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This map shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). Different colors indicate the level of consensus among five different MC1 simulations (i.e., one for each forecast provided by five different weather models), ranging from one of five to five of five simulations predicting high fire potential. The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using...
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The Standardized Precipitation Index (SPI) is a probability index that can be calculated for different time periods to indicate periods of abnormal wetness or dryness. SPI is derived solely from monthly precipitation and can be compared across regions with different climates. The SPI is an index based on the probability of recording a given amount of precipitation, and the probabilities are standardized so that an index of zero indicates the median precipitation amount (half of the historical precipitation amounts are below the median, and half are above the median). This dataset shows the average 12-month SPI (in classes ranging from extremely wet to extremely dry) for the three-month forecast period indentified...
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Global Drought Hazard Frequency and Distribution is a 2.5 by 2.5 minute grid based upon the International Research Institute for Climate Predition's (IRI) Weighted Anomaly of Standardized Precipitation (WASP). Utilizing average monthly precipitation data from 1980 through 2000 at a resolution of 2.5 degrees, WASP assesses the precipitation deficit or surplus over a three month temporal window that is weighted by the magnitude of the seasonal cyclic variation in precipitation. The three months' averages are derived from the precipitation data and the median rainfall for the 21 year period is calculated for each grid cell. Grid cells where the three month running average of precipitation is less than 1 mm per day...
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This dataset shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using National Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature, precipitation, and relative humidity) data, and fuel moisture and loading estimates. Monthly climatic data includes recorded values up to the last observed...
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This dataset shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using National Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature, precipitation, and relative humidity) data, and fuel moisture and loading estimates. Monthly climatic data includes recorded values up to the last observed...
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This data set maps sagebrush mortality in Utah delineated by Utah Division of Wildlife Resources personnel during the summer of 2003.
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This dataset shows the predicted area of high fire potential for the current year up to the end of the forecast period as simulated by a modified version of the MC1 Dynamic General Vegetation Model (DGVM). The area of high fire potential is where PDSI and MC1-calculated values of potential fire behavior (fireline intensity for forest and shrubland and rate of spread of spread for grassland) exceed calibrated threshold values. Potential fire behavior in MC1 is estimated using National Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature, precipitation, and relative humidity) data, and fuel moisture and loading estimates. Monthly climatic data includes recorded values up to the last observed...
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The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
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The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
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The Palmer Drought Severity Index (PDSI) is a measure of drought derived from both precipitation and temperature. Negative (i.e., dry) values of PDSI are closely associated with a high potential for wildland fire. PDSI is based on a supply-and-demand model of soil moisture originally developed by Wayne Palmer, who published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.The index has proven to be most effective in indicating long-term drought (or wetness) over a matter of several months. PDSI calculations are standardized for an individual station (or grid cell) based on the long-term variability of precipitation and temperature at that location....
This data release is provided in support of Arismendi, I., Dunham, J.B., Heck, M.P., Schultz, L.D., Hockman-Wert, D.P., 2017, A statistical method to predict flow permanence in dryland streams from time series of stream temperature: Water, v. 9, no. 12, p. 946, https://doi.org/10.3390/w9120946. This code release contains all of the source code from the "Hidden Markov Model" sections of the associated manuscript. The source code was written using the R programming language (www.r-project.org, version 3.3.1). Running the code requires knowlege of the R programming language. The code snippet requires the folder location containing the data, and the site being processed, to be updated. The code requires certain R packages,...
There is growing evidence that the rate of warming is amplified with elevation, such that high-mountain environments experience more rapid changes in temperature than environments at lower elevations. Elevation-dependent warming (EDW) can accelerate the rate of change in mountain ecosystems, cryospheric systems, hydrological regimes and biodiversity. Here we review important mechanisms that contribute towards EDW: snow albedo and surface-based feedbacks; water vapour changes and latent heat release; surface water vapour and radiative flux changes; surface heat loss and temperature change; and aerosols. All lead to enhanced warming with elevation (or at a critical elevation), and it is believed that combinations...
Climate policy developers and natural resource managers frequently desire high-resolution climate data to prepare for future effects of climate change. But they face a long-standing problem: the vast majority of climate models have been run at coarse resolutions—from hundreds of kilometers in global climate models (GCMs) down to 25–50 kilometers in regional climate models (RCMs).
The Eastern Shoshone and Northern Arapaho Tribes on the Wind River Indian Reservation in Wyoming are preparing for drought and other climate fluctuations with help from a broad coalition of scientists. Read More: https://www.drought.gov/drought/sites/drought.gov.drought/files/media/whatisnidis/Newsletter/October%202015%20v4.pdf
Members of the Eastern Shoshone and Northern Arapaho Tribes have been working with an interdisciplinary team of social, ecological, and climate scientists from the North Central CSC, the High Plains Regional Climate Center, and the National Drought Mitigation Center along with other university and agency partners to prepare regular climate and drought summaries to aid in managing water resources on the Wind River Reservation and in surrounding areas.
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The dataset represents benthic aquatic macoinvertebrates collected from eight streams to characterize production in Rio Grande cutthroat trout (Oncorhynchus clarkii virginalis; RGCT) populations throughout northern New Mexico from 2016 through to 2017. The macroinvertebrates were sampled using Hess samplers with a 250 micron mesh and all taxa were identified to the lowest level of taxonomic resolution.
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The impacts of climate change on cold water species will likely manifest in populations at the trailing edge of their distribution. Rio Grande cutthroat trout (Oncorhynchus clarkii virginalis, RGCT) occupy arid southwestern U.S.A. streams at the southern-most edge of all cutthroat trout distributions; thus making RGCT particularly vulnerable to the anticipated warming and drying in this region. We collected stream temperature and stream drying to determine how these environmental constraints influence life-history trait expression (length- and age-at-maturity), demography, and extirpation risk in RGCT populations from northern New Mexico, U.S.A. We found the rate at which RGCT reached maturity was highest at warm...
Abstract (from PNAS): Recent decades have seen droughts across multiple US river basins that are unprecedented over the last century and potentially longer. Understanding the drivers of drought in a long-term context requires extending instrumental data with paleoclimatic data. Here, a network of new millennial-length streamflow reconstructions and a regional temperature reconstruction from tree rings place 20th and early 21st century drought severity in the Upper Missouri River basin into a long-term context. Across the headwaters of the United States’ largest river basin, we estimated region-wide, decadal-scale drought severity during the “turn-of-the-century drought” ca. 2000 to 2010 was potentially unprecedented...
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Data presented are results of surveys in 2021 for San Diego Cactus Wren (Campylorhynchus brunneicapillus) in southern San Diego County. Surveys were conducted at 378 plots. Plots were surveyed twice in 2021 and the number, age (adult or juvenile), banding status (color banded or not), and breeding status (paired, unpaired, or unknown) of all wrens recorded. Habitat covariate data were collected including amount of dead and stressed cactus in the plot, percent cover of bare ground, and the dominant and percent cover of invasive species.


map background search result map search result map MC1 DGVM fire potential forecast January-December 2012 (based on ECHAM 7-month weather forecast) Palmer drought severity index forecast August - October 2012 (based on ECPC 7-mo weather forecast) MC1 DGVM fire potential forecast January-December 2012 (based on NSIPP 7-month weather forecast) Palmer drought severity index forecast June - August 2012 (based on CCM3V6 7-mo weather forecast) MC1 DGVM fire potential consensus forecast January-August 2012 (number of weather forecasts resulting in high potential) Palmer drought severity index forecast April - June 2012 (based on ECPC 7-mo weather forecast) MC1 DGVM fire potential forecast January-July 2012 (based on ECHAM 7-month weather forecast) Standardized precipitation index forecast April - October (based on ECPC 7-mo weather forecast) Global Drought Hazard Frequency and Distribution Sagebrush Mortality in Utah - 2003 Benthic Macroinvertebrates from Eight Streams Containing Rio Grande Cutthroat Trout in Northern New Mexico Influence of Stream Temperature on Eight Populations of Rio Grande Cutthroat Trout in Northern New Mexico Surveys and Monitoring of Coastal Cactus Wren in Southern San Diego County, 2021 Surveys and Monitoring of Coastal Cactus Wren in Southern San Diego County, 2021 Sagebrush Mortality in Utah - 2003 MC1 DGVM fire potential forecast January-December 2012 (based on ECHAM 7-month weather forecast) Palmer drought severity index forecast August - October 2012 (based on ECPC 7-mo weather forecast) MC1 DGVM fire potential forecast January-December 2012 (based on NSIPP 7-month weather forecast) Palmer drought severity index forecast June - August 2012 (based on CCM3V6 7-mo weather forecast) MC1 DGVM fire potential consensus forecast January-August 2012 (number of weather forecasts resulting in high potential) Palmer drought severity index forecast April - June 2012 (based on ECPC 7-mo weather forecast) MC1 DGVM fire potential forecast January-July 2012 (based on ECHAM 7-month weather forecast) Standardized precipitation index forecast April - October (based on ECPC 7-mo weather forecast) Global Drought Hazard Frequency and Distribution