ALBERT

Description: Ecological Applications, Volume 0, Issue 0, Ahead of Print. Tropical forests are important storehouses of carbon and biodiversity. In isolated island ecosystems such as the Hawaiian Islands, relative dominance of native and non-native tree species may influence patterns of forest carbon stocks and biodiversity. We determined aboveground carbon density (ACD) across a matrix of lava flows differing in age, texture and vegetation composition (i.e., native or non-native dominated) in wet lowland forests of Hawaii Island. To do this at the large scales necessary to accurately capture the inherent heterogeneity of these forests, we collected LiDAR data across areas of interest and developed relationships between LiDAR metrics and field-based estimates of forest ACD. This approach enabled us to inventory, rather than merely sample, the entire populations (i.e., forests) of interest. Native Hawaiian wet lowland forests exhibited ACD values similar to those of intact tropical forests elsewhere. In general, ACD of these forests increased with increasing lava flow age, but patterns differed between native and non-native forest stands. On the youngest lavas, native-dominated forest ACD averaged 〈 60 Mg ha-1 compared to ca. 100 Mg C ha-1 for non-native dominated forests. This difference was due to the presence of the non-native, N2-fixing trees, F. moluccana and C. equisetifolia in the non-native dominated forest stands, as well as the corresponding absence of N2-fixing trees in native-dominated forest stands. Following approximately 500 years of primary succession and thereafter, however, both forest types exhibited ACD values averaging ca. 130 Mg C ha-1, although it took non-native forests only 75 to 80 years of post-establishment succession to reach those values. Given the large areas of early successional M. polymorpha-dominated forest on young lava flows, further spread of F. moluccana and C. equisetifolia populations would likely increase ACD stocks but would constitute a significant erosion of the invaluable contribution of Hawaii's native ecosystems to global biodiversity.

Description: In this study we examine the hydrological processes that underpin non-stationarity in hydrological prediction. This is achieved by analysis of linkages between rainfall, groundwater storage, and runoff in Southwest Western Australia (SWWA), a region experiencing stream flow decline since the mid-1970s. We find a close connection between rainfall and changes in catchment groundwater storage, with increases in storage in years with annual rainfall above a threshold (1050–1400 mm), and declines during low rainfall years. Where groundwater is in contact with the stream bed, runoff, as a proportion of rainfall, is highly correlated with groundwater storage. Recent drought years have reduced groundwater storage and runoff ratio. In the absence of replenishing wetter years, lower runoff ratios are subsequently maintained. Runoff from a given depth of annual rainfall is now far lower than that produced 15 years ago. In this way groundwater storage acts as the catchment's “memory”. This study highlights the importance of catchment groundwater storage that may be used to improve runoff prediction in a drying climate.

Description: Land surface temperature and emissivity (LST&E) data are essential for a wide variety of surface-atmosphere studies, from calculating the evapotranspiration of the Earth's land surface to retrieving atmospheric water vapor. LST&E products are generated from thermal infrared data acquired from sensors such as ASTER and MODIS on NASA's EOS platforms. NASA has identified a major need to develop long-term, consistent products valid across multiple missions, with well-defined uncertainty statistics addressing specific Earth science questions. These products are termed Earth System Data Records (ESDRs) and LST&E have been identified as an important ESDR. Currently a lack of understanding in LST&E uncertainties limits their usefulness in land surface and climate models. To address this issue, a LST&E uncertainty simulator has been developed to quantify and model uncertainties for a variety of TIR sensors and LST algorithms. Using the simulator, uncertainties were estimated for the MODIS and ASTER TES algorithm, including water vapor scaling (WVS). These uncertainties were parameterized according to view angle and estimated total column water vapor for application to real data. The standard ASTER TES algorithm had a RMSE of 3.1 K (1.2 K with WVS), while the MODIS TES algorithm had a RMSE of 4.5 K (1.5 K with WVS). Accuracies in retrieved spectral emissivity for both sensors degraded with higher atmospheric water content, however, with WVS the emissivity uncertainties were reduced to

Description: We investigate the representation of the Sierra Barrier Jet (SBJ) in four numerical models at different resolutions, primarily documenting its representation within a high-resolution (6 km), 11-year WRF reanalysis downscaling (WRF-RD). A comprehensive validation of this dynamical downscaling is undertaken during 11 cool seasons (water years 2001–2011, October to March) using available wind profiler data at Chico, CA (CCO). We identify SBJ cases in the observed CCO wind profiler data, as well as in WRF-RD at the closest grid point. WRF-RD's representation of the SBJ at CCO is compared with that of other reanalysis products with coarser horizontal resolutions (i.e., the North American Regional Reanalysis (NARR), the California Reanalysis downscaling, and the NCEP/NCAR Reanalysis) to assess whether downscaling is necessary to correctly capture this topographically induced low-level jet. Detailed comparisons across California between WRF-RD and NARR suggest downscaling is necessary: Only WRF-RD at 6 km resolution is well-capturing this dynamical feature. A catalog of modeled SBJ events that have significant timing overlap with observations is created and used to further assess WRF-RD's representation of SBJ events. In addition, observation-model comparisons of other meteorologically important variables (e.g., precipitation melting level, wind profiles, temperature, and relative humidity) are performed in order to evaluate WRF-RD's ability to capture the dynamical evolution of the SBJ. The detailed, case-by-case comparisons reveal WRF-RD accurately represents 56 percent of the 256 observed SBJ cases occurring during these 11 cool seasons, albeit with a weak wind bias that increases with jet maximum wind strength.

Description: Characterizing the emission height of sulfur dioxide (SO2) from volcanic eruptions yields information about the strength of volcanic activity, and is crucial for the assessment of possible climate impacts and validation of satellite retrievals of SO2. Sensors such as the Ozone Monitoring Instrument (OMI) on the polar-orbiting Aura satellite provide accurate maps of the spatial distribution of volcanic SO2, but provide limited information on its vertical distribution. The goal of this work is to explore the possible use of a trajectory model in reconstructing both the temporal activity and injection altitude of volcanic SO2 from OMI column measurements observed far from the volcano. Using observations from the November 2006 eruption of Nyamuragira, back trajectories are run and statistical analyses are computed based on the distance of closest approach to the volcano. These statistical analyses provide information about the emission height time series of SO2 injection from that eruption. It is found that the eruption begins first injecting SO2 into the upper troposphere, between 13 km and 17 km, on November 28th 2006. This is then followed by a slow decay in injection altitude, down to 6 km, over subsequent days. The emission height profile is used to generate an optimal reconstruction based on forward trajectories and compared to OMI SO2 observations. The inferred altitude of the Nyamuragira SO2 cloud is also compared to the altitude of sulfate aerosols detected in aerosol backscatter vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO).

Description: We compare the characteristics of synthetic European droughts generated by the HiGEM 1 coupled climate model run with present day atmospheric composition with observed drought events extracted from the CRU TS3 data set. The results demonstrate consistency in both the rate of drought occurrence and the spatiotemporal structure of the events. Estimates of the probability density functions for event area, duration and severity are shown to be similar with confidence 〉 90%. Encouragingly, HiGEM is shown to replicate the extreme tails of the observed distributions and thus the most damaging European drought events. The soil moisture state is shown to play an important role in drought development. Once a large-scale drought has been initiated it is found to be 50% more likely to continue if the local soil moisture is below the 40 th percentile . In response to increased concentrations of atmospheric CO 2 , the modelled droughts are found to increase in duration, area and severity. The drought response can be largely attributed to temperature driven changes in relative humidity. Copyright © 2012 Royal Meteorological Society

Description: ABSTRACT Although the impact of sheet erosion on the evolution of soils, soil properties and associated ecosystem services across landscapes is undisputed, there are still large uncertainties in the estimation of sheet erosion, as the results obtained are highly scale dependent. Consequently, there is a need to develop a scale-explicit understanding of sediment erosion yields, from microplot to hillslope through to plot, to surmount actual erosion modelling flaws and to improve guidance for erosion mitigation. The main objective of this study was to compare sediment yields from small and large plots installed under different environmental conditions and to interpret these results in terms of the main mechanisms and controlling factors of sheet erosion. Fifteen 1 × 1 m² and ten 2 × 5 m² plots were installed on a hillslope in the foothills of the Drakensberg, South Africa. Data of runoff, sediment concentration (SC), soil loss (SL) and rainfall characteristics obtained during the 2009–2010 rainy season at the two spatial scales and from different soils, vegetation cover, geology and topographic conditions were used to identify the main controlling factors of sheet erosion. Scale ratios for SC and SL were subsequently calculated to assess the level of contribution of rain-impacted flow (RIF) to overall sheet erosion. The average runoff rate ( n  = 17 events) ranged between 4.9 ± 0.4 L m -2 on 1 m 2 and 5.4 ± 0.6 L m 2 on 10 m 2 , which did not correspond to significant differences at P  〈 0.05 level. Sediment losses were significantly higher on the 10 m 2 plots, compared with the 1 m 2 plots (2.2 ± 0.4 vs 1.5 ± 0.2 g L -1 for SC; 9.8 ± 1.8 vs 3.2 ± 0.3 g m -2 for SL), which illustrated a greater efficiency of sheet erosion on longer slopes. Results from a principal component analysis, whose two first axes explained 60% of the data variance, suggested that sheet erosion is mainly controlled by rainfall characteristics (rainfall intensity and amount) and soil surface features (crusting and vegetation coverage). The contribution of RIF to sheet erosion was the lowest at high soil clay content (r = 0.26) and the highest at high crusting and bulk density (r = 0.22), cumulative rainfall amount in the season and associated rise in soil water table (r = 0.29). Such an explicit consideration of the role of scale on sediment yields and process domination by either in situ (soil and soil surface conditions) or ex situ (rainfall characteristics and antecedent rainfall) factors, is expected to contribute to process-based modelling and erosion mitigation. Copyright © 2012 John Wiley & Sons, Ltd.

Description: Southeast-Asia (SEA) constitutes a global biodiversity hotspot, but is exposed to extensive deforestation and faces numerous threats to its biodiversity. Climate change represents a major challenge to the survival and viability of species, and the potential consequences must be assessed to allow for mitigation. We project the effects of several climate change scenarios on bat diversity, and predict changes in range size for 171 bat species throughout SEA. We predict decreases in species richness in all areas with high species richness (〉80 species) at 2050–2080, using bioclimatic IPCC scenarios A2 (a severe scenario, continuously increasing human population size, regional changes in economic growth) and B1 (the ‘greenest’ scenario, global population peaking mid-century). We also predicted changes in species richness in scenarios that project vegetation changes in addition to climate change up to 2050. At 2050 and 2080, A2 and B1 scenarios incorporating changes in climatic factors predicted that 3–9% species would lose all currently suitable niche space. When considering total extents of species distribution in SEA (including possible range expansions), 2–6% of species may have no suitable niche space in 2050–2080. When potential vegetation and climate changes were combined only 1% of species showed no changes in their predicted ranges by 2050. Although some species are projected to expand ranges, this may be ecologically impossible due to potential barriers to dispersal, especially for species with poor dispersal ability. Only 1–13% of species showed no projected reductions in their current range under bioclimatic scenarios. An effective way to facilitate range shift for dispersal-limited species is to improve landscape connectivity. If current trends in environmental change continue and species cannot expand their ranges into new areas, then the majority of bat species in SEA may show decreases in range size and increased extinction risk within the next century.