Interpretation of equatorial current meter data as internal waves

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution January 1987Garrett and Munk use linear dynamics to synthesize frequency-wavenumber energy spectra for internal waves (GM72, GM75, GM79). The GM internal wave models are horizontally isotropic, vertically symmetric, purely propagating, and universal in both time and space. This set of properties effectively eliminates all the interesting physics, since such models do not allow localized sources and sinks of energy. Thus an important step in understanding internal wave dynamics is to make measurements of deviations from the simple GM models. This thesis continues the search for deviations from the GM models. It has three advantages over earlier work: extensive data from an equatorial region, long time series (2 years), and relatively sophisticated linear internal wave models. Since the GM models are based on mid-latitude data, having data from an equatorial region which has a strong mean current system offers an opportunity to examine a region with a distinctly different basic state. The longer time series mean there is a larger statistical ensemble of realizations, making it possible to detect smaller internal wave signals. The internal wave models include several important extensions to the GM models: horizontal anisotropy and vertical asymmetry, resolution between standing modes and propagating waves, general vertical structure, and kinematic effects of mean shear flow. Also investigated are the effects of scattering on internal waves, effects that are especially strong on the equator because the buoyancy frequency variability is a factor of ten higher than at mid-latitudes. In the high frequency internal wave field considered (frequencies between .125 cph and .458 cph), several features are found that are not included in the GM models. Both the kinematic effects of a mean shear flow and the phase-locking that distinguishes standing modes from propagating waves are observed. There is a seasonal dependence in energy level of roughly 10% of the mean level. At times the wave field is zonally and vertically asymmetric, with resulting energy fluxes that are a small (4% to 10%) fraction of the maximum energy flux the internal wave field could support. The fluxes are, however, as big as many of the postulated sources of energy for the internal wave field.This work has been supported under grants from the National Science Foundation and the Office of Naval Research, grants numbered NSF-89076, ONR-88914, NSF-9l002, NSF-94971, and NSF-93661

Web-based climate information resources for malaria control in Africa

Malaria remains a major public health threat to more than 600 million Africans and its control is recognized as critical to achieving the Millennium Development Goals. The greatest burden of malaria in Africa occurs in the endemic regions where the disease pathogen is continuously present in the community. These regions are characterized by an environment that is conducive to interactions between the Anopheles mosquito, malaria parasites and human hosts, as well as housing of generally poor quality, which offers little protection from mosquito-human contact. Epidemic malaria tends to occur along the geographical margins of endemic regions, when the equilibrium between the human, parasite and mosquito vector populations is occasionally disturbed and a sharp but temporary increase in disease incidence results. When malaria control measures are inadequate, as is the case in much of sub-Saharan Africa, the disease distribution is closely linked with seasonal patterns of the climate and local environment. In the absence of good epidemiological data on malaria distribution in Africa, climate information has long been used to develop malaria risk maps that illustrate the boundaries of 'climatic suitability for endemic transmission.' The best known of these are produced by the Pan-African-based MARA Collaboration. This paper describes the development of additional malaria suitability maps which have been produced in an online, interactive format to enable temporal information (i.e., seasonality of climate conditions) to be queried and displayed along with spatial information. These maps and the seasonal information that they contain should be useful to the malaria control and health service communities for their planning and operational activities

Use of Remote Sensing for Monitoring Climate Variability for Integrated Early Warning Systems: Applications for Human Diseases and Desert Locust Management

A number of the major human infectious diseases (like malaria and dengue) and Desert Locusts that still plague the developing world are sensitive to inter-seasonal and inter-decadal changes in environment and climate. Monitoring variations in environmental conditions such as rainfall and vegetation helps decision-makers at Ministries of Agriculture and Ministries of Health to assess the risk levels of Desert Locust outbreaks or malaria epidemics. The International research institute for climate and society (IRI) has developed products based on remotely sensed data to monitor those changes and provide the information directly to the decision-makers. This paper presents recent developments which use remote sensing to monitor climate variability, environmental conditions and their impacts on the dynamics of infectious diseases (malaria) and Desert Locust outbreaks

IRI Data Library: enhancing accessibility of climate knowledge

Background: Climate variability affects a broad swath of socio-economic sectors, and if it increases or the sector becomes overly-tuned to past or present climate conditions, climate variability becomes of increasing concern to a wide range of non-climate specialists. The significant challenges to building the capacity of non-climate specialists to use climate information in research and decision-making include the difficulties in accessing relevant and timely quality-controlled data and information in formats that can be readily incorporated into specific analysis and reporting. Methods: The IRI Data Library is a facility designed to cope with these issues of information dissemination. Methods developed include Map Rooms which are designed for rapid access to needed information for particular user groups, analysis tools useful for a wide range of users (especially while training), and a metadata framework that uses semantic technologies to transform metadata from a variety of sources into a variety of standards. Results: The results are tools to merge standard climate products with GIS information (e.g. averaging climate data over the political boundaries used to geolocate health and socio-economic data), as well as simplified access/transformation of large datasets only available as collections of many files or service points elsewhere. Conclusions: The IRI Data Library is thus a key platform that makes climate and other data products more widely accessible through tool development, data organization and transformation, and data/technology transfer

An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa

Periodic epidemics of malaria are a major public health problem for many sub-Saharan African countries. Populations in epidemic prone areas have a poorly developed immunity to malaria and the disease remains life threatening to all age groups. The impact of epidemics could be minimized by prediction and improved prevention through timely vector control and deployment of appropriate drugs. Malaria Early Warning Systems are advocated as a means of improving the opportunity for preparedness and timely response. Rainfall is one of the major factors triggering epidemics in warm semi-arid and desert-fringe areas. Explosive epidemics often occur in these regions after excessive rains and, where these follow periods of drought and poor food security, can be especially severe. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization. The Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics recommended that a simple indicator of changes in epidemic risk in regions of marginal transmission, consisting primarily of rainfall anomaly maps, could provide immediate benefit to early warning efforts. In response to these recommendations, the Famine Early Warning Systems Network produced maps that combine information about dekadal rainfall anomalies, and epidemic malaria risk, available via their Africa Data Dissemination Service. These maps were later made available in a format that is directly compatible with HealthMapper, the mapping and surveillance software developed by the WHO's Communicable Disease Surveillance and Response Department. A new monitoring interface has recently been developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of the current rainfall estimates by comparing them to previous seasons and climatological averages. These resources are available at no cost to the user and are updated on a routine basis

Climate Influences on Human-Elephant Conflict in Sri Lanka

Contemporary ecological research supports focus on the preservation of habitats and the preservation of keystone species that are critical to the ecological character of the habitats. Conservation of endangered species works best with attention not only to the species but also to the needs of the people who may be adjacent to or bordering habitats. Southern Sri Lanka fall into the category of globally important biodiversity hotspots. The biggest land animal, the elephant is the keystone species in Sri Lanka outside the highlands. The population of elephants in Sri Lanka is estimated to be between 3000 and 4,000; yet there has been an alarming loss of 1000 elephants during from 1990-2003. Given its island setting and rich hydro-climatic data, Sri Lanka provides a unique opportunity to study the dynamics leading to species loss. Our work in this project was initially motivated by the practical concerns of our project partners in the Mahaweli River Basin in Sri Lanka where the human-elephant conflict was a major problem. The question that arose was: "Are the climate, water availability and river basin management practices contributing to conflict between elephants and people?" If this was indeed the case, then, could one adaptively manage the river basin, organize agricultural practices, and prioritize conflict mitigation options such as separate habitat enrichment programs? Moreover, could we propose various adaptive measures in changes if one could monitor the climate and environmental conditions and take advantage of seasonal climate predictions

Improving Decision-Making Activities for Meningitis and Malaria

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making

Climate Informatics

The impacts of present and potential future climate change will be one of the most important scientific and societal challenges in the 21st century. Given observed changes in temperature, sea ice, and sea level, improving our understanding of the climate system is an international priority. This system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. But with an ever-growing supply of climate data from satellites and environmental sensors, the magnitude of data and climate model output is beginning to overwhelm the relatively simple tools currently used to analyze them. A computational approach will therefore be indispensable for these analysis challenges. This chapter introduces the fledgling research discipline climate informatics: collaborations between climate scientists and machine learning researchers in order to bridge this gap between data and understanding. We hope that the study of climate informatics will accelerate discovery in answering pressing questions in climate science

Environmental Data and Surveillance

An overview of the IRI Data Library

Effects of supervision on tax compliance:Evidence from a field experiment in Austria

We conduct a field experiment on tax compliance, focusing on newly founded firms. As a novelty the effect of tax authorities’ supervision on timely tax payments is examined. Interestingly, results show no positive overall effect of close supervision on tax compliance