To forecast geomagnetic storms, we had examined initially observed parameters of coronal mass ejections (CMEs) and introduced an empirical storm forecast model in a previous study. Now we suggest a two-step forecast considering not only CME parameters observed in the solar vicinity but also solar wind conditions near Earth to improve the forecast capability. We consider the empirical solar wind...

To make optimal decisions, end-users of decision support systems require information accurately describing the uncertainty of the underlying weather forecasts. Air temperature, dew point temperature, and wind speed are critical surface weather variables in many economic sectors. The generation of sharp and calibrated probabilistic forecasts and their effective presentation to decision makers ar...

The Beveridge-Nelson decomposition defines the trend component in terms of the eventual forecast function, as the value the series would take if it were on its long-run path. The paper introduces the multistep Beveridge-Nelson decomposition, which arises when the forecast function is obtained by the direct autoregressive approach, which optimizes the predictive ability of the AR model at foreca...

clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

Density forecast combinations are becoming increasingly popular as a means of improving forecast ‘accuracy’, as measured by a scoring rule. In this paper we generalise this literature by letting the combination weights follow more general schemes. Sieve estimation is used to optimise the score of the generalised density combination where the combination weights depend on the variable one is try...

Introduction Conclusions References Tables Figures Back Close Full Screen / Esc Papers published in Hydrology and Earth System Sciences Discussions are under open-access review for the journal Hydrology and Earth System Sciences Abstract Introduction Conclusions References Tables Figures Back Close Full Screen / Esc Abstract In the present paper we describe some methods for verifying and evalua...

[1] Magnetically active times, e.g., Kp > 5, are notoriously difficult to predict, precisely the times when such predictions are crucial to the space weather users. Taking advantage of the routinely available solar wind measurements at Langrangian point (L1) and nowcast Kps, Kp forecast models based on neural networks were developed with the focus on improving the forecast for active times. To ...

In this paper we investigate whether and how far density forecasts sensibly can be combined to produce a “better” pooled density forecast. In so doing we bring together two important but hitherto largely unrelated areas of the forecasting literature in economics, density forecasting and forecast combination. We provide simple Bayesian methods of pooling information across alternative density fo...

JMA operates NWP models to meet various kinds of requirements on weather forecasting. The suite of the NWP models covers a wide temporal range of forecast periods from a few hours to two seasons providing a seamless sequence of products for the public. The Global Spectral Model (GSM) produces 84-hour forecast four times a day (00, 06, 12, 18 UTC) to support the official short-range forecasting ...

Central Banks regularly make forecasts, such as the Fed’s Greenbook forecast, that are conditioned on hypothetical paths for the policy interest rate. While there are good public policy reasons to evaluate the quality of such forecasts, up until now, the most common approach has been to ignore their conditional nature and apply standard forecast e¢ ciency tests. In this paper we derive tests fo...