Temporal and Spatial Trends of the Standardized Precipitation Index (SPI) in Greece Using Observations and Output from Regional Climate Models

2016 ◽  
pp. 475-481 ◽  
Author(s):  
E. Kostopoulou ◽  
C. Giannakopoulos ◽  
D. Krapsiti ◽  
A. Karali
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Regional Climate Models ◽  
Precipitation Index ◽  
Spatial Trends ◽  
Temporal And Spatial ◽  
The Standardized Precipitation Index ◽  
Temporal And Spatial Trends

scholarly journals Assessing the Added Value of Dynamical Downscaling Using the Standardized Precipitation Index

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Jared H. Bowden ◽  
Kevin D. Talgo ◽  
Tanya L. Spero ◽  
Christopher G. Nolte
Keyword(s):  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Added Value ◽  
Tropical Storms ◽  
The Standardized Precipitation Index ◽  
The Impact ◽  
Resources Planning

In this study, the Standardized Precipitation Index (SPI) is used to ascertain the added value of dynamical downscaling over the contiguous United States. WRF is used as a regional climate model (RCM) to dynamically downscale reanalysis fields to compare values of SPI over drought timescales that have implications for agriculture and water resources planning. The regional climate generated by WRF has the largest improvement over reanalysis for SPI correlation with observations as the drought timescale increases. This suggests that dynamically downscaled fields may be more reliable than larger-scale fields for water resource applications (e.g., water storage within reservoirs). WRF improves the timing and intensity of moderate to extreme wet and dry periods, even in regions with homogenous terrain. This study also examines changes in SPI from the extreme drought of 1988 and three “drought busting” tropical storms. Each of those events illustrates the importance of using downscaling to resolve the spatial extent of droughts. The analysis of the “drought busting” tropical storms demonstrates that while the impact of these storms on ending prolonged droughts is improved by the RCM relative to the reanalysis, it remains underestimated. These results illustrate the importance and some limitations of using RCMs to project drought.

scholarly journals FUTURE DROUGHT PROJECTION FOR THE GREEK REGION

2017 ◽  
Vol 50 (2) ◽  
pp. 1038
Author(s):  
C. Anagnostopoulou
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Regional Climate Models ◽  
Future Period ◽  
Spi Index ◽  
Dry Spells ◽  
The Impact ◽  
Greek Region

Drought is one of the most important factors of change. The epi-drops drought in one area are complex because they simultaneously affect many areas, such as climate, agriculture, the economy and in general the structure of society. This study deals only with the meteorological drought, particularly considering the phenomenon of drought through the index Standardized Precipitation Index (SPI). The Greece is characterized by frequent drought episodes that often exceed 10 consecutive days of drought (dry spells). Also, in recent years the area probably climate models have been used in a wide study of the impact of climate change in different regions on the planet. Rainfall data from five regional climate models (RCMs) have been used to calculate the SPI index in the Greek area, the reporting period and two subsequent periods by the end of the 21st century. All models show a decreasing trend of the SPI median during the period studied. For the first future period 2021-2050, there is a clear signal for a dry decade towards the end of the period that is most apparent in southern and island regions. On the other hand, in the second future period 2071-2100, there is an increasing trend resulting to normal or wetter years.

scholarly journals Spatiotemporal Characteristics of Meteorological Drought for the Island of Crete

2011 ◽  
Vol 12 (2) ◽  
pp. 206-226 ◽  
Author(s):  
Aristeidis G. Koutroulis ◽  
Aggeliki-Eleni K. Vrohidou ◽  
Ioannis K. Tsanis
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Drought Severity ◽  
Monthly Precipitation ◽  
Drought Conditions ◽  
First Time

Abstract A modified drought index, named the spatially normalized–standardized precipitation index (SN-SPI), has been developed for assessing meteorological droughts. The SN–SPI is a variant index to the standardized precipitation index and is based on the probability of precipitation at different time scales, but it is spatially normalized for improved assessment of drought severity. Results of this index incorporate the spatial distribution of precipitation and produce improved drought warnings. This index is applied in the island of Crete, Greece, and the drought results are compared to the ones of SPI. A 30-year-long average monthly precipitation dataset from 130 watersheds of the island is used by the above indices for drought classification in terms of its duration and intensity. Bias-adjusted monthly precipitation estimates from an ensemble of 10 regional climate models were used to quantify the influence of global warming to drought conditions over the period 2010–2100. Results based on both indices (calculated for three time scales of 12, 24, and 48 months) from 3 basins in west, central, and east parts of the island show that 1) the extreme drought periods are the same (reaching 7% of time) but the intensities based on SN–SPI are lower; 2) the area covered by extreme droughts is 3% (first time scale), 16% (second time scale), and 25% (third time scale), and 96% (first time scale), 95% (second time scale), and 80% (third time scale) based on the SN–SPI and SPI, respectively; 3) concerning the longest time scale (48 months), more than half of the area of Crete is about to experience drought conditions during 28%, 69%, and 97% for 2010–40, 2040–70, and 2070–2100, respectively; and 4) extremely dry conditions will cover 52%, 33%, and 25% of the island for the future 90-year period using 12-, 24-, and 48-month SN–SPI, respectively.

Regional Climate Scenarios for use in Nordic Water Resources Studies

2003 ◽  
Vol 34 (5) ◽  
pp. 399-412 ◽  
Author(s):  
M. Rummukainen ◽  
J. Räisänen ◽  
D. Bjørge ◽  
J.H. Christensen ◽  
O.B. Christensen ◽  
...  
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Soil Frost ◽  
Nordic Region ◽  
Regional Climate Projections

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

scholarly journals Cool season precipitation projections for California and the Western United States in NA-CORDEX models

2021 ◽  
Author(s):  
Kelly Mahoney ◽  
James D. Scott ◽  
Michael Alexander ◽  
Rachel McCrary ◽  
Mimi Hughes ◽  
...  
Keyword(s):  
United States ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Western United States ◽  
Monthly Precipitation ◽  
Wet Season ◽  
Cool Season ◽  
Projected Change

AbstractUnderstanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

scholarly journals Projecting Health Impacts of Future Temperature: A Comparison of Quantile-Mapping Bias-Correction Methods

2021 ◽  
Vol 18 (4) ◽  
pp. 1992
Author(s):  
Weijia Qian ◽  
Howard H. Chang
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Climate Science ◽  
Regional Climate Models ◽  
Health Impact ◽  
Quantile Mapping ◽  
Ed Visits

Health impact assessments of future environmental exposures are routinely conducted to quantify population burdens associated with the changing climate. It is well-recognized that simulations from climate models need to be bias-corrected against observations to estimate future exposures. Quantile mapping (QM) is a technique that has gained popularity in climate science because of its focus on bias-correcting the entire exposure distribution. Even though improved bias-correction at the extreme tails of exposure may be particularly important for estimating health burdens, the application of QM in health impact projection has been limited. In this paper we describe and apply five QM methods to estimate excess emergency department (ED) visits due to projected changes in warm-season minimum temperature in Atlanta, USA. We utilized temperature projections from an ensemble of regional climate models in the North American-Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). Across QM methods, we estimated consistent increase in ED visits across climate model ensemble under RCP 8.5 during the period 2050 to 2099. We found that QM methods can significantly reduce between-model variation in health impact projections (50–70% decreases in between-model standard deviation). Particularly, the quantile delta mapping approach had the largest reduction and is recommended also because of its ability to preserve model-projected absolute temporal changes in quantiles.

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