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Observing System Simulation Experiments for Fun and Profit

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

Observational Networks↗

The Influence of Observation Errors on Analysis Error and Forecast Skill Investigated with an Observing System Simulation Experiment

The Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework is used to explore the response of analysis error and forecast skill to observation quality. In an OSSE, synthetic observations may be created that have much smaller error than real observations, and precisely quantified error may be applied to these synthetic observations. Three experiments are performed in which synthetic observations with magnitudes of applied observation error that vary from zero to twice the estimated realistic error are ingested into the Goddard Earth Observing System Model (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation for a one-month period representing July. The analysis increment and observation innovation are strongly impacted by observation error, with much larger variances for increased observation error. The analysis quality is degraded by increased observation error, but the change in root-mean-square error of the analysis state is small relative to the total analysis error. Surprisingly, in the 120 hour forecast increased observation error only yields a slight decline in forecast skill in the extratropics, and no discernable degradation of forecast skill in the tropics.

Observation Error↗

Observing System Simulation Experiments: An Overview

An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.

OSSE↗

Observing System Simulation Experiments: An Overview

An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.

OSSE↗

Observing System Simulation Experiments

A very brief overview of Observing System Simulation Experiments for numerical weather prediction, including the Nature Run, synthetic observations, and calibration/validation of the OSSE framework will be given.

Prive, Nikki↗

Recent Observing System Simulation Experiments at the NASA DAO

Since the advent of meteorological satellites in the 1960's, numerous experiments have been conducted in order t o evaluate the impact of these and other data on atmospheric analysis and prediction. Such studies have included both OSE'S (Observing System Experiments) and OSSE's (Observing System Simulation Experiments). The OSE's were conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. Such experiments have been performed for selected types of conventional data and for various satellite data sets as they became avail- able. (See for example the 1989 ECMWF/EUMETSAT workshop proceedings on "The use of satellite data in operational numerical weather prediction" and the references contained therein.) The OSSE's were con- ducted to evaluate the potential for future observing systems to improve Numerical Weather Prediction (NWP) and to plan for the Global Weather Experiment and more recently for EOS. In addition, OSSE's have been run t o evaluate trade-offs in the design of observing systems and observing net-works, and to test new methodology for data assimilation.

Atlas, Robert↗

Observing System Simulation Experiments and their Requirements

A brief overview of Observing System Simulation Experiments is given, including the methodology used at NASA/GMAO for generating simulated observations. Some technical and computing requirements for current and expected future generation and use of simulated observations are discussed.

Prive, Nikki↗

A simulation experiment of photochemical reactions in the mesosphere

An ionospheric simulation experiment has been performed in a large vacuum chamber. The chamber is filled with NO and other gases including N2, O2, CO2, NH3 and H2O in the pressure range of 0.01 torr. A lamp which produces photons at 1236- and 1165-A by means of microwave discharge in krypton is utilized as an ionization source. In addition to 30+ large quantities of the water cluster ions 55+, H3O(+).(H2O)2, 73+, H3O(+).(H2O)3 and 91+, H3O(+).(H2O)4 were observed when nitric oxide and water were present. This closely approximates the condition of the terrestrial D region. After long periods of UV irradiation 74+ and 104+ ions grow in intensity. These ions are tentatively identified as NO(+).N2O and NO(+).NO.N2O. In addition the series 18+, 36+, 54+, and 72+ is detected which can be labeled NH4(+), NH4(+).(H2O), NH4(+).(H2O)2 and NH4(+).(H2O)3. These same species of ions are observed with the introduction of ammonia into the chamber. Presumably both N2O and NH3 are products of the photolysis.

Fugono, N.↗

Observing System Simulation Experiments

This presentation gives an overview of Observing System Simulation Experiments (OSSEs). The components of an OSSE are described, along with discussion of the process for validating, calibrating, and performing experiments. a.

OSSE↗

Results of NASA/FAA ground and flight simulation experiments concerning helicopter IFR airworthiness criteria

A sequence of ground and flight simulation experiments was conducted to investigate helicopter instrument-flight-rules airworthiness criteria. The first six of these experiments and major results are summarized. Five of the experiments were conducted on large-amplitude motion base simulators. The NASA-Army V/STOLAND UH-1H variable-stability helicopter was used in the flight experiment. Artificial stability and control augmentation, longitudinal and lateral control, and in pitch and roll attitude augmentation were investigated.

Lebacqz, J. V.↗

Design of a WINDSAT observing system simulation experiment

The following topics are addressed: (1) motivation for the National Meteorological Center (NMC) simulation project; (2) history of the NMC simulation project; (3) experimental design of the WINDSAT observing system simulation experiment; (4) preparation of the simulated observations; and (5) strengths and weaknesses of the experimental design.

Dey, Clifford H.↗

Introduction to Observing System Simulation Experiments (OSSEs)

This presentation gives a brief overview of Observing System Simulation Experiments (OSSEs), including what OSSEs are, and how and why they are performed. The intent is to educate the audience in light of the OSSE-related sections of the Forecast Improvement Act (H.R. 2413).

GMAO↗

Results of an observing system simulation experiment based on the proposed Windsat instrument

Two fraternal twin experiments were conducted as part of this study. A data impact experiment using real data (runs 1 and 2) was conducted to assess the impact that rawin wind observations have on both a 5-day assimilation and a single 5-day forecast generated at the end of each assimilation. An observing system simulation experiment (OSSE) using simulated observations (runs 3, 4, and 5) was conducted in order to first calibrate the OSSE results and second to use this calibration to estimate the 'real world' impact from the contribution of global 3-dimensional wind profiles generated from a space-based lidar system known as Windsat. Each of the three runs in the seond experiment were also 5-day assimilation runs with a 5-day forecast initialized from the last 6-hour update cycle of the assimilation. The data impact study revealed a consistent positive impact when rawin winds were added back into an otherwise complete FGGE data set. Both the 6-hour and 5-day forecasts were improved at all levels, in both hemispheres, and for both the wind and the geopotential height fields. Similar results were obtained from the two parallel simulation runs, 3 and 4. Together with the results from runs 1 and 2, calibration coefficients were generated so as to 'correct' the results determined from the addition of Windsat winds (run 5). The Windsat simulation showed a positive improvement in all cases studied. Even though only the tropics were enhanced with these wind observations, hemispheric rms errors were decreased in both the assimilation and 5-day forecast. The 6-hour forecasts of zonal wind from the assimilation run were improved by as much as 50 pct. on the average, and the single forecast showed an average improvement of near 30 pct. Even though these calibrated values are considered too optimistic, the skill of the forecast generated from this run extended the useful forecast period by 18-24 hours.

Arnold, Charles P., Jr.↗

An observing system simulation experiment for the Laser Atmospheric Wind Sounder (LAWS)

The present observing system-simulation experiments evaluate the potential of a Laser Atmospheric Wind Sounder (LAWS) instrument for 5-day forecasting, using a primitive-equation multilevel spectral global circulation model. A 55-deg-inclined and a 98-deg sun-synchronous orbit are examined, by adding LAWS wind profiles into a global 4D data-assimilation system, and comparing both the analyses and forecasts to a control experiment. The 4D data-assimilation system consists of a multivariate optimum interpolation analysis and a nonlinear, normal-mode intialization, using the aforementioned global circulation model.

Rohaly, G. D.↗