Quantifying uncertainty in citizen weather data

The sheer volume of citizen weather data collected and uploaded to online data hubs is immense. However as with any citizen data it is difficult to assess the accuracy of the measurements. Within this project we quantify just how much data is available, where it comes from, the frequency at which it is collected, and the types of automatic weather stations being used. We also list the numerous possible sources of error and uncertainty within citizen weather observations before showing evidence of such effects in real data. A thorough intercomparison field study was conducted, testing popular models of citizen weather stations. From this study we were able to parameterise key sources of bias. Most significantly the project develops a complete quality control system through which citizen air temperature observations can be passed. The structure of this system was heavily informed by the results of the field study. Using a Bayesian framework the system learns and updates its estimates of the calibration and radiation-induced biases inherent to each station. We then show the benefit of correcting for these learnt biases over using the original uncorrected data. The system also attaches an uncertainty estimate to each observation, which would provide real world applications that choose to incorporate such observations with a measure on which they may base their confidence in the data. The system relies on interpolated temperature and radiation observations from neighbouring professional weather stations for which a Bayesian regression model is used. We recognise some of the assumptions and flaws of the developed system and suggest further work that needs to be done to bring it to an operational setting. Such a system will hopefully allow applications to leverage the additional value citizen weather data brings to longstanding professional observing networks.

AWOS in Iowa, May 21, 2009

Automated Weather Observing Systems (AWOS) collect and disseminate weather data to various sources for the primary purpose of enhancing the safety of aircraft operations in Iowa’s air transportation system. A network of 41 AWOS systems is maintained by the Iowa Department of Transportation (Iowa DOT), and strategically located at airports around Iowa to provide both geographic and airport-specific coverage. AWOS enhances aviation safety by providing critical airport weather information to pilots to be used for flight planning and in-flight decision making. The system provides real-time weather observations, including wind, visibility, current weather, sky conditions, temperature, dew point, altimeter setting, and remarks, such as density altitude and local airport conditions.

The use of earth observation techniques to improve catchment-scale pollution predictions

Remote sensing can potentially provide information useful in improving pollution transport modelling in agricultural catchments. Realisation of this potential will depend on the availability of the raw data, development of information extraction techniques, and the impact of the assimilation of the derived information into models. High spatial resolution hyperspectral imagery of a farm near Hereford, UK is analysed. A technique is described to automatically identify the soil and vegetation endmembers within a field, enabling vegetation fractional cover estimation. The aerially-acquired laser altimetry is used to produce digital elevation models of the site. At the subfield scale the hypothesis that higher resolution topography will make a substantial difference to contaminant transport is tested using the AGricultural Non-Point Source (AGNPS) model. Slope aspect and direction information are extracted from the topography at different resolutions to study the effects on soil erosion, deposition, runoff and nutrient losses. Field-scale models are often used to model drainage water, nitrate and runoff/sediment loss, but the demanding input data requirements make scaling up to catchment level difficult. By determining the input range of spatial variables gathered from EO data, and comparing the response of models to the range of variation measured, the critical model inputs can be identified. Response surfaces to variation in these inputs constrain uncertainty in model predictions and are presented. Although optical earth observation analysis can provide fractional vegetation cover, cloud cover and semi-random weather patterns can hinder data acquisition in Northern Europe. A Spring and Autumn cloud cover analysis is carried out over seven UK sites close to agricultural districts, using historic satellite image metadata, climate modelling and historic ground weather observations. Results are assessed in terms of probability of acquisition probability and implications for future earth observation missions. (C) 2003 Elsevier Ltd. All rights reserved.

Data Compilation of the Research Vessel METEOR (1964)

In 2008, the 50th anniversary of the IGY (International Geophysical Year), WDCMARE presents with this CD publication 3632 data sets in Open Access as part of the most important results from 73 cruises of the research vessel METEOR between 1964 and 1985. The archive is a coherent organized collection of published and unpublished data sets produced by scientists of all marine research disciplines who participated in Meteor expeditions, measured environmental parameters during cruises and investigated sample material post cruise in the labs of the participating institutions. In most cases, the data was gathered from the Meteor Forschungsergebnisse, published by the Deutsche Forschungsgemeinschaft (DFG). A second important data source are time series and radiosonde ascensions of more than 20 years of ships weather observations, which were provided by the Deutscher Wetterdienst, Hamburg. The final inclusion of all data into the PANGAEA information system ensures secure archiving, future updates, widespread distribution in electronic, machine-readable form with longterm access via the Internet. To produce this publication, all data sets with metadata were extracted from PANGAEA and organized in a directory structure on a CD together with a search capability.

Avaliação do Impacto das Condições Ambientais nas Operações Navais

Os diagramas de impacto de missão, baseados nos limites de segurança para a realização de operações militares, tornaram-se uma ferramenta essencial no apoio às tomadas de decisão “go / no go” no âmbito militar. Estas ferramentas são vulgarmente utilizadas pelas forças armadas, tanto no planeamento estratégico como no emprego tático de meios, sistemas e armas. Para tal, estes critérios são confrontados com observações e previsões ambientais (meteo-oceanográficas) para produzir diagramas de impacto de missão, que antecipam em horas e dias, a existência de condições favoráveis ou desfavoráveis para a realização de uma determinada missão e para a execução de operações com o emprego de armas. Para uma utilização correta e eficiente destas ferramentas, por forma a revelarem-se um sistema de apoio à decisão útil e eficaz, torna-se necessário que os critérios a utilizar estejam em concordância com os meios e tarefas realizadas. Devendo para tal, traduzir a perceção dos militares relativa aos limites das condições ambientais no desempenho das plataformas, sensores e pessoal, conquistando dessa forma a sua confiança neste tipo de ferramentas. Pretende-se assim, com esta dissertação, analisar as atuais matrizes de critérios ambientais em uso na Marinha Portuguesa, no sentido de recolher a informação necessária, para elaborar uma proposta de novas tabelas mais adaptadas aos meios e missões da Marinha Portuguesa. Paralelamente, pretende-se também avaliar a opinião, dos principais utilizadores sobre a utilização destes instrumentos bem como, sobre a ferramenta que os disponibiliza na Marinha Portuguesa, o METOCMIL. Esta investigação foi desenvolvida a partir de questionários, submetidos à componente operacional da Marinha Portuguesa, permitindo a partir da sua análise estatística, propor uma nova matriz de critérios ambientais para a construção de MID. O produto desta dissertação, apresentado no capítulo três, demonstra as conclusões retiradas, apresentando os novos diagramas de impacto propostos.

Effects of anomalous propagation conditions on weather radar observations

In this chapter our objective is to provide an overview of the effects of anomalous propagation conditions on weather radar observations, based mostly on studies performed by the authors during the last decade, summarizing results from recent publications, presentations, or unpublished material. We believe this chapter may be useful as an introductory text for graduate students, or researchers and practitioners dealing with this topic. Throughout the text a spherical symmetric atmosphere is assumed and the focus is on the occurrence of ground and sea clutter and subsequent problems for weather radar applications. Other related topics such as long-path, over-the-horizon propagation and detection of radar targets (either clutter or weather systems) at long ranges is not considered here; however readers should be aware of the potential problems these phenomena may have as range aliasing may cause these echoes appear nearer than they are ¿ for more details see the discussion about second trip echoes by Zrnic, this volume.

On the impact of humidity observations in numerical weather prediction

The impact of humidity observations on forecast skill is explored by producing a series of global forecasts using initial data derived from the ERA-40 reanalyses system, in which all humidity data have been removed during the data assimilation. The new forecasts have been compared with the original ERA-40 analyses and forecasts made from them. Both sets of forecasts show virtually identical prediction skill in the extratropics and the tropics. Differences between the forecasts are small and undergo characteristic amplification rate. There are larger differences in temperature and geopotential in the tropics but the differences are small-scale and unstructured and have no noticeable effect on the skill of the wind forecasts. The results highlight the current very limited impact of the humidity observations, used to produce the initial state, on the forecasts.

Sensitivity of large-scale atmospheric analyses to humidity observations and its impact on the global water cycle and tropical and extratropical weather systems in ERA40

Reanalysis data obtained from data assimilation are increasingly used for diagnostic studies of the general circulation of the atmosphere, for the validation of modelling experiments and for estimating energy and water fluxes between the Earth surface and the atmosphere. Because fluxes are not specifically observed, but determined by the data assimilation system, they are not only influenced by the utilized observations but also by model physics and dynamics and by the assimilation method. In order to better understand the relative importance of humidity observations for the determination of the hydrological cycle, in this paper we describe an assimilation experiment using the ERA40 reanalysis system where all humidity data have been excluded from the observational data base. The surprising result is that the model, driven by the time evolution of wind, temperature and surface pressure, is able to almost completely reconstitute the large-scale hydrological cycle of the control assimilation without the use of any humidity data. In addition, analysis of the individual weather systems in the extratropics and tropics using an objective feature tracking analysis indicates that the humidity data have very little impact on these systems. We include a discussion of these results and possible consequences for the way moisture information is assimilated, as well as the potential consequences for the design of observing systems for climate monitoring. It is further suggested, with support from a simple assimilation study with another model, that model physics and dynamics play a decisive role for the hydrological cycle, stressing the need to better understand these aspects of model parametrization. .

Equatorial Kelvin waves as revealed by EOS Microwave Limb Sounder observations and European Centre for Medium-Range Weather Forecasts analyses: Evidence for slow Kelvin waves of zonal wave number 3

[1] Temperature and ozone observations from the Microwave Limb Sounder (MLS) on the EOS Aura satellite are used to study equatorial wave activity in the autumn of 2005. In contrast to previous observations for the same season in other years, the temperature anomalies in the middle and lower tropical stratosphere are found to be characterized by a strong wave-like eastward progression with zonal wave number equal to 3. Extended empirical orthogonal function (EOF) analysis reveals that the wave 3 components detected in the temperature anomalies correspond to a slow Kelvin wave with a period of 8 days and a phase speed of 19 m/s. Fluctuations associated with this Kelvin wave mode are also apparent in ozone profiles. Moreover, as expected by linear theory, the ozone fluctuations observed in the lower stratosphere are in phase with the temperature perturbations, and peak around 20–30 hPa where the mean ozone mixing ratios have the steepest vertical gradient. A search for other Kelvin wave modes has also been made using both the MLS observations and the analyses from one experiment where MLS ozone profiles are assimilated into the European Centre for Medium-Range Weather Forecasts (ECMWF) data assimilation system via a 6-hourly 3D var scheme. Our results show that the characteristics of the wave activity detected in the ECMWF temperature and ozone analyses are in good agreement with MLS data.

Evaluation of boundary-layer type in a weather forecast model utilising long-term Doppler lidar observations

Many studies evaluating model boundary-layer schemes focus either on near-surface parameters or on short-term observational campaigns. This reflects the observational datasets that are widely available for use in model evaluation. In this paper we show how surface and long-term Doppler lidar observations, combined in a way to match model representation of the boundary layer as closely as possible, can be used to evaluate the skill of boundary-layer forecasts. We use a 2-year observational dataset from a rural site in the UK to evaluate a climatology of boundary layer type forecast by the UK Met Office Unified Model. In addition, we demonstrate the use of a binary skill score (Symmetric Extremal Dependence Index) to investigate the dependence of forecast skill on season, horizontal resolution and forecast leadtime. A clear diurnal and seasonal cycle can be seen in the climatology of both the model and observations, with the main discrepancies being the model overpredicting cumulus capped and decoupled stratocumulus capped boundary-layers and underpredicting well mixed boundary-layers. Using the SEDI skill score the model is most skillful at predicting the surface stability. The skill of the model in predicting cumulus capped and stratocumulus capped stable boundary layer forecasts is low but greater than a 24 hr persistence forecast. In contrast, the prediction of decoupled boundary-layers and boundary-layers with multiple cloud layers is lower than persistence. This process based evaluation approach has the potential to be applied to other boundary-layer parameterisation schemes with similar decision structures.