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Basanta Raj Adhikari

Abstract

Lightning is one of the most devastating hazards in Nepal because of a large amount of atmospheric water vapor coming from the Indian Ocean and a large orographic lifting of this moist air. In 2019, a total of 2884 people were affected, with loss of USD 110,982, and the fatality number was the highest (94) in reported lightning events since 1971. The long-term analysis of this hazard is very scanty in Nepal. Therefore, this study analyzes lightning fatality events, fatality rates, and economic loss from 1971 to 2019 collected from the DesInventar dataset and the Disaster Risk Reduction portal of the government of Nepal using Statistical Package for Social Sciences (SPSS) and geographic information system (ArcGIS) tools. The analysis shows that the overall countrywide lightning fatality rate of the entire period is 1.77 per million per year. District lightning fatality rates range from 0.10 to 4.83 per million people per year, and the Bhaktapur district has the highest fatality density (0.067). Furthermore, there were a total of 2501 lightning fatality events in which 1927 people lost their lives and 20 569 people were affected. The increase in lightning fatality events in recent years is due to internet penetration and other measures of information gathering that result in lightning fatality reports reaching agencies collecting information. The high and low concentrations of loss and damage are mainly due to geographic distribution, population density, and economic activities. This study recommends the establishment of lightning early warning systems in the Nepal Himalayas to save life and property.

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Ronald L. Holle, William A. Brooks, and Kenneth L. Cummins

Abstract

National park visitors travel primarily to view natural features while outdoors; however, visits often occur in warmer months when lightning is present. This study uses cloud-to-ground flashes from 1999 to 2018 and cloud-to-ground strokes from 2009 to 2018 from the National Lightning Detection Network to identify lightning at the 46 contiguous United States national parks larger than 100 km2. The largest density is 6.10 flashes per kilometer squared per year within Florida’s Everglades, and the smallest is near zero in Pinnacles National Park. The six most-visited parks are Great Smoky Mountains, Grand Canyon, Rocky Mountain, Zion, Yosemite, and Yellowstone. For each of these parks, lightning data are described by frequency and location as well as time of year and day. The four parks west of the Continental Divide have most lightning from 1 July to 15 September and from 1100 to 1900 LST. Each park has its own spatial lightning pattern that is dependent on local topography. Deaths and injuries from lightning within national parks have the same summer afternoon dominance shown by lightning data. Most casualties occur to people visiting from outside the parks’ states. The most common activities and locations are mountain climbing, hiking, and viewing canyons from overlooks. Lightning fatality risk, the product of areal visitor and CG flash densities, shows that many casualties are not in parks with high risk, while very small risk indicates parks where lightning awareness efforts can be minimized. As a result, safety advice should focus on specific locations such as canyon rims, mountains, and exposed high-altitude roads where lightning-vulnerable activities are engaged in by many visitors.

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Kevin M. Grise and Mitchell K. Kelleher

Abstract

An effective method to understand cloud processes and to assess the fidelity with which they are represented in climate models is the cloud controlling factor framework, in which cloud properties are linked with variations in large-scale dynamical and thermodynamical variables. This study examines how midlatitude cloud radiative effects (CRE) over oceans covary with four cloud controlling factors—midtropospheric vertical velocity, estimated inversion strength (EIS), near-surface temperature advection, and sea surface temperature (SST)—and assesses their representation in CMIP6 models with respect to observations and CMIP5 models. CMIP5 and CMIP6 models overestimate the sensitivity of midlatitude CRE to perturbations in vertical velocity and underestimate the sensitivity of midlatitude shortwave CRE to perturbations in EIS and temperature advection. The largest improvement in CMIP6 models is a reduced sensitivity of CRE to vertical velocity perturbations. As in CMIP5 models, many CMIP6 models simulate a shortwave cloud radiative warming effect associated with a poleward shift in the Southern Hemisphere (SH) midlatitude jet stream, an effect not present in observations. This bias arises because most models’ shortwave CRE are too sensitive to vertical velocity perturbations and not sensitive enough to EIS perturbations, and because most models overestimate the SST anomalies associated with SH jet shifts. The presence of this bias directly impacts the transient surface temperature response to increasing greenhouse gases over the Southern Ocean, but not the global-mean surface temperature. Instead, the models’ climate sensitivity is correlated with their shortwave CRE sensitivity to surface temperature advection perturbations near 40°S, with models with more realistic values of temperature advection sensitivity generally having higher climate sensitivity.

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William E. Chapman, Aneesh C. Subramanian, Shang-Ping Xie, Michael D. Sierks, F. Martin Ralph, and Youichi Kamae

Abstract

Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño–Southern Oscillation (ENSO) forcing and background internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (~10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little to no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue “windows of forecast opportunity” in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated.

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Deepashree Dutta, Steven C. Sherwood, Katrin J. Meissner, Alex Sen Gupta, Daniel J. Lunt, Gregory J. L. Tourte, Robert Colman, Sugata Narsey, David Fuchs, and Josephine R. Brown

Abstract

When simulating past warm climates, such as the early Cretaceous and Paleogene periods, general circulation models (GCMs) underestimate the magnitude of warming in the Arctic. Additionally, model intercomparisons show a large spread in the magnitude of Arctic warming for these warmer-than-modern climates. Several mechanisms have been proposed to explain these disagreements, including the unrealistic representation of polar clouds or underestimated poleward heat transport in the models. This study provides an intercomparison of Arctic cloud and atmospheric heat transport (AHT) responses to strong imposed polar-amplified surface ocean warming across four atmosphere-only GCMs. All models simulate an increase in high clouds throughout the year; the resulting reduction in longwave radiation loss to space acts to support the imposed Arctic warming. The response of low- and midlevel clouds varies considerably across the models, with models responding differently to surface warming and sea ice removal. The AHT is consistently weaker in the imposed warming experiments due to a large reduction in dry static energy transport that offsets a smaller increase in latent heat transport, thereby opposing the imposed surface warming. Our idealized polar amplification experiments require very large increases in implied ocean heat transport (OHT) to maintain steady state. Increased CO2 or tropical temperatures that likely characterized past warm climates reduce the need for such large OHT increases.

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M. A. Altamirano del Carmen, F. Estrada, and C. Gay-García

Abstract

The reliability of general circulation models (GCMs) is commonly associated with their ability to reproduce relevant aspects of observed climate, and thus the evaluation of GCM performance has become a standard practice for climate change studies. As such, there is an ever-growing literature that focuses on developing and evaluating metrics to assess GCM performance. In this paper it is shown that some commonly applied metrics provide little information for discriminating GCMs based on their performance, once uncertainty is included. A new methodology is proposed that differs from common approaches in that it focuses on evaluating GCMs’ abilities to reproduce the observed response of surface temperature to changes in external radiative forcing (RF), while controlling for observed and simulated variability. It uses formal statistical tests to evaluate two aspects of the warming trend that are central for climate change studies: 1) if the response to RF produced by a particular GCM is compatible with observations and 2) if the magnitudes of the observed and simulated rates of warming are statistically similar. We illustrate the proposed methodology by evaluating the ability of 21 GCMs to reproduce the observed warming trend at the global scale and for eight subcontinental land domains. Results show that most of the GCMs provide an adequate representation of the observed warming trend for the global scale and for domains located in the Southern Hemisphere. However, GCMs tend to overestimate the warming rate for domains in the Northern Hemisphere, particularly since the mid-1990s.

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Ajitha Cyriac, Helen E. Phillips, Nathaniel L. Bindoff, Huabin Mao, and Ming Feng

Abstract

This study investigates the spatiotemporal variability of turbulent mixing in the eastern south Indian Ocean using a collection of data from electromagnetic autonomous profiling explorer (EM-APEX) profiling floats, shipboard CTD, and microstructure profilers. The floats collected 1566 profiles of temperature, salinity, and horizontal velocity data down to 1200 m over a period of about four months. A finescale parameterization is applied to the float and CTD data to estimate turbulent mixing. Elevated mixing is observed in the upper ocean, over bottom topography, and in mesoscale eddies. Mixing is enhanced in the anticyclonic eddies due to trapped near-inertial waves within the eddy. We found that cyclonic eddies contribute to turbulent mixing in the depth range of 500–1000 m, which is associated with downward-propagating internal waves. The mean diapycnal diffusivity over 250–500-m depth is O(10−6) m2 s−1, and it increases to O(10−5) m2 s−1 in 500–1000 m in cyclonic eddies. The turbulent mixing in this region has implications for water-mass transformation and large-scale circulation. Higher diffusivity [O(10−5) m2 s−1] is observed in the Antarctic Intermediate Water (AAIW) layer in cyclonic eddies, whereas weak diffusivity is observed in the Subantarctic Mode Water (SAMW) layer [O(10−6) m2 s−1]. Counterintuitively, then, the SAMW water-mass properties are strongly affected in cyclonic eddies, whereas the AAIW layer is less affected. Comparatively high diffusivity at the location of the South Indian Countercurrent (SICC) jets suggests there are wave–mean flow interactions in addition to the wave–eddy interactions that warrant further investigation.

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David R. Ryglicki, Christopher S. Velden, Paul D. Reasor, Daniel Hodyss, and James D. Doyle

Abstract

Multiple observation and analysis datasets are used to demonstrate two key features of the atypical rapid intensification (ARI) process that occurred in Atlantic Hurricane Dorian (2019): 1) precession and nutations of the vortex tilt and 2) blocking of the impinging upper-level environmental flow by the outflow. As Dorian came under the influence of an upper-level anticyclone, traditional methods of estimating vertical wind shear all indicated relatively low values were acting on the storm; however, high-spatiotemporal-resolution atmospheric motion vectors (AMVs) indicated that the environmental flow at upper levels was actually impinging on the vortex core, resulting in a vertical tilt. We employ a novel ensemble of centers of individual swaths of dual-Doppler radar data from WP-3D aircraft to characterize the precession and wobble of the vortex tilt. This tilting and wobbling preceded a sequence of outflow surges that acted to repel the impinging environmental flow, thereby reducing the shear and permitting ARI. We then apply prior methodology on satellite imagery for distinguishing ARI features. Finally, we use the AMV dataset to experiment with different shear calculations and show that the upper-level cross-vortex flow approaches zero. We discuss the implication of these results with regard to prior works on ARI and intensification in shear.

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C. A. Luecke, H. W. Wijesekera, E. Jarosz, D. W. Wang, J. C. Wesson, S. U. P. Jinadasa, H. J. S. Fernando, and W. J. Teague

Abstract

Long-term measurements of turbulent kinetic energy dissipation rate (ε), and turbulent temperature variance dissipation rate (χ T) in the thermocline, along with currents, temperature, and salinity were made at two subsurface moorings in the southern Bay of Bengal (BoB). This is a part of a major international program, conducted between July 2018 and June 2019, for investigating the role of the BoB on the monsoon intraseasonal oscillations. One mooring was located on the typical path of the Southwest Monsoon Current (SMC), and the other was in a region where the Sri Lanka dome is typically found during the summer monsoon. Microstructure and finescale estimates of vertical diffusivity revealed the long-term subthermocline mixing patterns in the southern BoB. Enhanced turbulence and large eddy diffusivities were observed within the SMC during the passage of a subsurface-intensified anticyclonic eddy. During this time, background shear and strain appeared to influence high-frequency motions such as near-inertial waves and internal tides, leading to increased mixing. Near the Sri Lanka dome, enhanced dissipation occurred at the margins of the cyclonic feature. Turbulent mixing was enhanced with the passage of Rossby waves and eddies. During these events, values of χ T exceeding 10−4 °C2 s−1 were recorded concurrently with ε values exceeding 10−5 W kg−1. Inferred diffusivity peaked well above background values of 10−6 m2 s−1, leading to an annually averaged diffusivity near 10−4 m2 s−1. Turbulence appeared low throughout much of the deployment period. Most of the mixing occurred in spurts during isolated events.

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Constantin W. Arnscheidt, John Marshall, Pierre Dutrieux, Craig D. Rye, and Ali Ramadhan

Abstract

Antarctic glacial meltwater is thought to play an important role in determining large-scale Southern Ocean climate trends, yet recent modeling efforts have proceeded without a good understanding of how its vertical distribution in the water column is set. To rectify this, here we conduct new large-eddy simulations of the ascent of a buoyant meltwater plume after its escape from beneath an Antarctic ice shelf. We find that the meltwater’s settling depth is primarily a function of the buoyancy forcing per unit width of the source and the ambient stratification, consistent with the classical theory of turbulent buoyant plumes and in contrast to previous work that suggested an important role for centrifugal instability. Our results further highlight the significant role played by localized variability in stratification; this helps explain observed interannual variability in the vertical meltwater distribution near Pine Island Glacier. Because of the vast heterogeneity in mass loss rates and ambient conditions at different Antarctic ice shelves, a dynamic parameterization of meltwater settling depth may be crucial for accurately simulating high-latitude climate in a warming world; we discuss how this may be developed following this work, and where the remaining challenges lie.

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