We continue to hear end of snow predictions like this (click here)…
“A warming planet has major ramifications on winter snowpack across the globe, including a long-term drying trend for many. That’s a concern for winter sports enthusiasts and communities that depend on snow throughout the year.”
Year-to-year variability is no cause for alarm.
“Up to 2 inches of snow had fallen by 8:20 a.m. CST, Thursday, in Kalamazoo, Michigan, which was enough to coat sidewalks and roads in a slick layer of snow and make for a messy morning commute. Parked cars had to be scraped clean of a thick layer of snow that had accumulated over them. By the time the final snow amount for Thursday is tallied, the daily snowfall record for Feb. 6, which currently stands at 4 inches set back in 1914, could be broken. “ click here
Udit Bhatia & Auroop Ratan Ganguly. Precipitation extremes and depth-duration-frequency under internal climate variability, Scientific Report, volume 9, 9112, 2019.
Natural climate variability, captured through multiple initial condition ensembles, may be comparable to the variability caused by knowledge gaps in future emissions trajectories and in the physical science basis, especially at adaptation-relevant scales and projection horizons. The relations to chaos theory, including sensitivity to initial conditions, have caused the resulting variability in projections to be viewed as the irreducible uncertainty component of climate. The multiplier effect of ensembles from emissions-trajectories, multiple-models and initial-conditions contribute to the challenge. We show that ignoring this variability results in underestimation of precipitation extremes return periods leading to maladaptation. However, we show that concatenating initial-condition ensembles results in reduction of hydroclimate uncertainty. We show how this reduced uncertainty in precipitation extremes percolates to adaptation-relevant-Depth-Duration Frequency curves. Hence, generation of additional initial condition ensembles therefore no longer needs to be viewed as an uncertainty explosion problem but as a solution that can lead to uncertainty reduction in assessment of extremes.
Conor Murphy, Robert L. Wilby, Tom, K.R. Matthews, Peter Thorne, Ciaran Broderick, Rowan Fealy, Julia Hall, Shaun Harrigan, Phil Jones, Gerard McCarthy, Neil Macdonald. Multi‐century trends to wetter winters and drier summers in the England and Wales precipitation series explained by observational and sampling bias in early records. International Journal of Climatology, https://doi.org/10.1002/joc.6208
Globally, few precipitation records extend to the 18th Century. The England Wales Precipitation (EWP) series is a notable exception with continuous monthly records from 1766. EWP has found widespread use across diverse fields of research including trend detection, evaluation of climate model simulations, as a proxy for mid‐latitude atmospheric circulation, a predictor in long‐term European gridded precipitation datasets, the assessment of drought and extremes, tree‐ring reconstructions and as a benchmark for other regional series. A key finding from EWP has been the multi‐centennial trends towards wetter winters and drier summers. We statistically reconstruct seasonal EWP using independent, quality‐assured temperature, pressure and circulation indices. Using a sleet and snow series for the UK derived by Profs. Gordon Manley and Elizabeth Shaw to examine winter reconstructions, we show that precipitation totals for pre‐1870 winters are likely biased low due to gauge under‐catch of snowfall and a higher incidence of snowfall during this period. When these factors are accounted for in our reconstructions, the observed trend to wetter winters in EWP is no longer evident. For summer, we find that pre‐1820 precipitation totals are too high, likely due to decreasing network density and less certain data at key stations. A significant trend to drier summers is not robustly present in our reconstructions of the EWP series. While our findings are more certain for winter than summer, we highlight i) that extreme caution should be exercised when using EWP to make inferences about multi‐centennial trends, and; ii) that assessments of 18th and 19th Century winter precipitation should be aware of potential snow biases in early records. Our findings underline the importance of continual re‐appraisal of established long‐term climate datasets as new evidence becomes available. It is also likely that the identified biases in winter EWP have distorted many other long‐term European precipitation series.
“Sixty-nine percent of the US has averaged below normal temperature this year, with thirty-four percent more than two degrees below normal.” click here
“We aren’t the first scientists to confirm this trend,” says Dr. Tobias Scharnweber, one of the authors of the article. “However, what is new in our reconstruction is that we were able to calculate these growth rates using our own data method that we had developed especially for this project. This enabled us to show that average summer rainfall amounts were much lower at the time of the Mediaeval Climate Optimum, i.e. approximately 1000 years ago, than previously presumed. Maybe ‘one-in-a-century’ summers, like the one we had in 2018, were not that rare back then.” click here
Tobias Scharnweber, Karl-Uwe Heußner, Marko Smiljanic, Ingo Heinrich, Marieke van der Maaten-Theunissen, Ernst van der Maaten, Thomas Struwe, Allan Buras & Martin Wilmking . Removing the no-analogue bias in modern accelerated tree growth leads to stronger medieval drought. Scientific Reports, volume 9, Article number: 2509 (2019).
In many parts of the world, especially in the temperate regions of Europe and North-America, accelerated tree growth rates have been observed over the last decades. This widespread phenomenon is presumably caused by a combination of factors like atmospheric fertilization or changes in forest structure and/or management. If not properly acknowledged in the calibration of tree-ring based climate reconstructions, considerable bias concerning amplitudes and trends of reconstructed climatic parameters might emerge or low frequency information is lost. Here we present a simple but effective, data-driven approach to remove the recent non-climatic growth increase in tree-ring data. Accounting for the no-analogue calibration problem, a new hydroclimatic reconstruction for northern-central Europe revealed considerably drier conditions during the medieval climate anomaly (MCA) compared with standard reconstruction methods and other existing reconstructions. This demonstrates the necessity to account for fertilization effects in modern tree-ring data from affected regions before calibrating reconstruction models, to avoid biased results.
“As we can see, there has been no trend over the past 30 years. Variability also appears unchanged. California has always been a state characterized by alternating periods of drought and rainfall influenced by oceanic cycles like ENSO. The data show everything is within the normal range.” click here