Modelling evaporation with local, regional and global BROOK90 frameworks: importance of parameterization and forcing

Observation and estimation of evaporation is a challenging task. Evaporation occurs on each surface and is driven by different energy sources. Thus the correct process approximation in modelling of the terrestrial water balance plays a crucial part. Here, we use a physically-based 1D lumped soil-plant-atmosphere model (BROOK90) to study the role of parameter selection and meteorological input for modelled evaporation on the point scale. Then, with the integration of the model into global, regional and local frameworks, we made cross-combinations out of their parameterization and forcing schemes to analyse the associated model uncertainty. Five sites with different land uses (grassland, cropland, deciduous broadleaf forest, two evergreen needleleaf forests) located in Saxony, Germany were selected for the study. All combinations of the model setups were validated using FLUXNET data and various goodness of fit criteria. The output from a calibrated model with in-situ meteorological measurements served as a benchmark. We focused on the analysis of the model performance with regard to different time-scales (daily, monthly, and annual). Additionally, components of evaporation are addressed, including their representation in BROOK90. Finally, all results are discussed in the context of different sources of uncertainty: model process representation, input meteorological data and evaporation measurements themselves.

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models. To quantify the aerosol mixing state, we used the aerosol mixing state indices for submicron aerosol based on the mixing of optically absorbing and non-absorbing species (χo), the mixing of primary carbonaceous and non-primary carbonaceous species (χc), and the mixing of hygroscopic and non-hygroscopic species (χh). To achieve a spatiotemporal comparison, we calculated the mixing state indices using output from the Community Earth System Model with the four-mode version of the Modal Aerosol Module (MAM4) and compared the results with the mixing state indices from a benchmark machine-learned model trained on high-detail particle-resolved simulations from the particle-resolved stochastic aerosol model PartMC-MOSAIC. The two methods yielded very different spatial patterns of the mixing state indices. In some regions, the yearly averaged χ value computed by the MAM4 model differed by up to 70 percentage points from the benchmark values. These errors tended to be zonally structured, with the MAM4 model predicting a more internally mixed aerosol at low latitudes and a more externally mixed aerosol at high latitudes compared to the benchmark. Our study quantifies potential model bias in simulating mixing state in different regions and provides insights into potential improvements to model process representation for a more realistic simulation of aerosols towards better quantification of radiative forcing and aerosol–cloud interactions.

Achieving realistic Arctic-midlatitude teleconnections in a climate model through stochastic process representation

The extent to which interannual variability in Arctic sea ice influences the midlatitude circulation has been extensively debated. While observational data supports the existence of a teleconnection between November sea ice in the Barents-Kara region and the subsequent winter circulation, climate models do not consistently reproduce such a link, with only very weak inter-model consensus. We show, using the EC-Earth3 climate model, that while a deterministic ensemble of coupled simulations shows no evidence of such a teleconnection, the inclusion of stochastic parameterizations to the ocean and sea ice component of EC-Earth3 results in the emergence of a robust teleconnection comparable in magnitude to that observed. We show that this can be accounted for entirely by an improved ice-ocean-atmosphere coupling due to the stochastic perturbations. In particular, the inconsistent signal in existing climate model studies may be due to model biases in surface coupling, with stochastic parameterizations being one possible remedy.

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol-cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models. To quantify the aerosol mixing state, we used the aerosol mixing state indices for submicron aerosol based on the mixing of optically absorbing and non-absorbing species (χo), the mixing of primary carbonaceous and non-primary carbonaceous species (χc), and the mixing of hygroscopic and non-hygroscopic species (χh). To achieve a spatiotemporal comparison, we calculated the mixing state indices using output from the Community Earth System Model with the modal MAM4 aerosol module, and compared the results with the mixing state indices from a benchmark machine-learned model trained on high-detail particle-resolved simulations from the particle-resolved stochastic aerosol model PartMC-MOSAIC. The two methods yielded very different spatial patterns of the mixing state indices. In some regions, the yearly-averaged χ value computed by the MAM4 model differed by up to 70 percentage points from the benchmark values. These errors tended to be zonally structured, with the MAM4 model predicting a more internally mixed aerosol at low latitudes, and a more externally mixed aerosol at high latitudes, compared to the benchmark. Our study quantifies potential model bias in simulating mixing state in different regions, and provides insights into potential improvements to model process representation for a more realistic simulation of aerosols.

Algorithms of multidimensional random process simulation

The article discusses two approaches to modeling signals and processes: the method of filter construction and the trigonometric method. It is shown that the later approach is more promising, since an increase in the signal/process representation dimension mathematically means adding a term to the basis function formula, which gives access to fast simulation algorithms. Examples of algorithms for multidimensional simulation of random processes using two methods are given and a software system that implements these algorithms is described. The results provided by the software system will allow you to predict characteristics of engineering projects (accuracy and speed of modeling algorithms). Due to the high relevance of and need for fundamental research of methods and algorithms for digital transformation of the component base, the digitalization of all aspects of activity, including the synthesis of new materials, the development of new methods for designing micro- and nano-systems, the article aims to expand the scope of the spectral method of simulating multidimensional processes using original algorithmic complexes.

Strategies for smarter catchment hydrology models: incorporating scaling and better process representation

Hydrological models have proliferated in the past several decades prompting debates on the virtues and shortcomings of various modelling approaches. Rather than critiquing individual models or modelling approaches, the objective here is to address the critical issues of scaling and hydrological process representation in various types of models with suggestions for improving these attributes in a parsimonious manner that captures and explains their functionality as simply as possible. This discussion focuses mostly on conceptual and physical/process-based models where understanding the internal catchment processes and hydrologic pathways is important. Such hydrological models can be improved by using data from advanced remote sensing (both spatial and temporal) and derivatives, applications of machine learning, flexible structures, and informing models through nested catchment studies in which internal catchment processes are elucidated. Incorporating concepts of hydrological connectivity into flexible model structures is a promising approach for improving flow path representation. Also important is consideration of the scale dependency of hydrological parameters to avoid scale mismatch between measured and modelled parameters. Examples are presented from remote high-elevation regions where water sources and pathways differ from temperate and tropical environments where more attention has been focused. The challenge of incorporating spatially and temporally variable water inputs, hydrologically pathways, climate, and land use into hydrological models requires modellers to collaborate with catchment hydrologists to include important processes at relevant scales—i.e. develop smarter hydrological models.

Exploring the future hydrology of a Canadian Rockies glacierized catchment and its sensitivity to meteorological forcings

<p>Glacierized mountain areas are witnessing strong changes in their streamflow generation processes, influencing their capacity to provide crucial water resources to downstream environments. Shifting precipitation patterns, a warming climate, changing snow dynamics and retreating glaciers are occurring simultaneously, driven by complex physical feedbacks. To predict and diagnose future hydrological behaviour in these glacierized catchments, a semi-distributed, physically-based hydrological model including both on and off-glacier process representation was applied to Peyto basin, a 21 km2 glacierized alpine catchment in the Canadian Rockies. The model was forced with bias-corrected outputs from a dynamically downscaled, 4-km resolution Weather and Research Forecasting (WRF) simulation, for the 2000-2015 and 2085-2100 period.  The future WRF runs had boundary conditions perturbed using RCP8.5 late century climate.  The simulations show by the end-of-century, the catchment shifts from a glacial to a nival regime. The increase in precipitation nearly compensates for the decreased ice melt associated with glacier retreat, with a decrease in annual streamflow of only 7%. Peak flow shifts from July to June and August streamflow is reduced by 68%. Changes in blowing snow transport and sublimation, avalanching, evaporation and subsurface water storage also contribute to the strong hydrological shift in the Peyto catchment. A sensitivity analysis to uncertainty in forcing meteorology reveals that streamflow volume is more sensitive to variations in precipitation whereas streamflow timing and variability are more sensitive to variations in temperature. The combination of the temperature and precipitation variations caused substantial changes both in the future snowpack and in the streamflow pattern. By including high-resolution atmospheric modelling and unprecedented both on and off-glacier process-representation in a physically-based hydrological model, the results provide a particularly comprehensive evaluation of the hydrological changes occurring in high-mountain environments in response to climate change.</p>

Peculiarities of the accounting display of transactions with the give-and-take raw materials at restaurant institutions

The essence of the definition of «give-and-take raw materials» is investigated and the own vision of this category used by restaurant enterprises is formed. The scheme of conducting transactions with raw materials obtained on the give-and-take conditions at restaurants institutions is given. The peculiarities of the accounting process representation caused by the procurement of raw materials, production of semi-finished products and home-produced dishes are revealed, as well as the order of the realization accounting of such commodity stocks using production-trade and production methods is highlighted. The advantages and disadvantages of the representation in the system of bookkeeping accounts of the economic resources cycle in different ways of the production and trade activity organization of restaurant institutions are given. The emphasis is placed on the fact that in catering establishments the give-and-take raw materials, semi-finished products and home-produced dishes, produced as a result of give-and-take raw materials processings, are not the property of the catering establishment. Therefore, in order to maintain the proper accounting for transactions with the give-and-take raw materials, information about changes in the value of the investigated assets should be represented in the system of bookkeeping off-balance sheet accounts. The order of the display on the bookkeeping accounts of the transactions with the give-and-take raw materials obtained on the give-and-take conditions is highlighted. The peculiarities of calculation of dishes produced on the conditions of the give-and-take transactions are described. It is established that the formation of the value of produced semi-finished products or dishes is carried out for each order received separately, i.e. using the out-of-order cost accounting method. The peculiarities of calculation of home-produced dishes at restaurants institutions are outlined. For reliable representation of information on the availability and movement of the give-and-take raw materials, it is proposed for the enterprises of the investigated economic activity type to open the additional analytical accounts. Recommendations for improving the representation order in the accounting system, of restaurant institutions, give-and-take transactions, using offered analytical accounts, are formed.