Including Uncertainties of Sea Surface Temperature in an Ensemble Kalman Filter: A Case Study of Typhoon Sinlaku (2008)

AbstractSea surface temperature (SST) plays an important role in tropical cyclone (TC) life cycle evolution, but often the uncertainties in SST estimates are not considered in the ensemble Kalman filter (EnKF). The lack of uncertainties in SST generally results in the lack of ensemble spread in the atmospheric states near the sea surface, particularly for temperature and moisture. In this study, the uncertainties of SST are included by adding ensemble perturbations to the SST field, and the impact of the SST perturbations is investigated using the local ensemble transform Kalman filter (LETKF) with the Weather Research and Forecasting Model (WRF) in the case of Typhoon Sinlaku (2008). In addition to the experiment with the perturbed SST, another experiment with manually inflated ensemble perturbations near the sea surface is performed for comparison. The results indicate that the SST perturbations within EnKF generally improve analyses and their subsequent forecasts, although manually inflating the ensemb...

[1]  M. Buehner,et al.  Atmospheric Data Assimilation with an Ensemble Kalman Filter: Results with Real Observations , 2005 .

[2]  Clifford F. Mass,et al.  Aspects of Effective Mesoscale, Short-Range Ensemble Forecasting , 2005 .

[3]  R. Tuleya,et al.  A Numerical Study on the Effects of Environmental Flow on Tropical Storm Genesis , 1981 .

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

[5]  Fuqing Zhang,et al.  Limited-Area Ensemble-Based Data Assimilation , 2011 .

[6]  Jeffrey L. Anderson An Ensemble Adjustment Kalman Filter for Data Assimilation , 2001 .

[7]  Takemasa Miyoshi,et al.  Applying a Four-dimensional Local Ensemble Transform Kalman Filter (4D-LETKF) to the JMA Nonhydrostatic Model (NHM) , 2006 .

[8]  Geir Evensen,et al.  The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .

[9]  J. Price,et al.  Upper Ocean Response to a Hurricane , 1981 .

[10]  J. Whitaker,et al.  Ensemble Data Assimilation without Perturbed Observations , 2002 .

[11]  Ryan D. Torn,et al.  A Data Assimilation Case Study Using a Limited-Area Ensemble Kalman Filter , 2007 .

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

[13]  I. Ginis,et al.  Real-Case Simulations of Hurricane-Ocean Interaction Using A High-Resolution Coupled Model: Effects on Hurricane Intensity , 2000 .

[14]  Kerry Emanuel,et al.  An Air-Sea Interaction Theory for Tropical Cyclones. Part I: Steady-State Maintenance , 1986 .

[15]  C. Bishop,et al.  Cloud-Resolving Hurricane Initialization and Prediction through Assimilation of Doppler Radar Observations with an Ensemble Kalman Filter , 2009 .

[16]  Louis J. Wicker,et al.  Wind and Temperature Retrievals in the 17 May 1981 Arcadia, Oklahoma, Supercell: Ensemble Kalman Filter Experiments , 2004 .

[17]  I. Ginis,et al.  Numerical simulations of tropical cyclone‐ocean interaction with a high‐resolution coupled model , 1993 .

[18]  P. L. Houtekamer,et al.  Ensemble Kalman filtering , 2005 .

[19]  Frederic Vitart,et al.  An Ensemble Generation Method for Seasonal Forecasting with an Ocean-Atmosphere Coupled Model , 2005 .

[20]  G. Evensen Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statistics , 1994 .

[21]  J. Chan,et al.  Tropical Cyclone Intensity Change from a Simple Ocean–Atmosphere Coupled Model , 2001 .

[22]  Christian L. Keppenne,et al.  Data Assimilation into a Primitive-Equation Model with a Parallel Ensemble Kalman Filter , 2000 .

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

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

[25]  E. Kalnay,et al.  Four-dimensional ensemble Kalman filtering , 2004 .

[26]  R. Torn Performance of a Mesoscale Ensemble Kalman Filter (EnKF) during the NOAA High-Resolution Hurricane Test , 2010 .

[27]  P. Houtekamer,et al.  Data Assimilation Using an Ensemble Kalman Filter Technique , 1998 .

[28]  D. M. Barker,et al.  Southern High-Latitude Ensemble Data Assimilation in the Antarctic Mesoscale Prediction System , 2005 .

[29]  Craig H. Bishop,et al.  Adaptive sampling with the ensemble transform Kalman filter , 2001 .

[30]  Neill E. Bowler,et al.  The MOGREPS short‐range ensemble prediction system , 2008 .

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

[32]  Kerry A. Emanuel,et al.  The Ocean’s Effect on the Intensity of Tropical Cyclones: Results from a Simple Coupled Atmosphere–Ocean Model , 1999 .

[33]  Paul Poli,et al.  Diagnosis of observation, background and analysis‐error statistics in observation space , 2005 .

[34]  Istvan Szunyogh,et al.  Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter , 2005, physics/0511236.

[35]  Lee Lawyer,et al.  The challenge of The Sudan , 1984 .

[36]  Uang,et al.  The NCEP Climate Forecast System Reanalysis , 2010 .

[37]  T. Miyoshi The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter , 2011 .

[38]  Ryan D. Torn,et al.  Boundary Conditions for Limited-Area Ensemble Kalman Filters , 2006 .

[39]  Takemasa Miyoshi,et al.  The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations , 2012, Pure and Applied Geophysics.

[40]  T. Marchok,et al.  The Operational GFDL Coupled Hurricane–Ocean Prediction System and a Summary of Its Performance , 2007 .

[41]  Massimo Bonavita,et al.  The ensemble Kalman filter in an operational regional NWP system: preliminary results with real observations , 2008 .

[42]  C. Snyder,et al.  Assimilation of Simulated Doppler Radar Observations with an Ensemble Kalman Filter , 2003 .

[43]  E. Kalnay,et al.  Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter , 2009 .

[44]  A. Rosati,et al.  System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies , 2007 .

[45]  Christopher G. DesAutels,et al.  Environmental Control of Tropical Cyclone Intensity , 2004 .

[46]  Jordan G. Powers,et al.  A Description of the Advanced Research WRF Version 2 , 2005 .

[47]  John S. Kain,et al.  Convective parameterization for mesoscale models : The Kain-Fritsch Scheme , 1993 .