Results 81 to 90 of about 6,728 (212)

Nowcasting Thunderstorms for Munich Airport

open access: yes, 2012
The successful demonstration and assessment of the DLR thunderstorm nowcasting algorithms at Munich Airport during two campaigns in the summers of 2010 and 2011 are described.
Tafferner, Arnold, Forster, Caroline
core  

The CASA Nowcasting System

open access: yes, 2011
Short-term prediction (nowcasting) of high-impact weather events can lead to significant improvement in warnings and advisories and is of great practical importance.
Evan Ruzanski   +2 more
core   +1 more source

Band‐Pass Filtering With High‐Dimensional Time Series. A Synthetic Indicator of the Medium‐to‐Long Run Component of Growth

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT The paper deals with the construction of a synthetic indicator of economic growth, obtained by projecting a quarterly measure of aggregate economic activity, namely gross domestic product (GDP), into the space spanned by a finite number of smooth principal components, representative of the medium‐to‐long‐run component of economic growth of a ...
Alessandro Giovannelli   +2 more
wiley   +1 more source

Nowcasting Business Cycles Using Toll Data [PDF]

open access: yes
Nowcasting has been a challenge in the recent economic crisis. We introduce the Toll Index, a new monthly indicator for business cycle forecasting and demonstrate its relevance using German data.
Zimmermann, Klaus F., Askitas, Nikos
core  

The Accuracy Smoothness Dilemma in Prediction: A Novel Multivariate M‐SSA Forecast Approach

open access: yesJournal of Time Series Analysis, EarlyView.
ABSTRACT Forecasting presents a complex estimation challenge, as it involves balancing multiple, often conflicting, priorities and objectives. Conventional forecast optimization methods typically emphasize a single metric, such as minimizing the mean squared error (MSE), which may neglect other crucial aspects of predictive performance. To address this
Marc Wildi
wiley   +1 more source

Convcast: An embedded convolutional LSTM based architecture for precipitation nowcasting using satellite data.

open access: yesPLoS ONE, 2020
Nowcasting of precipitation is a difficult spatiotemporal task because of the non-uniform characterization of meteorological structures over time. Recently, convolutional LSTM has been shown to be successful in solving various complex spatiotemporal ...
Ashutosh Kumar   +4 more
doaj   +1 more source

Nowcasting Swiss GDP Growth From Public Lead Texts: Simple Methods Are Sufficient

open access: yesOxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT Public lead texts from Swiss newspapers contain most of the signal needed to nowcast Swiss GDP growth in real time. I build an indicator from daily topic‐specific sentiment and recession measures extracted from three Swiss newspapers and evaluate it in pseudo‐real time.
Marc Burri
wiley   +1 more source

Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++

open access: yesRemote Sensing, 2020
A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called
Isabel Urbich   +2 more
doaj   +1 more source

Nowcasting and forecasting thunderstorms for air traffic with an integrated forecast system based on observations and model data

open access: yes, 2009
This study presents the concept and first results of the Weather Forecast User Oriented System Including Object Nowcasting (WxFUSION), an integrated system using observations and numerical model data to nowcast and forecast weather hazards for air ...
Tafferner, Arnold, Forster, Caroline
core  

Cointegration in a MIDAS Regression

open access: yesOxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT Mixed data sampling (MIDAS) cointegration models are used to analyse variables observed at different frequencies. In this paper, we start from an assumed autoregressive distributed lag (ADL) model for high‐frequency observations, and derive the resulting representation when the dependent variable is only observed at a lower frequency.
H. Peter Boswijk, Philip Hans Franses
wiley   +1 more source

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