Drivers of Twenty-First Century U.S. Winter Precipitation Trends in CMIP6 Models: A Storyline-Based Approach

2021 ◽  
pp. 1-48
Author(s):  
Daniel F. Schmidt ◽  
Kevin M. Grise

AbstractClimate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each.This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in 21st century U.S. winter precipitation trends across CMIP6 models under the SSP3-7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, the El Niño-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, and the East Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern U.S. result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern U.S. result from a combination of strong global warming and a negative PNA trend.

2007 ◽  
Vol 20 (4) ◽  
pp. 609-632 ◽  
Author(s):  
William L. Chapman ◽  
John E. Walsh

Abstract Simulations of Arctic surface air temperature and sea level pressure by 14 global climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change are synthesized in an analysis of biases and trends. Simulated composite GCM surface air temperatures for 1981–2000 are generally 1°–2°C colder than corresponding observations with the exception of a cold bias maximum of 6°–8°C in the Barents Sea. The Barents Sea bias, most prominent in winter and spring, occurs in 12 of the 14 GCMs and corresponds to a region of oversimulated sea ice. All models project a twenty-first-century warming that is largest in the autumn and winter, although the rates of the projected warming vary considerably among the models. The across-model and across-scenario uncertainties in the projected temperatures are comparable through the first half of the twenty-first century, but increases in variability associated with the choice of scenario begin to outpace increases in across-model variability by about the year 2070. By the end of the twenty-first century, the cross-scenario variability is about 50% greater than the across-model variability. The biases of sea level pressure are smaller than in the previous generation of global climate models, although the models still show a positive bias of sea level pressure in the Eurasian sector of the Arctic Ocean, surrounded by an area of negative pressure biases. This bias is consistent with an inability of the North Atlantic storm track to penetrate the Eurasian portion of the Arctic Ocean. The changes of sea level pressure projected for the twenty-first century are negative over essentially the entire Arctic. The most significant decreases of pressure are projected for the Bering Strait region, primarily in autumn and winter.


2019 ◽  
Vol 32 (5) ◽  
pp. 1551-1571 ◽  
Author(s):  
Kevin M. Grise ◽  
Sean M. Davis ◽  
Isla R. Simpson ◽  
Darryn W. Waugh ◽  
Qiang Fu ◽  
...  

AbstractPrevious studies have documented a poleward shift in the subsiding branches of Earth’s Hadley circulation since 1979 but have disagreed on the causes of these observed changes and the ability of global climate models to capture them. This synthesis paper reexamines a number of contradictory claims in the past literature and finds that the tropical expansion indicated by modern reanalyses is within the bounds of models’ historical simulations for the period 1979–2005. Earlier conclusions that models were underestimating the observed trends relied on defining the Hadley circulation using the mass streamfunction from older reanalyses. The recent observed tropical expansion has similar magnitudes in the annual mean in the Northern Hemisphere (NH) and Southern Hemisphere (SH), but models suggest that the factors driving the expansion differ between the hemispheres. In the SH, increasing greenhouse gases (GHGs) and stratospheric ozone depletion contributed to tropical expansion over the late twentieth century, and if GHGs continue increasing, the SH tropical edge is projected to shift further poleward over the twenty-first century, even as stratospheric ozone concentrations recover. In the NH, the contribution of GHGs to tropical expansion is much smaller and will remain difficult to detect in a background of large natural variability, even by the end of the twenty-first century. To explain similar recent tropical expansion rates in the two hemispheres, natural variability must be taken into account. Recent coupled atmosphere–ocean variability, including the Pacific decadal oscillation, has contributed to tropical expansion. However, in models forced with observed sea surface temperatures, tropical expansion rates still vary widely because of internal atmospheric variability.


2013 ◽  
Vol 26 (20) ◽  
pp. 7813-7828 ◽  
Author(s):  
John P. Krasting ◽  
Anthony J. Broccoli ◽  
Keith W. Dixon ◽  
John R. Lanzante

Abstract Using simulations performed with 18 coupled atmosphere–ocean global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), projections of the Northern Hemisphere snowfall under the representative concentration pathway (RCP4.5) scenario are analyzed for the period 2006–2100. These models perform well in simulating twentieth-century snowfall, although there is a positive bias in many regions. Annual snowfall is projected to decrease across much of the Northern Hemisphere during the twenty-first century, with increases projected at higher latitudes. On a seasonal basis, the transition zone between negative and positive snowfall trends corresponds approximately to the −10°C isotherm of the late twentieth-century mean surface air temperature, such that positive trends prevail in winter over large regions of Eurasia and North America. Redistributions of snowfall throughout the entire snow season are projected to occur—even in locations where there is little change in annual snowfall. Changes in the fraction of precipitation falling as snow contribute to decreases in snowfall across most Northern Hemisphere regions, while changes in total precipitation typically contribute to increases in snowfall. A signal-to-noise analysis reveals that the projected changes in snowfall, based on the RCP4.5 scenario, are likely to become apparent during the twenty-first century for most locations in the Northern Hemisphere. The snowfall signal emerges more slowly than the temperature signal, suggesting that changes in snowfall are not likely to be early indicators of regional climate change.


2013 ◽  
Vol 42 (1-2) ◽  
pp. 37-58 ◽  
Author(s):  
Valentina Radić ◽  
Andrew Bliss ◽  
A. Cody Beedlow ◽  
Regine Hock ◽  
Evan Miles ◽  
...  

2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.


2018 ◽  
Author(s):  
Elena Shevnina ◽  
Karoliina Pilli-Sihvola ◽  
Riina Haavisto ◽  
Timo Vihma ◽  
Andrey Silaev

Abstract. Potential hydropower production for 2020–2050 is calculated for 173 catchments located over the territories of Finland, Sweden, Norway, the Russian Federation, Canada and the United States. The results are based on hydrological river runoff projections assessed together with their exceedance probabilities. The annual runoff rate of particular exceedance probability was modelled with the Pearson type 3 distribution from three parameters (mean values, coefficient of variation and coefficient of skewness) simulated by the probabilistic hydrological MARcov Chain System (MARCS) model. The probabilistic projections of annual runoff were simulated from outputs of four global climate models under three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). The future potential hydropower production was evaluated based on annual runoff of low and high exceedance probabilities, and then aggregated at a country level. Under forcing from climate models that project a large increase in precipitation (CaEMS2 and MPI-EMS-LM), the expected potential hydropower production in the six countries increased by 14.0 to 18.0 % according to the projected values of annual runoff rate on exceedance probabilities of 10 and 90 %. This increase in water resources allows for 10–15 % more hydropower energy generation by rivers located in Russia, Finland, Norway, and Sweden. For the USA and Canada, the potential hydropower production is projected to increases by 4.0–9.0 %. Under forcing from climate models that project a smaller increase in precipitation (HadGEM2-ES and INMCM4), the increase of potential hydropower production by 2050 was predicted to be 2.1–8.4 % over the six countries considered.


2014 ◽  
Vol 27 (21) ◽  
pp. 8055-8069 ◽  
Author(s):  
Timothy E. LaRow ◽  
Lydia Stefanova ◽  
Chana Seitz

Abstract The effects on early and late twenty-first-century North Atlantic tropical cyclone statistics resulting from imposing the patterns of maximum/minimum phases of the observed Atlantic multidecadal oscillation (AMO) onto projected sea surface temperatures (SSTs) from two climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are examined using a 100-km resolution global atmospheric model. By imposing the observed maximum positive and negative phases of the AMO onto two CMIP5 SST projections from the representative concentration pathway (RCP) 4.5 scenario, this study places bounds on future North Atlantic tropical cyclone activity during the early (2020–39) and late (2080–99) twenty-first century. Averaging over both time periods and both AMO phases, the mean named tropical cyclones (NTCs) count increases by 35% when compared to simulations using observed SSTs from 1982 to 2009. The positive AMO simulations produce approximately a 68% increase in mean NTC count, while the negative AMO simulations are statistically indistinguishable from the mean NTC count determined from the 1995–2009 simulations—a period of observed positive AMO phase. Examination of the tropical cyclone track densities shows a statistically significant increase in the tracks along the East Coast of the United States in the future simulations compared to the models’ 1982–2009 climate simulations. The increase occurs regardless of AMO phase, although the negative phase produces higher track densities. The maximum wind speeds increase by 6%, in agreement with other climate change studies. Finally, the NTC-related precipitation is found to increase (approximately by 13%) compared to the 1982–2009 simulations.


Sign in / Sign up

Export Citation Format

Share Document