Strength and Challenges of global model MPAS with regional mesh refinement for mid-latitude storm forecasting: a case study

With the rising share of renewable energy sources like wind energy in the energy mix, high-impact weather events like mid-latitude storms increasingly affect energy production, grid stability and safety and reliable forecasting becomes very relevant for e.g. transmission system operators to allow for actions to reduce imbalances. Traditionally, meteorological forecasts are provided by limited-area weather prediction models (LAMs), which can use high enough model resolution to represent the range of atmospheric scales of motions associated with such storm structures. While generally satisfactory, deterioration and insufficient deepening of large-scale storm structures are observed when they are introduced near the lateral boundaries of the LAM due to inadequate spatial and temporal interpolation. Global models with regional mesh refinement capabilities like the Model for Prediction Across Scales (MPAS) have the potential to provide an alternative, while avoiding sharp resolution jumps and lateral boundaries. In this study, MPAS' capabilities of simulating key evaluation metrics like storm intensity, storm location and storm duration are investigated based on a case study and assessed in comparison with buoy measurements, forecast products from the Climate Forecast System (CFSv2) and simulations with the Weather Research and Forecasting (WRF) LAM. Quasi-uniform and variable-resolution MPAS mesh configurations with different model physics settings are designed to analyze the impact of the mesh refinement and model physics on the model performance. MPAS shows good performance in predicting storm intensity based on the local minimum sea level pressure, while time of local minimum sea level pressure (storm duration) was generally estimated too late (too long) in comparison with the buoy measurements in part due to an early west-wards shift of the storm center in MPAS. The variable-resolution configurations showed a combination of an additional south-westwards shift and deviations in the sea level pressure field south-west of the storm center that introduced additional bias to the time of local minimum sea level pressure at some locations. The study highlights the need for a more detailed analysis of applied mesh refinements for particular applications and emphasizes the importance of methods like data assimilation techniques to prevent model drifts.

The relative influence of dune aspect ratio and beach width on dune erosion as a function of storm duration and surge level

Dune height is an important predictor of impact during a storm event given that taller dunes have a lower likelihood of being overtopped than shorter dunes. However, the temporal dominance of the wave collision regime, wherein volume loss (erosion) from the dune occurs through dune retreat without overtopping, suggests that dune width must also be considered when evaluating the vulnerability of dunes to erosion. We use XBeach, a numerical model that simulates hydrodynamic processes, sediment transport, and morphologic change, to analyze storm-induced dune erosion as a function of dune aspect ratio (i.e., dune height versus dune width) for storms of varying intensity and duration. We find that low aspect ratio (low and wide) dunes lose less volume than high aspect ratio (tall and narrow) dunes during longer and more intense storms when the beach width is controlled for. In managed dune scenarios, where sand fences are used to construct a “fenced” dune seaward of the existing “natural” dune, we find that fenced dunes effectively prevent the natural dune behind them from experiencing any volume loss until the fenced dune is sufficiently eroded, reducing the magnitude of erosion of the natural dune by up to 50 %. We then control for dune morphology to assess volume loss as a function of beach width and confirm that beach width exerts a significant influence on dune erosion; a wide beach offers the greatest protection from erosion in all circumstances while the width of the dune determines how long the dune will last under persistent scarping. These findings suggest that efforts to maintain a wide beach may be effective at protecting coastal communities from dune loss. However, a trade-off may exist in maintaining wide beaches and dunes in that the protection offered in the short-term must be considered in concert with potentially long-term detrimental effects of limiting overwash, a process which is critical to maintaining island elevation as sea level rises.

Improved SCS-CN Model Incorporating Storm Duration and Rainfall-based Initial Abstraction for Runoff Estimation

The need of incorporating storm intensity or duration in Soil Conservation Service Curve Number (SCS-CN) methodology for improved direct surface runoff estimation for a watershed has been highlighted by many engineers and hydrologists since long and despite this fact, it is still poorly explored. Therefore, this study aims to present storm duration-based improved SCS-CN models for estimating more accurate direct surface runoff from rainfall events. The accuracy and consistency of improved models are tested on a large rainfall-runoff dataset (18,660 rainfall events) derived from 39 watersheds in the USDA-ARS. Furthermore, the quantitative model’s performance is also evaluated employing six widely accepted statistical measures viz. root mean square error (RMSE), mean absolute error (MAE), normalized root mean square error (NRMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), observations standard deviation ratio (RSR), and several grading criteria. These models are compared with the original SCS-CN model (M1) and its simple form (M2) with traditionally fixed initial abstraction ratio (λ) as 0.2. The resulting lowest values of RMSE, NRMSE, MAE, NSE, PBIAS and highest values of RSR and ranking grading system (RGS) for the proposed models (M3-M5) reveal that their performance is better than M1 and M2 models. The proposed M5 model incorporating both storm duration and varying initial abstraction (Ia) as a certain percentage of rainfall, performed the best followed by M3 incorporating only storm duration. According to RGS, M5 also ranked first with the highest marks (195) followed by M3 (140). Due to high accuracy in predicted runoff, M5 can be recommended for both small and large watersheds as it overcomes the following issues: fixed λ (=0.2), assumption of constant rainfall intensity (time-independent), fixation of Ia at 2% of rainfall and applicability to only small watersheds, restricting the application of original SCS-CN and its modified versions.

Strength and Challenges of global model MPAS with regional mesh refinement for mid-latitude storm forecasting: A case study

<p>Mid-latitude storms are large-scale weather patterns. They involve a large range of spatial and temporal atmospheric scales of motion. Their characteristic extreme precipitation, wind gusts and high surface winds can significantly impact wind farms (e.g. shutdowns of turbines due to exceedance of cut-off wind speed) <span><span>affecting </span></span>grid performance and safety. Adequate storm forecasting, which relies on high spatial model resolution, is crucial. Traditional methods usually involve the use of limited area models (LAMs). While the performance of LAMs is generally satisfactory, challenges arise when large-scale storm structures enter near the the lateral boundaries of the LAM. In this case, insufficient update intervals of the forcing data at the lateral boundaries <!-- What does this mean exactly -->and spatial and temporal interpolation can deteriorate the storm structure that cause insufficient storm deepening. The global Model for Prediction Across Scales (MPAS) with regional mesh refinement avoids lateral boundary conditions and allows refinement with smooth transition zones. Based on a case study of storm “Christian”, MPAS’ capabilities in simulating key storm characteristics are explored in this work. Buoy measurements of sea level pressure, reanalysis and forecast products from the Climate Forecast System (CFSv2) and simulations with the Weather Research and Forecasting (WRF) model are used to evaluate the forecast performance with respect to storm intensity, storm arrival time and storm duration. A mesh configuration with refinement from 54-km to 18-km (further referred to as variable-resolution mesh) is compared with quasi-uniform mesh configurations to examine the impact of transition zone and mesh refinement on the storm structure and forecast performance. It is found that MPAS is generally able to predict the storm intensity based on the local minimum sea level pressure, while the estimation of storm arrival time and storm duration have been negatively influenced by model drifts in MPAS and by impacts of the transition zone on the storm development in the variable-resolution configuration. <!-- Can be shortened. -->An additional low pressure system emerged in the variable-resolution mesh <!-- May need to explain this to the readers. -->whereby its presence is sensitive to model physics. The investigation highlights the importance of the transition zone design in MPAS and the need for additional strategies like data assimilation techniques to prevent model drifts for storm forecasting.</p>

Local time and longitudinal differences in the occurrence frequency of ionospheric EMIC waves during magnetic storm periods

<div><span>The spatial and temporal distributions of ionospheric electromagnetic ion cyclotron (EMIC) waves during magnetic storms from 2014 to 2018 were studied using Swarm observations. Ionospheric EMIC waves preferably occurred during storms and their recovery phases at subauroral regions within an average magnetic latitude of 40°-55°. There were more wave events during more intense and longer period storms. However, the correlation between event number and storm duration was not good. This might be due to the effect of heavy oxygen ions on EMIC wave generation and the loss of ring current high-energy ions by the EMIC waves. There are obvious magnetic local time (MLT) differences in the peak occurrence frequency of EMIC waves during storm phases. The enhanced solar wind dynamic pressure was favorable for duskside EMIC waves. With an increased substorm activity the wave occurrence rate peak shifted from the morning side to the dusk-premidnight sector. During the recovery phase of a storm, EMIC waves in the 12-24 MLT sector appeare preferably in the earlier part than those in the 00-12 MLT sector. This shift in local time is related to the eastward rotation of the plasmaspheric plume towards morning during the late storm recovery phase and its overlap with the ring current.  Highest occurrence frequency of the storm time EMIC waves could be found in the South Atlantic Anomaly region, which might be related to the drift shell splitting </span></div><div><span>and the wave propagation effect </span><span>in the weak magnetic field region</span></div><div><span>.</span></div>

Long-term ice-rich permafrost coast sensitivity to air temperatures and storm influence: lessons from Pullen Island, N.W.T.

Response of erosive mechanisms to climate change is of mounting concern on Beaufort Sea coasts, which experience some of the highest erosion rates in the Arctic. Collapse of intact permafrost blocks and slumping within sprawling retrogressive thaw complexes are two predominant mechanisms that manifest as cliff retreat in this region. Using aerial imagery and ground survey data from Pullen Island, N.W.T., Canada, from 13 time points between 1947 and 2018, we observe increasing mean retreat rates from 0 ± 4.8 m/a in 1947 to 12 ± 0.3 m/a in 2018. Mean summer air temperature was positively correlated with cliff retreat over each time step via block failure (r2 = 0.08; p = 0.5) and slumping (r2 = 0.41; p = 0.05), as was mean storm duration with cliff retreat via block failure (r2 = 0.84; p = 0.0002) and slumping (r2 = 0.34; p = 0.08). These data indicate that air temperature has a greater impact in slump-dominated areas, while storm duration has greater control in areas of block failure. Increasingly heterogeneous cliff retreat rates are likely resulting from different magnitudes of response to climate trends depending on mechanism, and on geomorphological variations that prescribe occurrences of retrogressive thaw slumps.

Evaluation of Permeable Brick Pavement on the Reduction of Stormwater Runoff Using a Coupled Hydrological Model

In several cities, permeable brick pavement (PBP) plays a key role in stormwater management. Although various hydrological models can be used to analyze the mitigation efficiency of PBP on rainfall runoff, the majority do not consider the effect of multi-layered pavement on infiltration in urban areas. Therefore, we developed a coupled model to evaluate the potential effect of PBP in reducing stormwater runoff at a watershed scale. Specifically, we compared the hydrological responses (outflow and overflow) of three different PBP scenarios. The potential effects of PBP on peak flow (PF), total volume (TV), and overflow volume (OV) were investigated for 20 design rainstorms with different return periods and durations. Our results indicate that an increase in PBP ratio reduces both PF (4.2–13.5%) and TV (4.2–10.5%) at the outfall as well as the OV (15.4–30.6%) across networks. The mitigation effect of PBP on OV is linearly correlated to storm return period and duration, but the effects on PF and TV are inversely correlated to storm duration. These results provide insight on the effects of infiltration-based infrastructure on urban flooding.

Hydrodynamic Measurements of Propagating Waves at Different Nearshore Depths in Hujeong Beach, Korea

This paper reports the results of hydrodynamic measurements at two different water depths to observe wave properties in the course of wave propagation, especially during storm periods, in Hujeong Beach, Korea. In addition to hydrodynamic measurements, video monitoring data and satellite images from Sentinel-II were employed to compare the temporal changes in shoreline positions and shallow water bathymetry during the storms. Through combination of a variety of observational data sets, the accuracy of analysis could be enhanced by preventing possible misinterpretation. Two significant storms were observed from two experiments conducted at different times and locations of the beach. The hydrodynamic conditions were similar in both of the periods in terms of wave and current conditions as well as wave nonlinearity such as skewness. However, the response of shoreline during the two storms was the opposite because it was eroded during the first storm but advanced during the second storm. This suggests that other controlling factors such as storm duration need to be investigated to support the analysis of cross-shore sediment transport and consequent shoreline evolution for future studies.

An Improved SCS-CN Method Incorporating Slope, Soil Moisture, and Storm Duration Factors for Runoff Prediction

Soil Conservation Service Curve Number (SCS-CN) is a popular surface runoff prediction method because it is simple in principle, convenient in application, and easy to accept. However, the method still has several limitations, such as lack of a land slope factor, discounting the storm duration, and the absence of guidance on antecedent moisture conditions. In this study, an equation was developed to improve the SCS-CN method by combining the CN value with the tabulated CN2 value and three introduced factors (slope gradient, soil moisture, and storm duration). The proposed method was tested for calibration and validation with a dataset from three runoff plots in a watershed of the Loess Plateau. The results showed the model efficiencies of the proposed method were improved to 80.58% and 80.44% during the calibration and validation period, respectively, which was better than the standard SCS-CN and the other two modified SCS-CN methods where only a single factor of soil moisture or slope gradient was considered, respectively. Using the parameters calibrated and validated by dataset of the initial three runoff plots, the proposed method was then applied to runoff estimation of the remaining three runoff plots in another watershed. The proposed method reduced the root-mean-square error between the observed and estimated runoff values from 5.53 to 2.01 mm. Furthermore, the parameters of soil moisture (b1 and b2) is the most sensitive, followed by parameters in storm duration (c) and slope equations (a1 and a2), and the least sensitive parameter is the initial abstraction ratio λ on the basis of the proposed method sensitivity analysis. Conclusions can be drawn from the above results that the proposed method incorporating the three factors in the SCS method may estimate runoff more accurately in the Loess Plateau of China.