Task 229

Evaluation of mesoscale model (WRF) and LIS-WRF under for various thunderstorm cases across continents

Principal Investigator(s):

A. Kumar


C. Peters- Lidard

Last Updated:

May 14, 2013 16:46:20

Description of Problem

a) To evaluate NASA developed Land Information System (LIS) in WRF (LIS coupled WRF) and also evaluate LIS spin-ups soil condition. First we have to run LIS spin-up for 5 years and evaluate simulated soil moisture, soil temperature at different soil depth, latent heat flux and sensible heat flux for summer and winter season and compare with station flux site data for verification. In second step we ran LIS-WRF coupled system for three summer cases and three winter season cases and evaluate LIS-WRF coupled system and its operational capabilities.

b) Self-guided research on mesoscale model evaluation and analysis: This work mostly done in my free time (weekends) and carried out with two groups: University of Washington- Prof. Robert Houze and Purdue University- Prof. Dev Niyogi. With Houze group, we are evaluating current microphysics scheme used in WRF mesoscale model and evaluating for severe thunderstorms cases over South America and West Africa. With Niyogi group, cyclone simulation based study and understanding then impact of land-surface feedback also investigating how large forcing impacted cyclone track and intensity.

Scientific Objectives and Approach

a) We have to selected Jan 2003 to June 2008 and run LIS separately for two different domains, one domain is set up over Southern Great Plains (SGP) for summer case evaluation and second domain is set up over Colorado and Wyoming for winter case evaluation. Evaluate soil and surface spin-up condition using ARM’s data site and Ameriflux Sites. In second stage, LIS coupled WRF is designed and ran for three summer cases and three winter cases and evaluation is done using domain averaged analysis software and over flux tower sites.

b) With Houze group: Identified very severe thunderstorm cases over South America, and conducted high resolution nested model runs with different microphysics schemes. We chose two cases, severe deep convective case and wide convective cases and evaluating different microphysics schemes specially which accounts hail mechanism. Overall goal is to understand microphysical process in thunderstorm.

With Dev Niyogi’s group: Analyzing the impact of large scale forcing errors on simulated track and intensity of tropical cyclones. Evaluating large scale model input forcing from GFS, ECMWF and MERRA system and its impact on track and intensity.


For Goal (a)

• Done evaluation of LIS spin-up condition and also evaluated LIS-WRF coupled model for three summer and three winter cases.

• Selected data flux sites which are used for verification mainly for 2008 year. ARM’s data site, Ameriflux data sites. For winter cases, we have Niwot Site(Ameriflux flux data sites) and Snowtel data from NCAR land surface group.

• LIS spin-ups verification results for summer season and winter season was presented in AFWA annual meeting.

• LIS-WRF model evaluated using NCAR’s based verification package and conduct domain average analysis (2m temperature, 2m- mixing ratio, vertical temperature and moisture profiles).

• LIS-WRF simulated surface fluxes are verified using ARM’s flux sites.

Future Work

For Goal (a)
Conducted evaluation for three cases, first two cases is storm cases and third one is clear sky case. The WRF-LIS and standard WRF with LISINIT capture all surface variables close to each other with very minor differences. The 2-m surface temperature, WRF-LIS and WRF-LISINIT shows improvement in day time but reproduce slightly higher 2-m temperature in night time. The WRF coupled LIS and WRF with LISINIT reproduce better soil conditions than standard WRF whereas WRF-LIS shows higher soil temperature (~0.5-1K). All models shows almost same magnitude of surface fluxes in day time, the latent heat flux is over-estimated by all models and on other hand sensible heat flux is well captured by all models (Fig 2). Precipitation analysis shows WRF coupled LIS reproduced better rainfall patterns in all three summer cases in comparison with STAGE_IV precipitation data (Fig. 1).

For Goal (b)
Microphysics Evaluation: Model output analyses are underway and provide valuable information about microphysics performance under different environmental conditions.
Tropical cyclone modeling using Advanced Hurricane WRF model: Impact on Track and intensity under various global forcing data, land-surface feedback on cyclone intensity over land.

Refereed Journal Publications

Kumar A., F. Chen, D. Niyogi, J. Alfieri, M. Ek, and K. Mitchell, 2010, Evaluation of a photosynthesis-based canopy resistance formulation in the Noah land surface model, Boundary-Layer Meteorology, Volume 138, Number 2, 263-284, DOI: 10.1007/s10546-010-9559-z

Charusombat U., D. Niyogi, A. Kumar, X. Wang, F. Chen, A. Guenther, A. Turnipseed, K. Alapaty, 2010: Evaluating a new Deposition Velocity Module in the Noah land surface model, Boundary-Layer Meteorology, DOI : 10.1007/s10546-010-9531-y

Medina, S., R. A. Houze, Jr., A. Kumar, and D. Niyogi, 2010, Summer Monsoon Convection in the Himalayan Region: Terrain and Land Cover Effects, Quart. J. Roy. Meteorol. Soc., 136, 593-616

O. Kellner, D. Niyogi, M. Lei, A. Kumar, 2011: The Role of Anomalous Soil Moisture on the Inland Reintensification of Tropical Storm Erin (2007), Natural Hazards – Special Issue on Tropical Cyclones, submitted

Anil Kumar, J. Done, J. Dudhia, D. Niyogi, 2009, Simulations of Cyclone Sidr in the Bay of Bengal with a high-resolution model: Impact of domain sizes, Meteorology and Atmospheric Physics, (third revision submitted)

Other Publications and Conferences

Webster P. J., R. A. Houze, V. Toma, H. Kim, K. Rasmussen, U. Romatschke, S. Medina, S. Brodzik, D. Niyogi, and A. Kumar, 2011, Pakistan flood 2010: Could it have been predicted, International Weather & Climate Events of 2010, AMS Annual Meeting, Seattle, 25 January 2011 –presented file can be obtained from:

Task Figures

Fig. 1 – Accumulated Precipitation for case 2 (22-24 June 2008). (a) Standard WRF, (b) Standard WRF with LISINIT, (c) WRF coupled LIS, and (d) STAG-IV precipitation.

Fig. 2 – Using 9 flux site data from ARM’s network and compare to different models. Black line is observed, red-standard WRF, blue-stand WRF with. Left panel is Latent flux and Right panel is sensible heat flux for all three cases.