Dynamical Precipitation Downscaling for Hydrologic Applications Using WRF 4D-Var Data Assimilation: Implications for GPM Era

AbstractThe objective of this study is to develop a framework for dynamically downscaling spaceborne precipitation products using the Weather Research and Forecasting (WRF) Model with four-dimensional variational data assimilation (4D-Var). Numerical experiments have been conducted to 1) understand the sensitivity of precipitation downscaling through point-scale precipitation data assimilation and 2) investigate the impact of seasonality and associated changes in precipitation-generating mechanisms on the quality of spatiotemporal downscaling of precipitation. The point-scale experiment suggests that assimilating precipitation can significantly affect the precipitation analysis, forecast, and downscaling. Because of occasional overestimation or underestimation of small-scale summertime precipitation extremes, the numerical experiments presented here demonstrate that the wintertime assimilation produces downscaled precipitation estimates that are in closer agreement with the reference National Centers for ...

[1]  Dong‐Kyou Lee,et al.  Effect of length scale tuning of background Error in WRF-3DVAR system on assimilation of high-resolution surface data for heavy rainfall simulation , 2012, Advances in Atmospheric Sciences.

[2]  E. Mlawer,et al.  Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave , 1997 .

[3]  Dusanka Zupanski,et al.  A Prototype WRF-Based Ensemble Data Assimilation System for Dynamically Downscaling Satellite Precipitation Observations , 2011 .

[4]  P. Bauer,et al.  618 Direct 4 D-Var assimilation of all-sky radiances . Part I : Implementation , 2010 .

[5]  Peter Bauer,et al.  488 Implementation of 1 D + 4 D-Var Assimilation of Precipitation Affected Microwave Radiances at ECMWF , Part II : 4 D-Var , 2006 .

[6]  Torben Schmith,et al.  Statistical and dynamical downscaling of precipitation: An evaluation and comparison of scenarios for the European Alps , 2007 .

[7]  Deliang Chen,et al.  Comparison of climate change scenarios for Sweden based on statistical and dynamical downscaling of monthly precipitation , 2001 .

[8]  Yudong Tian,et al.  Estimating evapotranspiration with land data assimilation systems , 2011 .

[9]  Jonathan L. Case,et al.  Improving Numerical Weather Predictions of Summertime Precipitation over the Southeastern United States through a High-Resolution Initialization of the Surface State , 2011 .

[10]  Fei Chen,et al.  Sensitivity of Orographic Moist Convection to Landscape Variability: A Study of the Buffalo Creek, Colorado, Flash Flood Case of 1996 , 2001 .

[11]  Peter Bauer,et al.  Implementation of 1D+4D‐Var assimilation of precipitation‐affected microwave radiances at ECMWF. II: 4D‐Var , 2006 .

[12]  Tadashi Tsuyuki,et al.  Assimilation of Precipitation Data to the JMA Mesoscale Model with a Four-dimensional Variational Method and its Impact on Precipitation Forecasts , 2005 .

[13]  Tadashi Tsuyuki,et al.  Variational Data Assimilation in the Tropics Using Precipitation Data. Part II: 3D Model , 1996 .

[14]  J. Dudhia,et al.  A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation , 2004 .

[15]  Dara Entekhabi,et al.  Hydrologic data assimilation with a hillslope‐scale‐resolving model and L band radar observations: Synthetic experiments with the ensemble Kalman filter , 2012 .

[16]  Milija Zupanski,et al.  Assessing the impact of pre‐GPM microwave precipitation observations in the Goddard WRF ensemble data assimilation system , 2014 .

[17]  E. Kalnay,et al.  North American Regional Reanalysis: Evaluation Highlights and Early Usage , 2005 .

[18]  Wei Huang,et al.  A Three-Dimensional Variational Data Assimilation System for MM5: Implementation and Initial Results , 2004 .

[19]  Dong‐Kyou Lee,et al.  Observation and numerical simulations with radar and surface data assimilation for heavy rainfall over central Korea , 2011 .

[20]  P. Bauer,et al.  619 Direct 4 D-Var assimilation of all-sky radiances . Part II : Assessment , 2010 .

[21]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[22]  Tadashi Tsuyuki,et al.  Variational data assimilation in the tropics using precipitation data part I: Column model , 1996 .

[23]  Philippe Lopez,et al.  Direct 4D-Var Assimilation of NCEP Stage IV Radar and Gauge Precipitation Data at ECMWF , 2011 .

[24]  Christian D. Kummerow,et al.  Global Precipitation Measurement , 2008 .

[25]  J. M. Shepherd,et al.  6 Global precipitation measurement , 2008 .

[26]  P. Bauer,et al.  Satellite cloud and precipitation assimilation at operational NWP centres , 2011 .

[27]  Craig S. Schwartz,et al.  Impact of Assimilating Microwave Radiances with a Limited-Area Ensemble Data Assimilation System on Forecasts of Typhoon Morakot , 2012 .

[28]  Hayley J. Fowler,et al.  Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling , 2007 .

[29]  A. Hou,et al.  Assimilation of Precipitation-Affected Radiances in a Cloud-Resolving WRF Ensemble Data Assimilation System , 2013 .

[30]  J. Dudhia,et al.  Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity , 2001 .

[31]  J. Dudhia.  Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model , 1989 .

[32]  J. Dudhia,et al.  A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes , 2006 .

[33]  Yong-Run Guo,et al.  The Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA , 2012 .

[34]  J. Kain,et al.  A One-Dimensional Entraining/Detraining Plume Model and Its Application in Convective Parameterization , 1990 .

[35]  Y. Kuo,et al.  Application of WRF 3DVAR to operational typhoon prediction in Taiwan: Impact of outer loop and partial cycling approaches , 2012 .

[36]  D. Entekhabi,et al.  Land data assimilation and estimation of soil moisture using measurements from the Southern Great Plains 1997 Field Experiment , 2001 .

[37]  T. Tsuyuki,et al.  Variational Data Assimilation in the Tropics Using Precipitation Data. Part III: Assimilation of SSM/I Precipitation Rates , 1997 .

[38]  J. Dudhia,et al.  A Comparison of Statistical and Dynamical Downscaling of Winter Precipitation over Complex Terrain , 2011 .

[39]  Juanzhen Sun,et al.  Radar Data Assimilation with WRF 4D-Var. Part I: System Development and Preliminary Testing , 2013 .

[40]  Chris Snyder,et al.  Impact of Assimilating AMSU-A Radiances on Forecasts of 2008 Atlantic Tropical Cyclones Initialized with a Limited-Area Ensemble Kalman Filter , 2012 .

[41]  A. Hou,et al.  The Global Precipitation Measurement Mission , 2014 .

[42]  G. Powers,et al.  A Description of the Advanced Research WRF Version 3 , 2008 .

[43]  Peter Bauer,et al.  Assimilating Satellite Observations of Clouds and Precipitation into NWP Models , 2011 .

[44]  U. C. Mohanty,et al.  Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR data assimilation system , 2010 .

[45]  Jimy Dudhia,et al.  Four-Dimensional Variational Data Assimilation for WRF : Formulation and Preliminary Results , 2009 .

[46]  John Derber,et al.  The National Meteorological Center's spectral-statistical interpolation analysis system , 1992 .

[47]  F. Mesinger,et al.  Four-dimensional variational assimilation of precipitation data , 1995 .

[48]  A. Powell,et al.  Dynamical downscaling precipitation over Southwest Asia: Impacts of radiance data assimilation on the forecasts of the WRF-ARW model , 2012 .

[49]  Peter Bauer,et al.  “1D+4DVAR” Assimilation of NCEP Stage-IV Radar and Gauge Hourly Precipitation Data at ECMWF , 2007 .