Seven centuries of reconstructed Brahmaputra River discharge demonstrate underestimated high discharge and flood hazard frequency.

The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309-2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956-1986 C.E.) ranks amongst the driest of the past seven centuries (13th percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24-38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.

Drought timing and local climate determine the sensitivity of eastern temperate forests to drought.

Projected changes in temperature and drought regime are likely to reduce carbon (C) storage in forests, thereby amplifying rates of climate change. While such reductions are often presumed to be greatest in semi-arid forests that experience widespread tree mortality, the consequences of drought may also be important in temperate mesic forests of Eastern North America (ENA) if tree growth is significantly curtailed by drought. Investigations of the environmental conditions that determine drought sensitivity are critically needed to accurately predict ecosystem feedbacks to climate change. We matched site factors with the growth responses to drought of 10,753 trees across mesic forests of ENA, representing 24 species and 346 stands, to determine the broad-scale drivers of drought sensitivity for the dominant trees in ENA. Here we show that two factors-the timing of drought, and the atmospheric demand for water (i.e., local potential evapotranspiration; PET)-are stronger drivers of drought sensitivity than soil and stand characteristics. Drought-induced reductions in tree growth were greatest when the droughts occurred during early-season peaks in radial growth, especially for trees growing in the warmest, driest regions (i.e., highest PET). Further, mean species trait values (rooting depth and ψ50 ) were poor predictors of drought sensitivity, as intraspecific variation in sensitivity was equal to or greater than interspecific variation in 17 of 24 species. From a general circulation model ensemble, we find that future increases in early-season PET may exacerbate these effects, and potentially offset gains in C uptake and storage in ENA owing to other global change factors.

Investigating the causes of increased 20th-century fall precipitation over the southeastern United States.

Much of the eastern United States (US) experienced increased precipitation over the 20th century. Characterizing these trends and their causes is critical for assessing future hydroclimate risks. Here, US precipitation trends are analyzed during 1895-2016, revealing that fall precipitation in the southeastern region north of the Gulf of Mexico (SE-Gulf) increased by nearly 40%, primarily increasing after the mid-1900s. As fall is the climatological dry season in the SE-Gulf and precipitation in other seasons changed insignificantly, the seasonal precipitation cycle diminished substantially. The increase in SE-Gulf fall precipitation was caused by increased southerly moisture transport from the Gulf of Mexico, which was almost entirely driven by stronger winds associated with enhanced anticyclonic circulation west of the North Atlantic Subtropical High (NASH) and not by increases in specific humidity. Atmospheric models forced by observed SSTs and fully-coupled models forced by historical anthropogenic forcing do not robustly simulate 20th-century fall wetting in the SE-Gulf. SST-forced atmospheric models do simulate an intensified anticyclonic low-level circulation around the NASH, but the modeled intensification occurred farther west than observed. CMIP5 analyses suggest an increased likelihood of positive SE-Gulf fall precipitation trends given historical and future GHG forcing. Nevertheless, individual model simulations (both SST-forced and fully-coupled) only very rarely produce the observed magnitude of the SE-Gulf fall precipitation trend. Further research into model representation of the western ridge of the fall NASH is needed, which will help us better predict whether 20th-century increases in SE-Gulf fall precipitation will persist into the future.

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America.

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO2 in individual models.

The 2016 southeastern US drought: an extreme departure from centennial wetting and cooling.

The fall 2016 drought in the southeastern United States (SE US) appeared exceptional based on its widespread impacts, but the current monitoring framework that only extends from 1979-present does not readily facilitate evaluation of soil-moisture anomalies in a centennial context. A new method to extend monthly gridded soil-moisture estimates back to 1895 is developed, indicating that since 1895, October-November 2016 soil moisture (0-200 cm) in the SE US was likely the second lowest on record, behind 1954. This severe drought developed rapidly and was brought on by low September-November precipitation and record-high September-November daily maximum temperatures (Tmax). Record Tmax drove record-high atmospheric moisture demand, accounting for 28% of the October-November 2016 soil-moisture anomaly. Drought and heat in fall 2016 contrasted with 20th-century wetting and cooling in the region, but resembled conditions more common from 1895-1956. Dynamically, the exceptional drying in fall 2016 was driven by anomalous ridging over the central United States that reduced south-southwesterly moisture transports into the SE US by approximately 75%. These circulation anomalies were likely promoted by a moderate La Niña and warmth in the tropical Atlantic, but these processes accounted for very little of the SE US drying in fall 2016, implying a large role for internal atmospheric variability. The extended analysis back to 1895 indicates that SE US droughts as strong as the 2016 event are more likely than indicated from a shorter 60-year perspective, and continued multi-decadal swings in precipitation may combine with future warming to further enhance the likelihood of such events.

Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.