Earth system modeling, climate modeling, water resource research as well as integrated modeling (e.g., climate impact studies) require the coupling of hydrological and meteorological models. The paper presents recent concepts on such a coupling. It points out the difficulties to be solved, and provides a brief overview on recently realized couplings. Furthermore, a concept of a hydrometeorological module to couple hydrological and meteorological models is introduced. / Wasserresourcenforschung, Erdsystem- und Klimamodellierung sowie integrierte Modellierung (z.B. Klimafolgenforschung) erfordern das Koppeln von hydrologischen und meteorologischen Modellen. Dieser Artikel präsentiert Konzepte für eine solche Kopplung. Er zeigt die zu lösenden Schwierigkeiten auf und gibt einen kurzen Überblick über bisher realisierte Kopplungen. Ferner stellt er ein Konzept für einen hydrometeorologischen Moduls zur Kopplung von hydrologischen mit meteorologischen Modellen vor.

Ph.D. (Geography) / Please refer to full text to view abstract

Thesis (Ph.D.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / Due to the direct magnetic connection of the high-latitude ionosphere to the outer magnetosphere, a great deal of knowledge of the physics and properties of magnetospheric regions and the fundamental plasma processes operating within them can be learned from studying low-altitude particle measurements. In this thesis the temporal and spatial aspects of the low-altitude auroral particle precipitation are investigated using a unique set of particle flux observations from two Defense Meteorological Satellite Program (DMSP) spacecraft in the same orbit but with varying time separation. Three different topics are investigated in this study: auroral stability, the accuracy of the Newell-Meng criteria for region identification, and the relative importance of various magnetopause reconnection models. In the first part the prevalent timescales and spatial dimensions of low-altitude auroral formations are examined using both electron and ion data. It is found that spatial scales larger than 50-100 km are stable for up to 1.5 minutes, while smaller size features vary more rapidly. In the second topic we explore quantitative and qualitative aspects of the Newell-Meng criteria. The flexibility and limitations of the numerical values used are examined with case and statistical studies; all but one are found to be sufficiently robust. Additionally, an expansion of the criteria to include a distinction between open and closed magnetic field line geometries is considered. The last part concentrates on the evaluation of currently proposed models of magnetopause reconnection, based on a case study of ion and electron low-altitude particle reconnection signatures. We conclude that a unique combination of the multiple x-line and bursty single x-line reconnection models is required for a full interpretation of the data. This scenario also provides a comprehensive mechanism for the formation of the low-latitude boundary layer on both open and closed field lines. Finally, the common conclusion of all three studies is that two-point measurements add considerably to our understanding of the low-altitude auroral environment and thereby, the remote processes governing its dynamics. / 2031-01-01

He, Zhengjun. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 125-129). / Abstracts in English and Chinese. / ABSTRACT --- p.i / ACKNOWLEDGEMENTS --- p.iv / TABLE OF CONTENTS --- p.v / LIST OF FIGURES --- p.vii / LIST OF TABLES --- p.xi / NOMENCLATURE --- p.xii / Chapter Chapter 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Issues and problems --- p.2 / Chapter 1.2 --- Objectives --- p.3 / Chapter 1.3 --- Methodology --- p.3 / Chapter 1.4 --- Significance and benefits --- p.5 / Chapter 1.5 --- Organization of the thesis --- p.5 / Chapter Chapter 2 --- BACKGROUND AND LITERATURE --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Daylight data measurement --- p.7 / Chapter 2.3 --- Satellite-based models to derive illuminance --- p.9 / Chapter 2.3.1 --- Irradiance derived from satellite pixel values to illuminance (indirect approaches) --- p.9 / Chapter 2.3.1.1 --- Heliosat algorithms --- p.10 / Chapter 2.3.1.2 --- Perez et al. model --- p.20 / Chapter 2.3.1.3 --- Uetani model --- p.24 / Chapter 2.3.1.4 --- Gautier et al. model --- p.25 / Chapter 2.3.1.5 --- Janjai et al. model --- p.27 / Chapter 2.3.1.6 --- Comparison of different models --- p.28 / Chapter 2.3.1.7 --- Irradiance to illuminance using luminous efficacy models --- p.31 / Chapter 2.3.2 --- Satellite pixel values to illuminance (direct approaches) --- p.34 / Chapter 2.4 --- CIE standard skies --- p.37 / Chapter 2.5 --- Sky luminance distribution and sky types prediction using meteorological data --- p.40 / Chapter 2.6 --- Sky types and sky luminance distribution prediction using satellite images --- p.48 / Chapter 2.7 --- The needs for deriving daylight data from satellite images in Subtropical southern China --- p.51 / Chapter 2.8 --- General climate information of Hong Kong --- p.52 / Chapter Chapter 3 --- USING SATELLITE-BASED METHODS TO PREDICT DAYLIGHT ILLUMINANCE --- p.55 / Chapter 3.1 --- Introduction --- p.55 / Chapter 3.2 --- Data --- p.56 / Chapter 3.3 --- Methodology --- p.62 / Chapter 3.3.1 --- Satellite pixel value to cloud index --- p.63 / Chapter 3.3.2 --- Cloud index to global illuminance: indirect approach --- p.69 / Chapter 3.3.2.1 --- Cloud index to global irradiance --- p.69 / Chapter 3.3.2.2 --- Global irradiance to global illuminance --- p.73 / Chapter 3.3.3 --- Cloud index to global illuminance: direct approach --- p.75 / Chapter 3.4 --- Model precision and results --- p.79 / Chapter 3.4.1 --- Irradiance model precision --- p.79 / Chapter 3.4.2 --- Illuminance models precision --- p.80 / Chapter 3.4.3 --- Model performance under different seasons --- p.85 / Chapter 3.5 --- Conclusions --- p.87 / Chapter Chapter 4 --- USING SATELLITE-BASED METHOD TO PREDICT SKY TYPES --- p.89 / Chapter 4.1 --- Introduction --- p.89 / Chapter 4.2 --- Data --- p.90 / Chapter 4.3 --- CIE Standard General Sky --- p.92 / Chapter 4.4 --- Sky type prediction --- p.93 / Chapter 4.4.1 --- Sample data --- p.93 / Chapter 4.4.2 --- Assessment of other approaches --- p.97 / Chapter 4.4.3 --- Formulation of a method to predict sky conditions under subtropical context --- p.101 / Chapter 4.5 --- Model precision and results --- p.105 / Chapter 4.6 --- Conclusions --- p.116 / Chapter Chapter 5 --- CONCLUSION --- p.117 / Chapter 5.1 --- Research summary --- p.117 / Chapter 5.1.1 --- The indirect approach to derive global illuminance --- p.117 / Chapter 5.1.2 --- The direct approach to derive global illuminance --- p.118 / Chapter 5.1.3 --- Sky types prediction --- p.118 / Chapter 5.2 --- Conclusion and discussion --- p.119 / Chapter 5.3 --- Research contributions and limitations --- p.122 / Chapter 5.4 --- Needs for further research --- p.123 / BIBLIOGRAPHY / APPENDIX

PM10 (suspended particles with diameter below 10 £gm) and O3 (ozone) are the dominant air pollutants in Kao-Ping airshed, in which ozone is a secondary pollutant produced from its precursors of NOx (= NO + NO2) and HC (hydrocarbons) via complex photochemical reactions in sunlight. This study first statistically summarized the trends of ozone concentrations using box plots over recent five to six years from four and three air-quality monitoring stations in Kaohsiung City and Ping-Tung County, respectively. Then, the long-term variations of ozone concentrations were analyzed using trend formula proposed by Holland et al. (1999). Finally, multi-variable factor analysis was applied to study the relationships among the ozone concentrations with other air pollutants and meteorological parameters. Results reveal that the highest peak of ozone concentration appears in October and the second peak appears in March, while the lowest one appears in summer. Except being moderate relationships in Tzyo-Yin station, trend results show strong relationships in all other stations. Results also show that the percentage annual increase in ozone concentration in Kaohsiung City is higher than those in Kaohsiung and Ping-Tung Counties. The factor analyses reveal that the concentration of ozone is positively correlated with air temperature, wind speed and period of sunshine, while negatively correlated with concentrations of NO2, CO, NO, and NOx in the seasons of spring, autumn and winter; but negatively correlated with relative humidity in autumn. Notably, the percentage increases of ozone events in recent years should be also related to the rises of air temperature and period of sunshine, which should be watched continuously.

Over the past 2001~2005 years, the ozone concentration of Kaohsiung county had a rising trend year by year. It¡¦s one of the main reasons that air quality was bad in Kaohsiung and Pingtung Counties. In order to reach the purpose to improve the ozone and air quality effectively, we need to make the whole investigation and of the ozone precursors VOCs and NOx. In addition, the ozone concentration is also influenced by factors, such as intensity of sunshine, temperature, humidity, rainfall, and speed of wind direction, etc. This research mainly investigated the distributing of the ozone precursors of the vertical height and the photochemical ozone formation reactivity with sounding for the 22nd ¡Vthe 25th of November in the Lin-Yuan petrochemical industrial park to discuss the relation of synoptic systems and meteorological parameterization, as the reference used in controlling ozone concentration. It is known the comprehensive synoptic systems are Northeasterly Monsoon Winds type by the analysis of the meteorological parameterization. The station of fishers association was the downwind position and the station of sin-yuan elementary school was the upwind position. The sea-land breeze, that is normally low-latitude (under about 700 meters) regional wind or local circulation, causes the position change of upper and lower wind. The whole trend of ozone and speed of wind of the two stations had negative correlation obviously and the correlation was bad for the height under 500 meters. The whole trend of ozone and NMHC was negative correlation in range of 100m to 300m that was better than above 500 meters. The whole trend of ozone and NOx was negative correlation in the height of 100 meters and had no correlation in above 300 meters. It shows that correlation of O3 and NOx is relatived to source of NOx pollution and is decreased with the altitude height.

This research analyzed the weather information (temperature, wind velocity, visibility, and total cloudiness) from the Taipei and the Kaohsiung Weather Station of Central Weather Bureau, and air pollution from the Air Quality Monitoring Station of Environmental Protection Administration, Executive Yuan ( Shihlin, Shihlin, Jhongshan, Wanhua, Guting, Songshan¡A), Nanzih, Zuoying, Cianjin, and Siaogan ) to evaluate the feasibility of using visibility as the ambient air quality index by statistical analysis¡C In regard to the visibility in Taipei metropolis, the visibility between 1983~1992 showed a steady status between 5~11 kilometers. The visibility after 1993 has increased gradually between 6~16 kilometers, which indicated that the visual air quality has been improved year by year in Taipei metropolis. In regard to the visibility in Kaohsiung metropolis, the index has a trend of decreasing year by year from 10~24 kilometers to 2~12 kilometers, and the decrease was particularly obvious after 1993. Analyzing the air quality index greater than 100 in the metropolis, the visibility is categorized as the level of "poor", which means that the visibility is within 3 kilometers. When the air quality index ranges between 76~100, the visibility is categorized as the level of median, which means the visibility is within 4 kilometers. When the air quality index ranges between 50~75, the visibility is categorized as the level of "good", which means the visibility is within 7 kilometers. When the air quality index ranges between 20~49, the visibility is categorized as the level of "excellent", which means the visibility is beyond 7 kilometers.

The long-term trends of PM10, O3 and NOx concentrations were analyzed using Holland model (without meteorological-adjusted) and MM-Regression model (with meteorological-adjusted) based on the data of ten EPA air quality stations from 1997 to 2006 in Kao-Ping area. The aim of this study was to determine the impact of meteorological factors on the trends of these pollutants in Kao-Ping. The annual variations (AV) of O3 was −0.496 % in Kaohsiung county, −0.200 in Pingtung county, and 0.277 % in Kaohsiung city, showing different characteristics in Kao-Pin area. On average, the annual variations (AV) influenced by meteorological factors were: PM10: 0.205 %, O3: −0.127 %, and NOx: 0.338 %. After being adjusted by meteorological factors, the seasonal variations (SV) were about 1, indicating little seasonal change. In Kao-Ping region, the influence by meteorological factors was 9.566 %, 8.026 % and 7.351 % in PM10, O3, NOx, respectively. In total, the average influence was 8.314% in Kao-Ping region, with 7.791% in Kaohsiung city (8.481% at Cianjin, the most influenced area), 9.439% in Kaohsiung County (10.368% at Linyuan, the most influenced area), and 7.110% in Pingtung County (7.516% at Chaojhou, the most influenced area). PM10 was influenced most by meteorological factors (PM10: 9.566 %, O3: 8.026 %, NOx: 7.351 %) in Kao-Ping area.. In Kao-Ping region, the contributions by individual meteorological factors were 70.78% in wind speed, 38.23% in total cloudiness, 36.56% in sunshine hour, 19.86% in temperature, 12.40% in atmospheric pressure, 5.96% in relative humidity and 1.27% in wind direction. The influences by the wind speed were 66.62 %, 72.35 % and 72.31 % on the concentrations of PM10, O3, NOx, respectively. Wind speed was the most important factor controlling concentration trends in Kao-Ping area.

The trends of PM10, O3, NOX and NMHC concentrations were analyzed by the Holland model (without meteorological-adjusted) and the MM-Regression model (with meteorological-adjusted) base on the data of eight EPA air quality stations from 1997 to 2006 in Kaohsiung. The aim of this study was to evaluate the influence of meteorological factors on the pollutants (PM10 and O3) trends. The trends of PM10 concentrations in Kaohsiung city analyzed without meteorological-adjusted were 7.18 % at Tzuo-Yin, 3.20 % at Chien-Chin and 9.72 % at Nan-Chie. After eliminating the meteorological factors, the percent of gradual trends were 1.91 % at Tzuo-Yin, 2.92 % at Chien-Chin and 2.02 % at Nan-Chie. The trends of O3 concentrations without meteorological-adjusted were 11.42 % at Tzuo-Yin, 20.92 % at Hsiung-Kong, 42.08 % at Chien-Chin and 13.69 % at Nan-Chie. The trends of PM10 concentrations in Kaohsiung County analyzed without meteorological-adjusted were 14.96 % at Lin-yuan and 3.24 % at Jen-wu. After meteorological factors eliminating, the trend was 3.15 % at Jen-wu but the trend was -2.53 % at Lin-yuan. Meteorological factor was a primary reason that influences the PM10 concentration in recent years. The trends of O3 in Kaohsiung County without meteorological-adjusted were 18.89 % at Da-liao, 4.40 % at Jen-wu, 35.16 % at Lin-yuan and 29.98 % at Mei-nung. After meteorological factors eliminating, the trends were 1.99 % at Da-liao, 2.23 % at Jen-wu, 1.16 % at Lin-yuan and -1.16 % at Mei-nung. The results show that the influence of meteorological factors for O3 trends was more sensitive in Kaohsiung county than in Kaohsiung city. The concentration of PM10 has no significant difference (64.8 ¡V 92.3 %) in Kaohsiung city. For the concentration of O3, the similarity (78 ¡V 100 %) was extensive in Kaohsiung city because O3 could diffuse easily. O3 episodes has no significant difference as PM10 episodes in Kaohsiung city. As above-mentioned, the results show that the contributions of ambient PM10 were individually but the contributions of ambient O3 were uniform extensively.

Thesis (Ph. D.)--University of Hong Kong, 1983.