Desert Research. Institute, Reno, NV

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1 Regional Climate Modeling: Transferability and sensitivity tests. John Mejia an nd Darko Koracin Desert Research Institute, Reno, NV Tri-State NSF-EPSCoR confe erence April 2010, Lake Tahoe, NV

2 NSF-EPSCoR Climate Change project, Climate Modeling Component. Main task: Create a regional/sub assessments for diffe century projections. Implement and devel to improve the applic Models (GCMs) in cli Develop and use a st Models (RCMs). Provide these results (hydrological, environ impact/adaptation wo b-regional climate change erent socio-economical 21st op transportable methodologies ability of General Circulation mate impact studies. tate-of-the-art the art Regional Climate s to the user community nmental, ecology ) for input to ork.

3 Concept of Regio onal Climate Models (R RCM) Dynamical Downsc Dynamical Downsc Force by GCMs (pre Limited area models climate as a tool for Long-term integratio limitations) Undergoing parallel Undergoing parallel Downscaling" caling. esent or future climate). s: Nested into regional dynamical downscaling. ons (computer resources effort using Statistical

4 RCM domain GCM GCM GCM GCM RCM-WRF domains for dynamical downscaling over the SW North thamerica (at 36 km grid size), the Great Basin (at 12 2km grid size) and Nevada (at 4km grid size). Gray shadings represent approxima ate location of the Great Basin region.

5 Ob bjective Develop a multi-scale framework to evaluate the RCM for use in downs scaling global climate projections. Evaluate and quantify the performance of different physical parameteriza ations for two different (relatively Dry and We et) winter seasons. Test the RCM transfer rability. Elucidate the strength hs and weaknesses of the RCM applied over Ne evada. What are the benefits attributable to fine resolution runs (from 36km to 12 2km to 4 km).

6 Regional C Weather and Researc limate Modeling: h Forecasting (WRF) model Microphysics (MP); short- and long- wave radiation (Rad); Land Surface Model (LSM); Planetary Boundary Layer (P PBL); Cumulus physics (Cu)

7 Model RCM setup: Forcing data: NCEP/NCA (NNRP). SST Updates. No Nudging 2-years spin-up period fo +2 nine-month periods O o Dry year o Wet year AR global reanalysis products or slow varying quantities OtJ Oct-June:

8 Obse ervations - 94 Active ( ) NOAA/NWS and Cooperative Observer Network Stations (NCDC), FAA, Agro-Met. QA/QC C: missing observations, "day- time-shifting" and other observer-related errors. - Daily Obs: Max and Min Temp, Rainfall, Snowfall, Snow Depth. - Hourly Obs: 12 Autom matic stations NWS, FAA, AgroMet. PRISM (PRISM Climat te Group, Oregon State University, prismclimate.org)

9 4km PRISM data: Wet minus Dry

10 From GCM ~250km to 4km Mean Temperature

11 On the grid-size e...36, 12, and 4km Not surprisingly, the finn ner grid improves the vertical location at the observation sites.

12 Day-to-da day Variability

13 Monthly Means

14 ...Monthly Means

15 RMS Error

16 Regional C Weather and Researc limate Modeling: h Forecasting (WRF) model Microphysics (MP); short- and long- wave radiation (Rad); Land Surface Model (LSM); Planetary Boundary Layer (P PBL); Cumulus physics (Cu)

17 ..RMS Error..

18 ..RMS Error..

19 ..RMS..

20 ..RMS..

21 ...RMS Error

22 Daily Rainfall Thresholds

23 Some level of intern Reduce RCM bias ( Grid-size and regim Physics schemes re regional optimizatio The RCM problems modeling challenge Appropriate implem present and future c amount of work/com Learning curve is ex Rem marks nal nudging is needed: (drifting) me dependence. eveal some potential for on. s identified here are persistent e. mentation of the RCM for climate requires an immense mputer resources. xponential!

24 Near-Fut ture activities Continue downscalin Validation using othe snow) CCSM4.0 Last 20 ye B1, A1F. Partnership with the distributing ib ti simulate Land Surface Model and development us ng for present climate er dataset (e.g. Nextelears of 21st century... A2, data portal group to start ddata. l: validation sing Transect data...

25 Acknow wledgements Paul Neeley and Ed Novak (DRI-IT) ( Dr L. R. Laung (PNW WL/DOE) Dr Liang (Univ. Illino ois) Ramesh and Travis for their constant assistance.

Climate Modeling Component

Nevada Infrastructure for Climate Change Science, Education, and Outreach Climate Modeling Component Regional Climate Modeling: Methodological issues and experimental designs John Mejia, Darko Koracin,