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The midlatitude poleward atmospheric energy transport increases in radiatively forced simulations of warmed climates across a range of models from comprehensive coupled general circulation models (GCMs) to idealized aquaplanet moist GCMs to diffusive moist energy balance models. These increases have been rationalized from two perspectives. The energetic (or radiative) perspective takes the atmospheric energy budget and decomposes energy flux changes (radiative forcing, feedbacks, or surface fluxes) to determine the energy transport changes required by the budget. The diffusive perspective takes the net effect of atmospheric macroturbulence to be a diffusive energy transport down-gradient, so transport changes can arise from changes in mean energy gradients or turbulent diffusivity. Here, we compare these perspectives in idealized moist, gray-radiation GCM simulations over a wide range of climates. The energetic perspective has a dominant role for radiative forcing in this GCM, with cancellation between the temperature feedback components that account for the GCM’s nonmonotonic energy transport changes in response to warming. Comprehensive CMIP5 simulations have similarities in the Northern Hemisphere to the idealized GCM, although a comprehensive GCM over several CO2 doublings has a distinctly different feedback evolution structure. The diffusive perspective requires a non-constant diffusivity to account for the idealized GCM-simulated changes, with important roles for the eddy velocity, dry static stability, and horizontal energy gradients. Beyond diagnostic analysis, GCM-independent a priori theories for components of the temperature feedback are presented that account for changes without knowledge of a perturbed climate state, suggesting that the energetic perspective is the more parsimonious one.

In recent decades, the Barents Sea has warmed more than twice as fast as the rest of the Arctic in winter, but the exact causes behind this amplified warming remain unclear. In this study, we quantify the wintertime Barents Sea warming (BSW, for near-surface air temperature) with an average linear trend of 1.74 °C decade −1 and an interdecadal change around 2003 based on a surface energy budget analysis using the ERA5 reanalysis dataset from 1979–2019. Our analysis suggests that the interdecadal change in the wintertime near-surface air temperature is dominated by enhanced clear-sky downward longwave radiation (CDLW) associated with increased total column water vapor. Furthermore, it is found that a mode of atmospheric variability over the North Atlantic region known as the Barents oscillation (BO) strongly contributed to the BSW with a stepwise jump in 2003. Since 2003, the BO turned into a strengthened and positive phase, characteristic of anomalous high pressure over the North Atlantic and South of the Barents Sea, which promoted two branches of heat and moisture transport from southern Greenland along the Norwegian Sea and from the Eurasian continent to the Barents Sea. This enhanced the water vapor convergence over the Barents Sea, resulting in BSW through enhanced CDLW. Our results highlight the atmospheric circulation related to the BO as an emerging driver of the wintertime BSW through enhanced meridional atmospheric heat and moisture transport over the North Atlantic Ocean.

Despite academic findings that performance information seldom is used in appropriations decisions, many professional organizations and governments continue to press for integrating performance information into local public management, planning, and budgeting processes. Is it possible to reconcile such inconsistencies? Looking beyond the executive— legislative relationship and departmental appropriations, the author examines the budget implications of applying performance information at the subdepartmental program level. Case analysis of Indianapolis's IndyStat initiative underscores that performance measurement application is positively related to intradepartmental program budget changes. Hence, performance-based budgeting (PBB) can improve local budgeting despite severe political constraints. Still, successful use of PBB requires strong executive leadership, and its effects remain less visible at the departmental level or within the wider political arena of legislative bargaining. The author concludes by recommending some rethinking of the current analytical focus of PBB both in future research as well as recommended practice.

Monitoring of canopy density with related metrics such as leaf area index (LAI) makes a significant contribution to understanding and predicting processes in the soil–plant–atmosphere system and to indicating crop health and potential yield for farm management. Remote sensing methods using optical sensors that rely on spectral reflectance to calculate LAI have become more mainstream due to easy entry and availability. Methods with vegetation indices (VI) based on multispectral reflectance data essentially measure the green area index (GAI) or response to chlorophyll content of the canopy surface and not the entire aboveground biomass that may be present from non-green elements that are key to fully assessing the carbon budget. Methods with light detection and ranging (LiDAR) have started to emerge using gap fraction (GF) to estimate the plant area index (PAI) based on canopy density. These LiDAR methods have the main advantage of being sensitive to both green and non-green plant elements. They have primarily been applied to forest cover with manned airborne LiDAR systems (ALS) and have yet to be used extensively with crops such as winter wheat using LiDAR on unmanned aircraft systems (UAS). This study contributes to a better understanding of the potential of LiDAR as a tool to estimate canopy structure in precision farming. The LiDAR method proved to have a high to moderate correlation in spatial variation to the multispectral method. The LiDAR-derived PAI values closely resemble the SunScan Ceptometer GAI ground measurements taken early in the growing season before major stages of senescence. Later in the growing season, when the canopy density was at its highest, a possible overestimation may have occurred. This was most likely due to the chosen flight parameters not providing the best depictions of canopy density with consideration of the LiDAR’s perspective, as the ground-based destructive measurements provided lower values of PAI. Additionally, a distinction between total LiDAR-derived PAI, multispectral-derived GAI, and brown area index (BAI) is made to show how the active and passive optical sensor methods used in this study can complement each other throughout the growing season.

Governments often use multiple policy instruments for pursuing policy goals with mutually reinforcing effects. These effects include supplementation and substitution. This article examines both effects by studying two instruments of state budget stabilization policy: general fund balances and budget stabilization funds. States normally maintain budget surpluses in the general fund. In recent decades, many also created separate budget stabilization funds to guard against economic downturns. Empirical results show that substitution occurs between these instruments. In other words, the influence of the first instrument is partially offset by the second. The second instrument also produces some independent impacts—called supplementation—that increase the overall influence of both instruments. Such selfreinforcement decreases over time, suggesting that multiple policy instruments are most effective in the initial stage of application.

Arctic ecosystems are particularly vulnerable to climate change because of Arctic amplification. Here, we assessed the climatic impacts of low-end, 1.5 °C, and 2.0 °C global temperature increases above pre-industrial levels, on the warming of terrestrial ecosystems in northern high latitudes (NHL, above 60 °N including pan-Arctic tundra and boreal forests) under the framework of the Inter-Sectoral Impact Model Intercomparison Project phase 2b protocol. We analyzed the simulated changes of net primary productivity, vegetation biomass, and soil carbon stocks of eight ecosystem models that were forced by the projections of four global climate models and two atmospheric greenhouse gas pathways (RCP2.6 and RCP6.0). Our results showed that considerable impacts on ecosystem carbon budgets, particularly primary productivity and vegetation biomass, are very likely to occur in the NHL areas. The models agreed on increases in primary productivity and biomass accumulation, despite considerable inter-model and inter-scenario differences in the magnitudes of the responses. The inter-model variability highlighted the inadequacies of the present models, which fail to consider important components such as permafrost and wildfire. The simulated impacts were attributable primarily to the rapid temperature increases in the NHL and the greater sensitivity of northern vegetation to warming, which contrasted with the less pronounced responses of soil carbon stocks. The simulated increases of vegetation biomass by 30-60 Pg C in this century have implications for climate policy such as the Paris Agreement. Comparison between the results at two warming levels showed the effectiveness of emission reductions in ameliorating the impacts and revealed unavoidable impacts for which adaptation options are urgently needed in the NHL ecosystems.

Li, Y. and Li, Q., 2020. The application of BIM technology in budget control of port construction cost. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 644–648. Coconut Creek (Florida), ISSN 0749-0208. In order to fully alleviate the practical economic pressure of port construction projects and establish a relatively good cost control environment, a budget control method for port construction projects based on BIM technology is proposed. Taking the selected area as the target research scope, through the definition of representative cost engineering, the standardized port construction cost budget price information is collected, and then the budget item rate conditions supported by BIM technology is combined to calculate the budget control weight of port construction cost required for practical processing, the construction of the BIM technology-based port construction cost budget control method is completed. The experimental results show that after applying the engineering cost budget control method, the related attributes between the various budget control indicators in the port operation area of Z province have become clear, and the overall cost control effect is gradually approaching the ideal level.

Cloud Infrastructure as a Service (IaaS) has been known as a suitable platform for the execution of workflow applications. Quality of service (QoS) in such platforms is considered a challenging problem from both customers’ and service providers’ perspectives to perform workflow schedules. This paper proposes Budget Deadline Delicate Cloud (BDDC) and Budget Deadline Cloud (BDC) algorithms to consider both budget and deadline constraints for scheduling scientific workflows on cloud IaaS platforms. Methods for distribution of budget and deadlines under task leveling are proposed. Four metrics (success rate, time ratio, cost ratio, and utilization rate) are utilized to evaluate the proposed algorithms’ performance. Results of our proposed algorithms are compared with the BDHEFT, DBCS, and BDSD algorithms under various scenarios. Simulation results demonstrate that BDDC outperforms other algorithms in achieving cheaper costs while earning a higher success rate and utilization rate, and BDC accomplishes higher success rates and faster makespan. The performance of the proposed methods is confirmed using a real cloud environment.