From California’s Extreme Drought to Major Flooding: Evaluating and Synthesizing Experimental Seasonal and Subseasonal Forecasts of Landfalling Atmospheric Rivers and Extreme Precipitation during Winter 2022/23DeFlorio, Michael J.; Sengupta, Agniv; Castellano, Christopher M.; Wang, Jiabao; Zhang, Zhenhai; Gershunov, Alexander; Guirguis, Kristen; Luna Niño, Rosa; Clemesha, Rachel E. S.; Pan, Ming; Xiao, Mu; Kawzenuk, Brian; Gibson, Peter B.; Scheftic, William; Broxton, Patrick D.; Switanek, Matthew B.; Yuan, Jing; Dettinger, Michael D.; Hecht, Chad W.; Cayan, Daniel R.; Cornuelle, Bruce D.; Miller, Arthur J.; Kalansky, Julie; Delle Monache, Luca; Ralph, F. Martin; Waliser, Duane E.; Robertson, Andrew W.; Zeng, Xubin; DeWitt, David G.; Jones, Jeanine; Anderson, Michael L.
doi: 10.1175/bams-d-22-0208.1pmid: N/A
AbstractCalifornia experienced a historic run of nine consecutive landfalling atmospheric rivers (ARs) in three weeks’ time during winter 2022/23. Following three years of drought from 2020 to 2022, intense landfalling ARs across California in December 2022–January 2023 were responsible for bringing reservoirs back to historical averages and producing damaging floods and debris flows. In recent years, the Center for Western Weather and Water Extremes and collaborating institutions have developed and routinely provided to end users peer-reviewed experimental seasonal (1–6 month lead time) and subseasonal (2–6 week lead time) prediction tools for western U.S. ARs, circulation regimes, and precipitation. Here, we evaluate the performance of experimental seasonal precipitation forecasts for winter 2022/23, along with experimental subseasonal AR activity and circulation forecasts during the December 2022 regime shift from dry conditions to persistent troughing and record AR-driven wetness over the western United States. Experimental seasonal precipitation forecasts were too dry across Southern California (likely due to their overreliance on La Niña), and the observed above-normal precipitation across Northern and Central California was underpredicted. However, experimental subseasonal forecasts skillfully captured the regime shift from dry to wet conditions in late December 2022 at 2–3 week lead time. During this time, an active MJO shift from phases 4 and 5 to 6 and 7 occurred, which historically tilts the odds toward increased AR activity over California. New experimental seasonal and subseasonal synthesis forecast products, designed to aggregate information across institutions and methods, are introduced in the context of this historic winter to provide situational awareness guidance to western U.S. water managers.
Grand-Scale Atmospheric Imaging Apparatus (GAIA) and Wind Lidar Multiscale Measurements in the Atmospheric Surface LayerIungo, Giacomo Valerio; Guala, Michele; Hong, Jiarong; Bristow, Nathaniel; Puccioni, Matteo; Hartford, Peter; Ehsani, Roozbeh; Letizia, Stefano; Li, Jiaqi; Moss, Coleman
doi: 10.1175/bams-d-23-0066.1pmid: N/A
AbstractUnderstanding the organization and dynamics of turbulence structures in the atmospheric surface layer (ASL) is important for fundamental and applied research in different fields, including weather prediction, snow settling, particle and pollutant transport, and wind energy. The main challenges associated with probing and modeling turbulence in the ASL are (i) the broad range of turbulent scales associated with the different eddies present in high Reynolds number boundary layers ranging from the viscous scale (on the order of millimeters) up to large energy-containing structures (on the order of kilometers); (ii) the nonstationarity of the wind conditions and the variability associated with the daily cycle of the atmospheric stability; and (iii) the interactions among eddies of different sizes populating different layers of the ASL, which contribute to momentum, energy, and scalar turbulent fluxes. Creative and innovative measurement techniques are required to probe near-surface turbulence by generating spatiotemporally resolved data in the proximity of the ground and, at the same time, covering the entire ASL height with large enough streamwise extent to characterize the dynamics of larger eddies evolving aloft. To this aim, the U.S. National Science Foundation sponsored the development of the Grand-scale Atmospheric Imaging Apparatus (GAIA) enabling super-large snow particle image velocimetry (SLPIV) in the near-surface region of the ASL. This inaugural version of GAIA provides a comprehensive measuring system by coupling SLPIV and two scanning Doppler lidars to probe the ASL at an unprecedented resolution. A field campaign performed in 2021–22 and its preliminary results are presented herein elucidating new research opportunities enabled by the GAIA measuring system.
Hydrological Projections under CMIP5 and CMIP6: Sources and Magnitudes of UncertaintyWu, Yi; Miao, Chiyuan; Slater, Louise; Fan, Xuewei; Chai, Yuanfang; Sorooshian, Soroosh
doi: 10.1175/bams-d-23-0104.1pmid: N/A
AbstractProjections of future hydrological conditions rely largely on global climate models, but model performance varies greatly. In this study, we investigated projected changes in runoff (R), precipitation (P), evapotranspiration (ET), and soil moisture (SM) based on the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) and quantified the uncertainties of their projected changes on annual and seasonal scales. The results indicate that all four hydrological variables show an increase over most of the global land: annual projections of R, P, ET, and SM from CMIP6 increase in 72%, 81%, 82%, and 66% of the global land area, respectively, under a high emissions scenario during the period 2080–99 relative to 1970–99. We estimated the uncertainties in CMIP6 from different sources on an annual scale and found that model uncertainty dominates the total projected uncertainties during the twenty-first century [76% (R), 73% (P), 89% (ET), and 95% (SM) in the 2090s], and the contribution of internal variability decreases with time. The low-latitude regions have the greatest uncertainty in hydrological projections. In CMIP6, the uncertainty of projected changes in P contributes the most to the uncertainty of projected changes in R, with a contribution of 93% on annual scale, followed by ET and SM. Overall, the performances of the CMIP5 and CMIP6 models are similar in terms of hydrological changes and the composition of their uncertainties. This study provides a theoretical reference for the further improvement and development of hydrological components in global climate models.Significance StatementPrevious studies concerning future hydrological changes have predominantly focused on trends in future drying or wetter conditions but often ignored or discounted obvious disparities in model performance across distinct regions. The purpose of this study is to investigate future hydrological changes, quantify the agreement among CMIP6 models regarding these changes, and then decompose the sources that contribute to the discrepancies in hydrological projections. This study has the potential to strengthen the reliability of hydrological components in global climate models, thereby contributing to more accurate future projections of global water conditions.
Searching for the Most Extreme Temperature Events in Recent HistoryCattiaux, Julien; Ribes, Aurélien; Thompson, Vikki
doi: 10.1175/bams-d-23-0095.1pmid: N/A
AbstractBecause they are rare, extreme weather events have critical impacts on societies and ecosystems and attract public and scientific attention. The most unusual events are regularly documented as part of routine climate monitoring by meteorological services. A growing number of attribution studies also aim at quantifying how their probability has evolved under human-induced climate change. However, it is often recognized that (i) the selection of studied events is geographically uneven, and (ii) the definition of a given event, in particular, its spatiotemporal scale, is subjective, which may impact attribution statements. Here we present an original method that objectively selects, defines, and compares extreme events that have occurred worldwide in the recent years. Building on previous work, the event definition consists of automatically selecting the spatiotemporal scale that maximizes the event rarity, accounting for the nonstationary context of climate change. We then explore all years, seasons, and regions and search for the most extreme events. We demonstrate how our searching procedure can be both useful for climate monitoring over a given territory, and resolve the geographical selection bias of attribution studies. Ultimately, we provide a selection of the most exceptional hot and cold events in the recent past, among which are iconic heatwaves such as those seen in 2021 in Canada and in 2003 in Europe.Significance StatementThe purpose of the article is to objectively select and rank the most exceptional heatwaves and cold spells that have occurred worldwide in the recent years. As these events often have the greatest socioeconomic impacts, better knowledge and characterization of historical events in a changing climate can inform adaptation strategies. We exhaustively scan temperature data over all years and regions to identify extreme events using the event probability as a universal metric. Applied over a specific location, such as on a national level, our method provides useful information for the climate monitoring of weather events. Applied globally, it can help attribution studies to pick events without the selection bias related to authors origin or media coverage.
Attribution of the August 2022 Extreme Heatwave in Southern China: Role of Dynamical and Thermodynamical ProcessesGong, Hainan; Ma, Kangjie; Hu, Zhiyuan; Dong, Zizhen; Ma, Yuanyuan; Chen, Wen; Wu, Renguang; Wang, Lin
doi: 10.1175/bams-d-23-0175.1pmid: N/A
AbstractWe estimate that anthropogenic forcing caused half of the observed temperature anomaly during the August 2022 heatwave in southern China. Thermodynamical processes, especially soil moisture–SAT feedback, amplified the heatwave.
The South American Tropopause Aerosol Layer (SATAL)Bresciani, Caroline; Herdies, Dirceu Luis; Figueroa, Silvio Nilo; Buchard, Virginie; da Silva, Arlindo M.; Jones, Charles; Carvalho, Leila M. V.
doi: 10.1175/bams-d-23-0074.1pmid: N/A
AbstractThe presence of an aerosol layer in the upper troposphere/lower stratosphere (UT/LS) in South America was identified with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2). This layer, which we shall refer to as the South American tropopause aerosol layer (SATAL), was identified over the Amazon basin at altitudes between 11 and 14 km. It exhibits a seasonal behavior similar to the Asian tropopause aerosol layer (ATAL) and the North American tropopause aerosol layer (NATAL). The SATAL is observed from October to March, coinciding with the presence of the South American monsoon. It forms first in the eastern Amazon basin in October, then moves to the southern Amazon, where it weakens in December–January and finally dissipates in February–March. We hypothesize that two main factors influence the SATAL formation in the UT/LS: 1) the source of aerosols from Africa and 2) the updraft mass flux from deep convective systems during the active phase of the South American monsoon system that transports aerosols to the UT/LS. Further satellite observations of aerosols and field campaigns are needed to provide useful information to find the origin and composition of the aerosols in the UT/LS during the South American monsoon.Significance StatementThe purpose of this study is to better understand an increase in aerosol concentration in the upper troposphere/lower stratosphere (UT/LS) in South America. This is important because the atmospheric aerosol influences the Earth’s radiative balance and climate and changes the temperature and precipitation cycles. Besides that, the aerosol in the UT/LS could be an aerosol source for remote regions and contribute to cloud formation. Our results suggest that an aerosol layer forms in the UT/LS during the summer months over South America, as soon as the region’s rainy season begins.
The Weather–Climate SchismRandall, David A.; Emanuel, Kerry
doi: 10.1175/bams-d-23-0124.1pmid: N/A
AbstractThe atmospheric science community includes both weather and climate scientists. These two groups interact much less than they should, particularly in the United States. The schism is widespread and has persisted for 50 years or more. It is found in academic departments, laboratories, professional societies, and even funding agencies. Mending the schism would promote better, faster science. We sketch the history of the schism and suggest ways to make our community whole.