Rechercher

Abstract Bulk microphysics parameterizations that are used to represent clouds and precipitation usually allow only solid and liquid hydrometeors. Predicting the bulk liquid fraction on ice allows an explicit representation of mixed-phase particles and various precipitation types, such as wet snow and ice pellets. In this paper, an approach for the representation of the bulk liquid fraction into the predicted particle properties (P3) microphysics scheme is proposed and described. Solid-phase microphysical processes, such as melting and sublimation, have been modified to account for the liquid component. New processes, such as refreezing and condensation of the liquid portion of mixed-phase particles, have been added to the parameterization. Idealized simulations using a one-dimensional framework illustrate the overall behavior of the modified scheme. The proposed approach compares well to a Lagrangian benchmark model. Temperatures required for populations of ice crystals to melt completely also agree well with previous studies. The new processes of refreezing and condensation impact both the surface precipitation type and feedback between the temperature and the phase changes. Overall, prediction of the bulk liquid fraction allows an explicit description of new precipitation types, such as wet snow and ice pellets, and improves the representation of hydrometeor properties when the temperature is near 0°C.

Abstract We develop a portfolio credit risk model that includes firm‐specific Markov‐switching regimes as well as individual stochastic and endogenous recovery rates. Using weekly credit default swap premiums for 35 financial firms, we analyze the credit risk of each of these companies and their statistical linkages, putting emphasis on the 2005–2012 period. Moreover, we study the systemic risk affecting both the banking and insurance subsectors.

Climate change in the current geological era, from approximately 11,000 years ago to the present

Abstract Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe‐Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon‐use efficiency (CUE), vegetation C turnover time ( τ veg ), leaf C fraction (F leaf ), specific leaf area (SLA), and leaf area index (LAI)‐level photosynthesis (P LAI ), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τ veg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. These results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems. , Key Points A GPP‐traceability framework is established to diagnose the uncertainty sources of modeled GPP Large intermodel differences of modeled GPP result from their different representation of vegetation functional properties Positive bias in simulated GPP over the East Asian monsoon region could be attributed to the higher simulated CUE and SLA comparing with observations

Abstract During the last glacial period, climate conditions in the North Atlantic region were determined by the alternation of relatively warm interstadials and relatively cool stadials, with superimposed rapid warming (Dansgaard‐Oeschger) and cooling (Heinrich) events. So far little is known about the impact of these rapid climate shifts on the seasonal variations in sea surface temperature (SST) within the North Atlantic region. Here, we present a high‐resolution seasonal SST record for the past 152 kyrs derived from Integrated Ocean Drilling Program “Shackleton” Site U1385, offshore Portugal. Assemblage counts of dinoflagellates cysts (dinocysts) in combination with a modern analog technique (MAT), and regression analyses were used for the reconstructions. We compare our records with previously published SST records from the same location obtained from the application of MAT on planktonic foraminifera. Our dinocyst‐based reconstructions confirm the impression of the Greenland stadials and interstadials offshore the Portuguese margin and indicate increased seasonal contrast of temperature during the cold periods of the glacial cycle (average 9.0 °C, maximum 12.2 °C) with respect to present day (5.1 °C), due to strong winter cooling by up to 8.3 °C. Our seasonal temperature reconstructions are in line with previously published data, which showed increased seasonality due to strong winter cooling during the Younger Dryas and the Last Glacial Maximum over the European continent and North Atlantic region. In addition, we show that over longer time scales, increased seasonal contrasts of temperature remained characteristic of the colder phases of the glacial cycle. , Key Points New high‐resolution dinocyst‐based summer and winter SST record from IODP “Shackleton” Site U1385 for the last 150 kyrs is presented Dinocyst‐based SST confirms the D‐O cycles and HEs at Site U1385 Increased seasonal contrast of SST (up to 12 degree C) during cold periods of the glacial cycle related to strong winter cooling is shown

Abstract Climate change can cause negative impacts to the agricultural sector by increasing pest damage to crops. The European corn borer (ECB) is a major insect pest of corn in North America. Its speed of development could potentially accelerate under a warmer climate, leading to an earlier development of the first generation and an increase in the number of generations per year. The main objective of this study was to assess the potential impacts of climate change on ECB management for the future period 2041–2070 in Quebec, Canada, using bioclimatic modelling and climate analogues. First flight of ECB moths could occur about 15 days earlier in the season in 2041–2070 compared to the reference period 1970–1999. The window for insecticide interventions may be reduced under climate change by 15.6% to 27.8% for univoltine ECB and by 13.8% to 52.7% for bivoltine ECB. Climate change could promote the development of an additional generation in the southern region for both races, considering temperature increases and factors inducing the overwintering diapause. ECB management could become more costly both economically and environmentally under the future climate, and it should be revised according to the results of this study.

We compare ensemble mean daily precipitation and near‐surface temperatures from regional climate model simulations over seven Coordinated Regional Climate Downscaling Experiment domains for the winter and summer seasons. We use Taylor diagrams to show the domain‐wide pattern similarity between the model ensemble and the observational data sets. We use the Climatic Research Unit (CRU) and the University of Delaware gridded observations and ERA‐Interim reanalysis data as an additional observationally based estimate of historical climatology. Taylor diagrams determine the relative skill of the seven sets of simulations and quantify these results in terms of center pattern root‐mean square error and correlation coefficient. Results suggest that there is good agreement between the models and the CRU, in terms of their respective seasonal cycles, as shown in Taylor diagrams and bias plots. There is also good agreement between both gridded observation sets. In addition, downscaled ERA‐Interim precipitation is closer to observations than raw ERA‐Interim precipitation. Domains located in the low latitudes and those having high topography appear to have larger biases, especially precipitation.