Regional Analysis

Abstract: In this study, we use our analogue method and Convolutional Neural Networks (CNNs) to assess the potential predictability of extreme precipitation occurrence based on Large-Scale Meteorological Patterns (LSMPs) for the winter (DJF) of Pacific Coast California (PCCA) and the summer (JJA) of Midwestern United States (MWST). We evaluate the LSMPs constructed with a large set of variables at multiple atmospheric levels and quantify the prediction skill with a variety of complementary performance measures.

Our results suggest that LSMPs provide useful predictability of extreme precipitation occurrence at a daily scale and its interannual variability over both regions. The 14-year (2006-2019) independent forecast shows Gilbert Skill Scores (GSS) in PCCA range from 0.06 to 0.32 across 24 CNN schemes and from 0.16 to 0.26 across 4 analogue schemes, in contrast to those from 0.1 to 0.24 and from 0.1 to 0.14 in MWST.

Overall, CNN seems more powerful in extracting the relevant features associated with extreme precipitation from the LSMPs than the analogue method, with several single-variate CNN schemes achieving more skillful prediction than the best multi-variate analogue scheme in PCCA and more than half of CNN schemes in MWST. Nevertheless, both methods highlight that Integrated Vapor Transport (IVT, or its zonal and meridional components) enables higher prediction skill than other atmospheric variables over both regions. Warm-season extreme precipitation in MWST presents a forecast challenge with overall lower prediction skill than in PCCA, attributed to the weak synoptic-scale forcing in summer.

Abstract: Infrastructure systems are vulnerable to weather risks. With climate change, extreme events are expected to increase.To evaluate these changes in the Northeastern United States, state-of-the-art high-resolution, convection-permitting regional climate modeling simulations are carried out to downscale projections of the Community Earth System Model (CESM) to 3 km horizontal resolution under a high impact emissions scenario for a near future time period (2025-2041). Changes in mean climate and extreme events are assessed relative to the present-day climate (2006-2020) for three key weather elements affecting electricity grid infrastructure and operations: temperatures, wind speeds and ice accumulation on infrastructure surfaces. An assessment of exceedance threshold calculations based on the safety thresholds set by National Electric Safety Code (NESC) and International Organization for Standardization (ISO) is also provided.

Canadian hydropower resources offer a potentially attractive option for meeting decarbonization targets in the US Northeast region, where there are ambitious climate goals and nearby hydro resources in Quebec. Existing transmission capacity is, however, a limiting factor in expanding hydropower imports to the region.

To examine the value of expanding transmission capacity from Quebec to the Northeast,  we employ an integrated top-down bottom-up modeling framework (USREP-EleMod). This research was part of an Energy Modeling Forum effort, EMF34, with a goal of better characterizing linkages in energy markets across North America. The scenarios we examine exogenously expand transmission capacity by 10, 30, and 50% above existing capacity into the US Northeast (New York/New England), finding the value to the economy of these expansions ranging from $.38-$.49 per kWh imported into New York, and $.30-$.33 per kWh imported into New England by 2050. 

The scenarios include economy-wide emissions goals these states have set for themselves. The carbon limits we impose raise fuel prices more than electricity prices, and as a result, we find greater electrification in the US Northeast region from 2030 onward--a result that one would not see using just an electricity sector model, This demonstrates a main hypothesis of EMF34, that models that looked at more integration across energy markets would give deeper insight than more narrowly focused models.

HIghlights:

    Canadian hydropower imports benefit the US Northeast region in transition to a low-carbon economy
    Transmission capacity expansion is evaluated based on a top-down bottom-up model
    The value to the economy of the expansion is significantly larger than the cost of the electricity itself

Abstract: We explore the performance of an addition to U.S. climate policy using authority under Section 115 of the Clean Air Act, with special attention to distributional effects among the states. This portion of the Act concerns trans-boundary air pollution, and under its provisions a national greenhouse target could be allocated among the states, with the details of state implementation optionally guided by a model rule as under other provisions of the Act. With trading allowed among the states, such a measure could lead to a national price on the covered gases. While we adopt features of a possible Section 115 implementation, the analysis is applicable to similar cap-and-trade programs that might be adopted under other authorities.

We investigate the implications of such a policy using MIT’s U.S. Regional Energy Policy (USREP) model, with its electric sector replaced by the Renewable Energy Development System (ReEDS) model developed by the U.S. National Renewable Energy Laboratory. Existing federal and state climate policies are assumed to remain in place, and a national constraint on CO2 emissions is applied to achieve 45% or 50% reductions below the 2005 level by 2030. We apply the policies in a Baseline and a Low-Cost Baseline, the latter with more aggressive assumptions of technology cost improvements. The U.S. is aggregated to 18 individual states and 12 multi-state regions, and the effects of the national emissions restriction are investigated under three alternative methods by which the EPA might allocate these targets among the states.

We find the cost of achieving either target to be modest - allowing for nearly identical economic growth, even without taking account of air quality and climate benefits. The alternative allocation methods generate varying per capita revenue outcomes among states and regions and drive most of the welfare impact through a direct income effect. It is assumed that states distribute permit revenue to their residents in equal lump-sum payments, which leads to net benefits to lower income households. Under the Low-Cost Baseline, carbon prices in 2030 are about ⅓ those in the Baseline, and the welfare effects are negligible. Considering climate benefits evaluated using the social cost of carbon and particulate matter air pollution health benefits, less the mitigation costs, we find net benefits to the U.S. in all cases, with slightly larger net benefits with the 50% reduction below 2005 emissions.

Abstract: Emissions of ozone-depleting substances, including trichlorofluoromethane (CFC11), have decreased since the mid-1980s in response to the Montreal Protocol. In recent years, an unexpected increase in CFC-11 emissions beginning in 2013 has been reported, with much of the global rise attributed to emissions from eastern China.

Here we use high-frequency atmospheric mole fraction observations from Gosan, South Korea and Hateruma, Japan, together with atmospheric chemical transport-model simulations, to investigate regional CFC-11 emissions from eastern China. We find that CFC-11 emissions returned to pre-2013 levels in 2019 (5.0 ± 1.0 gigagrams per year in 2019, compared to 7.2 ± 1.5 gigagrams per year for 2008–2012, ±1 standard deviation), decreasing by 10 ± 3 gigagrams per year since 2014–2017. Furthermore, we find that in this region, carbon tetrachloride (CCl4) and dichlorodifluoromethane (CFC-12) emissions—potentially associated with CFC-11 production—were higher than expected after 2013 and then declined one to two years before the CFC-11 emissions reduction.

This suggests that CFC-11 production occurred in eastern China after the mandated global phase-out, and that there was a subsequent decline in production during 2017–2018. We estimate that the amount of the CFC-11 bank (the amount of CFC-11 produced, but not yet emitted) in eastern China is up to 112 gigagrams larger in 2019 compared to pre-2013 levels, probably as a result of recent production. Nevertheless, it seems that any substantial delay in ozone-layer recovery has been avoided, perhaps owing to timely reporting and subsequent action by industry and government in China.

Abstract: The Turkish power sector achieved a rapid growth after the 1990s in line with economic growth and even beyond. However, this development was not supported by domestic resources and therefore culminated in a high dependency on imported fossil fuels. Over and above, the governments were slow of the mark in introducing policies for increasing the share of renewable energy. Nevertheless, even late actions of the government, as well as significant decreases in the cost of wind and especially solar technologies, have recently brought the Turkish power sector in a promising state. In this study, a large-scale generation expansion power system model (TR-Power) with a high temporal resolution (hours) is developed for the Turkish power generation sector. Several prospective scenarios (high penetration of renewable resources, limiting constraints on GHG emissions, and changes in subsidy schemes on renewable and local resources) were analyzed for assessing their environmental and economic impacts. The results indicate that a transition to a low-carbon power grid with around half of the electricity demand satisfied by renewable resources over a 25-year period would be possible with annual investments of 4.25 to 7.10 Billion 2019 US$. Moreover, TR-Power indicates that the shadow price of CO2 emissions in the power sector will be around 13.8 and 34.0 $/per tCO2 by 2042 under 30% and 40% emission reduction targets relative to the reference scenario.

Pages

Subscribe to Regional Analysis