Directional Bias of TAO Daily Buoy Wind Vectors in the Central Equatorial Pacific Ocean from November 2008 to January 2010

This article documents a systematic bias in surface wind directions between the TAO buoy measurements at 0°, 170°W and the ECMWF analysis and forecasts. This bias was of the order 10° and persisted from November 2008 to January 2010, which was consistent with a post-recovery calibration drift in the anemometer vane. Unfortunately, the calibration drift was too time-variant to be used to correct the data so the quality flag for this deployment was adjusted to reflect low data quality. The primary purpose of this paper is to inform users in the modelling and remote-sensing community about this systematic, persistent wind directional bias, which will allow users to make an educated decision on using the data and be aware of its potential impact to their downstream product quality. The uncovering of this bias and its source demonstrates the importance of continuous scientific oversight and effective user-data provider communication in stewarding scientific data. It also suggests the need for improvement in the ability of buoy data quality control procedures of the TAO and ECMWF systems to detect future wind directional systematic biases such as the one described here.

[1]  H.B. Milburn,et al.  ATLAS buoy-reengineered for the next decade , 1996, OCEANS 96 MTS/IEEE Conference Proceedings. The Coastal Ocean - Prospects for the 21st Century.

[2]  J. Bidlot,et al.  Evaluation of Various Surface Wind Products with OceanSITES Buoy Measurements , 2013 .

[3]  Y. Masumoto,et al.  RAMA: The Research Moored Array for African–Asian–Australian Monsoon Analysis and Prediction* , 2009 .

[4]  Sachin Chaturvedi,et al.  Genesis and Evolution , 2022, The Province and Politics of the Economic Torts.

[5]  Saleh Abdalla,et al.  Altimeter Near Real Time Wind and Wave Products: Random Error Estimation , 2011 .

[6]  Carl A. Mears,et al.  Comparison of Special Sensor Microwave Imager and buoy‐measured wind speeds from 1987 to 1997 , 2001 .

[7]  F. Wentz A well‐calibrated ocean algorithm for special sensor microwave / imager , 1997 .

[8]  Michael J. McPhaden,et al.  TOGA-TAO and the 1991–93 El Niño Southern Oscillation Event , 1993 .

[9]  Michael J. Caruso,et al.  Comparisons between the TAO Buoy and NASA Scatterometer Wind Vectors , 2001 .

[10]  A. Stoffelen Toward the true near-surface wind speed: Error modeling and calibration using triple collocation , 1998 .

[11]  Naoto Ebuchi,et al.  Evaluation of wind vectors observed by QuikSCAT/SeaWinds using ocean buoy data , 2000, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[12]  Michael J. Caruso,et al.  Evaluation of Wind Vectors Observed by QuikSCAT/SeaWinds Using Ocean Buoy Data , 2002 .

[13]  Antonio J. Busalacchi,et al.  The Tropical Ocean‐Global Atmosphere observing system: A decade of progress , 1998 .

[14]  Antonio J. Busalacchi,et al.  A TOGA Retrospective , 2010 .

[15]  Mark A. Bourassa,et al.  Quantifying variance due to temporal and spatial difference between ship and satellite winds , 2011 .

[16]  Peter Bauer,et al.  Direct 4D‐Var assimilation of all‐sky radiances. Part I: Implementation , 2010 .

[17]  H. Freitag,et al.  Calibration procedures and instrumental accuracies for ATLAS wind measurements , 2001 .

[18]  Michael H. Freilich,et al.  The accuracy of the NSCAT 1 vector winds: Comparisons with National Data Buoy Center buoys , 1999 .

[19]  Seungkoo Jo Genesis and Evolution , 2000 .

[20]  Frank J. Wentz,et al.  A Well Calibrated Ocean Algorithm for SSM/I , 1999 .

[21]  M. Mcphaden,et al.  Genesis and evolution of the 1997-98 El Nino , 1999, Science.

[22]  Fabrice Hernandez,et al.  THE PIRATA PROGRAM History, Accomplishments, and Future Directions * , 2008 .

[23]  Heikki Järvinen,et al.  Variational quality control , 1999 .