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Error Growth Dynamics within Convection-Allowing Ensemble Forecasts over Central U.S. Regions for Days of Active Convection

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  • 1 Jiangsu Meteorological Observatory, Jiangsu Meteorological Bureau, Nanjing, China
  • | 2 Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma
  • | 3 School of Meteorogy, University of Oklahoma, Norman, Oklahoma
  • | 4 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disaster of Education, Nanjing University of Information Science and Technology, Nanjing, China
  • | 5 Key Laboratory of Regional Numerical Weather Prediction, Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou, China
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Abstract

Error growth is investigated based on convection-allowing ensemble forecasts starting from 0000 UTC for 13 active convection events over central to eastern U.S. regions from spring 2018. The analysis domain is divided into the northwest (NW), northeast (NE), southeast (SE), and southwest (SW) quadrants (subregions). Total difference energy and its decompositions are used to measure and analyze error growth at and across scales. Special attention is paid to the dominant types of convection with respect to their forcing mechanisms in the four subregions and the associated difference in precipitation diurnal cycles. The discussions on the average behaviors of error growth in each region are supplemented by four representative cases. Results show that the meso-γ-scale error growth is directly linked to precipitation diurnal cycle while meso-α-scale error growth has a strong link to large-scale forcing. Upscale error growth is evident in all regions/cases but up-amplitude growth within its own scale plays different roles in different regions/cases. When large-scale flow is important (as in the NE region), precipitation is strongly modulated by the large-scale forcing and becomes more organized with time, and upscale transfer of forecast error is stronger. On the other hand, when local instability plays more dominant roles (as in the SE region), precipitation is overall less organized and has the weakest diurnal variations. Its associated errors at the γ and β scale can reach their peaks sooner and meso-α-scale error tends to rely more on growth of error with its own scale. Small-scale forecast errors are directly impacted by convective activities and have a short response time to convection while increasingly larger-scale errors have longer response times and delayed phase within the diurnal cycle.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Ming Xue, mxue@ou.edu

Abstract

Error growth is investigated based on convection-allowing ensemble forecasts starting from 0000 UTC for 13 active convection events over central to eastern U.S. regions from spring 2018. The analysis domain is divided into the northwest (NW), northeast (NE), southeast (SE), and southwest (SW) quadrants (subregions). Total difference energy and its decompositions are used to measure and analyze error growth at and across scales. Special attention is paid to the dominant types of convection with respect to their forcing mechanisms in the four subregions and the associated difference in precipitation diurnal cycles. The discussions on the average behaviors of error growth in each region are supplemented by four representative cases. Results show that the meso-γ-scale error growth is directly linked to precipitation diurnal cycle while meso-α-scale error growth has a strong link to large-scale forcing. Upscale error growth is evident in all regions/cases but up-amplitude growth within its own scale plays different roles in different regions/cases. When large-scale flow is important (as in the NE region), precipitation is strongly modulated by the large-scale forcing and becomes more organized with time, and upscale transfer of forecast error is stronger. On the other hand, when local instability plays more dominant roles (as in the SE region), precipitation is overall less organized and has the weakest diurnal variations. Its associated errors at the γ and β scale can reach their peaks sooner and meso-α-scale error tends to rely more on growth of error with its own scale. Small-scale forecast errors are directly impacted by convective activities and have a short response time to convection while increasingly larger-scale errors have longer response times and delayed phase within the diurnal cycle.

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Corresponding author: Ming Xue, mxue@ou.edu
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