Results 41 to 50 of about 202,091 (313)
MAPPING COLOURED DISSOLVED ORGANIC MATTER IN MANILA BAY USING SENTINEL-3 AND WASI [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Manila Bay is one of the most significant bodies of water in the Philippines; it has abundant natural resources that have been the source of livelihood and center of socio-economic development for centuries.
A. Manuel +5 more
doaj +1 more source
Frontiers in Environmental Science, 2022 Long-term near-surface soil moisture (SM) data can be obtained on a regional scale through microwave remote sensing. Therefore, to quantitatively analyze the accuracy of multisource remote sensing–based observation products, improve the retrieval ...
Jiazhi Fan +6 more
doaj +1 more source
Statistical post-processing of visibility ensemble forecasts [PDF]
Meteorological Applications 30 (2023), 1-18, 2023 To be able to produce accurate and reliable predictions of visibility has crucial importance in aviation meteorology, as well as in water- and road transportation. Nowadays, several meteorological services provide ensemble forecasts of visibility; however, the skill, and reliability of visibility predictions are far reduced compared to other variables,
arxiv +1 more source
Effect of Climate on Photovoltaic Yield Prediction Using Machine Learning Models
Global Challenges, Volume 7, Issue 1, January 2023., 2023 This work explores the effect of climate on photovoltaic (PV) yield prediction when using machine learning algorithms. A website with open‐source PV power data is created as result of the data gathering process. Forty eight PV systems worldwide divided into four climates are employed for this purpose.
Alba Alcañiz +4 more
wiley +1 more source
Geophysical Research Letters, 2023 Significant variability of raindrop size distributions (DSDs) has been observed in the “21·7” Henan extremely heavy rainfall event (the “21·7” Henan EHR event), while the capability of model to reproduce such complicated heavy rainfall DSDs is yet ...
Gang Chen +8 more
doaj +1 more source
RDIS: Random Drop Imputation With Self-Training for Incomplete Time Series Data
IEEE Access, 2023 Time-series data with missing values are a common occurrence in various fields, including healthcare, meteorology, and robotics. The process of imputation aims to fill in the missing values with valid values.
Tae-Min Choi, Ji-Su Kang, Jong-Hwan Kim
doaj +1 more source
Meteorological training for the digital age: A Blueprint for a new curriculum [PDF]
, 2018 Almost all professional meteorologists take part in meteorological training during their undergraduate or graduate study or professional job training in the public or private sector. Increased benefits can be accrued by employers and employees, if this training is based on the same underpinning skills and attributes, aimed to equip people entering ...
Elizabeth McCrum +9 more
openaire +2 more sources
Predicting post‐wildfire overland flow using remotely sensed indicators of forest productivity
Hydrological Processes, Volume 36, Issue 12, December 2022., 2022 Relations between runoff coefficient and landscape metrics. (a) linear regression for inland plots only, (b) no regression determined for the data, (c‐f) exponential decay function fitted to the data (C = ae(b×x)). Triangles are the mean value for C, the line is the median, the bar show the range between the 25th and 75th percentiles, whiskers are the ...
Philip J. Noske +4 more
wiley +1 more source
Meteorological Applications, 2020 Reliable and affordable telecommunications are an integral part of service‐based economies, but the nature of the associated physical infrastructure leads to considerable exposure to weather.
David J. Brayshaw +3 more
doaj +1 more source
A Machine Learning Tutorial for Operational Meteorology, Part II: Neural Networks and Deep Learning [PDF]
, 2022 Over the past decade the use of machine learning in meteorology has grown rapidly. Specifically neural networks and deep learning have been used at an unprecedented rate. In order to fill the dearth of resources covering neural networks with a meteorological lens, this paper discusses machine learning methods in a plain language format that is targeted
arxiv +1 more source