Projecting long-run socioeconomic and demographic trends in California under the SRES A2 and B1 scenarios

Second California Assessment: integrated climate change impacts assessment of natural and managed systems. Guest editorial

“…For these crops, SWAP internally estimated changes in prices but for global commodities such as rice, grain, and corn, prices are provided exogenously to SWAP (California is a price taker). SWAP also considered the amount of land that would no longer be available for agriculture production due to its conversion to urban dwellings given the urban projections reported by Sanstad et al (2011).…”

“…Shaw et al (2011) examined how climate change would affect two ecosystem services: 1) carbon sequestration in natural terrestrial ecosystems, and 2) non-irrigated forage production for livestock. Shaw et al used the MC1 dynamic vegetation model together with the urban expansion reported in Sanstad et al (2011) to estimate changes in carbon stocks in natural ecosystems. Using social cost of carbon figures reported in the literature by Tol (2007), Watkiss and Downing (2008), and Nordhaus (2008), they concluded that if a relatively mild form of climate change (climate scenarios from the PCM global change model) becomes a reality, carbon sequestration would result in a net benefit between $38 million annually in the period from 2005 to 2034 and about $22 billion annually by 2070.…”

“…This is important because human population expanding into wildland areas is one of the explanatory variables traditionally used to estimate fire risks. The urban projections by Sanstad et al (2011) were of little use for the study by Westerling et al, however, because their projections are only for core urban centers. Westerling et al found increases in burned area that go up with time (i.e., increases as the magnitude of climate change increases), with estimates in burned area by the end of the 21st Century exceeding 100% of the historical area burned in much of the forested areas of Northern California in all A2 runs.…”

Regional Assessment of Urban Impacts on Landcover and Open Space Finds a Smart Urban Growth Policy Performs Little Better than Business as Usual

“…We used human population growth projections on a county-by-county basis from the PPIC for 2050 [21], [34], in conjunction with county general development plans [35], and landscape features that attract or discourage urban growth (for details on model parameterization see Appendix SI). UPlan uses these inputs to spatially project new development for housing, commercial and industrial structures iteratively, placing each of the projected number of new units on the landscape into the grid cell with the highest attraction value, until all projected new growth is allocated.…”

Downscaling socioeconomic and emissions scenarios for global environmental change research: a review

“…The method, however, is very suitable for taking available (process) information into account, on a local scale. Within this category, methods may concentrate mainly on the overall characteristics of the global scenario, in combination with detailed modeling at the local level, such as the methods used to develop urbanization scenarios for the United States,12 to produce socioeconomic scenarios for California,27 and population and economic scenarios for the Millennium Ecosystem Assessment 28. In these studies, a matrix of scenario parameters was constructed such that scenarios were produced from existing models with general characteristics that match the storylines of the IPCC‐SRES scenarios (Special Report on Emission Scenarios) but using detailed regional data that was consistent with information already used in decision‐making processes in these regions.…”