Evaluating Modeled Intra- to Multidecadal Climate Variability Using Running Mann–Whitney \u3cem\u3eZ\u3c/em\u3e Statistics

An analysis method previously used to detect observed intra- to multidecadal (IMD) climate regimes was adapted to compare observed and modeled IMD climate variations. Pending the availability of the more appropriate phase 5 Coupled Model Intercomparison Project (CMIP-5) simulations, the method is demonstrated using CMIP-3 model simulations. Although the CMIP-3 experimental design will almost certainly prevent these model runs from reproducing features of historical IMD climate variability, these simulations allow for the demonstration of the method and illustrate how the models and observations disagree. This method samples a time series’s data rankings over moving time windows, converts those ranking sets to a Mann–Whitney U statistic, and then normalizes the U statistic into a Z statistic. By detecting optimally significant IMD ranking regimes of arbitrary onset and varying duration, this process generates time series of Z values that are an adaptively low-passed and normalized transformation of the original time series. Principal component (PC) analysis of the Z series derived from observed annual temperatures at 92 U.S. grid locations during 1919–2008 shows two dominant modes: a PC1 mode with cool temperatures before the late 1960s and warm temperatures after the mid-1980s, and a PC2 mode indicating a multidecadal temperature cycle over the Southeast. Using a graphic analysis of a Z error metric that compares modeled and observed Z series, the three CMIP-3 model simulations tested here are shown to reproduce the PC1 mode but not the PC2 mode. By providing a way to compare grid-level IMD climate response patterns in observed and modeled data, this method can play a useful diagnostic role in future model development and decadal climate forecasting

Comparing the Model-simulated Global Warming Signal to Observations Using Empirical Estimates of Unforced Noise

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario’s forced signal, but is likely inconsistent with the steepest emission scenario’s forced signal

Approximate calculations of the net economic impact of global warming mitigation targets under heightened damage estimates

Efforts to mitigate global warming are often justified through calculations of the economic damages that may occur absent mitigation. The earliest such damage estimates were speculative mathematical representations, but some more recent studies provide empirical estimates of damages on economic growth that accumulate over time and result in larger damages than those estimated previously. These heightened damage estimates have been used to suggest that limiting global warming this century to 1.5 °C avoids tens of trillions of 2010 US$in damage to gross world product relative to limiting global warming to 2.0 °C. However, in order to estimate the net effect on gross world product, mitigation costs associated with decarbonizing the world\u27s energy systems must be subtracted from the benefits of avoided damages. Here, we follow previous work to parameterize the aforementioned heightened damage estimates into a schematic global climate-economy model (DICE) so that they can be weighed against mainstream estimates of mitigation costs in a unified framework. We investigate the net effect of mitigation on gross world product through finite time horizons under a spectrum of exogenously defined levels of mitigation stringency. We find that even under heightened damage estimates, the additional mitigation costs of limiting global warming to 1.5 °C (relative to 2.0 °C) are higher than the additional avoided damages this century under most parameter combinations considered. Specifically, using our central parameter values, limiting global warming to 1.5 °C results in a net loss of gross world product of roughly forty trillion US$ relative to 2 °C and achieving either 1.5 °C or 2.0 °C require a net sacrifice of gross world product, relative to a no-mitigation case, though 2100 with a 3%/ year discount rate. However, the benefits of more stringent mitigation accumulate over time and our calculations indicate that stabilizing warming at 1.5 °C or 2.0 °C by 2100 would eventually confer net benefits of thousands of trillions of US$ in gross world product by 2300. The results emphasize the temporal asymmetry between the costs of mitigation and benefits of avoided damages from climate change and thus the long timeframe for which climate change mitigation investment pays off

Empirical Prediction of Short-Term Annual Global Temperature Variability

Global mean surface air temperature (Tglobal) variability on subdecadal timescales can be of substantial magnitude relative to the long-term global warming signal, and such variability has been associated with considerable environmental and societal impacts. Therefore, probabilistic foreknowledge of short-term Tglobal evolution may be of value for anticipating and mitigating some course-resolution climate-related risks. Here we present a simple, empirically based methodology that utilizes only global spatial patterns of annual mean surface air temperature anomalies to predict subsequent annual Tglobal anomalies via partial least squares regression. The method\u27s skill is primarily achieved via information on the state of long-term global warming as well as the state and recent evolution of the El Niño–Southern Oscillation and the Interdecadal Pacific Oscillation. We test the out-of-sample skill of the methodology using cross validation and in a forecast mode where statistical predictions are made precisely as they would have been if the procedure had been operationalized starting in the year 2000. The average forecast errors for lead times of 1 to 4 years are smaller than naïve benchmarks on average, and they perform favorably relative to most dynamical Global Climate Models retrospectively initialized to the observed state of the climate system. Thus, this method can be used as a computationally efficient benchmark for dynamical model forecast systems

Meteorology and climatology of historical weekly wind and solar power resource droughts over western North America in ERA5

Wind and solar electricity generation is projected to expand substantially over the next several decades due both to rapid cost declines as well as regulation designed to achieve climate targets. With increasing reliance on wind and solar generation, future energy systems may be vulnerable to previously underappreciated synoptic-scale variations characterized by low wind and/or surface solar radiation. Here we use western North America as a case study region to investigate the historical meteorology of weekly-scale “droughts” in potential wind power, potential solar power and their compound occurrence. We also investigate the covariability between wind and solar droughts with potential stresses on energy demand due to temperature deviations away human comfort levels. We find that wind power drought weeks tend to occur in late summer and are characterized by a mid-level atmospheric ridge centered over British Columbia and high sea level pressure on the lee side of the Rockies. Solar power drought weeks tend to occur near winter solstice when the seasonal minimum in incoming solar radiation co-occurs with the tendency for mid-level troughs and low pressure systems over the U.S. southwest. Compound wind and solar power drought weeks consist of the aforementioned synoptic pattern associated with wind droughts occurring near winter solstice when the solar resource is at its seasonal minimum. We find that wind drought weeks are associated with high solar power (and vice versa) both seasonally and in terms of synoptic meteorology, which supports the notion that wind and solar power generation can play complementary roles in a diversified energy portfolio at synoptic spatiotemporal scales over western North America

Break-even year: A concept for understanding intergenerational trade-offs in climate change mitigation policy

Global climate change mitigation is often framed in public discussions as a tradeoff between environmental protection and harm to the economy. However, climate-economy models have consistently calculated that the immediate implementation of greenhouse gas emissions restriction (via e.g. a global carbon price) would be in humanity’s best interest on purely economic grounds. Despite this, the implementation of global climate policy has been notoriously difficult to achieve. This evokes an apparent paradox: if the implementation of a global carbon price is not only beneficial to the environment, but is also ‘economically optimal’, why has it been so difficult to enact?One potential reason for this difficulty is that economically optimal greenhouse gas emissions restrictions are not economically beneficial for the generation of people that launch them. The purpose of this article is to explore this issue by introducing the concept of the break-even year, which we define as the year when the economically optimal policy begins to produce global mean net economic benefits. We show that in a commonly used climate-economy model (DICE), the break-even year is relatively far into the future—around 2080 for mitigation policy beginning in the early 2020s. Notably, the break-even year is not sensitive to the uncertain magnitudes of the costs of climate change mitigation policy or the costs of economic damages from climate change. This result makes it explicit and understandable why an economically optimal policy can be difficult to implement in practice

The Self-Taught Marketers Guide to Creating an Annual Report

Objective To produce an easy-to-read, visually appealing, 1-4 page annual report for the University of Maryland, Baltimore’s Health Sciences and Human Services Library (HSHSL). The report should be a mix of interesting statistics, highlights, stories, quotes, and photographs to promote the HSHSL’s annual accomplishments to the campus. Methods We gather all of the stories and statistics we think will be eligible material for the annual report, pulling content and ideas from: newsletters, workshops, blog posts, events, exhibits, and meetings with division and department heads. An annual report committee and visual designer decide upon the top stories and statistics, focusing upon high-impact events, meaningful statistics, and attractive design, images, and photographs to craft the report. We keep in mind that the report is meant to be read by non-librarians, and that the language and messages need to be understandable to our larger campus community.Results This will be our 5th year producing an annual report for the HSHSL. The process has become more streamlined and less time-consuming as we have become familiar with where to source content, design principles, and how to manage space limitations. This has decreased the amount of time it takes to produce the report and the number of iterations we go through before achieving our final product. Additionally, other libraries have been inspired by our designs and created their own colorful Annual Reports based on our layouts and ideas. Conclusions In our next report we plan to include a survey link to try to elicit feedback from our readers. We would like to know if the report was useful to them and if there is other information they would be interested to see in future reports

Change in the magnitude and mechanisms of global temperature variability with warming

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modelling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual pre-industrial conditions may have only limited relevance for understanding the unforced GMST variability of the future

Complete Genomic Sequences of Three Salmonella enterica subsp. enterica Serovar Muenchen Strains from an Orchard in San Joaquin County, California.

We present here the complete genome sequences of three Salmonella enterica subsp. enterica serovar Muenchen strains, LG24, LG25, and LG26. All three strains were isolated from almond drupes grown in an orchard in San Joaquin County, California, in 2016. These genomic sequences are nonidentical and will contribute to our understanding of S. enterica genomics

Periodic optical variability and debris accretion in white dwarfs: a test for a causal connection

Recent Kepler photometry has revealed that about half of white dwarfs (WDs) have periodic, low-level (~ 1e-4 - 1e-3), optical variations. Hubble Space Telescope (HST) ultraviolet spectroscopy has shown that up to about one half of WDs are actively accreting rocky planetary debris, as evidenced by the presence of photospheric metal absorption lines. We have obtained HST ultraviolet spectra of seven WDs that have been monitored for periodic variations, to test the hypothesis that these two phenomena are causally connected, i.e. that the optical periodic modulation is caused by WD rotation coupled with an inhomogeneous surface distribution of accreted metals. We detect photospheric metals in four out of the seven WDs. However, we find no significant correspondence between the existence of optical periodic variability and the detection of photospheric ultraviolet absorption lines. Thus the null hypothesis stands, that the two phenomena are not directly related. Some other source of WD surface inhomogeneity, perhaps related to magnetic field strength, combined with the WD rotation, or alternatively effects due to close binary companions, may be behind the observed optical modulation. We report the marginal detection of molecular hydrogen in WD J1949+4734, only the fourth known WD with detected H_2 lines. We also re-classify J1926+4219 as a carbon-rich He-sdO subdwarf.Comment: MNRAS, in pres