scholarly journals Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Description and Usage

2016 ◽  
Vol 33 (8) ◽  
pp. 1759-1777 ◽  
Author(s):  
Sid-Ahmed Boukabara ◽  
Isaac Moradi ◽  
Robert Atlas ◽  
Sean P. F. Casey ◽  
Lidia Cucurull ◽  
...  
Keyword(s):  
General Circulation ◽  
System Simulation ◽  
Weather Prediction ◽  
Circulation Model ◽  
Earth Observing System ◽  
Operational Systems ◽  
Cubed Sphere ◽  
New Sensors ◽  
Observing System Simulation Experiment ◽  
Observing Systems

AbstractA modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.

scholarly journals Operational ocean models in the Adriatic Sea: a skill assessment

Ocean Science ◽  
2008 ◽  
Vol 4 (1) ◽  
pp. 61-71 ◽  
Author(s):  
J. Chiggiato ◽  
P. Oddo
Keyword(s):  
General Circulation ◽  
Mean Squared Error ◽  
Three Dimensional ◽  
Circulation Model ◽  
Remote Sensing Data ◽  
Skill Assessment ◽  
Regional Models ◽  
Operational Systems ◽  
Forecasting System ◽  
The Mediterranean

Abstract. In the framework of the Mediterranean Forecasting System (MFS) project, the performance of regional numerical ocean forecasting systems is assessed by means of model-model and model-data comparison. Three different operational systems considered in this study are: the Adriatic REGional Model (AREG); the Adriatic Regional Ocean Modelling System (AdriaROMS) and the Mediterranean Forecasting System General Circulation Model (MFS-GCM). AREG and AdriaROMS are regional implementations (with some dedicated variations) of POM and ROMS, respectively, while MFS-GCM is an OPA based system. The assessment is done through standard scores. In situ and remote sensing data are used to evaluate the system performance. In particular, a set of CTD measurements collected in the whole western Adriatic during January 2006 and one year of satellite derived sea surface temperature measurements (SST) allow to asses a full three-dimensional picture of the operational forecasting systems quality during January 2006 and to draw some preliminary considerations on the temporal fluctuation of scores estimated on surface quantities between summer 2005 and summer 2006. The regional systems share a negative bias in simulated temperature and salinity. Nonetheless, they outperform the MFS-GCM in the shallowest locations. Results on amplitude and phase errors are improved in areas shallower than 50 m, while degraded in deeper locations, where major models deficiencies are related to vertical mixing overestimation. In a basin-wide overview, the two regional models show differences in the local displacement of errors. In addition, in locations where the regional models are mutually correlated, the aggregated mean squared error was found to be smaller, that is a useful outcome of having several operational systems in the same region.

scholarly journals Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Assessment and Validation of the OSSE System Using an OSSE–OSE Intercomparison of Summary Assessment Metrics

2018 ◽  
Vol 35 (10) ◽  
pp. 2061-2078 ◽  
Author(s):  
Sid-Ahmed Boukabara ◽  
Kayo Ide ◽  
Yan Zhou ◽  
Narges Shahroudi ◽  
Ross N. Hoffman ◽  
...  
Keyword(s):  
System Simulation ◽  
Weather Prediction ◽  
Real Data ◽  
New Techniques ◽  
Forecast Performance ◽  
Individual System ◽  
Assessment Metrics ◽  
The Individual ◽  
The Tropics ◽  
Observing System Simulation Experiment

AbstractObserving system simulation experiments (OSSEs) are used to simulate and assess the impacts of new observing systems planned for the future or the impacts of adopting new techniques for exploiting data or for forecasting. This study focuses on the impacts of satellite data on global numerical weather prediction (NWP) systems. Since OSSEs are based on simulations of nature and observations, reliable results require that the OSSE system be validated. This validation involves cycles of assessment and calibration of the individual system components, as well as the complete system, with the end goal of reproducing the behavior of real-data observing system experiments (OSEs). This study investigates the accuracy of the calibration of an OSSE system—here, the Community Global OSSE Package (CGOP) system—before any explicit tuning has been performed by performing an intercomparison of the OSSE summary assessment metrics (SAMs) with those obtained from parallel real-data OSEs. The main conclusion reached in this study is that, based on the SAMs, the CGOP is able to reproduce aspects of the analysis and forecast performance of parallel OSEs despite the simplifications employed in the OSSEs. This conclusion holds even when the SAMs are stratified by various subsets (the tropics only, temperature only, etc.).

Observing System Simulation Experiments to Assess the Potential Impact of New Observing Systems on Hurricane Forecasting

2015 ◽  
Vol 49 (6) ◽  
pp. 140-148 ◽  
Author(s):  
Robert Atlas ◽  
Lisa Bucci ◽  
Bachir Annane ◽  
Ross Hoffman ◽  
Shirley Murillo
Keyword(s):  
System Simulation ◽  
Weather Prediction ◽  
Simulation Experiments ◽  
Nasa Goddard Space ◽  
Trade Offs ◽  
Goddard Space Flight Center ◽  
Hurricane Track ◽  
Potential Impact ◽  
Hurricane Forecasting ◽  
Observing Systems

AbstractObserving System Simulation Experiments (OSSEs) are an important tool for evaluating the potential impact of new or proposed observing systems, as well as for evaluating trade-offs in observing system design, and in developing and assessing improved methodology for assimilating new observations. Extensive OSSEs have been conducted at the National Aeronautical and Space Administration (NASA) Goddard Space Flight Center (GSFC) and the National Oceanic and Atmospheric Administration (NOAA) Atlantic Oceanographic and Meteorological Laboratory (AOML) over the last three decades. These OSSEs determined correctly the quantitative potential for several proposed satellite observing systems to improve weather analysis and prediction prior to their launch; evaluated trade-offs in orbits, coverage, and accuracy for space-based wind lidars; and were used in the development of the methodology that led to the first beneficial impacts of satellite surface winds on numerical weather prediction. This paper summarizes early applications of global OSSEs to hurricane track forecasting and new experiments using both global and regional models. These latter experiments are aimed at assessing potential impact on hurricane track and intensity prediction over the oceans and at landfall.

Influence of gravity wave drag parametrisations on the stratospheric circulation of seasonal ICON-NWP experiments

2020 ◽  
Author(s):  
Raphael Köhler ◽  
Dörthe Handorf ◽  
Ralf Jaiser ◽  
Klaus Dethloff ◽  
Günther Zängl ◽  
...  
Keyword(s):  
Gravity Wave ◽  
General Circulation ◽  
Weather Prediction ◽  
Polar Vortex ◽  
Circulation Model ◽  
Seasonal Prediction ◽  
Wave Drag ◽  
Stratospheric Polar Vortex ◽  
Sensitivity Experiments ◽  
Hemisphere Winter

<p>The stratospheric polar vortex is highly variable in winter and thus, models often struggle to capture its variability and strength. Yet, the influence of the stratosphere on the tropospheric circulation becomes highly important in Northern Hemisphere winter and is one of the main potential sources for subseasonal to seasonal prediction skill in mid latitudes. Mid-latitude extreme weather patterns in winter are often preceded by sudden stratospheric warmings (SSWs), which are the strongest manifestation of the coupling between stratosphere and troposphere. Misrepresentation of the SSW-frequency and stratospheric biases in models can therefore also cause biases in the troposphere.</p><p>In this context this work comprises the analysis of four seasonal ensemble experiments with a high-resolution, nonhydrostatic global atmospheric general circulation model in numerical weather prediction mode (ICON-NWP). The main focus thereby lies on the variability and strength of the stratospheric polar vortex. We identified the gravity wave drag parametrisations as one important factor influencing stratospheric dynamics. As the control experiment with default gravity wave drag settings exhibits an overestimated amount of SSWs and a weak stratospheric polar vortex, three sensitivity experiments with adjusted drag parametrisations were generated. Hence, the parametrisations for the non-orographic gravity wave drag and the subgrid‐scale orographic (SSO) drag were chosen with the goal of strengthening the stratospheric polar vortex. Biases to ERA-Interim are reduced with both adjustments, especially in high latitudes. Whereas the positive effect of the reduced non-orographic gravity wave drag is strongest in the mid-stratosphere in winter, the adjusted SSO-scheme primarily affects the troposphere by reducing mean sea level pressure biases in all months. A fourth experiment using both adjustments exhibits improvements in the troposphere and stratosphere. Although the stratospheric polar vortex in winter is strengthened in all sensitivity experiments, it is still simulated too weak compared to ERA-Interim. Further mechanisms causing this weakness are also investigated in this study.</p>

scholarly journals Assessment of Radio Occultation Observations from the COSMIC-2 Mission with a Simplified Observing System Simulation Experiment Configuration

2017 ◽  
Vol 145 (9) ◽  
pp. 3581-3597 ◽  
Author(s):  
L. Cucurull ◽  
R. Li ◽  
T. R. Peevey
Keyword(s):  
Radio Occultation ◽  
Weather Forecasting ◽  
System Simulation ◽  
Weather Prediction ◽  
Forecast Model ◽  
Forecast Skill ◽  
Weather Forecasts ◽  
Global Coverage ◽  
Prediction Systems ◽  
Observing System Simulation Experiment

The mainstay of the global radio occultation (RO) system, the COSMIC constellation of six satellites launched in April 2006, is already past the end of its nominal lifetime and the number of soundings is rapidly declining because the constellation is degrading. For about the last decade, COSMIC profiles have been collected and their retrievals assimilated in numerical weather prediction systems to improve operational weather forecasts. The success of RO in increasing forecast skill and COSMIC’s aging constellation have motivated planning for the COSMIC-2 mission, a 12-satellite constellation to be deployed in two launches. The first six satellites (COSMIC-2A) are expected to be deployed in December 2017 in a low-inclination orbit for dense equatorial coverage, while the second six (COSMIC-2B) are expected to be launched later in a high-inclination orbit for global coverage. To evaluate the potential benefits from COSMIC-2, an earlier version of the NCEP’s operational forecast model and data assimilation system is used to conduct a series of observing system simulation experiments with simulated soundings from the COSMIC-2 mission. In agreement with earlier studies using real RO observations, the benefits from assimilating COSMIC-2 observations are found to be most significant in the Southern Hemisphere. No or very little gain in forecast skill is found by adding COSMIC-2A to COSMIC-2B, making the launch of COSMIC-2B more important for terrestrial global weather forecasting than that of COSMIC-2A. Furthermore, results suggest that further improvement in forecast skill might better be obtained with the addition of more RO observations with global coverage and other types of observations.

scholarly journals Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2

2014 ◽  
Vol 7 (6) ◽  
pp. 7575-7617 ◽  
Author(s):  
A. Molod ◽  
L. Takacs ◽  
M. Suarez ◽  
J. Bacmeister
Keyword(s):  
General Circulation Model ◽  
General Circulation ◽  
Atmospheric General Circulation Model ◽  
Weather Prediction ◽  
Circulation Model ◽  
Wave Drag ◽  
Atmospheric General Circulation ◽  
Wide Range ◽  
Simulated Climate ◽  
The Impact

Abstract. The Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) version of the GEOS-5 Atmospheric General Circulation Model (AGCM) is currently in use in the NASA Global Modeling and Assimilation Office (GMAO) at a wide range of resolutions for a variety of applications. Details of the changes in parameterizations subsequent to the version in the original MERRA reanalysis are presented here. Results of a series of atmosphere-only sensitivity studies are shown to demonstrate changes in simulated climate associated with specific changes in physical parameterizations, and the impact of the newly implemented resolution-aware behavior on simulations at different resolutions is demonstrated. The GEOS-5 AGCM presented here is the model used as part of the GMAO's MERRA2 reanalysis, the global mesoscale "nature run", the real-time numerical weather prediction system, and for atmosphere-only, coupled ocean–atmosphere and coupled atmosphere–chemistry simulations. The seasonal mean climate of the MERRA2 version of the GEOS-5 AGCM represents a substantial improvement over the simulated climate of the MERRA version at all resolutions and for all applications. Fundamental improvements in simulated climate are associated with the increased re-evaporation of frozen precipitation and cloud condensate, resulting in a wetter atmosphere. Improvements in simulated climate are also shown to be attributable to changes in the background gravity wave drag, and to upgrades in the relationship between the ocean surface stress and the ocean roughness. The series of "resolution aware" parameters related to the moist physics were shown to result in improvements at higher resolutions, and result in AGCM simulations that exhibit seamless behavior across different resolutions and applications.

scholarly journals Operational ocean models in the Adriatic Sea: a skill assessment

2006 ◽  
Vol 3 (6) ◽  
pp. 2087-2116
Author(s):  
J. Chiggiato ◽  
P. Oddo
Keyword(s):  
General Circulation ◽  
Three Dimensional ◽  
Circulation Model ◽  
Scale Model ◽  
Regional Models ◽  
Near Surface ◽  
Operational Systems ◽  
Forecasting System ◽  
The Mediterranean ◽  
Dimensional Picture

Abstract. In the framework of the Mediterranean Forecasting System project (MFS) sub-regional and regional numerical ocean forecasting systems performance are assessed by mean of model-model and model-data comparison. Three different operational systems have been considered in this study: the Adriatic REGional Model (AREG); the AdriaROMS and the Mediterranean Forecasting System general circulation model (MFS model). AREG and AdriaROMS are regional implementations (with some dedicated variations) of POM (Blumberg and Mellor, 1987) and ROMS (Shchepetkin and McWilliams, 2005) respectively, while MFS model is based on OPA (Madec et al., 1998) code. The assessment has been done by means of standard scores. The data used for operational systems assessment derive from in-situ and remote sensing measurements. In particular a set of CTDs covering the whole western Adriatic, collected in January 2006, one year of SST from space born sensors and six months of buoy data. This allowed to have a full three-dimensional picture of the operational forecasting systems quality during January 2006 and some preliminary considerations on the temporal fluctuation of scores estimated on surface (or near surface) quantities between summer 2005 and summer 2006. In general, the regional models are found to be colder and fresher than observations. They eventually outperform the large scale model in the shallowest locations, as expected. Results on amplitude and phase errors are also much better in locations shallower than 50 m, while degraded in deeper locations, where the models tend to have a higher homogeneity along the vertical column compared to observations. In a basin-wide overview, the two regional models show some dissimilarities in the local displacement of errors, something suggested by the full three-dimensional picture depicted using CTDs, but also confirmed by the comparison with SSTs. In locations where the regional models are mutually correlated, the aggregated mean-square-error has been found to be lower, which is a useful outcome of having several operational systems in the same region.

scholarly journals The Impact of Increased Frequency of Rawinsonde Observations on Forecast Skill Investigated with an Observing System Simulation Experiment

2014 ◽  
Vol 142 (5) ◽  
pp. 1823-1834 ◽  
Author(s):  
N. C. Privé ◽  
R. M. Errico ◽  
K.-S. Tai
Keyword(s):  
Northern Hemisphere ◽  
Simulation Experiment ◽  
System Simulation ◽  
Forecast Skill ◽  
Cycle Times ◽  
Earth Observing System ◽  
Observing System Simulation Experiment ◽  
The Impact ◽  
Mean Square Errors ◽  
Analysis Quality

Abstract Most rawinsondes are launched once or twice daily, at 0000 and/or 1200 UTC; only a small number of the total rawinsonde observations are taken at 0600 and 1800 UTC (“off hour” cycle times). In this study, the variations of forecast and analysis quality between cycle times and the potential improvement of skill due to supplemental rawinsonde measurements at 0600 and 1800 UTC are tested in the framework of an observing system simulation experiment (OSSE). The National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA GMAO) Goddard Earth Observing System Model, version 5 (GEOS-5), is used with the GMAO OSSE setup for an experiment emulating the months of July and August with the 2011 observational network. The OSSE is run with and without supplemental rawinsonde observations at 0600 and 1800 UTC, and the differences in analysis error and forecast skill are quantified. The addition of supplemental rawinsonde observations results in significant improvement of analysis quality in the Northern Hemisphere for both the 0000/1200 and 0600/1800 UTC cycle times, with greater improvement for the off-hour times. Reduction of root-mean-square errors on the order of 1%–3% for wind and temperature is found at the 24- and 48-h forecast times. There is a slight improvement in Northern Hemisphere anomaly correlations at the 120-h forecast time.

scholarly journals A Study of Coupling Parameter Estimation Implemented by 4D-Var and EnKF with a Simple Coupled System

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Guijun Han ◽  
Xinrong Wu ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Ionel Michael Navon ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
General Circulation ◽  
Coupling Parameter ◽  
Coupled Model ◽  
Circulation Model ◽  
Coupled System ◽  
Model Studies ◽  
Error Covariance ◽  
Estimated Parameters ◽  
Observing System Simulation Experiment

Coupling parameter estimation (CPE) that uses observations to estimate the parameters in a coupled model through error covariance between variables residing in different media may increase the consistency of estimated parameters in an air-sea coupled system. However, it is very challenging to accurately evaluate the error covariance between such variables due to the different characteristic time scales at which flows vary in different media. With a simple Lorenz-atmosphere and slab ocean coupled system that characterizes the interaction of two-timescale media in a coupled “climate” system, this study explores feasibility of the CPE with four-dimensional variational analysis and ensemble Kalman filter within a perfect observing system simulation experiment framework. It is found that both algorithms can improve the representation of air-sea coupling processes through CPE compared to state estimation only. These simple model studies provide some insights when parameter estimation is implemented with a coupled general circulation model for improving climate estimation and prediction initialization.

Systematic Metastable Atmospheric Regime Identification in an AGCM

2009 ◽  
Vol 66 (7) ◽  
pp. 1997-2012 ◽  
Author(s):  
Christian Franzke ◽  
Illia Horenko ◽  
Andrew J. Majda ◽  
Rupert Klein
Keyword(s):  
General Circulation ◽  
Prediction Models ◽  
Transition Probability ◽  
Weather Prediction ◽  
Circulation Model ◽  
Two Dimensions ◽  
High Dimensional ◽  
Clustering Method ◽  
Barotropic Model ◽  
High Dimensional Datasets

Abstract In this study the authors apply a recently developed clustering method for the systematic identification of metastable atmospheric regimes in high-dimensional datasets generated by atmospheric models. The novelty of this approach is that it decomposes the phase space in, possibly, overlapping clusters and simultaneously estimates the most likely switching sequence among the clusters. The parameters of the clustering and switching are estimated by a finite element approach. The switching among the clusters can be described by a Markov transition matrix. Possible metastable regime behavior is assessed by inspecting the eigenspectrum of the associated transition probability matrix. The recently introduced metastable data-analysis method is applied to high-dimensional datasets produced by a barotropic model and a comprehensive atmospheric general circulation model (GCM). Significant and dynamically relevant metastable regimes are successfully identified in both models. The metastable regimes in the barotropic model correspond to blocked and zonal states. Similar regime states were already previously identified in highly reduced phase spaces of just one and two dimensions in the same model. Next, the clustering method is applied to a comprehensive atmospheric GCM in which seven significant flow regimes are identified. The spatial structures of the regimes correspond to, among others, both phases of the Northern Annular Mode and Pacific blocking. The regimes are maintained predominantly by transient eddy fluxes of low-pass-filtered anomalies. It is demonstrated how the dynamical description of the slow process switching between the regimes can be acquired from the analysis results, and an investigation of the resulting simplified dynamical model with respect to predictability is performed. A predictability study shows that a simple Markov model is able to predict the regimes up to six days ahead, comparable to the ability of high-resolution state-of-the-art numerical weather prediction models to accurately predict the onset and decay of blockings. The implications of the results for derivation of reduced models for extended-range predictability are discussed.

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