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The Effect of Targeted Dropsonde Observations during the 1999 Winter Storm Reconnaissance Program

I. SzunyoghUCAR Visiting Scientist, National Centers for Environmental Prediction, Camp Springs, Maryland

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Z. TothGeneral Sciences Corporation, National Centers for Environmental Prediction, Camp Springs, Maryland

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R. E. MorssProgram in Atmospheres, Oceans, and Climate, Massachusetts Institute of Technology, Cambridge, Massachusetts

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S. J. MajumdarDepartment of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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B. J. EthertonDepartment of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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C. H. BishopDepartment of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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Abstract

In this paper, the effects of targeted dropsonde observations on operational global numerical weather analyses and forecasts made at the National Centers for Environmental Prediction (NCEP) are evaluated. The data were collected during the 1999 Winter Storm Reconnaissance field program at locations that were found optimal by the ensemble transform technique for reducing specific forecast errors over the continental United States and Alaska. Two parallel analysis–forecast cycles are compared; one assimilates all operationally available data including those from the targeted dropsondes, whereas the other is identical except that it excludes all dropsonde data collected during the program.

It was found that large analysis errors appear in areas of intense baroclinic energy conversion over the northeast Pacific and are strongly associated with errors in the first-guess field. The “signal,” defined by the difference between analysis–forecast cycles with and without the dropsonde data, propagates at an average speed of 30° per day along the storm track to the east. Hovmöller diagrams and eddy statistics suggest that downstream development plays a significant role in spreading out the effect of the dropsondes in space and time. On average, the largest rms surface pressure errors are reduced by 10%–20% associated with the eastward-propagating leading edge of the signal. The dropsonde data seem to be more effective in reducing forecast errors when zonal flow prevails over the eastern Pacific. Results from combined verification statistics (based on surface pressure, tropospheric winds, and precipitation amount) indicate that the dropsonde data improved the forecasts in 18 of the 25 targeted cases, while the impact was negative (neutral) in only 5 cases.

* Permanent affiliation: Department of Meteorology, Eotvos Lorand University, Budapest, Hungary.

Corresponding author address: Dr. Istvan Szunyogh, National Centers for Environmental Prediction, EMC, 5200 Auth Road, WWB, Room 207, Camp Springs, MD 20746.

Email: Istvan.Szunyogh@noaa.gov

Abstract

In this paper, the effects of targeted dropsonde observations on operational global numerical weather analyses and forecasts made at the National Centers for Environmental Prediction (NCEP) are evaluated. The data were collected during the 1999 Winter Storm Reconnaissance field program at locations that were found optimal by the ensemble transform technique for reducing specific forecast errors over the continental United States and Alaska. Two parallel analysis–forecast cycles are compared; one assimilates all operationally available data including those from the targeted dropsondes, whereas the other is identical except that it excludes all dropsonde data collected during the program.

It was found that large analysis errors appear in areas of intense baroclinic energy conversion over the northeast Pacific and are strongly associated with errors in the first-guess field. The “signal,” defined by the difference between analysis–forecast cycles with and without the dropsonde data, propagates at an average speed of 30° per day along the storm track to the east. Hovmöller diagrams and eddy statistics suggest that downstream development plays a significant role in spreading out the effect of the dropsondes in space and time. On average, the largest rms surface pressure errors are reduced by 10%–20% associated with the eastward-propagating leading edge of the signal. The dropsonde data seem to be more effective in reducing forecast errors when zonal flow prevails over the eastern Pacific. Results from combined verification statistics (based on surface pressure, tropospheric winds, and precipitation amount) indicate that the dropsonde data improved the forecasts in 18 of the 25 targeted cases, while the impact was negative (neutral) in only 5 cases.

* Permanent affiliation: Department of Meteorology, Eotvos Lorand University, Budapest, Hungary.

Corresponding author address: Dr. Istvan Szunyogh, National Centers for Environmental Prediction, EMC, 5200 Auth Road, WWB, Room 207, Camp Springs, MD 20746.

Email: Istvan.Szunyogh@noaa.gov

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