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Ashouri H.,University of California at Irvine | Hsu K.-L.,University of California at Irvine | Sorooshian S.,University of California at Irvine | Braithwaite D.K.,University of California at Irvine | And 4 more authors.
Bulletin of the American Meteorological Society | Year: 2015

A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S-60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset against available observations and satellite products are reported. The verification study over Hurricane Katrina (2005) shows that PERSIANN-CDR has good agreement with the stage IV radar data, noting that PERSIANN-CDR has more complete spatial coverage than the radar data. In addition, the comparison of PERSIANN-CDR against gauge observations during the 1986 Sydney flood in Australia reaffirms the capability of PERSIANN-CDR to provide reasonably accurate rainfall estimates. Moreover, the probability density function (PDF) of PERSIANN-CDR over the contiguous United States exhibits good agreement with the PDFs of the Climate Prediction Center (CPC) gridded gauge data and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product. The results indicate high potential for using PERSIANN-CDR for long-term hydroclimate studies in regional and global scales. © 2015 American Meteorological Society.

Xu F.,National Oceanic and Atmospheric Administration | Ignatov A.,Global Science and Technology Inc.
Journal of Atmospheric and Oceanic Technology | Year: 2014

The quality of in situ sea surface temperatures (SSTs) is critical for calibration and validation of satellite SSTs. In situ SSTs come fromdifferent countries, agencies, and platforms.As a result, their quality is often suboptimal,nonuniform, and measurement-type specific. This paper describes a system developed at the National Oceanic and Atmospheric Administration (NOAA), the in situ SST Quality Monitor (iQuam; www.star.nesdis.noaa. gov/sod/sst/iquam/). It performs threemajor functions with the Global Telecommunication System(GTS) data: 1) quality controls (QC) in situ SSTs, using Bayesian reference and buddy checks similar to those adopted in the MetOffice, in addition to providing basic screenings, such as duplicate removal, plausibility, platformtrack, and SST spike checks; 2)monitors quality-controlled SSTs online, in near-real time; and 3) serves reformatted GTS SST data to NOAA and external userswith quality flags appended.Currently, iQuam'sweb page displays global monthlymaps ofmeasurement locations stratified by four in situ platformtypes (drifters, ships, and tropical and coastal moorings) as well as their corresponding ''in situ minus reference'' SST statistics. Time series of all corresponding SST and QC statistics are also trended. The web page user can also monitor individual in situ platforms. The current status of iQuam and ongoing improvements are discussed. © 2014 American Meteorological Society.

Stramski D.,University of California at San Diego | Reynolds R.A.,University of California at San Diego | Kaczmarek S.,Polish Academy of Sciences | Uitz J.,University of California at San Diego | And 4 more authors.
Applied Optics | Year: 2015

Spectrophotometric measurement of particulate matter retained on filters is the most common and practical method for routine determination of the spectral light absorption coefficient of aquatic particles, ap(λ), at high spectral resolution over a broad spectral range. The use of differing geometrical measurement configurations and large variations in the reported correction for pathlength amplification induced by the particle/filter matrix have hindered adoption of an established measurement protocol. We describe results of dedicated laboratory experiments with a diversity of particulate sample types to examine variation in the pathlength amplification factor for three filter measurement geometries; the filter in the transmittance configuration (T), the filter in the transmittance- reflectance configuration (T-R), and the filter placed inside an integrating sphere (IS). Relationships between optical density measured on suspensions (ODs) and filters (ODf) within the visible portion of the spectrum were evaluated for the formulation of pathlength amplification correction, with power functions providing the best functional representation of the relationship for all three geometries. Whereas the largest uncertainties occur in the T method, the IS method provided the least sample-to-sample variability and the smallest uncertainties in the relationship between ODs and ODf. For six different samples measured with 1 nm resolution within the light wavelength range from 400 to 700 nm, a median error of 7.1% is observed for predicted values of ODs using the IS method. The relationships established for the three filter-pad methods are applicable to historical and ongoing measurements; for future work, the use of the IS method is recommended whenever feasible. © 2015 Optical Society of America.

Percivall G.S.,Open Geospatial Consortium | Alameh N.S.,Open Geospatial Consortium | Caumont H.,Terradue | Moe K.L.,NASA | Evans J.D.,Global Science and Technology Inc.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2013

This paper describes how the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS) are individually and collaboratively strengthening worldwide ability for agencies to manage the disasters lifecycle. The Architecture Implementation Pilot (AIP) of GEO has, through an agile development process, deployed and tested advanced information systems for Earth Observations based on interoperability arrangements. In particular, AIP has focused on several disaster management scenarios resulting in an architecture that has improved the ready viability and usability of data for disasters. CEOS is constructing a reference architecture, intended to streamline access to satellite data and services for disaster management and risk assessment. The CEOS approach aims to support disaster management activities with satellite information in a holistic fashion, taking account of their overlaps and interdependencies. Jointly GEO and CEOS are now working to align the approaches for disaster management to describe enterprise components and improve understanding of contributed systems and their roles. The coordination has lead to refinements of the Disaster Management Scenario via further implementation in AIP-5. By collaborating via the CEOS working groups and the Global Earth Observing System of Systems (GEOSS) communities of practice, these efforts are intended to engage the international community focused on disaster management and risk assessment to fully utilize remote sensing resources for societal benefit. © 2013 IEEE.

Zheng G.,Global Science and Technology Inc. | Stramski D.,University of California San DiegoLa Jolla | Digiacomo P.M.,Center for Satellite Application and ResearchCollege Park
Journal of Geophysical Research C: Oceans | Year: 2015

We present a model, referred to as Generalized Stacked-Constraints Model (GSCM), for partitioning the total light absorption coefficient of natural water (with pure-water contribution subtracted), anw(λ), into phytoplankton, aph(λ), nonalgal particulate, ad(λ), and CDOM, ag(λ), components. The formulation of the model is based on the so-called stacked-constraints approach, which utilizes a number of inequality constraints that must be satisfied simultaneously by the model outputs of component absorption coefficients. A major advancement is that GSCM provides a capability to separate the ad(λ) and ag(λ) coefficients from each other using only weakly restrictive assumptions about the component absorption coefficients. In contrast to the common assumption of exponential spectral shape of ad(λ) and ag(λ) in previous models, in our model these two coefficients are parameterized in terms of several distinct spectral shapes. These shapes are determined from field data collected in the Chesapeake Bay with an ultimate goal to adequately account for the actual variability in spectral shapes of ad(λ) and ag(λ) in the study area. Another advancement of this model lies in its capability to account for potentially nonnegligible magnitude of ad(λ) in the near-infrared spectral region. Evaluation of model performance demonstrates good agreement with measurements in the Chesapeake Bay. For example, the median ratio of the model-derived to measured ad(λ), ag(λ), and aph(λ) at 443 nm is 0.913, 1.064, and 1.056, respectively. Whereas our model in its present form can be a powerful tool for regional studies in the Chesapeake Bay, the overall approach is readily adaptable to other regions or bio-optical water types. © 2015. American Geophysical Union. All Rights Reserved.

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