Results 51 to 60 of about 6,728 (212)

Enhancing Rainfall Nowcasting Using Generative Deep Learning Model with Multi-Temporal Optical Flow

Remote Sensing, 2023
Precipitation nowcasting is critical for preventing damage to human life and the economy. Radar echo tracking methods such as optical flow algorithms have been widely employed for precipitation nowcasting because they can track precipitation motions well.
Ji-Hoon Ha, Hyesook Lee
doaj   +1 more source

The Impact of Dealiasing Biases on Bird and Insect Data Products of C-Band Weather Radars and Consequences for Aeroecological Applications

Remote Sensing
(1) The aliasing of radial velocities from weather radars is a known challenge in meteorology. It may also occur during bird migration if the unambiguous velocity threshold is below the birds’ ground speed.
Nadja Weisshaupt, Bent Harnist, Jarmo Koistinen   +2 more
doaj   +1 more source

Long lead-time radar rainfall nowcasting method incorporating atmospheric conditions using long short-term memory networks

Frontiers in Environmental Science, 2023
High-resolution radar rainfall data have great potential for rainfall predictions up to 6 h ahead (nowcasting); however, conventional extrapolation approaches based on in-built physical assumptions yield poor performance at longer lead times (3–6 h ...
Kexin Zhu, Kexin Zhu, Kexin Zhu, Kexin Zhu, Qiqi Yang, Qiqi Yang, Qiqi Yang, Shuliang Zhang, Shuliang Zhang, Shuliang Zhang, Shuai Jiang, Shuai Jiang, Shuai Jiang, Shuai Jiang, Tianle Wang, Tianle Wang, Tianle Wang, Jinchen Liu, Jinchen Liu, Jinchen Liu, Yuxuan Ye, Yuxuan Ye, Yuxuan Ye   +22 more
doaj   +1 more source

The Impact of Uncertainty on Forecasting the US Economy

Journal of Forecasting, EarlyView.
ABSTRACT This paper examines the predictive value of uncertainty measures for key macroeconomic indicators across multiple forecast horizons. We evaluate how different uncertainty proxies—economic policy uncertainty (EPU), VIX, geopolitical risk, and measures of macroeconomic and financial uncertainty—enhance forecast accuracy for industrial production,
Angelica Ghiselli
wiley   +1 more source

Experimental Study of Cloud-to-Ground Lightning Nowcasting with Multisource Data Based on a Video Prediction Method

Remote Sensing, 2022
The evolution of lightning generation and extinction is a nonlinear and complex process, and the nowcasting results based on extrapolation and numerical models largely differ from the real situation.
Shuchang Guo, Jinyan Wang, Ruhui Gan, Zhida Yang, Yi Yang   +4 more
doaj   +1 more source

Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence From Markov‐Switching Multifractal Models

Journal of Forecasting, EarlyView.
ABSTRACT This paper adopts a bivariate Markov‐switching multifractal (BMSM) model to reexamine comovement in SV between commodity, foreign exchange (FX), and stock markets. After the 2007–2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio
Ruipeng Liu, Mawuli Segnon, Oguzhan Cepni, Rangan Gupta   +3 more
wiley   +1 more source

DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

Journal of Forecasting, EarlyView.
ABSTRACT This paper compares within‐sample and out‐of‐sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets, and Wouters model is the chosen laboratory using quarterly real‐time euro area data vintages, covering 2001Q1–2019Q4.
Anders Warne
wiley   +1 more source

Nowcasting Economic Activity Using Electricity Market Data: The Case of Lithuania

Economies, 2023
Traditional forecasting methods usually rely on historical macroeconomic indicators with significant delays. To address this problem, new opportunities for economic modeling and forecasting are emerging by using real-time data and making nowcasting of ...
Alina Stundziene, Vaida Pilinkiene, Jurgita Bruneckiene, Andrius Grybauskas, Mantas Lukauskas   +4 more
doaj   +1 more source

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares

Journal of Forecasting, EarlyView.
ABSTRACT Dynamic factor models (DFMs) have found great success in nowcasting and short‐term macroeconomic forecasting when incorporating large sets of predictive information. The factor loadings are typically estimated cross‐sectionally with principal component analysis (PCA) or maximum likelihood (ML), which ignore whether the factors have predictive ...
Samuel Rauhala
wiley   +1 more source

Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now

Journal of Forecasting, EarlyView.
ABSTRACT We propose PRISM‐Now, a novel ensemble forecasting system for near‐term GDP projection. Recognizing that relevant economic information evolves over time, we treat forecasts from multiple base models as draws from a mixture distribution of “good” and “bad” estimates, whose composition changes continuously and cannot be identified ex ante.
Beomseok Seo, Hyungbae Cho, Dongjae Lee
wiley   +1 more source