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Unified Analysis and Nowcasting Through A 3D Rapidly Updating Analysis (RUA)


This presentation will describe a prototype Rapidly Updating Analysis (RUA) nowcasting system that is running in real-time at ESRL GSD and has the potential to unify NOAA real-time mesoscale analysis (RTMA) and nowcasting capabilities into a single system to meet user needs for situational awareness and verification. The system will be built upon and extend the current RTMA analysis to three dimensions, assimilate in-situ and remote observations (including radar and satellite) from a variety of platforms with a high-resolution very-short-range model background, and synthesize the output to produce new 3-D analysis products with a short latency and rapid updates. Key 2D nowcasting fields that are intrinsically a function of 3D space (PBL height, precipitable water, ceiling) would be diagnosed from the 3-D RUA fields, giving physical consistency with a high percentage of information content through a very accurate high-resolution model background. Extending the operational RTMA to three dimensions allows for the creation of highly useful nowcasting products, including full-column representation of standard meteorological fields such as temperature, water vapor, and wind, as well as hydrometeors (i.e., clouds, precipitation of all forms), and eventually aerosols. The RUA will also include 2-D land-surface diagnostics (e.g., soil moisture, snow state from multi-level land-surface fields), and convective (e.g., hail size, supercell rotation tracks) fields, developed through collaboration with the National Water Center (NWC) and National Severe Storms Laboratory (NSSL), respectively. The RUA will also improve analysis fields for the NOAA National Blend of Models (NBM) project and add a 3-dimensional perspective including cloud-hydrometeor fields, and could allow merging in of the NCEP/SPC Hourly Mesoscale Analysis and also provide an initial set of fields for a unified NOAA nowcast system. The are many potential applications for RUA products across numerous sectors (aviation, renewable energy, surface transportation, etc.) The RUA is designed for a 10-min latency, quickly available. An initial prototype RUA has already been developed at NOAA/ESRL and is running at 1-h frequency using a 1-h HRRR forecast background field and is available 60-75 min after the hour. The RUA analysis differs from an analysis used to initialize a model (such as the HRRR) by fitting the observations more closely (after careful observation quality control). This close fit applies to both in situ observations (especially surface observations), but also remotely sensed observations, such as radar data and satellite-derived cloud information. While highly desirable for RTMA/RUA applications, this close fit to observations has the potential to degrade model forecasts. As examples, specification of complete 3D hydrometeor fields from radar data can result in excessive short-range precipitation, leading to a high bias in the soil moisture and related problems. Similarly, full specification of saturated clouds throughout the atmosphere, can lead to a high relative humidity bias. Because the RUA uses a cycled model background, it benefits from the ability of the model to propagate information from observation-rich regions to observation-sparse regions. An example of this benefit is the analysis of precipitation hydrometeor fields (from the background) in regions that do not have radar reflectivity coverage. Planned work is to move the RUA to a 15-min update interval sand increase the update frequency of the underlying HRRR-system, as well as improving the horizontal resolution, and adding more observations to the assimilation. Further work will focus on improving the error covariance information, adding more output fields, and examining nowcast capabilities using the RUA fields as initial conditions. With these enhancements, the RUA has the potential to unify many existing NOAA systems and provide highly accurate, consistent 3D guidance for users in many sectors, including short-range forecasting, aviation, severe-weather, and hydrology. At the conference, an overview of the system and update on ongoing work will be presented.

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January 01, 2017

This publication was presented at the following:

2017 - 97th AMS Annual Meeting
Amer. Meteor. Soc.
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