Recent incidences of 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. To mitigate the effects of such events on the lives of herders, international agencies such as the World Bank are taking increasing interest in developing tailored market-based solutions like index-insurance. Their ultimate success depends on understanding the historical context and underlying causes of mortality. In this paper we examine mortality in 21 Mongolian aimags (provinces) between 1955 and 2013 in order 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, with incidences of mass mortality being most likely to occur because of an anomalously cold winter. Additionally, we find prior summer (July-September) drought and precipitation deficit to be important triggers for mortality that intensifies the effect of upcoming winter temperatures on livestock. Our density independent mortality model based on winter temperature, summer drought, summer precipitation, and summer potential evaporanspiration explains 48.4% of the total variability in the mortality dataset. The Mongolian index based livestock insurance program uses a threshold of 6% mortality to trigger payouts. We find that on average for Mongolia, the probability of exceedance of 6% mortality in any given year is 26% over the 59 year period between 1955 and 2013.
Semi-arid ecosystems play an important role in regulating global climate with the fate of these ecosystems in the Anthropocene depending upon interactions among temperature, precipitation, and CO 2. However, in cool-arid environments, precipitation is not the only limitation to forest productivity. Interactions between changes in precipitation and air temperature may enhance soil moisture stress while simultaneously extending growing season length, with unclear consequences for net carbon uptake. This study evaluates recent trends in productivity and phenology of Inner Asian forests (in Mongolia and Northern China) using satellite remote sensing, dendrochronology, and dynamic global vegetation model (DGVM) simulations to quantify the sensitivity of forest dynamics to decadal climate variability and trends. Trends in photosynthetically active radiation fraction (FPAR) between 1982 and 2010 show a greening of about 7% of the region in spring (March, April, May), and 3% of the area 'browning' during summertime (June, July, August). These satellite observations of FPAR are corroborated by trends in NPP simulated by the LPJ DGVM. Spring greening trends in FPAR are mainly explained by long-term trends in precipitation whereas summer browning trends are correlated with decreasing precipitation. Tree ring data from 25 sites confirm annual growth increments are mainly limited by summer precipitation (June, July, August) in Mongolia, and spring precipitation in northern China (March, April, May), with relatively weak prioryear lag effects. An ensemble of climate projections from the IPCC CMIP3 models indicates that warming temperatures (spring, summer) are expected to be associated with higher summer precipitation, which combined with CO 2 causes large increases in NPP and possibly even greater forest cover in the Mongolian steppe. In the absence of a strong direct CO 2 fertilization effect on plant growth (e.g., due to nutrient limitation), water stress or decreased carbon gain from higher autotrophic respiration results in decreased productivity and loss of forest cover. The fate of these semi-arid ecosystems thus appears to hinge upon the magnitude and subtleties of CO 2 fertilization effects, for which experimental observations in arid systems are needed to test and refine vegetation models.
Mongolian tree rings indicate that recent moisture extremes, although unusual, are not unprecedented in the last 2060 years.
Warming over Mongolia and adjacent Central Asia has been unusually rapid over the past few decades, 19particularly in the summer, with surface temperature anomalies higher than for much of the globe. With few 20 temperature station records available in this remote region prior to the 1950s, paleoclimatic data must be used to 21 understand annual-to-centennial scale climate variability, to local response to large-scale forcing mechanisms, and
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 data sets, and seasonal paleoclimate reconstructions (soil moisture, precipitation, geopotential heights, 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 posteruption years 2 and 3. The precipitation response occurs primarily in late spring and early summer (April–July), a pattern that strongly resembles the negative phase of the East Atlantic Pattern. Modulated by this mode of climate variability, eruptions force significant, widespread, and heterogeneous hydroclimate responses across Europe and the Mediterranean.
Key Points Significantly spatially and temporally improved streamflow reconstruction Greater variability captured then in the original reconstruction Drought conditions seen over the past decade may be return to normal conditions
Abstract. Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations. We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.
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