Skip to main content
Advanced Search

Filters: Tags: statistical downscaling (X)

16 results (43ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
Abstract (from http://link.springer.com/article/10.1007/s11069-016-2376-z): Drought is among the most insidious types of natural disasters and can have devastating economic and human health impacts. This research analyzes the relationship between two readily accessible drought indices—the Palmer Drought Severity Index (PDSI) and Palmer Hydrologic Drought Index (PHDI)—and the damage incurred by such droughts in terms of monetary loss, over the 1975–2010 time period on monthly basis, for five states in the south-central USA. Because drought damage in the Spatial Hazards Events and Losses Database for the United States (SHELDUS™) is reported at the county level, statistical downscaling techniques were used to estimate...
thumbnail
This data series contains 2868 temporal datasets.These data are climate model outputs that have been downscaled to 4-km spatial resolution using the Bias Corrected Statistical Downscaling (BCSD) method. Moore and Walden have modified the BCSD method described by Wood et al (2002), Long-range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research-Atmospheres 107: 4429-4443 and Salathe (2005), Downscaling simulations of future global climate with application to hydrologic modeling. International Journal of Climatology 25: 419-436. The modifications include a different interpolation scheme between GCM grid cells and a different approach to dealing with extreme values (Z-scores...
The Multivariate Adaptive Constructed Analogs(MACA)(Abatzoglou, Brown, 2011) method is a statistical downscaling method which utilizes a training dataset (i.e. a meteorological observation dataset) to remove historical biases and match spatial patterns in climate model output. The following products are available: MACAv1-METDATA is available for the Western USA, while MACAv2-LIVNEH/MACAv2-METDATA are available over the entire conterminous USA. MACAv2-LIVNEH/MACAv2-METDATA both use the newest version of the MACA method (version 2), while MACAv1-METDATA uses version 1. Both methods are very similar to that described by Abatzoglou and Brown, 2011. MACAv2-METDATA
The CA Academy of Science and Point Blue Conservation Science conducted a systematic analysis of uncertainty in modeling the future distributions of ~50 California endemic plant species and ~50 California land birds, explicitly partitioning among 5 alternative sources of variation and testing for their respective contributions to overall variation among modeled outcomes. They mapped the uncertainty from identified sources, which can guide decisions about monitoring, restoration, acquisition, infrastructure, etc., in relation to climate change.
thumbnail
In the expectation that global climate will change steadily in the coming decades, this research project had the goal to obtain a more detailed view of the climatic changes that Hawai’i could experience by the mid and late 21st century. Given the importance of rainfall for Hawaiian ecosystems and freshwater reserves, this project investigated past seasonal rainfall pattern and developed a statistical model to estimate future rainfall changes for the major islands. As a result of this research, high-resolution maps and data are now available that researchers can use to study potential impacts on endangered species, or use the rainfall changes as input in decision-support tools.This data product provides data files...
thumbnail
Drought is a natural hazard that inflicts costly damage to the environment and human communities. Although ample literature exists on the climatological aspects of drought, little is known on whether existing drought indices can predict the damages and how different human communities respond and adapt to the hazard. This project examines (1) whether existing drought indices can predict the occurrence of drought events and their actual damages; (2) how the adaptive capacity (i.e., resilience) varies across space; and (3) what public outreach and engagement effort would be most effective for mitigation of risk and impacts. The study region includes all 503 counties in Arkansas, Louisiana, New Mexico, Oklahoma, and...
Abstract: The aim of this paper is to present a statistical downscaling method in which the relationships between present-day daily weather patterns and local rainfall data are derived and used to project future shifts in the frequency of heavy rainfall events under changing global climate conditions. National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) reanalysis data from wet season months (November to April) 1958–2010 are composited for heavy rain days at 12 rainfall stations in the Hawaiian Islands. The occurrence of heavy rain events (days with amounts above the 90th percentile estimated from all wet season rain days 1958–2010) was found to be strongly correlated...
Abstract (from http://www.tandfonline.com/eprint/EBxQ7emIEP3P6pzxz74H/full) Drought is a hazard that inflicts costly damage to agricultural, hydrologic, and ecological systems and affects human health and prosperity. A comprehensive assessment of resilience to the drought hazard in various communities and an identification of the main variables that affect resilience is crucial to coping with the hazard and promoting resilience. This study assessed the community resilience to drought hazards of all 503 counties of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas using the resilience inference measurement (RIM) model for the period of 2000 to 2015. Through k-means cluster analysis, stepwise discriminant analysis...
This paper examines the hydrologic model performance in three snowmelt-dominated basins in the western United States to dynamically- and statistically downscaled output from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP). Runoff produced using a distributed hydrologic model is compared using daily precipitation and maximum and minimum temperature timeseries derived from the following sources: (1) NCEP output (horizontal grid spacing of approximately 210 km); (2) dynamically downscaled (DDS) NCEP output using a Regional Climate Model (RegCM2, horizontal grid spacing of approximately 52 km); (3) statistically downscaled (SDS) NCEP output; (4) spatially...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1002/2014JD022059/abstract): Seasonal mean rainfall projections for Hawai‘i are given based on statistical downscaling of the latest Coupled Model Intercomparison Project phase 5 (CMIP5) global model results for two future representative concentration pathways (RCP4.5 and RCP8.5). The spatial information content of our statistical downscaling method is improved over previous efforts through the inclusion of spatially extensive, high-quality monthly rainfall data set and the use of improved large-scale climate predictor information. Predictor variables include moisture transport in the middle atmosphere (700 hPa), vertical temperature gradients, and geopotential...
The asynchronous regional regression model (ARRM) is a flexible and computationally efficient statistical model that can downscale station-based or gridded daily values of any variable that can be transformed into an approximately symmetric distribution and for which a large-scale predictor exists. This technique was developed to bridge the gap between large-scale outputs from atmosphere–ocean general circulation models (AOGCMs) and the fine-scale output required for local and regional climate impact assessments. ARRM uses piecewise regression to quantify the relationship between observed and modelled quantiles and then downscale future projections. Here, we evaluate the performance of three successive versions...
Abstract (from http://link.springer.com/article/10.1007/s00382-015-2845-1): Humidity is important to climate impacts in hydrology, agriculture, ecology, energy demand, and human health and comfort. Nonetheless humidity is not available in some widely-used archives of statistically downscaled climate projections for the western U.S. In this work the Localized Constructed Analogs (LOCA) statistical downscaling method is used to downscale specific humidity to a 1°/16° grid over the conterminous U.S. and the results compared to observations. LOCA reproduces observed monthly climatological values with a mean error of ~0.5 % and RMS error of ~2 %. Extreme (1-day in 1- and 20-years) maximum values (relevant to human health...


    map background search result map search result map Downscaled Climate Model Output for the Contiguous United States from IPCC AR4 Scenarios [Bias Corrected Statistical Downscaling (BCSD) Method] Datasets for "Climate Change Research in Support of Hawaiian Ecosystem Management: An Integrated Approach" County-level drought indices The Palmer Drought Severity Index(PDSI)and Palmer Hydrological Drought Index(PHDI) Datasets for "Climate Change Research in Support of Hawaiian Ecosystem Management: An Integrated Approach" County-level drought indices The Palmer Drought Severity Index(PDSI)and Palmer Hydrological Drought Index(PHDI) Downscaled Climate Model Output for the Contiguous United States from IPCC AR4 Scenarios [Bias Corrected Statistical Downscaling (BCSD) Method]