Centennial-scale climate change from decadally-paced explosive volcanism: a coupled sea ice-ocean mechanism

Northern Hemisphere summer cooling through the Holocene is largely driven by the steady decrease in summer insolation tied to the precession of the equinoxes. However, centennial-scale climate departures, such as the Little Ice Age, must be caused by other forcings, most likely explosive volcanism and changes in solar irradiance. Stratospheric volcanic aerosols have the stronger forcing, but their short residence time likely precludes a lasting climate impact from a single eruption. Decadally paced explosive volcanism may produce a greater climate impact because the long response time of ocean surface waters allows for a cumulative decrease in sea-surface temperatures that exceeds that of any single eruption. Here we use a global climate model to evaluate the potential long-term climate impacts from four decadally paced large tropical eruptions. Direct forcing results in a rapid expansion of Arctic Ocean sea ice that persists throughout the eruption period. The expanded sea ice increases the flux of sea ice exported to the northern North Atlantic long enough that it reduces the convective warming of surface waters in the subpolar North Atlantic. In two of our four simulations the cooler surface waters being advected into the Arctic Ocean reduced the rate of basal sea-ice melt in the Atlantic sector of the Arctic Ocean, allowing sea ice to remain in an expanded state for?>?100 model years after volcanic aerosols were removed from the stratosphere. In these simulations the coupled sea ice-ocean mechanism maintains the strong positive feedbacks of an expanded Arctic Ocean sea ice cover, allowing the initial cooling related to the direct effect of volcanic aerosols to be perpetuated, potentially resulting in a centennial-scale or longer change of state in Arctic climate. The fact that the sea ice-ocean mechanism was not established in two of our four simulations suggests that a long-term sea ice response to volcanic forcing is sensitive to the stability of the seawater column, wind, and ocean currents in the North Atlantic during the eruptions.     

Mean and Turbulent Flow Statistics in a Trellised Agricultural Canopy

Flow physics is investigated in a two-dimensional trellised agricultural canopy to examine that architecture’s unique signature on turbulent transport. Analysis of meteorological data from an Oregon vineyard demonstrates that the canopy strongly influences the flow by channelling the mean flow into the vine-row direction regardless of the above-canopy wind direction. Additionally, other flow statistics in the canopy sub-layer show a dependance on the difference between the above-canopy wind direction and the vine-row direction. This includes an increase in the canopy displacement height and a decrease in the canopy-top shear length scale as the above-canopy flow rotates from row-parallel towards row-orthogonal. Distinct wind-direction-based variations are also observed in the components of the stress tensor, turbulent kinetic energy budget, and the energy spectra. Although spectral results suggest that sonic anemometry is insufficient for resolving all of the important scales of motion within the canopy, the energy spectra peaks still exhibit dependencies on the canopy and the wind direction. These variations demonstrate that the trellised-canopy’s effect on the flow during periods when the flow is row-aligned is similar to that seen by sparse canopies, and during periods when the flow is row-orthogonal, the effect is similar to that seen by dense canopies.     

Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling.     

Climate and economic competitiveness: Florida freezes and the global citrus processing industry

Summary Casual observers of the impacts associated with four recent freezes in Florida's citrus producing areas might be inclined to agree with an assessment by Miami Herald reporters that these freezes had caused the king of citrus to be toppled from its throne, enabling Brazil to take its place. Research on the citrus industry, however, reveals that the impacts of these recent freezes only explain part of the story of the interaction between climate variability and the relationship between the citrus industries of Florida and Brazil. Climate characteristics and their variability have directly as well as indirectly affected the economic competitiveness of citrus producers whose output is in large measure climate-dependent. Climate variability has had direct impacts on Florida's citrus industry by adversely affecting the productivity of citrus groves in some areas, by altering growers' perceptions of freeze probabilities and, occasionally, by suddenly reducing output, thus elevating the price that consumers must pay for that commodity. Indirectly, competition can be affected by climate as a potential producer identifies a weakness in the supply system of an existing industry and seeks to fill the gap.Brazil's involvement in the toppling of King Citrus began not in the early 1980s (as a result of the four freezes in the past six years), but in 1962 as a result of a major freeze in that year, one that sharply increased FCOJ prices by reducing Florida's output. It was then that the climate had an impact on the economic competitiveness of the citrus industry. The records document the steady, almost meteoric, rise in Brazilian FCOJ production and exports. Subsequent freezes only served to abet a process that had been well underway two decades before the recent devastating freezes.As for Florida's ability to continue and perhaps expand its key role in the global citrus economy, the recent freezes do not appear to have fatally damaged that. Rather, those freezes have reawakened Florida's citrus producers to the fact that they are involved in a climate-sensitive industry and have reminded them that the potential for freeze-related problems is never far away. That reawakening has sparked interest in developing hardier citrus varieties, more effective freeze protection methods, and better ways to hedge economically against freeze impacts to the industry.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Consequences of change and variability in sea ice on marine ecosystem and biogeochemical processes during the 2007–2008 Canadian International Polar Year program

Change and variability in the timing and magnitude of sea ice geophysical and thermodynamic state have consequences on many aspects of the arctic marine system. The changes in both the geophysical and thermodynamic state, and in particular the timing of the development of these states, have consequences throughout the marine system. In this paper we review the ??consequences?? of change in sea ice state on primary productivity, marine mammal habitats, and sea ice as a medium for storage and transport of contaminants and carbon exchange across the ocean-sea-ice-atmosphere interface based upon results from the International Polar Year. Pertinent results include: 1) conditions along ice edges can bring deep nutrient-rich ??pacific?? waters into nutrient-poor surface waters along the arctic coast, affecting local food webs; 2) both sea ice thermodynamic and dynamic processes ultimately affect ringed seal/polar bear habitats by controlling the timing, location and amount of surface deformation required for ringed seal and polar bear preferred habitat 3) the ice edges bordering open waters of flaw leads are areas of high biological production and are observed to be important beluga habitat. 4) exchange of climate-active gases, including CO₂, is extremely active in sea ice environments, and the overall question of whether the Arctic Ocean is (or will be) a source or sink for CO₂ will be dependent on the balance of competing climate-change feedbacks.     

Relationships between lightning activity and various thundercloud parameters: satellite and modelling studies

The lightning frequency model developed by Baker et al. [Baker, M.B., Christian, H.J., Latham, J., 1995. A computational study of the relationships linking lightning frequency and other thundercloud parameters, Q. J. R. Meteorol. Soc., 121, 1525–1548] has been refined and extended, in an effort to provide a more realistic framework from which to examine computationally the relationships that might exist between lightning frequency f (which is now being routinely measured from a satellite, using the NASA/MSFC Optical Transient Detector (OTD)) and a variety of cloud physical parameters. Specifically, superior or more comprehensive representations were utilised of: (1) glaciation via the Hallett–Mossop (H–M) process; (2) the updraught structure of the model cloud; (3) the liquid-water-content structure of the model cloud; (4) the role of the reversal temperature T_rev in influencing lightning characteristics; (5) the critical breakdown field for lightning initiation; and (6) the electrical characteristics of the ice crystal anvil of the model cloud. Although our extended studies yielded some new insights into the problem, the basic pattern of relationships between f and the other parameters was very close to that reported by Baker et al. (1995). The more elaborate treatment of T_rev restricted somewhat the range of conditions under which reverse-polarity lightning could be produced if the cloud glaciated via H–M, but confirmed the earlier conclusion that such lightning would not occur if the glaciation was of the Fletcher type. The computations yielded preliminary support for the hypothesis that satellite measurements of f might be used to determine values of the ice-content of cumulonimbus anvils: a parameter of climatological importance. The successful launch and continuing satisfactory functioning of the OTD [Christian, H.J., Goodman, S., 1992. Global observations of lightning from space, Proc. 9th Int. Conf. on Atmospheric Electricity, St. Petersburg, pp. 316–321; Christian, H.J., Blakesee, R.J., Goodman, S.J., 1992. Lightning imaging sensor (LIS) for the earth observing system. NASA Tech. Memorandum, 4350] make it possible—with a high degree of precision—to measure lightning location, occurrence time and frequency f over extensive areas of the Earth's surface. Measured global distributions of lightning and associated lightning stroke radiance demonstrate that: lightning activity is particularly pronounced over the tropics, much greater over land than over the oceans, and exhibits great seasonal variability; lightning radiance tends to be greater over the oceans, less when lightning activity is high, and greater in the Northern Hemisphere winter than summer.     

Evaluating regional climate model estimates against site-specific observed data in the UK

This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre’s HadRM3 regional climate model (RCM), (50 × 50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960–90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data.     

Evaluating a modified point-based method to downscale cell-based climate variable data to high-resolution grids

To address the demand for high spatial resolution gridded climate data, we have advanced the Daymet point-based interpolation algorithm for downscaling global, coarsely gridded data with additional output variables. The updated algorithm, High-Resolution Climate Downscaler (HRCD), performs very good downscaling of daily, global, historical reanalysis data from 1° input resolution to 2.5 arcmin output resolution for day length, downward longwave radiation, pressure, maximum and minimum temperature, and vapor pressure deficit. It gives good results for monthly and yearly cumulative precipitation and fair results for wind speed distributions and modeled downward shortwave radiation. Over complex terrain, 2.5 arcmin resolution is likely too low and aggregating it up to 15 arcmin preserves accuracy. HRCD performs comparably to existing daily and monthly US datasets but with a global extent for nine daily climate variables spanning 1948–2006. Furthermore, HRCD can readily be applied to other gridded climate datasets.     

Innovation for sustainable energy from a pro-poor perspective

The development and transfer of clean energy technologies to achieve universal energy access is challenging due to the inherent complexities of the energy sector, and the energy governance and financial systems in developing economies. Innovation is an essential part of successfully addressing these difficulties. Duplicating the energy infrastructure models of developed countries will not be sufficient to meet the needs of poor consumers. To the extent that innovation can accelerate energy access, it is important to understand the specific types of innovations that are necessary and how they might be facilitated. The general features of existing international clean energy innovation systems, which are predominantly driven by the markets and emissions reduction mechanisms of developed and rapidly growing emerging economies, are reviewed and the alignment of these systems to the innovation processes required to extend energy access globally is evaluated. Drawing on the innovation policy literature, the attributes of effective international and domestic energy innovation systems that are pro-poor and the associated policy approaches are identified.     

A BME solution of the inverse problem for saturated groundwater flow

In most real-world hydrogeologic situations, natural heterogeneity and measurement errors introduce major sources of uncertainty in the solution of the inverse problem. The Bayesian Maximum Entropy (BME) method of modern geostatistics offers an efficient solution to the inverse problem by first assimilating various physical knowledge bases (hydrologic laws, water table elevation data, uncertain hydraulic resistivity measurements, etc.) and then producing robust estimates of the subsurface variables across space. We present specific methods for implementing the BME conceptual framework to solve an inverse problem involving Darcys law for subsurface flow. We illustrate one of these methods in the case of a synthetic one-dimensional case study concerned with the estimation of hydraulic resistivity conditioned on soft data and hydraulic head measurements. The BME framework processes the physical knowledge contained in Darcys law and generates accurate estimates of hydraulic resistivity across space. The optimal distribution of hard and soft data needed to minimize the associated estimation error at a specified sampling cost is determined. This work was supported by grants from the National Institute of Environmental Health Sciences (Grant no. 5 P42 ES05948 and P30ES10126), the National Aeronautics and Space Administration (Grant no. 60-00RFQ041), the Army Research Office (Grant no. DAAG55-98-1-0289), and the National Science Foundation under Agreement No. DMS-0112069.