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Optimization of Cloud-Radiation Databases for Passive Microwave Precipitation Retrievals over Ocean
Title
Optimization of Cloud-Radiation Databases for Passive Microwave Precipitation Retrievals over Ocean.
Creator
Seo, Eun-Kyoung, Yang, Sung-Dae, Grecu, Mircea, Ryu, Geun-Hyeok, Liu, Guosheng, Hristova-Veleva, Svetla, Noh, Yoo-Jeong, Haddad, Ziad, Shin, Jinho
Abstract/Description
Using Tropical Rainfall Measuring Mission (TRMM) observations from storms collected over the oceans surrounding East Asia, during summer, a method of creating physically consistent cloud-radiation databases to support satellite radiometer retrievals is introduced. In this method, vertical profiles of numerical model simulated cloud and precipitation fields are optimized against TRMM radar and radiometer observations using a hybrid empirical orthogonal function (EOF)-one-dimensional...
Show moreUsing Tropical Rainfall Measuring Mission (TRMM) observations from storms collected over the oceans surrounding East Asia, during summer, a method of creating physically consistent cloud-radiation databases to support satellite radiometer retrievals is introduced. In this method, vertical profiles of numerical model simulated cloud and precipitation fields are optimized against TRMM radar and radiometer observations using a hybrid empirical orthogonal function (EOF)-one-dimensional variational (1DVAR) approach.The optimization is based on comparing simulated to observed radar reflectivity profiles and the corresponding passive microwave observations at the frequencies of the TRMM Microwave Imager (TMI) instrument. To minimize the discrepancies between the actual and the synthetic observations, the simulated cloud and precipitation profiles are optimized by adjusting the contents of the hydrometeors. To reduce the dimension of the hydrometeor content profiles in the optimization, multivariate relations among hydrometeor species are used. After applying the optimization method to modify the simulated clouds, the optimized cloud-radiation database has a joint distribution of reflectivity and associated brightness temperatures that is considerably closer to that observed by TRMM PR and TMI, especially at 85 GHz. This implies that the EOF-1DVAR approach can generate profiles with realistic distributions of frozen hydrometeors, such as snow and graupel. This approach may be similarly adapted to operate with the variety and capabilities of the passive microwave radiometers that compose the Global Precipitation Measurement (GPM) constellation. Furthermore, it can be extended to other oceanic regions and seasons.
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Date Issued
2016-08
Identifier
FSU_libsubv1_wos_000382896700006, 10.1175/JTECH-D-15-0198.1
Format
Citation
Applying Automated Underway Ship Observations to Numerical Model Evaluation
Title
Applying Automated Underway Ship Observations to Numerical Model Evaluation.
Creator
Smith, Shawn R., Briggs, Kristen, Lopez, Nicolas, Kourafalou, Vassiliki
Abstract/Description
Numerical models are used widely in the oceanic and atmospheric sciences to estimate and forecast conditions in the marine environment. Herein the application of in situ observations collected by automated instrumentation on ships at sampling rates
Show moreNumerical models are used widely in the oceanic and atmospheric sciences to estimate and forecast conditions in the marine environment. Herein the application of in situ observations collected by automated instrumentation on ships at sampling rates <= 5 min is demonstrated as a means to evaluate numerical model analyses. Specific case studies use near-surface ocean observations collected by a merchant vessel, an ocean racing yacht, and select research vessels to evaluate various ocean analyses from the Hybrid Coordinate Ocean Model (HYCOM). Although some specific differences are identified between the observations and numerical model analyses, the purpose of these comparisons is to demonstrate the value of high-sampling-rate in situ observations collected on ships for numerical model evaluation.
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Date Issued
2016-03
Identifier
FSU_libsubv1_wos_000372785000001, 10.1175/JTECH-D-15-0052.1
Format
Citation
Analysis methods for characterizing salinity variability from multivariate time series applied to the Apalachicola Bay estuary
Title
Analysis methods for characterizing salinity variability from multivariate time series applied to the Apalachicola Bay estuary.
Creator
Morey, Steven, Dukhovskoy, Dmitry
Abstract/Description
Statistical analysis methods are developed to quantify the impacts of multiple forcing variables on the hydrographic variability within an estuary instrumented with an enduring observational system. The methods are applied to characterize the salinity variability within Apalachicola Bay, a shallow multiple-inlet estuary along the northeastern Gulf of Mexico coast. Thirteen-year multivariate time series collected by the National Estuary Research Reserve at three locations within the bay are...
Show moreStatistical analysis methods are developed to quantify the impacts of multiple forcing variables on the hydrographic variability within an estuary instrumented with an enduring observational system. The methods are applied to characterize the salinity variability within Apalachicola Bay, a shallow multiple-inlet estuary along the northeastern Gulf of Mexico coast. Thirteen-year multivariate time series collected by the National Estuary Research Reserve at three locations within the bay are analyzed to determine how the estuary responds to variations in external forcing mechanisms, such as freshwater discharge, precipitation, tides and local winds, at multiple time scales. The analysis methods are used to characterize the estuarine variability under differing flow regimes of the Apalachicola River, a managed waterway, with particular focus on extreme events and scales of variability that are critical to local ecosystems. Multivariate statistical models are applied that describe the salinity response to winds from multiple directions, river flow, and precipitation at daily, weekly, and monthly time scales to understand the response of the estuary under different climate regimes. Results show that the salinity is particularly sensitive to river discharge and wind magnitude and direction, with local precipitation being largely unimportant. Applying statistical analyses with conditional sampling quantifies how the likelihoods of high salinity and long duration high salinity events, conditions of critical importance to estuarine organisms, change given the state of the river flow. Intraday salinity range is shown to be negatively correlated with the salinity, and correlated with river discharge rate.
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Date Issued
2012
Identifier
FSU_migr_coaps_pubs-0047, 10.1175/JTECH-D-11-00136.1
Format
Citation