.png){kind=icon}
.png){kind=icon}
Return
THE MESOSCALE PREDICTABILITY EXPERIMENT (MPEX)
.png){kind=icon}
OA
AI
DOI：10.1175/BAMS-D-13-00281.1.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The Mesoscale Predictability Experiment (MPEX) was conducted from 15 May to 15 June 2013 in the central United States. MPEX was motivated by the basic question of whether experimental, subsynoptic observations can extend convective-scale predictability and otherwise enhance skill in short-term regional numerical weather prediction.Observational tools for MPEX included the National Science Foundation (NSF)-National Center for Atmospheric Research (NCAR) Gulfstream V aircraft (GV), which featured the Airborne Vertical Atmospheric Profiling System mini-dropsonde system and a microwave temperature-profiling (MTP) system as well as several ground-based mobile upsonde systems. Basic operations involved two missions per day: an early morning mission with the GV, well upstream of anticipated convective storms, and an afternoon and early evening mission with the mobile sounding units to sample the initiation and upscale feedbacks of the convection.A total of 18 intensive observing periods (IOPs) were completed during the field phase, representing a wide spectrum of synoptic regimes and convective events, including several major severe weather and/or tornado outbreak days. The novel observational strategy employed during MPEX is documented herein, as is the unique role of the ensemble modeling effortswhich included an ensemble sensitivity analysisto both guide the observational strategies and help address the potential impacts of such enhanced observations on short-term convective forecasting. Preliminary results of retrospective data assimilation experiments are discussed, as are data analyses showing upscale convective feedbacks.
Keywords:
PROSPECTUS DEVELOPMENT TEAM
WEATHER RESEARCH-PROGRAM
TROPOSPHERIC JET STREAK
SEASON PRECIPITATION FORECASTS
SIMULATED CONVECTIVE SYSTEM
TROPICAL SQUALL-LINE
WRF MODEL
DATA ASSIMILATION
SENSITIVITY-ANALYSIS
INITIAL CONDITIONS
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.9
Papers:
3.7K
Citations:
2.7W
Organization
View more organizations