scholarly journals Modelling of orographic precipitation over Iberia: a springtime case study

2010 ◽  
Vol 25 ◽  
pp. 103-110 ◽  
Author(s):  
M. J. Costa ◽  
R. Salgado ◽  
D. Santos ◽  
V. Levizzani ◽  
D. Bortoli ◽  
...  
Keyword(s):  
Iberian Peninsula ◽  
Numerical Models ◽  
Model Performance ◽  
Warm Season ◽  
Atmospheric Model ◽  
Rain Gauge ◽  
Orographic Precipitation ◽  
Mountain Ranges ◽  
Simulated Precipitation

Abstract. Orographic precipitation is a result of very complex processes and its study using numerical models is of utmost importance since it can open an important avenue to the improvement of precipitation forecasts, especially during the warm season. Mainland Portugal is characterised by a very variable terrain between the north and south regions, the latter being much smoother, with sparse mountains that barely reach 1000 m. Conversely, several mountain ranges are distributed over Spain with heights often exceeding 1500 m altitude. A mesoscale non-hydrostatic atmospheric model (MesoNH) is used to study the orographic precipitation during a limited period in spring of 2002 over the Iberian Peninsula. In order to assess the effects of the mountains, case study simulations are done, with and without the orography. MesoNH is initialized and forced by the ECMWF analyses. The effects of orography on precipitation over neighbouring regions are also analyzed. Simulations show that orography is a key factor in determining the spatial distribution of precipitation over the Iberian Peninsula, with enhancements in the regions with mountain ranges and diminution or suppression over certain valleys. The simulated precipitation fields were visually compared with radar observations in central Portugal and quantitatively compared with rain gauge data all over Portugal in order to assess the model performance in the analyzed cases.

scholarly journals Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

2021 ◽  
Author(s):  
Ali Abdolali ◽  
Andre van der Westhuysen ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Aron Roland ◽  
...  
Keyword(s):  
Extreme Event ◽  
Numerical Models ◽  
Model Performance ◽  
Ground Truth ◽  
Wave Model ◽  
Atmospheric Model ◽  
Stationary Source ◽  
Source Point ◽  
Spectral Wave Model ◽  
Model Ensembles

AbstractVarious uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.

An Object-Based Approach for Quantification of GCM Biases of the Simulation of Orographic Precipitation. Part II: Quantitative Analysis

2015 ◽  
Vol 28 (12) ◽  
pp. 4863-4876 ◽  
Author(s):  
M. Soner Yorgun ◽  
Richard B. Rood
Keyword(s):  
Quantitative Analysis ◽  
Large Scale ◽  
Close Agreement ◽  
Evaluation Method ◽  
Qualitative Difference ◽  
Atmospheric Model ◽  
Orographic Precipitation ◽  
Object Based ◽  
Spectral Transform ◽  
Simulated Precipitation

Abstract An object-based evaluation method is applied to the simulated orographic precipitation for the idealized experimental setups using the National Center of Atmospheric Research (NCAR) Community Atmosphere Model (CAM) with the finite volume (FV) and Eulerian spectral transform dynamical cores with varying resolutions. The method consists of the application of k-means cluster analysis to the precipitation features to determine their spatial boundaries and the calculation of the semivariograms (SVs) for the isolated features for evaluation. The quantitative analysis revealed differences between the simulated precipitation by the FV and Eulerian spectral transform models that are not visually apparent. The simulated large-scale precipitation features of the idealized test cases provide analogs to orographic precipitation features observed in simulations of Atmospheric Model Intercomparison Project (AMIP) models. The spatial boundaries of these features (determined by k-means clustering) for Eulerian spectral T85 and T170 resolutions revealed the level of merger between the two large-scale features simulated because of each peak in the double mountain idealized setup. Both FV 1° and 0.5° resolutions were able to simulate the dryer region between the two mountains. The SVs of precipitation for the single and double mountain setups show close agreement between FV 1°, FV 0.5°, and Eulerian spectral T170 resolutions; however, Eulerian spectral T85 simulated the precipitation in lower intensity, indicating the qualitative difference in resolutions previously determined to be equivalent. Such close agreement was not observed in the more realistic idealized setup.

scholarly journals Comparison of Hydrologic Model Performance Statistics Using Rain Gauge and NEXRAD Precipitation Input at Different Watershed Spatial Scales and Rainfall Return Frequencies for the Upper St. Johns River, Florida USA

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 11
Author(s):  
Amanda Bredesen ◽  
Christopher J. Brown
Keyword(s):  
Spatial Scale ◽  
Model Simulation ◽  
Numerical Models ◽  
Spatial Scales ◽  
Model Performance ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Precipitation Data ◽  
Remotely Sensed Data ◽  
Model Input

Water resources numerical models are dependent upon various input hydrologic field data. As models become increasingly complex and model simulation times expand, it is critical to understand the inherent value in using different input datasets available. One important category of model input is precipitation data. For hydrologic models, the precipitation data inputs are perhaps the most critical. Common precipitation model input includes either rain gauge or remotely-sensed data such next-generation radar-based (NEXRAD) data. NEXRAD data provides a higher level of spatial resolution than point rain gauge coverage, but is subject to more extensive data pre and post processing along with additional computational requirements. This study first documents the development and initial calibration of a HEC-HMS model of a subtropical watershed in the Upper St. Johns River Basin in Florida, USA. Then, the study compares calibration performance of the same HEC-HMS model using either rain gauge or NEXRAD precipitation inputs. The results are further discretized by comparing key calibration statistics such as Nash–Sutcliffe Efficiency for different spatial scale and at different rainfall return frequencies. The study revealed that at larger spatial scale, the calibration performance of the model was about the same for the two different precipitation datasets while the study showed some benefit of NEXRAD for smaller watersheds. Similarly, the study showed that for smaller return frequency precipitation events, NEXRAD data was superior.

scholarly journals Combining TRMM and Surface Observations of Precipitation: Technique and Validation over South America

2010 ◽  
Vol 25 (3) ◽  
pp. 885-894 ◽  
Author(s):  
José Roberto Rozante ◽  
Demerval Soares Moreira ◽  
Luis Gustavo G. de Goncalves ◽  
Daniel A. Vila
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Spatial Scales ◽  
Model Performance ◽  
Evaluation Process ◽  
Tropical Rainfall Measuring Mission ◽  
Atmospheric Model ◽  
Continuous Assessment ◽  
Precipitation Estimates ◽  
Surface Observations

Abstract The measure of atmospheric model performance is highly dependent on the quality of the observations used in the evaluation process. In the particular case of operational forecast centers, large-scale datasets must be made available in a timely manner for continuous assessment of model results. Numerical models and surface observations usually work at distinct spatial scales (i.e., areal average in a regular grid versus point measurements), making direct comparison difficult. Alternatively, interpolation methods are employed for mapping observational data to regular grids and vice versa. A new technique (hereafter called MERGE) to combine Tropical Rainfall Measuring Mission (TRMM) satellite precipitation estimates with surface observations over the South American continent is proposed and its performance is evaluated for the 2007 summer and winter seasons. Two different approaches for the evaluation of the performance of this product against observations were tested: a cross-validation subsampling of the entire continent and another subsampling of only areas with sparse observations. Results show that over areas with a high density of observations, the MERGE technique’s performance is equivalent to that of simply averaging the stations within the grid boxes. However, over areas with sparse observations, MERGE shows superior results.

scholarly journals Distribution and Mechanisms of Orographic Precipitation Associated with Typhoon Morakot (2009)

2013 ◽  
Vol 70 (9) ◽  
pp. 2894-2915 ◽  
Author(s):  
Cheng-Ku Yu ◽  
Lin-Wen Cheng
Keyword(s):  
Doppler Radar ◽  
Rain Gauge ◽  
Orographic Precipitation ◽  
Typhoon Morakot ◽  
Study Region ◽  
Mountain Ranges ◽  
Physical Mechanisms ◽  
Orographic Enhancement ◽  
Microphysical Processes ◽  
Precipitation Enhancement

Abstract Using a combination of Doppler radar observations and rain gauge data, this study documents detailed aspects of the orographic precipitation associated with Typhoon Morakot (2009). Rainfall distribution over underlying topographical features and possible physical mechanisms responsible for the observed orographic enhancement are explored. The study region constitutes an approximately two-dimensional, south–north-oriented orographic barrier with higher, wider (lower, narrower) terrain features in its northern (southern) portions (i.e., the northern and southern barriers). Upstream conditions were characterized by abundant typhoon background precipitation embedded within strong, nearly saturated westerly to west-southwesterly oncoming flow. The observations show that a wide area of topographically enhanced precipitation and the rainfall maxima were confined to the windward slopes of the northern barrier, whereas the strongest rainfall tended to occur near and/or slightly downstream of the mountain crest of the southern barrier. Quantitative analysis indicates that upslope lifting may explain the observed precipitation enhancement over the northern barrier; however, this mechanism was found to be less relevant to precipitation enhancement for the southern barrier. The characteristics of the enhanced precipitation observed over the southern barrier are, instead, consistent with the theoretical prediction of the seeder–feeder process. In this context, the degree of orographic enhancement was shown to be proportional to the intensity of the typhoon background precipitation multiplied by the oncoming wind speed. The results suggest that for the tropical cyclone environment, understanding and predicting rainfall over narrow, low mountain ranges is particularly challenging because it involves complex dynamical and microphysical processes.

Orographic Enhancement of Precipitation over Low Mountain Ranges. Part I: Model Formulation and Idealized Simulations

2006 ◽  
Vol 45 (8) ◽  
pp. 1025-1040 ◽  
Author(s):  
Michael Kunz ◽  
Christoph Kottmeier
Keyword(s):  
Moisture Loss ◽  
Horizontal Wind ◽  
Diagnostic Model ◽  
Model Parameters ◽  
Orographic Precipitation ◽  
Ambient Conditions ◽  
Physical Processes ◽  
Mountain Ranges ◽  
Simulated Precipitation ◽  
Low Mountain Ranges

Abstract A diagnostic model for simulating orographic precipitation over low mountain ranges is presented. It is based on linear theory of hydrostatic flow over mountains and calculates condensation rates from vertical lifting at the different model layers. Several other physical processes, such as hydrometeor drifting, evaporation, and moisture loss, are incorporated in the model by simple parameterizations. Idealized simulations of precipitation with different model performances provide insight into the physical processes of orographic precipitation. Evaporation, in combination with hydrometeor drifting into descent regions, is identified as one of the key aspects that primarily determine the spatial distribution of precipitation. The variability in orographic precipitation that results from changes in model parameters and ambient conditions is investigated in sensitivity studies. Simulated intensities as well as their spatial distributions are very sensitive to the temperature T0 at the lowest layer and to the variables that define the Froude number Frm: the horizontal wind speed U, static stability Nm, and mountain height H. Most of the parameters exhibit a nonlinear relation to the simulated precipitation intensities. Relative to ambient conditions, orographic precipitation is found to be less sensitive to changes in formation time tice, terminal velocity of ice particles υice, and melting level Δz. In each case, the sensitivities of simulation results strongly depend on the location in the model domain.

scholarly journals Extreme Rainfall over Complex Terrain: An Application of the Linear Model of Orographic Precipitation to a Case Study in the Italian Pre-Alps

Geosciences ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 18
Author(s):  
Andrea Abbate ◽  
Monica Papini ◽  
Laura Longoni
Keyword(s):  
Complex Terrain ◽  
Extreme Event ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Orographic Precipitation ◽  
Mountain Areas ◽  
Rainfall Extremes ◽  
Realistic Description ◽  
Terrain Elevation

Intense meteorological events are the primary cause of geohazard phenomena in mountain areas. In this paper, we present a study of the intense rainfall event that occurred in the provinces of Lecco and Sondrio from 11 to 12 June 2019. The aim of our work is to understand the effect of local topography on the spatial distribution of rainfall and to attempt the reconstruction of a realistic rainfall field relative to that extreme event. This task represents a challenge in the context of complex orography. Classical rain-gauge interpolation techniques, such as Kriging, may be too approximate, while meteorological models can be complex and often unable to accurately predict rainfall extremes. For these reasons, we tested the linear upslope model (LUM) designed for estimating rainfall records in orographic precipitation. This model explicitly addresses the dependence of rainfall intensification caused by the terrain elevation. In our case study, the available radio sounding data identified the convective nature of the event with a sustained and moist southern flow directed northward across the Pre-Alps, resulting in an orographic uplift. The simulation was conducted along a smoothed elevation profile of the local orography. The result was a reliable reconstruction of the rainfall field, validated with the ground-based rain gauge data. The error analysis revealed a good performance of the LUM with a realistic description of the interaction between the airflow and local orography. The areas subjected to rainfall extremes were correctly identified, confirming the determinant role of complex terrain in precipitation intensification.

SEISMIC RISK AND RESILIENCE ASSESSMENT OF INDUSTRIAL FACILITIES: CASE STUDY ON A BLACK CARBON PLANT

2020 ◽  
Author(s):  
George Karagiannakis
Keyword(s):  
Seismic Risk ◽  
Numerical Models ◽  
Fragility Curves ◽  
Human Life ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Risk And Resilience ◽  
Industrial Plants ◽  
Plant Equipment

This paper deals with state of the art risk and resilience calculations for industrial plants. Resilience is a top priority issue on the agenda of societies due to climate change and the all-time demand for human life safety and financial robustness. Industrial plants are highly complex systems containing a considerable number of equipment such as steel storage tanks, pipe rack-piping systems, and other installations. Loss Of Containment (LOC) scenarios triggered by past earthquakes due to failure on critical components were followed by severe repercussions on the community, long recovery times and great economic losses. Hence, facility planners and emergency managers should be aware of possible seismic damages and should have already established recovery plans to maximize the resilience and minimize the losses. Seismic risk assessment is the first step of resilience calculations, as it establishes possible damage scenarios. In order to have an accurate risk analysis, the plant equipment vulnerability must be assessed; this is made feasible either from fragility databases in the literature that refer to customized equipment or through numerical calculations. Two different approaches to fragility assessment will be discussed in this paper: (i) code-based Fragility Curves (FCs); and (ii) fragility curves based on numerical models. A carbon black process plant is used as a case study in order to display the influence of various fragility curve realizations taking their effects on risk and resilience calculations into account. Additionally, a new way of representing the total resilience of industrial installations is proposed. More precisely, all possible scenarios will be endowed with their weighted recovery curves (according to their probability of occurrence) and summed together. The result is a concise graph that can help stakeholders to identify critical plant equipment and make decisions on seismic mitigation strategies for plant safety and efficiency. Finally, possible mitigation strategies, like structural health monitoring and metamaterial-based seismic shields are addressed, in order to show how future developments may enhance plant resilience. The work presented hereafter represents a highly condensed application of the research done during the XP-RESILIENCE project, while more detailed information is available on the project website https://r.unitn.it/en/dicam/xp-resilience.

scholarly journals Optimizing the Environmental and Economic Sustainability of Remote Community Infrastructure

2020 ◽  
Vol 12 (6) ◽  
pp. 2208 ◽  
Author(s):  
Jamie E. Filer ◽  
Justin D. Delorit ◽  
Andrew J. Hoisington ◽  
Steven J. Schuldt
Keyword(s):  
Environmental Impacts ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Assessment Model ◽  
Remote Communities ◽  
Remote Community ◽  
Rural Villages ◽  
Sustainable Technologies ◽  
Study Results

Remote communities such as rural villages, post-disaster housing camps, and military forward operating bases are often located in remote and hostile areas with limited or no access to established infrastructure grids. Operating these communities with conventional assets requires constant resupply, which yields a significant logistical burden, creates negative environmental impacts, and increases costs. For example, a 2000-member isolated village in northern Canada relying on diesel generators required 8.6 million USD of fuel per year and emitted 8500 tons of carbon dioxide. Remote community planners can mitigate these negative impacts by selecting sustainable technologies that minimize resource consumption and emissions. However, the alternatives often come at a higher procurement cost and mobilization requirement. To assist planners with this challenging task, this paper presents the development of a novel infrastructure sustainability assessment model capable of generating optimal tradeoffs between minimizing environmental impacts and minimizing life-cycle costs over the community’s anticipated lifespan. Model performance was evaluated using a case study of a hypothetical 500-person remote military base with 864 feasible infrastructure portfolios and 48 procedural portfolios. The case study results demonstrated the model’s novel capability to assist planners in identifying optimal combinations of infrastructure alternatives that minimize negative sustainability impacts, leading to remote communities that are more self-sufficient with reduced emissions and costs.

scholarly journals Seed Exchange as an Agrobiodiversity Conservation Mechanism. A Case Study in Vall Fosca, Catalan Pyrenees, Iberian Peninsula

2012 ◽  
Vol 17 (1) ◽  
Author(s):  
Laura Calvet-Mir ◽  
Maria Calvet-Mir ◽  
José Luis Molina ◽  
Victoria Reyes-García
Keyword(s):  
Iberian Peninsula ◽  
Seed Exchange ◽  
Agrobiodiversity Conservation
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