scholarly journals Climatology of Near‐Surface Daily Peak Wind Gusts Across Scandinavia: Observations and Model Simulations

2021 ◽  
Vol 126 (7) ◽  
Author(s):  
Lorenzo Minola ◽  
Cesar Azorin‐Molina ◽  
Jose A. Guijarro ◽  
Gangfeng Zhang ◽  
Seok‐Woo Son ◽  
...  
Keyword(s):  
Near Surface ◽  
Model Simulations ◽  
Wind Gusts

Estimating the Risk of Extreme Wind Gusts in Tropical Cyclones Using Idealized Large-Eddy Simulations and a Statistical-Dynamical Model

2021 ◽  
Author(s):  
Daniel P. Stern ◽  
George H. Bryan ◽  
Chia-Ying Lee ◽  
James D. Doyle
Keyword(s):  
Tropical Cyclones ◽  
The United States ◽  
Large Eddy Simulations ◽  
Dynamical Model ◽  
Near Surface ◽  
Southeastern Us ◽  
Wind Gusts ◽  
Extreme Wind ◽  
Large Eddy

AbstractRecent studies have shown that extreme wind gusts are ubiquitous within the eyewall of intense tropical cyclones (TCs). These gusts pose a substantial hazard to human life and property, but both the short-term (i.e., during the passage of a single TC) and long-term (over many years) risk of encountering such a gust at a given location is poorly understood. Here, simulated tower data from large-eddy simulations of idealized TCs in a quiescent (i.e., no mean flow or vertical wind shear) environment are used to estimate these risks for the offshore region of the United States. For both a category 5 and category 3 TC, there is a radial region where nearly all simulated towers experience near-surface (the lowest 200 m) 3-s gusts exceeding 70 m s−1 within a 10-minute period; on average, these towers respectively sample peak 3-s gusts of 110 and 80 m s−1. Analysis of an observational dropsonde database supports the idealized simulations, and indicates that offshore structures (such as wind turbines) in the eyewall of a major hurricane are likely to encounter damaging wind speeds. This result is then incorporated into an estimate of the long-term risk, using analyses of the return period for major hurricanes from both a best-track database and a statistical-dynamical model forced by reanalysis. For much of the nearshore region of the Gulf of Mexico and southeastern US coasts, this analysis yields an estimate of a 30-60% probability of any given point experiencing at least one 70 m s−1 gust within a 30-year period.

scholarly journals Cloud-resolving-model simulations of nocturnal precipitation over the Himalayan slopes and foothills

2021 ◽  
Author(s):  
Shiori Sugimoto ◽  
Kenichi Ueno ◽  
Hatsuki Fujinami ◽  
Tomoe Nasuno ◽  
Tomonori Sato ◽  
...  
Keyword(s):  
Moisture Transport ◽  
Wrf Model ◽  
Synoptic Scale ◽  
Reanalysis Dataset ◽  
Near Surface ◽  
Model Simulations ◽  
Lower Elevation ◽  
Circulation Patterns ◽  
Downslope Wind ◽  
Cloud Resolving Model

AbstractA numerical experiment with a 2-km resolution was conducted using the Weather Research and Forecasting (WRF) model to investigate physical processes driving nocturnal precipitation over the Himalayas during the mature monsoon seasons between 2003 and 2010. The WRF model simulations of increases in precipitation twice a day, one in the afternoon and another around midnight, over the Himalayan slopes, and of the single nocturnal peak over the Himalayan foothills were reasonably accurate. To understand the synoptic-scale moisture transport and its local-scale convergence generating the nocturnal precipitation, composite analyses were conducted using the reanalysis dataset and model outputs. In the synoptic scale, moisture transport associated with the westward propagation of low pressure systems was found when nocturnal precipitation dominated over the Himalayan slopes. In contrast, moisture was directly provided from the synoptic-scale monsoon westerlies for nocturnal precipitation over the foothills. The model outputs suggested that precipitation occurred on the mountain ridges in the Himalayas during the afternoon, and expanded horizontally towards lower-elevation areas through the night. During the nighttime, the downslope wind was caused by radiative cooling at the surface and was intensified by evaporative cooling by hydrometeors in the near-surface layer. As a result, convergence between the downslope wind and the synoptic-scale flow promoted nocturnal precipitation over the Himalayas and to the south, as well as the moisture convergence by orography and/or synoptic-scale circulation patterns. The nocturnal precipitation over the Himalayas was not simulated well when we used the coarse topographic resolution and the smaller number of vertical layers.

scholarly journals Weather extremes over Europe under 1.5 and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2021 ◽  
Vol 12 (2) ◽  
pp. 457-468
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Climate Indices ◽  
Weather Extremes ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel dataset of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. This is a unique and physically consistent dataset, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100×10-year simulations and 25×10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. To demonstrate how adaptation-relevant information can be derived from the HAPPI dataset, changes in four climate indices for periods with 1.5 and 2.0 ∘C global warming are quantified. These indices include number of days per year with daily mean near-surface apparent temperature of >28 ∘C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-year return period (RI50yr); and the annual consecutive dry days (CDDs). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature-related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 ∘C.

Evaluation of boundary-layer and urban-canopy parameterizations for simulating wind in Miami during Hurricane Irma (2017)

2021 ◽  
Author(s):  
Eric A. Hendricks ◽  
Jason C. Knievel ◽  
David S. Nolan
Keyword(s):  
Boundary Layer ◽  
Urban Environment ◽  
Weather Prediction ◽  
Urban Canopy ◽  
Surface Velocity ◽  
Urban Region ◽  
Near Surface ◽  
Model Simulations ◽  
Closure Scheme ◽  
Hurricane Irma

AbstractThe simulated winds within the urban canopy of landfalling tropical cyclones are sensitive to the representation of the planetary-boundary and urban-canopy layers in numerical weather prediction models. In order to assess the sub-grid-scale parameterizations of these layers, mesoscale model simulations were executed and evaluated against near-surface observations as the outer wind field of Hurricane Irma (2017) interacted with the built-up region from downtown Miami northward to West Palm Beach. Four model simulations were examined, comprised of two different planetary boundary layer (PBL) parameterizations (a local closure scheme with turbulent kinetic energy prediction and a nonlocal closure scheme) and two different urban canopy models (UCMs) [a zeroth order bulk scheme and a multilayer Building Effect Parameterization (BEP) that mimics the three-dimensionality of buildings]. Overall, the simulated urban canopy winds were weakly sensitive to the PBL scheme and strongly sensitive to the UCM. The bulk simulations compared most favorably to an analyzed wind swath in the urban environment, while the BEP simulations had larger negative biases in the same region. There is uncertainty in magnitude of the urban environment biases due to the lack of many urban sheltered measurements in the wind swath analysis. Biases in the rural environment were similar among the bulk and BEP simulations. An improved comparison with the analyzed wind swath in the urban region was obtained by reducing the drag coefficient in BEP in one of the PBL schemes. The usefulness of BEP was demonstrated in its ability to predict realistic heterogeneous near-surface velocity patterns in urban regions.

scholarly journals Weather extremes over Europe under 1.5 °C and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2020 ◽  
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Weather Extremes ◽  
Data Set ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel data set of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. The data set provides a unique and physically consistent data set, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100 × 10-year simulations and 25 × 10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. The changes in four climate indices for temperature targets of 1.5 °C and 2.0 °C global warming are quantified: number of days per year with daily mean near-surface apparent temperature of > 28 °C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-yr return period (RI50yr); and the annual Consecutive Dry Days (CDD). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at a policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 °C.

scholarly journals Influence of Soil Moisture on Urban Microclimate and Surface-Layer Meteorology in Oklahoma City

2014 ◽  
Vol 53 (1) ◽  
pp. 83-98 ◽  
Author(s):  
Syed Zahid Husain ◽  
Stéphane Bélair ◽  
Sylvie Leroyer
Keyword(s):  
Surface Layer ◽  
Soil Moisture ◽  
Wind Speed ◽  
Urban Soil ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Oklahoma City ◽  
Near Surface ◽  
Model Simulations ◽  
Urban Surface Layer

AbstractThe influence of soil moisture on the surface-layer atmosphere is examined in this paper by analyzing the outputs of model simulations for different initial soil moisture configurations, with particular emphasis on urban microclimate. In addition to a control case, four different soil moisture distributions within the urban and surrounding rural areas are considered in this study. Outputs from the Global Environmental Multiscale atmospheric model simulations are compared with observations from the Joint Urban 2003 experiment held in Oklahoma City, Oklahoma, and the relevant conclusions drawn in this paper are therefore valid for similar medium-size cities. In general, high soil moisture is found to be associated with colder near-surface temperature and lower near-surface wind speed, whereas drier soil resulted in warmer temperatures and enhanced low-level wind. Relative to urban soil moisture content, rural soil conditions are predicted to have larger impacts on both rural and urban surface-layer meteorological conditions. Dry rural and wet urban soil configurations are shown to have a strong influence on the urban–rural temperature contrast and resulted in city-induced secondary circulations that considerably affect the near-surface wind speed. Dry rural soil in particular is found to intensify the nocturnal low-level jet and significantly affect the thermal stability of nocturnal near-neutral urban surface layer by altering both thermal and mechanical generation of turbulence.

scholarly journals Reliability of regional climate model simulations of extremes and of long-term climate

2004 ◽  
Vol 4 (3) ◽  
pp. 417-431 ◽  
Author(s):  
U. Böhm ◽  
M. Kücken ◽  
D. Hauffe ◽  
F.-W. Gerstengarbe ◽  
P. C. Werner ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Model ◽  
Northeastern Brazil ◽  
Near Surface ◽  
Surface Parameters ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Niño event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near-surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our methodology to be applied as a common test bed to different fields of research in regional climate modeling.

scholarly journals Five Years of Spatially Resolved Ground-Based MAX-DOAS Measurements of Nitrogen Dioxide in the Urban Area of Athens: Synergies with In Situ Measurements and Model Simulations

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1634
Author(s):  
Myrto Gratsea ◽  
Eleni Athanasopoulou ◽  
Anastasia Kakouri ◽  
Andreas Richter ◽  
Andre Seyler ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Urban Area ◽  
In Situ Measurements ◽  
Scale Model ◽  
Urban Background ◽  
Near Surface ◽  
Model Simulations ◽  
Different Seasons ◽  
In Situ Observations

Long-term nitrogen dioxide (NO2) slant column density measurements using the MAX-DOAS (multi-axis differential optical absorption spectroscopy) technique were analyzed in order to demonstrate the temporal and horizontal variability of the trace gas in Athens for the period October 2012–July 2017. The synergy with in situ measurements and model simulations was exploited for verifying the MAX-DOAS technique and its ability to assess the spatiotemporal characteristics of NO2 pollution in the city. Tropospheric NO2 columns derived from ground-based MAX-DOAS observations in two horizontal and five vertical viewing directions were compared with in situ chemiluminescence measurements representative of urban, urban background and suburban conditions; a satisfactory correlation was found for the urban (r ≈ 0.55) and remote areas (r ≈ 0.40). Mean tropospheric slant columns retrieved from measurements at the lowest elevation over the urban area ranged from 0.1 to 32 × 1016 molec cm−2. The interannual variability showed a rate of increase of 0.3 × 1016 molec cm−2 per year since 2012 in the urban area, leading to a total increase of 20%. The retrieved annual cycles captured the seasonal variability with lower NO2 levels in summer, highly correlated (r ≈ 0.85) with the urban background and suburban in situ observations. The NO2 diurnal variation for different seasons exhibited varied patterns, indicating the different role of photochemistry and anthropogenic activities in the different seasons. Compared to in situ observations, the MAX-DOAS NO2 morning peak occurred with a one-hour delay and decayed less steeply in winter. Measurements at different elevation angles are shown as a primary indicator of the vertical distribution of NO2 at the urban environment; the vertical convection of the polluted air masses and the enhanced NO2 near-surface concentrations are demonstrated by this analysis. The inhomogeneity of the NO2 spatial distribution was shown using a relevant inhomogeneity index; greater variability was found during the summer period. Comparisons with city-scale model simulations demonstrated that the horizontal light path length of MAX-DOAS covered a distance of 15 km. An estimation of urban sources’ contribution was also made by applying two simple methodologies on the MAX-DOAS measurements. The results were compared to NO2 predictions from the high resolution air quality model to infer the importance of vehicle emissions for the urban NO2 levels; 20–35% of the urban NO2 was found to be associated with road transport.

scholarly journals The NorESM1-Happi used for evaluating differences between a global warming of 1.5 °C and 2 °C, and the role of Arctic Amplification

2017 ◽  
Author(s):  
Trond Iversen ◽  
Ingo Bethke ◽  
Jens B. Debernard ◽  
Lise S. Graff ◽  
Øyvind Seland ◽  
...  
Keyword(s):  
Global Change ◽  
Sea Ice ◽  
Extratropical Cyclone ◽  
The Arctic ◽  
Cmip5 Models ◽  
Arctic Amplification ◽  
Near Surface ◽  
Model Simulations ◽  
Slab Ocean ◽  
Fully Coupled

Abstract. Abstract. The global NorESM1-M model that produced results for CMIP5 (http://cmip-pcmdi.llnl.gov/cmip5/index.html) has been slightly upgraded to NorESM1-Happi, and has been run with double resolution (~ 1° in the atmosphere and the land surface) to provide model simulations to address the differences between a 1.5 °C and a 2.0 °C warmer climate than the 1850 pre-industrial. As a part of the validation of temperature-targeted model simulations, the atmosphere and land models have been run fully coupled with deep ocean and sea-ice as an extension of the NorESM1-M which produced CMIP5-results. Selected results from a standard set of validation experiments are discussed: a 500-year 1850 pre-industrial control run, three runs for the historical period 1850–2005, three detection and attribution runs, and three future projection runs based on RCPs. NorESM1-Happi has a better representation of sea-ice, improved Northern Hemisphere (NH) extratropical cyclone and blocking activity, and a fair representation of the Madden-Julian oscillation. The amplitude of ENSO signals is reduced and is too small, although the frequency is improved. The strength of the AMOC is larger and probably too large. Modern era global near-surface temperatures and the cloudiness are considerably under-estimated, while the precipitation and the intensity of the hydrological cycle are over-estimated, although the atmospheric residence time of water-vapour appears satisfactory. An ensemble of AMIP-type runs with prescribed SSTs and sea-ice from observations at present-day and a set of global CMIP5 models for a 1.5 °C and a 2.0 °C world (i.e. AMIP) has been provided by the model to a multi-model project (HAPPI, http://www.happimip.org/). This paper concentrates on the results from the NorESM1-Happi AMIP runs, which are compared to results from a slab-ocean version of the model (NorESM1-HappiSO) designed to emulate the AMIP simulation allowing SST and sea-ice to respond. The paper discusses the Arctic Amplification of the global change signal. The slab-ocean results generally show stronger response than the AMIP results to a global change, such as reduced NH extratropical cyclone activity, and different changes in the occurrence of blocking. A considerable difference in the reduction of sea-ice in the Arctic between a 1.5 °C and a 2.0 °C world is simulated. Ice-free summer conditions in the Arctic is estimated to be very rare for the 1.5 °C case, but to occur 40 % of the time for the 2.0 °C case. These results agree with some fully coupled models, but need to be further confirmed.

scholarly journals A decline of observed daily peak wind gusts with distinct seasonality in Australia, 1941-2016

2021 ◽  
pp. 1-63
Author(s):  
Cesar Azorin-Molina ◽  
Tim R. McVicar ◽  
Jose A. Guijarro ◽  
Blair Trewin ◽  
Andrew J. Frost ◽  
...  
Keyword(s):  
Wind Speed ◽  
Decadal Variability ◽  
Southern Annular Mode ◽  
Near Surface ◽  
Wind Gusts ◽  
Decadal Scale ◽  
Mean Wind Speed ◽  
Long Term Trends ◽  
The Indian Ocean

AbstractWind gusts represent one of the main natural hazards due to their increasing socioeconomic and environmental impacts on, as examples: human safety; maritime-terrestrial-aviation activities; engineering and insurance applications; and energy production. However, the existing scientific studies focused on observed wind gusts are relatively few compared to those on mean wind speed. In Australia, previous studies found a slowdown of near-surface mean wind speed, termed “stilling”, but a lack of knowledge on the multi-decadal variability and trends in the magnitude (wind speed maxima) and frequency (exceeding the 90th percentile) of wind gusts exists. A new homogenized daily peak wind gusts (DPWG) dataset containing 548 time series across Australia for the period 1941-2016 is analyzed to determine long-term trends in wind gusts. Here we show that both the magnitude and frequency of DPWG declined across much of the continent, with a distinct seasonality: negative trends in summer-spring-autumn and weak negative or non-trending (even positive) trends in winter. We demonstrate that ocean-atmosphere oscillations such as the Indian Ocean Dipole and the Southern Annular Mode partly modulate decadal-scale variations of DPWG. The long-term declining trend of DPWG is consistent with the “stilling” phenomenon, suggesting that global warming may have reduced Australian wind gusts.

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