Combination of WENO and Explicit Runge–Kutta Methods for Wind Transport in the Meso-NH Model

This paper investigates the use of the weighted essentially nonoscillatory (WENO) space discretization methods of third and fifth order for momentum transport in the Meso-NH meteorological model, and their association with explicit Runge–Kutta (ERK) methods, with the specific purpose of finding an optimal combination in terms of wall-clock time to solution. A linear stability analysis using von Neumann theory is first conducted that considers six different ERK time integration methods. A new graphical representation of linear stability is proposed, which allows a first discrimination between the ERK methods. The theoretical analysis is then completed by tests on numerical problems of increasing complexity (linear advection of high wind gradient, orographic waves, density current, large eddy simulation of fog, and windstorm simulation), using a fourth-order-centered scheme as a reference basis. The five-stage third-order and fourth-order ERK combinations appear as the time integration methods of choice for coupling with WENO schemes in terms of stability. An explicit time-splitting method added to the ERK temporal scheme for WENO improves the stability properties slightly more. When the spatial discretizations are compared, WENO schemes present the main advantage of maintaining stable, nonoscillatory transitions with sharp discontinuities, but WENO third order is excessively damping, while WENO fifth order provides better accuracy. Finally, WENO fifth order combined with the ERK method makes the whole physics of the model 3 times faster compared to the classical fourth-order centered scheme associated with the leapfrog temporal scheme

A cellular automaton framework for within-field vineyard variance and grape production simulation

Winegrowers for generations know it all too well that grapes harvested from different areas within a vineyard will produce wines of different flavours, mainly due to within-field variance in vine vigour caused by environmental variability from various factors, such as soil properties, microclimate conditions, and rootstock. Recent research attempts on the use of state-of-the-art technologies to model/ simulate within-field variance at a vineyard scale are outlined. Consequently, the paper illustrates a cellular automaton (CA) framework being developed for simulating the within-field variance in grapevine plant vigour, phenological events and vineyard production using random or real thematic mappings of likely key factors that contribute to the observed variance. The CA approach provides an alternative software tool to conventional crop estimation methods that are dependent upon expensive yield sampling methods

Integrated basin modeling

Simulation models / Irrigation management / Water balance / Groundwater / River basins / Hydrology / Flow / Evapotranspiration / Precipitation / Soils / Turkey / Gediz Basin

Applications of bioclimatology to assess effects of climate change on viticultural suitability in the DO León (Spain)

[EN] Spain accounts for 13.1% of the world’s vineyard area, and viticulture is crucial for the socioeconomic and cultural sectors. Vineyards are among the perennial crops that can suffer most negative impacts under climate change which can pose challenges to the sustainability of viticulture. Local and regional studies are needed to assess these impacts to help implement effective strategies in response to climate change. To this end, our approach involves integrating both conventional agroclimatic indices and those new bioclimatic indices that have proven to be essential for the characterization and demarcation of vineyards into species distribution models to assess areas suitable for viticulture under climate change projections. The proposed methodology was tested in a viticultural region located in northwestern Spain (DO León). An ensemble platform was used to build consensus models encompassing three general circulation models, two emission scenario pathways and two time horizons. Only the predictors that effectively characterize each grape variety were included in the models. The results revealed increases in the continentality index, compensated thermicity index, hydrothermic index of Branas, and temperature range during ripening in all the future scenarios analyzed in comparison to current conditions. Conversely, the values for the annual ombrothermic index and growing season precipitation may decrease in the future. The pattern of changes for 2070 will be more pronounced than for 2050. A significant loss of future habitat suitability was detected within the limits of the study area for the grape varieties analyzed. This negative impact could be counteracted to some degree with new and favorable areas for the cultivation of vineyards in territories located at the north of the DO limits. We suggest that our results could help policymakers to develop practices and strategies to conserve existing grape varieties and to implement efficient adaptation measures for mitigating or anticipating the effects of climate change on viticulture.SIThis work was supported by the Regional Ministry of Education, Junta de Castilla y León (Spain), EDU/667/201

Monitoring climate related risk and opportunities for the wine sector: The MED-GOLD pilot service

MED-GOLD was a 54-months research and innovation project, whose main aim was to co-develop climate services for three staples of the Mediterranean food system, namely grapes, olives and durum wheat. This paper describes the methodology adopted for the co-development of the pilot climate service for the wine sector, focusing on the Douro Wine Region in northern Portugal. In the first step, the MED-GOLD industrial partner SOGRAPE identified key decisions and users’ needs for the wine sector in the Douro region by involving managers from their own vineyards in that region. From this information, the relevant bioclimatic indicators (and associated essential climate variables) were selected. Afterwards, two compound risk indices, the Sanitary and Heat Risk indices, were introduced as a combination of some of the aforementioned bioclimatic indicators. This methodological work was validated against the empirical climate characterization for the region of interest, of several ‘bad’ and ‘good’ years chosen by users according to their recollections of grape and wine production outcomes, namely quality and yields. In this paper, the overall strategy for selection of these years is presented. The components of the service based on historical climate, seasonal predictions and longer-term climate projections are described along with the visual interface developed: the MED-GOLD Dashboard, an interactive tool that displays detailed historical climate data, seasonal predictions and climate projections. The Dashboard consists of an ICT platform with a map-based user-focused front end to aid easy access to and manipulation of the data. The Dashboard was iteratively co-designed with the users to ensure their needs were met.The authors acknowledge project MED-GOLD (Turning climate-related information into added value for traditional MEDiterranean Grape, Olive and Durum Wheat food systems, agreement no. 776467) funded by the European Union. Raul Marcos-Matamoros is a Serra Húnter fellow.Peer Reviewed"Article signat per 17 autors/es: Alessandro Dell'Aquila , António Graça, Marta Teixeira, Natacha Fontes, Nube Gonzalez-Reviriego, Raul Marcos-Matamoros, Chihchung Chou, Marta Terrado, Christos Giannakopoulos, Konstantinos V. Varotsos, Federico Caboni, Riccardo Locci, Martina Nanu, Sara Porru, Giulia Argiola, Marta Bruno Soares, Michael Sanderson"Postprint (published version

Ultra high-resolution climate simulations over the Stellenbosch wine producing region using a variable-resolution model

The study aims to generate a simulated, ultra high-resolution climatology over the southwestern Cape of South Africa, and in particular the Stellenbosch wine producing region, by the dynamical downscaling of observed synoptic-scale circulation. A variable-resolution global model, the conformal-cubic atmospheric model (CCAM), and a multiple-nudging strategy are applied in order to reach this goal. CCAM is employed in stretched-grid mode as a regional climate model (RCM) to simulate climate for the period 1976-2005 at four different spatial resolutions. Nudging from coarse-resoltion (2.5° in latitude and longitude), the model was first applied at a 60 km resolution over southern Africa in order to obtain a simulation of the synoptic-scale circulation over the region. Two higher resolution simulations, at 8 km and 1 km resolution, were obtained consecutively over the western and southwestern Cape, nudging from the 60 km and 8 km simulations, respectively. Finally, a 200 m simulation was performed over the Stellenbosch region. Because of the high computational requirements of high-resolution runs, each progressively higher resolution simulation is performed over a progressively smaller area of interest over which the spatial resolution is high. The simulations verify well against observed datasets, and generally capture the important climatic features over the area of interest. The 60 km CCAM simulation gives a good representation of the synoptic scale weather over southern Africa, with realistic seasonal circulation patterns and rainfall percentages as well as intra-annual rainfall totals over various regions. The mesoscale climate over the Western Cape of South Africa is captured by the 8 km simulation, especially with respect to seasonal variations in temperature and rainfall percentages - although the actual rainfall over the southwestern tip of the Western Cape is severely underestimated. The ultra high-resolution simulated diurnal cycle of temperature, relative humidity and screen level wind speed compared well against observations for the month of February. The CCAM climate simulations might not be accurate enough for some of the very sensitive studies of the wine industry, but it can have great value for the demarcation of areas which are climatically suited for viticulture and some more general viticultural studies. Ultra high-resolution climate parameter maps are presented for 1976-2005.Dissertation (MSc)--University of Pretoria, 2009.Geography, Geoinformatics and MeteorologyUnrestricte

Development of a land use-based spatial water requirements model for the Berg Water Management Area

This study was conducted to investigate the requirements for the spatial modelling of current and future water demand in the Berg River Water Management Area in the Western Cape of South Africa in order to produce a prototype model from which annual water requirements could be computed and spatially visualised. To accomplish this the spatial distribution of water demand within the study area was first investigated. The data required to perform spatial water demand modelling of diverse land uses and socio-economic activities were evaluated. Finally, the question of improving spatial water demand modelling at the catchment scale was considered from both a systems design and a technical perspective. The resulting model consists of two main modules; one performing a rudimentary monthly soil water balance to obtain monthly and annual irrigation requirements, and another applying preconfigured determinant layers derived from land use to town zone layers in order to determine annual urban water use intensities per areal unit. The resulting model prototype follows a sequential workflow based on a series of components that combine to produce a spatial overview of water use intensity within the study area. Water demand was found to be predominantly irrigated agriculture in the upper reaches of the Berg (mainly wine grape) and was found to be dominated by intensive industrial users in the central and lower reaches. The model was designed so that new data could be introduced in order to expand the system where required, as well as allowing for updated datasets to be incorporated as they become available. Due to the uncertainties inherent in the modelling and approximation of real world phenomena, the importance of establishing a set of structured, stable, predefined user requirements and system specifications were noted as a fundamental requirement for improving model development and design efficiency and ensuring model validity. It was further found that incorporating additional datasets, covering parameters related to the system, may serve to improve model accuracy, but could easily lead to compounded errors if not correctly parameterised or adequately validated

A suitability model for viticulture in England and Wales: opportunities for investment, sector growth and increased climate resilience

Despite continued investment and evidence of high quality wine production, English and Welsh wine grape yields remain low. To increase sector resilience to weather and climate risks we present the first combined terrestrial and climatic English and Welsh Viticulture Suitability (EWVS) model. Results show many existing vineyards (≥ 1 ha) are sub-optimally located. Limiting the model to the top 20% of suitable land in England and Wales resulted in 33,700 ha of prime viticulture land being identified, a scale just larger than the Champagne region of France. Beyond Kent and Sussex, large areas in Essex, with the warmest 30-year (1981–2010) Growing Season Average Temperature (13.9°C) on mainland Britain, and Suffolk, where few vineyards presently exist, appear especially suitable for viticulture. The EWVS model developed through this work allows, for the first time, a rapid assessment of land at local, regional and national scales to inform investment and policy related decisions

A general comprehensive evaluation method for cross-scale precipitation forecasts

With the development of refined numerical forecasts, problems such as score distortion due to the division of precipitation thresholds in both traditional and improved scoring methods for precipitation forecasts and the increasing subjective risk arising from the scale setting of the neighborhood spatial verification method have become increasingly prominent. To address these issues, a general comprehensive evaluation method (GCEM) is developed for cross-scale precipitation forecasts by directly analyzing the proximity of precipitation forecasts and observations in this study. In addition to the core indicator of the precipitation accuracy score (PAS), the GCEM system also includes score indices for insufficient precipitation forecasts, excessive precipitation forecasts, precipitation forecast biases, and clear/rainy forecasts. The PAS does not distinguish the magnitude of precipitation and does not delimit the area of influence; it constitutes a fair scoring formula with objective performance and can be suitable for evaluating rainfall events such as general and extreme precipitation. The PAS can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts, enabling the quantitative evaluation of the comprehensive capability of various refined precipitation forecasting products. Based on the GCEM, comparative experiments between the PAS and threat score (TS) are conducted for two typical precipitation weather processes. The results show that relative to the TS, the PAS better aligns with subjective expectations, indicating that the PAS is more reasonable than the TS. In the case of an extreme-precipitation event in Henan, China, two high-resolution models were evaluated using the PAS, TS, and fraction skill score (FSS), verifying the evaluation ability of PAS scoring for predicting extreme-precipitation events. In addition, other indices of the GCEM are utilized to analyze the range and extent of both insufficient and excessive forecasts of precipitation, as well as the precipitation forecasting ability for different weather processes. These indices not only provide overall scores similar to those of the TS for individual cases but also support two-dimensional score distribution plots which can comprehensively reflect the performance and characteristics of precipitation forecasts. Both theoretical and practical applications demonstrate that the GCEM exhibits distinct advantages and potential promotion and application value compared to the various mainstream precipitation forecast verification methods.</p

SURF: understanding and predicting urban convection and haze

Urbanization modifies atmospheric energy and moisture balances, forming distinct features, e.g., urban heat islands (UHIs) and enhanced or decreased precipitation. These produce significant challenges to science and society, including rapid and intense flooding, heat waves strengthened by UHIs, and air pollutant haze. The Study of Urban-Impacts on Rainfall and Fog/Haze (SURF) has brought together international expertise on observations and modeling, meteorology and atmospheric chemistry, and research and operational forecasting. The SURF overall science objective is a better understanding of urban, terrain, convection, and aerosol interactions for improved forecast accuracy. Specific objectives include: a) promoting cooperative international research to improve understanding of urban summer convective precipitation and winter particulate episodes via extensive field studies; b) improving high-resolution urban weather and air quality forecast-models; and c) enhancing urban weather forecasts for societal applications, e.g., health, energy, hydrologic, climate change, air quality, planning, and emergency-response management. Preliminary SURF observational and modeling results are shown, i.e., turbulent PBL structure, bifurcating thunderstorms, haze events, urban canopy model development, and model forecast evaluatio