Ecohydrological modelling in a deciduous boreal forest: Model evaluation for application in non-stationary climates

Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one-dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm³/cm³. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.     

Simulated water budget of a small forested watershed in the continental/maritime hydroclimatic region of the United States

Annual streamflows have decreased across mountain watersheds in the Pacific Northwest of the United States over the last ~70 years; however, in some watersheds, observed annual flows have increased. Physically based models are useful tools to reveal the combined effects of climate and vegetation on long‐term water balances by explicitly simulating the internal watershed hydrological fluxes that affect discharge. We used the physically based Simultaneous Heat and Water (SHAW) model to simulate the inter‐annual hydrological dynamics of a 4 km² watershed in northern Idaho. The model simulates seasonal and annual water balance components including evaporation, transpiration, storage changes, deep drainage, and trends in streamflow. Independent measurements were used to parameterize the model, including forest transpiration, stomatal feedback to vapour pressure, forest properties (height, leaf area index, and biomass), soil properties, soil moisture, snow depth, and snow water equivalent. No calibrations were applied to fit the simulated streamflow to observations. The model reasonably simulated the annual runoff variations during the evaluation period from water year 2004 to 2009, which verified the ability of SHAW to simulate the water budget in this small watershed. The simulations indicated that inter‐annual variations in streamflow were driven by variations in precipitation and soil water storage. One key parameterization issue was leaf area index, which strongly influenced interception across the catchment. This approach appears promising to help elucidate the mechanisms responsible for hydrological trends and variations resulting from climate and vegetation changes on small watersheds in the region. Copyright © 2015 John Wiley & Sons, Ltd.     

A Hubble Space Telescope/NICMOS view of the prototypical giant Hii region NGC604 in M33

We present the first high-spatial-resolution near-infrared (NIR) imaging of NGC604, obtained with the NICMOS camera onboard the Hubble Space Telescope (HST). These NICMOS broad-band images reveal new NIR point sources, clusters, and diffuse structures. We find an excellent spatial correlation between the 8.4 GHz radio continuum and the 2.2 μm nebular emission. Moreover, massive young stellar object candidates appear aligned with these radio peaks, reinforcing the idea that those areas are star-forming regions. Three different scaled OB associations are recognized in the NICMOS images. The brightest NIR sources in our images have properties that suggest that they are red supergiant stars, of which one was previously known. This preliminary analysis of the NICMOS images shows the complexity of the stellar content of the NGC604 nebula.     

Effect of climate change on watershed system: a regional analysis

Climate-induced increase in surface temperatures can impact hydrologic processes of a watershed system. This study uses a continuous simulation model to evaluate potential implications of increasing temperature on water quantity and quality at a regional scale in the Connecticut River Watershed of New England. The increase in temperature was modeled using Intergovernmental Panel on Climate Change (IPCC) high and low warming scenarios to incorporate the range of possible temperature change. It was predicted that climate change can have a significant affects on streamflow, sediment loading, and nutrient (nitrogen and phosphorus) loading in a watershed. Climate change also influences the timing and magnitude of runoff and sediment yield. Changes in variability of flows and pollutant loading that are induced by climate change have important implications on water supplies, water quality, and aquatic ecosystems of a watershed. Potential impacts of these changes include deficit supplies during peak seasons of water demand, increased eutrophication potential, and impacts on fish migration.     

Modeling the electric structures of two thunderstorms and their contributions to the global circuit

This study examines the electricity in two thunderstorms, typical for their respective locales (the Great Plains and the New Mexico mountains), by modeling them as a set of steady-state horizontal layers of external currents. The model electric sources, corresponding to the charge separation processes in the thundercloud, are embedded in an exponential conducting atmosphere. The source parameters are determined by fitting the model electric field to measured profiles. The resulting currents to the ionosphere (i.e., the Wilson current) from the two storms are 0.53 A and 0.16 A, while the calculated electrical energies of the storms are 2.3 × 10¹⁰ J and 2.8 × 10⁹ J, respectively. The more vigorous storm is estimated to transfer 16 000 C in the global circuit during 8.5 h of its lifetime, while the weaker mountain storm transferred about 1200 C in its entire 2-h lifetime. Removal of the screening charge layer from above the updraft region in one modeled storm leads to only a small increase in the net Wilson current of less than 3%, while it provides a substantial local disturbance of the electric field. Overall, the model findings indicate that differences in the Wilson currents and electrical energies of the two storms result from differences in their internal dynamical and electrical structures as well as their geographical locations.     

Automatic Detection of Limb Prominences in 304 Å EUV Images

A new algorithm for automatic detection of prominences on the solar limb in 304 Å EUV images is presented, and results of its application to SOHO/EIT data discussed. The detection is based on the method of moments combined with a classifier analysis aimed at discriminating between limb prominences, active regions, and the quiet corona. This classifier analysis is based on a Support Vector Machine (SVM). Using a set of 12 moments of the radial intensity profiles, the algorithm performs well in discriminating between the above three categories of limb structures, with a misclassification rate of 7%. Pixels detected as belonging to a prominence are then used as the starting point to reconstruct the whole prominence by morphological image-processing techniques. It is planned that a catalogue of limb prominences identified in SOHO and STEREO data using this method will be made publicly available to the scientific community.     

Self-Similar and Self-Affine Properties of Two-Dimensional Fracture Patterns in Rocks

In this paper, we investigate the fractal properties of binary maps of rock fractures at different scales and different geological types, as well as different families of fracture patterns obtained from a two-dimensional Laplacian growth model (LGM). From these analyses we figure out which families of the LGM patterns match the structural properties of the fracture binary maps. The LGM is defined in terms of a nonlinear map that depends on two parameters, λ and \mathfraka\mathfrak{a}, that respectively define the area and shape of the elements of the aggregate that conforms the patterns. The fractal dimension and roughness exponent of the LGM patterns are found to depend on \mathfraka\mathfrak{a}, with 0 < \mathfrak a < 10<\mathfrak {a}<1. From a detailed statistical analysis of these patterns we found that the fractal dimensions of capacity, correlation and information decrease monotonically as \mathfraka\mathfrak{a} increases. We also found that the values of these three fractal dimensions tend to collapse on top of each other as \mathfraka\lessapprox1\mathfrak{a}\lessapprox1. Remarkably, the fractal properties of rock fractures in the scales from millimeters up to a few meters appear to be well represented by the fractal structure of the LGM families of patterns with \mathfraka=0.15\mathfrak{a}=0.15 and 0.30, while the fractal properties of rock fractures in the scale of kilometers seems to be well represented by the LGM family with \mathfraka=0.90\mathfrak{a}=0.90. In addition, the three fractal dimension values of fracture binary maps in the scales from millimeters up to meters were found to be different between them. Nonetheless, for fractures in the scale of kilometers, the values of the three fractal dimensions are very close to each other as an indication of self-similar behavior. Analysis of the corrections to the scaling of the roughness exponent, ζ, suggests that they are negligible for the LGM family of fracture patterns with \mathfraka=0.9\mathfrak{a}=0.9. This finding points to a self-affine structure for this family of patterns. In fact, the calculated roughness exponent results are in the range of values characteristic of rock fractures.