Development of an AQUA Based Near-Surface Parameter Retrieval

The production of a satellite based turbulent surface flux product relies critically upon the near-surface input parameters. Development of retrieval algorithms for the necessary near-surface variables of wind speed, specific humidity, air temperature, and sea surface temperature has proceeded relatively independent of each another until recently. The use of a neural network approach using Special Sensor Microwave/Imager (SSM/I) data in conjunction with a first guess sea surface temperature has led to successful retrieval of all parameters simultaneously. However, SSM/I frequencies lack inherent sensitivity to the sea surface temperature (SST). Recent studies have found improved air temperature and humidity retrievals can be obtained via inclusion of microwave sounding channels weighted in the lower troposphere. The inclusion of SSM/I-like frequencies as well as SST-sensitive microwave channels on AMSR-E along with AMSU-A sounding data onboard the AQUA platform provides an unique opportunity. That is the ability to provide near-simultaneous (in space and time) measurements allowing the retrieval of all the near-surface variables, including SST. This study shows results of a new algorithm designed to take advantage of the unique sampling ability of AQUA based sensors. Results from a neural network based methodology will be shown as compared to in-situ based observations of near-surface variables. Implications for creation of an AQUA based turbulent surface product are also discussed

How the Changing Passive Microwave Observing System Challenges the Development of Water Cycle Climate Data Records

No abstract availabl

Tropical Ocean Surface Energy Balance Variability: Linking Weather to Climate Scales

Radiative and turbulent surface exchanges of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing the spatiotemporal variability of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. These fluxes are integral components to tropical ocean-atmosphere variability; they can drive ocean mixed layer variations and modify the atmospheric boundary layer properties including moist static stability, thereby influencing larger-scale tropical dynamics. Non-parametric cluster-based classification of atmospheric and ocean surface properties has shown an ability to identify coherent weather regimes, each typically associated with similar properties and processes. Using satellite-based observational radiative and turbulent energy flux products, this study investigates the relationship between these weather states and surface energy processes within the context of tropical climate variability. Investigations of surface energy variations accompanying intraseasonal and interannual tropical variability often use composite-based analyses of the mean quantities of interest. Here, a similar compositing technique is employed, but the focus is on the distribution of the heat and moisture fluxes within their weather regimes. Are the observed changes in surface energy components dominated by changes in the frequency of the weather regimes or through changes in the associated fluxes within those regimes? It is this question that the presented work intends to address. The distribution of the surface heat and moisture fluxes is evaluated for both normal and non-normal states. By examining both phases of the climatic oscillations, the symmetry of energy and water cycle responses are considered

Reintegration Process of Previously Incarcerated African American Women Older Than 50 Years

Successful reintegration of ex-offenders is difficult for most, evidenced by high recidivism rates. Ex-offenders face a broad range of obstacles once released from prison, including personal, social, and employment barriers. This study was an examination of the issues that contributed to a successful or unsuccessful reintegration as reported by ex-offenders. Participants included 10 ex-offenders who participated in interviews regarding the conditions that they believed were necessary for successful community reintegration. The conceptual framework for this study came from the ecological perspective, also known as the person-in-environment theory. Data collection involved one-on-one interviews with the participants. Data analysis was conducted through a line-by-line analysis of the responses, which resulted in disclosure of themes and patterns about their life experience. The key findings from the study suggest that older African American women, once released from prison, need additional support to reintegrate into their communities. Key findings include a need for housing, employment, and community involvement. The social change implications of this study may provide for positive social change if professionals working in the criminal justice system with older individuals are made aware of the hardships this population faces, such as finding housing and employment. The information from this study could be instrumental in how reintegration specialists, social workers, and policy makers create reintegration plans and programs for women in addition to creating programs that are specifically geared toward meeting the needs of older women

Improving near-surface retrievals of surface humidity over the global open oceans from passive microwave observations

Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Earth and Space Science, 6(7), (2019): 1220-1233, doi:10.1029/2018EA000436.Ocean evaporative fluxes are a critical component of the Earth's energy and water cycle, but their estimation remains uncertain. Near‐surface humidity is a required input to bulk flux algorithms that relate mean surface values to the turbulent fluxes. Several satellite‐derived turbulent flux products have been developed over the last decade that utilize passive microwave imager observations to estimate the surface humidity. It is known, however, that these estimates tend to diverge from one another and from in situ observations. Analysis of current state‐of‐the‐art satellite estimates provided herein reveals that regional‐scale biases in these products remain significant. Investigations reveal a link between the spatial coherency of the observed biases to atmospheric dynamical controls of water vapor vertical stratification, cloud liquid water, and sea surface temperature. This information is used to develop a simple state‐dependent bias correction that results in more consistent ocean surface humidity estimates. A principal conclusion is that further improvements to ocean near‐surface humidity estimation using microwave radiometers requires incorporation of prior information on water vapor stratification and sea surface temperature.Data products used in this study are made publicly available via multiple repositories hosted by individual data product producers. JOFUROv2 and JOFUROv3 data are available online (https://j‐ofuro.scc.u‐tokai.ac.jp/en/). IFREMERv4 and NOCS surface data are available through the OceanHeatFlux project (https://www.ifremer.fr/oceanheatflux/Data). GSSTFv3 (doi:10.5067/MEASURES/GSSTF/DATA301) and MERRA‐2 data are obtained from the Goddard Earth Sciences Data and Information Services Center. HOAPSv3.2 data are available from Satellite Application Facility on Climate Monitoring (https://doi.org/10.5676/EUM_SAF_CM/HOAPS/V001). SEAFLUXv2 data are accessed through the National Centers for Environmental Information (http://doi.org/10.7289/V59K4885). Daily surface observations were provided by David Berry and Elizabeth Kent. This work is supported under the NASA Physical Oceanography Program Grant NNX14AK48A

Estimating Ocean Surface Meteorology from Passive Microwave Observations for the Development of Satellite-Derived Turbulent Fluxes

No abstract availabl

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth's energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into accoun

Riverine Bacterial Communities Reveal Environmental Disturbance Signatures within the Betaproteobacteria and Verrucomicrobia

Riverine bacterial communities play an essential role in the biogeochemical coupling of terrestrial and marine environments, transforming elements and organic matter in their journey from land to sea. However, precisely due to the fact that rivers receive significant terrestrial input, the distinction between resident freshwater taxa vs. land-derived microbes can often become ambiguous. Furthermore, ecosystem perturbations could introduce allochthonous microbial groups and reshape riverine bacterial communities. Using full- and partial-length 16S ribosomal RNA gene sequences, we analyzed the composition of bacterial communities in the Tar River of North Carolina from November 2010 to November 2011, during which a natural perturbation occurred: the inundation of the lower reaches of an otherwise drought-stricken river associated with Hurricane Irene, which passed over eastern North Carolina in late August 2011. This event provided the opportunity to examine the microbiological, hydrological, and geochemical impacts of a disturbance, defined here as the large freshwater influx into the Tar River, superimposed on seasonal changes or other ecosystem variability independent of the hurricane. Our findings demonstrate that downstream communities are more taxonomically diverse and temporally variable than their upstream counterparts. More importantly, pre- vs. post-disturbance taxonomic comparison of the freshwater-dominant Betaproteobacteria class and the phylum Verrucomicrobia reveal a disturbance signature of previously undetected taxa of diverse origins. We use known traits of closely-related taxa to interpret the ecological function of disturbance-associated bacteria, and hypothesize that carbon cycling was enhanced post-disturbance in the Tar River, likely due to the flux of organic carbon into the system associated with the large freshwater pulse. Our analyses demonstrate the importance of geochemical and hydrological alterations in structuring bacterial communities, and illustrate the response of temperate riverine bacteria on fine taxonomic scales to a disturbance

Assessing Air-Sea Interaction in the Evolving NASA GEOS Model

No abstract availabl

Critical research needs for successful food systems adaptation to climate change

There is a growing sense of the fragility of agricultural production in the Global North and South and of increasing risks to food security, as scientific observations confirm significant changes in the Gulf Stream, polar ice, atmospheric CO2, methane release, and other measures of climate change. This sense is heightened as each of us experiences extreme weather, such as the increasing frequency of droughts, floods, unseasonal temperatures, and erratic seasonality. The central research challenge before us is how global, national, regional, and local food systems may adapt to accelerating climate change stresses and uncertainties to ensure the availability, access, consumption, and stability of healthy food for and by all people. Missing aspects of research fall into two broad categories: the impacts of rapid climate change on the environmental systems supporting food production, and climate change’s impact on the predominantly human systems that influence food security. Of particular concern is how different policy and governance mechanisms can support or hinder the collective decision-making needed to promote a swift adaptive response to increase and sustain food security. Human systems research is needed to investigate food system activities beyond production (processing, distribution, consumption, and waste management). It also must consider political, cultural, and regulatory factors that influence behavior and facilitate positive behavioral changes. To accurately envision future scenarios, research is needed to characterize risk comprehensively throughout the food system, assess barriers to and opportunities for changing food systems, and evaluate novel and traditional approaches that may lead to greater food security