Retrieving 4-dimensional Atmospheric Boundary-layer Structure from Multi-time Profiles over a Single Station
Zhaoxia Pu | University of Utah |
Lei Zhang | University of Utah |
Linbo Wei | |
Steven Krueger | University of Utah |
Category: Modeling
![Image Thumbnail](https://webarchive.library.unt.edu/web/20130217143234im_/http://asr.science.energy.gov/meetings/stm/posters/images/2012/thumbs/thumb_P00536.png.png)
Figure 1. The ratio of equitable threat scores (ETS), defined as R=ERS4DVAR/ETSCTRL for 1-hour accumulated precipitation between CTRL (without assimilation of wind profiles) and 4DVAR (with assimilation of wind profiles) experiments with threshold of 0.1, 0.25, 1.0, 2.5, and 5.0 mm at 2100 UTC 12 June 2002, 2300 UTC 12 June 2002, 0100 UTC 13 June 2002, and 0300 UTC 13 June 2002. When ETS ratio is greater than 1, the QPF skill is improved by 4DVAR.
Most routine measurements from climate study facilities, such as the Department of Energy’s ARM Southern Great Plains site, come from individual sites over a long period of time. While single-station data is very useful for many studies, it is challenging to obtain 3-dimensional spatial structures of atmospheric boundary layers that include prominent signatures of deep convection from these data. This study examines the ability of modern data assimilation techniques in retrieving 4-dimensional (both spatial and temporal) atmospheric boundary-layer structures from multi-time profiling data at a single station. To demonstrate the idea, multi-time wind profiles from a single station are assimilated into the mesoscale community Weather Research and Forecasting (WRF) model using its four-dimensional variational data assimilation system. The impact of data on the numerical simulations of a warm season mesoscale convection system during IHOP_2002 is evaluated. Results indicate that the assimilation of high temporal and vertical resolution wind profiles have a significant influence on the numerical simulation of the convective initiation and evolution. Not only the wind fields but also the structure of moisture fields associated with the convective system are improved. Data assimilation has also resulted in more accurate prediction of the locations and timing of the convection initiations; as a consequence, the skill of quantitative precipitation forecasting is enhanced greatly.
The method is now being applied to a recent convective case during the Midlatitude Continental Convective Clouds Experiment (MC3E). The impact of assimilating multi-time and multi-sensor soundings from the SGP site on the representation of convective properties of the selected convective case is examined.
Detailed results and recent progress will be reported in the presentation.
Reference:
Zhang, L, and Z Pu. 2011. “Four-dimensional Assimilation of Multi-time Wind Profiles Over a Single Station and Numerical Simulation of a Mesoscale Convective System Observed During IHOP_2002.” Monthly Weather Review 139, 3369–3388.
This poster will be displayed at ASR Science Team Meeting.