Impact of Turkish ground-based GPS-PW data assimilation on regional forecast: 8-9 March 2011 heavy snow case

Seyda Tilev-Tanriover; Abdullah Kahraman

doi:10.1002/asl2.482

Impact of Turkish ground-based GPS-PW data assimilation on regional forecast: 8-9 March 2011 heavy snow case

Seyda Tilev-Tanriover^*, Abdullah Kahraman

^*Corresponding author for this work

Department of Meteorological Engineering

Istanbul Technical University

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

A ground-based Global Positioning System (GPS) network which consists of 147 uniformly distributed stations has been implemented in Turkey in May 2009. Precipitable water (PW) data estimated using this network is available since October 2010. Three experiments for a specific heavy snow case have been conducted to assess the impact of assimilation of this new data on short range weather forecasts. Verifications with surface observations indicate some reduction in the biases of basic variables for whole domain, and improvement in precipitation forecasts. Upper air variables of all simulations are compared with radiosonde observations, and some improvement in dew point temperatures through troposphere is observed with cycling mode assimilation.

Original language	English
Pages (from-to)	159-165
Number of pages	7
Journal	Atmospheric Science Letters
Volume	15
Issue number	3
DOIs	https://doi.org/10.1002/asl2.482
Publication status	Published - 2014

Keywords

Data assimilation
GPS-PW
Ground-based GPS
Heavy snow
Numerical weather prediction

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10.1002/asl2.482

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title = "Impact of Turkish ground-based GPS-PW data assimilation on regional forecast: 8-9 March 2011 heavy snow case",

abstract = "A ground-based Global Positioning System (GPS) network which consists of 147 uniformly distributed stations has been implemented in Turkey in May 2009. Precipitable water (PW) data estimated using this network is available since October 2010. Three experiments for a specific heavy snow case have been conducted to assess the impact of assimilation of this new data on short range weather forecasts. Verifications with surface observations indicate some reduction in the biases of basic variables for whole domain, and improvement in precipitation forecasts. Upper air variables of all simulations are compared with radiosonde observations, and some improvement in dew point temperatures through troposphere is observed with cycling mode assimilation.",

keywords = "Data assimilation, GPS-PW, Ground-based GPS, Heavy snow, Numerical weather prediction",

author = "Seyda Tilev-Tanriover and Abdullah Kahraman",

year = "2014",

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language = "English",

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journal = "Atmospheric Science Letters",

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T1 - Impact of Turkish ground-based GPS-PW data assimilation on regional forecast

T2 - 8-9 March 2011 heavy snow case

AU - Tilev-Tanriover, Seyda

AU - Kahraman, Abdullah

PY - 2014

Y1 - 2014

N2 - A ground-based Global Positioning System (GPS) network which consists of 147 uniformly distributed stations has been implemented in Turkey in May 2009. Precipitable water (PW) data estimated using this network is available since October 2010. Three experiments for a specific heavy snow case have been conducted to assess the impact of assimilation of this new data on short range weather forecasts. Verifications with surface observations indicate some reduction in the biases of basic variables for whole domain, and improvement in precipitation forecasts. Upper air variables of all simulations are compared with radiosonde observations, and some improvement in dew point temperatures through troposphere is observed with cycling mode assimilation.

AB - A ground-based Global Positioning System (GPS) network which consists of 147 uniformly distributed stations has been implemented in Turkey in May 2009. Precipitable water (PW) data estimated using this network is available since October 2010. Three experiments for a specific heavy snow case have been conducted to assess the impact of assimilation of this new data on short range weather forecasts. Verifications with surface observations indicate some reduction in the biases of basic variables for whole domain, and improvement in precipitation forecasts. Upper air variables of all simulations are compared with radiosonde observations, and some improvement in dew point temperatures through troposphere is observed with cycling mode assimilation.

KW - Data assimilation

KW - GPS-PW

KW - Ground-based GPS

KW - Heavy snow

KW - Numerical weather prediction

UR - https://www.scopus.com/pages/publications/84904573944

U2 - 10.1002/asl2.482

DO - 10.1002/asl2.482

M3 - Article

AN - SCOPUS:84904573944

SN - 1530-261X

VL - 15

SP - 159

EP - 165

JO - Atmospheric Science Letters

JF - Atmospheric Science Letters

IS - 3

ER -

Impact of Turkish ground-based GPS-PW data assimilation on regional forecast: 8-9 March 2011 heavy snow case

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Keywords

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