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Title: County-Level Climate Uncertainty for Risk Assessments: Volume 2 Appendix A - Historical Near-Surface Air Temperature.

Abstract

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1365545
Report Number(s):
SAND2017-6209
654467
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Backus, George A., Lowry, Thomas Stephen, Jones, Shannon M., Walker, La Tonya Nicole, Roberts, Barry L., and Malczynski, Leonard A. County-Level Climate Uncertainty for Risk Assessments: Volume 2 Appendix A - Historical Near-Surface Air Temperature.. United States: N. p., 2017. Web. doi:10.2172/1365545.
Backus, George A., Lowry, Thomas Stephen, Jones, Shannon M., Walker, La Tonya Nicole, Roberts, Barry L., & Malczynski, Leonard A. County-Level Climate Uncertainty for Risk Assessments: Volume 2 Appendix A - Historical Near-Surface Air Temperature.. United States. doi:10.2172/1365545.
Backus, George A., Lowry, Thomas Stephen, Jones, Shannon M., Walker, La Tonya Nicole, Roberts, Barry L., and Malczynski, Leonard A. Thu . "County-Level Climate Uncertainty for Risk Assessments: Volume 2 Appendix A - Historical Near-Surface Air Temperature.". United States. doi:10.2172/1365545. https://www.osti.gov/servlets/purl/1365545.
@article{osti_1365545,
title = {County-Level Climate Uncertainty for Risk Assessments: Volume 2 Appendix A - Historical Near-Surface Air Temperature.},
author = {Backus, George A. and Lowry, Thomas Stephen and Jones, Shannon M. and Walker, La Tonya Nicole and Roberts, Barry L. and Malczynski, Leonard A.},
abstractNote = {This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.},
doi = {10.2172/1365545},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jun 01 00:00:00 EDT 2017},
month = {Thu Jun 01 00:00:00 EDT 2017}
}

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