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Abstract In the wake of climate change, extreme events such as heatwaves are considered to be key players in the terrestrial biosphere. In the past decades, the frequency and severity of heatwaves have risen substantially, and they are projected to continue to intensify in the future. One key question is therefore: how do changes in extreme heatwaves affect the carbon cycle? Although soil respiration (Rs) is the second largest contributor to the carbon cycle, the impacts of heatwaves on Rs have not been fully understood. Using a unique set of continuous high frequency in-situ measurements from our field site, we characterize the relationship between Rs and heatwaves. We further compare the Rs response to heatwaves across ten additional sites spanning the contiguous United States (CONUS). Applying a probabilistic framework, we conclude that during heatwaves Rs rates increase significantly, on average, by ~ 26% relative to that of non-heatwave conditions over the CONUS. Since previous in-situ observations have not measured the Rs response to heatwaves (e.g., rate, amount) at the high frequency that we present here, the terrestrial feedback to the carbon cycle may be underestimated without capturing these high frequency extreme heatwave events. 

Abstract Most previous studies of extreme temperatures have primarily focused on atmospheric temperatures. Using 18 years of the latest version of the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, we globally investigate the spatial patterns of hot and cold extremes as well as diurnal temperature range (DTR). We show that the world’s highest LST of 80.8 °C, observed in the Lut Desert in Iran and the Sonoran Desert in Mexico, is over ten degrees above the previous global record of 70.7 °C observed in 2005. The coldest place on Earth is Antarctica with the record low temperature of -110.9 °C. The world’s maximum DTR of 81.8 °C is observed in a desert environment in China. We see strong latitudinal patterns in hot and cold extremes as well as DTR. Biomes worldwide are faced with different levels of temperature extremes and DTR: we observe the highest zonal average maximum LST of 61.1 ± 5.3 °C in the deserts and xeric shrublands; the lowest zonal average minimum LST of -66.6 ± 14.8 °C in the Tundra; and the highest zonal average maximum DTR of 43.5 ± 9.9 °C in the montane grasslands and shrublands. This global exploration of extreme LST and DTR across different biomes sheds light on the type of extremes different ecosystems are faced with. 

Merging multiple data streams together can improve the overall length of record and achieve the number of observations required for robust statistical analysis. We merge complementary information from different data streams with a regression-based approach to estimate the 1 April snow water equivalent (SWE) volume over Sierra Nevada, USA. We more than double the length of available data-driven SWE volume records by leveragingin-situsnow depth observations from longer-length snow course records and SWE volumes from a shorter-length snow reanalysis. With the resulting data-driven merged time series (1940–2018), we conduct frequency analysis to estimate return periods and associated uncertainty, which can inform decisions about the water supply, drought response, and flood control. We show that the shorter (~30-year) reanalysis results in an underestimation of the 100-year return period by ~25 years (relative to the ~80-year merged dataset). Drought and flood risk and water resources planning can be substantially affected if return periods of SWE, which are closely related to potential flooding in spring and water availability in summer, are misrepresented.

 

Snow plays a fundamental role in global water resources, climate, and biogeochemical processes; however, no global snow drought assessments currently exist. Changes in the duration and intensity of droughts can significantly impact ecosystems, food and water security, agriculture, hydropower, and the socioeconomics of a region. We characterize the duration and intensity of snow droughts (snow water equivalent deficits) worldwide and differences in their distributions over 1980 to 2018. We find that snow droughts became more prevalent, intensified, and lengthened across the western United States (WUS). Eastern Russia, Europe, and the WUS emerged as hot spots for snow droughts, experiencing ∼2, 16, and 28% longer snow drought durations, respectively, in the latter half of 1980 to 2018. In this second half of the record, these regions exhibited a higher probability (relative to the first half of the record) of having a snow drought exceed the average intensity from the first period by 3, 4, and 15%. The Hindu Kush and Central Asia, extratropical Andes, greater Himalayas, and Patagonia, however, experienced decreases (percent changes) in the average snow drought duration (−4, −7, −8, and −16%, respectively). Although we do not attempt to separate natural and human influences with a detailed attribution analysis, we discuss some relevant physical processes (e.g., Arctic amplification and polar vortex movement) that likely contribute to observed changes in snow drought characteristics. We also demonstrate how our framework can facilitate drought monitoring and assessment by examining two snow deficits that posed large socioeconomic challenges in the WUS (2014/2015) and Afghanistan (2017/2018).

 

Climate change is expected to increase the scarcity and variability of fresh water supplies in some regions with important implications for irrigated agriculture. By allowing for increased flexibility in response to scarcity and by incentivizing the allocation of water to higher value use, markets can play an important role in limiting the economic losses associated with droughts. Using data on water demand, the seniority of water rights, county agricultural reports, high-resolution data on cropping patterns, and agronomic estimates of crop water requirements, we estimate the benefits of market-based allocations of surface water for California’s Central Valley. Specifically, we estimate the value of irrigation water and compare the agricultural costs of water shortages under the existing legal framework and under an alternate system that allows for trading of water. We find that a more efficient allocation of curtailments could reduce the costs of water shortages by as much as $362 million dollars per year or 4.4% of the net agricultural revenue in California in expectation, implying that institutional and market reform may offer important opportunities for adaptation.