Increases in Future AR Count and Size: Overview of the ARTMIP Tier 2 CMIP5/6 Experiment.

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi-model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA-2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

Atmospheric blocking and intercomparison of objective detection methods: flow field characteristics.

Objective methods for identifying and quantifying atmospheric blocking have been developed over recent decades, primarily targeting North Atlantic blocks. Differences arise from these methods, leading to changes in the resultant blocking climatology. To understand these differences, and better inform future assessments built on quantitative detection of blocks, this paper examines blocking properties produced by three different objective detection algorithms over the global extratropics. Blocking criteria examined include 500 hPa geopotential height anomaly ( Z ∗ ), column-averaged potential vorticity anomaly ( P V ∗ ), and 500 hPa geopotential height gradient (AGP). Results are analyzed for blocking climatologies and for instantaneous blocking patterns, as well as distributions of block size, speed, duration, and distance traveled. The results emphasize physical characteristics of the flow field and the subsequent blocking regions that emerge; overall, P V ∗ and Z ∗ blocked regions often have higher pattern correlation and spatial similarity, though these two methods also display high agreement with AGP in some instances. Z ∗ finds the largest (and greatest number of) blocked regions, while P V ∗ -detected regions are smallest in all instances except Southern Hemisphere winter. In some cases, P V ∗ tracks a nearby jet streak, leading to differences with height-based algorithms. All three algorithms detect some questionable low-latitude blocks that are stationary and persist but do not impair zonal flow, although at different times. Therefore, careful consideration of the algorithm biases is important in future blocking studies. For example, linking extreme weather to detected blocking could vary substantially depending on the algorithm used.

California's Drought of the Future: A Midcentury Recreation of the Exceptional Conditions of 2012-2017.

The California drought of 2012-2016 was a record-breaking event with extensive social, political, and economic repercussions. The impacts were widespread and exposed the difficulty in preparing for the effects of prolonged dry conditions. Although the lessons from this drought drove important changes to state law and policy, there is little doubt that climate change will only exacerbate future droughts. To understand the character of future drought, this paper examines this recent drought period retrospectively and prospectively, that is, as it occurred historically and if similar dynamical conditions to the historical period were to arise 30 years later (2042-2046) subject to the effects of climate change. Simulations were conducted using the Weather Research and Forecasting model using the pseudo global warming method. The simulated historical and future droughts are contrasted in terms of temperature, precipitation, snowpack, soil moisture, evapotranspiration, and forest health. Overall, the midcentury drought is observed to be significantly worse, with many more extreme heat days, record-low snowpack, increased soil drying, and record-high forest mortality. With these findings in mind, the data sets developed in this study provide a means to structure future drought planning around a drought scenario that is realistic and modeled after a memorable historical analog.