Modeling Seasonal and Weather Impacts on Cycling Count

Thesis (Master's)--University of Washington, 2016-06

Modelling the population dynamics of the Queensland fruit fly, Bactrocera (Dacus) tryoni: a cohort-based approach incorporating the effects of weather

Queensland fruit fly, Bactrocera (Dacus) tryoni (QFF) is arguably the most costly horticultural insect pest in Australia. Despite this, no model is available to describe its population dynamics and aid in its management. This paper describes a cohort-based model of the population dynamics of the Queensland fruit fly. The model is primarily driven by weather variables, and so can be used at any location where appropriate meteorological data are available. In the model, the life cycle is divided into a number of discreet stages to allow physiological processes to be defined as accurately as possible. Eggs develop and hatch into larvae, which develop into pupae, which emerge as either teneral females or males. Both females and males can enter reproductive and over-wintering life stages, and there is a trapped male life stage to allow model predictions to be compared with trap catch data. All development rates are temperature-dependent. Daily mortality rates are temperature-dependent, but may also be influenced by moisture, density of larvae in fruit, fruit suitability, and age. Eggs, larvae and pupae all have constant establishment mortalities, causing a defined proportion of individuals to die upon entering that life stage. Transfer from one immature stage to the next is based on physiological age. In the adult life stages, transfer between stages may require additional and/or alternative functions. Maximum fecundity is 1400 eggs per female per day, and maximum daily oviposition rate is 80 eggs/female per day. The actual number of eggs laid by a female on any given day is restricted by temperature, density of larva in fruit, suitability of fruit for oviposition, and female activity. Activity of reproductive females and males, which affects reproduction and trapping, decreases with rainfall. Trapping of reproductive males is determined by activity, temperature and the proportion of males in the active population. Limitations of the model are discussed. Despite these, the model provides a useful agreement with trap catch data, and allows key areas for future research to be identified. These critical gaps in the current state of knowledge exist despite over 50 years of research on this key pest. By explicitly attempting to model the population dynamics of this pest we have clearly identified the research areas that must be addressed before progress can be made in developing the model into an operational tool for the management of Queensland fruit fly. (C) 2003 Published by Elsevier B.V.

Coral bleaching following wintry weather

Extensive coral bleaching Occurred intertidally in early August 2003 in the Capricorn Bunker group (Wistari Reef, Heron and One Tree Islands; Southern Great Barrier Reef). The affected intertidal coral had been exposed to unusually cold (minimum = 13.3degreesC; wet bulb temperature = 9degreesC) and dry winds (44% relative humidity) for 2 d during predawn low tides. Coral bleached in the upper 10 cm of their branches and had less than 0.2 x 10(6) cell cm(-2) as compared with over 2.5 x 10(6), Cell cm(-2) in nonbleached areas. Dark-adapted quantum yields did not differ between symbionts in bleached and nonbleached areas. Exposing symbionts to light, however, led to greater quenching of Photosystem 11 in symbionts in the bleached coral. Bleached areas of the affected colonies had died by September 2003, with areas that were essentially covered by more than 80% living coral decreasing to less than 10% visible living coral cover. By January 2004, coral began to recover, principally from areas of colonies that were not exposed during low tide (i.e., from below dead, upper regions). These data highlight the importance of understanding local weather patterns as well as the effects of longer term trends in global climate.

A total electron content space weather study of the Nighttime Weddell Sea Anomaly of 1996/97 southern summer with TOPEX/Poseidon radar altimetry

This paper reports on a total electron content space weather study of the nighttime Weddell Sea Anomaly, overlooked by previously published TOPEX/Poseidon climate studies, and of the nighttime ionosphere during the 1996/1997 southern summer. To ascertain the morphology of spatial TEC distribution over the oceans in terms of hourly, geomagnetic, longitudinal and summer-winter variations, the TOPEX TEC, magnetic, and published neutral wind velocity data are utilized. To understand the underlying physical processes, the TEC results are combined with inclination and declination data plus global magnetic field-line maps. To investigate spatial and temporal TEC variations, geographic/magnetic latitudes and local times are computed. As results show, the nighttime Weddell Sea Anomaly is a large (∼1,600(°)2; ∼22 million km2 estimated for a steady ionosphere) space weather feature. Extending between 200°E and 300°E (geographic), it is an ionization enhancement peaking at 50°S–60°S/250°E–270°E and continuing beyond 66°S. It develops where the spacing between the magnetic field lines is wide/medium, easterly declination is large-medium (20°–50°), and inclination is optimum (∼55°S). Its development and hourly variations are closely correlated with wind speed variations. There is a noticeable (∼43%) reduction in its average area during the high magnetic activity period investigated. Southern summer nighttime TECs follow closely the variations of declination and field-line configuration and therefore introduce a longitudinal division of four (Indian, western/eastern Pacific, Atlantic). Northern winter nighttime TECs measured over a limited area are rather uniform longitudinally because of the small declination variation. TOPEX maps depict the expected strong asymmetry in TEC distribution about the magnetic dip equator.

Niveo-eolian Sediment Deposits in Coastal South Victoria Land, Antarctica: Indicators of Regional Variability in Weather and Climate

A 35 year chronology from 1965 to 2000 of the deposition of wind-blown sediment is constructed from snowpits for coastal southern Victoria Land, Antarctica. Analysis of local meteorology, contemporary eolian sedimentation, and mineralogy confirm a Victoria Valley provenance, while the presence of volcanic tephra is ascribed to an Erebus volcanic province source. Winter foelm winds associated with anticyclonic circulation are considered responsible for transporting fine-grained sediment from the snow- and ice-free Victoria Valley east toward the coast, while cyclonic storms transport tephra north along the Scott Coast. No trend could be identified in the occurrence of either tephra or wind-blown sediments sourced from the Victoria Valley and retrieved from the snowpits; excavated on the Victoria Lower and Wilson Piedmont Glaciers. We infer this to indicate that the region has not undergone a significant change in weather patterns for at least the last 35 years. Our results also confirm the McMurdo Dry Valleys as a regionally significant source of wind-blown sediment.

Impact of weather dependency on planning decisions in the australian national electricity market

A long-term planning method for the electricity market is to simulate market operation into the future. Outputs from market simulation include indicators for transmission augmentation and new generation investment. A key input to market simulations is demand forecasts. For market simulation purposes, regional demand forecasts for each half-hour interval of the forecasting horizon are required, and they must accurately represent realistic demand profiles and interregional demand relationships. In this paper, a demand model is developed to accurately model these relationships. The effects of uncertainty in weather patterns and inherent correlations between regional demands on market simulation results are presented. This work signifies the advantages of probabilistic modeling of demand levels when making market-based planning decisions.

The design of a real-time nowcasting system for localised weather

National meteorological offices are largely concerned with synoptic-scale forecasting where weather predictions are produced for a whole country for 24 hours ahead. In practice, many local organisations (such as emergency services, construction industries, forestry, farming, and sports) require only local short-term, bespoke, weather predictions and warnings. This thesis shows that the less-demanding requirements do not require exceptional computing power and can be met by a modern, desk-top system which monitors site-specific ground conditions (such as temperature, pressure, wind speed and direction, etc) augmented with above ground information from satellite images to produce `nowcasts'. The emphasis in this thesis has been towards the design of such a real-time system for nowcasting. Local site-specific conditions are monitored using a custom-built, stand alone, Motorola 6809 based sub-system. Above ground information is received from the METEOSAT 4 geo-stationary satellite using a sub-system based on a commercially available equipment. The information is ephemeral and must be captured in real-time. The real-time nowcasting system for localised weather handles the data as a transparent task using the limited capabilities of the PC system. Ground data produces a time series of measurements at a specific location which represents the past-to-present atmospheric conditions of the particular site from which much information can be extracted. The novel approach adopted in this thesis is one of constructing stochastic models based on the AutoRegressive Integrated Moving Average (ARIMA) technique. The satellite images contain features (such as cloud formations) which evolve dynamically and may be subject to movement, growth, distortion, bifurcation, superposition, or elimination between images. The process of extracting a weather feature, following its motion and predicting its future evolution involves algorithms for normalisation, partitioning, filtering, image enhancement, and correlation of multi-dimensional signals in different domains. To limit the processing requirements, the analysis in this thesis concentrates on an `area of interest'. By this rationale, only a small fraction of the total image needs to be processed, leading to a major saving in time. The thesis also proposes an extention to an existing manual cloud classification technique for its implementation in automatically classifying a cloud feature over the `area of interest' for nowcasting using the multi-dimensional signals.

Automatic processing, quality assurance and serving of real-time weather data over lightweight protocols

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Automatic processing, quality assurance and serving of real-time weather data

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Reduced dimension models for weather forecasting

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