Formative Evaluation of a Web-Based Course in Meteorology.
ERIC Educational Resources Information Center
Phelps, Julia; Reynolds, Ross
1999-01-01
Describes the formative-evaluation process for the EuroMET (European Meteorological Education and Training) project, Web-Based university courses in meteorology that were created to address the education and training needs of professional meteorologists and students throughout Europe. Usability and interactive and multimedia elements are…
Huading, Shi; Critto, Andrea; Torresan, Silvia; Qingxian, Gao
2018-06-13
With the rapid economic development and the continuous population growth, several important cities in China suffer serious air pollution, especially in the Beijing-Tianjin-Hebei economic developing area. Based on the daily air pollution index (API) and surface meteorological elements in Beijing, Tianjin and Shijiazhuang from 2001 to 2010, the relationships between API and meteorological elements were analyzed. The statistical analysis focused on the relationships at seasonal and monthly average scales, on different air pollution grades and air pollution processes. The results revealed that the air pollution conditions in the three areas gradually improved from 2001 to 2010, especially during summer; and the worst conditions in air quality were recorded in Beijing in spring due to the influences of dust, while in Tianjin and Shijiazhuang in winter due to household heating. Meteorological elements exhibited different influences on air pollution, showing similar relationships between API in monthly averages and four meteorological elements (i.e., the average, maximum and minimum temperatures, maximum air pressure, vapor pressure, and maximum wind speed); while the relationships on a seasonal average scale demonstrated significant differences. Compared with seasonal and monthly average scales of API, the relation coefficients based on different air pollution grades were significatively lower; while the relationship between API and meteorological elements based on air pollution process reduced the smoothing effect due to the average processing of seasonal and monthly API and improved the accuracy of the results based on different air pollution grades. Finally, statistical analysis of the distribution of pollution days in different wind directions indicated the directions of extreme and maximum wind speeds that mainly influence air pollution; representing a valuable information that could support the definition of air pollution control strategies through the identification of the regions (and the located emission sources) where to focus the implementation of emission reduction actions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
A Discretization Algorithm for Meteorological Data and its Parallelization Based on Hadoop
NASA Astrophysics Data System (ADS)
Liu, Chao; Jin, Wen; Yu, Yuting; Qiu, Taorong; Bai, Xiaoming; Zou, Shuilong
2017-10-01
In view of the large amount of meteorological observation data, the property is more and the attribute values are continuous values, the correlation between the elements is the need for the application of meteorological data, this paper is devoted to solving the problem of how to better discretize large meteorological data to more effectively dig out the hidden knowledge in meteorological data and research on the improvement of discretization algorithm for large scale data, in order to achieve data in the large meteorological data discretization for the follow-up to better provide knowledge to provide protection, a discretization algorithm based on information entropy and inconsistency of meteorological attributes is proposed and the algorithm is parallelized under Hadoop platform. Finally, the comparison test validates the effectiveness of the proposed algorithm for discretization in the area of meteorological large data.
40 CFR 57.402 - Elements of the supplementary control system.
Code of Federal Regulations, 2013 CFR
2013-07-01
... capable of routine real time measurement of maximum expected SO2 concentrations for the averaging times of... emission curtailment decisions based on the use of real time information from the air quality monitoring... meteorological information necessary to operate the system; (iv) The ambient concentrations and meteorological...
40 CFR 57.402 - Elements of the supplementary control system.
Code of Federal Regulations, 2011 CFR
2011-07-01
... capable of routine real time measurement of maximum expected SO2 concentrations for the averaging times of... emission curtailment decisions based on the use of real time information from the air quality monitoring... meteorological information necessary to operate the system; (iv) The ambient concentrations and meteorological...
40 CFR 57.402 - Elements of the supplementary control system.
Code of Federal Regulations, 2012 CFR
2012-07-01
... capable of routine real time measurement of maximum expected SO2 concentrations for the averaging times of... emission curtailment decisions based on the use of real time information from the air quality monitoring... meteorological information necessary to operate the system; (iv) The ambient concentrations and meteorological...
40 CFR 57.402 - Elements of the supplementary control system.
Code of Federal Regulations, 2014 CFR
2014-07-01
... capable of routine real time measurement of maximum expected SO2 concentrations for the averaging times of... emission curtailment decisions based on the use of real time information from the air quality monitoring... meteorological information necessary to operate the system; (iv) The ambient concentrations and meteorological...
40 CFR 57.402 - Elements of the supplementary control system.
Code of Federal Regulations, 2010 CFR
2010-07-01
... capable of routine real time measurement of maximum expected SO2 concentrations for the averaging times of... emission curtailment decisions based on the use of real time information from the air quality monitoring... meteorological information necessary to operate the system; (iv) The ambient concentrations and meteorological...
Li, Wen-Whai; Cardenas, Nidia; Walton, John; Trujillo, David; Morales, Hugo; Arimoto, Richard
2005-03-01
The causes for evening low-wind PM10 and PM2.5 peaks at Sunland Park, NM, were investigated by using wind sector analysis and by assessing relationships between PM loadings and meteorological parameters through canonical ordination analysis. Both PM10 and PM2.5 concentrations during the evening hours accounted for approximately 50% of their respective 24-hr averages, and the PM10 was mainly composed of coarse material (PM10-2.5 amounted to 77% of PM10). A wind sector analysis based on data from three surface meteorological monitoring stations in the region narrowed the potential source region for PM10 and PM2.5 to an area within a few kilometers south of Sunland Park. Canonical ordination analysis confirmed that the peak frequently occurred under stable conditions with weak southerly winds. Chemical analyses of PM showed that elemental and organic carbon (EC and OC, respectively) dominate PM2.5 and inorganic elements dominate PM10-2.5. The combined data for EC/OC, geologic elements, and various trace elements indicate that under low wind and stable conditions, traffic-related PM emissions (motor vehicle exhausts and re-suspended road dust) from the south of the site are the most likely sources for the evening PM10 and PM2.5 peaks.
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.
NASA Astrophysics Data System (ADS)
Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor
2015-09-01
The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.
Matyasovszky, István; Makra, László; Csépe, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Fülöp, Andrea; Tusnády, Gábor
2015-09-01
The paper examines the sensitivity of daily airborne Ambrosia (ragweed) pollen levels of a current pollen season not only on daily values of meteorological variables during this season but also on the past meteorological conditions. The results obtained from a 19-year data set including daily ragweed pollen counts and ten daily meteorological variables are evaluated with special focus on the interactions between the phyto-physiological processes and the meteorological elements. Instead of a Pearson correlation measuring the strength of the linear relationship between two random variables, a generalised correlation that measures every kind of relationship between random vectors was used. These latter correlations between arrays of daily values of the ten meteorological elements and the array of daily ragweed pollen concentrations during the current pollen season were calculated. For the current pollen season, the six most important variables are two temperature variables (mean and minimum temperatures), two humidity variables (dew point depression and rainfall) and two variables characterising the mixing of the air (wind speed and the height of the planetary boundary layer). The six most important meteorological variables before the current pollen season contain four temperature variables (mean, maximum, minimum temperatures and soil temperature) and two variables that characterise large-scale weather patterns (sea level pressure and the height of the planetary boundary layer). Key periods of the past meteorological variables before the current pollen season have been identified. The importance of this kind of analysis is that a knowledge of the past meteorological conditions may contribute to a better prediction of the upcoming pollen season.
Design of extensible meteorological data acquisition system based on FPGA
NASA Astrophysics Data System (ADS)
Zhang, Wen; Liu, Yin-hua; Zhang, Hui-jun; Li, Xiao-hui
2015-02-01
In order to compensate the tropospheric refraction error generated in the process of satellite navigation and positioning. Temperature, humidity and air pressure had to be used in concerned models to calculate the value of this error. While FPGA XC6SLX16 was used as the core processor, the integrated silicon pressure sensor MPX4115A and digital temperature-humidity sensor SHT75 are used as the basic meteorological parameter detection devices. The core processer was used to control the real-time sampling of ADC AD7608 and to acquire the serial output data of SHT75. The data was stored in the BRAM of XC6SLX16 and used to generate standard meteorological parameters in NEMA format. The whole design was based on Altium hardware platform and ISE software platform. The system was described in the VHDL language and schematic diagram to realize the correct detection of temperature, humidity, air pressure. The 8-channel synchronous sampling characteristics of AD7608 and programmable external resources of FPGA laid the foundation for the increasing of analog or digital meteorological element signal. The designed meteorological data acquisition system featured low cost, high performance, multiple expansions.
Graney, Joseph R; Landis, Matthew S
2013-03-15
A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16month period (July 1994-October 1995) at Bondville were parsed into six unique meteorological flow regimes using a minimum variance clustering technique on back trajectory endpoints. Pb isotope ratios and multi-element concentrations were measured using high resolution inductively coupled plasma-sector field mass spectrometry (ICP-SFMS) on the archived precipitation samples. Bondville is located in central Illinois, ~250km downwind from smelters in southeast Missouri. The Mississippi Valley Type ore deposits in Missouri provided a unique multi-element and Pb isotope fingerprint for smelter emissions which could be contrasted to industrial emissions from the Chicago and Indianapolis urban areas (~125km north and east, of Bondville respectively) and regional emissions from electric utility facilities. Differences in Pb isotopes and element concentrations in precipitation corresponded to flow regime. Industrial sources from urban areas, and thorogenic Pb from coal use, could be differentiated from smelter emissions from Missouri by coupling Pb isotopes with variations in element ratios and relative mass factors. Using a three endmember mixing model based on Pb isotope ratio differences, industrial processes in urban airsheds contributed 56±19%, smelters in southeast Missouri 26±13%, and coal combustion 18±7%, of the Pb in precipitation collected in Bondville in the mid-1990s. Copyright © 2012 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Winnicki, I.; Jasinski, J.; Kroszczynski, K.; Pietrek, S.
2009-04-01
The paper presents elements of research conducted in the Faculty of Civil Engineering and Geodesy of the Military University of Technology, Warsaw, Poland, concerning application of mesoscale models and remote sensing data to determining meteorological conditions of aircraft flight directly related with atmospheric instabilities. The quality of meteorological support of aviation depends on prompt and effective forecasting of weather conditions changes. The paper presents a computer module for detecting and monitoring zones of cloud cover, precipitation and turbulence along the aircraft flight route. It consists of programs and scripts for managing, processing and visualizing meteorological and remote sensing databases. The application was developed in Matlab® for Windows®. The module uses products of COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale non-hydrostatic model of the atmosphere developed by the US Naval Research Laboratory, satellite images acquisition system from the MSG-2 (Meteosat Second Generation) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and meteorological radars data acquired from the Institute of Meteorology and Water Management (IMGW), Warsaw, Poland. The satellite images acquisition system and the COAMPS model are run operationally in the Faculty of Civil Engineering and Geodesy. The mesoscale model is run on an IA64 Feniks multiprocessor 64-bit computer cluster. The basic task of the module is to enable a complex analysis of data sets of miscellaneous information structure and to verify COAMPS results using satellite and radar data. The research is conducted using uniform cartographic projection of all elements of the database. Satellite and radar images are transformed into the Lambert Conformal projection of COAMPS. This facilitates simultaneous interpretation and supports decision making process for safe execution of flights. Forecasts are based on horizontal distributions and vertical profiles of meteorological parameters produced by the module. Verification of forecasts includes research of spatial and temporal correlations of structures generated by the model, e.g.: cloudiness, meteorological phenomena (fogs, precipitation, turbulence) and structures identified on current satellite images. The developed module determines meteorological parameters fields for vertical profiles of the atmosphere. Interpolation procedures run at user selected standard (pressure) or height levels of the model enable to determine weather conditions along any route of aircraft. Basic parameters of the procedures determining e.g. flight safety include: cloud base, visibility, cloud cover, turbulence coefficient, icing and precipitation intensity. Determining icing and turbulence characteristics is based on standard and new methods (from other mesoscale models). The research includes also investigating new generation mesoscale models, especially remote sensing data assimilation. This is required by necessity to develop and introduce objective methods of forecasting weather conditions. Current research in the Faculty of Civil Engineering and Geodesy concerns validation of the mesoscale module performance.
The association of air temperature with cardiac arrhythmias
NASA Astrophysics Data System (ADS)
Čulić, Viktor
2017-11-01
The body response to meteorological influences may activate pathophysiological mechanisms facilitating the occurrence of cardiac arrhythmias in susceptible patients. Putative underlying mechanisms include changes in systemic vascular resistance and blood pressure, as well as a network of proinflammatory and procoagulant processes. Such a chain reaction probably occurs within the time window of several hours, so use of daily average values of meteorological elements do not seem appropriate for investigation in this area. In addition, overall synoptic situation, and season-specific combinations of meteorological elements and air pollutant levels probably cause the overall effect rather than a single atmospheric element. Particularly strong interrelations have been described among wind speed, air pressure and temperature, relative air humidity, and suspended particulate matter. This may be the main reason why studies examining the association between temperature and ventricular arrhythmias have found linear positive, negative, J-shaped or no association. Further understanding of the pathophysiological adaptation to atmospheric environment may help in providing recommendations for protective measures during "bad" weather conditions in patients with cardiac arrhythmias.
A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16 ...
Meteorological Error Budget Using Open Source Data
2016-09-01
ARL-TR-7831 ● SEP 2016 US Army Research Laboratory Meteorological Error Budget Using Open- Source Data by J Cogan, J Smith, P...needed. Do not return it to the originator. ARL-TR-7831 ● SEP 2016 US Army Research Laboratory Meteorological Error Budget Using...Error Budget Using Open-Source Data 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) J Cogan, J Smith, P Haines
NASA Technical Reports Server (NTRS)
King, R. B.; Fordyce, J. S.; Antoine, A. C.; Leibecki, H. F.; Neustadter, H. E.; Sidik, S. M.; Burr, J. C.; Craig, G. T.; Cornett, C. L.
1974-01-01
Beginning in 1971 a cooperative program has been carried on by the City of Cleveland Division of Air Pollution Control and NASA Lewis Research Center to study the trace element and compound concentrations in the ambient suspended particulate matter in Cleveland Ohio as a function of source, monitoring location and meteorological conditions. The major objectives were to determine the ambient concentration levels at representative urban sites and to develop a technique using trace element and compound data in conjunction with meteorological conditions to identify specific pollution sources which could be developed into a practical system that could be readily utilized by an enforcement agency.
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.
Tao, Zhengkai; Liu, Yang; Zhou, Meng; Chai, Xiaoli
2017-12-01
Landfill is known as a potential source of atmospheric Hg and an important component of the local or regional atmospheric Hg budget. This study investigated the gaseous elemental Hg surface-air fluxes under differing conditions at a typical municipal solid waste landfill site, highlighting the interactive effects of plant coverage and meteorological conditions. The results indicated that Hg fluxes exhibited a feature represented by diel variation. In particular, Hg deposition was observed under a condition of Kochia sieversiana coverage, whereas emission that occurred after K. sieversiana was removed. Hg emission was the dominant mode under conditions of Setaria viridis coverage and its removal; however, the average Hg emission flux with the S. viridis coverage was nearly four times lower than after its removal. These findings verified that the plant coverage should be a key factor influencing the Hg emission from landfills. In addition, Hg fluxes were correlated positively with solar radiation and air/soil temperature and correlated inversely with relative humidity under all conditions, except K. sieversiana coverage. This suggested that the interactive effects of meteorological conditions and plant coverage played a jointly significant role in the Hg emission from landfills. It was established that K. sieversiana can inhibit Hg emission efficiently, and therefore, it could potentially be suitable for use as a plant-based method to control Hg pollution from landfills.
Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA
NASA Technical Reports Server (NTRS)
Dreher, Joseph G.; Crawford, Winifred; Lafosse, Richard; Hoeth, Brian; Burns, Kerry
2009-01-01
The peak winds near the surface are an important forecast element for space shuttle landings. As defined in the Flight Rules (FR), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings, and is required to issue surface average and 10-minute peak wind speed forecasts. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMU) developed a PC-based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center (KSC; Lambert 2003). However, the shuttle occasionally may land at Edwards Air Force Base (EAFB) in southern California when weather conditions at KSC in Florida are not acceptable, so SMG forecasters requested a similar tool be developed for EAFB.
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.
IN SITU HIGH TEMPORAL RESOLUTION ANALYSIS OF ELEMENTAL MERCURY IN NATURAL WATER (R827915)
Volatilization of elemental Hg represents an important Hg flux for many aquatic systems. In order to model this flux accurately, it is necessary to measure elemental Hg concentrations in air and water, as well as meteorological variables. Up to now, temporal r...
Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane
2007-01-01
High-quality daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...
Abstraction the public from scientific - applied meteorological-climatologic data
NASA Astrophysics Data System (ADS)
Trajanoska, L.
2010-09-01
Mathematical and meteorological statistic processing of meteorological-climatologic data, which includes assessment of the exactness, level of confidence of the average and extreme values, frequencies (probabilities) of the occurrence of each meteorological phenomenon and element e.t.c. helps to describe the impacts climate may have on different social and economic activities (transportation, heat& power generation), as well as on human health. Having in mind the new technology and the commercial world, during the work with meteorological-climatologic data we have meet many different challenges. Priority in all of this is the quality of the meteorological-climatologic set of data. First, we need compatible modern, sophisticated measurement and informatics solution for data. Results of this measurement through applied processing and analyze is the second branch which is very important also. Should we all (country) need that? Today we have many unpleasant events connected with meteorology, many questions which are not answered and all of this has too long lasting. We must give the answers and solve the real and basic issue. In this paper the data issue will be presented. We have too much of data but so little of real and quality applied of them, Why? There is a data for: -public applied -for jurisdiction needs -for getting fast decision-solutions (meteorological-dangerous phenomenon's) -for getting decisions for long-lasting plans -for explore in different sphere of human living So, it is very important for what kind of data we are talking. Does the data we are talking are with public or scientific-applied character? So,we have two groups. The first group which work with the data direct from the measurement place and instrument. They are store a quality data base and are on extra help to the journalists, medical workers, human civil engineers, electromechanical engineers, agro meteorological and forestry engineer e.g. The second group do work with all scientific methods for the needed purposes. Hours, days, years and periods with characteristic meanings are separated for the purposes of the comprehensive analyze and application.
Daily Weather and Children's Physical Activity Patterns.
Remmers, Teun; Thijs, Carel; Timperio, Anna; Salmon, J O; Veitch, Jenny; Kremers, Stef P J; Ridgers, Nicola D
2017-05-01
Understanding how the weather affects physical activity (PA) may help in the design, analysis, and interpretation of future studies, especially when investigating PA across diverse meteorological settings and with long follow-up periods. The present longitudinal study first aims to examine the influence of daily weather elements on intraindividual PA patterns among primary school children across four seasons, reflecting day-to-day variation within each season. Second, we investigate whether the influence of weather elements differs by day of the week (weekdays vs weekends), gender, age, and body mass index. PA data were collected by ActiGraph accelerometers for 1 wk in each of four school terms that reflect each season in southeast Australia. PA data from 307 children (age range 8.7-12.8 yr) were matched to daily meteorological variables obtained from the Australian Government's Bureau of Meteorology (maximum temperature, relative humidity, solar radiation, day length, and rainfall). Daily PA patterns and their association with weather elements were analyzed using multilevel linear mixed models. Temperature was the strongest predictor of moderate and vigorous PA, followed by solar radiation and humidity. The relation with temperature was curvilinear, showing optimum PA levels at temperatures between 20°C and 22°C. Associations between weather elements on PA did not differ by gender, child's age, or body mass index. This novel study focused on the influence of weather elements on intraindividual PA patterns in children. As weather influences cannot be controlled, knowledge of its effect on individual PA patterns may help in the design of future studies, interpretation of their results, and translation into PA promotion.
A framework for improving a seasonal hydrological forecasting system using sensitivity analysis
NASA Astrophysics Data System (ADS)
Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah
2017-04-01
Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of the forecasting chain (i.e., IHC or MF) could potentially lead to the highest increase in seasonal hydrological forecasting performance, after each forecast update.
NASA Astrophysics Data System (ADS)
Silva, K.; Lawawirojwong, S.; Promping, J.
2017-06-01
Consequence assessment of a hypothetical severe accident is one of the important elements of the risk assessment of a nuclear power plant. It is widely known that the meteorological conditions can significantly influence the outcomes of such assessment, since it determines the results of the calculation of the radionuclide environmental transport. This study aims to assess the impacts of the meteorological conditions to the results of the consequence assessment. The consequence assessment code, OSCAAR, of Japan Atomic Energy Agency (JAEA) is used for the assessment. The results of the consequence assessment using Thai meteorological data are compared with those using Japanese meteorological data. The Thai case has following characteristics. Low wind speed made the radionuclides concentrate at the center comparing to the Japanese case. The squalls induced the peaks in the ground concentration distribution. The evacuated land is larger than the Japanese case though the relocated land is smaller, which is attributed to the concentration of the radionuclides near the release point.
NASA Astrophysics Data System (ADS)
Titov, A.; Gordov, E.; Okladnikov, I.
2009-04-01
In this report the results of the work devoted to the development of working model of the software system for storage, semantically-enabled search and retrieval along with processing and visualization of environmental datasets containing results of meteorological and air pollution observations and mathematical climate modeling are presented. Specially designed metadata standard for machine-readable description of datasets related to meteorology, climate and atmospheric pollution transport domains is introduced as one of the key system components. To provide semantic interoperability the Resource Description Framework (RDF, http://www.w3.org/RDF/) technology means have been chosen for metadata description model realization in the form of RDF Schema. The final version of the RDF Schema is implemented on the base of widely used standards, such as Dublin Core Metadata Element Set (http://dublincore.org/), Directory Interchange Format (DIF, http://gcmd.gsfc.nasa.gov/User/difguide/difman.html), ISO 19139, etc. At present the system is available as a Web server (http://climate.risks.scert.ru/metadatabase/) based on the web-portal ATMOS engine [1] and is implementing dataset management functionality including SeRQL-based semantic search as well as statistical analysis and visualization of selected data archives [2,3]. The core of the system is Apache web server in conjunction with Tomcat Java Servlet Container (http://jakarta.apache.org/tomcat/) and Sesame Server (http://www.openrdf.org/) used as a database for RDF and RDF Schema. At present statistical analysis of meteorological and climatic data with subsequent visualization of results is implemented for such datasets as NCEP/NCAR Reanalysis, Reanalysis NCEP/DOE AMIP II, JMA/CRIEPI JRA-25, ECMWF ERA-40 and local measurements obtained from meteorological stations on the territory of Russia. This functionality is aimed primarily at finding of main characteristics of regional climate dynamics. The proposed system represents a step in the process of development of a distributed collaborative information-computational environment to support multidisciplinary investigations of Earth regional environment [4]. Partial support of this work by SB RAS Integration Project 34, SB RAS Basic Program Project 4.5.2.2, APN Project CBA2007-08NSY and FP6 Enviro-RISKS project (INCO-CT-2004-013427) is acknowledged. References 1. E.P. Gordov, V.N. Lykosov, and A.Z. Fazliev. Web portal on environmental sciences "ATMOS" // Advances in Geosciences. 2006. Vol. 8. p. 33 - 38. 2. Gordov E.P., Okladnikov I.G., Titov A.G. Development of elements of web based information-computational system supporting regional environment processes investigations // Journal of Computational Technologies, Vol. 12, Special Issue #3, 2007, pp. 20 - 28. 3. Okladnikov I.G., Titov A.G. Melnikova V.N., Shulgina T.M. Web-system for processing and visualization of meteorological and climatic data // Journal of Computational Technologies, Vol. 13, Special Issue #3, 2008, pp. 64 - 69. 4. Gordov E.P., Lykosov V.N. Development of information-computational infrastructure for integrated study of Siberia environment // Journal of Computational Technologies, Vol. 12, Special Issue #2, 2007, pp. 19 - 30.
2. SOUTH FACE OF METEOROLOGICAL SHED (BLDG. 756) WITH METEOROLOGICAL ...
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
Synoptic Meteorology during the SNOW-ONE-A Field Experiment.
1983-05-01
AD ,34 888 SYNOPTIC METEOROLOGY DURING tHE SNOW-ONE A FIELD I EXPERIMENTIUP COLD REGIONS RESEARCH AND ENGINEERING LABHANOVER NN M A BILELLO MAY 83...PROGRAM ELEMENT. PROJECT. TASK U. S. Army Cold Regions Research and AREA & WORK UNIT NUMBERS Engineering Laboratory DA Project 4A762730AT42- Hanover, New...Hampshire 03755 B-El-5 It. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE Office of the Ch ief of Engineers May 1983 Washington, D.C. 20314 13
NASA Technical Reports Server (NTRS)
Diak, George R.; Smith, William L.
1992-01-01
A flexible system for performing observing system simulation experiments which made contributions to meteorology across all elements of the observing system simulation experiment (OSSE) components was developed. Future work will seek better understanding of the links between satellite-measured radiation and radiative transfer in the clear, cloudy and precipitating atmosphere and investigate how that understanding might be applied to improve the depiction of the initial state and the treatment of physical processes in forecast models of the atmosphere.
Crumrine, Milo D.; Morgan, David S.
1994-01-01
This report is a compilation of hydrologic, water- quality, and meteorologic data collected in the vicinity of Newberry Volcano near Bend, Oregon. These data were collected, in cooperation with the Bonneville Power Administration, the U.S. Forest Service, and the Bureau of Land Management, to provide baseline data for identifying and assessing the effects of proposed geothermal development in the vicinity of Newberry Volcano. Types of data collected include ground-water levels, lake levels, streamflow, water quality, and meteorologic measurements. Sites that were monitored include: (1) two thermal wells in the caldera, (2) several nonthermal wells in the caldera, (3) four wells outside of the caldera, (4) Paulina Creek, (5) Paulina and East Lakes, (6) hot springs that discharge into Paulina and East Lakes, and (7) meteorologic conditions near Paulina Lake. Data are presented for the period summer 1991 through fall 1993. Water-quality data collected include concentrations of common anions and cations, nutrients, trace elements, radiochemicals, and isotopes. Meteorologic data collected include wind velocity, air temperature, humidity, solar radiation, and precipitation.
Studies of atmospheric refraction effects on laser data
NASA Technical Reports Server (NTRS)
Dunn, P. J.; Pearce, W. A.; Johnson, T. S.
1982-01-01
The refraction effect from three perspectives was considered. An analysis of the axioms on which the accepted correction algorithms were based was the first priority. The integrity of the meteorological measurements on which the correction model is based was also considered and a large quantity of laser observations was processed in an effort to detect any serious anomalies in them. The effect of refraction errors on geodetic parameters estimated from laser data using the most recent analysis procedures was the focus of the third element of study. The results concentrate on refraction errors which were found to be critical in the eventual use of the data for measurements of crustal dynamics.
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.
New gridded database of clear-sky solar radiation derived from ground-based observations over Europe
NASA Astrophysics Data System (ADS)
Bartok, Blanka; Wild, Martin; Sanchez-Lorenzo, Arturo; Hakuba, Maria Z.
2017-04-01
Since aerosols modify the entire energy balance of the climate system through different processes, assessments regarding aerosol multiannual variability are highly required by the climate modelling community. Because of the scarcity of long-term direct aerosol measurements, the retrieval of aerosol data/information from other type of observations or satellite measurements are very relevant. One approach frequently used in the literature is analyze of the clear-sky solar radiation which offer a better overview of changes in aerosol content. In the study first two empirical methods are elaborated in order to separate clear-sky situations from observed values of surface solar radiation available at the World Radiation Data Center (WRDC), St. Petersburg. The daily data has been checked for temporal homogeneity by applying the MASH method (Szentimrey, 2003). In the first approach, clear sky situations are detected based on clearness index, namely the ratio of the surface solar radiation to the extraterrestrial solar irradiation. In the second approach the observed values of surface solar radiation are compared to the climatology of clear-sky surface solar radiation calculated by the MAGIC radiation code (Muller et al. 2009). In both approaches the clear-sky radiation values highly depend on the applied thresholds. In order to eliminate this methodological error a verification of clear-sky detection is envisaged through a comparison with the values obtained by a high time resolution clear-sky detection and interpolation algorithm (Long and Ackermann, 2000) making use of the high quality data from the Baseline Surface Radiation Network (BSRN). As the consequences clear-sky data series are obtained for 118 European meteorological stations. Next a first attempt has been done in order to interpolate the point-wise clear-sky radiation data by applying the MISH (Meteorological Interpolation based on Surface Homogenized Data Basis) method for the spatial interpolation of surface meteorological elements developed at the Hungarian Meteorological Service (Szentimrey 2007). In this way new gridded database of clear-sky solar radiation is created suitable for further investigations regarding the role of aerosols in the energy budget, and also for validations of climate model outputs. References 1. Long CN, Ackerman TP. 2000. Identification of clear skies from broadband pyranometer measurements and calculation of downwelling shortwave cloud effects, J. Geophys. Res., 105(D12), 15609-15626, doi:10.1029/2000JD900077. 2. Mueller R, Matsoukas C, Gratzki A, Behr H, Hollmann R. 2009. The CM-SAF operational scheme for the satellite based retrieval of solar surface irradiance - a LUT based eigenvector hybrid approach, Remote Sensing of Environment, 113 (5), 1012-1024, doi:10.1016/j.rse.2009. 01.012 3. Szentimrey T. 2014. Multiple Analysis of Series for Homogenization (MASHv3.03), Hungarian Meteorological Service, https://www.met.hu/en/omsz/rendezvenyek/homogenization_and_interpolation/software/ 4. Szentimrey T. Bihari Z. 2014: Meteorological Interpolation based on Surface Homogenized Data Basis (MISHv1.03) https://www.met.hu/en/omsz/rendezvenyek/homogenization_and_interpolation/software/
NASA Astrophysics Data System (ADS)
Lefebvre, Wouter; Vercauteren, Jordy; Schrooten, Liesbeth; Janssen, Stijn; Degraeuwe, Bart; Maenhaut, Willy; de Vlieger, Ina; Vankerkom, Jean; Cosemans, Guido; Mensink, Clemens; Veldeman, Nele; Deutsch, Felix; Van Looy, Stijn; Peelaerts, Wim; Lefebre, Filip
2011-12-01
The ability of a complex model chain to simulate elemental carbon (EC) concentrations was examined. The results of the model chain were compared to EC concentration measurements made at several locations, every sixth day. Two measurement campaigns were taken into account, one in 2006-2007 and one in 2008-2009. The model results compare very well for both periods, with an R2 of 0.74, a bias of 0.02 μg m -3 and a RMSE of 0.32 μg m -3. Sensitivity analyses to different meteorology inputs and changing emissions from year to year were performed. The differences between the two measurement periods were also investigated. It is shown that somewhat more than half of these differences is due to meteorology. However, emission changes also play an important role.
NASA Astrophysics Data System (ADS)
Padhee, S. K.; Nikam, B. R.; Aggarwal, S. P.; Garg, V.
2014-11-01
Drought is an extreme condition due to moisture deficiency and has adverse effect on society. Agricultural drought occurs when restraining soil moisture produces serious crop stress and affects the crop productivity. The soil moisture regime of rain-fed agriculture and irrigated agriculture behaves differently on both temporal and spatial scale, which means the impact of meteorologically and/or hydrological induced agriculture drought will be different in rain-fed and irrigated areas. However, there is a lack of agricultural drought assessment system in Indian conditions, which considers irrigated and rain-fed agriculture spheres as separate entities. On the other hand recent advancements in the field of earth observation through different satellite based remote sensing have provided researchers a continuous monitoring of soil moisture, land surface temperature and vegetation indices at global scale, which can aid in agricultural drought assessment/monitoring. Keeping this in mind, the present study has been envisaged with the objective to develop agricultural drought assessment and prediction technique by spatially and temporally assimilating effective drought index (EDI) with remote sensing derived parameters. The proposed technique takes in to account the difference in response of rain-fed and irrigated agricultural system towards agricultural drought in the Bundelkhand region (The study area). The key idea was to achieve the goal by utilizing the integrated scenarios from meteorological observations and soil moisture distribution. EDI condition maps were prepared from daily precipitation data recorded by Indian Meteorological Department (IMD), distributed within the study area. With the aid of frequent MODIS products viz. vegetation indices (VIs), and land surface temperature (LST), the coarse resolution soil moisture product from European Space Agency (ESA) were downscaled using linking model based on Triangle method to a finer resolution soil moisture product. EDI and spatially downscaled soil moisture products were later used with MODIS 16 days NDVI product as key elements to assess and predict agricultural drought in irrigated and rain-fed agricultural systems in Bundelkhand region of India. Meteorological drought, soil moisture deficiency and NDVI degradation were inhabited for each and every pixel of the image in GIS environment, for agricultural impact assessment at a 16 day temporal scale for Rabi seasons (October-April) between years 2000 to 2009. Based on the statistical analysis, good correlations were found among the parameters EDI and soil moisture anomaly; NDVI anomaly and soil moisture anomaly lagged to 16 days and these results were exploited for the development of a linear prediction model. The predictive capability of the developed model was validated on the basis of spatial distribution of predicted NDVI which was compared with MODIS NDVI product in the beginning of preceding Rabi season (Oct-Dec of 2010).The predictions of the model were based on future meteorological data (year 2010) and were found to be yielding good results. The developed model have good predictive capability based on future meteorological data (rainfall data) availability, which enhances its utility in analyzing future Agricultural conditions if meteorological data is available.
NASA Astrophysics Data System (ADS)
Septiadi, Deni; S, Yarianto Sugeng B.; Sriyana; Anzhar, Kurnia; Suntoko, Hadi
2018-03-01
The potential sources of meteorological phenomena in Nuclear Power Plant (NPP) area of interest are identified and the extreme values of the possible resulting hazards associated which such phenomena are evaluated to derive the appropriate design bases for the NPP. The appropriate design bases shall be determined according to the Nuclear Energy Regulatory Agency (Bapeten) applicable regulations, which presently do not indicate quantitative criteria for purposes of determining the design bases for meteorological hazards. These meteorological investigations are also carried out to evaluate the regional and site specific meteorological parameters which affect the transport and dispersion of radioactive effluents on the environment of the region around the NPP site. The meteorological hazards are to be monitored and assessed periodically over the lifetime of the plant to ensure that consistency with the design assumptions is maintained throughout the full lifetime of the facility.
Space Shuttle Pad Exposure Period Meteorological Parameters STS-1 Through STS-107
NASA Technical Reports Server (NTRS)
Overbey, B. G.; Roberts, B. C.
2005-01-01
During the 113 missions of the Space Transportation System (STS) to date, the Space Shuttle fleet has been exposed to the elements on the launch pad for approx. 4,195 days. The Natural Environments Branch at Marshall Space Flight Center archives atmospheric environments to which the Space Shuttle vehicles are exposed. This Technical Memorandum (TM) provides a summary of the historical record of the meteorological conditions encountered by the Space Shuttle fleet during the pad exposure period. Parameters included in this TM are temperature, relative humidity, wind speed, wind direction, sea level pressure, and precipitation. Extremes for each of these parameters for each mission are also summarized. Sources for the data include meteorological towers and hourly surface observations. Data are provided from the first launch of the STS in 1981 through the launch of STS-107 in 2003.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Espinar, B.; Blanc, P.; Wald, L.; Hoyer-Klick, C.; Schroedter-Homscheidt, M.; Wanderer, T.
2012-04-01
Meteorological data measured by ground stations are often a key element in the development and validation of methods exploiting satellite images. These data are considered as a reference against which satellite-derived estimates are compared. Long-term radiation and meteorological measurements are available from a large number of measuring stations. However, close examination of the data often reveals a lack of quality, often for extended periods of time. This lack of quality has been the reason, in many cases, of the rejection of large amount of available data. The quality data must be checked before their use in order to guarantee the inputs for the methods used in modelling, monitoring, forecast, etc. To control their quality, data should be submitted to several conditions or tests. After this checking, data that are not flagged by any of the test is released as a plausible data. In this work, it has been performed a bibliographical research of quality control tests for the common meteorological variables (ambient temperature, relative humidity and wind speed) and for the usual solar radiometrical variables (horizontal global and diffuse components of the solar radiation and the beam normal component). The different tests have been grouped according to the variable and the average time period (sub-hourly, hourly, daily and monthly averages). The quality test may be classified as follows: • Range checks: test that verify values are within a specific range. There are two types of range checks, those based on extrema and those based on rare observations. • Step check: test aimed at detecting unrealistic jumps or stagnation in the time series. • Consistency checks: test that verify the relationship between two or more time series. The gathered quality tests are applicable for all latitudes as they have not been optimized regionally nor seasonably with the aim of being generic. They have been applied to ground measurements in several geographic locations, what result in the detection of some control tests that are no longer adequate, due to different reasons. After the modification of some test, based in our experience, a set of quality control tests is now presented, updated according to technology advances and classified. The presented set of quality tests allows radiation and meteorological data to be tested in order to know their plausibility to be used as inputs in theoretical or empirical methods for scientific research. The research leading to those results has partly receive funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under Grant Agreement no. 262892 (ENDORSE project).
Spatial interpolation of solar global radiation
NASA Astrophysics Data System (ADS)
Lussana, C.; Uboldi, F.; Antoniazzi, C.
2010-09-01
Solar global radiation is defined as the radiant flux incident onto an area element of the terrestrial surface. Its direct knowledge plays a crucial role in many applications, from agrometeorology to environmental meteorology. The ARPA Lombardia's meteorological network includes about one hundred of pyranometers, mostly distributed in the southern part of the Alps and in the centre of the Po Plain. A statistical interpolation method based on an implementation of the Optimal Interpolation is applied to the hourly average of the solar global radiation observations measured by the ARPA Lombardia's network. The background field is obtained using SMARTS (The Simple Model of the Atmospheric Radiative Transfer of Sunshine, Gueymard, 2001). The model is initialised by assuming clear sky conditions and it takes into account the solar position and orography related effects (shade and reflection). The interpolation of pyranometric observations introduces in the analysis fields information about cloud presence and influence. A particular effort is devoted to prevent observations affected by large errors of different kinds (representativity errors, systematic errors, gross errors) from entering the analysis procedure. The inclusion of direct cloud information from satellite observations is also planned.
Jiang, Peng-Hui; Zhao, Rui-Feng; Zhao, Hai-Li; Lu, Li-Peng; Xie, Zuo-Lun
2013-06-01
Based on the 1975-2010 multi-temporal remotely sensed TM and ETM images and meteorological data, in combining with wavelet analysis, trend surface simulation, and interpolation method, this paper analyzed the meteorological elements' spatial distribution and change characteristics in the middle reaches of Heihe River, and elucidated the process of wetland landscape fragmentation in the study area by using the landscape indices patch density (PD), mean patch size (MPS), and patch shape fragment index (FS). The relationships between the wetland landscape fragmentation and climate change were also approached through correlation analysis and multiple stepwise regression analysis. In 1975-2010, the overall distribution patterns of precipitation and temperature in the study area were low precipitation in high temperature regions and high precipitation in low temperature regions, and the main characteristics of climate change were the conversion from dry to wet and from cold to warm. In the whole study period, the wetland landscape fragmentation was mainly manifested in the decrease of MPS, with a decrement of 48.95 hm2, and the increase of PD, with an increment of 0.006 ind x hm(-2).
NASA Technical Reports Server (NTRS)
Lambert, Winifred C.
2003-01-01
This report describes the results from Phase II of the AMU's Short-Range Statistical Forecasting task for peak winds at the Shuttle Landing Facility (SLF). The peak wind speeds are an important forecast element for the Space Shuttle and Expendable Launch Vehicle programs. The 45th Weather Squadron and the Spaceflight Meteorology Group indicate that peak winds are challenging to forecast. The Applied Meteorology Unit was tasked to develop tools that aid in short-range forecasts of peak winds at tower sites of operational interest. A seven year record of wind tower data was used in the analysis. Hourly and directional climatologies by tower and month were developed to determine the seasonal behavior of the average and peak winds. Probability density functions (PDF) of peak wind speed were calculated to determine the distribution of peak speed with average speed. These provide forecasters with a means of determining the probability of meeting or exceeding a certain peak wind given an observed or forecast average speed. A PC-based Graphical User Interface (GUI) tool was created to display the data quickly.
The use of a laser ceilometer for sky condition determination
NASA Astrophysics Data System (ADS)
Nadolski, Vickie L.; Bradley, James T.
The use of a laser ceilometer for determining sky condition is presented, with emphasis on the operation of the ceilometer, the sky-condition-reporting algorithm, and how the laser ceilometer and the sky-condition algorithm are used to give a report suitable for aircraft operations and meteorological application. The sampling and processing features of the Vaisala ceilometer produced a detailed and accurate cloud base 'signature' by taking 254 measurement samples of the energy scattered back from a single laser pulse as the pulse traveled from the surface to 12,000 ft. The transmit time from the projection of the laser pulse to its backscattering from a cloud element and subsequent return to a collocated receiver is measured and a cloud height element computed. Attention is given to the development of a vertical visibility concept and of a vertical-visibility algorithm, as well as the strengths and limitations of the sky condition report.
NASA Astrophysics Data System (ADS)
Chen, Bing; Stein, Ariel F.; Maldonado, Pabla Guerrero; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Castell, Nuria; de la Rosa, Jesus D.
2013-06-01
This study presents a description of the emission, transport, dispersion, and deposition of heavy metals contained in atmospheric aerosols emitted from a large industrial complex in southern Spain using the HYSPLIT model coupled with high- (MM5) and low-resolution (GDAS) meteorological simulations. The dispersion model was configured to simulate eight size fractions (<0.33, 0.66, 1.3, 2.5, 5, 14, 17, and >17 μm) of metals based on direct measurements taken at the industrial emission stacks. Twelve stacks in four plants were studied and the stacks showed considerable differences for both emission fluxes and size ranges of metals. We model the dispersion of six major metals; Cr, Co, Ni, La, Zn, and Mo, which represent 77% of the total mass of the 43 measured elements. The prediction shows that the modeled industrial emissions produce an enrichment of heavy metals by a factor of 2-5 for local receptor sites when compared to urban and rural background areas in Spain. The HYSPLIT predictions based on the meteorological fields from MM5 show reasonable consistence with the temporal evolution of concentrations of Cr, Co, and Ni observed at three sites downwind of the industrial area. The magnitude of concentrations of metals at two receptors was underestimated for both MM5 (by a factor of 2-3) and GDAS (by a factor of 4-5) meteorological runs. The model prediction shows that heavy metal pollution from industrial emissions in this area is dominated by the ultra-fine (<0.66 μm) and fine (<2.5 μm) size fractions.
Rewilding as nature based solution in land management
NASA Astrophysics Data System (ADS)
Novara, Agata; Gristina, Luciano; Keesstra, Saskia; Pereira, Paulo; Cerda, Artemio
2017-04-01
Rewilding is an effective tool of ecological restoration and a nature based solution for hydro-meteorological risk control. Rewilding contributes to reduce flood risk, resist droughts, helps to restore soil organic matter content, increases soil and plant biodiversity, improves the overall ecosystem and human health. The key element of rewilding is not the nature control, but following the natural processes to restore the key soil ecological factors and their connectivity. Rewilding can be applicable at different ecosystem stages, from natural reserve to more anthropogenic system such as agricultural land through the restoration of wild soil function trough permaculture or forest farming. The proposed nature based solution not only avoid the investment in traditional engineering but it also an opportunities for creating new economics model based on wild nature (ecoturism, education, wild edible plants). This work is a review of applied rewilding actions and considerations on future nature based solutions applications will be discussed .
NASA Technical Reports Server (NTRS)
King, R. B.; Fordyce, J. S.; Antoine, A. C.; Leibecki, H. F.; Neustadter, H. E.; Sidik, S. M.; Burr, J. C.; Craig, G. T.; Cornett, C. L.
1974-01-01
Preliminary review of a study of trace elements and compound concentrations in the ambient suspended particulate matter in Cleveland, Ohio, measured from August 1971 through June 1973, as a function of source, monitoring location, and meteorological conditions. The study is aimed at the development of techniques for identifying specific pollution sources which could be integrated into a practical system readily usable by an enforcement agency.
High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of ...
Meteorological Processes Affecting Air Quality – Research and Model Development Needs
Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...
Zhang, Hai Ping; Li, Feng Ri; Dong, Li Hu; Liu, Qiang
2017-06-18
Based on the 212 re-measured permanent plots for natural Betula platyphylla fore-sts in Daxing'an Mountains and Xiaoxing'an Mountains and 30 meteorological stations data, an individual tree growth model based on meteorological factors was constructed. The differences of stand and meteorological factors between Daxing'an Mountains and Xiaoxing'an Mountains were analyzed and the diameter increment model including the regional effects was developed by dummy variable approach. The results showed that the minimum temperature (T g min ) and mean precipitation (P g m ) in growing season were the main meteorological factors which affected the diameter increment in the two study areas. T g min and P g m were positively correlated with the diameter increment, but the influence strength of T g min was obviously different between the two research areas. The adjusted coefficient of determination (R a 2 ) of the diameter increment model with meteorological factors was 0.56 and had an 11% increase compared to the one without meteorological factors. It was concluded that meteorological factors could well explain the diameter increment of B. platyphylla. R a 2 of the model with regional effects was 0.59, and increased by 18% compared to the one without regional effects, and effectively solved the incompatible problem of parameters between the two research areas. The validation results showed that the individual tree diameter growth model with regional effect had the best prediction accuracy in estimating the diameter increment of B. platyphylla. The mean error, mean absolute error, mean error percent and mean prediction error percent were 0.0086, 0.4476, 5.8% and 20.0%, respectively. Overall, dummy variable model of individual tree diameter increment based on meteorological factors could well describe the diameter increment process of natural B. platyphylla in Daxing'an Mountains and Xiaoxing'an Mountains.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Powell, Thomas; Kueppers, Lara; Paton, Steve
This dataset is a derivative product of raw meteorological data collected at Barro Colorado Island, Panama (see acknowledgements below). This dataset contains the following: 1) a seven-year record (2008-2014) of meteorological observations from BCI that is in a comma delimited text format, 2) an R-script that converts the observed meteorology into an hdf5 format that can be read by the ED2 model, 3) two decades of meteorological drivers in hdf5 format that are based on the 7-year record of observations and include a synthetic 2-yr El Nino drought, 4) a ReadMe.txt file that explains how the data in the hdf5more » meteorological drivers correspond to the observations. The raw meteorological data were further QC'd as part of the NGEE-Tropics project to derive item 1 above. The R-script makes the appropriate unit conversions for all observed meteorological variables to be compatible with the ED2 model. The R-script also converts RH into specific humidity, splits total shortwave radiation into its 4-stream parts, and calculates longwave radiation from air temperature and RH. The synthetic El Nino drought is based on selected months from the observed meteorology where in each, precipitation (only) of the selected months was modified to reflect the precipitation patterns of the 1982/83 El Nino observed at BCI.« less
NASA Astrophysics Data System (ADS)
Deng, T.; Chen, Y.; Wan, Q.
2017-12-01
The Community Multiscale Air Quality (CMAQ) model was utilized for forecasting air quality over the Pearl River Delta (PRD) region from December 2013 to January 2014. The pollution forecasting performance of CMAQ coupled with the two different meteorological models, the Global/Regional Assimilation and Prediction System (GRAPES) and the 5th-generation Mesoscale Model (MM5), was assessed by combining observational data. The effect of meteorological factors and physical-chemical processes on forecast results was discussed through process analysis. The results showed that both models have similar good performance with better performance by GRAPES-CMAQ. GRAPES was superior in predicting the overall meteorological element variation tendencies but showed large deviations in atmospheric pressure and wind speed. It contributed to higher correlation coefficients of the pollutants with GRAPES-CMAQ, but with greater deviation. The underestimations of nitrate and ammonium salt contributed to the underestimations of Particle Matter (PM) and extinction coefficients. Surface layer SO2, CO and NO source emissions made the sole positive contribution. O3 originated mainly from horizontal and vertical transport and chemical processes were the main consumption item. On the contrary, NO2 derived mainly from chemical production.
Ozone process insights from field experiments - part I: overview
NASA Astrophysics Data System (ADS)
Hidy, G. M.
This paper gives an overview of selected approaches recently adopted to analyze observations from field experiments that characterize the tropospheric physics and chemistry of ozone and related oxidation products. Analysis of ambient oxidant and precursor concentration measurements, combined with meteorological observations, has provided important information about tropospheric processes. Projection of the response of tropospheric ozone concentrations to changes in precursor emissions is achieved through emissions based air quality models (AQMs). These models integrate several "process" elements from source emissions to meteorological and chemical phenomena. Through field campaigns, new knowledge has become available which has enabled workers to better understand the strengths and weaknesses of AQMs and their components. Examples of insightful results include: (a) reconciliation of ambient concentrations of speciated volatile organic compounds (VOCs) with estimates from emissions models, and inventories, (b) verification of chemical mechanisms for ozone formation from its precursors using approximations applicable in different chemical regimes, (c) inference of regimes of sensitivity in ozone concentration to changes in VOC and NO x precursors from ozone management practices, (d) conceptualization of important air mass transport and mixing processes on different spatial and temporal scales that affect ozone and precursor concentrations distributions, and (e) application of the analysis of spatial and temporal variance to infer the origins of chemical product transport, and precursor distributions. Studies from the first category have been used to improve emissions models substantially over previous forms. The remainder of the analyses has yielded valuable insight into the chemical and meteorological mechanisms at work on different spatial and temporal scales. The methods have provided an observationally based framework for effective choices to improve ozone management, notably in terms of NO x or VOC sensitive regimes. Investigation of meteorological processes relevant to ozone accumulation has illustrated the importance of accounting for both transport winds and the day-night vertical structure of the atmosphere in AQM analyses. Finally, variance analyses of O 3 concentrations with other aerometric parameters offer significant opportunities to use semi-empirically air monitoring data as a means determining space and time scales of O 3 variance, and detecting precursor emissions source-ozone receptor relationships.
NASA Astrophysics Data System (ADS)
Liang, Pengfei; Zhu, Tong; Fang, Yanhua; Li, Yingruo; Han, Yiqun; Wu, Yusheng; Hu, Min; Wang, Junxia
2017-11-01
To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.
THE VALUE OF NUDGING IN THE METEOROLOGY MODEL FOR RETROSPECTIVE CMAQ SIMULATIONS
Using a nudging-based data assimilation approach throughout a meteorology simulation (i.e., as a "dynamic analysis") is considered valuable because it can provide a better overall representation of the meteorology than a pure forecast. Dynamic analysis is often used in...
Yu, Xiaobing; Yu, Xianrui; Lu, Yiqun
2018-01-01
The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which includes the disaster rate, the inundated rate, and the complete loss rate. Following this, the relative weights of the three criteria are acquired using a novel proposed evolutionary algorithm. The proposed algorithm consists of a differential evolution algorithm and an evolution strategy. Finally, a novel evaluation model, based on the proposed algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is presented to estimate the agricultural meteorological disaster of 2008 in China. The geographic information system (GIS) technique is employed to depict the disaster. The experimental results demonstrated that the agricultural meteorological disaster of 2008 was very serious, especially in Hunan and Hubei provinces. Some useful suggestions are provided to relieve agriculture meteorological disasters. PMID:29597243
NASA Astrophysics Data System (ADS)
Okumura, Hiroshi; Takubo, Shoichiro; Kawasaki, Takeru; Abdullah, Indra Nugraha; Uchino, Osamu; Morino, Isamu; Yokota, Tatsuya; Nagai, Tomohiro; Sakai, Tetsu; Maki, Takashi; Arai, Kohei
2013-01-01
A web-base data acquisition and management system for GOSAT (Greenhouse gases Observation SATellite) validation lidar data-analysis has been developed. The system consists of data acquisition sub-system (DAS) and data management sub-system (DMS). DAS written in Perl language acquires AMeDAS (Automated Meteorological Data Acquisition System) ground-level local meteorological data, GPS Radiosonde upper-air meteorological data, ground-level oxidant data, skyradiometer data, skyview camera images, meteorological satellite IR image data and GOSAT validation lidar data. DMS written in PHP language demonstrates satellite-pass date and all acquired data. In this article, we briefly describe some improvement for higher performance and higher data usability. GPS Radiosonde upper-air meteorological data and U.S. standard atmospheric model in DAS automatically calculate molecule number density profiles. Predicted ozone density prole images above Saga city are also calculated by using Meteorological Research Institute (MRI) chemistry-climate model version 2 for comparison to actual ozone DIAL data.
Ma, Shi-Lei; Tang, Qiao-Ling; Liu, Hong-Wei; He, Juan; Gao, Si-Hua
2013-03-01
To explore the impact of meteorological factors on the outbreak of bacillary dysentery, so as to provide suggestions for disease prevention. Based on the Chinese medicine theory of Yunqi, the descriptive statistics, single-factor correlation analysis and back-propagation artificial neural net-work were conducted using data on five basic meteorological factors and data on incidence of bacillary dysentery in Beijing, China, for the period 1970-2004. The incidence of bacillary dysentery showed significant positive correlation relationship with the precipitation, relative humidity, vapor pressure, and temperature, respectively. The incidence of bacillary dysentery showed a negatively correlated relationship with the wind speed and the change trend of average wind speed. The results of medical-meteorological forecast model showed a relatively high accuracy rate. There is a close relationship between the meteorological factors and the incidence of bacillary dysentery, but the contributions of which to the onset of bacillary dysentery are different to each other.
Wu, Xianhua; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian
2014-01-01
Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries. PMID:24578666
Wu, Xianhua; Wei, Guo; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian
2014-01-01
Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.
WRF-based fire risk modelling and evaluation for years 2010 and 2012 in Poland
NASA Astrophysics Data System (ADS)
Stec, Magdalena; Szymanowski, Mariusz; Kryza, Maciej
2016-04-01
Wildfires are one of the main ecosystems' disturbances for forested, seminatural and agricultural areas. They generate significant economic loss, especially in forest management and agriculture. Forest fire risk modeling is therefore essential e.g. for forestry administration. In August 2015 a new method of forest fire risk forecasting entered into force in Poland. The method allows to predict a fire risk level in a 4-degree scale (0 - no risk, 3 - highest risk) and consists of a set of linearized regression equations. Meteorological information is used as predictors in regression equations, with air temperature, relative humidity, average wind speed, cloudiness and rainfall. The equations include also pine litter humidity as a measure of potential fuel characteristics. All these parameters are measured routinely in Poland at 42 basic and 94 auxiliary sites. The fire risk level is estimated for a current (basing on morning measurements) or next day (basing on midday measurements). Entire country is divided into 42 prognostic zones, and fire risk level for each zone is taken from the closest measuring site. The first goal of this work is to assess if the measurements needed for fire risk forecasting may be replaced by the data from mesoscale meteorological model. Additionally, the use of a meteorological model would allow to take into account much more realistic spatial differentiation of weather elements determining the fire risk level instead of discrete point-made measurements. Meteorological data have been calculated using the Weather Research and Forecasting model (WRF). For the purpose of this study the WRF model is run in the reanalysis mode allowing to estimate all required meteorological data in a 5-kilometers grid. The only parameter that cannot be directly calculated using WRF is the litter humidity, which has been estimated using empirical formula developed by Sakowska (2007). The experiments are carried out for two selected years: 2010 and 2012. The year 2010 was characterized by the smallest number of wildfires and burnt area whereas 2012 - by the biggest number of fires and the largest area of conflagration. The data about time, localization, scale and causes of individual wildfire occurrence in given years are taken from the National Forest Fire Information System (KSIPL), administered by Forest Fire Protection Department of Polish Forest Research Institute. The database is a part of European Forest Fire Information System (EFFIS). Basing on this data and on the WRF-based fire risk modelling we intend to achieve the second goal of the study, which is the evaluation of the forecasted fire risk with an occurrence of wildfires. Special attention is paid here to the number, time and the spatial distribution of wildfires occurred in cases of low-level predicted fire risk. Results obtained reveals the effectiveness of the new forecasting method. The outcome of our investigation allows to draw a conclusion that some adjustments are possible to improve the efficiency on the fire-risk estimation method.
Characterisation of particulate exposure during fireworks displays
NASA Astrophysics Data System (ADS)
Joly, Alexandre; Smargiassi, Audrey; Kosatsky, Tom; Fournier, Michel; Dabek-Zlotorzynska, Ewa; Celo, Valbona; Mathieu, David; Servranckx, René; D'amours, Réal; Malo, Alain; Brook, Jeffrey
2010-11-01
Little is known about the level and content of exposure to fine particles (PM 2.5) among persons who attend fireworks displays and those who live nearby. An evaluation of the levels of PM 2.5 and their elemental content was carried out during the nine launches of the 2007 Montréal International Fireworks Competition. For each event, a prediction of the location of the firework plume was obtained from the Canadian Meteorological Centre (CMC) of the Meteorological Service of Canada. PM 2.5 was measured continuously with a photometer (Sidepak™, TSI) within the predicted plume location ("predicted sites"), and integrated samples were collected using portable personal samplers. An additional sampler was located on a nearby roof ("fixed site"). The elemental composition of the collected PM 2.5 samples from the "predicted sites" was determined using both a non-destructive energy dispersive ED-XRF method and an ICP-MS method with a near-total microwave-assisted acid digestion. The elemental composition of the "fixed site" samples was determined by the ICP-MS with the near-total digestion method. The highest PM 2.5 levels reached nearly 10 000 μg m -3, roughly 1000 times background levels. Elements such as K, Cl, Al, Mg and Ti were markedly higher in plume-exposed filters. This study shows that 1) persons in the plume and in close proximity to the launch site may be exposed to extremely high levels of PM 2.5 for the duration of the display and, 2) that the plume contains specific elements for which little is known of their acute cardio-respiratory toxicity.
Problem-Based Learning Approaches in Meteorology
ERIC Educational Resources Information Center
Charlton-Perez, Andrew James
2013-01-01
Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a…
Drought Dynamics and Food Security in Ukraine
NASA Astrophysics Data System (ADS)
Kussul, N. M.; Kogan, F.; Adamenko, T. I.; Skakun, S. V.; Kravchenko, O. M.; Kryvobok, O. A.; Shelestov, A. Y.; Kolotii, A. V.; Kussul, O. M.; Lavrenyuk, A. M.
2012-12-01
In recent years food security became a problem of great importance at global, national and regional scale. Ukraine is one of the most developed agriculture countries and one of the biggest crop producers in the world. According to the 2011 statistics provided by the USDA FAS, Ukraine was the 8th largest exporter and 10th largest producer of wheat in the world. Therefore, identifying current and projecting future trends in climate and agriculture parameters is a key element in providing support to policy makers in food security. This paper combines remote sensing, meteorological, and modeling data to investigate dynamics of extreme events, such as droughts, and its impact on agriculture production in Ukraine. Two main problems have been considered in the study: investigation of drought dynamics in Ukraine and its impact on crop production; and investigation of crop growth models for yield and production forecasting and its comparison with empirical models that use as a predictor satellite-derived parameters and meteorological observations. Large-scale weather disasters in Ukraine such as drought were assessed using vegetation health index (VHI) derived from satellite data. The method is based on estimation of green canopy stress/no stress from indices, characterizing moisture and thermal conditions of vegetation canopy. These conditions are derived from the reflectance/emission in the red, near infrared and infrared parts of solar spectrum measured by the AVHRR flown on the NOAA afternoon polar-orbiting satellites since 1981. Droughts were categorized into exceptional, extreme, severe and moderate. Drought area (DA, in % from total Ukrainian area) was calculated for each category. It was found that maximum DA over past 20 years was 10% for exceptional droughts, 20% for extreme droughts, 50% for severe droughts, and 80% for moderate droughts. Also, it was shown that in general the drought intensity and area did not increase considerably over past 10 years. Analysis of interrelation between DA of different categories at oblast level with agriculture production will be discussed as well. A comparative study was carried out to assess three approaches to forecast winter wheat yield in Ukraine at oblast level: (i) empirical regression-based model that uses as a predictor 16-day NDVI composites derived from MODIS at the 250 m resolution, (ii) empirical regression-based model that uses as predictors meteorological parameters, and (iii) adapted for Ukraine Crop Growth Monitoring System (CGMS) that is based on WOFOST crop growth simulation model and meteorological parameters. These three approaches were calibrated for 2000-2009 and 2000-2010 data, and compared while performing forecasts on independent data for 2010 and 2011. For 2010, the best results in terms of root mean square error (RMSE, by oblast, deviation of predicted values from official statistics) were achieved using CGMS models: 0.3 t/ha. For NDVI and meteorological models RMSE values were 0.79 and 0.77 t/ha, respectively. When forecasting winter wheat yield for 2011, the following RMSE values were obtained: 0.58 t/ha for CGMS, 0.56 t/ha for meteorological model, and 0.62 t/ha for NDVI. In this case performance of all three approaches was relatively the same. Acknowledgements. This work was supported by the U.S. CRDF Grant "Analysis of climate change & food security based on remote sensing & in situ data sets" (UKB2-2972-KV-09).
The influence of weather on migraine – are migraine attacks predictable?
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
NASA Astrophysics Data System (ADS)
Sorooshian, Armin; Wonaschütz, Anna; Jarjour, Elias G.; Hashimoto, Bryce I.; Schichtel, Bret A.; Betterton, Eric A.
2011-10-01
This study reports a comprehensive characterization of atmospheric aerosol particle properties in relation to meteorological and back trajectory data in the southern Arizona region, which includes two of the fastest growing metropolitan areas in the United States (Phoenix and Tucson). Multiple data sets (MODIS, AERONET, OMI/TOMS, MISR, GOCART, ground-based aerosol measurements) are used to examine monthly trends in aerosol composition, aerosol optical depth (AOD), and aerosol size. Fine soil, sulfate, and organics dominate PM2.5 mass in the region. Dust strongly influences the region between March and July owing to the dry and hot meteorological conditions and back trajectory patterns. Because monsoon precipitation begins typically in July, dust levels decrease, while AOD, sulfate, and organic aerosol reach their maximum levels because of summertime photochemistry and monsoon moisture. Evidence points to biogenic volatile organic compounds being a significant source of secondary organic aerosol in this region. Biomass burning also is shown to be a major contributor to the carbonaceous aerosol budget in the region, leading to enhanced organic and elemental carbon levels aloft at a sky-island site north of Tucson (Mt. Lemmon). Phoenix exhibits different monthly trends for aerosol components in comparison with the other sites owing to the strong influence of fossil carbon and anthropogenic dust. Trend analyses between 1988 and 2009 indicate that the strongest statistically significant trends are reductions in sulfate, elemental carbon, and organic carbon, and increases in fine soil during the spring (March-May) at select sites. These results can be explained by population growth, land-use changes, and improved source controls.
NASA Astrophysics Data System (ADS)
Matyasovszky, István; Makra, László; Csépe, Zoltán; Sümeghy, Zoltán; Deák, Áron József; Pál-Molnár, Elemér; Tusnády, Gábor
2015-10-01
After extreme dry (wet) summers or years, pollen production of different taxa may decrease (increase) substantially. Accordingly, studying effects of current and past meteorological conditions on current pollen concentrations for different taxa have of major importance. The purpose of this study is separating the weight of current and past weather conditions influencing current pollen productions of three taxa. Two procedures, namely multiple correlations and factor analysis with special transformation are used. The 11-year (1997-2007) data sets include daily pollen counts of Ambrosia (ragweed), Poaceae (grasses) and Populus (poplar), as well as daily values of four climate variables (temperature, relative humidity, global solar flux and precipitation). Multiple correlations of daily pollen counts with simultaneous values of daily meteorological variables do not show annual course for Ambrosia, but do show definite trends for Populus and Poaceae. Results received using the two methods revealed characteristic similarities. For all the three taxa, the continental rainfall peak and additional local showers in the growing season can strengthen the weight of the current meteorological elements. However, due to the precipitation, big amount of water can be stored in the soil contributing to the effect of the past climate elements during dry periods. Higher climate sensitivity (especially water sensitivity) of the herbaceous taxa ( Ambrosia and Poaceae) can be definitely established compared to the arboreal Populus. Separation of the weight of the current and past weather conditions for different taxa involves practical importance both for health care and agricultural production.
A new method for determining water uptake in elderberry plantation
NASA Astrophysics Data System (ADS)
Tőkei, László; Dunkel, Zoltán; Jung, András
A considerable quantity of elderberry ( Sambucus nigra L.) fruit gets yearly on the market in Hungary. The decisive majority of this quantity is harvested from feral plants. The area of elderberry plantations is only 150-180 ha in spite of the fact that it would be possible to produce this valuable fruit on larger surface if suitable watering system were applied. The fruit of elderberry is important from the aspect of food industry. The goal of present study is promoting the effective irrigation of elder berry plantation. The experiments were carried out in the Experimental Farm of the University for Horticulture and Food Industry in Szigetcsép from 1989. The measuring of the water demand of elderberry using the heat pulse method was started in 1996. The measurement of the sap-flow in the trunk is a new element of phyto-climate researches. The development of the equipment was started in 1991 and improvement of the method is still going on. In this phase, first of all the connections between sap-flow velocity and meteorological data were investigated. Summarising the experiences of the trials it can be announced that: (1) The water circulation of elder plants principally depends on the conditions of atmosphere. It is barely sensitive to the water content of the soil. (2) The transpiration intensity reacts sensitively to the change of meteorological conditions. (3) The changing rate of the transpiration coefficient is particularly large in certain intervals of the meteorological elements.
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.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Wen, X.
2017-12-01
The Yellow River source region is situated in the northeast Tibetan Plateau, which is considered as a global climate change hot-spot and one of the most sensitive areas in terms of response to global warming in view of its fragile ecosystem. This region plays an irreplaceable role for downstream water supply of The Yellow River because of its unique topography and variable climate. The water energy cycle processes of the Yellow River source Region from July to September in 2015 were simulated by using the WRF mesoscale numerical model. The two groups respectively used Noah and CLM4 parameterization schemes of land surface process. Based on the observation data of GLDAS data set, ground automatic weather station and Zoige plateau wetland ecosystem research station, the simulated values of near surface meteorological elements and surface energy parameters of two different schemes were compared. The results showed that the daily variations about meteorological factors in Zoige station in September were simulated quite well by the model. The correlation coefficient between the simulated temperature and humidity of the CLM scheme were 0.88 and 0.83, the RMSE were 1.94 ° and 9.97%, and the deviation Bias were 0.04 ° and 3.30%, which was closer to the observation data than the Noah scheme. The correlation coefficients of net radiation, surface heat flux, upward short wave and upward longwave radiation were respectively 0.86, 0.81, 0.84 and 0.88, which corresponded better than the observation data. The sensible heat flux and latent heat flux distribution of the Noah scheme corresponded quite well to GLDAS. the distribution and magnitude of 2m relative humidity and soil moisture were closer to surface observation data because the CLM scheme described the photosynthesis and evapotranspiration of land surface vegetation more rationally. The simulating abilities of precipitation and downward longwave radiation need to be improved. This study provides a theoretical basis for the numerical simulation of water energy cycle in the source region over the Yellow River basin.
Seismic Monitoring of Stability of Unique Historical Buildings in the Czech Republic
NASA Astrophysics Data System (ADS)
Broz, M.; Strunc, J.; Buben, J.
2008-05-01
The persistence of unique Historical Buildings is restricted due to weathering of construction material enhanced by meteorological processes such as storms, driving rain and temperature variations beneath the freezing point. Dynamic forces endangering the mechanical stability of exposed elements of building structures could be caused also by impacts of seismic waves. The long-time decrease of earthquake resistance is monitored using empirical functions of seismic response. This method is based on evaluation the co-spectra of exciting and forced vibrations of foundations and the structure elements in question. This poster notifies three examples of utilization of this method as follows: 1) In the course of renovating the St. Barbora temple in the Kutná Hora village, the vibrations caused by meteorological processes, supersonic aircraft transit and blasting in quarries have been evaluated. After completing the renovation of endangered spire elements, the local maximum of co-spectral function at 4Hz was shifted to 7Hz and the function approached more likely a wide-band course. 2) In the course of installation of the third bell in the bell tower of the of the Sázava monastery, the co-spectra of forced vibrations of tower walls were monitored and a more convenient time-function of bell clang was adjusted. 3) In connection with the construction of a highway tunnel in the 1,4 km distance from the St. Vit cathedral in the Praha-Hradèany castle, the long-term schedule of motoring seismic vibrations was started. In the course of driving the tunnels, the mili-sec blasting of charges up to 5 kg is used. Seismic vibrations are recorded by pickups situated on the subsoil and on the voussoir arch. The digital multichannel seismic recording apparatus (256 samples per sec) is equipped for continuous telemetric data transfer and automated evaluation. (Grant Foundation of the Czech Republic, 103/07/1522).
Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding
2010-05-01
Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.
Tunick, Arnold
2003-10-01
A key element in determining point-to-point acoustic transmission within and above forests is modeling the variation (with height above ground) of the effective speed of sound. Effective speed of sound is readily derived from estimates of air temperature, relative humidity, and wind velocity. However, meteorological models for the forest canopy vary from comparatively simple to academically complex, requiring different amounts and numbers of inputs and computer capabilities. In addition, not all canopy profile models are suitable for acoustic applications. In this paper, a meteorological computer model for the forest canopy is developed to derive continuous profiles of effective sound speed from the ground to 3 h, where h is the height of the canopy. In turn, these profiles are used to make some initial approximations of short-range acoustic transmission loss through a uniform forest stand for typical clear sky, midday atmospheric conditions. Also, a radiative transfer and energy budget algorithm is incorporated into the model to obtain the appropriate heat source profile for any time of day. Thus, physics-based micrometeorology is coupled to acoustics for future applications of acoustic information in forest environments.
IDC Re-Engineering Phase 2 Iteration E2 Use Case Realizations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harris, James M.; Burns, John F.; Hamlet, Benjamin R.
2016-06-01
This architecturally significant use case describes how the System acquires meteorological data to build atmospheric models used in automatic and interactive processing of infrasound data. The System requests the latest available high-resolution global meteorological data from external data centers and puts it into the correct formats for generation of infrasound propagation models. The system moves the meteorological data from Data Acquisition Partition to the Data Processing Partition and stores the meteorological data. The System builds a new atmospheric model based on the meteorological data. This use case is architecturally significant because it describes acquiring meteorological data from various sources andmore » creating dynamic atmospheric transmission model to support the prediction of infrasonic signal detection« less
Uncertainties in key elements of emissions and meteorology inputs to air quality models (AQMs) can range from 50 to 100% with some areas of emissions uncertainty even higher (Russell and Dennis, 2000). Uncertainties in the chemical mechanisms are thought to be smaller (Russell an...
The NPOESS Preparatory Project Science Data Segment: Brief Overview
NASA Technical Reports Server (NTRS)
Schweiss, Robert J.; Ho, Evelyn; Ullman, Richard; Samadi, Shahin
2006-01-01
The NPOESS Preparatory Project (NPP) provides remotely-sensed land, ocean, atmospheric, ozone, and sounder data that will serve the meteorological and global climate change scientific communities while also providing risk reduction for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government s future low-Earth orbiting satellite system monitoring global weather and environmental conditions. NPOESS and NPP are a new era, not only because the sensors will provide unprecedented quality and volume of data but also because it is a joint mission of three federal agencies, NASA, NOAA, and DoD. NASA's primary science role in NPP is to independently assess the quality of the NPP science and environmental data records. Such assessment is critical for making NPOESS products the best that they can be for operational use and ultimately for climate studies. The Science Data Segment (SDS) supports science assessment by assuring the timely provision of NPP data to NASA s science teams organized by climate measurement themes. The SDS breaks down into nine major elements, an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. This paper will describe how the NPP SDS will leverage on NASA experience to provide a mission-reliable research capability for science assessment of NPP derived measurements.
Trace element distribution in the snow cover from an urban area in central Poland.
Siudek, Patrycja; Frankowski, Marcin; Siepak, Jerzy
2015-05-01
This work presents the first results from winter field campaigns focusing on trace metals and metalloid chemistry in the snow cover from an urbanized region in central Poland. Samples were collected between January and March 2013 and trace element concentrations were determined using GF-AAS. A large inter-seasonal variability depending on anthropogenic emission, depositional processes, and meteorological conditions was observed. The highest concentration (in μg L(-1)) was reported for Pb (34.90), followed by Ni (31.37), Zn (31.00), Cu (13.71), Cr (2.36), As (1.58), and Cd (0.25). In addition, several major anthropogenic sources were identified based on principal component analysis (PCA), among which the most significant was the activity of industry and coal combustion for residential heating. It was stated that elevated concentrations of some trace metals in snow samples were associated with frequent occurrence of south and southeast advection of highly polluted air masses toward the sampling site, suggesting a large impact of regional urban/industrial pollution plumes.
Research on Application of Automatic Weather Station Based on Internet of Things
NASA Astrophysics Data System (ADS)
Jianyun, Chen; Yunfan, Sun; Chunyan, Lin
2017-12-01
In this paper, the Internet of Things is briefly introduced, and then its application in the weather station is studied. A method of data acquisition and transmission based on NB-iot communication mode is proposed, Introduction of Internet of things technology, Sensor digital and independent power supply as the technical basis, In the construction of Automatic To realize the intelligent interconnection of the automatic weather station, and then to form an automatic weather station based on the Internet of things. A network structure of automatic weather station based on Internet of things technology is constructed to realize the independent operation of intelligent sensors and wireless data transmission. Research on networking data collection and dissemination of meteorological data, through the data platform for data analysis, the preliminary work of meteorological information publishing standards, networking of meteorological information receiving terminal provides the data interface, to the wisdom of the city, the wisdom of the purpose of the meteorological service.
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...
NASA Astrophysics Data System (ADS)
El Khattabi, El Mehdi; Mharzi, Mohamed; Raefat, Saad; Meghari, Zouhair
2018-05-01
In this paper, the thermal equivalence of the passive elements of a room in a building located in Fez-Morocco has been studied. The possibility of replacing them with a semi-passive element such as ventilation has been appraised. For this aim a Software in Fortran taking into account the meteorological external conditions along with different parameters of the building envelope has been performed. A new computational approach is adapted to determinate the temperature distribution throughout the building multilayer walls. A novel equation gathering the internal temperature with the external conditions, and the building envelope has been deduced in transient state.
Web-based data acquisition and management system for GOSAT validation Lidar data analysis
NASA Astrophysics Data System (ADS)
Okumura, Hiroshi; Takubo, Shoichiro; Kawasaki, Takeru; Abdullah, Indra N.; Uchino, Osamu; Morino, Isamu; Yokota, Tatsuya; Nagai, Tomohiro; Sakai, Tetsu; Maki, Takashi; Arai, Kohei
2012-11-01
An web-base data acquisition and management system for GOSAT (Greenhouse gases Observation SATellite) validation lidar data analysis is developed. The system consists of data acquisition sub-system (DAS) and data management sub-system (DMS). DAS written in Perl language acquires AMeDAS ground-level meteorological data, Rawinsonde upper-air meteorological data, ground-level oxidant data, skyradiometer data, skyview camera images, meteorological satellite IR image data and GOSAT validation lidar data. DMS written in PHP language demonstrates satellite-pass date and all acquired data.
NASA Astrophysics Data System (ADS)
Zhang, X. Y.; Wang, J. Z.; Wang, Y. Q.; Liu, H. L.; Sun, J. Y.; Zhang, Y. M.
2015-11-01
Since there have been individual reports of persistent haze-fog events in January 2013 in central-eastern China, questions on factors causing the drastic differences in changes in 2013 from changes in adjacent years have been raised. Changes in major chemical components of aerosol particles over the years also remain unclear. The extent of meteorological factors contributing to such changes is yet to be determined. The study intends to present the changes in daily based major water-soluble constituents, carbonaceous species, and mineral aerosol in PM10 at 13 stations within different haze regions in China from 2006 to 2013, which are associated with specific meteorological conditions that are highly related to aerosol pollution (parameterized as an index called Parameter Linking Aerosol Pollution and Meteorological Elements - PLAM). No obvious changes were found in annual mean concentrations of these various chemical components and PM10 in 2013, relative to 2012. By contrast, wintertime mass of these components was quite different. In Hua Bei Plain (HBP), sulfate, organic carbon (OC), nitrate, ammonium, element carbon (EC), and mineral dust concentrations in winter were approximately 43, 55, 28, 23, 21, and 130 μg m-3, respectively; these masses were approximately 2 to 4 times higher than those in background mass, which also exhibited a decline during 2006 to 2010 and then a rise till 2013. The mass of these concentrations and PM10, except minerals, respectively, increased by approximately 28 to 117 % and 25 % in January 2013 compared with that in January 2012. Thus, persistent haze-fog events occurred in January 2013, and approximately 60 % of this increase in component concentrations from 2012 to 2013 can be attributed to severe meteorological conditions in the winter of 2013. In the Yangtze River Delta (YRD) area, winter masses of these components, unlike HBP, have not significantly increase since 2010; PLAM were also maintained at a similar level without significant changes. In the Pearl River Delta (PRD) area, the regional background concentrations of the major chemical components were similar to those in the YRD, accounting for approximately 60-80 % of those in HBP. Since 2010, a decline has been found for winter concentrations, which can be partially attributable to persistently improving meteorological conditions and emission cutting with an emphasis on coal combustion in this area. In addition to the scattered and centralized coal combustion for heating, burning biomass fuels contributed to the large increase in concentrations of carbonaceous aerosol in major haze regions in winter, except in the PRD. No obvious changes were found for the proportions of each chemical components of PM10 from 2006 to 2013. Among all of the emissions recorded in chemical compositions in 2013, coal combustion was still the largest anthropogenic source of aerosol pollution in various areas in China, with a higher sulfate proportion of PM10 in most areas of China, and OC was normally ranked third. PM10 concentrations increased by approximately 25 % in January of 2013 relative to 2012, which caused persistent haze-fog events in HBP; emissions also reduced by approximately 35 % in Beijing and its vicinity (BIV) in late autumn of 2014, thereby producing the Asia Pacific Economic Cooperation (APEC) blue (extremely good air quality); thus, one can expect that the persistent haze-fog events would be reduced significantly in the BIV, if approx. one-third of the 2013 winter emissions were reduced, which can also be viewed as the upper limit of atmospheric aerosol pollution capacity in this area.
A Summary of Meteorological Parameters During Space Shuttle Pad Exposure Periods
NASA Technical Reports Server (NTRS)
Overbey, Glenn; Roberts, Barry C.
2005-01-01
During the 113 missions of the Space Transportation System (STS), the Space Shuffle fleet has been exposed to the elements on the launch pad for a total of 4195 days. The Natural Environments Branch at Marshall Space Flight Center archives atmospheric environments to which the Space Shuttle vehicles are exposed. This paper provides a summary of the historical record of the meteorological conditions encountered by the Space Shuttle fleet during the pad exposure period. Sources of the surface parameters, including temperature, dew point temperature, relative humidity, wind speed, wind direction, sea level pressure and precipitation are presented. Data is provided from the first launch of the STS in 1981 through the launch of STS-107 in 2003.
NASA Astrophysics Data System (ADS)
Papaspiropoulos, Giorgos; Martinsson, Bengt G.; Zahn, Andreas; Brenninkmeijer, Carl A. M.; Hermann, Markus; Heintzenberg, Jost; Fischer, Herbert; van Velthoven, Peter F. J.
2002-12-01
This study with the Civil Aircraft for Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) platform investigates the aerosol elemental concentrations at 9-11 km altitude in the northern hemisphere. Measurements from 31 intercontinental flights over a 2-year period between Germany and Sri Lanka/Maldives in the Indian Ocean are presented. Aerosol samples were collected with an impaction technique and were analyzed for the concentration of 18 elements using particle-induced X-ray emission (PIXE). Additional measurements of particle number concentrations, ozone and carbon monoxide concentrations, and meteorological modeling were included in the interpretation of the aerosol elemental concentrations. Particulate sulphur was found to be by far the most abundant element. Its upper tropospheric concentration increased, on average, by a factor of 2 from the tropics to midlatitudes, with another factor 2 higher concentrations in the lowermost stratosphere over midlatitudes. Correlation patterns and source profiles suggest contributions from crustal sources and biomass burning, but not from meteor ablation. Coinciding latitudinal gradients in particulate sulphur concentrations and emissions suggest that fossil fuel combustion is an important source of the aerosol in the upper troposphere and lowermost stratosphere. The measurements indicate aerosol transport along isentropic surfaces across the tropopause into the lowermost stratosphere. As a result of the prolonged residence time, ageing via oxidation of sulphur dioxide in the lowermost stratosphere was found to be a likely high-altitude, strong source that, along with downward transport of stratospheric air, could explain the vertical gradient of particulate sulphur mass concentration around the extratropical tropopause.
Spatial data standards meet meteorological data - pushing the boundaries
NASA Astrophysics Data System (ADS)
Wagemann, Julia; Siemen, Stephan; Lamy-Thepaut, Sylvie
2017-04-01
The data archive of the European Centre for Medium-Range Weather Forecasts (ECMWF) holds around 120 PB of data and is world's largest archive of meteorological data. This information is of great value for many Earth Science disciplines, but the complexity of the data (up to five dimensions and different time axis domains) and its native data format GRIB, while being an efficient archive format, limits the overall data uptake especially from users outside the MetOcean domain. ECMWF's MARS WebAPI is a very efficient and flexible system for expert users to access and retrieve meteorological data, though challenging for users outside the MetOcean domain. With the help of web-based standards for data access and processing, ECMWF wants to make more than 1 PB of meteorological and climate data easier accessible to users across different Earth Science disciplines. As climate data provider for the H2020 project EarthServer-2, ECMWF explores the feasibility to give on-demand access to it's MARS archive via the OGC standard interface Web Coverage Service (WCS). Despite the potential a WCS for climate and meteorological data offers, the standards-based modelling of meteorological and climate data entails many challenges and reveals the boundaries of the current Web Coverage Service 2.0 standard. Challenges range from valid semantic data models for meteorological data to optimal and efficient data structures for a scalable web service. The presentation reviews the applicability of the current Web Coverage Service 2.0 standard to meteorological and climate data and discusses challenges that are necessary to overcome in order to achieve real interoperability and to ensure the conformant sharing and exchange of meteorological data.
Leveraging ISI Multi-Model Prediction for Navy Operations: Proposal to the Office of Naval Research
2013-09-30
Operations: Proposal to the Office of Naval Research” PI: Benjamin Kirtman University of Miami – RSMAS Meteorology and Physical Oceanography...Prediction for Navy Operations: Proposal to the Office of Naval Research 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d
The WMO RA VI Regional Climate Centre Network - a support to users in Europe
NASA Astrophysics Data System (ADS)
Rösner, S.
2012-04-01
Climate, like weather, has no limits. Therefore the World Meteorological Organization (WMO), a specialized United Nations organization, has established a three-level infrastructure to better serve its member countries. This structure comprises Global Producing Centres for Long-range Forecasts (GPCs), Regional Climate Centres (RCCs) and National Meteorological or Hydrometeorological Services (NMHSs), in most cases representing their countries in WMO governance bodies. The elements of this infrastructure are also part of and contribute to the Global Framework for Climate Services (GFCS) agreed to be established by World Climate Conference 3 (WCC-3) and last year's Sixteenth World Meteorological Congress (WMO Cg-XVI). RCCs are the core element of this infrastructure at the regional level and are being establish in all WMO Regional Associations (RAs), i.e. Africa (RA I); Asia (II); South America (III); North America, Central America and the Caribbean (IV); South-West Pacific (V); Europe (VI). Addressing inter-regional areas of common interest like the Mediterranean or the Polar Regions may require inter-regional RCCs. For each region the RCCs follow a user driven approach with regard to governance and structure as well as products generated for the users in the respective region. However, there are common guidelines all RCCs do have to follow. This is to make sure that services are provided based on best scientific standards, are routinely and reliably generated and made available in an operational mode. These guidelines are being developed within WMO and make use of decade-long experience gained in the business of operational weather forecast. Based on the requirements of the 50 member countries of WMO RA VI it was agreed to establish the WMO RCC as a network of centres of excellence that create regional products including long-range forecasts that support regional and national climate activities, and thereby strengthen the capacity of WMO Members in the region to deliver better climate services to national users. On 1 June 2009 the WMO RA VI Pilot RCC-Network started its pilot phase to demonstrate its capability to provide, on an operational day-to-day basis, the products agreed upon by the member countries of RA VI. On 5 October 2011 the process to become formally designated WMO RA VI RCC-Network was initiated, and it is expected that the designation will happen mid to end 2012. The presentation will describe the global and regional activities related to RCCs and explain in more details the situation in WMO RA VI (Europe).
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.
Guo, Xiang; Wang, Ming Tian; Zhang, Guo Zhi
2017-12-01
The winter reproductive areas of Puccinia striiformis var. striiformis in Sichuan Basin are often the places mostly affected by wheat stripe rust. With data on the meteorological condition and stripe rust situation at typical stations in the winter reproductive area in Sichuan Basin from 1999 to 2016, this paper classified the meteorological conditions inducing wheat stripe rust into 5 grades, based on the incidence area ratio of the disease. The meteorological factors which were biologically related to wheat stripe rust were determined through multiple analytical methods, and a meteorological grade model for forecasting wheat stripe rust was created. The result showed that wheat stripe rust in Sichuan Basin was significantly correlated with many meteorological factors, such as the ave-rage (maximum and minimum) temperature, precipitation and its anomaly percentage, relative humidity and its anomaly percentage, average wind speed and sunshine duration. Among these, the average temperature and the anomaly percentage of relative humidity were the determining factors. According to a historical retrospective test, the accuracy of the forecast based on the model was 64% for samples in the county-level test, and 89% for samples in the municipal-level test. In a meteorological grade forecast of wheat stripe rust in the winter reproductive areas in Sichuan Basin in 2017, the prediction was accurate for 62.8% of the samples, with 27.9% error by one grade and only 9.3% error by two or more grades. As a result, the model could deliver satisfactory forecast results, and predicate future wheat stripe rust from a meteorological point of view.
Meteorological radar services: a brief discussion and a solution in practice
NASA Astrophysics Data System (ADS)
Nicolaides, K. A.
2014-08-01
The Department of Meteorology is the organization designated by the Civil Aviation Department and by the National Supervisory Authority of the Republic of Cyprus, as an air navigation service provider, based on the regulations of the Single European Sky. Department of Meteorology holds and maintains also an ISO: 9001/2008, Quality System, for the provision of meteorological and climatological services to aeronautic and maritime community, but also to the general public. In order to fulfill its obligations the Department of Meteorology customs the rather dense meteorological stations network, with long historical data series, installed and maintained by the Department, in parallel with modelling and Numerical Weather Prediction (NWP), along with training and gaining of expertise. Among the available instruments in the community of meteorologists is the meteorological radar, a basic tool for the needs of very short/short range forecasting (nowcasting). The Department of Meteorology installed in the mid 90's a C-band radar over «Throni» location and expanded its horizons in nowcasting, aviation safety and warnings issuance. The radar has undergone several upgrades but today technology has over passed its rather old technology. At the present the Department of Meteorology is in the process of buying Meteorological Radar Services as a result of a public procurement procedure. Two networked X-band meteorological radar will be installed (the project now is in the phase of infrastructure establishment while the hardware is in the process of assemble), and maintained from Space Hellas (the contractor) for a 13 years' time period. The present article must be faced as a review article of the efforts of the Department of Meteorology to support its weather forecasters with data from meteorological radar.
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.
NASA Astrophysics Data System (ADS)
Popov, V. N.; Botygin, I. A.; Kolochev, A. S.
2017-01-01
The approach allows representing data of international codes for exchange of meteorological information using metadescription as the formalism associated with certain categories of resources. Development of metadata components was based on an analysis of the data of surface meteorological observations, atmosphere vertical sounding, atmosphere wind sounding, weather radar observing, observations from satellites and others. A common set of metadata components was formed including classes, divisions and groups for a generalized description of the meteorological data. The structure and content of the main components of a generalized metadescription are presented in detail by the example of representation of meteorological observations from land and sea stations. The functional structure of a distributed computing system is described. It allows organizing the storage of large volumes of meteorological data for their further processing in the solution of problems of the analysis and forecasting of climatic processes.
PROMET - The Journal of Meteorological Education issued by DWD
NASA Astrophysics Data System (ADS)
Rapp, J.
2009-09-01
Promet is published by the German Meteorological Service (DWD) since 1971 to improve meteorologists and weather forecasters skills. The journal comprises mainly contributions to topics like biometeorology, the NAO, or meteorology and insurance business. The science-based articles should illustrate the special issue in an understandable and transparent way. In addition, the journal contains portraits of other national meteorological services and university departments, book reviews, list of university degrees, and other individual papers. Promet is published only in German language, but included English titles and abstracts. The journal is peer-reviewed by renowned external scientists. It is distributed free of charge by DWD to the own meteorological staff. On the other hand, DMG (the German Meteorological Society) hand it out to all members of the society. The current issues deal with "Modern procedures of weather forecasting in DWD” and "E-Learning in Meteorology”.
Phenological Versus Meteorological Controls on Land-atmosphere Water and Carbon Fluxes
NASA Technical Reports Server (NTRS)
Puma, Michael J.; Koster, Randal D.; Cook, Benjamin I.
2013-01-01
Phenological dynamics and their related processes strongly constrain land-atmosphere interactions, but their relative importance vis-à-vis meteorological forcing within general circulation models (GCMs) is still uncertain. Using an off-line land surface model, we evaluate leaf area and meteorological controls on gross primary productivity, evapotranspiration, transpiration, and runoff at four North American sites, representing different vegetation types and background climates. Our results demonstrate that compared to meteorological controls, variation in leaf area has a dominant control on gross primary productivity, a comparable but smaller influence on transpiration, a weak influence on total evapotranspiration, and a negligible impact on runoff. Climate regime and characteristic variations in leaf area have important modulating effects on these relative controls, which vary depending on the fluxes and timescales of interest. We find that leaf area in energylimited evaporative regimes tends to exhibit greater control on annual gross primary productivity than in moisture-limited regimes, except when vegetation exhibits little interannual variation in leaf area. For transpiration, leaf area control is somewhat less in energylimited regimes and greater in moisture-limited regimes for maximum pentad and annual fluxes. These modulating effects of climate and leaf area were less clear for other fluxes and at other timescales. Our findings are relevant to land-atmosphere coupling in GCMs, especially considering that leaf area variations are a fundamental element of land use and land cover change simulations.
Evaluation of a regional assimilation system coupled with the WRF-chem model
NASA Astrophysics Data System (ADS)
Liu, Yan-an; Gao, Wei; Huang, Hung-lung; Strabala, Kathleen; Liu, Chaoshun; Shi, Runhe
2013-09-01
Air quality has become a social issue that is causing great concern to humankind across the globe, but particularly in developing countries. Even though the Weather Research and Forecasting with Chemistry (WRF-Chem) model has been applied in many regions, the resolution for inputting meteorology field analysis still impacts the accuracy of forecast. This article describes the application of the CIMSS Regional Assimilation System (CRAS) in East China, and its capability to assimilate the direct broadcast (DB) satellite data for obtaining more detailed meteorological information, including cloud top pressure (CTP) and total precipitation water (TPW) from MODIS. Performance evaluation of CRAS is based on qualitative and quantitative analyses. Compared with data collected from ERA-Interim, Radiosonde, and the Tropical Rainfall Measuring Mission (TRMM) precipitation measurements using bias and Root Mean Square Error (RMSE), CRAS has a systematic error due to the impact of topography and other factors; however, the forecast accuracy of all elements in the model center area is higher at various levels. The bias computed with Radiosonde reveals that the temperature and geopotential height of CRAS are better than ERA-Interim at first guess. Moreover, the location of the 24 h accumulated precipitation forecast are highly consistent with the TRMM retrieval precipitation, which means that the performance of CRAS is excellent. In summation, the newly built Vtable can realize the function of inputting the meteorology field from CRAS output into WRF, which couples the CRAS with WRF-Chem. Therefore, this study not only provides for forecast accuracy of CRAS, but also increases the capability of running the WRF-Chem model at higher resolutions in the future.
Impact of El Nino and La Nina on the meteorological elements
NASA Astrophysics Data System (ADS)
Jaiswal, Rajasri Sen; Subitha, T.; Samuthra, G.; Punitha, M.; Vinotha, R.
2016-05-01
The El Nino and La Nina have been found to influence the weather at a remote place. In this paper, the authors investigate the impact of El Nino & La Nina on the surface temperature and rainfall over few selected locations in India and abroad. The study shows that the ENSO affects the surface rainfall; however, the impact is not the same over all the locations. In order to find out whether such influence is latitude sensitive, the study has been performed over locations located at different latitudes and at a fixed longitude. To check if the El Nino/La Nina leaves any impressions on the upper air meteorological elements, the cloud liquid water (CLW), precipitation water (PW), latent heat (LH), freezing level height (HFL) and the bright band height (BBH) over a few locations have been studied from the Earth's surface up to a height of 18 km above. The CLW, PW and LH values have been obtained from the data product 2A12 of the Tropical Microwave Imager (TMI) onboard the Tropical Rainfall Measuring Satellite (TRMM), while that of the BBH and the HFL are obtained from the data product 2A23 of the precipitation radar (PR) onboard the TRMM.
NASA Astrophysics Data System (ADS)
Radzka, Elżbieta; Rymuza, Katarzyna
2015-04-01
The work is based on meteorological data recorded by nine stations of the Institute of Meteorology and Water Management located in east-central Poland from 1971 to 2005. The region encompasses the North Podlasian Lowland and the South Podlasian Lowland. Average values of selected agroclimate indicators for the growing season were determined. Moreover, principal component analysis was conducted to indicate elements that exerted the greatest influence on the agroclimate. Also, cluster analysis was carried out to select stations with similar agroclimate. Ward method was used for clustering and the Euclidean distance was applied. Principal component analysis revealed that the agroclimate of east-central Poland was predominantly affected by climatic water balance, number of days of active plant growth, length of the farming period, and the average air temperature during the growing season (Apr-Sept). Based on the analysis, the region of east-central Poland was divided into two groups (areas) with different agroclimatic conditions. The first area comprized the following stations: Szepietowo and Białowieża located in the North Podlasian Lowland and Biała Podlaska situated in the northern part of the South Podlasian Lowland. This area was characterized by shorter farming periods and a lower average air temperature during the growing season. The other group included the remaining stations located in the western part of both the Lowlands which was warmer and where greater water deficits were recorded.
Atmospheric Science Data Center
2018-04-03
Surface meteorology and Solar Energy (SSE) Data and Information The Release 6.0 Surface meteorology and Solar Energy ( SSE ) data set contains parameters formulated for assessing and designing renewable energy systems. This latest release contains new parameters based on ...
NASA Astrophysics Data System (ADS)
Duda, James L.; Mulligan, Joseph; Valenti, James; Wenkel, Michael
2005-01-01
A key feature of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) is the Northrop Grumman Space Technology patent-pending innovative data routing and retrieval architecture called SafetyNetTM. The SafetyNetTM ground system architecture for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), combined with the Interface Data Processing Segment (IDPS), will together provide low data latency and high data availability to its customers. The NPOESS will cut the time between observation and delivery by a factor of four when compared with today's space-based weather systems, the Defense Meteorological Satellite Program (DMSP) and NOAA's Polar-orbiting Operational Environmental Satellites (POES). SafetyNetTM will be a key element of the NPOESS architecture, delivering near real-time data over commercial telecommunications networks. Scattered around the globe, the 15 unmanned ground receptors are linked by fiber-optic systems to four central data processing centers in the U. S. known as Weather Centrals. The National Environmental Satellite, Data and Information Service; Air Force Weather Agency; Fleet Numerical Meteorology and Oceanography Center, and the Naval Oceanographic Office operate the Centrals. In addition, this ground system architecture will have unused capacity attendant with an infrastructure that can accommodate additional users.
A climatological description of the Savannah River Site
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hunter, C.H.
1990-05-22
This report provides a general climatological description of the Savannah River Site. The description provides both regional and local scale climatology. The regional climatology includes a general regional climatic description and presents information on occurrence frequencies of the severe meteorological phenomena that are important considerations in the design and siting of a facility. These phenomena include tornadoes, thunderstorms, hurricanes, and ice/snow storms. Occurrence probabilities given for extreme tornado and non-tornado winds are based on previous site specific studies. Local climatological conditions that are significant with respect to the impact of facility operations on the environment are described using on-site ormore » near-site meteorological data. Summaries of wind speed, wind direction, and atmospheric stability are primarily based on the most recently generated five-year set of data collected from the onsite meteorological tower network (1982--86). Temperature, humidity, and precipitation summaries include data from SRL's standard meteorological instrument shelter and the Augusta National Weather Service office at Bush Field through 1986. A brief description of the onsite meteorological monitoring program is also provided. 24 refs., 15 figs., 22 tabs.« less
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.
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.
Effects of meteorological droughts on agricultural water resources in southern China
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...
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.
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
Long-term Changes in Extreme Air Pollution Meteorology and the Implications for Air Quality.
Hou, Pei; Wu, Shiliang
2016-03-31
Extreme air pollution meteorological events, such as heat waves, temperature inversions and atmospheric stagnation episodes, can significantly affect air quality. Based on observational data, we have analyzed the long-term evolution of extreme air pollution meteorology on the global scale and their potential impacts on air quality, especially the high pollution episodes. We have identified significant increasing trends for the occurrences of extreme air pollution meteorological events in the past six decades, especially over the continental regions. Statistical analysis combining air quality data and meteorological data further indicates strong sensitivities of air quality (including both average air pollutant concentrations and high pollution episodes) to extreme meteorological events. For example, we find that in the United States the probability of severe ozone pollution when there are heat waves could be up to seven times of the average probability during summertime, while temperature inversions in wintertime could enhance the probability of severe particulate matter pollution by more than a factor of two. We have also identified significant seasonal and spatial variations in the sensitivity of air quality to extreme air pollution meteorology.
NASA Technical Reports Server (NTRS)
Kiang, R.; Adimi, F.; Nigro, J.
2007-01-01
Meteorological and environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. These parameters can most conveniently be obtained using remote sensing. Selected provinces and districts in Thailand and Indonesia are used to illustrate how remotely sensed meteorological and environmental parameters may enhance the capabilities for malaria surveillance and control. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records.
Feng, Jinglan; Yu, Hao; Mi, Kai; Su, Xianfa; Chen, Yunqi; Sun, Jian-Hui; Li, Qilu
2018-06-01
The pollution characteristics of PM 2.5 and correlation analysis with meteorological parameters in Xinxiang during the Shanghai Cooperation Organization Prime Ministers' Meeting were investigated. During the whole meeting, nine PM 2.5 samples were collected at a suburban site of Xinxiang, and the average concentration of PM 2.5 was 122.28 μg m -3 . NO 3 - , NH 4 + , SO 4 2- accounted for 56.8% of the total water-soluble ions. In addition, with an exception of Cl - , all of water-soluble ions decreased during the meeting. Total concentrations of crustal elements ranged from 6.53 to 185.86 μg m -3 , with an average concentration of 52.51 μg m -3 , which accounted for 82.5% of total elements. The concentrations of organic carbon and elemental carbon were 7.71 and 1.52 μg m -3 , respectively, lower than those before and after the meeting. It is indicated that during the meeting, limiting motor vehicles is to reduce exhaust emissions, delay heating is to reduce the fossil fuel combustion, and other measures are to reduce the concentration of PM 2.5 . The directly dispersing by mixing layer height increase and the indirectly reducing the formation of secondary aerosol by low relative humidity, and these are the only two key removing mechanisms of PM 2.5 in Xinxiang during the meeting.
Evaluating meteo marine climatic model inputs for the investigation of coastal hydrodynamics
NASA Astrophysics Data System (ADS)
Bellafiore, D.; Bucchignani, E.; Umgiesser, G.
2010-09-01
One of the major aspects discussed in the recent works on climate change is how to provide information from the global scale to the local one. In fact the influence of sea level rise and changes in the meteorological conditions due to climate change in strategic areas like the coastal zone is at the base of the well known mitigation and risk assessment plans. The investigation of the coastal zone hydrodynamics, from a modeling point of view, has been the field for the connection between hydraulic models and ocean models and, in terms of process studies, finite element models have demonstrated their suitability in the reproduction of complex coastal morphology and in the capability to reproduce different spatial scale hydrodynamic processes. In this work the connection between two different model families, the climate models and the hydrodynamic models usually implemented for process studies, is tested. Together, they can be the most suitable tool for the investigation of climate change on coastal systems. A finite element model, SHYFEM (Shallow water Hydrodynamic Finite Element Model), is implemented on the Adriatic Sea, to investigate the effect of wind forcing datasets produced by different downscaling from global climate models in terms of surge and its coastal effects. The wind datasets are produced by the regional climate model COSMO-CLM (CIRA), and by EBU-POM model (Belgrade University), both downscaling from ECHAM4. As a first step the downscaled wind datasets, that have different spatial resolutions, has been analyzed for the period 1960-1990 to compare what is their capability to reproduce the measured wind statistics in the coastal zone in front of the Venice Lagoon. The particularity of the Adriatic Sea meteo climate is connected with the influence of the orography in the strengthening of winds like Bora, from North-East. The increase in spatial resolution permits the more resolved wind dataset to better reproduce meteorology and to provide a more realistic forcing for hydrodynamic simulations. After this analysis, effects on water level variations, under different wind forcing, has been analyzed to define what is the local effect on sea level changes in the coastal area of the North Adriatic. Surge statistics produced from different climate model forcings for the IPCC A1B scenario have been studied to provide local information on climate change effects on coastal hydrodynamics due to meteorological effect. This typology of application has been considered a suitable tool for coastal management and can be considered a study field that will increase its importance in the more general investigation on scale interaction processes as the effects of global scale climate phenomena on local areas.
NASA Astrophysics Data System (ADS)
Gochis, D. J.; Dugger, A. L.; Karsten, L. R.; Barlage, M. J.; Sampson, K. M.; Yu, W.; Pan, L.; McCreight, J. L.; Howard, K.; Busto, J.; Deems, J. S.
2017-12-01
Hydrometeorological processes vary over comparatively short length scales in regions of complex terrain such as the southern Rocky Mountains. Changes in temperature, precipitation, wind and solar radiation can vary significantly across elevation gradients, terrain landform and land cover conditions throughout the region. Capturing such variability in hydrologic models can necessitate the utilization of so-called `hyper-resolution' spatial meshes with effective element spacings of less than 100m. However, it is often difficult to obtain meteorological forcings of high quality in such regions at those resolutions which can result in significant uncertainty in fundamental in hydrologic model inputs. In this study we examine the comparative influences of meteorological forcing data fidelity and spatial resolution on seasonal simulations of snowpack evolution, runoff and streamflow in a set of high mountain watersheds in southern Colorado. We utilize the operational, NOAA National Water Model configuration of the community WRF-Hydro system as a baseline and compare against it, additional model scenarios with differing specifications of meteorological forcing data, with and without topographic downscaling adjustments applied, with and without experimental high resolution radar derived precipitation estimates and with WRF-Hydro configurations of progressively finer spatial resolution. The results suggest significant influence from and importance of meteorological downscaling techniques in controlling spatial distributions of meltout and runoff timing. The use of radar derived precipitation exhibits clear sensitivity on hydrologic simulation skill compared with the use of coarser resolution, background precipitation analyses. Advantages and disadvantages of the utilization of progressively higher resolution model configurations both in terms of computational requirements and model fidelity are also discussed.
Wang, Jizhi; Zhang, Xiaoye; Li, Duo; Yang, Yuanqin; Zhong, Junting; Wang, Yaqiang; Che, Haochi; Che, Huizheng; Zhang, Yangmei
2018-07-15
Winter is a season of much concern for aerosol pollution in China, but less concern for pollution in the summertime. There are even less concern and larger uncertainty about interdecadal changes in summer aerosol pollution, relative influence of meteorological conditions, and their links to climate change. Here we try to reveal the relation among interdecadal changes in summer's most important circulation system affecting China (East Asian Summer Monsoon-EASM), an index of meteorological conditions (called PLAM, Parameter Linking Air Quality and Meteorological Elements, which is almost linearly related with aerosol pollution), and aerosol optical depth (AOD) in the middle and lower reaches of the Yangtze River (M-LYR) in central eastern China during summertime since the 1960's. During the weak monsoon years, the aerosol pollution load was heavier in the M-LYR and opposite in the strong monsoon years mainly influenced by EASM and associated maintenance position of the anti-Hadley cell around 115°E. The interdecadal changes in meteorological conditions and their associated aerosol pollution in the context of such climate change have experienced four periods since the 1960's, which were a relatively large decreased period from 1961 to 1980, a large rise between 1980 and 1999, a period of slow rise or maintenance from 1999 to 2006, and a relatively rapid rise between 2006 and 2014. Among later three pollution increased periods, about 51%, 25% and 60% of the aerosol pollution change respectively come from the contribution of worsening weather conditions, which are found to be greatly affected by changes in EASM. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Spasova, Z.
2011-03-01
Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychological and emotional level has been made. Emotions affect the bio tone, working ability, and concentration; hence their significance in various domains of economic life such as health care, education, transportation, and tourism. The present pilot study was conducted in Sofia, Bulgaria over a period of eight months, using five psychological methods: Eysenck Personality Questionnaire, State-Trait Anxiety Inventory, Test for Self-assessment of the emotional state, Test for evaluation of moods and Test ''Self-confidence-Activity-Mood''. The Fiodorov-Chubukov's complex-climatic method was used to characterize meteorological conditions in order to include a maximal number of meteorological elements in the analysis. Sixteen weather types are defined depending on the meteorological elements values according to this method. Abrupt weather changes from one day to another, defined by the same method, were also considered. The results obtained by t-test showed that the different categories of weather led to changes in the emotional status, which indicates a character either positive or negative for the organism. The abrupt weather changes, according to expectations, have negative effects on human emotions - but only when a transition to the cloudy weather or weather type, classified as ''unfavorable'', has been realized. The relationship between weather and human emotions is rather complicated since it depends on individual characteristics of people. One of these individual psychological characteristics, marked by the dimension ''neuroticism'', has a strong effect on emotional reactions in different weather conditions. Emotionally stable individuals are more ''resistant'' to the weather influence on their emotions, while those who are emotionally unstable have a stronger dependence on the impacts of weather.
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.
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.
A Reduced Form Model for Ozone Based on Two Decades of ...
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
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.
Shen, Xiao-jun; Sun, Jing-sheng; Li, Ming-si; Zhang, Ji-yang; Wang, Jing-lei; Li, Dong-wei
2015-02-01
It is important to improve the real-time irrigation forecasting precision by predicting real-time water consumption of cotton mulched with plastic film under drip irrigation based on meteorological data and cotton growth status. The model parameters for calculating ET0 based on Hargreaves formula were determined using historical meteorological data from 1953 to 2008 in Shihezi reclamation area. According to the field experimental data of growing season in 2009-2010, the model of computing crop coefficient Kc was established based on accumulated temperature. On the basis of crop water requirement (ET0) and Kc, a real-time irrigation forecast model was finally constructed, and it was verified by the field experimental data in 2011. The results showed that the forecast model had high forecasting precision, and the average absolute values of relative error between the predicted value and measured value were about 3.7%, 2.4% and 1.6% during seedling, squaring and blossom-boll forming stages, respectively. The forecast model could be used to modify the predicted values in time according to the real-time meteorological data and to guide the water management in local film-mulched cotton field under drip irrigation.
Global meteorological data facility for real-time field experiments support and guidance
NASA Technical Reports Server (NTRS)
Shipham, Mark C.; Shipley, Scott T.; Trepte, Charles R.
1988-01-01
A Global Meteorological Data Facility (GMDF) has been constructed to provide economical real-time meteorological support to atmospheric field experiments. After collection and analysis of meteorological data sets at a central station, tailored meteorological products are transmitted to experiment field sites using conventional ground link or satellite communication techniques. The GMDF supported the Global Tropospheric Experiment Amazon Boundary Layer Experiment (GTE-ABLE II) based in Manaus, Brazil, during July and August 1985; an arctic airborne lidar survey mission for the Polar Stratospheric Clouds (PSC) experiment during January 1986; and the Genesis of Atlantic Lows Experiment (GALE) during January, February and March 1986. GMDF structure is similar to the UNIDATA concept, including meteorological data from the Zephyr Weather Transmission Service, a mode AAA GOES downlink, and dedicated processors for image manipulation, transmission and display. The GMDF improved field experiment operations in general, with the greatest benefits arising from the ability to communicate with field personnel in real time.
NASA Technical Reports Server (NTRS)
Bergeron, H. P.
1980-01-01
Data obtained from the NASA Aviation Safety Reporting System (ASRS) data base were used to determine problems in general aviation single pilot IFR operations. The data examined consisted of incident reports involving flight safety in the National Aviation System. Only those incidents involving general aviation fixed wing aircraft flying under IFR in instrument meteorological conditions were analyzed. The data were cataloged into one of five major problem areas: (1) controller judgement and response problems; (2) pilot judgement and response problems; (3) air traffic control intrafacility and interfacility conflicts; (4) ATC and pilot communications problems; and (5) IFR-VFR conflicts. The significance of the related problems, and the various underlying elements associated with each are discussed. Previous ASRS reports covering several areas of analysis are reviewed.
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
Atmospheric Science Data Center
2018-04-04
Surface meteorology and Solar Energy (SSE) Data and Information A new POWER home page ... The Release 6.0 Surface meteorology and Solar Energy (SSE) data set contains parameters formulated for assessing and designing renewable energy systems. This latest release contains new parameters based on ...
NASA Astrophysics Data System (ADS)
Medina, F.
2013-08-01
The contribution of the "Institut Scientifique Chérifien", the oldest scientific research centre in Morocco, is reviewed since its creation almost a century ago. Planned in 1914 by the French protectorate of Morocco, this institute has played, since its effective creation in 1920, an important role in the development of several geosciences in North Africa, such as meteorology and climatology, geophysics (gravimetry, magnetism and especially seismology), geomorphology, geology and oceanography. After the independence of Morocco in 1955, several activities, such as meteorology, were transferred elsewhere, but others, such as seismology and magnetism, remained important elements of the centre until recent years. In addition to the research activities, its observatories and libraries that were built during the early years are unique in Northwest Africa.
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.
Maize transpiration in response to meteorological conditions
NASA Astrophysics Data System (ADS)
Klimešová, Jana; Stŕedová, Hana; Stŕeda, Tomáš
2013-09-01
Differences in transpiration of maize (Zea mays L.) plants in four soil moisture regimes were quantified in a pot experiment. The transpiration was measured by the "Stem Heat Balance" method. The dependence of transpiration on air temperature, air humidity, global solar radiation, soil moisture, wind speed and leaf surface temperature were quantified. Significant relationships among transpiration, global radiation and air temperature (in the first vegetation period in the drought non-stressed variant, r = 0.881**, r = 0.934**) were found. Conclusive dependence of transpiration on leaf temperature (r = 0.820**) and wind speed (r = 0.710**) was found. Transpiration was significantly influenced by soil moisture (r = 0.395**, r = 0.528**) under moderate and severe drought stress. The dependence of transpiration on meteorological factors decreased with increasing deficiency of water. Correlation between transpiration and plant dry matter weight (r = 0.997**), plant height (r = 0.973**) and weight of corn cob (r = 0.987**) was found. The results of instrumental measuring of field crops transpiration under diverse moisture conditions at a concurrent monitoring of the meteorological elements spectra are rather unique. These results will be utilized in the effort to make calculations of the evapotranspiration in computing models more accurate.
NASA Astrophysics Data System (ADS)
Li, Binquan; Zhu, Changchang; Liang, Zhongmin; Wang, Guoqing; Zhang, Yu
2018-06-01
Differences between meteorological and hydrological droughts could reflect the regional water consumption by both natural elements and human water-use. The connections between these two drought types were analyzed using the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI), respectively. In a typical semi-arid basin of the middle Yellow River (Qingjianhe River basin), annual precipitation and air temperature showed significantly downward and upward trends, respectively, with the rates of -2.37 mm yr-1 and 0.03 °C yr-1 (1961-2007). Under their synthetic effects, water balance variable (represented by SPEI) showed obviously downward (drying) trend at both upstream and whole basin areas. For the spatial variability of precipitation, air temperature and the calculated SPEI, both upstream and downstream areas experienced very similar change characteristics. Results also suggested that the Qingjianhe River basin experienced near normal condition during the study period. As a whole, this semi-arid basin mainly had the meteorological drought episodes in the mid-1960s, late-1990s and the 2000s depicted by 12-month SPEI. The drying trend could also be depicted by the hydrological drought index (12-month SSI) at both upstream and downstream stations (Zichang and Yanchuan), but the decreasing trends were not significant. A correlation analysis showed that hydrological system responds rapidly to the change of meteorological conditions in this semi-arid region. This finding could be an useful implication to drought research for those semi-arid basins with intensive human activities.
Meteorology--An Interdisciplinary Base for Science Learning.
ERIC Educational Resources Information Center
Howell, David C.
1980-01-01
Described is a freshman science program at Deerfield Academy (Deerfield, Mass.) in meteorology, designed as the first part of a three-year unified science sequence. Merits of the course, in which particular emphasis is placed on observation skills and making predictions, are enumerated. (CS)
Procedures on installing, acceptance testing, operating, maintaining and quality assuring three types of ground-based, upper air meteorological measurement systems are described. he limitations and uncertainties in precision and accuracy measurements associated with these systems...
Rivers, James W.; Johnson, J. Matthew; Haig, Susan M.; Schwarz, Carl J.; Glendening, John W.; Burnett, L. Joseph; George, Daniel; Grantham, Jesse
2014-01-01
Condors and vultures are distinct from most other terrestrial birds because they use extensive soaring flight for their daily movements. Therefore, assessing resource selection by these avian scavengers requires quantifying the availability of terrestrial-based habitats, as well as meteorological variables that influence atmospheric conditions necessary for soaring. In this study, we undertook the first quantitative assessment of habitat- and meteorological-based resource selection in the endangered California condor (Gymnogyps californianus) within its California range and across the annual cycle. We found that condor use of terrestrial areas did not change markedly within the annual cycle, and that condor use was greatest for habitats where food resources and potential predators could be detected and where terrain was amenable for taking off from the ground in flight (e.g., sparse habitats, coastal areas). Condors originating from different release sites differed in their use of habitat, but this was likely due in part to variation in habitats surrounding release sites. Meteorological conditions were linked to condor use of ecological subregions, with thermal height, thermal velocity, and wind speed having both positive (selection) and negative (avoidance) effects on condor use in different areas. We found little evidence of systematic effects between individual characteristics (i.e., sex, age, breeding status) or components of the species management program (i.e., release site, rearing method) relative to meteorological conditions. Our findings indicate that habitat type and meteorological conditions can interact in complex ways to influence condor resource selection across landscapes, which is noteworthy given the extent of anthropogenic stressors that may impact condor populations (e.g., lead poisoning, wind energy development). Additional studies will be valuable to assess small-scale condor movements in light of these stressors to help minimize their risk to this critically endangered species. PMID:24523893
Johnson, J. Matthew; Haig, Susan M.; Schwarz, Carl J.; Glendening, John W.; Burnett, L. Joseph; George, Daniel; Grantham, Jesse
2014-01-01
Condors and vultures are distinct from most other terrestrial birds because they use extensive soaring flight for their daily movements. Therefore, assessing resource selection by these avian scavengers requires quantifying the availability of terrestrial-based habitats, as well as meteorological variables that influence atmospheric conditions necessary for soaring. In this study, we undertook the first quantitative assessment of habitat- and meteorological-based resource selection in the endangered California condor (Gymnogyps californianus) within its California range and across the annual cycle. We found that condor use of terrestrial areas did not change markedly within the annual cycle, and that condor use was greatest for habitats where food resources and potential predators could be detected and where terrain was amenable for taking off from the ground in flight (e.g., sparse habitats, coastal areas). Condors originating from different release sites differed in their use of habitat, but this was likely due in part to variation in habitats surrounding release sites. Meteorological conditions were linked to condor use of ecological subregions, with thermal height, thermal velocity, and wind speed having both positive (selection) and negative (avoidance) effects on condor use in different areas. We found little evidence of systematic effects between individual characteristics (i.e., sex, age, breeding status) or components of the species management program (i.e., release site, rearing method) relative to meteorological conditions. Our findings indicate that habitat type and meteorological conditions can interact in complex ways to influence condor resource selection across landscapes, which is noteworthy given the extent of anthropogenic stressors that may impact condor populations (e.g., lead poisoning, wind energy development). Additional studies will be valuable to assess small-scale condor movements in light of these stressors to help minimize their risk to this critically endangered species.
Mining key elements for severe convection prediction based on CNN
NASA Astrophysics Data System (ADS)
Liu, Ming; Pan, Ning; Zhang, Changan; Sha, Hongzhou; Zhang, Bolei; Liu, Liang; Zhang, Meng
2017-04-01
Severe convective weather is a kind of weather disasters accompanied by heavy rainfall, gust wind, hail, etc. Along with recent developments on remote sensing and numerical modeling, there are high-volume and long-term observational and modeling data accumulated to capture massive severe convective events over particular areas and time periods. With those high-volume and high-variety weather data, most of the existing studies and methods carry out the dynamical laws, cause analysis, potential rule study, and prediction enhancement by utilizing the governing equations from fluid dynamics and thermodynamics. In this study, a key-element mining method is proposed for severe convection prediction based on convolution neural network (CNN). It aims to identify the key areas and key elements from huge amounts of historical weather data including conventional measurements, weather radar, satellite, so as numerical modeling and/or reanalysis data. Under this manner, the machine-learning based method could help the human forecasters on their decision-making on operational weather forecasts on severe convective weathers by extracting key information from the real-time and historical weather big data. In this paper, it first utilizes computer vision technology to complete the data preprocessing work of the meteorological variables. Then, it utilizes the information such as radar map and expert knowledge to annotate all images automatically. And finally, by using CNN model, it cloud analyze and evaluate each weather elements (e.g., particular variables, patterns, features, etc.), and identify key areas of those critical weather elements, then help forecasters quickly screen out the key elements from huge amounts of observation data by current weather conditions. Based on the rich weather measurement and model data (up to 10 years) over Fujian province in China, where the severe convective weathers are very active during the summer months, experimental tests are conducted with the new machine-learning method via CNN models. Based on the analysis of those experimental results and case studies, the proposed new method have below benefits for the severe convection prediction: (1) helping forecasters to narrow down the scope of analysis and saves lead-time for those high-impact severe convection; (2) performing huge amount of weather big data by machine learning methods rather relying on traditional theory and knowledge, which provide new method to explore and quantify the severe convective weathers; (3) providing machine learning based end-to-end analysis and processing ability with considerable scalability on data volumes, and accomplishing the analysis work without human intervention.
Meteorological (MET) data required by watershed assessments comprising Integrated Environmental Modeling (IEM) traditionally have been provided by land-based weather (gauge) stations, although these data may not be the most appropriate for adequate spatial and temporal resolution...
NASA Technical Reports Server (NTRS)
Huning, J. R.; Logan, T. L.; Smith, J. H.
1982-01-01
The potential of using digital satellite data to establish a cloud cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of cloud development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed cloud information in selected areas and summarized information in other areas; and (5) development of a cloud/shadow model which details the percentage of each grid cell that is cloud and shadow covered, and the percentage of cloud or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of cloud cover statistics.
Lagrangian Turbulence and Transport in Semi-enclosed Basins and Coastal Regions
2009-01-01
enclosed Basins and Coastal Regions Annalisa Griffa Division of Meteorology and Physical Oceanography Rosenstiel School of Marine and Atmospheric...enclosed Basins and Coastal Regions 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER...variables. A set of diagnostics is then performed, including hydrological sections, transport, mean circulation and variability, aimed at quantifying
NASA Astrophysics Data System (ADS)
Zhang, Y.; Rong, Z.; Min, M.; Hao, X.; Yang, H.
2017-12-01
Meteorological satellites have become an irreplaceable weather and ocean-observing tool in China. These satellites are used to monitor natural disasters and improve the efficiency of many sectors of Chinese national economy. It is impossible to ignore the space-derived data in the fields of meteorology, hydrology, and agriculture, as well as disaster monitoring in China, a large agricultural country. For this reason, China is making a sustained effort to build and enhance its meteorological observing system and application system. The first Chinese polar-orbiting weather satellite was launched in 1988. Since then China has launched 14 meteorological satellites, 7 of which are sun synchronous and 7 of which are geostationary satellites; China will continue its two types of meteorological satellite programs. In order to achieve the in-orbit absolute radiometric calibration of the operational meteorological satellites' thermal infrared channels, China radiometric calibration sites (CRCS) established a set of in-orbit field absolute radiometric calibration methods (FCM) for thermal infrared channels (TIR) and the uncertainty of this method was evaluated and analyzed based on TERRA/AQUA MODIS observations. Comparisons between the MODIS at pupil brightness temperatures (BTs) and the simulated BTs at the top of atmosphere using radiative transfer model (RTM) based on field measurements showed that the accuracy of the current in-orbit field absolute radiometric calibration methods was better than 1.00K (@300K, K=1) in thermal infrared channels. Therefore, the current CRCS field calibration method for TIR channels applied to Chinese metrological satellites was with favorable calibration accuracy: for 10.5-11.5µm channel was better than 0.75K (@300K, K=1) and for 11.5-12.5µm channel was better than 0.85K (@300K, K=1).
NASA Astrophysics Data System (ADS)
Adavi, Zohre; Mashhadi-Hossainali, Masoud
2015-04-01
Water vapor is considered as one of the most important weather parameter in meteorology. Its non-uniform distribution, which is due to the atmospheric phenomena above the surface of the earth, depends both on space and time. Due to the limited spatial and temporal coverage of observations, estimating water vapor is still a challenge in meteorology and related fields such as positioning and geodetic techniques. Tomography is a method for modeling the spatio-temporal variations of this parameter. By analyzing the impact of troposphere on the Global Navigation Satellite (GNSS) signals, inversion techniques are used for modeling the water vapor in this approach. Non-uniqueness and instability of solution are the two characteristic features of this problem. Horizontal and/or vertical constraints are usually used to compute a unique solution for this problem. Here, a hybrid regularization method is used for computing a regularized solution. The adopted method is based on the Least-Square QR (LSQR) and Tikhonov regularization techniques. This method benefits from the advantages of both the iterative and direct techniques. Moreover, it is independent of initial values. Based on this property and using an appropriate resolution for the model, firstly the number of model elements which are not constrained by GPS measurement are minimized and then; water vapor density is only estimated at the voxels which are constrained by these measurements. In other words, no constraint is added to solve the problem. Reconstructed profiles of water vapor are validated using radiosonde measurements.
NASA Astrophysics Data System (ADS)
Li, Qingchen; Cao, Guangxi; Xu, Wei
2018-01-01
Based on a multifractal detrending moving average algorithm (MFDMA), this study uses the fractionally autoregressive integrated moving average process (ARFIMA) to demonstrate the effectiveness of MFDMA in the detection of auto-correlation at different sample lengths and to simulate some artificial time series with the same length as the actual sample interval. We analyze the effect of predictable and unpredictable meteorological disasters on the US and Chinese stock markets and the degree of long memory in different sectors. Furthermore, we conduct a preliminary investigation to determine whether the fluctuations of financial markets caused by meteorological disasters are derived from the normal evolution of the financial system itself or not. We also propose several reasonable recommendations.
Hanford meteorological station computer codes: Volume 9, The quality assurance computer codes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burk, K.W.; Andrews, G.L.
1989-02-01
The Hanford Meteorological Station (HMS) was established in 1944 on the Hanford Site to collect and archive meteorological data and provide weather forecasts and related services for Hanford Site approximately 1/2 mile east of the 200 West Area and is operated by PNL for the US Department of Energy. Meteorological data are collected from various sensors and equipment located on and off the Hanford Site. These data are stored in data bases on the Digital Equipment Corporation (DEC) VAX 11/750 at the HMS (hereafter referred to as the HMS computer). Files from those data bases are routinely transferred to themore » Emergency Management System (EMS) computer at the Unified Dose Assessment Center (UDAC). To ensure the quality and integrity of the HMS data, a set of Quality Assurance (QA) computer codes has been written. The codes will be routinely used by the HMS system manager or the data base custodian. The QA codes provide detailed output files that will be used in correcting erroneous data. The following sections in this volume describe the implementation and operation of QA computer codes. The appendices contain detailed descriptions, flow charts, and source code listings of each computer code. 2 refs.« less
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.
Capannesi, Geraldo; Lopez, Francesco
2013-01-01
Human activities introduce compounds increasing levels of many dangerous species for environment and population. In this way, trace elements in airborne particulate have a preeminent position due to toxic element presence affecting the biological systems. The main problem is the analytical determination of such species at ultratrace levels: a very specific methodology is necessary with regard to the accuracy and precision and contamination problems. Instrumental Neutron Activation Analysis and Instrumental Photon Activation Analysis assure these requirements. A retrospective element analysis in airborne particulate collected in the last 4 decades has been carried out for studying their trend. The samples were collected in urban location in order to determine only effects due to global aerosol circulation; semiannual samples have been used to characterize the summer/winter behavior of natural and artificial origin. The levels of natural origin element are higher than those in other countries owing to geological and meteorological factors peculiar to Central Italy. The levels of artificial elements are sometimes less than those in other countries, suggesting a less polluted general situation for Central Italy. However, for a few elements (e.g., Pb) the levels measured are only slight lower than those proposed as air ambient standard. PMID:23878525
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)
Zhou, Shengzhen; Davy, Perry K; Wang, Xuemei; Cohen, Jason Blake; Liang, Jiaquan; Huang, Minjuan; Fan, Qi; Chen, Weihua; Chang, Ming; Ancelet, Travis; Trompetter, William J
2016-12-01
Hourly-resolved PM 2.5 and PM 10-2.5 samples were collected in the industrial city Foshan in the Pearl River Delta region, China. The samples were subsequently analyzed for elemental components and black carbon (BC). A key purpose of the study was to understand the composition of particulate matter (PM) at high-time resolution in a polluted urban atmosphere to identify key components contributing to extreme PM concentration events and examine the diurnal chemical concentration patterns for air quality management purposes. It was found that BC and S concentrations dominated in the fine mode, while elements with mostly crustal and oceanic origins such as Si, Ca, Al and Cl were found in the coarse size fraction. Most of the elements showed strong diurnal variations. S did not show clear diurnal variations, suggesting regional rather than local origin. Based on empirical orthogonal functions (EOF) method, 3 forcing factors were identified contributing to the extreme events of PM 2.5 and selected elements, i.e., urban direct emissions, wet deposition and a combination of coarse mode sources. Conditional probability functions (CPF) were performed using wind profiles and elemental concentrations. The CPF results showed that BC and elemental Cl, K, Fe, Cu and Zn in the fine mode were mostly from the northwest, indicating that industrial emissions and combustion were the main sources. For elements in the coarse mode, Si, Al, K, Ca, Fe and Ti showed similar patterns, suggesting same sources such as local soil dust/construction activities. Coarse elemental Cl was mostly from the south and southeast, implying the influence of marine aerosol sources. For other trace elements, we found vanadium (V) in fine PM was mainly from the sources located to the southeast of the measuring site. Combined with CPF results of S and V in fine PM, we concluded shipping emissions were likely an important elemental emission source. Copyright © 2016. Published by Elsevier B.V.
IASI instrument onboard Metop-A: lessons learned after almost two years in orbit
NASA Astrophysics Data System (ADS)
Buffet, Laurence; Pequignot, Eric; Blumstein, Denis; Fjørtoft, Roger; Lonjou, Vincent; Millet, Bruno; Larigauderie, Carole
2017-11-01
The Infrared Atmospheric Sounding Interferometer (IASI) is a key element of the MetOp payload, dedicated to operational meteorology. IASI measurements allow to retrieve temperature and humidity profiles at a 1 km vertical resolution with an accuracy of respectively 1 K and 10%. The aim of this paper is to give a status of the instrument and to present some lessons learned after almost two years in orbit. As the first European infrared sounder, the IASI instrument has demonstrated its operational capability and its adequacy to user needs, with highly meaningful contributions to meteorology, climate and atmospheric chemistry studies. The in-flight performance of IASI is fully satisfactory. The sensitivity to radiative environment seems to be higher than expected: several SEU related anomalies were recorded, without any consequence on the instrument's health. The first decontamination since the commissioning phase was successfully performed in March 2008. The instrument globally shows a stable behaviour.
Antarctic Meteorology and Climatology
NASA Astrophysics Data System (ADS)
King, J. C.; Turner, J.
1997-07-01
This book is a comprehensive survey of the climatology and meteorology of Antarctica. The first section of the book reviews the methods by which we can observe the Antarctic atmosphere and presents a synthesis of climatological measurements. In the second section, the authors consider the processes that maintain the observed climate, from large-scale atmospheric circulation to small-scale processes. The final section reviews our current knowledge of the variability of Antarctic climate and the possible effects of "greenhouse" warming. The authors stress links among the Antarctic atmosphere, other elements of the Antarctic climate system (oceans, sea ice and ice sheets), and the global climate system. This volume will be of greatest interest to meteorologists and climatologists with a specialized interest in Antarctica, but it will also appeal to researchers in Antarctic glaciology, oceanography and biology. Graduates and undergraduates studying physical geography, and the earth, atmospheric and environmental sciences will find much useful background material in the book.
Zhang, Ying; Shao, Yi; Shang, Kezheng; Wang, Shigong; Wang, Jinyan
2014-09-01
Set up the model of forecasting the number of circulatorys death toll based on back-propagation (BP) artificial neural networks discuss the relationship between the circulatory system diseases death toll meteorological factors and ambient air pollution. The data of tem deaths, meteorological factors, and ambient air pollution within the m 2004 to 2009 in Nanjing were collected. On the basis of analyzing the ficient between CSDDT meteorological factors and ambient air pollution, leutral network model of CSDDT was built for 2004 - 2008 based on factors and ambient air pollution within the same time, and the data of 2009 est the predictive power of the model. There was a closely system diseases relationship between meteorological factors, ambient air pollution and the circulatory system diseases death toll. The ANN model structure was 17 -16 -1, 17 input notes, 16 hidden notes and 1 output note. The training precision was 0. 005 and the final error was 0. 004 999 42 after 487 training steps. The results of forecast show that predict accuracy over 78. 62%. This method is easy to be finished with smaller error, and higher ability on circulatory system death toll on independent prediction, which can provide a new method for forecasting medical-meteorological forecast and have the value of further research.
NASA Astrophysics Data System (ADS)
Khajehei, S.; Madadgar, S.; Moradkhani, H.
2014-12-01
The reliability and accuracy of hydrological predictions are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model parameters and model structure. To reduce the total uncertainty in hydrological applications, one approach is to reduce the uncertainty in meteorological forcing by using the statistical methods based on the conditional probability density functions (pdf). However, one of the requirements for current methods is to assume the Gaussian distribution for the marginal distribution of the observed and modeled meteorology. Here we propose a Bayesian approach based on Copula functions to develop the conditional distribution of precipitation forecast needed in deriving a hydrologic model for a sub-basin in the Columbia River Basin. Copula functions are introduced as an alternative approach in capturing the uncertainties related to meteorological forcing. Copulas are multivariate joint distribution of univariate marginal distributions, which are capable to model the joint behavior of variables with any level of correlation and dependency. The method is applied to the monthly forecast of CPC with 0.25x0.25 degree resolution to reproduce the PRISM dataset over 1970-2000. Results are compared with Ensemble Pre-Processor approach as a common procedure used by National Weather Service River forecast centers in reproducing observed climatology during a ten-year verification period (2000-2010).
Spatial clustering and meteorological drivers of summer ozone in Europe
NASA Astrophysics Data System (ADS)
Carro-Calvo, Leopoldo; Ordóñez, Carlos; García-Herrera, Ricardo; Schnell, Jordan L.
2017-10-01
We have applied the k-means clustering technique on a maximum daily 8-h running average near-surface ozone (MDA8 O3) gridded dataset over Europe at 1° × 1° resolution for summer 1998-2012. This has resulted in a spatial division of nine regions where ozone presents coherent spatiotemporal patterns. The role of meteorology in the variability of ozone at different time scales has been investigated by using daily meteorological fields from the NCEP-NCAR meteorological reanalysis. In the five regions of central-southern Europe ozone extremes (exceedances of the summer 95th percentile) occur mostly under anticyclonic circulation or weak sea level pressure gradients which trigger elevated temperatures and the recirculation of air masses. In the four northern regions extremes are associated with high-latitude anticyclones that divert the typical westerly flow at those latitudes and cause the advection of aged air masses from the south. The impact of meteorology on the day-to-day variability of ozone has been assessed by means of two different types of multiple linear models. These include as predictors meteorological fields averaged within the regions (;region-based; approach) or synoptic indices indicating the degree of resemblance between the daily meteorological fields over a large domain (25°-70° N, 35° W - 35° E) and their corresponding composites for extreme ozone days (;index-based; approach). With the first approach, a reduced set of variables, always including daily maximum temperature within the region, explains 47-66% of the variability (adjusted R2) in central-southern Europe, while more complex models are needed to explain 27-49% of the variability in the northern regions. The index-based approach yields better results for the regions of northern Europe, with adjusted R2 = 40-57%. Finally, both methodologies have also been applied to reproduce the interannual variability of ozone, with the best models explaining 66-88% of the variance in central-southern Europe and 45-66% in the north. Thus, the regionalisation carried out in this work has allowed establishing clear distinctions between the meteorological drivers of ozone in northern Europe and in the rest of the continent. These drivers are consistent across the different time scales examined (extremes, day-to-day and interannual), which gives confidence in the robustness of the results.
Weather or Not To Teach Junior High Meteorology.
ERIC Educational Resources Information Center
Knorr, Thomas P.
1984-01-01
Presents a technique for teaching meteorology allowing students to observe and analyze consecutive weather maps and relate local conditions; a model illustrating the three-dimensional nature of the atmosphere is employed. Instructional methods based on studies of daily weather maps to trace systems sweeping across the United States are discussed.…
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.
Ground and Space Radar Volume Matching and Comparison Software
NASA Technical Reports Server (NTRS)
Morris, Kenneth; Schwaller, Mathew
2010-01-01
This software enables easy comparison of ground- and space-based radar observations. The software was initially designed to compare ground radar reflectivity from operational, ground based Sand C-band meteorological radars with comparable measurements from the Tropical Rainfall Measuring Mission (TRMM) satellite s Precipitation Radar (PR) instrument. The software is also applicable to other ground-based and space-based radars. The ground and space radar volume matching and comparison software was developed in response to requirements defined by the Ground Validation System (GVS) of Goddard s Global Precipitation Mission (GPM) project. This software innovation is specifically concerned with simplifying the comparison of ground- and spacebased radar measurements for the purpose of GPM algorithm and data product validation. This software is unique in that it provides an operational environment to routinely create comparison products, and uses a direct geometric approach to derive common volumes of space- and ground-based radar data. In this approach, spatially coincident volumes are defined by the intersection of individual space-based Precipitation Radar rays with the each of the conical elevation sweeps of the ground radar. Thus, the resampled volume elements of the space and ground radar reflectivity can be directly compared to one another.
Characteristics of regional aerosols: Southern Arizona and eastern Pacific Ocean
NASA Astrophysics Data System (ADS)
Prabhakar, Gouri
Atmospheric aerosols impact the quality of our life in many direct and indirect ways. Inhalation of aerosols can have harmful effects on human health. Aerosols also have climatic impacts by absorbing or scattering solar radiation, or more indirectly through their interactions with clouds. Despite a better understanding of several relevant aerosol properties and processes in the past years, they remain the largest uncertainty in the estimate of global radiative forcing. The uncertainties arise because although aerosols are ubiquitous in the Earth's atmosphere they are highly variable in space, time and their physicochemical properties. This makes in-situ measurements of aerosols vital in our effort towards reducing uncertainties in the estimate of global radiative forcing due to aerosols. This study is an effort to characterize atmospheric aerosols at a regional scale, in southern Arizona and eastern Pacific Ocean, based on ground and airborne observations of aerosols. Metals and metalloids in particles with aerodynamic diameter (Dp) smaller than 2.5 μm are found to be ubiquitous in southern Arizona. The major sources of the elements considered in the study are identified to be crustal dust, smelting/mining activities and fuel combustion. The spatial and temporal variability in the mass concentrations of these elements depend both on the source strength and meteorological conditions. Aircraft measurements of aerosol and cloud properties collected during various field campaigns over the eastern Pacific Ocean are used to study the sources of nitrate in stratocumulus cloud water and the relevant processes. The major sources of nitrate in cloud water in the region are emissions from ships and wildfires. Different pathways for nitrate to enter cloud water and the role of meteorology in these processes are examined. Observations of microphysical properties of ambient aerosols in ship plumes are examined. The study shows that there is an enhancement in the number concentration of giant cloud condensation nuclei (Dp > 2 microm) in ship plumes relative to the unperturbed background regions over the ocean.
Gary Achtemeier
2012-01-01
A cellular automata fire model represents âelementsâ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for âsuper-diffusiveâ fire spread and coupled surface-layer (2-m) fireâatmosphere processes. Pressure anomalies, which are integrals of the thermal...
Toward Seamless Weather-Climate Prediction with a Global Cloud Resolving Model
2016-01-14
distribution is unlimited. TOWARD SEAMLESS WEATHER- CLIMATE PREDICTION WITH A GLOBAL CLOUD RESOLVING MODEL PI: Tim Li IPRC/SOEST, University of Hawaii at...Project Final Report 3. DATES COVERED (From - To) 1 May 2012 - 30 September 2015 4. TITLE AND SUBTITLE TOWARD SEAMLESS WEATHER- CLIMATE PREDICTION WITH...A GLOBAL CLOUD RESOLVING MODEL 5a. CONTRACT NUMBER 5b. GRANT NUMBER N000141210450 5c. PROGRAM ELEMENT NUMBER ONR Marine Meteorology Program 6
NASA Astrophysics Data System (ADS)
Wen, Xiaohang; Dong, Wenjie; Yuan, Wenping; Zheng, Zhiyuan
For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global Land Data Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We find that the simulated results of monthly 2 m temperature from HRADC is improved compared with the control simulation and has effectively reproduced the observed patterns. The simulated special distribution of ground surface temperature and specific humidity from HRADC are much closer to GLDAS outputs. The spatial distribution of root mean square errors (RMSE) and bias of 2 m temperature between observations and HRADC is reduced compared with the bias between observations and the control run. The monthly spatial distribution of surface temperature and specific humidity from HRADC is consistent with the GLDAS outputs over China. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations, and the simulated results could be used in further research on the long-term climatic effects and characteristics of the water-energy cycle over China.
An airborne meteorological data collection system using satellite relay (ASDAR)
NASA Technical Reports Server (NTRS)
Bagwell, J. W.; Lindow, B. G.
1978-01-01
The National Aeronautics and Space Administration (NASA) has developed an airborne data acquisition and communication system for the National Oceanic and Atmospheric Administration (NOAA). This system known as ASDAR, the Aircraft to Satellite Data Relay, consists of a microprocessor based controller, time clock, transmitter and antenna. Together they acquire meteorological and position information from existing aircraft systems on B-747 aircraft, convert and format these, and transmit them to the ground via the GOES meteorological satellite series. The development and application of the ASDAR system is described with emphasis on unique features. Performance to date is exceptional, providing horizon-to-horizon coverage of aircraft flights. The data collected is of high quality and is considered a valuable addition to the data base from which NOAA generates its weather forecasts.
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.
European Meteorological Society and education in atmospheric sciences
NASA Astrophysics Data System (ADS)
Halenka, T.; Belda, M.
2010-09-01
EMS is supporting the exchange of information in the area of education in atmospheric sciences as one of its priority and organizing the educational sessions during EMS annual meetings as a good occasion for such an exchange. Brief thought will be given to the fate of the series of International Conferences on School and Popular Meteorological and Oceanographic Education - EWOC (Education in Weather, Ocean and Climate) and to the project oriented basis of further cooperation in education in atmospheric sciences across Europe. Another tool of EMS is the newly established and developed EDU portal of EMS. In most European countries the process of integration of education at university level was started after Bologna Declaration with the objective to have the system where students on some level could move to another school, or rather university. The goal is to achieve the compatibility between the systems and levels in individual countries to have no objections for students when transferring between the European countries. From this point of view EMS is trying to provide the information about the possibility of education in meteorology and climatology in different countries in centralised form, with uniform shape and content, but validated on national level. In most European countries the necessity of education in Science and Mathematics to achieve higher standard and competitiveness in research and technology development has been formulated after the Lisboa meeting. The European Meteorological Society is trying to follow this process with implication to atmospheric sciences. One of the important task of the EMS is the activity to promote public understanding of meteorology (and sciences related to it), and the ability to make use of it, through schools and more generally. One of the elements of EMS activity is the analysis of the position of atmospheric science in framework of curricula in educational systems of European countries as well as in more general sense, the place of Science education in the system.
NASA Technical Reports Server (NTRS)
Mckenna, D. S.; Jones, R. L.; Buckland, A. T.; Austin, J.; Tuck, A. F.; Winkler, R. H.; Chan, K. R.
1989-01-01
This paper presents a series of meteorological analyses used to aid the interpretation of the in situ Airborne Antarctic Ozone Experiment (AAOE) observations obtained aboard the ER-2 and DC-8 aircraft and examines the basis and accuracy of the analytical procedure. Maps and sections of meteorological variables derived from the UK Meteorological Office Global Model are presented for ER-2 and DC-8 flight days. It is found that analyzed temperatures and winds are generally in good agreement with AAOE observations at all levels; minor discrepancies were evident only at DC-8 altitudes. Maps of potential vorticity presented on the 428-K potential temperature surface show that the vortex is essentially circumpolar, although there are periods when major distortions are apparent.
NASA Technical Reports Server (NTRS)
Lambert, Winifred C.; Merceret, Francis J. (Technical Monitor)
2002-01-01
This report describes the results of the ANU's (Applied Meteorology Unit) Short-Range Statistical Forecasting task for peak winds. The peak wind speeds are an important forecast element for the Space Shuttle and Expendable Launch Vehicle programs. The Keith Weather Squadron and the Spaceflight Meteorology Group indicate that peak winds are challenging to forecast. The Applied Meteorology Unit was tasked to develop tools that aid in short-range forecasts of peak winds at tower sites of operational interest. A 7 year record of wind tower data was used in the analysis. Hourly and directional climatologies by tower and month were developed to determine the seasonal behavior of the average and peak winds. In all climatologies, the average and peak wind speeds were highly variable in time. This indicated that the development of a peak wind forecasting tool would be difficult. Probability density functions (PDF) of peak wind speed were calculated to determine the distribution of peak speed with average speed. These provide forecasters with a means of determining the probability of meeting or exceeding a certain peak wind given an observed or forecast average speed. The climatologies and PDFs provide tools with which to make peak wind forecasts that are critical to safe operations.
Making the Introductory Meteorology Class Relevant in a Minority Serving Community College
NASA Astrophysics Data System (ADS)
Marchese, P. J.; Tremberger, G.; Bluestone, C.
2008-12-01
Queensborough Community College (QCC), a constituent campus of the City University of New York (CUNY), has modified the introductory Meteorology Class lecture and lab to include active learning activities and discovery based learning. The modules were developed at QCC and other 4 year colleges and designed to introduce basic physical concepts important in meteorology. The modules consisted of either interactive lecture demonstrations or discovery-based activities. The discovery based activities are intended to have students become familiar with scientific investigation. Students engage in formulating hypotheses, developing and carrying out experiments, and analyzing scientific data. These activities differ from traditional lab experiments in that they avoid "cookbook" procedures and emphasize having the students learn about physical concepts by applying the scientific method. During the interactive lecture demonstrations the instructor describes an experiment/phenomenon that is to be demonstrated in class. Students discuss the phenomenon based on their experiences and make a prediction about the outcome. The class then runs the experiment, makes observations, and compares the expected results to the actual outcome. As a result of these activities students in the introductory Meteorology class scored higher in exams questions measuring conceptual understanding, as well as factual knowledge. Lower scoring students demonstrated the greatest benefit, while the better students had little (or no) changes. All students also had higher self-efficacy scores after the intervention, compared to an unmodified class.
Meteorological tower design for severe weather and remote locations
Kelly Elder; Ilkoo Angutikjuak; Jessica Baker; Matt Belford; Tom Bennett; Karl Birkeland; Daniel Bowker; Doug Chabot; April Cheuvront; Mark Dixon; Dylan Elder; Lee Elder; Shari Gearheard; Greg Giedt; Kim Grant; Sam Green; Ethan Greene; Nick Houfek; Caleb Huntington; Henry Huntington; Thomas Huntington; Daniel Janigian; Crane Johnson; Glen Liston; Rob Maris; Andrea Marsh; Hans-Peter Marshall; Aidan Meiners; Alex Meiners; Theo Meiners; Limakee Palluq; Josh Pope; Esa Qillaq; Joelli Sanguya; Sam Sehnert; Ron Simenhois; Banning Starr; Roger Tyler
2012-01-01
We have developed a robust meteorological tower for deployment in locations with extreme conditions and for applications that require relatively maintenance-free structures. The basic design consists of a triangular base with two horizontal rails on each side, and uprights at the triangle vertices for various instrument configurations. The fabrication materials include...
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.
Ozone time scale decomposition and trend assessment from surface observations
NASA Astrophysics Data System (ADS)
Boleti, Eirini; Hueglin, Christoph; Takahama, Satoshi
2017-04-01
Emissions of ozone precursors have been regulated in Europe since around 1990 with control measures primarily targeting to industries and traffic. In order to understand how these measures have affected air quality, it is now important to investigate concentrations of tropospheric ozone in different types of environments, based on their NOx burden, and in different geographic regions. In this study, we analyze high quality data sets for Switzerland (NABEL network) and whole Europe (AirBase) for the last 25 years to calculate long-term trends of ozone concentrations. A sophisticated time scale decomposition method, called the Ensemble Empirical Mode Decomposition (EEMD) (Huang,1998;Wu,2009), is used for decomposition of the different time scales of the variation of ozone, namely the long-term trend, seasonal and short-term variability. This allows subtraction of the seasonal pattern of ozone from the observations and estimation of long-term changes of ozone concentrations with lower uncertainty ranges compared to typical methodologies used. We observe that, despite the implementation of regulations, for most of the measurement sites ozone daily mean values have been increasing until around mid-2000s. Afterwards, we observe a decline or a leveling off in the concentrations; certainly a late effect of limitations in ozone precursor emissions. On the other hand, the peak ozone concentrations have been decreasing for almost all regions. The evolution in the trend exhibits some differences between the different types of measurement. In addition, ozone is known to be strongly affected by meteorology. In the applied approach, some of the meteorological effects are already captured by the seasonal signal and already removed in the de-seasonalized ozone time series. For adjustment of the influence of meteorology on the higher frequency ozone variation, a statistical approach based on Generalized Additive Models (GAM) (Hastie,1990;Wood,2006), which corrects for meteorological effects, has been developed in order to a) investigate if trends are masked by meteorological variability and b) to understand which part of the observed trends is meteorology driven. By correlating short-term variation of ozone, as obtained from the EEMD, with the corresponding short-term variation of relevant meteorological parameters, we subtract the variation of ozone concentrations that is related to the meteorological effects explained by the GAM. We find that higher frequency meteorological correction reduces further the uncertainty in trend estimation by a small factor. In addition, the seasonal variability of ozone as obtained from the EEMD has been studied in more detail for possible changes in its behavior. A shortening of the seasonal cycle was observed, i.e. reduction of maximum and in-crease of minimum concentration per year, while the occurrence of maximum is shifted to earlier times during a year. In summary, we present a sophisticated and consistent approach for detecting and categorizing trends and meteorological influences on ozone concentrations in long-term measurements across Europe.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fan, Linlin; Wang, Hongrui; Wang, Cheng
Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI.more » The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.« less
Fan, Linlin; Wang, Hongrui; Wang, Cheng; ...
2017-05-16
Drought risk analysis is essential for regional water resource management. In this study, the probabilistic relationship between precipitation and meteorological drought in Beijing, China, was calculated under three different precipitation conditions (precipitation equal to, greater than, or less than a threshold) based on copulas. The Standardized Precipitation Evapotranspiration Index (SPEI) was calculated based on monthly total precipitation and monthly mean temperature data. The trends and variations in the SPEI were analysed using Hilbert-Huang Transform (HHT) and Mann-Kendall (MK) trend tests with a running approach. The results of the HHT and MK test indicated a significant decreasing trend in the SPEI.more » The copula-based conditional probability indicated that the probability of meteorological drought decreased as monthly precipitation increased and that 10 mm can be regarded as the threshold for triggering extreme drought. From a quantitative perspective, when R ≤ mm, the probabilities of moderate drought, severe drought, and extreme drought were 22.1%, 18%, and 13.6%, respectively. This conditional probability distribution not only revealed the occurrence of meteorological drought in Beijing but also provided a quantitative way to analyse the probability of drought under different precipitation conditions. Furthermore, the results provide a useful reference for future drought prediction.« less
Latin American Network of students in Atmospheric Sciences and Meteorology
NASA Astrophysics Data System (ADS)
Cuellar-Ramirez, P.
2017-12-01
The Latin American Network of Students in Atmospheric Sciences and Meteorology (RedLAtM) is a civil nonprofit organization, organized by students from Mexico and some Latin- American countries. As a growing organization, providing human resources in the field of meteorology at regional level, the RedLAtM seeks to be a Latin American organization who helps the development of education and research in Atmospheric Sciences and Meteorology in order to engage and promote the integration of young people towards a common and imminent future: Facing the still unstudied various weather and climate events occurring in Latin America. The RedLAtM emerges from the analysis and observation/realization of a limited connection between Latin American countries around research in Atmospheric Sciences and Meteorology. The importance of its creation is based in cooperation, linking, research and development in Latin America and Mexico, in other words, to join efforts and stablish a regional scientific integration who leads to technological progress in the area of Atmospheric Sciences and Meteorology. As ultimate goal the RedLAtM pursuit to develop climatic and meteorological services for those countries unable to have their own programs, as well as projects linked with the governments of Latin American countries and private companies for the improvement of prevention strategies, research and decision making. All this conducing to enhance the quality of life of its inhabitants facing problems such as poverty and inequality.
NASA Astrophysics Data System (ADS)
Spasova, Z.
2010-09-01
Introduction Given the proven effects of weather on the human organism, an attempt to examine its effects on a psychic and emotional level has been made. Emotions affect the bio-tonus, working ability and concentration, hence their significance in various domains of economic life, such as health care, education, transportation, tourism, etc. Data and methods The research has been made in Sofia City within a period of 8 months, using 5 psychological methods (Eysenck Personality Questionnaire (EPQ), State-Trait Anxiety Inventory (STAI), Test for Self-assessment of the emotional state (developed by Wessman and Ricks), Test for evaluation of moods and Test "Self-confidence - Activity - Mood" (developed by the specialists from the Military Academy in Saint Petersburg). The Fiodorov-Chubukov's complex-climatic method was used to characterize meteorological conditions because of the purpose to include in the analysis a maximal number of meteorological elements. 16 weather types are defined in dependence of the meteorological elements values according to this method. Abrupt weather changes from one day to another, defined by the same method, were considered as well. Results and discussions The results obtained by t-test show that the different categories of weather lead to changes in the emotional status, which indicates a character either positive or negative for the organism. The abrupt weather changes, according to expectations, have negative effect on human emotions but only when a transition to the cloudy weather or weather type, classified as "unfavourable" has been realized. The relationship between weather and human emotions is rather complicated since it depends on individual characteristics of people. One of these individual psychological characteristics, marked by the dimension "neuroticism", has a strong effect on emotional reactions in different weather conditions. Emotionally stable individuals are more "protected" to the weather influence on their emotions, while those who are emotionally unstable have a stronger dependence to the impacts of the weather.
Weather types and strokes in the Augsburg region (Southern Germany)
NASA Astrophysics Data System (ADS)
Beck, Christoph; Ertl, Michael; Giemsa, Esther; Jacobeit, Jucundus; Naumann, Markus; Seubert, Stefanie
2017-04-01
Strokes are one of the leading causes of morbidity and mortality worldwide and the main reason for longterm care dependency in Germany. Concerning the economical impact on patients and healthcare systems it is of particular importance to prevent this disease as well as to improve the outcome of the affected persons. Beside the primary well-known risk factors like hypertension, cigarette smoking, physical inactivity and others, also weather seems to have pronounced influence on the occurrence and frequency of strokes. Previous studies most often focused on effects of singular meteorological variables like ambient air temperature, air pressure or humidity. An advanced approach is to link the entire suite of daily weather elements classified to air mass- or weather types to cerebrovascular morbidity or mortality. In a joint pilot study bringing together climatologists, environmental scientists and physicians from the University of Augsburg and the clinical centre Augsburg, we analysed relationships between singular meteorological parameters as well as combined weather effects (e.g. weather types) and strokes in the urban area of Augsburg and the surrounding rural region. A total of 17.501 stroke admissions to Neurological Clinic and Clinical Neurophysiology at Klinikum Augsburg between 2006 and 2015 are classified to either "ischaemic" (16.354) or "haemorrhagic" (1.147) subtype according to etiology (based on the International Classification of Diseases - 10th Revision). Spearman correlations between daily frequencies of ischaemic and haemorrhagic strokes and singular atmospheric parameters (T, Tmin, Tmax, air pressure, humidity etc.) measured at the DWD (German weather service) meteorological station at Augsburg Muehlhausen are rather low. However, higher correlations are achieved when considering sub-samples of "homogenous weather conditions" derived from synoptic circulation classifications: e.g. within almost all of 10 types arising from a classification of central European mean sea level pressure fields into "Großwettertypes" (Beck 2000) the relationships between meteorological variables and stroke frequencies are increasing. Mainly temperature variables (Tmin, Tmax, Tmean) appear to be important particularly in winter and summer. Moreover distinct correlations of similar magnitude are obtained with other variables like wind speed or precipitation for specific weather types (e.g. westerly type). In how far these initial findings do really point to additional health impacts beyond temperature effects is subject of ongoing work.
Surface and Tower Meteorological Instrumentation at NSA Handbook - January 2006
DOE Office of Scientific and Technical Information (OSTI.GOV)
MT Ritsche
2006-01-30
The Surface and Tower Meteorological Instrumentation at Atqasuk (METTWR2H) uses mainly conventional in situ sensors to measure wind speed, wind direction, air temperature, dew point and humidity mounted on a 10-m tower. It also obtains barometric pressure, visibility, and precipitation data from sensors at or near the base of the tower. In addition, a Chilled Mirror Hygrometer is located at 1 m for comparison purposes. Temperature and relative humidity probes are mounted at 2 m and 5 m on the tower. For more information, see the Surface and Tower Meteorological Instrumentation at Atqasuk Handbook.
Compositional variability of the aerosols collected on Kerkennah Islands (central Tunisia)
NASA Astrophysics Data System (ADS)
Trabelsi, A.; Masmoudi, M.; Quisefit, J. P.; Alfaro, S. C.
2016-03-01
The aim of the present study is to investigate the seasonal variability of the aerosol concentrations and origins in central Tunisia. Four field campaigns were carried out in 2010/2011 to collect air-suspended particles on the Kerkennah Islands. The elemental composition (Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, Cr, Mn, Fe, Cu, Zn, Pb, Ni, V, and As) of the particles collected in summer (June and July), autumn (September and November), winter (February and March), and spring (April and May) is determined by X-ray fluorescence analysis. Examination of the enrichment factors (EF) of all elements indicate that Al, Fe, Si, Ca, Ti, Mn, and Cr are mainly derived from soil sources, whereas Na and Cl are mostly of marine origin. Other elements such as K and Mg or S and P have multiple origins (Marine/crustal and crustal/anthropogenic, respectively). Finally, V, Cu, Ni, As, and Pb appear to be produced by anthropogenic activities. Based on the inter-elemental correlations, the mass concentrations of mineral dust (MD), sea-salt (SS) and anthropogenic (non-crustal and non-marine) sulfates (NSS) are quantified. MD, SS and NSS display significant inter-seasonal differences: on the one hand, MD and SS are the highest in spring and the lowest in winter, probably because of the seasonal change in meteorological conditions. On the other hand, NSS and Cu concentrations are above their autumn and winter values in spring and summer, which suggests the existence of a common source of the combustion type for these two pollutants.
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.
2011-01-01
Background The evaluation of exposure to ambient temperatures in epidemiological studies has generally been based on records from meteorological stations which may not adequately represent local temperature variability. Here we propose a spatially explicit model to estimate local exposure to temperatures of large populations under various meteorological conditions based on satellite and meteorological data. Methods A general linear model was used to estimate surface temperatures using 15 LANDSAT 5 and LANDSAT 7 images for Quebec Province, Canada between 1987 and 2002 and spanning the months of June to August. The images encompassed both rural and urban landscapes and predictors included: meteorological records of temperature and wind speed, distance to major water bodies, Normalized Differential Vegetation Index (NDVI), land cover (built and bare land, water, or vegetation), latitude, longitude, and week of the year. Results The model explained 77% of the variance in surface temperature, accounting for both temporal and spatial variations. The standard error of estimates was 1.42°C. Land cover and NDVI were strong predictors of surface temperature. Conclusions This study suggests that a statistical approach to estimating surface temperature incorporating both spatially explicit satellite data and time-varying meteorological data may be relevant to assessing exposure to heat during the warm season in the Quebec. By allowing the estimation of space- and time-specific surface temperatures, this model may also be used to assess the possible impacts of land use changes under various meteorological conditions. It can be applied to assess heat exposure within a large population and at relatively fine-grained scale. It may be used to evaluate the acute health effect of heat exposure over long time frames. The method proposed here could be replicated in other areas around the globe for which satellite data and meteorological data is available. PMID:21251286
A program and data base for evaluating SMMR algorithms
NASA Technical Reports Server (NTRS)
1979-01-01
A program (PARAM) is described which enables a user to compare the values of meteorological parameters derived from data obtained by the scanning multichannel microwave radiometer (SMMR) instrument on NIMBUS 7 with surface observations made over the ocean. The input to this program is a data base, also described, which contains the surface observations and coincident SMMR data. The evaluation of meteorological parameters using SMMR data is done by a user supplied subroutine. Instruments are given for executing the program and writing the subroutine.
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.
A meteorological distribution system for high-resolution terrestrial modeling (MicroMet)
Glen E. Liston; Kelly Elder
2006-01-01
An intermediate-complexity, quasi-physically based, meteorological model (MicroMet) has been developed to produce high-resolution (e.g., 30-m to 1-km horizontal grid increment) atmospheric forcings required to run spatially distributed terrestrial models over a wide variety of landscapes. The following eight variables, required to run most terrestrial models, are...
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...
REDRAW-Based Evapotranspiration Estimation in Chongli, North China
NASA Astrophysics Data System (ADS)
Zhang, Z.; Wang, Z.
2017-12-01
Evapotranspiration (ET) is the key component of hydrological cycle and spatial estimates of ET are important elements of atmospheric circulation and hydrologic models. Quantifying the ET over large region is significant for water resources planning, hydrologic water balances, water rights management, and water division. In this study, Evapotranspiration (ET) was estimated using REDRAW model in the Chongli on 2014. REDRAW is a satellite-based balance algorithm with reference dry and wet limits model developed to estimate ET. Remote sensing data obtained from MODIS and meteorological data from China Meteorological Data Sharing Service System were used in ET model. In order to analyze the distribution and time variation of ET over the study region, daily, monthly and yearly ET were calculated for the study area, and ET of different land cover types were calculated. In terms of the monthly ET, the figure was low in winter and high in other seasons, and reaches the maximum value in August, showing a high monthly difference. The ET value of water body was the highest and that of barren or sparse vegetation were the lowest, which accorded with local actual condition. Evaluating spatial temporal distribution of actual ET could assist to understand the water consumption regularity in region and figure out the effect from different land cover, which helped to establish links between land use, water allocation, and water use planning in study region. Due to the groundwater recession in north China, the evaluation of regional total water resources become increasingly essential, and the result of this study can be used to plan the water use. As the Chongli will prepare the ski slopes for Winter Olympics on 2022, accuracy estimation of actual ET can efficiently resolve water conflict and relieve water scarcity.
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.
Applications of "Integrated Data Viewer'' (IDV) in the classroom
NASA Astrophysics Data System (ADS)
Nogueira, R.; Cutrim, E. M.
2006-06-01
Conventionally, weather products utilized in synoptic meteorology reduce phenomena occurring in four dimensions to a 2-dimensional form. This constitutes a road-block for non-atmospheric-science majors who need to take meteorology as a non-mathematical and complementary course to their major programs. This research examines the use of Integrated Data Viewer-IDV as a teaching tool, as it allows a 4-dimensional representation of weather products. IDV was tested in the teaching of synoptic meteorology, weather analysis, and weather map interpretation to non-science students in the laboratory sessions of an introductory meteorology class at Western Michigan University. Comparison of student exam scores according to the laboratory teaching techniques, i.e., traditional lab manual and IDV was performed for short- and long-term learning. Results of the statistical analysis show that the Fall 2004 students in the IDV-based lab session retained learning. However, in the Spring 2005 the exam scores did not reflect retention in learning when compared with IDV-based and MANUAL-based lab scores (short term learning, i.e., exam taken one week after the lab exercise). Testing the long-term learning, seven weeks between the two exams in the Spring 2005, show no statistically significant difference between IDV-based group scores and MANUAL-based group scores. However, the IDV group obtained exam score average slightly higher than the MANUAL group. Statistical testing of the principal hypothesis in this study, leads to the conclusion that the IDV-based method did not prove to be a better teaching tool than the traditional paper-based method. Future studies could potentially find significant differences in the effectiveness of both manual and IDV methods if the conditions had been more controlled. That is, students in the control group should not be exposed to the weather analysis using IDV during lecture.
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.
Round table discussion " Development of qualification framework in meteorology (TEMPUS QUALIMET)"
NASA Astrophysics Data System (ADS)
Bashmakova, I.; Belotserkovsky, A.; Karlin, L.; Petrosyan, A.; Serditova, N.; Zilitinkevich, S.
2010-09-01
The international consortium has started implementing a project aimed at the development of unified framework of qualifications in meteorology (QualiMet), setting a system of recognition and award of qualifications up to Doctoral level based on standards of knowledge, skill and competence acquired by learners is underway. The QualiMet has the following specific objectives: 1. To develop standards of knowledge, skills and competence for all qualifications up to Doctoral level needed in all possible occupations meteorology learner can undertake, by July 2011 2. To develop reciprocally recognized rubrics, criteria, methods and tools for assessing the compliance with the developed standards (quality assurance), by July 2012 3. To set the network of Centers of Excellence as the primary designer of sample education programs and learning experiences, both in brick-and-mortar and distant setting of delivery, leading to achievement of the developed standards, by December 2012 4. To set a system of mutual international recognition and award of qualifications in meteorology based on the developed procedures and establishment of self-regulatory public organization, by December 2012 The main beneficiaries of the project are: 1. Meteorology learners from the consortium countries. They will be able to make informed decisions about available qualification choices and progression options and provided an opportunity for students and graduates to participate in the system of international continuous education. 2. Meteorology employers from the consortium countries, They will be able to specify the level of knowledge, skill and competence required for occupational roles, evaluate qualifications presented, connect training and development with business needs. 3. Students and academic staff of all the consortium members, who will gain the increased mobility and exchange the fluxes of culturally and institutionally diversified lecturers and qualified specialists
Thermal IR exitance model of a plant canopy
NASA Technical Reports Server (NTRS)
Kimes, D. S.; Smith, J. A.; Link, L. E.
1981-01-01
A thermal IR exitance model of a plant canopy based on a mathematical abstraction of three horizontal layers of vegetation was developed. Canopy geometry within each layer is quantitatively described by the foliage and branch orientation distributions and number density. Given this geometric information for each layer and the driving meteorological variables, a system of energy budget equations was determined and solved for average layer temperatures. These estimated layer temperatures, together with the angular distributions of radiating elements, were used to calculate the emitted thermal IR radiation as a function of view angle above the canopy. The model was applied to a lodgepole pine (Pinus contorta) canopy over a diurnal cycle. Simulated vs measured radiometric average temperatures of the midcanopy layer corresponded with 2 C. Simulation results suggested that canopy geometry can significantly influence the effective radiant temperature recorded at varying sensor view angles.
Development of the Semi-implicit Time Integration in KIM-SH
NASA Astrophysics Data System (ADS)
NAM, H.
2015-12-01
The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. The KIM-SH is a KIAPS integrated model-spectral element based in the HOMME. In KIM-SH, the explicit schemes are employed. We introduce the three- and two-time-level semi-implicit scheme in KIM-SH as the time integration. Explicit schemes however have a tendancy to be unstable and require very small timesteps while semi-implicit schemes are very stable and can have much larger timesteps.We define the linear and reference values, then by definition of semi-implicit scheme, we apply the linear solver as GMRES. The numerical results from experiments will be introduced with the current development status of the time integration in KIM-SH. Several numerical examples are shown to confirm the efficiency and reliability of the proposed schemes.
Microphysics, Meteorology, Microwave and Modeling of Mediterranean Storms: The M(sup 5) Problem
NASA Technical Reports Server (NTRS)
Smith, Eric A.; Fiorino, Steven; Mugnai, Alberto; Panegrossi, Giulia; Tripoli, Gregory; Starr, David (Technical Monitor)
2001-01-01
Comprehensive understanding of the microphysical nature of Mediterranean storms requires a combination of in situ meteorological data analysis and radar-passive microwave data analysis, effectively integrated with numerical modeling studies at various scales, particularly from synoptic scale down to mesoscale. The microphysical properties of and their controls on severe storms are intrinsically related to meteorological processes under which storms have evolved, processes which eventually select and control the dominant microphysical properties themselves. Insofar as hazardous Mediterranean storms, highlighted by the September 25-28/1992 Genova flood event, the October 5-7/1998 Friuli flood event, and the October 13-15/2000 Piemonte flood event (all taking place in northern Italy), developing a comprehensive microphysical interpretation requires an understanding of the multiple phases of storm evolution and the heterogeneous nature of precipitation fields within the storm domains. This involves convective development, stratiform transition and decay, orographic lifting, and sloped frontal lifting proc esses. This also involves vertical motions and thermodynamical instabilities governing physical processes that determine details of the liquid/ice water contents, size distributions, and fall rates of the various modes of hydrometeors found within the storm environments. This paper presents detailed 4-dimensional analyses of the microphysical elements of the three severe Mediterranean storms identified above, investigated with the aid of SSM/I and TRMM satellite measurements (and other remote sensing measurements). The analyses are guided by nonhydrostatic mesoscale model simulations at high resolution of the intense rain producing portions of the storm environments. The results emphasize how meteorological controls taking place at the large scale, coupled with localized terrain controls, ultimately determine the most salient features of the bulk microphysical properties of the storms. These results have bearing on precipitation remote sensing from space, and the role of modeling in designing precipitation retrieval algorithms.
NASA Astrophysics Data System (ADS)
Dudley, R. W.; Hodgkins, G. A.; Nielsen, M. G.; Qi, S. L.
2018-07-01
A number of previous studies have examined relations between groundwater levels and hydrologic and meteorological variables over parts of the glacial aquifer system, but systematic analyses across the entire U.S. glacial aquifer system are lacking. We tested correlations between monthly groundwater levels measured at 1043 wells in the U.S. glacial aquifer system considered to be minimally influenced by human disturbance and selected hydrologic and meteorological variables with the goal of extending historical groundwater records where there were strong correlations. Groundwater levels in the East region correlated most strongly with short-term (1 and 3 month) averages of hydrologic and meteorological variables, while those in the Central and West Central regions yielded stronger correlations with hydrologic and meteorological variables averaged over longer time intervals (6-12 months). Variables strongly correlated with high and low annual groundwater levels were identified as candidate records for use in statistical linear models as a means to fill in and extend historical high and low groundwater levels respectively. Overall, 37.4% of study wells meeting data criteria had successful models for high and (or) low groundwater levels; these wells shared characteristics of relatively higher local precipitation, higher local land-surface slope, lower amounts of clay within the surficial sediments, and higher base-flow index. Streamflow and base flow served as explanatory variables in about two thirds of both high- and low-groundwater-level models in all three regions, and generally yielded more and better models compared to precipitation and Palmer Drought Severity Index. The use of variables such as streamflow with substantially longer and more complete records than those of groundwater wells provide a means for placing contemporary groundwater levels in a longer historical context and can support site-specific analyses such as groundwater modeling.
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.
Darniot, Magali; Pitoiset, Cécile; Millière, Laurine; Aho-Glélé, Ludwig Serge; Florentin, Emmanuel; Bour, Jean-Baptiste; Manoha, Catherine
2018-05-05
Both human metapneumovirus (hMPV) and respiratory syncytial virus (RSV) cause epidemics during the cold season in temperate climates. The purpose of this study was to find out whether climatic factors are associated with RSV and hMPV epidemics. Our study was based on data from 4300 patients admitted to the Dijon University Hospital for acute respiratory infection (ARI) over three winter seasons chosen for their dissimilar meteorological and virological patterns. Cases of hMPV and RSV were correlated with meteorological parameters recorded in the Dijon area. The relationship between virus data and local meteorological conditions was analyzed by univariate and multivariate negative binomial regression analysis. RSV detection was inversely associated with temperature and positively with relative humidity and air pressure, whereas hMPV was inversely associated with temperature and positively with wind speed. The association among meteorological variables and weekly ARIs cases due to RSV and hMPV demonstrated the relevance of climate factors as contributors to both hMPV and RSV activities. Meteorological drivers of RSV and hMPV epidemics are different. Low temperatures influence both hMPV and RSV activity. Relative humidity is an important predictor of RSV activity, but it does not influence hMPV activity. Copyright © 2018 Elsevier B.V. All rights reserved.
Owen-Joyce, Sandra J.; Brown, Paul W.
1995-01-01
Data were collected at temporary meteorological stations installed in agricultural fields in Pinal County, Arizona, to evaluate the spatial and temporal variability of point data and to examine how station location affects ground-based meteorological data and the resulting values of evapotranspiration calculated using remotely sensed multispectral data from satellites. Time-specific data were collected to correspond with satellite overpasses from April to October 1989, and June 27-28, 1990. Meteorological data consisting of air temperature, relative humidity, wind speed, solar radiation, and net radiation were collected at each station during all periods of the project. Supplementary measurements of soil temperature, soil heat flux density, and surface or canopy temperature were obtained at some locations during certain periods of the project. Additional data include information on data-collection periods, station positions, instrumentation, sensor heights, and field dimensions. Other data, which correspond to the extensive field measurements made in con- junction with satellite overpasses in 1989 and 1990, include crop type, canopy cover, canopy height, irrigation, cultivation, and orientation of rows. Field boundaries and crop types were mapped in a 2- to 3-square-kilometer area surrounding each meteorological station. Field data are presented in tabular and graphic form. Meteorological and supplementary data are available, upon request, in digital form.
NASA Astrophysics Data System (ADS)
Réveillet, Marion; Six, Delphine; Vincent, Christian; Rabatel, Antoine; Dumont, Marie; Lafaysse, Matthieu; Morin, Samuel; Vionnet, Vincent; Litt, Maxime
2018-04-01
This study focuses on simulations of the seasonal and annual surface mass balance (SMB) of Saint-Sorlin Glacier (French Alps) for the period 1996-2015 using the detailed SURFEX/ISBA-Crocus snowpack model. The model is forced by SAFRAN meteorological reanalysis data, adjusted with automatic weather station (AWS) measurements to ensure that simulations of all the energy balance components, in particular turbulent fluxes, are accurately represented with respect to the measured energy balance. Results indicate good model performance for the simulation of summer SMB when using meteorological forcing adjusted with in situ measurements. Model performance however strongly decreases without in situ meteorological measurements. The sensitivity of the model to meteorological forcing indicates a strong sensitivity to wind speed, higher than the sensitivity to ice albedo. Compared to an empirical approach, the model exhibited better performance for simulations of snow and firn melting in the accumulation area and similar performance in the ablation area when forced with meteorological data adjusted with nearby AWS measurements. When such measurements were not available close to the glacier, the empirical model performed better. Our results suggest that simulations of the evolution of future mass balance using an energy balance model require very accurate meteorological data. Given the uncertainties in the temporal evolution of the relevant meteorological variables and glacier surface properties in the future, empirical approaches based on temperature and precipitation could be more appropriate for simulations of glaciers in the future.
ERIC Educational Resources Information Center
Brown, Mary; Dickinson, Rosemary
This book consists of two complete units on meteorology. The first unit is created for lower elementary students and the second one is for upper elementary grade levels. The units are designed for gifted students and encourage students to be responsible for their own education. Each unit is based on an interdisciplinary approach. Suggestions for…
Modeling the Effects of Meteorological Conditions on the Neutron Flux
2017-05-22
a statistical model that predicts environmental neutron background as a function of five meteorological variables: inverse barometric pressure...variable of the model was inverse barometric pressure with a contribution an order of magnitude larger than any other variable’s contribution. The...is based on the sensitivity of each sensor. . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.2 Neutron counts from the LNS and inverse pressure
NASA Astrophysics Data System (ADS)
Lin, J.
2011-12-01
Nitrogen oxides (NOx ≡ NO + NO2) are important atmospheric constituents affecting the tropospheric chemistry, surface air quality and climatic forcing. They are emitted both from anthropogenic and from natural (soil, lightning, biomass burning, etc.) sources, which can be estimated inversely from satellite remote sensing of the vertical column densities (VCDs) of nitrogen dioxide (NO2) in the troposphere. Based on VCDs of NO2 retrieved from OMI, a novel approach is developed in this study to separate anthropogenic emissions of NOx from natural sources over East China for 2006. It exploits the fact that anthropogenic and natural emissions vary with seasons with distinctive patterns. The global chemical transport model (CTM) GEOS-Chem is used to establish the relationship between VCDs of NO2 and emissions of NOx for individual sources. Derived soil emissions are compared to results from a newly developed bottom-up approach. Effects of uncertainties in model meteorology and chemistry over China, an important source of errors in the emission inversion, are evaluated systematically for the first time. Meteorological measurements from space and the ground are used to analyze errors in meteorological parameters driving the CTM.
Wu, Yan-feng; Bake, Batur; Li, Wei; Wei, Xiao-qin; Wozatihan, Jiayinaguli; Rasulov, Hamid
2015-02-01
Based on the daily meteorological data of seven stations in Altay region, China, this study investigated the temporal ( seasonal, inter-annual and decadal) and spatial variations of drought by using composite index of meteorological drought, as well as trend analysis, M-K abrupt analysis, wavelet analysis and interpolation tools in ArcGIS. The results indicated that the composite index of meteorological drought could reflect the drought condition in Altay region well. Although the frequency and the covered area of both inter-annual and seasonal droughts presented decreasing trends in the recent 52 a, the drought was still serious when considering the annual drought. The frequencies of inter-annual and spring droughts had no abrupt changes, whereas the frequencies of inter-summer, autumn and winter droughts had abrupt changes during the past 52 a. A significant periodic trend was also observed for the frequencies of inter-annual and seasonal droughts. The distribution of frequency and covered area suggested that the conditions of drought were heavily serious in Qinghe County, moderately serious in Altay City, Fuyun County, Buerjin County and Fuhai County, and slightly serious in Habahe County and Jimunai County.
The Nimbus 4 data catalog. Volume 5: 1 November - 31 December 1970, data orbits 2776-3594
NASA Technical Reports Server (NTRS)
1971-01-01
A catalog of data acquired from the Nimbus 4 meteorological satellite is presented. The volume covers the period 1 November through 31 December 1970. The Nimbus 4 catalog presents the type of data available, anomalies in the data, and geographic location and time of the data. The subjects discussed are: (1) summary of operations, (2) orbital elements and daily sensors on table, (3) image dissector camera system montages, and (4) temperature-humidity infrared radiometer montages.
Meteorological risks are drivers of environmental innovation in agro-ecosystem management
NASA Astrophysics Data System (ADS)
Gobin, Anne; Van de Vijver, Hans; Vanwindekens, Frédéric; de Frutos Cachorro, Julia; Verspecht, Ann; Planchon, Viviane; Buyse, Jeroen
2017-04-01
Agricultural crop production is to a great extent determined by weather conditions. The research hypothesis is that meteorological risks act as drivers of environmental innovation in agro-ecosystem management. The methodology comprised five major parts: the hazard, its impact on different agro-ecosystems, vulnerability, risk management and risk communication. Generalized Extreme Value (GEV) theory was used to model annual maxima of meteorological variables based on a location-, scale- and shape-parameter that determine the center of the distribution, the deviation of the location-parameter and the upper tail decay, respectively. Spatial interpolation of GEV-derived return levels resulted in spatial temperature extremes, precipitation deficits and wet periods. The temporal overlap between extreme weather conditions and sensitive periods in the agro-ecosystem was realised using a bio-physically based modelling framework that couples phenology, a soil water balance and crop growth. 20-year return values for drought and waterlogging during different crop stages were related to arable yields. The method helped quantify agricultural production risks and rate both weather and crop-based agricultural insurance. The spatial extent of vulnerability is developed on different layers of geo-information to include meteorology, soil-landscapes, crop cover and management. Vulnerability of agroecosystems was mapped based on rules set by experts' knowledge and implemented by Fuzzy Inference System modelling and Geographical Information System tools. The approach was applied for cropland vulnerability to heavy rain and grassland vulnerability to drought. The level of vulnerability and resilience of an agro-ecosystem was also determined by risk management which differed across sectors and farm types. A calibrated agro-economic model demonstrated a marked influence of climate adapted land allocation and crop management on individual utility. The "chain of risk" approach allowed for investigating the hypothesis that meteorological risks act as drivers for agricultural innovation. Risk types were quantified in terms of probability and distribution, and further distinguished according to production type. Examples of strategies and options were provided at field, farm and policy level using different modelling methods.
Adde, Antoine; Roux, Emmanuel; Mangeas, Morgan; Dessay, Nadine; Nacher, Mathieu; Dusfour, Isabelle; Girod, Romain; Briolant, Sébastien
2016-01-01
Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l’Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l’Oyapock. The final cross-validated model integrated two landscape variables—dense forest surface and built surface—together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner. PMID:27749938
Adde, Antoine; Roux, Emmanuel; Mangeas, Morgan; Dessay, Nadine; Nacher, Mathieu; Dusfour, Isabelle; Girod, Romain; Briolant, Sébastien
2016-01-01
Local variation in the density of Anopheles mosquitoes and the risk of exposure to bites are essential to explain the spatial and temporal heterogeneities in the transmission of malaria. Vector distribution is driven by environmental factors. Based on variables derived from satellite imagery and meteorological observations, this study aimed to dynamically model and map the densities of Anopheles darlingi in the municipality of Saint-Georges de l'Oyapock (French Guiana). Longitudinal sampling sessions of An. darlingi densities were conducted between September 2012 and October 2014. Landscape and meteorological data were collected and processed to extract a panel of variables that were potentially related to An. darlingi ecology. Based on these data, a robust methodology was formed to estimate a statistical predictive model of the spatial-temporal variations in the densities of An. darlingi in Saint-Georges de l'Oyapock. The final cross-validated model integrated two landscape variables-dense forest surface and built surface-together with four meteorological variables related to rainfall, evapotranspiration, and the minimal and maximal temperatures. Extrapolation of the model allowed the generation of predictive weekly maps of An. darlingi densities at a resolution of 10-m. Our results supported the use of satellite imagery and meteorological data to predict malaria vector densities. Such fine-scale modeling approach might be a useful tool for health authorities to plan control strategies and social communication in a cost-effective, targeted, and timely manner.
Modeling Current Transfer from PV Modules Based on Meteorological Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hacke, Peter; Smith, Ryan; Kurtz, Sarah
2016-11-21
Current transferred from the active cell circuit to ground in modules undergoing potential-induced degradation (PID) stress is analyzed with respect to meteorological data. Duration and coulombs transferred as a function of whether the module is wet (from dew or rain) or the extent of uncondensed surface humidity are quantified based on meteorological indicators. With this, functions predicting the mode and rate of coulomb transfer are developed for use in estimating the relative PID stress associated with temperature, moisture, and system voltage in any climate. Current transfer in a framed crystalline silicon module is relatively high when there is no condensedmore » water on the module, whereas current transfer in a thin-film module held by edge clips is not, and displays a greater fraction of coulombs transferred when wet compared to the framed module in the natural environment.« less
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.
Trace elements in groundwater used for water supply in Latvia
NASA Astrophysics Data System (ADS)
Retike, Inga; Kalvans, Andis; Babre, Alise; Kalvane, Gunta; Popovs, Konrads
2014-05-01
Latvia is rich with groundwater resources of various chemical composition and groundwater is the main drinking source. Groundwater quality can be easily affected by pollution or overexploitation, therefore drinking water quality is an issue of high importance. Here the first attempt is made to evaluate the vast data base of trace element concentrations in groundwater collected by Latvian Environment, Geology and Meteorology Centre. Data sources here range from National monitoring programs to groundwater resources prospecting and research projects. First available historical records are from early 1960, whose quality is impossible to test. More recent systematic research has been focused on the agricultural impact on groundwater quality (Levins and Gosk, 2007). This research was mainly limited to Quaternary aquifer. Monitoring of trace elements arsenic, cadmium and lead was included in National groundwater monitoring program of Latvia in 2008 and 2009, but due to lack of funding the monitoring was suspended until 2013. As a result there are no comprehensive baseline studies regarding the trace elements concentration in groundwater. The aim of this study is to determine natural major and trace element concentration in aquifers mainly used for water supply in Latvia and to compare the results with EU potable water standards. A new overview of artesian groundwater quality will be useful for national and regional planning documents. Initial few characteristic traits of trace element concentration have been identified. For example, elevated fluorine, strontium and lithium content can be mainly associated with gypsum dissolution, but the highest barium concentrations are found in groundwaters with low sulphate content. The groundwater composition data including trace element concentrations originating from heterogeneous sources will be processed and analyzed as a part of a newly developed geologic and hydrogeological data management and modeling system with working name "GeoVipum". This study is supported by the European Social Fund project Nr.2013/0054/2DP/2.1.1.1.0/13/APIA/VIAA/007 in Latvia and European Social Fund Mobilitas grant No MJD309 in Estonia. Reference: Levins I., Gosk, E. 2007. Trace elements in groundwater as indicators of anthropogenic impact. Environmental Geology, 55, 285-290.
NASA Astrophysics Data System (ADS)
Lin, Kuan-Hui Elaine; Wang, Pao-Kuan; Fan, I.-Chun; Liao, Yi-Chun; Liao, Hsiung-Ming; Pai, Pi-Ling
2016-04-01
Global climate change in the form of extreme, variation, and short- or mid-term fluctuation is now widely conceived to challenge the survival of the human beings and the societies. Meanwhile, improving present and future climate modeling needs a comprehensive understanding of the past climate patterns. Although historical climate modeling has gained substantive progress in recent years based on the new findings from dynamical meteorology, phenology, or paleobiology, less known are the mid- to short-term variations or lower-frequency variabilities at different temporal scale and their regional expressions. Enabling accurate historical climate modeling would heavily rely on the robustness of the dataset that could carry specific time, location, and meteorological information in the continuous temporal and spatial chains. This study thus presents an important methodological innovation to reconstruct historical climate modeling at multiple temporal and spatial scales through building a historical climate dataset, based on the Chinese chronicles compiled in a Zhang (2004) edited Compendium of Chinese Meteorological Records of the Last 3,000 Years since Zhou Dynasty (1100BC). The dataset reserves the most delicate meteorological data with accurate time, location, meteorological event, duration, and other phonological, social and economic impact information, and is carefully digitalized, coded, and geo-referenced on the Geographical Information System based maps according to Tan's (1982) historical atlas in China. The research project, beginning in January 2015, is a collaborative work among scholars across meteorology, geography, and historical linguistics disciplines. The present research findings derived from the early 100+ years of the Qing dynasty include the following. First, the analysis is based on the sampling size, denoted as cities/counties, n=1398 across the Mainland China in the observation period. Second, the frequencies of precipitation, cold-warm temperature, flood and drought with an index of social unrest are counted in an interval of a year, five years, ten years, and twenty years to gain their running mean(s) for every cites/counties to depict their temporal variations. Third, the cities and counties are divided into seven zones based on their meteorological and geographical characteristics, in order to interpret the regional expressions of the climate variations. Finally, the Ordinary Least Square regression model is used to estimate the coefficients among precipitation, temperature, flood and drought. Significantly, it is found that in general all these indices fluctuated in past 100+ years. However, the occurrence of drought and flood all have significant correlation with lower (colder) temperature (P=0.00) and also with precipitation (P<0.05). This implies that cold temperature tends to have higher meteorological extremes, and both flood and drought can occur approximately in the same year with abundant precipitation at different time. Among seven geographical zones, North China is found more vulnerable to the temperature changes considering these extreme weathers. Temperature change in Central and South China however are less significant. Central China on the other hand is more sensitive to the precipitation that are both correlated with drought and flood.
Description and evaluation of the Community Multiscale Air ...
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O3) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM2. 5) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O3 mixing ratios, primarily due to reduced
NASA Astrophysics Data System (ADS)
Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.
2013-07-01
Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g., lack of soil temperature and moisture nudging), limitations in the physical parameterizations (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol-meteorology interactions at all scales.
Applied Meteorology Unit (AMU) Quarterly Report Third Quarter FY-08
NASA Technical Reports Server (NTRS)
Bauman, William; Crawford, Winifred; Barrett, Joe; Watson, Leela; Dreher, Joseph
2008-01-01
This report summarizes the Applied Meteorology Unit (AMU) activities for the third quarter of Fiscal Year 2008 (April - June 2008). Tasks reported on are: Peak Wind Tool for User Launch Commit Criteria (LCC), Anvil Forecast Tool in AWIPS Phase II, Completion of the Edward Air Force Base (EAFB) Statistical Guidance Wind Tool, Volume Averaged Height Integ rated Radar Reflectivity (VAHIRR), Impact of Local Sensors, Radar Scan Strategies for the PAFB WSR-74C Replacement, VAHIRR Cost Benefit Analysis, and WRF Wind Sensitivity Study at Edwards Air Force Base
NASA Technical Reports Server (NTRS)
Graves, M. E.; King, R. L.; Brown, S. C.
1973-01-01
Extreme values, median values, and nine percentile values are tabulated for eight meteorological variables at Cape Kennedy, Florida and at Vandenberg Air Force Base, California. The variables are temperature, relative humidity, station pressure, water vapor pressure, water vapor mixing ratio, density, and enthalpy. For each month eight hours are tabulated, namely, 0100, 0400, 0700, 1000, 1300, 1600, 1900, and 2200 local time. These statistics are intended for general use for the space shuttle design trade-off analysis and are not to be used for specific design values.
MATISSE: a meteorological aviation supporting system developed in a GIS environment
NASA Astrophysics Data System (ADS)
Rillo, Valeria; Mercogliano, Paola
2014-05-01
Awareness of weather conditions plays an increasing role in different societal and economic sectors, in particular the aviation one which is very sensitive to the meteorological conditions. In fact, adverse meteorological conditions are among the most important causes of accidents causing human and economic losses. For these reasons it is crucial to monitor and nowcast such events and avoid risks during all the flight phases. In this framework CIRA (Italian Aerospace Research Center) has implemented MATISSE (Meteorological AviaTIon Supporting SystEm), an ArcGIS Desktop Plug in, in order to detect and forecast meteorological aviation hazards over the main European airports, by using different sources of meteorological data (synoptic information, satellite data, numerical weather prediction models outputs). Such functionalities are realized after a preprocessing of raw data achieving more complex information, useful for the detection and the forecast of aviation hazards. After that, the data are stored in a database used by ArcGIS and further processed in order to provide maps, graphs and statistics. MATISSE presents a dockable toolbar in a GIS environment, allowing the user to easily select and visualize the desired information. In particular, the user can access to real time functionalities and visualize, on a map, the chosen meteorological hazard or variable (such as visibility conditions, cumulonimbi, wind speeds and directions, present weather, pressure, relative humidity, past weather, cloud cover, height of base of clouds, cloud type, geopotential, altimeter settings, three hour pressure change) over an airport or an area of interest (Europe, Italy). Such variables are represented in a user friendly way, by using simple icons easy to understand and reporting the risk level for aviation in order to provide pilots information about the meteorological conditions during the flight and the following hours. MATISSE, in fact, is able to handle the output of COSMO LM model (NetCDF files) and visualize such information. Moreover it is interfaced to an innovative tool based on MSG-2 satellite data, able to forecast the evolution of cumulonimbi, clouds responsible of thunderstorms, wind shear, icing and turbulence phenomena. MATISSE includes also tool for the statistical characterization of the typical weather bad conditions on the airport of interest, for example percentage of fog events on particular time windows.
Estimating monthly temperature using point based interpolation techniques
NASA Astrophysics Data System (ADS)
Saaban, Azizan; Mah Hashim, Noridayu; Murat, Rusdi Indra Zuhdi
2013-04-01
This paper discusses the use of point based interpolation to estimate the value of temperature at an unallocated meteorology stations in Peninsular Malaysia using data of year 2010 collected from the Malaysian Meteorology Department. Two point based interpolation methods which are Inverse Distance Weighted (IDW) and Radial Basis Function (RBF) are considered. The accuracy of the methods is evaluated using Root Mean Square Error (RMSE). The results show that RBF with thin plate spline model is suitable to be used as temperature estimator for the months of January and December, while RBF with multiquadric model is suitable to estimate the temperature for the rest of the months.
A portable real-time data processing system for standard meteorological radiosondes
NASA Technical Reports Server (NTRS)
Staffanson, F. L.
1983-01-01
The UMET-1 is a microprocessor-based portable system for automatic real-time processing of flight data transmitted from the standard RAWINSONDE upper atmosphere meteorological balloonsonde. The first 'target system' is described which was designed to receive data from a mobile tracking and telemetry receiving station (TRADAT), as the balloonsonde ascends to apogee. After balloon-burst, the UMET-1 produces user-ready hardcopy.
2. SOUTH FACE OF PYROTECHNIC SHED (BLDG. 757) SHOWING SIGN ...
2. SOUTH FACE OF PYROTECHNIC SHED (BLDG. 757) SHOWING SIGN HOLDER ON LEFT AND ENTRANCE TO TEST CELL. METEOROLOGICAL TOWER AND METEOROLOGICAL SHED (BLDG. 756) IN BACKGROUND ON LEFT; SOUTHEAST CORNER OF GPS AZIMUTH STATION (BLDG. 775) IN BACKGROUND BEHIND AND RIGHT OF PYROTECHNIC SHED. - Vandenberg Air Force Base, Space Launch Complex 3, Pyrotechnic Shed, Napa & Alden Roads, Lompoc, Santa Barbara County, CA
NASA Astrophysics Data System (ADS)
Nasonova, O. N.; Gusev, Ye. M.; Kovalev, Ye. E.
2009-04-01
Global estimates of the components of terrestrial water balance depend on a technique of estimation and on the global observational data sets used for this purpose. Land surface modelling is an up-to-date and powerful tool for such estimates. However, the results of modelling are affected by the quality of both a model and input information (including meteorological forcing data and model parameters). The latter is based on available global data sets containing meteorological data, land-use information, and soil and vegetation characteristics. Now there are a lot of global data sets, which differ in spatial and temporal resolution, as well as in accuracy and reliability. Evidently, uncertainties in global data sets will influence the results of model simulations, but to which extent? The present work is an attempt to investigate this issue. The work is based on the land surface model SWAP (Soil Water - Atmosphere - Plants) and global 1-degree data sets on meteorological forcing data and the land surface parameters, provided within the framework of the Second Global Soil Wetness Project (GSWP-2). The 3-hourly near-surface meteorological data (for the period from 1 July 1982 to 31 December 1995) are based on reanalyses and gridded observational data used in the International Satellite Land-Surface Climatology Project (ISLSCP) Initiative II. Following the GSWP-2 strategy, we used a number of alternative global forcing data sets to perform different sensitivity experiments (with six alternative versions of precipitation, four versions of radiation, two pure reanalysis products and two fully hybridized products of meteorological data). To reveal the influence of model parameters on simulations, in addition to GSWP-2 parameter data sets, we produced two alternative global data sets with soil parameters on the basis of their relationships with the content of clay and sand in a soil. After this the sensitivity experiments with three different sets of parameters were performed. As a result, 16 variants of global annual estimates of water balance components were obtained. Application of alternative data sets on radiation, precipitation, and soil parameters allowed us to reveal the influence of uncertainties in input data on global estimates of water balance components.
NASA Astrophysics Data System (ADS)
Massabo, Marco; Molini, Luca; Kostic, Bojan; Campanella, Paolo; Stevanovic, Slavimir
2015-04-01
Disaster risk reduction has long been recognized for its role in mitigating the negative environmental, social and economic impacts of natural hazards. Flood Early Warning System is a disaster risk reduction measure based on the capacities of institutions to observe and predict extreme hydro-meteorological events and to disseminate timely and meaningful warning information; it is furthermore based on the capacities of individuals, communities and organizations to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss. An operational definition of an Early Warning System has been suggested by ISDR - UN Office for DRR [15 January 2009]: "EWS is the set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities and organizations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss.". ISDR continues by commenting that a people-centered early warning system necessarily comprises four key elements: 1-knowledge of the risks; 2-monitoring, analysis and forecasting of the hazards; 3-communication or dissemination of alerts and warnings; and 4- local capabilities to respond to the warnings received." The technological platform DEWETRA supports the strengthening of the first three key elements of EWS suggested by ISDR definition, hence to improve the capacities to build real-time risk scenarios and to inform and warn the population in advance The technological platform DEWETRA has been implemented for the Republic of Serbia. DEWETRA is a real time-integrate system that supports decision makers for risk forecasting and monitoring and for distributing warnings to end-user and to the general public. The system is based on the rapid availability of different data that helps to establish up-to-date and reliable risk scenarios. The integration of all relevant data for risk management significantly increases the value of available information and the level of knowledge of forecasters and disaster managers. Different data, forecast and monitoring products, which are generated by different national and international institution and organizations, can be visualized and processed in real-time within the platform. DEWETRA is a web application ensuring the capillary distribution of information among institutions. The system is used as an infrastructure for exchanging and sharing data, procedures, models and expertise among the Sector of Emergency Management (SEM), the Republic Hydro-Meteorological Service of Serbia (RHMSS) and the Serbian Public Water Companies (PWCs): Serbia Waters, Vojvodina Waters and Belgrade Waters.
NASA Astrophysics Data System (ADS)
Srivastava, P. K.; Han, D.; Rico-Ramirez, M. A.; Bray, M.; Islam, T.; Petropoulos, G.; Gupta, M.
2015-12-01
Hydro-meteorological variables such as Precipitation and Reference Evapotranspiration (ETo) are the most important variables for discharge prediction. However, it is not always possible to get access to them from ground based measurements, particularly in ungauged catchments. The mesoscale model WRF (Weather Research & Forecasting model) can be used for prediction of hydro-meteorological variables. However, hydro-meteorologists would like to know how well the downscaled global data products are as compared to ground based measurements and whether it is possible to use the downscaled data for ungauged catchments. Even with gauged catchments, most of the stations have only rain and flow gauges installed. Measurements of other weather hydro-meteorological variables such as solar radiation, wind speed, air temperature, and dew point are usually missing and thus complicate the problems. In this study, for downscaling the global datasets, the WRF model is setup over the Brue catchment with three nested domains (D1, D2 and D3) of horizontal grid spacing of 81 km, 27 km and 9 km are used. The hydro-meteorological variables are downscaled using the WRF model from the National Centers for Enviromental Prediction (NCEP) reanalysis datasets and subsequently used for the ETo estimation using the Penman Monteith equation. The analysis of weather variables and precipitation are compared against the ground based datasets, which indicate that the datasets are in agreement with the observed datasets for complete monitoring period as well as during the seasons except precipitation whose performance is poorer in comparison to the measured rainfall. After a comparison, the WRF estimated precipitation and ETo are then used as a input parameter in the Probability Distributed Model (PDM) for discharge prediction. The input data and model parameter sensitivity analysis and uncertainty estimation are also taken into account for the PDM calibration and prediction following the Generalised Likelihood Uncertainty Estimation (GLUE) approach. The overall analysis suggests that the uncertainty estimates in predicted discharge using WRF downscaled ETo have comparable performance to ground based observed datasets and hence is promising for discharge prediction in the absence of ground based measurements.
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.
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.
Climate-dependence of ecosystem services in a nature reserve in northern China
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.
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.
Sensitivity of polar ozone recovery predictions of the GMI 3D CTM to GCM and DAS dynamics
NASA Astrophysics Data System (ADS)
Considine, D.; Connell, P.; Strahan, S.; Douglass, A.; Rotman, D.
2003-04-01
The Global Modeling Initiative (GMI) 3-D chemistry and transport model has been used to generate 2 simulations of the 1995-2030 time period. The 36-year simulations both used the source gas and aerosol boundary conditions of the 2002 World Meteorological Organization assessment exercise MA2. The first simulation was based on a single year of meteorological data (winds, temperatures) generated by the new Goddard Space Flight Center "Finite Volume" General Circulation Model (FVGCM), repeated for each year of the simulation. The second simulation used a year of meteorological data generated by a new data assimilation system based on the FVGCM (FVDAS), using observations for July 1, 1999 - June 30, 2000. All other aspects of the two simulations were identical. The increase in vortex-averaged south polar springtime ozone concentrations in the lower stratosphere over the course of the simulations is more robust in the simulation driven by the GCM meteorological data than in the simulation driven by DAS winds. At the same time, the decrease in estimated chemical springtime ozone loss is similar. We thus attribute the differences between the two simulations to differences in the representations of polar dynamics which reduce the sensitivity of the simulation driven by DAS winds to changes in vortex chemistry. We also evaluate the representations in the two simulations of trace constituent distributions in the current polar lower stratosphere using various observations. In these comparisons the GCM-based simulation often is in better agreement with the observations than the DAS-based simulation.
3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE
NASA Astrophysics Data System (ADS)
Fernández, Pablo; Suárez, José Pablo; Trujillo, Agustín; Domínguez, Conrado; Santana, José Miguel
2018-04-01
Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as "The Internet of Things" solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.
3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE
NASA Astrophysics Data System (ADS)
Fernández, Pablo; Suárez, José Pablo; Trujillo, Agustín; Domínguez, Conrado; Santana, José Miguel
2018-03-01
Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as "The Internet of Things" solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.
Transported acid aerosols measured in southern Ontario
NASA Astrophysics Data System (ADS)
Keeler, Gerald J.; Spengler, John D.; Koutrakis, Petros; Allen, George A.; Raizenne, Mark; Stern, Bonnie
During the period 29 June 1986-9 August 1986, a field health study assessing the acute health effects of air pollutants on children was conducted at a summer girls' camp on the northern shore of Lake Erie in SW Ontario. Continuous air pollution measurements of SO 2, O 3, NO x, particulate sulfates, light scattering, and meteorological measurements including temperature, dew point, and wind speed and direction were made. Twelve-hour integrated samples of size fractioned particles were also obtained using dichotomous samplers and Harvard impactors equipped with an ammonia denuder for subsequent hydrogen ion determination. Particulate samples were analyzed for trace elements by X-ray fluorescence and Neutron Activation, and for organic and elemental carbon by a thermal/optical technique. The measured aerosol was periodically very acidic with observed 12-h averaged H + concentrations in the range < 10-560 nmoles m -3. The aerosol H + appeared to represent the net strong acidity after H 2SO 4 reaction with NH 3(g). Average daytime concentrations were higher than night-time for aerosol H +, sulfate, fine mass and ozone. Prolonged episodes of atmospheric acidity, sulfate, and ozone were associated with air masses arriving at the measurement site from the west and from the southwest over Lake Erie. Sulfate concentrations measured at the lakeshore camp were more than twice those measured at inland sites during extreme pollution episodes. The concentration gradient observed with onshore flow was potentially due to enhanced deposition near the lakeshore caused by discontinuities in the meteorological fields in this region.
Yu, Xing-na; Ma, Jia; Zhu, Bin; Wang, Hong-lei; Yan, Shu-qi; Xia, Hang
2015-06-01
To understand the effects of relative humidity (RH) and aerosol physicochemical properties on the atmospheric visibility in autumn and winter in northern suburb of Nanjing, the relationships between meteorological elements, particulate matter and visibility were analyzed with the data of meteorological elements, aerosol particle spectra, particulate matter concentration and chemical composition. The average visibility was 4.76 km in autumn and winter in northern suburb of Nanjing. There was a certain negative correlation between the particulate matter concentration and the visibility, especially the influence of fine particles on the visibility was more remarkable. The occurrence frequencies of low visibilities showed an increasing trend with the increasing concentration of fine particles and RH. When the visibility decreased from 5-10 km to <5 km, the mass concentrations of PM10 and PM2.5 increased by 7.56% and 37.64%, respectively. Meanwhile, the mass concentrations of SO4(2-) and NO3-increased significantly. Effects of aerosol particle number concentration on the visibility were related with RH. Aerosol number concentration with diameters ranging from 0.5 microm to 2 microm increased slowly with the increase of RH, while those ranging from 2 microm to 10 microm decreased. The correlation analysis between the aerosol surface area concentration and the visibility showed that RH and fine particles between 0.5 microm and 2 microm were the main factors which caused the decrease of atmospheric visibility in autumn and winter in northern suburb of Nanjing.
Hu, Dongmei; Wu, Jianping; Tian, Kun; Liao, Lyuchao; Xu, Ming; Du, Yiman
2017-09-01
A heavy 16-day pollution episode occurred in Beijing from December 19, 2015 to January 3, 2016. The mean daily AQI and PM 2.5 were 240.44 and 203.6μg/m 3 . We analyzed the spatiotemporal characteristics of air pollutants, meteorology and road space speed during this period, then extended to reveal the combined effects of traffic restrictions and meteorology on urban air quality with observational data and a multivariate mutual information model. Results of spatiotemporal analysis showed that five pollution stages were identified with remarkable variation patterns based on evolution of PM 2.5 concentration and weather conditions. Southern sites (DX, YDM and DS) experienced heavier pollution than northern ones (DL, CP and WL). Stage P2 exhibited combined functions of meteorology and traffic restrictions which were delayed peak-clipping effects on PM 2.5 . Mutual information values of Air quality-Traffic-Meteorology (ATM-MI) revealed that additive functions of traffic restrictions, suitable relative humidity and temperature were more effective on the removal of fine particles and CO than NO 2 . Copyright © 2017. Published by Elsevier B.V.
Exposure to PM2.5 and PAHs from the Tong Liang, China epidemiological study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chow, J.C.; Watson, J.G.; Chen, L.W.A.
2006-07-01
Chemically speciated PM2.5 and particle-bound polycyclic aromatic hydrocarbon (PAH) measurements were made at three sites near urban Tong Liang, Chongqing, a Chinese inland city where coal combustion is used for electricity generation and residential purposes outside of the central city. Ambient sampling was based on 72-hr averages between 3/2/2002 and 2/26/2003. Elevated PM2.5 and PAH concentrations were observed at all three sites, with the highest concentrations found in winter and the lowest in summer. This reflects a coupling effect of source variability and meteorological conditions. The PM2.5 mass estimated from sulfate, nitrate, ammonium, organics, elemental carbon, crustal material, and saltmore » corresponded with the annual average gravimetric mass within 10%. Carbonaceous aerosol was the dominant species, while positive correlations between organic carbon and trace elements (e.g., As, Se, Br, Pb, and Zn) were consistent with coal-burning and motor vehicle contributions. Ambient particle-bound PAHs of molecular weight 168-266 were enriched by 1.5 to 3.5 times during the coal-fired power plant operational period. However, further investigation is needed to determine the relative contribution from residential and utility coal combustion and vehicular activities.« less
Wang, Fumin; Gonsamo, Alemu; Chen, Jing M; Black, T Andrew; Zhou, Bin
2014-11-01
Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.
Recommendations of the panels: Panel on flight planning to avoid high ozone
NASA Technical Reports Server (NTRS)
Mohnen, V. A.
1979-01-01
Flights planned or accomplished during certain months of the year at the higher latitudes and altitudes at or above the tropopause are discussed. Cabin ozone level limitations are established, and additional information is required for more accurate and qualtitative forecasting and design data base for operational utilization. Better tropopause heights, ozone concentration and corresponding meteorological data along selected flight routes, and meteorological data were investigated.
Synchronous meteorological satellite system description document, volume 3
NASA Technical Reports Server (NTRS)
Pipkin, F. B.
1971-01-01
The structural design, analysis, and mechanical integration of the synchronous meteorological satellite system are presented. The subjects discussed are: (1) spacecraft configuration, (2) structural design, (3) static load tests, (4) fixed base sinusoidal vibration survey, (5) flight configuration sinusoidal vibration tests, (6) spacecraft acoustic test, and (7) separation and shock test. Descriptions of the auxiliary propulsion subsystem, the apogee boost motor, communications system, and thermal control subsystem are included.
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.
Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei
2014-01-01
Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties. PMID:24919017
Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei
2014-06-10
Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.
NASA Astrophysics Data System (ADS)
Sommer, Philipp; Kaplan, Jed
2016-04-01
Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.
NASA Astrophysics Data System (ADS)
Alshawaf, Fadwa; Dick, Galina; Heise, Stefan; Balidakis, Kyriakos; Schmidt, Torsten; Wickert, Jens
2017-04-01
Ground-based GNSS (Global Navigation Satellite Systems) have efficiently been used since the 1990s as a meteorological observing system. Recently scientists used GNSS time series of precipitable water vapor (PWV) for climate research although they may not be sufficiently long. In this work, we compare the trend estimated from GNSS time series with that estimated from European Center for Medium-RangeWeather Forecasts Reanalysis (ERA-Interim) data and meteorological measurements.We aim at evaluating climate evolution in Central Europe by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: 1) estimated from ground-based GNSS observations using the method of precise point positioning, 2) inferred from ERA-Interim data, and 3) determined based on daily surface measurements of temperature and relative humidity. The other variables are available from surface meteorological stations or received from ERA-Interim. The PWV trend component estimated from GNSS data strongly correlates (>70%) with that estimated from the other data sets. The linear trend is estimated by straight line fitting over 30 years of seasonally-adjusted PWV time series obtained using the meteorological measurements. The results show a positive trend in the PWV time series with an increase of 0.2-0.7 mm/decade with a mean standard deviations of 0.016 mm/decade. In this paper, we present the results at three GNSS stations. The temporal increment of the PWV correlates with the temporal increase in the temperature levels.
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.
The closure problem for turbulence in meteorology and oceanography
NASA Technical Reports Server (NTRS)
Pierson, W. J., Jr.
1985-01-01
The dependent variables used for computer based meteorological predictions and in plans for oceanographic predictions are wave number and frequency filtered values that retain only scales resolvable by the model. Scales unresolvable by the grid in use become 'turbulence'. Whether or not properly processed data are used for initial values is important, especially for sparce data. Fickian diffusion with a constant eddy diffusion is used as a closure for many of the present models. A physically realistic closure based on more modern turbulence concepts, especially one with a reverse cascade at the right times and places, could help improve predictions.
Potato Production as Affected by Crop Parameters and Meteoro Logical Elements
NASA Astrophysics Data System (ADS)
Pereira, André B.; Villa Nova, Nilson A.; Pereira, Antonio R.
Meteorological elements directly influence crop potential productivity, regulating its transpiration, photosynthesis, and respiration processes in such a way as to control the growth and development of the plants throughout their physiological mechanisms at a given site. The interaction of the meteorological factors with crop responses is complex and has been the target of attention of many researchers from all over the world. There is currently a great deal of interest in estimating crop productivity as a function of climate by means of different crop weather models in order to help growers choose planting locations and timing to produce high yields with good tuber quality under site-specific atmospheric conditions. In this manuscript an agrometeorological model based on maximum carbon dioxide assimilation rates for C3 plants, fraction of photosynthetically active radiation, air temperature, photoperiod duration, and crop parameters is assessed as to its performance under tropical conditions. Crop parameters include leaf areaand harvest indexes, dry matter content of potato tubers, and crop cycles to estimate potato potential yields. Productivity obtained with the cultivar Itararé, grown with adequate soil water supply conditions at four different sites in the State of São Paulo (Itararé, Piracicaba, TatuÍ, and São Manuel), Brazil, were used to test the model. The results showed thatthe agrometeorological model tested under the climatic conditions of the State of São Paulo in general underestimated irrigated potato yield by less than 10%.This justifies the recommendation to test the performance of the model in study in other climaticregions for different crops and genotypes under optimal irrigationconditions in further scientific investigations. We reached the conclusion that the agrometeorological model taking into account information on leaf area index, photoperiod duration, photosynthetically active radiation and air temperature is feasible to estimate potential tuber yield at a commercial scale. The performance test shows that it can then be used to forecast harvest time, and also as an effective tool to predict the suitability of potential regions to the cultivation of potato crop, cultivar Itararé, at the State of São Paulo, Brazil.
NASA Astrophysics Data System (ADS)
Kubota, T.; Silva, I. C.; Hasnawir, H.
2009-12-01
The research including observation of rain, soil moisture content and sediment discharge is conducted on a torrent in northern Kyushu whose geology consists of Paleozoic metamorphic rocks (mainly schist) and whose vegetation consists of mainly Japanese cypress and cedar. Soil depth is approximately 50cm in average and permeability k is 0.1~0.01 order. With data obtained by the observation for more than 4 years, standard rainfalls of warning and evacuation against the sudden sediment runoffs are analyzed. Then, the result was compared with the ones in Nuevo Leon Mexico (geology of schist, slate, k=0.01~0.001 order) and in southern Sulawesi Island Indonesia (volcanic geology, k=0.001~0.0001 order). Hitherto, various methods were proposed to analyze the warning critical standard for landslide disaster or large sediment discharge. In this study, we employed Hirano's element slope runoff theory, the Self Organized Criticality Assumption (SOC), and the Elementary Catastrophe Theory (ETC) to analyze the data, although the soil moisture fluctuation, meteorological condition such as upper air wind and dew point depression, the rainfall-soil moisture index provided by Japan Meteorological Agency was considered. The last one is a cutting edge technology based on the tank model calculation of soil moisture content combined with short term rainfall prediction which is a product of numerical simulation using radar image advection analysis compensated with surface rain data and with orographic rain effect. In Hirano's theory, we can describe the critical rain Rc and rain intensity Ric as following equation. Q/A/M/ cosθ = Ri ∫(r*cosθ)dt = Ri*R (1) ∴ Ric*Rc = C (2) Here, Q: sediment runoff or debris flow discharge, A: watershed area, M: function concerning with sediment deposit features on the upstream torrents or slopes (porosity, torrent bed slope gradient, sediment accumulation length and depth, cohesion), t: time, θ: torrent bed or hillside slope gradient, r: instant precipitation. C: constant, given as 8000 in Fukuoka (Kyushu, Japan), as 3750 in Sierra Madere Oriental (Nuevo Leon, Mexico), as 9000 in southern Sulawesi(Indonesia). Consequently, the forecast-warning system which has enough accuracy of 80% against sediment runoffs or debris flows for both wide range region with meteorological conditions and narrow region with the critical rain standard are established. However, in the region with lower soil permeability we may revise the standard rain by the compensation with the soil moisture content response such as increasing rate.
MOM: A meteorological data checking expert system in CLIPS
NASA Technical Reports Server (NTRS)
Odonnell, Richard
1990-01-01
Meteorologists have long faced the problem of verifying the data they use. Experience shows that there is a sizable number of errors in the data reported by meteorological observers. This is unacceptable for computer forecast models, which depend on accurate data for accurate results. Most errors that occur in meteorological data are obvious to the meteorologist, but time constraints prevent hand-checking. For this reason, it is necessary to have a 'front end' to the computer model to ensure the accuracy of input. Various approaches to automatic data quality control have been developed by several groups. MOM is a rule-based system implemented in CLIPS and utilizing 'consistency checks' and 'range checks'. The system is generic in the sense that it knows some meteorological principles, regardless of specific station characteristics. Specific constraints kept as CLIPS facts in a separate file provide for system flexibility. Preliminary results show that the expert system has detected some inconsistencies not noticed by a local expert.
The design of 1-wire net meteorological observatory for 2.4 m telescope
NASA Astrophysics Data System (ADS)
Zhu, Gao-Feng; Wei, Ka-Ning; Fan, Yu-Feng; Xu, Jun; Qin, Wei
2005-03-01
The weather is an important factor to affect astronomical observations. The 2.4 m telescope can not work in Robotic Mode without the weather data input. Therefore it is necessary to build a meteorological observatory near the 2.4 m telescope. In this article, the design of the 1-wire net meteorological observatory, which includes hardware and software systems, is introduced. The hardware system is made up of some kinds of sensors and ADC. A suited power station system is also designed. The software system is based on Windows XP operating system and MySQL data management system, and a prototype system of browse/server model is developed by JAVA and JSP. After being tested, the meteorological observatory can register the immediate data of weather, such as raining, snowing, and wind speed. At last, the data will be stored for feature use. The product and the design can work well for the 2.4 m telescope.
Li, Li; Qian, Jun; Ou, Chun-Quan; Zhou, Ying-Xue; Guo, Cui; Guo, Yuming
2014-07-01
There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001-2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures. Copyright © 2014 Elsevier Ltd. All rights reserved.
Cal Tech's Program in Meteorology: 1933-1948.
NASA Astrophysics Data System (ADS)
Lewis, J. M.
1994-01-01
The California Institute of Technology (Cal Tech) established a course of study in meteorology in 1933. It was intimately tied to the upsurge of activity in commercial and military aviation that occurred in the period between the world wars. The tragic crash of the airship U.S.S. Akron provided the stimulus for including meteorology as a subprogram in the aeronautics department at Cal Tech. Thoodore von K´rm´n, head of the department and director of the school's Guggenheim Aeronautics Laboratory, masterminded the design of the program and geared it toward the solution of practical problems using the principles of dynamic meteorology. One of his doctoral students, Irving Krick, was groomed to develop the program.Robert Millikan, head of the institute, fostered an approach to science that encouraged the faculty to consuit and work with industry. In this environment, Krick established links with aviation, motion picture studios, and public utilities that would set the stage for the research thrust in meteorology. The program was primarily designed for training at the master' degree level, and a significant number of the graduates became entrepreneurs in meteorology. Based on letters of reminiscence and oral histories from some of these consulting meteorologists, it has been concluded that the Millikan/von K´rm´n philosophy of science played an important part in directing the meteorologists into the private sector.Following World War II, Lee DuBridge replaced Millikan as head of the institute. DuBridge's efforts were directed toward making the small elite school scientifically competitive in the changed conditions of a postwar world. In this climate, the merging of private business with academic work fell into disfavor. Without champions such as Millikan and von K´rm´n,the meteorology program was unable to survive.
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.
Analysis of Cumulonimbus (Cb), Thunderstorm and Fog for Izmir Adnan Menderes Airport
NASA Astrophysics Data System (ADS)
Avsar, Ercument
2016-07-01
Demand for airline transport has been increasing day by day with the development of the aviation industry in Turkey. Meteorological conditions are among the most important factors that influence aviation facilities. Meteorological events cause delays and cancellation of flights which create economic and time losses, and they even lead to accidents and breakups. The most important meteorological events that affect the takeoff and landing of airplanes can be listed as wind, runway visual range, cloud, rain, icing, turbulence, and low level windshear. Meteorological events that affect the aviation facilities most often in Adnan Menderes Airport (LTBJ), the fourth largest airport in Turkey in terms of air traffic, are fog, Cumulonimbus (Cb) clouds and thunderstorms (TS-Thunderstorm). Therefore, it is important to identify the occurrence time of these events based on the analysis of data over many years and do the flight plans based on this meteorological information in order to make the aviation facilities safer and without delays. In this study, statistical analysis on the formation of Cb clouds, thunderstorm and foggy days is conducted using observations produced for aviation (METAR) and special observers (SPECI). It is found that there are two types of fog that are observed most often at LTBJ, namely radiation and advection fogs, accordingly to the results of statistical analysis based on data from 2004 to 2014. Fog events are found to occur most often in the months of December and January, during 04:00 - 07:00 UTC time interval, between pressure values over 1015-1020 hPa, in 130-190 degree light breeze (1-5KT) and in temperature levels between 5°C and 8°C. Thunderstorm events recorded at LTBJ between the years 2004 and 2014 are most often observed in the months of January and February, in 120-210 degree gentle breeze winds (6-10KT), and in temperature levels between 8 and 18 °C. Key Words: Adnan Menderes International Airport, LTBJ, Fog, Thunderstorm (TS), Cb Clouds
Pattern recognition of satellite cloud imagery for improved weather prediction
NASA Technical Reports Server (NTRS)
Gautier, Catherine; Somerville, Richard C. J.; Volfson, Leonid B.
1986-01-01
The major accomplishment was the successful development of a method for extracting time derivative information from geostationary meteorological satellite imagery. This research is a proof-of-concept study which demonstrates the feasibility of using pattern recognition techniques and a statistical cloud classification method to estimate time rate of change of large-scale meteorological fields from remote sensing data. The cloud classification methodology is based on typical shape function analysis of parameter sets characterizing the cloud fields. The three specific technical objectives, all of which were successfully achieved, are as follows: develop and test a cloud classification technique based on pattern recognition methods, suitable for the analysis of visible and infrared geostationary satellite VISSR imagery; develop and test a methodology for intercomparing successive images using the cloud classification technique, so as to obtain estimates of the time rate of change of meteorological fields; and implement this technique in a testbed system incorporating an interactive graphics terminal to determine the feasibility of extracting time derivative information suitable for comparison with numerical weather prediction products.
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.
Hennigan, Christopher J; Bergin, Michael H; Weber, Rodney J
2008-12-15
Ground-based measurements of meteorological parameters and water-soluble organic carbon in the gas(WSOCg) and particle (WSOCp) phases were carried out in Atlanta, Georgia, from May to September 2007. Fourteen separate events were observed throughout the summer in which WSOCp and water vapor concentrations were highly correlated (average WSOCp-water vapor r = 0.92); however, for the entire summer, no well-defined relationship existed between the two. The correlation events, which lasted on average 19 h, were characterized by a wide range of WSOCp and water vapor concentrations. Several hypotheses for the correlation are explored, including heterogeneous liquid phase SOA formation and the co-emission of biogenic VOCs and water vapor. The data provide supporting evidence for contributions from both and suggest the possibility of a synergistic effect between the co-emission of water vapor and VOCs from biogenic sources on SOA formation. Median WSOCp concentrations were also correlated with elemental carbon (EC), although this correlation extended over the entire summer. Despite the emission of water vapor from anthropogenic mobile sources and the WSOCp-EC correlation, mobile sources were not considered a potential cause for the WSOCp-water vapor correlations because of their low contribution to the water vapor budget. Meteorology could perhaps have influenced the WSOCp-EC correlation, but other factors are implicated as well. Overall, the results suggest that the temperature-dependent co-emission of water vapor through evapotranspiration and SOA precursor-VOCs by vegetation may be an important process contributing to SOA in some environments.
NASA Technical Reports Server (NTRS)
Merrill, John T.; Rodriguez, Jose M.
1991-01-01
Trajectory and photochemical model calculations based on retrospective meteorological data for the operations areas of the NASA Pacific Exploratory Mission (PEM)-West mission are summarized. The trajectory climatology discussed here is intended to provide guidance for flight planning and initial data interpretation during the field phase of the expedition by indicating the most probable path air parcels are likely to take to reach various points in the area. The photochemical model calculations which are discussed indicate the sensitivity of the chemical environment to various initial chemical concentrations and to conditions along the trajectory. In the post-expedition analysis these calculations will be used to provide a climatological context for the meteorological conditions which are encountered in the field.
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.
Analysis of Meteorological Observations from an Array of Buoys During JASIN.
1980-01-01
13 1:3.06 13 18 40.16 b .4 9 5 , 13 1. . 2 65,16 8 4 10 4.08 "’ I 1 18 1. 3 09 :132’.., 127 46൛ 19 . 0 6" 7’ "" -’ 1111 , 3 ... 11 10 1,3 96...N00014-79-C-0004 i 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10 . PROGRAM ELEMENT. PROJECT, TASK School of Oceanography AREAB WORK UNIT NUMBERS Oregon...III. OBSERVATIONS ---------------------------------------------- 5 IV. SPECTRA-------------------------------------------------- 10 V. TAYLOR’S
NASA Astrophysics Data System (ADS)
Rodrigues, M. A.; Monteiro, A.; Rocha, A.; Quenol, H.; de Freita, J. R.
2012-04-01
The aim of this study was to determine the climatic zones in Demarcated Douro Region (DDR), based on meso-climatic analyses for the region. We have used eighteen meteorological stations from very different areas in the region and using the meteorological data we have determined the bioclimatic indexes and afterwards we have created in SIG the representative maps of the areas with different aptitudes for the vineyards.
Atmospheric mercury in the Canadian Arctic. Part II: insight from modeling.
Dastoor, Ashu; Ryzhkov, Andrew; Durnford, Dorothy; Lehnherr, Igor; Steffen, Alexandra; Morrison, Heather
2015-03-15
A review of mercury in the Canadian Arctic with a focus on field measurements is presented in part I (see Steffen et al., this issue). Here we provide insights into the dynamics of mercury in the Canadian Arctic from new and published mercury modeling studies using Environment Canada's mercury model. The model simulations presented in this study use global anthropogenic emissions of mercury for the period 1995-2005. The most recent modeling estimate of the net gain of mercury from the atmosphere to the Arctic Ocean is 75 Mg year(-1) and the net gain to the terrestrial ecosystems north of 66.5° is 42 Mg year(-1). Model based annual export of riverine mercury from North American, Russian and all Arctic watersheds to the Arctic Ocean are in the range of 2.8-5.6, 12.7-25.4 and 15.5-31.0 Mg year(-1), respectively. Analysis of long-range transport events of Hg at Alert and Little Fox Lake monitoring sites indicates that Asia contributes the most ambient Hg to the Canadian Arctic followed by contributions from North America, Russia, and Europe. The largest anthropogenic Hg deposition to the Canadian Arctic is from East Asia followed by Europe (and Russia), North America, and South Asia. An examination of temporal trends of Hg using the model suggests that changes in meteorology and changes in anthropogenic emissions equally contribute to the decrease in surface air elemental mercury concentrations in the Canadian Arctic with an overall decline of ~12% from 1990 to 2005. A slow increase in net deposition of Hg is found in the Canadian Arctic in response to changes in meteorology. Changes in snowpack and sea-ice characteristics and increase in precipitation in the Arctic related with climate change are found to be primary causes for the meteorology-related changes in air concentrations and deposition of Hg in the region. The model estimates that under the emissions reduction scenario of worldwide implementation of the best emission control technologies by 2020, mercury deposition could potentially be reduced by 18-20% in the Canadian Arctic. Copyright © 2014. Published by Elsevier B.V.
Evidence of Aerosol's Influence on Climate from Beijing Olympics
NASA Astrophysics Data System (ADS)
Chen, S.; Fu, Q.; Huang, J.; Ge, J.; Su, J.
2009-12-01
Air pollution is a difficult problem during the process of industrialization in most developing countries. In China, the main air pollutants are inhaled aerosol particles. Because of the extremely high loading and rapid development, Beijing became a heavily polluted city, with a population of more than 16 million. The 2008 Olympic Summer Games provided a unique opportunity for the study of climate effects of aerosols due to many measurements taken to fight pollution caused by industrialization and economic growth.Surface temperature is the most intuitive meteorological factor and easy to get. Therefore, aerosol’s radiative effects on regional climate can be known by studying the relationship between aerosols and surface temperature in Beijing city in August 2008. However, many factors can affect the surface temperature and cloud is considered as a very important meteorological element in radiation balance. In order to remove the impact of clouds on surface temperature, here the ground temperature in clear sky days (when cloud cover is less than 2) are selected. Aerosol data from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Earth Observing System (EOS) Aqua shows that aerosol concentration decreased significantly in the area of Olympic venues in August 2008. Meanwhile, the ground-based observation data shows the surface temperature during the day (14LT) and night (02LT) in August 2008 is higher and lower than the mean temperature in August from 2002 to 2008, respectively. It is discovered that the distribution of satellite-retrieved aerosol optical Depth (AOD) in the whole area of Beijing in August of 2003 and 2004 is similar to that in 2008. We chosen four meteorological stations to analyze surface temperature and found that the diurnal changes of surface temperature are consistent with that in August of 2003, 2004 and 2008. Meanwhile, the decrease of AOD in the area of Olympic venues in August 2008 leads to the increase of precipitation, and furthermore produces more water vapor content with previous years. The effect of water vapor increase an asymmetric departure from the normal during the day and night and make the increase of daily temperature range caused by the decrease of aerosol concentration is not obvious in Beijing Olympic venues in August 2008.
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.
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.
Data Democratization - Promoting Real-Time Data Sharing and Use throughout the Americas
NASA Astrophysics Data System (ADS)
Yoksas, T. C.
2006-05-01
The Unidata Program Center (Unidata) of the University Corporation of Atmospheric Research (UCAR) is actively involved in international collaborations whose goals are real-time sharing of hydro-meteorological data by institutions of higher education throughout the Americas; in the distribution of analysis and visualization tools for those data; and in the establishment of server sites that provide easy-to-use, programmatic remote- access to a wide variety of datasets. Data sharing capabilities are being provided by Unidata's Internet Data Distribution (IDD) system, a community-based effort that has been the primary source of real-time meteorological data for approximately 150 US universities for over a decade. A collaboration among Unidata, Brazil's Centro de PreviSão de Tempo e Estudos Climáticos (CPTEC), the Universidad Federal do Rio de Janeiro (UFRJ), and the Universidade de São Paulo (USP) has resulted in the creation of a Brazilian peer of the North American IDD, the IDD-Brasil. Collaboration among Unidata, the Universidad de Costa Rica (UCR), and the University of Puerto Rico at Mayaguez (UPRM) seeks to extend IDD data sharing throughout Central America and the Caribbean in an IDD-Caribe. Collaboration between Unidata and the Caribbean Institute for Meteorology and Hydrology (CIMH), a World Meteorological Organization (WMO) Regional Meteorological Training Center (RMTC) based in Barbados, has been launched to investigate the possibility of expansion of IDD data sharing throughout Caribbean RMTC member countries. Most recently, efforts aimed at creating a data sharing network for researchers on the Antarctic continent have resulted in the establishment of the Antarctic-IDD. Data analysis and visualization capabilities are being provided by Unidata through a suite of freely-available applications: the National Centers for Environmental Prediction (NCEP) GEneral Meteorology PAcKage (GEMPAK); the Unidata Integrated Data Viewer (IDV); and University of Wisconsin, Space Science and Engineering Center (SSEC) Man-computer Interactive Data Access System (McIDAS). Remote data access capabilities are provided by Unidata's Thematic Realtime Environmental Data Services (THREDDS) servers (which incorporate Open-source Project for a Network Data Access (OPeNDAP) data services), and the Abstract Data Distribution Environment (ADDE) of McIDAS. It is envisioned that the data sharing capabilities available in the IDD, IDD-Brasil, and IDD-Caribe, remote data access capabilities available in THREDDS and ADDE, and analysis capabilities available in GEMPAK, the IDV, and McIDAS will help foster new collaborations among prominent university educators and researchers, national meteorological agencies, and WMO Regional Meteorological Training Centers throughout North, Central, and South America.
Statistical Short-Range Guidance for Peak Wind Speed Forecasts at Edwards Air Force Base, CA
NASA Technical Reports Server (NTRS)
Dreher, Joseph; Crawford, Winifred; Lafosse, Richard; Hoeth, Brian; Burns, Kerry
2008-01-01
The peak winds near the surface are an important forecast element for Space Shuttle landings. As defined in the Shuttle Flight Rules (FRs), there are peak wind thresholds that cannot be exceeded in order to ensure the safety of the shuttle during landing operations. The National Weather Service Spaceflight Meteorology Group (SMG) is responsible for weather forecasts for all shuttle landings. They indicate peak winds are a challenging parameter to forecast. To alleviate the difficulty in making such wind forecasts, the Applied Meteorology Unit (AMTJ) developed a personal computer based graphical user interface (GUI) for displaying peak wind climatology and probabilities of exceeding peak-wind thresholds for the Shuttle Landing Facility (SLF) at Kennedy Space Center. However, the shuttle must land at Edwards Air Force Base (EAFB) in southern California when weather conditions at Kennedy Space Center in Florida are not acceptable, so SMG forecasters requested that a similar tool be developed for EAFB. Marshall Space Flight Center (MSFC) personnel archived and performed quality control of 2-minute average and 10-minute peak wind speeds at each tower adjacent to the main runway at EAFB from 1997- 2004. They calculated wind climatologies and probabilities of average peak wind occurrence based on the average speed. The climatologies were calculated for each tower and month, and were stratified by hour, direction, and direction/hour. For the probabilities of peak wind occurrence, MSFC calculated empirical and modeled probabilities of meeting or exceeding specific 10-minute peak wind speeds using probability density functions. The AMU obtained and reformatted the data into Microsoft Excel PivotTables, which allows users to display different values with point-click-drag techniques. The GUT was then created from the PivotTables using Visual Basic for Applications code. The GUI is run through a macro within Microsoft Excel and allows forecasters to quickly display and interpret peak wind climatology and likelihoods in a fast-paced operational environment. A summary of how the peak wind climatologies and probabilities were created and an overview of the GUT will be presented.
Influence of Ice Cloud Microphysics on Imager-Based Estimates of Earth's Radiation Budget
NASA Astrophysics Data System (ADS)
Loeb, N. G.; Kato, S.; Minnis, P.; Yang, P.; Sun-Mack, S.; Rose, F. G.; Hong, G.; Ham, S. H.
2016-12-01
A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget from the TOA down to the surface along with the associated atmospheric and surface properties that influence it. CERES relies on a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, high-resolution spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. While the TOA radiation budget is largely determined directly from accurate broadband radiometer measurements, the surface radiation budget is derived indirectly through radiative transfer model calculations initialized using imager-based cloud and aerosol retrievals and meteorological assimilation data. Because ice cloud particles exhibit a wide range of shapes, sizes and habits that cannot be independently retrieved a priori from passive visible/infrared imager measurements, assumptions about the scattering properties of ice clouds are necessary in order to retrieve ice cloud optical properties (e.g., optical depth) from imager radiances and to compute broadband radiative fluxes. This presentation will examine how the choice of an ice cloud particle model impacts computed shortwave (SW) radiative fluxes at the top-of-atmosphere (TOA) and surface. The ice cloud particle models considered correspond to those from prior, current and future CERES data product versions. During the CERES Edition2 (and Edition3) processing, ice cloud particles were assumed to be smooth hexagonal columns. In the Edition4, roughened hexagonal columns are assumed. The CERES team is now working on implementing in a future version an ice cloud particle model comprised of a two-habit ice cloud model consisting of roughened hexagonal columns and aggregates of roughened columnar elements. In each case, we use the same ice particle model in both the imager-based cloud retrievals (inverse problem) and the computed radiative fluxes (forward calculation). In addition to comparing radiative fluxes using the different ice cloud particle models, we also compare instantaneous TOA flux calculations with those observed by the CERES instrument.
Analysis of the Meteorology Associated with the 1998 NASA Glenn Twin Otter Icing Flights
NASA Technical Reports Server (NTRS)
Bernstein, Ben C.
2000-01-01
This document contains a basic analysis of the meteorology associated with the NASA Glenn Twin Otter icing encounters between December 1997 and March 1998. The purpose of this analysis is to provide a meteorological context for the aircraft data collected during these flights. For each case, the following data elements are presented: (1) A brief overview of the Twin Otter encounter, including locations, liquid water contents, temperatures and microphysical makeup of the clouds and precipitation aloft, (2) Upper-air charts, providing hand-analyzed locations of lows, troughs, ridges, saturated/unsaturated air, temperatures, warm/cold advection, and jet streams, (3) Balloon-borne soundings, providing vertical profiles of temperature, moisture and winds, (4) Infrared and visible satellite data, providing cloud locations and cloud top temperature, (5) 3-hourly surface charts, providing hand-analyzed locations of lows, highs, fronts, precipitation (including type) and cloud cover, (6) Hourly, regional radar mosaics, providing fine resolution of the locations of precipitation (including intensity and type), pilot reports of icing (including intensity and type), surface observations of precipitation type and Twin Otter tracks for a one hour window centered on the time of the radar data, and (7) Hourly plots of icing pilot reports, providing the icing intensity, icing type, icing altitudes and aircraft type. Outages occurred in nearly every dataset at some point. All relevant data that was available is presented here. All times are in UTC and all heights are in feet above mean sea level (MSL).
NASA Astrophysics Data System (ADS)
Ruan, Jinshuai; Wen, Xiaohang; Fan, Guangzhou; Li, Deqin; Hua, Wei; Wang, Bingyun; Zhang, Yi; Zhang, Mingjun; Wang, Chao; Wang, Lei
2017-11-01
To study the land surface and atmospheric meteorological characteristics of non-uniform underlying surfaces in the semi-arid area of Northeast China, we use a "High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC)". The grid points of three different underlying surfaces were selected, and their meteorological elements were averaged for each type (i.e., mixed forest, grassland, and cropland). For 2009, we compared and analyzed the different components of leaf area index (LAI), soil temperature and moisture, surface albedo, precipitation, and surface energy for various underlying surfaces in Northeast China. The results indicated that the LAI of mixed forest and cropland during the summer is greater than 5 m2 m-2 and below 2.5 m2 m-2 for grassland; in the winter and spring seasons, the Green Vegetation Fraction (GVF) is below 30%. The soil temperature and moisture both vary greatly. Throughout the year, the mixed forest is dominated by latent heat evaporation; in grasslands and croplands, the sensible heat flux and the latent heat flux are approximately equal, and the GVF contributed more to latent heat flux than sensible heat flux in the summer. This study compares meteorological characteristics between three different underlying surfaces of the semi-arid area of Northeast China and makes up for the insufficiency of purely using observations for the study. This research is important for understanding the water-energy cycle and transport in the semi-arid area.
NASA Astrophysics Data System (ADS)
Peultier, Laetitia; Lion, Alexis; Chary-Valckenaere, Isabelle; Loeuille, Damien; Zhang, Zheng; Rat, Anne-Christine; Gueguen, René; Paysant, Jean; Perrin, Philippe P.
2017-05-01
This study aimed to determine if pain and balance control are related to meteorological modifications in patients with knee osteoarthritis (OA). One hundred and thirteen patients with knee OA (mean age = 65 ± 9 years old, 78 women) participated in this study. Static posturography was performed, sway area covered and sway path traveled by the center of foot pressure being recorded under six standing postural conditions that combine three visual situations (eyes open, eyes closed, vision altered) with two platform situations (firm and foam supports). Knee pain score was assessed using a visual analog scale. Balance control and pain measurements recorded in the morning were correlated with the meteorological data. Morning and daily values for temperature, precipitation, sunshine, height of rain in 1 h, wind speed, humidity, and atmospheric pressure were obtained from the nearest data collecting weather station. The relationship between postural control, pain, and weather variations were assessed for each patient on a given day with multiple linear regressions. A decrease of postural stability was observed when atmospheric pressure and maximum humidity decreased in the morning ( p < 0.05) and when atmospheric pressure decreased within a day ( p < 0.05). Patient's knee pain was more enhanced when it is warmer in the morning ( p < 0.05) and when it is wetter and warmer within a day ( p < 0.05). The relationship between weather, pain, and postural control can help patients and health professionals to better manage daily activities.
NASA Astrophysics Data System (ADS)
Ragosta, Maria; Caggiano, Rosa; D'Emilio, Mariagrazia; Macchiato, Maria
In this paper, we investigate the relationships among atmospheric concentration of trace elements and some meteorological parameters. In particular, the effects of different meteorological conditions on heavy metal levels are interpreted by means of a multivariate statistical approach. The analysed variables were measured during a monitoring survey that started in 1997, and this survey was carried out in order to evaluate the atmospheric concentrations of heavy metals in the industrial area of Tito Scalo (Basilicata Region, Southern Italy). Here we present and analyse the data set collected from 1997 to 1999. The data set includes daily concentrations of total suspended particulates (TSP), daily concentrations of eight metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) in TSP and daily meteoclimatic data (temperature, rainfall, speed and wind directions). Both the concentration level and the occurrence of peak concentration events are consistent with the characteristics of the study area: abundant small and medium industrial plants in a mountainous and unpolluted zone. Regarding the origin of sources of heavy metals in TSP, the statistical procedure allows us to identify three profiles: SP 1 and SP 2 related to industrial sources and SP 3 related to other sources (natural and/or anthropogenic). In particular, taking into account the effect of different meteorological conditions, we are able to distinguish the contribution of different fractions of the same metal in the detected source profiles.
Droegemeier, K.K.; Smith, J.D.; Businger, S.; Doswell, C.; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L.D.; Krajewski, V.; LeMone, M.; Lettenmaier, D.; Mass, C.; Pielke, R.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.
2000-01-01
Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.
NASA Astrophysics Data System (ADS)
Zhang, Y.; Sartelet, K.; Wu, S.-Y.; Seigneur, C.
2013-02-01
Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.
NASA Astrophysics Data System (ADS)
Droegemeier, K. K.; Smith, J. D.; Businger, S.; Doswell, C., III; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L. D.; Krajewski, V.; Lemone, M.; Lettenmaier, D.; Mass, C.; Pielke, R., Sr.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.
2000-11-01
Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists-in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems-to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research (especially multiparameter) and operational radars against gauge data as well as output produced by meso- and storm-scale models; (d) use of data from dense, temporary river gauge networks to trace the fate of rain from its starting location in small basins to the entire stream and river network; and (e) sensitivity testing in the design and implementation of separate as well as coupled meteorological and hydrologic models, the latter designed to better represent those nonlinear feedbacks between the atmosphere and land that are known to play an important role in runoff prediction. Vital to this effort will be the creation of effective and sustained linkages between the historically separate though scientifically related disciplines of meteorology and hydrology, as well as their observational infrastructures and research methodologies.
NASA Astrophysics Data System (ADS)
Coz, Esther; Gómez-Moreno, Francisco J.; Casuccio, Gary S.; ArtíñAno, BegoñA.
2010-06-01
Mineral dust is the second major source of PM10 in Madrid, reaching up to 80% of the PM10 mass during certain long-range dust transport events. Three different types of scenarios have been found to be associated with the high particle concentration episodes in the city: local anthropogenic, regional recirculation, and African dust transport processes. The present study focuses on the characterization of the individual mineral dust particles related to some chemical and morphological features during these three types of episodes, with special attention to local and regional episodes. To achieve this purpose, four different samples were selectively collected during the 2004-2005 period campaigns, one corresponding to each type of scenario and other sample from an Atlantic ventilated one. Meteorological situation, dust source identification, impact on ambient concentrations, size range distribution, and particle individual analysis have been characterized for each of them. Elemental composition and morphology of more than 30,000 mineral particles were analyzed by computer-controlled scanning electron microscopy. Particles were grouped into clusters based on their elemental composition, and the aspect ratio (AR) of each cluster or category was compared for each type of episode. The AR was related to the mineralogical crystal structure of each chemical cluster. The dates chosen for microscopy analysis were in good agreement in size distribution and chemical composition with the average of the dates in the entire campaign and with those from previous campaigns. Major differences between local/regional and long-range transported mineral dust were found in the relative abundance between carbonates and silicates, with much higher abundance of calcium carbonates in the first ones. These differences between silicate and carbonate contents were consistent with the results found in previous campaigns and were directly related to the composition of the parent topsoil by studying the Ca/Si ratios of similar episodes recorded all over the Iberian Peninsula. Differences in morphology were also found for these scenarios. The predominance of calcium carbonate under regional and local influence is scientifically relevant since this mineral is known to react with both SO2 and HNO3 in the atmosphere. Larger average AR values were found for dust particles from long-range transport, and smaller average AR values were found for particles from local and regional resuspended dust. The increasing average AR value has been linked to the silicate cluster presence, whereas a reduction has been observed within the carbonate cluster.
A method to determine agro-climatic zones based on correlation and cluster analyses
NASA Astrophysics Data System (ADS)
Borges Valeriano, Taynara Tuany; de Souza Rolim, Glauco; de Oliveira Aparecido, Lucas Eduardo
2017-12-01
Determining agro-climatic zones (ACZs) is traditionally made by cross-comparing meteorological elements such as air temperature, rainfall, and water deficit (DEF). This study proposes a new method based on correlations between monthly DEFs during the crop cycle and annual yield and performs a multivariate cluster analysis on these correlations. This `correlation method' was applied to all municipalities in the state of São Paulo to determine ACZs for coffee plantations. A traditional ACZ method for coffee, which is based on temperature and DEF ranges (Evangelista et al.; RBEAA, 6:445-452, 2002), was applied to the study area to compare against the correlation method. The traditional ACZ classified the "Alta Mogina," "Média Mogiana," and "Garça and Marília" regions as traditional coffee regions that were either suitable or even restricted for coffee plantations. These traditional regions have produced coffee since 1800 and should not be classified as restricted. The correlation method classified those areas as high-producing regions and expanded them into other areas. The proposed method is innovative, because it is more detailed than common ACZ methods. Each developmental crop phase was analyzed based on correlations between the monthly DEF and yield, improving the importance of crop physiology in relation to climate.
Monitoring of atmospheric particles and ozone in Sequoia National Park: 1985-1987. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cahill, T.A.
1989-06-01
The Air Quality Group Monitored particles and ozone in Sequoia National Park as part of an effort to understand the impact of acid deposition and other air pollutants on the park's forests and watersheds. For high-elevation ozone measurement, the project developed a new solar-powered ozone monitoring system. The particulate matter sampled was analyzed for elemental content using nuclear techniques. The measurements were correlated with meteorology, known elemental sources, and wet and dry deposition measurements. The results show that particulate matter at Sequoia National Park is similar to that present at other sites on the western slope of the Sierra Nevadamore » range at equivalent elevations. Some anthropogenic species, including nickel and sulfate, are present in higher concentrations at Sequoia than at Yosemite National Park.« less
Integrating Meteorology into Research on Migration
Shamoun-Baranes, Judy; Bouten, Willem; van Loon, E. Emiel
2010-01-01
Atmospheric dynamics strongly influence the migration of flying organisms. They affect, among others, the onset, duration and cost of migration, migratory routes, stop-over decisions, and flight speeds en-route. Animals move through a heterogeneous environment and have to react to atmospheric dynamics at different spatial and temporal scales. Integrating meteorology into research on migration is not only challenging but it is also important, especially when trying to understand the variability of the various aspects of migratory behavior observed in nature. In this article, we give an overview of some different modeling approaches and we show how these have been incorporated into migration research. We provide a more detailed description of the development and application of two dynamic, individual-based models, one for waders and one for soaring migrants, as examples of how and why to integrate meteorology into research on migration. We use these models to help understand underlying mechanisms of individual response to atmospheric conditions en-route and to explain emergent patterns. This type of models can be used to study the impact of variability in atmospheric dynamics on migration along a migratory trajectory, between seasons and between years. We conclude by providing some basic guidelines to help researchers towards finding the right modeling approach and the meteorological data needed to integrate meteorology into their own research. PMID:20811515
Gao, Jinghong; Chen, Xiaojun; Woodward, Alistair; Liu, Xiaobo; Wu, Haixia; Lu, Yaogui; Li, Liping; Liu, Qiyong
2016-01-01
Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and −27.66 (t = −5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future. PMID:27853316
NASA Astrophysics Data System (ADS)
Cheng, Chad Shouquan; Li, Qian; Li, Guilong
2010-05-01
The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been applied in Environment Canada to analyze climatic change impacts on various meteorological/hydrological risks, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the hazardous events, (2) statistical downscaling to provide station-scale future climate information, and (3) estimates of changes in frequency and magnitude of future hazardous meteorological/hydrological events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and various linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into the entire modeling exercise. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. This paper will briefly summarize these research projects, focusing on the modeling exercise and results.
Study on paddy rice yield estimation based on multisource data and the Grey system theory
NASA Astrophysics Data System (ADS)
Deng, Wensheng; Wang, Wei; Liu, Hai; Li, Chen; Ge, Yimin; Zheng, Xianghua
2009-10-01
The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation, and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing estimation.
Establishment and analysis of High-Resolution Assimilation Dataset of water-energy cycle over China
NASA Astrophysics Data System (ADS)
Wen, Xiaohang; Liao, Xiaohan; Dong, Wenjie; Yuan, Wenping
2015-04-01
For better prediction and understanding of water-energy exchange process and land-atmospheric interaction, the in-situ observed meteorological data which were acquired from China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated by the Normalized Difference Vegetation Index (NDVI) of Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS), Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system were also integrated in the WRF model over China. Further, the High-Resolution Assimilation Dataset of water-energy cycle over China (HRADC) was produced by WRF model. This dataset include 25 km horizontal resolution near surface meteorological data such as air temperature, humidity, ground temperature, and pressure at 19 levels, soil temperature and soil moisture at 4 levels, green vegetation coverage, latent heat flux, sensible heat flux, and ground heat flux for 3 hours. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method; 2) Compare results of meteorological elements such as 2 m temperature, precipitation and ground temperature generated by the HRADC with the gridded observation data from CMA, and Global Land Data Assimilation System (GLDAS) output data from National Aeronautics and Space Administration (NASA). It is found that the results of 2 m temperature were improved compared with the control simulation and has effectively reproduced the observed patterns, and the simulated results of ground temperature, 0-10 cm soil temperature and specific humidity were as much closer to GLDAS outputs. Root mean square errors are reduced in assimilation run than control run, and the assimilation run of ground temperature, 0-10 cm soil temperature, radiation and surface fluxes were agreed well with the GLDAS outputs over China. The HRADC could be used in further research on the long period climatic effects and characteristics of water-energy cycle over China.
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.
NASA Astrophysics Data System (ADS)
Amil, N.; Latif, M. T.; Khan, M. F.; Mohamad, M.
2015-09-01
This study attempts to investigate the fine particulate matter (PM2.5) variability in the Klang Valley urban-industrial environment. In total, 94 daily PM2.5 samples were collected during a one-year campaign from August 2011 to July 2012, covering all four seasons. The samples were analysed for various inorganic components and black carbon. The chemical compositions were statistically analysed and the aerosol pattern was characterised using descriptive analysis, correlation matrices, enrichment factors (EF), stoichiometric analysis and chemical mass closure (CMC). For source apportionment purposes, a combination of positive matrix factorisation (PMF) and multi-linear regression (MLR) was employed. Further, meteorological-gaseous parameters were incorporated into each analysis for improved assessment. The results showed that PM2.5 mass averaged at 28 ± 18 μg m-3, 2.8 fold higher than the World Health Organisation (WHO) annual guideline. On a daily basis, the PM2.5 mass ranged between 6 and 118 μg m-3 with 43 % exceedance of the daily WHO guideline. The North-East monsoon (NE) was the only season with < 50 % sample exceedance of the daily WHO guideline. On an annual scale, PM2.5 mass correlated positively with temperature (T) and wind speed (WS) but negatively with relative humidity (RH). With the exception of NOx, the gases analysed (CO, NO2, NO and SO2) were found to significantly influence the PM2.5 mass. Seasonal variability unexpectedly showed that rainfall, WS and wind direction (WD) did not significantly correlate with PM2.5 mass. Further analysis on the PM2.5 / PM10, PM2.5 / TSP and PM10 / TSP ratios reveal that meteorological parameters only greatly influenced the coarse particles (PM > 2.5μm) and less so the fine particles at the site. Chemical composition showed that both primary and secondary pollutants of PM2.5 are equally important, albeit with seasonal variability. The CMC components identified were: black carbon (BC) > secondary inorganic aerosols (SIA) > dust > trace elements (TE) > sea salt > K+. The EF analysis distinguished two groups of trace elements: those with anthropogenic sources (Pb, Se, Zn, Cd, As, Bi, Ba, Cu, Rb, V and Ni) and those with a crustal source (Sr, Mn, Co and Li). The five identified factors resulting from PMF 5.0 were: (1) combustion of engine oil; (2) mineral dust; (3) mixed SIA and biomass burning; (4) mixed traffic and industrial; and (5) sea salt. Each of these sources had an annual mean contribution of 17, 14, 42, 10 and 17 %, respectively. The dominance of each identified source largely varied with changing season and a few factors were in agreement with the CMC, EF and stoichiometric analysis, accordingly. In relation to meteorological-gaseous parameters, PM2.5 sources were influenced by different parameters during different seasons. In addition, two air pollution episodes (HAZE) revealed the influence of local and/or regional sources. Overall, our study clearly suggests that the chemical constituents and sources of PM2.5 were greatly influenced and characterised by meteorological and gaseous parameters which largely vary with season.
Probabilistic Meteorological Characterization for Turbine Loads
NASA Astrophysics Data System (ADS)
Kelly, M.; Larsen, G.; Dimitrov, N. K.; Natarajan, A.
2014-06-01
Beyond the existing, limited IEC prescription to describe fatigue loads on wind turbines, we look towards probabilistic characterization of the loads via analogous characterization of the atmospheric flow, particularly for today's "taller" turbines with rotors well above the atmospheric surface layer. Based on both data from multiple sites as well as theoretical bases from boundary-layer meteorology and atmospheric turbulence, we offer probabilistic descriptions of shear and turbulence intensity, elucidating the connection of each to the other as well as to atmospheric stability and terrain. These are used as input to loads calculation, and with a statistical loads output description, they allow for improved design and loads calculations.
2013-09-30
forcing through an ensemble-based method. The results of our findings were presented at the 2013 American Meteorological Society (AMS) annual meeting...Forcing to the Existing Satellite Observations, 93rd American Meteorological Society Annual Meeting, Austin, Texas, January 5-10, 2013b...Ceburnis, D., Chang, R., Clarke, A., de Leeuw, G., Deane, G., DeMott, P. J., Elliot, S., Facchini, M. C., Fairall, C. W., Hawkins, L., Hu, Y., Hudson , J
NASA Astrophysics Data System (ADS)
Qin, Jin; Bai, Hongying; Su, Kai; Liu, Rongjuan; Zhai, Danping; Wang, Jun; Li, Shuheng; Zhou, Qi; Li, Bin
2018-01-01
Previous dendroclimatical studies have been based on the relationship between tree growth and instrumental climate data recorded at lower land meteorological stations, but the climate conditions somehow differ between sampling sites and distant population centers. Thus, in this study, we performed a comparison between the 152-year reconstruction of June to July mean air temperature on the basis of interpolated meteorological data and instrumental meteorological data. The reconstruction explained 38.7% of the variance in the interpolated temperature data (37.2% after the degrees of freedom were adjusted) and 39.6% of the variance in the instrumental temperature data (38.4% after adjustment for loss of degrees of freedom) during the period 1962-2013 AD. The first global warming (the 1920s) and recent warming (1990-2013) found from the reconstructed temperature series match reasonably well with two other reported summer temperature reconstructions from north-central China. Cold periods occurred three times during 1866-1885, 1901-1921, and 1981-2000, while hot periods occurred four times during 1886-1900, 1922-1933, 1953-1966, and 2001-2007. The extreme warm (cold) years are coherent with the documentary drought (flood) events. Significant 31-22-year, 22-18-year, and 12-8-year cycles indicate major fluctuations in regional temperatures may reflect large-scale climatic shifts.
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.
NASA Astrophysics Data System (ADS)
Brázdil, R.; Büntgen, U.; Dobrovolný, P.; Trnka, M.; Kyncl, T.
2010-09-01
Precipitation is one of the most important meteorological elements for different natural processes as well as for human society. Its long term fluctuations in the Czech Lands (recent Czech Republic) can be studied using long instrumental series (Brno since January 1803, Prague-Klementinum since May 1804), a tree-ring chronology from southern Moravian fir Abies alba Mill. developed from living and historical trees (since A.D. 1376), and monthly precipitation indices derived from documentary evidence (from A.D. 1500). The analysis focuses on May-June precipitation and drought patterns represented by the Z-index for the past 500 years showing the highest response of the tree-ring chronology to the mentioned months in the calibration/verification period between 1803 and 1932. Tree-ring and documentary-based May-June Z-index reconstructions explaining ca 30-40% of its variability are compared with existing reconstructions of hydroclimatic patterns of the Central European region. Uncertainties of tree-ring and documentary datasets and corresponding reconstructions are discussed.
Optimum space shuttle launch times relative to natural environment
NASA Technical Reports Server (NTRS)
King, R. L.
1977-01-01
Three sets of meteorological criteria were analyzed to determine the probabilities of favorable launch and landing conditions. Probabilities were computed for every 3 hours on a yearly basis using 14 years of weather data. These temporal probability distributions, applicable to the three sets of weather criteria encompassing benign, moderate and severe weather conditions, were computed for both Kennedy Space Center (KSC) and Edwards Air Force Base. In addition, conditional probabilities were computed for unfavorable weather conditions occurring after a delay which may or may not be due to weather conditions. Also, for KSC, the probabilities of favorable landing conditions at various times after favorable launch conditions have prevailed have been computed so that mission probabilities may be more accurately computed for those time periods when persistence strongly correlates weather conditions. Moreover, the probabilities and conditional probabilities of the occurrence of both favorable and unfavorable events for each individual criterion were computed to indicate the significance of each weather element to the overall result.
Emerging methods for the study of coastal ecosystem landscape structure and change
Brock, John C.; Danielson, Jeffrey J.; Purkis, Sam
2013-01-01
Coastal landscapes are heterogeneous, dynamic, and evolve over a range of time scales due to intertwined climatic, geologic, hydrologic, biologic, and meteorological processes, and are also heavily impacted by human development, commercial activities, and resource extraction. A diversity of complex coastal systems around the globe, spanning glaciated shorelines to tropical atolls, wetlands, and barrier islands are responding to multiple human and natural drivers. Interdisciplinary research based on remote-sensing observations linked to process studies and models is required to understand coastal ecosystem landscape structure and change. Moreover, new techniques for coastal mapping and monitoring are increasingly serving the needs of policy-makers and resource managers across local, regional, and national scales. Emerging remote-sensing methods associated with a diversity of instruments and platforms are a key enabling element of integrated coastal ecosystem studies. These investigations require both targeted and synoptic mapping, and involve the monitoring of formative processes such as hydrodynamics, sediment transport, erosion, accretion, flooding, habitat modification, land-cover change, and biogeochemical fluxes.
Yamazaki, Shin; Shima, Masayuki; Yoda, Yoshiko; Oka, Katsumi; Kurosaka, Fumitake; Shimizu, Shigeta; Takahashi, Hironobu; Nakatani, Yuji; Nishikawa, Jittoku; Fujiwara, Katsuhiko; Mizumori, Yasuyuki; Mogami, Akira; Yamada, Taku; Yamamoto, Nobuharu
2014-03-01
In January 2013, extremely high concentrations of fine particles (PM2.5) were observed around Beijing, China. In Japan, the health effects of transboundary air pollution have been a matter of concern. We examined the association between the levels of outdoor PM2.5 and other air pollutants with primary care visits (PCVs) at night due to asthma attack in Himeji City, western Japan. A case-crossover study was conducted in a primary care clinic in Himeji City, Japan, involving 112 subjects aged 0-80 years who visited the clinic due to an asthma attack between 9 p.m. and 6 a.m. during the period January-March, 2013. Daily concentrations of particulate matter, ozone, nitrogen dioxide, and some meteorological elements were measured, and a conditional logistic regression model was used to estimate the odds ratios (OR) of PCVs per unit increment in air pollutants or meteorological elements. Of the 112 subjects, 76 (68 %) were aged <15 years. We did not note any association between daily PM2.5 levels and PCVs due to asthma attack at night. A positive relation between ozone and PCVs due to asthma attack was detected. The OR per 10 ppb increment in daily mean ozone the day before the visit was 2.31 (95 % confidence interval 1.16-4.61). These findings do not support an association between daily mean concentration of PM2.5 and PCVs at night. However, we did find evidence suggesting that ozone is associated with PCVs.
NASA Technical Reports Server (NTRS)
Rui, Hualan; Vollmer, B.; Teng, W.; Beaudoing, H.; Rodell, M.; Silberstein, D.
2015-01-01
GLDAS-2.0 data have been reprocessed with updated Princeton meteorological forcing data within the Land Information System (LIS) Version 7, and temporal coverage have been extended to 1948-2012.Global Land Data Assimilation System Version 2 (GLDAS-2) has two components: GLDAS-2.0: entirely forced with the Princeton meteorological forcing data GLDAS-2.1: forced with atmospheric analysis and observation-based data after 2001In order to create more climatologically consistent data sets, NASA GSFC's Hydrological Sciences Laboratory (HSL) has recently reprocessed the GLDAS-2.0, by using updated Princeton meteorological forcing data within the LIS Version 7.GLDAS-2.0 data and data services are provided at NASA GES DISC Hydrology Data and Information Services Center (HDISC), in collaboration with HSL.
Public understanding of cyclone warning in India: Can wind be predicted?
Dash, Biswanath
2015-11-01
In spite of meteorological warning, many human lives are lost every year to cyclone mainly because vulnerable populations were not evacuated on time to a safe shelter as per recommendation. It raises several questions, most prominently what explains people's behaviour in the face of such danger from a cyclonic storm? How do people view meteorological advisories issued for cyclone and what role they play in defining the threat? What shapes public response during such situation? This article based on an ethnographic study carried out in coastal state of Odisha, India, argues that local public recognising inherent limitations of meteorological warning, fall back on their own system of observation and forecasting. Not only are the contents of cyclone warning understood, its limitations are accommodated and explained. © The Author(s) 2014.
Homogeneity study of fixed-point continuous marine environmental and meteorological data: a review
NASA Astrophysics Data System (ADS)
Yang, Jinkun; Yang, Yang; Miao, Qingsheng; Dong, Mingmei; Wan, Fangfang
2018-02-01
The principle of inhomogeneity and the classification of homogeneity test methods are briefly described, and several common inhomogeneity methods and relative merits are described in detail. Then based on the applications of the different homogeneity methods to the ground meteorological data and marine environment data, the present status and the progress are reviewed. At present, the homogeneity research of radiosonde and ground meteorological data is mature at home and abroad, and the research and application in the marine environmental data should also be given full attention. To carry out a variety of test and correction methods combined with the use of multi-mode test system, will make the results more reasonable and scientific, and also can be used to provide accurate first-hand information for the coastal climate change researches.
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.
NASA Astrophysics Data System (ADS)
Stauffer, R. M.; Thompson, A. M.
2017-12-01
Previous studies employing the self-organizing map (SOM) clustering technique to US ozonesonde data proved valuable for quantifying UT/LS O3 variability, and linking meteorological and chemical drivers to the shape of the ozone (O3) profile from the troposphere to the lower stratosphere. Focus has thus far been limited to specific geographical regions, but SOM has demonstrated the advantages of clustering over monthly climatological O3 averages, which mask day-to-day variability in the O3 profile and the correspondence between O3 and meteorology. We expand SOM to a global set of ozonesonde profiles, mostly from WOUDC, spanning 1980-present from 30 sites to evaluate global O3 climatologies and quantify links to geophysical processes for various meteorological regimes. Four clusters of O3 mixing ratio profiles are generated for each site, which show dominant profile shapes that correspond to site latitude. Offsets among O3 profile clusters and monthly O3 climatologies are 100s of ppbv in the UT/LS at higher latitude sites with active dynamics. Examination of meteorological reanalyses reveals a clear relationship among SOM clusters and covarying meteorological fields (geopotential height, potential vorticity, and tropopause height) for most sites. Tropical SOM clusters show marked dependence on velocity potential anomalies calculated from reanalysis winds, with low UT/LS O3 amounts corresponding to enhanced upper-level divergence, and vice versa. In addition to creating SOM cluster-based O3 climatologies, these results are meant to inform future approaches to validation of chemical transport models and satellite retrievals, which often struggle in the UT/LS region.
NASA Astrophysics Data System (ADS)
Abaza, Mabrouk; Anctil, François; Fortin, Vincent; Perreault, Luc
2017-12-01
Meteorological and hydrological ensemble prediction systems are imperfect. Their outputs could often be improved through the use of a statistical processor, opening up the question of the necessity of using both processors (meteorological and hydrological), only one of them, or none. This experiment compares the predictive distributions from four hydrological ensemble prediction systems (H-EPS) utilising the Ensemble Kalman filter (EnKF) probabilistic sequential data assimilation scheme. They differ in the inclusion or not of the Distribution Based Scaling (DBS) method for post-processing meteorological forecasts and the ensemble Bayesian Model Averaging (ensemble BMA) method for hydrological forecast post-processing. The experiment is implemented on three large watersheds and relies on the combination of two meteorological reforecast products: the 4-member Canadian reforecasts from the Canadian Centre for Meteorological and Environmental Prediction (CCMEP) and the 10-member American reforecasts from the National Oceanic and Atmospheric Administration (NOAA), leading to 14 members at each time step. Results show that all four tested H-EPS lead to resolution and sharpness values that are quite similar, with an advantage to DBS + EnKF. The ensemble BMA is unable to compensate for any bias left in the precipitation ensemble forecasts. On the other hand, it succeeds in calibrating ensemble members that are otherwise under-dispersed. If reliability is preferred over resolution and sharpness, DBS + EnKF + ensemble BMA performs best, making use of both processors in the H-EPS system. Conversely, for enhanced resolution and sharpness, DBS is the preferred method.
NASA Astrophysics Data System (ADS)
Kim, Gibaek; Yoon, Young-Jun; Kim, Hyun-A.; Cho, Hee-joo; Park, Kihong
2017-08-01
Two laser-induced breakdown spectroscopy (LIBS) systems (soil LIBS and aerosol LIBS) were used to determine the elemental composition of soils and ambient aerosols less than 2.5 μm in Ny-Ålesund, Svalbard (the world's most northerly human settlement). For soil LIBS measurements, matrix effects such as moisture content, soil grain size, and surrounding gas on the LIBS response were minimized. When Ar gas was supplied onto the soil sample surfaces, a significant enhancement in LIBS emission lines was observed. Arctic soil samples were collected at 10 locations, and various elements (Al, Ba, C, Ca, Cu, Fe, H, K, Mg, Mn, N, Na, O, Pb, and Si) were detected in soils. The elemental distribution in arctic soils was clearly distinguishable from those in urban and abandoned mining soils in Korea. Moreover, the concentrations of most of anthropogenic metals were fairly low, and localized sources in extremely close proximity affected the elevated level of Cu in the soil samples derived from Ny-Ålesund. The number of elements detected in aerosols (C, Ca, H, K, Mg, Na, and O) was lower than those determined in soils. The elements in aerosols can mainly originate from minerals and sea salts. The elemental distribution in aerosols was also clearly distinguishable from that in soils, suggesting that the resuspension of local soil particles by wind erosion into aerosols was minimal. The daily variation of particle number concentration (RSD = 71%) and the elements in aerosols (RSD = 25%) varied substantially, possibly due to fluctuating air masses and meteorological conditions.
NASA Astrophysics Data System (ADS)
Surovyatkina, Elena; Stolbova, Veronika; Kurths, Jurgen
2017-04-01
The monsoon is the season of rain caused by a global seasonal reverse in winds direction and a change in pressure distribution. The Southwest winds bring summer monsoon to India. The economy of India is able to maintain its GDP in the wake of a good monsoon. However, if monsoon gets delayed by even two weeks, it can spell disaster because the high population depending on agriculture - 70% of its people directly related to farming. Agriculture, in turn, is dependent on the monsoon. Although the rainy season happens annually between June and September, the time of monsoon season's onset and withdrawal varies within a month from year to year. The important feature of the monsoon is that it starts and ends suddenly. Hence, despite enormous progress having been made in predicting monsoon since 1886, it remains a significant scientific challenge. To make predictions of monsoon timing in 2016, we applied our recently developed method [1]. Our approach is based on a teleconnection between the Eastern Ghats (EG) and North Pakistan (NP) - Tipping Elements of Indian Summer Monsoon. Both our predictions - for monsoon onset and withdrawal - were made for the Eastern Ghats region (EG-20N,80E) in the central part of India, while the Indian Meteorological Department forecasts monsoon over Kerala - a state at the southern tip of the Indian subcontinent. Our prediction for monsoon onset was published on May 6-th, 2016 [2]. We predicted the monsoon arrival to the EG on the 13th of June with a deviation of +/-4 days. In fact, monsoon onset was on June 17-th, that was confirmed by information from meteorological stations located around the EG-region. Hence, our prediction of monsoon onset (made 40 days in advance) was correct. We delivered the prediction of monsoon withdrawal on July 27, 2016 [3], announcing the monsoon withdrawal from the EG on October 5-th with a deviation of +/-5 days. The actual monsoon withdrawal started on October 10-th when the relative humidity in the region started to decrease, and after two days meteorological stations reported 'No rain' in the EG and also in areas located across the subcontinent in the direction from the North Pakistan to the Bay of Bengal. Hence, the date of monsoon withdrawal - October 10-th, predicted 70 days in advance, lies within our prediction interval. Our results show that our method allows predicting a future monsoon, and not only retrospectively or hindcast. In 2016 we predicted of the onset and withdrawal dates of the Southwest monsoon over the Eastern Ghats region in Central India for 40 and 70 days in advance respectively. Our general framework for predicting spatial-temporal critical transitions is applicable for systems of different nature. It allows predicting future from observational data only, when the model of a transition does not exist yet. [1] Stolbova, V., E. Surovyatkina, B. Bookhagen, and J. Kurths (2016): Tipping elements of the Indian monsoon: Prediction of onset and withdrawal. Geophys. Res. Lett., 43, 1-9. [2]https://www.pik-potsdam.de/news/press-releases/indian-monsoon-novel-approach-allows-early-forecasting?set_language=en [3] https://www.pik-potsdam.de/kontakt/pressebuero/fotos/monsoon-withdrawal/view
Improving of local ozone forecasting by integrated models.
Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš
2016-09-01
This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.
NASA Technical Reports Server (NTRS)
Dreher, Joseph G.
2009-01-01
For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.
NASA Astrophysics Data System (ADS)
Wang, Chaolin; Zhong, Shaobo; Zhang, Fushen; Huang, Quanyi
2016-11-01
Precipitation interpolation has been a hot area of research for many years. It had close relation to meteorological factors. In this paper, precipitation from 91 meteorological stations located in and around Yunnan, Guizhou and Guangxi Zhuang provinces (or autonomous region), Mainland China was taken into consideration for spatial interpolation. Multivariate Bayesian maximum entropy (BME) method with auxiliary variables, including mean relative humidity, water vapour pressure, mean temperature, mean wind speed and terrain elevation, was used to get more accurate regional distribution of annual precipitation. The means, standard deviations, skewness and kurtosis of meteorological factors were calculated. Variogram and cross- variogram were fitted between precipitation and auxiliary variables. The results showed that the multivariate BME method was precise with hard and soft data, probability density function. Annual mean precipitation was positively correlated with mean relative humidity, mean water vapour pressure, mean temperature and mean wind speed, negatively correlated with terrain elevation. The results are supposed to provide substantial reference for research of drought and waterlog in the region.
Applied Meteorology Unit (AMU)
NASA Technical Reports Server (NTRS)
Bauman, William H., Jr.; Crawford, Winifred; Short, David; Barrett, Joe; Watson, Leela
2008-01-01
This report summarizes the Applied Meteorology Unit (AMU) activities for the second quarter of Fiscal Year 2008 (January - March 2008). Projects described are: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Peak Wind Tool for General Forecasting, (3) Situational Lightning Climatologies for Central Florida. Phase III, (4) Volume Averaged Height Integrated Radar Reflectivity (VAHIRR), (5) Impact of Local Sensors, (6) Radar Scan Strategies for the PAFB WSR-74C Replacement and (7) WRF Wind Sensitivity Study at Edwards Air Force Base.
28. VIEW SOUTH FROM SLC3W MST STATION 63. FOREGROUND LEFT: ...
28. VIEW SOUTH FROM SLC-3W MST STATION 63. FOREGROUND LEFT: THEODOLITE SHELTER (BLDG. 786) CENTER LEFT TO RIGHT: GLOBAL POSITIONING SYSTEM AZIMUTH STATION (BLDG. 775), PYROTECHNIC SHED (BLDG. 757), PORTABLE GUARD SHED, METEOROLOGICAL SHED (BLDG. 756), METEOROLOGICAL TOWER. BACKGROUND CENTER TO RIGHT: STORAGE SHED (BLDG. 776), LIQUID OXYGEN APRON, SLC-3E MST, TOP OF SLC-3E FUEL STORAGE TANK. - Vandenberg Air Force Base, Space Launch Complex 3, Launch Pad 3 West, Napa & Alden Roads, Lompoc, Santa Barbara County, CA
NASA Astrophysics Data System (ADS)
Li, Qiong; Geng, Fangzhi
2018-03-01
Based on the characteristics of complex terrain and different seasons’ weather in Qinghai Tibet Plateau, through statistic the daily rainfall that from 2002 to 2012, nearly 11 years, by Bomi meteorological station, Bomi area rainfall forecast model is established, and which can provide the basis forecasting for dangerous weather warning system on the balloon borne radar in the next step, to protect the balloon borne radar equipment’s safety work and combat effectiveness.
Improvement of Meteorological Inputs for TexAQS-II Air Quality Simulations
NASA Astrophysics Data System (ADS)
Ngan, F.; Byun, D.; Kim, H.; Cheng, F.; Kim, S.; Lee, D.
2008-12-01
An air quality forecasting system (UH-AQF) for Eastern Texas, which is in operation by the Institute for Multidimensional Air Quality Studies (IMAQS) at the University of Houston, uses the Fifth-Generation PSU/NCAR Mesoscale Model MM5 model as the meteorological driver for modeling air quality with the Community Multiscale Air Quality (CMAQ) model. While the forecasting system was successfully used for the planning and implementation of various measurement activities, evaluations of the forecasting results revealed a few systematic problems in the numerical simulations. From comparison with observations, we observe some times over-prediction of northerly winds caused by inaccurate synoptic inputs and other times too strong southerly winds caused by local sea breeze development. Discrepancies in maximum and minimum temperature are also seen for certain days. Precipitation events, as well as clouds, are simulated at the incorrect locations and times occasionally. Model simulatednrealistic thunderstorms are simulated, causing sometimes cause unrealistically strong outflows. To understand physical and chemical processes influencing air quality measures, a proper description of real world meteorological conditions is essential. The objective of this study is to generate better meteorological inputs than the AQF results to support the chemistry modeling. We utilized existing objective analysis and nudging tools in the MM5 system to develop the MUltiscale Nest-down Data Assimilation System (MUNDAS), which incorporates extensive meteorological observations available in the simulated domain for the retrospective simulation of the TexAQS-II period. With the re-simulated meteorological input, we are able to better predict ozone events during TexAQS-II period. In addition, base datasets in MM5 such as land use/land cover, vegetation fraction, soil type and sea surface temperature are updated by satellite data to represent the surface features more accurately. They are key physical parameters inputs affecting transfer of heat, momentum and soil moisture in land-surface process in MM5. Using base the accurate input datasets, we are able to have improved see the differences of predictions of ground temperatures, winds and even thunderstorm activities within boundary layer.
NASA Astrophysics Data System (ADS)
Xu, Yu; Xu, Youpeng; Wang, Yuefeng; Wu, Lei; Li, Guang; Song, Song
2017-11-01
Reference crop evapotranspiration (ETo) is one of the most important links in hydrologic circulation and greatly affects regional agricultural production and water resource management. Its variation has drawn more and more attention in the context of global warming. We used the Penman-Monteith method of the Food and Agriculture Organization, based on meteorological factors such as air temperature, sunshine duration, wind speed, and relative humidity to calculate the ETo over 46 meteorological stations located in the Yangtze River Delta, eastern China, from 1957 to 2014. The spatial distributions and temporal trends in ETo were analyzed based on the modified Mann-Kendall trend test and linear regression method, while ArcGIS software was employed to produce the distribution maps. The multiple stepwise regression method was applied in the analysis of the meteorological variable time series to identify the causes of any observed trends in ETo. The results indicated that annual ETo showed an obvious spatial pattern of higher values in the north than in the south. Annual increasing trends were found at 34 meteorological stations (73.91 % of the total), which were mainly located in the southeast. Among them, 12 (26.09 % of the total) stations showed significant trends. We saw a dominance of increasing trends in the monthly ETo except for January, February, and August. The high value zone of monthly ETo appeared in the northwest from February to June, mid-south area from July to August, and southeast coastal area from September to January. The research period was divided into two stages—stage I (1957-1989) and stage II (1990-2014)—to investigate the long-term temporal ETo variation. In stage I, almost 85 % of the total stations experienced decreasing trends, while more than half of the meteorological stations showed significant increasing trends in annual ETo during stage II except in February and September. Relative humidity, wind speed, and sunshine duration were identified as the most dominant meteorological variables influencing annual ETo changes. The results are expected to assist water resource managers and policy makers in making better planning decisions in the research region.
NASA Astrophysics Data System (ADS)
Vaidyanathan, A.; Yip, F.
2017-12-01
Context: Studies that have explored the impacts of environmental exposure on human health have mostly relied on data from weather stations, which can be limited in geographic scope. For this assessment, we: (1) evaluated the performance of the meteorological data from the North American Land Data Assimilation System Phase 2 (NLDAS) model with measurements from weather stations for public health and specifically for CDC's Environmental Public Health Tracking Program, and (2) conducted a health assessment to explore the relationship between heat exposure and mortality, and examined region-specific differences in heat-mortality (H-M) relationships when using model-based estimates in place of measurements from weather stations.Methods: Meteorological data from the NLDAS Phase 2 model was evaluated against measurements from weather stations. A time-series analysis was conducted, using both station- and model-based data, to generate H-M relationships for counties in the U.S. The county-specific risk information was pooled to characterize regional relationships for both station- and model-based data, which were then compared to identify degrees of overlap and discrepancies between results generated using the two data sources. Results: NLDAS-based heat metrics were in agreement with those generated using weather station data. In general, the H-M relationship tended to be non-linear and varied by region, particularly the heat index value at which the health risks become positively significant. However, there was a high degree of overlap between region-specific H-M relationships generated from weather stations and the NLDAS model.Interpretation: Heat metrics from NLDAS model are available for all counties in the coterminous U.S. from 1979-2015. These data can facilitate health research and surveillance activities exploring health impacts associated with long-term heat exposures at finer geographic scales.Conclusion: High spatiotemporal coverage of environmental health data is an important attribute in understanding potential public health impacts. With the limited geographic scope of station-based measurements, adopting NLDAS-based modeled estimates in CDC's Tracking Network would provide a more comprehensive understanding of specific meteorological exposures on human health.
NASA Astrophysics Data System (ADS)
Finley, Jason Paul
This study examined the impact of dialogue-based group instruction on student learning and engagement in community college meteorology education. A quasi-experimental design was used to compare lecture-based instruction with dialogue-based group instruction during two class sessions at one community college in southern California. Pre- and post-tests were used to measure learning and interest, while surveys were conducted two days after the learning events to assess engagement, perceived learning, and application of content. The results indicated that the dialogue-based group instruction was more successful in helping students learn than the lecture-based instruction. Each question that assessed learning had a higher score for the dialogue group that was statistically significant (alpha < 0.05) compared to the lecture group. The survey questions about perceived learning and application of content also exhibited higher scores that were statistically significant for the dialogue group. The qualitative portion of these survey questions supported the quantitative results and showed that the dialogue students were able to remember more concepts and apply these concepts to their lives. Dialogue students were also more engaged, as three out of the five engagement-related survey questions revealed statistically significantly higher scores for them. The qualitative data also supported increased engagement for the dialogue students. Interest in specific meteorological topics did not change significantly for either group of students; however, interest in learning about severe weather was higher for the dialogue group. Neither group found the learning events markedly meaningful, although more students from the dialogue group found pronounced meaning centered on applying severe weather knowledge to their lives. Active engagement in the dialogue approach kept these students from becoming distracted and allowed them to become absorbed in the learning event. This higher engagement most likely contributed to the resulting higher learning. Together, these results indicate that dialogue education, especially compared to lecture methods, has a great potential for helping students learn meteorology. Dialogue education can also help students engage in weather-related concepts and potentially develop better-informed citizens in a world with a changing climate.
NASA Astrophysics Data System (ADS)
Lanorte, R.; Lasaponara, R.; De Santis, F.; Aromando, A.; Nole, G.
2012-04-01
Daily estimates of fire danger using multitemporal satellite MODIS data: the experience of FIRE-SAT in the Basilicata Region (Italy) A. Lanorte, F. De Santis , A. Aromando, G. Nolè, R. Lasaponara, CNR-IMAA, Potenza, Italy In the recent years the Basilicata Region (Southern Italy) has been characterized by an increasing incidence of fire disturbance which also tends to affect protected (Regional and national parks) and natural vegetated areas. FIRE_SAT project has been funded by the Civil Protection of the Basilicata Region in order to set up a low cost methodology for fire danger/risk monitoring based on satellite Earth Observation techniques. To this aim, NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data were used. The spectral capability and daily availability makes MODIS products especially suitable for estimating the variations of fuel characteristics. This work presents new significant results obtained in the context of FIRE-SAT project. In order to obtain a dynamical indicator of fire susceptibility based on multitemporal MODIS satellite data, up-datable in short-time periods (daily), we used the spatial/temporal variations of following parameters: (1) Relative Greenness Index (2) Live and dead fuel moisture content (3) Temperature In particular, the dead fuel moisture content is a key factor in fire ignition. Dead fuel moisture dynamics are significantly faster than those observed for live fuel. Dead fine vegetation exhibits moisture and density values dependent on rapid atmospheric changes and strictly linked to local meteorological conditions. For this reason, commonly, the estimation of dead fuel moisture content is based on meteorological variables. In this study we propose to use MODIS data to estimate meteorological data (specifically Relative Humidity) at an adequate spatial and temporal resolution. The assessment of dead fuel moisture content plays a decisive role in determining a fire dynamic danger index in combination with other factors. This greatly improves the reliability of fire danger maps obtained on the basis of a integrated approach of the dynamic factors mentioned above and the static factors (fuel physical properties, morphological parameters and social-historical factors). The validation of the fire danger indices was carried out by the use of statistics of occurred forest fires. The validation results show satisfactory agreement with the fire danger map taking into account that . fire events are indirect indicator of fire danger; indeed, many factor influence fire ignition and spread such as human pressure, fire-fighting conditions, wind, etc.. Therefore, in this study we have defined and used several fire statistic data useful for the validation of the fire danger maps in order to create the basic elements for the design of a validation protocol.
Elemental composition of PM 10 and PM 2.5 in urban environment in South Brazil
NASA Astrophysics Data System (ADS)
Braga, C. F.; Teixeira, E. C.; Meira, L.; Wiegand, F.; Yoneama, M. L.; Dias, J. F.
The purpose of the present study is to analyze the elemental composition and the concentrations of PM 10 and PM 2.5 in the Guaíba Hydrographic Basin with HV PM 10 and dichotomous samplers. Three sampling sites were selected: 8° Distrito, CEASA and Charqueadas. The sampling was conducted from October 2001 to December 2002. The mass concentrations of the samplers were evaluated, while the elemental concentrations of Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu and Zn were determined using the Particle-Induced X-ray Emission (PIXE) technique. Factor Analysis and Canonical Correlation Analysis were applied to the chemical and meteorological variables in order to identify the sources of particulate matter. Industrial activities such as steel plants, coal-fired power plants, hospital waste burning, vehicular emissions and soil were identified as the sources of the particulate matter. Concentration levels higher than the daily and the annual average air quality standards (150 and 50 μg m -3, respectively) set by the Brazilian legislation were not observed.
Applied Meteorology Unit (AMU)
NASA Technical Reports Server (NTRS)
Bauman, William; Crawford, Winifred; Watson, Leela; Wheeler, Mark
2011-01-01
The AMU Team began four new tasks in this quarter: (1) began work to improve the AMU-developed tool that provides the launch weather officers information on peak wind speeds that helps them assess their launch commit criteria; (2) began updating lightning climatologies for airfields around central Florida. These climatologies help National Weather Service and Air Force forecasters determine the probability of lightning occurrence at these sites; (3) began a study for the 30th Weather Squadron at Vandenberg Air Force Base in California to determine if precursors can be found in weather observations to help the forecasters determine when they will get strong wind gusts in their northern towers; and (4) began work to update the AMU-developed severe weather tool with more data and possibly improve its performance using a new statistical technique. Include is a section of summaries and detail reporting on the quarterly tasks: (1) Peak Wind Tool for user Meteorological Interactive Data Display System (LCC), Phase IV, (2) Situational Lightning climatologies for Central Florida, Phase V, (3) Vandenberg AFB North Base Wind Study and (4) Upgrade Summer Severe Weather Tool Meteorological Interactive Data Display System (MIDDS).
Active Learning in an Introductory Meteorology Class
NASA Astrophysics Data System (ADS)
Marchese, P. J.; Bluestone, C.
2007-12-01
Active learning modules were introduced to the primarily minority population in the introductory meteorology class at Queensborough Community College (QCC). These activities were developed at QCC and other 4 year colleges and designed to reinforce basic meteorological concepts. The modules consisted of either Interactive Lecture Demonstrations (ILD) or discovery-based activities. During the ILD the instructor would describe an experiment that would be demonstrated in class. Students would predict what the outcome would be and compare their expected results to the actual outcome of the experiment. In the discovery-based activities students would learn about physical concepts by performing basic experiments. These activities differed from the traditional lab in that it avoided "cookbook" procedures and emphasized having the students learn about the concept using the scientific method. As a result of these activities student scores measuring conceptual understanding, as well as factual knowledge, increased as compared to student scores in a more affluent community college. Students also had higher self- efficacy scores. Lower scoring students demonstrated the greatest benefit, while the better students had little (or no) changes.
NASA Astrophysics Data System (ADS)
Liu, Hongli; He, Jing; Guo, Jianping; Miao, Yucong; Yin, Jinfang; Wang, Yuan; Xu, Hui; Liu, Huan; Yan, Yan; Li, Yuan; Zhai, Panmao
2017-10-01
Most previous studies attributed the alleviation of aerosol pollution to either emission control measures or favorable meteorological conditions. However, our understanding of their quantitative contribution is far from complete. In this study, based on model simulation using the CMA (China Meteorological Administration) Unified Atmospheric Chemistry Environment for aerosols (CUACE/Aero), in combination with simultaneous ground-based hourly PM2.5 observations, we aim to quantify the relative contributions of the emission control measures and meteorology to the blue-skies seen in Beijing during the Asia-Pacific Economic Cooperation (APEC) summit held in November of 2014. A series of model simulations have been performed over Beijing-Tianjin-Hebei (BTH) region by implementing nine different emission control schemes. To investigate the relative contributions of the emission control measures and meteorology, the study period has been divided into five episodes. Overall, the CUACE/Aero model can reasonably well reproduce the temporal and spatial evolution of PM2.5 during APEC 2014, although the model performance varies by different time periods and regions of interest. Model results show the emission control measures on average reduced the PM2.5 concentration by 41.3% in urban areas of Beijing and 39.7% in Huairou district, respectively, indicating emission control plays a significant role for the blue skies observed. Among all the emission control measures under investigation, local emission control in Beijing contributed the largest to the reduction of PM2.5 concentrations with a reduction of 35.5% in urban area of Beijing and 34.8% in Huairou, in contrast with the vehicle emission control in Hebei that contributed the least with a reduction of less than 1%. The emission control efficiency in five episodes has been assessed quantitatively, which falls in the range of 36.2%-41.2% in urban area of Beijing and 34.9%-40.7% in Huairou, indicative of no significant episode and geographic dependence in the emission control efficiency. The emission control measures and meteorology, however, alternated to dominate the absolute reduction of PM2.5 concentrations. When the weather conditions are unfavorable, emission control measures outperformed meteorology with a reduction of 55.3-59.4 μg/m3 in urban area of Beijing and 32.5-33 μg/m3 in Huairou. Conversely, when the northwesterly winds prevailed, meteorology tends to outweigh the role of emission control in accounting for the drop of PM2.5. The atmospheric dilution conditions are determined through the model calculation of the mass inflow of PM2.5 per unit volume near the surface. Our findings have significant implications for effective planning and implementation of emission control measures.
NASA Astrophysics Data System (ADS)
Badawy, Bakr; Polavarapu, Saroja; Jones, Dylan B. A.; Deng, Feng; Neish, Michael; Melton, Joe R.; Nassar, Ray; Arora, Vivek K.
2018-02-01
The Canadian Land Surface Scheme and the Canadian Terrestrial Ecosystem Model (CLASS-CTEM) together form the land surface component in the family of Canadian Earth system models (CanESMs). Here, CLASS-CTEM is coupled to Environment and Climate Change Canada (ECCC)'s weather and greenhouse gas forecast model (GEM-MACH-GHG) to consistently model atmosphere-land exchange of CO2. The coupling between the land and the atmospheric transport model ensures consistency between meteorological forcing of CO2 fluxes and CO2 transport. The procedure used to spin up carbon pools for CLASS-CTEM for multi-decadal simulations needed to be significantly altered to deal with the limited availability of consistent meteorological information from a constantly changing operational environment in the GEM-MACH-GHG model. Despite the limitations in the spin-up procedure, the simulated fluxes obtained by driving the CLASS-CTEM model with meteorological forcing from GEM-MACH-GHG were comparable to those obtained from CLASS-CTEM when it is driven with standard meteorological forcing from the Climate Research Unit (CRU) combined with reanalysis fields from the National Centers for Environmental Prediction (NCEP) to form CRU-NCEP dataset. This is due to the similarity of the two meteorological datasets in terms of temperature and radiation. However, notable discrepancies in the seasonal variation and spatial patterns of precipitation estimates, especially in the tropics, were reflected in the estimated carbon fluxes, as they significantly affected the magnitude of the vegetation productivity and, to a lesser extent, the seasonal variations in carbon fluxes. Nevertheless, the simulated fluxes based on the meteorological forcing from the GEM-MACH-GHG model are consistent to some extent with other estimates from bottom-up or top-down approaches. Indeed, when simulated fluxes obtained by driving the CLASS-CTEM model with meteorological data from the GEM-MACH-GHG model are used as prior estimates for an atmospheric CO2 inversion analysis using the adjoint of the GEOS-Chem model, the retrieved CO2 flux estimates are comparable to those obtained from other systems in terms of the global budget and the total flux estimates for the northern extratropical regions, which have good observational coverage. In data-poor regions, as expected, differences in the retrieved fluxes due to the prior fluxes become apparent. Coupling CLASS-CTEM into the Environment Canada Carbon Assimilation System (EC-CAS) is considered an important step toward understanding how meteorological uncertainties affect both CO2 flux estimates and modeled atmospheric transport. Ultimately, such an approach will provide more direct feedback to the CLASS-CTEM developers and thus help to improve the performance of CLASS-CTEM by identifying the model limitations based on atmospheric constraints.
NASA Astrophysics Data System (ADS)
Bachmair, Sophie; Tanguy, Maliko; Hannaford, Jamie; Stahl, Kerstin
2016-04-01
Drought monitoring and early warning (M&EW) is an important component of agricultural and silvicultural risk management. Meteorological indicators such as the Standardized Precipitation Index (SPI) are widely used in operational M&EW systems and for drought hazard assessment. Meteorological drought yet does not necessarily equate to agricultural drought given differences in drought susceptibility, e.g. crop-specific vulnerability, soil water holding capacity, irrigation and other management practices. How useful are meteorological indicators such as SPI to assess agricultural drought? Would the inclusion of vegetation indicators into drought M&EW systems add value for the agricultural sector? To answer these questions, it is necessary to investigate the link between meteorological indicators and agricultural impacts of drought. Crop yield or loss data is one source of information for drought impacts, yet mostly available as aggregated data at the annual scale. Remotely sensed vegetation stress data offer another possibility to directly assess agricultural impacts with high spatial and temporal resolution and are already used by some M&EW systems. At the same time, reduced crop yield and satellite-based vegetation stress potentially suffer from multi-causality. The aim of this study is therefore to investigate the relation between meteorological drought indicators and agricultural drought impacts for Europe, and to intercompare different agricultural impact variables. As drought indicators we used SPI and the Standardized Precipitation Evaporation Index (SPEI) for different accumulation periods. The focus regarding drought impact variables was on remotely sensed vegetation stress derived from MODIS NDVI (Normalized Difference Vegetation Index) and LST (Land Surface Temperature) data, but the analysis was complemented with crop yield data and text-based information from the European Drought Impact report Inventory (EDII) for selected countries. A correlation analysis between meteorological drought indicators and remotely sensed vegetation stress at the EU NUTS3 region level revealed a high correlation between the two types of indicators for many regions; however some spatial variability was observed in (i) strength of correlation, (ii) performance of SPI versus SPEI, and (iii) best linked SPI/SPEI time scale. We additionally explored whether geographic properties like climate, soil texture, land use, and location explain the observed spatial patterns. Our study revealed that climatically dryer areas (water limited) showed high correlations between SPI/SPEI and vegetation stress, whereas the wettest parts of Europe (radiation limited regions) showed negative correlations especially for short accumulation periods, suggesting that for these regions, short droughts could actually be beneficial for vegetation growth. These findings suggest that relying solely on meteorological indicators for agricultural risk assessment in some regions might be inadequate. Overall, such information may help to tailor agricultural drought M&EW systems to specific regions.
González-Castanedo, Y; Sanchez-Rodas, D; Sánchez de la Campa, A M; Pandolfi, M; Alastuey, A; Cachorro, V E; Querol, X; de la Rosa, J D
2015-01-01
Sampling and chemical analyses, including major compounds and trace elements, of atmospheric particulate matter (PM10 and PM2.5) have been performed during 2006-2007 in a regional background monitoring station located within the Doñana Natural Park (SW of Spain). This region is strategic for air quality and climate change studies, representing a meeting place of the European and African continents, and the Atlantic Ocean and Mediterranean Sea. The present study based on meteorological parameters demonstrated long-range transport and impact of industrial plumes on the Doñana Natural. Inorganic arsenic species (arsenate and arsenite) have been analyzed in particulate matter (PM) to characterize the impact of near Cu-smelter plumes and demonstrated the long-range transport of industrial pollutants. As(V) is the main specie of As and varies between 95% and 98% of total As in PM10 and 96-97% in PM2.5. The As(V)/As(III) ratio measured in emission plumes of a Cu-smelter are similar to the ratio found in the Doñana Natural Park. The application of Positive Matrix Factorization (PMF) to atmospheric particulate matter estimated the contributions and chemical profiles of natural and anthropogenic sources impacting the Natural Park, demonstrating the industrial origin of the As and other toxic elements in the air. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
1990-01-01
As the NASA center responsible for assembly, checkout, servicing, launch, recovery, and operational support of Space Transportation System elements and payloads, Kennedy Space Center (KSC) is placing increasing emphasis on KSC's research and technology program. In addition to strengthening those areas of engineering and operations technology that contribute to safer, more efficient, and more economical execution of the current mission, the technological tools needed to execute KSC's mission relative to future programs are being developed. The Engineering Development Directorate encompasses most of the laboratories and other KSC resources that are key elements of research and technology program implementation and is responsible for implementation of the majority of the projects in this KSC 1990 annual report. Projects under the following topics are covered: (1) materials science; (2) hazardous emissions and contamination monitoring; (3) biosciences; (4) autonomous systems; (5) communications and control; (6) meteorology; (7) technology utilization; and (8) mechanics, structures, and cryogenics.
A Proposal for a Thesaurus for Web Services in Solar Radiation
NASA Technical Reports Server (NTRS)
Gschwind, Benoit; Menard, Lionel; Ranchin, Thierry; Wald, Lucien; Stackhouse, Paul W., Jr.
2007-01-01
Metadata are necessary to discover, describe and exchange any type of information, resource and service at a large scale. A significant amount of effort has been made in the field of geography and environment to establish standards. Efforts still remain to address more specific domains such as renewable energies. This communication focuses on solar energy and more specifically on aspects in solar radiation that relate to geography and meteorology. A thesaurus in solar radiation is proposed for the keys elements in solar radiation namely time, space and radiation types. The importance of time-series in solar radiation is outlined and attributes of the key elements are discussed. An XML schema for encoding metadata is proposed. The exploitation of such a schema in web services is discussed. This proposal is a first attempt at establishing a thesaurus for describing data and applications in solar radiation.
Integrating meteorology into research on migration.
Shamoun-Baranes, Judy; Bouten, Willem; van Loon, E Emiel
2010-09-01
Atmospheric dynamics strongly influence the migration of flying organisms. They affect, among others, the onset, duration and cost of migration, migratory routes, stop-over decisions, and flight speeds en-route. Animals move through a heterogeneous environment and have to react to atmospheric dynamics at different spatial and temporal scales. Integrating meteorology into research on migration is not only challenging but it is also important, especially when trying to understand the variability of the various aspects of migratory behavior observed in nature. In this article, we give an overview of some different modeling approaches and we show how these have been incorporated into migration research. We provide a more detailed description of the development and application of two dynamic, individual-based models, one for waders and one for soaring migrants, as examples of how and why to integrate meteorology into research on migration. We use these models to help understand underlying mechanisms of individual response to atmospheric conditions en-route and to explain emergent patterns. This type of models can be used to study the impact of variability in atmospheric dynamics on migration along a migratory trajectory, between seasons and between years. We conclude by providing some basic guidelines to help researchers towards finding the right modeling approach and the meteorological data needed to integrate meteorology into their own research. © The Author 2010. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved.
NASA Astrophysics Data System (ADS)
Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo
2012-07-01
To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.
Surface meteorology and Solar Energy
NASA Technical Reports Server (NTRS)
Stackhouse, Paul W. (Principal Investigator)
The Release 5.1 Surface meteorology and Solar Energy (SSE) data contains parameters formulated for assessing and designing renewable energy systems. Parameters fall under 11 categories including: Solar cooking, solar thermal applications, solar geometry, tilted solar panels, energy storage systems, surplus product storage systems, cloud information, temperature, wind, other meteorological factors, and supporting information. This latest release contains new parameters based on recommendations by the renewable energy industry and it is more accurate than previous releases. On-line plotting capabilities allow quick evaluation of potential renewable energy projects for any region of the world. The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Mission Objectives] The SSE project contains insolation and meteorology data intended to aid in the development of renewable energy systems. Collaboration between SSE and technology industries such as the Hybrid Optimization Model for Electric Renewables ( HOMER ) may aid in designing electric power systems that employ some combination of wind turbines, photovoltaic panels, or diesel generators to produce electricity. [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].
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.
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.
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.
Meteorological Development Laboratory Student Career Experience Program
NASA Astrophysics Data System (ADS)
McCalla, C., Sr.
2007-12-01
The National Oceanic and Atmospheric Administration's (NOAA) National Weather Service (NWS) provides weather, hydrologic, and climate forecasts and warnings for the protection of life and property and the enhancement of the national economy. The NWS's Meteorological Development Laboratory (MDL) supports this mission by developing meteorological prediction methods. Given this mission, NOAA, NWS, and MDL all have a need to continually recruit talented scientists. One avenue for recruiting such talented scientist is the Student Career Experience Program (SCEP). Through SCEP, MDL offers undergraduate and graduate students majoring in meteorology, computer science, mathematics, oceanography, physics, and statistics the opportunity to alternate full-time paid employment with periods of full-time study. Using SCEP as a recruiting vehicle, MDL has employed students who possess some of the very latest technical skills and knowledge needed to make meaningful contributions to projects within the lab. MDL has recently expanded its use of SCEP and has increased the number of students (sometimes called co- ops) in its program. As a co-op, a student can expect to develop and implement computer based scientific techniques, participate in the development of statistical algorithms, assist in the analysis of meteorological data, and verify forecasts. This presentation will focus on describing recruitment, projects, and the application process related to MDL's SCEP. In addition, this presentation will also briefly explore the career paths of students who successfully completed the program.
Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
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
Wang, Miaomiao; Li, Bofeng
2016-01-01
An empirical tropospheric delay model, together with a mapping function, is commonly used to correct the tropospheric errors in global navigation satellite system (GNSS) processing. As is well-known, the accuracy of tropospheric delay models relies mainly on the correction efficiency for tropospheric wet delays. In this paper, we evaluate the accuracy of three tropospheric delay models, together with five mapping functions in wet delays calculation. The evaluations are conducted by comparing their slant wet delays with those measured by water vapor radiometer based on its satellite-tracking function (collected data with large liquid water path is removed). For all 15 combinations of three tropospheric models and five mapping functions, their accuracies as a function of elevation are statistically analyzed by using nine-day data in two scenarios, with and without meteorological data. The results show that (1) no matter with or without meteorological data, there is no practical difference between mapping functions, i.e., Chao, Ifadis, Vienna Mapping Function 1 (VMF1), Niell Mapping Function (NMF), and MTT Mapping Function (MTT); (2) without meteorological data, the UNB3 is much better than Saastamoinen and Hopfield models, while the Saastamoinen model performed slightly better than the Hopfield model; (3) with meteorological data, the accuracies of all three tropospheric delay models are improved to be comparable, especially for lower elevations. In addition, the kinematic precise point positioning where no parameter is set up for tropospheric delay modification is conducted to further evaluate the performance of tropospheric delay models in positioning accuracy. It is shown that the UNB3 model is best and can achieve about 10 cm accuracy for the N and E coordinate component while 20 cm accuracy for the U coordinate component no matter the meteorological data is available or not. This accuracy can be obtained by the Saastamoinen model only when meteorological data is available, and degraded to 46 cm for the U component if the meteorological data is not available. PMID:26848662
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.
Preliminary validation of WRF model in two Arctic fjords, Hornsund and Porsanger
NASA Astrophysics Data System (ADS)
Aniskiewicz, Paulina; Stramska, Małgorzata
2017-04-01
Our research is focused on development of efficient modeling system for arctic fjords. This tool should include high-resolution meteorological data derived using downscaling approach. In this presentation we have focused on modeling, with high spatial resolution, of the meteorological conditions in two Arctic fjords: Hornsund (H), located in the western part of Svalbard archipelago and Porsanger (P) located in the coastal waters of the Barents Sea. The atmospheric downscaling is based on The Weather Research and Forecasting Model (WRF, www.wrf-model.org) with polar stereographic projection. We have created two parent domains with grid point distances of about 3.2 km (P) and 3.0 km (H) and with nested domains (almost 5 times higher resolution than parent domains). We tested what is the impact of the spatial resolution of the model on derived meteorological quantities. For both fjords the input topography data resolution is 30 sec. To validate the results we have used meteorological data from the Norwegian Meteorological Institute for stations Lakselv (L) and Honningsvåg (Ho) located in the inner and outer parts of the Porsanger fjord as well as from station in the outer part of the Hornsund fjord. We have estimated coefficients of determination (r2), statistical errors (St) and systematic errors (Sy) between measured and modelled air temperature and wind speed at each station. This approach will allow us to create high resolution spatially variable meteorological fields that will serve as forcing for numerical models of the fjords. We will investigate the role of different meteorological quantities (e. g. wind, solar insolation, precipitation) on hydrohraphic processes in fjords. The project has been financed from the funds of the Leading National Research Centre (KNOW) received by the Centre for Polar Studies for the period 2014-2018. This work was also funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support comes from the Institute of Oceanology (IO PAN).
Incidences of Waterborne and Foodborne Diseases After Meteorologic Disasters in South Korea.
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.
Zhang, Yang; Shen, Jing; Li, Yu
2018-02-01
This paper presents an atmospheric vulnerability assessment framework based on CAMx that should be helpful to assess potential impacts of changes in human, atmospheric environment, and social economic elements of atmospheric vulnerability. It is also a useful and effective tool that can provide policy-guidance for environmental protection and management to reduce the atmospheric vulnerability. The developed framework was applied to evaluate the atmospheric environment vulnerability of 13 cities in the Beijing-Tianjin-Hebei (BTH) region for verification. The results indicated that regional disparity of the atmospheric vulnerability existed in the study site. More specifically, the central and southern regions show more atmospheric environment vulnerability than the northern regions. The impact factors of atmospheric environment vulnerability in the BTH region mainly derived from increasing population press, frequently unfavorable meteorological conditions, extensive economic growth of secondary industry, increased environmental pollution, and accelerating population aging. The framework shown in this paper is an interpretative and heuristic tool for a better understanding of atmospheric vulnerability. This framework can also be replicated at different spatial and temporal scales using context-specific datasets to straightly support environmental managers with decision-making. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Ho, Evelyn L.; Schweiss, Robert J.
2008-01-01
The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.
Estimation of clear-sky insolation using satellite and ground meteorological data
NASA Technical Reports Server (NTRS)
Staylor, W. F.; Darnell, W. L.; Gupta, S. K.
1983-01-01
Ground based pyranometer measurements were combined with meteorological data from the Tiros N satellite in order to estimate clear-sky insolations at five U.S. sites for five weeks during the spring of 1979. The estimates were used to develop a semi-empirical model of clear-sky insolation for the interpretation of input data from the Tiros Operational Vertical Sounder (TOVS). Using only satellite data, the estimated standard errors in the model were about 2 percent. The introduction of ground based data reduced errors to around 1 percent. It is shown that although the errors in the model were reduced by only 1 percent, TOVS data products are still adequate for estimating clear-sky insolation.
NASA Astrophysics Data System (ADS)
Titov, A. G.; Okladnikov, I. G.; Gordov, E. P.
2017-11-01
The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.
The climate and bioclimate of Bursa (Turkey) from the perspective of tourism
NASA Astrophysics Data System (ADS)
Çalışkan, Onur; Çiçek, Ihsan; Matzarakis, Andreas
2012-02-01
Climate is an important resource for tourism and an equally important element that needs to be included in tourism promotions. This study reveals Bursa's bioclimatological conditions. These conditions were identified by using physiologically equivalent temperature and a Climate-Tourism-Information-Scheme over 10-day periods and analyzing the mean thermal perception values that emerged. Evaluating bioclimatic conditions and meteorological parameters such as air temperature, duration of sunshine, number of wet days, amount of precipitation, and wind from the perspective of tourism will help people choose the best holiday times depending on their individual needs and circumstances.
Passive Wake Acoustics Measurements at Denver International Airport
NASA Technical Reports Server (NTRS)
Wang, Frank Y.; Wassaf, Hadi; Dougherty, Robert P.; Clark, Kevin; Gulsrud, Andrew; Fenichel, Neil; Bryant, Wayne H.
2004-01-01
From August to September 2003, NASA conducted an extensive measurement campaign to characterize the acoustic signal of wake vortices. A large, both spatially as well as in number of elements, phased microphone array was deployed at Denver International Airport for this effort. This paper will briefly describe the program background, the microphone array, as well as the supporting ground-truth and meteorological sensor suite. Sample results to date are then presented and discussed. It is seen that, in the frequency range processed so far, wake noise is generated predominantly from a very confined area around the cores.
2009-10-27
CAPE CANAVERAL, Fla. - At the weather station on Cape Canaveral Air Force Station in Florida, a meteorological data specialist prepares to release a low resolution flight element rawinsonde to support the countdown for the flight test of NASA's Ares I-X rocket. A GPS-tracked weather balloon, a rawinsonde has a tethered instrument package which radios its altitude to the ground along with atmospheric data such as temperature, dewpoint and humidity, and wind speed and direction. Rawinsondes can reach altitudes up to 110,000 feet. For information on the Ares I-X vehicle and flight test, visit http://www.nasa.gov/aresIX. Photo credit: NASA/Jack Pfaller
2009-10-27
CAPE CANAVERAL, Fla. - At the weather station on Cape Canaveral Air Force Station in Florida, a meteorological data specialist releases a low resolution flight element rawinsonde to support the countdown for the flight test of NASA's Ares I-X rocket. A GPS-tracked weather balloon, a rawinsonde has a tethered instrument package which radios its altitude to the ground along with atmospheric data such as temperature, dewpoint and humidity, and wind speed and direction. Rawinsondes can reach altitudes up to 110,000 feet. For information on the Ares I-X vehicle and flight test, visit http://www.nasa.gov/aresIX. Photo credit: NASA/Jack Pfaller
2009-10-27
CAPE CANAVERAL, Fla. - In the weather station on Cape Canaveral Air Force Station in Florida, a meteorological data specialist prepares a low resolution flight element rawinsonde to support the countdown for the flight test of NASA's Ares I-X rocket. A GPS-tracked weather balloon, a rawinsonde has a tethered instrument package which radios its altitude to the ground along with atmospheric data such as temperature, dewpoint and humidity, and wind speed and direction. Rawinsondes can reach altitudes up to 110,000 feet. For information on the Ares I-X vehicle and flight test, visit http://www.nasa.gov/aresIX. Photo credit: NASA/Jack Pfaller
2009-10-27
CAPE CANAVERAL, Fla. - In the weather station on Cape Canaveral Air Force Station in Florida, meteorological data specialists prepare two low resolution flight element rawinsonde to support the countdown for the flight test of NASA's Ares I-X rocket. A GPS-tracked weather balloon, a rawinsonde has a tethered instrument package which radios its altitude to the ground along with atmospheric data such as temperature, dewpoint and humidity, and wind speed and direction. Rawinsondes can reach altitudes up to 110,000 feet. For information on the Ares I-X vehicle and flight test, visit http://www.nasa.gov/aresIX. Photo credit: NASA/Jack Pfaller
PBO Integrated Real-Time Observing Sites at Volcanic Sites
NASA Astrophysics Data System (ADS)
Mencin, D.; Jackson, M.; Borsa, A.; Feaux, K.; Smith, S.
2009-05-01
The Plate Boundary Observatory, an element of NSF's EarthScope program, has six integrated observatories in Yellowstone and four on Mt St Helens. These observatories consist of some combination of borehole strainmeters, borehole seismometers, GPS, tiltmeters, pore pressure, thermal measurements and meteorological data. Data from all these instruments have highly variable data rates and formats, all synchronized to GPS time which can cause significant congestion of precious communication resources. PBO has been experimenting with integrating these data streams to both maximize efficiency and minimize latency through the use of software that combines the streams, like Antelope, and VPN technologies.
NASA Astrophysics Data System (ADS)
Saleh, F.; Ramaswamy, V.; Wang, Y.; Georgas, N.; Blumberg, A.; Pullen, J.
2017-12-01
Estuarine regions can experience compound impacts from coastal storm surge and riverine flooding. The challenges in forecasting flooding in such areas are multi-faceted due to uncertainties associated with meteorological drivers and interactions between hydrological and coastal processes. The objective of this work is to evaluate how uncertainties from meteorological predictions propagate through an ensemble-based flood prediction framework and translate into uncertainties in simulated inundation extents. A multi-scale framework, consisting of hydrologic, coastal and hydrodynamic models, was used to simulate two extreme flood events at the confluence of the Passaic and Hackensack rivers and Newark Bay. The events were Hurricane Irene (2011), a combination of inland flooding and coastal storm surge, and Hurricane Sandy (2012) where coastal storm surge was the dominant component. The hydrodynamic component of the framework was first forced with measured streamflow and ocean water level data to establish baseline inundation extents with the best available forcing data. The coastal and hydrologic models were then forced with meteorological predictions from 21 ensemble members of the Global Ensemble Forecast System (GEFS) to retrospectively represent potential future conditions up to 96 hours prior to the events. Inundation extents produced by the hydrodynamic model, forced with the 95th percentile of the ensemble-based coastal and hydrologic boundary conditions, were in good agreement with baseline conditions for both events. The USGS reanalysis of Hurricane Sandy inundation extents was encapsulated between the 50th and 95th percentile of the forecasted inundation extents, and that of Hurricane Irene was similar but with caveats associated with data availability and reliability. This work highlights the importance of accounting for meteorological uncertainty to represent a range of possible future inundation extents at high resolution (∼m).
Temporal variations in reference evapotranspiration in Hubei Province, China, from 1960 to 2014
NASA Astrophysics Data System (ADS)
Wu, Hao; Wang, Xiugui; Wang, Yan; Xu, Yaxin; Han, Xudong
2018-01-01
Reference evapotranspiration (ET0) plays a critical role in irrigation planning and is also important for hydrological cycle, environmental, and other studies. Thus, this research examined the trends in ET0 on seasonal and annual timescales in Hubei Province, China. ET0 was estimated using the Penman Monteith method (P-M) at 16 meteorological stations located in different areas of Hubei Province during the period 1960-2014. The trends in seasonal and annual ET0 were investigated using the Mann-Kendall test and Sen's slope estimator. The periodicities of ET0 in different regions were investigated using wavelet analysis. The major meteorological factors affecting ET0 were investigated using partial correlation analysis and the contribution rate method. The results showed, on a seasonal timescale, that in spring, ET0 increased in all geographic zones. In summer, ET0 decreased in all geographic zones. In autumn and winter, ET0 displayed no significant changes in any of the geographic zones. On an annual timescale, ET0 decreased in all geographic zones, and the magnitudes of the negative trend in annual ET0 were 2.58-10.04 mm 10a-1. In the five geographic zones, the periodic characteristics of ET0 were identical; the significant wavelet power spectra of ET0 had 3-7, 13-17, and 24-32-year modulations in variation. Among the meteorological factors, sunshine hours were the major climate element that influenced the variability in ET0. The results will provide important references for scientific planning for agriculture, water resource allocation, and water-saving irrigation.
NASA Astrophysics Data System (ADS)
Allis, E. C.; Greene, A. M.; Cousin, R.
2014-12-01
We describe a comprehensive project for developing climate information and decision support / climate risk management tools in Lao PDR, Bangladesh and Indonesia. Mechanisms are developed for bringing the benefits of these tools to both policy makers and poor rural farmers, with the goal of enabling better management, at the farm level, of the risks associated with climate variability and change. The project comprises several interwoven threads, differentially applied in the different study regions. These include data management and quality control, development of seasonal forecast capabilities, use of dynamic cropping calendars and climate advisories, the development of longer-term climate information for both past and future and a weather index insurance component. Stakeholder engagement and capacity building served as reinforcing and complementary elements to all components. In this talk we will provide a project overview, show how the various components fit together and describe some lessons learned in this attempt to promote the uptake of actionable climate information from farmer to policy level. The applied research project was led by the International Research Institute for Climate and Society (IRI) at Columbia University with funding from the International Fund for Agriculture Development (IFAD) and in close collaboration with our regional partners at the Centre for Climate Risk and Opportunity Management in Southeast Asia Pacific (at Bogor Agricultural University in Indonesia), Indonesia's National Agency for Meteorology, Climatology and Geophysics (BMKG), Lao PDR's National Agriculture and Forestry Research Institute (NAFRI), Laotian Department of Meteorology and Hydrology (DMH), WorldFish Center, Bangladesh Meteorology Department (BMD), and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).
Solving the African Climate Observation Puzzle, and Concurrently Building Capacity
NASA Astrophysics Data System (ADS)
Selker, J. S.; Van De Giesen, N.; Annor, F. O.; Hochreutener, R.; Jachens, E. R.
2017-12-01
The Trans-African Hydro-Meteorological Observatory (TAHMO.org) is directly addressing basic issues of climate observation, climate science, and education through a novel public-private partnership. With 500 stations now reporting from over 20 African countries, TAHMO is the largest single source of continental-scale weather and climate data for Africa. Working directly with national meteorological agencies, TAHMO first builds local human capacity and real-time data to the host country. TAHMO also provides all of these data free of charge to all researchers and teams seeking to develop peer-reviewed scientific contributions. This will be the basis of a whole new level of observation-informed science for the African continent. Most TAHMO stations are housed at African schools, with a local host-teacher who attends to basic day-to-day cleaning. These schools also receive free curricular support providing geographic, mathematical, statistical, hydrologic, and meteorological lessons that connect student to their environment and creates climate-aware citizens, which we believe is the most fundamental element of developing a climate-resilient society. Installation of these stations have been made possible through the support of private companies like IBM and development programmes through the Global Resilience Partnership, World Bank, USAID among others. The availability of these new data sets will help generate more accurate weather forecasts which will be made freely available across the African continent. TAHMO leverages low-cost cell phone data transmission with solid-state sensor technology (provided by the METER corporation) to provide a cost-effective, sustainable, and transformative solution to the climate observation gap in Africa.
Analysis of the Meteorology Associated with the 1997 NASA Glenn Twin Otter Icing Events
NASA Technical Reports Server (NTRS)
Bernstein, Ben C.
2000-01-01
This part of the document contains an analysis of the meteorology associated with the premier icing encounters from the January-March 1997 NASA Twin Otter dataset. The purpose of this analysis is to provide a meteorological context for the aircraft data collected during these flights. For each case, the following data elements are presented: (1) A detailed discussion of the Twin Otter encounter, including locations, liquid water contents, temperatures and microphysical makeup of the clouds and precipitation aloft, (2) Upper-air charts, providing hand-analyzed locations of lows, troughs, ridges, saturated/unsaturated air, temperatures, warm/cold advection, and jet streams, (3) Balloon-borne soundings, providing vertical profiles of temperature, moisture and winds, (4) Infrared satellite data, providing cloud locations and cloud top temperature, (5) 3-hourly surface charts, providing hand-analyzed locations of lows, highs, fronts, precipitation (including type) and cloud cover, (6) Hourly plots of icing pilot reports, providing the icing intensity, icing type, icing altitudes and aircraft type, (7) Hourly, regional radar mosaics, providing fine resolution of the locations of precipitation (including intensity and type), pilot reports of icing (including intensity and type), surface observations of precipitation type and Twin Otter tracks for a one hour window centered on the time of the radar data, and (8) Plots of data from individual NEXRAD radars at times and elevation angles that have been matched to Twin Otter flight locations. Outages occurred in nearly every dataset at some point. All relevant data that was available is presented here. All times are in UTC and all heights are in feet above mean sea level (MSL).
NASA Astrophysics Data System (ADS)
Koo, Youn-Seo; Yun, Hui-Young; Choi, Dae-Ryun; Han, Jin-Seok; Lee, Jae-Bum; Lim, Yong-Jae
2018-04-01
The chemical characteristics of secondary inorganic and carbonaceous aerosols as well as their formation mechanisms during the haze event of January 12-18, 2013, in the Seoul Metropolitan Area (SMA) were investigated using measurements at the Baengnyeong and Seoul supersites with data available from LIDAR, meteorology, and modeling. An extraordinary haze event that occurred in northern China during that period extended to the Korean Peninsula and initiated the haze event in the SMA. Local emissions of primary aerosol and gaseous precursors in the SMA then made the situation worse under adverse meteorological conditions. OM (Organic Matter) and SO42- were the major long-range transport (LRT) aerosols from the Beijing, Tianjin and Hebei province (BTH) area to the SMA during the initial stage of the haze event. The LRT of SO42- from the BTH area, which was detected at Baengnyeong Island, was mostly acidic, while in Seoul, it was fully neutralized to (NH4)2SO4. The SIAs (Secondary Inorganic Aerosols) consisting of 56.5% PM2.5 during the haze period were the major chemical species causing haze problems in the SMA. NO3- was the most dominant chemical species among the SIAs and was locally formed by a heavy burden of NOx emissions from mobile sources in the SMA. Carbonaceous aerosols of OM and EC (Elemental Carbon) in the SMA during the haze period consisted of 18.9% PM2.5, but secondary organic carbon (SOC) was not the key species inducing the haze event during the January episode in the SMA.
Correlations between the modelled potato crop yield and the general atmospheric circulation
NASA Astrophysics Data System (ADS)
Sepp, Mait; Saue, Triin
2012-07-01
Biology-related indicators do not usually depend on just one meteorological element but on a combination of several weather indicators. One way to establish such integral indicators is to classify the general atmospheric circulation into a small number of circulation types. The aim of present study is to analyse connections between general atmospheric circulation and potato crop yield in Estonia. Meteorologically possible yield (MPY), calculated by the model POMOD, is used to characterise potato crop yield. Data of three meteorological stations and the biological parameters of two potato sorts were applied to the model, and 73 different classifications of atmospheric circulation from catalogue 1.2 of COST 733, domain 05 are used to qualify circulation conditions. Correlation analysis showed that there is at least one circulation type in each of the classifications with at least one statistically significant (99%) correlation with potato crop yield, whether in Kuressaare, Tallinn or Tartu. However, no classifications with circulation types correlating with MPY in all three stations at the same time were revealed. Circulation types inducing a decrease in the potato crop yield are more clearly represented. Clear differences occurred between the observed geographical locations as well as between the seasons: derived from the number of significant circulation types, summer and Kuressaare stand out. Of potato varieties, late 'Anti' is more influenced by circulation. Analysis of MSLP maps of circulation types revealed that the seaside stations (Tallinn, Kuressaare) suffer from negative effects of anti-cyclonic conditions (drought), while Tartu suffers from the cyclonic activity (excessive water).
NASA Astrophysics Data System (ADS)
McGinty, A. B.
1982-04-01
Contents: The Air Force Geophysics Laboratory; Aeronomy Division--Upper Atmosphere Composition, Middle Atmosphere Effects, Atmospheric UV Radiation, Satellite Accelerometer Density Measurement, Theoretical Density Studies, Chemical Transport Models, Turbulence and Forcing Functions, Atmospheric Ion Chemistry, Energy Budget Campaign, Kwajalein Reference Atmospheres, 1979, Satellite Studies of the Neutral Atmosphere, Satellite Studies of the Ionosphere, Aerospace Instrumentation Division--Sounding Rocket Program, Satellite Support, Rocket and Satellite Instrumentation; Space Physics Division--Solar Research, Solar Radio Research, Environmental Effects on Space Systems, Solar Proton Event Studies, Defense Meteorological Satellite Program, Ionospheric Effects Research, Spacecraft Charging Technology; Meteorology Division--Cloud Physics, Ground-Based Remote-Sensing Techniques, Mesoscale Observing and Forecasting, Design Climatology, Aircraft Icing Program, Atmospheric Dynamics; Terrestrial Sciences Division--Geodesy and Gravity, Geokinetics; Optical Physics Division--Atmospheric Transmission, Remote Sensing, INfrared Background; and Appendices.
NASA Astrophysics Data System (ADS)
Lorrey, A. M.; Chappell, P. R.
2015-08-01
Reverend Richard Davis (1790-1863) was a Colonial-era missionary stationed in the Far North of New Zealand who was a key figure in the early efforts of the Church Mission Society. He kept meticulous meteorological records for the early settlements of Waimate North and Kaikohe, and his observations are preserved in a two-volume set in the rare manuscripts archive at the Auckland City Library. The Davis diary volumes are significant because they constitute some of the earliest land-based meteorological measurements that were continually chronicled for New Zealand. The diary measurements cover nine years within the 1839-1851 timespan that are broken into two parts: 1839-1844 and 1848-1851. Davis' meteorological recordings include daily 9 AM and noon temperatures and mid-day pressure measurements. Qualitative comments in the diary note prevailing wind flow, wind strength, cloud cover, climate variability impacts, bio-indicators suggestive of drought, and notes on extreme weather events. "Dirty weather" comments scattered throughout the diary describe disturbed conditions with strong winds and driving rainfall. The Davis diary entries coincide with the end of the Little Ice Age (LIA) and they indicate southerly and westerly circulation influences and cooler winter temperatures were more frequent than today. A comparison of climate field reconstructions derived from the Davis diary data and tree ring-based winter temperature reconstructions are supported by tropical coral palaeotemperature evidence. Davis' pressure measurements were corroborated using ship log data from vessels associated with iconic Antarctic exploration voyages that were anchored in the Bay of Islands, and suggest the pressure series he recorded are robust and can be used as `station data'. The Reverend Davis meteorological data are expected to make a significant contribution to the Atmospheric Circulation Reconstructions across the Earth (ACRE) project, which feeds the major data requirements for the longest historical reanalysis - the 20th Century Reanalysis Project (20CR). Thus these new data will help extend surface pressure-based re-analysis reconstructions of past weather covering New Zealand within the data-sparse Southern Hemisphere.
NASA Astrophysics Data System (ADS)
Lorrey, Andrew M.; Chappell, Petra R.
2016-03-01
Reverend Richard Davis (1790-1863) was a colonial-era missionary stationed in the Far North of New Zealand who was a key figure in the early efforts of the Church Mission Society. He kept meticulous meteorological records for the early settlements of Waimate North and Kaikohe, and his observations are preserved in a two-volume set in the Sir George Grey Special Collections in the Auckland Central Library. The Davis diary volumes are significant because they constitute some of the earliest land-based meteorological measurements that were continually chronicled for New Zealand. The diary measurements cover nine years within the 1839-1851 time span that are broken into two parts: 1839-1844 and 1848-1851. Davis' meteorological recordings include daily 9 a.m. and noon temperatures and midday pressure measurements. Qualitative comments in the diary note prevailing wind flow, wind strength, cloud cover, climate variability impacts, bio-indicators suggestive of drought, and notes on extreme weather events. "Dirty weather" comments scattered throughout the diary describe disturbed conditions with strong winds and driving rainfall. The Davis diary entries coincide with the end of the Little Ice Age (LIA) and they indicate southerly and westerly circulation influences and cooler winter temperatures were more frequent than today. A comparison of climate field reconstructions derived from the Davis diary data and tree-ring-based winter temperature reconstructions are supported by tropical coral palaeotemperature evidence. Davis' pressure measurements were corroborated using ship log data from vessels associated with iconic Antarctic exploration voyages that were anchored in the Bay of Islands, and suggest the pressure series he recorded are robust and can be used as "station data". The Reverend Davis meteorological data are expected to make a significant contribution to the Atmospheric Circulation Reconstructions across the Earth (ACRE) project, which feeds the major data requirements for the longest historical reanalysis - the 20th Century Reanalysis Project (20CR). Thus these new data will help extend surface pressure-based reanalysis reconstructions of past weather covering New Zealand within the data-sparse Southern Hemisphere.
Remote Sensing of Surficial Process Responses to Extreme Meteorological Events
NASA Technical Reports Server (NTRS)
Brakenridge, G. Robert
1997-01-01
Changes in the frequency and magnitude of extreme meteorological events are associated with changing environmental means. Such events are important in human affairs, and can also be investigated by orbital remote sensing. During the course of this project, we applied ERS-1, ERS-2, Radarsat, and an airborne sensor (AIRSAR-TOPSAR) to measure flood extents, flood water surface profiles, and flood depths. We established a World Wide Web site (the Dartmouth Flood Observatory) for publishing remote sensing-based maps of contemporary floods worldwide; this is also an online "active archive" that presently constitutes the only global compilation of extreme flood events. We prepared an article for EOS concerning SAR imaging of the Mississippi Valley flood; an article for the International Journal of Remote Sensing on measurement of a river flood wave using ERS-2, began work on an article (since completed and published) on the Flood Observatory for a Geoscience Information Society Proceedings volume, and presented lectures at several Geol. Soc. of America Natl. Meetings, an Assoc. of Amer. Geographers Natl. Meeting, and a Binghamton Geomorphology Symposium (all on SAR remote sensing of the Mississippi Valley flood). We expanded in-house modeling capabilities by installing the latest version of the Army Corps of Engineers RMA two-dimensional hydraulics software and BYU Engineering Graphics Lab's Surface Water Modeling System (finite elements based pre- and post-processors for RMA work) and also added watershed modeling software. We are presently comparing the results of the 2-d flow models with SAR image data. The grant also supported several important upgrades of pc-based remote sensing infrastructure at Dartmouth. During work on this grant, we collaborated with several workers at the U.S. Army Corps of Engineers, Remote Sensing/GIS laboratory (for flood inundation mapping and modeling; particularly of the Illinois River using the AIRSAR/TOPSAR/ERS-2 combined data), with Dr. Karen Prestegaard at the University of Maryland (geomorphological responses to the extreme 1993 flood along the Raccoon drainage in central Iowa), and with Mr Tim Scrom of the Albany National Weather Service River Forecast Center (initial planning for the use of Radarsat and ERS-2 for flood warning). The work thus initiated with this proposal is continuing.
Regionalisation of statistical model outputs creating gridded data sets for Germany
NASA Astrophysics Data System (ADS)
Höpp, Simona Andrea; Rauthe, Monika; Deutschländer, Thomas
2016-04-01
The goal of the German research program ReKliEs-De (regional climate projection ensembles for Germany, http://.reklies.hlug.de) is to distribute robust information about the range and the extremes of future climate for Germany and its neighbouring river catchment areas. This joint research project is supported by the German Federal Ministry of Education and Research (BMBF) and was initiated by the German Federal States. The Project results are meant to support the development of adaptation strategies to mitigate the impacts of future climate change. The aim of our part of the project is to adapt and transfer the regionalisation methods of the gridded hydrological data set (HYRAS) from daily station data to the station based statistical regional climate model output of WETTREG (regionalisation method based on weather patterns). The WETTREG model output covers the period of 1951 to 2100 with a daily temporal resolution. For this, we generate a gridded data set of the WETTREG output for precipitation, air temperature and relative humidity with a spatial resolution of 12.5 km x 12.5 km, which is common for regional climate models. Thus, this regionalisation allows comparing statistical to dynamical climate model outputs. The HYRAS data set was developed by the German Meteorological Service within the German research program KLIWAS (www.kliwas.de) and consists of daily gridded data for Germany and its neighbouring river catchment areas. It has a spatial resolution of 5 km x 5 km for the entire domain for the hydro-meteorological elements precipitation, air temperature and relative humidity and covers the period of 1951 to 2006. After conservative remapping the HYRAS data set is also convenient for the validation of climate models. The presentation will consist of two parts to present the actual state of the adaptation of the HYRAS regionalisation methods to the statistical regional climate model WETTREG: First, an overview of the HYRAS data set and the regionalisation methods for precipitation (REGNIE method based on a combination of multiple linear regression with 5 predictors and inverse distance weighting), air temperature and relative humidity (optimal interpolation) will be given. Finally, results of the regionalisation of WETTREG model output will be shown.
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.
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.
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
Characterization of carbonaceous species of ambient PM2.5 in Beijing, China
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fumo Yang; Kebin He; Yongliang Ma
2005-07-01
One-week integrated fine particulate matter (i.e., particles {lt}2.5 {mu}m in diameter; PM2.5) samples were collected continuously with a low-flow rate sampler at a downtown site (Chegongzhuang) and a residential site (Tsinghua University) in Beijing between July 1999 and June 2000. The annual average concentrations of organic carbon (OC) and elemental carbon (EC) at the urban site were 23.9 and 8.8 {mu}g m{sup -3}, much higher than those in some cities with serious air pollution. Similar weekly variations of OC and EC concentrations were found for the two sampling sites with higher concentrations in the winter and autumn. The highest weeklymore » variations of OC and EC occurred in the winter, suggesting that combustion sources for space heating were important contributors to carbonaceous particles, along with a significant impact from variable meteorological conditions. High emissions coupled with unfavorable meteorological conditions led to the maximum weekly carbonaceous concentration the week of November 18-25, 1999. The weekly mass ratios of OC:EC ranged between 2 and 4 for most samples and averaged 2.9, probably suggesting that secondary OC (SOC) is present most weeks. The range of contemporary carbon fraction, based on the C14 analyses of eight samples collected in 2001, is 0.330-0.479. Estimated SOC accounted for {approximately}38% of the total OC at the two sites. Average OC and EC concentrations at Tsinghua University were 25% and 18%, respectively, higher than those at Chegongzhuang, which could be attributed to different local emissions of primary carbonaceous particles and gaseous precursors of SOC, as well as different summer photochemical intensities between the two locations. Main carbonaceous sources are from coal combustion, vehicles and cooking. 44 refs., 5 figs., 2 tabs.« less
Characterization of carbonaceous species of ambient PM2.5 in Beijing, China.
Yang, Fumo; He, Kebin; Ma, Yongliang; Zhang, Qiang; Cadle, Steven H; Chan, Tai; Mulawa, Patricia A
2005-07-01
One-week integrated fine particulate matter (i.e., particles <2.5 microm in diameter; PM2.5) samples were collected continuously with a low-flow rate sampler at a downtown site (Chegongzhuang) and a residential site (Tsinghua University) in Beijing between July 1999 and June 2000. The annual average concentrations of organic carbon (OC) and elemental carbon (EC) at the urban site were 23.9 and 8.8 microg m(-3), much higher than those in some cities with serious air pollution. Similar weekly variations of OC and EC concentrations were found for the two sampling sites with higher concentrations in the winter and autumn. The highest weekly variations of OC and EC occurred in the winter, suggesting that combustion sources for space heating were important contributors to carbonaceous particles, along with a significant impact from variable meteorological conditions. High emissions coupled with unfavorable meteorological conditions led to the max weekly carbonaceous concentration the week of November 18-25, 1999. The weekly mass ratios of OC:EC ranged between 2 and 4 for most samples and averaged 2.9, probably suggesting that secondary OC (SOC) is present most weeks. The range of contemporary carbon fraction, based on the C14 analyses of eight samples collected in 2001, is 0.330-0.479. Estimated SOC accounted for approximately 38% of the total OC at the two sites. Average OC and EC concentrations at Tsinghua University were 25% and 18%, respectively, higher than those at Chegongzhuang, which could be attributed to different local emissions of primary carbonaceous particles and gaseous precursors of SOC, as well as different summer photochemical intensities between the two locations.
Verification of different forecasts of Hungarian Meteorological Service
NASA Astrophysics Data System (ADS)
Feher, B.
2009-09-01
In this paper I show the results of the forecasts made by the Hungarian Meteorological Service. I focus on the general short- and medium-range forecasts, which contains cloudiness, precipitation, wind speed and temperature for six regions of Hungary. I would like to show the results of some special forecasts as well, such as precipitation predictions which are made for the catchment area of Danube and Tisza rivers, and daily mean temperature predictions used by Hungarian energy companies. The product received by the user is made by the general forecaster, but these predictions are based on the ALADIN and ECMWF outputs. Because of these, the product of the forecaster and the models were also verified. Method like this is able to show us, which weather elements are more difficult to forecast or which regions have higher errors. During the verification procedure the basic errors (mean error, mean absolute error) are calculated. Precipitation amount is classified into five categories, and scores like POD, TS, PC,â¦etc. were defined by contingency table determined by these categories. The procedure runs fully automatically, all the things forecasters have to do is to print the daily result each morning. Beside the daily result, verification is also made for longer periods like week, month or year. Analyzing the results of longer periods we can say that the best predictions are made for the first few days, and precipitation forecasts are less good for mountainous areas, even, the scores of the forecasters sometimes are higher than the errors of the models. Since forecaster receive results next day, it can helps him/her to reduce mistakes and learn the weakness of the models. This paper contains the verification scores, their trends, the method by which these scores are calculated, and some case studies on worse forecasts.
NASA Astrophysics Data System (ADS)
Größ, Johannes; Hamed, Amar; Sonntag, André; Spindler, Gerald; Elina Manninen, Hanna; Nieminen, Tuomo; Kulmala, Markku; Hõrrak, Urmas; Plass-Dülmer, Christian; Wiedensohler, Alfred; Birmili, Wolfram
2018-02-01
This paper revisits the atmospheric new particle formation (NPF) process in the polluted Central European troposphere, focusing on the connection with gas-phase precursors and meteorological parameters. Observations were made at the research station Melpitz (former East Germany) between 2008 and 2011 involving a neutral cluster and air ion spectrometer (NAIS). Particle formation events were classified by a new automated method based on the convolution integral of particle number concentration in the diameter interval 2-20 nm. To study the relevance of gaseous sulfuric acid as a precursor for nucleation, a proxy was derived on the basis of direct measurements during a 1-month campaign in May 2008. As a major result, the number concentration of freshly produced particles correlated significantly with the concentration of sulfur dioxide as the main precursor of sulfuric acid. The condensation sink, a factor potentially inhibiting NPF events, played a subordinate role only. The same held for experimentally determined ammonia concentrations. The analysis of meteorological parameters confirmed the absolute need for solar radiation to induce NPF events and demonstrated the presence of significant turbulence during those events. Due to its tight correlation with solar radiation, however, an independent effect of turbulence for NPF could not be established. Based on the diurnal evolution of aerosol, gas-phase, and meteorological parameters near the ground, we further conclude that the particle formation process is likely to start in elevated parts of the boundary layer rather than near ground level.
A meteorological potential forecast model for acid rain in Fujian Province, China.
Cai, Yi Yong; Lin, Chang Cheng; Liu, Jing Xiong; Wu, De Hui; Lian, Dong Ying; Chen, Bin Bin
2010-05-01
Based on the acid rain and concurrent meteorological observational data during the past 10 years in Fujian Province, China, the dependence of distribution characteristics of acid rain on season, rain rate, weather pattern and dominant airflow in four regions of Fujian Province is analyzed. On the annual average, the acid rain frequency is the highest (above 40%) in the southern and mid-eastern regions, and the lowest (16.2%) in the western region. The acid rain occurs most frequently in spring and winter, and least frequent in summer. The acid rain frequency in general increases with the increase of precipitation. It also depend on the direction of dominant airflows at 850 hPa. In the mid-eastern region, more than 40% acid rains appear when the dominant wind directions are NW, W, SW, S and SE. In the southern region, high acid rain occurrence happens when the dominant wind directions are NW, W, SW and S. In the northern region, 41.8% acid rains occur when the southwesterly is pronounced. In the western region, the southwesterly is associated with a 17% acid rain rate. The examination of meteorological sounding conditions over Fuzhou, Xiamen and Shaowu cities shows that the acid rain frequency increases with increased inversion thickness. Based on the results above, a meteorological potential forecast model for acid rain is established and tested in 2007. The result is encouraging. The model provides an objective basis for the development of acid rain forecasting operation in the province.
Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen
2013-01-01
The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T a) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T a estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T a based on MODIS land surface temperature (LST) data. The verification results of maximum T a, minimum T a, GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001–2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale. PMID:23365013
Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen
2013-02-01
The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on MODIS land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.
NASA Astrophysics Data System (ADS)
Delgado, Jordi; Cereijo-Arango, José Luis; Juncosa-Rivera, Ricardo
2016-04-01
Precipitation constitutes an important source of soluble materials to surface waters and, in areas where they are diluted precipitation (either dry or wet) it can be the most relevant solute source. Certain trace elements may have a limited natural availability in soils and rocks although they can be important with respect the operation of different biogeochemical cycles, for the computation of local/regional atmospheric pollutant loads or from the global mass budget. In the present study we report the results obtained in a long-lasting (December 2008-December 2015) monitoring survey of the chemical composition of bulk precipitation as monthly-integrated samples taken at the headwaters of the Barcés river watershed (A Coruña, Spain). This location was selected based on the necessity of quantification of the chemical composition and elemental loads associated with the different water types (stream water, ground water and precipitation) contributing to the flooding of the Meirama lake. Available data includes information on meteorological parameters (air temperature, relative humidity, atmospheric pressure, wind speed and direction, total and PAR radiation and precipitation) as well as a wide bundle of physico-chemical (pH, redox, electrical conductivity, alkalinity, Li, Na, K, Mg, Ca, Sr, Mn, Fe, NH4, Cs, Rb, Ba, Zn, Cu, Sb, Ni, Co, Cr, V, Cd, Ag, Pb, Se, Hg, Ti, Sn, U, Mo, F, Cl, Br, SO4, NO3, NO2, Al, As, PO4, SIO2, B, O2, DIC, DOC) and isotopic (18Ov-smow and 2Hv-smow) constituents. The average pH of local precipitation is 5.6 (n=65) which is consistent with the expected value for natural, unpolluted rain water. Most of the studied elements (eg. Na, Ca, K, Mg, SiO2, etc.) shows significant increases in their concentration in the dry period of the year. That points towards a more significant contribution of dry deposition in these periods compared with the wet ones. The average electrical conductivity is about 67 S/cm while the average chloride concentration 8 mg/L. Based on standard normalization procedures, the source of some major and trace precipitation elements have been identified, including sea water, soil and pollution/anthropogenic sources as well as multiyear trends. Available data has allowed also the computation of elemental loads in the studied area.
Evaluation of ET-based drought index derived from geostationary satellite data
USDA-ARS?s Scientific Manuscript database
The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle,...
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...
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.
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.
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.
Pan, Long; Yao, Enjian; Yang, Yang
2016-12-01
With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.
Accelerator-based chemical and elemental analysis of atmospheric aerosols
NASA Astrophysics Data System (ADS)
Mentes, Besim
Aerosol particles have always been present in the atmosphere, arising from natural sources. But it was not until recently when emissions from anthropogenic (man made) sources began to dominate, that atmospheric aerosols came into focus and the aerosol science in the environmental perspective started to grow. These sources emit or produce particles with different elemental and chemical compositions, as well as different sizes of the individual aerosols. The effects of increased pollution of the atmosphere are many, and have different time scales. One of the effects known today is acid rain, which causes problems for vegetation. Pollution is also a direct human health risk, in many cities where traffic driven by combustion engines is forbidden at certain times when the meteorological conditions are unfavourable. Aerosols play an important role in the climate, and may have both direct and indirect effect which cause cooling of the planet surface, in contrast to the so-called greenhouse gases. During this work a technique for chemical and elemental analysis of atmospheric aerosols and an elemental analysis methodology for upper tropospheric aerosols have been developed. The elemental analysis is performed by the ion beam analysis (IBA) techniques, PIXE (elements heavier than Al). PESA (C, N and O), cPESA (H) and pNRA (Mg and Na). The chemical speciation of atmospheric aerosols is obtained by ion beam thermography (IBT). During thermography the sample temperature is stepwise increased and the IBA techniques are used to continuously monitor the elemental concentration. A thermogram is obtained for each element. The vaporisation of the compounds in the sample appears as a concentration decrease in the thermograms at characteristic vaporisation temperatures (CVTs). Different aspects of IBT have been examined in Paper I to IV. The features of IBT are: almost total elemental speciation of the aerosol mass, chemical speciation of the inorganic compounds, carbon content obtained as volatile and non-volatile fractions, analysis of acidic aerosols is possible, aerosols can be size-fractionated using a cascade impactor as collection device, total analysis time for a sample is around 45 min, the sample mass load is from around 1 to 30 μg/cm2. An intercomparison of IBT and ion chromatography (IC) when a DMPS system was used as a reference instrument has been performed (Paper IV). Ions of K, Na, SO4, NO3 and NH4 were determined and quantified by both IBT and IC. The intercomparison showed that the procedure used in IBT does not suffer from any selective losses, especially not from the NO3 and NH4 compounds, which exhibit an appreciable interaction with the gas phase as NH3 and HNO3. An impactor-based aerosol sampler for upper tropospheric conditions has been developed (Paper V). Despite the low aerosol concentration at that altitude the sulphur concentration can be measured, with a detection limit of 1 ng/m 3 for one hour sampling by optimising parameters in the use of PIXE analysis.
USDA-ARS?s Scientific Manuscript database
The utility and reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, precipitation-based indices only reflect one component of the surface hydrologic cycle, ...
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.
Fantozzi, L; Manca, G; Ammoscato, I; Pirrone, N; Sprovieri, F
2013-03-15
An oceanographic cruise campaign on-board the Italian research vessel Urania was carried out from the 26th of August to the 13th of September 2010 in the Eastern Mediterranean. The campaign sought to investigate the mercury cycle at coastal and offshore locations in different weather conditions. The experimental activity focused on measuring mercury speciation in both seawater and in air, and using meteorological parameters to estimate elemental mercury exchange at the sea-atmosphere interface. Dissolved gaseous mercury (DGM), unfiltered total mercury (UTHg) and filtered total mercury (FTHg) surface concentrations ranged from 16 to 114, 300 to 18,760, and 230 to 10,990pgL(-1), respectively. The highest DGM, UTHg and FTHg values were observed close to Augusta (Sicily), a highly industrialized area of the Mediterranean region, while the lowest values were recorded at offshore stations. DGM vertical profiles partially followed the distribution of sunlight, as a result of the photoinduced transformations of elemental mercury in the surface layers of the water column. However, at some stations, we observed higher DGM concentrations in samples taken from the bottom of the water column, suggesting biological mercury production processes or the presence of tectonic activity. Moreover, two days of continuous measurement at one location demonstrated that surface DGM concentration is affected by solar radiation and atmospheric turbulence intensity. Atmospheric measurements of gaseous elemental mercury (GEM) showed an average concentration (1.6ngm(-3)) close to the background level for the northern hemisphere. For the first time this study used a numerical scheme based on a two-thin film model with a specific parameterization for mercury to estimate elemental mercury flux. The calculated average mercury flux during the entire cruise was 2.2±1.5ngm(-2)h(-1). The analysis of flux data highlights the importance of the wind speed on the mercury evasion from sea surfaces. Copyright © 2012 Elsevier B.V. All rights reserved.
Prediction of size-fractionated airborne particle-bound metals using MLR, BP-ANN and SVM analyses.
Leng, Xiang'zi; Wang, Jinhua; Ji, Haibo; Wang, Qin'geng; Li, Huiming; Qian, Xin; Li, Fengying; Yang, Meng
2017-08-01
Size-fractionated heavy metal concentrations were observed in airborne particulate matter (PM) samples collected from 2014 to 2015 (spanning all four seasons) from suburban (Xianlin) and industrial (Pukou) areas in Nanjing, a megacity of southeast China. Rapid prediction models of size-fractionated metals were established based on multiple linear regression (MLR), back propagation artificial neural network (BP-ANN) and support vector machine (SVM) by using meteorological factors and PM concentrations as input parameters. About 38% and 77% of PM 2.5 concentrations in Xianlin and Pukou, respectively, were beyond the Chinese National Ambient Air Quality Standard limit of 75 μg/m 3 . Nearly all elements had higher concentrations in industrial areas, and in winter among the four seasons. Anthropogenic elements such as Pb, Zn, Cd and Cu showed larger percentages in the fine fraction (ø≤2.5 μm), whereas the crustal elements including Al, Ba, Fe, Ni, Sr and Ti showed larger percentages in the coarse fraction (ø > 2.5 μm). SVM showed a higher training correlation coefficient (R), and lower mean absolute error (MAE) as well as lower root mean square error (RMSE), than MLR and BP-ANN for most metals. All the three methods showed better prediction results for Ni, Al, V, Cd and As, whereas relatively poor for Cr and Fe. The daily airborne metal concentrations in 2015 were then predicted by the fully trained SVM models and the results showed the heaviest pollution of airborne heavy metals occurred in December and January, whereas the lightest pollution occurred in June and July. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
The initial conceptualization and design of a meteorological satellite
NASA Technical Reports Server (NTRS)
Greenfield, S. M.
1982-01-01
The meteorological satellite had its substantive origin in the analytical process that helped initiate America's military satellite program. Its impetus lay in the desire to acquire current meteorological information in large areas for which normal meteorological observational data were not available on a day-to-day basis. Serious consideration was given to the feasibility of reconnaissance from meteorological satellites. The conceptualization of a meteorological satellite is discussed along with the early research which gave substance to that concept.
NASA Earth Science Research Results for Improved Regional Crop Yield Prediction
NASA Astrophysics Data System (ADS)
Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.
2007-12-01
National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.
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.
Actual vs. Perceived Climate Variability among Smallholding Rice Farmers
NASA Astrophysics Data System (ADS)
Carrico, A.; Gilligan, J. M.; Truelove, H. B.
2016-12-01
It is recognized that those engaged in resource-dependent livelihoods often hold extensive knowledge of their surrounding environment that, in some cases, facilitates sustainable practices and adaptation to environmental shocks. However, there remain significant gaps in our understanding of how actors at this scale perceive, understand, and respond to climate variability, particularly in the absence of good information. There are further unanswered questions about how these perceptions translate into livelihood decisions. In this paper, we use data collected in 2015 from 607 paddy farmers living in 12 villages throughout the heavily agricultural dry zone of Sri Lanka. Farmers were asked to report their perceptions of decadal scale changes in temperature and rainfall along a number of dimensions (e.g., annual rainfall, onset of monsoon rains, frequency of droughts, temperature). These data are compared to local meteorological data collected over the same time period to examine the perceptions of meteorological trends. Furthermore, we examine heterogeneity in perceptions as a function of demographic factors, reliance on irrigation, use of agricultural technology, and other socioeconomic characteristics of the farmer. The impact of perceptions on agricultural practices such as crop selection and water management, and resultant yields, will also be examined. Preliminary results based on five communities suggest a strong negativity bias in perceptions, with widespread agreement that meteorological conditions have become less hospitable for farming. Perceptions of temperature changes largely corresponded to meteorological records; however, perceptions of rainfall changes did not. There was some evidence that length of time spent in a village and the presence of elders in the household was associated with perceptions that more closely corresponded to the observed meteorological data. Updated analyses based on the complete data set will be presented. We will discuss the implications of these findings on the projected agricultural impacts of climate change, as well as for policies and programs designed to support adaptation among smallholding farmers.
NASA Astrophysics Data System (ADS)
Zhu, Suling; Lian, Xiuyuan; Wei, Lin; Che, Jinxing; Shen, Xiping; Yang, Ling; Qiu, Xuanlin; Liu, Xiaoning; Gao, Wenlong; Ren, Xiaowei; Li, Juansheng
2018-06-01
The PM2.5 is the culprit of air pollution, and it leads to respiratory system disease when the fine particles are inhaled. Therefore, it is increasingly significant to develop an effective model for PM2.5 forecasting and warnings that informs people to foresee the air quality. People can reduce outdoor activities and take preventive measures if they know the air quality is bad ahead of time. In addition, reliable forecasting results can remind the relevant departments to control and reduce pollutants discharge. According to our knowledge, the current hybrid forecasting techniques of PM2.5 do not take the meteorological factors into consideration. Actually, meteorological factors affect the concentrations of air pollution, but it is unclear whether meteorological factors are helpful for improving the PM2.5 forecasting results or not. This paper proposes a hybrid model called CEEMD-PSOGSA-SVR-GRNN, based on complementary ensemble empirical mode decomposition (CEEMD), particle swarm optimization and gravitational search algorithm (PSOGSA), support vector regression (SVR), generalized regression neural network (GRNN) and grey correlation analysis (GCA), for the daily PM2.5 concentrations forecasting. The main steps of proposed model are described as follows: the original PM2.5 data decomposition with CEEMD, optimal SVR selection with PSOGCA, meteorological factors selection with GCA, residual revision by GRNN and forecasting results analysis. Three cities (Chongqing, Harbin and Jinan) in China with different characteristics of climate, terrain and pollution sources are selected to verify the effectiveness of proposed model, and CEEMD-PSOGSA-SVR*, EEMD-PSOGSA-SVR, PSOGSA-SVR, CEEMD-PSO-SVR, CEEMD-GSA-SVR, CEEMD-GWO-SVR are considered to be compared models. The experimental results show that the hybrid CEEMD-PSOGSA-SVR-GRNN model outperforms other six compared models. Therefore, the proposed CEEMD-PSOGSA-SVR-GRNN model can be used to develop air quality forecasting and warnings.
Meteorological Effects of Land Cover Changes in Hungary during the 20th Century
NASA Astrophysics Data System (ADS)
Drüszler, Á.; Vig, P.; Csirmaz, K.
2012-04-01
Geological, paleontological and geomorphologic studies show that the Earth's climate has always been changing since it came into existence. The climate change itself is self-evident. Therefore the far more serious question is how much does mankind strengthen or weaken these changes beyond the natural fluctuation and changes of climate. The aim of the present study was to restore the historical land cover changes and to simulate the meteorological consequences of these changes. Two different land cover maps for Hungary were created in vector data format using GIS technology. The land cover map for 1900 was reconstructed based on statistical data and two different historical maps: the derived map of the 3rd Military Mapping Survey of the Austro-Hungarian Empire and the Synoptic Forestry Map of the Kingdom of Hungary. The land cover map for 2000 was derived from the CORINE land cover database. Significant land cover changes were found in Hungary during the 20th century according to the examinations of these maps and statistical databases. The MM5 non-hydrostatic dynamic model was used to further evaluate the meteorological effects of these changes. The lower boundary conditions for this mesoscale model were generated for two selected time periods (for 1900 and 2000) based on the reconstructed maps. The dynamic model has been run with the same detailed meteorological conditions of selected days from 2006 and 2007, but with modified lower boundary conditions. The set of the 26 selected initial conditions represents the whole set of the macrosynoptic situations for Hungary. In this way, 2×26 "forecasts" were made with 48 hours of integration. The effects of land cover changes under different weather situations were further weighted by the long-term (1961-1990) mean frequency of the corresponding macrosynoptic types, to assume the climatic effects from these stratified averages. The detailed evaluation of the model results were made for three different meteorological variables (temperature, dew point and precipitation).
Space Transportation System Meteorological Expert
NASA Technical Reports Server (NTRS)
Beller, Arthur E.; Stafford, Sue P.
1987-01-01
The STS Meteorological Expert (STSMET) is a long-term project to acquire general Shuttle operational weather forecasting expertise specific to the launch locale, to apply it to Shuttle operational weather forecasting tasks at the Cape Canaveral Forecast Facility, and ultimately to provide an on-line real-time operational aid to the duty forecasters in performing their tasks. Particular attention is given to the development of an approach called scenario-based reasoning, with specific application to summer thunderstorms; this type of reasoning can also be applied to frontal weather phenomena, visibility including fog, and wind shear.
Diurnal Ensemble Surface Meteorology Statistics
Excel file containing diurnal ensemble statistics of 2-m temperature, 2-m mixing ratio and 10-m wind speed. This Excel file contains figures for Figure 2 in the paper and worksheets containing all statistics for the 14 members of the ensemble and a base simulation.This dataset is associated with the following publication:Gilliam , R., C. Hogrefe , J. Godowitch, S. Napelenok , R. Mathur , and S.T. Rao. Impact of inherent meteorology uncertainty on air quality model predictions. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES. American Geophysical Union, Washington, DC, USA, 120(23): 12,259–12,280, (2015).
Meteorological conditions during the summer 1986 CITE 2 flight series
NASA Technical Reports Server (NTRS)
Shipham, Mark C.; Cahoon, Donald R.; Bachmeier, A. Scott
1990-01-01
An overview of meteorological conditions during the NASA Global Tropospheric Experiment/Chemical Instrumentation Testing and Evaluation (GTE/CITE 2) summer 1986 flight series is presented. Computer-generated isentropic trajectories are used to trace the history of air masses encountered along each aircraft flight path. The synoptic-scale wind fields are depicted based on Montgomery stream function analyses. Time series of aircraft-measured temperature, dew point, ozone, and altitude are shown to depict air mass variability. Observed differences between maritime tropical and maritime polar air masses are discussed.
NASA Technical Reports Server (NTRS)
Swift, C. T.; Goodberlet, M. A.; Wilkerson, J. C.
1990-01-01
The Defence Meteorological Space Program's (DMSP) Special Sensor Microwave/Imager (SSM/I), an operational wind speed algorithm was developed. The algorithm is based on the D-matrix approach which seeks a linear relationship between measured SSM/I brightness temperatures and environmental parameters. D-matrix performance was validated by comparing algorithm derived wind speeds with near-simultaneous and co-located measurements made by off-shore ocean buoys. Other topics include error budget modeling, alternate wind speed algorithms, and D-matrix performance with one or more inoperative SSM/I channels.
[Meteorological risk factors of stroke].
Lebedev, I A; Gilvanov, V A; Akinina, S A; Anishchenko, L I
2013-01-01
Based on correlation analysis of stroke, recorded in Khanty-Mansiysk during 5 years, and standard meteorological factors, we found the significant relationship between the frequency of stroke and daily temperature amplitude. The positive correlation between the frequency of stroke and between-day changes in air temperature in the combination with changes in atmospheric pressure during 3 h was identified. A maximal number of strokes was recorded in December, April, May and July and a minimal number was in January, June, August and September. The frequency of stroke and fatal outcomes did not depend on the season.
Applications of a shadow camera system for energy meteorology
NASA Astrophysics Data System (ADS)
Kuhn, Pascal; Wilbert, Stefan; Prahl, Christoph; Garsche, Dominik; Schüler, David; Haase, Thomas; Ramirez, Lourdes; Zarzalejo, Luis; Meyer, Angela; Blanc, Philippe; Pitz-Paal, Robert
2018-02-01
Downward-facing shadow cameras might play a major role in future energy meteorology. Shadow cameras directly image shadows on the ground from an elevated position. They are used to validate other systems (e.g. all-sky imager based nowcasting systems, cloud speed sensors or satellite forecasts) and can potentially provide short term forecasts for solar power plants. Such forecasts are needed for electricity grids with high penetrations of renewable energy and can help to optimize plant operations. In this publication, two key applications of shadow cameras are briefly presented.
SpaceX Jason-3 Live Launch Broadcast - Part 1 of 4
2016-01-17
At Space Launch Complex 4 at Vandenberg Air Force Base in California, a SpaceX Falcon 9 rocket launches the Jason-3 spacecraft into orbit for NOAA, the National Oceanic and Atmospheric Administration, and EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites. Built by Thales Alenia of France, Jason-3 will measure the topography of the ocean surface for a four-agency international partnership consisting of NOAA, NASA, Centre National d’Etudes Spatiales, France’s space agency, and the European Organization for the Exploitation of Meteorological Satellites.
SpaceX Jason-3 Live Launch Broadcast - Part 4 of 4
2016-01-17
At Space Launch Complex 4 at Vandenberg Air Force Base in California, a SpaceX Falcon 9 rocket launches the Jason-3 spacecraft into orbit for NOAA, the National Oceanic and Atmospheric Administration, and EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites. Built by Thales Alenia of France, Jason-3 will measure the topography of the ocean surface for a four-agency international partnership consisting of NOAA, NASA, Centre National d’Etudes Spatiales, France’s space agency, and the European Organization for the Exploitation of Meteorological Satellites.
SpaceX Jason-3 Live Launch Broadcast - Part 3 of 4
2016-01-17
At Space Launch Complex 4 at Vandenberg Air Force Base in California, a SpaceX Falcon 9 rocket launches the Jason-3 spacecraft into orbit for NOAA, the National Oceanic and Atmospheric Administration, and EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites. Built by Thales Alenia of France, Jason-3 will measure the topography of the ocean surface for a four-agency international partnership consisting of NOAA, NASA, Centre National d’Etudes Spatiales, France’s space agency, and the European Organization for the Exploitation of Meteorological Satellites.
SpaceX Jason-3 Live Launch Broadcast - Part 2 of 4
2016-01-17
At Space Launch Complex 4 at Vandenberg Air Force Base in California, a SpaceX Falcon 9 rocket launches the Jason-3 spacecraft into orbit for NOAA, the National Oceanic and Atmospheric Administration, and EUMETSAT, the European Organization for the Exploitation of Meteorological Satellites. Built by Thales Alenia of France, Jason-3 will measure the topography of the ocean surface for a four-agency international partnership consisting of NOAA, NASA, Centre National d’Etudes Spatiales, France’s space agency, and the European Organization for the Exploitation of Meteorological Satellites.
Meteorology/Oceanography Help - Naval Oceanography Portal
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Detecting urban warming signals in climate records
NASA Astrophysics Data System (ADS)
He, Yuting; Jia, Gensuo; Hu, Yonghong; Zhou, Zijiang
2013-07-01
Determining whether air temperatures recorded at meteorological stations have been contaminated by the urbanization process is still a controversial issue at the global scale. With support of historical remote sensing data, this study examined the impacts of urban expansion on the trends of air temperature at 69 meteorological stations in Beijing, Tianjin, and Hebei Province over the last three decades. There were significant positive relations between the two factors at all stations. Stronger warming was detected at the meteorological stations that experienced greater urbanization, i.e., those with a higher urbanization rate. While the total urban area affects the absolute temperature values, the change of the urban area (urbanization rate) likely affects the temperature trend. Increases of approximately 10% in urban area around the meteorological stations likely contributed to the 0.13°C rise in air temperature records in addition to regional climate warming. This study also provides a new approach to selecting reference stations based on remotely sensed urban fractions. Generally, the urbanization-induced warming contributed to approximately 44.1% of the overall warming trends in the plain region of study area during the past 30 years, and the regional climate warming was 0.30°C (10 yr)-1 in the last three decades.
Assessment of the Casualty Risk of Multiple Meteorological Hazards in China
Xu, Wei; Zhuo, Li; Zheng, Jing; Ge, Yi; Gu, Zhihui; Tian, Yugang
2016-01-01
A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales. PMID:26901210
Development and testing of meteorology and air dispersion models for Mexico City
NASA Astrophysics Data System (ADS)
Williams, M. D.; Brown, M. J.; Cruz, X.; Sosa, G.; Streit, G.
Los Alamos National Laboratory and Instituto Mexicano del Petróleo are completing a joint study of options for improving air quality in Mexico City. We have modified a three-dimensional, prognostic, higher-order turbulence model for atmospheric circulation (HOTMAC) and a Monte Carlo dispersion and transport model (RAPTAD) to treat domains that include an urbanized area. We used the meteorological model to drive models which describe the photochemistry and air transport and dispersion. The photochemistry modeling is described in a separate paper. We tested the model against routine measurements and those of a major field program. During the field program, measurements included: (1) lidar measurements of aerosol transport and dispersion, (2) aircraft measurements of winds, turbulence, and chemical species aloft, (3) aircraft measurements of skin temperatures, and (4) Tethersonde measurements of winds and ozone. We modified the meteorological model to include provisions for time-varying synoptic-scale winds, adjustments for local wind effects, and detailed surface-coverage descriptions. We developed a new method to define mixing-layer heights based on model outputs. The meteorology and dispersion models were able to provide reasonable representations of the measurements and to define the sources of some of the major uncertainties in the model-measurement comparisons.
Assessment of the Casualty Risk of Multiple Meteorological Hazards in China.
Xu, Wei; Zhuo, Li; Zheng, Jing; Ge, Yi; Gu, Zhihui; Tian, Yugang
2016-02-17
A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Luetzow, H.B.v.
1983-08-01
Following an introduction, the paper discusses in section 2 the collection or generation of final geodetic data from conventional surveys, satellite observations, satellite altimetry, the Global Positioning System, and moving base gravity gradiometers. Section 3 covers data utilization and accuracy aspects including gravity programmed inertial positioning and subterraneous mass detection. Section 4 addresses the usefulness and limitation of the collocation method of physical geodesy. Section 5 is concerned with the computation of classical climatological data. In section 6, meteorological data assimilation is considered. Section 7 deals with correlated aspects of initial data generation with emphasis on initial wind field determination,more » parameterized and classical hydrostatic prediction models, non-hydrostatic prediction, computational networks, and computer capacity. The paper concludes that geodetic and meteorological data are expected to become increasingly more diversified and voluminous both regionally and globally, that its general availability will be more or less restricted for some time to come, that its quality and quantity are subject to change, and that meteorological data generation, accuracy and density have to be considered in conjunction with advanced as well as cost-effective numerical weather prediction models and associated computational efforts.« less
Multiscale wind cycles and current pulses at the Black Sea eastern boundary
NASA Astrophysics Data System (ADS)
Melnikov, Vasiliy; Moskalenko, Lidija; Piotoukh, Vladimir; Zatsepin, Andrey
2015-04-01
The goal of the research is to examine meteorological descriptive elements, sea-water properties, regional hydrodynamics and energy conversion fluxes in order to study sea responses to the local and far-field weather system. The Black Sea is situated in the chain of internal basins between the North Atlantic and Central Asia deserts in the marginal interaction zone and, accordingly, is under the influence of the Azores and Siberian anticyclones, Arctic cold-air surges and subtropical desert belt to the south. The analysis is based on the data of modern oceanographic measuring network "Hydro-physical Polygon" of the Institute of oceanology, using contact and remote sensing methods, weather stations around the Black Sea coasts, including long-term (1938-2014) measurements at the Gelendzhik weather station. Various satellite and Reanalysis databases are used. Currently, there are three long-time measuring moored stations (each contains ADCP and thermistor chain) and scanning profiling system "Akvalog". Hydrological sections and field surveys using towed ADCP and CTD are performed on a regular basis. The data are accumulated in the coastal archive which allows calibration of satellite measurements and testing results of numerical modeling. Data processing includes data sets preparation, editing, time series statistical calculations using histograms, progressive vector diagrams, traditional Fourier spectral analysis including auto- and cross spectra, auto and mutual wavelet diagrams, moving spectrograms, vector data methods using rotary components, spectral invariants, empirical modes, hodograph and pre-specified spectrum representations on the basis of stochastic models with imposed dynamical assumptions. Due to the intermittent nature of the time rows, spectral representation is misleading, often. In order to identify the individual evolving dynamical phenomenon, typical background (seasonal) three-dimensional structures of the hydrological field, as well as quantified anomalies, associated with different frequency components of variability, such as sub-meso-scale eddies, marginal shelf waves, inertial oscillations, diurnal, semi-diurnal and short-period internal waves, long surface waves, were estimated. Based on estimates of the statistical relationships between the different parameters of hydro-meteorological system, including meteorological elements, sea level, sea temperature and flow fields, space/time scales of the observed fields variability were estimated. Several new features of the physical mechanisms of multiscale hydro-physical processes in the shelf zone of the Black Sea, have been revealed. In particular, it is shown, that there are wind self-similar cycles at different time scales, each cycle being consisted of a pair of northeast and then southeast winds, which corresponds to the alternative influences of the Azores and Siberian highs(in winter). In the range of decadal (10 years) scale and in macro space view, long-term wind cycles support basic Black Sea circulation(Rim Current).Wind cycles with a time scale of about 20 days give rise to distinct upwellings, appeared with the same frequency. Along with each upwelling, radical hydrological restructuring of the stratification is accompanied by intense advection with high velocities(up to 1 m/s). Kinetic energy is dominated by alongshore currents, the direction being reversed periodically. The vertical structure of currents is rather complicated. When the current speed exceeds some threshold value, the flow gives rise to relaxation oscillations with a period of about 24 hours with counterclockwise velocity vector rotation. All the above mentioned events and current pulses cause significant variations of air-sea fluxes. This research was jointly supported by Ministry of Education of the RF (Agreement №14.604.21.0044), Russian Academy of Sciences(Program No 23), RFBR grant 14-05-00159,contract No 10/2013 RGS-RFBR.
NASA Astrophysics Data System (ADS)
Hu, Taiyang; Lv, Rongchuan; Jin, Xu; Li, Hao; Chen, Wenxin
2018-01-01
The nonlinear bias analysis and correction of receiving channels in Chinese FY-3C meteorological satellite Microwave Temperature Sounder (MWTS) is a key technology of data assimilation for satellite radiance data. The thermal-vacuum chamber calibration data acquired from the MWTS can be analyzed to evaluate the instrument performance, including radiometric temperature sensitivity, channel nonlinearity and calibration accuracy. Especially, the nonlinearity parameters due to imperfect square-law detectors will be calculated from calibration data and further used to correct the nonlinear bias contributions of microwave receiving channels. Based upon the operational principles and thermalvacuum chamber calibration procedures of MWTS, this paper mainly focuses on the nonlinear bias analysis and correction methods for improving the calibration accuracy of the important instrument onboard FY-3C meteorological satellite, from the perspective of theoretical and experimental studies. Furthermore, a series of original results are presented to demonstrate the feasibility and significance of the methods.
Schemel, Laurence E.
2002-01-01
Meteorological data were collected during 1998-2001 at the Port of Redwood City, California, to support hydrologic studies in South San Francisco Bay. The measured meteorological variables were air temperature, atmospheric pressure, quantum flux (insolation), and four parameters of wind speed and direction: scalar mean horizontal wind speed, (vector) resultant horizontal wind speed, resultant wind direction, and standard deviation of the wind direction. Hourly mean values based on measurements at five-minute intervals were logged at the site. Daily mean values were computed for temperature, infolation, pressure, and scalar wind speed. Daily mean values for 1998-2001 are described in this report, and a short record of hourly mean values is compared to data from another near-by station. Data (hourly and daily mean) from the entire period of record (starting in April 1992) and reports describing data prior to 1998 are provided.
NASA Astrophysics Data System (ADS)
Bedoya, Andres; Navas-Guzmán, Francisco; Guerrero-Rascado, Juan Luis; Alados-Arboledas, Lucas
2017-04-01
Profiles of meteorological variables such as temperature, relative humidity and integrated water vapor derived from a ground-based microwave radiometer (MWR, RPG-HATPRO) are continuously monitored since 2012 at Granada station (Southeastern Spain). During this period up to 210 collocated meteorological balloons, equipped with a radiosonde DFM-09 (GRAWMET), were launched. This study is carried out with a twofold goal. On one hand, a validation of the MWR products such as temperature and water vapor mixing ratio profiles and the IWV from MWR is carried out comparing with radiosonde measurements. The behavior of MWR retrievals under clear and cloudy conditions and for special situations such as inversions has been analyzed. On the other hand, the whole period with continuous measurements is used for a statistical evaluation of the meteorological variables derived from MWR in order to thermodynamically characterize the atmosphere over Granada.
[Relationships between horqin meadow NDVI and meteorological factors].
Qu, Cui-ping; Guan, De-xin; Wang, An-zhi; Jin, Chang-jie; Wu, Jia-bing; Wang, Ji-jun; Ni, Pan; Yuan, Feng-hui
2009-01-01
Based on the 2000-2006 MODIS 8-day composite NDVI and day-by-day meteorological data, the seasonal and inter-annual variations of Horqin meadow NDVI as well as the relationships between the NDVI and relevant meteorological factors were studied. The results showed that as for the seasonal variation, Horqin meadow NDVI was more related to water vapor pressure than to precipitation. Cumulated temperature and cumulated precipitation together affected the inter-annual turning-green period significantly, and the precipitation in growth season (June and July), compared with that in whole year, had more obvious effects on the annual maximal NDVI. The analysis of time lag effect indicated that water vapor pressure had a persistent (about 12 days) prominent effect on the NDVI. The time lag effect of mean air temperature was 11-15 days, and the cumulated dual effect of the temperature and precipitation was 36-52 days.
Meteorological satellites: Past, present, and future
NASA Technical Reports Server (NTRS)
1982-01-01
Past developments, accomplishments and future potential of meteorological satellites are discussed. Meteorological satellite design is described in detail. Space platforms and their meteorological applications are discussed. User needs are also discussed.
Research on the method of establishing the total radiation meter calibration device
NASA Astrophysics Data System (ADS)
Gao, Jianqiang; Xia, Ming; Xia, Junwen; Zhang, Dong
2015-10-01
Pyranometer is an instrument used to measure the solar radiation, according to pyranometer differs as installation state, can be respectively measured total solar radiation, reflected radiation, or with the help of shading device for measuring scattering radiation. Pyranometer uses the principle of thermoelectric effect, inductive element adopts winding plating type multi junction thermopile, its surface is coated with black coating with high absorption rate. Hot junction in the induction surface, while the cold junction is located in the body, the cold and hot junction produce thermoelectric potential. In the linear range, the output signal is proportional to the solar irradiance. Traceability to national meteorological station, as the unit of the national legal metrology organizations, the responsibility is to transfer value of the sun and the earth radiation value about the national meteorological industry. Using the method of comparison, with indoor calibration of solar simulator, at the same location, standard pyranometer and measured pyranometer were alternately measured radiation irradiance, depending on the irradiation sensitivity standard pyranometer were calculated the radiation sensitivity of measured pyranometer. This paper is mainly about the design and calibration method of the pyranometer indoor device. The uncertainty of the calibration result is also evaluated.
Auditory performance in an open sound field
NASA Astrophysics Data System (ADS)
Fluitt, Kim F.; Letowski, Tomasz; Mermagen, Timothy
2003-04-01
Detection and recognition of acoustic sources in an open field are important elements of situational awareness on the battlefield. They are affected by many technical and environmental conditions such as type of sound, distance to a sound source, terrain configuration, meteorological conditions, hearing capabilities of the listener, level of background noise, and the listener's familiarity with the sound source. A limited body of knowledge about auditory perception of sources located over long distances makes it difficult to develop models predicting auditory behavior on the battlefield. The purpose of the present study was to determine the listener's abilities to detect, recognize, localize, and estimate distances to sound sources from 25 to 800 m from the listing position. Data were also collected for meteorological conditions (wind direction and strength, temperature, atmospheric pressure, humidity) and background noise level for each experimental trial. Forty subjects (men and women, ages 18 to 25) participated in the study. Nine types of sounds were presented from six loudspeakers in random order; each series was presented four times. Partial results indicate that both detection and recognition declined at distances greater than approximately 200 m and distance estimation was grossly underestimated by listeners. Specific results will be presented.
What determines transitions between energy- and moisture-limited evaporative regimes?
NASA Astrophysics Data System (ADS)
Haghighi, E.; Gianotti, D.; Akbar, R.; Salvucci, G.; Entekhabi, D.
2017-12-01
The relationship between evaporative fraction (EF) and soil moisture (SM) has traditionally been used in atmospheric and land-surface modeling communities to determine the strength of land-atmosphere coupling in the context of the dominant evaporative regime (energy- or moisture-limited). However, recent field observations reveal that EF-SM relationship is not unique and could vary substantially with surface and/or meteorological conditions. This implies that conventional EF-SM relationships (exclusive of surface and meteorological conditions) are embedded in more complex dependencies and that in fact it is a multi-dimensional function. To fill the fundamental knowledge gaps on the important role of varying surface and meteorological conditions not accounted for by the traditional evaporative regime conceptualization, we propose a generalized EF framework using a mechanistic pore-scale model for evaporation and energy partitioning over drying soil surfaces. Nonlinear interactions among the components of the surface energy balance are reflected in a critical SM that marks the onset of transition between energy- and moisture-limited evaporative regimes. The new generalized EF framework enables physically based estimates of the critical SM, and provides new insights into the origin of land surface EF partitioning linked to meteorological input data and the evolution of land surface temperature during surface drying that affect the relative efficiency of surface energy balance components. Our results offer new opportunities to advance predictive capabilities quantifying land-atmosphere coupling for a wide range of present and projected meteorological input data.
Development of a Greek solar map based on solar model estimations
NASA Astrophysics Data System (ADS)
Kambezidis, H. D.; Psiloglou, B. E.; Kavadias, K. A.; Paliatsos, A. G.; Bartzokas, A.
2016-05-01
The realization of Renewable Energy Sources (RES) for power generation as the only environmentally friendly solution, moved solar systems to the forefront of the energy market in the last decade. The capacity of the solar power doubles almost every two years in many European countries, including Greece. This rise has brought the need for reliable predictions of meteorological data that can easily be utilized for proper RES-site allocation. The absence of solar measurements has, therefore, raised the demand for deploying a suitable model in order to create a solar map. The generation of a solar map for Greece, could provide solid foundations on the prediction of the energy production of a solar power plant that is installed in the area, by providing an estimation of the solar energy acquired at each longitude and latitude of the map. In the present work, the well-known Meteorological Radiation Model (MRM), a broadband solar radiation model, is engaged. This model utilizes common meteorological data, such as air temperature, relative humidity, barometric pressure and sunshine duration, in order to calculate solar radiation through MRM for areas where such data are not available. Hourly values of the above meteorological parameters are acquired from 39 meteorological stations, evenly dispersed around Greece; hourly values of solar radiation are calculated from MRM. Then, by using an integrated spatial interpolation method, a Greek solar energy map is generated, providing annual solar energy values all over Greece.
Tornado! An Event-Based Science Module. Student Edition. Meteorology Module.
ERIC Educational Resources Information Center
Wright, Russell G.
This book is designed for middle school students to learn scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning, teamwork, independent research, hands-on investigations, and…
NASA Astrophysics Data System (ADS)
Chen, Ziyue; Cai, Jun; Gao, Bingbo; Xu, Bing; Dai, Shuang; He, Bin; Xie, Xiaoming
2017-01-01
Due to complicated interactions in the atmospheric environment, quantifying the influence of individual meteorological factors on local PM2.5 concentration remains challenging. The Beijing-Tianjin-Hebei (short for Jing-Jin-Ji) region is infamous for its serious air pollution. To improve regional air quality, characteristics and meteorological driving forces for PM2.5 concentration should be better understood. This research examined seasonal variations of PM2.5 concentration within the Jing-Jin-Ji region and extracted meteorological factors strongly correlated with local PM2.5 concentration. Following this, a convergent cross mapping (CCM) method was employed to quantify the causality influence of individual meteorological factors on PM2.5 concentration. The results proved that the CCM method was more likely to detect mirage correlations and reveal quantitative influences of individual meteorological factors on PM2.5 concentration. For the Jing-Jin-Ji region, the higher PM2.5 concentration, the stronger influences meteorological factors exert on PM2.5 concentration. Furthermore, this research suggests that individual meteorological factors can influence local PM2.5 concentration indirectly by interacting with other meteorological factors. Due to the significant influence of local meteorology on PM2.5 concentration, more emphasis should be given on employing meteorological means for improving local air quality.
NASA Astrophysics Data System (ADS)
Letortu, P.; Costa, S.; Cantat, O.; Levoy, F.; Dauvin, J. C.; De Saint-Léger, E.
2012-04-01
On account of increasing inhabitation and development of coastal areas, the economical stakes are high for forecasting and prevention of coastal flooding risk. Because of its exposure to prevailing Westerlies, morphological, and topographic features, low coastal areas on the French coast of the eastern English Channel are particularly sensitive to this natural risk. This sensitivity, that has always characterized this study area, is becoming worrying to politicians and inhabitants. The study aim is to identify, from 1949 to 2010, the possible increase of frequency and intensity of these meteorological and marine events, and their characteristics for forecasting objectives. The chosen approach is made up of three elements: 1) An analysis of strong west wind over the last decades has been implemented from Meteo-France data of Dieppe, reliable regional meteorological station. Beyond multi-annual random fluctuations, we have noticed a decrease in frequency and intensity of strong winds traditionally involved in flooding events. 2) An analysis of past events has been carried out from many information sources to warrant the accuracy of statements and their exhaustiveness. Thanks to this database, the main results are: i) the absence of increasing trend about frequency and intensity of coastal flooding events; ii) the cartography of coastal flooding risk for each urbanized area; iii) the definition of wind and tide level thresholds (7 m/s and 8.49 m at Dieppe) above which there is flooding. 3) A characterization, on the synoptic scale, of meteorological conditions ending in flooding has been performed. In matching this piece of information with the past events inventory, we have identified: firstly the two major types of low pressure trajectories that generated overflowing, so the two main atmospheric circulations prone to flooding, and secondly the fundamental meteorological aspect of the high north-west pressure gradient (≥ 20 hPa from "Pointe du Raz" (France) to Cromer city (U.K.)) of these flooding events. Frequency of this particular pressure configuration in the English Channel does not highlight any significant trend during the last century. Beyond tide level and wind (speed, direction) thresholds, another factor explains coastal flooding events. This is the matter of atmospheric cold front during high tide, observable in 70 % of coastal flooding events in the eastern English Channel. Analysis of these coastal flooding events cannot be restricted to simple meteorological and marine conditions during overflowing by the sea. This work emphasizes the need for longer analysis period. It is important to encompass the possible beach "preparation time" (lowering of the beach profile) by meteorological and marine conditions for a few days or weeks before flooding event. This "preparation time" may be short: 48 hours of strong winds (> 8 m/s) may be sufficient to shape a beach profile prone to overflowing. Coastal flooding is the result of a combination of factors from various time and space scales, which goes over the simple combination of extreme sea-level and strong wind perpendicular to coast.
Terrain Portrayal for Head-Down Displays Flight Test
NASA Technical Reports Server (NTRS)
Hughes, Monica F.; Glaab, Louis J.
2003-01-01
The Synthetic Vision Systems General Aviation (SVS-GA) element of NASA's Aviation Safety Program is developing technology to eliminate low visibility induced General Aviation (GA) accidents through the application of synthetic vision techniques. SVS displays present computer generated 3-dimensional imagery of the surrounding terrain to greatly enhance pilot's situation awareness (SA), reducing or eliminating Controlled Flight into Terrain (CFIT), as well as Low-Visibility Loss of Control (LVLOC) accidents. In addition to substantial safety benefits, SVS displays have many potential operational benefits that can lead to flight in instrument meteorological conditions (IMC) resembling those conducted in visual meteorological conditions (VMC). Potential benefits could include lower landing minimums, more approach options, reduced training time, etc. SVS conducted research will develop display concepts providing the pilot with an unobstructed view of the outside terrain, regardless of weather conditions and time of day. A critical component of SVS displays is the appropriate presentation of terrain to the pilot. The relationship between the realism of the terrain presentation and resulting enhancements of pilot SA and pilot performance has been largely undefined. Comprised of coordinated simulation and flight test efforts, the terrain portrayal for head-down displays (TP-HDD) test series examined the effects of two primary elements of terrain portrayal: variations of digital elevation model (DEM) resolution and terrain texturing. Variations in DEM resolution ranged from sparsely spaced (30 arc-sec/2,953ft) to very closely spaced data (1 arc-sec/98 ft). Variations in texture involved three primary methods: constant color, elevation-based generic, and photo-realistic, along with a secondary depth cue enhancer in the form of a fishnet grid overlay. The TP-HDD test series was designed to provide comprehensive data to enable design trades to optimize all SVS applications, as well as develop requirements and recommendations to facilitate the implementation and certification of SVS displays. The TP-HDD flight experiment utilized the NASA LaRC Cessna 206 Stationaire and evaluated eight terrain portrayal concepts in an effort to confirm and extend results from the previously conducted TP-HDD simulation experiment. A total of 15 evaluation pilots, of various qualifications, accumulated over 75 hours of dedicated research flight time at Newport News (PHF) and Roanoke (ROA), VA, airports from August through October, 2002. This report will present results from the portion of testing conducted at Roanoke, VA.
Airline meteorological requirements
NASA Technical Reports Server (NTRS)
Chandler, C. L.; Pappas, J.
1985-01-01
A brief review of airline meteorological/flight planning is presented. The effects of variations in meteorological parameters upon flight and operational costs are reviewed. Flight path planning through the use of meteorological information is briefly discussed.
NASA Astrophysics Data System (ADS)
Jorba, O.; Pérez, C.; Baldasano, J. M.
2009-04-01
Chemical processes in air quality modelling systems are usually treated independently from the meteorological models. This approach is computationally attractive since off-line chemical transport simulations only require a single meteorological dataset to produce many chemical simulations. However, this separation of chemistry and meteorology produces a loss of important information about atmospheric processes and does not allow for feedbacks between chemistry and meteorology. To take into account such processes current models are evolving to an online coupling of chemistry and meteorology to produce consistent chemical weather predictions. The Earth Sciences Department of the Barcelona Supercomputing Center (BSC) develops the NMMB/BSC-DUST (Pérez et al., 2008), an online dust model within the global-regional NCEP/NMMB numerical weather prediction model (Janjic and Black, 2007) under development at National Centers for Environmental Prediction (NCEP). Current implementation is based on the well established regional dust model and forecast system DREAM (Nickovic et al., 2001). The most relevant characteristics of NMMB/BSC-DUST are its on-line coupling of the dust scheme with the meteorological driver, the wide range of applications from meso to global scales, and the inclusion of dust radiative effects allowing feedbacks between aerosols and meteorology. In order to complement such development, BSC works also in the implementation of a fully coupled online chemical mechanism within NMMB/BSC-DUST. The final objective is to develop a fully chemical weather prediction system able to resolve gas-aerosol-meteorology interactions from global to local scales. In this contribution we will present the design of the chemistry coupling and the current progress of its implementation. Following the NCEP/NMMB approach, the chemistry part will be coupled through the Earth System Modeling Framework (ESMF) as a pluggable component. The chemical mechanism and chemistry solver is based on the Kinetic PreProcessor KPP (Sandu and Sander, 2006) package with the main purpose to maintain a wide flexibility when configuring the model. Such approach will allow using a simple general chemical mechanism for global applications or a more complex mechanism for regional to local applications at higher resolution. REFERENCES Janjic, Z.I., and Black, T.L., 2007. An ESMF unified model for a broad range of spatial and temporal scales, Geophysical Research Abstracts, 9, 05025. Nickovic, S., Papadopoulos, A., Kakaliagou, O., and Kallos, G., 2001. Model for prediciton of desert dust cycle in the atmosphere. J. Geophys. Res., 106, 18113-18129. Pérez, C., Haustein, K., Janjic, Z.I., Jorba, O., Baldasano, J.M., Black, T.L., and Nickovic, S., 2008. An online dust model within the meso to global NMMB: current progress and plans. AGU Fall Meeting, San Francisco, A41K-03, 2008. Sandu, A., and Sander, R., 2006. Technical note:Simulating chemical systems in Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1. Atmos. Chem. and Phys., 6, 187-195.
NASA Astrophysics Data System (ADS)
Ruhoff, Anderson; Santini Adamatti, Daniela
2017-04-01
MODIS evapotranspiration (MOD16) is currently available with 1 km of spatial resolution over 109.03 Million km2 of vegetated land surface areas and this information is widely used to evaluate the linkages between hydrological, energy and carbon cycles. The algorithm is driven by meteorological reanalysis data and MODIS remotely-sensed data, which include land use and land cover classification (MCD12Q1), leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) (MOD15A2) and albedo (MOD43b3). For calibration and parameterization, the algorithm uses a Biome Property Look-up Table (BPLUT) based on MCD12Q1 land cover classification. Several studies evaluated MOD16 accuracy using evapotranspiration measurements and water balance analysis, showing that this product can reproduce global evapotranspiration effectively under a variety climate condition, from local to wide-basin scale, with uncertainties up to 25%. In this study, we evaluated the sensitivity of MOD16 algorithm to land use and land cover parameterization and to meteorological data. Considering that MCD12Q1 has an accuracy between 70 and 85% at continental scale, we changed land cover parametererization to understand the influence of land use and land cover classification on MOD16 evapotranspiration estimations. Knowing that meteorological reanalysis data also have uncertainties (mostly related to the coarse spatial resolution), we compared MOD16 evapotranspiration driven by observed meteorological data to those driven by the reanalysis data. Our analysis were carried in South America, with evapotranspiration and meteorological measurements from the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) at 8 different sites, including tropical rainforest, tropical dry forest, selective logged forest, seasonal flooded forest and pasture/agriculture. Our results indicate that land use and land cover classification has a strong influence on MOD16 algorithm. The use of incorrect parametererization due to land use and land cover misclassification can introduce large erros in estimates of evapotranspiration. We also found that the biases in meteorological reanalysis data can introduce considerable errors into the estimations. Overall, there is a significant potential for mapping and monitoring global evapotranspiration using MODIS remotely-sensed images combined to meteorological reanalysis data.
NASA Technical Reports Server (NTRS)
Duda, David P.; Minnis, Patrick
2009-01-01
Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hoel, D.D.
1984-01-01
Two computer codes have been developed for operational use in performing real time evaluations of atmospheric releases from the Savannah River Plant (SRP) in South Carolina. These codes, based on mathematical models, are part of the SRP WIND (Weather Information and Display) automated emergency response system. Accuracy of ground level concentrations from a Gaussian puff-plume model and a two-dimensional sequential puff model are being evaluated with data from a series of short range diffusion experiments using sulfur hexafluoride as a tracer. The models use meteorological data collected from 7 towers on SRP and at the 300 m WJBF-TV tower aboutmore » 15 km northwest of SRP. The winds and the stability, which is based on turbulence measurements, are measured at the 60 m stack heights. These results are compared to downwind concentrations using only standard meteorological data, i.e., adjusted 10 m winds and stability determined by the Pasquill-Turner stability classification method. Scattergrams and simple statistics were used for model evaluations. Results indicate predictions within accepted limits for the puff-plume code and a bias in the sequential puff model predictions using the meteorologist-adjusted nonstandard data. 5 references, 4 figures, 2 tables.« less
Tornado! An Event-Based Science Module. Teacher's Guide. Meteorology Module.
ERIC Educational Resources Information Center
Wright, Russell G.
This book is designed for middle school earth science teachers to help their students learn about problems with tornadoes and scientific literacy through event-based science. Unlike traditional curricula, the event-based earth science module is a student-centered, interdisciplinary, inquiry-oriented program that emphasizes cooperative learning,…
Development of gridded solar radiation data over Belgium based on Meteosat and in-situ observations
NASA Astrophysics Data System (ADS)
Journée, Michel; Vanderveken, Gilles; Bertrand, Cédric
2013-04-01
Knowledge on solar resources is highly important for all forms of solar energy applications. With the recent development in solar-based technologies national meteorological services are faced with increasing demands for high-quality and reliable site-time specific solar resource information. Traditionally, solar radiation is observed by means of networks of meteorological stations. Costs for installation and maintenance of such networks are very high and national networks comprise only few stations. Consequently the availability of ground-based solar radiation measurements has proven to be spatially and temporally inadequate for many applications. To overcome such a limitation, a major effort has been undertaken at the Royal Meteorological Institute of Belgium (RMI) to provide the solar energy industry, the electricity sector, governments, and renewable energy organizations and institutions with the most suitable and accurate information on the solar radiation resources at the Earth's surface over the Belgian territory. Only space-based observations can deliver a global coverage of the solar irradiation impinging on horizontal surface at the ground level. Because only geostationary data allow to capture the diurnal cycle of the solar irradiance at the Earth's surface, a method that combines information from Meteosat Second Generation satellites and ground-measurement has been implemented at RMI to generate high resolution solar products over Belgium on an operational basis. Besides these new products, the annual and seasonal variability of solar energy resource was evaluated, solar radiation climate zones were defined and the recent trend in solar radiation was characterized.
NASA Astrophysics Data System (ADS)
Zhu, X.; Wen, X.; Zheng, Z.
2017-12-01
For better prediction and understanding of land-atmospheric interaction, in-situ observed meteorological data acquired from the China Meteorological Administration (CMA) were assimilated in the Weather Research and Forecasting (WRF) model and the monthly Green Vegetation Coverage (GVF) data, which was calculated using the Normalized Difference Vegetation Index (NDVI) of the Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and Digital Elevation Model (DEM) data of the Shuttle Radar Topography Mission (SRTM) system. Furthermore, the WRF model produced a High-Resolution Assimilation Dataset of the water-energy cycle in China (HRADC). This dataset has a horizontal resolution of 25 km for near surface meteorological data, such as air temperature, humidity, wind vectors and pressure (19 levels); soil temperature and moisture (four levels); surface temperature; downward/upward short/long radiation; 3-h latent heat flux; sensible heat flux; and ground heat flux. In this study, we 1) briefly introduce the cycling 3D-Var assimilation method and 2) compare results of meteorological elements, such as 2 m temperature and precipitation generated by the HRADC with the gridded observation data from CMA, and surface temperature and specific humidity with Global LandData Assimilation System (GLDAS) output data from the National Aeronautics and Space Administration (NASA). We found that the satellite-derived GVF from MODIS increased over southeast China compared with the default model over the whole year. The simulated results of soil temperature, net radiation and surface energy flux from the HRADC are improved compared with the control simulation and are close to GLDAS outputs. The values of net radiation from HRADC are higher than the GLDAS outputs, and the differences in the simulations are large in the east region but are smaller in northwest China and on the Qinghai-Tibet Plateau. The spatial distribution of the sensible heat flux and the ground heat flux from HRADC is consistent with the GLDAS outputs in summer. In general, the simulated results from HRADC are an improvement on the control simulation and can present the characteristics of the spatial and temporal variation of the water-energy cycle in China.
NASA Astrophysics Data System (ADS)
Hejkrlík, Libor; Plachá, Helena
2017-04-01
Number concentrations of fine particles had been measured by SMPS in a diameter range of 10 to 800 nm in 7 channels with time resolution of one hour since June 2012 to December 2015 at a background urban site in Northern Bohemia. At nearly the same place hourly means of three meteorological elements were available (air temperature Th, relative air humidity Hh and global radiation Rh) and as a complementary index of atmospheric pollution the mass concentrations of PM1-BC (black carbon). The whole period of observations covered 1309 days, periodically involving all of the seasons of the year. Th varied between 11,2 ˚ C and 36,1 ˚ C, for Hh it was between 21% and 100% and Rh reached its extremes between 0,2 and 940,5 W/m2 (night hours were excluded). Resulting number of analyzed rows of 11 variables was approximately 14 000. The nearly-continuous combinations of meteorological data were transformed into three-dimensional matrix where Th,Hh and Rh were assigned only few discrete values (48, 13 and 13 respectively). In the cells of the 3D matrix mean concentrations of different modes of fine particles and of PM1-BC were calculated. The results were displayed in the form of XYZ bubble graph, diameters of the spheres being the fourth dimension. The results offer insight into relation between sub-micron particles concentrations and meteorological conditions on parallel time basis. The nucleation mode of nanoparticles (10-30 nm) demonstrate strong proliferation (N˜104/cm3/hour) under extreme both temperature and solar radiation while air moisture remains moderate. The effect is less obvious for Aitken mode (30-70 nm) and fades gradually away for fine particles (100-800 nm, N˜103/cm3/hour). Particles PM1-BC (≤ 1000 nm, Cm ˜1 μg/m3/hour), measured by MAAP, show considerable affinity to low visibility and high humidity but the overall picture persists, what may serve as a proof of equivalence of the measuring procedures.
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)
Self-Nowcast Model of extreme precipitation events for operational meteorology
NASA Astrophysics Data System (ADS)
França, G. B.; de Almeida, M. V.; Rosette, A. C.
2015-10-01
Nowadays many social activities require short-term (one to two hours) and local area forecasts of extreme weather. In particular, air traffic systems have been studying how to minimize the impact of meteorological events, such as turbulence, wind shear, ice, and heavy rain, which are related to the presence of convective systems during all flight phases. This paper presents an alternative self-nowcast model, based on neural network techniques, to produce short-term and local-specific forecasts of extreme meteorological events in the area of the landing and take-off region of Galeão, the principal airport in Rio de Janeiro, Brazil. Twelve years of data were used for neural network training and validation. Data are originally from four sources: (1) hourly meteorological observations from surface meteorological stations at five airports distributed around the study area, (2) atmospheric profiles collected twice a day at the meteorological station at Galeão Airport, (3) rain rate data collected from a network of twenty-nine rain gauges in the study area; and (4) lightning data regularly collected by national detection networks. An investigation was done about the capability of a neural network to produce early warning signs - or as a nowcasting tool - for extreme meteorological events. The self-nowcast model was validated using results from six categorical statistics, indicated in parentheses for forecasts of the first, second, and third hours, respectively, namely: proportion correct (0.98, 0.96, and 0.94), bias (1.37, 1.48, and 1.83), probability of detection (0.84, 0.80, and 0.76), false-alarm ratio (0.38, 0.46, and 0.58), and threat score (0.54, 0.47, and 0.37). Possible sources of error related to the validation procedure are discussed. Two key points have been identified in which there is a possibility of error: i.e., subjectivity on the part of the meteorologist making the observation, and a rain gauge measurement error of about 20 % depending on wind speed. The latter was better demonstrated when lightning data were included in the validation. The validation showed that the proposed model's performance was quite encouraging for the first and second hours.
Computer Training for Entrepreneurial Meteorologists.
NASA Astrophysics Data System (ADS)
Koval, Joseph P.; Young, George S.
2001-05-01
Computer applications of increasing diversity form a growing part of the undergraduate education of meteorologists in the early twenty-first century. The advent of the Internet economy, as well as a waning demand for traditional forecasters brought about by better numerical models and statistical forecasting techniques has greatly increased the need for operational and commercial meteorologists to acquire computer skills beyond the traditional techniques of numerical analysis and applied statistics. Specifically, students with the skills to develop data distribution products are in high demand in the private sector job market. Meeting these demands requires greater breadth, depth, and efficiency in computer instruction. The authors suggest that computer instruction for undergraduate meteorologists should include three key elements: a data distribution focus, emphasis on the techniques required to learn computer programming on an as-needed basis, and a project orientation to promote management skills and support student morale. In an exploration of this approach, the authors have reinvented the Applications of Computers to Meteorology course in the Department of Meteorology at The Pennsylvania State University to teach computer programming within the framework of an Internet product development cycle. Because the computer skills required for data distribution programming change rapidly, specific languages are valuable for only a limited time. A key goal of this course was therefore to help students learn how to retrain efficiently as technologies evolve. The crux of the course was a semester-long project during which students developed an Internet data distribution product. As project management skills are also important in the job market, the course teamed students in groups of four for this product development project. The success, failures, and lessons learned from this experiment are discussed and conclusions drawn concerning undergraduate instructional methods for computer applications in meteorology.
Planetary entry, descent, and landing technologies
NASA Astrophysics Data System (ADS)
Pichkhadze, K.; Vorontsov, V.; Polyakov, A.; Ivankov, A.; Taalas, P.; Pellinen, R.; Harri, A.-M.; Linkin, V.
2003-04-01
Martian meteorological lander (MML) is intended for landing on the Martian surface in order to monitor the atmosphere at landing point for one Martian year. MMLs shall become the basic elements of a global network of meteorological mini-landers, observing the dynamics of changes of the atmospheric parameters on the Red Planet. The MML main scientific tasks are as follows: (1) Study of vertical structure of the Martian atmosphere throughout the MML descent; (2) On-surface meteorological observations for one Martian year. One of the essential factors influencing the lander's design is its entry, descent, and landing (EDL) sequence. During Phase A of the MML development, five different options for the lander's design were carefully analyzed. All of these options ensure the accomplishment of the above-mentioned scientific tasks with high effectiveness. CONCEPT A (conventional approach): Two lander options (with a parachute system + airbag and an inflatable airbrake + airbag) were analyzed. They are similar in terms of fulfilling braking phases and completely analogous in landing by means of airbags. CONCEPT B (innovative approach): Three lander options were analyzed. The distinguishing feature is the presence of inflatable braking units (IBU) in their configurations. SELECTED OPTION (innovative approach): Incorporating a unique design approach and modern technologies, the selected option of the lander represents a combination of the options analyzed in the framework of Concept B study. Currently, the selected lander option undergoes systems testing (Phase D1). Several MMLs can be delivered to Mars in frameworks of various missions as primary or piggybacking payload: (1) USA-led "Mars Scout" (2007); (2) France-led "NetLander" (2007/2009); (3) Russia-led "Mars-Deimos-Phobos sample return" (2007); (4) Independent mission (currently under preliminary study); etc.
Colombo, Nicola; Gruber, Stephan; Martin, Maria; Malandrino, Mery; Magnani, Andrea; Godone, Danilo; Freppaz, Michele; Fratianni, Simona; Salerno, Franco
2018-10-15
Three hypotheses exist to explain how meteorological variables drive the amount and concentration of solute-enriched water from rock glaciers: (1) Warm periods cause increased subsurface ice melt, which releases solutes; (2) rain periods and the melt of long-lasting snow enhance dilution of rock-glacier outflows; and (3) percolation of rain through rock glaciers facilitates the export of solutes, causing an opposite effect as that described in hypothesis (2). This lack of detailed understanding likely exists because suitable studies of meteorological variables, hydrologic processes and chemical characteristics of water bodies downstream from rock glaciers are unavailable. In this study, a rock-glacier pond in the North-Western Italian Alps was studied on a weekly basis for the ice-free seasons 2014 and 2015 by observing the meteorological variables (air temperature, snowmelt, rainfall) assumed to drive the export of solute-enriched waters from the rock glacier and the hydrochemical response of the pond (water temperature as a proxy of rock-glacier discharge, stable water isotopes, major ions and selected trace elements). An intra-seasonal pattern of increasing solute export associated with higher rock-glacier discharge was found. Specifically, rainfall, after the winter snowpack depletion and prolonged periods of atmospheric temperature above 0 °C, was found to be the primary driver of solute export from the rock glacier during the ice-free season. This occurs likely through the flushing of isotopically- and geochemically-enriched icemelt, causing concomitant increases in the rock-glacier discharge and the solute export (SO 4 2- , Mg 2+ , Ca 2+ , Ni, Mn, Co). Moreover, flushing of microbially-active sediments can cause increases in NO 3 - export. Copyright © 2018 Elsevier B.V. All rights reserved.
a Map Mash-Up Application: Investigation the Temporal Effects of Climate Change on Salt Lake Basin
NASA Astrophysics Data System (ADS)
Kirtiloglu, O. S.; Orhan, O.; Ekercin, S.
2016-06-01
The main purpose of this paper is to investigate climate change effects that have been occurred at the beginning of the twenty-first century at the Konya Closed Basin (KCB) located in the semi-arid central Anatolian region of Turkey and particularly in Salt Lake region where many major wetlands located in and situated in KCB and to share the analysis results online in a Web Geographical Information System (GIS) environment. 71 Landsat 5-TM, 7-ETM+ and 8-OLI images and meteorological data obtained from 10 meteorological stations have been used at the scope of this work. 56 of Landsat images have been used for extraction of Salt Lake surface area through multi-temporal Landsat imagery collected from 2000 to 2014 in Salt lake basin. 15 of Landsat images have been used to make thematic maps of Normalised Difference Vegetation Index (NDVI) in KCB, and 10 meteorological stations data has been used to generate the Standardized Precipitation Index (SPI), which was used in drought studies. For the purpose of visualizing and sharing the results, a Web GIS-like environment has been established by using Google Maps and its useful data storage and manipulating product Fusion Tables which are all Google's free of charge Web service elements. The infrastructure of web application includes HTML5, CSS3, JavaScript, Google Maps API V3 and Google Fusion Tables API technologies. These technologies make it possible to make effective "Map Mash-Ups" involving an embedded Google Map in a Web page, storing the spatial or tabular data in Fusion Tables and add this data as a map layer on embedded map. The analysing process and map mash-up application have been discussed in detail as the main sections of this paper.
NASA Astrophysics Data System (ADS)
Chen, Bing; Stein, Ariel F.; Castell, Nuria; de la Rosa, Jesus D.; Sanchez de la Campa, Ana M.; Gonzalez-Castanedo, Yolanda; Draxler, Roland R.
2012-03-01
Arsenic is a toxic element for human health. Consequently, a mean annual target level for arsenic at 6 ng m-3 in PM10 was established by the European Directive 2004/107/CE to take effect January 2013. Cu-smelters can contribute to one-third of total emissions of arsenic in the atmosphere. Surface observations taken near a large Cu-smelter in the city of Huelva (Spain) show hourly arsenic concentrations in the range of 0-20 ng m-3. The arsenic peaks of 20 ng m-3 are higher than values normally observed in urban areas around Europe by a factor of 10. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model has been employed to predict arsenic emissions, transport, and dispersion from the Cu-smelter. The model utilized outputs from different meteorological models and variations in the model physics options to simulate the uncertainty in the dispersion of the arsenic plume. Modeling outputs from the physics ensemble for each meteorological model driving HYSPLIT show the same number of arsenic peaks. HYSPLIT coupled with the Weather Research and Forecasting (WRF-ARW) meteorological output predicted the right number of peaks for arsenic concentration at the observation site. The best results were obtained when the WRF simulation used both four-dimensional data assimilation and surface analysis nudging. The prediction was good in local sea breeze circulations or when the flow was dominated by the synoptic scale prevailing winds. However, the predicted peak was delayed when the transport and dispersion was under the influence of an Atlantic cyclone. The calculated concentration map suggests that the plume from the Cu-smelter can cause arsenic pollution events in the city of Huelva as well as other cities and tourist areas in southwestern Spain.
NASA Astrophysics Data System (ADS)
Agrawal, Anubha; Upadhyay, Vinay K.; Sachdeva, Kamna
2011-07-01
Two important festival events were selected to assess their impacts on atmospheric chemistry by understanding settling velocity and emission time of aerosols. Using high volume sampler, aerosols were collected in a sequential manner to understand settling velocity and emission time of aerosols on a particular day. Composition and total suspended particulate load of the aerosols collected during the festivals were used as markers for strengthening the assessment. Terminal settling velocity of the aerosols were calculated using morphological and elemental compositional data, obtained from scanning electron microcopy (SEM) and energy dispersive X-ray (EDX) study. Aerosol load, black carbon, aromatic carbon and terminal velocity calculations were correlated to obtain conclusion that aerosols collected on the festival day might have been emitted prior to the festival. Settling time of aerosols collected on 17th and 19th October'09 during Diwali were found to be 36.5 (1.5 days) and 12.8 h, respectively. Carbon concentration estimated using EDX was found to be almost double in the sample collected after 2 days of the festival event. This strengthens our inference of time calculation where carbon with high concentration of load must have settled approximately after two days of the event. Settling time of aerosols collected on Holi morning and afternoon was found to be 1.7 and 24.8 h, respectively. Further, because of the small distance of 5.4 km between the meteorological station and sampling site, observed TSP values were compared with theoretical load values, calculated by using visibility values taken from the meteorological data. And it was found that both experimental and calculated values are close to each other about 50% of the times, which proves the assumption that experimental and meteorological data are comparable.
Multidisciplinary studies of the dust storm that affected Sydney in September 2009
NASA Astrophysics Data System (ADS)
De Deckker, P.
2012-04-01
A major dust storm transgressed over southeastern Australia in September 2009 and continued as far as northern Queensland [to the north], New Zealand and New Caledonia [to the east] . We analysed samples of the dust for organic compounds, its microbiological composition, pollen, trace and rare earth elements as well as Sr and Nd isotopes. Grain size analysis was also performed on some of the samples. We also obtained information on the meteorological conditions that led to the large dust plume and its pathway. Our geochemical fingerprinting allowed us to determine the origin of the dust, and this was confirmed by meteorological observations and satellite imagery. As the pathway of the dust plume went over the city of Canberra, located to the southwest of Sydney, we were able to collect samples of dust that fell with rain, and the surprise was that the geochemical composition of the dust varied with time [and dust fall], identifying that as the dust plume transgressed over the landscape, it picked up additional material that was compositionally different from its point of origin. We also compared our data with those obtained from another major dust event that affected Canberra in October 2002, and a number of important differences are noted, particularly with respect of the microbiological composition of the dust, and its chemical composition. Collaborators on this project are: Chris Munday and Gwen Allison [microbiology]: Research School of Biology, ANU; Jochen Brocks and Janet Hope [organic chemistry] and Marc Norman [inorganic geochemistry]: Research School of Earth Sciences, ANU; Tadhg O'Loingsigh and Nigel Tapper [meteorology, satellite imagery] and Sander van der Kaars [palynology]: Geography and Environmental Science, Monash University; and J.-B. Stuut [grain size analysis], NIOZ.
Robotic missions to Mars - Paving the way for humans
NASA Technical Reports Server (NTRS)
Pivirotto, D. S.; Bourke, R. D.; Cunningham, G. E.; Golombek, M. P.; Sturms, F. M.; Kahl, R. C.; Lance, N.; Martin, J. S.
1990-01-01
NASA is in the planning stages of a program leading to the human exploration of Mars. A critical element in that program is a set of robotic missions that will acquire information on the Martian environment and test critical functions (such as aerobraking) at the planet. This paper presents some history of Mars missions, as well as results of recent studies of the Mars robotic missions that are under consideration as part of the exploration program. These missions include: (1) global synoptic geochemical and climatological characterization from orbit (Mars Observer), (2) global network of small meteorological and seismic stations, (3) sample returns, (4) reconnaissance orbiters and (5) rovers.
NASA Technical Reports Server (NTRS)
Merritt, E. S. (Principal Investigator); Sabatini, R. R.; Heitkemper, L.; Hart, W. D.; Hlavka, D. L.
1976-01-01
The author has identified the following significant results. The three budget analyses show a weak correspondence between LANDSAT cloud patterns and elements of the energy and moisture budgets. It was found that a little more energy is contributed by the ground to heat the air in cloudy areas. Improvements are warranted in the budget models and data coverage necessary to describe the environment. These models can serve as a basis for more complex models of surface air heat and moisture exchanges which would utilize readily available meteorological data on a mesoscale.
10 CFR 960.5-2-3 - Meteorology.
Code of Federal Regulations, 2010 CFR
2010-01-01
... REPOSITORY Preclosure Guidelines Preclosure Radiological Safety § 960.5-2-3 Meteorology. (a) Qualifying condition. The site shall be located such that expected meteorological conditions during repository.... Prevailing meteorological conditions such that any radioactive releases to the atmosphere during repository...
Levels of selected metals in ambient air PM10 in an urban site of Zaragoza (Spain).
López, J M; Callén, M S; Murillo, R; García, T; Navarro, M V; de la Cruz, M T; Mastral, A M
2005-09-01
An assessment of the air quality of Zaragoza (Spain) was performed by determining the trace element content in airborne PM10 in a sampling campaign from July 2001 to July 2002. Samples were collected in a heavy traffic area with a high volume air sampler provided with a PM10 cutoff inlet. The levels of 16 elements (Al, Ba, Ca, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, V, and Zn) were quantified after collecting the PM10 on Teflon-coated glass fiber filters (GFF). Regarding the PM10, 32% exceedance of the proposed PM10 daily limit was obtained, some of them corresponding to summer and autumn periods. The limit values of toxic trace elements from US-EPA, WHO, and EC were not exceeded, considering Zaragoza as a moderately polluted city under the current air quality guidelines. The contribution of anthropogenic sources to atmospheric elemental levels was reflected by the high values of enrichment factors for Zn, Pb, and Cu compared to the average crustal composition. Statistical analyses also determined the contribution of different sources to the PM10, finding that vehicle traffic and anthropogenic emissions related to combustion and industrial processes were the main pollutant sources as well as natural sources associated with transport of dust from Africa for specific dates. Regarding the influence of meteorological conditions on PM10 and trace elements concentrations, it was found that calm weather conditions with low wind speed favor the PM10 collection and the pollution for trace elements, suggesting the influence of local sources.
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
NASA Astrophysics Data System (ADS)
Zhang, Yang; Hong, Chaopeng; Yahya, Khairunnisa; Li, Qi; Zhang, Qiang; He, Kebin
2016-08-01
An online-coupled meteorology-chemistry model, WRF/Chem-MADRID, has been deployed for real time air quality forecast (RT-AQF) in southeastern U.S. since 2009. A comprehensive evaluation of multi-year RT-AQF shows overall good performance for temperature and relative humidity at 2-m (T2, RH2), downward surface shortwave radiation (SWDOWN) and longwave radiation (LWDOWN), and cloud fraction (CF), ozone (O3) and fine particles (PM2.5) at surface, tropospheric ozone residuals (TOR) in O3 seasons (May-September), and column NO2 in winters (December-February). Moderate-to-large biases exist in wind speed at 10-m (WS10), precipitation (Precip), cloud optical depth (COT), ammonium (NH4+), sulfate (SO42-), and nitrate (NO3-) from the IMPROVE and SEARCH networks, organic carbon (OC) at IMPROVE, and elemental carbon (EC) and OC at SEARCH, aerosol optical depth (AOD) and column carbon monoxide (CO), sulfur dioxide (SO2), and formaldehyde (HCHO) in both O3 and winter seasons, column nitrogen dioxide (NO2) in O3 seasons, and TOR in winters. These biases indicate uncertainties in the boundary layer and cloud process treatments (e.g., surface roughness, microphysics cumulus parameterization), emissions (e.g., O3 and PM precursors, biogenic, mobile, and wildfire emissions), upper boundary conditions for all major gases and PM2.5 species, and chemistry and aerosol treatments (e.g., winter photochemistry, aerosol thermodynamics). The model shows overall good skills in reproducing the observed multi-year trends and inter-seasonal variability in meteorological and radiative variables such as T2, WS10, Precip, SWDOWN, and LWDOWN, and relatively well in reproducing the observed trends in surface O3 and PM2.5, but relatively poor in reproducing the observed column abundances of CO, NO2, SO2, HCHO, TOR, and AOD. The sensitivity simulations using satellite-constrained boundary conditions for O3 and CO show substantial improvement for both spatial distribution and domain-mean performance statistics. The model's forecasting skills for air quality can be further enhanced through improving model inputs (e.g., anthropogenic emissions for urban areas and upper boundary conditions of chemical species), meteorological forecasts (e.g., WS10, Precip) and meteorologically-dependent emissions (e.g., biogenic and wildfire emissions), and model physics and chemical treatments (e.g., gas-phase chemistry in winter conditions, cloud processes and their interactions with radiation and aerosol).
NASA Astrophysics Data System (ADS)
Kempe, Michael D.
2016-09-01
Photovoltaic devices are often sensitive to moisture and must be packaged in such a way as to limit moisture ingress for 25 years or more. Typically, this is accomplished through the use of impermeable front and backsheets (e.g., glass sheets or metal foils). However, this will still allow moisture ingress between the sheets from the edges. Attempts to hermetically seal with a glass frit or similarly welded bonds at the edge have had problems with costs and mechanical strength. Because of this, low diffusivity polyisobutylene materials filled with desiccant are typically used. Although it is well known that these materials will substantially delay moisture ingress, correlating that to outdoor exposure has been difficult. Here, we use moisture ingress measurements at different temperatures and relative humidities to find fit parameters for a moisture ingress model for an edge-seal material. Then, using meteorological data, a finite element model is used to predict the moisture ingress profiles for hypothetical modules deployed in different climates and mounting conditions, assuming no change in properties of the edge-seal as a function of aging.
NASA Technical Reports Server (NTRS)
Lambert, WInifred; Roeder, William
2007-01-01
This conference presentation describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations. The tool will include climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.
NASA Technical Reports Server (NTRS)
Crawford, Winifred
2010-01-01
This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violations.The tool includes climatologies of the 5-minute mean and peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.
A Peak Wind Probability Forecast Tool for Kennedy Space Center and Cape Canaveral Air Force Station
NASA Technical Reports Server (NTRS)
Crawford, Winifred; Roeder, William
2008-01-01
This conference abstract describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida. The peak winds are an important forecast element for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a short-range peak-wind forecast tool to assist in forecasting LCC violatioas.The tool will include climatologies of the 5-minute mean end peak winds by month, hour, and direction, and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.
A radiation and energy budget algorithm for forest canopies
NASA Astrophysics Data System (ADS)
Tunick, A.
2006-01-01
Previously, it was shown that a one-dimensional, physics-based (conservation-law) computer model can provide a useful mathematical representation of the wind flow, temperatures, and turbulence inside and above a uniform forest stand. A key element of this calculation was a radiation and energy budget algorithm (implemented to predict the heat source). However, to keep the earlier publication brief, a full description of the radiation and energy budget algorithm was not given. Hence, this paper presents our equation set for calculating the incoming total radiation at the canopy top as well as the transmission, reflection, absorption, and emission of the solar flux through a forest stand. In addition, example model output is presented from three interesting numerical experiments, which were conducted to simulate the canopy microclimate for a forest stand that borders the Blossom Point Field Test Facility (located near La Plata, Maryland along the Potomac River). It is anticipated that the current numerical study will be useful to researchers and experimental planners who will be collecting acoustic and meteorological data at the Blossom Point Facility in the near future.
NASA Astrophysics Data System (ADS)
Dunn, S. M.; Colohan, R. J. E.
1999-09-01
A snow component has been developed for the distributed hydrological model, DIY, using an approach that sequentially evaluates the behaviour of different functions as they are implemented in the model. The evaluation is performed using multi-objective functions to ensure that the internal structure of the model is correct. The development of the model, using a sub-catchment in the Cairngorm Mountains in Scotland, demonstrated that the degree-day model can be enhanced for hydroclimatic conditions typical of those found in Scotland, without increasing meteorological data requirements. An important element of the snow model is a function to account for wind re-distribution. This causes large accumulations of snow in small pockets, which are shown to be important in sustaining baseflows in the rivers during the late spring and early summer, long after the snowpack has melted from the bulk of the catchment. The importance of the wind function would not have been identified using a single objective function of total streamflow to evaluate the model behaviour.
AWE: Aviation Weather Data Visualization Environment
NASA Technical Reports Server (NTRS)
Spirkovska, Lilly; Lodha, Suresh K.; Norvig, Peter (Technical Monitor)
2000-01-01
Weather is one of the major causes of aviation accidents. General aviation (GA) flights account for 92% of all the aviation accidents, In spite of all the official and unofficial sources of weather visualization tools available to pilots, there is an urgent need for visualizing several weather related data tailored for general aviation pilots. Our system, Aviation Weather Data Visualization Environment AWE), presents graphical displays of meteorological observations, terminal area forecasts, and winds aloft forecasts onto a cartographic grid specific to the pilot's area of interest. Decisions regarding the graphical display and design are made based on careful consideration of user needs. Integral visual display of these elements of weather reports is designed for the use of GA pilots as a weather briefing and route selection tool. AWE provides linking of the weather information to the flight's path and schedule. The pilot can interact with the system to obtain aviation-specific weather for the entire area or for his specific route to explore what-if scenarios and make "go/no-go" decisions. The system, as evaluated by some pilots at NASA Ames Research Center, was found to be useful.
The international fine aerosol networks
NASA Astrophysics Data System (ADS)
Cahill, Thomas A.
1993-04-01
The adoption by the United States of a PIXE-based protocol for its fine aerosol network, after open competitions involving numerous laboratories and methods, has encouraged cooperation with other countries possessing similar capabilities and similar needs. These informal cooperative programs, involving about a dozen countries at the end of 1991, almost all use PIXE as a major component of the analytical protocols. The University of California, Davis, Air Quality Group assisted such programs through indefinite loans of a quality assurance sampler, the IMPROVE Channel A, and analyses at no cost of a small fraction of the samples taken in a side-by-side configuration. In December 1991, the World Meteorological Organization chose a protocol essentially identical to IMPROVE for the Global Atmospheric Watch (GAW) network and began deploying units, the IMPROVE Channel A, to sites around the world. Preferred analyses include fine (less than about 2.5 μm) mass, ions by ion chromatography and elements by PIXE + PESA (or, lacking that, XRF). This paper will describe progress in both programs, giving examples of the utility of the data and projecting the future expansion of the network to about 20 GAW sites by 1994.
Understanding the Role of Biology in the Global Environment: NASA'S Mission to Planet Earth
NASA Technical Reports Server (NTRS)
Townsend, William F.
1996-01-01
NASA has long used the unique perspective of space as a means of expanding our understanding of how the Earth's environment functions. In particular, the linkages between land, air, water, and life-the elements of the Earth system-are a focus for NASA's Mission to Planet Earth. This approach, called Earth system science, blends together fields like meteorology, biology, oceanography, and atmospheric science. Mission to Planet Earth uses observations from satellites, aircraft, balloons, and ground researchers as the basis for analysis of the elements of the Earth system, the interactions between those elements, and possible changes over the coming years and decades. This information is helping scientists improve our understanding of how natural processes affect us and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, an enhanced ability to predict how the climate will change in the future. NASA has designed Mission to Planet Earth to focus on five primary themes: Land Cover and Land Use Change; Seasonal to Interannual Climate Prediction; Natural Hazards; Long-Term Climate Variability; and Atmosphere Ozone.
NASA Astrophysics Data System (ADS)
Bezrukova, Natalia A.; Jeck, Richard K.; Khalili, Marat F.; Minina, Ludmila S.; Naumov, Alexander Ya.; Stulov, Evgeny A.
2006-11-01
This work is a continuation of the previous climatological study of freezing precipitation and rime over the USSR territory [ Bezrukova, N.A., Minina, L.S., Naumov, A.Ya., 2000. Freezing precipitation climatology in the former European USSR. Proceedings of the 13th International Conference on Clouds and Precipitation, pp.737-739, Reno, Nevada, USA, 14-18 August 2000; Bezrukova, N.A., Jeck, R.K., Minina, L.S., Khalili, M.F., Stulov, E.A., 2004. 10-year Statistics on Freezing Precipitation across the former USSR from surface weather observations. Proceedings of the 14th International Conference on Clouds and Precipitation, pp.731-734, Bologna, Italy, 19-23 August 2004.] aimed at creating an atlas of the frequency of these phenomena. This study gives considerable information about and a statistical analysis of freezing precipitation and rime events observed over the territory of the former USSR during a decade (1981-1990) and over the European territory of the USSR during two decades (1971-1990). This paper intends to draw the attention of the reader to the atlas and statistics by showing some interesting points. The authors used the data provided by the ground-based weather stations involved in the international exchange of meteorological data. The USSR network's Monthly Meteorological Tables (1971-1990) [Monthly Meteorological Tables, 1971-1990. Part 1, Novosibirsk-Obninsk. (in Russian).] comprising selected daily ground-based meteorological observations from more than 220 stations served as a basis for the analysis. All the types of freezing precipitation (FP) events were given as WMO Codes 56, 57, 66, 67, 24 and freezing fog (FF) deposited rime as WMO Codes 48, 49. The entire territory was divided into six major regions: the Arctic, the European part of the USSR, the Trans-Caucasus, Central Asia, Siberia, and the Far East. The frequency and distribution of events by regions versus temperature, atmospheric pressure, clouds base height, and some other meteorological parameters concerned were obtained. Climatic maps of annual mean, monthly mean, and seasonal mean occurrences of FP and FF were constructed for these regions. The study also analyzes the space-time variability of monthly mean ice-coating duration in hours for the 20-year period of 1971-1990 as observed at over 80 stations in the European part of the USSR (ET), and climatic maps of annual mean and monthly mean ice coating duration for the ET are constructed. The correlation between ice coating duration and height has been evaluated.
NASA Astrophysics Data System (ADS)
Bhattacharya, Biswa; Tohidul Islam, Md.
2014-05-01
This research focuses on the flood risk of the Haor region in the north-eastern part of Bangladesh. The prediction of the hydrological variables at different spatial and temporal scales in the Haor region is dependent on the influence of several upstream rivers in the Meghalaya catchment in India. Limitation in hydro-meteorological data collection and data sharing issues between the two countries dominate the feasibility of hydrological studies, particularly for near-realtime predictions. One of the possible solutions seems to be in making use of the variety of satellite based and meteorological model products for rainfall. The abundance of a variety of rainfall products provides a good basis of hydrological modelling of a part of the Ganges and Brahmaputra basin. In this research the TRMM data and rainfall forecasts from ECMWF have been compared with the scarce rain gauge data from the upstream Meghalaya catchment. Subsequently, the TRMM data and rainfall forecasts from ECMWF have been used as the meteorological input to a rainfall-runoff model of the Meghalaya catchment. The rainfall-runoff model of Meghalaya has been developed using the DEM data from SRTM. The generated runoff at the outlet of Meghalaya has been used as the upstream boundary condition in the existing rainfall-runoff model of the Haor region. The simulation results have been compared with the existing results based on simulations without any information of the rainfall-runoff in the upstream Meghalaya catchment. The comparison showed that the forecasting lead time has been substantially increased. As per the existing results the forecasting lead time at a number of locations in the catchment was about 6 to 8 hours. With the new results the forecasting lead time has gone up, with different levels of accuracy, to about 24 hours. This additional lead time will be highly beneficial in managing flood risk of the Haor region of Bangladesh. The research shows that satellite based rainfall products and rainfall forecasts from meteorological models can be very useful in flood risk management, particularly for data scarce regions and/or transboundary regions with data sharing issues. Keywords: flood risk management, TRMM, ECMWF, flood forecasting, Haor, Bangladesh. Abbreviations: TRMM: Tropical Rainfall Measuring Mission ECMWF: European Centre for Medium-Range Weather Forecasts DEM: Digital Elevation Model SRTM: Shuttle Radar Topography Mission
Comparing interpolation techniques for annual temperature mapping across Xinjiang region
NASA Astrophysics Data System (ADS)
Ren-ping, Zhang; Jing, Guo; Tian-gang, Liang; Qi-sheng, Feng; Aimaiti, Yusupujiang
2016-11-01
Interpolating climatic variables such as temperature is challenging due to the highly variable nature of meteorological processes and the difficulty in establishing a representative network of stations. In this paper, based on the monthly temperature data which obtained from the 154 official meteorological stations in the Xinjiang region and surrounding areas, we compared five spatial interpolation techniques: Inverse distance weighting (IDW), Ordinary kriging, Cokriging, thin-plate smoothing splines (ANUSPLIN) and Empirical Bayesian kriging(EBK). Error metrics were used to validate interpolations against independent data. Results indicated that, the ANUSPLIN performed best than the other four interpolation methods.
Remote sensing for control of tsetse flies
NASA Technical Reports Server (NTRS)
Giddings, L. E.
1976-01-01
Remotely sensed information is discussed which has potential for aiding in the control or eradication of tsetse flies. Data are available from earth resources meteorological, and manned satellites, from airborne sensors, and possibly from data collection platforms. A new zone discrimination technique, based on data from meteorological satellites may also allow the identification of zones hospitable to one or another species of tsetse. For background, a review is presented of the vegetation of Tanzania and Zanzibar, and illustrations presented of automatic processing of data from these areas. In addition, a review is presented of the applicability of temperature data to tsetse areas.
NASA Technical Reports Server (NTRS)
Susko, M.; Hill, C. K.; Kaufman, J. W.
1974-01-01
The quantitative estimates are presented of pollutant concentrations associated with the emission of the major combustion products (HCl, CO, and Al2O3) to the lower atmosphere during normal launches of the space shuttle. The NASA/MSFC Multilayer Diffusion Model was used to obtain these calculations. Results are presented for nine sets of typical meteorological conditions at Kennedy Space Center, including fall, spring, and a sea-breeze condition, and six sets at Vandenberg AFB. In none of the selected typical meteorological regimes studied was a 10-min limit of 4 ppm exceeded.
NASA Technical Reports Server (NTRS)
Heitkotter, Robert H
1956-01-01
A flight investigation of two Nike-Deacon (DAN) two-stage solid-propellant rocket vehicles indicated satisfactory performance may be expected from the DAN meteorological sounding rocket. Peak altitudes of 356,000 and 350,000 feet, respectively, were recorded for the two flight tests when both vehicles were launched from sea level at an elevation angle of 75 degrees. Performance calculations based on flight-test results show that altitudes between 358,000 feet and 487,000 feet may be attained with payloads varying between 60 pounds and 10 pounds.
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.
Meteorology Products - Naval Oceanography Portal
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Comparison of Earth Science Achievement between Animation-Based and Graphic-Based Testing Designs
ERIC Educational Resources Information Center
Wu, Huang-Ching; Chang, Chun-Yen; Chen, Chia-Li D.; Yeh, Ting-Kuang; Liu, Cheng-Chueh
2010-01-01
This study developed two testing devices, namely the animation-based test (ABT) and the graphic-based test (GBT) in the area of earth sciences covering four domains that ranged from astronomy, meteorology, oceanography to geology. Both the students' achievements of and their attitudes toward ABT compared to GBT were investigated. The purposes of…
Edge Detection Method Based on Neural Networks for COMS MI Images
NASA Astrophysics Data System (ADS)
Lee, Jin-Ho; Park, Eun-Bin; Woo, Sun-Hee
2016-12-01
Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.
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.
The short-term association between meteorological factors and mumps in Jining, China.
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.
NASA Astrophysics Data System (ADS)
Herath, Imali Kaushalya; Ye, Xuchun; Wang, Jianli; Bouraima, Abdel-Kabirou
2018-02-01
Reference evapotranspiration (ETr) is one of the important parameters in the hydrological cycle. The spatio-temporal variation of ETr and other meteorological parameters that influence ETr were investigated in the Jialing River Basin (JRB), China. The ETr was estimated using the CROPWAT 8.0 computer model based on the Penman-Montieth equation for the period 1964-2014. Mean temperature (MT), relative humidity (RH), sunshine duration (SD), and wind speed (WS) were the main input parameters of CROPWAT while 12 meteorological stations were evaluated. Linear regression and Mann-Kendall methods were applied to study the spatio-temporal trends while the inverse distance weighted (IDW) method was used to identify the spatial distribution of ETr. Stepwise regression and partial correlation methods were used to identify the meteorological variables that most significantly influenced the changes in ETr. The highest annual ETr was found in the northern part of the basin, whereas the lowest rate was recorded in the western part. In the autumn, the highest ETr was recorded in the southeast part of JRB. The annual ETr reflected neither significant increasing nor decreasing trends. Except for the summer, ETr is slightly increasing in other seasons. The MT significantly increased whereas SD and RH were significantly decreased during the 50-year period. Partial correlation and stepwise regression methods found that the impact of meteorological parameters on ETr varies on an annual and seasonal basis while SD, MT, and RH contributed to the changes of annual and seasonal ETr in the JRB.
NASA Astrophysics Data System (ADS)
Rockwell, A.; Clark, R. D.; Stevermer, A.
2017-12-01
The National Center for Atmospheric Research Earth Observing Laboratory, Millersville University and The COMET Program are collaborating to produce a series of nine online modules on the the topic of meteorological instrumentation and measurements. These interactive, multimedia educational modules can be integrated into undergraduate and graduate meteorology courses on instrumentation, measurement science, and observing systems to supplement traditional pedagogies and enhance blended instruction. These freely available and open-source training tools are designed to supplement traditional pedagogies and enhance blended instruction. Three of the modules are now available and address the theory and application of Instrument Performance Characteristics, Meteorological Temperature Instrumentation and Measurements, and Meteorological Pressure Instrumentation and Measurements. The content of these modules is of the highest caliber as it has been developed by scientists and engineers who are at the forefront of the field of observational science. Communicating the availability of these unique and influential educational resources with the community is of high priority. These modules will have a profound effect on the atmospheric observational sciences community by fulfilling a need for contemporary, interactive, multimedia guided education and training modules integrating the latest instructional design and assessment tools in observational science. Thousands of undergraduate and graduate students will benefit, while course instructors will value a set of high quality modules to use as supplements to their courses. The modules can serve as an alternative to observational research training and fill the void between field projects or assist those schools that lack the resources to stage a field- or laboratory-based instrumentation experience.
NASA Astrophysics Data System (ADS)
Andersen, Hendrik; Cermak, Jan
2015-04-01
This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.
NASA Astrophysics Data System (ADS)
You, Ting; Wu, Renguang; Huang, Gang
2018-02-01
We compared the regional synoptic patterns and local meteorological conditions during persistent and non-persistent pollution events in Beijing using US NCEP-Department of Energy reanalysis outputs and observations from meteorological stations. The analysis focused on the impacts of high-frequency (period < 90 days) variations in meteorological conditions on persistent pollution events (those lasting for at least 3 days). Persistent pollution events tended to occur in association with slow-moving weather systems producing stagnant weather conditions, whereas rapidly moving weather systems caused a dramatic change in the local weather conditions so that the pollution event was short-lived. Although Beijing was under the influence of anomalous southerly winds in all four seasons during pollution events, notable differences were identified in the regional patterns of sea-level pressure and local anomalies in relative humidity among persistent pollution events in different seasons. A region of lower pressure was present to the north of Beijing in spring, fall, and winter, whereas regions of lower and higher pressures were observed northwest and southeast of Beijing, respectively, in summer. The relative humidity near Beijing was higher in fall and winter, but lower in spring and summer. These differences may explain the seasonal dependence of the relationship between air pollution and the local meteorological variables. Our analysis showed that the temperature inversion in the lower troposphere played an important part in the occurrence of air pollution under stagnant weather conditions. Some results from this study are based on a limited number of events and thus require validation using more data.
NASA Astrophysics Data System (ADS)
Zhou, Jianzhong; Zhang, Hairong; Zhang, Jianyun; Zeng, Xiaofan; Ye, Lei; Liu, Yi; Tayyab, Muhammad; Chen, Yufan
2017-07-01
An accurate flood forecasting with long lead time can be of great value for flood prevention and utilization. This paper develops a one-way coupled hydro-meteorological modeling system consisting of the mesoscale numerical weather model Weather Research and Forecasting (WRF) model and the Chinese Xinanjiang hydrological model to extend flood forecasting lead time in the Jinshajiang River Basin, which is the largest hydropower base in China. Focusing on four typical precipitation events includes: first, the combinations and mode structures of parameterization schemes of WRF suitable for simulating precipitation in the Jinshajiang River Basin were investigated. Then, the Xinanjiang model was established after calibration and validation to make up the hydro-meteorological system. It was found that the selection of the cloud microphysics scheme and boundary layer scheme has a great impact on precipitation simulation, and only a proper combination of the two schemes could yield accurate simulation effects in the Jinshajiang River Basin and the hydro-meteorological system can provide instructive flood forecasts with long lead time. On the whole, the one-way coupled hydro-meteorological model could be used for precipitation simulation and flood prediction in the Jinshajiang River Basin because of its relatively high precision and long lead time.
Effects of Meteorological Data Quality on Snowpack Modeling
NASA Astrophysics Data System (ADS)
Havens, S.; Marks, D. G.; Robertson, M.; Hedrick, A. R.; Johnson, M.
2017-12-01
Detailed quality control of meteorological inputs is the most time-intensive component of running the distributed, physically-based iSnobal snow model, and the effect of data quality of the inputs on the model is unknown. The iSnobal model has been run operationally since WY2013, and is currently run in several basins in Idaho and California. The largest amount of user input during modeling is for the quality control of precipitation, temperature, relative humidity, solar radiation, wind speed and wind direction inputs. Precipitation inputs require detailed user input and are crucial to correctly model the snowpack mass. This research applies a range of quality control methods to meteorological input, from raw input with minimal cleaning, to complete user-applied quality control. The meteorological input cleaning generally falls into two categories. The first is global minimum/maximum and missing value correction that could be corrected and/or interpolated with automated processing. The second category is quality control for inputs that are not globally erroneous, yet are still unreasonable and generally indicate malfunctioning measurement equipment, such as temperature or relative humidity that remains constant, or does not correlate with daily trends observed at nearby stations. This research will determine how sensitive model outputs are to different levels of quality control and guide future operational applications.
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.
Syllabi for Instruction in Agricultural Meteorology.
ERIC Educational Resources Information Center
De Villiers, G. D. B.; And Others
A working group of the Commission for Agricultural Meteorology has prepared this report to fill a need for detailed syllabi for instruction in agricultural meteorology required by different levels of personnel. Agrometeorological personnel are classified in three categories: (1) professional meteorological personnel (graduates with basic training…
This paper utilizes a two-stage clustering approach as part of an objective classification scheme designed to elucidate 03's dependence on meteorology. hen applied to ten years (1981-1990) of meteorological data for Birmingham, Alabama, the classification scheme identified seven ...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-09-01
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LINKING THE CMAQ AND HYSPLIT MODELING SYSTEM INTERFACE PROGRAM AND EXAMPLE APPLICATION
A new software tool has been developed to link the Eulerian-based Community Multiscale Air Quality (CMAQ) modeling system with the Lagrangian-based HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model. Both models require many of the same hourly meteorological...
Coates, Peter S.; Casazza, Michael L.; Halstead, Brian J.; Fleskes, Joseph P.; Laughlin, James A.
2011-01-01
Radar systems designed to detect avian activity at airfields are useful in understanding factors that influence the risk of bird and aircraft collisions (bird strikes). We used an avian radar system to measure avian activity at Beale Air Force Base, California, USA, during 2008 and 2009. We conducted a 2-part analysis to examine relationships among avian activity, bird strikes, and meteorological and time-dependent factors. We found that avian activity around the airfield was greater at times when bird strikes occurred than on average using a permutation resampling technique. Second, we developed generalized linear mixed models of an avian activity index (AAI). Variation in AAI was first explained by seasons that were based on average migration dates of birds at the study area. We then modeled AAI by those seasons to further explain variation by meteorological factors and daily light levels within a 24-hour period. In general, avian activity increased with decreased temperature, wind, visibility, precipitation, and increased humidity and cloud cover. These effects differed by season. For example, during the spring bird migration period, most avian activity occurred before sunrise at twilight hours on clear days with low winds, whereas during fall migration, substantial activity occurred after sunrise, and birds generally were more active at lower temperatures. We report parameter estimates (i.e., constants and coefficients) averaged across models and a relatively simple calculation for safety officers and wildlife managers to predict AAI and the relative risk of bird strike based on time, date, and meteorological values. We validated model predictability and assessed model fit. These analyses will be useful for general inference of avian activity and risk assessment efforts. Further investigation and ongoing data collection will refine these inference models and improve our understanding of factors that influence avian activity, which is necessary to inform management decisions aimed at reducing risk of bird strikes.
MERINOVA: Meteorological risks as drivers of environmental innovation in agro-ecosystem management
NASA Astrophysics Data System (ADS)
Gobin, Anne; Oger, Robert; Marlier, Catherine; Van De Vijver, Hans; Vandermeulen, Valerie; Van Huylenbroeck, Guido; Zamani, Sepideh; Curnel, Yannick; Mettepenningen, Evi
2013-04-01
The BELSPO funded project 'MERINOVA' deals with risks associated with extreme weather phenomena and with risks of biological origin such as pests and diseases. The major objectives of the proposed project are to characterise extreme meteorological events, assess the impact on Belgian agro-ecosystems, characterise their vulnerability and resilience to these events, and explore innovative adaptation options to agricultural risk management. The project comprises of five major parts that reflect the chain of risks: (i) Hazard: Assessing the likely frequency and magnitude of extreme meteorological events by means of probability density functions; (ii) Impact: Analysing the potential bio-physical and socio-economic impact of extreme weather events on agro-ecosystems in Belgium using process-based modelling techniques commensurate with the regional scale; (iii) Vulnerability: Identifying the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (iv) Risk Management: Uncovering innovative risk management and adaptation options using actor-network theory and fuzzy cognitive mapping techniques; and, (v) Communication: Communicating to research, policy and practitioner communities using web-based techniques. The different tasks of the MERINOVA project require expertise in several scientific disciplines: meteorology, statistics, spatial database management, agronomy, bio-physical impact modelling, socio-economic modelling, actor-network theory, fuzzy cognitive mapping techniques. These expertises are shared by the four scientific partners who each lead one work package. The MERINOVA project will concentrate on promoting a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. Impacts developed from physically based models will not only provide information on the state of the damage at any given time, but also assist in understanding the links between different factors causing damage and determining bio-physical vulnerability. Socio-economic impacts will enlarge the basis for vulnerability mapping, risk management and adaptation options. A strong expert and end-user network will be established to help disseminating and exploiting project results to meet user needs.
Meterology-driven Prediction of RSV/RHV Incidence in Rural Nepal
Scott, Anna; Englund, Janet; Chu, Helen; Tielsch, James; Tielsch, James; Khatry, Subarna; Leclerq, Steven C; Shrestha, Laxman; Kuypers, Jane; Steinhoff, Mark C; Katz, Joanne
2017-01-01
Abstract Background Incidence of respiratory syncytial virus (RSV) and rhinovirus (RHV) varies throughout the year. We aim to quantify the relationship between weather variables (temperature, humidity, precipitation, and aerosol concentration) and disease incidence in order to quantify how outbreaks of RSV and RHV are related to seasonal or sub-seasonal meteorology, and if these relationships can predict viral outbreaks of RSV and RHV. Methods Health data were collected in a community-based, prospective randomized trial of maternal influenza immunization of pregnant women and their infants conducted in rural Nepal from 2011–2014. Adult illness episodes were defined as fever plus cough, sore throat, runny nose, and/or myalgia, with infant illness defined similarly but without fever requirement. Cases were identified through longitudinal household-based weekly surveillance. Temperature, humidity, precipitation, and fine particulate matter (PM 2.5) data come from reanalysis data products NCEP, Era-Interim, and Merra-2, which are produced by assimilating historical in-situ and satellite-based observations into a weather model. Results RSV exhibits a relationship with temperature after removing the seasonal cycle (r = -0.16, N = 208, P = 0.02), and RHV exhibits a strong relationship to daily temperature (r =-0.14, N =208, P = 0.05). When lagging meteorology by up to 15 weeks, correlations with disease count and weather improve (RSV: r_max = 0.45, P < 0.05; RHV: r_max = 0.15, P = 0.05). We use an SIR model forced by lagged meteorological variables to predict RSV and RHV, suggesting that disease burden can be predicted at lead times of weeks to months. Conclusion Meteorological variables are associated with RSV and RHV incidence in rural Nepal and can be used to drive predictive models with a lead time of several months. Disclosures J. Englund, Gilead: Consultant and Investigator, Research support Chimerix: Investigator, Research support Alios: Investigator, Research support Novavax: Investigator, Research support MedImmune: Investigator, Research support GlaxoSmithKline: Investigator, Research support
Morii, Yuta; Ohkubo, Yusaku; Watanabe, Sanae
2018-05-13
Citizen science is a powerful tool that can be used to resolve the problems of introduced species. An amateur naturalist and author of this paper, S. Watanabe, recorded the total number of Limax maximus (Limacidae, Pulmonata) individuals along a fixed census route almost every day for two years on Hokkaido Island, Japan. L. maximus is an invasive slug considered a pest species of horticultural and agricultural crops. We investigated how weather conditions were correlated to the intensity of slug activity using for the first time in ecology the recently developed statistical analyses, Bayesian regularization regression with comparisons among Laplace, Horseshoe and Horseshoe+ priors for the first time in ecology. The slug counts were compared with meteorological data from 5:00 in the morning on the day of observation (OT- and OD-models) and the day before observation (DBOD-models). The OT- and OD-models were more supported than the DBOD-models based on the WAIC scores, and the meteorological predictors selected in the OT-, OD- and DBOD-models were different. The probability of slug appearance was increased on mornings with higher than 20-year-average humidity (%) and lower than average wind velocity (m/s) and precipitation (mm) values in the OT-models. OD-models showed a pattern similar to OT-models in the probability of slug appearance, but also suggested other meteorological predictors for slug activities; positive effect of solar radiation (MJ) for example. Five meteorological predictors, mean and highest temperature (°C), wind velocity (m/s), precipitation amount (mm) and atmospheric pressure (hPa), were selected as the effective factors for the counts in the DBOD-models. Therefore, the DBOD-models will be valuable for the prediction of slug activity in the future, much like a weather forecast. Copyright © 2018 Elsevier B.V. All rights reserved.
Development of an analysis tool for cloud base height and visibility
NASA Astrophysics Data System (ADS)
Umdasch, Sarah; Reinhold, Steinacker; Manfred, Dorninger; Markus, Kerschbaum; Wolfgang, Pöttschacher
2014-05-01
The meteorological variables cloud base height (CBH) and horizontal atmospheric visibility (VIS) at surface level are of vital importance for safety and effectiveness in aviation. Around 20% of all civil aviation accidents in the USA from 2003 to 2007 were due to weather related causes, around 18% of which were owing to decreased visibility or ceiling (main CBH). The aim of this study is to develop a system generating quality-controlled gridded analyses of the two parameters based on the integration of various kinds of observational data. Upon completion, the tool is planned to provide guidance for nowcasting during take-off and landing as well as for flights operated under visual flight rules. Primary input data consists of manual as well as instrumental observation of CBH and VIS. In Austria, restructuring of part of the standard meteorological stations from human observation to automatic measurement of VIS and CBH is currently in progress. As ancillary data, satellite derived products can add 2-dimensional information, e.g. Cloud Type by NWC SAF (Nowcasting Satellite Application Facilities) MSG (Meteosat Second Generation). Other useful available data are meteorological surface measurements (in particular of temperature, humidity, wind and precipitation), radiosonde, radar and high resolution topography data. A one-year data set is used to study the spatial and weather-dependent representativeness of the CBH and VIS measurements. The VERA (Vienna Enhanced Resolution Analysis) system of the Institute of Meteorology and Geophysics of the University of Vienna provides the framework for the analysis development. Its integrated "Fingerprint" technique allows the insertion of empirical prior knowledge and ancillary information in the form of spatial patterns. Prior to the analysis, a quality control of input data is performed. For CBH and VIS, quality control can consist of internal consistency checks between different data sources. The possibility of two-dimensional consistency checks has to be explored. First results in the development of quality control features and fingerprints will be shown.
New exposure-based metric approach for evaluating O3 risk to North American aspen forests
K.E. Percy; M. Nosal; W. Heilman; T. Dann; J. Sober; A.H. Legge; D.F. Karnosky
2007-01-01
The United States and Canada currently use exposure-based metrics to protect vegetation from O3. Using 5 years (1999-2003) of co-measured O3, meteorology and growth response, we have developed exposure-based regression models that predict Populus tremuloides growth change within the North American ambient...
NASA Astrophysics Data System (ADS)
Henneman, Lucas R. F.; Holmes, Heather A.; Mulholland, James A.; Russell, Armistead G.
2015-10-01
The effectiveness of air pollution regulations and controls are evaluated based on measured air pollutant concentrations. Air pollution levels, however, are highly sensitive to both emissions and meteorological fluctuations. Therefore, an assessment of the change in air pollutant levels due to emissions controls must account for these meteorological fluctuations. Two empirical methods to quantify the impact of meteorology on pollutant levels are discussed and applied to the 13-year time period between 2000 and 2012 in Atlanta, GA. The methods employ Kolmogorov-Zurbenko filters and linear regressions to detrended pollutant signals into long-term, seasonal, weekly, short-term, and white-noise components. The methods differ in how changes in weekly and holiday emissions are accounted for. Both can provide meteorological adjustments on a daily basis for future use in acute health analyses. The meteorological impact on daily signals of ozone, NOx, CO, SO2, PM2.5, and PM species are quantified. Analyses show that the substantial decreases in seasonal averages of NOx and SO2 correspond with controls implemented in the metropolitan Atlanta area. Detrending allows for the impacts of some controls to be observed with averaging times of as little as 3 months. Annual average concentrations of NOx, SO2, and CO have all fallen by at least 50% since 2000. Reductions in NOx levels, however, do not lead to uniform reductions in ozone. While average detrended summer average maximum daily average 8 h ozone (MDA8h O3) levels fell by 4% (2.2 ± 2 ppb) between 2000 and 2012, winter averages have increased by 12% (3.8 ± 1.4 ppb), providing further evidence that high ozone levels are NOx-limited and lower ozone concentrations are NOx-inhibited. High ozone days (with MDA8h O3 greater than 60 ppb) decreased both in number and in magnitude over the study period.
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Gaseous Elemental Mercury (GEM) Emissions from Snow Surfaces in Northern New York
Maxwell, J. Alexander; Holsen, Thomas M.; Mondal, Sumona
2013-01-01
Snow surface-to-air exchange of gaseous elemental mercury (GEM) was measured using a modified Teflon fluorinated ethylene propylene (FEP) dynamic flux chamber (DFC) in a remote, open site in Potsdam, New York. Sampling was conducted during the winter months of 2011. The inlet and outlet of the DFC were coupled with a Tekran Model 2537A mercury (Hg) vapor analyzer using a Tekran Model 1110 two port synchronized sampler. The surface GEM flux ranged from −4.47 ng m−2 hr−1 to 9.89 ng m−2 hr−1. For most sample periods, daytime GEM flux was strongly correlated with solar radiation. The average nighttime GEM flux was slightly negative and was not well correlated with any of the measured meteorological variables. Preliminary, empirical models were developed to estimate GEM emissions from snow surfaces in northern New York. These models suggest that most, if not all, of the Hg deposited with and to snow is reemitted to the atmosphere. PMID:23874951
Gaseous elemental mercury (GEM) emissions from snow surfaces in northern New York.
Maxwell, J Alexander; Holsen, Thomas M; Mondal, Sumona
2013-01-01
Snow surface-to-air exchange of gaseous elemental mercury (GEM) was measured using a modified Teflon fluorinated ethylene propylene (FEP) dynamic flux chamber (DFC) in a remote, open site in Potsdam, New York. Sampling was conducted during the winter months of 2011. The inlet and outlet of the DFC were coupled with a Tekran Model 2537A mercury (Hg) vapor analyzer using a Tekran Model 1110 two port synchronized sampler. The surface GEM flux ranged from -4.47 ng m(-2) hr(-1) to 9.89 ng m(-2) hr(-1). For most sample periods, daytime GEM flux was strongly correlated with solar radiation. The average nighttime GEM flux was slightly negative and was not well correlated with any of the measured meteorological variables. Preliminary, empirical models were developed to estimate GEM emissions from snow surfaces in northern New York. These models suggest that most, if not all, of the Hg deposited with and to snow is reemitted to the atmosphere.
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…
Operational on-line coupled chemical weather forecasts for Europe with WRF/Chem
NASA Astrophysics Data System (ADS)
Hirtl, Marcus; Mantovani, Simone; Krüger, Bernd C.; Flandorfer, Claudia; Langer, Matthias
2014-05-01
Air quality is a key element for the well-being and quality of life of European citizens. Air pollution measurements and modeling tools are essential for the assessment of air quality according to EU legislation. The responsibilities of ZAMG as the national weather service of Austria include the support of the federal states and the public in questions connected to the protection of the environment in the frame of advisory and counseling services as well as expert opinions. ZAMG conducts daily Air-Quality forecasts using the on-line coupled model WRF/Chem. Meteorology is simulated simultaneously with the emissions, turbulent mixing, transport, transformation, and fate of trace gases and aerosols. The emphasis of the application is on predicting pollutants over Austria. Two domains are used for the simulations: the mother domain covers Europe with a resolution of 12 km, the inner domain includes the alpine region with a horizontal resolution of 4 km; 45 model levels are used in the vertical direction. The model runs 2 times per day for a period of 72 hours and is initialized with ECMWF forecasts. On-line coupled models allow considering two-way interactions between different atmospheric processes including chemistry (both gases and aerosols), clouds, radiation, boundary layer, emissions, meteorology and climate. In the operational set-up direct-, indirect and semi-direct effects between meteorology and air chemistry are enabled. The model is running on the HPCF (High Performance Computing Facility) of the ZAMG. In the current set-up 1248 CPUs are used. As the simulations need a big amount of computing resources, a method to safe I/O-time was implemented. Every MPI task writes all its output into the shared memory filesystem of the compute nodes. Once the WRF/Chem integration is finished, all split NetCDF-files are merged and saved on the global file system. The merge-routine is based on parallel-NetCDF. With this method the model runs about 30% faster on the SGI-ICEX. Different additional external data sources can be used to improve the forecasts. Satellite measurements of the Aerosol Optical Thickness (AOT) and ground-based PM10-measurements are combined to highly-resolved initial fields using regression- and assimilation techniques. The available local emission inventories provided by the different Austrian regional governments were harmonized and are used for the model simulations. A model evaluation for a selected episode in February 2010 is presented with respect to PM10 forecasts. During that month exceedances of PM10-thresholds occurred at many measurement stations of the Austrian network. Different model runs (only model/only ground stations assimilated/satellite and ground stations assimilated) are compared to the respective measurements.
Factors influencing the spatial extent of mobile source air pollution impacts: a meta-analysis
Zhou, Ying; Levy, Jonathan I
2007-01-01
Background There has been growing interest among exposure assessors, epidemiologists, and policymakers in the concept of "hot spots", or more broadly, the "spatial extent" of impacts from traffic-related air pollutants. This review attempts to quantitatively synthesize findings about the spatial extent under various circumstances. Methods We include both the peer-reviewed literature and government reports, and focus on four significant air pollutants: carbon monoxide, benzene, nitrogen oxides, and particulate matter (including both ultrafine particle counts and fine particle mass). From the identified studies, we extracted information about significant factors that would be hypothesized to influence the spatial extent within the study, such as the study type (e.g., monitoring, air dispersion modeling, GIS-based epidemiological studies), focus on concentrations or health risks, pollutant under study, background concentration, emission rate, and meteorological factors, as well as the study's implicit or explicit definition of spatial extent. We supplement this meta-analysis with results from some illustrative atmospheric dispersion modeling. Results We found that pollutant characteristics and background concentrations best explained variability in previously published spatial extent estimates, with a modifying influence of local meteorology, once some extreme values based on health risk estimates were removed from the analysis. As hypothesized, inert pollutants with high background concentrations had the largest spatial extent (often demonstrating no significant gradient), and pollutants formed in near-source chemical reactions (e.g., nitrogen dioxide) had a larger spatial extent than pollutants depleted in near-source chemical reactions or removed through coagulation processes (e.g., nitrogen oxide and ultrafine particles). Our illustrative dispersion model illustrated the complex interplay of spatial extent definitions, emission rates, background concentrations, and meteorological conditions on spatial extent estimates even for non-reactive pollutants. Our findings indicate that, provided that a health risk threshold is not imposed, the spatial extent of impact for mobile sources reviewed in this study is on the order of 100–400 m for elemental carbon or particulate matter mass concentration (excluding background concentration), 200–500 m for nitrogen dioxide and 100–300 m for ultrafine particle counts. Conclusion First, to allow for meaningful comparisons across studies, it is important to state the definition of spatial extent explicitly, including the comparison method, threshold values, and whether background concentration is included. Second, the observation that the spatial extent is generally within a few hundred meters for highway or city roads demonstrates the need for high resolution modeling near the source. Finally, our findings emphasize that policymakers should be able to develop reasonable estimates of the "zone of influence" of mobile sources, provided that they can clarify the pollutant of concern, the general site characteristics, and the underlying definition of spatial extent that they wish to utilize. PMID:17519039
Vaughan, Catherine; Dessai, Suraje
2014-01-01
Climate services involve the generation, provision, and contextualization of information and knowledge derived from climate research for decision making at all levels of society. These services are mainly targeted at informing adaptation to climate variability and change, widely recognized as an important challenge for sustainable development. This paper reviews the development of climate services, beginning with a historical overview, a short summary of improvements in climate information, and a description of the recent surge of interest in climate service development including, for example, the Global Framework for Climate Services, implemented by the World Meteorological Organization in October 2012. It also reviews institutional arrangements of selected emerging climate services across local, national, regional, and international scales. By synthesizing existing literature, the paper proposes four design elements of a climate services evaluation framework. These design elements include: problem identification and the decision-making context; the characteristics, tailoring, and dissemination of the climate information; the governance and structure of the service, including the process by which it is developed; and the socioeconomic value of the service. The design elements are intended to serve as a guide to organize future work regarding the evaluation of when and whether climate services are more or less successful. The paper concludes by identifying future research questions regarding the institutional arrangements that support climate services and nascent efforts to evaluate them. PMID:25798197
Vaughan, Catherine; Dessai, Suraje
2014-09-01
Climate services involve the generation, provision, and contextualization of information and knowledge derived from climate research for decision making at all levels of society. These services are mainly targeted at informing adaptation to climate variability and change, widely recognized as an important challenge for sustainable development. This paper reviews the development of climate services, beginning with a historical overview, a short summary of improvements in climate information, and a description of the recent surge of interest in climate service development including, for example, the Global Framework for Climate Services, implemented by the World Meteorological Organization in October 2012. It also reviews institutional arrangements of selected emerging climate services across local, national, regional, and international scales. By synthesizing existing literature, the paper proposes four design elements of a climate services evaluation framework. These design elements include: problem identification and the decision-making context; the characteristics, tailoring, and dissemination of the climate information; the governance and structure of the service, including the process by which it is developed; and the socioeconomic value of the service. The design elements are intended to serve as a guide to organize future work regarding the evaluation of when and whether climate services are more or less successful. The paper concludes by identifying future research questions regarding the institutional arrangements that support climate services and nascent efforts to evaluate them.
NASA Astrophysics Data System (ADS)
Camarero, Lluís; Bacardit, Montserrat; de Diego, Alberto; Arana, Gorka
2017-10-01
Atmospheric deposition collected at remote, high elevation stations is representative of long-range transport of elements. Here we present time-series of Al, Fe, Ti, Mn, Zn, Ni, Cu, As, Cd and Pb deposition sampled in the Central Pyrenees at 2240 m a.s.l, representative of the fluxes of these elements over South West Europe. Trace element deposition did not show a simple trend. Rather, there was statistical evidence of several underlying factors governing the variability of the time-series recorded: seasonal cycles, trends, the effects of the amount of precipitation, climate-controlled export of dust, and changes in anthropogenic emissions. Overall, there were three main modes of variation in deposition. The first mode was related to North Atlantic Oscillation (NAO), and affected Al, Fe, Ti, Mn and Pb. We interpret this as changes in the dust export from Northern Africa under the different meteorological conditions that the NAO index indicates. The second mode was an upward trend related to a rise in the frequency of precipitation events (that also lead to an increase in the amount). More frequent events might cause a higher efficiency in the scavenging of aerosols. As, Cu and Ni responded to this. And finally, the third mode of variation was related to changes in anthropogenic emissions of Pb and Zn.
NASA Astrophysics Data System (ADS)
Salma, Imre; Maenhaut, Willy; Zemplén-Papp, Éva; Záray, Gyula
As part of an air pollution project in Budapest, aerosol samples were collected by stacked filter units and cascade impactors at an urban background site, two downtown sites, and within a road tunnel in field campaigns conducted in 1996, 1998 and 1999. Some criteria pollutants were also measured at one of the downtown sites. The aerosol samples were analysed by one or more of the following methods: instrumental neutron activation analysis, particle-induced X-ray emission analysis, a light reflection technique, gravimetry, thermal profiling carbon analysis and capillary electrophoresis. The quantities measured or derived include atmospheric concentrations of elements (from Na to U), of particulate matter, of black and elemental carbon, and total carbonaceous fraction, of some ionic species (e.g., nitrate and sulphate) in the fine ( <2 μm equivalent aerodynamic diameter, EAD) or in both coarse (10- 2 μm EAD) and fine size fractions, atmospheric concentrations of NO, NO 2, SO 2, CO and total suspended particulate matter, and meteorological parameters. The analytical results were used for characterisation of the concentration levels, elemental composition, time trends, enrichment of and relationships among the aerosol species in coarse and fine size fractions, for studying their fine-to-coarse concentration ratios, spatial and temporal variability, for determining detailed elemental mass size distributions, and for examining the extent of chemical mass closure.
NASA Astrophysics Data System (ADS)
Cammalleri, C.; Anderson, M. C.; Ciraolo, G.; Durso, G.; Kustas, W. P.; La Loggia, G.; Minacapilli, M.
2010-12-01
For open orchard and vineyard canopies containing significant fractions of exposed soil (>50%), typical of Mediterranean agricultural regions, the energy balance of the vegetation elements is strongly influenced by heat exchange with the bare soil/substrate. For these agricultural systems a "two-source" approach, where radiation and turbulent exchange between the soil and canopy elements are explicitly modelled, appears to be the only suitable methodology for reliably assessing energy fluxes. In strongly clumped canopies, the effective wind speed profile inside and below the canopy layer can strongly influence the partitioning of energy fluxes between the soil and vegetation components. To assess the impact of in-canopy wind profile on model flux estimates, an analysis of three different formulations is presented, including algorithms from Goudriaan (1977), Massman (1987) and Lalic et al. (2003). The in-canopy wind profile formulations are applied to the thermal-based two-source energy balance (TSEB) model developed by Norman et al. (1995) and modified by Kustas and Norman (1999). High resolution airborne remote sensing images, collected over an agricultural area located in the western part of Sicily (Italy) comprised primarily of vineyards, olive and citrus orchards, are used to derive all the input parameters needed to apply the TSEB. The images were acquired from June to October 2008 and include a relatively wide range of meteorological and soil moisture conditions. A preliminary sensitivity analysis of the three wind profile algorithms highlights the dependence of wind speed just above the soil/substrate to leaf area index and canopy height over the typical range of canopy properties encountered in these agricultural areas. It is found that differences among the models in wind just above the soil surface are most significant under sparse and medium fractional cover conditions (15-50%). The TSEB model heat flux estimates are compared with micro-meteorological measurements from a small aperture scintillometer and an eddy covariance tower collected over an olive orchard characterized by moderate fractional vegetation cover (≍35%) and relatively tall crop (≍3.5 m). TSEB fluxes for the 7 image acquisition dates generated using both the Massman and Goudriaan in-canopy wind profile formulations give close agreement with measured fluxes, while the Lalic et al. equations yield poor results. The Massman wind profile scheme slightly outperforms that of Goudriaan, but it requires an additional parameter accounting for the roughness sub-layer of the underlying vegetative surface. The analysis also suggests that within-canopy wind profile model discrepancies become important, in terms of impact on modelled sensible heat flux, only for sparse canopies with moderate vegetation coverage.
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,…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-01-24
... 206, Aeronautical Information and Meteorological Data Link Services AGENCY: Federal Aviation... 206, Aeronautical Information and Meteorological Data Link Services. SUMMARY: The FAA is issuing this... Information and Meteorological Data Link Services. DATES: The meeting will be held February 11-15, 2013 from 8...
NASA Astrophysics Data System (ADS)
Bieringer, Paul E.; Rodriguez, Luna M.; Vandenberghe, Francois; Hurst, Jonathan G.; Bieberbach, George; Sykes, Ian; Hannan, John R.; Zaragoza, Jake; Fry, Richard N.
2015-12-01
Accurate simulations of the atmospheric transport and dispersion (AT&D) of hazardous airborne materials rely heavily on the source term parameters necessary to characterize the initial release and meteorological conditions that drive the downwind dispersion. In many cases the source parameters are not known and consequently based on rudimentary assumptions. This is particularly true of accidental releases and the intentional releases associated with terrorist incidents. When available, meteorological observations are often not representative of the conditions at the location of the release and the use of these non-representative meteorological conditions can result in significant errors in the hazard assessments downwind of the sensors, even when the other source parameters are accurately characterized. Here, we describe a computationally efficient methodology to characterize both the release source parameters and the low-level winds (eg. winds near the surface) required to produce a refined downwind hazard. This methodology, known as the Variational Iterative Refinement Source Term Estimation (STE) Algorithm (VIRSA), consists of a combination of modeling systems. These systems include a back-trajectory based source inversion method, a forward Gaussian puff dispersion model, a variational refinement algorithm that uses both a simple forward AT&D model that is a surrogate for the more complex Gaussian puff model and a formal adjoint of this surrogate model. The back-trajectory based method is used to calculate a ;first guess; source estimate based on the available observations of the airborne contaminant plume and atmospheric conditions. The variational refinement algorithm is then used to iteratively refine the first guess STE parameters and meteorological variables. The algorithm has been evaluated across a wide range of scenarios of varying complexity. It has been shown to improve the source parameters for location by several hundred percent (normalized by the distance from source to the closest sampler), and improve mass estimates by several orders of magnitude. Furthermore, it also has the ability to operate in scenarios with inconsistencies between the wind and airborne contaminant sensor observations and adjust the wind to provide a better match between the hazard prediction and the observations.
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.
NASA Astrophysics Data System (ADS)
Karki, S.; Sultan, M.; Elkadiri, R.; Chouinard, K.
2017-12-01
Numerous occurrences of harmful algal blooms (Karenia Brevis) were reported from Southwest Florida along the coast of Charlotte County, Florida. We are developing data-driven (remote sensing, field, and meteorological data) models to accomplish the following: (1) identify the factors controlling bloom development, (2) forecast bloom occurrences, and (3) make recommendations for monitoring variables that are found to be most indicative of algal bloom occurrences and for identifying optimum locations for monitoring stations. To accomplish these three tasks we completed/are working on the following steps. Firstly, we developed an automatic system for downloading and processing of ocean color data acquired through MODIS Terra and MODIS Aqua products using SeaDAS ocean color processing software. Examples of extracted variables include: chlorophyll a (OC3M), chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel- Maritorena (GSM), sea surface temperature (SST), Secchi disk depth, euphotic depth, turbidity index, wind direction and speed, colored dissolved organic material (CDOM). Secondly we are developing a GIS database and a web-based GIS to host the generated remote sensing-based products in addition to relevant meteorological and field data. Examples of the meteorological and field inputs include: precipitation amount and rates, concentrations of nitrogen, phosphorous, fecal coliform and Dissolved Oxygen (DO). Thirdly, we are constructing and validating a multivariate regression model and an artificial neural network model to simulate past algal bloom occurrences using the compiled archival remote sensing, meteorological, and field data. The validated model will then be used to predict the timing and location of algal bloom occurrences. The developed system, upon completion, could enhance the decision making process, improve the citizen's quality of life, and strengthen the local economy.
NASA Technical Reports Server (NTRS)
Collow, Allie Marquardt; Bosilovich, Mike; Ullrich, Paul; Hoeck, Ian
2017-01-01
Extreme precipitation events can have a large impact on society through flooding that can result in property destruction, crop losses, economic losses, the spread of water-borne diseases, and fatalities. Observations indicate there has been a statistically significant increase in extreme precipitation events over the past 15 years in the Northeastern United States and other localized regions of the country have become crippled with record flooding events, for example, the flooding that occurred in the Southeast United States associated with Hurricane Matthew in October 2016. Extreme precipitation events in the United States can be caused by various meteorological influences such as extratropical cyclones, tropical cyclones, mesoscale convective complexes, general air mass thunderstorms, upslope flow, fronts, and the North American Monsoon. Reanalyses, such as the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), have become a pivotal tool to study the meteorology surrounding extreme precipitation events. Using days classified as an extreme precipitation events based on a combination of observational gauge and radar data, two techniques for the classification of these events are used to gather additional information that can be used to determine how events have changed over time using atmospheric data from MERRA-2. The first is self organizing maps, which is an artificial neural network that uses unsupervised learning to cluster like patterns and the second is an automated detection technique that searches for characteristics in the atmosphere that define a meteorological phenomena. For example, the automated detection for tropical cycles searches for a defined area of suppressed sea level pressure, alongside thickness anomalies aloft, indicating the presence of a warm core. These techniques are employed for extreme precipitation events in preselected regions that were chosen based an analysis of the climatology of precipitation.
An application of ensemble/multi model approach for wind power production forecasting
NASA Astrophysics Data System (ADS)
Alessandrini, S.; Pinson, P.; Hagedorn, R.; Decimi, G.; Sperati, S.
2011-02-01
The wind power forecasts of the 3 days ahead period are becoming always more useful and important in reducing the problem of grid integration and energy price trading due to the increasing wind power penetration. Therefore it's clear that the accuracy of this forecast is one of the most important requirements for a successful application. The wind power forecast applied in this study is based on meteorological models that provide the 3 days ahead wind data. A Model Output Statistic correction is then performed to reduce systematic error caused, for instance, by a wrong representation of surface roughness or topography in the meteorological models. For this purpose a training of a Neural Network (NN) to link directly the forecasted meteorological data and the power data has been performed. One wind farm has been examined located in a mountain area in the south of Italy (Sicily). First we compare the performances of a prediction based on meteorological data coming from a single model with those obtained by the combination of models (RAMS, ECMWF deterministic, LAMI). It is shown that the multi models approach reduces the day-ahead normalized RMSE forecast error (normalized by nominal power) of at least 1% compared to the singles models approach. Finally we have focused on the possibility of using the ensemble model system (EPS by ECMWF) to estimate the hourly, three days ahead, power forecast accuracy. Contingency diagram between RMSE of the deterministic power forecast and the ensemble members spread of wind forecast have been produced. From this first analysis it seems that ensemble spread could be used as an indicator of the forecast's accuracy at least for the first three days ahead period.
NASA Astrophysics Data System (ADS)
Chen, Hui; Wu, Wei; Liu, Hong-Bin
2018-04-01
Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.
Enhancing seasonal climate prediction capacity for the Pacific countries
NASA Astrophysics Data System (ADS)
Kuleshov, Y.; Jones, D.; Hendon, H.; Charles, A.; Cottrill, A.; Lim, E.-P.; Langford, S.; de Wit, R.; Shelton, K.
2012-04-01
Seasonal and inter-annual climate variability is a major factor in determining the vulnerability of many Pacific Island Countries to climate change and there is need to improve weekly to seasonal range climate prediction capabilities beyond what is currently available from statistical models. In the seasonal climate prediction project under the Australian Government's Pacific Adaptation Strategy Assistance Program (PASAP), we describe a comprehensive project to strengthen the climate prediction capacities in National Meteorological Services in 14 Pacific Island Countries and East Timor. The intent is particularly to reduce the vulnerability of current services to a changing climate, and improve the overall level of information available assist with managing climate variability. Statistical models cannot account for aspects of climate variability and change that are not represented in the historical record. In contrast, dynamical physics-based models implicitly include the effects of a changing climate whatever its character or cause and can predict outcomes not seen previously. The transition from a statistical to a dynamical prediction system provides more valuable and applicable climate information to a wide range of climate sensitive sectors throughout the countries of the Pacific region. In this project, we have developed seasonal climate outlooks which are based upon the current dynamical model POAMA (Predictive Ocean-Atmosphere Model for Australia) seasonal forecast system. At present, meteorological services of the Pacific Island Countries largely employ statistical models for seasonal outlooks. Outcomes of the PASAP project enhanced capabilities of the Pacific Island Countries in seasonal prediction providing National Meteorological Services with an additional tool to analyse meteorological variables such as sea surface temperatures, air temperature, pressure and rainfall using POAMA outputs and prepare more accurate seasonal climate outlooks.
Towards seasonal forecasting of malaria in India.
Lauderdale, Jonathan M; Caminade, Cyril; Heath, Andrew E; Jones, Anne E; MacLeod, David A; Gouda, Krushna C; Murty, Upadhyayula Suryanarayana; Goswami, Prashant; Mutheneni, Srinivasa R; Morse, Andrew P
2014-08-10
Malaria presents public health challenge despite extensive intervention campaigns. A 30-year hindcast of the climatic suitability for malaria transmission in India is presented, using meteorological variables from a state of the art seasonal forecast model to drive a process-based, dynamic disease model. The spatial distribution and seasonal cycles of temperature and precipitation from the forecast model are compared to three observationally-based meteorological datasets. These time series are then used to drive the disease model, producing a simulated forecast of malaria and three synthetic malaria time series that are qualitatively compared to contemporary and pre-intervention malaria estimates. The area under the Relative Operator Characteristic (ROC) curve is calculated as a quantitative metric of forecast skill, comparing the forecast to the meteorologically-driven synthetic malaria time series. The forecast shows probabilistic skill in predicting the spatial distribution of Plasmodium falciparum incidence when compared to the simulated meteorologically-driven malaria time series, particularly where modelled incidence shows high seasonal and interannual variability such as in Orissa, West Bengal, and Jharkhand (North-east India), and Gujarat, Rajastan, Madhya Pradesh and Maharashtra (North-west India). Focusing on these two regions, the malaria forecast is able to distinguish between years of "high", "above average" and "low" malaria incidence in the peak malaria transmission seasons, with more than 70% sensitivity and a statistically significant area under the ROC curve. These results are encouraging given that the three month forecast lead time used is well in excess of the target for early warning systems adopted by the World Health Organization. This approach could form the basis of an operational system to identify the probability of regional malaria epidemics, allowing advanced and targeted allocation of resources for combatting malaria in India.
Expendable Bathythermograph (XBT) Measurements in the Western Alboran Sea, October 1982
1983-08-01
aircraft, shore- based radar, and shore- based meteorological stations cooperated in an intense measurement effort. As one part of this effort USNS BARTLETT...de Castillejo (1972). Contribucion a1 Conocimiento del mar de Alboran: III. Variaciones del Remolino Anticiclonico. Boletin del Institute Espanol
Data base to compare calculations and observations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tichler, J.L.
Meteorological and climatological data bases were compared with known tritium release points and diffusion calculations to determine if calculated concentrations could replace measure concentrations at the monitoring stations. Daily tritium concentrations were monitored at 8 stations and 16 possible receptors. Automated data retrieval strategies are listed. (PSB)
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.
NASA Astrophysics Data System (ADS)
Bahi, Hicham; Rhinane, Hassan; Bensalmia, Ahmed
2016-10-01
Air temperature is considered to be an essential variable for the study and analysis of meteorological regimes and chronics. However, the implementation of a daily monitoring of this variable is very difficult to achieve. It requires sufficient of measurements stations density, meteorological parks and favourable logistics. The present work aims to establish relationship between day and night land surface temperatures from MODIS data and the daily measurements of air temperature acquired between [2011-20112] and provided by the Department of National Meteorology [DMN] of Casablanca, Morocco. The results of the statistical analysis show significant interdependence during night observations with correlation coefficient of R2=0.921 and Root Mean Square Error RMSE=1.503 for Tmin while the physical magnitude estimated from daytime MODIS observation shows a relatively coarse error with R2=0.775 and RMSE=2.037 for Tmax. A method based on Gaussian process regression was applied to compute the spatial distribution of air temperature from MODIS throughout the city of Casablanca.
Estimation of Monthly Near Surface Air Temperature Using Geographically Weighted Regression in China
NASA Astrophysics Data System (ADS)
Wang, M. M.; He, G. J.; Zhang, Z. M.; Zhang, Z. J.; Liu, X. G.
2018-04-01
Near surface air temperature (NSAT) is a primary descriptor of terrestrial environment conditions. The availability of NSAT with high spatial resolution is deemed necessary for several applications such as hydrology, meteorology and ecology. In this study, a regression-based NSAT mapping method is proposed. This method is combined remote sensing variables with geographical variables, and uses geographically weighted regression to estimate NSAT. The altitude was selected as geographical variable; and the remote sensing variables include land surface temperature (LST) and Normalized Difference vegetation index (NDVI). The performance of the proposed method was assessed by predict monthly minimum, mean, and maximum NSAT from point station measurements in China, a domain with a large area, complex topography, and highly variable station density, and the NSAT maps were validated against the meteorology observations. Validation results with meteorological data show the proposed method achieved an accuracy of 1.58 °C. It is concluded that the proposed method for mapping NSAT is very operational and has good precision.
NASA Astrophysics Data System (ADS)
Chen, K. S.; Ho, Y. T.; Lai, C. H.; Chou, Youn-Min
The events of high ozone concentrations and meteorological conditions covering the Kaohsiung metropolitan area were investigated based on data analysis and model simulation. A photochemical grid model was employed to analyze two ozone episodes in autumn (2000) and winter (2001) seasons, each covering three consecutive days (or 72 h) in the Kaohsiung City. The potential influence of the initial and boundary conditions on model performance was assessed. Model performance can be improved by separately considering the daytime and nighttime ozone concentrations on the lateral boundary conditions of the model domain. The sensitivity analyses of ozone concentrations to the emission reductions in volatile organic compounds (VOC) and nitrogen oxides (NO x) show a VOC-sensitive regime for emission reductions to lower than 30-40% VOC and 30-50% NO x and a NO x-sensitive regime for larger percentage reductions. Meteorological parameters show that warm temperature, sufficient sunlight, low wind, and high surface pressure are distinct parameters that tend to trigger ozone episodes in polluted urban areas, like Kaohsiung.
Potential sources of precipitation in Lake Baikal basin
NASA Astrophysics Data System (ADS)
Shukurov, K. A.; Mokhov, I. I.
2017-11-01
Based on the data of long-term measurements at 23 meteorological stations in the Russian part of the Lake Baikal basin the probabilities of daily precipitation with different intensity and their contribution to the total precipitation are estimated. Using the trajectory model HYSPLIT_4 for each meteorological station for the period 1948-2016 the 10-day backward trajectories of air parcels, the height of these trajectories and distribution of specific humidity along the trajectories are calculated. The average field of power of potential sources of daily precipitation (less than 10 mm) for all meteorological stations in the Russian part of the Lake Baikal basin was obtained using the CWT (concentration weighted trajectory) method. The areas have been identified from which within 10 days water vapor can be transported to the Lake Baikal basin, as well as regions of the most and least powerful potential sources. The fields of the mean height of air parcels trajectories and the mean specific humidity along the trajectories are compared with the field of mean power of potential sources.
NASA Astrophysics Data System (ADS)
Roberts, Greg; Calmer, Radiance; Sanchez, Kevin; Cayez, Grégoire; Nicoll, Kerianne; Hashimshoni, Eyal; Rosenfeld, Daniel; Ansmann, Albert; Sciare, Jean; Ovadneite, Jurgita; Bronz, Murat; Hattenberger, Gautier; Preissler, Jana; Buehl, Johannes; Ceburnis, Darius; O'Dowd, Colin
2016-04-01
Clouds are omnipresent in earth's atmosphere and constitute an important role in regulating the radiative budget of the planet. However, the response of clouds to climate change remains uncertain, in particular, with respect to aerosol-cloud interactions and feedback mechanisms between the biosphere and atmosphere. Aerosol-cloud interactions and their feedbacks are the main themes of the European project FP7 BACCHUS (Impact of Biogenic versus Anthropogenic Emissions on Clouds and Climate: towards a Holistic Understanding). The National Center for Meteorological Research (CNRM-GAME, Toulouse, France) conducted airborne experiments in Cyprus and Ireland in March and August 2015 respectively to link ground-based and satellite observations. Multiple RPAS (remotely piloted aircraft systems) were instrumented for a specific scientific focus to characterize the vertical distribution of aerosol, cloud microphysical properties, radiative fluxes, 3D wind vectors and meteorological state parameters. Flights below and within clouds were coordinated with satellite overpasses to perform 'top-down' closure of cloud micro-physical properties. Measurements of cloud condensation nuclei spectra at the ground-based site have been used to determine cloud microphyical properties using wind vectors and meteorological parameters measured by the RPAS at cloud base. These derived cloud properties have been validated by in-situ RPAS measurements in the cloud and compared to those derived by the Suomi-NPP satellite. In addition, RPAS profiles in Cyprus observed the layers of dust originating from the Arabian Peninsula and the Sahara Desert. These profiles generally show a well-mixed boundary layer and compare well with ground-based LIDAR observations.
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.