The current and future capabilities of MCP based UV detectors

At the heart of future space-based astronomical UV instruments will be a sensitive UV detector. Though there has been a death of new UV mission opportunities, detector development has continued. Improvements have been made in spatial resolution, dynamic range, detector size, quantum efficiency and background. At the same time the power and mass required to achieve these goals have decreased. We review the current capabilities of microchannel plate based detectors at Berkeley, both in the laboratory and aboard current on-orbit spacecraft. We also discuss what can be expected from the next generation of UV detectors over the next decade.     

The evolution of star clusters: the resolved-star approach

We present the first results of a new technique to detect, locate, and characterize young dissolving star clusters. Using Hubble Space Telescope/Advanced Camera for Surveys archival images of the nearby galaxy IC2574, we performed stellar PSF photometry and selected the most massive stars as our first test sample. We used a group-finding algorithm on the selected massive stars to find cluster candidates. We then plot the color-magnitude diagrams for each group, and use stellar evolutionary models to estimate their age. So far, we found 79 groups with ages of up to about 100 Myr, displaying various sizes and densities.     

Titan's surface: Search for spectral diversity and composition using the Cassini VIMS investigation

The surface composition of Titan is of great importance for understanding both the internal evolution of Titan and its atmosphere. The Visual and Infrared Mapping Spectrometer (VIMS) investigation on Cassini is observing Titan from 0.35 to 5.11 μm with spatial resolution down to a few kilometers during each flyby of the spacecraft as it orbits Saturn. Our search for spectral diversity using seven methane transmission windows in the near infrared suggests that spectrally distinct units exist on the surface of Titan and that most of the surface can be modeled using only a few distinct spectral units: water frost, CO₂ frost, atmospheric scattering, and an unknown material bright at 2 μm. A dark, spectrally neutral material is also implied. Use of an atmospheric scattering component with spectral mixing analysis may provide a method for partially removing atmospheric effects. In some locations, atmospheric scattering accounts for the majority of the signal. There are also small regions with unusual spectra that may be due to low signal and high noise and/or may be exotic materials of interest. Further, we searched within the methane windows for spectral features associated with Titan's surface. Only the 5-μm and, to a lesser extent, the 2-μm window provide a reasonable opportunity for this, as the shorter-wavelength windows are too narrow and the 2.8-μm window is cluttered with an unknown atmospheric constituent. We find evidence for only one spectral feature: near 4.92 μm for the 5-μm bright Tui Regio region. CO₂ frost with grains smaller than about 10 μm is the best candidate we have found so far to explain this absorption as well as the feature's spectral contrast between the 2.7- and the 2.8-μm atmosphere subwindows. This suggested CO₂ identification is supported by the presence of an endmember in the spectral mixture analysis that is consistent with CO₂ frost with large grain sizes. We find no other absorption features that are statistically significant, including those reported earlier by others. These results are consistent with but greatly extend our early analysis that treated only the Ta data set [McCord, T.B., et al., 2006a. Planet. Space Sci. 54, 1524-1539]. In the spectral feature search process, we explored in detail the noise characteristics of the VIMS data within the 5-μm window, which has generally very low signal (4-20 DN), due to the measurement conditions and low illumination levels. We find noise of nearly Gaussian statistics except for some erratic darks and noise spikes, and the data set seems generally well behaved. We present examples of our attempt to improve on the standard VIMS pipeline data calibration.     

The impact of Eurasian dust storms and anthropogenic emissions on atmospheric nutrient deposition rates in forested Japanese catchments and adjacent regional seas

Bulk precipitation and stream water chemistry data from 1993 to 2005 are used to analyze the relationship between Eurasian dust storms and nutrient deposition rates in the Kutsuki experimental forest (near Lake Biwa). From 2000 to 2005, atmospheric deposition, total nitrogen (TN), total phosphorus (TP) and dissolved silica (DSi) deposition rates increased by 26%, 132%, and 38%, respectively in the Kutsuki experimental forest. These TN and TP increases are associated with three seasonal factors: the increasing frequency and intensity of Eurasian spring dust events (March/April); the annual typhoon period (late August/September); and autumn/early winter (October to December) monsoons. The annual typhoon and monsoon winter periods are drivers for atmospheric TP and DSi deposition due to the correlation between the deposition and precipitation. In addition, increased spring dust deposition is a primarily driver for TN deposition changes. Increased emissions from urbanized areas in China (and likely Korea) affect the chemical properties of aerosols reaching downwind Japanese regions. Aerosol processes are responsible for increasing TN in aerosols, which are affected primarily by anthropogenic emissions. From 2000 to 2005, coal burning emissions from East Asia have contributed to an increase in TP (and possibly DSi) deposition rates. The observed increase in nutrient deposition did not noticeably impact short-term (5 year) stream water fluxes in the Kutsuki experimental forest. Due to plant uptake, the forest ecosystem retained atmospherically deposited N and P. Finally, the observed increases in nutrient deposition rates over the East China Sea and the Sea of Japan may significantly influence intra-annual net primary production. It is recommended that earth system modelling incorporate changes in atmospheric nutrient deposition rates and their impacts on the regional carbon cycle as well as aquatic and terrestrial ecosystems.     

The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates

The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework.     

Impacts of climate change on August stream discharge in the Central-Rocky Mountains

In the snowmelt dominated hydrology of arid western US landscapes, late summer low streamflow is the most vulnerable period for aquatic ecosystem habitats and trout populations. This study analyzes mean August discharge at 153 streams throughout the Central Rocky Mountains of North America (CRMs) for changes in discharge from 1950–2008. The purpose of this study was to determine if: (1) Mean August stream discharge values have decreased over the last half-century; (2) Low discharge values are occurring more frequently; (3) Climatic variables are influencing August discharge trends. Here we use a strict selection process to characterize gauging stations based on amount of anthropogenic impact in order to identify heavily impacted rivers and understand the relationship between climatic variables and discharge trends. Using historic United States Geologic Survey discharge data, we analyzed data for trends of 40–59 years. Combining of these records along with aerial photos and water rights records we selected gauging stations based on the length and continuity of discharge records and categorized each based on the amount of diversion. Variables that could potentially influence discharge such as change in vegetation and Pacific Decadal Oscillation (PDO) were examined, but we found that that both did not significantly influence August discharge patterns. Our analyses indicate that non-regulated watersheds are experiencing substantial declines in stream discharge and we have found that 89% of all non-regulated stations exhibit a declining slope. Additionally our results here indicate a significant (α?≤?0.10) decline in discharge from 1951–2008 for the CRMs. Correlations results at our pristine sites show a negative relationship between air temperatures and discharge and these results coupled with increasing air temperature trends pose serious concern for aquatic ecosystems in CRMs.     

Scenarios of methane emission reductions to 2030: abatement costs and co-benefits to ozone air quality and human mortality

Methane emissions contribute to global baseline surface ozone concentrations; therefore reducing methane to address climate change has significant co-benefits for air quality and human health. We analyze the costs of reducing methane from 2005 to 2030, as might be motivated to reduce climate forcing, and the resulting benefits from lower surface ozone to 2060. We construct three plausible scenarios of methane emission reductions, relative to a base scenario, ranging from 75 to 180 Mton CH₄ yr^?1 decreased in 2030. Using compilations of the global availability of methane emission reductions, the least aggressive scenario (A) does not incur any positive marginal costs to 2030, while the most aggressive (C) requires discovery of new methane abatement technologies. The present value of implementation costs for Scenario B are nearly equal to Scenario A, as it implements cost-saving options more quickly, even though it adopts positive cost measures. We estimate the avoided premature human mortalities due to surface ozone decreases by combining transient full-chemistry simulations of these scenarios in a global atmospheric chemical transport model, with concentration-mortality relationships from a short-term epidemiologic study and projected global population. An estimated 38,000 premature mortalities are avoided globally in 2030 under Scenario B. As benefits of methane reduction are positive but costs are negative for Scenario A, it is justified regardless of how avoided mortalities are valued. The incremental benefits of Scenario B also far outweigh the incremental costs. Scenario C has incremental costs that roughly equal benefits, only when technological learning is assumed. Benefits within industrialized nations alone also exceed costs in Scenarios A and B, assuming that the lowest-cost emission reductions, including those in developing nations, are implemented. Monetized co-benefits of methane mitigation for human health are estimated to be $13–17 per ton CO₂eq, with a wider range possible under alternative assumptions. Methane mitigation can be a cost-effective means of long-term and international air quality management, with concurrent benefits for climate.     

Evaluating the performance of a WRF physics ensemble over South-East Australia

When using the Weather Research and Forecasting (WRF) modelling system it is necessary to choose between many parametrisations for each physics option. This study examines the performance of various physics scheme combinations on the simulation of a series of rainfall events near the south-east coast of Australia known as East Coast Lows. A thirty-six member multi-physics ensemble was created such that each member had a unique set of physics parametrisations. No single ensemble member was found to perform best for all events, variables and metrics. This is reflected in the fact that different climate variables are found to be sensitive to different physical parametrisations. While a standardised super-metric can be used to identify best performers, a step-wise decision approach described here, allows explicit recognition of the “robustness” of choosing one parameterisation over another, allowing the identification of a group of “equally robustly” performing physics combinations. These results suggest that the Mellor-Yamada-Janjic planetary boundary layer scheme and the Betts-Miller-Janjic cumulus scheme can be chosen with some robustness. Possibly with greater confidence, the results also suggest that the Yonsei University planetary boundary layer scheme, Kain-Fritsch cumulus scheme and RRTMG radiation scheme should not be used in combination in this region. Results further indicate that the selection of physics scheme options has larger impact on model performance during the more intensive rainfall events.     

A step-response approach for predicting and understanding non-linear precipitation changes

Future changes in precipitation represent one of the most important and uncertain possible effects of future climate change. We demonstrate a new approach based on idealised CO₂ step-change general circulation model (GCM) experiments, and test it using the HadCM3 GCM. The approach has two purposes: to help understand GCM projections, and to build and test a fast simple model for precipitation projections under a wide range of forcing scenarios. Overall, we find that the CO₂ step experiments contain much information that is relevant to transient projections, but that is more easily extracted due to the idealised experimental design. We find that the temporary acceleration of global-mean precipitation in this GCM following CO₂ ramp-down cannot be fully explained simply using linear responses to CO₂ and temperature. A more complete explanation can be achieved with an additional term representing interaction between CO₂ and temperature effects. Energy budget analysis of this term is dominated by clear-sky outgoing long-wave radiation (CSOLR) and sensible heating, but cloud and short-wave terms also contribute. The dominant CSOLR interaction is attributable to increased CO₂ raising the mean emission level to colder altitudes, which reduces the rate of increase of OLR with warming. This behaviour can be reproduced by our simple model. On regional scales, we compare our approach with linear ‘pattern-scaling’ (scaling regional responses by global-mean temperature change). In regions where our model predicts linear change, pattern-scaling works equally well. In some regions, however, substantial deviations from linear scaling with global-mean temperature are found, and our simple model provides more accurate projections. The idealised experiments reveal a complex pattern of non-linear behaviour. There are likely to be a range of controlling physical mechanisms, different from those dominating the global-mean response, requiring focussed investigation for individual regions, and in other GCMs.     

Mid-21st century projections in temperature extremes in the southern Colorado Rocky Mountains from regional climate models

This study analyzes mid-21st century projections of daily surface air minimum (T_min) and maximum (T_max) temperatures, by season and elevation, over the southern range of the Colorado Rocky Mountains. The projections are from four regional climate models (RCMs) that are part of the North American Regional Climate Change Assessment Program (NARCCAP). All four RCMs project 2°C or higher increases in T_min and T_max for all seasons. However, there are much greater (>3°C) increases in T_max during summer at higher elevations and in T_min during winter at lower elevations. T_max increases during summer are associated with drying conditions. The models simulate large reductions in latent heat fluxes and increases in sensible heat fluxes that are, in part, caused by decreases in precipitation and soil moisture. T_min increases during winter are found to be associated with decreases in surface snow cover, and increases in soil moisture and atmospheric water vapor. The increased moistening of the soil and atmosphere facilitates a greater diurnal retention of the daytime solar energy in the land surface and amplifies the longwave heating of the land surface at night. We hypothesize that the presence of significant surface moisture fluxes can modify the effects of snow-albedo feedback and results in greater wintertime warming at night than during the day.