The impact of GMS (Geostationary Meteorological Satellite) data in the GDAPS (Global Data Assimilation and Prediction System)

2002 ◽  
Author(s):  
Sang-Won Joo ◽  
Nam-Ouk Kim
Keyword(s):  
Data Assimilation ◽  
Satellite Data ◽  
Prediction System ◽  
Geostationary Meteorological Satellite ◽  
The Impact ◽  
Meteorological Satellite ◽  
Global Data

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

scholarly journals Impact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts

2006 ◽  
Vol 21 (4) ◽  
pp. 663-669 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Yihong Duan ◽  
Johnny C. L. Chan
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Mesoscale Model ◽  
State University ◽  
Motion Vectors ◽  
Geostationary Meteorological Satellite ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Data Assimilation Technique ◽  
The Impact

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.

The impact of Argo observations in a global weakly coupled ocean–atmosphere data assimilation and short‐range prediction system

2019 ◽  
Vol 146 (726) ◽  
pp. 401-414 ◽  
Author(s):  
Robert R. King ◽  
Daniel J. Lea ◽  
Matthew J. Martin ◽  
Isabelle Mirouze ◽  
Julian Heming
Keyword(s):  
Data Assimilation ◽  
Short Range ◽  
Prediction System ◽  
Weakly Coupled ◽  
Ocean Atmosphere ◽  
The Impact

scholarly journals Single cell and multiple cell clouds analysed with satellite data in and around Bangladesh

MAUSAM ◽  
2021 ◽  
Vol 50 (2) ◽  
pp. 177-180
Author(s):  
C. M. MUKAMMEL WARID ◽  
Md. REZAUR RAHMAN ◽  
Md. NAZRUL ISLAM
Keyword(s):  
Single Cell ◽  
Satellite Data ◽  
Mature Stage ◽  
Convective Component ◽  
Geostationary Meteorological Satellite ◽  
Multiple Cell ◽  
Meteorological Satellite

Multi-cell and single-cell clouds were analysed using Geostationary Meteorological Satellite (GMS-5) data on 6 and 13 August 1997 in and around Bangladesh. The multi-cell cloud moved NE with a speed of about 6 m/s and lasted approximately 21 hours. The single-cell cloud moved SE with a speed of about 13 m/s and lasted approximately 12 hours. Clouds move faster on oceans than on land. At the mature stage of the cloud, convective component was 40% and the rest was stratiform. The precipitable portion of the cloud was 74% and the rest was non-precipitable which differs from the reported value.

scholarly journals Assessing the impact of multiple altimeter missions and Argo in a global eddy permitting data assimilation system

2017 ◽  
Author(s):  
Simon Verrier ◽  
Pierre-Yves Le Traon ◽  
Elisabeth Remy
Keyword(s):  
Data Assimilation ◽  
Sea Level ◽  
Error Reduction ◽  
Altimeter Data ◽  
Error Level ◽  
Global Data Assimilation System ◽  
The Impact ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System

Abstract. A series of Observing System Simulation Experiments (OSSEs) is carried out with a global data assimilation system at 1/4° resolution using simulated data derived from a 1/12° resolution free run simulation. The objective is to quantify how well multiple altimeter missions and Argo profiling floats can constrain a global data assimilation system but also to better understand the sensitivity of results to data assimilation techniques used in Mercator Ocean operational systems. Impact of multiple altimeter data is clearly evidenced. Forecasts of sea level and ocean currents are significantly improved when moving from one altimeter to two altimeters. In high eddy energy regions, sea level and surface current forecast errors when assimilating one altimeter data set are respectively 20 % and 45 % of the error of the simulation without assimilation. Forecasts of sea level and ocean currents continue to be improved when moving from one altimeter to two altimeters with a relative error reduction of almost 30 %. The addition of a third altimeter still improves the forecasts even at this medium 1/4° resolution and brings an additional relative error reduction of about 10 %. The error level of the analysis with one altimeter is close to the forecast error level when two or three altimeter data sets are assimilated. Assimilating altimeter data also improves the representation of the 3D ocean fields. The addition of Argo has a major impact to improve temperature and demonstrates the essential role of Argo together with altimetry to constrain a global data assimilation system. Salinity fields are only marginally improved. Results derived from these OSSEs are consistent with those derived from experiments with real data (observing system evaluations/OSEs) but they allow a more detailed characterization of errors on analyses and forecasts. Both OSEs and OSSEs should be systematically used and intercompared to test data assimilation systems and quantify the impact of existing observing systems.

scholarly journals Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite

2016 ◽  
Vol 43 (11) ◽  
pp. 5886-5894 ◽  
Author(s):  
K. Yumimoto ◽  
T.M. Nagao ◽  
M. Kikuchi ◽  
T.T Sekiyama ◽  
H. Murakami ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Next Generation ◽  
Geostationary Meteorological Satellite ◽  
Using Data ◽  
Meteorological Satellite

scholarly journals Comparing Impacts of Satellite Data Assimilation and Lateral Boundary Conditions on Regional Model Forecasting: A Case Study of Hurricane Sandy (2012)

2017 ◽  
Vol 32 (2) ◽  
pp. 595-608
Author(s):  
Tong Zhu ◽  
Sid Ahmed Boukabara ◽  
Kevin Garrett
Keyword(s):  
Data Assimilation ◽  
Boundary Conditions ◽  
Satellite Data ◽  
Regional Model ◽  
Hurricane Sandy ◽  
Track Forecast ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
Outer Domain ◽  
The Impact

Abstract The impacts of both satellite data assimilation (DA) and lateral boundary conditions (LBCs) on the Hurricane Weather Research and Forecasting (HWRF) Model forecasts of Hurricane Sandy 2012 were assessed. To investigate the impact of satellite DA, experiments were run with and without satellite data assimilated, as well as with all satellite data but excluding Geostationary Operational Environmental Satellite (GOES) Sounder data. To gauge the LBC impact, these experiments were also run with a variety of outer domain (D-1) sizes. The inclusion of satellite DA resulted in analysis fields that better characterized the tropical storm structures including the warm core anomaly and wavenumber-1 asymmetry near the eyewall, and also served to reduce the forecast track errors for Hurricane Sandy. The specific impact of assimilating the GOES Sounder data showed positive impacts on forecasts of the storm minimum sea level pressure. Increasing the D-1 size resulted in increases in the day 4/5 forecast track errors when verified against the best track and the Global Forecast System (GFS) forecast, which dominated any benefits from assimilating an increased volume of satellite observations due to the larger domain. It was found that the LBCs with realistic environmental flow information could provide better constraints on smaller domain forecasts. This study demonstrated that satellite DA can improve the analysis of a hurricane asymmetry, especially in a shear environment, and then lead to a better track forecast, and also emphasized the importance of the LBCs and the challenges associated with the evaluation of satellite data impacts on regional model prediction.

scholarly journals Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part II: Combined Radar and Satellite Data Experiments

2016 ◽  
Vol 31 (1) ◽  
pp. 297-327 ◽  
Author(s):  
Thomas A. Jones ◽  
Kent Knopfmeier ◽  
Dustan Wheatley ◽  
Gerald Creager ◽  
Patrick Minnis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Satellite Data ◽  
Positive Impact ◽  
Lessons Learned ◽  
Supercell Storms ◽  
Thermodynamic Conditions ◽  
System Part ◽  
Tornadic Storms ◽  
Ice Water ◽  
The Impact

Abstract This research represents the second part of a two-part series describing the development of a prototype ensemble data assimilation system for the Warn-on-Forecast (WoF) project known as the NSSL Experimental WoF System for ensembles (NEWS-e). Part I describes the NEWS-e design and results from radar reflectivity and radial velocity data assimilation for six severe weather events occurring during 2013 and 2014. Part II describes the impact of assimilating satellite liquid and ice water path (LWP and IWP, respectively) retrievals from the GOES Imager along with the radar observations. Assimilating LWP and IWP observations may improve thermodynamic conditions at the surface over the storm-scale domain through better analysis of cloud coverage in the model compared to radar-only experiments. These improvements sometimes corresponded to an improved analysis of supercell storms leading to better forecasts of low-level vorticity. This positive impact was most evident for events where convection is not ongoing at the beginning of the radar and satellite data assimilation period. For more complex cases containing significant amounts of ongoing convection, only assimilating clear-sky satellite retrievals in place of clear-air reflectivity resulted in spurious regions of light precipitation compared to the radar-only experiments. The analyzed tornadic storms in these experiments are sometimes too weak and quickly diminished in intensity in the forecasts. The lessons learned as part of these experiments should lead to improved iterations of the NEWS-e system, building on the modestly successful results described here.

Sign in / Sign up

Export Citation Format

Share Document