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Results for “Journal of Space Weather and Space Climate”

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6 recordsLinked to original sources
USGS2024

On the uncertain intensity estimate of the 1859 Carrington storm

A study is made of the intensity of the Carrington magnetic storm of September 1859 as inferred from visual measurements of horizontal-component geomagnetic disturbance made at the Colaba observatory in India. Using data from modern observatories, a lognormal statistical model of storm intensity is developed, to characterize the maximum-negative value of the storm-time disturbance index (maximum – Dst) versus geomagnetic disturbance recorded at low-latitude observatories during magnetic storms. With this model and a recently published presentation of the Colaba data, the most likely maximum – Dst of the Carrington storm and its credibility interval are estimated. A related model is used to examine individual Colaba disturbance values reported for the Carrington storm. Results indicate that only about one in a million storms with maximum – Dst like the Carrington storm would result in local disturbance greater than that reported from Colaba. This indicates that either the Colaba data were affected by magnetospheric-ionospheric current systems in addition to the ring current, or there might be something wrong with the Colaba data. If the most extreme Colaba disturbance value is included in the analysis, then, of all hypothetical storms generating the hourly average disturbance recorded at Colaba during the Carrington storm, the median maximum – Dst = 964 nT, with a 68% credibility interval of [855,1087] nT. If the most extreme Colaba disturbance value is excluded from the analysis, then the median maximum – Dst = 866 nT, with a 68% credibility interval of [768,977] nT. The widths of these intervals indicate that estimates of the occurrence frequency of Carrington-class storms are very uncertain, as are related estimates of risk for modern technological systems.

Journal of Space Weather and Space Climate↗
USGS2020

RestoreNet: An emerging restoration network reveals controls on seeding success across dryland ecosystems

Drylands are Earth's largest terrestrial biome and support one‐third of the global population. However, they are also highly vulnerable to land degradation. Despite widespread demand for dryland restoration and rehabilitation, little information is available to help land managers effectively re‐establish native perennial vegetation across drylands. RestoreNet is an emerging dryland restoration network that systematically tests revegetation techniques across environmental gradients. Using the RestoreNet experimental framework, we tested the effectiveness of restoration treatments (i.e. ConMod nurse plant structures, mulch, pits) that increase soil moisture and seed mixes with different climatic niches to achieve revegetation goals. Across sites, seedling recruitment was consistently influenced by treatment and seed mix type. Pit and mulch treatments increased total seedling density, with pits promoting the highest seeded species recruitment while limiting non‐native species establishment. Seeding increased total seedling density regardless of seed mix type, but cooler‐adapted seed mixes promoted greater seeded species density and resulted in lower density of unseeded (non‐native) species relative to warmer‐adapted mixes. Seedling recruitment was also controlled by the temporal and environmental context of restoration with the positive effect of high precipitation greatest in the weeks immediately following seeding. Above‐average precipitation during the study period across most of the sites may partially explain why the highest seeded species recruitment occurred in pit treatments and seed mixes with cooler, wetter niche requirements. Synthesis and applications . Results from the dryland restoration network, RestoreNet help to better understand variation in seeding and restoration treatment success across space and time in drylands. Relationships between restoration practices and environmental conditions in our study suggest the importance of anticipatory restoration strategies that forecast seasonal and sub‐seasonal weather conditions and select plant species with climate niche requirements appropriate for current and future climate conditions. This information is critical to land managers tasked with improving ecosystem conditions across degraded dryland regions.

Arizona↗
USGS2015

The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate

SSTs in the western Pacific Ocean have tracked closely with CMIP5 simulations despite recent hiatus cooling in the eastern Pacific. This paper quantifies these similarities and associated circulation and precipitation variations using the first global 1900–2012 ENSO-residual empirical orthogonal functions (EOFs) of 35 variables: observed SSTs; 28 CMIP5 SST simulations; Simple Ocean Data Assimilation (SODA) 25-, 70-, and 171-m ocean temperatures and sea surface heights (SSHs); and Twentieth Century Reanalysis, version 2 (20CRv2), surface winds and precipitation. While estimated independently, these leading EOFs across all variables fit together in a meaningful way, and the authors refer to them jointly as the west Pacific warming mode (WPWM). WPWM SST EOFs correspond closely in space and time. Their spatial patterns form a “western V” extending from the Maritime Continent into the extratropical Pacific. Their temporal principal components (PCs) have increased rapidly since 1990; this increase has been primarily due to radiative forcing and not natural decadal variability. WPWM circulation changes appear consistent with a Matsuno–Gill-like atmospheric response associated with an ocean–atmosphere dipole structure contrasting increased (decreased) western (eastern) Pacific precipitation, SSHs, and ocean temperatures. These changes have enhanced the Walker circulation and modulated weather on a global scale. An AGCM experiment and the WPWM of global boreal spring precipitation indicate significant drying across parts of East Africa, the Middle East, the southwestern United States, southern South America, and Asia. Changes in the WPWM have tracked closely with precipitation and the increase in drought frequency over the semiarid and water-insecure areas of East Africa, the Middle East, and southwest Asia.

Journal of Climate↗
USGS2008

Temporal and spatial structure in a daily wildfire-start data set from the western United States (198696)

The temporal and spatial structure of 332 404 daily fire-start records from the western United States for the period 1986 through 1996 is illustrated using several complimentary visualisation techniques. We supplement maps and time series plots with Hovmo??ller diagrams that reduce the spatial dimensionality of the daily data in order to reveal the underlying space?time structure. The mapped distributions of all lightning- and human-started fires during the 11-year interval show similar first-order patterns that reflect the broad-scale distribution of vegetation across the West and the annual cycle of climate. Lightning-started fires are concentrated in the summer half-year and occur in widespread outbreaks that last a few days and reflect coherent weather-related controls. In contrast, fires started by humans occur throughout the year and tend to be concentrated in regions surrounding large-population centres or intensive-agricultural areas. Although the primary controls of human-started fires are their location relative to burnable fuel and the level of human activity, spatially coherent, weather-related variations in their incidence can also be noted. ?? IAWF 2008.

International Journal of Wildland Fire↗
USGS2023

Integrated analysis shows how the effects of extreme flooding events propagate through fish communities to impact amphibians

Research Highlight: Davis, C. L., Walls, S. C., Barichivich, W. J., Brown, M. E., & Miller, D. A. (2022). Disentangling direct and indirect effects of extreme events on coastal wetland communities. Journal of Animal Ecology , https://doi.org/10.1111/1365-2656.13874 . Catastrophic events such as floods, hurricanes, winter storms, droughts and wildfires increasingly touch our lives either directly or indirectly. These events draw our attention to the seriousness of changes in climate not only to human well-being but also to the integrity of ecological systems upon which we depend. Understanding the impacts of extreme events on ecological systems requires the ability to characterize the cascading effects of environmental changes on the environments in which organisms live and the altered biological interactions produced. This scientific ambition represents no small challenge for the study of animal communities, which are typically difficult to census as well as dynamic in time and space. Davis et al. (2022) in a recent study in the Journal of Animal Ecology examined the amphibian and fish communities found in depressional coastal wetlands to better understand how they respond to major rainfall and flooding events. Data from the U.S. Geological Survey's Amphibian Research and Monitoring Initiative provided an 8-year record of observations as well as environmental measurements. For this study, the authors integrated techniques for assessing the dynamics of animal populations with a Bayesian implementation of structural equation modelling. Using their integrated methodological approach permitted the authors to reveal the direct and indirect effects of extreme weather events on co-occurring amphibian and fish communities while accounting for observational uncertainty and temporal variation in population-level processes. Their findings indicate that the most prominent effects of flooding on the amphibian community were caused by changes in the fish community that led to increased predation and resource competition. In their conclusions, the authors emphasize the importance of understanding networks of abiotic and biotic effects if we are to predict and mitigate the influence of extreme weather events.

Journal of Animal Ecology↗
USGS2017

Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission. Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [ Cervus Canadensis ] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem. Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts. Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands. Synthesis and applications . Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.

Journal of Applied Ecology↗