Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products

2012 ◽  
Vol 39 (12) ◽  
pp. 2769-2787 ◽  
Author(s):  
Hyelim Yoo ◽  
Zhanqing Li
Keyword(s):  
Global Forecast System ◽  
Forecast System ◽  
Cloud Properties ◽  
Ncep Global Forecast System

scholarly journals Ensemble Data Assimilation with the NCEP Global Forecast System

2008 ◽  
Vol 136 (2) ◽  
pp. 463-482 ◽  
Author(s):  
Jeffrey S. Whitaker ◽  
Thomas M. Hamill ◽  
Xue Wei ◽  
Yucheng Song ◽  
Zoltan Toth
Keyword(s):  
Data Assimilation ◽  
Southern Hemisphere ◽  
Global Forecast System ◽  
Forecast System ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
Triangular Truncation ◽  
Data Assimilation System ◽  
Ncep Global Forecast System ◽  
Assimilation System

Abstract Real-data experiments with an ensemble data assimilation system using the NCEP Global Forecast System model were performed and compared with the NCEP Global Data Assimilation System (GDAS). All observations in the operational data stream were assimilated for the period 1 January–10 February 2004, except satellite radiances. Because of computational resource limitations, the comparison was done at lower resolution (triangular truncation at wavenumber 62 with 28 levels) than the GDAS real-time NCEP operational runs (triangular truncation at wavenumber 254 with 64 levels). The ensemble data assimilation system outperformed the reduced-resolution version of the NCEP three-dimensional variational data assimilation system (3DVAR), with the biggest improvement in data-sparse regions. Ensemble data assimilation analyses yielded a 24-h improvement in forecast skill in the Southern Hemisphere extratropics relative to the NCEP 3DVAR system (the 48-h forecast from the ensemble data assimilation system was as accurate as the 24-h forecast from the 3DVAR system). Improvements in the data-rich Northern Hemisphere, while still statistically significant, were more modest. It remains to be seen whether the improvements seen in the Southern Hemisphere will be retained when satellite radiances are assimilated. Three different parameterizations of background errors unaccounted for in the data assimilation system (including model error) were tested. Adding scaled random differences between adjacent 6-hourly analyses from the NCEP–NCAR reanalysis to each ensemble member (additive inflation) performed slightly better than the other two methods (multiplicative inflation and relaxation-to-prior).

Assimilation of TRMM Multisatellite Precipitation Analysis with a Low-Resolution NCEP Global Forecast System

2016 ◽  
Vol 144 (2) ◽  
pp. 643-661 ◽  
Author(s):  
Guo-Yuan Lien ◽  
Takemasa Miyoshi ◽  
Eugenia Kalnay
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Cumulative Distribution ◽  
Precipitation Data ◽  
Global Forecast System ◽  
Low Resolution ◽  
Forecast System ◽  
Original Solution ◽  
Precipitation Analysis ◽  
Ncep Global Forecast System

Abstract Current methods of assimilation of precipitation into numerical weather prediction models are able to make the model precipitation become similar to the observed precipitation during the assimilation, but the model forecasts tend to return to their original solution after a few hours. To facilitate the precipitation assimilation, a logarithm transformation has been used in several past studies. Lien et al. proposed instead to assimilate precipitation using the local ensemble transform Kalman filter (LETKF) with a Gaussian transformation technique and succeeded in improving the model forecasts in perfect-model observing system simulation experiments (OSSEs). In this study, the method of Lien et al. is tested within a more realistic configuration: the TRMM Multisatellite Precipitation Analysis (TMPA) data are assimilated into a low-resolution version of the NCEP Global Forecast System (GFS). With guidance from a statistical study comparing the GFS model background precipitation and the TMPA data, some modifications of the assimilation methods proposed in Lien et al. are made, including 1) applying separate Gaussian transformations to model and to observational precipitation based on their own cumulative distribution functions; 2) adopting a quality control criterion based on the correlation between the long-term model and observed precipitation data at the observation location; and 3) proposing a new method to define the transformation of zero precipitation that takes into account the zero precipitation probability in the background ensemble rather than the climatology. With these modifications, the assimilation of the TMPA precipitation data improves both the analysis and 5-day model forecasts when compared with a control experiment assimilating only rawinsonde data.

scholarly journals A Preliminary Assessment of the Impact of Assimilating Satellite Soil Moisture Data Products on NCEP Global Forecast System

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Weizhong Zheng ◽  
Xiwu Zhan ◽  
Jicheng Liu ◽  
Michael Ek
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Prediction Models ◽  
Precipitation Forecast ◽  
Global Forecast System ◽  
Forecast System ◽  
Numerical Weather ◽  
Soil Moisture Data ◽  
Data Products ◽  
Ncep Global Forecast System

It is well documented that soil moisture has a strong impact on precipitation forecasts of numerical weather prediction models. Several microwave satellite soil moisture retrieval data products have also been available for applications. However, these observational data products have not been employed in any operational numerical weather or climate prediction models. In this study, a preliminary test of assimilating satellite soil moisture data products from the NOAA-NESDIS Soil Moisture Operational Product System (SMOPS) into the NOAA-NCEP Global Forecast System (GFS) is conducted. Using the ensemble Kalman filter (EnKF) introduced in recent year publications and implemented in the GFS, the multiple satellite blended daily global soil moisture data from SMOPS for the month of April 2012 are assimilated into the GFS. The forecasts of surface variables, anomaly correlations of isobar heights, and precipitation forecast skills of the GFS with and without the soil moisture data assimilation are assessed. The surface and deep layer soil moisture estimates of the GFS after the satellite soil moisture assimilation are found to have slightly better agreement with the ground soil moisture measurements at dozens of sites across the continental United States (CONUS). Forecasts of surface humidity and air temperature, 500 hPa height anomaly correlations, and the precipitation forecast skill demonstrated certain level of improvements after the soil moisture assimilation against those without the soil moisture assimilation. However, the methodology for the soil moisture data assimilation into operational GFS runs still requires further development efforts and tests.

scholarly journals Improving the Stable Surface Layer in the NCEP Global Forecast System

2017 ◽  
Vol 145 (10) ◽  
pp. 3969-3987 ◽  
Author(s):  
Weizhong Zheng ◽  
Michael Ek ◽  
Kenneth Mitchell ◽  
Helin Wei ◽  
Jesse Meng
Keyword(s):  
Surface Layer ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Global Forecast System ◽  
Surface Cooling ◽  
Forecast System ◽  
Near Surface ◽  
Stable Surface ◽  
Stable Surface Layer ◽  
Ncep Global Forecast System

This study examines the performance of the NCEP Global Forecast System (GFS) surface layer parameterization scheme for strongly stable conditions over land in which turbulence is weak or even disappears because of high near-surface atmospheric stability. Cases of both deep snowpack and snow-free conditions are investigated. The results show that decoupling and excessive near-surface cooling may appear in the late afternoon and nighttime, manifesting as a severe cold bias of the 2-m surface air temperature that persists for several hours or more. Concurrently, because of negligible downward heat transport from the atmosphere to the land, a warm temperature bias develops at the first model level. The authors test changes to the stable surface layer scheme that include introduction of a stability parameter constraint that prevents the land–atmosphere system from fully decoupling and modification to the roughness-length formulation. GFS sensitivity runs with these two changes demonstrate the ability of the proposed surface layer changes to reduce the excessive near-surface cooling in forecasts of 2-m surface air temperature. The proposed changes prevent both the collapse of turbulence in the stable surface layer over land and the possibility of numerical instability resulting from thermal decoupling between the atmosphere and the surface. The authors also execute and evaluate daily GFS 7-day test forecasts with the proposed changes spanning a one-month period in winter. The assessment reveals that the systematic deficiencies and substantial errors in GFS near-surface 2-m air temperature forecasts are considerably reduced, along with a notable reduction of temperature errors throughout the lower atmosphere and improvement of forecast skill scores for light and medium precipitation amounts.

scholarly journals GSI 3DVar-Based Ensemble–Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single-Resolution Experiments

2013 ◽  
Vol 141 (11) ◽  
pp. 4098-4117 ◽  
Author(s):  
Xuguang Wang ◽  
David Parrish ◽  
Daryl Kleist ◽  
Jeffrey Whitaker
Keyword(s):  
Data Assimilation ◽  
Hybrid System ◽  
Coupled System ◽  
Global Forecast System ◽  
Forecast System ◽  
Outer Loop ◽  
Hybrid Data Assimilation ◽  
Hybrid Data ◽  
The One ◽  
Ncep Global Forecast System

Abstract An ensemble Kalman filter–variational hybrid data assimilation system based on the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVar) system was developed. The performance of the system was investigated using the National Centers for Environmental Prediction (NCEP) Global Forecast System model. Experiments covered a 6-week Northern Hemisphere winter period. Both the control and ensemble forecasts were run at the same, reduced resolution. Operational conventional and satellite observations along with an 80-member ensemble were used. Various configurations of the system including one- or two-way couplings, with zero or nonzero weights on the static covariance, were intercompared and compared with the GSI 3DVar system. It was found that the hybrid system produced more skillful forecasts than the GSI 3DVar system. The inclusion of a static component in the background-error covariance and recentering the analysis ensemble around the variational analysis did not improve the forecast skill beyond the one-way coupled system with zero weights on the static covariance. The one-way coupled system with zero static covariances produced more skillful wind forecasts averaged over the globe than the EnKF at the 1–5-day lead times and more skillful temperature forecasts than the EnKF at the 5-day lead time. Sensitivity tests indicated that the difference may be due to the use of the tangent linear normal mode constraint in the variational system. For the first outer loop, the hybrid system showed a slightly slower (faster) convergence rate at early (later) iterations than the GSI 3DVar system. For the second outer loop, the hybrid system showed a faster convergence.

Sensitivity of Typhoon Track Predictions in a Regional Prediction System to Initial and Lateral Boundary Conditions

2009 ◽  
Vol 48 (9) ◽  
pp. 1913-1928 ◽  
Author(s):  
Ling-Feng Hsiao ◽  
Melinda S. Peng ◽  
Der-Song Chen ◽  
Kang-Ning Huang ◽  
Tien-Chiang Yeh
Keyword(s):  
Boundary Conditions ◽  
Initial Conditions ◽  
Forecast Model ◽  
Western Pacific ◽  
Lateral Boundary ◽  
Global Forecast System ◽  
Forecast System ◽  
Lateral Boundary Conditions ◽  
The Western Pacific ◽  
Ncep Global Forecast System

Abstract Tropical cyclone (TC) track predictions from the operational regional nonhydrostatic TC forecast system of the Taiwanese Central Weather Bureau (CWB) are examined for their sensitivities to initial and lateral boundary conditions. Five experiments are designed and discussed, each using a combination of different initial and lateral boundary conditions coming either from the CWB or the National Centers for Environmental Prediction (NCEP) global forecast system. Eight typhoons in the western Pacific Ocean with 51 cases in 2004 and 2005 are tested with the five designed experiments for the 3-day forecast. The average track forecasts are the best when both the initial and lateral boundary conditions are from the NCEP global forecast system. This reflects the generally superior performance of the NCEP global forecast system relative to that of the CWB. Using different lateral boundary conditions has a greater impact on the track than using different initial conditions. Diagnostics using piecewise inversion of potential vorticity perturbations are carried out to identify synoptic features surrounding the featured typhoon that impact the track the most in each experiment. For the two cases demonstrated with the largest track improvement using NCEP global fields, the diagnostics indicate that the prediction of the strength and extent of the subtropical high in the western Pacific plays the major role in affecting these storm tracks. Using the analysis and predictions of the CWB global forecast system as the initial and lateral boundary conditions produces an overintensified subtropical ridge in the regional TC forecast model. Because most of the typhoons studied are located in the southwestern peripheral of the western Pacific subtropical high, the stronger steering from the more intense and extended high system is the main cause of the poleward bias in the predicted typhoon tracks in the operational run, which uses the CWB global forecast fields. The study suggests that, when efforts are made to improve a regional TC forecast model, it is also critically important to improve the global forecast system that provides the lateral boundary and initial conditions to the regional system.

scholarly journals A Multiconserving Discretization with Enthalpy as a Thermodynamic Prognostic Variable in Generalized Hybrid Vertical Coordinates for the NCEP Global Forecast System

2011 ◽  
Vol 139 (5) ◽  
pp. 1583-1607 ◽  
Author(s):  
Hann-Ming Henry Juang
Keyword(s):  
Implicit Time ◽  
Global Forecast System ◽  
Forecast System ◽  
Vertical Coordinate ◽  
Prognostic Variable ◽  
Specific Hybrid ◽  
Environmental Prediction ◽  
Daily Forecast ◽  
Isentropic Coordinates ◽  
Ncep Global Forecast System

A new vertical discretization used in the atmospheric dynamics of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) is illustrated, with enthalpy as the thermodynamic prognostic variable to reduce computation in thermodynamic equations while concerning all gas tracers in the model. Mass, energy, entropy, and angular momentum conservations are utilized as constraints to discretize the vertical integration with a finite-difference scheme. A specific definition of a generalized hybrid vertical coordinate, including sigma, isobaric, and isentropic surfaces, is introduced to define pressure at the model levels. Vertical fluxes are obtained by the equation of local changes in variables defined for vertical coordinates at all model layers. The forward-weighting semi-implicit time scheme is utilized to eliminate computational noise for stable integration. Because of time splitting between the dynamic and physics processes, the vertical advection is required both in the model dynamics and model physics, and the semi-implicit time scheme is used both in dynamics and after physics computation. Three configurations—sigma, sigma pressure, and sigma entropy—from the specific hybrid vertical coordinates with layer definition similar to NCEP operational GFS have been implemented in the NCEP GFS. Results from the sigma-isentropic coordinate show the largest anomaly correlation and the smallest root-mean-square error in tropical wind among all results at all layers, especially the upper layers. The scores from a period of daily forecast up to 5 days with the sigma-isentropic coordinate show the same level of skill as compared to the NCEP operational GFS. The results from the hurricane tracks for the fall of 2005 with sigma-isentropic coordinates show better scores compared with the operational GFS.

Predictability of PM2.5 in Seoul based on atmospheric blocking forecasts using the NCEP global forecast system

2021 ◽  
Vol 246 ◽  
pp. 118141
Author(s):  
Uju Shin ◽  
Sang-Hun Park ◽  
Joon-Sung Park ◽  
Ja-Ho Koo ◽  
Changhyun Yoo ◽  
...  
Keyword(s):  
Global Forecast System ◽  
Atmospheric Blocking ◽  
Forecast System ◽  
Ncep Global Forecast System
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