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1. Diel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling does

   https://doi.org/10.5194/hess-26-3393-2022  

   Krogh, Sebastian A. ; Scaff, Lucia ; Kirchner, James W. ; Gordon, Beatrice ; Sterle, Gary ; Harpold, Adrian ( January 2022 , Hydrology and Earth System Sciences)

   Abstract. Climate warming will cause mountain snowpacks to melt earlier, reducing summer streamflow and threatening water supplies and ecosystems. Quantifying how sensitive streamflow timing is to climate change and where it is most sensitive remain key questions. Physically based hydrological models are often used for this purpose; however, they have embedded assumptions that translate into uncertain hydrological projections that need to be quantified and constrained to provide reliable inferences. The purpose of this study is to evaluate differences in projected end-of-century changes to streamflow timing between a new empirical model based on diel (daily) streamflow cycles and regional land surface simulations across the mountainous western USA. We develop an observational technique for detecting streamflow responses to snowmelt using diel cycles of incoming solar radiation and streamflow to detect when snowmelt occurs. We measure the date of the 20th percentile of snowmelt days (DOS20) across 31 western USA watersheds affected by snow, as a proxy for the beginning of snowmelt-initiated streamflow. Historic DOS20 varies from mid-January to late May among our sites, with warmer basins having earlier snowmelt-mediated streamflow. Mean annual DOS20 strongly correlates with the dates of 25 % and 50 % annual streamflow volume (DOQ25 and DOQ50, both R2=0.85), suggesting that a 1 d earlier DOS20more »corresponds with a 1 d earlier DOQ25 and 0.7 d earlier DOQ50. Empirical projections of future DOS20 based on a stepwise multiple linear regression across sites and years under the RCP8.5 scenario for the late 21st century show that DOS20 will occur on average 11±4 d earlier per 1 ∘C of warming. However, DOS20 in colder watersheds (mean November–February air temperature, TNDJF<-8 ∘C) is on average 70 % more sensitive to climate change than in warmer watersheds (TNDJF>0 ∘C). Moreover, empirical projections of DOQ25 and DOQ50 based on DOS20 are about four and two times more sensitive to climate change, respectively, than those simulated by a state-of-the-art land surface model (NoahMP-WRF) under the same scenario. Given the importance of changes in streamflow timing for water resources, and the significant discrepancies found in projected streamflow sensitivity, snowmelt detection methods such as DOS20 based on diel streamflow cycles may help to constrain model parameters, improve hydrological predictions, and inform process understanding.« less
2. Snow Phenology and Hydrologic Timing in the Yukon River Basin, AK, USA

   https://doi.org/10.3390/rs13122284  

   Pan, Caleb G. ; Kirchner, Peter B. ; Kimball, John S. ; Du, Jinyang ; Rawlins, Michael A. ( June 2021 , Remote Sensing)

   The Yukon River basin encompasses over 832,000 km2 of boreal Arctic Alaska and northwest Canada, providing a major transportation corridor and multiple natural resources to regional communities. The river seasonal hydrology is defined by a long winter frozen season and a snowmelt-driven spring flood pulse. Capabilities for accurate monitoring and forecasting of the annual spring freshet and river ice breakup (RIB) in the Yukon and other northern rivers is limited, but critical for understanding hydrologic processes related to snow, and for assessing flood-related risks to regional communities. We developed a regional snow phenology record using satellite passive microwave remote sensing to elucidate interactions between the timing of upland snowmelt and the downstream spring flood pulse and RIB in the Yukon. The seasonal snow metrics included annual Main Melt Onset Date (MMOD), Snowoff (SO) and Snowmelt Duration (SMD) derived from multifrequency (18.7 and 36.5 GHz) daily brightness temperatures and a physically-based Gradient Ratio Polarization (GRP) retrieval algorithm. The resulting snow phenology record extends over a 29-year period (1988–2016) with 6.25 km grid resolution. The MMOD retrievals showed good agreement with similar snow metrics derived from in situ weather station measurements of snowpack water equivalence (r = 0.48, bias = −3.63 days)more »and surface air temperatures (r = 0.69, bias = 1 day). The MMOD and SO impact on the spring freshet was investigated by comparing areal quantiles of the remotely sensed snow metrics with measured streamflow quantiles over selected sub-basins. The SO 50% quantile showed the strongest (p < 0.1) correspondence with the measured spring flood pulse at Stevens Village (r = 0.71) and Pilot (r = 0.63) river gaging stations, representing two major Yukon sub-basins. MMOD quantiles indicating 20% and 50% of a catchment under active snowmelt corresponded favorably with downstream RIB (r = 0.61) from 19 river observation stations spanning a range of Yukon sub-basins; these results also revealed a 14–27 day lag between MMOD and subsequent RIB. Together, the satellite based MMOD and SO metrics show potential value for regional monitoring and forecasting of the spring flood pulse and RIB timing in the Yukon and other boreal Arctic basins.« less
3. Cloud cover and delayed herbivory relative to timing of spring onset interact to dampen climate change impacts on net ecosystem exchange in a coastal Alaskan wetland

   https://doi.org/10.1088/1748-9326/ab1c91  

   Leffler, A. Joshua ; Beard, Karen H. ; Kelsey, Katharine C. ; Choi, Ryan T. ; Schmutz, Joel A. ; Welker, Jeffrey M. ( August 2019 , Environmental Research Letters)

   Rapid warming in northern ecosystems over the past four decades has resulted in earlier spring, increased precipitation, and altered timing of plant–animal interactions, such as herbivory. Advanced spring phenology can lead to longer growing seasons and increased carbon (C) uptake. Greater precipitation coincides with greater cloud cover possibly suppressing photosynthesis. Timing of herbivory relative to spring phenology influences plant biomass. None of these changes are mutually exclusive and their interactions could lead to unexpected consequences for Arctic ecosystem function. We examined the influence of advanced spring phenology, cloud cover, and timing of grazing on C exchange in the Yukon–Kuskokwim Delta of western Alaska for three years. We combined advancement of the growing season using passive-warming open-top chambers (OTC) with controlled timing of goose grazing (early, typical, and late season) and removal of grazing. We also monitored natural variation in incident sunlight to examine the C exchange consequences of these interacting forcings. We monitored net ecosystem exchange of C (NEE) hourly using an autochamber system. Data were used to construct daily light curves for each experimental plot and sunlight data coupled with a clear-sky model was used to quantify daily and seasonal NEE over a range of incident sunlight conditions.more »Cloudy days resulted in the largest suppression of NEE, reducing C uptake by approximately 2 g C m⁻²d⁻¹regardless of the timing of the season or timing of grazing. Delaying grazing enhanced C uptake by approximately 3 g C m⁻²d⁻¹. Advancing spring phenology reduced C uptake by approximately 1.5 g C m⁻²d⁻¹, but only when plots were directly warmed by the OTCs; spring advancement did not have a long-term influence on NEE. Consequently, the two strongest drivers of NEE, cloud cover and grazing, can have opposing effects and thus future growing season NEE will depend on the magnitude of change in timing of grazing and incident sunlight.

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4. Limits on phenological response to high temperature in the Arctic

   https://doi.org/10.1038/s41598-022-26955-9  

   Elmendorf, Sarah C. ; Hollister, Robert D. ( December 2023 , Scientific Reports)

   Abstract Tundra plants are widely considered to be constrained by cool growing conditions and short growing seasons. Furthermore, phenological development is generally predicted by daily heat sums calculated as growing degree days. Analyzing over a decade of seasonal flower counts of 23 plant species distributed across four plant communities, together with hourly canopy-temperature records, we show that the timing of flowering of many tundra plants are best predicted by a modified growing degree day model with a maximum temperature threshold. Threshold maximums are commonly employed in agriculture, but until recently have not been considered for natural ecosystems and to our knowledge have not been used for tundra plants. Estimated maximum temperature thresholds were found to be within the range of daily temperatures commonly experienced for many species, particularly for plants at the colder, high Arctic study site. These findings provide an explanation for why passive experimental warming—where moderate changes in mean daily temperatures are accompanied by larger changes in daily maximum temperatures—generally shifts plant phenology less than ambient warming. Our results also suggest that many plants adapted to extreme cold environments may have limits to their thermal responsiveness.
5. Pervasive alterations to snow-dominated ecosystem functions under climate change

   https://doi.org/10.1073/pnas.2202393119  

   Wieder, William R. ; Kennedy, Daniel ; Lehner, Flavio ; Musselman, Keith N. ; Rodgers, Keith B. ; Rosenbloom, Nan ; Simpson, Isla R. ; Yamaguchi, Ryohei ( July 2022 , Proceedings of the National Academy of Sciences)

   Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annualmore »runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.« less