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.

Observing System Simulation Experiments (OSSEs) to Evaluate the Potential Impact of an Optical Autocovariance Wind Lidar (OAWL) on Numerical Weather Prediction

2015 ◽  
Vol 32 (9) ◽  
pp. 1593-1613 ◽  
Author(s):  
Robert Atlas ◽  
Ross N. Hoffman ◽  
Zaizhong Ma ◽  
G. David Emmitt ◽  
Sidney A. Wood ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Sampling Error ◽  
System Simulation ◽  
Weather Prediction ◽  
Simulation Experiments ◽  
Wind Lidar ◽  
Potential Impact ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

AbstractThe potential impact of Doppler wind lidar (DWL) observations from a proposed optical autocovariance wind lidar (OAWL) instrument is quantified in observing system simulation experiments (OSSEs). The OAWL design would provide profiles of useful wind vectors along a ground track to the left of the International Space Station (ISS), which is in a 51.6° inclination low-Earth orbit (LEO). These observations are simulated realistically, accounting for cloud and aerosol distributions inferred from the OSSE nature runs (NRs), and measurement and sampling error sources. The impact of the simulated observations is determined in both global and regional OSSE frameworks. The global OSSE uses the ECMWF T511 NR and the NCEP operational Global Data Assimilation System at T382 resolution. The regional OSSE uses an embedded hurricane NR and the NCEP operational HWRF data assimilation system with outer and inner domains of 9- and 3-km resolution, respectively.The global OSSE results show improved analyses and forecasts of tropical winds and extratropical geopotential heights. The tropical wind RMSEs are significantly reduced in the analyses and in short-term forecasts. The tropical wind improvement decays as the forecasts lengthen. The regional OSSEs are limited but show some improvements in hurricane track and intensity forecasts.

Improved impacts in observing system simulation experiments of radio occultation observations as a result of model and data assimilation changes

2020 ◽  
Author(s):  
L. CUCURULL ◽  
S. P. F. CASEY
Keyword(s):  
Data Assimilation ◽  
Radio Occultation ◽  
Weather Forecasting ◽  
Positive Impact ◽  
System Simulation ◽  
Weather Prediction ◽  
Wind Fields ◽  
Simulation Experiments ◽  
The Impact ◽  
Forward Operator

AbstractAs global data assimilation systems continue to evolve, Observing System Simulation Experiments (OSSEs) need to be updated to accurately quantify the impact of proposed observing technologies in weather forecasting. Earlier OSSEs with radio occultation (RO) observations have been updated and the impact of the originally proposed Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, with a high-inclination and low-inclination component, has been investigated by using the operational data assimilation system at NOAA and a 1-dimensional bending angle RO forward operator. It is found that the impact of the low-inclination component of the originally planned COSMIC-2 mission (now officially named COSMIC-2) has significantly increased as compared to earlier studies, and significant positive impact is now found globally in terms of mass and wind fields. These are encouraging results as COSMIC-2 was successfully launched in June 2019 and data have been recently released to operational weather centers. Earlier findings remain valid indicating that globally distributed RO observations are more important to improve weather prediction globally than a denser sampling of the tropical latitudes. Overall, the benefits reported here from assimilating RO soundings are much more significant than the impacts found in previous OSSEs. This is largely attributed to changes in the data assimilation and forecast system and less to the more advanced 1-dimensional forward operator chosen for the assimilation of RO observations.

scholarly journals Parameter Sensitivity of the WRF–LETKF System for Assimilation of Radar Observations: Imperfect-Model Observing System Simulation Experiments

2020 ◽  
Vol 35 (4) ◽  
pp. 1345-1362 ◽  
Author(s):  
Paula Maldonado ◽  
Juan Ruiz ◽  
Celeste Saulo
Keyword(s):  
Data Assimilation ◽  
Short Range ◽  
System Simulation ◽  
Weather Prediction ◽  
Doppler Velocity ◽  
Convective System ◽  
Model Errors ◽  
Spatiotemporal Resolution ◽  
Simulation Experiments ◽  
The Impact

AbstractSpecification of suitable initial conditions to accurately forecast high-impact weather events associated with intense thunderstorms still poses a significant challenge for convective-scale forecasting. Radar data assimilation has been showing encouraging results to produce an accurate estimate of the state of the atmosphere at the mesoscale, as it combines high-spatiotemporal-resolution observations with convection-permitting numerical weather prediction models. However, many open questions remain regarding the configuration of state-of-the-art data assimilation systems at the mesoscale and their potential impact upon short-range weather forecasts. In this work, several observing system simulation experiments of a mesoscale convective system were performed to assess the sensitivity of the local ensemble transform Kalman filter to both relaxation-to-prior spread (RTPS) inflation and horizontal localization of the error covariance matrix. Realistic large-scale forcing and model errors have been taken into account in the simulation of reflectivity and Doppler velocity observations. Overall, the most accurate analyses in terms of RMSE were produced with a relatively small horizontal localization cutoff radius (~3.6–7.3 km) and large RTPS inflation parameter (~0.9–0.95). Additionally, the impact of horizontal localization on short-range ensemble forecast was larger compared to inflation, almost doubling the lead times up to which the effect of using a more accurate state to initialize the forecast persisted.

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 Assimilation of Circumpolar Wind Vectors Derived from Highly Elliptical Orbit Imagery: Impact Assessment Based on Observing System Simulation Experiments

2013 ◽  
Vol 52 (8) ◽  
pp. 1891-1908 ◽  
Author(s):  
L. Garand ◽  
J. Feng ◽  
S. Heilliette ◽  
Y. Rochon ◽  
A. P. Trishchenko
Keyword(s):  
System Simulation ◽  
Weather Prediction ◽  
Elliptical Orbit ◽  
Added Value ◽  
The Arctic ◽  
Polar Regions ◽  
Simulation Experiments ◽  
The Real ◽  
Forecast Validation ◽  
The Impact

AbstractThere is a well-recognized spatiotemporal meteorological observation gap at latitudes higher than 55°, especially in the region 55°–70°. A possible solution to address this issue is a constellation of four satellites in a highly elliptical orbit (HEO), that is, two satellites for each polar region. An important satellite product to support weather prediction is atmospheric motion wind vectors (AMVs). This study uses observing system simulation experiments (OSSEs) to evaluate the benefit to forecasts resulting from the assimilation of HEO AMVs covering one or both polar regions. The OSSE employs the operational global data assimilation system of the Canadian Meteorological Center. HEO AMVs are assimilated north of 50°N and south of 50°S. From 2-month assimilation cycles, the study examines the following three issues: 1) the impact of AMV assimilation in the real system, and how this compares to the impact seen in the simulated system, 2) the added value of HEO AMVs in the Arctic on top of what is currently available, and 3) the relative impact of HEO AMVs in the Arctic and Antarctic in comparison with no AMVs. Although the simulated impact of currently available AMVs is somewhat higher than the real impact, a firm conclusion is that the added value of Arctic HEO AMVs is substantial, improving predictability at days 3–5 by a few hours in terms of 500-hPa geopotential height. The impact of HEO AMVs is relatively stronger in the Southern Hemisphere. Forecast validation of atmospheric profiles against the simulated “true” state and against analyses generated within the assimilation cycles yields very similar results beyond 48 h.

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