Many contemporaneously aggregated variables have stochastic aggregation weights. We compare different forecasts for such variables including univariate forecasts of the aggregate, a multivariate forecast of the aggregate that uses information from the disaggregate components, a forecast which aggregates a multivariate forecast of the disaggregate components and the aggregation weights, and a fo...

A series of experimental forecasts are performed to evaluate the impact of satellite-derived winds on numerical hurricane track predictions using the GFDL model. Over 100 cases are examined from 10 different storms covering 3 seasons (1996-1998), enabling us to account for the large case-to-case variability in the forecast results when assessing the wind impact. On average, assimilation of the ...

Abstract Permafrost and seasonally frozen ground are important surface features in highlatitudes. Because of this, a soil-frost parameterization was added to the Penn State University/NCAR mesoscale meteorological model MM5 in combination with the well validated hydro-thermodynamic soil vegetation scheme HTSVS, which takes into account among other things soil freezing and thawing. Reanalysis of...

Four different error-forecast updating models are investigated in terms of their capability of providing real-time river flow forecast accuracy superior to that of rainfall-runoff models applied in the simulation (nonupdating) mode. The first and most widely used is the single autoregressive (AR) model, the second being an elaboration of that model, namely the autoregressive-threshold (AR-TS) u...

The 24–25 January 2000 eastern United States snowstorm was noteworthy as operational numerical weather prediction (NWP) guidance was poor for lead times as short as 36 h. Despite improvements in the forecast of the surface cyclone position and intensity at 1200 UTC 25 January 2000 with decreasing lead time, NWP guidance placed the westward extent of the midtropospheric, frontogenetically forced...

The focus of this paper is to construct daily time series exchange rate forecast models of Samoan Tala/USD and Tala/AUD during the year 2008 to 2012 with neural network The performance of the models was measured by using varies error functions such as Root Square mean error (RSME), Mean absolute error (MAE), and Mean absolute percentage error (MAPE). Our empirical findings suggest that AR (1) m...