Uncertainty in recurrence rates of large magnitude events due to short historic catalogs

Seismic hazard analysis requires knowledge of the recurrence rates of large magnitude earthquakes that drive the hazard at low probabilities of interest for seismic design. Earthquake recurrence is usually determined through studies of the historic earthquake catalogue for a given region. Reliable historic catalogues generally span time periods of 100–200 years in North America, while large magnitude events (M?≥?7) have recurrence rates on the order of hundreds or thousands of years in many areas, resulting in large uncertainty in recurrence rates for large events. Using Monte Carlo techniques and assuming typical recurrence parameters, we simulate earthquake catalogues that span long periods of time. We then split these catalogues into smaller catalogues spanning 100–200 years that mimic the length of historic catalogues. For each of these simulated “historic” catalogues, a recurrence rate for large magnitude events is determined. By comparing recurrence rates from one historic-length catalogue to another, we quantify the uncertainty associated with determining recurrence rates from short historic catalogues. The use of simulations to explore the uncertainty (rather than analytical solutions) allows us flexibility to consider issues such as the relative contributions of aleatory versus epistemic uncertainty, and the influence of fitting method, as well as lending insight into extreme-event statistics. The uncertainty in recurrence rates of large (M?>?7) events is about a factor of two in regions of high seismicity, due to the shortness of historic catalogues. This uncertainty increases greatly with decreasing seismic activity. Uncertainty is dependent on the length of the catalogue as well as the fitting method used (least squares vs. maximum likelihood). Examination of 90th percentile recurrence rates reveals that epistemic uncertainty in the true parameters may cause recurrence rates determined from historic catalogues to be uncertain by a factor greater than 50.     

Regional Temperature Forecast for the Next Day in Hong Kong

For a century or so, the Hong Kong Observatory (HKO) has been providing temperature forecast for the whole of Hong Kong with the HKO Headquarters as the reference location. In recent decades, due to spreading of population from the main urban center to satellite towns, there is an increasing demand for regional temperature forecasts. To support such provision, the HKO has developed a regression model to provide objective guidance to forecasters in formulating forecasts of maximum and minimum temperatures for the next day at various locations in Hong Kong. In this paper, the regression model is presented, together with the assessment of its performance. Based on the verification of one year of forecasts, it is found that the root mean square errors (RMSEs) of maximum (minimum) temperature forecasts are from about 1.3 to 2.1 (1.1 to 1.4) degrees, respectively. The regression model is shown to have generally out-performed the operational regional spectral model then operated by HKO. Regional temperature forecast methods of other meteorological or research centers are also surveyed. Equipped with the regression model, the HKO has launched an online regional temperature forecast service for the next day in Hong Kong since March 2008.     

Quantifying Organization of Atmospheric Turbulent Eddy Motion Using Nonlinear Time Series Analysis

Using three methods from nonlinear dynamics, we contrast the level of organization inthe vertical wind velocity (w) time series collected in the atmospheric surface layer(ASL) and the canopy sublayer (CSL) for a wide range of atmospheric stability ()conditions. The nonlinear methods applied include a modified Shannon entropy, waveletthresholding, and mutual information content. Time series measurements collected overa pine forest, a hardwood forest, a grass-covered forest clearing, and a bare soil, desertsurface were used for this purpose. The results from applying all three nonlinear timeseries measures suggest that w in the CSL is more organized than that in the ASL, and that as the flows in both layers evolve from near-neutral to near-convective conditions, the level of organization increases. Furthermore, we found that the degree of organization in w associated with changes in is more significant than the transition from CSL to ASL.     

Trends in Canadian Short‐Duration Extreme Rainfall: Including an Intensity–Duration–Frequency Perspective

Short-duration (5 minutes to 24 hours) rainfall extremes are important for a number of purposes, including engineering infrastructure design, because they represent the different meteorological scales of extreme rainfall events. Both single location and regional analyses of the changes in short-duration extreme rainfall amounts across Canada, as observed by tipping bucket rain gauges from 1965 to 2005, are presented. The single station analysis shows a general lack of a detectable trend signal, at the 5% significance level, because of the large variability and the relatively short period of record of the extreme short-duration rainfall amounts. The single station 30-minute to 24-hour durations show that, on average, 4% of the total number of stations have statistically significant increasing amounts of rainfall, whereas 1.6% of the cases have significantly decreasing amounts. However, regional spatial patterns are apparent in the single station trend results. Thus, for the same durations regional trends are presented by grouping the single station trend statistics across Canada. This regional trend analysis shows that at least two-thirds of the regions across Canada have increasing trends in extreme rainfall amounts, with up to 33% being significant (depending on location and duration). Both the southwest and the east (Newfoundland) coastal regions generally show significant increasing regional trends for 1- and 2-hour extreme rainfall durations. For the shortest durations of 5–15 minutes, the general overall regional trends in the extreme amounts are more variable, with increasing and decreasing trends occurring with similar frequency; however, there is no evidence of statistically significant decreasing regional trends in extreme rainfall amounts. The decreasing regional trends for the 5- to 15-minute duration amounts tend to be located in the St. Lawrence region of southern Quebec and in the Atlantic provinces. Additional analysis using criteria specified for traditional water management practice (e.g., Intensity-Duration-Frequency (IDF)) shows that fewer than 5.6% and 3.4% of the stations have significant increasing and decreasing trends, respectively, in extreme annual maximum single location observation amounts. This indicates that at most locations across Canada the traditional single station IDF assumption that historical extreme rainfall observations are stationary (in terms of the mean) over the period of record for an individual station is not violated. However, the trend information is still useful complementary information that can be considered for water management purposes, especially in terms of regional analysis.     

Learning from CDM SD tool experience for Article 6.4 of the Paris Agreement

The Paris Agreement (PA) emphasizes the intrinsic relationship between climate change and sustainable development (SD) and welcomes the 2030 agenda for the global Sustainable Development Goals (SDGs). Yet, there is a lack of assessment approaches to ensure that climate and development goals are achieved in an integrated fashion and trade-offs avoided. Article 6.4 of the PA introduces a new Sustainable Mitigation Mechanism (SMM) with the dual aim to contribute to the mitigation of greenhouse gas emissions and foster SD. The Kyoto Protocol’s Clean Development Mechanism (CDM) has a similar objective and in 2014, the CDM SD tool was launched by the Executive Board of the CDM to highlight the SD benefits of CDM activities. This article analyses the usefulness of the CDM SD tool for stakeholders and compares the SD tool’s SD reporting requirements against other flexible mechanisms and multilateral standards to provide recommendations for improvement. A key conclusion is that the Paris Agreement’s SMM has a stronger political mandate than the CDM to measure that SD impacts are ‘real, measurable and long-term’. Recommendations for an improved CDM SD tool are a relevant starting point to develop rules, modalities, and procedures for SD assessment in Article 6.4 as well as for other cooperative mitigation approaches.

POLICY RELEVANCE

Research findings are relevant for developing the rulebook of modalities and procedures for Article 6.4 of the Paris Agreement, which introduces a new mechanism for mitigation of greenhouse gas emissions and sustainable development. Lessons learnt from the CDM SD tool and recommendations for enhanced SD assessment are discussed in context of Article 6 cooperative approaches, and make a timely contribution to inform negotiations on the rulebook agreed by the Conference of the Parties serving as the Meeting of the Parties to the Paris Agreement.     

Impact of stratospheric variability on tropospheric climate change

An improved stratospheric representation has been included in simulations with the Hadley Centre HadGEM1 coupled ocean atmosphere model with natural and anthropogenic forcings for the period 1979–2003. An improved stratospheric ozone dataset is employed that includes natural variations in ozone as well as the usual anthropogenic trends. In addition, in a second set of simulations the quasi biennial oscillation (QBO) of stratospheric equatorial zonal wind is also imposed using a relaxation towards ERA-40 zonal wind values. The resulting impact on tropospheric variability and trends is described. We show that the modelled cooling rate at the tropopause is enhanced by the improved ozone dataset and this improvement is even more marked when the QBO is also included. The same applies to warming trends in the upper tropical troposphere which are slightly reduced. Our stratospheric improvements produce a significant increase of internal variability but no change in the positive trend of annual mean global mean near-surface temperature. Warming rates are increased significantly over a large portion of the Arctic Ocean. The improved stratospheric representation, especially the QBO relaxation, causes a substantial reduction in near-surface temperature and precipitation response to the El Chichón eruption, especially in the tropical region. The winter increase in the phase of the northern annular mode observed in the aftermath of the two major recent volcanic eruptions is partly captured, especially after the El Chichón eruption. The positive trend in the southern annular mode (SAM) is increased and becomes statistically significant which demonstrates that the observed increase in the SAM is largely subject to internal variability in the stratosphere. The possible inclusion in simulations for future assessments of full ozone chemistry and a gravity wave scheme to internally generate a QBO is discussed.     

Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs

The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique.     

Effects of observed and experimental climate change on terrestrial ecosystems in northern Canada: results from the Canadian IPY program

Tundra and taiga ecosystems comprise nearly 40?% of the terrestrial landscapes of Canada. These permafrost ecosystems have supported humans for more than 4500?years, and are currently home to ca. 115,000 people, the majority of whom are First Nations, Inuit and Métis. The responses of these ecosystems to the regional warming over the past 30?C50?years were the focus of four Canadian IPY projects. Northern residents and researchers reported changes in climate and weather patterns and noted shifts in vegetation and other environmental variables. In forest-tundra areas tree growth and reproductive effort correlated with temperature, but seedling establishment was often hindered by other factors resulting in site-specific responses. Increased shrub cover has occurred in sites across the Arctic at the plot and landscape scale, and this was supported by results from experimental warming. Experimental warming increased vegetation cover and nutrient availability in most tundra soils; however, resistance to warming was also found. Soil microbial diversity in tundra was no different than in other biomes, although there were shifts in mycorrhizal diversity in warming experiments. All sites measured were sinks for carbon during the growing season, with expected seasonal and latitudinal patterns. Modeled responses of a mesic tundra system to climate change showed that the sink status will likely continue for the next 50?C100?years, after which these tundra systems will likely become a net source of carbon dioxide to the atmosphere. These IPY studies were the first comprehensive assessment of the state and change in Canadian northern terrestrial ecosystems and showed that the inherent variability in these systems is reflected in their site-specific responses to changes in climate. They also showed the importance of using local traditional knowledge and science, and provided extensive data sets, sites and researchers needed to study and manage the inevitable changes in the Canadian North.