Exploring the assimilation of IASI radiances in forecasting polar lows

We studied the use of IASI data to improve the forecasts of extreme weather events in the Arctic region. For this purpose, the HARMONIE/Norway regional model was used. A set of 366 IASI channels was initially chosen from the ECMWF archived database. Active channels showing the best fit with the analysis system were selected by applying a multi‐step monitoring technique. The IASI data were assimilated together with most of the available conventional and operational satellite observations using a three‐dimensional variational data assimilation system. Four experiments with cyclic assimilations and subsequent 48‐hour forecasts were performed during the IPY‐THORPEX campaign period to evaluate the impact of the IASI data and the campaign observations on the hydrostatic HARMONIE/Norway analyses and forecasts.

[1]  Thomas Spengler,et al.  The Norwegian IPY–THORPEX: Polar Lows and Arctic Fronts during the 2008 Andøya Campaign , 2011 .

[2]  Jørn Kristiansen,et al.  High‐resolution ensemble prediction of a polar low development , 2011 .

[3]  T. Iversen,et al.  Short-range probabilistic forecasts from the Norwegian limited-area EPS: long-term validation and a polar low study , 2011 .

[4]  T. Iversen,et al.  High-resolution ensemble prediction of a polar low development , 2011 .

[5]  Roger Randriamampianina,et al.  Ensemble variational assimilation for the representation of background error covariances in a high‐latitude regional model , 2010 .

[6]  Øyvind Saetra,et al.  Can CAPE Maintain Polar Lows , 2010 .

[7]  K. Karlsson,et al.  Evaluation of Arctic cloud products from the EUMETSAT Climate Monitoring Satellite Application Facility based on CALIPSO-CALIOP observations , 2009 .

[8]  G. Noer,et al.  A Polar Low Pair over the Norwegian Sea , 2009 .

[9]  A. Mcnally,et al.  The assimilation of Infrared Atmospheric Sounding Interferometer radiances at ECMWF , 2009 .

[10]  Andrew Collard,et al.  Selection of IASI channels for use in numerical weather prediction , 2007 .

[11]  Dick Dee,et al.  Adaptive bias correction for satellite data in a numerical weather prediction system , 2007 .

[12]  Florence Rabier,et al.  Relative impact of polar‐orbiting and geostationary satellite radiances in the Aladin/France numerical weather prediction system , 2007 .

[13]  S. Ştefănescu,et al.  An overview of the variational assimilation in the ALADIN/France numerical weather‐prediction system , 2005 .

[14]  C. Fischer,et al.  A posteriori validation applied to the 3D-VAR Arpège and Aladin data assimilation systems , 2005 .

[15]  Erik Andersson,et al.  Influence‐matrix diagnostic of a data assimilation system , 2004 .

[16]  A. Mcnally,et al.  A cloud detection algorithm for high‐spectral‐resolution infrared sounders , 2003 .

[17]  M. Shupe,et al.  An annual cycle of Arctic cloud characteristics observed by radar and lidar at SHEBA , 2002 .

[18]  Florence Rabier,et al.  Channel selection methods for Infrared Atmospheric Sounding Interferometer radiances , 2002 .

[19]  Graeme Kelly,et al.  A satellite radiance‐bias correction scheme for data assimilation , 2001 .

[20]  Ronald M. Errico,et al.  Singular-Vector Perturbation Growth in a Primitive Equation Model with Moist Physics , 1999 .

[21]  Laurence S. Rothman,et al.  Reprint of: The HITRAN molecular spectroscopic database and HAWKS (HITRAN Atmospheric Workstation): 1996 edition , 1998 .

[22]  Laurence S. Rothman,et al.  The HITRAN molecular spectroscopic database and HAWKS (HITRAN atmospheric workstation) , 1998, Defense, Security, and Sensing.

[23]  G. Radnoti,et al.  Comments on “A Spectral Limited-Area Formulation with Time-Dependent Boundary Conditions Applied to the Shallow-Water Equations” , 1995 .

[24]  Pierre Bénard,et al.  Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following coordinate in the framework of the ARPEGE/Aladin NWP system , 1995 .

[25]  B. Farrell,et al.  Polar Low Dynamics , 1992 .

[26]  M. Shapiro,et al.  Research aircraft measurements of a polar low over the Norwegian Sea , 1987 .

[27]  S. Grønås,et al.  Numerical simulations of polar lows in the Norwegian Sea , 1987 .

[28]  A. Bratseth A note on CISK in polar air masses , 1985 .

[29]  T. Warner,et al.  On the Mechanism for the, Development of Polar Lows , 1983 .

[30]  A. Storto,et al.  A new bias correction scheme for assimilating GPS zenith tropospheric delay estimates , 2010 .

[31]  Roger Randriamampianina,et al.  The relative impact of meteorological observations in the Norwegian regional model as determined using an energy norm‐based approach , 2010 .

[32]  J. Eyre,et al.  Assimilation of IASI at the Met Office and assessment of its impact through observing system experiments , 2009 .

[33]  A. Storto,et al.  ALADIN-HARMONIE/Norway and its assimilation system - the implementation phase , 2008 .

[34]  A. Storto,et al.  MONITORING THE USE OF IASI DATA IN A LIMITED AREA DATA ASSIMILATION SYSTEM , 2008 .

[35]  Roger Randriamampianina,et al.  Impact of high resolution satellite observations in the ALADIN/HU model , 2006 .

[36]  O. Talagrand,et al.  Diagnosis and tuning of observational error in a quasi‐operational data assimilation setting , 2006 .

[37]  R. Randriamampianina Radiance-bias correction for a limited area model , 2005 .

[38]  Jean-Noël Thépaut,et al.  An improved general fast radiative transfer model for the assimilation of radiance observations , 2004 .

[39]  Marco Matricardi,et al.  RTIASI-4 : a new version of the ECMWF fast radiative transfer model for the infrared atmospheric sounding interferometer , 2003 .

[40]  J. Thepaut,et al.  The information content of clear sky IASI radiances and their potential for numerical weather prediction , 1998 .

[41]  Andras Horanyi,et al.  ARPEGE/ALADIN : A numerical weather prediction model for Central-Europe with the participation of the Hungarian Meteorological Service , 1996 .

[42]  K. Emanuel,et al.  Polar lows as arctic hurricanes , 1989 .

[43]  R. Rifkin Information content. , 1981, Circulation.