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At least 91 records · Page 5Linked to original sources
USGS2026

Development of projected depth-duration-frequency curves for precipitation in Florida, 2020–59 and 2050–89

The planning, permitting, and design of stormwater-management projects require estimates of the depths of extreme precipitation for current and future events with specified durations and return periods. In this project, precipitation data from six downscaled climate datasets were used to determine changes in precipitation depth-duration-frequency curves from the period 1966–2005 to the periods 2020–59 and 2050–89. The downscaled climate datasets are from the Coupled Model Intercomparison Project Phases 5 and 6 and include (1) Coordinated Regional Downscaling Experiment (CORDEX), (2) Localized Constructed Analogs (LOCA), (3) Multivariate Adaptive Constructed Analogs (MACA), (4) Jupiter Intelligence Weather Research and Forecasting model (JupiterWRF), (5) LOCA version 2 (LOCA2), and (6) National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). Change factors—multiplicative changes in expected extreme precipitation magnitude from a historical to future period—were computed for grid cells containing National Oceanic and Atmospheric Administration Atlas 14 stations in Florida. Change factors for specific durations and return periods were developed to scale the National Oceanic and Atmospheric Administration Atlas 14 historical depth-duration-frequency values to the periods 2020–59 and 2050–89 on the basis of changes in extreme precipitation derived from six downscaled climate datasets. Overall, a large variation in change factors across downscaled climate datasets was found, with change factors generally being greater than 1 and increasing with return period. In general, median change factors were found to range within 1.01–1.58 for 2020–59 and 1.01–1.63 for 2050–89, depending on the downscaled climate dataset, region, duration, and return period, indicating a projected overall increase in future extreme-precipitation events. When data from all datasets are considered together, median change factors range within 1.04–1.18 for the period 2020–59 and within 1.04–1.23 for the period 2050–89, depending on the region, duration, and return period. Spatial patterns in median change factors were found to vary by dataset.

Florida↗
USGS2008

Amount and Percentage of Current Societal Assets in Areas on Kaua'i, Hawai'i, within the 1992 Hurricane 'Iniki Storm-Surge Inundation Zone

The Pacific Risk Management 'Ohana (PRiMO) is a network of partners and stakeholders involved in the development, delivery, and communication of risk management-related information, products, and services across the Pacific Ocean (National Oceanic and Atmospheric Administration Pacific Services Center, 2008). One PRiMO-related project is the NOAA National Climatic Data Center's Integrated Data and Environmental Applications (IDEA) Center's Pacific Region Integrated Climatology Information Products (PRICIP) initiative, which seeks to improve the understanding of patterns and trends of storm frequency and intensity ('storminess') within the Pacific region and to develop a suite of integrated information products that can be used by emergency managers, mitigation planners, government agencies, and other decision-makers (National Oceanic and Atmospheric Administration Integrated Data and Environmental Applications Center, 2008a). One of the PRICIP information products is a historical storm 'event anatomy', which includes a summary of sector-specific socioeconomic impacts associated with a particular event, as well as information about the event and its climatological context. The intent of an event anatomy is to convey the causes of an extreme storm event and the associated impacts in a format that users can understand. The event anatomies also are intended to familiarize users with the in-place and remotely sensed products typically employed to track and forecast weather and climate. The first event anatomy developed as a prototype and hosted on the PRICIP portal is for Hurricane 'Iniki (National Oceanic and Atmospheric Administration Integrated Data and Environmental Applications Center, 2008b), a Category 3-4 hurricane that made landfall on the south coast of Kaua'i Island on September 11, 1992, with estimated maximum sustained winds of more than 140 mph and gusts as high as 175 mph. Storm-surge inundation occurred on the southern and northeastern coast of Kaua'i Island. In an effort to increase the amount of available information on the Hurricane 'Iniki event anatomy of the PRICIP portal, representatives from the NOAA NCDC IDEA Center contacted the U.S. Geological Survey (USGS) in 2007 for assistance in determining what current societal assets are in areas that were inundated by storm surge during Hurricane 'Iniki in 1992. This report contains data summarizing the amount and percentage of current societal assets on Kaua'i Island, Hawai'i, that exist in the historic Hurricane 'Iniki storm-surge inundation zone. Coupled with an array of information on the socioeconomic impacts of Hurricane 'Iniki and distributed through the PRICIP portal, the results of this effort will help managers and the general public to understand the current risks posed by extreme storms in the Pacific Basin.

Open-File Report↗
USGS2006

Projecting future sea level

California’s coastal observations and global model projections indicate that California’s open coast and estuaries will experience increasing sea levels over the next century. Sea level rise has affected much of the coast of California, including the Southern California coast, the Central California open coast, and the San Francisco Bay and upper estuary. These trends, quantified from a small set of California tide gages, have ranged from 10–20 centimeters (cm) (3.9–7.9 inches) per century, quite similar to that estimated for global mean sea level. So far, there is little evidence that the rate of rise has accelerated, and the rate of rise at California tide gages has actually flattened since 1980, but projections suggest substantial sea level rise may occur over the next century. Climate change simulations project a substantial rate of global sea level rise over the next century due to thermal expansion as the oceans warm and runoff from melting land-based snow and ice accelerates. Sea level rise projected from the models increases with the amount of warming. Relative to sea levels in 2000, by the 2070–2099 period, sea level rise projections range from 11–54 cm (4.3–21 in) for simulations following the lower (B1) greenhouse gas (GHG) emissions scenario, from 14–61 cm (5.5–24 in) for the middle-upper (A2) emission scenario, and from 17–72 cm (6.7–28 in) for the highest (A1fi) scenario. In addition to relatively steady secular trends, sea levels along the California coast undergo shorter period variability above or below predicted tide levels and changes associated with long-term trends. These variations are caused by weather events and by seasonal to decadal climate fluctuations over the Pacific Ocean that in turn affect the Pacific coast. Highest coastal sea levels have occurred when winter storms and Pacific climate disturbances, such as El Niño, have coincided with high astronomical tides. This study considers a range of projected future global sea level rises in examining possible impacts at California coastal and estuarine stations. Two climate models and three scenarios considered in this scenarios study provide a set of possible future weather and short-period climate fluctuations, and a range of potential long-term sea level rise values. A range of mean sea level rise was considered in combination with weather and El Niño fluctuations extracted from two global climate models and two GHG emissions scenarios. The mean sea level rise values, determined from a survey of several climate models, range from approximately 10–80 cm (3.9–31 in) between 2000 and 2100. The middle to higher end of this range would substantially exceed the historical rate of sea level rise of 15–20 cm (5.9–7.9 in)per century observed at San Francisco and San Diego during the last 100 years. Gradual sea level rise progressively worsens the impacts of high tides and the surge and waves associated with storms. The potential for impacts of future sea level rise was assessed from the occurrence of hourly sea level extremes. The occurrence of extreme events follows a sharply escalating pattern as the magnitude of future sea level rise increases. The confluence of Low barometric pressures from storms and the presence large waves at the same time substantially increases the likelihood of high, damaging sea levels along the California coast. Similarly, astronomical tides and disturbances in sea level that are caused by weather and climate fluctuations are x transmitted into the San Francisco Bay and Delta, and on into the lower reaches of the Sacramento River. In addition to elevating Bay and Delta sea levels directly through inverse barometer and wind effects, storms may generate heavy precipitation and high fresh water runoff and cause floods in the Sacramento/San Joaquin Delta, increasing the potential for inundation of levees and other structures. There may also be increased risk of levee failure due to the hydraulics and geometry of these structures. Rising sea levels from climate change will increase the frequency and duration of extreme high water levels, causing historical coastal and San Francisco Bay/Delta structure design criteria to be exceeded.

California↗
USGS2018

Longevity and population age structure of the arroyo southwestern toad (Anaxyrus californicus) with drought implications

The arroyo southwestern toad is a specialized and federally endangered amphibian endemic to the coastal plains and mountains of central and southern California and northwestern Baja California. It is largely unknown how long these toads live in natural systems, how their population demographics vary across occupied drainages, and how hydrology affects age structure. We used skeletochronology to estimate the ages of adult arroyo toads in seven occupied drainages with varying surface water hydrology in southern California. We processed 179 adult toads with age estimates between 1 and 6 years. Comparisons between skeletochronological ages and known ages of PIT tagged toads showed that skeletochronology likely underestimated toad age by up to 2 years, indicating they may live to 7 or 8 years, but nonetheless major patterns were evident. Arroyo toads showed sexual size dimorphism with adult females reaching a maximum size of 12 mm greater than males. Population age structure varied among the sites. Age structure at sites with seasonally predictable surface water was biased toward younger individuals, which indicated stable recruitment for these populations. Age structures at the ephemeral sites were biased toward older individuals with cohorts roughly corresponding to higher rainfall years. These populations are driven by surface water availability, a stochastic process, and thus more unstable. Based on our estimates of toad ages, climate predictions of extreme and prolonged drought events could mean that the number of consecutive dry years could surpass the maximum life span of toads making them vulnerable to extirpation, especially in ephemeral freshwater systems. Understanding the relationship between population demographics and hydrology is essential for predicting species resilience to projected changes in weather and rainfall patterns. The arroyo toad serves as a model for understanding potential responses to climatic and hydrologic changes in Mediterranean stream systems. We recommend development of adaptive management strategies to address these threats.

California↗
USGS2006

User's Guide, software for reduction and analysis of daily weather and surface-water data: Tools for time series analysis of precipitation, temperature, and streamflow data

The software described here is used to process and analyze daily weather and surface-water data. The programs are refinements of earlier versions that include minor corrections and routines to calculate frequencies above a threshold on an annual or seasonal basis. Earlier versions of this software were used successfully to analyze historical precipitation patterns of the Mojave Desert and the southern Colorado Plateau regions, ecosystem response to climate variation, and variation of sediment-runoff frequency related to climate (Hereford and others, 2003; 2004; in press; Griffiths and others, 2006). The main program described here (Day_Cli_Ann_v5.3) uses daily data to develop a time series of various statistics for a user specified accounting period such as a year or season. The statistics include averages and totals, but the emphasis is on the frequency of occurrence in days of relatively rare weather or runoff events. These statistics are indices of climate variation; for a discussion of climate indices, see the Climate Research Unit website of the University of East Anglia (http://www.cru.uea.ac.uk/projects/stardex/) and the Climate Change Indices web site (http://cccma.seos.uvic.ca/ETCCDMI/indices.html). Specifically, the indices computed with this software are the frequency of high intensity 24-hour rainfall, unusually warm temperature, and unusually high runoff. These rare, or extreme events, are those greater than the 90th percentile of precipitation, streamflow, or temperature computed for the period of record of weather or gaging stations. If they cluster in time over several decades, extreme events may produce detectable change in the physical landscape and ecosystem of a given region. Although the software has been tested on a variety of data, as with any software, the user should carefully evaluate the results with their data. The programs were designed for the range of precipitation, temperature, and streamflow measurements expected in the semiarid Southwest United States. The user is encouraged to review the examples provided with the software. The software is written in Fortran 90 with Fortran 95 extensions and was compiled with the Digital Visual Fortran compiler version 6.6. The executables run on Windows 2000 and XP, and they operate in a MS-DOS console window that has only very simple graphical options such as font size and color, background color, and size of the window. Error trapping was not written into the programs. Typically, when an error occurs, the console window closes without a message.

Open-File Report↗
USGS2013

A natural resource condition assessment for Sequoia and Kings Canyon National Parks: Appendix 22: climatic change

Climate is a master controller of the structure, composition, and function of biotic communities, affecting them both directly, through physiological effects, and indirectly, by mediating biotic interactions and by influencing disturbance regimes. Sequoia and Kings Canyon National Park’s (SEKI’s) dramatic elevational changes in biotic communities -- from warm mediterranean to cold alpine -- are but one manifestation of climate’s overarching importance in shaping SEKI’s landscape. Yet humans are now altering the global climate, with measurable effects on ecosystems (IPCC 2007). Over the last few decades across the western United States, human-induced climatic changes have likely contributed to observed declines in fraction of precipitation falling as snow and snowpack water content (Mote et al. 2005, Knowles et al. 2006), advance in spring snowmelt (Stewart et al. 2005, Barnett et al. 2008), and consequent increase in area burned in wildfires (Westerling et al. 2006). In the Sierra Nevada, warming temperatures have likely contributed to observed glacial recession (Basagic 2008), uphill migration of small mammals (Moritz et al. 2008), and increasing tree mortality rates (van Mantgem and Stephenson 2007, van Mantgem et al. 2009). More substantial changes can be expected for the future (e.g., IPCC 2007). Given the central importance of climate and climatic changes, we sought to describe long-term trends in temperature and precipitation at SEKI. Time and budget constraints limited us to analyses of mean annual temperature and mean annual precipitation, using readily-available data. If funds become available in the future, further analyses will be needed to analyze trends by season, trends in daily minimum and maximum temperatures, and so on. We chose to analyze data from individual weather stations rather than use interpolated climatic data from sources such as PRISM (http://www.prism.oregonstate.edu/). In topographically complex mountainous regions with few weather stations, like SEKI, the addition or subtraction of even a single weather station through time has the potential to significantly bias trends in interpolated data. In particular, this analysis was motivated by our questioning of some PRISM results presented in Appendix 1 (Landscape Context) that compared temperature averages between two 30-year periods of the 20th Century. Figures 6 and 11 of Appendix 1 indicate that recent (1971-2000) temperatures in northern Kings Canyon National Park averaged some 2° C cooler than those of 1911-1940. This would represent a truly profound and persistent cooling, and seems to be at odds both with the glacial retreats observed in the area over the century (Basagic 2008), and with the reported PRISM warming of nearly 2° C just to the west of the cooling (see Figs. 6 and 11 in Appendix 1). We suspect that the extreme localized Kings Canyon cooling reported by PRISM is an artifact of sparsely-distributed weather stations in the region being added and discontinued over the span of the 20th Century. For example, data from the Western Regional Climate Center (http://www.wrcc.dri.edu/coopmap/) suggest that for the period 1911 through 1924 PRISM must interpolate northern Kings Canyon temperatures based on a few low-elevation stations -- separated by hundreds of kilometers -- in Nevada and California’s San Joaquin Valley. In contrast, by 1970 PRISM interpolations will be dominated by closer, higher-elevation stations (see this report). The single weather station closest to northern Kings Canyon that has a temperature record at least partly spanning Appendix 1’s two 30-year time periods -- the Independence station, with a relatively continuous temperature record starting in 1925 -- shows a modest warming, not a cooling, between 1925-1940 and 1971-2000, further casting doubt on the Kings Canyon cooling shown in Figs. 6 and 11 of Appendix 1. If funds become available, it will be useful to more formally analyze potential PRISM biases in long-term SEKI climatic trends. Until then, the analyses of individual weather station records presented here (effectively an analysis of source data that PRISM uses) are meant to provide a robust summary of climatic changes in SEKI.

California↗
USGS2015

Non-linear responses of glaciated prairie wetlands to climate warming

The response of ecosystems to climate warming is likely to include threshold events when small changes in key environmental drivers produce large changes in an ecosystem. Wetlands of the Prairie Pothole Region (PPR) are especially sensitive to climate variability, yet the possibility that functional changes may occur more rapidly with warming than expected has not been examined or modeled. The productivity and biodiversity of these wetlands are strongly controlled by the speed and completeness of a vegetation cover cycle driven by the wet and dry extremes of climate. Two thresholds involving duration and depth of standing water must be exceeded every few decades or so to complete the cycle and to produce highly functional wetlands. Model experiments at 19 weather stations employing incremental warming scenarios determined that wetland function across most of the PPR would be diminished beyond a climate warming of about 1.5–2.0 °C, a critical temperature threshold range identified in other climate change studies.

Prairie Pothole Region↗
USGS2021

Seed production patterns of surviving Sierra Nevada conifers show minimal change following drought

Reproduction is a key component of ecological resilience in forest ecosystems, so understanding how seed production is influenced by extreme drought is key to understanding forest recovery trajectories. If trees respond to mortality-inducing drought by preferentially allocating resources for reproduction, the recovery of the stand to pre-drought conditions may be enhanced accordingly. We used a 20-year annual seed capture data set to investigate whether seed production by three tree genera commonly found in the Sierra Nevada ( Abies , Pinus , and Calocedrus ) was correlated with variation in local weather, which included an extreme drought spanning multiple years. We tested whether average seed production differed during the drought years, and whether annual seed counts could be explained by three weather variables: spring temperature, annual precipitation, and summer climatic water deficit (CWD). We fit models testing for four separate effects: (1) a priming year model (weather 1 year prior to reproductive bud initiation), (2) a bud initiation model (weather in the year of reproductive bud initiation), (3) a pollination year model (weather in the year of pollination), and (4) maturation year model (weather in the year of seed maturation). For genera with two-year reproductive cycles, the pollination and maturation models were combined. We found support for the summer CWD Abies maturation year model, which suggested higher seed outputs immediately following dry summer conditions. The spring temperature pollination year model was selected for Pinus , which suggested that seed output is higher following warm spring weather during pollination. The annual precipitation priming year model was selected for Calocedrus , which showed a negative association between seed production and wetter conditions two years prior to seed production. More parent tree basal area resulted in higher seed output for all genera, though the confidence intervals overlapped 0 for Calocedrus . Permutation tests sugested there was no systematic difference in mean seed production during the drought after accounting for live tree basal area, regardless of genus. These results highlight the variability in response across genera, and suggest that the influence of seed production on forest recovery following drought-related mortality may depend on affected species and the timing of the mortality event within the masting cycle. A greater understanding of species-level masting to drought stress is needed to more precisely predict community-level recovery following drought.

California↗
USGS2013

Chemical transfers along slowly eroding catenas developed on granitic cratons in southern Africa

A catena is a series of distinct but co-evolving soils arrayed along a slope. On low-slope, slowly eroding catenas the redistribution of mass occurs predominantly as plasma, the dissolved and suspended constituents in soil water. We applied mass balance methods to track how redistribution via plasma contributed to physical and geochemical differentiation of nine slowly eroding (~ 5 mm ky − 1 ) granitic catenas. The catenas were arrayed in a 3 × 3 climate by relief matrix and located in Kruger National Park, South Africa. Most of the catenas contained at least one illuviated soil profile that had undergone more volumetric expansion and less mass loss, and these soils were located in the lower halves of the slopes. By comparison, the majority of slope positions were eluviated. Soils from the wetter climates (550 and 730 mm precipitation yr − 1 ) generally had undergone greater collapse and lost more mass, while soils in the drier climate (470 mm yr − 1 ) had undergone expansion and lost less mass. Effects of differences in catena relief were less clear. Within each climate zone, soil horizon mass loss and strain were correlated, as were losses of most major elements, illustrating the predominant influence of primary mineral weathering. Nevertheless, mass loss and volumetric collapse did not become extreme because of the skeleton of resistant primary mineral grains inherited from the granite. Colloidal clay redistribution, as traced by the ratio of Ti to Zr in soil, suggested clay losses via suspension from catena eluvial zones. Thus illuviation of colloidal clays into downslope soils may be crucial to catena development by restricting subsurface flow there. Our analysis provides quantitative support for the conceptual understanding of catenas in cratonic landscapes and provides an endmember reference point in understanding the development of slowly eroding soil landscapes.

Geoderma↗
USGS2014

Comparing species distribution models constructed with different subsets of environmental predictors

Aim To assess the usefulness of combining climate predictors with additional types of environmental predictors in species distribution models for range-restricted species, using common correlative species distribution modelling approaches. Location Florida, USA Methods We used five different algorithms to create distribution models for 14 vertebrate species, using seven different predictor sets: two with bioclimate predictors only, and five ‘combination’ models using bioclimate predictors plus ‘additional’ predictors from groups representing: human influence, land cover, extreme weather or noise (spatially random data).We use a linear mixed-model approach to analyse the effects of predictor set and algorithm on model accuracy, variable importance scores and spatial predictions. Results Regardless of modelling algorithm, no one predictor set produced significantly more accurate models than all others, though models including human influence predictors were the only ones with significantly higher accuracy than climate-only models. Climate predictors had consistently higher variable importance scores than additional predictors in combination models, though there was variation related to predictor type and algorithm. While spatial predictions varied moderately between predictor sets, discrepancies were significantly greater between modelling algorithms than between predictor sets. Furthermore, there were no differences in the level of agreement between binary ‘presence–absence’ maps and independent species range maps related to the predictor set used. Main conclusions Our results indicate that additional predictors have relatively minor effects on the accuracy of climate-based species distribution models and minor to moderate effects on spatial predictions. We suggest that implementing species distribution models with only climate predictors may provide an effective and efficient approach for initial assessments of environmental suitability.

Florida↗
USGS2021

Wildfires and global change

No single factor produces wildfires; rather, they occur when fire thresholds (ignitions, fuels, and drought) are crossed. Anomalous weather events may lower these thresholds and thereby enhance the likelihood and spread of wildfires. Climate change increases the frequency with which some of these thresholds are crossed, extending the duration of the fire season and increasing the frequency of dry years. However, climate-related factors do not explain all of the complexity of global fire-regime changes, as altered ignition patterns (eg human behavior) and fuel structures (eg land-use changes, fire suppression, drought-induced dieback, fragmentation) are extremely important. When the thresholds are crossed, the size of a fire will largely depend on the duration of the fire weather and the extent of the available area with continuous fuels in the landscape.

southeast Australia↗
USGS2022

Ecologically relevant moisture and temperature metrics for assessing dryland ecosystem dynamics

In drylands, water-limited regions that cover ~40% of the global land surface, ecosystems are primarily controlled by access to soil moisture and exposure to simultaneously hot and dry conditions. Quantifying ecologically relevant environmental metrics is difficult in drylands because the response of vegetation to moisture and temperature conditions is not easily explained solely by climate-based metrics. To address this knowledge gap, we developed and examined 27 climate and ecological drought metrics across dryland areas of the western U.S. Included in the 27 metrics is a suite of 19 largely new “ecological drought metrics” that are designed to quantify multiple aspects of environmental limitation in drylands, including overall growing conditions, seasonal fluctuations, seasonal moisture timing, exposure to extreme drought, and recruitment potential for perennial plants. To quantify these metrics, we simulated water balance pools and fluxes of daily soil moisture at multiple depths with historical weather from 1970-2010 using the SOILWAT2 ecosystem water balance model. We assessed the relationships among these metrics and their spatial and temporal patterns. We found that the inclusion of ecological drought metrics substantially increased the dimensionality of the climate metrics dataset; the number of independent variables needed to explain 90% of the variance in the dataset increased with the addition of ecological drought metrics. Spatial patterns in overall growing conditions represented well-known differences among ecoregions, for example high temperatures and low precipitation in the southwest and cool temperatures and greater precipitation in the northeast. Seasonal fluctuation in soil water availability (SWA) was greatest in the southwest (Mojave Desert) while fluctuation in climatic water deficit (CWD) was greatest in the northwest (northern Great Basin and Columbia Plateau). Seasonal timing of moisture also differed among metrics; the timing of wet degree days (WDD), SWA and CWD were only weakly related to seasonal timing of precipitation. Plant recruitment metrics varied strongly across western drylands. In the Great Plains, recruitment events occurred more frequently and lasted longer than in the intermountain regions, where recruitment events were comparatively rare and short. These ecological drought metrics provide new insight into patterns of soil moisture and temperature that shape the structure and function of dryland ecosystems. The metrics will be useful for assessing the potential impact of climate change on dryland ecosystems and developing adaptive resource management strategies to sustain dryland ecosystem services in a changing world.

Ecohydrology↗
USGS2024

Characterizing future streamflows in Massachusetts using stochastic modeling—A pilot study

Communities throughout Massachusetts face the potential effects of climate change, ranging from more extreme rainfall to more pronounced and frequent droughts. Understanding the effects of climate change on hydrology is important to State and community officials to evaluate the potential effects on infrastructure and water systems. To better understand the effects of climate change on hydrology, the U.S. Geological Survey, in partnership with Cornell University and Tufts University, conducted a study in cooperation with the Massachusetts Executive Office of Energy and Environmental Affairs to develop tools for projecting 21st-century climate and hydrologic characteristics in Massachusetts. A stochastic weather generator was developed to project future climatic characteristics for Massachusetts. The stochastic weather generator estimates daily precipitation, minimum temperature, and maximum temperature for 17 warming scenarios (from 0 to 8 degrees Celsius, in 0.5-degree increments). To project future hydrologic characteristics, the stochastic weather generator output data were input to the Precipitation-Watershed Modeling System deterministic watershed model for the Squannacook River watershed, which is the watershed selected as the pilot study location for investigating future hydrologic characteristics. Hydrologic data output from the deterministic watershed model were then input to a stochastic watershed model developed for this study to correct model errors (model errors are often observed in the output from deterministic models at the high- and low-flow extremes). The output from the stochastic watershed model was then used to characterize hydrology for the 17 warming scenarios. For the Squannacook River watershed, the results project more extreme flood and low streamflows under the warming scenarios. Output from the tools allows the characterization of future streamflows for the years 2030, 2050, 2070, and 2090, which expands our understanding of 21st-century climatic and hydrologic risk in Massachusetts. These tools could improve Federal, State, and community officials’ ability to mitigate the effects of climate change over the next several decades.

Massachusetts↗
USGS2020

Investigating the effects of land use and land cover on the relationship between moisture and reflectance using Landsat Time Series

To better understand the Earth system, it is important to investigate the interactions between precipitation, land use/land cover (LULC), and the land surface, especially vegetation. An improved understanding of these land-atmosphere interactions can aid understanding of the climate system and modeling of time series satellite data. Here, we investigate the effect of precipitation and LULC on the reflectance of the land surface in the northern U.S. Great Plains. We utilize time series satellite data from the 45 year Landsat archive. The length of the Landsat record allows for analysis of multiple periods of drought and wet conditions (reflecting climate, as well as weather), such that the precipitation-reflectance relationship can be investigated robustly for every individual pixel in the study area. The high spatial resolution of Landsat (30 m) allows for investigation of spatial patterns in weather (i.e., precipitation extremes) interactions with land surface reflectance at the scale of individual fields. Weather history is represented by a drought index that describes effective moisture availability, the Standardized Precipitation and Evaporation Index (SPEI). We find that effective moisture has a robust and consistent effect on reflectance over many types of land cover, with ∼90% of all pixels having significantly ( p &lt; 0.01 "> p < 0.01 ) higher visible reflectance during dry periods than during wet, occurring in nearly all regional, temporal, and LULC categories investigated. In grassland, the relationship is especially strong; there is an average reflectance increase of more than a third between very wet and very dry conditions (red band), and ∼99% of pixels have a significant relationship. In cropland, the effective moisture-reflectance relationship is more variable, suggesting that management decisions are an important factor in cropland-reflectance relationships.

North Dakota, South Dakota↗
USGS2006

Salt marsh dieback in coastal Louisiana: Survey of plant and soil conditions in Barataria and Terrebonne basins, June 2000-September 2001

Sudden and extensive dieback of the perennial marsh grass, Spartina alterniflora Loisel (smooth cordgrass), which dominates regularly flooded salt marshes along the Gulf of Mexico and Atlantic coastlines, occurred in the coastal zone of Louisiana. The objectives of this study were to assess soil and plant conditions in dieback areas of the Barataria-Terrebonne estuarine system as well as vegetative recovery during and after this dieback event. Multiple dieback sites were examined along 100 km of shoreline from the Atchafalaya River to the Mississippi River during the period from June 2000 through September 2001. The species primarily affected was S. alterniflora; sympatric species such as Avicennia germinans (L.) Stearn (black mangrove) and Juncus roemerianus Scheele (needlegrass rush) showed no visible signs of stress. The pattern of marsh dieback was distinctive with greatest mortality in the marsh interior, suggesting a correlation with local patterns of soil chemistry and/or hydrology. Little or no expansion of dieback occurred subsequent to the initial event, and areas with 50 percent or less mortality in the fall of 2000 had completely recovered by April 2001. Recovery was slower in interior marshes with 90 percent or greater mortality initially. However, regenerating plants in dieback areas showing some recovery were robust, and reproductive output was high, indicating that the causative agent was no longer present and that post-dieback soil conditions were actually promoting plant growth. Stands of other species within or near some dieback sites remained largely unchanged or expanded (A. germinans) into the dead salt marsh. The cause of the dieback is currently unknown. Biotic agents and excessive soil waterlogging/high sulfide were ruled out as primary causes of this acute event, although they could have contributed to overall plant stress and/or interacted with the primary agent to cause plant mortality. Our observations over the 15 month study specifically do not support the contention that dieback was caused by excessive grazing by Littoraria irrorata (marsh periwinkle). Instead, the data show that snails were responding to plant mortality and played an important role in rapid degradation of dead material in some areas. The dieback event was coincident with an extreme drought, low river discharge, and low sea level. These conditions could have caused plant mortality by directly decreasing water availability, increasing salinity, and/or causing oxidation and acidification of soils. The latter scenario was supported by findings of higher pyrite and acid-extractable aluminum and iron, higher acidification potential of dieback soils, and higher concentrations of aluminum and iron in dieback plant tissues (indicating uptake of potentially toxic metals) when compared to reference marshes showing no dieback. The implication of these findings is that periodic weather extremes may play a greater role in shaping coastal plant communities than has previously been recognized. Although such events may not be controlled directly, the resilience and recovery of the system may be altered by management. Such considerations will become increasingly important as global climate changes and human pressures in the coastal zone grow.

Louisiana↗
USGS2017

Climatic history of the northeastern United States during the past 3000 years

Many ecosystem processes that influence Earth system feedbacks, including vegetation growth, water and nutrient cycling, and disturbance regimes, are strongly influenced by multi-decadal to millennial-scale variations in climate that cannot be captured by instrumental climate observations. Paleoclimate information is therefore essential for understanding contemporary ecosystems and their potential trajectories under a variety of future climate conditions. With the exception of fossil pollen records, there are a limited number of northeastern US (NE US) paleoclimate archives that can provide constraints on its temperature and hydroclimate history. Moreover, the records that do exist have not been considered together. Tree-ring data indicate that the 20th century was one of the wettest of the past 500 years in the eastern US (Pederson et al., 2014), and lake-level records suggest it was one of the wettest in the Holocene (Newby et al., 2014); how such results compare with other available data remains unclear, however. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions are consistent with the long-term cooling trend (1000 BCE–1700 CE) evident in hemispheric-scale reconstructions, but hydroclimate reconstructions reveal new information, including an abrupt transition from wet to dry conditions around 550–750 CE. NE US paleo data suggest that conditions during the Medieval Climate Anomaly were warmer and drier than during the Little Ice Age, and drier than today. There is some evidence for an acceleration over the past century of a longer-term wetting trend in the NE US, and coupled with the abrupt shift from a cooling trend to a warming trend from increased greenhouse gases, may have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US, make inter-proxy comparisons, and improve estimates of uncertainty in the reconstructions.

Climate of the Past↗
USGS2021

Five decades of observed daily precipitation reveal longer and more variable drought events across much of the western United States

Multiple lines of evidence suggest climate change will result in increased precipitation variability and consequently more frequent extreme events. These hydroclimatic changes will likely have significant socioecological impacts, especially across water-limited regions. Here we present an analysis of daily meteorological observations from 1976 to 2019 at 337 long-term weather stations distributed across the western United States (US). In addition to widespread warming (0.2 °C ± 0.01°C/decade, daily maximum temperature), we observed trends of reduced annual precipitation (−2.3 ± 1.5 mm/decade) across most of the region, with increasing interannual variability of precipitation. Critically, daily observations showed that extreme-duration drought became more common, with increases in both the mean and longest dry interval between precipitation events (0.6 ± 0.2, 2.4 ± 0.3 days/decade) and greater interannual variability in these dry intervals. These findings indicate that, against a backdrop of warming and drying, large regions of the western US are experiencing intensification of precipitation variability, with likely detrimental consequences for essential ecosystem services.

Geophysical Research Letters↗
USGS2014

Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts

The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.

Natural Hazards↗