scholarly journals Impact of Global Data Assimilation System atmospheric models on astroparticle showers

2021 ◽  
Author(s):  
J. Grisales-Casadiegos ◽  
C. Sarmiento-Cano ◽  
L.A. Núñez
Keyword(s):  
Data Assimilation ◽  
Latin American ◽  
Ground Level ◽  
Atmospheric Models ◽  
Global Data Assimilation System ◽  
The Impact ◽  
The City ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System

We present a methodology to simulate the impact of the atmospheric models in the background particle flux on ground detectors using the Global Data Assimilation System. The methodology was within the ARTI simulation framework developed by the Latin American Giant Observatory Collaboration. The ground level secondary flux simulations were performed with a tropical climate at the city of Bucaramanga, Colombia. To validate our methodology, we built monthly profiles over Malargüe between 2006 and 2011, comparing the maximum atmospheric depth, X<sub>max</sub>, with those calculated with the Auger atmospheric option in CORSIKA. The results show significant differences between the predefined CORSIKA atmospheres and their corresponding Global Data Assimilation System atmospheric profiles.

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 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 Impact Study of AMSR-E Radiances in the NCEP Global Data Assimilation System

2008 ◽  
Vol 136 (2) ◽  
pp. 541-559 ◽  
Author(s):  
Masahiro Kazumori ◽  
Quanhua Liu ◽  
Russ Treadon ◽  
John C. Derber
Keyword(s):  
Data Assimilation ◽  
Geopotential Height ◽  
Track Forecast ◽  
Significant Difference ◽  
Emissivity Model ◽  
Global Data Assimilation System ◽  
The Impact ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System

Abstract The impact of radiance observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) was investigated in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). The GDAS used NCEP’s Gridpoint Statistical Interpolation (GSI) analysis system and the operational NCEP global forecast model. To improve the performance of AMSR-E low-frequency channels, a new microwave ocean emissivity model and its adjoint with respect to the surface wind speed and temperature were developed and incorporated into the assimilation system. The most significant impacts of AMSR-E radiances on the analysis were an increase in temperature of about 0.2 K at 850 hPa at the higher latitudes and a decrease in humidity of about 0.1 g kg−1 at 850 hPa over the ocean when the new emissivity model was used. There was no significant difference in the mean 6-h rainfall in the assimilation cycle. The forecasts made from the assimilation that included the AMSR-E data showed small improvements in the anomaly correlation of geopotential height at 1000 and 500 hPa in the Southern Hemisphere and reductions in the root-mean-square error (RMSE) for 500-hPa geopotential height in the extratropics of both hemispheres. Use of the new emissivity model resulted in improved RMSE for temperature forecasts from 1000 to 100 hPa in the extratropics of both hemispheres. The assimilation of AMSR-E radiances data using the emissivity model improved the track forecast for Hurricane Katrina in the 26 August 2005 case, whereas the assimilation using the NCEP operational emissivity model, FAST Emissivity Model, version 1 (FASTEM-1), degraded it.

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

Ocean Science ◽  
2017 ◽  
Vol 13 (6) ◽  
pp. 1077-1092 ◽  
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 not only quantify how well multiple altimeter missions and Argo profiling floats can constrain the global ocean analysis and 7-day forecast at 1∕4° resolution but also to better understand the sensitivity of results to data assimilation techniques used in Mercator Ocean operational systems. The impact of multiple altimeter data is clearly evidenced even at a 1∕4° resolution. Seven-day forecasts of sea level and ocean currents are significantly improved when moving from one altimeter to two altimeters not only on the sea level, but also on the 3-D thermohaline structure and currents. In high-eddy-energy regions, sea level and surface current 7-day forecast errors when assimilating one altimeter data set are respectively 20 and 45 % of the error of the simulation without assimilation. Seven-day 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 7-day 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 7-day forecast error level when two or three altimeter data sets are assimilated. Assimilating altimeter data also improves the representation of the 3-D ocean fields. The addition of Argo has a major impact on improving temperature and demonstrates the essential role of Argo together with altimetry in constraining 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 for more detailed characterisation of errors on analyses and 7-day 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 A Two-Season Impact Study of NOAA Polar-Orbiting Satellites in the NCEP Global Data Assimilation System

2008 ◽  
Vol 23 (5) ◽  
pp. 854-877 ◽  
Author(s):  
James A. Jung ◽  
Tom H. Zapotocny ◽  
John F. Le Marshall ◽  
Russ E. Treadon
Keyword(s):  
Data Assimilation ◽  
Forecast System ◽  
Anomaly Correlation ◽  
Global Data Assimilation System ◽  
Polar Orbiting Satellite ◽  
The Impact ◽  
Data Assimilation System ◽  
Global Data ◽  
Assimilation System ◽  
Forecast Quality

Abstract Observing system experiments (OSEs) during two seasons are used to quantify the important contributions made to forecast quality from the use of the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting satellites. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using one NOAA polar-orbiting satellite with results from using two and three polar-orbiting satellites in complementary orbits. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System–Global Forecast System (GDAS–GFS). The case studies chosen consist of periods during January–February and August–September 2003. Differences between the forecasts are accumulated over the two seasons and are analyzed to demonstrate the impact of these satellites. Anomaly correlations (ACs) and geographical forecasts (FIs) are evaluated for all experimental runs during both seasons. The anomaly correlations are generated using the standard NCEP verification software suite and cover the polar regions (60°–90°) and midlatitudes (20°–80°) of each hemisphere. The rms error for 850- and 200-hPa wind vector differences are shown for the tropical region (20°N–20°S). The geographical distribution of forecast impact on geopotential heights, relative humidity, precipitable water, and the u component of wind are also examined. The results demonstrate that the successive addition of each NOAA polar-orbiting satellite increases forecast quality. The use of three NOAA polar-orbiting satellites generally provides the largest improvement to the anomaly correlation scores in the polar and midlatitude regions. Improvements to the anomaly correlation scores are also realized from the use of two NOAA polar-orbiting satellites over only one. The forecast improvements from two satellites are generally smaller than if using three satellites, consistent with the increase in areal coverage obtained with the third satellite.

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