scholarly journals An Impact Study of Five Remotely Sensed and Five In Situ Data Types in the Eta Data Assimilation System

2002 ◽  
Vol 17 (2) ◽  
pp. 263-285 ◽  
Author(s):  
Tom H. Zapotocny ◽  
W. Paul Menzel ◽  
James P. Nelson ◽  
James A. Jung
Keyword(s):  
Data Assimilation ◽  
Remotely Sensed ◽  
Impact Study ◽  
Data Types ◽  
In Situ Data ◽  
Data Assimilation System ◽  
Assimilation System

A Two-Season Impact Study of Satellite and In Situ Data in the NCEP Global Data Assimilation System

2007 ◽  
Vol 22 (4) ◽  
pp. 887-909 ◽  
Author(s):  
Tom H. Zapotocny ◽  
James A. Jung ◽  
John F. Le Marshall ◽  
Russ E. Treadon
Keyword(s):  
Data Assimilation ◽  
Satellite Data ◽  
Geopotential Height ◽  
Remotely Sensed ◽  
Data Types ◽  
In Situ Data ◽  
Hurricane Track ◽  
Experimental Runs ◽  
Global Data

Abstract Observing system experiments are used to quantify the contributions to the forecast made by conventional in situ and remotely sensed satellite data. The impact of each data type is assessed by comparing the analyses and forecasts based on an observing system using all data types. The analysis and forecast model used for these observing system experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation/Forecast System (GDAS/GFS). The case studies chosen consist of 45-day periods during January–February 2003 and August–September 2003. During these periods, a T254–64 layer version of NCEP’s Global Spectral Model was used. The control run utilizes NCEP’s operational database and consists of all data types routinely assimilated in the GDAS. The two experimental runs have either all the conventional in situ data denied (NoCon) or all the remotely sensed satellite data denied (NoSat). Differences between the control and experimental runs are accumulated over the 45-day periods and analyzed to demonstrate the forecast impact of these data types through 168 h. Anomaly correlations, forecast impacts, and hurricane track forecasts are evaluated for both experiments. Anomaly correlations of geopotential height are evaluated over the polar caps and midlatitudes of both the Northern and Southern Hemispheres for spectral waves 1–20. Forecast impacts related to conventional meteorological parameters are evaluated. The parameters examined include geopotential height, precipitable water, temperature, the u component of the wind, wind vector differences, and relative humidity. Comparisons are made on multiple pressure levels extending from 10 to 1000 hPa. Hurricane track forecasts are evaluated during August and September for both the Atlantic and eastern Pacific basins. The results demonstrate a positive forecast impact from both the conventional in situ and remotely sensed satellite data during both seasons in both hemispheres. The positive forecast impacts from the conventional and satellite data are of similar magnitude in the Northern Hemisphere; however, the contribution to forecast quality from satellite data is considerably larger than the conventional data in the Southern Hemisphere. The importance of satellite data also generally increases at longer forecast times relative to conventional data. Finally, the accuracy of hurricane track forecasts benefits from the inclusion of both conventional and satellite data.

scholarly journals Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System

Hydrology ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 57 ◽  
Author(s):  
Debjani Ghatak ◽  
Benjamin Zaitchik ◽  
Sujay Kumar ◽  
Mir A. Matin ◽  
Birendra Bajracharya ◽  
...  
Keyword(s):  
South Asia ◽  
Hydrological Simulation ◽  
Meteorological Forcing ◽  
In Situ Data ◽  
Precipitation Estimates ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Assimilation System

: Accurate meteorological estimates are critical for process-based hydrological simulation and prediction. This presents a significant challenge in mountainous Asia where in situ meteorological stations are limited and major river basins cross international borders. In this context, remotely sensed and model-derived meteorological estimates are often necessary inputs for distributed hydrological analysis. However, these datasets are difficult to evaluate on account of limited access to ground data. In this case, the implications of uncertainty associated with precipitation forcing for hydrological simulations is explored by driving the South Asia Land Data Assimilation System (South Asia LDAS) using a range of meteorological forcing products. MERRA2, GDAS, and CHIRPS produce a wide range of estimates for rainfall, which causes a widespread simulated streamflow and evapotranspiration. A combination of satellite-derived and limited in situ data are applied to evaluate model simulations and, by extension, to constrain the estimates of precipitation. The results show that available gridded precipitation estimates based on in situ data may systematically underestimate precipitation in mountainous regions and that performance of gridded satellite-derived or modeled precipitation estimates varies systematically across the region. Since no station-based data or product including station data is satisfactory everywhere, our results suggest that the evaluation of the hydrological simulation of streamflow and ET can be used as an indirect evaluation of precipitation forcing based on ground-based products or in-situ data. South Asia LDAS produces reasonable evapotranspiration and streamflow when forced with appropriate meteorological forcing and the choice of meteorological forcing should be made based on the geographical location as well as on the purpose of the simulations.

scholarly journals The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015

2017 ◽  
Author(s):  
Ingrid T. van der Laan-Luijkx ◽  
Ivar R. van der Velde ◽  
Emma van der Veen ◽  
Aki Tsuruta ◽  
Karolina Stanislawska ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Carbon Sink ◽  
Carbon Sources ◽  
Sources And Sinks ◽  
Wide Range ◽  
Abstract Data ◽  
Global Carbon ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to space-based remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system which is called the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO2 growth rate compared to 2014, due to reduced land carbon uptake in later year. The European carbon sink is especially present in the forests, and is reduced during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.

scholarly journals Use and Impact of Automated Aircraft Data in a Global 4DVAR Data Assimilation System

2003 ◽  
Vol 131 (8) ◽  
pp. 1865-1877 ◽  
Author(s):  
Carla Cardinali ◽  
Lars Isaksen ◽  
Erik Andersson
Keyword(s):  
Data Assimilation ◽  
North Atlantic ◽  
Positive Impact ◽  
Impact Study ◽  
Forecast Performance ◽  
The North ◽  
Medium Range ◽  
Data Assimilation System ◽  
Aircraft Data ◽  
Assimilation System

Abstract The use of automated aircraft data [Aircraft Meteorological Data Relay (AMDAR) and Aircraft Communication Addressing and Reporting System (ACARS)] has recently been extended in ECMWF's operational 4DVAR data assimilation system. Herein, a modified data selection procedure is reported on that allows the use of more aircraft profiling data during the aircraft's ascending and descending phase, and more of the most frequent reports at cruise level. It is shown that the accuracy of analyzed jet streams is improved through these changes, as verified against independent (non–real time) aircraft data that had not been used in the experiments. The modifications are shown to have a clear positive impact on the short- and medium-range forecast performance. The revised aircraft usage was implemented operationally in January 2002. The impact in 4DVAR of profiles from American and European automated aircraft in ascending and descending phase has been tested in a data denial impact study, for January and July 2001. This particular impact study was run partly on the request of the WMO/Commission for Basic Systems (CBS) Expert Team on data requirements and the redesign of the global observing system. Their interest is in testing whether a modern data assimilation system (such as 4DVAR) obtains substantial benefit from the aircraft profiles, which sample very irregularly in space and time, given that America and Europe are relatively well covered by radiosondes and wind profilers. The results show a substantial positive impact of the profiling aircraft data on analysis and forecast accuracy. The short-range forecast performance is improved over North America, the North Atlantic, and Europe. In the medium range a clear positive impact is found in the North Atlantic, the European, and Arctic areas in the winter period, and beyond day 6 in the summer period. These results are statistically significant and support the ongoing WMO initiative for further expansion of the AMDAR/ACARS coverage. The results also illustrate the effectiveness of 4DVAR with respect to observations that are irregularly distributed in space and time.

scholarly journals Operational Assimilation of glider temperature and salinity in a mesoscale flow field: Eastern Mediterranean test case

2016 ◽  
Author(s):  
Daniel R. Hayes ◽  
Srdjan Dobricic ◽  
Hezi Gildor
Keyword(s):  
Eastern Mediterranean ◽  
Background Field ◽  
Test Case ◽  
Surface Currents ◽  
Predictive Capacity ◽  
In Situ Data ◽  
Operational Data ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. An operational data assimilation system for the Eastern Mediterranean is described and evaluated for a 6-month twin experiment. In the assimilative run, glider profiles of temperature and salinity are assimilated daily into a high resolution ocean forecast, after an initial spin up of one week. In the control run, the same initial and boundary conditions are used to produce an operational forecast, but without assimilation of in situ data. While both runs were similar for most of the time and most of the domain, significant differences were found near the region of assimilation, particularly when the glider passed through the anticyclonic Cyprus eddy. Root mean square differences of the misfits between the temperature and salinity observations and the model background field at those locations (before any assimilation) were approximately 15% lower in the assimilative run. Improvements in the forecasting capability of surface currents were found, and would provide a significant improvement of predictive capacity for applications such as pollutant spreading or offshore operational safety.

scholarly journals How essential are Argo observations to constrain a global ocean data assimilation system?

Ocean Science ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 257-274 ◽  
Author(s):  
V. Turpin ◽  
E. Remy ◽  
P. Y. Le Traon
Keyword(s):  
Data Assimilation ◽  
Surface Temperature ◽  
Sea Surface ◽  
Global Ocean ◽  
Argo Data ◽  
In Situ Observations ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. Observing system experiments (OSEs) are carried out over a 1-year period to quantify the impact of Argo observations on the Mercator Ocean 0.25° global ocean analysis and forecasting system. The reference simulation assimilates sea surface temperature (SST), SSALTO/DUACS (Segment Sol multi-missions dALTimetrie, d'orbitographie et de localisation précise/Data unification and Altimeter combination system) altimeter data and Argo and other in situ observations from the Coriolis data center. Two other simulations are carried out where all Argo and half of the Argo data are withheld. Assimilating Argo observations has a significant impact on analyzed and forecast temperature and salinity fields at different depths. Without Argo data assimilation, large errors occur in analyzed fields as estimated from the differences when compared with in situ observations. For example, in the 0–300 m layer RMS (root mean square) differences between analyzed fields and observations reach 0.25 psu and 1.25 °C in the western boundary currents and 0.1 psu and 0.75 °C in the open ocean. The impact of the Argo data in reducing observation–model forecast differences is also significant from the surface down to a depth of 2000 m. Differences between in situ observations and forecast fields are thus reduced by 20 % in the upper layers and by up to 40 % at a depth of 2000 m when Argo data are assimilated. At depth, the most impacted regions in the global ocean are the Mediterranean outflow, the Gulf Stream region and the Labrador Sea. A significant degradation can be observed when only half of the data are assimilated. Therefore, Argo observations matter to constrain the model solution, even for an eddy-permitting model configuration. The impact of the Argo floats' data assimilation on other model variables is briefly assessed: the improvement of the fit to Argo profiles do not lead globally to unphysical corrections on the sea surface temperature and sea surface height. The main conclusion is that the performance of the Mercator Ocean 0.25° global data assimilation system is heavily dependent on the availability of Argo data.

scholarly journals Global methane emission estimates for 2000–2012 from CarbonTracker Europe-CH<sub>4</sub> v1.0

2017 ◽  
Vol 10 (3) ◽  
pp. 1261-1289 ◽  
Author(s):  
Aki Tsuruta ◽  
Tuula Aalto ◽  
Leif Backman ◽  
Janne Hakkarainen ◽  
Ingrid T. van der Laan-Luijkx ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
The United States ◽  
Total Carbon ◽  
Ch4 Emissions ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. We present a global distribution of surface methane (CH4) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516 ± 51 Tg CH4 yr−1, with an increase of 18 Tg CH4 yr−1 from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( <  2 Tg CH4 yr−1 difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33 Tg CH4 yr−1), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16–20 Tg CH4 yr−1). However, this study could not conclusively separate a small trend in biospheric emissions (−5 to +6.9 Tg CH4 yr−1) from the much larger trend in anthropogenic emissions (15–27 Tg CH4 yr−1). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

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