Introduction to and validation of MM5/VIC modeling system

The PSU/NCAR Mesoscale Model ● a limited-area, nonhydrostatic, terrain-following sigma-coordinate model ● designed to simulate or predict mesoscale atmospheric circulation. ● developed at Penn State and NCAR as a community mesoscale model Global 5-day MM5 forecasts: Today's 24 hour precipitation forecast

MM5 modeling system The model is supported by several pre- and post- processing programs. TERRAIN, REGRID: Horizontal interpolation from a latitude-longitude grid to a mesoscale, rectangular domain on either a Mercator, Lambert Conformal, or Polar Stereographic projection. INTERPF : Vertical interpolation from pressure level to model σ-levels.

The PSU/NCAR Mesoscale Model DocumPublicatios Links Precipitation Pressure Radiation Wind Humidity Air temperature Sensible heat flux Latent heat fluxes … First coupled by Drs. Ruby Leung at Pacific Northwest National Laboratory (PNNL) and Xu Liang at University of California, Berkeley

Modification of coupled MM5/VIC modeling system PNNL UW vegetation type: Single Multiple elevation band: Single Multiple Parameters: Soil, veg type dependant cell dependant initialization: Spinning up 3 months Offline VIC Original VIC driver vicNl.c Initialize global parameters Initialize model state Read in soil parameter Vegetation parameter Snowband parameter Run model in grid cell for all time steps MM5-VIC Two important interface subroutines RDINIT.F : initialize parameters and model state VICSURF.C : driver for VIC model

RDINIT.F Allomem Initialize global parameters Read in vegetation library DM_DIST_READ Load in soil parameter veg. parameter snowband param initial conditions (by offline VIC running) Inivic Called once per cell Passing initial atmos fluxes Passing parameters into soil_con_vic & veg_con_vic Passing initial soil condition into dist_prcp_struct

VICSURF.C VICMODEL Provide all forcings to drive VIC model for a grid cell, and feedback the boundary conditions to the MM5 model VIC_band Single call to VIC model for each cell Dist_prec ● ●● (The main physical processes keep the same as original VIC)

Validation with 2004 NAME Field Experiment

Monthly Precipitation Comparison Negative bias over coastal land region

Monthly Mean Surface Air Temperature Comparison

MM5-VIC Observation

Seasonal Mean Downward Shortwave Radiation Diurnal Cycle Arizona

Downward Shortwave Radiation New Mexico

Downward Shortwave Radiation Mexico Generally positive bias of downward shortwave radiation

Seasonal Mean Surface Air Temperature Diurnal Cycle Arizona

Surface Air Temperature New Mexico

Surface Air Temperature

Seasonal Mean Precipitation Diurnal Cycle Coastal region

Precipitation Mountainous region

Precipitation Transect I

Precipitation Transect II

Precipitation Transect III

Precipitation II I Arizona

SMEX04 Soil Climate Analysis Network (SCAN) Station 2026, Tombstone, Arizona Diurnal Cycle First Layer Soil Moisture Daily Time Series Precipitation *Positively biased initial soil wetness condition

SMEX04 Walnut Gulch Experimental Watershed Soil Moisture Network Data, Tombstone, Arizona First Layer Soil Temperature Diurnal Cycle First Layer Soil Moisture Daily Timeseries

2004 NAME site at Estacion Obispo, MX Diurnal Cycle First Layer Soil Moisture Daily Timeseries

MM5/VIC Modeling Evaluation of the Influence of Antecedent Soil Moisture on Variability of the North American Monsoon System Experimental Design:

Winter Precipitation - Monsoon Rainfall feedback hypothesis Higher (lower) winter precipitation & spring snowpack More (less) spring & early summer soil moisture Lower (higher) spring & early summer surface temperature Weak (strong) monsoon Hypothesis to be tested by MM5-VIC coupling system:

Study Domain Monsoon regions are defined as in Comrie & Glenn (1998) Monsoon West Monsoon South Monsoon North Monsoon East

Summary from data analysis ● MW monsoon is negatively related with Southwest winter precipitation. NW Mexico summer monsoon onset date is positively related with Southwest winter precipitation and snow especially for extreme late and early years. ● Spring soil wetness conditions in the SW U.S. and northwestern Mexico are strongly determined by the previous winter’s precipitation, this land memory appears to play some role in the surface thermal condition, then influence the NW Mexico monsoon onset, but seems to contribute little to MW summer monsoon. ● May Z500 anomalies shows strong relationship with May Ts anomaly all over the North America continent, which suggesting that the atmospheric circulation condition may contribute more to the pre-monsoon Ts anomalies than land surface conditions.

Domain LateEarly Winter precipitation related region to summer monsoon MW MS Soil Moisture prescribing domain 1

Running Parameters Domain Size: 170*170 Spatial resolution: 20km Running timestep: 60 seconds Running period: May 1 ~ Sep. 30 Output: 6 hrly Computer timing: ~115hrs if using 20 processors

Experiment Design Initial soil moisture prescribed at OctSepAugJulyJune SM free running May 1 ?? Field capacityWilting point Normal (VIC climatology) ► Running on wet, normal and dry monsoon years to represent different atmospheric circulation conditions 1 ► The initial soil wetness condition on May 1 st represents winter precipitation condition.

Sensitivity Experiments ► Prescribing initial soil moisture (above- normal, normal, below-normal) in domain 1 on May 1, then let SM free running until October in wet, normal, dry monsoon years respectively. soil moisturemonsoon year Above-normal wet Normal normal Below-normal dry Totally 9 runs, which may take about 45 days. ►

MSa JJAS Precipitation and Onset MSa and MW JJAS Precipitation Wet year: 1984 (much earlier onset than 1990) Dry year: 1973, 1979, 1995 ?? Wet year, dry year???

dry year : 1995 (with later onset than 1979) With drought produced extended damages to crops and cattle in Northern Mexico documented from newspapers