scholarly journals Idealized Simulations of Mei-yu Rainfall in Taiwan under Uniform Southwesterly Flow using A Could-Resolving Model

2021 ◽  
Author(s):  
Chung-Chieh Wang ◽  
Pi-Yu Chuang ◽  
Shi-Ting Chen ◽  
Dong-In Lee ◽  
Kazuhisa Tsuboki
Keyword(s):  
Large Angle ◽  
Complex Topography ◽  
Near Surface ◽  
Rainfall Characteristics ◽  
Mixed Regime ◽  
Fixed Direction ◽  
Real Atmosphere ◽  
Thermodynamic Effects ◽  
Rainfall Regimes

Abstract. In this study, idealized cloud-resolving simulations are performed for horizontally uniform and steady southwesterly flow at fixed direction/speed combinations to investigate rainfall characteristics and the role of the complex topography in Taiwan during the Mei-yu season, without the influence of a front or other disturbances. Eight directions (180° to 285°, every 15°) and eight speeds (5 to 22.5 m s−1, every 2.5 m s−1) are considered, and near-surface relative humidity (RH) is also altered (from 55–100 %) in a subset of these tests to further investigate the effects of moisture content, yielding a total 109 experiments each having a integration length of 50 h. Three rainfall regimes that correspond to different ranges of the wet Froude number (Frw) are identified from the idealized simulations (with a grid size of 2 km). The low-Frw regime (Frw ≤ ~0.3) where the island circulation from thermodynamic effects during daytime is the main cause of rainfall in local afternoon. The lower the wind speed (and Frw), the more widespread and amount of rainfall. On the other hand, the high-Frw regime (Frw ≥ ~0.4) occurs when the flow at least 12.5 m s−1 impinges on Taiwan terrain at a large angle to favor the flow-over scenario. Thus, topographic rainfall production becomes dominant through mechanical uplift of unstable air. In this scenario, the faster and wetter the flow, the heavier the rainfall on the windward slopes, with the most favorable direction from 240°–255°. Between the two regimes above, a third and mixed regime also exists. The idealized results are discussed for their applicability to the real atmosphere.

Applications of Energy Beams in Material and Device Processing

1983 ◽  
Vol 23 ◽  
Author(s):  
G.J. Galvin ◽  
L.S. Hung ◽  
J.W. Mayer ◽  
M. Nastasi
Keyword(s):  
Ion Beam ◽  
High Energy ◽  
Ion Beams ◽  
Traditional Role ◽  
Near Surface ◽  
Device Processing ◽  
Composition Modification ◽  
Directed Energy ◽  
Transistor Fabrication

ABSTRACTEnergetic ion beams used outside the traditional role of ion implantation are considered for semiconductor applications involving interface modification for self-aligned silicide contacts, composition modification for formation of buried oxide layers in Si on insulator structures and reduced disorder in high energy ion beam annealing for buried collectors in transistor fabrication. In metals, aside from their use in modification of the composition of near surface regions, energetic ion beams are being investigated for structural modification in crystalline to amorphous transitions. Pulsed beams of photons and electrons are used as directed energy sources in rapid solidification. Here, we consider the role of temperature gradients and impurities in epitaxial growth of silicon.

scholarly journals A warm jet in a cold ocean

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jennifer A. MacKinnon ◽  
Harper L. Simmons ◽  
John Hargrove ◽  
Jim Thomson ◽  
Thomas Peacock ◽  
...  
Keyword(s):  
The Arctic ◽  
Bering Strait ◽  
Near Surface ◽  
Ice Melt ◽  
Beaufort Gyre ◽  
The Pacific ◽  
Climate Simulations ◽  
Initial Evolution ◽  
Forecast Models

AbstractUnprecedented quantities of heat are entering the Pacific sector of the Arctic Ocean through Bering Strait, particularly during summer months. Though some heat is lost to the atmosphere during autumn cooling, a significant fraction of the incoming warm, salty water subducts (dives beneath) below a cooler fresher layer of near-surface water, subsequently extending hundreds of kilometers into the Beaufort Gyre. Upward turbulent mixing of these sub-surface pockets of heat is likely accelerating sea ice melt in the region. This Pacific-origin water brings both heat and unique biogeochemical properties, contributing to a changing Arctic ecosystem. However, our ability to understand or forecast the role of this incoming water mass has been hampered by lack of understanding of the physical processes controlling subduction and evolution of this this warm water. Crucially, the processes seen here occur at small horizontal scales not resolved by regional forecast models or climate simulations; new parameterizations must be developed that accurately represent the physics. Here we present novel high resolution observations showing the detailed process of subduction and initial evolution of warm Pacific-origin water in the southern Beaufort Gyre.

Extreme Surface Winds During Landfalling Atmospheric Rivers: The Modulating Role of Near-Surface Stability

2021 ◽  
Author(s):  
Terence J. Pagano ◽  
Duane E. Waliser ◽  
Bin Guan ◽  
Hengchun Ye ◽  
F. Martin Ralph ◽  
...  
Keyword(s):  
Water Vapor ◽  
Static Stability ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Surface Winds ◽  
Near Surface ◽  
Extreme Surface ◽  
Atmospheric Rivers ◽  
Explained Variance

AbstractAtmospheric rivers (ARs) are long and narrow regions of strong horizontal water vapor transport. Upon landfall, ARs are typically associated with heavy precipitation and strong surface winds. A quantitative understanding of the atmospheric conditions that favor extreme surface winds during ARs has implications for anticipating and managing various impacts associated with these potentially hazardous events. Here, a global AR database (1999–2014) with relevant information from MERRA-2 reanalysis, QuikSCAT and AIRS satellite observations are used to better understand and quantify the role of near-surface static stability in modulating surface winds during landfalling ARs. The temperature difference between the surface and 1 km MSL (ΔT; used here as a proxy for near-surface static stability), and integrated water vapor transport (IVT) are analyzed to quantify their relationships to surface winds using bivariate linear regression. In four regions where AR landfalls are common, the MERRA-2-based results indicate that IVT accounts for 22-38% of the variance in surface wind speed. Combining ΔT with IVT increases the explained variance to 36-52%. Substitution of QuikSCAT surface winds and AIRS ΔT in place of the MERRA-2 data largely preserves this relationship (e.g., 44% compared to 52% explained variance for USA West Coast). Use of an alternate static stability measure–the bulk Richardson number–yields a similar explained variance (47%). Lastly, AR cases within the top and bottom 25% of near-surface static stability indicate that extreme surface winds (gale or higher) are more likely to occur in unstable conditions (5.3%/14.7% during weak/strong IVT) than in stable conditions (0.58%/6.15%).

Decomposing the time-mean Atlantic Meridional Overturning Circulation and its variability with latitude.

2021 ◽  
Author(s):  
Tomas Jonathan ◽  
Mike Bell ◽  
Helen Johnson ◽  
David Marshall
Keyword(s):  
Global Climate ◽  
Dominant Role ◽  
Meridional Overturning Circulation ◽  
Western Boundary ◽  
Relative Role ◽  
Overturning Circulation ◽  
Near Surface ◽  
Boundary Density ◽  
Meridional Overturning

<p>The Atlantic Meridional Overturning Circulations (AMOC) is crucial to our global climate, transporting heat and nutrients around the globe. Detecting  potential climate change signals first requires a careful characterisation of inherent natural AMOC variability. Using a hierarchy of global coupled model  control runs (HadGEM-GC3.1, HighResMIP) we decompose the overturning circulation as the sum of (near surface) Ekman, (depth-dependent) bottom velocity, eastern and western boundary density components, as a function of latitude. This decomposition proves a useful low-dimensional characterisation of the full 3-D overturning circulation. In particular, the decomposition provides a means to investigate and quantify the constraints which boundary information imposes on the overturning, and the relative role of eastern versus western contributions on different timescales. </p><p>The basin-wide time-mean contribution of each boundary component to the expected streamfunction is investigated as a function of depth, latitude and spatial resolution. Regression modelling supplemented by Correlation Adjusted coRrelation (CAR) score diagnostics provide a natural ranking of the contributions of the various components in explaining the variability of the total streamfunction. Results reveal the dominant role of the bottom component, western boundary and Ekman components at short time-scales, and of boundary density components at decadal and longer timescales.</p>

Evaluating the role of soil physical properties on simulated land-atmosphere interactions over South Africa using coupled atmosphere-hydrological modeling

2021 ◽  
Author(s):  
Zhenyu Zhang ◽  
Patrick Laux ◽  
Joël Arnault ◽  
Jianhui Wei ◽  
Jussi Baade ◽  
...  
Keyword(s):  
South Africa ◽  
Physical Properties ◽  
Land Degradation ◽  
Land Surface ◽  
Soil Physical Properties ◽  
Near Surface ◽  
Soil Database ◽  
Global Soil ◽  
The Impact

<p>Land degradation with its direct impact on vegetation, surface soil layers and land surface albedo, has great relevance with the climate system. Assessing the climatic and ecological effects induced by land degradation requires a precise understanding of the interaction between the land surface and atmosphere. In coupled land-atmosphere modeling, the low boundary conditions impact the thermal and hydraulic exchanges at the land surface, therefore regulates the overlying atmosphere by land-atmosphere feedback processes. However, those land-atmosphere interactions are not convincingly represented in coupled land-atmosphere modeling applications. It is partly due to an approximate representation of hydrological processes in land surface modeling. Another source of uncertainties relates to the generalization of soil physical properties in the modeling system. This study focuses on the role of the prescribed physical properties of soil in high-resolution land surface-atmosphere simulations over South Africa. The model used here is the hydrologically-enhanced Weather Research and Forecasting (WRF-Hydro) model. Four commonly used global soil datasets obtained from UN Food and Agriculture Organization (FAO) soil database, Harmonized World Soil Database (HWSD), Global Soil Dataset for Earth System Model (GSDE), and SoilGrids dataset, are incorporated within the WRF-Hydro experiments for investigating the impact of soil information on land-atmosphere interactions. The simulation results of near-surface temperature, skin temperature, and surface energy fluxes are presented and compared to observational-based reference dataset. It is found that simulated soil moisture is largely influenced by soil texture features, which affects its feedback to the atmosphere.</p>

NMME-based Assessment of Prediction Skills of US Summertime Droughts and Pluvials: Role of Near-surface Temperature Prediction Skill

2021 ◽  
Author(s):  
Jonghun Kam ◽  
Sungyoon Kim ◽  
Joshua Roundy
Keyword(s):  
Surface Temperature ◽  
Climate Extremes ◽  
Prediction Skill ◽  
Seasonal Forecasts ◽  
Near Surface ◽  
Anomaly Correlation ◽  
The North ◽  
Anomaly Correlation Coefficient ◽  
Precipitation Anomalies

<p>This study used the North American Multi-Model Ensemble (NMME) system to understand the role of near surface temperature in the prediction skill for US climate extremes. In this study, the forecasting skill was measured by anomaly correlation coefficient (ACC) between the observed and forecasted precipitation (PREC) or 2-meter air temperature (T2m) over the contiguous United States (CONUS) during 1982–2012. The strength of the PREC-T2m coupling was measured by ACC between observed PREC and T2m or forecasted PREC and T2m over the CONUS. This study also assessed the NMME forecasting skill for the summers of 2004 (spatial anomaly correlation between PREC and T2m: 0.05), 2011 (-0.65), and 2012 (-0.60) when the PREC-T2m coupling is weaker or stronger than the 1982–2012 climatology (ACC:-0.34). This study found that most of the NMME models show stronger (negative) PREC-T2m coupling than the observed coupling, indicating that they fail to reproduce interannual variability of the observed PREC-T2m coupling. Some NMME models with skillful prediction for T2m show the skillful prediction of the precipitation anomalies and US droughts in 2011 and 2012 via strong PREC-T2m coupling despite the fact that the forecasting skill is year-dependent and model-dependent. Lastly, we explored how the forecasting skill for SSTs over north Pacific and Atlantic Oceans affects the forecasting skill for T2m and PREC over the US. The findings of this study suggest a need for the selective use of the current NMME seasonal forecasts for US droughts and pluvials.</p>

Quantum Coherences as a Thermodynamic Potential

2019 ◽  
Vol 26 (04) ◽  
pp. 1950022
Author(s):  
César A. Rodríguez-Rosario ◽  
Thomas Frauenheim ◽  
Alán Aspuru-Guzik
Keyword(s):  
Entropy Production ◽  
Quantum Transport ◽  
Thermodynamic Potential ◽  
Quantum Measurements ◽  
Second Law ◽  
General Sense ◽  
Thermodynamic Potentials ◽  
General Systems ◽  
Thermodynamic Effects

Here we demonstrate how the interplay between quantum coherences and a decoherence bath, such as one given by continuos quantum measurements, lead to new kinds of thermodynamic potentials and flows. We show how a mathematical extension of thermodynamics includes decoherence baths leading to a more general sense of the zeroth and first law. We also show how decoherence adds contributions to the change in entropy production in the second law. We derive a thermodynamic potential that depends only on the interplay between quantum coherences and a decoherence thermodynamic bath. This leads to novel thermodynamic effects, such as Onsager relationships that depend on quantum coherences. This provides a thermodynamics interpretation of the role of decoherence on quantum transport in very general systems.

scholarly journals The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

2018 ◽  
Vol 18 (11) ◽  
pp. 2991-3006 ◽  
Author(s):  
Matthew D. K. Priestley ◽  
Helen F. Dacre ◽  
Len C. Shaffrey ◽  
Kevin I. Hodges ◽  
Joaquim G. Pinto
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geographic Region ◽  
Near Surface ◽  
Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

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