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Revealing Data Assimilation System Issues with the GMAO OSSE
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An OSSE Study for Snow Mission Development: Evaluation Over A Western Colorado Domain
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An OSSE for Measuring Winds from the Cubesat Infrared Atmospheric Sounder (CIRAS)
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GEO IR Sounder Case Study: Multi-Band Retrieval Simulation and Forecast OSSE Results
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OSSEs - Lessons Learned in the Troposphere
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Significance of Radiative Transfer Models in Satellite Instrumentation Development and OSSEs
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GMAO Capabilities for Simulated Observations and OSSEs
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Numerical Weather Prediction Impact of GEO and LEO IR Sounders in an OSSE Framework
Low Earth Orbit (LEO) hyperspectral radiances from instruments such as CrIS, AIRS, and IASI are essential to NWP (among many other applications!), providing high vertical resolution T and humidity information. The United States is considering launching a hyperspectral sounder into a Geostationary Orbit (GEO) in the 2030s, creating a global ring with international partners. The combination of sounders in LEO and GEO provide both global coverage and high temporal resolution regional observations with the capability to dwell on high impact weather events.
An Observing System Simulation Experiment (OSSE) to Assess the Impact of Doppler Wind Lidar (DWL) Measurements on the Numerical Simulation of a Tropical Cyclone
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Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.