The Rapid Refresh (RAP), an hourly updated assimilation and model forecast system, replaced the Rapid Update Cycle (RUC) as an operational regional analysis and forecast system among the suite of models at the NOAA/National Centers for Environmental Prediction (NCEP) in 2012. The need for an effective hourly updated assimilation and modeling system for the United States for situational awareness and related decision-making has continued to increase for various applications including aviation (and transportation in general), severe weather, and energy. The RAP is distinct from the previous RUC in three primary aspects: a larger geographical domain (covering North America), use of the community-based Advanced Research version of the Weather Research and Forecasting (WRF) Model (ARW) replacing the RUC forecast model, and use of the Gridpoint Statistical Interpolation analysis system (GSI) instead of the RUC three-dimensional variational data assimilation (3DVar). As part of the RAP development, modifications have been made to the community ARW model (especially in model physics) and GSI assimilation systems, some based on previous model and assimilation design innovations developed initially with the RUC. Upper-air comparison is included for forecast verification against both rawinsondes and aircraft reports, the latter allowing hourly verification. In general, the RAP produces superior forecasts to those from the RUC, and its skill has continued to increase from 2012 up to RAP version 3 as of 2015. In addition, the RAP can improve on persistence forecasts for the 1–3-h forecast range for surface, upper-air, and ceiling forecasts.

The Rapid Update Cycle (RUC), an operational regional analysis-forecast system among the suite of models at the National Centers for Environmental Prediction (NCEP), is distinctive in two primary aspects: its hourly assimilation cycle and its use of a hybrid isentropic-sigma vertical coordinate. The use of a quasi-isentropic coordinate for the analysis increment allows the influence of observations to be adaptively shaped by the potential temperature structure around the observation, while the hourly update cycle allows for a very current analysis and short-range forecast. Herein, the RUC analysis framework in the hybrid coordinate is described, and some considerations for high-frequency cycling are discussed. A 20-km 50-level hourly version of the RUC was implemented into operations at NCEP in April 2002. This followed an initial implementation with 60-km horizontal grid spacing and a 3-h cycle in 1994 and a major upgrade including 40-km horizontal grid spacing in 1998. Verification of forecasts from the latest 20-km version is presented using rawinsonde and surface observations. These verification statistics show that the hourly RUC assimilation cycle improves short-range forecasts (compared to longer-range forecasts valid at the same time) even down to the 1-h projection.

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A mesoscale atmospheric forecast model configured in a hybrid isentropic-sigma vertical coordinate and used in the NOAA Rapid Update Cycle (RUC) for operational numerical guidance is presented. The RUC model is the only quasi-isentropic forecast model running operationally in the world and is distinguished from other hybrid-isentropic models by its application at fairly high horizontal resolution (10-20 km) and a generalized vertical coordinate formulation that allows model levels to remain continuous and yet be purely isentropic well into the middle and even lower troposphere. The RUC model is fully described in its 2003 operational version, including numerics and a set of fairly advanced physical parameterizations. The use of these parameterizations, including mixed-phase cloud microphysics and an ensemble-closure-based cumulus parameterization, is fully consistent with the RUC vertical coordinate without any loss of generality. A series of experiments confirm that the RUC hybrid θ-σ coordinate reduces cross-coordinate transport over quasi-horizontal σ formulation. This reduction in cross-coordinate vertical transport results in less numerical vertical diffusion, and thereby improves numerical accuracy for moist reversible processes. Finally, a forecast of a strong cyclogenesis case over the eastern United States is presented in which the RUC model produced an accurate 36-h prediction, especially in a 10-km nested version. Horizontal and vertical plots from these forecasts give evidence of detailed yet coherent structures of potential vorticity, moisture, and vertical motion.

Abstract. A coupled atmospheric/land-surface model covering the conterminous UnitedStates with an associated 1-hour atmospheric data assimilation cycle, the Mesoscale Analysis and Prediction System (MAPS), has been improved to include a snow accumulation/melting scheme and also parameterization of processes in frozen soil. The new aspects of the land-surface model are described in this paper, along with detailed one-dimensional (l-D) tests using an 18-year observation data set from Valday, Russia. These tests show that the MAPS 1-D soil/vegetation/snow model is capable of providing accurate simulations over multiyear periods at locations with significant snow cover and frozen soil. A statistical analysis of the tests shows the expected improvement in snow depth, skin temperature, and especially in runoff from inclusion of these additional surface processes during the spring melting season. This performance in 1-D tests is a necessary prerequisite for robust long-term behavior of soil temperature and moisture fields and other components of the hydrological cycle in the 3-D MAPS coupled assimilation cycle. For GCIP a key question is the degree to which a coupled atmospheric/land-surface model, constrained by hourly assimilation of atmospheric observations to follow the evolution of the atmosphere accurately, can provide a realistic evolution of hydrological fields and time-varying soil fields that are not observed over large areas. A prerequisite for success is that the soil/vegetation/snow component of the coupled model, which is constrained only by atmospheric boundary conditions and definition of fields such as vegetation type and fraction and soil type, must be sufficiently robust to avoid drift over long periods of time. The land surface component of this model must also account for cold-season processes important in middle and 4077