Search Results
Netherlands and using an experimental reforcasting dataset produced by the ECMWF (see below), Schmeits and Kok (2010) have shown a similar skill improvement for the extended logistic regression and a modified version of the Bayesian model averaging for the first five forecast days. To determine the error characteristics corresponding to a specific NWP model, it has been proposed to perform hindcasts of past meteorological situations using the same model. Such hindcast datasets have been built and tested
Netherlands and using an experimental reforcasting dataset produced by the ECMWF (see below), Schmeits and Kok (2010) have shown a similar skill improvement for the extended logistic regression and a modified version of the Bayesian model averaging for the first five forecast days. To determine the error characteristics corresponding to a specific NWP model, it has been proposed to perform hindcasts of past meteorological situations using the same model. Such hindcast datasets have been built and tested
500-hPa geopotential height field, achieving a hindcast correlation skill ( r s ) of r s = 0.45 for the period 1948–97. Saunders and Qian (2002) found that two modes of late summer/early autumn North Atlantic SST variability 1950–2001 were skillful in predicting a range of upcoming winter NAO indices with r s between r s = 0.47 and r s = 0.63. A horseshoelike North Atlantic summer SST pattern has also been shown to explain up to 16% of the early winter atmospheric variance 1958
500-hPa geopotential height field, achieving a hindcast correlation skill ( r s ) of r s = 0.45 for the period 1948–97. Saunders and Qian (2002) found that two modes of late summer/early autumn North Atlantic SST variability 1950–2001 were skillful in predicting a range of upcoming winter NAO indices with r s between r s = 0.47 and r s = 0.63. A horseshoelike North Atlantic summer SST pattern has also been shown to explain up to 16% of the early winter atmospheric variance 1958
1. Introduction The U.S. Army Corps of Engineers (USACE) Wave Information Study (WIS) program ( Tracy and Cialone 2004 ) is establishing a multidecade wave climatology for the Pacific basin to support a variety of coastal planning and engineering activities. To facilitate selection of an appropriate wave hindcast technology, the performance of three modern numerical spectral wave models is evaluated in the Pacific basin over calendar year 2000. The technologies evaluated include the third
1. Introduction The U.S. Army Corps of Engineers (USACE) Wave Information Study (WIS) program ( Tracy and Cialone 2004 ) is establishing a multidecade wave climatology for the Pacific basin to support a variety of coastal planning and engineering activities. To facilitate selection of an appropriate wave hindcast technology, the performance of three modern numerical spectral wave models is evaluated in the Pacific basin over calendar year 2000. The technologies evaluated include the third
look” approach), whereupon more objective statistical or physical models could be employed for smaller areas (e.g., expected contrail distributions relative to flight frequencies and aircraft types) or to yield a higher temporal resolution ( Schumann 2012 ). Prior to the possibility for application of the synoptic attributes of CFAs to their near-real-time prediction for wide areas, it is necessary that past outbreak events be accurately hindcast. Thus, detailed knowledge of CONUS subregions where
look” approach), whereupon more objective statistical or physical models could be employed for smaller areas (e.g., expected contrail distributions relative to flight frequencies and aircraft types) or to yield a higher temporal resolution ( Schumann 2012 ). Prior to the possibility for application of the synoptic attributes of CFAs to their near-real-time prediction for wide areas, it is necessary that past outbreak events be accurately hindcast. Thus, detailed knowledge of CONUS subregions where
shore ( Resio and Westerink 2008 ). One cost of these model enhancements has been a substantial escalation in the required computer time ( Tanaka et al. 2010 ). Consequently, their uses have been limited mostly to forensic hindcast studies ( Ebersole et al. 2007 ), design studies ( USACE 2009 ), and Federal Emergency Management Agency (FEMA) National Flood Insurance Program studies ( FEMA 2008 ), all of which allow flexible limits on model execution time. On the other hand, real-time forecasting
shore ( Resio and Westerink 2008 ). One cost of these model enhancements has been a substantial escalation in the required computer time ( Tanaka et al. 2010 ). Consequently, their uses have been limited mostly to forensic hindcast studies ( Ebersole et al. 2007 ), design studies ( USACE 2009 ), and Federal Emergency Management Agency (FEMA) National Flood Insurance Program studies ( FEMA 2008 ), all of which allow flexible limits on model execution time. On the other hand, real-time forecasting
al. 2010 ; Boyle and Klein 2010 ; Lin et al. 2012 ; Xie et al. 2012 ). To facilitate the use of NWP approach in climate model evaluation and development and to allow for an effective assessment of model performance with both satellite observations and detailed field data, we compiled several metrics and diagnostics in this study, especially for climate model hindcasts on tropical precipitation-related processes. Applying metrics to systematically evaluate climate model performance in
al. 2010 ; Boyle and Klein 2010 ; Lin et al. 2012 ; Xie et al. 2012 ). To facilitate the use of NWP approach in climate model evaluation and development and to allow for an effective assessment of model performance with both satellite observations and detailed field data, we compiled several metrics and diagnostics in this study, especially for climate model hindcasts on tropical precipitation-related processes. Applying metrics to systematically evaluate climate model performance in
studying the variability of the inertial KE jet and the Kuroshio recirculation, both highly nonlinear phenomena full of internal variability. Opportunities are emerging to study low-frequency variability of the narrow KE jet owing to the accumulation of satellite altimeter observations and a recent multidecadal, eddy-resolving (0.1° horizontal resolution) OGCM hindcast performed on Japan’s Earth Simulator supercomputer. From 11-yr-long satellite SSH data, Qiu (2003) found decadal modulations in the
studying the variability of the inertial KE jet and the Kuroshio recirculation, both highly nonlinear phenomena full of internal variability. Opportunities are emerging to study low-frequency variability of the narrow KE jet owing to the accumulation of satellite altimeter observations and a recent multidecadal, eddy-resolving (0.1° horizontal resolution) OGCM hindcast performed on Japan’s Earth Simulator supercomputer. From 11-yr-long satellite SSH data, Qiu (2003) found decadal modulations in the
capable of outperforming a persistence forecast in a perfect-prognostic mode, indicating that statistical–dynamical forecasts of IKE might be possible in the future. Building upon those results, the focus of this study is to further evaluate the operational potential of IKE forecasts using a more sophisticated statistical–dynamical scheme in a hindcast mode. Despite the successes of the proof-of-concept SPIKE model from KM14 , linear regression is suboptimal for statistical weather prediction because
capable of outperforming a persistence forecast in a perfect-prognostic mode, indicating that statistical–dynamical forecasts of IKE might be possible in the future. Building upon those results, the focus of this study is to further evaluate the operational potential of IKE forecasts using a more sophisticated statistical–dynamical scheme in a hindcast mode. Despite the successes of the proof-of-concept SPIKE model from KM14 , linear regression is suboptimal for statistical weather prediction because
fields of (left) SST and (right) SLP for boreal winter (November–March) of 1976–85 calculated from (a) HadISST, (b) NCEP ( Kalnay et al. 1996 ), (c),(d) the ensemble mean of the initialization runs, and (e),(f) the ensemble mean of the hindcast runs. Contour interval of SST is 0.1°C. The contours for SLP are ±3, ±2, ±1, ±0.5, and 0 hPa. The zero contours for both SST and SLP are highlighted. All the major features in the plots from the model runs are significantly different from zero at the 95% level
fields of (left) SST and (right) SLP for boreal winter (November–March) of 1976–85 calculated from (a) HadISST, (b) NCEP ( Kalnay et al. 1996 ), (c),(d) the ensemble mean of the initialization runs, and (e),(f) the ensemble mean of the hindcast runs. Contour interval of SST is 0.1°C. The contours for SLP are ±3, ±2, ±1, ±0.5, and 0 hPa. The zero contours for both SST and SLP are highlighted. All the major features in the plots from the model runs are significantly different from zero at the 95% level
this study, we will use a series of GCM hindcast experiments to assess the contributions of these two components to the seasonal predictability in the Atlantic SST and in the precipitation over South America. We will analyze the behavior of the simulated SST anomalies in ensemble hindcast experiments using an atmospheric GCM partially coupled to a mixed layer ocean model for the Atlantic. The experimental design is described in section 2 . The results of the model simulations of the Atlantic SST
this study, we will use a series of GCM hindcast experiments to assess the contributions of these two components to the seasonal predictability in the Atlantic SST and in the precipitation over South America. We will analyze the behavior of the simulated SST anomalies in ensemble hindcast experiments using an atmospheric GCM partially coupled to a mixed layer ocean model for the Atlantic. The experimental design is described in section 2 . The results of the model simulations of the Atlantic SST
