scholarly journals Quantifying Extreme Precipitation Forecasting Skill in High-Resolution Models Using Spatial Patterns: A Case Study of the 2016 and 2018 Ellicott City Floods

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 136
Author(s):  
Stephanie E. Zick
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Extreme Precipitation ◽  
Stage Iv ◽  
Precipitation Forecasting ◽  
Object Based ◽  
Detailed Surface ◽  
Spatial Attributes ◽  
High Resolution Models ◽  
Environmental Prediction

Recent historic floods in Ellicott City, MD, on 30 July 2016 and 27 May 2018 provide stark examples of the types of floods that are expected to become more frequent due to urbanization and climate change. Given the profound impacts associated with flood disasters, it is crucial to evaluate the capability of state-of-the-art weather models in predicting these hydrometeorological events. This study utilizes an object-based approach to evaluate short range (<12 h) hourly forecast precipitation from the High-Resolution Rapid Refresh (HRRR) versus observations from the National Centers for Environmental Prediction (NCEP) Stage IV precipitation analysis. For both datasets, a binary precipitation field is delineated using thresholds that span trace to extreme precipitation rates. Next, spatial metrics of area, perimeter, solidity, elongation, and fragmentation, as well as centroid positions for the forecast and observed fields are calculated. A Mann–Whitney U-test reveals biases (using a confidence level of 90%) related to the spatial attributes and locations of model forecast precipitation. Results indicate that traditional pixel-based precipitation verification metrics are limited in their ability to quantify and characterize model skill. In contrast, an object-based methodology offers encouraging results in that the HRRR can skillfully predict the extreme precipitation rates that are anticipated with anthropogenic climate change. Yet, there is still room for improvement, since model forecasts of extreme convective rainfall tend to be slightly too numerous and fragmented compared with observations. Lastly, results are sensitive to the HRRR model’s representation of synoptic-scale and mesoscale processes. Therefore, detailed surface analyses and an “ingredients-based” approach should remain central to the process of forecasting excessive rainfall.

scholarly journals Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Historical Period ◽  
Mountainous Regions ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

scholarly journals The importance of model resolution on simulated precipitation in Europe – from global to regional model

2020 ◽  
Author(s):  
Gustav Strandberg ◽  
Petter Lind
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Horizontal Resolution ◽  
Model Resolution ◽  
Simulated Precipitation ◽  
The Difference ◽  
Model Ensembles ◽  
High Resolution Models

Abstract. Precipitation, and especially extreme precipitation, is a key climate variable as it effects large parts of society. It is difficult to simulate in a climate model because of its large variability in time and space. This study investigates the importance of model resolution on the simulated precipitation in Europe for a wide range of climate model ensembles: from global climate models (GCM) at horizontal resolution of around 300 km to regional climate models (RCM) at horizontal resolution of 12.5 km. The aim is to investigate the differences between models and model ensembles, but also to evaluate their performance compared to gridded observations from E-OBS. Model resolution has a clear effect on precipitation. Generally, extreme precipitation is more intense and more frequent in high-resolution models compared to low-resolution models. Models of low resolution tend to underestimate intense precipitation. This is improved in high-resolution simulations, but there is a risk that high resolution models overestimate precipitation. This effect is seen in all ensembles, and GCMs and RCMs of similar resolution give similar results. The number of precipitation days, which is more governed by large-scale atmospheric flow, is not dependent on model resolution, while the number of days with heavy precipitation is. The difference between different models is often larger than between the low- and high-resolution versions of the same model, which makes it difficult to quantify the improvement. In this sense the quality of an ensemble is depending more on the models it consists of rather than the average resolution of the ensemble. Furthermore, the difference in simulated precipitation between an RCM and the driving GCM depend more on the choice of RCM and less on the down-scaling itself; as different RCMs driven by the same GCM may give different results. The results presented here are in line with previous similar studies but this is the first time an analysis like this is done across such relatively large model ensembles of different resolutions, and with a method studying all parts of the precipitation distribution.

scholarly journals How Do Continuous High-Resolution Models of Patchy Seabed Habitats Enhance Classification Schemes?

Geosciences ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 237 ◽  
Author(s):  
Gustav Kågesten ◽  
Dario Fiorentino ◽  
Finn Baumgartner ◽  
Lovisa Zillén
Keyword(s):  
High Resolution ◽  
Multiple Scales ◽  
Natura 2000 ◽  
Boosted Regression Trees ◽  
Biological Information ◽  
Classification Schemes ◽  
Object Based ◽  
Thematic Resolution ◽  
High Resolution Models ◽  
The Baltic

Predefined classification schemes and fixed geographic scales are often used to simplify and cost-effectively map the spatial complexity of nature. These simplifications can however limit the usefulness of the mapping effort for users who need information across a different range of thematic and spatial resolutions. We demonstrate how substrate and biological information from point samples and photos, combined with continuous multibeam data, can be modeled to predictively map percentage cover conforming with multiple existing classification schemes (i.e., HELCOM HUB; Natura 2000), while also providing high-resolution (5 m) maps of individual substrate and biological components across a 1344 km2 offshore bank in the Baltic Sea. Data for substrate and epibenthic organisms were obtained from high-resolution photo mosaics, sediment grab samples, legacy data and expert annotations. Environmental variables included pixel and object based metrics at multiple scales (0.5 m–2 km), which improved the accuracy of models. We found that using Boosted Regression Trees (BRTs) to predict continuous models of substrate and biological components provided additional detail for each component without losing accuracy in the classified maps, compared with a thematic model. Results demonstrate the sensitivity of habitat maps to the effects of spatial and thematic resolution and the importance of high-resolution maps to management applications.

scholarly journals Overview of spatial verification methods and their application to ensemble forecasting

2021 ◽  
Vol 4 ◽  
pp. 30-49
Author(s):  
A.Yu. Bundel ◽  
◽  
A.V. Muraviev ◽  
E.D. Olkhovaya ◽  
◽  
...  
Keyword(s):  
High Resolution ◽  
Ensemble Forecasting ◽  
Object Based ◽  
Verification Methods ◽  
International Projects ◽  
Resolution Model ◽  
High Gradients ◽  
High Resolution Models ◽  
High Degree ◽  
Spatial Verification

State-of-the-art high-resolution NWP models simulate mesoscale systems with a high degree of detail, with large amplitudes and high gradients of fields of weather variables. Higher resolution leads to the spatial and temporal error growth and to a well-known double penalty problem. To solve this problem, the spatial verification methods have been developed over the last two decades, which ignore moderate errors (especially in the position), but can still evaluate the useful skill of a high-resolution model. The paper refers to the updated classification of spatial verification methods, briefly describes the main methods, and gives an overview of the international projects for intercomparison of the methods. Special attention is given to the application of the spatial approach to ensemble forecasting. Popular software packages are considered. The Russian translation is proposed for the relevant English terms. Keywords: high-resolution models, verification, double penalty, spatial methods, ensemble forecasting, object-based methods

scholarly journals 21st Century Projections of Extreme Precipitation Indicators for Cyprus

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 343 ◽  
Author(s):  
George Zittis ◽  
Adriana Bruggeman ◽  
Corrado Camera
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
High Resolution ◽  
21St Century ◽  
Extreme Precipitation ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Daily Rainfall ◽  
Climatic Conditions ◽  
The Impact

According to observational and model-based studies, the eastern Mediterranean region is one of the most prominent climate-change hotspots in the world. The combined effect of warming and drying is expected to augment the regional impacts of global warming. In addition to changes in mean climatic conditions, global warming is likely to induce changes in several aspects of extreme rainfall such as duration and magnitude. In this context, we explore the impact of climate change on precipitation with the use of several indicators. We focus on Cyprus, a water-stressed island located in the eastern Mediterranean Basin. Our results are derived from a new high-resolution simulation for the 21st century, which is driven by a “business-as-usual” scenario. In addition to a strong temperature increase (up to 4.1 °C), our analysis highlights that, on average for the island, most extreme precipitation indicators decrease, suggesting a transition to much drier conditions. The absolute daily rainfall maxima exhibit strong local variability, indicating the need for high resolution simulations to understand the potential impacts on future flooding.

Differences in representation of extreme precipitation events in two high resolution models

2021 ◽  
Author(s):  
Emma D. Thomassen ◽  
Elizabeth J. Kendon ◽  
Hjalte J. D. Sørup ◽  
Steven C. Chan ◽  
Peter L. Langen ◽  
...  
Keyword(s):  
High Resolution ◽  
Extreme Precipitation ◽  
Extreme Precipitation Events ◽  
High Resolution Models ◽  
Precipitation Events

scholarly journals Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?

2016 ◽  
Vol 20 (9) ◽  
pp. 3843-3857 ◽  
Author(s):  
Hossein Tabari ◽  
Rozemien De Troch ◽  
Olivier Giot ◽  
Rafiq Hamdi ◽  
Piet Termonia ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Impact Analysis ◽  
Climate Models ◽  
Daily Precipitation ◽  
Reanalysis Data ◽  
Precipitation Extremes ◽  
Added Value ◽  
Intensity Duration Frequency ◽  
High Resolution Models

Abstract. This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3–4 km are compared with those from the coarse-scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. Validation of historical design precipitation statistics derived from intensity–duration–frequency (IDF) curves shows a better match of the convection-permitting model results with the observations-based IDF statistics compared to the driving GCMs and reanalysis data. This is the case for simulation of local sub-daily precipitation extremes during the summer season, while the convection-permitting models do not appear to bring added value to simulation of daily precipitation extremes. Results moreover indicate that one has to be careful in assuming spatial-scale independency of climate change signals for the delta change downscaling method, as high-resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the timescale, since such intensification is not observed for daily timescales for both the ALARO and CCLM models.

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