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1
Webb, Mathew, and Budiman Minasny. "A digital mapping application for quantifying and displaying air temperatures at high spatiotemporal resolutions in near real-time across Australia." PeerJ 8 (October 7, 2020): e10106. http://dx.doi.org/10.7717/peerj.10106.
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Surface air temperature (Ta) required for real-time environmental modelling applications should be spatially quantified to capture the nuances of local-scale climates. This study created near real-time air temperature maps at a high spatial resolution across Australia. This mapping is achieved using the thin plate spline interpolation in concert with a digital elevation model and ‘live’ recordings garnered from 534 telemetered Australian Bureau of Meteorology automatic weather station (AWS) sites. The interpolation was assessed using cross-validation analysis in a 1-year period using 30-min interval observation. This was then applied to a fully automated mapping system—based in the R programming language—to produce near real-time maps at sub-hourly intervals. The cross-validation analysis revealed broad similarities across the seasons with mean-absolute error ranging from 1.2 °C (autumn and summer) to 1.3 °C (winter and spring), and corresponding root-mean-square error in the range 1.6 °C to 1.7 °C. The R2 and concordance correlation coefficient (Pc ) values were also above 0.8 in each season indicating predictions were strongly correlated to the validation data. On an hourly basis, errors tended to be highest during the late afternoons in spring and summer from 3 pm to 6 pm, particularly for the coastal areas of Western Australia. The mapping system was trialled over a 21-day period from 1 June 2020 to 21 June 2020 with majority of maps completed within 28-min of AWS site observations being recorded. All outputs were displayed in a web mapping application to exemplify a real-time application of the outputs. This study found that the methods employed would be highly suited for similar applications requiring real-time processing and delivery of climate data at high spatiotemporal resolutions across a considerably large land mass.
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Woldemeskel, Fitsum, David McInerney, Julien Lerat, Mark Thyer, Dmitri Kavetski, Daehyok Shin, Narendra Tuteja, and George Kuczera. "Evaluating post-processing approaches for monthly and seasonal streamflow forecasts." Hydrology and Earth System Sciences 22, no. 12 (December 6, 2018): 6257–78. http://dx.doi.org/10.5194/hess-22-6257-2018.
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Abstract. Streamflow forecasting is prone to substantial uncertainty due to errors in meteorological forecasts, hydrological model structure, and parameterization, as well as in the observed rainfall and streamflow data used to calibrate the models. Statistical streamflow post-processing is an important technique available to improve the probabilistic properties of the forecasts. This study evaluates post-processing approaches based on three transformations – logarithmic (Log), log-sinh (Log-Sinh), and Box–Cox with λ=0.2 (BC0.2) – and identifies the best-performing scheme for post-processing monthly and seasonal (3-months-ahead) streamflow forecasts, such as those produced by the Australian Bureau of Meteorology. Using the Bureau's operational dynamic streamflow forecasting system, we carry out comprehensive analysis of the three post-processing schemes across 300 Australian catchments with a wide range of hydro-climatic conditions. Forecast verification is assessed using reliability and sharpness metrics, as well as the Continuous Ranked Probability Skill Score (CRPSS). Results show that the uncorrected forecasts (i.e. without post-processing) are unreliable at half of the catchments. Post-processing of forecasts substantially improves reliability, with more than 90 % of forecasts classified as reliable. In terms of sharpness, the BC0.2 scheme substantially outperforms the Log and Log-Sinh schemes. Overall, the BC0.2 scheme achieves reliable and sharper-than-climatology forecasts at a larger number of catchments than the Log and Log-Sinh schemes. The improvements in forecast reliability and sharpness achieved using the BC0.2 post-processing scheme will help water managers and users of the forecasting service make better-informed decisions in planning and management of water resources. Highlights. Uncorrected and post-processed streamflow forecasts (using three transformations, namely Log, Log-Sinh, and BC0.2) are evaluated over 300 diverse Australian catchments. Post-processing enhances streamflow forecast reliability, increasing the percentage of catchments with reliable predictions from 50 % to over 90 %. The BC0.2 transformation achieves substantially better forecast sharpness than the Log-Sinh and Log transformations, particularly in dry catchments.
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Susilo and E. Y. Handoko. "An Analysis of Spatio-Temporal Water Vapor Variation in the East Java using Ground Based GPS Receivers." IOP Conference Series: Earth and Environmental Science 950, no. 1 (January 1, 2022): 012085. http://dx.doi.org/10.1088/1755-1315/950/1/012085.
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Abstract Water vapor plays a critical role in the global/regional scale of weather and climate changes. Traditionally, the water vapor measurement uses radiosonde balloons which are very sparse in the distribution. The utilization of GPS as a new method for studying water vapor has been studied in several publications. This research analyzed the precipitable water vapor (PWV) based on ground-based GPS receivers in the East Java region. In the first part, the datasets are compared. The Zenith Total Delay (ZTD) from GPS processing will be compared with the Zenith Path Delay from the International GNSS Service (IGS) results. The comparison of ZTD and ZPD shows a good agreement. The comparison of GPS PWV and Radiosonde shows a good agreement. The spatio-temporal of GPS PWV is correlated with the Monsoon Asian-Australian cycles that affect weather and climate in Indonesia. The result indicates that GPS data provide valuable information in meteorology and climatology.
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Haq, M. S., Haolia, M. I. Sulaiman, I. Madrinovella, S. Satiawan, D. A. Zaky, S. K. Suhardja, et al. "Early Results of P Wave Regional Tomography Study at Sunda-Banda Arc using BMKG Seismic Network." IOP Conference Series: Earth and Environmental Science 873, no. 1 (October 1, 2021): 012065. http://dx.doi.org/10.1088/1755-1315/873/1/012065.
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Abstract The plate movement, geological structure, magmatism, and seismic activity in the area of Bali to East Nusa Tenggara are mainly related with the subducting of Indo-Australian Plate underneath the Eurasian plate. The complexity is added with the recent collision of Australian continent lithosphere with the western Banda arc, along the islands of Flores, Sumba and Timor island. Our study area is known as the Sunda-Banda arc transition. With the aim of imaging subsurface structure, we perform seismic tomography inversion using regional events. We collected 5 years of earthquake data (January 2015 – December 2019) from the Indonesian Agency of Meteorology, Climatology, and Geophysics (BMKG). The output of our data processing is not limited to only P wave velocity model, but also relocated seismicity pattern in the region. In general, seismicity pattern shows dominant shallow events in the south that progressively shift into deeper events in the north down to a few 500 km, marking a dipping subduction zone in this region. A group of shallow events down to a depth of 50 km is also seen at the norther region that may relate to back-arc thrust activity. P wave tomogram model show a lower velocity perturbation at a depth of 30 km that could be associated with magmatic activity along the volcanic front line. Higher P wave perturbation model are spotted at two different zones, the first one is marking a dipping Indo-Australian plate down to depth of 400 km. We noticed that the angle of dipping is steeper in the Eastern part compared to the Western part. The second a relatively flat at shallow depth at the northern region from the island of Lombok to Nusa Tenggara Timur that may mark the back-arc thrust region
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Brilianti, P. T., Haolia, M. I. Sulaiman, S. S. Angkasa, S. Widyanti, I. Herawati, S. K. Suhardja, et al. "Initial Result of P Wave Tomography Model in Sunda-Banda Arc Transition using FMTOMO." IOP Conference Series: Earth and Environmental Science 873, no. 1 (October 1, 2021): 012057. http://dx.doi.org/10.1088/1755-1315/873/1/012057.
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Abstract Our study area is located near island Sumbawa, Sumba, Flores, West Timor, Indonesia and East Timor, popularly known as Sunda-Banda arc transition zone. The tectonic setting is mainly controlled by the movement of the oceanic lithosphere Indo-Australian plate subducting the Eurasian plate and Northward migration of Australian continental lithosphere into western Banda-arc in the region of Flores, Sumba and Timor island. We tried to image velocity structure beneath these regions using regional events and tomography inversion model. We collected 5 years of regional events from the Indonesian Agency of Meteorology, Climatology and Geophysics. In total, we reserved 3186 events recorded on 29 stations. For data processing, we used fast marching method as ray tracing between sources and receiver. We then employed subspace inversion as the tomography procedure to estimate the best velocity model representing the tectonic model in the region. Hypocenter data distribution is concentrated on shallow parts of the region and along the Benioff zone down to a maximum depth of 400 km. One of challenge of this study is that although events are abundance, the stations used are mostly located onshore and does not extend in the south-north direction that leads us to under determined problem in the inversion process. However, checker-board models show most our target area can be retrieved to its initial model with sign of smearing effects shown start from a depth of 50 km. After six iteration and optimized selection of damping and smoothing parameters, we observed low velocity anomaly under Bali, Lombok, Sumba, East Nusa Tenggara at shallow depth that may be related with volcanic activity. Deeper low anomaly can also be seen that may be related with partial melting process. A band of fast velocity is clearly seen that goes deepen to the north depicting subducting slabs own to a depth of 300 km. We also observed a possible of fast velocity in the northern part of our stations at shallow depth that we believe may represent the back arc thrust.
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Rodger, C. J., J. B. Brundell, R. L. Dowden, and N. R. Thomson. "Location accuracy of long distance VLF lightning locationnetwork." Annales Geophysicae 22, no. 3 (March 19, 2004): 747–58. http://dx.doi.org/10.5194/angeo-22-747-2004.
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Abstract. An experimental VLF WorldWide Lightning Location (WWLL) network is being developed to provide realtime locations of cloud to ground lightning discharges occurring throughout the globe. This network has expanded from a limited number of stations in the Western Pacific to its current state of 11 stations, in most longitude sectors, with additional stations planned in the near future. As part of the initial testing phase of the WWLL the network has operated in a simple mode, sending the station trigger times into a central processing point rather than using the sferic Time of Group Arrival (TOGA). During this initial stage, a significant quantity of lightning location data has been collected, some of which is being applied to research questions. In this paper the operation of the WWLL network is described, and the location accuracy of the pre-TOGA WWLL network is characterised. This is performed by contrasting commercial lightning location data from an Australian network, Kattron, over 2 days in January 2002, with 4 WWLL stations covering the same region. It was found that there were 426 matched lightning events, corresponding to lightning discharges with large lightning return stroke peak currents (mean absolute peak current of ~26kA compared with ~12kA for all Kattron events). By considering the random errors in the difference locations between the matching lightning events, an appropriate Gaussian timing error for the WWLL network of receiving stations is determined, and hence an estimate for the global location errors for the existing 11-station network is found. The "worst-case" global location error for the existing network ranges spatially from 7.5–100km, with the global median being 15km, and the global mean 30km. When the TOGA method is implemented, the station timing errors will decrease, allowing for an increase in the location accuracies. Hence, the location accuracy estimates determined in this paper will be very conservative for the future WWLL network employing the TOGA technique. Key words. Meteorology and atmospheric dynamics (lightning, atmospheric electricity, instruments and techniques)
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Foster, James, Michael Bevis, and Steven Businger. "GPS Meteorology: Sliding-Window Analysis*." Journal of Atmospheric and Oceanic Technology 22, no. 6 (June 1, 2005): 687–95. http://dx.doi.org/10.1175/jtech1717.1.
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Abstract The sliding-window technique uses a moving time window to select GPS data for processing. This makes it possible to routinely incorporate the most recently collected data and generate estimates for atmospheric delay or precipitable water in (near) real time. As a consequence of the technique several estimates may be generated for each time epoch, and these multiple estimates can be used to explore and analyze the characteristics of the atmospheric estimates and the effect of the processing model and parameters. Examples of some of the analyses that can be undertaken are presented. Insights into the phenomenology of the atmospheric estimates provided by sliding-window analysis permit the fine-tuning of the GPS processing as well as the possibility of both improving the accuracy of the near-real-time estimates themselves and constraining the errors associated with them. The overlapping data windows and the multiple estimates that characterize the sliding-window method can lead to ambiguity in the meaning of many terms and expressions commonly used in GPS meteorology. In order to prevent confusion in discussions of sliding-window processing, a nomenclature is proposed that formalizes the meaning of the primary terms and defines the geometric and physical relationships between them.
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Afanasyev, V. S., and S. A. Kiselev. "Modern methods of processing and visualization of meteorological data." Quality. Innovation. Education, no. 4 (2020): 61–66. http://dx.doi.org/10.31145/1999-513x-2020-4-61-66.
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The paper presents the results of processing meteorological data obtained using software that allows standard mathematical and statistical processing of model data (global and regional climate modeling, Reanalysis data), followed by a graphical representation of the results. The main tools for data processing are Panoply and GrADS, which allow you to save time when solving problems related to meteorology and climatology.
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E, Băutu. "Osimin - A meteorological data platform for processing SIMIN data built on open source software." Scientific Bulletin of Naval Academy XIX, no. 1 (July 15, 2018): 555–60. http://dx.doi.org/10.21279/1454-864x-18-i1-083.
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In 2003, the Romanian National Institute of Meteorology and Hydrology inaugurated National Integrated Meteorological System (SIMIN), consisting of a network of stations and instruments for measurement and detection of hydro and meteorological data, a specialized communication network, a forecasting network, and a dissemination network. With a setup cost of $55 million and a national priority role, SIMIN (implemented by Lockheed Martin) is relatively black boxed even today, using proprietary technology and software. Few institutions have direct access to the data it provides. In this paper, we present the design of a web-based software application built on open source software that allows easy access to and processing of data available in SIMIN.
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Rachmawati, L. M., A. Mardiansyah, I. W. Kinanti, A. Ramadhan, A. S. Adiwidya, A. Jalasena, and I. Chandra. "Natural, Meteorology, And Novel – IAP Data Processing Method for Tipping Bucket Based Rain Gauge." Journal of Physics: Conference Series 2243, no. 1 (June 1, 2022): 012071. http://dx.doi.org/10.1088/1742-6596/2243/1/012071.
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Abstract Air pollution transport is entangled with weather and climate factors. As the pollutants tend to move due to the metrological condition. Naturally, pollutants will be deposited to the ground at the end part of the deposition cycle. One of the factors of pollutant deposition in a wet deposition is rain. The soluble pollutants and particulate matter are precipitated to the earth’s surface during precipitation. In order to analyse it, we need a rainfall measuring device/rain gauge, as rainfall is an important parameter to find the correlation between the two. However, there is a limited number of rain-gauge in Indonesia. Thus, we proposed a tipping bucket rain gauge, which consists of a funnel, a bucket, a magnetic switch sensor, and a microcontroller-based processing unit. The prototype is equipped with a GSM module so that the data can be sent in real-time via text message every minute, also an SD Card as the backup storage data. It was calibrated using ISO 17025:2005 standard, the result obtained by a resolution of 0.2 mm/tip with a capacity of 4.2 ml buckets, and U95 uncertainty of ±0,04 - ±0,12 mm/minute. To find the suitable method of rainfall calculation for the prototype, we observe three methods, Natural, Meteorology, and Novel-IAP. From the three we found, Novel-IAP has the best result since the calculation is executed every second. And the other methods are found to have a high error result.
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Lehmann, V., and G. Teschke. "Wavelet based methods for improved wind profiler signal processing." Annales Geophysicae 19, no. 8 (August 31, 2001): 825–36. http://dx.doi.org/10.5194/angeo-19-825-2001.
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Abstract. In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes) from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.Key words. Meteorology and atmospheric dynamics (instruments and techniques) – Radio science (remote sensing; signal processing)
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Nakaegawa, Tosiyuki. "High-Performance Computing in Meteorology under a Context of an Era of Graphical Processing Units." Computers 11, no. 7 (July 13, 2022): 114. http://dx.doi.org/10.3390/computers11070114.
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This short review shows how innovative processing units—including graphical processing units (GPUs)—are used in high-performance computing (HPC) in meteorology, introduces current scientific studies relevant to HPC, and discusses the latest topics in meteorology accelerated by HPC computers. The current status surrounding HPC is distinctly complicated in both hardware and software terms, and flows similar to fast cascades. It is difficult to understand and follow the status for beginners; they need to overcome the obstacle of catching up on the information on HPC and connecting it to their studies. HPC systems have accelerated weather forecasts with physical-based models since Richardson’s dream in 1922. Meteorological scientists and model developers have written the codes of the models by making the most of the latest HPC technologies available at the time. Several of the leading HPC systems used for weather forecast models are introduced. Each institute chose an HPC system from many possible alternatives to best match its purposes. Six of the selected latest topics in high-performance computing in meteorology are also reviewed: floating points; spectral transform in global weather models; heterogeneous computing; exascale computing; co-design; and data-driven weather forecasts.
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Su, Chun-Hsu, Nathan Eizenberg, Peter Steinle, Dörte Jakob, Paul Fox-Hughes, Christopher J. White, Susan Rennie, Charmaine Franklin, Imtiaz Dharssi, and Hongyan Zhu. "BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia." Geoscientific Model Development 12, no. 5 (May 24, 2019): 2049–68. http://dx.doi.org/10.5194/gmd-12-2049-2019.
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Abstract. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) is the first atmospheric regional reanalysis over a large region covering Australia, New Zealand, and Southeast Asia. The production of the reanalysis with approximately 12 km horizontal resolution – BARRA-R – is well underway with completion expected in 2019. This paper describes the numerical weather forecast model, the data assimilation methods, the forcing and observational data used to produce BARRA-R, and analyses results from the 2003–2016 reanalysis. BARRA-R provides a realistic depiction of the meteorology at and near the surface over land as diagnosed by temperature, wind speed, surface pressure, and precipitation. Comparing against the global reanalyses ERA-Interim and MERRA-2, BARRA-R scores lower root mean square errors when evaluated against (point-scale) 2 m temperature, 10 m wind speed, and surface pressure observations. It also shows reduced biases in daily 2 m temperature maximum and minimum at 5 km resolution and a higher frequency of very heavy precipitation days at 5 and 25 km resolution when compared to gridded satellite and gauge analyses. Some issues with BARRA-R are also identified: biases in 10 m wind, lower precipitation than observed over the tropical oceans, and higher precipitation over regions with higher elevations in south Asia and New Zealand. Some of these issues could be improved through dynamical downscaling of BARRA-R fields using convective-scale (<2 km) models.
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Murphy, Tara, Peter Lamb, Christopher Owen, and Malte Marquarding. "Data Storage, Processing, and Visualization for the Australia Telescope Compact Array." Publications of the Astronomical Society of Australia 23, no. 1 (2006): 25–32. http://dx.doi.org/10.1071/as05033.
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AbstractWe present three Virtual Observatory tools developed at the Australia Telescope National Facility (ATNF) for the storage, processing and visualization of Australia Telescope Compact Array (ATCA) data. These are the Australia Telescope Online Archive, a prototype data-reduction pipeline, and the Remote Visualization System. These tools were developed in the context of the Virtual Observatory and were intended to be both useful for astronomers and technology demonstrators. We discuss the design and implementation of these tools, as well as issues that should be considered when developing similar systems for future telescopes.
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Sharma, Saroj Kumar, Jagannath Aryal, and Abbas Rajabifard. "Remote Sensing and Meteorological Data Fusion in Predicting Bushfire Severity: A Case Study from Victoria, Australia." Remote Sensing 14, no. 7 (March 29, 2022): 1645. http://dx.doi.org/10.3390/rs14071645.
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The extent and severity of bushfires in a landscape are largely governed by meteorological conditions. An accurate understanding of the interactions of meteorological variables and fire behaviour in the landscape is very complex, yet possible. In exploring such understanding, we used 2693 high-confidence active fire points recorded by a Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for nine different bushfires that occurred in Victoria between 1 January 2009 and 31 March 2009. These fires include the Black Saturday Bushfires of 7 February 2009, one of the worst bushfires in Australian history. For each fire point, 62 different meteorological parameters of bushfire time were extracted from Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) data. These remote sensing and meteorological datasets were fused and further processed in assessing their relative importance using four different tree-based ensemble machine learning models, namely, Random Forest (RF), Fuzzy Forest (FF), Boosted Regression Tree (BRT), and Extreme Gradient Boosting (XGBoost). Google Earth Engine (GEE) and Landsat images were used in deriving the response variable–Relative Difference Normalised Burn Ratio (RdNBR), which was selected by comparing its performance against Difference Normalised Burn Ratio (dNBR). Our findings demonstrate that the FF algorithm utilising the Weighted Gene Coexpression Network Analysis (WGCNA) method has the best predictive performance of 96.50%, assessed against 10-fold cross-validation. The result shows that the relative influence of the variables on bushfire severity is in the following order: (1) soil moisture, (2) soil temperature, (3) air pressure, (4) air temperature, (5) vertical wind, and (6) relative humidity. This highlights the importance of soil meteorology in bushfire severity analysis, often excluded in bushfire severity research. Further, this study provides a scientific basis for choosing a subset of meteorological variables for bushfire severity prediction depending on their relative importance. The optimal subset of high-ranked variables is extremely useful in constructing simplified and computationally efficient surrogate models, which can be particularly useful for the rapid assessment of bushfire severity for operational bushfire management and effective mitigation efforts.
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Benny Hartanto, Ningrum Astriawati, Supartini, and Damar Kuncoro Yekti. "Pencarian dan Pemanfaatan Informasi Data Badan Meteorologi, Klimatologi, dan Geofisika (BMKG)." INSOLOGI: Jurnal Sains dan Teknologi 1, no. 5 (October 29, 2022): 553–64. http://dx.doi.org/10.55123/insologi.v1i5.906.
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The Meteorology, Climatology, and Geophysics Agency (BMKG) has the task of carrying out government duties in the fields of Meteorology, Climatology, Air Quality, and Geophysics by the provisions of the applicable legislation. This study aims to search and utilize BMKG meteorological data in the Yogyakarta area. This research was conducted at the Mlati Climatology Station, Sleman, Yogyakarta. The analysis used uses descriptive analysis. The data collection method uses observation techniques, interviews, documentation from offline data centers, and BMKG online data. From the results of the study, the search for meteorological data of BMKG Yogyakarta for the benefit of the community includes inputting data until processing until it is published to the public through social media such as Whatsapp, Instagram, Facebook, Twitter, Email, Radio, and Television. The utilization and importance of BMKG weather information are very influential for the survival of the people in Yogyakarta. With the information from the BMKG, the community can know the weather forecasts in the next few days and adjust the work that makes the weather as its indicator such as farming, tourism, fisheries, transportation, trade, and government as well as government agencies working in the field of disaster management.
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Jacobs, Stephanie J., Ailie J. E. Gallant, and Nigel J. Tapper. "The Sensitivity of Urban Meteorology to Soil Moisture Boundary Conditions: A Case Study in Melbourne, Australia." Journal of Applied Meteorology and Climatology 56, no. 8 (August 2017): 2155–72. http://dx.doi.org/10.1175/jamc-d-17-0007.1.
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AbstractThe sensitivity of near-surface urban meteorological conditions to three different soil moisture initialization experiments under heat-wave conditions is investigated for the city of Melbourne, Australia. The Weather Research and Forecasting Model is used to simulate a domain over Melbourne and its surrounding rural areas. The experiments employ three suites of simulations. Two suites initialize the model with soil moisture from the top layer of the ERA-Interim soil moisture data with a 3-month and 24-h coupled spinup period, respectively. The third suite initializes the model with the arguably more realistic soil moistures from the Australian Water Availability Project (AWAP), which are an order of magnitude drier than the ERA-Interim data, again using a 24-h spinup period. The simulations employing the AWAP data are found to have smaller errors when compared with observations, with biases in urban maximum temperature reduced by 4.1°C and biases in the skin temperature reduced by 3.0°C relative to the biases of the 3-month-spinup experiment. Despite urban areas only having a small proportion of soil-covered surfaces, the results show that urban soils have a greater influence on urban near-surface temperatures at night, whereas rural soils have a greater influence on urban near-surface temperatures during the daytime.
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Parker, Albert, and Clifford D. Ollier. "Discussion of the “Hottest Year on Record” in Australia." Quaestiones Geographicae 36, no. 1 (March 1, 2017): 79–91. http://dx.doi.org/10.1515/quageo-2017-0006.
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Abstract The global temperature trends provided by the Australian Bureau of Meteorology are artificially exaggerated due to subjective and unidirectional adjustments of recorded values. The present paper aims to promote the use of the raw stations’ data corrected only for urban heat island formation. The longer temperature records of Australia exhibit significant oscillations with a strong quasi-60 years’ signature of downward phases 1880 to 1910, 1940 to 1970 and 2000 to present, and upwards phases 1910 to 1940 and 1970 to 2000. A longer oscillation with downward phase until 1910 and an upwards phase afterwards is also detected. The warming since 1910 occurred at a nearly constant rate. Over the full length of the long Australian records since the end of the 1800s, there is no sign of warming or increased occurrence of extreme events. The monthly highest and mean maximum temperatures do not exhibit any positive trend. The differences between monthly highest and lowest, or monthly mean maximum and mean minimum temperatures, are all reducing because of urban heat island formation.
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Le Marshall, John, Robert Norman, David Howard, Susan Rennie, Michael Moore, Jan Kaplon, Yi Xiao, et al. "Corrigendum to: Using global navigation satellite system data for real-time moisture analysis and forecasting over the Australian region I. The system." Journal of Southern Hemisphere Earth Systems Science 70, no. 1 (2020): 394. http://dx.doi.org/10.1071/es19009_co.
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The use of high spatial and temporal resolution data assimilation and forecasting around Australia’s capital cities and rural land provided an opportunity to improve moisture analysis and forecasting. To support this endeavour, RMIT University and Geoscience Australia worked with the Bureau of Meteorology (BoM) to provide real-time GNSS (global navigation satellite system) zenith total delay (ZTD) data over the Australian region, from which a high-resolution total water vapour field for SE Australia could be determined. The ZTD data could play an important role in high-resolution data assimilation by providing mesoscale moisture data coverage from existing GNSS surface stations over significant areas of the Australian continent. The data were used by the BoM’s high-resolution ACCESS-C3 capital city numerical weather prediction (NWP) systems, the ACCESS-G3 Global system and had been used by the ACCESS-R2-Regional NWP model. A description of the data collection and analysis system is provided. An example of the application of these local GNSS data for a heavy rainfall event over SE Australia/Victoria is shown using the 1.5-km resolution ACCESS-C3 model, which was being prepared for operational use. The results from the test were assessed qualitatively, synoptically and also examined quantitatively using the Fractions Skills Score which showed the reasonableness of the forecasts and demonstrated the potential for improving rainfall forecasts over south-eastern Australia by the inclusion of ZTD data in constructing the moisture field. These data have been accepted for operational use in NWP.
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Marshall, John Le, Robert Norman, David Howard, Susan Rennie, Michael Moore, Jan Kaplon, Yi Xiao, et al. "Using global navigation satellite system data for real-time moisture analysis and forecasting over the Australian region I. The system." Journal of Southern Hemisphere Earth Systems Science 69, no. 1 (2019): 161. http://dx.doi.org/10.1071/es19009.
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The use of high spatial and temporal resolution data assimilation and forecasting around Australia’s capital cities and rural land provided an opportunity to improve moisture analysis and forecasting. To support this endeavour, RMIT University and Geoscience Australia worked with the Bureau of Meteorology (BoM) to provide real-time GNSS (global navigation satellite system) zenith total delay (ZTD) data over the Australian region, from which a high-resolution total water vapour field for SE Australia could be determined. The ZTD data could play an important role in high-resolution data assimilation by providing mesoscale moisture data coverage from existing GNSS surface stations over significant areas of the Australian continent. The data were used by the BoM’s high-resolution ACCESS-C3 capital city numerical weather prediction (NWP) systems, the ACCESS-G3 Global system and had been used by the ACCESS-R2-Regional NWP model. A description of the data collection and analysis system is provided. An example of the application of these local GNSS data for a heavy rainfall event over SE Australia/Victoria is shown using the 1.5-km resolution ACCESS-C3 model, which was being prepared for operational use. The results from the test were assessed qualitatively, synoptically and also examined quantitatively using the Fractions Skills Score which showed the reasonableness of the forecasts and demonstrated the potential for improving rainfall forecasts over south-eastern Australia by the inclusion of ZTD data in constructing the moisture field. These data have been accepted for operational use in NWP.
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Fowler, Keirnan J. A., Suwash Chandra Acharya, Nans Addor, Chihchung Chou, and Murray C. Peel. "CAMELS-AUS: hydrometeorological time series and landscape attributes for 222 catchments in Australia." Earth System Science Data 13, no. 8 (August 6, 2021): 3847–67. http://dx.doi.org/10.5194/essd-13-3847-2021.
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Abstract. This paper presents the Australian edition of the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS) series of datasets. CAMELS-AUS (Australia) comprises data for 222 unregulated catchments, combining hydrometeorological time series (streamflow and 18 climatic variables) with 134 attributes related to geology, soil, topography, land cover, anthropogenic influence and hydroclimatology. The CAMELS-AUS catchments have been monitored for decades (more than 85 % have streamflow records longer than 40 years) and are relatively free of large-scale changes, such as significant changes in land use. Rating curve uncertainty estimates are provided for most (75 %) of the catchments, and multiple atmospheric datasets are included, offering insights into forcing uncertainty. This dataset allows users globally to freely access catchment data drawn from Australia's unique hydroclimatology, particularly notable for its large interannual variability. Combined with arid catchment data from the CAMELS datasets for the USA and Chile, CAMELS-AUS constitutes an unprecedented resource for the study of arid-zone hydrology. CAMELS-AUS is freely downloadable from https://doi.org/10.1594/PANGAEA.921850 (Fowler et al., 2020a).
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Islam, Mohammad S., Tianxin Fang, Callum Oldfield, Puchanee Larpruenrudee, Hamidreza Mortazavy Beni, Md M. Rahman, Shahid Husain, and Yuantong Gu. "Heat Wave and Bushfire Meteorology in New South Wales, Australia: Air Quality and Health Impacts." International Journal of Environmental Research and Public Health 19, no. 16 (August 20, 2022): 10388. http://dx.doi.org/10.3390/ijerph191610388.
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The depletion of air quality is a major problem that is faced around the globe. In Australia, the pollutants emitted by bushfires play an important role in making the air polluted. These pollutants in the air result in many adverse impacts on the environment. This paper analysed the air pollution from the bushfires from November 2019 to July 2020 and identified how it affects the human respiratory system. The bush fires burnt over 13 million hectares, destroying over 2400 buildings. While these immediate effects were devastating, the long-term effects were just as devastating, with air pollution causing thousands of people to be admitted to hospitals and emergency departments because of respiratory complications. The pollutant that caused most of the health effects throughout Australia was Particulate Matter (PM) PM2.5 and PM10. Data collection and analysis were covered in this paper to illustrate where and when PM2.5 and PM10, and other pollutants were at their most concerning levels. Susceptible areas were identified by analysing environmental factors such as temperature and wind speed. The study identified how these pollutants in the air vary from region to region in the same time interval. This study also focused on how these pollutant distributions vary according to the temperature, which helps to determine the relationship between the heatwave and air quality. A computational model for PM2.5 aerosol transport to the realistic airways was also developed to understand the bushfire exhaust aerosol transport and deposition in airways. This study would improve the knowledge of the heat wave and bushfire meteorology and corresponding respiratory health impacts.
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Hartono, Henny, Rourentsia Meylovsky, and Johanes Fernandes Andry. "ARSITEKTUR ENTERPRISE PADA BMKG DENGAN FRAMEWORK TOGAF ADM." Infotech: Journal of Technology Information 6, no. 2 (November 26, 2020): 63–68. http://dx.doi.org/10.37365/jti.v6i2.92.
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As a government institution that performs tasks in the fields of meteorology, climatology, air quality and geophysics, BMKG (Meteorology, Climatology and Geophysics Agency) does not yet have an integrated information system to support each of its activities, such as instrumentation, engineering and calibration, observation, processing, dissemination, and service. The purpose of this study is to produce enterprise architecture design including business architecture, data architecture, technology architecture, and application architecture, and produce activity solutions and information system solutions that can help BMKG in developing its business processes. In this study, the framework of enterprise architecture design uses The Open Group Framework (TOGAF) with the Architecture Development Method (ADM) method. The results of this study, namely a proposed TOGAF model that is tailored to the business needs process of BMKG in designing enterprise architecture for IS / IT development.
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Pettit, C. J., S. N. Lieske, and S. Z. Leao. "BIG BICYCLE DATA PROCESSING: FROM PERSONAL DATA TO URBAN APPLICATIONS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-2 (June 2, 2016): 173–79. http://dx.doi.org/10.5194/isprsannals-iii-2-173-2016.
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Understanding the flows of people moving through the built environment is a vital source of information for the planners and policy makers who shape our cities. Smart phone applications enable people to trace themselves through the city and these data can potentially be then aggregated and visualised to show hot spots and trajectories of macro urban movement. In this paper our aim is to develop procedures for cleaning, aggregating and visualising human movement data and translating this into policy relevant information. In conducting this research we explore using bicycle data collected from a smart phone application known as RiderLog. We focus on the RiderLog application initially in the context of Sydney, Australia and discuss the procedures and challenges in processing and cleaning this data before any analysis can be made. We then present some preliminary map results using the CartoDB online mapping platform where data are aggregated and visualised to show hot spots and trajectories of macro urban movement. We conclude the paper by highlighting some of the key challenges in working with such data and outline some next steps in processing the data and conducting higher volume and more extensive analysis.
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Pettit, C. J., S. N. Lieske, and S. Z. Leao. "BIG BICYCLE DATA PROCESSING: FROM PERSONAL DATA TO URBAN APPLICATIONS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-2 (June 2, 2016): 173–79. http://dx.doi.org/10.5194/isprs-annals-iii-2-173-2016.
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Understanding the flows of people moving through the built environment is a vital source of information for the planners and policy makers who shape our cities. Smart phone applications enable people to trace themselves through the city and these data can potentially be then aggregated and visualised to show hot spots and trajectories of macro urban movement. In this paper our aim is to develop procedures for cleaning, aggregating and visualising human movement data and translating this into policy relevant information. In conducting this research we explore using bicycle data collected from a smart phone application known as RiderLog. We focus on the RiderLog application initially in the context of Sydney, Australia and discuss the procedures and challenges in processing and cleaning this data before any analysis can be made. We then present some preliminary map results using the CartoDB online mapping platform where data are aggregated and visualised to show hot spots and trajectories of macro urban movement. We conclude the paper by highlighting some of the key challenges in working with such data and outline some next steps in processing the data and conducting higher volume and more extensive analysis.
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Lee, Haeju, and Sung Hoon Park. "Stepwise Assessment of Different Saltation Theories in Comparison with Field Observation Data." Atmosphere 11, no. 1 (December 20, 2019): 10. http://dx.doi.org/10.3390/atmos11010010.
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Wind-blown dust models use input data, including soil conditions and meteorology, to interpret the multi-step wind erosion process and predict the quantity of dust emission. Therefore, the accuracy of the wind-blown dust models is dependent on the accuracy of each input condition and the robustness of the model schemes for each elemental step of wind erosion. A thorough evaluation of a wind-blown model thus requires validation of the input conditions and the elemental model schemes. However, most model evaluations and intercomparisons have focused on the final output of the models, i.e., the vertical dust emission. Recently, a delicate set of measurement data for saltation flux and friction velocity was reported from the Japan-Australia Dust Experiment (JADE) Project, which enabled the step-by-step evaluation of wind-blown dust models up to the saltation step. When all the input parameters were provided from the observations, both the two widely used saltation schemes showed very good agreement with measurements, with the correlation coefficient and the agreement of index both being larger than 0.9, which demonstrated the strong robustness of the physical schemes for saltation. However, using the meteorology model to estimate the input conditions such as weather and soil conditions, considerably degraded the models’ performance. The critical reason for the model failure was determined to be the inaccuracy in the estimation of the threshold friction velocity (representing soil condition), followed by inaccurate estimation of surface wind speed. It was not possible to determine which of the two saltation schemes was superior, based on the present study results. Such differentiation will require further evaluation studies using more measurements of saltation flux and vertical dust emissions.
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Monk, Khalia, Elise-Andrée Guérette, Clare Paton-Walsh, Jeremy D. Silver, Kathryn M. Emmerson, Steven R. Utembe, Yang Zhang, et al. "Evaluation of Regional Air Quality Models over Sydney and Australia: Part 1—Meteorological Model Comparison." Atmosphere 10, no. 7 (July 4, 2019): 374. http://dx.doi.org/10.3390/atmos10070374.
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The ability of meteorological models to accurately characterise regional meteorology plays a crucial role in the performance of photochemical simulations of air pollution. As part of the research funded by the Australian government’s Department of the Environment Clean Air and Urban Landscape hub, this study set out to complete an intercomparison of air quality models over the Sydney region. This intercomparison would test existing modelling capabilities, identify any problems and provide the necessary validation of models in the region. The first component of the intercomparison study was to assess the ability of the models to reproduce meteorological observations, since it is a significant driver of air quality. To evaluate the meteorological component of these air quality modelling systems, seven different simulations based on varying configurations of inputs, integrations and physical parameterizations of two meteorological models (the Weather Research and Forecasting (WRF) and Conformal Cubic Atmospheric Model (CCAM)) were examined. The modelling was conducted for three periods coinciding with comprehensive air quality measurement campaigns (the Sydney Particle Studies (SPS) 1 and 2 and the Measurement of Urban, Marine and Biogenic Air (MUMBA)). The analysis focuses on meteorological variables (temperature, mixing ratio of water, wind (via wind speed and zonal wind components), precipitation and planetary boundary layer height), that are relevant to air quality. The surface meteorology simulations were evaluated against observations from seven Bureau of Meteorology (BoM) Automatic Weather Stations through composite diurnal plots, Taylor plots and paired mean bias plots. Simulated vertical profiles of temperature, mixing ratio of water and wind (via wind speed and zonal wind components) were assessed through comparison with radiosonde data from the Sydney Airport BoM site. The statistical comparisons with observations identified systematic overestimations of wind speeds that were more pronounced overnight. The temperature was well simulated, with biases generally between ±2 °C and the largest biases seen overnight (up to 4 °C). The models tend to have a drier lower atmosphere than observed, implying that better representations of soil moisture and surface moisture fluxes would improve the subsequent air quality simulations. On average the models captured local-scale meteorological features, like the sea breeze, which is a critical feature driving ozone formation in the Sydney Basin. The overall performance and model biases were generally within the recommended benchmark values (e.g., ±1 °C mean bias in temperature, ±1 g/kg mean bias of water vapour mixing ratio and ±1.5 m s−1 mean bias of wind speed) except at either end of the scale, where the bias tends to be larger. The model biases reported here are similar to those seen in other model intercomparisons.
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Henderson, Roger. "ASEG History Committee: A history of geophysical data and image processing in Australia." Preview 2020, no. 207 (July 3, 2020): 5. http://dx.doi.org/10.1080/14432471.2020.1800381.
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Rautenhaus, Marc, Michael Bottinger, Stephan Siemen, Robert Hoffman, Robert M. Kirby, Mahsa Mirzargar, Niklas Rober, and Rudiger Westermann. "Visualization in Meteorology—A Survey of Techniques and Tools for Data Analysis Tasks." IEEE Transactions on Visualization and Computer Graphics 24, no. 12 (December 1, 2018): 3268–96. http://dx.doi.org/10.1109/tvcg.2017.2779501.
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Kataev, M. Yu, M. O. Krylov, and P. P. Geiko. "Software to compare images of the vegetation index obtained by satellite devices and unmanned aircraft." Proceedings of Tomsk State University of Control Systems and Radioelectronics 23, no. 4 (December 25, 2020): 63–70. http://dx.doi.org/10.21293/1818-0442-2020-23-4-63-70.
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At present, the practice of supporting many types of human activities requires the use of the spatial data infrastructure. Such an infrastructure integrates spatio-temporal sets from many sources of information within itself, providing the user with various types of processing, analysis and visualization methods. This article describes the architecture of the software system and the processes for managing sets of spatio-temporal data to solve agricultural problems. Measurement data using multispectral satellite systems, unmanned aerial vehicles (UAVs), as well as a priori information (meteorology, agrochemical information, etc.) are taken as input information. The User of the Software System is provided with the opportunity to control the spatial information of the territory of agricultural fields, sets of temporal data from various spatial data. An important achievement of the work is the combination of the results of satellite and UAV images according to the controlled parameters, that makes possible to expand the area of use of UAVs and verify them. The results of real data processing are presented.
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Fujita, Kazuhisa. "Estimation of the number of clusters on d-dimensional sphere." Artificial Intelligence Research 10, no. 1 (May 13, 2021): 57. http://dx.doi.org/10.5430/air.v10n1p57.
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Spherical data is distributed on the sphere. The data appears in various fields such as meteorology, biology, and natural language processing. However, a method for analysis of spherical data does not develop enough yet. One of the important issues is an estimation of the number of clusters in spherical data. To address the issue, I propose a new method called the Spherical X-means (SX-means) that can estimate the number of clusters on d-dimensional sphere. The SX-means is the model-based method assuming that the data is generated from a mixture of von Mises-Fisher distributions. The present paper explains the proposed method and shows its performance of estimation of the number of clusters.
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Peng, Li, Fei Fei Tang, Zhi Yue Zhou, Xing Liu, and Zhi Min Ruan. "Applying Lightweight UAV in Landslide Monitoring." Applied Mechanics and Materials 738-739 (March 2015): 738–45. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.738.
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With the advantages of small size, cost efficient, low noise, energy saving, fine definition and high current, UAV has been widely used in various fields such as military, agriculture, forestry,meteorology, environment, etc. Moreover, this technique can obtain large area, large angle and 3D surface information without shadows resulting from cloud cover which is the common shortage insatellite images, it is also widespread in geological hazards monitoring. In this article, the applications of hazards monitoring using UAV has been reviewed at first, then according to the needof landslide monitoring, based on UAV data processing in geological hazard in east-north of Chongqing on 31th August, 2014, route planning method for lightweight and low altitude UAV inmountainous district is introduced, also the workflow and relevant experiences of UAV data processing by applying Agisoft photoscan software. After data processing, both geo-referencedDSM and DOM of landslide are obtained by interpolation with assistance of chosen GPS control points. The interpolated topographic map of landslide can provide important information forgeological hazards monitoring and emergency relief.
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Horton, Brian, and Ross Corkrey. "A weighted coefficient model for estimation of Australian daily soil temperature at depths of 5cm to 100cm based on air temperature and rainfall." Soil Research 49, no. 4 (2011): 305. http://dx.doi.org/10.1071/sr10151.
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Soil temperatures are related to air temperature and rainfall on the current day and preceding days, and this can be expressed in a non-linear relationship to provide a weighted value for the effect of air temperature or rainfall based on days lag and soil depth. The weighted minimum and maximum air temperatures and weighted rainfall can then be combined with latitude and a seasonal function to estimate soil temperature at any depth in the range 5–100 cm. The model had a root mean square deviation of 1.21–1.85°C for minimum, average, and maximum soil temperature for all weather stations in Australia (mainland and Tasmania), except for maximum soil temperature at 5 and 10 cm, where the model was less precise (3.39° and 2.52°, respectively). Data for this analysis were obtained from 32–40 Bureau of Meteorology weather stations throughout Australia and the proposed model was validated using 5-fold cross-validation.
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Tozer, C. R., A. S. Kiem, and D. C. Verdon-Kidd. "On the uncertainties associated with using gridded rainfall data as a proxy for observed." Hydrology and Earth System Sciences Discussions 8, no. 5 (September 15, 2011): 8399–433. http://dx.doi.org/10.5194/hessd-8-8399-2011.
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Abstract. Gridded rainfall datasets are used in many hydrological and climatological studies, in Australia and elsewhere, including for hydroclimatic forecasting, climate attribution studies and climate model performance assessments. The attraction of the spatial coverage provided by gridded data is clear, particularly in Australia where the spatial and temporal resolution of the rainfall gauge network is sparse. However, the question that must be asked is whether it is suitable to use gridded data as a proxy for observed point data, given that gridded data is inherently "smoothed" and may not necessarily capture the temporal and spatial variability of Australian rainfall which leads to hydroclimatic extremes (i.e. droughts, floods)? This study investigates this question through a statistical analysis of three monthly gridded Australian rainfall datasets – the Bureau of Meteorology (BOM) dataset, the Australian Water Availability Project (AWAP) and the SILO dataset. To demonstrate the hydrological implications of using gridded data as a proxy for gauged data, a rainfall-runoff model is applied to one catchment in South Australia (SA) initially using gridded data as the source of rainfall input and then gauged rainfall data. The results indicate a markedly different runoff response associated with each of the different sources of rainfall data. It should be noted that this study does not seek to identify which gridded dataset is the "best" for Australia, as each gridded data source has its pros and cons, as does gauged or point data. Rather the intention is to quantify differences between various gridded data sources and how they compare with gauged data so that these differences can be considered and accounted for in studies that utilise these gridded datasets. Ultimately, if key decisions are going to be based on the outputs of models that use gridded data, an estimate (or at least an understanding) of the uncertainties relating to the assumptions made in the development of gridded data and how that gridded data compares with reality should be made.
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Reji, A. Amala Arul, and S. Muruganantham. "Building Detection From Satellite Images for Urban Planning Using MATLAB-Based Pattern Matching Method." International Journal of Creative Interfaces and Computer Graphics 10, no. 2 (July 2019): 17–28. http://dx.doi.org/10.4018/ijcicg.2019070102.
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Remote sensing and satellite image processing has many applications and an emerging field of trending in recent research. Remote sensing methods for extraction of information are used to obtain information related to the Earth's resources and environment for most government-based research applications. Few enhanced hybrid algorithms are reported and in use for real-world applications in recent years by extensive research for digital image processing. The digital images and satellite images are now extensively used for its information, which have many advantages over present analog image processing methods. The satellite data are larger and carry enormous amounts of information for applications like land description, crop assessment, cultivation monitoring, meteorology, regional description, underwater analysis, sea water interpretation, and so on. This paper analyses the requirements of better interpretation methods of received/captured images and newer processing techniques required. This paper presents complete study and pattern matching research in image processing tools using MATLAB programming and its capabilities that could be used in remote sensing applications in the future.
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BI, P., J. E. HILLER, A. S. CAMERON, Y. ZHANG, and R. GIVNEY. "Climate variability and Ross River virus infections in Riverland, South Australia, 1992–2004." Epidemiology and Infection 137, no. 10 (March 19, 2009): 1486–93. http://dx.doi.org/10.1017/s0950268809002441.
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SUMMARYRoss River virus (RRV) infection is the most common notifiable vector-borne disease in Australia, with around 6000 cases annually. This study aimed to examine the relationship between climate variability and notified RRV infections in the Riverland region of South Australia in order to set up an early warning system for the disease in temperate-climate regions. Notified data of RRV infections were collected by the South Australian Department of Health. Climatic variables and monthly river flow were provided by the Australian Bureau of Meteorology and South Australian Department of Water, Land and Biodiversity Conservation over the period 1992–2004. Spearman correlation and time-series-adjusted Poisson regression analysis were performed. The results indicate that increases in monthly mean minimum and maximum temperatures, monthly total rainfall, monthly mean Southern Oscillation Index and monthly flow in the Murray River increase the likelihood, but an increase in monthly mean relative humidity decreases the likelihood, of disease transmission in the region, with different time-lag effects. This study demonstrates that a useful early warning system can be developed for local regions based on the statistical analysis of readily available climate data. These early warning systems can be utilized by local public health authorities to develop disease prevention and control activities.
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Manage, Nadeeka Parana, Natalie Lockart, Garry Willgoose, George Kuczera, Anthony S. Kiem, AFM Kamal Chowdhury, Lanying Zhang, and Callum Twomey. "Statistical testing of dynamically downscaled rainfall data for the Upper Hunter region, New South Wales, Australia." Journal of Southern Hemisphere Earth Systems Science 66, no. 2 (2016): 203. http://dx.doi.org/10.1071/es16016.
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This study tests the statistical properties of downscaled climate data, concentrating on the rainfall which is required for hydrology predictions used in water supply reservoir simulations. The datasets used in this study have been produced by the New South Wales (NSW) / Australian Capital Territory (ACT) Regional Climate Modelling (NARCliM) project which provides a dynamically downscaled climate dataset for southeast Australia at 10 km resolution. In this paper, we present an evaluation of the downscaled NARCliM National Centers for Environmental Prediction (NCEP) / National Center for Atmospheric Research (NCAR) reanalysis simulations. The validation has been performed in the Goulburn River catchment in the Upper Hunter region of New South Wales, Australia. The analysis compared time series of the downscaled NARCliM rain-fall data with ground based measurements for selected Bureau of Meteorology rainfall stations and 5 km gridded data from the Australian Water Availability Project (AWAP). The initial testing of the rainfall was focused on autocorrelations as persistence is an important factor in hydrological and water availability analysis. Additionally, a cross-correlation analysis was performed at daily, fort-nightly, monthly and annually averaged time resolutions. The spatial variability of these statistics were calculated and plotted at the catchment scale. The auto-correlation analysis shows that the seasonal cycle in the NARCliM data is stronger than the seasonal cycle present in the ground based measurements and AWAP data. The cross-correlation analysis also shows a poor agreement between NARCliM data, and AWAP and ground based measurements. The spatial variability plots show a possible link between these discrepancies and orography at the catchment scale.
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Kusch, Wolfgang, Reinhold Zöllner, and Frank-Ulrich Dentler. "Georg von Neumayer: his influence on marine meteorology in the German Meteorological Service." Proceedings of the Royal Society of Victoria 123, no. 1 (2011): 27. http://dx.doi.org/10.1071/rs11027.
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Georg von Neumayer achieved outstanding scientific results and created the organisational framework for the successful completion of scientific tasks. Returning from Australia, Neumayer aimed to set up in Germany a state-owned centre for marine meteorology, hydrography, navigation, marine instruments and geomagnetism, with an emphasis on scientific research with practical application of the findings. Since 1868, a successfully operating private institute, Norddeutsche Seewarte, had existed in Hamburg. This institute provided instructions for sailing routes and the optimal use of favourable winds and currents. In 1875, the institute was transformed into an imperial institution, the ‘Deutsche Seewarte’ (German Marine Observatory), with a broad spectrum of marine responsibilities including meteorological forecasts and warnings, data acquisition and management, and climatology. Its first director was Georg von Neumayer, who led it to worldwide recognition. In 1903, he retired but the Deutsche Seewarte continued in his spirit. At the end of World War II, the institute was destroyed by bombs and ceased to exist. Today, the tasks are shared between Marine Meteorological Office of the Deutscher Wetterdienst specialising in the marine meteorological and related topics and the Federal Maritime and Hydrographic Agency.
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He, Ming-Chuan, and Geng-Ming Jiang. "Typhoon Identification and Positioning Using the FY-4A AGRI Thermal Infrared Data." Journal of Physics: Conference Series 2400, no. 1 (December 1, 2022): 012027. http://dx.doi.org/10.1088/1742-6596/2400/1/012027.
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Abstract This paper addresses typhoon identification and positioning by using the thermal infrared data acquired by the Advanced Geostationary Radiation Imager (AGRI) on the Chinese Fengyun 4A (FY-4A) satellite. First, a training dataset, a validation dataset, and a test dataset of typhoons in the West Pacific Ocean close to China are created from the FY-4A AGRI thermal infrared data. Then, the YOLOX neural network is configured and trained, in which an average precision (AP) of 33.2 is obtained for the test dataset. Finally, with the prior knowledge that the brightness temperature of the typhoon eye is higher than that of its surroundings, the typhoon eyes are located using the morphological image processing method. The results of typhoon eye positioning are generally consistent with the Optimal Path (OP) dataset of tropical cyclones created by the China Meteorology Administration (CMA), and the mean errors in latitude and longitude are 0.0391° and 0.0334°, respectively.
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Unwin, Elizabeth, James Codde, Louise Gill, Suzanne Stevens, and Timothy Nelson. "The WA Hospital Morbidity Data System: An Evaluation of its Performance and the Impact of Electronic Data Transfer." Health Information Management 26, no. 4 (December 1996): 189–92. http://dx.doi.org/10.1177/183335839702600407.
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This paper evaluates the performance of the Hospital Morbidity Data System, maintained by the Health Statistics Branch (HSB) of the Health Department of Western Australia (WA). The time taken to process discharge summaries was compared in the first and second halves of 1995, using the number of weeks taken to process 90% of all discharges and the percentage of records processed within four weeks as indicators of throughput. Both the hospitals and the HSB showed improvements in timeliness during the second half of the year. The paper also examines the impact of a recently introduced electronic data transfer system for WA country public hospitals on the timeliness of morbidity data. The processing time of country hospital records by the HSB was reduced to a similar time as for metropolitan hospitals, but the processing time in the hospitals increased, resulting in little improvement in total processing time.
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s, Sowmiyaa S., Moghana Lavanya S,, Mahendran K, and Geethalakshmi V. V. "An Insight into Fuzzy Logic Computation Technology and Its Applications in Agriculture and Meteorology." Oriental journal of computer science and technology 13, no. 0203 (January 30, 2021): 97–101. http://dx.doi.org/10.13005/ojcst13.0203.06.
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Speaking of recent advances, many computing technologies have been applied to several domains and have proved to provide more approximate and acceptable results. Fuzzy logic being one of them has been very useful in solving many real-world problems that are inherent for their uncertainty, complexity, impreciseness and a high degree of randomness. Soft computing aims to mimic human thinking and thus solve problems as a human does. The systems embedded with one or more soft computing technologies tend to make decisions quicker (reducing the processing timeframe) and more accurate in the light of uncertain and indefinite data. This paper aims at an extensive review of fuzzy logic also unraveling some of the applications of the same in the field of agricultural science and meteorology.
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Pranowo, Widodo S., and Sugiarta Wirasantosa. "TIDAL REGIMS OF ARAFURA AND TIMOR SEA." Marine Research in Indonesia 36, no. 1 (October 7, 2018): 21–28. http://dx.doi.org/10.14203/mri.v36i1.525.
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Tidal range in the Arafura and Teimor Sea region is estimated from the actual field records collected by five tidal stations during March 2011. These stations include Rote and Saumlaki tidal stations of Badan Koordinasi Survei dan Pemetaan Nasional (Bakosurtanal) Indonesia, and Broome, Darwin and Groote Eylandt tidal stations of Australia Bureau of Meteorology (BoM). In addition to data from these stations, datasets of sea surface height obtained from Topex/Poseidon altimetry at seven (7) virtual stations were used. Generally, the results of this study are in agreement with that of Wyrtki (1961). However, by utilizing spectral analysis and form factor, this study shows difference in terms of tidal types from that of Wyrtki's, particularly at Karumba and Groote Eylandt stations.
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Jackson, Stephen. "Thornthwaite Moisture Index and Climate Zones in the Northern Territory." Australian Geomechanics Journal 57, no. 3 (September 1, 2022): 69–85. http://dx.doi.org/10.56295/agj5733.
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The Thornthwaite Moisture Index (TMI) is an established climate parameter for geotechnical engineers to categorise a site and enable estimation of seasonal ground movements associated with soil moisture changes. TMI assessment and mapping for the Northern Territory are presented, using the TMI calculation method commonly used for similar recent studies elsewhere in Australia. The assessment included the analysis of 17 sites within the Northern Territory and one site in Queensland which has enabled development of Climate Zone classifications. Climate data was obtained from the Australian Bureau of Meteorology to calculate the TMI on a ‘year by year’ basis over a target period of 29 years (1990 to 2019). Related work in Queensland (Fox 2002) and Western Australia (Hu et al, 2016) has guided the development of the Northern Territory Climate Zone Map. Further work is required to characterise the soil moisture behaviour in arid zones. A general lack of guidance in AS2870 (2011) for arid areas, including much of the Northern Territory, could be addressed with further research and development.
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Tang, Lin, Jian Zhang, Micheal Simpson, Ami Arthur, Heather Grams, Yadong Wang, and Carrie Langston. "Updates on the Radar Data Quality Control in the MRMS Quantitative Precipitation Estimation System." Journal of Atmospheric and Oceanic Technology 37, no. 9 (September 1, 2020): 1521–37. http://dx.doi.org/10.1175/jtech-d-19-0165.1.
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AbstractThe Multi-Radar-Multi-Sensor (MRMS) system was transitioned into operations at the National Centers for Environmental Prediction in the fall of 2014. It provides high-quality and high-resolution severe weather and precipitation products for meteorology, hydrology, and aviation applications. Among processing modules, the radar data quality control (QC) plays a critical role in effectively identifying and removing various nonhydrometeor radar echoes for accurate quantitative precipitation estimation (QPE). Since its initial implementation in 2014, the radar QC has undergone continuous refinements and enhancements to ensure its robust performance across seasons and all regions in the continental United States and southern Canada. These updates include 1) improved melting-layer delineation, 2) clearance of wind farm contamination, 3) mitigation of corrupt data impacts due to hardware issues, 4) mitigation of sun spikes, and 5) mitigation of residual ground/lake/sea clutter due to sidelobe effects and anomalous propagation. This paper provides an overview of the MRMS radar data QC enhancements since 2014.
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Spencer, G. A., D. F. Pridmore, and D. J. Isles. "Data integration of exploration data using colour space on an image processor." Exploration Geophysics 20, no. 2 (1989): 31. http://dx.doi.org/10.1071/eg989031.
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lmage processing in exploration has rapidly evolved into the field of data integration, whereby independent data sets which coincide in space are displayed concurrently. Interrelation-ships between data sets which may be crucial to exploration can thus be identified much more effectively than with conventional hard copy overlays. The use of perceptual colour space; hue, saturation and luminosity (HSL) provides an effective means for integrating raster data sets, as illustrated with the multi-spectral scanner and airborne geophysical data from the Kambalda area in Western Australia. The integration process must also cater for data in vector format, which is more appropriate for geological, topographic and cultural information, but to date, image processing systems have poorly captured and managed such data. As a consequence, the merging of vector data management software such as GIS (geographic information system) with existing advanced image enhancement packages is an area of active development in the exploration industry.
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Teng, Keat Huat, Joe Zhou, Rao Yandapalli Hanumantha, Yingjie Feng, Zhengmin Zhang, and Loic Michel. "Simplify the variable-depth streamer data processing through pre- migration deghosting: a case study from NWS Australia Data." ASEG Extended Abstracts 2013, no. 1 (December 2013): 1–4. http://dx.doi.org/10.1071/aseg2013ab286.
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Tsagalidis, Evangelos, and Georgios Evangelidis. "Exploiting Domain Knowledge to Address Class Imbalance in Meteorological Data Mining." Applied Sciences 12, no. 23 (December 4, 2022): 12402. http://dx.doi.org/10.3390/app122312402.
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We deal with the problem of class imbalance in data mining and machine learning classification algorithms. This is the case where some of the class labels are represented by a small number of examples in the training dataset compared to the rest of the class labels. Usually, those minority class labels are the most important ones, implying that classifiers should primarily perform well on predicting those labels. This is a well-studied problem and various strategies that use sampling methods are used to balance the representation of the labels in the training dataset and improve classifier performance. We explore whether expert knowledge in the field of Meteorology can enhance the quality of the training dataset when treated by pre-processing sampling strategies. We propose four new sampling strategies based on our expertise on the data domain and we compare their effectiveness against the established sampling strategies used in the literature. It turns out that our sampling strategies, which take advantage of expert knowledge from the data domain, achieve class balancing that improves the performance of most classifiers.
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Ticehurst, Catherine, Zheng-Shu Zhou, Eric Lehmann, Fang Yuan, Medhavy Thankappan, Ake Rosenqvist, Ben Lewis, and Matt Paget. "Building a SAR-Enabled Data Cube Capability in Australia Using SAR Analysis Ready Data." Data 4, no. 3 (July 15, 2019): 100. http://dx.doi.org/10.3390/data4030100.
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A research alliance between the Commonwealth Scientific and Industrial Research Organization and Geoscience Australia was established in relation to Digital Earth Australia, to develop a Synthetic Aperture Radar (SAR)-enabled Data Cube capability for Australia. This project has been developing SAR analysis ready data (ARD) products, including normalized radar backscatter (gamma nought, γ0), eigenvector-based dual-polarization decomposition and interferometric coherence, all generated from the European Space Agency (ESA) Sentinel-1 interferometric wide swath mode data available on the Copernicus Australasia Regional Data Hub. These are produced using the open source ESA SNAP toolbox. The processing workflows are described, along with a comparison of the γ0 backscatter and interferometric coherence ARD produced using SNAP and the proprietary software GAMMA. This comparison also evaluates the effects on γ0 backscatter due to variations related to: Near- and far-range look angles; SNAP’s default Shuttle Radar Topography Mission (SRTM) DEM and a refined Australia-wide DEM; as well as terrain. The agreement between SNAP and GAMMA is generally good, but also presents some systematic geometric and radiometric differences. The difference between SNAP’s default SRTM DEM and the refined DEM showed a small geometric shift along the radar view direction. The systematic geometric and radiometric issues detected can however be expected to have negligible effects on analysis, provided products from the two processors and two DEMs are used separately and not mixed within the same analysis. The results lead to the conclusion that the SNAP toolbox is suitable for producing the Sentinel-1 ARD products.
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Merzlyakov, E. G., Yu I. Portnyagin, C. Jacobi, N. J. Mitchell, H. G. Muller, A. H. Manson, A. N. Fachrutdinova, W. Singer, and P. Hoffmann. "On the longitudinal structure of the transient day-to-day variation of the semidiurnal tide in the mid-latitude lower thermosphere − I. Winter season." Annales Geophysicae 19, no. 5 (May 31, 2001): 545–62. http://dx.doi.org/10.5194/angeo-19-545-2001.
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Abstract. The longitudinal structure of the day-to-day variations of semidiurnal tide amplitudes is analysed based on coordinated mesosphere/lower thermosphere wind measurements at several stations during three winter campaigns. Possible excitation sources of these variations are discussed. Special attention is given to a nonlinear interaction between the semidiurnal tide and the day-to-day mean wind variations. Data processing includes the S-transform analysis which takes into account transient behaviour of secondary waves. It is shown that strong tidal modulations appear during a stratospheric warming and may be caused by aperiodic mean wind variations during this event.Key words. Meteorology and atmospheric dynamics (middle atmosphere dynamics; waves and tides)
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Cimini, D., M. Nelson, J. Güldner, and R. Ware. "Forecast indices from ground-based microwave radiometer for operational meteorology." Atmospheric Measurement Techniques Discussions 7, no. 7 (July 14, 2014): 6971–7011. http://dx.doi.org/10.5194/amtd-7-6971-2014.
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Abstract. Today, commercial microwave radiometers profilers (MWRP) are robust and unattended instruments providing real time accurate atmospheric observations at ~ 1 min temporal resolution under nearly all-weather conditions. Common commercial units operate in the 20–60 GHz frequency range and are able to retrieve profiles of temperature, vapour density, and relative humidity. Temperature and humidity profiles retrieved from MWRP data are used here to feed tools developed for processing radiosonde observations to obtain values of forecast indices (FI) commonly used in operational meteorology. The FI considered here include K index, Total Totals, KO index, Showalter index, T1 Gust, Fog Threat, Lifted Index, S Index (STT), Jefferson Index, MDPI, Thompson Index, TQ Index, and CAPE. Values of FI computed from radiosonde and MWRP-retrieved temperature and humidity profiles are compared in order to quantitatively demonstrate the level of agreement and the value of continuous FI updates. This analysis is repeated for two sites at midlatitude, the first one located at low altitude in Central Europe (Lindenberg, Germany), while the second one located at high altitude in North America (Whistler, Canada). It is demonstrated that FI computed from MWRP well correlate with those computed from radiosondes, with the additional advantage of nearly continuous update. The accuracy of MWRP-derived FI is tested against radiosondes, taken as a reference, showing different performances depending upon index and environmental situation. Overall, FI computed from MWRP retrievals agree well with radiosonde values, with correlation coefficients usually above 0.8 (with few exceptions). We conclude that MWRP retrievals can be used to produce meaningful FI, with the advantage (with respect to radiosondes) of nearly continuous update.