Summer atmospheric circulation over Greenland in response to Arctic amplification and diminished spring snow cover.

The exceptional atmospheric conditions that have accelerated Greenland Ice Sheet mass loss in recent decades have been repeatedly recognized as a possible dynamical response to Arctic amplification. Here, we present evidence of two potentially synergistic mechanisms linking high-latitude warming to the observed increase in Greenland blocking. Consistent with a prominent hypothesis associating Arctic amplification and persistent weather extremes, we show that the summer atmospheric circulation over the North Atlantic has become wavier and link this wavier flow to more prevalent Greenland blocking. While a concomitant decline in terrestrial snow cover has likely contributed to this mechanism by further amplifying warming at high latitudes, we also show that there is a direct stationary Rossby wave response to low spring North American snow cover that enforces an anomalous anticyclone over Greenland, thus helping to anchor the ridge over Greenland in this wavier atmospheric state.

Increasing extreme melt in northeast Greenland linked to foehn winds and atmospheric rivers.

The Greenland Ice Sheet has been losing mass at an increased rate in recent decades. In northeast Greenland, increasing surface melt has accompanied speed-ups in the outlet glaciers of the Northeast Greenland Ice Stream, which contain over one meter of sea level rise potential. Here we show that the most intense northeast Greenland melt events are driven by atmospheric rivers (ARs) affecting northwest Greenland that induce foehn winds in the northeast. Near low-elevation outlet glaciers, 80-100% of extreme (> 99th percentile) melt occurs during foehn conditions and 50-75% during ARs. These events have become more frequent during the twenty-first century, with 5-10% of total northeast Greenland melt in several recent summers occurring during the ~1% of times with strong AR and foehn conditions. We conclude that the combined AR-foehn influence on northeast Greenland extreme melt will likely continue to grow as regional atmospheric moisture content increases with climate warming.

Future precipitation variability during the early rainfall season in the El Yunque National Forest.

El Yunque National Forest, situated in the Luquillo Mountains of northeast Puerto Rico, is home to a wide range of climate-sensitive ecosystems and forest types. In particular, these ecosystems are highly sensitive to changes in the hydroclimate, even on short time scales. Current global climate models (GCMs) predict coarse-scale reductions in precipitation across the Caribbean prompting the need to investigate future fine-scale hydroclimate variability in the Luquillo Mountains. This research downscales coarse-resolution GCM RCP8.5 predictions from the IPCC CMIP5 project to the local scale to better assess future rainfall variability during the most critical period of the annual hydroclimate cycle, the early rainfall season (ERS). An artificial neural network (ANN) is developed using five field variables (1000-, 850-, 700-, and 500-hPa specific humidity and 1000-700-hPa bulk wind shear) and four derived precipitation forecasting parameters from the ERA-Interim reanalysis. During the historical period (1985-2016), the ANN predicts a binary dry (<5 mm) versus wet (≥5 mm) day outcome with 92% percent accuracy. When the historical inputs are replaced with bias-corrected data from four CMIP5 GCMs, the downscaled ensemble mean indicates a 7.2% increase in ERS dry-day frequency by mid-century (2041-2060), yielding an ERS dry-day percentage of 70% by mid-century. The results presented here show that the decrease in precipitation and wet-days is, at least in part, due to an increase in 1000-700 hPa bulk wind shear and a less favorable thermodynamic environment driven by increased mid-tropospheric warming and a stronger trade wind inversion. By regressing ERS total precipitation against dry-day frequency (R2 = 0.95), the predicted mid-century dry-day proportion corresponds to a ~200-mm decrease in seasonal precipitation. In contrast, the ensemble predicts a dry-day frequency recovery back towards the historical climatological mean by end-century (2081-2100).