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Large-scale atmospheric circulation refers to patterns of movement in the atmosphere on the scale of 1000s of kilometers. Different patterns are associated with and can be the driving force behind different weather conditions on the ground, like storms or heat waves. This work evaluates how well climate models can capture these patterns, and analyzes how these patterns may change over the Pacific Northwest in future global warming.
Winter Circulation Patterns and Associated Meteorology
Historical (1985:2014) reanalysis data from MERRA-2 is used to characterize the range of circulation patterns impacting the Pacific Northwest. A machine learning algorith, self-organizing maps, is used to cluster daily data into a representative set of patterns. With this historical range of patterns, we can evaluate how well models capture the range, strength, and frequency of patterns.
Historical circulation patterns over the Pacific Northwest in winter. 500 hPa anomalies are shaded and height is contoured. Percentages are frequency of occurence.
Temperature anomalies (difference from average in °C) associated with winter circulation patterns, as simulated by climate models.
Precipitation anomalies (% of average) associated with each winter circulation pattern, as simulated by climate models.
Summer Circulation Patterns and Associated Meteorology
Historical circulation patterns over the Pacific Northwest in summer. 500 hPa anomalies are shaded and height is contoured.
Temperature anomalies (difference from average in °C) associated with summer circulation patterns, as simulated by climate models.
Precipitation anomalies (% of average) associated with each summer circulation pattern, as simulated by climate models.
Large-Scale Atmospheric Circulation and Climate Change
Climate models from the latest suite of CMIP6 models are used to compare historical circulation patterns with those simulated by the models under a high-end global warming scenario, by the end of the 21st century. Results shown here are the ensemble mean of 26 models. Temperature and precipitation associated with circulation patterns are compared to historical patterns.
Models show some reduction in the strength of DJF circulation, but disagree on significance
DJF difference between the 2071:2100 Z500 anomaly patterns and the historical anomaly patterns (contours every 3 meters) in a. Solid contours indicate positive change while dashed contours indicate negative change. The dotted line is the zero contour. Shading shows end-of-century pseudo-SOMs. Grid cells with green dots are where at least half of the CMIP6 models exhibit a statistically significant change of the same sign at the
95% confidence level according to a t-test. Grid cells with grey dots are where at least half of the 26 models agree on the sign of change without the significance constraint.
Models robustly agree on a systematic decrease in the strength of JJA circulation patterns
JJA difference between the 2071:2100 Z500 anomaly patterns and the historical anomaly patterns (contours every 3 meters) in a. Solid contours indicate positive change while dashed contours indicate negative change. The dotted line is the zero contour. Shading shows end-of-century pseudo-SOMs. Grid cells with green dots are where at least half of the CMIP6 models exhibit a statistically significant change of the same sign at the
95% confidence level according to a t-test. Grid cells with grey dots are where at least half of the 26 models agree on the sign of change without the significance constraint.
Change in temperature and precipitation
Projected changes in winter time temperature are highest in northern areas, and patterns historically associated with cold air outbreaks. This makes sense, as the arctic warms faster than the rest of the globe.
Almost all patterns show increases in winter precipitation, especially northern latitudes. This aligns with scientific knowledge, as warmer air holds more water vapor.
a. Change in DJF MMEM temperature, shaded in degrees C. Contours are the MMEM historical anomalies with solid contours depicting positive and dashed negative values, spaced every 1°C. All changes are statistically significant so stippling is not used. b. Change in precipitation as percentage change from historical climatology. Solid contours are positive and dashed contours are negative historical anomalies spaced every 25%. White stippling shows where at least half of the 25 models project
statistically significant change of the same sign at the 95% confidence interval according to a t-test. Gray stippling shows where at least half of the models agree on the sign of change without the significance
constraint.
Projected changes in summer temperature are highest in inland areas.
Patterns historically associated with (rare) summer rainfall in the PNW are shown to become drier. This would be impactful for water resources and wildfire concerns.
a. Change in JJA MMEM temperature, shaded in degrees C. Contours are the MMEM historical anomalies with solid contours depicting positive and dashed negative values, spaced every 1°C. All changes are statistically significant so stippling is not used. b. Change in precipitation as percentage change from historical climatology. Solid contours are positive and dashed contours are negative historical anomalies spaced every 25%. White stippling shows where at least half of the 25 models project
statistically significant change of the same sign at the 95% confidence interval according to a t-test. Gray stippling shows where at least half of the models agree on the sign of change without the significance
constraint.
Publications:
Taylor, G., P. C. Loikith, H. K. Lee, B. Lintner, and C. M. Aragon, 2023: Projections of Large-Scale Atmospheric Circulation Patterns and Associated Temperature and Precipitation over the Pacific Northwest using CMIP6 Models, J. Climate, 36, 7257-7275, https://doi.org/10.1175/JCLI-D-23-0108.1
Taylor, G., P. C. Loikith, C. M. Aragon, D. E. Waliser, and H. Lee, 2023: CMIP6 Model Fidelity at Simulating Large-Scale Atmospheric
Circulation Patterns and Associated Temperature and Precipitation over the Pacific Northwest. Clim. Dyn., 60, 2199-2218,
https://doi.org/10.1007/s00382-022-06410-1.
Aragon, C. A., P. C. Loikith, N. McCullar, and A. Mandilag, 2020: Large Scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR. Int. J. Climatol., https://doi.org/10.1002/joc.6487. RMets Link
Presentations:
Projections of Large-Scale Atmospheric Circulation Patterns and Associated Temperature and Precipitation Anomalies over the Pacific Northwest using CMIP6 Models, Fall Meeting of the American Geophysical Union, San Francisco, CA, December 2023 (talk by Graham Taylor).
Projections of Large-Scale Atmospheric Circulation Patterns and Associated Temperature and Precipitation Anomalies over the Pacific Northwest using CMIP6 Models, Fall Meeting of the American Geophysical Union, Chicago, IL, December 2022 (poster by Graham Taylor).
Projections of Large-Scale Atmospheric Circulation Patterns and Associated Temperature and Precipitation Anomalies over the Pacific Northwest using CMIP6 Models, Fall Meeting of the American Geophysical Union, New Orleans, LA, December 2021 (talk by Graham Taylor).
Evaluating CMIP6 Model Fidelity at Simulating Large-Scale Atmospheric Circulation Patterns and Associated Temperature and Precipitation over the Pacific Northwest, Fall Meeting of the American Geophysical Union, New Orleans, LA, December 2021 (poster by Paul Loikith).
Projections of Large-Scale Meteorological Patterns, Temperature, and Precipitation over the Pacific Northwest using CMIP6 Models, Virtual 11th Northwest Climate Conference, April, 2021 (talk by Graham Taylor).
Projections of Future Large-Scale Meteorological Patterns, Temperature, and Precipitation over the Pacific Northwest, Virtual Fall Meeting of the American Geophysical Union, December, 2020 (poster by Graham Taylor).
Assessing Climate Change Impacts on Precipitation Over Bull Run Watershed, Northwest Climate Conference, Portland, Oregon, October, 2019 (poster by Graham Taylor)
Evaluation of CMIP5 model fidelity at capturing wet season large-scale meteorological patterns over the Pacific Northwest using self-organizing maps, Northwest Climate Conference, Portland, Oregon, October, 2019 (talk by Christina Aragon)
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