uri,href,identifier,attrs.Abstract,attrs.Author,attrs.DOI,attrs.ISSN,attrs.Issue,attrs.Journal,attrs.Keywords,attrs.Pages,attrs.Title,attrs.URL,attrs.Volume,attrs.Year,attrs.\.reference_type,attrs.\.text_styles,attrs._chapter,attrs._record_number,attrs._uuid,attrs.reftype,child_publication
/reference/a7f8dbf5-3ec8-4ee1-8740-014006b72bfd,https://data.globalchange.gov/reference/a7f8dbf5-3ec8-4ee1-8740-014006b72bfd,a7f8dbf5-3ec8-4ee1-8740-014006b72bfd,"Statistical relationships between annual floods at 200 long-term (85–127 years of record) streamgauges in the coterminous United States and the global mean carbon dioxide concentration (GMCO2) record are explored. The streamgauge locations are limited to those with little or no regulation or urban development. The coterminous US is divided into four large regions and stationary bootstrapping is used to evaluate if the patterns of these statistical associations are significantly different from what would be expected under the null hypothesis that flood magnitudes are independent of GMCO2. In none of the four regions defined in this study is there strong statistical evidence for flood magnitudes increasing with increasing GMCO2. One region, the southwest, showed a statistically significant negative relationship between GMCO2 and flood magnitudes. The statistical methods applied compensate both for the inter-site correlation of flood magnitudes and the shorter-term (up to a few decades) serial correlation of floods.","Hirsch, R.M.
K.R. Ryberg",10.1080/02626667.2011.621895,0262-6667,1,"Hydrological Sciences Journal","floods, ; trends, ; climate change, ; statistics, ; carbon dioxide",1-9,"Has the magnitude of floods across the USA changed with global CO2 levels?",http://www.tandfonline.com/doi/abs/10.1080/02626667.2011.621895,57,2012,0,"<record><field id=""4""><run start=""0"" /><run face=""subscript"" start=""65"" /><run start=""66"" /></field></record>","[""Ch. 2: Our Changing Climate FINAL"",""RF 2"",""Ch. 3: Water Resources FINAL""]",825,a7f8dbf5-3ec8-4ee1-8740-014006b72bfd,"Journal Article",/article/10.1080/02626667.2011.621895
/reference/aae26529-edab-4278-8fe1-5763251ddb97,https://data.globalchange.gov/reference/aae26529-edab-4278-8fe1-5763251ddb97,aae26529-edab-4278-8fe1-5763251ddb97,,"Douglass, S.L.; Krolak, J.",,,,,,250,"Highways in the Coastal Environment, Second Edition. Hydraulic Engineering Circular No. 25. FHWA-NHI-07-096",http://www.fhwa.dot.gov/engineering/hydraulics/pubs/07096/07096.pdf,,2008,10,,"[""Ch. 25: Coastal Zone FINAL"",""RG 10 Coasts""]",849,aae26529-edab-4278-8fe1-5763251ddb97,Report,/report/fhwa-nhi-07-096
/reference/b05cd14d-f90c-42ba-92d7-ab8235603a3c,https://data.globalchange.gov/reference/b05cd14d-f90c-42ba-92d7-ab8235603a3c,b05cd14d-f90c-42ba-92d7-ab8235603a3c,,"Niemeier, Deb A.; Anne V. Goodchild; Maura Rowell; Joan L. Walker; Jane Lin; Lisa Schweitzer",,,,,,297-311,Transportation,https://www.swcarr.arizona.edu/chapter/14,,2013,7,,,26035,b05cd14d-f90c-42ba-92d7-ab8235603a3c,"Book Section",/report/swccar-assessment-climate-change-in-southwest-us
/reference/b0fc2727-11d7-4627-84ac-33c201875b58,https://data.globalchange.gov/reference/b0fc2727-11d7-4627-84ac-33c201875b58,b0fc2727-11d7-4627-84ac-33c201875b58,,"Chinowsky, Paul S.; Price, Jason C.; Neumann, James E.",10.1016/j.gloenvcha.2013.03.004,0959-3780,4,"Global Environmental Change","Infrastructure; Roads; Degradation; Economic impact",764-773,"Assessment of climate change adaptation costs for the U.S. road network",,23,2013,,,,24540,b0fc2727-11d7-4627-84ac-33c201875b58,"Journal Article",/article/10.1016/j.gloenvcha.2013.03.004
/reference/b19545a1-2e63-458c-8497-32a6d023aa89,https://data.globalchange.gov/reference/b19545a1-2e63-458c-8497-32a6d023aa89,b19545a1-2e63-458c-8497-32a6d023aa89,,"Smith, Jane McKee; Cialone, Mary A.; Wamsley, Ty V.; McAlpin, Tate O.",10.1016/j.oceaneng.2009.07.008,0029-8018,1,"Ocean Engineering","Hurricane; Katrina; Sea level rise; Southeast Louisiana; Storm surge; Waves; ADCIRC; STWAVE; IPET",37-47,"Potential impact of sea level rise on coastal surges in southeast Louisiana",,37,2010,0,,,19983,b19545a1-2e63-458c-8497-32a6d023aa89,"Journal Article",/article/10.1016/j.oceaneng.2009.07.008
/reference/b4808700-a94a-44da-b2bb-d360a83146f1,https://data.globalchange.gov/reference/b4808700-a94a-44da-b2bb-d360a83146f1,b4808700-a94a-44da-b2bb-d360a83146f1,"Tidal floods (i.e., “nuisance” flooding) are occurring more often during seasonal high tides or minor wind events, and the frequency is expected to increase dramatically in the coming decades. During these flood events, coastal communities’ roads are often impassable or difficult to pass, thus impacting routine transport needs. This study identifies vulnerable roads and quantifies the risk from nuisance flooding in the Eastern United States by combining public road information from the Federal Highway Administration’s Highway Performance Monitoring System with flood frequency maps, tidal gauge historic observations, and future projections of annual minor tidal flood frequencies and durations. The results indicate that tidal nuisance flooding across the East Coast threatens 7508 miles (12,083 km) of roadways including over 400 miles (644 km) of interstate roadways. From 1996–2005 to 2006–2015, there was a 90% average increase in nuisance floods. With sea level rise, nuisance-flood frequency is projected to grow at all locations assessed. The total induced vehicle-hours of delay due to nuisance flooding currently exceed 100 million hours annually. Nearly 160 million vehicle-hours of delay across the East Coast by 2020 (85% increase from 2010); 1.2 billion vehicle-hours by 2060 (126% increase from 2010); and 3.4 billion vehicle-hours by 2100 (392% increase from 2010) are projected under an intermediate low sea-level-rise scenario. By 2056–2065, nuisance flooding could occur almost daily at sites in Connecticut, New Jersey, Maryland, the District of Columbia, North Carolina, and Florida under an intermediate sea-level-rise scenario.","Jacobs, Jennifer M.; Cattaneo, Lia R.; Sweet, William; Mansfield, Theodore",10.1177/0361198118756366,,,"Transportation Research Record",,,"Recent and future outlooks for nuisance flooding impacts on roadways on the US East Coast",,,2018,,,,26046,b4808700-a94a-44da-b2bb-d360a83146f1,"Journal Article",/article/10.1177/0361198118756366
/reference/b65e9759-8397-48fc-bb41-fca6d6036994,https://data.globalchange.gov/reference/b65e9759-8397-48fc-bb41-fca6d6036994,b65e9759-8397-48fc-bb41-fca6d6036994,,"De La Fuente, Juan A.; Mikulovsky, Ryan P.",,,,,,"Abstract H43G-1540","Debris flows and road damage following a wildfire in 2014 on the Klamath National Forest, Northern California, near the community of Seiad, CA",https://agu.confex.com/agu/fm16/meetingapp.cgi/Paper/138852,,2016,47,,,26026,b65e9759-8397-48fc-bb41-fca6d6036994,"Conference Paper",/generic/f52e4542-9d2d-4ada-839e-5298f03ed98d
/reference/b7b33c40-58c1-4a5d-a6fa-f850a96d0981,https://data.globalchange.gov/reference/b7b33c40-58c1-4a5d-a6fa-f850a96d0981,b7b33c40-58c1-4a5d-a6fa-f850a96d0981,,"Mauger, Guillaume S.; Casola, Joseph H.; Harriet A. Morgan; Ronda L. Strauch; Brittany Jones; Beth Curry; Busch Isaksen, Tania M.; Whitely Binder, Lara; Meade B. Krosby; Amy K. Snover",10.7915/CIG93777D,,,,,various,"State of knowledge: Climate change in Puget Sound",https://cig.uw.edu/resources/special-reports/ps-sok/,,2015,10,,,24550,b7b33c40-58c1-4a5d-a6fa-f850a96d0981,Report,/report/state-knowledge-climate-change-puget-sound
/reference/b86b6e3d-2579-4e53-a2ca-a257d04c8df9,https://data.globalchange.gov/reference/b86b6e3d-2579-4e53-a2ca-a257d04c8df9,b86b6e3d-2579-4e53-a2ca-a257d04c8df9,,"Clancy, Justin B.; Grannis, Jessica",,,,,,17,"Lessons learned from [Hurricane] Irene: Climate change, federal disaster relief, and barriers to adaptive reconstruction",http://www.georgetownclimate.org/reports/lessons-learned-from-irene-climate-change-federal-disaster-relief-and-barriers-to-adaptive-reconstruction.html,,2013,10,,,24596,b86b6e3d-2579-4e53-a2ca-a257d04c8df9,Report,/report/lessons-learned-hurricane-irene-climate-change-federal-disaster-relief-barriers-adaptive-reconstruction
/reference/bab690fd-db14-4554-96c3-1d8a92b23a48,https://data.globalchange.gov/reference/bab690fd-db14-4554-96c3-1d8a92b23a48,bab690fd-db14-4554-96c3-1d8a92b23a48,,"Khatami, Dena; Behrouz Shafei",,,,,,"No. 17-04849","Climate change impact on management of deteriorating bridges: A case study of US Midwest region",http://docs.trb.org/prp/17-04849.pdf,,2017,47,,,26029,bab690fd-db14-4554-96c3-1d8a92b23a48,"Conference Paper",/generic/4feffc11-8d22-46a8-81df-02bb1f63d7da
/reference/bc4f3fef-d1f5-465a-9376-6aa2aaa731a1,https://data.globalchange.gov/reference/bc4f3fef-d1f5-465a-9376-6aa2aaa731a1,bc4f3fef-d1f5-465a-9376-6aa2aaa731a1,,"Collins, Mathias J.; Kirk, Johnathan P.; Pettit, Joshua; DeGaetano, Arthur T.; McCown, M. Sam; Peterson, Thomas C.; Means, Tiffany N.; Zhang, Xuebin",10.1080/02723646.2014.888510,0272-3646,3,"Physical Geography",,195-219,"Annual floods in New England (USA) and Atlantic Canada: Synoptic climatology and generating mechanisms",,35,2014,,,,26022,bc4f3fef-d1f5-465a-9376-6aa2aaa731a1,"Journal Article",/article/10.1080/02723646.2014.888510
/reference/bde3292e-b7bb-4a48-b2ea-40a594f37eb5,https://data.globalchange.gov/reference/bde3292e-b7bb-4a48-b2ea-40a594f37eb5,bde3292e-b7bb-4a48-b2ea-40a594f37eb5,"TRB’s Airport Cooperative Research Program (ACRP) Synthesis 33: Airport Climate Adaptation and Resilience reviews the range of risks to airports from projected climate change and the emerging approaches for handling them.","Transportation Research Board,; National Academies of Sciences Engineering and Medicine,",10.17226/22773,,,,"Transportation and Infrastructure",,"Airport Climate Adaptation and Resilience",,,2012,9,,,26045,bde3292e-b7bb-4a48-b2ea-40a594f37eb5,Book,/book/airport-climate-adaptation-resilience
/reference/c4151050-1289-41b6-a2ac-b760afe3c98b,https://data.globalchange.gov/reference/c4151050-1289-41b6-a2ac-b760afe3c98b,c4151050-1289-41b6-a2ac-b760afe3c98b,,"Douglass, Scott L.; Webb, Bret M.; Kilgore, Roger",,,,,,123,"Highways in the Coastal Environment: Assessing Extreme Events: Volume 2 (Hydraulic Engineering Circular No. 25–Volume 2)",https://www.fhwa.dot.gov/engineering/hydraulics/library_arc.cfm?pub_number=192&id=158,,2014,10,,,24544,c4151050-1289-41b6-a2ac-b760afe3c98b,Report,/report/highways-coastal-environment-assessing-extreme-events-volume-2-hydraulic-engineering-circular-no-25volume-2
/reference/c66bf5a9-a6d7-4043-ad99-db0ae6ae562c,https://data.globalchange.gov/reference/c66bf5a9-a6d7-4043-ad99-db0ae6ae562c,c66bf5a9-a6d7-4043-ad99-db0ae6ae562c,,"Sweet, W.V.; R.E. Kopp; C.P. Weaver; J. Obeysekera; R.M. Horton; E.R. Thieler; C. Zervas ",,,,,,75,"Global and Regional Sea Level Rise Scenarios for the United States",https://tidesandcurrents.noaa.gov/publications/techrpt83_Global_and_Regional_SLR_Scenarios_for_the_US_final.pdf,,2017,10,,,20608,c66bf5a9-a6d7-4043-ad99-db0ae6ae562c,Report,/report/global-regional-sea-level-rise-scenarios-united-states
/reference/cc670795-0251-48b0-8bf3-2f87fc67f8fd,https://data.globalchange.gov/reference/cc670795-0251-48b0-8bf3-2f87fc67f8fd,cc670795-0251-48b0-8bf3-2f87fc67f8fd,,"Federal Highway Administration,",,,,,,52,"Sea level rise and storm surge impacts on a coastal bridge: I-10 Bayway, Mobile Bay, Alabama",https://www.fhwa.dot.gov/environment/sustainability/resilience/ongoing_and_current_research/teacr/al_i-10/index.cfm,,2016,10,,,24589,cc670795-0251-48b0-8bf3-2f87fc67f8fd,Report,/report/sea-level-rise-storm-surge-impacts-on-coastal-bridge-i-10-bayway-mobile-bay-alabama
/reference/ccb1b544-9a86-4b57-a3d7-9499227d67c7,https://data.globalchange.gov/reference/ccb1b544-9a86-4b57-a3d7-9499227d67c7,ccb1b544-9a86-4b57-a3d7-9499227d67c7,"Numerous studies have shown that precipitation has a significant impact on motor vehicle crashes. Hourly weather radar data with a 4-km resolution and over 600 000 crashes from 2002 to 2012 in Iowa are used to assess the effects of precipitation on motor vehicle crashes. Using a matched pairs analysis, this study finds that the relative accident risk (RAR) across the state during the study period was 1.69 [1.66, 1.71]. However, RAR increased to as high as 3.7 [3.6, 4.0] and as low as 1.1 [1.0, 1.2] for frozen and liquid precipitation types, respectively. RAR also varied significantly by hour of the day, with RAR near 2 in the late afternoon and 1.3 during the early morning hours, suggesting an interaction effect between precipitation and traffic volume and/or density on crash risk. The study also shows that interstates and major highways tend to have higher RAR than smaller roads, and it was able to identify locations that are particularly sensitive to precipitation with regard to crashes. This study can be used to inform future studies on the effects of weather and climate change on crashes.","Tamerius, J. D.; X. Zhou; R. Mantilla; T. Greenfield-Huitt",10.1175/wcas-d-16-0009.1,,4,"Weather, Climate, and Society","Geographic location/entity,North America,Observational techniques and algorithms,Radars/Radar observations,Applications,Geographic information systems (GIS),Local effects,Societal impacts,Transportation meteorology",399-407,"Precipitation effects on motor vehicle crashes vary by space, time, and environmental conditions",,8,2016,,,,24565,ccb1b544-9a86-4b57-a3d7-9499227d67c7,"Journal Article",/article/10.1175/wcas-d-16-0009.1
/reference/cd7183d0-7e06-4d08-bba2-3765b2eba3fe,https://data.globalchange.gov/reference/cd7183d0-7e06-4d08-bba2-3765b2eba3fe,cd7183d0-7e06-4d08-bba2-3765b2eba3fe,,"Gopalakrishna, Deepak; Jeremy Schroeder; Amy Huff; Amy Thomas; Amy Leibrand ",,,,,,37,"Planning for systems management & operations as part of climate change adaptation ",https://ops.fhwa.dot.gov/publications/fhwahop13030/index.htm,,2013,10,,,24586,cd7183d0-7e06-4d08-bba2-3765b2eba3fe,Report,/report/planning-systems-management-operations-as-part-climate-change-adaptation
/reference/d09c22ad-256c-4fc1-998b-cf888a93fa58,https://data.globalchange.gov/reference/d09c22ad-256c-4fc1-998b-cf888a93fa58,d09c22ad-256c-4fc1-998b-cf888a93fa58,"Coastal communities with road infrastructure close to the shoreline are vulnerable to the effects of sea level rise caused by climate change. The sea level in coastal New Hampshire is projected to rise by 3.9 to 6.6 ft (1.2 to 2.0 m) by 2100. Climate change vulnerability and adaptation studies have focused on surface water flooding caused by sea level rise; however, little attention has been given to the effects of climate change on groundwater. Groundwater is expected to rise with sea level rise and will intersect the unbound layers of coastal road infrastructure, thus reducing the service life of pavement. Vulnerability studies are an essential part of adaptation planning, and pavement engineers are looking for methods to identify roads that may experience premature failure. In this study, a regional groundwater flow model of coastal New Hampshire was used to identify road infrastructure for which rising groundwater will move into the unbound materials during the design life of the pavement. Multilayer elastic theory was used to analyze typical pavement profiles in several functional classifications of roadway to determine the magnitude of fatigue and rutting life reduction expected from four scenarios of sea level rise. All the evaluation sites experienced service life reduction, the magnitude and timing of which depended on the current depth to groundwater, the pavement structure, and the subgrade. The use of this methodology will enable pavement engineers to target coastal road adaptation projects effectively and will result in significant cost savings compared with implementation of broad adaptation projects or the costs of no action.","Knott, Jayne F.; Mohamed Elshaer; Jo Sias Daniel; Jennifer M. Jacobs; Paul Kirshen",10.3141/2639-01,,,"Transportation Research Record: Journal of the Transportation Research Board",,1-10,"Assessing the effects of rising groundwater from sea level rise on the service life of pavements in coastal road infrastructure",,2639,2017,,,,21756,d09c22ad-256c-4fc1-998b-cf888a93fa58,"Journal Article",/article/10.3141/2639-01
/reference/d339d85e-f249-4ab4-acbb-eb605b777dd9,https://data.globalchange.gov/reference/d339d85e-f249-4ab4-acbb-eb605b777dd9,d339d85e-f249-4ab4-acbb-eb605b777dd9,"The objective of this research was to integrate current data sources to develop a methodology for assessing and mitigating the potential impacts of sea level rise (SLR) on Florida’s transportation infrastructure to assist transportation planning. The proposed approach integrates the Florida Department of Transportation (FDOT) information system with existing topographical and geological data to facilitate (1)&nbsp;the evaluation of current and projected SLR impacts on Florida’s coastline and low-lying terrain areas, and (2)&nbsp;the identification of the physical transportation infrastructure that is most likely to be affected by frequent to continuous flooding because of SLR so that solutions could be sought. The projection of SLR, and the timing for the same, was outlined using a benchmark approach that brackets time intervals as opposed to specific timing for improvements. Further research to evaluate the impact of sea level rise on ponding and storm surge is a future, more difficult area of investigation.","Bloetscher, Frederick; Leonard Berry; Jarice Rodriguez-Seda; Nicole Hernandez Hammer; Thomas Romah; Dusan Jolovic; Barry Heimlich; Maria Abadal Cahill",10.1061/(ASCE)IS.1943-555X.0000174,,2,"Journal of Infrastructure Systems",,04013015,"Identifying FDOT's physical transportation infrastructure vulnerable to sea level rise",,20,2014,,,,24536,d339d85e-f249-4ab4-acbb-eb605b777dd9,"Journal Article",/article/10.1061/(ASCE)IS.1943-555X.0000174
/reference/d67e92b2-0e74-45a2-8e13-5cb22ea12623,https://data.globalchange.gov/reference/d67e92b2-0e74-45a2-8e13-5cb22ea12623,d67e92b2-0e74-45a2-8e13-5cb22ea12623,"A method to assess the impacts of forecasted climate change on pavement deterioration is presented. Traditional methods of pavement design use historic climate data and assume that climate is stationary with time. Climate change challenges this assumption of stationarity (i.e., natural driving forces of engineering have a variability described by a time-invariant probability density function). Therefore, the use of historic climate data is insufficient for the prediction of climate conditions. The focus is on the preparation and the use of climate model data sets as inputs to the Mechanistic-Empirical Pavement Design Guide (MEPDG) model to simulate flexible pavement performance and deterioration over time. The method is illustrated with a case study that uses future climate model temperature data from three North American Regional Climate Change Assessment Program scenarios at four sites across New England. Pavement distress predicted with future temperature scenarios is compared with that from MEPDG temperature data. Application of the method demonstrates the importance of matching the overlapping periods before using climate forecast output in the MEPDG. Although the simulated impact of future temperature changes on pavement performance was negligible for alligator cracking at the four study sites, asphalt concrete rutting differences were great enough to warrant additional consideration and to suggest that climate change and variability in future climate scenarios could affect pavement design and evaluation. The proposed method can be used to evaluate the impact of other climate variables alone or in combination. The method also can readily use new climate model output and be adapted for new downscaling methods.","Meagher, William; Jo Daniel; Jennifer Jacobs; Ernst Linder",10.3141/2305-12,,,"Transportation Research Record: Journal of the Transportation Research Board",,111-120,"Method for evaluating implications of climate change for design and performance of flexible pavements",,2305,2012,,,,24551,d67e92b2-0e74-45a2-8e13-5cb22ea12623,"Journal Article",/article/10.3141/2305-12
/reference/dd5b893d-4462-4bb3-9205-67b532919566,https://data.globalchange.gov/reference/dd5b893d-4462-4bb3-9205-67b532919566,dd5b893d-4462-4bb3-9205-67b532919566,,,10.7930/J0Z31WJ2,,,,,,"Climate Change Impacts in the United States: The Third National Climate Assessment",http://nca2014.globalchange.gov,,2014,9,,"[""Ch. 0: About this Report FINAL""]",4692,dd5b893d-4462-4bb3-9205-67b532919566,"Edited Book",/report/nca3
/reference/df6fcad4-f0ea-4c60-97e1-ae2a40455f51,https://data.globalchange.gov/reference/df6fcad4-f0ea-4c60-97e1-ae2a40455f51,df6fcad4-f0ea-4c60-97e1-ae2a40455f51,,"Melvin, April M.; Larsen, Peter; Boehlert, Brent; Neumann, James E.; Chinowsky, Paul; Espinet, Xavier; Martinich, Jeremy; Baumann, Matthew S.; Rennels, Lisa; Bothner, Alexandra; Nicolsky, Dmitry J.; Marchenko, Sergey S.",10.1073/pnas.1611056113,"0027-8424, 1091-6490",2,"Proceedings of the National Academy of Sciences of the United States of America","adaptation; Alaska; climate change; damages; infrastructure",E122-E131,"Climate change damages to Alaska public infrastructure and the economics of proactive adaptation",,114,2017,,,,22252,df6fcad4-f0ea-4c60-97e1-ae2a40455f51,"Journal Article",/article/10.1073/pnas.1611056113
/reference/e192e196-23b1-417f-b4a3-ce2a8ef52268,https://data.globalchange.gov/reference/e192e196-23b1-417f-b4a3-ce2a8ef52268,e192e196-23b1-417f-b4a3-ce2a8ef52268,,"Freudenberg, Robert; Lucrecia Montemayor; Ellis Calvin; Emily Korman; Sarabrent McCoy; Julieet Michaelson; Chris Jones; Richard Barone; Moses Gates; Wendy Pollack; Ben Oldenburg",,,,,,25,"Under water: How sea level rise threatens the Tri-State Region",http://library.rpa.org/pdf/RPA-Under-Water-How-Sea-Level-Rise-Threatens-the-Tri-State-Region.pdf,,2016,10,,,24587,e192e196-23b1-417f-b4a3-ce2a8ef52268,Report,/report/under-water-how-sea-level-rise-threatens-tri-state-region
/reference/e1b34455-2f79-4bb8-8983-521b2e1c3f82,https://data.globalchange.gov/reference/e1b34455-2f79-4bb8-8983-521b2e1c3f82,e1b34455-2f79-4bb8-8983-521b2e1c3f82,"A method for deriving quantitative relationships between road slipperiness, traffic accident risk and winter road maintenance (WRM) activity is described. The method is also applied to data from an area in southern Sweden. If a specific type of road slipperiness represents a large accident risk despite high WRM activity it is important to increase public awareness during such periods. If the type of slipperiness represents a large accident risk but is accompanied by low WRM activity, it is also important to increase the WRM to reduce the accident risk. In the method, a road slipperiness classification, based on atmospheric processes, is used to classify the road conditions at the time an accident occurred. The road condition is classified either as non-slippery or as one out of 10 types of slipperiness. Data for the slipperiness classification are taken from the Swedish Road Weather Information System (RWIS). Results from this study show that the traffic accident risk was different for different types of road slipperiness. Highest accident risk was associated with road slipperiness due to rain or sleet on a frozen road surface. When accidents occurred in these situations, there was always high WRM activity. This indicates that, in order to reduce the accident rate during these situations, public awareness must be increased by providing information to drivers. The study also demonstrates the benefits of applying a standardized road slipperiness classification to all kinds of sources of road safety information, such as a RWIS, traffic accident reports and WRM reports. With a standardized and objective classification of the road conditions and digitally stored data, all evaluations are easily conducted.","Norrman, Jonas; Marie Eriksson; Sven Lindqvist",10.3354/cr015185,,3,"Climate Research",,185-193,"Relationships between road slipperiness, traffic accident risk and winter road maintenance activity",,15,2000,,,,24557,e1b34455-2f79-4bb8-8983-521b2e1c3f82,"Journal Article",/article/10.3354/cr015185