TY - JOUR TI - Land Surface Air Temperature Data Are Considerably Different Among BEST‐LAND, CRU‐TEM4v, NASA‐GISS, and NOAA‐NCEI AU - Rao, Yuhan AU - Liang, Shunlin AU - Yu, Yunyue T2 - Journal of Geophysical Research: Atmospheres AB - Abstract Several groups routinely produce gridded land surface air temperature (LSAT) data sets using station measurements to assess the status and impact of climate change. The Intergovernmental Panel on Climate Change Fifth Assessment Report suggests that estimated global and hemispheric mean LSAT trends of different data sets are consistent. However, less attention has been paid to the intercomparison at local/regional scales, which is important for local/regional studies. In this study we comprehensively compare four data sets at different spatial and temporal scales, including Berkley Earth Surface Temperature land surface air temperature data set (BEST‐LAND), Climate Research Unit Temperature Data Set version 4 (CRU‐TEM4v), National Aeronautics and Space Administration Goddard Institute for Space Studies data (NASA‐GISS), and data provided by National Oceanic and Atmospheric Administration National Center for Environmental Information (NOAA‐NCEI). The mean LSAT anomalies are remarkably different because of the data coverage differences, with the magnitude nearly 0.4°C for the global and Northern Hemisphere and 0.6°C for the Southern Hemisphere. This study additionally finds that on the regional scale, northern high latitudes, southern middle‐to‐high latitudes, and the equator show the largest differences nearly 0.8°C. These differences cause notable differences for the trend calculation at regional scales. At the local scale, four data sets show significant variations over South America, Africa, Maritime Continent, central Australia, and Antarctica, which leads to remarkable differences in the local trend analysis. For some areas, different data sets produce conflicting results of whether warming exists. Our analysis shows that the differences across scales are associated with the availability of stations and the use of infilling techniques. Our results suggest that conventional LSAT data sets using only station observations have large uncertainties across scales, especially over station‐sparse areas. In developing future LSAT data sets, the data uncertainty caused by limited and unevenly distributed station observations must be reduced. DA - 2018/6/16/ PY - 2018/6/16/ DO - 10.1029/2018JD028355 VL - 123 IS - 11 SP - 5881-5900 UR - https://doi.org/10.1029/2018JD028355 KW - land surface air temperature KW - intercomparison KW - surface warming KW - warming hiatus ER - TY - JOUR TI - A practical sampling method for assessing accuracy of detected land cover/land use change: Theoretical analysis and simulation experiments AU - Li, Yang AU - Chen, Jin AU - Rao, Yuhan T2 - ISPRS Journal of Photogrammetry and Remote Sensing AB - Accuracy assessment plays a crucial role in the implementation of change detection, which is commonly used to track land surface changes and ecosystem dynamics. There are currently two major indicators for accuracy assessment of change detection: the binary change accuracy (ca) and the overall transition accuracy (ta). The overall transition accuracy has been recommended over change accuracy, because the binary change accuracy does not consider the accuracy of the types of changes of the underlying land cover classes. However, the application of overall transition accuracy has been limited by the challenge of collecting enough representative samples with a practical sampling strategy to meet the users’ requirement of precision. This study provides an iterative sampling framework to ensure that the precision of the estimated overall transition accuracy meets the users’ predefined requirement. We use a set of simulated change maps to comprehensively examine the effectiveness and robustness of the proposed sampling strategy. The simulation-based results demonstrate that the proposed framework can achieve satisfactory performance for transition accuracy assessment and it is robust against different properties of classification results and target landscapes, including the degree of fragmentation, proportions of land cover types, and temporal correlation of the classification error between individual dates. The effectiveness, robustness and practicality of the proposed sampling strategy will enable producers and users of land cover/land use change maps to get reliable and meaningful accuracy assessment for further applications. DA - 2018/10// PY - 2018/10// DO - 10.1016/j.isprsjprs.2018.08.006 VL - 144 SP - 379-389 UR - https://doi.org/10.1016/j.isprsjprs.2018.08.006 KW - Land use land cover change KW - Accuracy assessment KW - Transition accuracy KW - Sample design ER - TY - CONF TI - ESIP Information Quality Cluster - Fostering collaborations in managing Earth Science Data Quality AU - Peng, G. AU - Ramapriyan, H.K. AU - Moroni, D. C2 - 2018/1/15/ C3 - Research Data Alliance (RDA) Europe, DA - 2018/1/15/ ER - TY - JOUR TI - The State of Assessing Data Stewardship Maturity – An Overview AU - Peng, Ge T2 - Data Science Journal AB -

Data stewardship encompasses all activities that preserve and improve the information content, accessibility, and usability of data and metadata. Recent regulations, mandates, policies, and guidelines set forth by the U.S. government, federal other, and funding agencies, scientific societies and scholarly publishers, have levied stewardship requirements on digital scientific data. This elevated level of requirements has increased the need for a formal approach to stewardship activities that supports compliance verification and reporting. Meeting or verifying compliance with stewardship requirements requires assessing the current state, identifying gaps, and, if necessary, defining a roadmap for improvement. This, however, touches on standards and best practices in multiple knowledge domains. Therefore, data stewardship practitioners, especially these at data repositories or data service centers or associated with data stewardship programs, can benefit from knowledge of existing maturity assessment models. This article provides an overview of the current state of assessing stewardship maturity for federally funded digital scientific data. A brief description of existing maturity assessment models and related application(s) is provided. This helps stewardship practitioners to readily obtain basic information about these models. It allows them to evaluate each model’s suitability for their unique verification and improvement needs. DA - 2018/3/26/ PY - 2018/3/26/ DO - 10.5334/dsj-2018-007 VL - 17 UR - https://doi.org/10.5334/dsj-2018-007 ER - TY - JOUR TI - A Conceptual Enterprise Framework for Managing Scientific Data Stewardship AU - Peng, Ge AU - Privette, Jeffrey L. AU - Tilmes, Curt AU - Bristol, Sky AU - Maycock, Tom AU - Bates, John J. AU - Hausman, Scott AU - Brown, Otis AU - Kearns, Edward J. T2 - Data Science Journal AB - Scientific data stewardship is an important part of long-term preservation and the use/reuse of digital research data. It is critical for ensuring trustworthiness of data, products, and services, which is important for decision-making. Recent U.S. federal government directives and scientific organization guidelines have levied specific requirements, increasing the need for a more formal approach to ensuring that stewardship activities support compliance verification and reporting. However, many science data centers lack an integrated, systematic, and holistic framework to support such efforts. The current business- and process-oriented stewardship frameworks are too costly and lengthy for most data centers to implement. They often do not explicitly address the federal stewardship requirements and/or the uniqueness of geospatial data. This work proposes a data-centric conceptual enterprise framework for managing stewardship activities, based on the philosophy behind the Plan-Do-Check-Act (PDCA) cycle, a proven industrial concept. This framework, which includes the application of maturity assessment models, allows for quantitative evaluation of how organizations manage their stewardship activities and supports informed decision-making for continual improvement towards full compliance with federal, agency, and user requirements. DA - 2018/6/28/ PY - 2018/6/28/ DO - 10.5334/dsj-2018-015 UR - https://doi.org/10.5334/dsj-2018-015 ER - TY - JOUR TI - Temporal Means and Variability of Arctic Sea Ice Melt and Freeze Season Climate Indicators Using a Satellite Climate Data Record AU - Peng, Ge AU - Steele, Michael AU - Bliss, Angela AU - Meier, Walter AU - Dickinson, Suzanne T2 - Remote Sensing AB - Information on the timing of Arctic snow and ice melt onset, sea ice opening, retreat, advance, and closing, can be beneficial to a variety of stakeholders. Sea ice modelers can use information on the evolution of the ice cover through the rest of the summer to improve their seasonal sea ice forecasts. The length of the open water season (as derived from retreat/advance dates) is important for human activities and for wildlife. Long-term averages and variability of these dates as climate indicators are beneficial to business strategic planning and climate monitoring. In this study, basic characteristics of temporal means and variability of Arctic sea ice climate indicators derived from a satellite-based climate data record from March 1979 to February 2017 melt and freeze seasons are described. Our results show that, over the Arctic region, anomalies of snow and ice melt onset, ice opening and retreat dates are getting earlier in the year at a rate of more than 5 days per decade, while that of ice advance and closing dates are getting later at a rate of more than 5 days per decade. These significant trends resulted in significant upward trends for anomalies of inner and outer ice-free periods at a rate of nearly 12 days per decade. Small but significant downward trends of seasonal ice loss and gain period anomalies were also observed at a rate of −1.48 and −0.53 days per decade, respectively. Our analyses also demonstrated that the means of these indicators and their trends are sensitive to valid data masks and regional averaging methods. DA - 2018/8// PY - 2018/8// DO - 10.3390/rs10091328 VL - 10 IS - 9 SP - 1328 UR - http://www.mdpi.com/2072-4292/10/9/1328 KW - Arctic sea ice KW - climate data record KW - climate indicator KW - decadal trend KW - melt onset KW - sea ice retreat KW - sea ice freeze-up KW - variability ER - TY - JOUR TI - Practical Application of a Data Stewardship Maturity Matrix for the NOAA OneStop Project AU - Peng, Ge AU - Milan, Anna AU - Ritchey, Nancy A. AU - Partee, Robert P., II AU - Zinn, Sonny AU - McQuinn, Evan AU - Casey, Kenneth S. AU - Lemieux, Paul, III AU - Ionin, Raisa AU - Jones, Philip AU - Jakositz, Arianna AU - Collins, Donald AU - Zinn, Sonny AU - McQuinn, Evan AU - Casey, Kenneth S. AU - Lemieux, Paul, III AU - Ionin, Raisa AU - Jones, Philip AU - Jakositz, Arianna AU - Collins, Donald AB - Assessing the stewardship maturity of individual datasets is an essential part of ensuring and improving the way datasets are documented, preserved, and disseminated to users. It is a critical step towards meeting U.S. federal regulations, organizational requirements, and user needs. However, it is challenging to do so consistently and quantifiably. The Data Stewardship Maturity Matrix (DSMM), developed jointly by NOAA’s National Centers for Environmental Information (NCEI) and the Cooperative Institute for Climate and Satellites–North Carolina (CICS-NC), provides a uniform framework for consistently rating stewardship maturity of individual datasets in nine key components: preservability, accessibility, usability, production sustainability, data quality assurance, data quality control/monitoring, data quality assessment, transparency/traceability, and data integrity. So far, the DSMM has been applied to over 900 individual datasets that are archived and/or managed by NCEI, in support of the NOAA’s OneStop Data Discovery and Access Framework Project. As a part of the OneStop-ready process, tools, implementation guidance, workflows, and best practices are developed to assist the application of the DSMM and described in this paper. The DSMM ratings are also consistently captured in the ISO standard-based dataset-level quality metadata and citable quality descriptive information documents, which serve as interoperable quality information to both machine and human end-users. These DSMM implementation and integration workflows and best practices could be adopted by other data management and stewardship projects or adapted for applications of other maturity assessment models. DA - 2018/10/18/ PY - 2018/10/18/ DO - 10.31219/osf.io/fp3js VL - 10 UR - https://doi.org/10.31219/osf.io/fp3js ER - TY - JOUR TI - The AMSU-Based Hydrological Bundle Climate Data RecordDescription and Comparison with Other Data Sets AU - Ferraro, R. R. AU - Nelson, B. R. AU - Smith, T. AU - Prat, O. P. T2 - Remote Sensing AB - Passive microwave measurements have been available on satellites back to the 1970s, first flown on research satellites developed by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager—SSM/I; the Advanced Microwave Sounding Unit—AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer—AMSR; the Tropical Rainfall Measurement Mission Microwave Imager—TMI; the Global Precipitation Mission Microwave Imager—GMI). Here, the focus is on measurements from the AMSU-A, AMSU-B, and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998, with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19, and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a climate data record (CDR) that utilizes brightness temperatures from fundamental CDRs (FCDRs) to generate thematic CDRs (TCDRs). The TCDRs include total precipitable water (TPW), cloud liquid water (CLW), sea-ice concentration (SIC), land surface temperature (LST), land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDRs are shown to be in general good agreement with similar products from other sources, such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Due to the careful intercalibration of the FCDRs, little bias is found among the different TCDRs produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences. DA - 2018/// PY - 2018/// DO - 10.3390/rs10101640 VL - 10 IS - 10 SP - 18 UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000448555800140&KeyUID=WOS:000448555800140 KW - remote sensing KW - climate data record KW - passive microwave KW - hydrology ER - TY - JOUR TI - The Simulation of East Asian Summer Monsoon Precipitation With a Regional Ocean-Atmosphere Coupled Model AU - Dai, Yongjiu AU - Li, Haiqin AU - Sun, Liqiang T2 - JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES AB - Abstract A fully coupled regional ocean‐atmosphere model was used to simulate the East Asian summer monsoon (EASM) precipitation. This coupled regional climate modeling system consists of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System for the ocean. The ocean and atmosphere share the same horizontal grid resolution. The coupled model is forced by the National Centers for Environmental Prediction‐Department of Energy (R‐2) global atmospheric reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis through the lateral boundary. This study examines EASM surface oceanic state and precipitation variability from a 22‐year (1984–2005) integration with a horizontal resolution of 40 km. The coupled model captures the features of observed sea surface temperature (SST), sea surface height, and ocean surface currents. Compared with the control run of the uncoupled RSM forced with observed SSTs, the coupled model shows more realistic simulation of the EASM precipitation climatology. The coupled model also improves the simulation of precipitation variability at both interannual and intraseasonal scales. It is the coupled model, not the uncoupled RSM, represents the observed SST‐precipitation and SST‐evaporation relationships. This study indicates that the ocean‐atmosphere coupling is essential for model simulations of the EASM precipitation. DA - 2018/10/27/ PY - 2018/10/27/ DO - 10.1029/2018JD028541 VL - 123 IS - 20 SP - 11362-11376 SN - 2169-8996 ER - TY - JOUR TI - Wavefront steering of elastic shear vertical waves in solids via a composite-plate-based metasurface AU - Zhang, Jun AU - Su, Xiaoshi AU - Pennec, Yan AU - Jing, Yun AU - Liu, Xiaofeng AU - Hu, Ning T2 - JOURNAL OF APPLIED PHYSICS AB - We report a novel approach to control the wavefronts of shear vertical (SV) waves in solids using metasurfaces constituted by a stacked array of composite plates, which are composed of two connecting parts made of different materials. The metasurfaces are connected at two ends to the half-space solids where the elastic SV waves propagate. The incident SV waves in the left half-space solid induce flexural waves in the composite plates and subsequently are converted back to SV waves in the right half-space solid. The time delay of flexural waves in each composite plate of the metasurfaces is tuned through the varying length of the two connecting components. To quantitatively evaluate the time delay in each composite plate, a theoretical model for analyzing the phase of the transmitted SV waves is developed based on the Mindlin plate theory. To control the SV waves at will, each composite plate in the metasurface is delicately designed according to the proposed theoretical model. For illustrative purposes, two metasurfaces are designed and numerically validated. DA - 2018/10/28/ PY - 2018/10/28/ DO - 10.1063/1.5049515 VL - 124 IS - 16 SP - SN - 1089-7550 ER - TY - JOUR TI - Experimental investigations on the boiling heat transfer of horizontal flow in the near-critical region AU - Lei, Xianliang AU - Zhang, Weiqiang AU - Zhang, Jun AU - Dinh, Nam AU - Li, Huixiong T2 - INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER AB - The critical point is the end point of a phase equilibrium curve; liquid and its vapor can coexist under designated points. Close to the critical point, thermophysical properties present clear variations, especially in the region of 0.85Pcr∼Pcr. Latent heat and liquid density in this region decrease more quickly than in lower-pressure areas, resulting in unique boiling heat transfer behavior. This region is also called the near-critical region. However, only a few scholars have discussed the heat transfer phenomenon; thus, it is difficult to ascertain the near-critical region’s properties and characteristics from extant literature. In the present study, we conduct experimental investigations to explore the specificities of the heat transfer characteristics of carbon dioxide in horizontal flow within the near-critical region in a circular channel with a diameter of 4 mm. The operating pressure ranges from 6.26 MPa to 7.3 MPa with a mass flow rate between 200 and 400 kg/m2 s, heat flux between 5 and 140 kW/m2, and test section inlet temperature of −5 °C. Then, we examine the inner-wall temperature and heat transfer coefficient profiles at different pressures within the near-critical region. The results show that at high heat flux, departure from nucleate boiling (DNB) phenomenon presents with a sudden decrease in the heat transfer coefficient in the subcooled region. The higher the heat flux, the more seriously deteriorating the heat transfer is. Interestingly, the temperature reaches its peak in the post-DNB region rather than at the critical vapor quality point. With an increase in pressure, DNB occurs early with lower vapor quality, and the temperature peak decreases at the given heat flux and mass flux. On the contrary, DNB is delayed with an increase in mass flux. A series of boiling heat transfer correlations in a subcooled region, two-phase flow region, and superheated region are proposed in addition to a new predictive correlation for critical heat flux in the near-critical region at a given mass flux. DA - 2018/10// PY - 2018/10// DO - 10.1016/j.ijheatmasstransfer.2018.04.043 VL - 125 SP - 618-628 SN - 1879-2189 KW - Carbon dioxide KW - Critical region KW - DNB KW - Heat transfer correlation KW - Heat transfer coefficient KW - Critical heat flux ER - TY - JOUR TI - Testing ontogenetic patterns of sexual size dimorphism against expectations of the expensive tissue hypothesis, an intraspecific example using oyster toadfish (Opsanus tau) AU - Dornburg, Alex AU - Warren, Dan L. AU - Zapfe, Katerina L. AU - Morris, Richard AU - Iglesias, Teresa L. AU - Lamb, April AU - Hogue, Gabriela AU - Lukas, Laura AU - Wong, Richard T2 - ECOLOGY AND EVOLUTION AB - Abstract Trade‐offs associated with sexual size dimorphism ( SSD ) are well documented across the Tree of Life. However, studies of SSD often do not consider potential investment trade‐offs between metabolically expensive structures under sexual selection and other morphological modules. Based on the expectations of the expensive tissue hypothesis, investment in one metabolically expensive structure should come at the direct cost of investment in another. Here, we examine allometric trends in the ontogeny of oyster toadfish ( Opsanus tau ) to test whether investment in structures known to have been influenced by strong sexual selection conform to these expectations. Despite recovering clear changes in the ontogeny of a sexually selected trait between males and females, we find no evidence for predicted ontogenetic trade‐offs with metabolically expensive organs. Our results are part of a growing body of work demonstrating that increased investment in one structure does not necessarily drive a wholesale loss of mass in one or more organs. DA - 2018/4// PY - 2018/4// DO - 10.1002/ece3.3835 VL - 8 IS - 7 SP - 3609-3616 SN - 2045-7758 KW - evolutionary ecology KW - fishes KW - life history trade-offs KW - phenotypic evolution KW - reproductive physiology KW - swim bladder ER - TY - JOUR TI - Changes in extreme events and the potential impacts on human health AU - Bell, Jesse E. AU - Brown, Claudia Langford AU - Conlon, Kathryn AU - Herring, Stephanie AU - Kunkel, Kenneth E. AU - Lawrimore, Jay AU - Luber, George AU - Schreck, Carl AU - Smith, Adam AU - Uejio, Christopher T2 - JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION AB - Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future.Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. DA - 2018/// PY - 2018/// DO - 10.1080/10962247.2017.1401017 VL - 68 IS - 4 SP - 265-287 SN - 2162-2906 ER - TY - JOUR TI - Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation AU - Kim, Beomgeun AU - Seo, Dong-Jun AU - Noh, Seong Jin AU - Prat, Olivier P. AU - Nelson, Brian R. T2 - JOURNAL OF HYDROLOGY AB - A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance. DA - 2018/1// PY - 2018/1// DO - 10.1016/j.jhydrol.2016.10.052 VL - 556 SP - 1096-1109 SN - 1879-2707 UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000423641300085&KeyUID=WOS:000423641300085 KW - Multisensor quantitative precipitation estimation KW - Radar precipitation KW - Rain gauges KW - Conditional bias KW - Cokriging ER - TY - JOUR TI - INTRODUCTION TO EXPLAINING EXTREME EVENTS OF 2016 FROM A CLIMATE PERSPECTIVE AU - Herring, Stephanie C. AU - Christidis, Nikolaos AU - Hoell, Andrew AU - Kossssin, James P. AU - Schreck, Carl J., III AU - Stott, Peter A. T2 - BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY AB - © 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). DA - 2018/1// PY - 2018/1// DO - 10.1175/bams-d-17-0284.1 VL - 99 IS - 1 SP - S1-S6 SN - 1520-0477 ER - TY - JOUR TI - FUTURE CHALLENGES IN EVENT ATTRIBUTION METHODOLOGIES AU - Stott, Peter A. AU - Christidis, Nikos AU - Herring, Stephananie C. AU - Hoell, Andrew AU - Kossssin, James P. AU - Schreck, Carl J., III T2 - BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY DA - 2018/1// PY - 2018/1// DO - 10.1175/bams-d-17-0285.1 VL - 99 IS - 1 SP - S155-S157 SN - 1520-0477 ER - TY - JOUR TI - Sensitivity Analysis of Arctic Sea Ice Extent Trends and Statistical Projections Using Satellite Data AU - Peng, Ge AU - Matthews, Jessica L. AU - Yu, Jason T. T2 - REMOTE SENSING AB - An ice-free Arctic summer would have pronounced impacts on global climate, coastal habitats, national security, and the shipping industry. Rapid and accelerated Arctic sea ice loss has placed the reality of an ice-free Arctic summer even closer to the present day. Accurate projection of the first Arctic ice-free summer year is extremely important for business planning and climate change mitigation, but the projection can be affected by many factors. Using an inter-calibrated satellite sea ice product, this article examines the sensitivity of decadal trends of Arctic sea ice extent and statistical projections of the first occurrence of an ice-free Arctic summer. The projection based on the linear trend of the last 20 years of data places the first Arctic ice-free summer year at 2036, 12 years earlier compared to that of the trend over the last 30 years. The results from a sensitivity analysis of six commonly used curve-fitting models show that the projected timings of the first Arctic ice-free summer year tend to be earlier for exponential, Gompertz, quadratic, and linear with lag fittings, and later for linear and log fittings. Projections of the first Arctic ice-free summer year by all six statistical models appear to converge to the 2037 ± 6 timeframe, with a spread of 17 years, and the earliest first ice-free Arctic summer year at 2031. DA - 2018/2// PY - 2018/2// DO - 10.3390/rs10020230 VL - 10 IS - 2 SP - SN - 2072-4292 UR - http://www.mdpi.com/2072-4292/10/2/230 KW - Arctic KW - sea ice KW - sea ice trend KW - Arctic ice-free projection KW - sensitivity analysis ER -