Forecast Impact of Assimilating Aircraft WVSS-II Water Vapor Mixing Ratio Observations in the Global Data Assimilation System (GDAS)

2017 ◽  
Vol 32 (4) ◽  
pp. 1603-1611 ◽  
Author(s):  
Brett T. Hoover ◽  
David A. Santek ◽  
Anne-Sophie Daloz ◽  
Yafang Zhong ◽  
Richard Dworak ◽  
...  
Keyword(s):  
Water Vapor ◽  
Data Assimilation ◽  
Positive Impact ◽  
Weather Prediction ◽  
Warm Season ◽  
Precipitation Forecast ◽  
Global Data Assimilation System ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System

Abstract Automated aircraft observations of wind and temperature have demonstrated positive impact on numerical weather prediction since the mid-1980s. With the advent of the Water Vapor Sensing System (WVSS-II) humidity sensor, the expanding fleet of commercial aircraft with onboard automated sensors is also capable of delivering high quality moisture observations, providing vertical profiles of moisture as aircraft ascend out of and descend into airports across the continental United States. Observations from the WVSS-II have to date only been monitored within the Global Data Assimilation System (GDAS) without being assimilated. In this study, aircraft moisture observations from the WVSS-II are assimilated into the GDAS, and their impact is assessed in the Global Forecast System (GFS). A two-season study is performed, demonstrating a statistically significant positive impact on both the moisture forecast and the precipitation forecast at short range (12–36 h) during the warm season. No statistically significant impact is observed during the cold season.

Assessment of the Impact of Simulated Satellite Lidar Wind and Retrieved 183 GHz Water Vapor Observations on a Global Data Assimilation System

1990 ◽  
Vol 118 (12) ◽  
pp. 2513-2542 ◽  
Author(s):  
Ross N. Hoffman ◽  
Christopher Grassotti ◽  
Ronald G. Isaacs ◽  
Jean-Francois Louis ◽  
Thomas Nehrkorn ◽  
...  
Keyword(s):  
Water Vapor ◽  
Data Assimilation ◽  
Global Data Assimilation System ◽  
The Impact ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System

Operational Implementation of COSMIC Observations into NCEP’s Global Data Assimilation System

2008 ◽  
Vol 23 (4) ◽  
pp. 702-711 ◽  
Author(s):  
L. Cucurull ◽  
J. C. Derber
Keyword(s):  
Data Assimilation ◽  
Positive Impact ◽  
Global Positioning ◽  
Global Data Assimilation System ◽  
The Tropics ◽  
Mean Square Errors ◽  
Data Assimilation System ◽  
Global Data ◽  
Global Reduction ◽  
Assimilation System

Abstract The next generation of NCEP’s Global Data Assimilation System became operational on 1 May 2007. This system incorporates the assimilation of global positioning system (GPS) radio occultation (RO) profiles from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) mission launched in April 2006. Roughly 1 yr after the launch of COSMIC, NCEP has begun operational use of this new dataset. A preliminary assessment of this observation type was performed with an earlier version of NCEP’s analysis at a lower resolution. These experiments showed positive impact when GPS RO soundings from the Challenging Minisatellite Payload (CHAMP) mission were assimilated into the system in non–real time. In these earlier studies, two different forward operators for the GPS RO profiles were evaluated: one for refractivity and another one for bending angle. In this paper, the data assimilation experiments with COSMIC observations that led NOAA/NCEP to assimilate COSMIC data into operations are described. The experiments were conducted with the current operational version of the code and at full operational resolution. Based on the results of the experiments analyzed here, profiles of refractivity were selected as the type of GPS RO observation to be assimilated. Further enhancement to the assimilation of bending angles is currently being evaluated at NCEP. The results show a significant improvement of the anomaly correlation skill and a global reduction of the NCEP model bias and root-mean-square errors when COSMIC observations are assimilated into the system. The improvement is found for the temperature, geopotential heights, and moisture variables. Larger benefits are found in the Southern Hemisphere extratropics, although a significant positive impact is also found in the Northern Hemisphere extratropics and the tropics. Even if GPS RO observations cannot produce direct impact on the wind field through the adjoint of the forward operator, a slight benefit is found in the wind components.

scholarly journals Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System

2021 ◽  
Author(s):  
Magnus Lindskog ◽  
Adam Dybbroe ◽  
Roger Randriamampianina
Keyword(s):  
Data Assimilation ◽  
Positive Impact ◽  
Weather Prediction ◽  
Implementation Process ◽  
Satellite System ◽  
Limited Area ◽  
Global Navigation Satellite ◽  
Microwave Radiances ◽  
Data Assimilation System ◽  
Assimilation System

AbstractMetCoOp is a Nordic collaboration on operational Numerical Weather Prediction based on a common limited-area km-scale ensemble system. The initial states are produced using a 3-dimensional variational data assimilation scheme utilizing a large amount of observations from conventional in-situ measurements, weather radars, global navigation satellite system, advanced scatterometer data and satellite radiances from various satellite platforms. A version of the forecasting system which is aimed for future operations has been prepared for an enhanced assimilation of microwave radiances. This enhanced data assimilation system will use radiances from the Microwave Humidity Sounder, the Advanced Microwave Sounding Unit-A and the Micro-Wave Humidity Sounder-2 instruments on-board the Metop-C and Fengyun-3 C/D polar orbiting satellites. The implementation process includes channel selection, set-up of an adaptive bias correction procedure, and careful monitoring of data usage and quality control of observations. The benefit of the additional microwave observations in terms of data coverage and impact on analyses, as derived using the degree of freedom of signal approach, is demonstrated. A positive impact on forecast quality is shown, and the effect on the precipitation for a case study is examined. Finally, the role of enhanced data assimilation techniques and adaptions towards nowcasting are discussed.

Introduction of the GSI into the NCEP Global Data Assimilation System

2009 ◽  
Vol 24 (6) ◽  
pp. 1691-1705 ◽  
Author(s):  
Daryl T. Kleist ◽  
David F. Parrish ◽  
John C. Derber ◽  
Russ Treadon ◽  
Wan-Shu Wu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Environmental Modeling ◽  
Analysis Scheme ◽  
Global Data Assimilation System ◽  
Analysis System ◽  
Data Assimilation System ◽  
Global Data ◽  
Statistical Interpolation ◽  
New System ◽  
Assimilation System

Abstract At the National Centers for Environmental Prediction (NCEP), a new three-dimensional variational data assimilation (3DVAR) analysis system was implemented into the operational Global Data Assimilation System (GDAS) on 1 May 2007. The new analysis system, the Gridpoint Statistical Interpolation (GSI), replaced the Spectral Statistical Interpolation (SSI) 3DVAR system, which had been operational since 1991. The GSI was developed at the Environmental Modeling Center at NCEP as part of an effort to create a more unified, robust, and efficient analysis scheme. The key aspect of the GSI is that it formulates the analysis in model grid space, which allows for more flexibility in the application of the background error covariances and makes it straightforward for a single analysis system to be used across a broad range of applications, including both global and regional modeling systems and domains. Due to the constraints of working with an operational system, the final GDAS package included many changes other than just a simple replacing of the SSI with the new GSI. The new GDAS package contained an upgrade to the Global Forecast System model, including a new vertical coordinate, as well as new features in the GSI that were never developed for the SSI. Some of these new features included changes to the observation selection, quality control, minimization algorithm, dynamic balance constraint, and assimilation of new observation types. The evaluation of the new system relative to the SSI-based system was performed for nearly an entire year of analyses and forecasts. The objective and subjective evaluations showed that the new package exhibited superior forecast performance relative to the old SSI-based system. The new system has been shown to improve forecast skill in the tropics and substantially reduce the short-term forecast error in the extratropics. This implementation has laid the groundwork for future scientific advancements in data assimilation at NCEP.

The Canadian Global Data Assimilation System: Description and Evaluation

1993 ◽  
Vol 121 (5) ◽  
pp. 1467-1492 ◽  
Author(s):  
Herschel L. Mitchell ◽  
Cécilien Charette ◽  
Steven J. Lambert ◽  
Jacques Hallé ◽  
Clément Chouinard
Keyword(s):  
Data Assimilation ◽  
System Description ◽  
Global Data Assimilation System ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System
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