Searched for: subject%3A%22nowcasting%22
(1 - 18 of 18)
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Martinez Lopez, V.A. (author), van Urk, G.A. (author), Doodkorte, P.J.F. (author), Zeman, M. (author), Isabella, O. (author), Ziar, H. (author)
Clouds moving in front or away from the sun are the leading cause of irradiance variability. These variations have a repercussion on the electricity production of photovoltaic systems. Predicting such changes is essential for proper control of these systems and for maintaining grid stability. Images from the sky have proven to help with short...
journal article 2024
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Zou, Yanghuan (author)
Machine learning models offer promising potential in precipitation nowcasting. However, a common issue faced by many of these models is the tendency to produce blurry precipitation nowcasts, which are unrealistic. Previous research on the deep learning model - TrajGRU (Shi et al., 2017) indicated that data imbalance in radar images and the...
master thesis 2023
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Grzebyk, Daniel (author), Alcañiz Moya, A. (author), Donker, Jaap (author), Zeman, M. (author), Ziar, H. (author), Isabella, O. (author)
Due to the inherent uncertainty in photovoltaic (PV) energy generation, an accurate power forecasting is essential to ensure a reliable operation of PV systems and a safe electric grid. Machine learning (ML) techniques have gained popularity on the development of this task due to its increased accuracy. Most literature, however, focuses only...
journal article 2023
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Imhoff, Ruben O. (author), De Cruz, Lesley (author), Dewettinck, Wout (author), Brauer, Claudia C. (author), Uijlenhoet, R. (author), van Heeringen, Klaas Jan (author), Velasco-Forero, Carlos (author), Nerini, Daniele (author), Van Ginderachter, Michiel (author), Weerts, Albrecht H. (author)
Flash flood early warning requires accurate rainfall forecasts with a high spatial and temporal resolution. As the first few hours ahead are already not sufficiently well captured by the rainfall forecasts of numerical weather prediction (NWP) models, radar rainfall nowcasting can provide an alternative. Because this observation-based method...
journal article 2023
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Lin, Steven (author)
Extreme rainfall brings substantial threats to lives, infrastructure, and the economy in cities. Radar rainfall nowcasting was proven able to provide forecasts up to 2 to 3 hours in advance on a catchment scale. However, an extensive evaluation of nowcasting skills for urban areas has not been performed yet. In this study, we selected 80 extreme...
master thesis 2022
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Bi, Haoran (author)
Extreme precipitation can often cause serious hazards such as flooding and landslide. Both pose a threat to human lives and lead to substantial economic loss. It is crucial to develop a reliable weather forecasting system that can predict such extreme events to mitigate the effect of heavy precipitation and increase resilience to these hazards....
master thesis 2022
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Wang, Zhiyi (author)
Deep-learning models are commonly used in short-term precipitation forecasting. However, most deep-learning models are likely to produce blurry output problems. In order to get realistic and accurate results, AENN, a variant of Generative Adversarial Networks (GANs), has been developed. The AENN implements an additional temporal discriminator to...
master thesis 2022
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Dekker, Diewertje (author)
Accurate short term rain predictions are important for flood early warning systems, emergency services, energy management and other services that that make weather dependent decisions. Recently introduced machine learning models suffer from blurry and unrealistic predictions at longer lead times, causing poor performance on the rarer heavy...
master thesis 2022
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Schoenmaker, Karlijn (author)
Disasters like inland floods and landslides are a cause of extreme rainfall. To increase the time to take early measures against such disasters it is of great importance to have access to accurate prediction of the rainfall. For the prediction of floods, Quantitative Precipitation Forecasts (QPFs) are used as input for hydrologic models....
master thesis 2022
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Imhoff, R. O. (author), Brauer, C. C. (author), van Heeringen, K. J. (author), Uijlenhoet, R. (author), Weerts, A. H. (author)
To assess the potential of radar rainfall nowcasting for early warning, nowcasts for 659 events were used to construct discharge forecasts for 12 Dutch catchments. Four open-source nowcasting algorithms were tested: Rainymotion Sparse (RM-S), Rainymotion DenseRotation (RM-DR), Pysteps deterministic (PS-D), and probabilistic (PS-P) with 20...
journal article 2022
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Rosin, T. R. (author), Kapelan, Z. (author), Keedwell, E. (author), Romano, M. (author)
Blockages are a major issue for wastewater utilities around the world, causing loss of service, environmental pollution, and significant cleanup costs. Increasing telemetry in combined sewer overflows (CSOs) provides the opportunity for near real-time data-driven modelling of wastewater networks. This paper presents a novel methodology,...
journal article 2022
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Dong, Xichao (author), Zhao, Zewei (author), Wang, Yupei (author), Wang, J. (author), Hu, Cheng (author)
Nowadays deep learning-based weather radar echo extrapolation methods have competently improved nowcasting quality. Current pure convolutional or convolutional recurrent neural network-based extrapolation pipelines inherently struggle in capturing both global and local spatiotemporal interactions simultaneously, thereby limiting nowcasting...
journal article 2022
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van der Kooij, Eva (author)
Accurate short-term forecasts, also known as nowcasts, of heavy precipitation are desirable for creating early warning systems for extreme weather and its consequences, e.g. urban flooding. In this research, we explore the use of machine learning for short-term prediction of heavy summer rainfall showers in the Netherlands. We explore the use of...
master thesis 2021
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Rosin, T. R. (author), Romano, M. (author), Keedwell, E. (author), Kapelan, Z. (author)
Combined Sewer Overflows (CSOs) are a major source of pollution and urban flooding, spilling untreated wastewater directly into water bodies and the surrounding environment. If overflows can be predicted sufficiently in advance, then techniques are available for mitigation. This paper presents a novel bi-model committee evolutionary...
journal article 2021
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Esseveld, J.R. (author)
Records from ledgers of Dutch companies all across the Netherlands are used in this study. Records can be submitted in the ledgers with various lags, because the data of many different bookkeepers is involved with different workflows. Bookkeepers can be punctual or late, therefore records can be submitted with various lags in the ledgers. This...
master thesis 2020
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Kabbouch, Y. (author)
Radar rainfall nowcasting stands for the prediction of rainfall amounts and intensities over the next 6 hours by means of statistical extrapolation of radar measurements. It is the principal ingredient for modern flood forecasting and early warning systems. Radar forecasts are generated by identifying and tracking rainfall cells in radar images...
master thesis 2020
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Grzebyk, Daniel (author)
An increasing number of photovoltaic (PV) systems are being installed worldwide and residential sector is responsible for a large part of this growth. Small scale PV systems do not have complex measuring devices and their breakdowns are not spotted immediately by the system owners. This might lead to prolonged time without generating power and...
master thesis 2020
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Snoek, Jasper (author)
Nowcasting, synonymous for short term (0-6h) forecasting of precipitation with high detail in terms of location, timing and intensity, is a dynamic field of research in weather forecasting that is relevant in mitigating the impact of severe weather events. Along with the development of remote sensing instruments, the first methods that were...
master thesis 2017
Searched for: subject%3A%22nowcasting%22
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