No abstract

Abstract. Glacier changes are a vivid example of how environmental systems react to a changing climate. Distributed surface mass balance models, which translate the meteorological conditions on glaciers into local melting rates, help to attribute and detect glacier mass and volume responses to changes in the climate drivers. A well-calibrated model is a suitable test bed for sensitivity, detection, and attribution analyses for many scientific applications and often serves as a tool for quantifying the inherent uncertainties. Here, we present the open-source COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY), which provides a flexible and user-friendly framework for modeling distributed snow and glacier mass changes. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The framework consists of a computational kernel, which forms the runtime environment and takes care of the initialization, the input–output routines, and the parallelization, as well as the grid and data structures. This structure offers maximum flexibility without having to worry about the internal numerical flow. The adaptive subsurface scheme allows an efficient and fast calculation of the otherwise computationally demanding fundamental equations. The surface energy balance scheme uses established standard parameterizations for radiation as well as for the energy exchange between atmosphere and surface. The schemes are coupled by solving both surface energy balance and subsurface fluxes iteratively such that consistent surface skin temperature is returned at the interface. COSIPY uses a one-dimensional approach limited to the vertical fluxes of energy and matter but neglects any lateral processes. Accordingly, the model can be easily set up in parallel computational environments for calculating both energy balance and climatic surface mass balance of glacier surfaces based on flexible horizontal grids and with varying temporal resolution. The model is made available on a freely accessible site and can be used for non-profit purposes. Scientists are encouraged to actively participate in the extension and improvement of the model code.

Total electron-scattering cross sections of pyrimidine, the basic component for the nucleic bases cytosine and thymine, were measured for electron energies from 5 eV to 1 keV using the linear transmission method. The measured results were compared to semiempirical data obtained by means of the additivity rule and to experimental data for benzene since it has a similar ring structure and the same number of valence electrons as pyrimidine. Furthermore, integral elastic and inelastic electron-scattering cross sections of pyrimidine were calculated by applying the spherical complex optical potential model. The sum of both cross sections agrees reasonably well with the experimental total electron-scattering cross sections of pyrimidine in the energy range from 20 eV to 1 keV. The experimental data are, however, significantly lower than the theoretical cross sections when including the contribution of rotational excitations to the electron scattering. Total electron-scattering cross sections of pyrimidine, the basic component for the nucleic bases cytosine and thymine, were measured for electron energies from 5 eV to 1 keV using the linear transmission method. The measured results were compared to semiempirical data obtained by means of the additivity rule and to experimental data for benzene since it has a similar ring structure and the same number of valence electrons as pyrimidine. Furthermore, integral elastic and inelastic electron-scattering cross sections of pyrimidine were calculated by applying the spherical complex optical potential model. The sum of both cross sections agrees reasonably well with the experimental total electron-scattering cross sections of pyrimidine in the energy range from 20 eV to 1 keV. The experimental data are, however, significantly lower than the theoretical cross sections when including the contribution of rotational excitations to the electron scattering.

The COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) was employed to investigate the relationship between the variability and sensitivity of the mass balance record of the Halji glacier, in the Himalayas, north-western Nepal, over a 40 year period since October 1981 to atmospheric drivers. COSIPY was forced with the atmospheric reanalysis dataset ERA5-Land that has been statistically downscaled to the location of an automatic weather station at the Halji glacier. Glacier mass balance simulations with air temperature and precipitation perturbations were executed and teleconnections investigated. For the mass-balance years 1982 to 2019, a mean annual glacier-wide climatic mass balance of -0.48 meters water equivalent per year (mw.e./a) with large interannual variability (standard deviation 0.71mw.e./a) was simulated. This variability is dominated by temperature and precipitation patterns. The Halji glacier is mostly sensitive to summer temperature and monsoon-related precipitation perturbations, which is reflected in a strong correlation with albedo. According to the simulations, the climate sensitivity with respect to either positive or negative air temperature and precipitation changes is nonlinear: A mean temperature increase (decrease) of 1K would result in a change of the glacier-wide climatic mass balance of −1.43mw.e./a ( 0.99mw.e./a) while a precipitation increase (decrease) of 10 % would cause a change of 0.45mw.e./a ( −0.59mw.e./a). Out of 22 circulation and monsoon indexes, only the Webster and Yang Monsoon index and Polar/Eurasia index provide significant correlations with the glacier-wide climatic mass balance. Based on the strong dependency of the climatic mass balance from summer season conditions, we conclude that the snow–albedo feedback in summer is crucial for the Halji glacier. This finding is also reflected in the correlation of albedo with the Webster and Yang Monsoon index.

Precipitation is a central quantity of hydrometeorological research and applications. Especially in complex terrain, such as in High Mountain Asia (HMA), surface precipitation observations are scarce. Gridded precipitation products are one way to overcome the limitations of ground truth observations. They can provide datasets continuous in both space and time. However, there are many products available, which use various methods for data generation and lead to different precipitation values. In our study we compare nine different gridded precipitation products from different origins (ERA5, ERA5-Land, ERA-interim, HAR v2 10 km, HAR v2 2 km, JRA-55, MERRA-2, GPCC and PRETIP) over a subregion of the Central Himalaya and the Southwest Tibetan Plateau, from May to September 2017. Total spatially averaged precipitation over the study period ranged from 411 mm (GPCC) to 781 mm (ERA-Interim) with a mean value of 623 mm and a standard deviation of 132 mm. We found that the gridded products and the few observations, with few exceptions, are consistent among each other regarding precipitation variability and rough amount within the study area. It became obvious that higher grid resolution can resolve extreme precipitation much better, leading to overall lower mean precipitation spatially, but higher extreme precipitation events. We also found that generally high terrain complexity leads to larger differences in the amount of precipitation between products. Due to the considerable differences between products in space and time, we suggest carefully selecting the product used as input for any research application based on the type of application and specific research question. While coarse products such as ERA-Interim or ERA5 that cover long periods but have coarse grid resolution have previously shown to be able to capture long-term trends and help with identifying climate change features, this study suggests that more regional applications, such as glacier mass-balance modeling, require higher spatial resolution, as is reproduced, for example, in HAR v2 10 km.

Abstract. Glacial changes play a key role both from a socio-economical and political, and scientific point of view. The identification and the understanding of the nature of these changes still poses fundamental challenges for climate, glacier and water research. Many studies aim to identify the climatic drivers behind the observed glacial changes using distributed surface mass and energy balance models. Distributed surface mass balance models, which translate the meteorological conditions on glaciers into local melting rates, thus offer the possibility to attribute and detect glacier mass and volume responses to changes in the climatic forcings. A well calibrated model is a suitable test-bed for sensitivity, detection and attribution analyses for many scientific applications and often serves as a tool for quantifying the inherent uncertainties. Here we present the open-source coupled snowpack and ice surface energy and mass balance model in Python COSIPY, which provides a lean, flexible and user-friendly framework for modelling distributed snow and glacier mass changes. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The framework consists of a computational kernel, which forms the runtime environment and takes care of the initialization, the input-output routines, the parallelization as well as the grid and data structures. This structure offers maximum flexibility without having to worry about the internal numerical flow. The adaptive sub-surface scheme allows an efficient and fast calculation of the otherwise computationally demanding fundamental equations. The surface energy-balance scheme uses established standard parameterizations for radiation as well as for the energy exchange between atmosphere and surface. The schemes are coupled by solving both surface energy balance and subsurface fluxes iteratively in such that consistent surface skin temperature is returned at the interface. COSIPY uses a one-dimensional approach limited to the vertical fluxes of energy and matter but neglects any lateral processes. Accordingly, the model can be easily set up in parallel computational environments for calculating both energy balance and climatic surface mass balance of glacier surfaces based on flexible horizontal grids and with varying temporal resolution. The model is made available on a freely accessible site and can be used for non-profit purposes. Scientists are encouraged to actively participate in the extension and improvement of the model code.

No abstract

A system of logic disconnection or construction of organic molecules is given to overcome serious problems in the study of organic chemistry. Based on the logic system of polar reactions of donors and acceptors several different reactions can be created to access a required target molecule. By a following careful analysis of these proposals several transformations can be detected as the preferred ones. Moreover, by the introduction of the ''umpolung'' principle additional options are given to synthesize a required molecule. These considerations were discussed in the 1,2-, 1,3-, 1,4-, 1,5-and 1,6-difunctional series.