded as the highest anomaly (119cm) at Tokyo tide station (JMA) in Tokyo Bay over the last 10 years. Furthermore, the future projection (2050) under global warming scenario (RCP8.5) was conducted. The coupled model was composed of 3 models; ARW-WRFV3 (Skamarock et al., 2008), FVCOM (Chen et al., 2011) and WXTide32. WRF firstly calculated downscaled meteorological field by using FiNal anaLysis (FNL) as initial/boundary (I/B) condition. In this calculation, single layer urban canopy model (Kusaka et al., 2001) and topography data from SRTM3 (90m mesh) and GSI (50m mesh) were applied. Then the output was used as I/B condition to FVCOM, which calculated storm surge. Finally tide level was calculated by adding storm surge to astronomical tide calculated by WXTide32. For 2050 case, sea surface temperature (SST) from 26 GCM under RCP8.5 was used for constructing pseudo global warming meteorological fields. In details, ensemble average of SST variation between 2006-2015 and 2041-2060 was added to FNL's SST by following Oya et al (2016). In this case, calculating astronomical tide is omitted due to the limitation of WXTide32. The reproduced result of typhoon Roke shows that the difference of maximum tide level (first peak) to the observation is less than 10cm, the difference of second peak is about 50cm. The future projection result shows that the increase of storm surge at Tokyo tide station is about 20cm and that at Funabashi is about 30cm. This intensification is mainly caused by wind speed increment, since the variation of low pressure due to higher SST is relatively small. Moreover, Funabashi is located in front of the open space at inner part of Tokyo Bay, Tokyo tide station is similar however is installed at Tokyo harbor which has intricate terrain. This implies that the geographical condition will affect storm surge significantly for typhoon Roke-like case.

Assessing the value of increased model resolution in forecasting fire danger

Treesearch

Jeanne Hoadley; Miriam Rorig; Ken Westrick; Larry Bradshaw; Sue Ferguson; Scott Goodrick; Paul Werth

2003-01-01

The fire season of 2000 was used as a case study to assess the value of increasing mesoscale model resolution for fire weather and fire danger forecasting. With a domain centered on Western Montana and Northern Idaho, MM5 simulations were run at 36, 12, and 4-km resolutions for a 30 day period at the height of the fire season. Verification analyses for meteorological...

Spatial impact and triggering conditions of the exceptional hydro-geomorphological event of December 1909 in Iberia

NASA Astrophysics Data System (ADS)

Pereira, S.; Ramos, A. M.; Zêzere, J. L.; Trigo, R. M.; Vaquero, J. M.

2016-02-01

According to the DISASTER database the 20-28 December 1909 event was the hydro-geomorphologic event with the highest number of flood and landslide cases that occurred in Portugal in the period 1865-2010 (Zêzere et al., 2014). This event also caused important social impacts over the Spanish territory, especially in the Douro Basin, having triggered the highest floods in more than 100 years at the river's mouth in the city of Oporto. This work has a dual purpose: (i) to characterize the spatial distribution and social impacts of the December 1909 hydro-geomorphologic DISASTER event over Portugal and Spain; (ii) to analyse the meteorological conditions that triggered the event and the spatial distribution of the precipitation anomalies. Social impacts that occurred in Portugal were obtained from the Disaster database (Zêzere et al., 2014) whereas the data collection for Spain was supported by the systematic analysis of Spanish daily newspapers. In addition, the meteorological conditions that triggered the event are analysed using the 20th Century Reanalysis data set from NOAA and precipitation data from Iberian meteorological stations. The Iberian Peninsula was spatially affected during this event along the SW-NE direction spanning from Lisbon, Santarém, Oporto, and Guarda (in Portugal), to Salamanca, Valladolid, Zamora, Orense, León, and Palencia (in Spain). In Iberia, 134 DISASTER cases were recorded (130 flood cases; 4 landslides cases) having caused 89 casualties (57 due to floods and 32 due to landslides) and a further total of 3876 affected people, including fatalities, injured, missing, evacuated, and homeless people. This event was associated with outstanding precipitation registered at Guarda (Portugal) on 22 December 1909 and unusual meteorological conditions characterized by the presence of a deep low-pressure system located over the NW Iberian Peninsula with a stationary frontal system striking the western Iberian Peninsula. The presence of an upper-level jet (250 hPa) and low-level jet (900 hPa) located SW-NE oriented towards Iberia along with upper-level divergence and lower-level convergence favoured large-scale precipitation. Finally, associated with these features it is possible to state that this extreme event was clearly associated with the presence of an elongated Atmospheric River, crossing the entire northern Atlantic Basin and providing a continuous supply of moisture that contributed to enhance precipitation. This work contributes to a comprehensive and systematic synoptic evaluation of the second most deadly hydro-geomorphologic DISASTER event that has occurred in Portugal since 1865 and will help to better understand the meteorological system that was responsible for triggering the event.

Research Vessel Meteorological and Oceanographic Systems Support Satellite and Model Validation Studies

NASA Astrophysics Data System (ADS)

Smith, S. R.; Lopez, N.; Bourassa, M. A.; Rolph, J.; Briggs, K.

2012-12-01

The research vessel data center at the Florida State University routinely acquires, quality controls, and distributes underway surface meteorological and oceanographic observations from vessels. The activities of the center are coordinated by the Shipboard Automated Meteorological and Oceanographic System (SAMOS) initiative in partnership with the Rolling Deck to Repository (R2R) project. The data center evaluates the quality of the observations, collects essential metadata, provides data quality feedback to vessel operators, and ensures the long-term data preservation at the National Oceanographic Data Center. A description of the SAMOS data stewardship protocols will be provided, including dynamic web tools that ensure users can select the highest quality observations from over 30 vessels presently recruited to the SAMOS initiative. Research vessels provide underway observations at high-temporal frequency (1 min. sampling interval) that include navigational (position, course, heading, and speed), meteorological (air temperature, humidity, wind, surface pressure, radiation, rainfall), and oceanographic (surface sea temperature and salinity) samples. Recruited vessels collect a high concentration of data within the U.S. continental shelf and also frequently operate well outside routine shipping lanes, capturing observations in extreme ocean environments (Southern Ocean, Arctic, South Atlantic and Pacific). The unique quality and sampling locations of research vessel observations and there independence from many models and products (RV data are rarely distributed via normal marine weather reports) makes them ideal for validation studies. We will present comparisons between research vessel observations and model estimates of the sea surface temperature and salinity in the Gulf of Mexico. The analysis reveals an underestimation of the freshwater input to the Gulf from rivers, resulting in an overestimation of near coastal salinity in the model. Additional comparisons between surface atmospheric products derived from satellite observations and the underway research vessel observations will be shown. The strengths and limitations of research observations for validation studies will be highlighted through these case studies.

Identification of Mesoscale Convective Complex (MCC) phenomenon with image of Himawari 8 Satellite and WRF ARW Model on Bangka Island (Case Study: 7-8 February 2016)

NASA Astrophysics Data System (ADS)

Rinaldy, Nanda; Saragih, Immanuel J. A.; Wandala Putra, Agie; Redha Nugraheni, Imma; Wijaya Yonas, Banu

2017-12-01

Based on monitoring on 7th and 8th February 2016 there has been a flood that occurred due to heavy rainfall in a long time in some areas of Bangka Island. Mesoscale Convective Complex (MCC) is one type of Mesoscale Convective System (MCS). Previous research on MCC mentions that MCC can cause heavy rain for a long time. This study aims to identify the phenomenon of MCC in Bangka Island both in the satellite imagery and the output of the model. In addition, this study was also conducted to determine the effect of MCC on the weather conditions in Bangka Island. The study area in this research is Bangka Island with Pangkalpinang Meteorological Station as the centre of research. The data used in this research are FNL (Final Analysis) data from http://rda.ucar.edu/, Satellite Image of Himawari-8 IR1 Channel from BMKG, and meteorological observation data (synoptic and radiosonde) from Pangkalpinang Meteorological Station. The FNL data is simulated using the WRF-ARW model, verified using observation data and then visualized using GrADS. The results of the analysis of Himawari-8 satellite image data showed that two MCCs occurred on 7th and 8th February 2016 on Bangka Island and the MCC was nocturnal, which appeared at night which then continued until extinction in the morning the next day. In a peak cloud temperature review with the coordinates of Pangkalpinang Meteorological Station (-2,163 N 106,137 E) when 1st MCC and 2nd MCC events ranged from -60°C to -80°C. The result of WRF-ARW model output analysis shows that MCC area has high humidity value and positive vertical velocity value which indicates the potential of heavy rain for a long time.

Air pollution and children's asthma-related emergency hospital visits in southeastern France.

PubMed

Mazenq, Julie; Dubus, Jean-Christophe; Gaudart, Jean; Charpin, Denis; Nougairede, Antoine; Viudes, Gilles; Noel, Guilhem

2017-06-01

Children's asthma is multifactorial. Environmental factors like air pollution exposure, meteorological conditions, allergens, and viral infections are strongly implicated. However, place of residence has rarely been investigated in connection with these factors. The primary aim of our study was to measure the impact of particulate matter (PM), assessed close to the children's homes, on asthma-related pediatric emergency hospital visits within the Bouches-du-Rhône area in 2013. In a nested case-control study on 3- to 18-year-old children, each control was randomly matched on the emergency room visit day, regardless of hospital. Each asthmatic child was compared to 15 controls. PM 10 and PM 2.5 , meteorological conditions, pollens, and viral data were linked to ZIP code and analyzed by purpose of emergency visit. A total of 68,897 visits were recorded in children, 1182 concerning asthma. Short-term exposure to PM 10 measured near children's homes was associated with excess risk of asthma emergency visits (adjusted odds ratio 1.02 (95% CI 1.01-1.04; p = 0.02)). Male gender, young age, and temperature were other risk factors. Conversely, wind speed was a protective factor. PM 10 and certain meteorological conditions near children's homes increased the risk of emergency asthma-related hospital visits in 3- to 18-year-old children in Bouches-du-Rhône. What is Known: • A relationship between short-term exposure to air pollution and increase in emergency room visits or hospital admissions as a result of increased pollution levels has already been demonstrated. What is New: • This study confirms these results but took into account confounding factors (viral data, pollens, and meteorological conditions) and is based on estimated pollution levels assessed close to the children's homes, rather than those recorded at the hospital. • The study area, the Mediterranean, is favorable to creation of secondary pollutants in these sunny and dry seasons.

How sensitive are estimates of carbon fixation in agricultural models to input data?

PubMed Central

2012-01-01

Background Process based vegetation models are central to understand the hydrological and carbon cycle. To achieve useful results at regional to global scales, such models require various input data from a wide range of earth observations. Since the geographical extent of these datasets varies from local to global scale, data quality and validity is of major interest when they are chosen for use. It is important to assess the effect of different input datasets in terms of quality to model outputs. In this article, we reflect on both: the uncertainty in input data and the reliability of model results. For our case study analysis we selected the Marchfeld region in Austria. We used independent meteorological datasets from the Central Institute for Meteorology and Geodynamics and the European Centre for Medium-Range Weather Forecasts (ECMWF). Land cover / land use information was taken from the GLC2000 and the CORINE 2000 products. Results For our case study analysis we selected two different process based models: the Environmental Policy Integrated Climate (EPIC) and the Biosphere Energy Transfer Hydrology (BETHY/DLR) model. Both process models show a congruent pattern to changes in input data. The annual variability of NPP reaches 36% for BETHY/DLR and 39% for EPIC when changing major input datasets. However, EPIC is less sensitive to meteorological input data than BETHY/DLR. The ECMWF maximum temperatures show a systematic pattern. Temperatures above 20°C are overestimated, whereas temperatures below 20°C are underestimated, resulting in an overall underestimation of NPP in both models. Besides, BETHY/DLR is sensitive to the choice and accuracy of the land cover product. Discussion This study shows that the impact of input data uncertainty on modelling results need to be assessed: whenever the models are applied under new conditions, local data should be used for both input and result comparison. PMID:22296931

Meteorological and hydrological extremes derived from taxation records: case study for south-western Moravia (Czech Republic)

NASA Astrophysics Data System (ADS)

Chromá, Kateřina; Brázdil, Rudolf; Valášek, Hubert; Zahradníček, Pavel

2013-04-01

Meteorological and hydrological extremes (MHEs) cause great material damage or even loss of human lives in the present time, similarly as it was in the past. In the Czech Lands (recently the Czech Republic), systematic meteorological and hydrological observations started generally in the latter half of the 19th century. Therefore, in order to create long-term series of such extremes, it is necessary to search for other sources of information. Different types of documentary evidence are used in historical climatology and hydrology to find such information. Some of them are related to records connected with taxation system. The taxation system in Moravia allowed farmers to request tax relief if their crops have been damaged by MHEs. The corresponding documents contain information about the type of extreme event and the date of its occurrence; often also impacts on crops or land may be derived. The nature of events leading to damage include particularly hailstorms, torrential rain, flash floods, floods (in regions along larger rivers), less frequently windstorms, late frosts and in some cases also information about droughts or extreme snow depths. However, the results obtained are influenced by uncertainties related to taxation records - their temporal and spatial incompleteness, limitation of the MHEs occurrence in the period of main agricultural work (May-August) and the purpose for which they were originally collected (primarily tax alleviation, i.e. information about MHEs was of secondary importance). All these aspects related to the study of MHEs from taxation records are demonstrated for five estates (Bítov, Budkov, Jemnice with Staré Hobzí, Nové Syrovice and Uherčice) in the south-western part of Moravia for the 18th-19th centuries. The analysis shows importance of taxation records for the study of past MHEs as well as great potential for their use.

Calculation of new snow densities from sub-daily automated snow measurements

NASA Astrophysics Data System (ADS)

Helfricht, Kay; Hartl, Lea; Koch, Roland; Marty, Christoph; Lehning, Michael; Olefs, Marc

2017-04-01

In mountain regions there is an increasing demand for high-quality analysis, nowcasting and short-range forecasts of the spatial distribution of snowfall. Operational services, such as for avalanche warning, road maintenance and hydrology, as well as hydropower companies and ski resorts need reliable information on the depth of new snow (HN) and the corresponding water equivalent (HNW). However, the ratio of HNW to HN can vary from 1:3 to 1:30 because of the high variability of new snow density with respect to meteorological conditions. In the past, attempts were made to calculate new snow densities from meteorological parameters mainly using daily values of temperature and wind. Further complex statistical relationships have been used to calculate new snow densities on hourly to sub-hourly time intervals to drive multi-layer snow cover models. However, only a few long-term in-situ measurements of new snow density exist for sub-daily time intervals. Settling processes within the new snow due to loading and metamorphism need to be considered when computing new snow density. As the effect of these processes is more pronounced for long time intervals, a high temporal resolution of measurements is desirable. Within the pluSnow project data of several automatic weather stations with simultaneous measurements of precipitation (pluviometers), snow water equivalent (SWE) using snow pillows and snow depth (HS) measurements using ultrasonic rangers were analysed. New snow densities were calculated for a set of data filtered on the basis of meteorological thresholds. The calculated new snow densities were compared to results from existing new snow density parameterizations. To account for effects of settling of the snow cover, a case study based on a multi-year data set using the snow cover model SNOWPACK at Weissfluhjoch was performed. Measured median values of hourly new snow densities at the different stations range from 54 to 83 kgm-3. This is considerably lower than a 1:10 approximation (i.e. 100 kgm-3), which is mainly based on daily values in the Alps. Variations in new snow density could not be explained in a satisfactory manner using meteorological data measured at the same location. Likewise, some of the tested parametrizations of new snow density, which primarily use air temperature as a proxy, result in median new snow densities close to the ones from automated measurements, but show only a low correlation between calculated and measured new snow densities. The case study on the influence of snow settling on HN resulted on average in an underestimation of HN by 17%, which corresponds to 2-3% of the cumulated HN from the previous 24 hours. Therefore, the mean hourly new snow densities may be overestimated by 14%. The analysis in this study is especially limited with respect to the meteorological influence on the HS measurement using ultra-sonic rangers. Nevertheless, the reasonable mean values encourage calculating new snow densities from standard hydro-meteorological measurements using more precise observation devices such as optical snow depth sensors and more sensitive scales for SWE measurements also on sub-daily time-scales.

Multimodel hydrological ensemble forecasts for the Baskatong catchment in Canada using the TIGGE database.

NASA Astrophysics Data System (ADS)

Tito Arandia Martinez, Fabian

2014-05-01

Adequate uncertainty assessment is an important issue in hydrological modelling. An important issue for hydropower producers is to obtain ensemble forecasts which truly grasp the uncertainty linked to upcoming streamflows. If properly assessed, this uncertainty can lead to optimal reservoir management and energy production (ex. [1]). The meteorological inputs to the hydrological model accounts for an important part of the total uncertainty in streamflow forecasting. Since the creation of the THORPEX initiative and the TIGGE database, access to meteorological ensemble forecasts from nine agencies throughout the world have been made available. This allows for hydrological ensemble forecasts based on multiple meteorological ensemble forecasts. Consequently, both the uncertainty linked to the architecture of the meteorological model and the uncertainty linked to the initial condition of the atmosphere can be accounted for. The main objective of this work is to show that a weighted combination of meteorological ensemble forecasts based on different atmospheric models can lead to improved hydrological ensemble forecasts, for horizons from one to ten days. This experiment is performed for the Baskatong watershed, a head subcatchment of the Gatineau watershed in the province of Quebec, in Canada. Baskatong watershed is of great importance for hydro-power production, as it comprises the main reservoir for the Gatineau watershed, on which there are six hydropower plants managed by Hydro-Québec. Since the 70's, they have been using pseudo ensemble forecast based on deterministic meteorological forecasts to which variability derived from past forecasting errors is added. We use a combination of meteorological ensemble forecasts from different models (precipitation and temperature) as the main inputs for hydrological model HSAMI ([2]). The meteorological ensembles from eight of the nine agencies available through TIGGE are weighted according to their individual performance and combined to form a grand ensemble. Results show that the hydrological forecasts derived from the grand ensemble perform better than the pseudo ensemble forecasts actually used operationally at Hydro-Québec. References: [1] M. Verbunt, A. Walser, J. Gurtz et al., "Probabilistic flood forecasting with a limited-area ensemble prediction system: Selected case studies," Journal of Hydrometeorology, vol. 8, no. 4, pp. 897-909, Aug, 2007. [2] N. Evora, Valorisation des prévisions météorologiques d'ensemble, Institu de recherceh d'Hydro-Québec 2005. [3] V. Fortin, Le modèle météo-apport HSAMI: historique, théorie et application, Institut de recherche d'Hydro-Québec, 2000.

Effectiveness of submerged drains in reducing subsidence of peat soils in agricultural use, and their effects on water management and nutrient loading of surface water: modelling of a case study in the western peat soil area of The Netherlands

NASA Astrophysics Data System (ADS)

Hendriks, Rob F. A.; van den Akker, Jan J. A.

2017-04-01

Effectiveness of submerged drains in reducing subsidence of peat soils in agricultural use, and their effects on water management and nutrient loading of surface water: modelling of a case study in the western peat soil area of The Netherlands In the Netherlands, about 8% of the area is covered by peat soils. Most of these soils are in use for dairy farming and, consequently, are drained. Drainage causes decomposition of peat by oxidation and accordingly leads to surface subsidence and greenhouse gas emission. Submerged drains that enhance submerged infiltration of water from ditches during the dry and warm summer half year were, and are still, studied in The Netherlands as a promising tool for reducing peat decomposition by raising groundwater levels. For this purpose, several pilot field studies in the Western part of the Dutch peat area were conducted. Besides the effectiveness of submerged drains in reducing peat decomposition and subsidence by raising groundwater tables, some other relevant or expected effects of these drains were studied. Most important of these are water management and loading of surface water with nutrients nitrogen, phosphorus and sulphate. Because most of these parameters are not easy to assess and all of them are strongly depending on the meteorological conditions during the field studies some of these studies were modelled. The SWAP model was used for evaluating the hydrological results on groundwater table and water discharge and recharge. Effects of submerged drains were assessed by comparing the results of fields with and without drains. An empirical relation between deepest groundwater table and subsidence was used to convert effects on groundwater table to effects on subsidence. With the SWAP-ANIMO model nutrient loading of surface water was modelled on the basis of field results on nutrient concentrations . Calibrated models were used to assess effects in the present situation, as thirty-year averages, under extreme weather conditions and for two extreme climate scenarios of the Royal Netherlands Meteorological Institute. In this study the model results of one of the pilot studies are presented. The case study 'de Krimpenerwaard' is situated in the peat area in the "Green Heart" between the major cities of Amsterdam, The Hague, Rotterdam and Utrecht. Model results show a halving of soil subsidence, a strong increase of water recharge but a lower increase of water discharge, and generally small to moderate effects on nutrient loading , all depending (strongly) on meteorological conditions.

Meteorological conditions during the formation of ice on aircraft

NASA Technical Reports Server (NTRS)

Samuels, L T

1932-01-01

These are the results of a number of records recently secured from autographic meteorological instruments mounted on airplanes at times when ice formed. Ice is found to collect on an airplane only when the airplane is in some form of visible moisture, such as cloud, fog, mist, rain. etc., and the air temperature is within certain critical limits. Described here are the characteristics of clear ice and rime ice and the specific types of hazards they present to airplanes and lighter than air vehicles. The weather records are classified according to the two general types of formation (clear ice and rime) together with the respective temperatures, relative humidities, clouds, and elevations above ground at which formations occurred. This classification includes 108 cases where rime formed, 43 cases in which clear ice formed, and 4 cases when both rime and clear ice formed during the same flight. It is evident from the above figures that there was a preponderance of rime by the ratio of 2.5 to 1, while in only a few cases both types of ice formation occurred during the same flight.

Mesoscale acid deposition modeling studies

NASA Technical Reports Server (NTRS)

Kaplan, Michael L.; Proctor, F. H.; Zack, John W.; Karyampudi, V. Mohan; Price, P. E.; Bousquet, M. D.; Coats, G. D.

1989-01-01

The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts.

Analysis of a solar PV/battery/DG set-based hybrid system for a typical telecom load: a case study

NASA Astrophysics Data System (ADS)

Iqbal, A.; Arif, M. Saad Bin; Ayob, Shahrin Md; Siddiqui, Khursheed

2017-03-01

This paper analyses the technical and economic feasibility of using a hybrid renewable energy source for a typical telecom load in the state of Qatar. The hybrid system considered in this work consists of a solar photovoltaic with storage battery and diesel generator set. For this particular hybrid system, the meteorological data of solar irradiance in Doha city (latitude 25.15 ° North and longitude 51.33 ° East) are taken from NASA surface meteorology and solar energy websites. The solar irradiance in Doha is 5.33 kWh/m2/day on an annual average scale. The data are also taken through the study of load consumption of Qatar telecommunication hybrid power system. The system is designed and its techno-economic analysis is carried out using the Hybrid Optimization Model for Electrical Renewable software. The results show both technical and economic viability of replacing the conventional DG sets with the proposed renewable energy source.

Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila, Philippines.

PubMed

Carvajal, Thaddeus M; Viacrusis, Katherine M; Hernandez, Lara Fides T; Ho, Howell T; Amalin, Divina M; Watanabe, Kozo

2018-04-17

Several studies have applied ecological factors such as meteorological variables to develop models and accurately predict the temporal pattern of dengue incidence or occurrence. With the vast amount of studies that investigated this premise, the modeling approaches differ from each study and only use a single statistical technique. It raises the question of whether which technique would be robust and reliable. Hence, our study aims to compare the predictive accuracy of the temporal pattern of Dengue incidence in Metropolitan Manila as influenced by meteorological factors from four modeling techniques, (a) General Additive Modeling, (b) Seasonal Autoregressive Integrated Moving Average with exogenous variables (c) Random Forest and (d) Gradient Boosting. Dengue incidence and meteorological data (flood, precipitation, temperature, southern oscillation index, relative humidity, wind speed and direction) of Metropolitan Manila from January 1, 2009 - December 31, 2013 were obtained from respective government agencies. Two types of datasets were used in the analysis; observed meteorological factors (MF) and its corresponding delayed or lagged effect (LG). After which, these datasets were subjected to the four modeling techniques. The predictive accuracy and variable importance of each modeling technique were calculated and evaluated. Among the statistical modeling techniques, Random Forest showed the best predictive accuracy. Moreover, the delayed or lag effects of the meteorological variables was shown to be the best dataset to use for such purpose. Thus, the model of Random Forest with delayed meteorological effects (RF-LG) was deemed the best among all assessed models. Relative humidity was shown to be the top-most important meteorological factor in the best model. The study exhibited that there are indeed different predictive outcomes generated from each statistical modeling technique and it further revealed that the Random forest model with delayed meteorological effects to be the best in predicting the temporal pattern of Dengue incidence in Metropolitan Manila. It is also noteworthy that the study also identified relative humidity as an important meteorological factor along with rainfall and temperature that can influence this temporal pattern.

Solar Occultation Satellite Data and Derived Meteorological Products: Sampling Issues and Comparisons with Aura MLS

NASA Technical Reports Server (NTRS)

Manney, Gloria; Daffer, William H.; Zawodny, Joseph M.; Bernath, Peter F.; Hoppel, Karl W.; Walker, Kaley A.; Knosp, Brian W.; Boone, Chris; Remsberg, Ellis E.; Santee, Michelle L.;

Spatial Analysis of Severe Fever with Thrombocytopenia Syndrome Virus in China Using a Geographically Weighted Logistic Regression Model

PubMed Central

Wu, Liang; Deng, Fei; Xie, Zhong; Hu, Sheng; Shen, Shu; Shi, Junming; Liu, Dan

2016-01-01

Severe fever with thrombocytopenia syndrome (SFTS) is caused by severe fever with thrombocytopenia syndrome virus (SFTSV), which has had a serious impact on public health in parts of Asia. There is no specific antiviral drug or vaccine for SFTSV and, therefore, it is important to determine the factors that influence the occurrence of SFTSV infections. This study aimed to explore the spatial associations between SFTSV infections and several potential determinants, and to predict the high-risk areas in mainland China. The analysis was carried out at the level of provinces in mainland China. The potential explanatory variables that were investigated consisted of meteorological factors (average temperature, average monthly precipitation and average relative humidity), the average proportion of rural population and the average proportion of primary industries over three years (2010–2012). We constructed a geographically weighted logistic regression (GWLR) model in order to explore the associations between the selected variables and confirmed cases of SFTSV. The study showed that: (1) meteorological factors have a strong influence on the SFTSV cover; (2) a GWLR model is suitable for exploring SFTSV cover in mainland China; (3) our findings can be used for predicting high-risk areas and highlighting when meteorological factors pose a risk in order to aid in the implementation of public health strategies. PMID:27845737

Systematic review of the association between climate and hip fractures

NASA Astrophysics Data System (ADS)

Román Ortiz, Carmen; Tenías, José María; Estarlich, Marisa; Ballester, Ferran

2015-10-01

This study aims to systematically review epidemiological studies that evaluate the relationship between meteorology and the incidence of hip fracture (HF). After a search in Scopus, PubMed, and Embase, two independent authors assessed the relevance of studies and extracted data for description. From each study, we extracted the geographic and temporal scope, design, study variables (meteorological and related to HF), statistical analysis, and estimated associations. Of a total of 134 works, 20 studies were selected. All use an ecological design but one case-crossover. Most studies have been conducted in northern latitudes. The analysis methodology did not take into account the temporal structure of the data in 10 studies (regression and linear correlations); the rest used Poisson regression (7) and ARIMA model (3). Most studies showed significant positive associations with rainfall, especially in the form of snow: HF relative risk (RR) on days with precipitation vs. days without precipitation that ranged from 1.14 (95 % confidence interval (CI)1.04 to 1.24) to 1.60 (95 % CI 1.06 to 2.41), the temperature, with RR by one degree Celsius decline from 1.012 (95 % CI 1.004 to 1.020) to 1.030 (95 % CI 1.023 to 1.037), and wind (3) RR FC windiest days vs. calm days: 1.32 (95 % CI 1.10 to 1.58) to 1.35 (95 % CI 0.88 to 2.08). This review shows that analytic methods are very heterogeneous and poorly adapted to the temporary nature of the data. Studies confirm a certain seasonality, with more fractures in winter and meaningful relationships with meteorological conditions typical of this season.

How is rainfall interception in urban area affected by meteorological parameters?

NASA Astrophysics Data System (ADS)

Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

2017-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be relatively high in case of very low wind speeds.

Meteorologically Driven Simulations of Dengue Epidemics in San Juan, PR

PubMed Central

Morin, Cory W.; Monaghan, Andrew J.; Hayden, Mary H.; Barrera, Roberto; Ernst, Kacey

2015-01-01

Meteorological factors influence dengue virus ecology by modulating vector mosquito population dynamics, viral replication, and transmission. Dynamic modeling techniques can be used to examine how interactions among meteorological variables, vectors and the dengue virus influence transmission. We developed a dengue fever simulation model by coupling a dynamic simulation model for Aedes aegypti, the primary mosquito vector for dengue, with a basic epidemiological Susceptible-Exposed-Infectious-Recovered (SEIR) model. Employing a Monte Carlo approach, we simulated dengue transmission during the period of 2010–2013 in San Juan, PR, where dengue fever is endemic. The results of 9600 simulations using varied model parameters were evaluated by statistical comparison (r2) with surveillance data of dengue cases reported to the Centers for Disease Control and Prevention. To identify the most influential parameters associated with dengue virus transmission for each period the top 1% of best-fit model simulations were retained and compared. Using the top simulations, dengue cases were simulated well for 2010 (r2 = 0.90, p = 0.03), 2011 (r2 = 0.83, p = 0.05), and 2012 (r2 = 0.94, p = 0.01); however, simulations were weaker for 2013 (r2 = 0.25, p = 0.25) and the entire four-year period (r2 = 0.44, p = 0.002). Analysis of parameter values from retained simulations revealed that rain dependent container habitats were more prevalent in best-fitting simulations during the wetter 2010 and 2011 years, while human managed (i.e. manually filled) container habitats were more prevalent in best-fitting simulations during the drier 2012 and 2013 years. The simulations further indicate that rainfall strongly modulates the timing of dengue (e.g., epidemics occurred earlier during rainy years) while temperature modulates the annual number of dengue fever cases. Our results suggest that meteorological factors have a time-variable influence on dengue transmission relative to other important environmental and human factors. PMID:26275146

Thunderstorm asthma: an overview of the evidence base and implications for public health advice.

PubMed

Dabrera, G; Murray, V; Emberlin, J; Ayres, J G; Collier, C; Clewlow, Y; Sachon, P

2013-03-01

Thunderstorm asthma is a term used to describe an observed increase in acute bronchospasm cases following the occurrence of thunderstorms in the local vicinity. The roles of accompanying meteorological features and aeroallergens, such as pollen grains and fungal spores, have been studied in an effort to explain why thunderstorm asthma does not accompany all thunderstorms. Despite published evidence being limited and highly variable in quality due to thunderstorm asthma being a rare event, this article reviews this evidence in relation to the role of aeroallergens, meteorological features and the impact of thunderstorm asthma on health services. This review has found that several thunderstorm asthma events have had significant impacts on individuals' health and health services with a range of different aeroallergens identified. This review also makes recommendations for future public health advice relating to thunderstorm asthma on the basis of this identified evidence.

Improvised Nuclear Device Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buddemeier, Brooke; Suski, Nancy

2011-07-12

Reducing the casualties of catastrophic terrorist attacks requires an understanding of weapons of mass destruction (WMD) effects, infrastructure damage, atmospheric dispersion, and health effects. The Federal Planning Guidance for Response to a Nuclear Detonation provides the strategy for response to an improvised nuclear device (IND) detonation. The supporting science developed by national laboratories and other technical organizations for this document significantly improves our understanding of the hazards posed by such an event. Detailed fallout predictions from the advanced suite of three-dimensional meteorology and plume/fallout models developed at Lawrence Livermore National Laboratory, including extensive global geographical and real-time meteorological databases tomore » support model calculations, are a key part of response planning. This presentation describes the methodology and results to date, including visualization aids developed for response organizations. These products have greatly enhanced the community planning process through first-person points of view and description of the dynamic nature of the event.« less

Atmospheric transport of radioactive debris to Norway in case of a hypothetical accident related to the recovery of the Russian submarine K-27.

PubMed

Bartnicki, Jerzy; Amundsen, Ingar; Brown, Justin; Hosseini, Ali; Hov, Øystein; Haakenstad, Hilde; Klein, Heiko; Lind, Ole Christian; Salbu, Brit; Szacinski Wendel, Cato C; Ytre-Eide, Martin Album

2016-01-01

The Russian nuclear submarine K-27 suffered a loss of coolant accident in 1968 and with nuclear fuel in both reactors it was scuttled in 1981 in the outer part of Stepovogo Bay located on the eastern coast of Novaya Zemlya. The inventory of spent nuclear fuel on board the submarine is of concern because it represents a potential source of radioactive contamination of the Kara Sea and a criticality accident with potential for long-range atmospheric transport of radioactive particles cannot be ruled out. To address these concerns and to provide a better basis for evaluating possible radiological impacts of potential releases in case a salvage operation is initiated, we assessed the atmospheric transport of radionuclides and deposition in Norway from a hypothetical criticality accident on board the K-27. To achieve this, a long term (33 years) meteorological database has been prepared and used for selection of the worst case meteorological scenarios for each of three selected locations of the potential accident. Next, the dispersion model SNAP was run with the source term for the worst-case accident scenario and selected meteorological scenarios. The results showed predictions to be very sensitive to the estimation of the source term for the worst-case accident and especially to the sizes and densities of released radioactive particles. The results indicated that a large area of Norway could be affected, but that the deposition in Northern Norway would be considerably higher than in other areas of the country. The simulations showed that deposition from the worst-case scenario of a hypothetical K-27 accident would be at least two orders of magnitude lower than the deposition observed in Norway following the Chernobyl accident. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Meteorology Assessment of Historic Rainfall for Los Alamos During September 2013

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruggeman, David Alan; Dewart, Jean Marie

2016-02-12

DOE Order 420.1, Facility Safety, requires that site natural phenomena hazards be evaluated every 10 years to support the design of nuclear facilities. The evaluation requires calculating return period rainfall to determine roof loading requirements and flooding potential based on our on-site rainfall measurements. The return period rainfall calculations are done based on statistical techniques and not site-specific meteorology. This and future studies analyze the meteorological factors that produce the significant rainfall events. These studies provide the meteorology context of the return period rainfall events.

Prototype Local Data Integration System and Central Florida Data Deficiency

NASA Technical Reports Server (NTRS)

Manobianco, John; Case, Jonathan

1998-01-01

This report describes the Applied Meteorology Unit's (AMU) task on the Local Data Integration System (LDIS) and central Florida data deficiency. The objectives of the task are to identify all existing meteorological data sources within 250 km of the Kennedy Space Center (KSC) and the Eastern Range at Cape Canaveral Air Station (CCAS), identify and configure an appropriate LDIS to integrate these data, and implement a working prototype to be used for limited case studies and data non-incorporation (DNI) experiments. The ultimate goal for running LDIS is to generate products that may enhance weather nowcasts and short-range (less than 6 h) forecasts issued in support of the 45th Weather Squadron (45 WS), Spaceflight Meteorology Group (SMG), and the Melbourne National Weather Service (NWS MLB) operational requirements. The LDIS has the potential to provide added value for nowcasts and short term forecasts for two reasons. First, it incorporates all data operationally available in east central Florida. Second, it is run at finer spatial and temporal resolutions than current national-scale operational models. In combination with a suitable visualization tool, LDIS may provide users with a more complete and comprehensive understanding of evolving fine-scale weather features than could be developed by individually examining the disparate data sets over the same area and time. The utility of LDIS depends largely on the reliability and availability of observational data. Therefore, it is important to document all existing meteorological data sources around central Florida that can be incorporated by it. Several factors contribute to the data density and coverage over east central Florida including the level in the atmosphere, distance from KSC/CCAS, time, and prevailing weather. The central Florida mesonet consists of existing surface meteorological and hydrological data available from the Tampa NWS and data servers at Miami and Jacksonville. However the utility of these data for operational use is limited, mainly because there are relatively few additional meteorological observations within 50 km of KSC/CCAS to supplement existing METAR and KSC/CCAS tower reports.

Synoptic versus regional causes of icing on wind turbines at an exposed wind farm site in Germany

NASA Astrophysics Data System (ADS)

Weissinger, Maximilian; Strauss, Lukas; Serafin, Stefano; Dorninger, Manfred; Burchhart, Thomas; Fink, Martin

2017-04-01

Ice accretion on wind turbine blades can lead to significant power production loss or even permanent structural damage on the turbine. With the ongoing construction of wind farms at sites with increased icing potential in cold climates, accurate icing predictions are needed to optimise power plant operation. To this end, the frequency of occurrence and the causes of meteorological icing need to be better understood. The project ICE CONTROL, an Austrian research initiative, aims to improve icing forecasts through measurements, probabilistic forecasting, and verification of icing on wind turbine blades. The project focuses on a wind farm site near Ellern, Germany, located on the Hunsrück, a hilly terrain rising above the surrounding plain by 200-300 metres. Production data from the last three winters show that icing events tend to occur more often at the wind turbines on top of the highest hills. The present study aims to investigate historical cases of wind turbine icing and their meteorological causes at the Ellern wind farm. The data available consists of a three-year period (2013-2016) of operational data from the Ellern wind farm as well as meteorological measurements at nearby stations operated by the German Weather Service (DWD). In addition, radiosondes and weather charts are taken into account. The main objective of this work is, first, to link the local and regional weather conditions to larger-scale weather patterns and prevailing air masses, and second, to determine the types of icing (in-cloud vs. freezing precipation). Results show that in most icing cases the cloud base height was below the hub height while the temperature was just below the freezing point. Precipitation was absent in most cases. This suggests that most of the observed icing events were due to in-cloud icing. Icing conditions occurred often (but not exclusively) under specific synoptic-scale weather conditions, such as north-westerly flow advecting maritime polar air masses to Central Europe. In other cases, icing events were favoured by the development of low-level thermal inversions during weak south-easterly flow conditions.

Does a more skilful meteorological input lead to a more skilful flood forecast at seasonal timescales?

NASA Astrophysics Data System (ADS)

Neumann, Jessica; Arnal, Louise; Magnusson, Linus; Cloke, Hannah

2017-04-01

Seasonal river flow forecasts are important for many aspects of the water sector including flood forecasting, water supply, hydropower generation and navigation. In addition to short term predictions, seasonal forecasts have the potential to realise higher benefits through more optimal and consistent decisions. Their operational use however, remains a challenge due to uncertainties posed by the initial hydrologic conditions (e.g. soil moisture, groundwater levels) and seasonal climate forcings (mainly forecasts of precipitation and temperature), leading to a decrease in skill with increasing lead times. Here we present a stakeholder-led case study for the Thames catchment (UK), currently being undertaken as part of the H2020 IMPREX project. The winter of 2013-14 was the wettest on record in the UK; driven by 12 major Atlantic depressions, the Thames catchment was subject to compound (concurrent) flooding from fluvial and groundwater sources. Focusing on the 2013-14 floods, this study aims to see whether increased skill in meteorological input translates through to more accurate forecasting of compound flood events at seasonal timescales in the Thames catchment. An earlier analysis of the ECMWF System 4 (S4) seasonal meteorological forecasts revealed that it did not skilfully forecast the extreme event of winter 2013-14. This motivated the implementation of an atmospheric experiment by the ECMWF to force the S4 to more accurately represent the low-pressure weather conditions prevailing in winter 2013-14 [1]. Here, we used both the standard and the "improved" S4 seasonal meteorological forecasts to force the EFAS (European Flood Awareness System) LISFLOOD hydrological model. Both hydrological forecasts were started on the 1st of November 2013 and run for 4 months of lead time to capture the peak of the 2013-14 flood event. Comparing the seasonal hydrological forecasts produced with both meteorological forcing data will enable us to assess how the improved meteorology translates into skill in the hydrological forecast for this extreme compound event. As primary stakeholders involved in the study, the Environment Agency and Flood Forecasting Centre are responsible for managing flood risk in the UK. For them, the detection of a potential flood signal weeks or months in advance could be of great value in terms of operational practice, decision-making and early warning. [1] Rodwell, M.J., Ferranti, L., Magnusson, L., Weisheimer, A., Rabier, F. & Richardson, D. (2015) Diagnosis of northern hemispheric regime behaviour during winter 2013/14. ECMWF Technical Memoranda 769.

Numerical Modeling Studies of Wake Vortices: Real Case Simulations

NASA Technical Reports Server (NTRS)

Shen, Shao-Hua; Ding, Feng; Han, Jongil; Lin, Yuh-Lang; Arya, S. Pal; Proctor, Fred H.

1999-01-01

A three-dimensional large-eddy simulation model, TASS, is used to simulate the behavior of aircraft wake vortices in a real atmosphere. The purpose for this study is to validate the use of TASS for simulating the decay and transport of wake vortices. Three simulations are performed and the results are compared with the observed data from the 1994-1995 Memphis field experiments. The selected cases have an atmospheric environment of weak turbulence and stable stratification. The model simulations are initialized with appropriate meteorological conditions and a post roll-up vortex system. The behavior of wake vortices as they descend within the atmospheric boundary layer and interact with the ground is discussed.

Utilization of Meteorological Satellite Imagery for World-Wide Environmental Monitoring the Lower Mississippi River Flood of 1979 - Case 1. [St. Louis, Missouri

NASA Technical Reports Server (NTRS)

Helfert, M. R.; Mccrary, D. G.; Gray, T. I. (Principal Investigator)

1981-01-01

The 1979 Lower Mississippi River flood was selected as a test case of environmental disaster monitoring utilizing NOAA-n imagery. A small scale study of the St. Louis Missouri area comparing ERTS-1 (LANDSAT) and NOAA-2 imagery and flood studies using only LANDSAT imagery for mapping the Rad River of the North, and Nimbus-5 imagery for East Australia show the nonmeteorological applications of NOAA satellites. While the level of NOAA-n imagery detail is not that of a LANDSAT image, for operational environmental monitoring users the NOAA-n imagery may provide acceptable linear resolution and spectral isolation.

Applications of the TIROS-N sounding and cloud motion wind enhancement for the FGGE 'special effort'. [Global Weather Experiment

NASA Technical Reports Server (NTRS)

Atlas, R.

1980-01-01

In January of 1978, a panel of experts recommended that a 'special effort' be made to enhance and edit satellite soundings and cloud tracked winds in data sparse regions. It was felt that these activities would be necessary to obtain maximum benefits from an evaluation of satellite data during the Global Weather Experiment (FGGE). The 'special effort' is being conducted for the two special observing periods of FGGE. More than sixty cases have been selected for enhancement on the basis of meteorological interest. These cases include situations of blocking, cutoff low development, cyclogenesis, and tropical circulations. The sounding data enhancement process consists of supplementing the operational satellite sounding data set with higher resolution soundings in meteorologically active regions, and with new soundings where data voids or soundings of questionable quality exist.

Meteorological Influences on the Seasonality of Lyme Disease in the United States

PubMed Central

Moore, Sean M.; Eisen, Rebecca J.; Monaghan, Andrew; Mead, Paul

2014-01-01

Lyme disease (Borrelia burgdorferi infection) is the most common vector-transmitted disease in the United States. The majority of human Lyme disease (LD) cases occur in the summer months, but the timing of the peak occurrence varies geographically and from year to year. We calculated the beginning, peak, end, and duration of the main LD season in 12 highly endemic states from 1992 to 2007 and then examined the association between the timing of these seasonal variables and several meteorological variables. An earlier beginning to the LD season was positively associated with higher cumulative growing degree days through Week 20, lower cumulative precipitation, a lower saturation deficit, and proximity to the Atlantic coast. The timing of the peak and duration of the LD season were also associated with cumulative growing degree days, saturation deficit, and cumulative precipitation, but no meteorological predictors adequately explained the timing of the end of the LD season. PMID:24470565

Meteorological and air pollution modeling for an urban airport

NASA Technical Reports Server (NTRS)

Swan, P. R.; Lee, I. Y.

1980-01-01

Results are presented of numerical experiments modeling meteorology, multiple pollutant sources, and nonlinear photochemical reactions for the case of an airport in a large urban area with complex terrain. A planetary boundary-layer model which predicts the mixing depth and generates wind, moisture, and temperature fields was used; it utilizes only surface and synoptic boundary conditions as input data. A version of the Hecht-Seinfeld-Dodge chemical kinetics model is integrated with a new, rapid numerical technique; both the San Francisco Bay Area Air Quality Management District source inventory and the San Jose Airport aircraft inventory are utilized. The air quality model results are presented in contour plots; the combined results illustrate that the highly nonlinear interactions which are present require that the chemistry and meteorology be considered simultaneously to make a valid assessment of the effects of individual sources on regional air quality.

NASA aviation safety reporting system

NASA Technical Reports Server (NTRS)

1977-01-01

A decline in reports concerning small aircraft was noted; more reports involved transport aircraft, professional pilots, instrument meteorological conditions, and weather problems. A study of 136 reports of operational problems in terminal radar service areas was made. Pilot, controller, and system factors were found to be associated with these occurrences. Information transfer difficulties were prominent. Misunderstandings by pilots, and in some cases by controllers, of the policies and limitations of terminal radar programs were observed.

Conflicts of Shared Resources: A Case Study of River Nile

DTIC Science & Technology

2012-03-22

as Lake Kivu. Rwanda joined the earlier Nile basin project, Hydromet , in 1967, with the support on the UNDP. 18 Although the country does not...operation Hydromet . In 1967, with the assistance of the United Nations Development Program (UNDP) and the World Meteorological Organization (WMO), Egypt...Kenya, Sudan, Tanzania and Uganda launched the Hydromet Survey project to regulate the water level of the Nile.”30 Rwanda joined later while Ethiopia

Development of a fine scale smoke dispersion modeling system. Part II: Case study of a prescribed burn in the New Jersey Pine Barrens

Treesearch

Michael T. Kiefer; Warren E. Heilman; Shiyuan Zhong; Joseph J. Charney; X. Bian; Ryan P. Shadbolt; John Hom; Kenneth Clark; Nicholas Skowronski; Michael Gallagher; Matthew Patterson

2011-01-01

Smoke dispersion from wildland fires is a critical health and safety issue, impacting air quality and visibility across a broad range of space and time scales. Predicting the dispersion of smoke from low-intensity fires is particularly challenging due to the fact that it is highly sensitive to factors such as near-surface meteorological conditions, local topography,...

The association between the incidence of mumps and meteorological parameters in Taiwan

PubMed Central

Ho, Yi-Chien; Su, Bo-Hua; Su, Huey-Jen; Chang, Hsiao-Ling; Lin, Chuan-Yao; Chen, Huifen; Chen, Kow-Tong

2015-01-01

Mumps is caused by a paramyxovirus. It is an acute, but mild infectious disease. However, approximately 10% of patients with mumps can develop severe meningoencephalitis, disability, and death. Seasonal patterns in mumps vary across countries, but the reasons for this phenomenon remain unclear. The aim of this study was to assess the role of meteorological factors on mumps infection. We investigated the relationships between weather variability and the incidence of mumps in Taiwan using a Poisson regression analysis and case-crossover methodology. Between 2006 and 2011, 6,612 cases of mumps were reported to the Centers for Disease Control, Taiwan (Taiwan CDC). The incidence of mumps showed a significant seasonality in summertime (for oscillation, P < 0.001). The number of mumps started to increase at temperatures of 20°C (r2 = 0.73, P < 0.001), and the case count of mumps began to decline when the temperatures were higher than approximately 25°C (r2 = 0.24, p = 0.04), producing an inverted V-shaped relationship. Similarly, the number of mumps began to increase at a vapor pressure of 5–9 hPa (r2 = 0.87, P < 0.005) and decreased at a vapor pressure higher than 25–29 hPa (r2 = 0.21, p = 0.05). The number of mumps cases was positively associated with temperature and vapor pressure in the preceding period of the infection. In conclusion, this study showed that the occurrence of mumps is significantly associated with increasing temperature and vapor pressure in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures. PMID:25891825

The association between the incidence of mumps and meteorological parameters in Taiwan.

PubMed

Ho, Yi-Chien; Su, Bo-Hua; Su, Huey-Jen; Chang, Hsiao-Ling; Lin, Chuan-Yao; Chen, Huifen; Chen, Kow-Tong

2015-01-01

Mumps is caused by a paramyxovirus. It is an acute, but mild infectious disease. However, approximately 10% of patients with mumps can develop severe meningoencephalitis, disability, and death. Seasonal patterns in mumps vary across countries, but the reasons for this phenomenon remain unclear. The aim of this study was to assess the role of meteorological factors on mumps infection. We investigated the relationships between weather variability and the incidence of mumps in Taiwan using a Poisson regression analysis and case-crossover methodology. Between 2006 and 2011, 6,612 cases of mumps were reported to the Centers for Disease Control, Taiwan (Taiwan CDC). The incidence of mumps showed a significant seasonality in summertime (for oscillation, P < 0.001). The number of mumps started to increase at temperatures of 20°C (r(2) = 0.73, P < 0.001), and the case count of mumps began to decline when the temperatures were higher than approximately 25°C (r(2) = 0.24, p = 0.04), producing an inverted V-shaped relationship. Similarly, the number of mumps began to increase at a vapor pressure of 5-9 hPa (r(2) = 0.87, P < 0.005) and decreased at a vapor pressure higher than 25-29 hPa (r(2) = 0.21, p = 0.05). The number of mumps cases was positively associated with temperature and vapor pressure in the preceding period of the infection. In conclusion, this study showed that the occurrence of mumps is significantly associated with increasing temperature and vapor pressure in Taiwan. Therefore, these factors could be regarded as warning signals indicating the need to implement preventive measures.

The cross wavelet analysis of dengue fever variability influenced by meteorological conditions

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung; Lee, Chieh-Han

2015-04-01

The multiyear variation of meteorological conditions induced by climate change causes the changing diffusion pattern of infectious disease and serious epidemic situation. Among them, dengue fever is one of the most serious vector-borne diseases distributed in tropical and sub-tropical regions. Dengue virus is transmitted by several species of mosquito and causing lots amount of human deaths every year around the world. The objective of this study is to investigate the impact of meteorological variables to the temporal variation of dengue fever epidemic in southern Taiwan. Several extreme and average indices of meteorological variables, i.e. temperature and humidity, were used for this analysis, including averaged, maximum and minimum temperature, and average rainfall, maximum 1-hr rainfall, and maximum 24-hr rainfall. This study plans to identify and quantify the nonlinear relationship of meteorological variables and dengue fever epidemic, finding the non-stationary time-frequency relationship and phase lag effects of those time series from 1998-2011 by using cross wavelet method. Results show that meteorological variables all have a significant time-frequency correlation region to dengue fever epidemic in frequency about one year (52 weeks). The associated phases can range from 0 to 90 degrees (0-13 weeks lag from meteorological factors to dengue incidences). Keywords: dengue fever, cross wavelet analysis, meteorological factor

The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models

PubMed Central

Mahara, Gehendra; Wang, Chao; Yang, Kun; Chen, Sipeng; Guo, Jin; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-01

(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran’s I statistic and Anselin’s local Moran’s I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R2 = 0.0741, log likelihood = −1819.69, AIC = 3665.38), SLM (R2 = 0.0786, log likelihood = −1819.04, AIC = 3665.08) and SEM (R2 = 0.0743, log likelihood = −1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide (p = 0.027), rainfall (p = 0.036) and sunshine hour (p = 0.048), while the relative humidity (p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention. PMID:27827946

The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models.

PubMed

Mahara, Gehendra; Wang, Chao; Yang, Kun; Chen, Sipeng; Guo, Jin; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-11-04

(1) Background: Evidence regarding scarlet fever and its relationship with meteorological, including air pollution factors, is not very available. This study aimed to examine the relationship between ambient air pollutants and meteorological factors with scarlet fever occurrence in Beijing, China. (2) Methods: A retrospective ecological study was carried out to distinguish the epidemic characteristics of scarlet fever incidence in Beijing districts from 2013 to 2014. Daily incidence and corresponding air pollutant and meteorological data were used to develop the model. Global Moran's I statistic and Anselin's local Moran's I (LISA) were applied to detect the spatial autocorrelation (spatial dependency) and clusters of scarlet fever incidence. The spatial lag model (SLM) and spatial error model (SEM) including ordinary least squares (OLS) models were then applied to probe the association between scarlet fever incidence and meteorological including air pollution factors. (3) Results: Among the 5491 cases, more than half (62%) were male, and more than one-third (37.8%) were female, with the annual average incidence rate 14.64 per 100,000 population. Spatial autocorrelation analysis exhibited the existence of spatial dependence; therefore, we applied spatial regression models. After comparing the values of R-square, log-likelihood and the Akaike information criterion (AIC) among the three models, the OLS model (R² = 0.0741, log likelihood = -1819.69, AIC = 3665.38), SLM (R² = 0.0786, log likelihood = -1819.04, AIC = 3665.08) and SEM (R² = 0.0743, log likelihood = -1819.67, AIC = 3665.36), identified that the spatial lag model (SLM) was best for model fit for the regression model. There was a positive significant association between nitrogen oxide ( p = 0.027), rainfall ( p = 0.036) and sunshine hour ( p = 0.048), while the relative humidity ( p = 0.034) had an adverse association with scarlet fever incidence in SLM. (4) Conclusions: Our findings indicated that meteorological, as well as air pollutant factors may increase the incidence of scarlet fever; these findings may help to guide scarlet fever control programs and targeting the intervention.

Application of Kolomogorov-Zurbenko Filter and the decoupled direct 3D method for the dynamic evaluation of a regional air quality model

EPA Science Inventory

Regional air quality models are being used in a policy-setting to estimate the response of air pollutant concentrations to changes in emissions and meteorology. Dynamic evaluation entails examination of a retrospective case(s) to assess whether an air quality model has properly p...

Evaluation of Tower Shadowing on Anemometer Measurements at Los Alamos National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruggeman, David Alan

2016-06-14

The objective of this study is to evaluate the effect of tower shadowing from the meteorology towers at LANL during 2014. This study is in response to the Department of Energy Meteorological Coordinating Council visit in 2015 that recommended an evaluation of any biases in the wind data introduced by the tower and boom alignment at all meteorology towers.

Meteorological needs of the aviation community

NASA Technical Reports Server (NTRS)

Luers, J. K.

1977-01-01

A study was conducted to determine the important meteorological needs of the aviation community and to recommend research in those areas judged most beneficial. The study was valuable in that it provided a comprehensive list of suspected meteorological deficiencies and ideas for research programs relative to these deficiencies. The list and ideas were generated from contacts with various pilots, air traffic controllers, and meteorologists.

Extreme temperature indices analyses: A case study of five meteorological stations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Hasan, Husna; Salleh, Nur Hanim Mohd

2015-10-01

Extreme temperature events affect many human and natural systems. Changes in extreme temperature events can be detected and monitored by developing the indices based on the extreme temperature data. As an effort to provide the understanding of these changes to the public, a study of extreme temperature indices is conducted at five meteorological stations in Peninsular Malaysia. In this study, changes in the means and extreme events of temperature are assessed and compared using the daily maximum and minimum temperature data for the period of 2004 to 2013. The absolute extreme temperature indices; TXx, TXn, TXn and TNn provided by Expert Team on Climate Change Detection and Indices (ETCCDI) are utilized and linear trends of each index are extracted using least square likelihood method. The results indicate that there exist significant decreasing trend in the TXx index for Kota Bharu station and increasing trend in TNn index for Chuping and Kota Kinabalu stations. The comparison between the trend in mean and extreme temperatures show the same significant tendency for Kota Bharu and Kuala Terengganu stations.

The Unmanned Aerial System SUMO: an alternative measurement tool for polar boundary layer studies

NASA Astrophysics Data System (ADS)

Mayer, S.; Jonassen, M. O.; Reuder, J.

2012-04-01

Numerical weather prediction and climate models face special challenges in particular in the commonly stable conditions in the high-latitude environment. For process studies as well as for model validation purposes in-situ observations in the atmospheric boundary layer are highly required, but difficult to retrieve. We introduce a new measurement system for corresponding observations. The Small Unmanned Meteorological Observer SUMO consists of a small and light-weight auto-piloted model aircraft, equipped with a meteorological sensor package. SUMO has been operated in polar environments, among others during IPY on Spitsbergen in the year 2009 and has proven its capabilities for atmospheric measurements with high spatial and temporal resolution even at temperatures of -30 deg C. A comparison of the SUMO data with radiosondes and tethered balloons shows that SUMO can provide atmospheric profiles with comparable quality to those well-established systems. Its high data quality allowed its utilization for evaluation purposes of high-resolution model runs performed with the Weather Research and Forecasting model WRF and for the detailed investigation of an orographically modified flow during a case study.

Assessment of the visibility impairment caused by the emissions from the proposed power plant at Boron, California

NASA Technical Reports Server (NTRS)

Bergstrom, R. W.; Doyle, J. R.; Johnson, C. D.; Holman, H. Y.; Wojcik, M. A.

1980-01-01

The current atmospheric conditions and visibility were modeled, and the effect of the power plant effluent was then added to determine its influence upon the prevailing visibility; the actual reduction in visibility being a function of meteorological conditions and observer-plume-target geometry. In the cases investigated, the perceptibility of a target was reduced by a minimum of 10 percent and a maximum of 100 percent. This significant visual impact would occur 40 days per year in the Edwards area with meteorological conditions such as to cause some visual impact 80 days per year.

ICT approaches to integrating institutional and non-institutional data services for better understanding of hydro-meteorological phenomena

NASA Astrophysics Data System (ADS)

Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.

2012-06-01

It is widely recognised that an effective exploitation of Information and Communication Technologies (ICT) is an enabling factor to achieve major advancements in Hydro-Meteorological Research (HMR). Recently, a lot of attention has been devoted to the use of ICT in HMR activities, e.g. in order to facilitate data exchange and integration, to improve computational capabilities and consequently model resolution and quality. Nowadays, ICT technologies have demonstrated that it is possible to extend monitoring networks by integrating sensors and other sources of data managed by volunteer's communities. These networks are constituted by peers that span a wide portion of the territory in many countries. The peers are "location aware" in the sense that they provide information strictly related with their geospatial location. The coverage of these networks, in general, is not uniform and the location of peers may follow random distribution. The ICT features used to set up the network are lightweight and user friendly, thus, permitting the peers to join the network without the necessity of specialised ICT knowledge. In this perspective it is of increasing interest for HMR activities to elaborate of Personal Weather Station (PWS) networks, capable to provide almost real-time, location aware, weather data. Moreover, different big players of the web arena are now providing world-wide backbones, suitable to present on detailed map location aware information, obtained by mashing up data from different sources. This is the case, for example, with Google Earth and Google Maps. This paper presents the design of a mashup application aimed at aggregating, refining and visualizing near real-time hydro-meteorological datasets. In particular, we focused on the integration of instant precipitation depths, registered either by widespread semi-professional weather stations and official ones. This sort of information has high importance and usefulness in decision support systems and Civil Protection applications. As a significant case study, we analysed the rainfall data observed during the severe flash-flood event of 4 November 2011 over Liguria region, Italy. The joint use of official observation network with PWS networks and meteorological radar allowed for the making of evident finger-like convection structure.

Study of meteorological parameters over the central Himalayan region using balloon-borne sensor

NASA Astrophysics Data System (ADS)

Shrivastava, Rahul; Naja, Manish; Gwal, A. K.

2013-06-01

In the present paper we accumulate the recent advances in atmospheric research by analyzing meteorological data. We have calculated meteorological parameters over the central Himalayan region at Nainital (longitude 79.45□ E, latitude 29.35□N). It is a high altitude place (1951 meters) which is very useful for such type of measurement. We have done our work on meteorological parameters in GVAX (Ganges Valley Aerosol Experiment) project. It was an American-Indo project which was use to capture pre-monsoon to post-monsoon conditions to establish a comprehensive baseline for advancements in the study of the effects of Atmospheric conditions of the Ganges Valley. The Balloon Borne Sounding System (BBSS) technique was also used for in-situ measurements of meteorological parameters.

Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach

NASA Technical Reports Server (NTRS)

Balashov, Nikolay V.; Thompson, Anne M.; Young, George S.

2017-01-01

The recent change in the Environmental Protection Agency's surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a step wise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Probabilistic discrimination between liquid rainfall events, hailstorms, biomass burning and industrial fires from C-Band Radar Polarimetric Variables

NASA Astrophysics Data System (ADS)

Valencia, J. M.; Sepúlveda, J.; Hoyos, C.; Herrera, L.

2017-12-01

Characterization and identification of fire and hailstorm events using weather radar data in a tropical complex topography region is an important task in risk management and agriculture. Polarimetric variables from a C-Band Dual polarization weather radar have potential uses in particle classification, due to the relationship their sensitivity to shape, spatial orientation, size and fall behavior of particles. In this sense, three forest fires and two chemical fires were identified for the Áburra Valley regions. Measurements were compared between each fire event type and with typical data radar retrievals for liquid precipitation events. Results of this analysis show different probability density functions for each type of event according to the particles present in them. This is very important and useful result for early warning systems to avoid precipitation false alarms during fire events within the study region, as well as for the early detection of fires using radar retrievals in remote cases. The comparative methodology is extended to hailstorm cases. Complementary sensors like laser precipitation sensors (LPM) disdrometers and meteorological stations were used to select dates of solid precipitation occurrence. Then, in this dates weather radar data variables were taken in pixels surrounding the stations and solid precipitation polar values were statistically compared with liquid precipitation values. Spectrum precipitation measured by LPM disdrometer helps to define typical features like particles number, fall velocities and diameters for both precipitation types. In addition, to achieve a complete hailstorm characterization, other meteorological variables were analyzed: wind field from meteorological stations and radar wind profiler, profiling data from Micro Rain Radar (MRR), and thermodynamic data from a microwave radiometer.

Random Forest Application for NEXRAD Radar Data Quality Control

NASA Astrophysics Data System (ADS)

Keem, M.; Seo, B. C.; Krajewski, W. F.

2017-12-01

Identification and elimination of non-meteorological radar echoes (e.g., returns from ground, wind turbines, and biological targets) are the basic data quality control steps before radar data use in quantitative applications (e.g., precipitation estimation). Although WSR-88Ds' recent upgrade to dual-polarization has enhanced this quality control and echo classification, there are still challenges to detect some non-meteorological echoes that show precipitation-like characteristics (e.g., wind turbine or anomalous propagation clutter embedded in rain). With this in mind, a new quality control method using Random Forest is proposed in this study. This classification algorithm is known to produce reliable results with less uncertainty. The method introduces randomness into sampling and feature selections and integrates consequent multiple decision trees. The multidimensional structure of the trees can characterize the statistical interactions of involved multiple features in complex situations. The authors explore the performance of Random Forest method for NEXRAD radar data quality control. Training datasets are selected using several clear cases of precipitation and non-precipitation (but with some non-meteorological echoes). The model is structured using available candidate features (from the NEXRAD data) such as horizontal reflectivity, differential reflectivity, differential phase shift, copolar correlation coefficient, and their horizontal textures (e.g., local standard deviation). The influence of each feature on classification results are quantified by variable importance measures that are automatically estimated by the Random Forest algorithm. Therefore, the number and types of features in the final forest can be examined based on the classification accuracy. The authors demonstrate the capability of the proposed approach using several cases ranging from distinct to complex rain/no-rain events and compare the performance with the existing algorithms (e.g., MRMS). They also discuss operational feasibility based on the observed strength and weakness of the method.

The IHMC CmapTools software in research and education: a multi-level use case in Space Meteorology

NASA Astrophysics Data System (ADS)

Messerotti, Mauro

2010-05-01

The IHMC (Institute for Human and Machine Cognition, Florida University System, USA) CmapTools software is a powerful multi-platform tool for knowledge modelling in graphical form based on concept maps. In this work we present its application for the high-level development of a set of multi-level concept maps in the framework of Space Meteorology to act as the kernel of a space meteorology domain ontology. This is an example of a research use case, as a domain ontology coded in machine-readable form via e.g. OWL (Web Ontology Language) is suitable to be an active layer of any knowledge management system embedded in a Virtual Observatory (VO). Apart from being manageable at machine level, concept maps developed via CmapTools are intrinsically human-readable and can embed hyperlinks and objects of many kinds. Therefore they are suitable to be published on the web: the coded knowledge can be exploited for educational purposes by the students and the public, as the level of information can be naturally organized among linked concept maps in progressively increasing complexity levels. Hence CmapTools and its advanced version COE (Concept-map Ontology Editor) represent effective and user-friendly software tools for high-level knowledge represention in research and education.

Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale.

PubMed

Mauree, Dasaraden; Coccolo, Silvia; Kaempf, Jérôme; Scartezzini, Jean-Louis

2017-01-01

A new methodology is proposed to couple a meteorological model with a building energy use model. The aim of such a coupling is to improve the boundary conditions of both models with no significant increase in computational time. In the present case, the Canopy Interface Model (CIM) is coupled with CitySim. CitySim provides the geometrical characteristics to CIM, which then calculates a high resolution profile of the meteorological variables. These are in turn used by CitySim to calculate the energy flows in an urban district. We have conducted a series of experiments on the EPFL campus in Lausanne, Switzerland, to show the effectiveness of the coupling strategy. First, measured data from the campus for the year 2015 are used to force CIM and to evaluate its aptitude to reproduce high resolution vertical profiles. Second, we compare the use of local climatic data and data from a meteorological station located outside the urban area, in an evaluation of energy use. In both experiments, we demonstrate the importance of using in building energy software, meteorological variables that account for the urban microclimate. Furthermore, we also show that some building and urban forms are more sensitive to the local environment.

Multi-scale modelling to evaluate building energy consumption at the neighbourhood scale

PubMed Central

Coccolo, Silvia; Kaempf, Jérôme; Scartezzini, Jean-Louis

2017-01-01

A new methodology is proposed to couple a meteorological model with a building energy use model. The aim of such a coupling is to improve the boundary conditions of both models with no significant increase in computational time. In the present case, the Canopy Interface Model (CIM) is coupled with CitySim. CitySim provides the geometrical characteristics to CIM, which then calculates a high resolution profile of the meteorological variables. These are in turn used by CitySim to calculate the energy flows in an urban district. We have conducted a series of experiments on the EPFL campus in Lausanne, Switzerland, to show the effectiveness of the coupling strategy. First, measured data from the campus for the year 2015 are used to force CIM and to evaluate its aptitude to reproduce high resolution vertical profiles. Second, we compare the use of local climatic data and data from a meteorological station located outside the urban area, in an evaluation of energy use. In both experiments, we demonstrate the importance of using in building energy software, meteorological variables that account for the urban microclimate. Furthermore, we also show that some building and urban forms are more sensitive to the local environment. PMID:28880883

Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

NASA Astrophysics Data System (ADS)

Zhu, Dehua; Echendu, Shirley; Xuan, Yunqing; Webster, Mike; Cluckie, Ian

2016-11-01

Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2-3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.

The passive control of air pollution exposure in Dublin, Ireland: a combined measurement and modelling case study.

PubMed

Gallagher, J; Gill, L W; McNabola, A

2013-08-01

This study investigates the potential real world application of passive control systems to reduce personal pollutant exposure in an urban street canyon in Dublin, Ireland. The implementation of parked cars and/or low boundary walls as a passive control system has been shown to minimise personal exposure to pollutants on footpaths in previous investigations. However, previous research has been limited to generic numerical modelling studies. This study combines real-time traffic data, meteorological conditions and pollution concentrations, in a real world urban street canyon before and after the implementation of a passive control system. Using a combination of field measurements and numerical modelling this study assessed the potential impact of passive controls on personal exposure to nitric oxide (NO) concentrations in the street canyon in winter conditions. A calibrated numerical model of the urban street canyon was developed, taking into account the variability in traffic and meteorological conditions. The modelling system combined the computational fluid dynamic (CFD) simulations and a semi-empirical equation, and demonstrated a good agreement with measured field data collected in the street canyon. The results indicated that lane distribution, fleet composition and vehicular turbulence all affected pollutant dispersion, in addition to the canyon geometry and local meteorological conditions. The introduction of passive controls displayed mixed results for improvements in air quality on the footpaths for different wind and traffic conditions. Parked cars demonstrated the most comprehensive passive control system with average improvements in air quality of up to 15% on the footpaths. This study highlights the potential of passive controls in a real street canyon to increase dispersion and improve air quality at street level. Copyright © 2013 Elsevier B.V. All rights reserved.

Meteorological Variables and Behavior of Learners with Autism: An Examination of Possible Relationships

ERIC Educational Resources Information Center

VanBuskirk, Sabrina E.; Simpson, Richard L.

2013-01-01

For this study, we collected classroom behavioral data for three children with autism relative to daily meteorological conditions. Meteorological data, including barometric pressure, humidity, outdoor temperature, and moon illumination, were obtained from the National Weather Service. Relationships between children's individual target behaviors…

A Methodology for the Parametric Reconstruction of Non-Steady and Noisy Meteorological Time Series

NASA Astrophysics Data System (ADS)

Rovira, F.; Palau, J. L.; Millán, M.

2009-09-01

Climatic and meteorological time series often show some persistence (in time) in the variability of certain features. One could regard annual, seasonal and diurnal time variability as trivial persistence in the variability of some meteorological magnitudes (as, e.g., global radiation, air temperature above surface, etc.). In these cases, the traditional Fourier transform into frequency space will show the principal harmonics as the components with the largest amplitude. Nevertheless, meteorological measurements often show other non-steady (in time) variability. Some fluctuations in measurements (at different time scales) are driven by processes that prevail on some days (or months) of the year but disappear on others. By decomposing a time series into time-frequency space through the continuous wavelet transformation, one is able to determine both the dominant modes of variability and how those modes vary in time. This study is based on a numerical methodology to analyse non-steady principal harmonics in noisy meteorological time series. This methodology combines both the continuous wavelet transform and the development of a parametric model that includes the time evolution of the principal and the most statistically significant harmonics of the original time series. The parameterisation scheme proposed in this study consists of reproducing the original time series by means of a statistically significant finite sum of sinusoidal signals (waves), each defined by using the three usual parameters: amplitude, frequency and phase. To ensure the statistical significance of the parametric reconstruction of the original signal, we propose a standard statistical t-student analysis of the confidence level of the amplitude in the parametric spectrum for the different wave components. Once we have assured the level of significance of the different waves composing the parametric model, we can obtain the statistically significant principal harmonics (in time) of the original time series by using the Fourier transform of the modelled signal. Acknowledgements The CEAM Foundation is supported by the Generalitat Valenciana and BANCAIXA (València, Spain). This study has been partially funded by the European Commission (FP VI, Integrated Project CIRCE - No. 036961) and by the Ministerio de Ciencia e Innovación, research projects "TRANSREG” (CGL2007-65359/CLI) and "GRACCIE” (CSD2007-00067, Program CONSOLIDER-INGENIO 2010).

Local environmental and meteorological conditions influencing the invasive mosquito Ae. albopictus and arbovirus transmission risk in New York City.

PubMed

Little, Eliza; Bajwa, Waheed; Shaman, Jeffrey

2017-08-01

Ae. albopictus, an invasive mosquito vector now endemic to much of the northeastern US, is a significant public health threat both as a nuisance biter and vector of disease (e.g. chikungunya virus). Here, we aim to quantify the relationships between local environmental and meteorological conditions and the abundance of Ae. albopictus mosquitoes in New York City. Using statistical modeling, we create a fine-scale spatially explicit risk map of Ae. albopictus abundance and validate the accuracy of spatiotemporal model predictions using observational data from 2016. We find that the spatial variability of annual Ae. albopictus abundance is greater than its temporal variability in New York City but that both local environmental and meteorological conditions are associated with Ae. albopictus numbers. Specifically, key land use characteristics, including open spaces, residential areas, and vacant lots, and spring and early summer meteorological conditions are associated with annual Ae. albopictus abundance. In addition, we investigate the distribution of imported chikungunya cases during 2014 and use these data to delineate areas with the highest rates of arboviral importation. We show that the spatial distribution of imported arboviral cases has been mostly discordant with mosquito production and thus, to date, has provided a check on local arboviral transmission in New York City. We do, however, find concordant areas where high Ae. albopictus abundance and chikungunya importation co-occur. Public health and vector control officials should prioritize control efforts to these areas and thus more cost effectively reduce the risk of local arboviral transmission. The methods applied here can be used to monitor and identify areas of risk for other imported vector-borne diseases.

Local environmental and meteorological conditions influencing the invasive mosquito Ae. albopictus and arbovirus transmission risk in New York City

PubMed Central

Bajwa, Waheed; Shaman, Jeffrey

2017-01-01

Ae. albopictus, an invasive mosquito vector now endemic to much of the northeastern US, is a significant public health threat both as a nuisance biter and vector of disease (e.g. chikungunya virus). Here, we aim to quantify the relationships between local environmental and meteorological conditions and the abundance of Ae. albopictus mosquitoes in New York City. Using statistical modeling, we create a fine-scale spatially explicit risk map of Ae. albopictus abundance and validate the accuracy of spatiotemporal model predictions using observational data from 2016. We find that the spatial variability of annual Ae. albopictus abundance is greater than its temporal variability in New York City but that both local environmental and meteorological conditions are associated with Ae. albopictus numbers. Specifically, key land use characteristics, including open spaces, residential areas, and vacant lots, and spring and early summer meteorological conditions are associated with annual Ae. albopictus abundance. In addition, we investigate the distribution of imported chikungunya cases during 2014 and use these data to delineate areas with the highest rates of arboviral importation. We show that the spatial distribution of imported arboviral cases has been mostly discordant with mosquito production and thus, to date, has provided a check on local arboviral transmission in New York City. We do, however, find concordant areas where high Ae. albopictus abundance and chikungunya importation co-occur. Public health and vector control officials should prioritize control efforts to these areas and thus more cost effectively reduce the risk of local arboviral transmission. The methods applied here can be used to monitor and identify areas of risk for other imported vector-borne diseases. PMID:28832586

Ensemble data assimilation of total column ozone using a coupled meteorology-chemistry model and its impact on the structure of Typhoon Nabi (2005)

NASA Astrophysics Data System (ADS)

Lim, S.; Park, S. K.; Zupanski, M.

2015-09-01

Ozone (O3) plays an important role in chemical reactions and is usually incorporated in chemical data assimilation (DA). In tropical cyclones (TCs), O3 usually shows a lower concentration inside the eyewall and an elevated concentration around the eye, impacting meteorological as well as chemical variables. To identify the impact of O3 observations on TC structure, including meteorological and chemical information, we developed a coupled meteorology-chemistry DA system by employing the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and an ensemble-based DA algorithm - the maximum likelihood ensemble filter (MLEF). For a TC case that occurred over East Asia, Typhoon Nabi (2005), our results indicate that the ensemble forecast is reasonable, accompanied with larger background state uncertainty over the TC, and also over eastern China. Similarly, the assimilation of O3 observations impacts meteorological and chemical variables near the TC and over eastern China. The strongest impact on air quality in the lower troposphere was over China, likely due to the pollution advection. In the vicinity of the TC, however, the strongest impact on chemical variables adjustment was at higher levels. The impact on meteorological variables was similar in both over China and near the TC. The analysis results are verified using several measures that include the cost function, root mean square (RMS) error with respect to observations, and degrees of freedom for signal (DFS). All measures indicate a positive impact of DA on the analysis - the cost function and RMS error have decreased by 16.9 and 8.87 %, respectively. In particular, the DFS indicates a strong positive impact of observations in the TC area, with a weaker maximum over northeastern China.

Nowcasting Aircraft Icing Conditions in Moscow Region Using Geostationary Meteorological Satellite Data

NASA Astrophysics Data System (ADS)

Barabanova, Olga

2013-04-01

Nowadays the Main Aviation Meteorological Centre in Moscow (MAMC) provides forecasts of icing conditions in Moscow Region airports using information of surface observation network, weather radars and atmospheric sounding. Unfortunately, satellite information is not used properly in aviation meteorological offices in Moscow Region: weather forecasters deal with satellites images of cloudiness only. The main forecasters of MAMC realise that it is necessary to employ meteorological satellite numerical data from different channels in aviation forecasting and especially in nowcasting. Algorithm of nowcasting aircraft in-flight icing conditions has been developed using data from geostationary meteorological satellites "Meteosat-7" and "Meteosat-9". The algorithm is based on the brightness temperature differences. Calculation of brightness temperature differences help to discriminate clouds with supercooled large drops where severe icing conditions are most likely. Due to the lack of visible channel data, the satellite icing detection methods will be less accurate at night. Besides this method is limited by optically thick ice clouds where it is not possible to determine the extent to which supercooled large drops exists within the underlying clouds. However, we determined that most of the optically thick cases are associated with convection or mid-latitude cyclones and they will nearly always have a layer where which supercooled large drops exists with an icing threat. This product is created hourly for the Moscow Air Space and mark zones with moderate or severe icing hazards. The results were compared with mesoscale numerical atmospheric model COSMO-RU output. Verification of the algorithms results using aircraft pilot reports shows that this algorithm is a good instrument for the operational practise in aviation meteorological offices in Moscow Region. The satellite-based algorithms presented here can be used in real time to diagnose areas of icing for pilots to avoid.

Associations between meteorological parameters and influenza activity in a subtropical country: Case of five sentinel sites in Yaoundé-Cameroon

PubMed Central

Monamele, Gwladys C.; Vernet, Marie-Astrid; Nsaibirni, Robert F. J.; Bigna, Jean Joel R.; Kenmoe, Sebastien; Njankouo, Mohamadou Ripa

2017-01-01

Influenza is associated with highly contagious respiratory infections. Previous research has found that influenza transmission is often associated with climate variables especially in temperate regions. This study was performed in order to fill the gap of knowledge regarding the relationship between incidence of influenza and three meteorological parameters (temperature, rainfall and humidity) in a tropical setting. This was a retrospective study performed in Yaoundé-Cameroon from January 2009 to November 2015. Weekly proportions of confirmed influenza cases from five sentinel sites were considered as dependent variables, whereas weekly values of mean temperature, average relative humidity and accumulated rainfall were considered as independent variables. A univariate linear regression model was used in determining associations between influenza activity and weather covariates. A time-series method was used to predict on future values of influenza activity. The data was divided into 2 parts; the first 71 months were used to calibrate the model, and the last 12 months to test for prediction. Overall, there were 1173 confirmed infections with influenza virus. Linear regression analysis showed that there was no statistically significant association observed between influenza activity and weather variables. Very weak relationships (-0.1 < r < 0.1) were observed. Three prediction models were obtained for the different viral types (overall positive, Influenza A and Influenza B). Model 1 (overall influenza) and model 2 (influenza A) fitted well during the estimation period; however, they did not succeed to make good forecasts for predictions. Accumulated rainfall was the only external covariate that enabled good fit of both models. Based on the stationary R2, 29.5% and 41.1% of the variation in the series can be explained by model 1 and 2, respectively. This study laid more emphasis on the fact that influenza in Cameroon is characterized by year-round activity. The meteorological variables selected in this study did not enable good forecast of future influenza activity and certainly acted as proxies to other factors not considered, such as, UV radiation, absolute humidity, air quality and wind. PMID:29088290

Atmosphere-ionosphere coupling from convectively generated gravity waves

NASA Astrophysics Data System (ADS)

Azeem, Irfan; Barlage, Michael

2018-04-01

Ionospheric variability impacts operational performances of a variety of technological systems, such as HF communication, Global Positioning System (GPS) navigation, and radar surveillance. The ionosphere is not only perturbed by geomagnetic inputs but is also influenced by atmospheric tides and other wave disturbances propagating from the troposphere to high altitudes. Atmospheric Gravity Waves (AGWs) excited by meteorological sources are one of the largest sources of mesoscale variability in the ionosphere. In this paper, Total Electron Content (TEC) data from networks of GPS receivers in the United States are analyzed to investigate AGWs in the ionosphere generated by convective thunderstorms. Two case studies of convectively generated gravity waves are presented. On April 4, 2014 two distinct large convective systems in Texas and Arkansas generated two sets of concentric AGWs that were observed in the ionosphere as Traveling Ionospheric Disturbances (TIDs). The period of the observed TIDs was 20.8 min, the horizontal wavelength was 182.4 km, and the horizontal phase speed was 146.4 m/s. The second case study shows TIDs generated from an extended squall line on December 23, 2015 stretching from the Gulf of Mexico to the Great Lakes in North America. Unlike the concentric wave features seen in the first case study, the extended squall line generated TIDs, which exhibited almost plane-parallel phase fronts. The TID period was 20.1 min, its horizontal wavelength was 209.6 km, and the horizontal phase speed was 180.1 m/s. The AGWs generated by both of these meteorological events have large vertical wavelength (>100 km), which are larger than the F2 layer thickness, thus allowing them to be discernible in the TEC dataset.

Navy Tactical Applications Guide. Volume 6, Part 1. Tropics Weather Analysis and Forecast Applications.

DTIC Science & Technology

1986-08-01

the staff of the Walter A. Bohan Company is again acknowledged. Lido A. Andreoni designed the format of the publication and layout of the case studies...A. Bohan Company 1986 L THE WALTER A. BOHAN COMPANY 2026 OAKTON STREET PARK RIDGE ILLINOIS 60068 APPLIED RESEARCH IN SATELLITE METEOROLOGY AND...Walter A. Bohan. Certified Consulting Meteorologist The Walter A. B 1 ohan Company ParK Ridge. IL 60068 Robert H. Whritner, Manager Scripps

Electrical and kinematic structure of an Oklahoma mesoscale convective system

NASA Technical Reports Server (NTRS)

Hunter, Steven M.; Schuur, Terry J.; Marshall, Thomas C.; Rust, W. D.

1990-01-01

The case study examines the dynamics and kinematics of a mesoscale convective system (MCS) by comparing its meteorological parameters with in situ electrical measurements. Conventional MCS characteristics are reported including a rear inflow jet, wake low, and a bipolar cloud-to-ground pattern, but some nonclassical conditions are also reported. Horizontally long cloud-to-ground electrical strikes are noted which demonstrate that cloud-to-ground electrical data alone cannot entirely characterize stratiform electrification in MCSs.

Synergy between air pollution and urban meteorological changes through aerosol-radiation-diffusion feedback―A case study of Beijing in January 2013

NASA Astrophysics Data System (ADS)

Kajino, Mizuo; Ueda, Hiromasa; Han, Zhiwei; Kudo, Rei; Inomata, Yayoi; Kaku, Hidenori

2017-12-01

The interactions of aerosol-radiation-stratification-turbulence-cloud processes during a severe haze event in Beijing in January 2013 were studied using a numerical model. For the clear days, solar radiation flux was reduced by approximately 15% and surface temperature was slightly decreased from 0 to 0.5 K throughout the day and night, except for a 1.4 K decrease around sunrise when fog was presented. The longwave radiation cooling was intensified by the fog or drizzle droplets near the top of the fog layer. Thus, in Beijing, both in the daytime and at night, the surface air temperature was decreased by air pollutants. In the presence of the low-level stratus and light precipitation, the modification of meteorology by aerosols was amplified and changed the wind speed and direction much more significantly compared to clear days. The non-linear effect (or positive feedback) of pollutant emission control on the surface air concentration was newly assessed―severe air pollution leads to the intensification of stable stratification near the surface at night and delays the evolution of the mixing layer, which in turn causes more severe air pollution. The non-linear effect was not significant for the current emission levels in the current case, approximately 10%. In another word, the mixing ratio of aerosols became higher by 10% due to their radiation effects.

The Impacts of Different Meteorology Data Sets on Nitrogen Fate and Transport in the SWAT Watershed Model

EPA Science Inventory

In this study, we investigated how different meteorology data sets impacts nitrogen fate and transport responses in the Soil and Water Assessment Tool (SWAT) model. We used two meteorology data sets: National Climatic Data Center (observed) and Mesoscale Model 5/Weather Research ...

BOREAS TE-21 Daily Surface Meteorological Data

NASA Technical Reports Server (NTRS)

Kimball, John; Hall, Forrest G. (Editor); Papagno, Andrea (Editor)

2000-01-01

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-21 (Terrestrial Ecology) team collected data sets in support of its efforts to characterize and interpret information on the meteorology of boreal forest areas. Daily meteorological data were derived from half-hourly BOREAS tower flux (TF) and Automatic Meteorological Station (AMS) mesonet measurements collected in the Southern and Northern Study Areas (SSA and NSA) for the period of 01 Jan 1994 until 31 Dec 1994. The data were stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Understanding meteorological influences on PM2.5 concentrations across China: a temporal and spatial perspective

NASA Astrophysics Data System (ADS)

Chen, Ziyue; Xie, Xiaoming; Cai, Jun; Chen, Danlu; Gao, Bingbo; He, Bin; Cheng, Nianliang; Xu, Bing

2018-04-01

With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Reconstitution de données climatiques pour l’Algérie du Nord : application des réseaux neuronaux

NASA Astrophysics Data System (ADS)

Bouaoune, Djahida; Dahmani-Megrerouche, Malika

2010-11-01

In the present context of climate change and preservation of biodiversity, the appreciation of the vulnerability of the natural ecosystems and their capacity of adaptation appears among the main preoccupations to the world level (GIEC, 2007). This assessment of the ecosystems requires the availability of climatic data, what is often made difficult by the weak density or even the absence of meteorological stations notably, to the level of the mountains zones. In order to study the climate-vegetation relationship in North Algeria, we use an automatic interpolation method, the neural network method, for the reconstitution of climatic data of the sampled sites, (1035 phytoecological samples), from the existing meteorological network (269 stations). This method is characterized by a great suppleness of non-linearity and by its capacity for reconstituting information from partial and not well-defined indications such as the case of data provided from meteorological networks. In order to reconstitution of climatic data, we use the explicate variables, longitude, latitude and altitude, the variables to explain being the rainfall and temperatures. To define the best approach, the network calibration has been activated on climatic parameters taken globally or solely, for the whole of study zone, and by geographical sector. The results of the interpolation are expressed through a climatic parameter cartography, released automatically by the MapInfo software. The reliability results obtained by this method can be appreciated by elaboration of errors maps comparing to reference data.

Meteorological Processes Affecting the Transport of Emissions from the Navajo Generating Station to Grand Canyon National Park.

NASA Astrophysics Data System (ADS)

Lindsey, Charles G.; Chen, Jun; Dye, Timothy S.; Willard Richards, L.; Blumenthal, Donald L.

1999-08-01

During the 1990 Navajo Generating Station (NGS) Winter Visibility Study, a network of surface and upper-air meteorological measurement systems was operated in and around Grand Canyon National Park to investigate atmospheric processes in complex terrain that affected the transport of emissions from the nearby NGS. This network included 15 surface monitoring stations, eight balloon sounding stations (equipped with a mix of rawinsonde, tethersonde, and Airsonde sounding systems), three Doppler radar wind profilers, and four Doppler sodars. Measurements were made from 10 January through 31 March 1990. Data from this network were used to prepare objectively analyzed wind fields, trajectories, and streak lines to represent transport of emissions from the NGS, and to prepare isentropic analyses of the data. The results of these meteorological analyses were merged in the form of a computer animation that depicted the streak line analyses along with measurements of perfluorocarbon tracer, SO2, and sulfate aerosol concentrations, as well as visibility measurements collected by an extensive surface monitoring network. These analyses revealed that synoptic-scale circulations associated with the passage of low pressure systems followed by the formation of high pressure ridges accompanied the majority of cases when NGS emittants appeared to be transported to the Grand Canyon. The authors' results also revealed terrain influences on transport within the topography of the study area, especially mesoscale flows inside the Lake Powell basin and along the plain above the Marble Canyon.

Drier Air, Lower Temperatures, and Triggering of Paroxysmal Atrial Fibrillation

PubMed Central

Nguyen, Jennifer L.; Link, Mark S.; Luttmann-Gibson, Heike; Laden, Francine; Schwartz, Joel; Wessler, Benjamin S.; Mittleman, Murray A.; Gold, Diane R.; Dockery, Douglas W.

2015-01-01

Background The few previous studies on the onset of paroxysmal atrial fibrillation and meteorologic conditions have focused on outdoor temperature and hospital admissions, but hospital admissions are a crude indicator of atrial fibrillation incidence, and studies have found other weather measures in addition to temperature to be associated with cardiovascular outcomes. Methods Two hundred patients with dual chamber implantable cardioverter-defibrillators were enrolled and followed prospectively from 2006 to 2010 for new onset episodes of atrial fibrillation. The date and time of arrhythmia episodes documented by the implanted cardioverter-defibrillators were linked to meteorologic data and examined using a case-crossover analysis. We evaluated associations with outdoor temperature, apparent temperature, air pressure, and three measures of humidity (relative humidity, dew point, and absolute humidity). Results Of the 200 enrolled patients, 49 patients experienced 328 atrial fibrillation episodes lasting ≥30 seconds. Lower temperatures in the prior 48 hours were positively associated with atrial fibrillation. Lower absolute humidity (ie, drier air) had the strongest and most consistent association: each 0.5 g/m3 decrease in the prior 24 hours increased the odds of atrial fibrillation by 4% (95% confidence interval [CI]: 0%, 7%) and by 5% (95% CI: 2%, 8%) for exposure in the prior 2 hours. Results were similar for dew point but slightly weaker. Conclusions Recent exposure to drier air and lower temperatures were associated with the onset of atrial fibrillation among patients with known cardiac disease, supporting the hypothesis that meteorologic conditions trigger acute cardiovascular episodes. PMID:25756220

Estimation of Agricultural Water Consumption from Meteorological and Yield Data: A Case Study of Hebei, North China

PubMed Central

Yuan, Zaijian; Shen, Yanjun

2013-01-01

Over-exploitation of groundwater resources for irrigated grain production in Hebei province threatens national grain food security. The objective of this study was to quantify agricultural water consumption (AWC) and irrigation water consumption in this region. A methodology to estimate AWC was developed based on Penman-Monteith method using meteorological station data (1984–2008) and existing actual ET (2002–2008) data which estimated from MODIS satellite data through a remote sensing ET model. The validation of the model using the experimental plots (50 m2) data observed from the Luancheng Agro-ecosystem Experimental Station, Chinese Academy of Sciences, showed the average deviation of the model was −3.7% for non-rainfed plots. The total AWC and irrigation water (mainly groundwater) consumption for Hebei province from 1984–2008 were then estimated as 864 km3 and 139 km3, respectively. In addition, we found the AWC has significantly increased during the past 25 years except for a few counties located in mountainous regions. Estimations of net groundwater consumption for grain food production within the plain area of Hebei province in the past 25 years accounted for 113 km3 which could cause average groundwater decrease of 7.4 m over the plain. The integration of meteorological and satellite data allows us to extend estimation of actual ET beyond the record available from satellite data, and the approach could be applicable in other regions globally where similar data are available. PMID:23516537

Meteorological Simulations of Ozone Episode Case Days during the 1996 Paso del Norte Ozone Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, M.J.; Costigan, K.; Muller, C.

1999-02-01

Meteorological simulations centered around the border cities of El Paso and Ciudad Juarez have been performed during an ozone episode that occurred on Aug. 13,1996 during the 1996 Paso del Norte Ozone Study field campaign. Simulations were petiormed using the HOTMAC mesoscale meteorological model using a 1,2,4, and 8 km horizontal grid size nested mesh system. Investigation of the vertical structure and evolution of the atmospheric boundary layer for the Aug. 11-13 time period is emphasized in this paper. Comparison of model-produced wind speed profiles to rawirisonde and radar profiler measurements shows reasonable agreement. A persistent upper-level jet was capturedmore » in the model simulations through data assimilation. In the evening hours, the model was not able to produce the strong wind direction shear seen in the radar wind profiles. Based on virtual potential temperature profile comparisons, the model appears to correctly simulate the daytime growth of the convective mixed layer. However, the model underestimates the cooling of the surface layer at night. We found that the upper-level jet significantly impacted the turbulence structure of the boundary layer, leading to relatively high turbulent kinetic energy (tke) values aloft at night. The model indicates that these high tke values aloft enhance the mid-morning growth of the boundary layer. No upper-level turbulence measurements were available to verify this finding, however. Radar profiler-derived mixing heights do indicate relatively rapid morning growth of the mixed layer.« less

Forecasting zoonotic cutaneous leishmaniasis using meteorological factors in eastern Fars province, Iran: a SARIMA analysis.

PubMed

Tohidinik, Hamid Reza; Mohebali, Mehdi; Mansournia, Mohammad Ali; Niakan Kalhori, Sharareh R; Ali-Akbarpour, Mohsen; Yazdani, Kamran

2018-05-22

To predict the occurrence of zoonotic cutaneous leishmaniasis (ZCL) and evaluate the effect of climatic variables on disease incidence in the east of Fars province, Iran using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The Box-Jenkins approach was applied to fit the SARIMA model for ZCL incidence from 2004 to 2015. Then the model was used to predict the number of ZCL cases for the year 2016. Finally, we assessed the relation of meteorological variables (rainfall, rainy days, temperature, hours of sunshine and relative humidity) with ZCL incidence. SARIMA(2,0,0) (2,1,0)12 was the preferred model for predicting ZCL incidence in the east of Fars province (validation Root Mean Square Error, RMSE = 0.27). It showed that ZCL incidence in a given month can be estimated by the number of cases occurring 1 and 2 months, as well as 12 and 24 months earlier. The predictive power of SARIMA models was improved by the inclusion of rainfall at a lag of 2 months (β = -0.02), rainy days at a lag of 2 months (β = -0.09) and relative humidity at a lag of 8 months (β = 0.13) as external regressors (P-values < 0.05). The latter was the best climatic variable for predicting ZCL cases (validation RMSE = 0.26). Time series models can be useful tools to predict the trend of ZCL in Fars province, Iran; thus, they can be used in the planning of public health programmes. Introducing meteorological variables into the models may improve their precision. © 2018 John Wiley & Sons Ltd.

A trajectory modeling investigation of the biomass burning-tropical ozone relationship

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Thompson, Anne M.; Mcnamara, Donna P.; Schoeberl, Mark R.; Lait, Leslie R.; Newman, Paul A.; Justice, Christopher O.; Kendall, Jacqueline D.

1994-01-01

The hypothesis that tropical total O3 maxima seen by the TOMS satellite derive from African biomass burning has been tested using isentropic trajectory analyses with global meteorological data fields. Two case studies from the 1989 biomass burning season demonstrate that a large fraction of the air arriving at the location of TOMS O3 maxima passed over regions of intense burning. Other trajectories initiated at a series of points over Africa and the Atlantic suggest flight strategies for field studies to be conducted in September 1992.

Utilizing Multi-Ensemble of Downscaled CMIP5 GCMs to Investigate Trends and Spatial and Temporal Extent of Drought in Willamette Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Beal, B.; Moradkhani, H.

2015-12-01

Changing climate and potential future increases in global temperature are likely to have impacts on drought characteristics and hydrologic cylce. In this study, we analyze changes in temporal and spatial extent of meteorological and hydrological droughts in future, and their trends. Three statistically downscaled datasets from NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), Multivariate Adaptive Constructed Analogs (MACA), and Bias Correction and Spatial Disagregation (BCSD-PSU) each consisting of 10 CMIP5 Global Climate Models (GCM) are utilized for RCP4.5 and RCP8.5 scenarios. Further, Precipitation Runoff Modeling System (PRMS) hydrologic model is used to simulate streamflow from GCM inputs and assess the hydrological drought characteristics. Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI) are the two indexes used to investigate meteorological and hydrological drought, respectively. Study is done for Willamette Basin with a drainage area of 29,700 km2 accommodating more than 3 million inhabitants and 25 dams. We analyze our study for annual time scale as well as three future periods of near future (2010-2039), intermediate future (2040-2069), and far future (2070-2099). Large uncertainty is found from GCM predictions. Results reveal that meteorological drought events are expected to increase in near future. Severe to extreme drought with large areal coverage and several years of occurance is predicted around year 2030 with the likelihood of exceptional drought for both drought types. SPI is usually showing positive trends, while SDI indicates negative trends in most cases.

Rapid Transpacific Transport in Autumn Observed by the A-Train Satellites

NASA Technical Reports Server (NTRS)

Li. Can; Hsu, N. Christina; Krotkov, Nickolay A.; Liang, Qing; Yang, Kai; Tsay, Si-Chee

2011-01-01

Transpacific transport of dust and pollutants is well documented for spring, but less so for other seasons. Here we investigate rapid transpacific transport in autumn utilizing the A-train satellites. In three episodes studied as examples, SO2 plumes over East Asia were detected by the Ozone Monitoring Instrument aboard the Aura satellite, and found to reach North America in 5-6 days. They were likely derived from anthropogenic sources, given that identical transport patterns of CO, a tracer for incomplete combustion, were simultaneously observed by the Aqua satellite. Trajectory analysis and meteorological data were employed to explore the meteorological circumstances surrounding these events: like many of their counterparts in spring, all three plumes were lifted to the free troposphere in warm conveyor belt associated with mid-latitude wave cyclones, and their migration to downwind region was regulated by the meteorology over the East Pacific. These cases provide further evidence that a fraction of S02 could escape wet scavenging, and be transported at much greater efficiency than NOx (NO + N02). An analysis of the S02 and CO data from September to November during 2005-2008 found 16 S02 long-range transport episodes, out of 62 Asian outflow events. While the counts are sensitive to the choice of criteria, they suggest that the long-range transport of Asian sulfur species occurs quite frequently, and could exert strong impacts on large downstream areas. This study also highlights the importance of transpacific transport in autumn, which has thus far been rarely studied and deserves more attention from the community.

Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information

NASA Astrophysics Data System (ADS)

Fang, Wei; Huang, Shengzhi; Huang, Qiang; Huang, Guohe; Meng, Erhao; Luan, Jinkai

2018-06-01

In this study, reference evapotranspiration (ET0) forecasting models are developed for the least economically developed regions subject to meteorological data scarcity. Firstly, the partial mutual information (PMI) capable of capturing the linear and nonlinear dependence is investigated regarding its utility to identify relevant predictors and exclude those that are redundant through the comparison with partial linear correlation. An efficient input selection technique is crucial for decreasing model data requirements. Then, the interconnection between global climate indices and regional ET0 is identified. Relevant climatic indices are introduced as additional predictors to comprise information regarding ET0, which ought to be provided by meteorological data unavailable. The case study in the Jing River and Beiluo River basins, China, reveals that PMI outperforms the partial linear correlation in excluding the redundant information, favouring the yield of smaller predictor sets. The teleconnection analysis identifies the correlation between Nino 1 + 2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1 + 2 as predictors helps to yield more accurate ET0 forecasts. A model performance comparison also shows that non-linear stochastic models (SVR or RF with input selection through PMI) do not always outperform linear models (MLR with inputs screen by linear correlation). However, the former can offer quite comparable performance depending on smaller predictor sets. Therefore, efforts such as screening model inputs through PMI and incorporating global climatic indices interconnected with ET0 can benefit the development of ET0 forecasting models suitable for data-scarce regions.

Using Multiple Big Datasets and Machine Learning to Produce a New Global Particulate Dataset: A Technology Challenge Case Study

NASA Astrophysics Data System (ADS)

Lary, D. J.

2013-12-01

A BigData case study is described where multiple datasets from several satellites, high-resolution global meteorological data, social media and in-situ observations are combined using machine learning on a distributed cluster using an automated workflow. The global particulate dataset is relevant to global public health studies and would not be possible to produce without the use of the multiple big datasets, in-situ data and machine learning.To greatly reduce the development time and enhance the functionality a high level language capable of parallel processing has been used (Matlab). A key consideration for the system is high speed access due to the large data volume, persistence of the large data volumes and a precise process time scheduling capability.

Spatial impact and triggering conditions of the exceptional hydro-geomorphological event of December 1909 in Iberia

NASA Astrophysics Data System (ADS)

Pereira, S.; Ramos, A. M.; Zêzere, J. L.; Trigo, R. M.; Vaquero, J. M.

2015-09-01

According to the DISASTER database the 20-28 December 1909 was the hydro-geomorphologic event with the highest number of flood and landslide cases occurred in Portugal in the period 1865-2010 (Zêzere et al., 2014). This event also caused important social impacts over the Spanish territory, especially in the Douro basin, having triggered the highest floods in more than 100 years at the river's mouth in the city of Oporto. This work aims to characterize the spatial distribution and social impacts of the December 1909 hydro-geomorphologic event over Iberia. In addition, the meteorological conditions that triggered the event are analysed using the 20 Century Reanalysis dataset from NOAA and precipitation data from Iberian meteorological stations. The Iberian Peninsula was spatially affected during this event along the SW-NE direction spanning from Lisbon, Santarém, Oporto and Guarda (in Portugal), until Salamanca, Valladolid, Zamora, Orense, León and Palencia (in Spain). In Iberia, 134 DISASTER cases were recorded (130 flood cases; 4 landslides cases) having caused a total of 89 casualties (57 in floods and 32 in landslides) and a total of 3876 people were affected, including fatalities, injured, missing, evacuated and homeless people. This event was associated with some outstanding precipitation values at Guarda station (Portugal) in 22 December 1909 and unusual meteorological conditions characterized by the presence of a deep low pressure system located over NW Iberian Peninsula with a stationary frontal system striking the Western Iberian Peninsula. The presence of an upper-level jet (250 hPa) and low-level jet (900 hPa) located on SW-NE oriented towards the Iberia along with upper-level divergence and lower-level convergence favoured large-scale precipitation. Finally, associated with these features it is possible to state that this extreme event was clearly associated to the presence of an elongated Atmospheric River, crossing the entire northern Atlantic basin and providing a continuous supply of moisture that contributed to enhance precipitation. This work contributes to a comprehensive and systematic synoptic evaluation of the second most deadly hydro-geomorphologic Disaster event occurred in Portugal since 1865 and will help to better understand the meteorological system that was responsible for triggering the event.

Development of the ClearSky smoke dispersion forecast system for agricultural field burning in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Jain, Rahul; Vaughan, Joseph; Heitkamp, Kyle; Ramos, Charleston; Claiborn, Candis; Schreuder, Maarten; Schaaf, Mark; Lamb, Brian

The post-harvest burning of agricultural fields is commonly used to dispose of crop residue and provide other desired services such as pest control. Despite careful regulation of burning, smoke plumes from field burning in the Pacific Northwest commonly degrade air quality, particularly for rural populations. In this paper, ClearSky, a numerical smoke dispersion forecast system for agricultural field burning that was developed to support smoke management in the Inland Pacific Northwest, is described. ClearSky began operation during the summer through fall burn season of 2002 and continues to the present. ClearSky utilizes Mesoscale Meteorological Model version 5 (MM5v3) forecasts from the University of Washington, data on agricultural fields, a web-based user interface for defining burn scenarios, the Lagrangian CALPUFF dispersion model and web-served animations of plume forecasts. The ClearSky system employs a unique hybrid source configuration, which treats the flaming portion of a field as a buoyant line source and the smoldering portion of the field as a buoyant area source. Limited field observations show that this hybrid approach yields reasonable plume rise estimates using source parameters derived from recent field burning emission field studies. The performance of this modeling system was evaluated for 2003 by comparing forecast meteorology against meteorological observations, and comparing model-predicted hourly averaged PM 2.5 concentrations against observations. Examples from this evaluation illustrate that while the ClearSky system can accurately predict PM 2.5 surface concentrations due to field burning, the overall model performance depends strongly on meteorological forecast error. Statistical evaluation of the meteorological forecast at seven surface stations indicates a strong relationship between topographical complexity near the station and absolute wind direction error with wind direction errors increasing from approximately 20° for sites in open areas to 70° or more for sites in very complex terrain. The analysis also showed some days with good forecast meteorology with absolute mean error in wind direction less than 30° when ClearSky correctly predicted PM 2.5 surface concentrations at receptors affected by field burns. On several other days with similar levels of wind direction error the model did not predict apparent plume impacts. In most of these cases, there were no reported burns in the vicinity of the monitor and, thus, it appeared that other, non-reported burns were responsible for the apparent plume impact at the monitoring site. These cases do not provide information on the performance of the model, but rather indicate that further work is needed to identify all burns and to improve burn reports in an accurate and timely manner. There were also a number of days with wind direction errors exceeding 70° when the forecast system did not correctly predict plume behavior.

GPS IPW as a Meteorological Parameter and Climate Global Change Indicator

NASA Astrophysics Data System (ADS)

Kruczyk, M.; Liwosz, T.

2011-12-01

Paper focuses on comprehensive investigation of the GPS derived IPW (Integrated Precipitable Water, also IWV) as a geophysical tool. GPS meteorology is now widely acknowledged indirect method of atmosphere sensing. First we demonstrate GPS IPW quality. Most thorough inter-technique comparisons of directly measured IPW are attainable only for some observatories (note modest percentage of GPS stations equipped with meteorological devices). Nonetheless we have managed to compare IPW series derived from GPS tropospheric solutions (ZTD mostly from IGS and EPN solutions) and some independent techniques. IPW values from meteorological sources we used are: radiosoundings, sun photometer and input fields of numerical weather prediction model. We can treat operational NWP models as meteorological database within which we can calculate IWV for all GPS stations independently from network of direct measurements (COSMO-LM model maintained by Polish Institute of Meteorology and Water Management was tried). Sunphotometer (CIMEL-318, Central Geophysical Observatory IGF PAS, Belsk, Poland) data seems the most genuine source - so we decided for direct collocation of GPS measurements and sunphotometer placing permanent GPS receiver on the roof of Belsk Observatory. Next we analyse IPW as geophysical parameter: IPW demonstrates some physical effects evoked by station location (height and series correlation coefficient as a function of distance) and weather patterns like dominant wind directions (in case of neighbouring stations). Deficiency of surface humidity data to model IPW is presented for different climates. This inadequacy and poor humidity data representation in NWP model extremely encourages investigating information exchange potential between Numerical Model and GPS network. The second and most important aspect of this study concerns long series of IPW (daily averaged) which can serve as climatological information indicator (water vapour role in climate system is hard to exaggerate). Especially intriguing are relatively unique shape of such series in different climates. Long lasting changes in weather conditions: 'dry' and 'wet' years are also visible. The longer and more uniform our series are the better chance to estimate the magnitude of climatological IWV changes. Homogenous ZTD solution during long period is great concern in this approach (problems with GPS strategy and reference system changes). In case of continental network (EUREF Permanent Network) reliable data we get only after reprocessing. Simple sinusoidal model has been adjusted to the IPW series (LS method) for selected stations (mainly Europe but also other continents - IGS stations), every year separately. Not only amplitudes but also phases of annual signal differ from year to year. Longer IPW series (up to 14 years) searched for some climatological signal sometimes reveal weak steady trend. Large number of GPS permanent stations, relative easiness of IPW derivation (only and surface meteo data needed apart from GPS solution) and water vapour significance in water cycle and global climate make this GPS IPW promising element of global environmental change monitoring.

Roles of Meteorology in Changes of Air Pollutants Concentrations in China from 2010 to 2015

NASA Astrophysics Data System (ADS)

Wang, P.; Kota, S. H.; Hu, J.; Ying, Q.; Zhang, H.

2017-12-01

Tremendous efforts have been made to control the severe air pollution in China in recent years. However, no significant improvement was observed according to annual fine particulate matter (PM2.5) concentrations and the concentrations in severe air pollution events in winter. This is partially due to the role of meteorology, which affects the emission, transport, transformation, and deposition of air pollutants. In this study, simulation of air pollutants over China was conducted for six years from 2010 to 2015 with constant anthropogenic emissions to verify the changes of air pollutants due to meteorology changes only. Model performance was validated by comparing with meteorological observations and air pollutants measures from various sources. Four different regions/cities were selected to understand the changes in wind, mixing layer height, temperature, and relative humanity at different seasons. The changes in concentrations of pollutants including PM2.5 and its chemical components and ozone were analyzed and associated with meteorological changes. This study would provide information for designing effective control strategies in different areas with the consideration of meteorological and climate changes.

Characteristics of Fine Particles in an Urban Atmosphere-Relationships with Meteorological Parameters and Trace Gases.

PubMed

Zhang, Tianhao; Zhu, Zhongmin; Gong, Wei; Xiang, Hao; Fang, Ruimin

2016-08-10

Atmospheric fine particles (diameter < 1 μm) attract a growing global health concern and have increased in urban areas that have a strong link to nucleation, traffic emissions, and industrial emissions. To reveal the characteristics of fine particles in an industrial city of a developing country, two-year measurements of particle number size distribution (15.1 nm-661 nm), meteorological parameters, and trace gases were made in the city of Wuhan located in central China from June 2012 to May 2014. The annual average particle number concentrations in the nucleation mode (15.1 nm-30 nm), Aitken mode (30 nm-100 nm), and accumulation mode (100 nm-661 nm) reached 4923 cm(-3), 12193 cm(-3) and 4801 cm(-3), respectively. Based on Pearson coefficients between particle number concentrations and meteorological parameters, precipitation and temperature both had significantly negative relationships with particle number concentrations, whereas atmospheric pressure was positively correlated with the particle number concentrations. The diurnal variation of number concentration in nucleation mode particles correlated closely with photochemical processes in all four seasons. At the same time, distinct growth of particles from nucleation mode to Aitken mode was only found in spring, summer, and autumn. The two peaks of Aitken mode and accumulation mode particles in morning and evening corresponded obviously to traffic exhaust emissions peaks. A phenomenon of "repeated, short-lived" nucleation events have been created to explain the durability of high particle concentrations, which was instigated by exogenous pollutants, during winter in a case analysis of Wuhan. Measurements of hourly trace gases and segmental meteorological factors were applied as proxies for complex chemical reactions and dense industrial activities. The results of this study offer reasonable estimations of particle impacts and provide references for emissions control strategies in industrial cities of developing countries.

Socio-demographic Characteristics and Leading Causes of Death Among the Casualties of Meteorological Events Compared With All-cause Deaths in Korea, 2000-2011

PubMed Central

Lee, Kyung Eun; Myung, Hyung-Nam; Na, Wonwoong

2013-01-01

Objectives This study investigated the socio-demographic characteristics and medical causes of death among meteorological disaster casualties and compared them with deaths from all causes. Methods Based on the death data provided by the National Statistical Office from 2000 to 2011, the authors analyzed the gender, age, and region of 709 casualties whose external causes were recorded as natural events (X330-X389). Exact matching was applied to compare between deaths from meteorological disasters and all deaths. Results The total number of deaths for last 12 years was 2 728 505. After exact matching, 642 casualties of meteorological disasters were matched to 6815 all-cause deaths, which were defined as general deaths. The mean age of the meteorological disaster casualties was 51.56, which was lower than that of the general deaths by 17.02 (p<0.001). As for the gender ratio, 62.34% of the meteorological event casualties were male. While 54.09% of the matched all-cause deaths occurred at a medical institution, only 7.6% of casualties from meteorological events did. As for occupation, the rate of those working in agriculture, forestry, and fishery jobs was twice as high in the casualties from meteorological disasters as that in the general deaths (p<0.001). Meteorological disaster-related injuries like drowning were more prevalent in the casualties of meteorological events (57.48%). The rate of amputation and crushing injury in deaths from meteorological disasters was three times as high as in the general deaths. Conclusions The new information gained on the particular characteristics contributing to casualties from meteorological events will be useful for developing prevention policies. PMID:24137528

Economic benefits of meteorological services

NASA Astrophysics Data System (ADS)

Freebairn, John W.; Zillman, John W.

2002-03-01

There is an increasing need for more rigorous and more broadly based determination of the economic value of meteorological services as an aid to decision-making on the appropriate level of funding to be committed to their provision at the national level. This paper develops an overall framework for assessment of the economic value of meteorological services based on the recognition that most national meteorological infrastructure and services possess the non rival properties of public goods. Given this overall framework for determination of both total and marginal benefits, four main methodologies appropriate for use in valuation studies - market prices, normative or prescriptive decision-making models, descriptive behavioural response studies and contingent valuation studies - are outlined and their strengths and limitations described. Notwithstanding the methodological limitations and the need for a much more comprehensive set of studies for the various application sectors, it is clear that the actual and potential benefits to individuals, firms, industry sectors and national economies from state-of-the-art meteorological and related services are substantial and that, at this stage, they are inadequately recognised and insufficiently exploited in many countries.

THE NEW YORK MIDTOWN DISPERSION STUDY (MID-05) METEOROLOGICAL DATA REPORT.

DOE Office of Scientific and Technical Information (OSTI.GOV)

REYNOLDS,R.M.; SULLIVAN, T.M.; SMITH, S.

2007-01-01

The New York City midtown dispersion program, MID05, examined atmospheric transport in the deep urban canyons near Rockefeller Center. Little is known about air flow and hazardous gas dispersion under such conditions, since previous urban field experiments have focused on small to medium sized cities with much smaller street canyons and examined response over a much larger area. During August, 2005, a series of six gas tracer tests were conducted and sampling was conducted over a 2 km grid. A critical component of understanding gas movement in these studies is detailed wind and meteorological information in the study zone. Tomore » support data interpretation and modeling, several meteorological stations were installed at street level and on roof tops in Manhattan. In addition, meteorological data from airports and other weather instrumentation around New York City were collected. This document describes the meteorological component of the project and provides an outline of data file formats for the different instruments. These data provide enough detail to support highly-resolved computational simulations of gas transport in the study zone.« less

Newly Digitized Historical Climate Data of the German Bight and the Southern Baltic Sea Coasts

NASA Astrophysics Data System (ADS)

Röhrbein, Dörte; Tinz, Birger; von Storch, Hans

2015-04-01

The detection of historical climate information plays an important role with regard to the discussion on climate change, particularly on storminess. The German Meteorological Service houses huge archives of historical handwritten journals of weather observations. A considerable number of original observation sheets from stations along the coast of the German Bight and the southern Baltic Sea exists which has been until recently almost unnoticed. These stations are called signal stations and are positioned close to the shore. However, for this region meteorological observation data of 128 stations exist from 1877 to 1999 and are partly digitized. In this study we show an analysis of firstly newly digitized wind and surface air pressure data of 15 stations from 1877 to 1939 and we also present a case study of the storm surge at the coast of the southern Baltic Sea in December 1913. The data are quality controlled by formal, climatological, temporal and consistency checks. It is shown that these historical climate data are usable in consistency and quality for further investigations on climate change, e.g. as input for regional and global reanalysis.

A Simulation Study of Instrument Meteorological Condition Approaches to Dual Parallel Runways Spaced 3400 and 2500 Feet Apart Using Flight-Deck-Centered Technology

NASA Technical Reports Server (NTRS)

Waller, Marvin C.; Scanlon, Charles H.

1999-01-01

A number of our nations airports depend on closely spaced parallel runway operations to handle their normal traffic throughput when weather conditions are favorable. For safety these operations are curtailed in Instrument Meteorological Conditions (IMC) when the ceiling or visibility deteriorates and operations in many cases are limited to the equivalent of a single runway. Where parallel runway spacing is less than 2500 feet, capacity loss in IMC is on the order of 50 percent for these runways. Clearly, these capacity losses result in landing delays, inconveniences to the public, increased operational cost to the airlines, and general interruption of commerce. This document presents a description and the results of a fixed-base simulation study to evaluate an initial concept that includes a set of procedures for conducting safe flight in closely spaced parallel runway operations in IMC. Consideration of flight-deck information technology and displays to support the procedures is also included in the discussions. The procedures and supporting technology rely heavily on airborne capabilities operating in conjunction with the air traffic control system.

Assessment of Drought Severity Using Normal Precipitation Index (Case Study: Sistan and Baluchistan Province)

NASA Astrophysics Data System (ADS)

Rahimi, D.; Movahedi, S.

2009-04-01

In the last decades, water crisis is one of the most important critical phenomenons in the environment planning and human society's management which affecting on development aspects in the international, national and regional levels. In this research, have been considered the Drought as the main parameter in water rare serious. For drought assessment, can treat the different methods, such as statistical model, meteorological and hydrological methods. In this research, have been used the Normal Precipitation index to meteorological analysis of drought severity in Sistan and Baluchistan province with high drought severity during recent years. According to the obtained result, the annual precipitation of studied area was between 36 to 52 percent more than mean precipitation of province. 10%-23 percent of precipitation amount involved the drought threshold border, 3%-13 percent of precipitations contain the weakness drought, 6.7% -23 percent were considered for moderate drought, 6%-20 percent involved the severe drought and ultimately, 6.7% to 23 percent of precipitations were considered as very severe drought. Keywords: Drought, Normal index, precipitation, Sistan and Baluchistan

Extreme fog events in Poland with respect to circulation conditions

NASA Astrophysics Data System (ADS)

Ustrnul, Z.; Czekierda, D.; Wypych, A.

2010-09-01

Fog is a phenomenon which belongs to a group of so-called hydrometeorites and, according to the different dictionaries, it is a suspension of water droplets or ice crystals in the ground layer of the air that impairs visibility in the horizontal direction below 1 km. The phenomenon of fog, although much less dynamic or violent than other extreme phenomena, such as thunderstorms or hail, is equally dangerous and brings about huge social and economic complications. Land and air transportation suffer and fog may sometimes leads to a complete crippling of the whole economy in an area where fog occurs. The main objective of the study is determination of the circulation types bringing extreme fog events in Poland. The duration of fog at each meteorological station was considered as the main input data originated from 54 synoptic stations located across the country. The mentioned data series cover the period of 56 years (1951-2006). The occurrence of fog depends on meteorological conditions caused to a large extent by a given synoptic situation and local terrain conditions. In this study, according to its objectives, only circulation conditions are taken into consideration. These have been described by 5 different circulation classifications (Grosswetterlagen, Litynski, Osuchowska-Klein, Niedzwiedz and Ustrnul). Situations when this phenomenon occurred across a large part of the country were taken into detailed consideration. Special attention was paid to fog coverage during 24-hour periods. In this work, in light of certain doubts about the homogeneity of the observation material available, the intensity of fog was not included, as it requires additional and very tedious analysis. In the first step all cases of fog during the 1966-2006 study period which lasted 24 hours at more than 10 of the considered weather stations, i.e: at least 5 stations have been considered. As expected, in most cases, either a centre of a classical high pressure system or a high pressure wedge prevailed over Poland. In many cases, the dominance of baric patterns with advection from the eastern or southern sectors can be observed. Only in a few cases does a type with advection from the western sector come into play. In summary, it can be stated that intensive extreme fog of long duration occurred first of all in high pressure non-advective situations or along with weak advection, mainly from the southern or eastern direction. This statement, however, is not revolutionary. It simply confirms that the most troublesome of fog types is the radiation type, and can cover all of Poland at the same time and last up to several days. The study contains detailed meteorological-synoptic analyses of the most extreme events during the whole investigated period.

Hydrometeorological network for flood monitoring and modeling

NASA Astrophysics Data System (ADS)

Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris

2013-08-01

Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its functionality has been implemented as open-source software for use in a wide range of applications in the field of water resources monitoring and management, such as the demonstration case study outlined in this work.

A comparison between modeled and measured permafrost temperatures at Ritigraben borehole, Switzerland

NASA Astrophysics Data System (ADS)

Mitterer-Hoinkes, Susanna; Lehning, Michael; Phillips, Marcia; Sailer, Rudolf

2013-04-01

The area-wide distribution of permafrost is sparsely known in mountainous terrain (e.g. Alps). Permafrost monitoring can only be based on point or small scale measurements such as boreholes, active rock glaciers, BTS measurements or geophysical measurements. To get a better understanding of permafrost distribution, it is necessary to focus on modeling permafrost temperatures and permafrost distribution patterns. A lot of effort on these topics has been already expended using different kinds of models. In this study, the evolution of subsurface temperatures over successive years has been modeled at the location Ritigraben borehole (Mattertal, Switzerland) by using the one-dimensional snow cover model SNOWPACK. The model needs meteorological input and in our case information on subsurface properties. We used meteorological input variables of the automatic weather station Ritigraben (2630 m) in combination with the automatic weather station Saas Seetal (2480 m). Meteorological data between 2006 and 2011 on an hourly basis were used to drive the model. As former studies showed, the snow amount and the snow cover duration have a great influence on the thermal regime. Low snow heights allow for deeper penetration of low winter temperatures into the ground, strong winters with a high amount of snow attenuate this effect. In addition, variations in subsurface conditions highly influence the temperature regime. Therefore, we conducted sensitivity runs by defining a series of different subsurface properties. The modeled subsurface temperature profiles of Ritigraben were then compared to the measured temperatures in the Ritigraben borehole. This allows a validation of the influence of subsurface properties on the temperature regime. As expected, the influence of the snow cover is stronger than the influence of sub-surface material properties, which are significant, however. The validation presented here serves to prepare a larger spatial simulation with the complex hydro-meteorological 3-dimensional model Alpine 3D, which is based on a distributed application of SNOWPACK.

Association between meteorological factors and bacillary dysentery incidence in Chaoyang city, China: an ecological study

PubMed Central

Zhao, Yang; Zhu, Yaxin; Zhu, Zhiwei; Qu, Bo

2016-01-01

Objectives To quantify the relationship between meteorological factors and bacillary dysentery incidence. Design Ecological study. Setting We collected bacillary dysentery incidences and meteorological data of Chaoyang city from the year 1981 to 2010. The climate in this city was a typical northern temperate continental monsoon. All meteorological factors in this study were divided into 4 latent factors: temperature, humidity, sunshine and airflow. Structural equation modelling was used to analyse the relationship between meteorological factors and the incidence of bacillary dysentery. Material Incidences of bacillary dysentery were obtained from the Center for Disease Control and Prevention of Chaoyang city, and meteorological data were collected from the Bureau of Meteorology in Chaoyang city. Primary outcome measures The indexes including χ2, root mean square error of approximation (RMSEA), comparative fit index (CFI), standardised root mean square residual (SRMR) and goodness-of-fit index (GFI) were used to evaluate the goodness-of-fit of the theoretical model to the data. The factor loads were used to explore quantitative relationship between bacillary dysentery incidences and meteorological factors. Results The goodness-of-fit results of the model showing that RMSEA=0.08, GFI=0.84, CFI=0.88, SRMR=0.06 and the χ2 value is 231.95 (p=0.0) with 15 degrees of freedom. Temperature and humidity factors had positive correlations with incidence of bacillary dysentery, with the factor load of 0.59 and 0.78, respectively. Sunshine had a negative correlation with bacillary dysentery incidence, with a factor load of −0.15. Conclusions Humidity and temperature should be given greater consideration in bacillary dysentery prevention measures for northern temperate continental monsoon climates, such as that of Chaoyang. PMID:27940632

Observed correlations between aerosol and cloud properties in an Indian Ocean trade cumulus regime

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pistone, Kristina; Praveen, Puppala S.; Thomas, Rick M.

There are many contributing factors which determine the micro- and macrophysical properties of clouds, including atmospheric vertical structure, dominant meteorological conditions, and aerosol concentration, all of which may be coupled to one another. In the quest to determine aerosol effects on clouds, these potential relationships must be understood. Here we describe several observed correlations between aerosol conditions and cloud and atmospheric properties in the Indian Ocean winter monsoon season.In the CARDEX (Cloud, Aerosol, Radiative forcing, Dynamics EXperiment) field campaign conducted in February and March 2012 in the northern Indian Ocean, continuous measurements were made of atmospheric precipitable water vapor (PWV)more » and the liquid water path (LWP) of trade cumulus clouds, concurrent with measurements of water vapor flux, cloud and aerosol vertical profiles, meteorological data, and surface and total-column aerosol from instrumentation at a ground observatory and on small unmanned aircraft. We present observations which indicate a positive correlation between aerosol and cloud LWP only when considering cases with low atmospheric water vapor (PWV < 40 kg m –2), a criterion which acts to filter the data to control for the natural meteorological variability in the region.We then use the aircraft and ground-based measurements to explore possible mechanisms behind this observed aerosol–LWP correlation. The increase in cloud liquid water is found to coincide with a lowering of the cloud base, which is itself attributable to increased boundary layer humidity in polluted conditions. High pollution is found to correlate with both higher temperatures and higher humidity measured throughout the boundary layer. A large-scale analysis, using satellite observations and meteorological reanalysis, corroborates these covariations: high-pollution cases are shown to originate as a highly polluted boundary layer air mass approaching the observatory from a northwesterly direction. The source air mass exhibits both higher temperatures and higher humidity in the polluted cases. While the warmer temperatures may be attributable to aerosol absorption of solar radiation over the subcontinent, the factors responsible for the coincident high humidity are less evident: the high-aerosol conditions are observed to disperse with air mass evolution, along with a weakening of the high-temperature anomaly, while the high-humidity condition is observed to strengthen in magnitude as the polluted air mass moves over the ocean toward the site of the CARDEX observations. In conclusion, potential causal mechanisms of the observed correlations, including meteorological or aerosol-induced factors, are explored, though future research will be needed for a more complete and quantitative understanding of the aerosol–humidity relationship.« less

Observed correlations between aerosol and cloud properties in an Indian Ocean trade cumulus regime

NASA Astrophysics Data System (ADS)

Pistone, Kristina; Praveen, Puppala S.; Thomas, Rick M.; Ramanathan, Veerabhadran; Wilcox, Eric M.; Bender, Frida A.-M.

2016-04-01

There are many contributing factors which determine the micro- and macrophysical properties of clouds, including atmospheric vertical structure, dominant meteorological conditions, and aerosol concentration, all of which may be coupled to one another. In the quest to determine aerosol effects on clouds, these potential relationships must be understood. Here we describe several observed correlations between aerosol conditions and cloud and atmospheric properties in the Indian Ocean winter monsoon season.In the CARDEX (Cloud, Aerosol, Radiative forcing, Dynamics EXperiment) field campaign conducted in February and March 2012 in the northern Indian Ocean, continuous measurements were made of atmospheric precipitable water vapor (PWV) and the liquid water path (LWP) of trade cumulus clouds, concurrent with measurements of water vapor flux, cloud and aerosol vertical profiles, meteorological data, and surface and total-column aerosol from instrumentation at a ground observatory and on small unmanned aircraft. We present observations which indicate a positive correlation between aerosol and cloud LWP only when considering cases with low atmospheric water vapor (PWV < 40 kg m-2), a criterion which acts to filter the data to control for the natural meteorological variability in the region.We then use the aircraft and ground-based measurements to explore possible mechanisms behind this observed aerosol-LWP correlation. The increase in cloud liquid water is found to coincide with a lowering of the cloud base, which is itself attributable to increased boundary layer humidity in polluted conditions. High pollution is found to correlate with both higher temperatures and higher humidity measured throughout the boundary layer. A large-scale analysis, using satellite observations and meteorological reanalysis, corroborates these covariations: high-pollution cases are shown to originate as a highly polluted boundary layer air mass approaching the observatory from a northwesterly direction. The source air mass exhibits both higher temperatures and higher humidity in the polluted cases. While the warmer temperatures may be attributable to aerosol absorption of solar radiation over the subcontinent, the factors responsible for the coincident high humidity are less evident: the high-aerosol conditions are observed to disperse with air mass evolution, along with a weakening of the high-temperature anomaly, while the high-humidity condition is observed to strengthen in magnitude as the polluted air mass moves over the ocean toward the site of the CARDEX observations. Potential causal mechanisms of the observed correlations, including meteorological or aerosol-induced factors, are explored, though future research will be needed for a more complete and quantitative understanding of the aerosol-humidity relationship.

Observed correlations between aerosol and cloud properties in an Indian Ocean trade cumulus regime

DOE PAGES

Pistone, Kristina; Praveen, Puppala S.; Thomas, Rick M.; ...

2016-04-27

There are many contributing factors which determine the micro- and macrophysical properties of clouds, including atmospheric vertical structure, dominant meteorological conditions, and aerosol concentration, all of which may be coupled to one another. In the quest to determine aerosol effects on clouds, these potential relationships must be understood. Here we describe several observed correlations between aerosol conditions and cloud and atmospheric properties in the Indian Ocean winter monsoon season.In the CARDEX (Cloud, Aerosol, Radiative forcing, Dynamics EXperiment) field campaign conducted in February and March 2012 in the northern Indian Ocean, continuous measurements were made of atmospheric precipitable water vapor (PWV)more » and the liquid water path (LWP) of trade cumulus clouds, concurrent with measurements of water vapor flux, cloud and aerosol vertical profiles, meteorological data, and surface and total-column aerosol from instrumentation at a ground observatory and on small unmanned aircraft. We present observations which indicate a positive correlation between aerosol and cloud LWP only when considering cases with low atmospheric water vapor (PWV < 40 kg m –2), a criterion which acts to filter the data to control for the natural meteorological variability in the region.We then use the aircraft and ground-based measurements to explore possible mechanisms behind this observed aerosol–LWP correlation. The increase in cloud liquid water is found to coincide with a lowering of the cloud base, which is itself attributable to increased boundary layer humidity in polluted conditions. High pollution is found to correlate with both higher temperatures and higher humidity measured throughout the boundary layer. A large-scale analysis, using satellite observations and meteorological reanalysis, corroborates these covariations: high-pollution cases are shown to originate as a highly polluted boundary layer air mass approaching the observatory from a northwesterly direction. The source air mass exhibits both higher temperatures and higher humidity in the polluted cases. While the warmer temperatures may be attributable to aerosol absorption of solar radiation over the subcontinent, the factors responsible for the coincident high humidity are less evident: the high-aerosol conditions are observed to disperse with air mass evolution, along with a weakening of the high-temperature anomaly, while the high-humidity condition is observed to strengthen in magnitude as the polluted air mass moves over the ocean toward the site of the CARDEX observations. In conclusion, potential causal mechanisms of the observed correlations, including meteorological or aerosol-induced factors, are explored, though future research will be needed for a more complete and quantitative understanding of the aerosol–humidity relationship.« less

Clustering of Synoptic Pattern over the Korean Peninsula from Meteorological Models

NASA Astrophysics Data System (ADS)

Kim, Jinah; Heo, Kiyoung; Choi, Jungwoon; Jung, Sanghoon

2017-04-01

Numerical modeling data on meteorological and ocean science is one of example of big geographic data sources. The properties of the data including the volume, variety, and dynamic aspects pose new challenges for geographic visualization, and visual geoanalytics using big data analysis using machine learning method. A combination of algorithmic and visual approaches that make sense of large volumes of various types of spatiotemporal data are required to gain knowledge about complex phenomena. In the East coast of Korea, it is suffering from property damages and human causalities due to abnormal high waves (swell-like high-height waves). It is known to be caused by local meteorological conditions on the East Sea of Korean Peninsula in previous research and they proposed three kinds of pressure patterns that generate abnormal high waves. However, they cannot describe all kinds of pressure patterns that generate abnormal high waves. In our study, we propose unsupervised machine learning method for pattern clustering and applied it to classify a pattern which has occurred abnormal high waves using numerical meteorological model's reanalysis data from 2000 to 2015 and past historical records of accidents by abnormal high waves. About 25,000 patterns of total spatial distribution of sea surface pressure are clustered into 30 patterns and they are classified into seasonal sea level pressure patterns based on meteorological characteristics of Korean peninsula. Moreover, in order to determine the representative patterns which occurs abnormal high waves, we classified it again using historical accidents cases among the winter season pressure patterns. In this work, we clustered synoptic pattern over the Korean Peninsula in meteorological modeling reanalysis data and we could understand a seasonal variation through identifying the occurrence of clustered synoptic pattern. For the future work, we have to identify the relationship of wave modeling data for better understanding of abnormal high waves and we will develop pattern decision system to predict abnormal high waves in advances. This research was a part of the project titled "Development of Korea Operational Oceanographic System (KOOS), Phase 2" and "Investigation of Large Swell Waves and Rip currents and Development of The Disaster Response System," funded by the Ministry of Oceans & Fisheries Korea (Grant PM59691 and PM59240).

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China

NASA Astrophysics Data System (ADS)

Fang, G. H.; Yang, J.; Chen, Y. N.; Zammit, C.

2015-06-01

Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash-Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

Developing a Time Series Predictive Model for Dengue in Zhongshan, China Based on Weather and Guangzhou Dengue Surveillance Data.

PubMed

Zhang, Yingtao; Wang, Tao; Liu, Kangkang; Xia, Yao; Lu, Yi; Jing, Qinlong; Yang, Zhicong; Hu, Wenbiao; Lu, Jiahai

2016-02-01

Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information. We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation. Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845-2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938-0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance. Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement.

Impact of two chemistry mechanisms fully coupled with mesoscale model on the atmospheric pollutants distribution

NASA Astrophysics Data System (ADS)

Arteta, J.; Cautenet, S.; Taghavi, M.; Audiffren, N.

Air quality models (AQM) consist of many modules (meteorology, emission, chemistry, deposition), and in some conditions such as: vicinity of clouds or aerosols plumes, complex local circulations (mountains, sea breezes), fully coupled models (online method) are necessary. In order to study the impact of lumped chemical mechanisms in AQM simulations, we examine the ability of both different chemical mechanisms: (i) simplified: Condensed Version of the MOdèle de Chimie Atmosphérique 2.2 (CV-MOCA2.2), and (ii) reference: Regional Atmospheric Chemistry Model (RACM), which are coupled online with the Regional Atmospheric Modeling Systems (RAMS) model, on the distribution of pollutants. During the ESCOMPTE experiment (Expérience sur Site pour COntraindre les Modèles de Pollution et de Transport d'Emissions) conducted over Southern France (including urban and industrial zones), Intensive observation periods (IOP) characterized by various meteorological and mixed chemical conditions are simulated. For both configurations of modeling, numerical results are compared with surface measurements (75 stations) for primary (NO x) and secondary (O 3) species. We point out the impact of the two different chemical mechanisms on the production of species involved in the oxidizing capacity such as ozone and radicals within urban and industrial areas. We highlight that both chemical mechanisms produce very similar results for the main pollutants (NO x and O 3) in three-dimensional (3D) distribution, despite large discrepancies in 0D modeling. For ozone concentration, we found sometimes small differences (5-10 ppb) between the mechanisms under study according to the cases (polluted or not). The relative difference between the two mechanisms over the whole domain is only -7% for ozone from CV-MOCA 2.2 versus RACM. When the order of magnitude is needed rather than an accurate estimate, a reduced mechanism is satisfactory. It has the advantage of running faster (four times less than CPU time on SGI 3800 with 30 processors). Simplified mechanisms are really important to study cases for which an online coupling is necessary between meso-scale and chemistry models (clouds or aerosols plumes impacts, highly variable meteorology).

Aircraft measurements of pollution species near Bermuda and the east coast of the United States during CASE-WATOX. Technical memo

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunter, R.L.; Boatman, J.F.

1989-10-01

Chemical, meteorological, and aerosol measurements were made with the NOAA King Air C-90 aircraft during July 1988 near Bermuda and the east coast of the U.S. The study extended the 1985 and 1986 Western Atlantic Ocean Experiment (WATOX) and initiated coordinated aircraft and ship measurements, following the design of the Coordinated Air Sea Experiment (CASE), in which flights were planned to be made in the vicinity of the NOAA ship Mt. Mitchell. The report lists the objectives of the CASE-WATOX program; the instrumentation used, and the data obtained with the aircraft; a general outline of ship and aircraft coordination andmore » instrumentation; and the aircraft data processing, quality and availability.« less

Compendium of Lecture Notes for Training Class III Meteorological Personnel.

ERIC Educational Resources Information Center

Retallack, B. J.

This compendium of lecture notes provides a course of study for persons who may be involved in a variety of specialized meteorological tasks. The course is considered to be advanced and assumes students have had introductory experiences in meteorology and earth science (covered in a similar compendium). The material is presented in seven units…

NASA Cold Land Processes Experiment (CLPX 2002/03): Ground-based and near-surface meteorological observations

Treesearch

Kelly Elder; Don Cline; Angus Goodbody; Paul Houser; Glen E. Liston; Larry Mahrt; Nick Rutter

2009-01-01

A short-term meteorological database has been developed for the Cold Land Processes Experiment (CLPX). This database includes meteorological observations from stations designed and deployed exclusively for CLPXas well as observations available from other sources located in the small regional study area (SRSA) in north-central Colorado. The measured weather parameters...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reiter, R.; Kanter, H. J.; Sladkovic, R.

The balance of the tropospheric ozone is studied with regard to sources and sinks. The influx of stratospheric ozone through stratospheric intrusions and photochemical production under pure air conditions is discussed. The 4-year measuring series (1977-1980) of the ozone concentration measured at 3 different levels are evaluated, the influence of meteorological parameters is examined. The time variation of the ozone layer between 1000 and 3000 m ASL is investigated as a function of different ozone sources. First results show that stratospheric ozone arriving at the troposphere penetrates only in a few rare cases to the ground layer below 1500 mmore » ASL. Most of the time, the variation of ozone concentration in this layer is determined by photochemical processes which are, in turn, controlled by meteorological parameters. The upper boundary of the photochemically active layer is found at about 500 m above ground. Variability of the concentration of stratospheric aerosol and its optical properties after the volcanic eruptions in the year 1980 are discussed on the basis on lidar backscattering measurements.« less

Environmental risk analysis of oil handling facilities in port areas. Application to Tarragona harbor (NE Spain).

PubMed

Valdor, Paloma F; Gómez, Aina G; Puente, Araceli

2015-01-15

Diffuse pollution from oil spills is a widespread problem in port areas (as a result of fuel supply, navigation and loading/unloading activities). This article presents a method to assess the environmental risk of oil handling facilities in port areas. The method is based on (i) identification of environmental hazards, (ii) characterization of meteorological and oceanographic conditions, (iii) characterization of environmental risk scenarios, and (iv) assessment of environmental risk. The procedure has been tested by application to the Tarragona harbor. The results show that the method is capable of representing (i) specific local pollution cases (i.e., discriminating between products and quantities released by a discharge source), (ii) oceanographic and meteorological conditions (selecting a representative subset data), and (iii) potentially affected areas in probabilistic terms. Accordingly, it can inform the design of monitoring plans to study and control the environmental impact of these facilities, as well as the design of contingency plans. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using Convective Stratiform Technique (CST) method to estimate rainfall (case study in Bali, December 14th 2016)

NASA Astrophysics Data System (ADS)

Vista Wulandari, Ayu; Rizki Pratama, Khafid; Ismail, Prayoga

2018-05-01

Accurate and realtime data in wide spatial space at this time is still a problem because of the unavailability of observation of rainfall in each region. Weather satellites have a very wide range of observations and can be used to determine rainfall variability with better resolution compared with a limited direct observation. Utilization of Himawari-8 satellite data in estimating rainfall using Convective Stratiform Technique (CST) method. The CST method is performed by separating convective and stratiform cloud components using infrared channel satellite data. Cloud components are classified by slope because the physical and dynamic growth processes are very different. This research was conducted in Bali area on December 14, 2016 by verifying the result of CST process with rainfall data from Ngurah Rai Meteorology Station Bali. It is found that CST method result had simililar value with data observation in Ngurah Rai meteorological station, so it assumed that CST method can be used for rainfall estimation in Bali region.

Snow precipitation in Adelie Land, Antarctica. MAR validation using data from a meteorological radar

NASA Astrophysics Data System (ADS)

Gallée, Hubert; Grazioli, Jacopo; Berne, Alexis; Christophe, Genthon

2017-04-01

The regional climate model MAR (Modèle Atmosphérique Régional) has been run over Adélie Land in the frame of the APRES3 project, in order to understand the different physical mechanisms affecting precipitation in this region. An horizontal resolution of 5 km is used. Several case studies have been considered during the period between december 2015 and may 2016. MAR snow precipitation flux is compared to observations made with a meteorological radar operating at Dumont d'Urville during this period. It is found that MAR sometimes simulates a maximum in the precipitation flux which is situated well above the ground, as in the observations. Possible causes may the found in the influence of the dry katabatic airflow often observed in Adélie Land. Our work indicates that the retreive of a precipitation climatology from satellite observations must be done with caution, when these observations are possible only for a significant height above the ground.

Experimental Forecasts of Wildfire Pollution at the Canadian Meteorological Centre

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Beaulieu, Paul-Andre; Chen, Jack; Landry, Hugo; Cousineau, Sophie; Moran, Michael

2016-04-01

Environment and Climate Change Canada's Canadian Meteorological Centre Operations division (CMCO) has been running an experimental North American air quality forecast system with near-real-time wildfire emissions since 2014. This system, named FireWork, also takes anthropogenic and other natural emission sources into account. FireWork 48-hour forecasts are provided to CMCO forecasters and external partners in Canada and the U.S. twice daily during the wildfire season. This system has proven to be very useful in capturing short- and long-range smoke transport from wildfires over North America. Several upgrades to the FireWork system have been made since 2014 to accommodate the needs of operational AQ forecasters and to improve system performance. In this talk we will present performance statistics and some case studies for the 2014 and 2015 wildfire seasons. We will also describe current limitations of the FireWork system and ongoing and future work planned for this air quality forecast system.

LES-based generation of high-frequency fluctuation in wind turbulence obtained by meteorological model

NASA Astrophysics Data System (ADS)

Tamura, Tetsuro; Kawaguchi, Masaharu; Kawai, Hidenori; Tao, Tao

2017-11-01

The connection between a meso-scale model and a micro-scale large eddy simulation (LES) is significant to simulate the micro-scale meteorological problem such as strong convective events due to the typhoon or the tornado using LES. In these problems the mean velocity profiles and the mean wind directions change with time according to the movement of the typhoons or tornadoes. Although, a fine grid micro-scale LES could not be connected to a coarse grid meso-scale WRF directly. In LES when the grid is suddenly refined at the interface of nested grids which is normal to the mean advection the resolved shear stresses decrease due to the interpolation errors and the delay of the generation of smaller scale turbulence that can be resolved on the finer mesh. For the estimation of wind gust disaster the peak wind acting on buildings and structures has to be correctly predicted. In the case of meteorological model the velocity fluctuations have a tendency of diffusive variation without the high frequency component due to the numerically filtering effects. In order to predict the peak value of wind velocity with good accuracy, this paper proposes a LES-based method for generating the higher frequency components of velocity and temperature fields obtained by meteorological model.

Usage of NASA's Near Real-Time Solar and Meteorological Data for Monitoring Building Energy Systems Using RETScreen International's Performance Analysis Module

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Charles, Robert W.; Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Ziegler, Urban; Leng, Gregory J.; Meloche, Nathalie; Bourque, Kevin

2012-01-01

This paper describes building energy system production and usage monitoring using examples from the new RETScreen Performance Analysis Module, called RETScreen Plus. The module uses daily meteorological (i.e., temperature, humidity, wind and solar, etc.) over a period of time to derive a building system function that is used to monitor building performance. The new module can also be used to target building systems with enhanced technologies. If daily ambient meteorological and solar information are not available, these are obtained over the internet from NASA's near-term data products that provide global meteorological and solar information within 3-6 days of real-time. The accuracy of the NASA data are shown to be excellent for this purpose enabling RETScreen Plus to easily detect changes in the system function and efficiency. This is shown by several examples, one of which is a new building at the NASA Langley Research Center that uses solar panels to provide electrical energy for building energy and excess energy for other uses. The system shows steady performance within the uncertainties of the input data. The other example involves assessing the reduction in energy usage by an apartment building in Sweden before and after an energy efficiency upgrade. In this case, savings up to 16% are shown.

Using satellites and global models to investigate aerosol-cloud interactions

NASA Astrophysics Data System (ADS)

Gryspeerdt, E.; Quaas, J.; Goren, T.; Sourdeval, O.; Mülmenstädt, J.

2017-12-01

Aerosols are known to impact liquid cloud properties, through both microphysical and radiative processes. Increasing the number concentration of aerosol particles can increase the cloud droplet number concentration (CDNC). Through impacts on precipitation processes, this increase in CDNC may also be able to impact the cloud fraction (CF) and the cloud liquid water path (LWP). Several studies have looked into the effect of aerosols on the CDNC, but as the albedo of a cloudy scene depends much more strongly on LWP and CF, an aerosol influence on these properties could generate a significant radiative forcing. While the impact of aerosols on cloud properties can be seen in case studies involving shiptracks and volcanoes, producing a global estimate of these effects remains challenging due to the confounding effect of local meteorology. For example, relative humidity significantly impacts the aerosol optical depth (AOD), a common satellite proxy for CCN, as well as being a strong control on cloud properties. This can generate relationships between AOD and cloud properties, even when there is no impact of aerosol-cloud interactions. In this work, we look at how aerosol-cloud interactions can be distinguished from the effect of local meteorology in satellite studies. With a combination global climate models and multiple sources of satellite data, we show that the choice of appropriate mediating variables and case studies can be used to develop constraints on the aerosol impact on CF and LWP. This will lead to improved representations of clouds in global climate models and help to reduce the uncertainty in the global impact of anthropogenic aerosols on cloud properties.

A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Demirel, Mehmet C.

2017-10-01

The changing climate and the associated future increases in temperature are expected to have impacts on drought characteristics and hydrologic cycle. This paper investigates the projected changes in spatiotemporal characteristics of droughts and their future attributes over the Willamette River Basin (WRB) in the Pacific Northwest U.S. The analysis is performed using two subsets of downscaled CMIP5 global climate models (GCMs) each consisting of 10 models from two future scenarios (RCP4.5 and RCP8.5) for 30 years of historical period (1970-1999) and 90 years of future projections (2010-2099). Hydrologic modeling is conducted using the Precipitation Runoff Modeling System (PRMS) as a robust distributed hydrologic model with lower computational cost compared to other models. Meteorological and hydrological droughts are studied using three drought indices (i.e. Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index, Standardized Streamflow Index). Results reveal that the intensity and duration of hydrological droughts are expected to increase over the WRB, albeit the annual precipitation is expected to increase. On the other hand, the intensity of meteorological droughts do not indicate an aggravation for most cases. We explore the changes of hydrometeolorogical variables over the basin in order to understand the causes for such differences and to discover the controlling factors of drought. Furthermore, the uncertainty of projections are quantified for model, scenario, and downscaling uncertainty.

Sensitivity of surface meteorological analyses to observation networks

NASA Astrophysics Data System (ADS)

Tyndall, Daniel Paul

A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.

Sensitivity of Hydrologic Extremes to Spatial Resolution of Meteorological Forcings: A Case Study of the Conterminous United States

NASA Astrophysics Data System (ADS)

Kao, S. C.; Naz, B. S.; Gangrade, S.; Ashfaq, M.; Rastogi, D.

2016-12-01

The magnitude and frequency of hydroclimate extremes are projected to increase in the conterminous United States (CONUS) with significant implications for future water resource planning and flood risk management. Nevertheless, apart from the change of natural environment, the choice of model spatial resolution could also artificially influence the features of simulated extremes. To better understand how the spatial resolution of meteorological forcings may affect hydroclimate projections, we test the runoff sensitivity using the Variable Infiltration Capacity (VIC) model that was calibrated for each CONUS 8-digit hydrologic unit (HUC8) at 1/24° ( 4km) grid resolution. The 1980-2012 gridded Daymet and PRISM meteorological observations are used to conduct the 1/24° resolution control simulation. Comparative simulations are achieved by smoothing the 1/24° forcing into 1/12° and 1/8° resolutions which are then used to drive the VIC model for the CONUS. In addition, we also test how the simulated high and low runoff conditions would react to change in precipitation (±10%) and temperature (+1°C). The results are further analyzed for various types of hydroclimate extremes across different watersheds in the CONUS. This work helps us understand the sensitivity of simulated runoff to different spatial resolutions of climate forcings and also its sensitivity to different watershed sizes and characteristics of extreme events in the future climate conditions.

Effect of Meteorological Conditions and Geographical Factors in the Onset of Enterovirus 71

NASA Astrophysics Data System (ADS)

Chen, Yu-An; Yu, Hwa-Lung

2015-04-01

Since it was first recognized in California in 1969, enterovirus 71 (EV71) infection has been a significant cause of neurological disorder and death in children worldwide. In 1998 a historic epidemic of EV71 infection caused hand-foot-and-mouth disease and herpangina in thousands of people in Taiwan. The impact of EV71 infection is greatest during the summer months in Asia, and epidemics recur with a seasonal pattern. It was reported that seasonal patterns of EV71 differed by geographical localities. Previous studies have also showed significant relationships between meteorological variables, in particular, temperature and relative humidity, and the seasonal epidemic patterns of EV71. However, important issues that remain unclear include the spatiotemporal pattern of the EV71 outbreaks in Taiwan, and what role of favorable meteorological conditions in the transmission of the disease in the space-time domain. Thus, this study used a semiparametric generalized additive model (GAM) to understand the association between EV71 and meteorological factors across space and time. This study utilized a population-based database containing space-time data for clinic and hospital visits (i.e., hospital location and appointment times) of EV71 occurring in children less than 18 years old in Taipei from 1998 to 2008. Meteorological data (i.e., temperature, rainfall, and relative humidity) for the study period were provided by the Taiwan Central Weather Bureau. This study expect to find out an important meteorological factor and threshold.

Dynamical behavior of the correlation between meteorological factors

NASA Astrophysics Data System (ADS)

You, Cheol-Hwan; Chang, Ki-Ho; Lee, Jun-Ho; Kim, Kyungsik

2017-12-01

We study the temporal and spatial variation characteristics of meteorological factors (temperature, humidity, and wind velocity) at a meteorological tower located on Bosung-gun of South Korea. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation from data of meteorological factors. The relationships between meteorological factors are identified and quantified by using DCCA coefficients. From our results, we ascertain that the DCCA coefficient between temperature and humidity at time lag m = 24 has the smallest value at the height of 10 m of the measuring tower. Particularly, the DCCA coefficient between temperature and wind speed at time lag m = 24 has the largest value at a height of 10 m of the measuring tower

Meteorological interpretation of transient LOD changes

NASA Astrophysics Data System (ADS)

Masaki, Y.

2008-04-01

The Earth’s spin rate is mainly changed by zonal winds. For example, seasonal changes in global atmospheric circulation and episodic changes accompanied with El Nĩ os are clearly detected n in the Length-of-day (LOD). Sub-global to regional meteorological phenomena can also change the wind field, however, their effects on the LOD are uncertain because such LOD signals are expected to be subtle and transient. In our previous study (Masaki, 2006), we introduced atmospheric pressure gradients in the upper atmosphere in order to obtain a rough picture of the meteorological features that can change the LOD. In this presentation, we compare one-year LOD data with meteorological elements (winds, temperature, pressure, etc.) and make an attempt to link transient LOD changes with sub-global meteorological phenomena.

A Reduced Form Model for Ozone Based on Two Decades of ...

EPA Pesticide Factsheets

A Reduced Form Model (RFM) is a mathematical relationship between the inputs and outputs of an air quality model, permitting estimation of additional modeling without costly new regional-scale simulations. A 21-year Community Multiscale Air Quality (CMAQ) simulation for the continental United States provided the basis for the RFM developed in this study. Predictors included the principal component scores (PCS) of emissions and meteorological variables, while the predictand was the monthly mean of daily maximum 8-hour CMAQ ozone for the ozone season at each model grid. The PCS form an orthogonal basis for RFM inputs. A few PCS incorporate most of the variability of emissions and meteorology, thereby reducing the dimensionality of the source-receptor problem. Stochastic kriging was used to estimate the model. The RFM was used to separate the effects of emissions and meteorology on ozone concentrations. by running the RFM with emissions constant (ozone dependent on meteorology), or constant meteorology (ozone dependent on emissions). Years with ozone-conducive meteorology were identified, and meteorological variables best explaining meteorology-dependent ozone were identified. Meteorology accounted for 19% to 55% of ozone variability in the eastern US, and 39% to 92% in the western US. Temporal trends estimated for original CMAQ ozone data and emission-dependent ozone were mostly negative, but the confidence intervals for emission-dependent ozone are much

Lightning characterization through acoustic and electromagnetic measurements recorded during the HyMeX SOP1 and simulation of the acoustic nonlinear propagation in realistic thunderstorm meteorological conditions

NASA Astrophysics Data System (ADS)

Gallin, L.; Coulouvrat, F.; Farges, T.; Marchiano, R.; Defer, E.; Rison, W.; Schulz, W.; Nuret, M.

2013-12-01

The goal is to study the transformation of the thunder (amplitude, spectrum) during its travel from the lightning channel towards a detector (microphone, microbarometer), considering propagation distances of less than 50 km and complex local meteorological properties. Inside the European HyMeX project, the SOP1 campaign (2012) took place from September 2012 to November 2012 in South of France. An acoustic station (center: 4.39° E, 44.08° N) composed of a microphone array placed inside a microbarometer array was installed by CEA near city of Uzès. It was located in the center of an LMA network coming with two slow antennas. This network was deployed in France for the first time by the New Mexico Tech and LERMA laboratory. The detections from the European lightning location system EUCLID complete this dataset. During the SOP1 period several storms passed over the station. The post-processings of the records point out days with interesting thunderstorms. Especially during the 26th of October 2012 in the evening (around 8 pm) a thunderstorm passed just over the acoustic station. Not too many lightning strokes are detected by EUCLID, the corresponding flashes are then well characterized by the LMA network. Slow antennas present good electric field measurements. The acoustic records have excellent quality. We present for some selected flashes a comparative study of the different measurements (LMA, slow antenna, EUCLID, microphones, microbarometers): focusing on amplitude and spectrum of the thunder waveforms, and on propagation effects due to the meteorological conditions. To quantify the impact of these meteorological conditions on the propagating thunder (from the lightning sources to the acoustic array), a code named Flhoward is used [Dagrau et al., J. Acoust. Soc. Am., 130, 20-32, 2011][Coulouvrat, Wave Motion, 49, 50--63, 2012]. It is designed to simulate the nonlinear propagation of acoustic shock waves through a realistic atmosphere model (including temperature gradients, rigid ground, and wind flows). The meteorological conditions are extracted from the data calculated by Météo-France weather forecast model AROME-WMED for the chosen days. Some cases where numerical simulation helps to understand the observations are presented.

Daily weather variables and affective disorder admissions to psychiatric hospitals

NASA Astrophysics Data System (ADS)

McWilliams, Stephen; Kinsella, Anthony; O'Callaghan, Eadbhard

2014-12-01

Numerous studies have reported that admission rates in patients with affective disorders are subject to seasonal variation. Notwithstanding, there has been limited evaluation of the degree to which changeable daily meteorological patterns influence affective disorder admission rates. A handful of small studies have alluded to a potential link between psychiatric admission rates and meteorological variables such as environmental temperature (heat waves in particular), wind direction and sunshine. We used the Kruskal-Wallis test, ARIMA and time-series regression analyses to examine whether daily meteorological variables—namely wind speed and direction, barometric pressure, rainfall, hours of sunshine, sunlight radiation and temperature—influence admission rates for mania and depression across 12 regions in Ireland over a 31-year period. Although we found some very weak but interesting trends for barometric pressure in relation to mania admissions, daily meteorological patterns did not appear to affect hospital admissions overall for mania or depression. Our results do not support the small number of papers to date that suggest a link between daily meteorological variables and affective disorder admissions. Further study is needed.

Assessment of the ARW-WRF model over complex terrain: the case of the Stellenbosch Wine of Origin district of South Africa

NASA Astrophysics Data System (ADS)

Soltanzadeh, Iman; Bonnardot, Valérie; Sturman, Andrew; Quénol, Hervé; Zawar-Reza, Peyman

2017-08-01

Global warming has implications for thermal stress for grapevines during ripening, so that wine producers need to adapt their viticultural practices to ensure optimum physiological response to environmental conditions in order to maintain wine quality. The aim of this paper is to assess the ability of the Weather Research and Forecasting (WRF) model to accurately represent atmospheric processes at high resolution (500 m) during two events during the grapevine ripening period in the Stellenbosch Wine of Origin district of South Africa. Two case studies were selected to identify areas of potentially high daytime heat stress when grapevine photosynthesis and grape composition were expected to be affected. The results of high-resolution atmospheric model simulations were compared to observations obtained from an automatic weather station (AWS) network in the vineyard region. Statistical analysis was performed to assess the ability of the WRF model to reproduce spatial and temporal variations of meteorological parameters at 500-m resolution. The model represented the spatial and temporal variation of meteorological variables very well, with an average model air temperature bias of 0.1 °C, while that for relative humidity was -5.0 % and that for wind speed 0.6 m s-1. Variation in model performance varied between AWS and with time of day, as WRF was not always able to accurately represent effects of nocturnal cooling within the complex terrain. Variations in performance between the two case studies resulted from effects of atmospheric boundary layer processes in complex terrain under the influence of the different synoptic conditions prevailing during the two periods.

Sub-kilometer Numerical Weather Prediction in complex urban areas

NASA Astrophysics Data System (ADS)

Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

2013-12-01

A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

BOREAS TF-2 SSA-OA Tethersonde Meteorological and Ozone Data

NASA Technical Reports Server (NTRS)

Arnold, A. James; Mickle, Robert E.; Hall, Forrest G. (Editor); Huemmrich, Karl (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study Tower Flux-2 (BOREAS TF-2) team collected meteorological and ozone measurements from instruments mounted below a tethered balloon. These data were collected at the Southern Study Area Old Aspen (SSA-OA) site to extend meteorological and ozone measurements made from the flux tower to heights of 300 m. The tethersonde operated during the fall of 1993 and the spring, summer, and fall of 1994. The data are available in tabular ASCII files.

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis

NASA Astrophysics Data System (ADS)

Gemitzi, Alexandra; Stefanopoulos, Kyriakos

2011-06-01

SummaryGroundwaters and their dependent ecosystems are affected both by the meteorological conditions as well as from human interventions, mainly in the form of groundwater abstractions for irrigation needs. This work aims at investigating the quantitative effects of meteorological conditions and man intervention on groundwater resources and their dependent ecosystems. Various seasonal Auto-Regressive Integrated Moving Average (ARIMA) models with external predictor variables were used in order to model the influence of meteorological conditions and man intervention on the groundwater level time series. Initially, a seasonal ARIMA model that simulates the abstraction time series using as external predictor variable temperature ( T) was prepared. Thereafter, seasonal ARIMA models were developed in order to simulate groundwater level time series in 8 monitoring locations, using the appropriate predictor variables determined for each individual case. The spatial component was introduced through the use of Geographical Information Systems (GIS). Application of the proposed methodology took place in the Neon Sidirochorion alluvial aquifer (Northern Greece), for which a 7-year long time series (i.e., 2003-2010) of piezometric and groundwater abstraction data exists. According to the developed ARIMA models, three distinct groups of groundwater level time series exist; the first one proves to be dependent only on the meteorological parameters, the second group demonstrates a mixed dependence both on meteorological conditions and on human intervention, whereas the third group shows a clear influence from man intervention. Moreover, there is evidence that groundwater abstraction has affected an important protected ecosystem.

Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

NASA Astrophysics Data System (ADS)

Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

2009-04-01

In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be either an intermediate forecast between the extremes of the ensemble spread or a manually selected forecast based on a meteorologists advice. 2. Downstream catchments with low influence of weather forecast In downstream catchments with strong human impact on discharge (e.g. by reservoir operation) and large influence of upstream gauge observation quality on forecast quality, the 'overall error' may in most cases be larger than the combination of the 'model error' and an ensemble spread. Therefore, the overall forecast uncertainty bounds are calculated differently: a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. Here, additionally the corresponding inflow hydrograph from all upstream catchments must be used. b) As for an upstream catchment, the uncertainty range is determined by combination of 'model error' and the ensemble member forecasts c) In addition, the 'overall error' is superimposed on the 'lead forecast'. For reasons of consistency, the lead forecast must be based on the same meteorological forecast in the downstream and all upstream catchments. d) From the resulting two uncertainty ranges (one from the ensemble forecast and 'model error', one from the 'lead forecast' and 'overall error'), the envelope is taken as the most prudent uncertainty range. In sum, the uncertainty associated with each forecast run is calculated and communicated to the public in the form of 10% and 90% percentiles. As in part I of this study, the methodology as well as the useful- or uselessness of the resulting uncertainty ranges will be presented and discussed by typical examples.

Alarm Variables for Dengue Outbreaks: A Multi-Centre Study in Asia and Latin America

PubMed Central

Bowman, Leigh R.; Tejeda, Gustavo S.; Coelho, Giovanini E.; Sulaiman, Lokman H.; Gill, Balvinder S.; McCall, Philip J.; Olliaro, Piero L.; Ranzinger, Silvia R.; Quang, Luong C.; Ramm, Ronald S.; Kroeger, Axel; Petzold, Max G.

2016-01-01

Background Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently. Methodology/Principal Findings The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007–2013. These data were split between the years 2007–2011 (historic period) and 2012–2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1–12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1–12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4–16 weeks. Conclusions/Significance An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission. PMID:27348752

ANALYSIS OF METEOROLOGICAL CONDITIONS DURING THE 1977 ANCLOTE KEYS PLUME STUDY

EPA Science Inventory

Meteorological conditions are described and analyzed for nine experimental observation periods of the Anclote Keys Plume Study, which was conducted near Tampa, Florida during February 1977. The primary objective of the Plume Study was to investigate both the short and long range ...

Assessing Fire Weather Index using statistical downscaling and spatial interpolation techniques in Greece

NASA Astrophysics Data System (ADS)

Karali, Anna; Giannakopoulos, Christos; Frias, Maria Dolores; Hatzaki, Maria; Roussos, Anargyros; Casanueva, Ana

2013-04-01

Forest fires have always been present in the Mediterranean ecosystems, thus they constitute a major ecological and socio-economic issue. The last few decades though, the number of forest fires has significantly increased, as well as their severity and impact on the environment. Local fire danger projections are often required when dealing with wild fire research. In the present study the application of statistical downscaling and spatial interpolation methods was performed to the Canadian Fire Weather Index (FWI), in order to assess forest fire risk in Greece. The FWI is used worldwide (including the Mediterranean basin) to estimate the fire danger in a generalized fuel type, based solely on weather observations. The meteorological inputs to the FWI System are noon values of dry-bulb temperature, air relative humidity, 10m wind speed and precipitation during the previous 24 hours. The statistical downscaling methods are based on a statistical model that takes into account empirical relationships between large scale variables (used as predictors) and local scale variables. In the framework of the current study the statistical downscaling portal developed by the Santander Meteorology Group (https://www.meteo.unican.es/downscaling) in the framework of the EU project CLIMRUN (www.climrun.eu) was used to downscale non standard parameters related to forest fire risk. In this study, two different approaches were adopted. Firstly, the analogue downscaling technique was directly performed to the FWI index values and secondly the same downscaling technique was performed indirectly through the meteorological inputs of the index. In both cases, the statistical downscaling portal was used considering the ERA-Interim reanalysis as predictands due to the lack of observations at noon. Additionally, a three-dimensional (3D) interpolation method of position and elevation, based on Thin Plate Splines (TPS) was used, to interpolate the ERA-Interim data used to calculate the index. Results from this method were compared with the statistical downscaling results obtained from the portal. Finally, FWI was computed using weather observations obtained from the Hellenic National Meteorological Service, mainly in the south continental part of Greece and a comparison with the previous results was performed.

Lower Stratospheric Temperature Differences Between Meteorological Analyses in two cold Arctic Winters and their Impact on Polar Processing Studies

NASA Technical Reports Server (NTRS)

Manney, Gloria L.; Sabutis, Joseph L.; Pawson, Steven; Santee, Michelle L.; Naujokat, Barbara; Swinbank, Richard; Gelman, Melvyn E.; Ebisuzaki, Wesley; Atlas, Robert (Technical Monitor)

2001-01-01

A quantitative intercomparison of six meteorological analyses is presented for the cold 1999-2000 and 1995-1996 Arctic winters. The impacts of using different analyzed temperatures in calculations of polar stratospheric cloud (PSC) formation potential, and of different winds in idealized trajectory-based temperature histories, are substantial. The area with temperatures below a PSC formation threshold commonly varies by approximately 25% among the analyses, with differences of over 50% at some times/locations. Freie University at Berlin analyses are often colder than others at T is less than or approximately 205 K. Biases between analyses vary from year to year; in January 2000. U.K. Met Office analyses were coldest and National Centers for Environmental Prediction (NCEP) analyses warmest. while NCEP analyses were usually coldest in 1995-1996 and Met Office or NCEP[National Center for Atmospheric Research Reanalysis (REAN) warmest. European Centre for Medium Range Weather Forecasting (ECMWF) temperatures agreed better with other analyses in 1999-2000, after improvements in the assimilation model. than in 1995-1996. Case-studies of temperature histories show substantial differences using Met Office, NCEP, REAN and NASA Data Assimilation Office (DAO) analyses. In January 2000 (when a large cold region was centered in the polar vortex), qualitatively similar results were obtained for all analyses. However, in February 2000 (a much warmer period) and in January and February 1996 (comparably cold to January 2000 but with large cold regions near the polar vortex edge), distributions of "potential PSC lifetimes" and total time spent below a PSC formation threshold varied significantly among the analyses. Largest peaks in "PSC lifetime" distributions in January 2000 were at 4-6 and 11-14 days. while in the 1996 periods, they were at 1-3 days. Thus different meteorological conditions in comparably cold winters had a large impact on expectations for PSC formation and on the discrepancies between different meteorological analyses. Met Office. NCEP, REAN, ECMWF and DAO analyses are commonly used for trajectory calculations and in chemical transport models; the choice of which analysis to use can strongly influence the results of such studies.

Observed Cloud Properties Above the Northern Indian Ocean During CARDEX 2012

NASA Astrophysics Data System (ADS)

Gao, L.; Wilcox, E. M.

2016-12-01

An analysis of cloud microphysical, macrophysical and radiative properties during the dry winter monsoon season above the northern Indian Ocean is presented. The Cloud Aerosol Radiative Forcing Experiment (CARDEX), conducted from 16 February to 30 March 2012 at the Maldives Climate Observatory on Hanimaadhoo (MCOH), used autonomous unmanned aerial vehicles (UAVs) to measure the aerosol profiles, water vapor flux and cloud properties concurrent with continuous ground measurements of surface aerosol and meteorological variables as well as the total-column precipitable water vapor (PWV) and the cloud liquid water path (LWP). Here we present the cloud properties only for the cases with lower atmospheric water vapor using the criterion that the PWV less than 40 kg/m2. This criterion acts to filter the data to control for the natural meteorological variability in the region according to previous studies. The high polluted case is found to correlate with warmer temperature, higher relative humidity in boundary layer and lower lifted condensation level (LCL). Micro Pulse Lidar (MPL) retrieved cloud base height coincides with calculated LCL height which is lower for high polluted case. Meanwhile satellite retrieved cloud top height didn't show obvious variation indicating cloud deepening which is consistent with the observed greater cloud LWP in high polluted case. Those high polluted clouds are associated with more cloud droplets and smaller effective radius and are generally becoming narrower due to the stronger cloud side evaporation-entrainment effect and becoming deeper due to more moist static energy. Clouds in high polluted condition become brighter with higher albedo which can cause a net shortwave forcing over -40 W/m2 in this region.

Lack of evidence for meteorological effects on infradian dynamics of testosterone

NASA Astrophysics Data System (ADS)

Celec, Peter; Smreková, Lucia; Ostatníková, Daniela; Čabajová, Zlata; Hodosy, Július; Kúdela, Matúš

2009-09-01

Climatic factors are known to influence the endocrine system. Previous studies have shown that circannual seasonal variations of testosterone might be partly explained by changes in air temperature. Whether infradian variations are affected by meteorological factors is unknown. To analyze possible effects of meteorological parameters on infradian variations of salivary testosterone levels in both sexes, daily salivary testosterone levels were measured during 1 month in 14 men and 17 women. A correlation analysis between hormonal levels and selected meteorological parameters was performed. The results indicate that high testosterone levels are loosely associated with cold, sunny and dry weather in both sexes. However, only the correlations between testosterone and air temperature (men) and actual cloudiness (women) were statistically significant ( p < 0,05). Although some correlations reached the level of statistical significance, the effects of selected meteorological parameters on salivary testosterone levels remain unclear. Further longer-term studies concentrating on air temperature, cloudiness and average relative humidity in relation to the sex hormone axis are needed.

Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

PubMed Central

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-01-01

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356

Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences.

PubMed

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-10-16

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.

Estimating urban ground-level PM10 using MODIS 3km AOD product and meteorological parameters from WRF model

NASA Astrophysics Data System (ADS)

Ghotbi, Saba; Sotoudeheian, Saeed; Arhami, Mohammad

2016-09-01

Satellite remote sensing products of AOD from MODIS along with appropriate meteorological parameters were used to develop statistical models and estimate ground-level PM10. Most of previous studies obtained meteorological data from synoptic weather stations, with rather sparse spatial distribution, and used it along with 10 km AOD product to develop statistical models, applicable for PM variations in regional scale (resolution of ≥10 km). In the current study, meteorological parameters were simulated with 3 km resolution using WRF model and used along with the rather new 3 km AOD product (launched in 2014). The resulting PM statistical models were assessed for a polluted and largely variable urban area, Tehran, Iran. Despite the critical particulate pollution problem, very few PM studies were conducted in this area. The issue of rather poor direct PM-AOD associations existed, due to different factors such as variations in particles optical properties, in addition to bright background issue for satellite data, as the studied area located in the semi-arid areas of Middle East. Statistical approach of linear mixed effect (LME) was used, and three types of statistical models including single variable LME model (using AOD as independent variable) and multiple variables LME model by using meteorological data from two sources, WRF model and synoptic stations, were examined. Meteorological simulations were performed using a multiscale approach and creating an appropriate physic for the studied region, and the results showed rather good agreements with recordings of the synoptic stations. The single variable LME model was able to explain about 61%-73% of daily PM10 variations, reflecting a rather acceptable performance. Statistical models performance improved through using multivariable LME and incorporating meteorological data as auxiliary variables, particularly by using fine resolution outputs from WRF (R2 = 0.73-0.81). In addition, rather fine resolution for PM estimates was mapped for the studied city, and resulting concentration maps were consistent with PM recordings at the existing stations.

Traffic congestion and ozone precursor emissions in Bilbao, Spain.

PubMed

Ibarra-Berastegi, Gabriel; Madariaga, Imanol

2003-01-01

In urban environments, the measured levels of ozone are the result of the interaction between emissions of precursors (mainly VOCs and NOx) and meteorological effects. In this work, time series of daily values of ozone, measured at three locations in Bilbao (Spain), have been built. Then, after removing meteorological effects from them, ozone and traffic data have been analyzed jointly. The goal was to identify traffic situations and link them to ozone levels in the area of Bilbao. To remove meteorological effects from the selected ozone time series, the technique developed by Rao and Zurbenko was used. This is a widely used technique and, after its application, the fraction obtained from a given ozone time series represents an ozone forming capability attributable to emissions of precursors. This fraction is devoid of any meteorological influence and includes only the apportion of periodicities above 1.7 years. In the case of Bilbao, the ozone fractions obtained at three locations have been compared on that time scale with traffic data from the area. For the 1993-1996 period, a regression analysis of the ozone and traffic fractions due to periodicities above 1.7 years (long-term fractions), shows that traffic is the main explanatory factor for ozone with R2 ranging from 0.916 to 0.996 at the three locations studied. Analysis of these longterm fractions has made it possible to identify two traffic regimes for the whole area, associated to different profiles of ozone forming capability. The first one favors low ozone forming capability, and is associated with a situation of fluent traffic. The second one shows high ozone forming capability and represents congestion. Joint analysis of raw data of ozone and traffic do not show any clear pattern due to the strong masking effects that seasonal-meteorological effects (mainly radiation) have on the measured ozone signal. If only immission data of ozone are available, as in this case, a comparison between ozone and traffic can only be made on the long-term time scale, since that is the only fraction embedded in the ozone time series that can exclusively be attributed to emissions of precursors. This fact stresses the need to study the different fractions embedded in the time series of ozone measured levels separately. Though the coefficients obtained in the regression are only valid for the 1993-1996 period, these traffic regimes represent long-term targets (congestion or fluent traffic) that can inspire policies for a joint management of the traffic and pollution by ozone in the area of Bilbao beyond that period. The results of this work show the need of a joint management of ozone and traffic in Bilbao. Since an accurate knowledge of traffic was not available, the use of emission factors to relate traffic and actual ozone levels has not been possible. For this reason, this study has focused on the long-term fractions of traffic and ozone. In the future, if a more accurate knowledge of traffic is available, it will be possible to find relationships between traffic and ozone on all time scales.

Ozone indices based on simple meteorological parameters: potentials and limitations of regression and neural network models

NASA Astrophysics Data System (ADS)

Soja, G.; Soja, A.-M.

This study tested the usefulness of extremely simple meteorological models for the prediction of ozone indices. The models were developed with the input parameters of daily maximum temperature and sunshine duration and are based on a data collection period of three years. For a rural environment in eastern Austria, the meteorological and ozone data of three summer periods have been used to develop functions to describe three ozone exposure indices (daily maximum, 7 h mean 9.00-16.00 h, accumulated ozone dose AOT40). Data sets for other years or stations not included in the development of the models were used as test data to validate the performance of the models. Generally, optimized regression models performed better than simplest linear models, especially in the case of AOT40. For the description of the summer period from May to September, the mean absolute daily differences between observed and calculated indices were 8±6 ppb for the maximum half hour mean value, 6±5 ppb for the 7 h mean and 41±40 ppb h for the AOT40. When the parameters were further optimized to describe individual months separately, the mean absolute residuals decreased by ⩽10%. Neural network models did not always perform better than the regression models. This is attributed to the low number of inputs in this comparison and to the simple architecture of these models (2-2-1). Further factorial analyses of those days when the residuals were higher than the mean plus one standard deviation should reveal possible reasons why the models did not perform well on certain days. It was observed that overestimations by the models mainly occurred on days with partly overcast, hazy or very windy conditions. Underestimations more frequently occurred on weekdays than on weekends. It is suggested that the application of this kind of meteorological model will be more successful in topographically homogeneous regions and in rural environments with relatively constant rates of emission and long-range transport of ozone precursors. Under conditions too demanding for advanced physico/chemical models, the presented models may offer useful alternatives to derive ecologically relevant ozone indices directly from meteorological parameters.

Integrating data and mashup concepts in Hydro-Meteorological Research: the torrential rainfall event in Genoa (4th November 2011) case study.

NASA Astrophysics Data System (ADS)

Bedrina, T.; Parodi, A.; Quarati, A.; Clematis, A.; Rebora, N.; Laiosa, D.

2012-04-01

One of the critical issues in Hydro-Meteorological Research (HMR) is a better exploitation of data archives according to a multidisciplinary perspective. Different Earth science databases offer a huge amount of observational data, which often need to be assembled, processed, combined accordingly HM scientists needs. The cooperation between scientists active in HMR and Information and Communication Technologies (ICT) is essential in the development of innovative tools and applications for manipulating, aggregating and re-arranging heterogeneous information in flexible way. In this paper it is described an application devoted to the collection and integration of HM datasets, originated by public or private sources, freely exposed via Web services API. This application uses the mashup, recently become very popular in many fields, (Chow S.-W., 2007) technology concepts. Such methodology means combination of data and/or programs published by external online sources into an integrated experience. Mashup seems to be a promising methodology to respond to the multiple data-related activities into which HM researchers are daily involved (e.g. finding and retrieving high volume data; learning formats and developing readers; extracting parameters; performing filtering and mask; developing analysis and visualization tools). The specific case study of the recent extreme rainfall event, occurred over Genoa in Italy on the 4th November 2011 is shown through the integration of semi-professional weather observational networks as free available data source in addition to official weather networks.

Cluster analyses of association of weather, daily factors and emergent medical conditions.

PubMed

Malkić, Jasmin; Sarajlić, Nermin; Smrke, Barbara U R; Smrke, Dragica

2013-03-01

The goal of this study was to evaluate associations between the meteorological conditions and the number of emergency cases for five distinctive causes of dispatch groups reported to SOS dispatch centre in Uppsala, Sweden. Center's responsibility include alerting to 17 ambulances in whole Uppsala County, area of 8,209 km2 with around 320,000 inhabitants representing the target patient group. Source of the medical data for this study is the database of dispatch data for the year of 2009, while the metrological data have been provided from Uppsala University Department of Earth Sciences yearly weather report. Medical and meteorological data were summoned into the unified data space where each point represents a day with its weather parameters and dispatch cause group cardinality. DBSCAN data mining algorithm was implemented to five distinctive groups of dispatch causes after the data spaces have gone through the variance adjustment and the principal component analyses. As the result, several point clusters were discovered in each of the examined data spaces indicating the distinctive conditions regarding the weather and daily cardinality of the dispatch cause, as well as the associations between these two. Most interesting finding is that specific type of winter weather formed a cluster only around the days with the high count of breathing difficulties, while one of the summer weather clusters made similar association with the days with low number of cases. Findings were confirmed by confidence level estimation based on signal to noise ratio for the observed data points.

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi, China.

PubMed

Wu, Hao; Zhang, Yan; Yu, Qi; Ma, Weichun

2018-04-01

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM 10 ], sulfur dioxide [SO 2 ], and nitrogen oxides [NO x ]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants. The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality. Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.

Re-assess Vector Indices Threshold as an Early Warning Tool for Predicting Dengue Epidemic in a Dengue Non-endemic Country

PubMed Central

Hsu, Pi-Shan; Chen, Chaur-Dong; Lian, Ie-Bin; Chao, Day-Yu

2015-01-01

Background Despite dengue dynamics being driven by complex interactions between human hosts, mosquito vectors and viruses that are influenced by climate factors, an operational model that will enable health authorities to anticipate the outbreak risk in a dengue non-endemic area has not been developed. The objectives of this study were to evaluate the temporal relationship between meteorological variables, entomological surveillance indices and confirmed dengue cases; and to establish the threshold for entomological surveillance indices including three mosquito larval indices [Breteau (BI), Container (CI) and House indices (HI)] and one adult index (AI) as an early warning tool for dengue epidemic. Methodology/Principal Findings Epidemiological, entomological and meteorological data were analyzed from 2005 to 2012 in Kaohsiung City, Taiwan. The successive waves of dengue outbreaks with different magnitudes were recorded in Kaohsiung City, and involved a dominant serotype during each epidemic. The annual indigenous dengue cases usually started from May to June and reached a peak in October to November. Vector data from 2005–2012 showed that the peak of the adult mosquito population was followed by a peak in the corresponding dengue activity with a lag period of 1–2 months. Therefore, we focused the analysis on the data from May to December and the high risk district, where the inspection of the immature and mature mosquitoes was carried out on a weekly basis and about 97.9% dengue cases occurred. The two-stage model was utilized here to estimate the risk and time-lag effect of annual dengue outbreaks in Taiwan. First, Poisson regression was used to select the optimal subset of variables and time-lags for predicting the number of dengue cases, and the final results of the multivariate analysis were selected based on the smallest AIC value. Next, each vector index models with selected variables were subjected to multiple logistic regression models to examine the accuracy of predicting the occurrence of dengue cases. The results suggested that Model-AI, BI, CI and HI predicted the occurrence of dengue cases with 83.8, 87.8, 88.3 and 88.4% accuracy, respectively. The predicting threshold based on individual Model-AI, BI, CI and HI was 0.97, 1.16, 1.79 and 0.997, respectively. Conclusion/Significance There was little evidence of quantifiable association among vector indices, meteorological factors and dengue transmission that could reliably be used for outbreak prediction. Our study here provided the proof-of-concept of how to search for the optimal model and determine the threshold for dengue epidemics. Since those factors used for prediction varied, depending on the ecology and herd immunity level under different geological areas, different thresholds may be developed for different countries using a similar structure of the two-stage model. PMID:26366874

Predictive study on the risk of malaria spreading due to global warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ono, Masaji

Global warming will bring about a temperature elevation, and the habitat of vectors of infectious diseases, such as malaria and dengue fever, will spread into subtropical or temperate zone. The purpose of this study is to simulate the spreading of these diseases through reexamination of existing data and collection of some additional information by field survey. From these data, the author will establish the relationship between meteorological conditions, vector density and malaria occurrence. And then he will simulate and predict the malaria epidemics in case of temperature elevation in southeast Asia and Japan.

Forecasting Temporal Dynamics of Cutaneous Leishmaniasis in Northeast Brazil

PubMed Central

Lewnard, Joseph A.; Jirmanus, Lara; Júnior, Nivison Nery; Machado, Paulo R.; Glesby, Marshall J.; Ko, Albert I.; Carvalho, Edgar M.; Schriefer, Albert; Weinberger, Daniel M.

2014-01-01

Introduction Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions. Methodology/Principal Findings We fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation. Significance These outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets. PMID:25356734

Forecasting temporal dynamics of cutaneous leishmaniasis in Northeast Brazil.

PubMed

Lewnard, Joseph A; Jirmanus, Lara; Júnior, Nivison Nery; Machado, Paulo R; Glesby, Marshall J; Ko, Albert I; Carvalho, Edgar M; Schriefer, Albert; Weinberger, Daniel M

2014-10-01

Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions. We fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation. These outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets.

AICE Survey of USSR Air Pollution Literature, Volume 12: Technical Papers from the Leningrad International Symposium on the Meteorological Aspects of Atmospheric Pollution, Part I.

ERIC Educational Resources Information Center

Nuttonson, M. Y.

Twelve papers dealing with the meteorological aspects of air pollution were translated. These papers were initially presented at an international symposium held in Leningrad during July 1968. The papers are: Status and prospective development of meteorological studies of atmospheric pollution, Effect of the stability of the atmosphere on the…

Effects of meteorological factors on incidence of scarlet fever during different periods in different districts of China.

PubMed

Duan, Yu; Yang, Li-Juan; Zhang, Yan-Jie; Huang, Xiao-Lei; Pan, Gui-Xia; Wang, Jing

2017-03-01

To reveal the difference of meteorological effect on scarlet fever in Beijing and Hong Kong, China, during different periods among 2004-2014. The data of monthly incidence of scarlet fever and meteorological variables from 2004 to 2014 in Beijing and Hong Kong were collected from Chinese science data center of public health, meteorological data website and Hong Kong observatory website. The whole study period was separated into two periods by the outbreak year 2011 (Jan 2004-Dec 2010 and Jan 2011-Dec 2014). A generalized additive Poisson model was conducted to estimate the effect of meteorological variables on monthly incidence of scarlet fever during two periods in Beijing and Hong Kong, China. Incidence of scarlet fever in two districts were compared and found the average incidence during period of 2004-2010 were significantly different (Z=203.973, P<0.001) while average incidence became generally equal during 2011-2014 (Z=2.125, P>0.05). There was also significant difference in meteorological variables between Beijing and Hong Kong during whole study period, except air pressure (Z=0.165, P=0.869). After fitting GAM model, it could be found monthly mean temperature showed a negative effect (RR=0.962, 95%CI: 0.933, 0.992) on scarlet fever in Hong Kong during the period of 2004-2010. By comparison, for data in Beijing during the period of 2011-2014, the RRs of monthly mean temperature range growing 1°C and monthly sunshine duration growing 1h was equal to 1.196(1.022, 1.399) and 1.006(1.001, 1.012), respectively. The changes of meteorological effect on scarlet fever over time were not significant both in Beijing and Hong Kong. This study suggests that meteorological variables were important factors for incidence of scarlet fever during different period in Beijing and Hong Kong. It also support that some meteorological effects were opposite in different period although these differences might not completely statistically significant. Copyright © 2017 Elsevier B.V. All rights reserved.

Trajectory mapping of middle atmospheric water vapor by a mini network of NDACC instruments

NASA Astrophysics Data System (ADS)

Lainer, M.; Kämpfer, N.; Tschanz, B.; Nedoluha, G. E.; Ka, S.; Oh, J. J.

2015-08-01

The important task to observe the global coverage of middle atmospheric trace gases like water vapor or ozone usually is accomplished by satellites. Climate and atmospheric studies rely upon the knowledge of trace gas distributions throughout the stratosphere and mesosphere. Many of these gases are currently measured from satellites, but it is not clear whether this capability will be maintained in the future. This could lead to a significant knowledge gap of the state of the atmosphere. We explore the possibilities of mapping middle atmospheric water vapor in the Northern Hemisphere by using Lagrangian trajectory calculations and water vapor profile data from a small network of five ground-based microwave radiometers. Four of them are operated within the frame of NDACC (Network for the Detection of Atmospheric Composition Change). Keeping in mind that the instruments are based on different hardware and calibration setups, a height-dependent bias of the retrieved water vapor profiles has to be expected among the microwave radiometers. In order to correct and harmonize the different data sets, the Microwave Limb Sounder (MLS) on the Aura satellite is used to serve as a kind of traveling standard. A domain-averaging TM (trajectory mapping) method is applied which simplifies the subsequent validation of the quality of the trajectory-mapped water vapor distribution towards direct satellite observations. Trajectories are calculated forwards and backwards in time for up to 10 days using 6 hourly meteorological wind analysis fields. Overall, a total of four case studies of trajectory mapping in different meteorological regimes are discussed. One of the case studies takes place during a major sudden stratospheric warming (SSW) accompanied by the polar vortex breakdown; a second takes place after the reformation of stable circulation system. TM cases close to the fall equinox and June solstice event from the year 2012 complete the study, showing the high potential of a network of ground-based remote sensing instruments to synthesize hemispheric maps of water vapor.

Trajectory mapping of middle atmospheric water vapor by a mini network of NDACC instruments

NASA Astrophysics Data System (ADS)

Lainer, M.; Kämpfer, N.; Tschanz, B.; Nedoluha, G. E.; Ka, S.; Oh, J. J.

2015-04-01

The important task to observe the global coverage of middle atmospheric trace gases like water vapor or ozone usually is accomplished by satellites. Climate and atmospheric studies rely upon the knowledge of trace gas distributions throughout the stratosphere and mesosphere. Many of these gases are currently measured from satellites, but it is not clear whether this capability will be maintained in the future. This could lead to a significant knowledge gap of the state of the atmosphere. We explore the possibilities of mapping middle atmospheric water vapor in the Northern Hemisphere by using Lagrangian trajectory calculations and water vapor profile data from a small network of five ground-based microwave radiometers. Four of them are operated within the frame of NDACC (Network for the Detection of Atmospheric Composition Change). Keeping in mind that the instruments are based on different hardware and calibration setups, a height dependent bias of the retrieved water vapor profiles has to be expected among the microwave radiometers. In order to correct and harmonize the different datasets, the Microwave Limb Sounder (MLS) on the Aura satellite is used to serve as a kind of travelling standard. A domain-averaging TM (trajectory mapping) method is applied which simplifies the subsequent validation of the quality of the trajectory mapped water vapor distribution towards direct satellite observations. Trajectories are calculated forwards and backwards in time for up to 10 days using 6 hourly meteorological wind analysis fields. Overall, a total of four case studies of trajectory mapping in different meteorological regimes are discussed. One of the case studies takes place during a major sudden stratospheric warming (SSW) accompanied by the polar vortex breakdown, a second takes place after the reformation of stable circulation system. TM cases close to the fall equinox and June solstice event from the year 2012 complete the study, showing the high potential of a network of ground-based remote sensing instruments to synthesize hemispheric maps of water vapor.

Investigation of time-resolved atmospheric conditions and indoor/outdoor particulate matter concentrations in homes with gas and biomass cook stoves in Nogales, Sonora, Mexico.

PubMed

Holmes, Heather A; Pardyjak, Eric R

2014-07-01

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States-Mexico border During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14-30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM3 concentrations in the range of 134 to 157 microg m(-3) and biomass stoves 163 to 504 microg m(-1). Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM3: 130 to 770 microg m(-3)). The former is evident in the median and range of daytime PM values (median PM3: 250 microg m(-3), maximum: 9411 microg m(-3)), while the meteorological influences appear to be dominant during nighttime periods (median PM3: 251 microg m(-3), maximum: 10,846 microg m(-3)). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 microg m(-3)). Implications: Regulatory air quality standards are based on outdoor ambient air measurements. However, a large fraction of time is typically spent indoors where a variety of activities including cooking, heating, tobacco smoking, and cleaning can lead to elevated PM concentrations. This study investigates the influence of meteorology, outdoor PM, and indoor activities on indoor air pollution (IAP) levels in the United States-Mexico border region. Results indicate that cooking fuel type and meteorology greatly influence the IAP in homes, with biomass fuel use causing the largest increase in PM concentration.

Association between floods and infectious diarrhea and their effect modifiers in Hunan province, China: A two-stage model.

PubMed

Liu, Zhidong; Zhang, Feifei; Zhang, Ying; Li, Jing; Liu, Xuena; Ding, Guoyong; Zhang, Caixia; Liu, Qiyong; Jiang, Baofa

2018-06-01

Understanding the potential links between floods and infectious diarrhea is important under the context of climate change. However, little is known about the risk of infectious diarrhea after floods and what factors could modify these effects in China. This study aims to quantitatively examine the relationship between floods and infectious diarrhea and their effect modifiers. Weekly number of infectious diarrhea cases from 2004 to 2011 during flood season in Hunan province were supplied by the National Notifiable Disease Surveillance System. Flood and meteorological data over the same period were obtained. A two-stage model was used to estimate a provincial average association and their effect modifiers between floods and infectious diarrhea, accounting for other confounders. A total of 134,571 cases of infectious diarrhea were notified from 2004 to 2011. After controlling for seasonality, long-term trends, and meteorological factors, floods were significantly associated with infectious diarrhea in the provincial level with a cumulative RR of 1.22 (95% CI: 1.05, 1.43) with a lagged effect of 0-1 week. Geographic locations and economic levels were identified as effect modifiers, with a higher impact of floods on infectious diarrhea in the western and regions with a low economic level of Hunan. Our study provides strong evidence of a positive association between floods and infectious diarrhea in the study area. Local control strategies for public health should be taken in time to prevent and reduce the risk of infectious diarrhea after floods, especially for the vulnerable regions identified. Copyright © 2018 Elsevier B.V. All rights reserved.

Association between meteorological factors and bacillary dysentery incidence in Chaoyang city, China: an ecological study.

PubMed

Zhao, Yang; Zhu, Yaxin; Zhu, Zhiwei; Qu, Bo

2016-12-09

To quantify the relationship between meteorological factors and bacillary dysentery incidence. Ecological study. We collected bacillary dysentery incidences and meteorological data of Chaoyang city from the year 1981 to 2010. The climate in this city was a typical northern temperate continental monsoon. All meteorological factors in this study were divided into 4 latent factors: temperature, humidity, sunshine and airflow. Structural equation modelling was used to analyse the relationship between meteorological factors and the incidence of bacillary dysentery. Incidences of bacillary dysentery were obtained from the Center for Disease Control and Prevention of Chaoyang city, and meteorological data were collected from the Bureau of Meteorology in Chaoyang city. The indexes including χ 2 , root mean square error of approximation (RMSEA), comparative fit index (CFI), standardised root mean square residual (SRMR) and goodness-of-fit index (GFI) were used to evaluate the goodness-of-fit of the theoretical model to the data. The factor loads were used to explore quantitative relationship between bacillary dysentery incidences and meteorological factors. The goodness-of-fit results of the model showing that RMSEA=0.08, GFI=0.84, CFI=0.88, SRMR=0.06 and the χ 2 value is 231.95 (p=0.0) with 15 degrees of freedom. Temperature and humidity factors had positive correlations with incidence of bacillary dysentery, with the factor load of 0.59 and 0.78, respectively. Sunshine had a negative correlation with bacillary dysentery incidence, with a factor load of -0.15. Humidity and temperature should be given greater consideration in bacillary dysentery prevention measures for northern temperate continental monsoon climates, such as that of Chaoyang. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Preliminary Evaluation of Air Quality Model Performance Utilizing Measurements at the University of Houston Moody Tower and others during the TexAQS-II

NASA Astrophysics Data System (ADS)

Byun, D. W.; Rappenglueck, B.; Lefer, B.

2007-12-01

Accurate meteorological and photochemical modeling efforts are necessary to understand the measurements made during the Texas Air Quality Study (TexAQS-II). The main objective of the study is to understand the meteorological and chemical processes of high ozone and regional haze events in the Eastern Texas, including the Houston-Galveston metropolitan area. Real-time and retrospective meteorological and photochemical model simulations were performed to study key physical and chemical processes in the Houston Galveston Area. In particular, the Vertical Mixing Experiment (VME) at the University of Houston campus was performed on selected days during the TexAQS-II. Results of the MM5 meteorological model and CMAQ air quality model simulations were compared with the VME and other TexAQS-II measurements to understand the interaction of the boundary layer dynamics and photochemical evolution affecting Houston air quality.

The effects of daily weather variables on psychosis admissions to psychiatric hospitals

NASA Astrophysics Data System (ADS)

McWilliams, Stephen; Kinsella, Anthony; O'Callaghan, Eadbhard

2013-07-01

Several studies have noted seasonal variations in admission rates of patients with psychotic illnesses. However, the changeable daily meteorological patterns within seasons have never been examined in any great depth in the context of admission rates. A handful of small studies have posed interesting questions regarding a potential link between psychiatric admission rates and meteorological variables such as environmental temperature (especially heat waves) and sunshine. In this study, we used simple non-parametric testing and more complex ARIMA and time-series regression analysis to examine whether daily meteorological patterns (wind speed and direction, barometric pressure, rainfall, sunshine, sunlight and temperature) exert an influence on admission rates for psychotic disorders across 12 regions in Ireland. Although there were some weak but interesting trends for temperature, barometric pressure and sunshine, the meteorological patterns ultimately did not exert a clinically significant influence over admissions for psychosis. Further analysis is needed.

The Relationships Between Weather and Climate and Attacks of Bronchitis

NASA Astrophysics Data System (ADS)

Talaia, M. A. R.; Saraiva, M. A. C.; Vieira da Cruz, A. A.

The area of Aveiro, more concretely Aveiro lagoon, a natural laboratory has been con- sidered, for promoting the development and the application of several investigations worked. The importance of the influences of weather and climate on human health has been well known since ancient teams and many decisions concerning human be- haviour it are clearly weather related. However, decisions related to weather criteria can be important and economically significant, but the real economic effect of the weather is difficult to assess. Talaia et al. (2000) and Talaia and Vieira da Cruz (2001) have shown the possible harmful effect of certain meteorological factors on respiratory conditions. Bronchitis is a disease caused by inflammation of the bronchi as a result of infectious agents or air pollutants. In this study our attention is to relate, the be- ginning of bronchitis attacks in the services of urgency of the Hospital of Aveiro with meteorological factors, and the risk group are studied. We used the medical records and the database of meteorological factors. The obtained analysis allows to conclude that some meteorological factors have correlation with the occurrences of the disease and to allow improving the work in the urgency services in the requested periods. The knowledge that will be extracted of this study can be used later in studies that inte- grate other important components for the characterisation of the environmental impact in the area. References: Talaia, M.A.R., Vieira da Cruz, A.A., Saraiva, M.A.C., Amaro, G.S., Oliveira, C.J. and Carvalho, C.F., 2000, The Influence of Meteorological Fac- tors on Pneumonia Emergencies in Aveiro, International Symposium on Human- Biometeorology, St. Petersburg (Pushkin), Russia, pp. 67-68. Talaia, M.A.R. and Vieira of Cruz, A.A., (2001), Meteorological Effects on the Resistance of the Body to Influenza - One Study in Aveiro Region, Proceedings 2nd Symposium of Meteorol- ogy and Geophysics of APMG and 3rd Meeting Portuguese-Spanish of Meteorology (in press).

Long-term analysis and appropriate metrics of climate change in Mongolia

NASA Astrophysics Data System (ADS)

Jamiyansharav, Khishigbayar

This study addresses three important issues related to long-term climate change study in Mongolia. Mongolia is one of the biggest land-locked countries in Asia and 75--80 percent of the land is rangeland, which is highly vulnerable to climate change. Climate will affect many sectors critical to the country's economic, social, and ecological welfare. Therefore, it is regionally and globally important to evaluate climate change in Mongolia. Chapter 1 discusses the qualitative and descriptive study on exposure characteristics of the 17 Mongolian meteorological stations, which are part of the Global Climate Observing Network (GCON). The global average temperature anomalies are based in part on the GCON stations' meteorological data. To document the possible exposures surrounding the weather stations, the Mongolian meteorological stations were surveyed during July--August 2005. From the total 17 stations, 47 percent were determined strongly influenced by urban character landscape, 41 percent received some anthropogenic influences, and 12 percent had very little to no anthropogenic influences. Even though the Mongolian meteorological stations' exposure characteristics are better than the European and North American stations' the strict adherence in following WMO guidelines is important and urgently needed. Chapter 2 evaluates the long-term (1961--2005) trends in seasonal and annual surface mean, maximum, minimum temperatures and precipitation. Furthermore, this study compares the long-term mean temperature trends with decadal (1998--2007) trends. This chapter also discusses the extreme climate indices on spatial and temporal scales. According to the results, the long-term linear temperature trends show a clear increasing trend whereas the decadal trends show the decreasing trend mostly in winter and spring. The analysis of extreme indices (1961--2001) indicate that most of the stations frost and icing days are decreased and summer days, tropical nights, monthly maximum value of daily minimum, maximum temperatures and growing season length are increased. Precipitation indices varied substantially and there were no unified temporal and spatial pattern. In addition to that, I am suggesting effective temperature as an appropriate metric to evaluate surface heat change because it counts not only air temperature but also surface humidity. Chapter 3 discusses a case study of grazing intensity on surface energy budgets. To evaluate the land atmospheric interactions over the grassland area depending on the different grazing intensity I conducted the case study over the Shortgrass Steppe Long-Term Ecological Research site on Northern Great Plains of US to imply the findings in semiarid shortgrass steppe of Mongolia. The study site has much of similarities with Mongolian shortgrass steppe and has more frequent, high quality data. This study evaluates the impact of grazing on microclimate and energy budgets in a dry (163 mm) and two near-normal (262 and 260 mm) precipitation years based on continuously measured 20 minute interval data. This study helps to describe surface energy partitioning in semi-arid grasslands that has long history of grazing. The main finding of the study is grazing has a potential impact on the energy partitioning under conditions of higher water availability, but not during dry conditions.

Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wall, Casey J.; Hartmann, Dennis L.; Ma, Po-Lun

Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the middle-troposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm- and cold-sector of cyclones. The observed relationships between clouds andmore » meteorology are compared to those in the Community Atmosphere Model version 5 (CAM5) using satellite simulators. Low-clouds simulated by CAM5 are too few, too bright, and contain too much ice, and low-clouds located in the cold-sector of cyclones are too sensitive to variations in the meteorology. The latter two biases are dramatically reduced when CAM5 is coupled with an updated boundary layer parameterization know as Cloud Layers Unified by Binormals (CLUBB). More generally, this study demonstrates that examining the instantaneous timescale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.« less

Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate

PubMed Central

Hay, S. I.; Lennon, J. J.

2012-01-01

Summary This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme’s (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy. PMID:10203175

Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate.

PubMed

Hay, S I; Lennon, J J

1999-01-01

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Characterization of east Asian dust outbreaks in the spring of 2001 using ground-based and satellite data

NASA Astrophysics Data System (ADS)

Darmenova, Kremena; Sokolik, Irina N.; Darmenov, Anton

2005-01-01

This study presents a detailed examination of east Asian dust events during March-April of 2001, by combining satellite multisensor observation (Total Ozone Mapping Spectrometer (TOMS), Moderate-Resolution Imaging Spectroradiometer (MODIS), and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS)) meteorological data from weather stations in China and Mongolia and the Pennsylania State University/National Center for Atmospheric Research Mesoscale Modeling System (MM5) driven by the National Centers for Environmental Prediction Reanalysis data. The main goal is to determine the extent to which the routine surface meteorological observations (including visibility) and satellite data can be used to characterize the spatiotemporal distribution of dust plumes at a range of scales. We also examine the potential of meteorological time series for constraining the dust emission schemes used in aerosol transport models. Thirty-five dust events were identified in the source region during March and April of 2001 and characterized on a case-by-case basis. The midrange transport routes were reconstructed on the basis of visibility observations and observed and MM5-predicted winds with further validation against satellite data. We demonstrate that the combination of visibility data, TOMS aerosol index, MODIS aerosol optical depth over the land, and a qualitative analysis of MODIS and SeaWiFS imagery enables us to constrain the regions of origin of dust outbreaks and midrange transport, though various limitations of individual data sets were revealed in detecting dust over the land. Only two long-range transport episodes were found. The transport routes and coverage of these dust episodes were reconstructed by using MODIS aerosol optical depth and TOMS aerosol index. Our analysis reveals that over the oceans the presence of persistent clouds poses a main problem in identifying the regions affected by dust transport, so only partial reconstruction of dust transport routes reaching the west coast of the United States was possible.

Meteorological contribution to the mitigation and adaptation of the 'extreme water events' of Hungarian Great Plain

NASA Astrophysics Data System (ADS)

Dunkel, Z.; Vincze, E.; Moring, A.

2012-04-01

The lack of water is a traditional problem of Hungarian agriculture. Two big rivers cross the territory of Hungary and times to times they produce huge floods. In the Carpathian basin a flood and a drought can occur in the same year. The general problem of Hungarian agriculture is the 'water' in two contexts, in lack of water and in surplus. Not only of the next year but of the next decades the basic question of the Hungarian planning is how the national economy can handle the increasing numbers of unexpected negative events of climate change because the growing numbers of sometimes catastrophic floods and droughts seems to be connected with global warming. Beside the 'normal floods' in the last few years the numbers of so called flash floods show increasing tendency too. The presentation summarises the 'extreme water events' of Hungarian Great Plain, and the forecast problems of Hungarian meteorology together with the National strategy in mitigation and adaptation in connection with climate change. From meteorological point of view the handling of flood and drought problem is totally different. In case of flood the stress is on the forecast, in case of drought mainly of the evaluation of the historical data mainly the short and long term evaluation of drought indices. Drought indices seem to be the simplest tools in drought analysis. The more or less well known and popular indices have been collected and compared not only with the well known simple but more complicated water balance and so called 'recursive' indices beside few ones use remotely sensed data, mainly satellite born information. The indices are classified into five groups, namely 'precipitation', 'water balance', 'soil moisture', 'recursive' and 'remote sensing' indices. For every group typical expressions are given and the possible use in the decision making and hazard risk evaluation and compensation of the farmers after the events. The meteorological elements of new Hungarian agricultural risk strategy will be shown.

New alternatives for reference evapotranspiration estimation in West Africa using limited weather data and ancillary data supply strategies.

NASA Astrophysics Data System (ADS)

Landeras, Gorka; Bekoe, Emmanuel; Ampofo, Joseph; Logah, Frederick; Diop, Mbaye; Cisse, Madiama; Shiri, Jalal

2018-05-01

Accurate estimation of reference evapotranspiration ( ET 0 ) is essential for the computation of crop water requirements, irrigation scheduling, and water resources management. In this context, having a battery of alternative local calibrated ET 0 estimation methods is of great interest for any irrigation advisory service. The development of irrigation advisory services will be a major breakthrough for West African agriculture. In the case of many West African countries, the high number of meteorological inputs required by the Penman-Monteith equation has been indicated as constraining. The present paper investigates for the first time in Ghana, the estimation ability of artificial intelligence-based models (Artificial Neural Networks (ANNs) and Gene Expression Programing (GEPs)), and ancillary/external approaches for modeling reference evapotranspiration ( ET 0 ) using limited weather data. According to the results of this study, GEPs have emerged as a very interesting alternative for ET 0 estimation at all the locations of Ghana which have been evaluated in this study under different scenarios of meteorological data availability. The adoption of ancillary/external approaches has been also successful, moreover in the southern locations. The interesting results obtained in this study using GEPs and some ancillary approaches could be a reference for future studies about ET 0 estimation in West Africa.

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 2-Hazard Modeling.

PubMed

Blanton, Brian; Dresback, Kendra; Colle, Brian; Kolar, Randy; Vergara, Humberto; Hong, Yang; Leonardo, Nicholas; Davidson, Rachel; Nozick, Linda; Wachtendorf, Tricia

2018-04-25

Hurricane track and intensity can change rapidly in unexpected ways, thus making predictions of hurricanes and related hazards uncertain. This inherent uncertainty often translates into suboptimal decision-making outcomes, such as unnecessary evacuation. Representing this uncertainty is thus critical in evacuation planning and related activities. We describe a physics-based hazard modeling approach that (1) dynamically accounts for the physical interactions among hazard components and (2) captures hurricane evolution uncertainty using an ensemble method. This loosely coupled model system provides a framework for probabilistic water inundation and wind speed levels for a new, risk-based approach to evacuation modeling, described in a companion article in this issue. It combines the Weather Research and Forecasting (WRF) meteorological model, the Coupled Routing and Excess STorage (CREST) hydrologic model, and the ADvanced CIRCulation (ADCIRC) storm surge, tide, and wind-wave model to compute inundation levels and wind speeds for an ensemble of hurricane predictions. Perturbations to WRF's initial and boundary conditions and different model physics/parameterizations generate an ensemble of storm solutions, which are then used to drive the coupled hydrologic + hydrodynamic models. Hurricane Isabel (2003) is used as a case study to illustrate the ensemble-based approach. The inundation, river runoff, and wind hazard results are strongly dependent on the accuracy of the mesoscale meteorological simulations, which improves with decreasing lead time to hurricane landfall. The ensemble envelope brackets the observed behavior while providing "best-case" and "worst-case" scenarios for the subsequent risk-based evacuation model. © 2018 Society for Risk Analysis.

A conditional approach to determining the effect of anthropogenic climate change on very rare events.

NASA Astrophysics Data System (ADS)

Wehner, Michael; Pall, Pardeep; Zarzycki, Colin; Stone, Daithi

2016-04-01

Probabilistic extreme event attribution is especially difficult for weather events that are caused by extremely rare large-scale meteorological patterns. Traditional modeling techniques have involved using ensembles of climate models, either fully coupled or with prescribed ocean and sea ice. Ensemble sizes for the latter case ranges from several 100 to tens of thousand. However, even if the simulations are constrained by the observed ocean state, the requisite large-scale meteorological pattern may not occur frequently enough or even at all in free running climate model simulations. We present a method to ensure that simulated events similar to the observed event are modeled with enough fidelity that robust statistics can be determined given the large scale meteorological conditions. By initializing suitably constrained short term ensemble hindcasts of both the actual weather system and a counterfactual weather system where the human interference in the climate system is removed, the human contribution to the magnitude of the event can be determined. However, the change (if any) in the probability of an event of the observed magnitude is conditional not only on the state of the ocean/sea ice system but also on the prescribed initial conditions determined by the causal large scale meteorological pattern. We will discuss the implications of this technique through two examples; the 2013 Colorado flood and the 2014 Typhoon Haiyan.

Guided Inquiry for Teacher Enhancement Utilizing Internet-Delivered Geophysical Data

NASA Astrophysics Data System (ADS)

Clark, J.; Weinbeck, R. S.; Geer, I. W.; Moran, J. M.

2002-12-01

The Education Program of the American Meteorological Society (AMS) designed and nationally implemented two distance-learning courses for K-12 teacher enhancement that model scientific inquiry through investigations written that employ Internet-delivered geophysical data. DataStreme Atmosphere, launched in 1996, has introduced almost 6000 teachers nationwide to the basics of meteorology. DataStreme Water in the Earth System (WES), now in its fourth semester offering, employs the global water cycle as a vehicle to explore the flow and transformations of water and energy in the Earth system. By Spring 2003 almost 1000 teachers will have completed DataStreme WES. In both 12-week courses, participants complete two investigations per week and submit their work to a mentor on their Local Implementation Team (LIT) for discussion and evaluation. AMS staff scientists write part of each investigation to a current or archived situation utilizing specially formatted meteorological, hydrological, or oceanographic data. This component of the investigation is posted to the course homepage and has proven to be an exciting and highly motivational aspect of the DataStreme courses. In many cases, teachers learn scientific concepts by investigating a case (e.g., hurricane, flash flood) as it is happening, in near real-time. Participants who successfully complete a DataStreme course agree to serve their schools and school districts as a resource teacher and to offer peer training on the use of Internet-delivered geophysical data to upgrade science in the classroom.

Spatial-temporal detection of risk factors for bacillary dysentery in Beijing, Tianjin and Hebei, China.

PubMed

Xu, Chengdong; Li, Yuanyuan; Wang, Jinfeng; Xiao, Gexin

2017-09-25

Bacillary dysentery is the third leading notifiable disease and remains a major public health concern in China. The Beijing-Tianjin-Hebei urban region is the biggest urban agglomeration in northern China, and it is one of the areas in the country that is most heavily infected with bacillary dysentery. The objective of the study was to analyze the spatial-temporal pattern and to determine any contributory risk factors on the bacillary dysentery. Bacillary dysentery case data from 1 January 2012 to 31 December 2012 in Beijing-Tianjin- Hebei were employed. GeoDetector method was used to determine the impact of potential risk factors, and to identify regions and seasons at high risk of the disease. There were 36,472 cases of bacillary dysentery in 2012 in the study region. The incidence of bacillary dysentery varies widely amongst different age groups; the higher incidence of bacillary dysentery mainly occurs in the population under the age of five. Bacillary dysentery presents apparent seasonal variance, with the highest incidence occurring from June to September. In terms of the potential meteorological risk factors, mean temperature, relative humidity, precipitation, mean wind speed and sunshine hours explain the time variant of bacillary dysentery at 83%, 31%, 25%, 17% and 13%, respectively. The interactive effect between temperature and humidity has an explanatory power of 87%, indicating that a hot and humid environment is more likely to lead to the occurrence of bacillary dysentery. Socio-economic factors affect the spatial distribution of bacillary dysentery. The top four factors are age group, per capita GDP, population density and rural population proportion, and their determinant powers are 61%, 27%, 25% and 21%, respectively. The interactive effect between age group and the other factors accounts for more than 60% of bacillary dysentery transmission. Bacillary dysentery poses a higher risk in the population of children. It is affected by meteorological and socio-economic factors, and it is necessary to pay more attention to the meteorological period and situation, particularly in period with high temperature and humidity, as well as places in urban areas with high population density, and a low proportion of rural population.

Priority of a Hesitant Fuzzy Linguistic Preference Relation with a Normal Distribution in Meteorological Disaster Risk Assessment.

PubMed

Wang, Lihong; Gong, Zaiwu

2017-10-10

As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In some complex and non-procedural meteorological disaster risk assessments, a hesitant fuzzy linguistic preference relation (HFLPR) is often used to deal with a situation in which experts may be hesitant while providing preference information of a pairwise comparison of alternatives, that is, the degree of preference of one alternative over another. This study explores hesitation from the perspective of statistical distributions, and obtains an optimal ranking of an HFLPR based on chance-restricted programming, which provides a new approach for hesitant fuzzy optimisation of decision-making in meteorological disaster risk assessments.

Computer simulations of space-borne meteorological systems on the CYBER 205

NASA Technical Reports Server (NTRS)

Halem, M.

1984-01-01

Because of the extreme expense involved in developing and flight testing meteorological instruments, an extensive series of numerical modeling experiments to simulate the performance of meteorological observing systems were performed on CYBER 205. The studies compare the relative importance of different global measurements of individual and composite systems of the meteorological variables needed to determine the state of the atmosphere. The assessments are made in terms of the systems ability to improve 12 hour global forecasts. Each experiment involves the daily assimilation of simulated data that is obtained from a data set called nature. This data is obtained from two sources: first, a long two-month general circulation integration with the GLAS 4th Order Forecast Model and second, global analysis prepared by the National Meteorological Center, NOAA, from the current observing systems twice daily.

On the early history of the Finnish Meteorological Institute

NASA Astrophysics Data System (ADS)

Nevanlinna, H.

2014-03-01

This article is a review of the foundation (in 1838) and later developments of the Helsinki (Finland) magnetic and meteorological observatory, today the Finnish Meteorological Institute (FMI). The main focus of the study is in the early history of the FMI up to the beginning of the 20th century. The first director of the observatory was Physics Professor Johan Jakob Nervander (1805-1848). He was a famous person of the Finnish scientific, academic and cultural community in the early decades of the 19th century. Finland was an autonomously part of the Russian Empire from 1809 to 1917, but the observatory remained organizationally under the University of Helsinki, independent of Russian scientific institutions, and funded by the Finnish Government. Throughout the late-19th century the Meteorological Institute was responsible of nationwide meteorological, hydrological and marine observations and research. The observatory was transferred to the Finnish Society of Sciences and Letters under the name the Central Meteorological Institute in 1881. The focus of the work carried out in the Institute was changed gradually towards meteorology. Magnetic measurements were still continued but in a lower level of importance. The culmination of Finnish geophysical achievements in the 19th century was the participation to the International Polar Year programme in 1882-1883 by setting up a full-scale meteorological and magnetic observatory in Sodankylä, Lapland.

A study of the mechanism of internal gravity wave generation by quasigeostrophic meteorological motions

NASA Technical Reports Server (NTRS)

Medvedev, A. S.

1987-01-01

Numerous experiments on the detection of atmospheric waves in the frequency range from acoustic to planetary at meteor heights have revealed that important wave sources are meteorological processes in the troposphere (cyclones, atmospheric fronts, jet streams, etc.). A dynamical theory based on the others work include describing the adaptation of meteorological fields to the geostropic equilibrium state. According to this theory, wave motions appear as a result of constant competition between the maladjustment of the wind and pressure fields due to nonlinear effects and the tendency of the atmosphere to establish a quasi-geostrophic equilibrium of these fields. These meteorological fields are discussed.

A study of the mechanism of internal gravity wave generation by quasigeostrophic meteorological motions

NASA Astrophysics Data System (ADS)

Medvedev, A. S.

1987-08-01

Numerous experiments on the detection of atmospheric waves in the frequency range from acoustic to planetary at meteor heights have revealed that important wave sources are meteorological processes in the troposphere (cyclones, atmospheric fronts, jet streams, etc.). A dynamical theory based on the others work include describing the adaptation of meteorological fields to the geostropic equilibrium state. According to this theory, wave motions appear as a result of constant competition between the maladjustment of the wind and pressure fields due to nonlinear effects and the tendency of the atmosphere to establish a quasi-geostrophic equilibrium of these fields. These meteorological fields are discussed.

The Amazon Boundary-Layer Experiment (ABLE 2B) - A meteorological perspective

NASA Technical Reports Server (NTRS)

Garstang, Michael; Greco, Steven; Scala, John; Swap, Robert; Ulanski, Stanley; Fitzjarrald, David; Martin, David; Browell, Edward; Shipman, Mark; Connors, Vickie

1990-01-01

The Amazon Boundary-Layer Experiments (ABLE) 2A and 2B, which were performed near Manaus, Brazil in July-August, 1985, and April-May, 1987 are discussed. The experiments were performed to study the sources, sinks, concentrations, and transports of trace gases and aerosols in rain forest soils, wetlands, and vegetation. Consideration is given the design and preliminary results of the experiment, focusing on the relationships between meteorological scales of motion and the flux, transports, and reactions of chemical species and aerosols embedded in the atmospheric fluid. Meteorological results are presented and the role of the meteorological results in the atmospheric chemistry experiment is examined.

Aircraft measurements of trace gases and particles near the tropopause

NASA Technical Reports Server (NTRS)

Falconer, P.; Pratt, R.; Detwiler, A.; Chen, C. S.; Hogan, A.; Bernard, S.; Krebschull, K.; Winters, W.

1983-01-01

Research activities which were performed using atmospheric constituent data obtained by the NASA Global Atmospheric Sampling Program are described. The characteristics of the particle size spectrum in various meteorological settings from a special collection of GASP data are surveyed. The relationship between humidity and cloud particles is analyzed. Climatological and case studies of tropical ozone distributions measured on a large number of flights are reported. Particle counter calibrations are discussed as well as the comparison of GASP particle data in the upper troposphere with other measurements at lower altitudes over the Pacific Ocean.

Introduction of the in-orbit test and its performance for the first meteorological imager of the Communication, Ocean, and Meteorological Satellite

NASA Astrophysics Data System (ADS)

Kim, D. H.; Ahn, M. H.

2014-08-01

The first geostationary Earth observation satellite of Korea - the Communication, Ocean, and Meteorological Satellite (COMS) - was successfully launched on 27 June 2010. After arrival at its operational orbit, the satellite underwent an in-orbit test (IOT) that lasted for about 8 months. During the IOT period, the main payload for the weather application, the meteorological imager, went through successful tests for demonstrating its function and performance, and the test results are introduced here. The radiometric performance of the meteorological imager (MI) is tested by means of signal-to-noise ratio (SNR) for the visible channel, noise-equivalent differential temperature (NEdT) for the infrared channels, and pixel-to-pixel nonuniformity for both the visible and infrared channels. In the case of the visible channel, the SNR of all eight detectors is obtained using the ground-measured parameters with the background signals obtained in orbit. The overall performance shows a value larger than 26 at 5% albedo, exceeding the user requirement of 10 by a significant margin. Also, the relative variability of detector responsivity among the eight visible channels meets the user requirement, showing values within 10% of the user requirement. For the infrared channels, the NEdT of each detector is well within the user requirement and is comparable with or better than the legacy instruments, except for the water vapor channel, which is slightly noisier than the legacy instruments. The variability of detector responsivity of infrared channels is also below the user requirement, within 40% of the requirement, except for the shortwave infrared channel. The improved performance result is partly due to the stable and low detector temperature obtained due to spacecraft design, i.e., by installing a single solar panel on the opposite side of the MI.

The relationship between meteorological factors and mumps incidence in Guangzhou, China, 2005–2012:

PubMed Central

Yang, Qiongying; Yang, Zhicong; Ding, Haiyuan; Zhang, Xiao; Dong, Zhiqiang; Hu, Wensui; Liu, Xiangyi; Wang, Ming; Hu, Guifang; Fu, Chuanxi

2014-01-01

Background Over the past decade, there have been resurgences and large-scale outbreaks of mumps worldwide. Little evidence is available on the relationship between meteorological factors and the incidence of mumps. We aimed to explore the effects of meteorological factors on mumps incidence. Methods: A Poisson regression model combined with a distributed lag non-linear model (DLNM) was used to evaluate the association between meteorological factors and the mumps incidence in Guangzhou, China, 2005–2012. Results Nonlinear relationships between meteorological factors, except sunshine hours, and mumps incidence were observed. The relative risks (RRs) of mean temperature, relative humidity and atmospheric pressure were 1.81 (95% confidence interval (CI), 1.41 to 2.32), 1.28 (95% CI, 1.02 to 1.59), and 0.80 (95% CI, 0.67 to 0.95) comparing the 99th percentile to the median of their own, respectively. For wind velocity, the RR was 0.70 (95%CI, 0.54 to 0.91) comparing the 1st percentile to the median. The hot effect and cold effect were larger in females than in males, and the hot effect increased with age. Conclusions Mean temperature, relative humidity, wind velocity and atmospheric pressure might be important predictors of the mumps incidence. Tropical cyclone caused a higher increase in mumps cases. Our findings highlight the need to strengthen the awareness of using protective measures during typhoon days and allocating more attention to the susceptible populations during the summer. The two-dose regimen of mumps vaccine should be included in the National Immunization Program schedule, and the catch-up vaccination campaigns should be promoted among adults. PMID:25424950

Atmospheric effects on voice command intelligibility from acoustic hail and warning devices.

PubMed

Bostron, Jason H; Brungart, Timothy A; Barnard, Andrew R; McDevitt, Timothy E

2011-04-01

Voice command sound pressure levels (SPLs) were recorded at distances up to 1500 m. Received SPLs were related to the meteorological condition during sound propagation and compared with the outdoor sound propagation standard ISO 9613-2. Intelligibility of received signals was calculated using ANSI S3.5. Intelligibility results for the present voice command indicate that meteorological condition imposes little to no effect on intelligibility when the signal-to-noise ratio (SNR) is low (<-9 dB) or high (>0 dB). In these two cases the signal is firmly unintelligible or intelligible, respectively. However, at moderate SNRs, variations in received SPL can cause a fully intelligible voice command to become unintelligible, depending on the meteorological condition along the sound propagation path. These changes in voice command intelligibility often occur on time scales as short as minutes during upward refracting conditions, typically found above ground during the day or upwind of a sound source. Reliably predicting the intelligibility of a voice command in a moderate SNR environment can be challenging due to the inherent variability imposed by sound propagation through the atmosphere.

Spatial Interpolation of Reference Evapotranspiration in India: Comparison of IDW and Kriging Methods

NASA Astrophysics Data System (ADS)

Hodam, Sanayanbi; Sarkar, Sajal; Marak, Areor G. R.; Bandyopadhyay, A.; Bhadra, A.

2017-12-01

In the present study, to understand the spatial distribution characteristics of the ETo over India, spatial interpolation was performed on the means of 32 years (1971-2002) monthly data of 131 India Meteorological Department stations uniformly distributed over the country by two methods, namely, inverse distance weighted (IDW) interpolation and kriging. Kriging was found to be better while developing the monthly surfaces during cross-validation. However, in station-wise validation, IDW performed better than kriging in almost all the cases, hence is recommended for spatial interpolation of ETo and its governing meteorological parameters. This study also checked if direct kriging of FAO-56 Penman-Monteith (PM) (Allen et al. in Crop evapotranspiration—guidelines for computing crop water requirements, Irrigation and drainage paper 56, Food and Agriculture Organization of the United Nations (FAO), Rome, 1998) point ETo produced comparable results against ETo estimated with individually kriged weather parameters (indirect kriging). Indirect kriging performed marginally well compared to direct kriging. Point ETo values were extended to areal ETo values by IDW and FAO-56 PM mean ETo maps for India were developed to obtain sufficiently accurate ETo estimates at unknown locations.

An ecological assessment of pasturelands in the Balkhash area of Kazakhstan with remote sensing and models

NASA Astrophysics Data System (ADS)

Lebed, L.; Qi, J.; Heilman, P.

2012-06-01

The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation’s economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation.

Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics

NASA Astrophysics Data System (ADS)

Sundberg, Mikaela

While the distinction between theory and experiment is often used to discuss the place of simulation from a philosophical viewpoint, other distinctions are possible from a sociological perspective. Turkle (1995) distinguishes between cultures of calculation and cultures of simulation and relates these cultures to the distinction between modernity and postmodernity, respectively. What can we understand about contemporary simulation practices in science by looking at them from the point of view of these two computer cultures? What new questions does such an analysis raise for further studies? On the basis of two case studies, the present paper compares and discusses simulation activities in astrophysics and meteorology. It argues that simulation practices manifest aspects of both of these cultures simultaneously, but in different situations. By employing the dichotomies surface/depth, play/seriousness, and extreme/reasonable to characterize and operationalize cultures of calculation and cultures of simulation as sensitizing concepts, the analysis shows how simulation code work shifts from development to use, the importance of but also resistance towards too much visualizations, and how simulation modelers play with extreme values, yet also try to achieve reasonable results compared to observations.

Regional projection of climate impact indices over the Mediterranean region

NASA Astrophysics Data System (ADS)

Casanueva, Ana; Frías, M.; Dolores; Herrera, Sixto; Bedia, Joaquín; San Martín, Daniel; Gutiérrez, José Manuel; Zaninovic, Ksenija

2014-05-01

Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts and risks to stakeholders. CIIs are typically based on different weather variables such as temperature, wind speed, precipitation or humidity and comprise, in a single index, the relevant meteorological information for the particular impact sector (in this study wildfires and tourism). This dependence on several climate variables poses important limitations to the application of statistical downscaling techniques, since physical consistency among variables is required in most cases to obtain reliable local projections. The present study assesses the suitability of the "direct" downscaling approach, in which the downscaling method is directly applied to the CII. In particular, for illustrative purposes, we consider two popular indices used in the wildfire and tourism sectors, the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), respectively. As an example, two case studies are analysed over two representative Mediterranean regions of interest for the EU CLIM-RUN project: continental Spain for the FWI and Croatia for the PET. Results obtained with this "direct" downscaling approach are similar to those found from the application of the statistical downscaling to the individual meteorological drivers prior to the index calculation ("component" downscaling) thus, a wider range of statistical downscaling methods could be used. As an illustration, future changes in both indices are projected by applying two direct statistical downscaling methods, analogs and linear regression, to the ECHAM5 model. Larger differences were found between the two direct statistical downscaling approaches than between the direct and the component approaches with a single downscaling method. While these examples focus on particular indices and Mediterranean regions of interest for CLIM-RUN stakeholders, the same study could be extended to other indices and regions.

Evaluation of the Emergency Response Dose Assessment System(ERDAS)

NASA Technical Reports Server (NTRS)

Evans, Randolph J.; Lambert, Winifred C.; Manobianco, John T.; Taylor, Gregory E.; Wheeler, Mark M.; Yersavich, Ann M.

1996-01-01

The emergency response dose assessment system (ERDAS) is a protype software and hardware system configured to produce routine mesoscale meteorological forecasts and enhanced dispersion estimates on an operational basis for the Kennedy Space Center (KSC)/Cape Canaveral Air Station (CCAS) region. ERDAS provides emergency response guidance to operations at KSC/CCAS in the case of an accidental hazardous material release or an aborted vehicle launch. This report describes the evaluation of ERDAS including: evaluation of sea breeze predictions, comparison of launch plume location and concentration predictions, case study of a toxic release, evaluation of model sensitivity to varying input parameters, evaluation of the user interface, assessment of ERDA's operational capabilities, and a comparison of ERDAS models to the ocean breeze dry gultch diffusion model.

INSTRUMENTATION, RECORDING, AND PROCESSING OF METEOROLOGICAL DATA NEAR PORTAGE, WISCONSIN: WISCONSIN POWER PLANT IMPACT STUDY

EPA Science Inventory

As part of the Columbia Power Plant Impact Study meteorological data were collected at a network of monitoring sites from 1972 through 1977. The data were the basis for a series of studies whose purpose was to elucidate the transport of airborne pollutants and to assess the clima...

A clustering approach for the analysis of solar energy yields: A case study for concentrating solar thermal power plants

NASA Astrophysics Data System (ADS)

Peruchena, Carlos M. Fernández; García-Barberena, Javier; Guisado, María Vicenta; Gastón, Martín

2016-05-01

The design of Concentrating Solar Thermal Power (CSTP) systems requires a detailed knowledge of the dynamic behavior of the meteorology at the site of interest. Meteorological series are often condensed into one representative year with the aim of data volume reduction and speeding-up of energy system simulations, defined as Typical Meteorological Year (TMY). This approach seems to be appropriate for rather detailed simulations of a specific plant; however, in previous stages of the design of a power plant, especially during the optimization of the large number of plant parameters before a final design is reached, a huge number of simulations are needed. Even with today's technology, the computational effort to simulate solar energy system performance with one year of data at high frequency (as 1-min) may become colossal if a multivariable optimization has to be performed. This work presents a simple and efficient methodology for selecting number of individual days able to represent the electrical production of the plant throughout the complete year. To achieve this objective, a new procedure for determining a reduced set of typical weather data in order to evaluate the long-term performance of a solar energy system is proposed. The proposed methodology is based on cluster analysis and permits to drastically reduce computational effort related to the calculation of a CSTP plant energy yield by simulating a reduced number of days from a high frequency TMY.

Reduction Continuous Rank Probability Score for Hydrological Ensemble Prediction System

NASA Astrophysics Data System (ADS)

Trinh, Nguyen Bao; Thielen Del-Pozo, Jutta; Pappenberger, Florian; Cloke, Hannah L.; Bogner, Konrad

2010-05-01

Ensemble Prediction System (EPS), calculated operationally by the weather services for various lead-times, are increasingly used as input to hydrological models to extend warning times from short- to medium and even long-range. Although the general skill of EPS has been demonstrated to increase continuously over the past decades, it remains comparatively low for precipitation, one of the driving forces of hydrological processes. Due to the non-linear integrating nature of river runoff and the complexities of catchment runoff processes, one cannot assume that the skill of the hydrological forecasts is necessarily similar to the skill of the meteorological predictions. Furthermore, due to the integrating nature of discharge, which accumulates effects from upstream catchment and slow-responding groundwater processes, commonly applied skill scores in meteorology may not be fully adapted to describe the skill of probabilistic discharge predictions. For example, while for hydrological applications it may be interesting to compare the forecast skill between upstream and downstream stations, meteorological applications focus more on climatologically relevant regions. In this paper, a range of widely used probabilistic skill scores for assessing reliability, spread-skill, sharpness and bias are calculated for a 12 months case study in the Danube river basin. The Continuous Rank Probability Score (CRPS) is demonstrated to have deficiencies when comparing skill of discharge forecast for different hydrological stations. Therefore, we propose a modified CRPS that allows this comparison and is therefore particularly useful for hydrological applications.

The effect of wind and eruption source parameter variations on tephra fallout hazard assessment: an example from Vesuvio (Italy)

NASA Astrophysics Data System (ADS)

Macedonio, Giovanni; Costa, Antonio; Scollo, Simona; Neri, Augusto

2015-04-01

Uncertainty in the tephra fallout hazard assessment may depend on different meteorological datasets and eruptive source parameters used in the modelling. We present a statistical study to analyze this uncertainty in the case of a sub-Plinian eruption of Vesuvius of VEI = 4, column height of 18 km and total erupted mass of 5 × 1011 kg. The hazard assessment for tephra fallout is performed using the advection-diffusion model Hazmap. Firstly, we analyze statistically different meteorological datasets: i) from the daily atmospheric soundings of the stations located in Brindisi (Italy) between 1962 and 1976 and between 1996 and 2012, and in Pratica di Mare (Rome, Italy) between 1996 and 2012; ii) from numerical weather prediction models of the National Oceanic and Atmospheric Administration and of the European Centre for Medium-Range Weather Forecasts. Furthermore, we modify the total mass, the total grain-size distribution, the eruption column height, and the diffusion coefficient. Then, we quantify the impact that different datasets and model input parameters have on the probability maps. Results shows that the parameter that mostly affects the tephra fallout probability maps, keeping constant the total mass, is the particle terminal settling velocity, which is a function of the total grain-size distribution, particle density and shape. Differently, the evaluation of the hazard assessment weakly depends on the use of different meteorological datasets, column height and diffusion coefficient.

Possibility of Cloudless Optical Remote Sensing Images Acquisition Study by Using Meteorological Satellite Observations

NASA Astrophysics Data System (ADS)

Zhang, T.; Lei, B.; Hu, Y.; Liu, K.; Gan, Y.

2018-04-01

Optical remote sensing images have been widely used in feature interpretation and geo-information extraction. All the fundamental applications of optical remote sensing, are greatly influenced by cloud coverage. Generally, the availability of cloudless images depends on the meteorological conditions for a given area. In this study, the cloud total amount (CTA) products of the Fengyun (FY) satellite were introduced to explore the meteorological changes in a year over China. The cloud information of CTA products were tested by using ZY-3 satellite images firstly. CTA products from 2006 to 2017 were used to get relatively reliable results. The window period of cloudless images acquisition for different areas in China was then determined. This research provides a feasible way to get the cloudless images acquisition window by using meteorological observations.

Climatological variables and the incidence of Dengue fever in Barbados.

PubMed

Depradine, Colin; Lovell, Ernest

2004-12-01

A retrospective study to determine relationships between the incidence of dengue cases and climatological variables and to obtain a predictive equation was carried out for the relatively small Caribbean island of Barbados which is divided into 11 parishes. The study used the weekly dengue cases and precipitation data for the years (1995 - 2000) that occurred in the small area of a single parish. Other climatological data were obtained from the local meteorological offices. The study used primarily cross correlation analysis and found the strongest correlation with the vapour pressure at a lag of 6 weeks. A weaker correlation occurred at a lag of 7 weeks for the precipitation. The minimum temperature had its strongest correlation at a lag of 12 weeks and the maximum temperature a lag of 16 weeks. There was a negative correlation with the wind speed at a lag of 3 weeks. The predictive models showed a maximum explained variance of 35%.

Aircraft measurements of electrified clouds at Kennedy Space Center. Part 2: Case study: 4 November 1988 (88309)

NASA Technical Reports Server (NTRS)

Jones, J. J.; Winn, W. P.; Hunyady, S. J.; Moore, C. B.; Bullock, J. W.

1990-01-01

During the fall of 1988, a Schweizer airplane equipped to measure electric field and other meteorological parameters flew over Kennedy Space Center (KSC) in a program to study clouds defined in the existing launch restriction criteria. A case study is presented of a single flight over KSC on November 4, 1988. This flight was chosen for two reasons: (1) the clouds were weakly electrified, and no lightning was reported during the flight; and (2) electric field mills in the surface array at KSC indicated field strengths greater than 3 kV/m, yet the aircraft flying directly over them at an altitude of 3.4 km above sea level measured field strengths of less than 1.6 kV/m. A weather summary, sounding description, record of cloud types, and an account of electric field measurements are included.

High troposphere O3 filament at mid-latitude: a BORTAS campaign case study

NASA Astrophysics Data System (ADS)

Aruffo, Eleonora; Peterson, David; Di Carlo, Piero; Biancofiore, Fabio; Busilacchio, Marcella; Dari Salisburgo, Cesare; Giammaria, Franco; Bauguitte, Stephane; Lee, James; Moller, Sarah; Hopkins, James; Punjabi, Shalini; Lewis, Alistair C.; Palmer, Paul; Hyer, Edward

2016-04-01

During a flight (B625, 24 July 2011) of the BORTAS campaign (BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites, Nova Scotia, Canada, July-August 2011), an increase in the ozone (O3) concentrations has been observed at high altitude (about 7.5 Km a.s.l.) correlated with a significant growth of total peroxy nitrates (∑PNs), CO, NO2, NOy, black carbon (BC), isoprene and other species. We will illustrate the data analysis, the Hysplit back trajectories calculation and the analysis of the meteorological/physical conditions occurred during this case study in order to demonstrate that the O3 filament measured at high altitude over the Atlantic Ocean (between Nova Scotia and the Gulf of St. Lawrence) is a consequence of boreal biomass burning fires.

The influences of wildfires and stratospheric-tropospheric exchange on ozone during seacions mission over St. Louis

NASA Astrophysics Data System (ADS)

Wilkins, Joseph L.

The influence of wildfire biomass burning and stratospheric air mass transport on tropospheric ozone (O3) concentrations in St. Louis during the SEAC4RS and SEACIONS-2013 measurement campaigns has been investigated. The Lagrangian particle dispersion model FLEXPART-WRF analysis reveals that 55% of ozonesonde profiles during SEACIONS were effected by biomass burning. Comparing ozonesonde profiles with numerical simulations show that as biomass burning plumes age there is O3 production aloft. A new plume injection height technique was developed based on the Naval Research Laboratory's (NRL) detection algorithm for pyro-convection. The NRL method identified 29 pyro-cumulonimbus events that occurred during the summer of 2013, of which 13 (44%) impacted the SEACIONS study area, and 4 (14%) impacted the St. Louis area. In this study, we investigate wildfire plume injection heights using model simulations and the FLAMBE emissions inventory using 2 different algorithms. In the first case, wildfire emissions are injected at the surface and allowed to mix within the boundary layer simulated by the meteorological model. In the second case, the injection height of wildfire emissions is determined by a guided deep-convective pyroCb run using the NRL detection algorithm. Results show that simulations using surface emissions were able to represent the transport of carbon monoxide plumes from wildfires when the plumes remained below 5 km or occurred during large convective systems, but that the surface effects were over predicted. The pyroCb cases simulated the long-range transport of elevated plumes above 5 km 68% of the time. In addition analysis of potential vorticity suggests that stratospheric intrusions or tropopause folds affected 13 days (48%) when there were sonde launches and 27 days (44%) during the entire study period. The largest impact occurred on September 12, 2013 when ozone-rich air impacted the nocturnal boundary layer. By analyzing ozonesonde profiles with meteorological transport models, we were able to identify biomass burning and stratospheric intrusions in St. Louis.

Revisiting the radionuclide atmospheric dispersion event of the Chernobyl disaster - modelling sensitivity and data assimilation

NASA Astrophysics Data System (ADS)

Roustan, Yelva; Duhanyan, Nora; Bocquet, Marc; Winiarek, Victor

2013-04-01

A sensitivity study of the numerical model, as well as, an inverse modelling approach applied to the atmospheric dispersion issues after the Chernobyl disaster are both presented in this paper. On the one hand, the robustness of the source term reconstruction through advanced data assimilation techniques was tested. On the other hand, the classical approaches for sensitivity analysis were enhanced by the use of an optimised forcing field which otherwise is known to be strongly uncertain. The POLYPHEMUS air quality system was used to perform the simulations of radionuclide dispersion. Activity concentrations in air and deposited to the ground of iodine-131, caesium-137 and caesium-134 were considered. The impact of the implemented parameterizations of the physical processes (dry and wet depositions, vertical turbulent diffusion), of the forcing fields (meteorology and source terms) and of the numerical configuration (horizontal resolution) were investigated for the sensitivity study of the model. A four dimensional variational scheme (4D-Var) based on the approximate adjoint of the chemistry transport model was used to invert the source term. The data assimilation is performed with measurements of activity concentrations in air extracted from the Radioactivity Environmental Monitoring (REM) database. For most of the investigated configurations (sensitivity study), the statistics to compare the model results to the field measurements as regards the concentrations in air are clearly improved while using a reconstructed source term. As regards the ground deposited concentrations, an improvement can only be seen in case of satisfactorily modelled episode. Through these studies, the source term and the meteorological fields are proved to have a major impact on the activity concentrations in air. These studies also reinforce the use of reconstructed source term instead of the usual estimated one. A more detailed parameterization of the deposition process seems also to be able to improve the simulation results. For deposited activities the results are more complex probably due to a strong sensitivity to some of the meteorological fields which remain quite uncertain.

Impact of the Loess Plateau on the atmospheric boundary layer structure and air quality in the North China Plain: a case study.

PubMed

Hu, Xiao-Ming; Ma, ZhiQiang; Lin, Weili; Zhang, Hongliang; Hu, Jianlin; Wang, Ying; Xu, Xiaobin; Fuentes, Jose D; Xue, Ming

2014-11-15

The North China Plain (NCP), to the east of the Loess Plateau, experiences severe regional air pollution. During the daytime in the summer, the Loess Plateau acts as an elevated heat source. The impacts of such a thermal effect on meteorological phenomena (e.g., waves, precipitation) in this region have been discussed. However, its impacts on the atmospheric boundary layer structure and air quality have not been reported. It is hypothesized that the thermal effect of the Plateau likely modulates the boundary layer structure and ambient concentrations of pollutants over the NCP under certain meteorological conditions. Thus, this study investigates such effect and its impacts using measurements and three-dimensional model simulations. It is found that in the presence of daytime westerly wind in the lower troposphere (~1 km above the NCP), warmer air above the Loess Plateau was transported over the NCP and imposed a thermal inversion above the mixed boundary layer, which acted as a lid and suppressed the mixed layer growth. As a result, pollutants accumulated in the shallow mixed layer and ozone was efficiently produced. The downward branch of the thermally-induced Mountain-Plains Solenoid circulation over the NCP contributed to enhancing the capping inversion and exacerbating air pollution. Previous studies have reported that low mixed layer, a factor for elevated pollution in the NCP, may be caused by aerosol scattering and absorption of solar radiation, frontal inversion, and large scale subsidence. The present study revealed a different mechanism (i.e., westerly warm advection) for the suppression of the mixed layer in summer NCP, which caused severe O3 pollution. This study has important implications for understanding the essential meteorological factors for pollution episodes in this region and forecasting these severe events. Copyright © 2014 Elsevier B.V. All rights reserved.

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

On the monitoring and prediction of flash floods in small and medium-sized catchments - the EXTRUSO project

NASA Astrophysics Data System (ADS)

Wiemann, Stefan; Eltner, Anette; Sardemann, Hannes; Spieler, Diana; Singer, Thomas; Thanh Luong, Thi; Janabi, Firas Al; Schütze, Niels; Bernard, Lars; Bernhofer, Christian; Maas, Hans-Gerd

2017-04-01

Flash floods regularly cause severe socio-economic damage worldwide. In parallel, climate change is very likely to increase the number of such events, due to an increasing frequency of extreme precipitation events (EASAC 2013). Whereas recent work primarily addresses the resilience of large catchment areas, the major impact of hydro-meteorological extremes caused by heavy precipitation is on small areas. Those are very difficult to observe and predict, due to sparse monitoring networks and only few means for hydro-meteorological modelling, especially in small catchment areas. The objective of the EXTRUSO project is to identify and implement appropriate means to close this gap by an interdisciplinary approach, combining comprehensive research expertise from meteorology, hydrology, photogrammetry and geoinformatics. The project targets innovative techniques for achieving spatio-temporal densified monitoring and simulations for the analysis, prediction and warning of local hydro-meteorological extreme events. The following four aspects are of particular interest: 1. The monitoring, analysis and combination of relevant hydro-meteorological parameters from various sources, including existing monitoring networks, ground radar, specific low-cost sensors and crowdsourcing. 2. The determination of relevant hydro-morphological parameters from different photogrammetric sensors (e.g. camera, laser scanner) and sensor platforms (e.g. UAV (unmanned aerial vehicle) and UWV (unmanned water vehicle)). 3. The continuous hydro-meteorological modelling of precipitation, soil moisture and water flows by means of conceptual and data-driven modelling. 4. The development of a collaborative, web-based service infrastructure as an information and communication point, especially in the case of an extreme event. There are three major applications for the planned information system: First, the warning of local extreme events for the population in potentially affected areas, second, the support for decision makers and emergency responders in the case of an event and, third, the development of open, interoperable tools for other researchers to be applied and further developed. The test area of the project is the Free State of Saxony (Germany) with a number of small and medium catchment areas. However, the whole system, comprising models, tools and sensor setups, is planned to be transferred and tested in other areas, within and outside Europe, as well. The team working on the project consists of eight researchers, including five PhD students and three postdocs. The EXTRUSO project is funded by the European Social Fund (ESF grant nr. 100270097) with a project duration of three years until June 2019. EASAC (2013): Trends in extreme weather events in Europe: implications for national and European Union adaption strategies. European Academies Science Advisory Council. Policy report 22, November 2013 The EXTRUSO project is funded by the European Social Fund (ESF), grant nr. 100270097

Enviro-HIRLAM in Studies of Urban and Aerosol Impacts on Metropolitan Areas: Science-Education Approach

NASA Astrophysics Data System (ADS)

Mahura, Alexander; Nuterman, Roman; Mazeikis, Adomas; Gonzalez-Aparicio, Iratxe; Ivanov, Sergey; Palamarchuk, Julia

2014-05-01

To attract more perspective young scientists (and especially, MSc and PhD students) for advanced research and development of complex and modern modelling systems, a specific approach is required. It should allow within a short period of time to evaluate personal background levels, skills, capabilities, etc. To learn more about new potential science-oriented developers of the models, it is often not enough to look into the personal resume. Thus, a special event such as Young Scientist Summer School (YSSS) can be organized, where young researchers could have an opportunity to attend not only relevant lectures, but also participate in practical exercises allowing to solidify lecture materials. Here, the practical exercises are presented as independent small-scale (having duration of up to a week) research projects or studies oriented on specific topics of YSSS. Developed approach was tested and realized during 2008 and 2011 YSSS events held and organized in Zelenogorsk, Russia (by NetFAM et al.; http://netfam.fmi.fi/YSSS08) and Odessa, Ukraine (by MUSCATEN et al.; http://atmos.physic.ut.ee/~muscaten/YSSS/1info.html), respectively. It has been refined for the new YSSS (Jul 2014) to be organized by the COST Action EuMetChem. The main focus of all these YSSSs was/is on the integrated modelling of meteorological and chemical transport processes and impact of chemical weather on numerical weather prediction and climate modelling. During previous YSSSs some of such projects - "URBAN: The Influence of Metropolitan Areas on Meteorology", "AEROSOL: The Impact of Aerosols Effects on Meteorology", and "COASTAL: The Coastal & Cities Effects on Meteorology" - were focused on evaluation of influence of metropolitan areas on formation of meteorological and chemical fields above urban areas (such as Paris, France; Copenhagen, Denmark, and Bilbao, Spain) and surroundings. The Environment - HIgh Resolution Limited Area Model (Enviro-HIRLAM) was used and modifications were made taking into account urban (anthropogenic heat flux, roughness, buildings and their characteristics), chemical species/ aerosol (feedback mechanisms) effects with further analysis of temporal and spatial variability of diurnal cycle for meteorological variables of key importance. Main items of listed above YSSS small-scale research projects include the following: • Introduction with background discussions (with brainstorming to outline research and technical tasks planned including main goal, specific objectives, etc.) in groups; • Analysis of meteorological situations (selecting specific cases/ dates using surface maps, diagrams of vertical sounding, and surface meteorological measurements); • Learning practical technical steps (in order to make necessary changes in the model and implementing urban and aerosol effects, compiling executables, making test runs); • Performing model runs/simulations at different options (dates, control vs. modified urban and aerosol runs, forecast lengths, spatial and temporal resolutions, etc.); • Visualization/ plotting of results obtained (in a form of graphs, tables, animations); • Evaluation of possible impact on urban areas (estimating differences between the control and modified runs through temporal and spatial variability of simulated meteorological (air temperature, wind speed, relative humidity, sensible and latent heat fluxes, etc.) and chemical pollutants (concentration and deposition) fields/ patterns; • Team's oral presentation of the project about results and findings and following guidelines (including aim and specific objectives, methodology and approaches, results and discussions with examples, conclusions, acknowledgements, references). Outline and detailed description of the developed approach, key items of the research projects and their schedules, preparatory steps including team of students' familiarization with general information on planned exercises and literature list (composed of required, recommended, and additional readings), requirements for successful completion and defense of the project, team independent work as well as under supervision are presented and discussed.

Relationship between meteorological phenomena and air pollution in an urbanized and industrialized coastal area in northern France

NASA Astrophysics Data System (ADS)

Gengembre, Cyril; Zhang, Shouwen; Dieudonné, Elsa; Sokolov, Anton; Augustin, Patrick; Riffault, Véronique; Dusanter, Sébastien; Fourmentin, Marc; Delbarre, Hervé

2016-04-01

Impacts of global climate evolution are quite uncertain at regional and local scales, especially on air pollution. Air quality is associated with local atmospheric dynamics at a time scale shorter than a few weeks, while the climate change time scale is on the order of fifty years. To infer consequences of climate evolution on air pollution, it is necessary to fill the gap between these different scales. Another challenge is to understand the effect of global warming on the frequency of meteorological phenomena that influence air pollution. In this work, we classified meteorological events related to air pollution during a one-year long field campaign in Dunkirk (northern France). Owing to its coastal location under urban and industrial exposures, the Dunkirk agglomeration is an interesting area for studying gaseous and aerosols pollutants and their relationship with weather events such as sea breezes, fogs, storms and fronts. The air quality in the northern region of France is also greatly influenced by highly populated and industrialized cities along the coast of the North Sea, and by London and Paris agglomerations. During a field campaign, we used simultaneously a three-dimensional sonic anemometer and a weather station network, along with a scanning Doppler Lidar system to analyse the vertical structure of the atmosphere. An Aerosol Chemical Speciation Monitor enabled investigating the PM1 behaviour during the studied events. Air contaminants such as NOx (NO and NO2) were also measured by the regional pollution monitoring network ATMO Nord Pas-de-Calais. The events were identified by finding specific criteria from meteorological and turbulent parameters. Over a hundred cases of sea breezes, fog periods, stormy days and atmospheric front passages were investigated. Variations of turbulent parameters (vertical sensible heat flux and momentum flux) give estimations on the transport and the dispersal of pollutants. As the fluxes are weak during fogs, an increase of PM1 concentrations was observed, which causes a deposition of the particles. Due to turbulence and horizontal dilution, PM1 concentrations were weak during storms.

1km Global Terrestrial Carbon Flux: Estimations and Evaluations

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Saito, M.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.

2017-12-01

Estimating global scale of the terrestrial carbon flux change with high accuracy and high resolution is important to understand global environmental changes. Furthermore the estimations of the global spatiotemporal distribution may contribute to the political and social activities such as REDD+. In order to reveal the current state of terrestrial carbon fluxes covering all over the world and a decadal scale. The satellite-based diagnostic biosphere model is suitable for achieving this purpose owing to observing on the present global land surface condition uniformly at some time interval. In this study, we estimated the global terrestrial carbon fluxes with 1km grids by using the terrestrial biosphere model (BEAMS). And we evaluated our new carbon flux estimations on various spatial scales and showed the transition of forest carbon stocks in some regions. Because BEAMS required high resolution meteorological data and satellite data as input data, we made 1km interpolated data using a kriging method. The data used in this study were JRA-55, GPCP, GOSAT L4B atmospheric CO2 data as meteorological data, and MODIS land product as land surface satellite data. Interpolating process was performed on the meteorological data because of insufficient resolution, but not on MODIS data. We evaluated our new carbon flux estimations using the flux tower measurement (FLUXNET2015 Datasets) in a point scale. We used 166 sites data for evaluating our model results. These flux sites are classified following vegetation type (DBF, EBF, ENF, mixed forests, grass lands, croplands, shrub lands, Savannas, wetlands). In global scale, the BEAMS estimations was underestimated compared to the flux measurements in the case of carbon uptake and release. The monthly variations of NEP showed relatively high correlations in DBF and mixed forests, but the correlation coefficients of EBF, ENF, and grass lands were less than 0.5. In the meteorological factors, air temperature and solar radiation showed very high correlations, and slight variations were showed in precipitation data. LAI data that was another large driving factor of terrestrial carbon cycle was not included in FLUXNET2015 datasets and it could not be evaluated.

[Simplification of crop shortage water index and its application in drought remote sensing monitoring].

PubMed

Liu, Anlin; Li, Xingmin; He, Yanbo; Deng, Fengdong

2004-02-01

Based on the principle of energy balance, the method for calculating latent evaporation was simplified, and hence, the construction of the drought remote sensing monitoring model of crop water shortage index was also simplified. Since the modified model involved fewer parameters and reduced computing times, it was more suitable for the operation running in the routine services. After collecting the concerned meteorological elements and the NOAA/AVHRR image data, the new model was applied to monitor the spring drought in Guanzhong, Shanxi Province. The results showed that the monitoring results from the new model, which also took more considerations of the effects of the ground coverage conditions and meteorological elements such as wind speed and the water pressure, were much better than the results from the model of vegetation water supply index. From the view of the computing times, service effects and monitoring results, the simplified crop water shortage index model was more suitable for practical use. In addition, the reasons of the abnormal results of CWSI > 1 in some regions in the case studies were also discussed in this paper.

Vertical ozone characteristics in urban boundary layer in Beijing.

PubMed

Ma, Zhiqiang; Xu, Honghui; Meng, Wei; Zhang, Xiaoling; Xu, Jing; Liu, Quan; Wang, Yuesi

2013-07-01

Vertical ozone and meteorological parameters were measured by tethered balloon in the boundary layer in the summer of 2009 in Beijing, China. A total of 77 tethersonde soundings were taken during the 27-day campaign. The surface ozone concentrations measured by ozonesondes and TEI 49C showed good agreement, albeit with temporal difference between the two instruments. Two case studies of nocturnal secondary ozone maxima are discussed in detail. The development of the low-level jet played a critical role leading to the observed ozone peak concentrations in nocturnal boundary layer (NBL). The maximum of surface ozone was 161.7 ppbv during the campaign, which could be attributed to abundant precursors storage near surface layer at nighttime. Vertical distribution of ozone was also measured utilizing conventional continuous analyzers on 325-m meteorological observation tower. The results showed the NBL height was between 47 and 280 m, which were consistent with the balloon data. Southerly air flow could bring ozone-rich air to Beijing, and the ozone concentrations exceeded the China's hourly ozone standard (approximately 100 ppb) above 600 m for more than 12 h.

Ground and satellite based assessment of meteorological droughts: The Coello river basin case study

NASA Astrophysics Data System (ADS)

Cruz-Roa, A. F.; Olaya-Marín, E. J.; Barrios, M. I.

2017-10-01

The spatial distribution of droughts is a key factor for designing water management policies at basin scale in arid and semi-arid regions. Ground hydro-meteorological data in neo-tropical areas are scarce; therefore, the merging of ground and satellite datasets is a promissory approach for improving our understanding of water distribution. This paper compares three monthly rainfall interpolation methods for drought evaluation. The ordinary kriging technique based on ground data, and cokriging with elevation as auxiliary variable were compared against cokriging using the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA). Twenty rain gauge stations and the 3B42V7 version of the TMPA research dataset were considered. Comparisons were made over the Coello river basin (Colombia) at 3″ spatial resolution covering a period of eight years (1998-2005). The best spatial rainfall estimation was found for cokriging using ground data and elevation. The spatial support of TMPA dataset is very coarse for a merged interpolation with ground data, this spatial scales discrepancy highlight the need to consider scaling rules in the interpolation process.

Investigation of spatiotemporal relationship between dengue fever and drought

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2016-04-01

Dengue Fever is a vector-borne disease that is transmitted between human and mosquitos in tropical and sub-tropical regions. Previous studies have found significant relationship between the epidemic of dengue cases and climate variables, especially temperature and precipitation. Besides, the natural phenomena (e.g., drought) are considered that significantly drop the number of dengue cases by killing vector's breeding environment. However, in Kaohsiung City, Taiwan, there are evidences that the temporal pattern of dengue is correlated to drought events. Kaohsiung City experienced two main dengue outbreaks in 2002 and 2014 that both years were confirmed with serious drought. Especially in 2014, Kaohsiung City was suffered from extremely dengue outbreak in 2014 that reported the highest number of dengue cases in the history. Otherwise, another nearby city, Tainan City, had reported the biggest outbreak in 2015. This study constructs the spatiotemporal model of dengue incidences and index of drought events (Standardized Precipitation Index, SPI) based on the distributed lag nonlinear model (DLNM). Other meteorological measures are also included in the analysis.

Is drought helping or killing dengue? Investigation of spatiotemporal relationship between dengue fever and drought

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2015-04-01

Dengue Fever is a vector-borne disease that is transmitted between human and mosquitos in tropical and sub-tropical regions. Previous studies have found significant relationship between the epidemic of dengue cases and climate variables, especially temperature and precipitation. Besides, the natural phenomena (e.g., drought) are considered that significantly drop the number of dengue cases by killing vector's breeding environment. However, in Kaohsiung City, Taiwan, there are evidences that the temporal pattern of dengue is correlated to drought events. Kaohsiung City experienced two main dengue outbreaks in 2002 and 2014 that both years were confirmed with serious drought. Especially in 2014, Kaohsiung City was suffered from extremely dengue outbreak in 2014 that reported the highest number of dengue cases in the history. This study constructs the spatiotemporal model of dengue incidences and index of drought events (Standardized Precipitation Index, SPI) based on the distributed lag nonlinear model (DLNM). Other meteorological measures are also included in the analysis.

WMO's activities in gender mainstreaming in geosciences, with a special focus on integrated flood management

NASA Astrophysics Data System (ADS)

Manaenkova, Elena; Caponi, Claudio; Alexieva, Assia; Poissonnier, Maud; Tripathi, Ramesh

2017-04-01

Statistics show that women represent a minority in science, technology, engineering and mathematics (STEM). They are significantly underrepresented in governance, management and international negotiations. They further comprise only a third of the global workforce at National Meteorological and Hydrological Services and only one out of five senior managers is a woman. This paper presents historical trends and statistics on the participation of women and men in all structures and activities of the World Meteorological Organization (WMO). It explores the root causes of women's underrepresentation in the meteorological, hydrological and climatological profession as well as analyzes its adverse effects in terms of the scarcity of role models for young female professionals and the lack of gender considerations in the provision of weather, hydrological and climate services. The paper presents WMO's approach to addressing these issues through the adoption of a WMO Gender Equality Policy, a comprehensive Gender Action Plan, targeted leadership training, a series of awareness raising campaigns, and specific recommendations on how to make weather, hydrological and climate services more gender-sensitive. As a specific example, the Associated Programme on Flood Management (APFM) of WMO and the Global Water Partnership (GWP) is in the process of developing a training manual for gender mainstreaming in integrated flood management. This generic, instructive, at the same time informative training manual and facilitator's guide will strive to fill gaps in practical knowledge, decision-making and further provide assistance in gender sensitive approaches for both local policy makers and communities affected by floods. The format and contents of the manual are particularly focused on every phase of the flood management cycle, incorporating gender based needs, strategies and actions/approaches. The facilitator or training instructor is encouraged to adapt the materials with local case studies for conducting short exercises with the intended participants (women and men) using a participatory design approach. Keywords: Meteorological, Hydrological, Climatological, Gender equality, Integrated flood management, Training manual, Participatory design

Influence of Meteorological Regimes on Cloud Microphysics Over Ross Island, Antarctica

NASA Astrophysics Data System (ADS)

Glennon, C.; Wang, S. H.; Scott, R. C.; Bromwich, D. H.; Lubin, D.

2017-12-01

The Antarctic provides a sharp contrast in cloud microphysics from the high Arctic, due to orographic lifting and resulting strong vertical motions induced by mountain ranges and other varying terrain on several spatial scales. The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) deployed advanced cloud remote sensing equipment to Ross Island, Antarctica, from December 2015 until January 2016. This equipment included scanning and zenith radars operating in the Ka and X bands, a high spectral resolution lidar (HSRL), and a polarized micropulse lidar (MPL). A major AWARE objective is to provide state-of-the-art data for improving cloud microphysical parameterizations in climate models. To further this objective we have organized and classified the local Ross Island meteorology into distinct regimes using k-means clustering on ERA-Interim reanalysis data. We identify synoptic categories producing unique regimes of cloud cover and cloud microphysical properties over Ross Island. Each day of observations can then be associated with a specific meteorological regime, thus assisting modelers with identifying case studies. High-resolution (1 km) weather forecasts from the Antarctic Mesoscale Prediction System (AMPS) are sorted into these categories. AMPS-simulated anomalies of cloud fraction, near-surface air temperature, and vertical velocity at 500-mb are composited and compared with ground-based radar and lidar-derived cloud properties to identify mesoscale meteorological processes driving Antarctic cloud formation. Synoptic lows over the Ross and Amundsen Seas drive anomalously warm conditions at Ross Island by injecting marine air masses inland over the West Antarctic Ice Sheet (WAIS). This results in ice and mixed-phase orographic cloud systems arriving at Ross Island from the south to southeast along the Transantarctic Mountains. In contrast, blocking over the Amundsen Sea region brings classical liquid-dominated mixed-phase and thin liquid water clouds from the Southern Ocean. Low pressure systems over the Bellingshausen Sea produce outflow of cold, dry continental polar air, yielding predominantly tenuous ice cloud at Ross Island.

Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

NASA Astrophysics Data System (ADS)

Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

2013-04-01

The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of flood preparedness and crisis management for basins greater than 1.000 km2.

Simulating land-atmosphere feedbacks and response to widespread forest disturbance: The role of lower boundary configuration and dynamic water table in meteorological modeling

NASA Astrophysics Data System (ADS)

Forrester, M.; Maxwell, R. M.; Bearup, L. A.; Gochis, D.

2017-12-01

Numerical meteorological models are frequently used to diagnose land-atmosphere interactions and predict large-scale response to extreme or hazardous events, including widespread land disturbance or perturbations to near-surface moisture. However, few atmospheric modeling platforms consider the impact that dynamic groundwater storage, specifically 3D subsurface flow, has on land-atmosphere interactions. In this study, we use the Weather Research and Forecasting (WRF) mesoscale meteorological model to identify ecohydrologic and land-atmosphere feedbacks to disturbance by the mountain pine beetle (MPB) over the Colorado Headwaters region. Disturbance simulations are applied to WRF with various lower boundary configurations: Including default Noah land surface model soil moisture representation; a version of WRF coupled to ParFlow (PF), an integrated groundwater-surface water model that resolves variably saturated flow in the subsurface; and WRF coupled to PF in a static water table version, simulating only vertical and no lateral subsurface flow. Our results agree with previous literature showing MPB-induced reductions in canopy transpiration in all lower boundary scenarios, as well as energy repartitioning, higher water tables, and higher planetary boundary layer over infested regions. Simulations show that expanding from local to watershed scale results in significant damping of MPB signal as unforested and unimpacted regions are added; and, while deforestation appears to have secondary feedbacks to planetary boundary layer and convection, these slight perturbations to cumulative summer precipitation are insignificant in the context of ensemble methodologies. Notably, the results suggest that groundwater representation in atmospheric modeling affects the response intensity of a land disturbance event. In the WRF-PF case, energy and atmospheric processes are more sensitive to disturbance in regions with higher water tables. Also, when dynamic subsurface hydrology is removed, WRF simulates a greater response to MPB at the land-atmosphere interface, including greater changes to daytime skin temperature, Bowen ratio and near-surface humidity. These findings highlight lower boundary representations in computational meteorology and numerical land-atmosphere modeling.

Sensitivity of the interannual variability of mineral aerosol simulations to meteorological forcing dataset

DOE PAGES

Smith, Molly B.; Mahowald, Natalie M.; Albani, Samuel; ...

2017-03-07

Interannual variability in desert dust is widely observed and simulated, yet the sensitivity of these desert dust simulations to a particular meteorological dataset, as well as a particular model construction, is not well known. Here we use version 4 of the Community Atmospheric Model (CAM4) with the Community Earth System Model (CESM) to simulate dust forced by three different reanalysis meteorological datasets for the period 1990–2005. We then contrast the results of these simulations with dust simulated using online winds dynamically generated from sea surface temperatures, as well as with simulations conducted using other modeling frameworks but the same meteorological forcings, in order tomore » determine the sensitivity of climate model output to the specific reanalysis dataset used. For the seven cases considered in our study, the different model configurations are able to simulate the annual mean of the global dust cycle, seasonality and interannual variability approximately equally well (or poorly) at the limited observational sites available. Altogether, aerosol dust-source strength has remained fairly constant during the time period from 1990 to 2005, although there is strong seasonal and some interannual variability simulated in the models and seen in the observations over this time period. Model interannual variability comparisons to observations, as well as comparisons between models, suggest that interannual variability in dust is still difficult to simulate accurately, with averaged correlation coefficients of 0.1 to 0.6. Because of the large variability, at least 1 year of observations at most sites are needed to correctly observe the mean, but in some regions, particularly the remote oceans of the Southern Hemisphere, where interannual variability may be larger than in the Northern Hemisphere, 2–3 years of data are likely to be needed.« less

Characteristics of Fine Particles in an Urban Atmosphere—Relationships with Meteorological Parameters and Trace Gases

PubMed Central

Zhang, Tianhao; Zhu, Zhongmin; Gong, Wei; Xiang, Hao; Fang, Ruimin

2016-01-01

Atmospheric fine particles (diameter < 1 μm) attract a growing global health concern and have increased in urban areas that have a strong link to nucleation, traffic emissions, and industrial emissions. To reveal the characteristics of fine particles in an industrial city of a developing country, two-year measurements of particle number size distribution (15.1 nm–661 nm), meteorological parameters, and trace gases were made in the city of Wuhan located in central China from June 2012 to May 2014. The annual average particle number concentrations in the nucleation mode (15.1 nm–30 nm), Aitken mode (30 nm–100 nm), and accumulation mode (100 nm–661 nm) reached 4923 cm−3, 12193 cm−3 and 4801 cm−3, respectively. Based on Pearson coefficients between particle number concentrations and meteorological parameters, precipitation and temperature both had significantly negative relationships with particle number concentrations, whereas atmospheric pressure was positively correlated with the particle number concentrations. The diurnal variation of number concentration in nucleation mode particles correlated closely with photochemical processes in all four seasons. At the same time, distinct growth of particles from nucleation mode to Aitken mode was only found in spring, summer, and autumn. The two peaks of Aitken mode and accumulation mode particles in morning and evening corresponded obviously to traffic exhaust emissions peaks. A phenomenon of “repeated, short-lived” nucleation events have been created to explain the durability of high particle concentrations, which was instigated by exogenous pollutants, during winter in a case analysis of Wuhan. Measurements of hourly trace gases and segmental meteorological factors were applied as proxies for complex chemical reactions and dense industrial activities. The results of this study offer reasonable estimations of particle impacts and provide references for emissions control strategies in industrial cities of developing countries. PMID:27517948

Should Variations of d2H, d18O and d17O in Precipitation be Considered 'Settled Science' or a 'New Frontier' For Understanding Cloud Dynamics and Microphysics?

NASA Astrophysics Data System (ADS)

Aggarwal, P. K.; araguas Araguas, L.; Belachew, D.; Terzer, S.; Wassenaar, L. I.; Longstaffe, F. J.; Schumacher, C.; Funk, A. B.; Steinacker, R.; Kaltenboeck, R.

2017-12-01

After more than 60 years of isotope measurements in precipitation, there are relatively well established patterns of variation, but their origin and controlling parameters remain a matter of debate, preventing a fuller integration of isotope-based information in meteorology. The prevailing hypothesis based on temperature and Rayleigh distillation has been successful in explaining many of the patterns, particularly at a seasonal or annual scale, and attempts to explain variances by 'tweaking' the prevailing hypothesis suggest that the underlying science may be considered to be 'settled'. A rigorous evaluation at the storm event scale, where precipitation acquires its isotope composition, however, does not provide a satisfactory explanation in most cases. We have conducted an year-long study with high-frequency sampling (5-15 min) of mid-latitude precipitation at Vienna and more than 1000 samples have been analyzed for d2H, d18O and d17O. We have also collected profiles of reflectivity and doppler velocity using a vertically pointed micro-rain radar, particle size distribution in precipitation using a disdrometer, and conducted aerological analysis of air and moisture circulation using sounding data. A combined evaluation of isotope and meteorological data provides a detailed understanding of isotope variability. We will discuss these results and the light they shed on boundary layer and tropospheric moisture circulation in frontal or convective precipitation, the relative roles of vapor deposition and riming growth of precipitation, and the origin of d-excess. The agreement between meteorological observations and isotopic variability is extremely promising and may help open a new frontier in the use of isotopes for weather and climate studies.

Diagnosis of an intense atmospheric river impacting the pacific northwest: Storm summary and offshore vertical structure observed with COSMIC satellite retrievals

USGS Publications Warehouse

Neiman, P.J.; Ralph, F.M.; Wick, G.A.; Kuo, Y.-H.; Wee, T.-K.; Ma, Z.; Taylor, G.H.; Dettinger, M.D.

2008-01-01

This study uses the new satellite-based Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission to retrieve tropospheric profiles of temperature and moisture over the data-sparse eastern Pacific Ocean. The COSMIC retrievals, which employ a global positioning system radio occultation technique combined with "first-guess" information from numerical weather prediction model analyses, are evaluated through the diagnosis of an intense atmospheric river (AR; i.e., a narrow plume of strong water vapor flux) that devastated the Pacific Northwest with flooding rains in early November 2006. A detailed analysis of this AR is presented first using conventional datasets and highlights the fact that ARs are critical contributors to West Coast extreme precipitation and flooding events. Then, the COSMIC evaluation is provided. Offshore composite COSMIC soundings north of, within, and south of this AR exhibited vertical structures that are meteorologically consistent with satellite imagery and global reanalysis fields of this case and with earlier composite dropsonde results from other landfalling ARs. Also, a curtain of 12 offshore COSMIC soundings through the AR yielded cross-sectional thermodynamic and moisture structures that were similarly consistent, including details comparable to earlier aircraft-based dropsonde analyses. The results show that the new COSMIC retrievals, which are global (currently yielding ???2000 soundings per day), provide high-resolution vertical-profile information beyond that found in the numerical model first-guess fields and can help monitor key lower-tropospheric mesoscale phenomena in data-sparse regions. Hence, COSMIC will likely support a wide array of applications, from physical process studies to data assimilation, numerical weather prediction, and climate research. ?? 2008 American Meteorological Society.

Climate-dependence of ecosystem services in a nature reserve in northern China

PubMed Central

Fang, Jiaohui; Song, Huali; Zhang, Yiran; Li, Yanran

2018-01-01

Evaluation of ecosystem services has become a hotspot in terms of research focus, but uncertainties over appropriate methods remain. Evaluation can be based on the unit price of services (services value method) or the unit price of the area (area value method). The former takes meteorological factors into account, while the latter does not. This study uses Kunyu Mountain Nature Reserve as a study site at which to test the effects of climate on the ecosystem services. Measured data and remote sensing imagery processed in a geographic information system were combined to evaluate gas regulation and soil conservation, and the influence of meteorological factors on ecosystem services. Results were used to analyze the appropriateness of the area value method. Our results show that the value of ecosystem services is significantly affected by meteorological factors, especially precipitation. Use of the area value method (which ignores the impacts of meteorological factors) could considerably impede the accuracy of ecosystem services evaluation. Results were also compared with the valuation obtained using the modified equivalent value factor (MEVF) method, which is a modified area value method that considers changes in meteorological conditions. We found that MEVF still underestimates the value of ecosystem services, although it can reflect to some extent the annual variation in meteorological factors. Our findings contribute to increasing the accuracy of evaluation of ecosystem services. PMID:29438427

Climate-dependence of ecosystem services in a nature reserve in northern China.

PubMed

Fang, Jiaohui; Song, Huali; Zhang, Yiran; Li, Yanran; Liu, Jian

2018-01-01

Evaluation of ecosystem services has become a hotspot in terms of research focus, but uncertainties over appropriate methods remain. Evaluation can be based on the unit price of services (services value method) or the unit price of the area (area value method). The former takes meteorological factors into account, while the latter does not. This study uses Kunyu Mountain Nature Reserve as a study site at which to test the effects of climate on the ecosystem services. Measured data and remote sensing imagery processed in a geographic information system were combined to evaluate gas regulation and soil conservation, and the influence of meteorological factors on ecosystem services. Results were used to analyze the appropriateness of the area value method. Our results show that the value of ecosystem services is significantly affected by meteorological factors, especially precipitation. Use of the area value method (which ignores the impacts of meteorological factors) could considerably impede the accuracy of ecosystem services evaluation. Results were also compared with the valuation obtained using the modified equivalent value factor (MEVF) method, which is a modified area value method that considers changes in meteorological conditions. We found that MEVF still underestimates the value of ecosystem services, although it can reflect to some extent the annual variation in meteorological factors. Our findings contribute to increasing the accuracy of evaluation of ecosystem services.

The influence of weather on migraine – are migraine attacks predictable?

PubMed Central

Hoffmann, Jan; Schirra, Tonio; Lo, Hendra; Neeb, Lars; Reuter, Uwe; Martus, Peter

2015-01-01

Objective The study aimed at elucidating a potential correlation between specific meteorological variables and the prevalence and intensity of migraine attacks as well as exploring a potential individual predictability of a migraine attack based on meteorological variables and their changes. Methods Attack prevalence and intensity of 100 migraineurs were correlated with atmospheric pressure, relative air humidity, and ambient temperature in 4-h intervals over 12 consecutive months. For each correlation, meteorological parameters at the time of the migraine attack as well as their variation within the preceding 24 h were analyzed. For migraineurs showing a positive correlation, logistic regression analysis was used to assess the predictability of a migraine attack based on meteorological information. Results In a subgroup of migraineurs, a significant weather sensitivity could be observed. In contrast, pooled analysis of all patients did not reveal a significant association. An individual prediction of a migraine attack based on meteorological data was not possible, mainly as a result of the small prevalence of attacks. Interpretation The results suggest that only a subgroup of migraineurs is sensitive to specific weather conditions. Our findings may provide an explanation as to why previous studies, which commonly rely on a pooled analysis, show inconclusive results. The lack of individual attack predictability indicates that the use of preventive measures based on meteorological conditions is not feasible. PMID:25642431

Meteorological Data Visualization in Multi-User Virtual Reality

NASA Astrophysics Data System (ADS)

Appleton, R.; van Maanen, P. P.; Fisher, W. I.; Krijnen, R.

2017-12-01

Due to their complexity and size, visualization of meteorological data is important. It enables the precise examining and reviewing of meteorological details and is used as a communication tool for reporting, education and to demonstrate the importance of the data to policy makers. Specifically for the UCAR community it is important to explore all of such possibilities.Virtual Reality (VR) technology enhances the visualization of volumetric and dynamical data in a more natural way as compared to a standard desktop, keyboard mouse setup. The use of VR for data visualization is not new but recent developments has made expensive hardware and complex setups unnecessary. The availability of consumer of the shelf VR hardware enabled us to create a very intuitive and low cost way to visualize meteorological data. A VR viewer has been implemented using multiple HTC Vive head sets and allows visualization and analysis of meteorological data in NetCDF format (e.g. of NCEP North America Model (NAM), see figure). Sources of atmospheric/meteorological data include radar and satellite as well as traditional weather stations. The data includes typical meteorological information such as temperature, humidity, air pressure, as well as those data described by the climate forecast (CF) model conventions (http://cfconventions.org). Other data such as lightning-strike data and ultra-high-resolution satellite data are also becoming available. The users can navigate freely around the data which is presented in a virtual room at a scale of up to 3.5 X 3.5 meters. The multiple users can manipulate the model simultaneously. Possible mutations include scaling/translating, filtering by value and using a slicing tool to cut-off specific sections of the data to get a closer look. The slicing can be done in any direction using the concept of a `virtual knife' in real-time. The users can also scoop out parts of the data and walk though successive states of the model. Future plans are (a.o.) to further improve the performance to a higher update rate (for the reduction of possible motion sickness) and to add more advanced filtering and annotation capabilities. We are looking for cooperation with data owners with use cases such as the above mentioned. This will help in further improving and developing our tool and to broaden its application into other domains.

Assessment of ozone variations and meteorological effects in an urban area in the Mediterranean Coast.

PubMed

Dueñas, C; Fernández, M C; Cañete, S; Carretero, J; Liger, E

2002-11-01

Ozone concentrations are valuable indicators of possible health and environmental impacts. However, they are also used to monitor changes and trends in the sources of both ozone and its precursors. For this purpose, the influence of meteorological variables is a confusing factor. This study presents an analysis of a year of ozone concentrations measured in a coastal Spanish city. Firstly, the aim of this study was to perceive the daily, monthly and seasonal variation patterns of ozone concentrations. Diurnal cycles are presented by season and the fit of the data to a normal distribution is tested. In order to assess ozone behaviour under temperate weather conditions, local meteorological variables (wind direction and speed, temperature, relative humidity, pressure and rainfall) were monitored together with ozone concentrations. The main relationships we could observe in these analyses were then used to obtain a regression equation linking diurnal ozone concentrations in summer with meteorological parameters.

The Urban Heat Island Phenomenon and Potential Mitigation Strategies

NASA Technical Reports Server (NTRS)

Estes, Maurice G., Jr.; Gorsevski, Virginia; Russell, Camille; Quattrochi, Dale; Luvall, Jeffrey

1999-01-01

A survey of urban heat island research is provided to describe how heat islands develop, urban landscape and meteorological characteristics that facilitate development, use of aircraft remote sensing data, and why heat islands are of interest to planners, elected officials, and the public. The roles of the National Aeronautics and Space Administration (NASA), the Environmental Protection Agency (EPA), other federal agencies, national laboratories and universities, state and local governments, and non-governmental organizations (NGOS) in studying the urban heat island effect and developing mitigation strategies are explored. Barriers that hamper mitigation efforts and case studies in Atlanta and Salt Lake City are discussed.

Investigation of the cold drops in the European area, study based on ERA Interim and ECMWF ensemble model

NASA Astrophysics Data System (ADS)

Gaal, Nikolett; Ihasz, Istvan

2013-04-01

We aimed to analyze the cold drops and the upper level lows formed in the middle troposphere - which are often difficult to be predicted - by means of the statistical methods and case studies. Cold drops are often followed by intensive events such as heavy rainfall, rainstorm, at times tubas and non mesocyclonical tornadoes. Due to the above mentioned events and the incentive of Aviation and Severe Weather Forecasting Division at Hungarian Meteorological Service, the phenomenon was analyzed in a complex way by a self-developed multiple method. Upper-Level Lows (ULL-s) are closed; cyclonically circulating eddies isolated from the main western stream in the middle and upper troposphere. They are also sometimes called "cold drops" because the air within an Upper Level low is colder than in its surroundings. The cold air within usually does not show up on the surface, meaning the vertical temperature gradient is high, which in turn causes instability and heavy storms, especially during the summer. An ULL-s diameter is about a couple hundred km-s, so it looks like a miniature cyclone. ERA INTERIM is the current state of reanalysis that is still in development. It also has the best possible spatial resolution, which leads to its usage in a wide area of fields. Our studies focused mainly on the cold drops' statistics and meteorology, as well as a few case studies. Since ULL's occur rarely, we developed a new ULL-recognition process to increase the number of samples available. First of all, we gathered 70days when cold drops occurred in the past 10 years. Then we analyzed them in 6-hour periods, for a total of 280 separate time periods. Finally, we have four main case studies in the paper. In the future, we would like to run further tests with our ULL-recognition algorithm to study the last 30 years of cold drops, and we would also like to experiment more with ULL forecasting as well.

Model variations in predicting incidence of Plasmodium falciparum malaria using 1998-2007 morbidity and meteorological data from south Ethiopia.

PubMed

Loha, Eskindir; Lindtjørn, Bernt

2010-06-16

Malaria transmission is complex and is believed to be associated with local climate changes. However, simple attempts to extrapolate malaria incidence rates from averaged regional meteorological conditions have proven unsuccessful. Therefore, the objective of this study was to determine if variations in specific meteorological factors are able to consistently predict P. falciparum malaria incidence at different locations in south Ethiopia. Retrospective data from 42 locations were collected including P. falciparum malaria incidence for the period of 1998-2007 and meteorological variables such as monthly rainfall (all locations), temperature (17 locations), and relative humidity (three locations). Thirty-five data sets qualified for the analysis. Ljung-Box Q statistics was used for model diagnosis, and R squared or stationary R squared was taken as goodness of fit measure. Time series modelling was carried out using Transfer Function (TF) models and univariate auto-regressive integrated moving average (ARIMA) when there was no significant predictor meteorological variable. Of 35 models, five were discarded because of the significant value of Ljung-Box Q statistics. Past P. falciparum malaria incidence alone (17 locations) or when coupled with meteorological variables (four locations) was able to predict P. falciparum malaria incidence within statistical significance. All seasonal AIRMA orders were from locations at altitudes above 1742 m. Monthly rainfall, minimum and maximum temperature was able to predict incidence at four, five and two locations, respectively. In contrast, relative humidity was not able to predict P. falciparum malaria incidence. The R squared values for the models ranged from 16% to 97%, with the exception of one model which had a negative value. Models with seasonal ARIMA orders were found to perform better. However, the models for predicting P. falciparum malaria incidence varied from location to location, and among lagged effects, data transformation forms, ARIMA and TF orders. This study describes P. falciparum malaria incidence models linked with meteorological data. Variability in the models was principally attributed to regional differences, and a single model was not found that fits all locations. Past P. falciparum malaria incidence appeared to be a superior predictor than meteorology. Future efforts in malaria modelling may benefit from inclusion of non-meteorological factors.

Is suicide mortality associated with meteorological and socio-economic factors? An ecological study in a city in Taiwan with a high suicide rate.

PubMed

Wu, Ya Wen; Chen, Chih Ken; Wang, Liang Jen

2014-06-01

Keelung City has the highest suicide rate in Taiwan. This study aimed to determine whether meteorological and socio-economic factors are associated with suicide mortality in Keelung City, by gender and by means of suicide. Data on suicides between January 2006 and December 2010 were provided by the Department of Health, Keelung City Government. The suicide victims were categorized into non-violent and violent groups, based on the International Classification of Disease, Ninth Revision. Meteorological data were obtained from the Central Weather Bureau of Taiwan. Socio-economic data were gathered from the Accounting and Statistics Office, Keelung City Government. Multiple linear regression analysis with backward elimination was performed to determine the model that was most effective in predicting dependent variables. During the 5-year study period, the overall suicide mortality rate was negatively associated with ambient temperature. Male suicide mortality was positively correlated with unemployment, and negatively correlated with ambient temperature, barometric pressure, rainy days, family income and number of holidays. Female suicide mortality and violent suicide mortality were not significantly correlated with any meteorological or socio-economic factors. Non-violent suicide mortality was positively correlated with unemployment, and negatively correlated with ambient temperature, barometric pressure and family income. Suicide is a complex psychopathological phenomenon. Further studies with individual data are warranted to confirm how meteorological and socio-economic conditions influence ones' suicidal behaviour.

Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in Houston/Texas

NASA Astrophysics Data System (ADS)

Cuchiara, G. C.; Li, X.; Carvalho, J.; Rappenglück, B.

2014-10-01

With over 6 million inhabitants the Houston metropolitan area is the fourth-largest in the United States. Ozone concentration in this southeast Texas region frequently exceeds the National Ambient Air Quality Standard (NAAQS). For this reason our study employed the Weather Research and Forecasting model with Chemistry (WRF/Chem) to quantify meteorological prediction differences produced by four widely used PBL schemes and analyzed its impact on ozone predictions. The model results were compared to observational data in order to identify one superior PBL scheme better suited for the area. The four PBL schemes include two first-order closure schemes, the Yonsei University (YSU) and the Asymmetric Convective Model version 2 (ACM2); as well as two turbulent kinetic energy closure schemes, the Mellor-Yamada-Janjic (MYJ) and Quasi-Normal Scale Elimination (QNSE). Four 24 h forecasts were performed, one for each PBL scheme. Simulated vertical profiles for temperature, potential temperature, relative humidity, water vapor mixing ratio, and the u-v components of the wind were compared to measurements collected during the Second Texas Air Quality Study (TexAQS-II) Radical and Aerosol Measurements Project (TRAMP) experiment in summer 2006. Simulated ozone was compared against TRAMP data, and air quality stations from Continuous Monitoring Station (CAMS). Also, the evolutions of the PBL height and vertical mixing properties within the PBL for the four simulations were explored. Although the results yielded high correlation coefficients and small biases in almost all meteorological variables, the overall results did not indicate any preferred PBL scheme for the Houston case. However, for ozone prediction the YSU scheme showed greatest agreements with observed values.

Intercomparison of Planetary Boundary Layer Parameterization and its Impacts on Surface Ozone Concentration in the WRF/Chem Model for a Case Study in Houston/Texas

NASA Astrophysics Data System (ADS)

Cuchiara, Gustavo C.; Li, Xiangshang; Carvalho, Jonas; Rappenglück, Bernhard

2015-04-01

With over 6 million inhabitants the Houston metropolitan area is the fourth-largest in the United States. Ozone concentration in this southeast Texas region frequently exceeds the National Ambient Air Quality Standard (NAAQS). For this reason our study employed the Weather Research and Forecasting model with Chemistry (WRF/Chem) to quantify meteorological prediction differences produced by four widely used PBL schemes and analyzed its impact on ozone predictions. The model results were compared to observational data in order to identify one superior PBL scheme better suited for the area. The four PBL schemes include two first-order closure schemes, the Yonsei University (YSU) and the Asymmetric Convective Model version 2 (ACM2); as well as two turbulent kinetic energy closure schemes, the Mellor-Yamada-Janjic (MYJ) and Quasi-Normal Scale Elimination (QNSE). Four 24 h forecasts were performed, one for each PBL scheme. Simulated vertical profiles for temperature, potential temperature, relative humidity, water vapor mixing ratio, and the u-v components of the wind were compared to measurements collected during the Second Texas Air Quality Study (TexAQS-II) Radical and Aerosol Measurements Project (TRAMP) experiment in summer 2006. Simulated ozone was compared against TRAMP data, and air quality stations from Continuous Monitoring Station (CAMS). Also, the evolutions of the PBL height and vertical mixing properties within the PBL for the four simulations were explored. Although the results yielded high correlation coefficients and small biases in almost all meteorological variables, the overall results did not indicate any preferred PBL scheme for the Houston case. However, for ozone prediction the YSU scheme showed greatest agreements with observed values.

The effect of soil moisture anomalies on maize yield in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis

2018-03-01

Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

Quantifying the adverse effect of excessive heat on children: An elevated risk of hand, foot and mouth disease in hot days.

PubMed

Zhang, Wangjian; Du, Zhicheng; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2016-01-15

Hand, foot and mouth disease (HFMD) is a common childhood infection and has become a major public health issue in China. Considerable research has focused on the role of meteorological factors such as temperature and relative humidity in HFMD development. However, no studies have specifically quantified the impact of another major environmental agent, excessive heat, on HFMD. The current study was designed to help address this research gap. Case-based HFMD surveillance data and daily meteorological data collected between 2010 and 2012 was obtained from China CDC and the National Meteorological Information Center, respectively. Distributed lag nonlinear models were applied to assess the impact of excessive heat on HFMD and its variability across social-economic status and age groups. After controlling the effects of several potential confounders, the commonly hot days were found to positively affect the HFMD burdens with the relative risk (RR) peaking at around 6 days of lag. The RR of HFMD in the Pearl-River Delta Region was generally higher and persisted longer than that in the remaining developing areas. Regarding the inter-age group discrepancy, children aged 3-6 years old had the highest risk of HFMD under conditions of excessive heat whereas those greater than 6 years old had the lowest. The lag structure of the impact of the extremely hot days was quite similar to that of the commonly hot days, although the relative effect of these two kinds of conditions of excessive heat might vary across regions. This study indicated significantly facilitating effects of excessive heat on HFMD especially among those aged 3-6 and from developed areas. Results from the current study were particularly practical and important for developing area-and-age-targeted control programs in the context of climate change and urbanization. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

A Study on the Potential Applications of Satellite Data in Air Quality Monitoring and Forecasting

NASA Technical Reports Server (NTRS)

Li, Can; Hsu, N. Christina; Tsay, Si-Chee

2011-01-01

In this study we explore the potential applications of MODIS (Moderate Resolution Imaging Spectroradiometer) -like satellite sensors in air quality research for some Asian regions. The MODIS aerosol optical thickness (AOT), NCEP global reanalysis meteorological data, and daily surface PM(sub 10) concentrations over China and Thailand from 2001 to 2009 were analyzed using simple and multiple regression models. The AOT-PM(sub 10) correlation demonstrates substantial seasonal and regional difference, likely reflecting variations in aerosol composition and atmospheric conditions, Meteorological factors, particularly relative humidity, were found to influence the AOT-PM(sub 10) relationship. Their inclusion in regression models leads to more accurate assessment of PM(sub 10) from space borne observations. We further introduced a simple method for employing the satellite data to empirically forecast surface particulate pollution, In general, AOT from the previous day (day 0) is used as a predicator variable, along with the forecasted meteorology for the following day (day 1), to predict the PM(sub 10) level for day 1. The contribution of regional transport is represented by backward trajectories combined with AOT. This method was evaluated through PM(sub 10) hindcasts for 2008-2009, using ohservations from 2005 to 2007 as a training data set to obtain model coefficients. For five big Chinese cities, over 50% of the hindcasts have percentage error less than or equal to 30%. Similar performance was achieved for cities in northern Thailand. The MODIS AOT data are responsible for at least part of the demonstrated forecasting skill. This method can be easily adapted for other regions, but is probably most useful for those having sparse ground monitoring networks or no access to sophisticated deterministic models. We also highlight several existing issues, including some inherent to a regression-based approach as exemplified by a case study for Beijing, Further studies will be necessa1Y before satellite data can see more extensive applications in the operational air quality monitoring and forecasting.

Influenza forecasting with Google Flu Trends.

PubMed

Dugas, Andrea Freyer; Jalalpour, Mehdi; Gel, Yulia; Levin, Scott; Torcaso, Fred; Igusa, Takeru; Rothman, Richard E

2013-01-01

We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy. Forecast models designed to predict one week in advance were developed from weekly counts of confirmed influenza cases over seven seasons (2004-2011) divided into seven training and out-of-sample verification sets. Forecasting procedures using classical Box-Jenkins, generalized linear models (GLM), and generalized linear autoregressive moving average (GARMA) methods were employed to develop the final model and assess the relative contribution of external variables such as, Google Flu Trends, meteorological data, and temporal information. A GARMA(3,0) forecast model with Negative Binomial distribution integrating Google Flu Trends information provided the most accurate influenza case predictions. The model, on the average, predicts weekly influenza cases during 7 out-of-sample outbreaks within 7 cases for 83% of estimates. Google Flu Trend data was the only source of external information to provide statistically significant forecast improvements over the base model in four of the seven out-of-sample verification sets. Overall, the p-value of adding this external information to the model is 0.0005. The other exogenous variables did not yield a statistically significant improvement in any of the verification sets. Integer-valued autoregression of influenza cases provides a strong base forecast model, which is enhanced by the addition of Google Flu Trends confirming the predictive capabilities of search query based syndromic surveillance. This accessible and flexible forecast model can be used by individual medical centers to provide advanced warning of future influenza cases.

BOREAS TF-3 NSA-OBS Tower Flux, Meteorological, and Soil Temperature Data

NASA Technical Reports Server (NTRS)

Wofsy, Steven; Sutton, Doug; Goulden, Mike; Hall, Forrest G. (Editor); Huemmrich, Karl (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study Tower Flux (BOREAS TF-3) team collected tower flux, surface meteorological, and soil temperature data at the BOREAS Northern Study Area-Old Black Spruce (NSA-OBS) site continuously from the March 1994 through October 1996. The data are available in tabular ASCII files.

Application of the Bulgarian emergency response system in case of nuclear accident in environmental assessment study

NASA Astrophysics Data System (ADS)

Syrakov, Dimiter; Veleva, Blagorodka; Georgievs, Emilia; Prodanova, Maria; Slavov, Kiril; Kolarova, Maria

2014-05-01

The development of the Bulgarian Emergency Response System (BERS) for short term forecast in case of accidental radioactive releases to the atmosphere has been started in the mid 1990's [1]. BERS comprises of two main parts - operational and accidental, for two regions 'Europe' and 'Northern Hemisphere'. The operational part runs automatically since 2001 using the 72 hours meteorological forecast from DWD Global model, resolution in space of 1.5o and in time - 12 hours. For specified Nuclear power plants (NPPs), 3 days trajectories are calculated and presented on NIMH's specialized Web-site (http://info.meteo.bg/ews/). The accidental part is applied when radioactive releases are reported or in case of emergency exercises. BERS is based on numerical weather forecast information and long-range dispersion model accounting for the transport, dispersion, and radioactive transformations of pollutants. The core of the accidental part of the system is the Eulerian 3D dispersion model EMAP calculating concentration and deposition fields [2]. The system is upgraded with a 'dose calculation module' for estimation of the prognostic dose fields of 31 important radioactive gaseous and aerosol pollutants. The prognostic doses significant for the early stage of a nuclear accident are calculated as follows: the effective doses from external irradiation (air submersion + ground shinning); effective dose from inhalation; summarized effective dose and absorbed thyroid dose [3]. The output is given as 12, 24, 36, 48, 60 and 72 hours prognostic dose fields according the updated meteorology. The BERS was upgraded to simulate the dispersion of nuclear materials from Fukushima NPP [4], and results were presented in NIMH web-site. In addition BERS took part in the respective ENSEMBLE exercises to model 131I and 137Cs in Fukushima source term. In case of governmental request for expertise BERS was applied for environmental impact assessment of hypothetical accidental transboundary radioactive pollution. The consequences were estimated based on the worst emission scenario for the existing basic reactor type, selection of real meteorological forecast conditions, favoring the direct transport of the contaminated air masses to the territory of the country in consideration. In the present work BERS is used to estimate the worst case accidental scenario impact from a possible new unit of Paks Nuclear Power Plant, Hungary over the territory of Bulgaria. 1. D.Syrakov, M.Prodanova, 1998, Atmospheric Environment, 32 (24), 4367-4375. 2. D. Syrakov, M. Prodanova, K. Slavov, Inernationsal J. Environment and Pollution, 20, 1-6 (2003) 286-296. 3. D. Syrakov, B. Veleva, M. Prodanova, T. Popova, M. Kolarova, Journal of Environmental Radioactivity 100 (2009) 151-156. 4. D.Syrakov, M Prodanova, J. Intern. Sci. Publ.: Ecology & Safety Vol. 6 Part 1 (2011) 94-102. www.scientific-publications.net.

Task 1, Design Analysis Report: Pulsed plasma solid propellant microthruster for the synchronous meteorological satellite

NASA Technical Reports Server (NTRS)

Guman, W. J. (Editor)

1971-01-01

Thermal vacuum design supporting thruster tests indicate no problems under the worst case conditions of sink temperature and spin rate. The reliability of the system was calculated to be 0.92 for a five-year mission. Minus the main energy storage capacitor it is 0.98.

Variability of winds and temperature in the Bergen area

NASA Astrophysics Data System (ADS)

Schönbein, Daniel; Ólafsson, Haraldur; Asle Olseth, Jan; Furevik, Birgitte

2017-04-01

In recent years, observations have been made by a dense network of automatic weather stations in the Bergen area in W-Norway (Bergen School of Meteorology). Here, cases are presented that feature large spatial variability in winds and temperature and the ability of a numerical model to reproduce this variability is assessed.

High-resolution satellite imagery for mesoscale meteorological studies

NASA Technical Reports Server (NTRS)

Johnson, David B.; Flament, Pierre; Bernstein, Robert L.

1994-01-01

In this article high-resolution satellite imagery from a variety of meteorological and environmental satellites is compared. Digital datasets from Geostationary Operational Environmental Satellite (GOES), National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program (DMSP), Landsat, and Satellite Pour l'Observation de la Terre (SPOT) satellites were archived as part of the 1990 Hawaiian Rainband Project (HaRP) and form the basis of the comparisons. During HaRP, GOES geostationary satellite coverage was marginal, so the main emphasis is on the polar-orbiting satellites.

Kinematic and Hydrometer Data Products from Scanning Radars during MC3E

DOE Data Explorer

matthews, Alyssa; Dolan, Brenda; Rutledge, Steven

2016-02-29

Recently the Radar Meteorology Group at Colorado State University has completed major case studies of some top cases from MC3E including 25 April, 20 May and 23 May 2011. A discussion on the analysis methods as well as radar quality control methods is included. For each case, a brief overview is first provided. Then, multiple Doppler (using available X-SAPR and C-SAPR data) analyses are presented including statistics on vertical air motions, sub-divided by convective and stratiform precipitation. Mean profiles and CFAD's of vertical motion are included to facilitate comparison with ASR model simulations. Retrieved vertical motion has also been verified with vertically pointing profiler data. Finally for each case, hydrometeor types are included derived from polarimetric radar observations. The latter can be used to provide comparisons to model-generated hydrometeor fields. Instructions for accessing all the data fields are also included. The web page can be found at: http://radarmet.atmos.colostate.edu/mc3e/research/

M-TraCE: a new tool for high-resolution computation and statistical elaboration of backward trajectories on the Italian domain

NASA Astrophysics Data System (ADS)

Vitali, Lina; Righini, Gaia; Piersanti, Antonio; Cremona, Giuseppe; Pace, Giandomenico; Ciancarella, Luisella

2017-12-01

Air backward trajectory calculations are commonly used in a variety of atmospheric analyses, in particular for source attribution evaluation. The accuracy of backward trajectory analysis is mainly determined by the quality and the spatial and temporal resolution of the underlying meteorological data set, especially in the cases of complex terrain. This work describes a new tool for the calculation and the statistical elaboration of backward trajectories. To take advantage of the high-resolution meteorological database of the Italian national air quality model MINNI, a dedicated set of procedures was implemented under the name of M-TraCE (MINNI module for Trajectories Calculation and statistical Elaboration) to calculate and process the backward trajectories of air masses reaching a site of interest. Some outcomes from the application of the developed methodology to the Italian Network of Special Purpose Monitoring Stations are shown to assess its strengths for the meteorological characterization of air quality monitoring stations. M-TraCE has demonstrated its capabilities to provide a detailed statistical assessment of transport patterns and region of influence of the site under investigation, which is fundamental for correctly interpreting pollutants measurements and ascertaining the official classification of the monitoring site based on meta-data information. Moreover, M-TraCE has shown its usefulness in supporting other assessments, i.e., spatial representativeness of a monitoring site, focussing specifically on the analysis of the effects due to meteorological variables.

Effective Utilization of Satellite Observations for Assessing Transnational Impact of Disasters

NASA Astrophysics Data System (ADS)

Alozie, J. E.; Anuforom, A. C.

2014-12-01

General meteorological observations sources for the surface, upper air and outer space are conducted using different technological equipment and instruments that meet international standards prescribed and approved by the United Nations organizations such as the International Civil Aviation Organization (ICAO) and the World Meteorological Organization (WMO). Satellite weather observations are critical for effective monitoring of the developments, propagations and disseminations of cold clouds and their expected adverse weather conditions as they move across national and transnational boundaries. The Nigerian Meteorological Agency (NiMet) which is the national weather service provider for Nigeria, utilizes an array of satellite products obtained from mainly the European Meteorological Satellite (EUMETSAT) for its routine weather and climate monitoring and forecasts. Overtime, NiMet has used weather workstations such as MSG, SYNERGIE and now PUMA for accessing satellite products such as RGB, Infra-red, Water vapour and the Multi-sensor Precipitation Estimate (MPE) obtained at near real-time periods. The satellite imageries find extensive applications in the delivery of early warning of raising of severe weather conditions such as dust storm and dust haze during the harmattan season (November - February); and thunderstorm accompanied by severe lightning and destructive strong winds. The paper will showcase some special cases of the tracking of squall lines and issuance of weather alerts through the media. The good result is that there was limited damage to infrastructure and no loss of life from the flash floods caused by the heavy rainfall from the squally thunderstorm.

Assessing relationships between cattle egret migration and meteorology in the southwest Pacific: a review

NASA Astrophysics Data System (ADS)

Bridgman, H. A.; Maddock, M.; Geering, D. J.

The evolution of research into meteorological factors affecting the migration of the Cattle Egret (Ardeola ibis coromandus) in the southwestern Pacific region (Australia, New Zealand and the Tasman Sea) - from ground-based studies dependent on volunteer observers to a pilot satellite-tracking project - is reviewed and the results are related to the literature on bird migration. The predominant pattern is a seasonal migration from breeding colonies in southeast Queensland and northern New South Wales which takes place in stages along the east coastal plain under favourable meteorological conditions. Migration outward (southward) occurs in February through April and return to the breeding colonies occurs in October and November. Wintering destinations include Tasmania, southern Victoria and parts of New Zealand. Favourable meteorological conditions for migration southward include:moderate north to northwest airflow behind a high; light and variable winds in a high or col; and light and variable winds over New South Wales with moderate westerlies over Victoria and Tasmania. A satellite-tracking project helped to validate findings from the ground-based studies, provided additional information not otherwise obtainable, and demonstrated the potential of the technique to further clarify the relation between timing and staging of migration, and meteorology.

Meteorological factors and timing of the initiating event of human parturition

NASA Astrophysics Data System (ADS)

Hirsch, Emmet; Lim, Courtney; Dobrez, Deborah; Adams, Marci G.; Noble, William

2011-03-01

The aim of this study was to determine whether meteorological factors are associated with the timing of either onset of labor with intact membranes or rupture of membranes prior to labor—together referred to as `the initiating event' of parturition. All patients delivering at Evanston Hospital after spontaneous labor or rupture of membranes at ≥20 weeks of gestation over a 6-month period were studied. Logistic regression models of the initiating event of parturition using clinical variables (maternal age, gestational age, parity, multiple gestation and intrauterine infection) with and without the addition of meteorological variables (barometric pressure, temperature and humidity) were compared. A total of 1,088 patients met the inclusion criteria. Gestational age, multiple gestation and chorioamnionitis were associated with timing of initiation of parturition ( P < 0.01). The addition of meteorological to clinical variables generated a statistically significant improvement in prediction of the initiating event; however, the magnitude of this improvement was small (less than 2% difference in receiver-operating characteristic score). These observations held regardless of parity, fetal number and gestational age. Meteorological factors are associated with the timing of parturition, but the magnitude of this association is small.

Assessing the impacts of seasonal and vertical atmospheric conditions on air quality over the Pearl River Delta region

NASA Astrophysics Data System (ADS)

Tong, Cheuk Hei Marcus; Yim, Steve Hung Lam; Rothenberg, Daniel; Wang, Chien; Lin, Chuan-Yao; Chen, Yongqin David; Lau, Ngar Cheung

2018-05-01

Air pollution is an increasingly concerning problem in many metropolitan areas due to its adverse public health and environmental impacts. Vertical atmospheric conditions have strong effects on vertical mixing of air pollutants, which directly affects surface air quality. The characteristics and magnitude of how vertical atmospheric conditions affect surface air quality, which are critical to future air quality projections, have not yet been fully understood. This study aims to enhance understanding of the annual and seasonal sensitivities of air pollution to both surface and vertical atmospheric conditions. Based on both surface and vertical meteorological characteristics provided by 1994-2003 monthly dynamic downscaling data from the Weather and Research Forecast Model, we develop generalized linear models (GLMs) to study the relationships between surface air pollutants (ozone, respirable suspended particulates, and sulfur dioxide) and atmospheric conditions in the Pearl River Delta (PRD) region. Applying Principal Component Regression (PCR) to address multi-collinearity, we study the contributions of various meteorological variables to pollutants' concentration levels based on the loading and model coefficient of major principal components. Our results show that relatively high pollutant concentration occurs under relatively low mid-level troposphere temperature gradients, low relative humidity, weak southerly wind (or strong northerly wind) and weak westerly wind (or strong easterly wind). Moreover, the correlations vary among pollutant species, seasons, and meteorological variables at various altitudes. In general, pollutant sensitivity to meteorological variables is found to be greater in winter than in other seasons, and the sensitivity of ozone to meteorology differs from that of the other two pollutants. Applying our GLMs to anomalous air pollution episodes, we find that meteorological variables up to mid troposphere (∼700 mb) play an important role in influencing surface air quality, pinpointing the significant and unique associations between meteorological variables at higher altitudes and surface air quality.

The Relationships between PM2.5 and Meteorological Factors in China: Seasonal and Regional Variations

PubMed Central

Yang, Qianqian; Li, Tongwen; Shen, Huanfeng; Zhang, Liangpei

2017-01-01

The interactions between PM2.5 and meteorological factors play a crucial role in air pollution analysis. However, previous studies that have researched the relationships between PM2.5 concentration and meteorological conditions have been mainly confined to a certain city or district, and the correlation over the whole of China remains unclear. Whether spatial and seasonal variations exist deserves further research. In this study, the relationships between PM2.5 concentration and meteorological factors were investigated in 68 major cities in China for a continuous period of 22 months from February 2013 to November 2014, at season, year, city, and regional scales, and the spatial and seasonal variations were analyzed. The meteorological factors were relative humidity (RH), temperature (TEM), wind speed (WS), and surface pressure (PS). We found that spatial and seasonal variations of their relationships with PM2.5 exist. Spatially, RH is positively correlated with PM2.5 concentration in north China and Urumqi, but the relationship turns to negative in other areas of China. WS is negatively correlated with PM2.5 everywhere except for Hainan Island. PS has a strong positive relationship with PM2.5 concentration in northeast China and mid-south China, and in other areas the correlation is weak. Seasonally, the positive correlation between PM2.5 concentration and RH is stronger in winter and spring. TEM has a negative relationship with PM2.5 in autumn and the opposite in winter. PS is more positively correlated with PM2.5 in autumn than in other seasons. Our study investigated the relationships between PM2.5 and meteorological factors in terms of spatial and seasonal variations, and the conclusions about the relationships between PM2.5 and meteorological factors are more comprehensive and precise than before. We suggest that the variations could be considered in PM2.5 concentration prediction and haze control to improve the prediction accuracy and policy efficiency. PMID:29206181

Effects of climate change on aerosol concentrations in Europe

NASA Astrophysics Data System (ADS)

Megaritis, Athanasios G.; Fountoukis, Christos; Pandis, Spyros N.

2013-04-01

High concentrations of particulate matter less than 2.5 μm in size (PM2.5), ozone and other major constituents of air pollution, have adverse effects on human health, visibility and ecosystems (Seinfeld and Pandis, 2006), and are strongly influenced by meteorology. Emissions control policy is currently made assuming that climate will remain constant in the future. However, climate change over the next decades is expected to be significant (IPCC, 2007) and may impact local and regional air quality. Determining the sensitivity of the concentrations of air pollutants to climate change is an important step toward estimating future air quality. In this study we applied PMCAMx (Fountoukis et al., 2011), a three dimensional chemical transport model, over Europe, in order to quantify the individual effects of various meteorological parameters on fine particulate matter (PM2.5) concentrations. A suite of perturbations in various meteorological factors, such as temperature, wind speed, absolute humidity and precipitation were imposed separately on base case conditions to determine the sensitivities of PM2.5 concentrations and composition to these parameters. Different simulation periods (summer, autumn 2008 and winter 2009) are used to examine also the seasonal dependence of the air quality - climate interactions. The results of these sensitivity simulations suggest that there is an important link between changes in meteorology and PM2.5 levels. We quantify through separate sensitivity simulations the processes which are mainly responsible for the final predicted changes in PM2.5 concentration and composition. The predicted PM2.5 response to those meteorology perturbations was found to be quite variable in space and time. These results suggest that, the changes in concentrations caused by changes in climate should be taken into account in long-term air quality planning. References Fountoukis C., Racherla P. N., Denier van der Gon H. A. C., Polymeneas P., Charalampidis P. E., Pilinis C., Wiedensohler A., Dall'Osto M., O'Dowd C., and S. N. Pandis: Evaluation of a three-dimensional chemical transport model (PMCAMx) in the European domain during the EUCAARI May 2008 campaign, Atmos. Chem. Phys., 11, 10331-10347, 2011. Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report: Summary for Policymakers, 2007. Seinfeld, J. H., and Pandis, S. N.: Atmospheric chemistry and physics: From air pollution to climate change, 2nd ed.; John Wiley and Sons, Hoboken, NJ, 2006.

Meteorological operational services for civil protection in Veneto region (North-eastern Italy).

NASA Astrophysics Data System (ADS)

Barbi, A.; Monai, M.; Zardini, F.

2009-09-01

The Meteorological Centre of Teolo (CMT), part of the Regional Agency for Environmental Prevention and Protection of the North-eastern Italian region Veneto (ARPAV), is the operational regional meteorological service. Since April 2009 the Centre is linked to and supplies meteorological monitoring and forecasting to the recently constituted Functional Centre of the regional civil protection (CFD Veneto), which operates in the framework of National Civil Protection. The CFD Veneto supplies a multi-disciplinary, technical-scientific support to civil protection activities, to early warnings of natural hazards, in particular related to hydrogeological, hydraulic, and avalanches risks. The north-eastern part of Italy is known to be one of the rainiest regions in Europe. The region Veneto, due to its topographic configuration which includes Alpine reliefs, plans and a coast exposed to the Adriatic Sea, is conducive to heavy and long-lasting precipitation events. Also, strong thunderstorm activity with high precipitation rates, hail, wind gusts, and even tornadoes are relatively frequent occurrences. In this contribution two recent examples of different types of extreme events are briefly analysed by means of the ARPAV multi-sensor observing system which includes weather radar and a dense surface network. We show some of the impacts of such weather events on the territory, the services provided by CFD Veneto, in terms of meteorological forecasting and nowcasting products, and hydrogeologic/hydraulic hazard bullettins. The analysis highlights the difficulty of an efficient wheather forecast for civil defence purposes in a complex situation as ours, where many types of different events are possible. Especially cases of rapid convective events with their intense and very localized phenomena are a significant challenge. It is well-known that such events can bring remarkable material damages and serious danger for the people. For this reason an effective warning system which can handle this type of events is needed, and may feature different procedures and warning methods than for long-lasting precipitation events. The latter are generally more predictable by meteorological models, have slow and more continuous time-spatial evolutions with delayed hydrogeologic and hydraulic impacts (landslides, landslips, floods, etc.). This allows anticipated more efficient warnings, also supported, to some extent, by hydrologic modelling.

Availability of selected meteorological data in computer-based files of the U.S. Geological Survey, Montana, North Dakota, South Dakota, and Wyoming

USGS Publications Warehouse

Link, Brenda L.; Cary, L.E.

1986-01-01

Meteorological data were located, acquired, and stored from selected stations in Montana and North Dakota coal regions and adjacent areas including South Dakota and Wyoming. Data that were acquired have potential use in small watershed modeling studies. Emphasis was placed on acquiring data that was collected during the period 1970 to the present (1984). A map shows the location and type of stations selected. A narration summarizing conventions used in acquiring and storing the meteorological data is provided along with the various retrieval options available. Individual station descriptions are followed by tables listing the meteorological variables collected, period of obtained record, percentage of data recovery, and the instruments used and their description. (USGS)

The POLIMI forecasting chain for real time flood and drought predictions

NASA Astrophysics Data System (ADS)

Ceppi, Alessandro; Ravazzani, Giovanni; Corbari, Chiara; Mancini, Marco

2016-04-01

Nowadays coupling meteorological and hydrological models is recognized by scientific community as a necessary way to forecast extreme hydrological phenomena, in order to activate useful mitigation measurements and alert systems in advance. The development and implementation of a real-time forecasting chain with a hydro-meteorological operational alert procedure for flood and drought events is presented in this study. Different weather models are used to build the POLIMI operative chain: the probabilistic COSMO-LEPS model with 16 ensembles developed by ARPA-Emilia Romagna, the deterministic Bolam and Moloch models, developed by the Italian ISAC-CNR, and nine further simulations obtained by different runs of the WRF-ARW (3), WRF-NMM (2), ETA2012 (1) and the GFS (3), provided by the private Epson Meteo Center and Terraria companies. All the meteorological runs are then implemented with the rainfall-runoff physically-based distributed FEST-WB model, developed at Politecnico di Milano to obtain a multi-model approach system with hydrological ensemble forecasts in different areas of study over the Italian country. As far as concerning drought predictions, three test-beds are monitored: two in maize fields, one in the Puglia region (South of Italy), and another in the Po Valley area, (northern Italy), and one in a golf course in Milan city. The hydrological model was here calibrated and validated against measurements of latent heat flux and soil moisture acquired by an eddy-covariance station, TDR probes and remote sensing images. Regarding flood forecasts, two test-sites are chosen: the first one is the urban area northern Milan where three catchments (the Seveso, Olona, and Lambro River basins) are used to show how early warning systems are an effective complement to structural measures for flood control in Milan city which flooded frequently in the last 25 years, while the second test-site is the Idro Lake, located between the Lombardy and Trentino region where the POLIMI hydro-meteorological chain is performed to forecast the hydrometric lake level for a better management of the upstream and downstream basin. The same hydrological model has been here calibrated and validated with observed data coming from local bodies: ARPA Lombardy, Meteonetwork and Meteo Trentino. Reliability of the forecasting system and its benefits are assessed with skill scores on some cases-study occurred in the recent years and through the real-time visualization of the implemented dashboards.

Freezing Rain as an In-Flight Icing Hazard

NASA Technical Reports Server (NTRS)

Bernstein, Ben C.; Ratvasky, Thomas P.; Miller, Dean R.; McDonough, Frank

2000-01-01

Exposure to supercooled large drops (SLD-subfreezing water droplets with diameters greater than approx. 50 microns) can pose a significant threat to the safety of some aircraft. Although SLD includes both freezing drizzle (FZDZ) and freezing rain (FZRA), much of the SLD research and development of operational SLD forecast tools has focused on FZDZ and ignored FZRA, regarding is as less of a hazard to aviation. This paper provides a counterpoint case study that demonstrates FZRA as a significant in-flight icing hazard. The case study is based on flight and meteorological data from a joint NASA/FAA/NCAR SLD icing research project collected on February 4, 1998. The NASA Twin Otter Icing Research Aircraft experienced a prolonged exposure to "classical" FZRA that formed extensive ice formations including ridges and nodules on the wing and tail, and resulted in a substantial performance penalty. Although the case study provides only a singular FZRA event with one aircraft type, it is clear that classical FZRA can pose a significant in-flight icing hazard, and should not be ignored when considering SLD issues.

Windshear certification data base for forward-look detection systems

NASA Technical Reports Server (NTRS)

Switzer, George F.; Hinton, David A.; Proctor, Fred H.

1994-01-01

Described is an introduction to a comprehensive database that is to be used for certification testing of airborne forward-look windshear detection systems. The database was developed by NASA Langley Research Center, at the request of the Federal Aviation Administration (FAA), to support the industry initiative to certify and produce forward-looking windshear detection equipment. The database contains high-resolution three-dimensional fields for meteorological variables that may be sensed by forward-looking systems. The database is made up of seven case studies that are generated by the Terminal Area Simulation System, a state-of-the-art numerical system for the realistic modeling of windshear phenomena. The selected cases contained in the certification documentation represent a wide spectrum of windshear events. The database will be used with vendor-developed sensor simulation software and vendor-collected ground-clutter data to demonstrate detection performance in a variety of meteorological conditions using NASA/FAA pre-defined path scenarios for each of the certification cases. A brief outline of the contents and sample plots from the database documentation are included. These plots show fields of hazard factor, or F-factor (Bowles 1990), radar reflectivity, and velocity vectors on a horizontal plane overlayed with the applicable certification paths. For the plot of the F-factor field the region of 0.105 and above signify an area of hazardous, performance decreasing windshear, while negative values indicate regions of performance increasing windshear. The values of F-factor are based on 1-Km averaged segments along horizontal flight paths, assuming an air speed of 150 knots (approx. 75 m/s). The database has been released to vendors participating in the certification process. The database and associated document have been transferred to the FAA for archival storage and distribution.

An analytical analysis of the dispersion predictions for effluents from the Saturn 5 and Scout-Algol 3 rocket exhausts

NASA Technical Reports Server (NTRS)

Stephens, J. B.; Susko, M.; Kaufman, J. W.; Hill, C. K.

1973-01-01

Predictions of the spatial concentration mapping of the potentially toxic constituents of the exhaust effluents from a launch of a Saturn 5 and of a Scout-Algol 3 vehicle utilizing the NASA/MSFC Multilayer Diffusion Program are provided. In the case of the Saturn 5, special attention was given to the concentration fields of carbon monoxide with a correlation of carbon dioxide concentrations. The Scout-Algol 3 provided an example of the centerline concentrations of hydrogen chloride, carbon monoxide, and alumina under typical meteorological conditions. While these results define the specific environmental impact of these two launches under the meteorological conditions existing during launches, they also provide a basis for the empirical monitoring of the constituents of the exhaust effluents of these vehicles.

Users' instructions for the NASA/MSFC cloud-rise preprocessor program, version 6, and the NASA/MSFC multilayer diffusion program, version 6: Research version for Univac 1108 system

NASA Technical Reports Server (NTRS)

Bjorklund, J. R.

1978-01-01

The cloud-rise preprocessor and multilayer diffusion computer programs were used by NASA in predicting concentrations and dosages downwind from normal and abnormal launches of rocket vehicles. These programs incorporated: (1) the latest data for the heat content and chemistry of rocket exhaust clouds; (2) provision for the automated calculation of surface water pH due to deposition of HCl from precipitation scavenging; (3) provision for automated calculation of concentration and dosage parameters at any level within the vertical grounds for which meteorological inputs have been specified; and (4) provision for execution of multiple cases of meteorological data. Procedures used to automatically calculate wind direction shear in a layer were updated.

Exploring the link between meteorological drought and streamflow to inform water resource management

NASA Astrophysics Data System (ADS)

Lennard, Amy; Macdonald, Neil; Hooke, Janet

2015-04-01

Drought indicators are an under-used metric in UK drought management. Standardised drought indicators offer a potential monitoring and management tool for operational water resource management. However, the use of these metrics needs further investigation. This work uses statistical analysis of the climatological drought signal based on meteorological drought indicators and observed streamflow data to explore the link between meteorological drought and hydrological drought to inform water resource management for a single water resource region. The region, covering 21,000 km2 of the English Midlands and central Wales, includes a variety of landscapes and climatological conditions. Analysis of the links between meteorological drought and hydrological drought performed using streamflow data from 'natural' catchments indicates a close positive relationship between meteorological drought indicators and streamflow, enhancing confidence in the application of drought indicators for monitoring and management. However, many of the catchments in the region are subject to modification through impoundments, abstractions and discharge. Therefore, it is beneficial to explore how climatological drought signal propagates into managed hydrological systems. Using a longitudinal study of catchments and sub-catchments that include natural and modified river reaches the relationship between meteorological and hydrological drought is explored. Initial statistical analysis of meteorological drought indicators and streamflow data from modified catchments shows a significantly weakened statistical relationship and reveals how anthropogenic activities may alter hydrological drought characteristics in modified catchments. Exploring how meteorological drought indicators link to streamflow across the water supply region helps build an understanding of their utility for operational water resource management.

Analysis of source regions and meteorological factors for the variability of spring PM10 concentrations in Seoul, Korea

NASA Astrophysics Data System (ADS)

Lee, Jangho; Kim, Kwang-Yul

2018-02-01

CSEOF analysis is applied for the springtime (March, April, May) daily PM10 concentrations measured at 23 Ministry of Environment stations in Seoul, Korea for the period of 2003-2012. Six meteorological variables at 12 pressure levels are also acquired from the ERA Interim reanalysis datasets. CSEOF analysis is conducted for each meteorological variable over East Asia. Regression analysis is conducted in CSEOF space between the PM10 concentrations and individual meteorological variables to identify associated atmospheric conditions for each CSEOF mode. By adding the regressed loading vectors with the mean meteorological fields, the daily atmospheric conditions are obtained for the first five CSEOF modes. Then, HYSPLIT model is run with the atmospheric conditions for each CSEOF mode in order to back trace the air parcels and dust reaching Seoul. The K-means clustering algorithm is applied to identify major source regions for each CSEOF mode of the PM10 concentrations in Seoul. Three main source regions identified based on the mean fields are: (1) northern Taklamakan Desert (NTD), (2) Gobi Desert and (GD), and (3) East China industrial area (ECI). The main source regions for the mean meteorological fields are consistent with those of previous study; 41% of the source locations are located in GD followed by ECI (37%) and NTD (21%). Back trajectory calculations based on CSEOF analysis of meteorological variables identify distinct source characteristics associated with each CSEOF mode and greatly facilitate the interpretation of the PM10 variability in Seoul in terms of transportation route and meteorological conditions including the source area.

The Study of the Atmosphere in the Science Curriculum.

ERIC Educational Resources Information Center

Fisher, Brian

1998-01-01

Seeks to justify the inclusion of meteorology within the science curriculum. Reflects upon the nature of science and some current issues in science education, and examines the reality of including meteorology within worldwide science curricula. Contains 37 references. (Author/DDR)

Small-scale field-aligned currents caused by tropical cyclones as observed by the SWARM satellites above the ionosphere

NASA Astrophysics Data System (ADS)

Aoyama, T.; Iyemori, T.; Nakanishi, K.

2014-12-01

We present case studies of small-scale magnetic fluctuations above typhoons, hurricanes and cyclones as observed by the swarm constellation. It is reported lately that AGWs(atmospheric gravity waves) generated by meteorological phenomena in the troposphere such as typhoons and tornadoes, large earthquakes and volcanic eruptions propagate to the mesosphere and thermosphere. We observe them in various forms(e.g. airglows, ionospheric disturbances and TEC variations). We are proposing the following model. AGWs caused by atmospheric disturbances in the troposphere propagate to the ionospheric E-layer, drive dynamo action and generate field-aligned currents. The satellites observe magnetic fluctuations above the ionosphere. In this presentation, we focus on cases of tropical cyclone(hurricanes in North America, typhoons in North-West Pacific).

A Meteorological Model's Dependence on Radiation Update Frequency

NASA Technical Reports Server (NTRS)

Eastman, Joseph L.; Peters-Lidard, Christa; Tao, Wei-Kuo; Kumar, Sujay; Tian, Yudong; Lang, Stephen E.; Zeng, Xiping

2004-01-01

Numerical weather models are used to simulate circulations in the atmosphere including clouds and precipitation by applying a set of mathematical equations over a three-dimensional grid. The grid is composed of discrete points at which the meteorological variables are defined. As computing power continues to rise these models are being used at finer grid spacing, but they must still cover a wide range of scales. Some of the physics that must be accounted for in the model cannot be explicitly resolved, and their effects, therefore, must be estimated or "parameterized". Some of these parameterizations are computationally expensive. To alleviate the problem, they are not always updated at the time resolution of the model with the assumption being that the impact will be small. In this study, a coupled land-atmosphere model is used to assess the impact of less frequent updates of the computationally expensive radiation physics for a case on June 6, 2002, that occurred during a field experiment over the central plains known as International H20 Project (IHOP). The model was tested using both the original conditions, which were dry, and with modified conditions wherein moisture was added to the lower part of the atmosphere to produce clouds and precipitation (i.e., a wet case). For each of the conditions (i.e., dry and wet), four set of experiments were conducted wherein the model was run for a period of 24 hours and the radiation fields (including both incoming solar and outgoing longwave) were updated every 1, 3, 10, and 100 time steps. Statistical tests indicated that average quantities of surface variables for both the dry and wet cases were the same for the various update frequencies. However, spatially the results could be quite different especially in the wet case after it began to rain. The near-surface wind field was found to be different most of the time even for the dry case. In the wet case, rain intensities and average vertical profiles of heating associated with cloudy areas were found to differ for the various radiation update frequencies. The latter implies that the mean state of the model could be different as a result of not updating the radiation fields every time step and has important implications for longer term climate studies

Dune mobility in the St. Anthony Dune Field, Idaho, USA: Effects of meteorological variables and lag time

NASA Astrophysics Data System (ADS)

Hoover, R. H.; Gaylord, D. R.; Cooper, C. M.

2018-05-01

The St. Anthony Dune Field (SADF) is a 300 km2 expanse of active to stabilized transverse, barchan, barchanoid, and parabolic sand dunes located in a semi-arid climate in southeastern Idaho. The northeastern portion of the SADF, 16 km2, was investigated to examine meteorological influences on dune mobility. Understanding meteorological predictors of sand-dune migration for the SADF informs landscape evolution and impacts assessment of eolian activity on sensitive agricultural lands in the western United States, with implications for semi-arid environments globally. Archival aerial photos from 1954 to 2011 were used to calculate dune migration rates which were subsequently compared to regional meteorological data, including temperature, precipitation and wind speed. Observational analyses based on aerial photo imagery and meteorological data indicate that dune migration is influenced by weather for up to 5-10 years and therefore decadal weather patterns should be taken into account when using dune migration rates as proxies from climate fluctuation. Statistical examination of meteorological variables in this study indicates that 24% of the variation of sand dune migration rates is attributed to temperature, precipitation and wind speed, which is increased to 45% when incorporating lag time.

Experimenting with sodar in support of emergency preparedness at Three Mile Island-1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heck, W.J.

1989-01-01

In November 1988 at Three Mile Island Unit 1 (TMI-1), GPU Nuclear successfully completed the annual drill-for-grade that, from a modeling point of view, broke new ground for this plant. The meteorological and modeling aspects of the drill scenario were unprecedented for two reasons. First, the plume was buoyant and rose far above the height of the meteorological tower located at TMI. Second, the wind direction data from the meteorological tower were not representative of the wind direction at plume height. In the drill scenario, the buoyant plume resulted from a steam generator tube rupture where the steam ejects directlymore » into the atmosphere via safety relief valves. Plume modeling indicated that the plume would rise to 400 ft, given the scenario meteorology. Wind data from the on-site meteorological tower, however, was only available up to 150 ft. Comparisons of sodar and tower winds were made for various weather conditions. Sodar results were studied in detail during light, moderate, and high winds; various wind directions; occurrences of rain and snow; and by time of day to determine effects of diurnal meteorological conditions on sodar performance.« less

Future directions of meteorology related to air-quality research.

PubMed

Seaman, Nelson L

2003-06-01

Meteorology is one of the major factors contributing to air-pollution episodes. More accurate representation of meteorological fields has been possible in recent years through the use of remote sensing systems, high-speed computers and fine-mesh meteorological models. Over the next 5-20 years, better meteorological inputs for air quality studies will depend on making better use of a wealth of new remotely sensed observations in more advanced data assimilation systems. However, for fine mesh models to be successful, parameterizations used to represent physical processes must be redesigned to be more precise and better adapted for the scales at which they will be applied. Candidates for significant overhaul include schemes to represent turbulence, deep convection, shallow clouds, and land-surface processes. Improvements in the meteorological observing systems, data assimilation and modeling, coupled with advancements in air-chemistry modeling, will soon lead to operational forecasting of air quality in the US. Predictive capabilities can be expected to grow rapidly over the next decade. This will open the way for a number of valuable new services and strategies, including better warnings of unhealthy atmospheric conditions, event-dependent emissions restrictions, and now casting support for homeland security in the event of toxic releases into the atmosphere.

Wind Field Extractions from SAR Sentinel-1 Images Using Electromagnetic Models

NASA Astrophysics Data System (ADS)

La, Tran Vu; Khenchaf, Ali; Comblet, Fabrice; Nahum, Carole

2016-08-01

Among available wind sources, i.e. measured data, numeric weather models, the retrieval of wind vectors from Synthetic Aperture Radar (SAR) data / images is particularly preferred due to a lot of SAR systems (available data in most meteorological conditions, revisit mode, high resolution, etc.). For this purpose, the retrieval of wind vectors is principally based on the empirical (EP) models, e.g. CMOD series in C-band. Little studies have been reported about the use of the electromagnetic (EM) models for wind vector retrieval, since it is quite complicated to invert. However, the EM models can be applied for most cases of polarization, frequency and wind regime. In order to evaluate the advantages and limits of the EM models for wind vector retrieval, we compare in this study estimated results by the EM and EP models for both cases of polarization (vertical-vertical, or VV-pol and horizontal- horizontal, or HH-pol).

2. SOUTH FACE OF METEOROLOGICAL SHED (BLDG. 756) WITH METEOROLOGICAL ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. SOUTH FACE OF METEOROLOGICAL SHED (BLDG. 756) WITH METEOROLOGICAL DATA ACQUISITION TERMINAL (MDAT) INSIDE BUILDING - Vandenberg Air Force Base, Space Launch Complex 3, Meteorological Shed & Tower, Napa & Alden Roads, Lompoc, Santa Barbara County, CA

Model studies on the role of moist convection as a mechanism for interaction between the mesoscales

NASA Technical Reports Server (NTRS)

Waight, Kenneth T., III; Song, J. Aaron; Zack, John W.; Price, Pamela E.

1991-01-01

A three year research effort is described which had as its goal the development of techniques to improve the numerical prediction of cumulus convection on the meso-beta and meso-gamma scales. Two MESO models are used, the MASS (mesoscale) and TASS (cloud scale) models. The primary meteorological situation studied is the 28-29 Jun. 1986 Cooperative Huntsville Meteorological Experiment (COHMEX) study area on a day with relatively weak large scale forcing. The problem of determining where and when convection should be initiated is considered to be a major problem of current approaches. Assimilation of moisture data from satellite, radar, and surface data is shown to significantly improve mesoscale simulations. The TASS model is shown to reproduce some observed mesoscale features when initialized with 3-D observational data. Convection evolution studies center on comparison of the Kuo and Fritsch-Chappell cumulus parameterization schemes to each other, and to cloud model results. The Fritsch-Chappell scheme is found to be superior at about 30 km resolution, while the Kuo scheme does surprisingly well in simulating convection down to 10 km in cases where convergence features are well-resolved by the model grid. Results from MASS-TASS interaction experiments are presented and discussed. A discussion of the future of convective simulation is given, with the conclusion that significant progress is possible on several fronts in the next few years.

Characterization of extreme years in Central Europe between 2000 and 2016 according to specific vegetation characteristics based on Earth Observatory data

NASA Astrophysics Data System (ADS)

Kern, Anikó; Marjanović, Hrvoje; Barcza, Zoltán

2017-04-01

Extreme weather events frequently occur in Central Europe, affecting the state of the vegetation in large areas. Droughts and heat-waves affect all plant functional types, but the response of the vegetation is not uniform and depends on other parameters, plant strategies and the antecedent meteorological conditions as well. Meteorologists struggle with the definition of extreme events and selection of years that can be considered as extreme in terms of meteorological conditions due to the large variability of the meteorological parameters both in time and space. One way to overcome this problem is the definition of extreme weather based on its observed effect on plant state. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Leaf Area Index (LAI), the Fraction of Photosynthetically Active Radiation (FPAR) and the Gross Primary Production (GPP) are different measures of the land vegetation derived from remote sensing data, providing information about the plant state, but it is less known how weather anomalies affect these measures. We used the vegetation related official products created from the measurements of the MODerate resolution Imaging Spectroradiometer (MODIS) on board satellite Terra to select and characterize the extreme years in Central European countries during the 2000-2016 time period. The applied Collection-6 MOD13 NDVI/EVI, MOD15 LAI/FPAR and MOD17 GPP datasets have 500 m × 500 m spatial resolution covering the region of the Carpathian-Basin. After quality and noise filtering (and temporal interpolation in case of MOD13) 8-day anomaly values were derived to investigate the different years. The freely available FORESEE meteorological database was used to study climate variability in the region. Daily precipitation and maximum/minimum temperature fields at 1/12° × 1/12° grid were resampled to the 8-day temporal and 500 m × 500 m spatial resolution of the MODIS products. To discriminate the different behavior of the various plant functional types MODIS (MCD12) and CORINE (CLC2012) land cover datasets were applied and handled together. Based on the determination of the reliable pixels with different plant types the response of broadleaf forests, coniferous forests, grasslands and croplands were discriminated and investigated. Characteristic time periods were selected based on the remote sensing data to define anomalies, and then the meteorological data were used to define critical time periods within the year that has the strongest effect on the observed anomalies. Similarities/dissimilarities between the behaviors of the different remotely sensed measures are also studied to elucidate the consistency of the indices. The results indicate that the diverse remote sensing indices typically co-vary but reveal strong plant functional type dependency. The study suggest that the selection of extreme years based on annual data is not the best choice, as shorter time periods within the years explain the anomalies to a higher degree than annual data. The results can be used to select anomalous years outside of the satellite era as well. Keywords: Remote sensing, meteorology; extreme years; MODIS, NDVI; EVI; LAI; FPAR; GPP; phenology

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY. For the case of 280 DOY, Crop yield estimation showed better accuracy for soybean at county level. Though the case of 200 DOY resulted in less accuracy (i.e. 20% mean bias), it provides a useful tool for early forecasting of crop yield. We improved the spatial accuracy of estimated crop yield at county level by developing county-specific crop conversion coefficient. Our results indicate that the aboveground crop biomass can be estimated successfully with the simple LUE and respiration models combined with MODIS data and then, county-specific conversion coefficient can be different with each other across different counties. Hence, applying region-specific conversion coefficient is necessary to estimate crop yield with better accuracy.

Log Books and the Law of Storms: Maritime Meteorology and the British Admiralty in the Nineteenth Century.

PubMed

Naylor, Simon

2015-12-01

This essay contributes to debates about the relationship between science and the military by examining the British Admiralty's participation in meteorological projects in the first half of the nineteenth century. It focuses on attempts to transform Royal Navy log books into standardized meteorological registers that would be of use to both science and the state. The essay begins with a discussion of Admiralty Hydrographer Francis Beaufort, who promoted the use of standardized systems for the observation of the weather at sea. It then examines the application of ships' logs to the science of storms. The essay focuses on the Army engineer William Reid, who studied hurricanes while stationed in Barbados and Bermuda. Reid was instrumental in persuading the Admiralty to implement a naval meteorological policy, something the Admiralty Hydrographer had struggled to achieve. The essay uses the reception and adoption of work on storms at sea to reflect on the means and ends of maritime meteorology in the mid-nineteenth century.

In search of colonial El Niño events and a brief history of meteorology in Ecuador

NASA Astrophysics Data System (ADS)

Terneus, A.; Gioda, A.

2006-02-01

This study shows a brief overview of the development of meteorology in Ecuador from historical documentation of climatic events in the Colonial era through to modern data collection. In the colonial era (16th century-1824), historical documents of rogation ceremonies and municipal proceedings, from the Quito area, provide a rich source of climate information, including El Niño events. Our preliminary findings show that very few of the historically documented catastrophes and other marked environmental events in Quito match known El Niño episodes. Independently, the first meteorological data was collected in Ecuador (beginning with La Condamine in 1738), followed by the earliest attempts to build a national meteorological network in the 1860's, linked closely to President Gabriel García Moreno and the Jesuits. The 1925 El Niño phenomenon was the first important meteorological episode recorded with scientific instrumentation in Ecuador, with newspapers providing complementary archives about the extreme impact of this event.

Engineering assessment and feasibility study of Chattanooga Shale as a future source of uranium. [Preliminary mining; data on soils, meteorology, water resources, and biological resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

This volume contains five appendixes: Chattanooga Shale preliminary mining study, soils data, meteorologic data, water resources data, and biological resource data. The area around DeKalb County in Tennessee is the most likely site for commercial development for recovery of uranium. (DLC)

AN INTERDISCIPLINARY APPROACH TO ADDRESSING NEIGHBORHOOD SCALE AIR QUALITY CONCERNS: THE INTEGRATION OF GIS, URBAN MORPHOLOGY, PREDICTIVE METEOROLOGY, AND AIR QUALITY MONITORING TOOLS

EPA Science Inventory

The paper describes a project that combines the capabilities of urban geography, raster-based GIS, predictive meteorological and air pollutant diffusion modeling, to support a neighborhood-scale air quality monitoring pilot study under the U.S. EPA EMPACT Program. The study ha...

Effects of meteorological droughts on agricultural water resources in southern China

Treesearch

Houquan Lu; Yihua Wu; Yijun Li; Yongqiang Liu

2017-01-01

With the global warming, frequencies of drought are rising in the humid area of southern China. In this study, the effects of meteorological drought on the agricultural water resource based on the agricultural water resource carrying capacity (AWRCC) in southern China were investigated. The entire study area was divided into three regions based on the...

A Research Study of Tropospheric Ozone and Meteorological Parameters to Introduce High School Students to Scientific Procedures

ERIC Educational Resources Information Center

Diaz-de-Mera, Yolanda; Notario, Alberto; Aranda, Alfonso; Adame, Jose Antonio; Parra, Alfonso; Romero, Eugenio; Parra, Jesus; Munoz, Fernando

2011-01-01

An environmental research project was carried out by a consortium established among scientists and university lecturers in collaboration with two high schools. High school students participated in a long-term study of the local temporal profiles of tropospheric ozone and the relationship to pollution and meteorological parameters. Low-cost…

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

PubMed Central

Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations. PMID:29057838

A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion

Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

NASA Technical Reports Server (NTRS)

Belle, Jessica H.; Chang, Howard H.; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-01-01

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition.

PubMed

Belle, Jessica H; Chang, Howard H; Wang, Yujie; Hu, Xuefei; Lyapustin, Alexei; Liu, Yang

2017-10-18

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM 2.5 ) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM 2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM 2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM 2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM 2.5 concentrations.

Surface Meteorology, Barrow, Alaska, Area A, B, C and D, Ongoing from 2012

DOE Data Explorer

Bob Busey; Larry Hinzman; William Cable; Vladimir Romanovsky

2014-12-04

Meteorological data are being collected at several points within four intensive study areas in Barrow. These data assist in the calculation of the energy balance at the land surface and are also useful as inputs into modeling activities.

High Aerosol Concentration cases measured at Vessel Gisang 1 over the Yellow Sea during KORUS-AQ Campaign

NASA Astrophysics Data System (ADS)

Ryoo, S. B.; Yun Kyu, L.; Lee, H. C.; Cha, J. W.

2017-12-01

ADAM-Haze (Asian Dust and Haze Model) model of NIMS (National Institute of Meteorological Sciences) /KMA (Korean Meteorological Administration) was used to assess the high aerosol mass concentration cases for the cruise area using research vessel Gisang 1 over the Yellow sea during KORUS-AQ (Korea-United States Air Quality Study) campaign in 2016. In order to simplify the analysis of the route of the air mass, it is classified into five categories according to the regional characteristics of the pollution sources.(I: Around inner Mongolia and Beijing regions in China, II: Around Liaoning province in China and North Korea, III: Around South Korea and Japan, IV: Around East China sea, V: Around Shandong Peninsula and Shanghai regions in China.) using by the HYSPLIT 4 model developed by the National Oceanic and Atmospheric Administration / Air Resources Laboratory. The most frequent airborne trajectories were category V, which accounted for 32% of the total. The category I, II, and III also accounted for 19%, 21% and 26% , respectively. That means the atmospheric aerosol over the Yellow sea during the campaign was affected about 70% from China and 26% from South Korea. To clearly investigate the transport process, ADAM-Haze model separately ran for dust and non-dust cases over the Yellow sea during the cruise. For example, the model showed the Asian dust influenced the vessel observations with pollutants on May 7 2016 in I category and strong haze from Shandong peninsula in China attributed to them on May 29 2016 in V category. In addition, the comparison of the vessel observation with the model out is under study and the source apportionment will be implemented by using numerical method such as DDM (Decoupled Direct Method) calculation. Therefore, we will show you the results for the comparison and DDM calculation as well as detail results of the evaluating model performance in the conference.

The Science Behind Moravian Meteorological Observations for Late-18th Century Labrador

NASA Astrophysics Data System (ADS)

Newell, Dianne; Lüdecke, Cornelia; Matiu, Michael; Menzel, Annette

2017-04-01

From the time they established their first shelter among the Inuit population of the northern coast of Labrador in 1771, the brethren of the Moravian Church began producing series of daily instrumental and qualitative meteorological observations of significance to science networks of the day (Macpherson, 1987, Demarée & Ogilvie, 2008). Contrary to what is understood, missionaries did not make these observations for their own purposes. Rather, they responded to requests from scientists who commissioned the data. Scientists also equipped these undertakings. The enlightened observers provided handwritten copies that were publicized in England and continental Europe by individuals and their philosophical and scientific institutions. This pattern of producing reliable records specifically for scientists was true for the 15-year span of Moravian meteorological observations for all 3 Labrador stations in the late 18th century; the 40-year span of records for 10 Moravian stations in Labrador and Greenland in the mid-19th century; and the observations from 5 Labrador stations commissioned for the 1st international Polar Year, 1882, and continuing for several decades afterward, and longer in the case of Nain. When Nain data is combined with that from the Canadian meteorological service, we have a relatively straight run from 1882 to 2015. In this paper, we examine the late-18th century Moravian meteorological observations for qualitative information of interest to modern scientific research. The daily entries comprise not only measurements of temperature and air pressure, but also other weather observations, such as wind direction, estimated wind speed, cloudiness, information which has already allowed us to begin tracking polar lows travelling from Labrador to Greenland across the Labrador Sea. The annual missionary reports of Moravians provide critical supplementary data identifying recurring local phenological events in nature, which offer an integrated signal of weather conditions, such as the timing and lengths of the seasons (Menzel, 2002; Dose and Menzel, 2006). Phenological data also display impacts of climate change (Rosenzweig et al., 2007). So far, historical phenological records are unknown for the Labrador coast. Thus, a systematic digitalization of the original meteorological observations will provide unique material on historical paleoclimatic data about an environmentally sensitive and understudied region. And, if we expand the spatial scope of our future research, we will explore comparable meteorological and phenological data generated (1774-1811) by the Hudson Bay Company for the Royal Society of London at a dozen company trading posts in subarctic Canada. Like the Moravians, post managers also kept daily post journals. These contain an abundance of phenological data that will help amplify the cryptic information in HBC meteorological journals. Five company posts on James Bay and Hudson Bay are examples.

Selection of meteorological conditions to apply in an Ecotron facility

NASA Astrophysics Data System (ADS)

Leemans, Vincent; De Cruz, Lesley; Dumont, Benjamin; Hamdi, Rafiq; Delaplace, Pierre; Heinesh, Bernard; Garré, Sarah; Verheggen, François; Theodorakopoulos, Nicolas; Longdoz, Bernard

2017-04-01

This presentation aims to propose a generic method to produce meteorological input data that is useful for climate research infrastructures such as an Ecotron, where researchers will face the need to generate representative actual or future climatic conditions. Depending on the experimental objectives and the research purposes, typical conditions or more extreme values such as dry or wet climatic scenarios might be requested. Four variables were considered here, the near-surface air temperature, the near-surface relative humidity, the cloud cover and precipitation. The meteorological datasets, among which a specific meteorological year can be picked up, are produced by the ALARO-0 model from the RMIB (Royal Meteorological Institute of Belgium). Two future climate scenarios (RCP 4.5 and 8.5) and two time periods (2041-2070 and 2071-2100) were used as well as a historical run of the model (1981-2010) which is used as a reference. When the data from a historical run were compared to the observed historical data, biases were noticed. A linear correction was proposed for all the variables except for precipitation, for which a non-linear correction (using a power function) was chosen to maintain a zero-precipitation occurrences. These transformations were able to remove most of the differences between the observed and historical run of the model for the means and for the standard deviations. For the relative humidity, because of non-linearities, only one half of the average bias was corrected and a different path might have to be chosen. For the selection of a meteorological year, a position and a dispersion parameter have been proposed to characterise each meteorological year for each variable. For precipitation, a third parameter quantifying the importance of dry and wet periods has been defined. In order to select a specific climate, for each of these nine parameters the experimenter should provide a percentile and a weight to prioritize the importance of each variable in the process of a global climate selection. The proposed algorithm computed the weighted distance for each year between the parameters and the point representing the position of the percentile in the nine-dimensional space. The five closest values were then selected and represented in different graphs. The proposed method is able to provide a decision aid in the selection of the meteorological conditions to be generated within an Ecotron. However, with a limited number of years available in each case (thirty years for each RCP and each time period), there is no perfect match and the ultimate trade-off will be the responsibility of the researcher. For typical years, close to the median, the relative frequency is higher and the trade-off is more easy than for more extreme years where the relative frequency is low.

Evaluating aerosol impacts on Numerical Weather Prediction in two extreme dust and biomass-burning events

NASA Astrophysics Data System (ADS)

Remy, Samuel; Benedetti, Angela; Jones, Luke; Razinger, Miha; Haiden, Thomas

2014-05-01

The WMO-sponsored Working Group on Numerical Experimentation (WGNE) set up a project aimed at understanding the importance of aerosols for numerical weather prediction (NWP). Three cases are being investigated by several NWP centres with aerosol capabilities: a severe dust case that affected Southern Europe in April 2012, a biomass burning case in South America in September 2012, and an extreme pollution event in Beijing (China) which took place in January 2013. At ECMWF these cases are being studied using the MACC-II system with radiatively interactive aerosols. Some preliminary results related to the dust and the fire event will be presented here. A preliminary verification of the impact of the aerosol-radiation direct interaction on surface meteorological parameters such as 2m Temperature and surface winds over the region of interest will be presented. Aerosol optical depth (AOD) verification using AERONET data will also be discussed. For the biomass burning case, the impact of using injection heights estimated by a Plume Rise Model (PRM) for the biomass burning emissions will be presented.

47 CFR 95.1211 - Channel use policy.

Code of Federal Regulations, 2012 CFR

2012-10-01

... in the 400.150-406.000 MHz band in the Meteorological Aids, Meteorological Satellite, or Earth... in the 400.150-406.000 MHz band in the Meteorological Aids, Meteorological Satellite, or Earth..., Meteorological Satellite, or Earth Exploration Satellite Services, or to other authorized stations operating in...

Integration of ambient seismic noise monitoring, displacement and meteorological measurements to infer the temperature-controlled long-term evolution of a complex prone-to-fall cliff

NASA Astrophysics Data System (ADS)

Colombero, C.; Baillet, L.; Comina, C.; Jongmans, D.; Larose, E.; Valentin, J.; Vinciguerra, S.

2018-06-01

Monitoring the temporal evolution of resonance frequencies and velocity changes detected from ambient seismic noise recordings can help in recognizing reversible and irreversible modifications within unstable rock volumes. With this aim, the long-term ambient seismic noise data set acquired at the potentially unstable cliff of Madonna delSasso (NW Italian Alps) was analysed in this study, using both spectral analysis and cross-correlation techniques. Noise results were integrated and compared with direct displacement measurements and meteorological data, to understand the long-term evolution of the cliff. No irreversible modifications in the stability of the site were detected over the monitored period. Conversely, daily and seasonal air temperature fluctuations were found to control resonance frequency values, amplitudes and directivities and to induce reversible velocity changes within the fractured rock mass. The immediate modification in the noise parameters due to temperature fluctuations was interpreted as the result of rock mass thermal expansion and contraction, inducing variations in the contact stiffness along the fractures isolating two unstable compartments. Differences with previous case studies were highlighted in the long-term evolution of noise spectral amplitudes and directivities, due to the complex 3-D fracture setting of the site and to the combined effects of the two unstable compartments.

Statistical considerations in creating water vapor data records from combinations of satellite and other observation types, including in situ and ground-based remote sensing

NASA Astrophysics Data System (ADS)

Dykema, J. A.; Anderson, J. G.

2014-12-01

Measuring water vapor at the highest spatial and temporal at all vertical levels and at arbitrary times requires strategic utilization of disparate observations from satellites, ground-based remote sensing, and in situ measurements. These different measurement types have different response times and very different spatial averaging properties, both horizontally and vertically. Accounting for these different measurement properties and explicit propagation of associated uncertainties is necessary to test particular scientific hypotheses, especially in cases of detection of weak signals in the presence of natural fluctuations, and for process studies with small ensembles. This is also true where ancillary data from meteorological analyses are required, which have their own sampling limitations and uncertainties. This study will review two investigations pertaining to measurements of water vapor in the mid-troposphere and lower stratosphere that mix satellite observations with observations from other sources. The focus of the mid-troposphere analysis is to obtain improved estimates of water vapor at the instant of a sounding satellite overpass. The lower stratosphere work examines the uncertainty inherent in a small ensemble of anomalously elevated lower stratospheric water vapor observations when meteorological analysis products and aircraft in situ observations are required for interpretation.

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

Migration Related to Climate Change: Impact, Challenges and Proposed Policy Initiatives

NASA Astrophysics Data System (ADS)

Sarkar, A.

2015-12-01

Migration of human population possesses a great threat to human development and nation building. A significant cause for migration is due to change in climatic conditions and vulnerabilities associated with it. Our case study focuses on the consequent reason and impact of such migration in the coastal areas of West Bengal, India. The changes in rainfall pattern and the variation of temperature have been considered as parameters which have resulted in migration. It is worthy to note that the agricultural pattern has subsequently changed over the last two decades due to change in rainfall and temperature. India being an agriculture oriented economy, the changes in the meteorological variables have not only altered the rate of agricultural pattern but also the rate of migration. A proposed framework depicting relationship between changes in meteorological variables and the migration pattern, and an estimate of how the migration pattern is expected to change over the next century by utilizing the downscaled values of future rainfall and temperature has been analyzed. Moreover, various public policy frameworks has also been proposed through the study for addressing the challenges of migration related to climate change. The proposed public policy framework has been streamlined along the lines of various international treaties and conventions in order to integrate the policy initiatives through universalization of law and policy research.

Risk analysis of technological hazards: Simulation of scenarios and application of a local vulnerability index.

PubMed

Sanchez, E Y; Represa, S; Mellado, D; Balbi, K B; Acquesta, A D; Colman Lerner, J E; Porta, A A

2018-06-15

The potential impact of a technological accident can be assessed by risk estimation. Taking this into account, the latent or potential condition can be warned and mitigated. In this work we propose a methodology to estimate risk of technological hazards, focused on two components. The first one is the processing of meteorological databases to define the most probably and conservative scenario of study, and the second one, is the application of a local social vulnerability index to classify the population. In this case of study, the risk was estimated for a hypothetical release of liquefied ammonia in a meat-packing industry in the city of La Plata, Argentina. The method consists in integrating the simulated toxic threat zone with ALOHA software, and the layer of sociodemographic classification of the affected population. The results show the areas associated with higher risks of exposure to ammonia, which are worth being addressed for the prevention of disasters in the region. Advantageously, this systemic approach is methodologically flexible as it provides the possibility of being applied in various scenarios based on the available information of both, the exposed population and its meteorology. Furthermore, this methodology optimizes the processing of the input data and its calculation. Copyright © 2018 Elsevier B.V. All rights reserved.

Case study of dust event sources from the Gobi and Taklamakan deserts: An investigation of the horizontal evolution and topographical effect using numerical modeling and remote sensing.

PubMed

Fan, Jin; Yue, Xiaoying; Sun, Qinghua; Wang, Shigong

2017-06-01

A severe dust event occurred from April 23 to April 27, 2014, in East Asia. A state-of-the-art online atmospheric chemistry model, WRF/Chem, was combined with a dust model, GOCART, to better understand the entire process of this event. The natural color images and aerosol optical depth (AOD) over the dust source region are derived from datasets of moderate resolution imaging spectroradiometer (MODIS) loaded on a NASA Aqua satellite to trace the dust variation and to verify the model results. Several meteorological conditions, such as pressure, temperature, wind vectors and relative humidity, are used to analyze meteorological dynamic. The results suggest that the dust emission occurred only on April 23 and 24, although this event lasted for 5days. The Gobi Desert was the main source for this event, and the Taklamakan Desert played no important role. This study also suggested that the landform of the source region could remarkably interfere with a dust event. The Tarim Basin has a topographical effect as a "dust reservoir" and can store unsettled dust, which can be released again as a second source, making a dust event longer and heavier. Copyright © 2016. Published by Elsevier B.V.

Meteorological and chemical impacts on ozone formation: A case study in Hangzhou, China

NASA Astrophysics Data System (ADS)

Li, Kangwei; Chen, Linghong; Ying, Fang; White, Stephen J.; Jang, Carey; Wu, Xuecheng; Gao, Xiang; Hong, Shengmao; Shen, Jiandong; Azzi, Merched; Cen, Kefa

2017-11-01

Regional ozone pollution has become one of the most challenging problems in China, especially in the more economically developed and densely populated regions like Hangzhou. In this study, measurements of O3, CO, NOx and non-methane hydrocarbons (NMHCs), together with meteorological data, were obtained for the period July 1, 2013-August 15, 2013 at three sites in Hangzhou. These sites included an urban site (Zhaohui ;ZH;), a suburban site (Xiasha ;XS;) and a rural site (Qiandaohu ;QDH;). During the observation period, both ZH and XS had a higher ozone level than QDH, with exceeding rates of 41.3% and 47.8%, respectively. Elevated O3 levels in QDH were found at night, which could be explained by less prominent NO titration effect in rural area. Detailed statistical analysis of meteorological and chemical impacts on ozone formation was carried out for ZH, and higher ozone concentration was observed when the wind direction was from the east. This is possibly due to emissions of VOCs from XS, a typical chemical industrial park located in 30 km upwind area of ZH. A comprehensive comparison between three ozone episode periods and one non-episode period were made in ZH. It was concluded that elevated concentrations of precursors and temperatures, low relative humidity and wind speed and easterly-dominated wind direction contribute to urban ozone episodes in Hangzhou. VOCs reactivity analysis indicated that reactive alkenes like isoprene and isobutene contributed most to ozone formation. Three methods were applied to evaluate O3-VOCs-NOx sensitivity in ZH: VOCs/NOx ratio method, Smog Production Model (SPM) and Relative Incremental Reactivity (RIR). The results show that summer ozone in urban Hangzhou mostly presents VOCs-limited and transition region alternately. Our study implies that the increasing automobiles and VOCs emissions from upwind area could result in ozone pollution in urban Hangzhou, and synergistic reduction of VOCs and NOx will be more effective.

Recommended Values of Meteorological Factors to Be Considered in the Design of Aircraft Ice-Prevention Equipment

NASA Technical Reports Server (NTRS)

Jones, Alun R; Lewis, William

1949-01-01

Meteorological conditions conducive to aircraft icing are arranged in four classifications: three are associated with cloud structure and the fourth with freezing rain. The range of possible meteorological factors for each classification is discussed and specific values recommended for consideration in the design of ice-prevention equipment for aircraft are selected and tabulated. The values selected are based upon a study of the available observational data and theoretical considerations where observations are lacking. Recommendations for future research in the field are presented.

Jesuits' Contribution to Meteorology.

NASA Astrophysics Data System (ADS)

Udías, Agustín

1996-10-01

Starting in the middle of the nineteenth century, as part of their scientific tradition, Jesuits founded a considerable number of meteorological observatories throughout the world. In many countries, Jesuits established and maintained the first meteorological stations during the period from 1860 to 1950. The Jesuits' most important contribution to atmospheric science was their pioneer work related to the study and forecast of tropical hurricanes. That research was carried out at observatories of Belén (Cuba), Manila (Philippines), and Zikawei (China). B. Viñes, M. Decheyrens, J. Aigué, and C.E. Deppermann stood out in this movement.