Recent mass livestock mortality, known as dzud, have called into question
the sustainability of pastoral nomadic herding, the cornerstone of
Mongolian culture. A total of 20 million head of livestock perished in the
mortality events of 2000-2002, and 2009-2010. We examine mortality in 21
Mongolian aimags (provinces) between 1955-2013 to explain its density
independent cause(s) related to climate variability. We show that
livestock mortality is most strongly linked to winter (November-February)
temperatures. Additionally, we find prior summer (July-September) drought
and precipitation deficit to be an important trigger for mortality that
intensifies the effect of upcoming winter temperatures. Our density
independent mortality model explains 48.4% of the total variability in the
mortality dataset.

Volcanic eruptions have global climate impacts, but their effect on the
hydrologic cycle is poorly understood. We use a modified version of
superposed epoch analysis, an eruption year list collated from multiple
datasets, and seasonal paleoclimate reconstructions (soil moisture,
precipitation, and temperature) to investigate volcanic forcing of spring
and summer hydroclimate over Europe and the Mediterranean over the last
millennium. In the western Mediterranean, wet conditions occur in the
eruption year and the following 3 years. Conversely, northwestern Europe
and the British Isles experience dry conditions in response to volcanic
eruptions, with the largest moisture deficits in post-eruption years 2 and
3. The precipitation response strongly resembles the negative phase of the
East Atlantic Pattern. Modulated through this mode of climate variability,
eruptions force significant, widespread, and heterogeneous hydroclimate
responses across regions of Europe with diverse precipitation
seasonalities.

We present a tree-ring reconstruction of Upper Indus River watershed flow
using hierarchical Bayesian regression (HBR). One distinct advantage of
HBR is that we can use partial pooling of information across multiple
streamflow gauges allowing us to reconstruct streamflow across a watershed
network (seven gauges), including at stations where streamflow records are
too short to reconstruct using traditional methods. We do this by
explicitly modelling the covariance structure of streamflow residuals and
regression coefficients across different gauges. Additionally, using
Bayesian methods we can develop reconstructions for gauge records with
missing data, which may be interspersed through the length of the record.
Consistent with a prior study we find that current flows since the 1980s
are higher than average for past five centuries, but may be comparable to
streamflow during the mid 1500s and late 1600s.