Dynamical Downscaling
(1) Why downscaling?

The islands are 'missing' or 'flat' in a typical Global Climate Model (GCM). The horizontal resolution of a typical GCM is around 200*200 km, while many tropical (subtropical) islands are even smaller than one sigle GCM grid but with complex topography

Snoptic Background for the Hawaiian Islands

(2) How to downscale?

The pseudo-global-warming method is employed to project the future climate for the Hawaiian Islands (Lauer et al. 2013).

Shallow cumulus (SC) is the dominant cloud type in Hawaii. The model is able to realistically capture SC with Tiedtke scheme (Zhang et al. 2011).

The original land surface dataset is replaced by a newly implemented dataset, including land cover/use, soil types, green vegetation fraction, and surface ALBEDO (Zhang et al. 2012).

(3) Projected future changes for the Hawaiian Islands

The projected future temperature change in CMIP3 A1B senario (Zhang et al. 2016b)

The projected future change of rainfall.

Funded Projects
Climate Adaptation Partnership for the Pacific, subsward from the East-West Center on a project funded by National Ocean and Atmosphere Administration (NOAA) Regional Integrated Sciences and Assessments (RISA) Program (Sep 2010 - Aug 2015).

Published Papers
Zhang, C., Y. Wang, and K. Hamilton, 2011: Improved representation of boundary layer clouds over the Southeast Pacific in WRF-ARW using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev., 139, 3489-3513, doi: 10.1175/MWR-D-10-05091.1.

Zhang, C., Y. Wang, A. Lauer, and K. Hamilton, 2012: Configuration and Evaluation of the WRF Model for the Study of Hawaiian Regional Climate. Mon. Wea. Rev., 140, 3259-3277, doi: 10.1175/MWR-D-11-00260.1.

Lauer, A., C. Zhang, O. Elison Timm, Y. Wang, and K. Hamilton, 2013: Downscaling of climate change in the Hawaii region using CMIP5 results: On the choice of the forcing fields. J. Climate, 26 (24), 10006-10030,doi:10.1175/JCLI-D-13-00126.1.

Zhang, C., Y. Wang, K. Hamilton, and A. Lauer, 2016a: Dynamical downscaling of the climate for the Hawaiian Islands. Part I: Present Day. J. Climate, 29, 3027-3048, doi: 10.11175/JCLI-D-15-0432.1.

Zhang, C., Y. Wang, K. Hamilton, and A. Lauer, 2016b: Dynamical downscaling of the climate for the Hawaiian Islands. Part II: Projection for the late 21st Century. J. Climate. (In revision)

Cloud Water Interception (CWI)

CWI is a complicated cloud water deposition process. It can be parameterized by CWI=a(LAI/h)^b |u| (rho) q_c in WRF

The cloud water is not very sensitive to the vertical resolution. The deposited cloud water is removed from the lowest model level

The main goal of the project is aimed to build a climatological CWI map for the Hawaiian Islands.

Funded projects
Cloud Water Interception in Hawaii: Building Spatial Pattern Maps for the Present-day Climate and Projected Changes by the Late 21st Century using the Hawaii Regional Climate Model, Funded by U.S. Geological Survey (USGS) (Oct 2015 - Sep 2017).

Very fine Resolution Dynamical Downscaling of Past and Future Climate for Assessment of Climate Change Impacts on the Islands of Oahu and Kauai, funded by U.S. Geological Survey (USGS) (Sep 2013 - Aug 2015).

Monitoring the Hawaiian Climate by Satellite Observations
(1) Clouds

The cloud base and top height (CBH, CTH) from CALIPSO. The Trade Wind Inversion Base Height from COSMIC.

The relation between cloud thicknesses and rainfall rate

Published Papers
Zhang, C., Y. Wang, A. Lauer, K. Hamilton, and F. Xie, 2012: Cloud base and top heights in the Hawaiian region determined with satellite and ground-based measurements. Geophys. Res. Lett., 39, L15706, doi:10.1029/2012GL052355.

(2) Snow

Observed daily snow cover index and its relation to model simulated snowfall

Present-day and Future snow change

Papers in preparation
Zhang, C., K. Hamilton and Y. Wang, Monitoring and projecting trends of Hawaii snow cover.

Tropical cyclones
Future change

Simulated OLR over the West Pacific

Observed and Simulated TC tracks

Funded projects
21st Century High-resolution Climate Projections for Guam and American Samoa, funded by U.S. Geological Survey (USGS) (Sep 2012 - Sep 2015)

Papers in preparation
Zhang, C., and Y. Wang, Projected future changes of tropical cyclone activity over the western North and South Pacific in a 20-km-mesh regional climate model.

Physics schemes - Cumulus Parameterization (CP)
(1) Modified Tiedtke Scheme - Since WRFV3.3

The biases of Theta and Qv

Simulated Cloud base and top heights for each CP scheme

Published papers
Zhang, C., Y. Wang, and K. Hamilton, 2011: Improved representation of boundary layer clouds over the Southeast Pacific in WRF-ARW using a modified Tiedtke cumulus parameterization scheme. Mon. Wea. Rev., 139, 3489-3513, doi: 10.1175/MWR-D-10-05091.1.

(2) New Tiedtke Scheme - Since WRFV3.7

The new Tiedtke scheme has numerous changes to the "modified Tiedtke" scheme, including new trigger functions, new entrainment/detrainment rate for both updraft and downdraft, new closure for shallow and deep convection, new cloud/rain water conversion, new convection momentum transport...
The scheme is tested in both IPRC Reginal Tropical Channel Model (iRegTCM) and WRF-ARW. The figure show the observed and simulated diurnal rainfall.

Real-time Weather Forecast System

The flow chart for the system.

3D 'radar reflectivity' in the initial condition after the data assimilation.

Dr. Zhang has great enthusiasm in weather forecast. He spent five years on designing a real-time weather forecast system with the cutting-edge technology. The system aims at predicting the weather within 3 days more accurate. The system was created by Fortran, C, Perl and C shell.