Abstract
Abstract This paper describes a forecasting configuration of the Geophysical Fluid Dynamics Laboratory (GFDL) High-resolution Atmospheric Model (HiRAM). HiRAM represents an early attempt in unifying, within a global modeling framework, the capabilities of GFDL’s low-resolution climate models for Intergovernmental Panel on Climate Change (IPCC) type climate change assessments and high-resolution limited-area models for hurricane predictions. In this study, the potential of HiRAM as a forecasting tool is investigated by applying the model to the near-term and intraseasonal hindcasting of tropical cyclones (TCs) in the Atlantic basin from 2006 to 2009. Results demonstrate that HiRAM provides skillful near-term forecasts of TC track and intensity relative to their respective benchmarks from t = 48 h through t = 144 h. At the intraseasonal time scale, a simple HiRAM ensemble provides skillful forecasts of 21-day Atlantic basin TC activity at a 2-day lead time. It should be noted that the methodology used to produce these hindcasts is applicable in a real-time forecasting scenario. While the initial experimental results appear promising, the HiRAM forecasting system requires various improvements in order to be useful in an operational setting. These modifications are currently under development and include a data assimilation system for forecast initialization, increased horizontal resolution to better resolve the vortex structure, 3D ocean model coupling, and wave model coupling. An overview of these ongoing developments is provided, and the specifics of each will be described in subsequent papers.
Highlights
Global forecasting models and their data assimilation systems, even at much lower resolution, are critical to weather prediction at the regional scale
This paper introduces an early version of the HighResolution Atmosphere Model (HiRAM) developed at the National Atmospheric and Oceanic Administration/ Geophysical Fluid Dynamics Laboratory (NOAA/GFDL) and applied to forecasting tropical cyclones (TCs) activity in the Atlantic basin
This contrasts with operational global numerical weather prediction (NWP) or climate models, which require significant modifications to many of their physical parameterizations any time the horizontal resolution is upgraded
Summary
Global forecasting models and their data assimilation systems, even at much lower resolution, are critical to weather prediction at the regional scale. Many of the global operational models used for TC track forecasting in the Atlantic are handicapped by the resolution, initialization, and parameterizations of the smaller-scale processes (Knaff et al 2007) As a result, these models cannot adequately resolve the inner core of a TC, which leads to little skill in forecasting TC intensity (DeMaria et al 2007). HiRAM’s superior modeling of the large-scale environmental flow, and the simultaneous initial condition error growth saturation, are the most likely reasons for the observed track forecast improvement relative to both NOGAPS and GFDL at these later lead times By t 5 120 h, the HiRAM forecast track error is 260 n mi, which is 15 and 25 n mi smaller, respectively, than for the GFDL and NOGAPS forecast track errors. Likely lead to an improved initial wind–pressure relationship, which should further reduce the initial negative intensity bias
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