scholarly journals High-resolution multisite daily rainfall projections in India with statistical downscaling for climate change impacts assessment

2013 ◽  
Vol 118 (9) ◽  
pp. 3557-3578 ◽  
Author(s):  
Kaustubh Salvi ◽  
Kannan S. ◽  
Subimal Ghosh
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Statistical Downscaling ◽  
Daily Rainfall ◽  
Climate Change Impacts

A hybrid dynamical-statistical downscaling approach for climate change impacts analysis on high resolution in the Greater Athens Area

2021 ◽  
Author(s):  
Konstantinos V. Varotsos ◽  
Aggeliki Dandou ◽  
Giorgos Papangelis ◽  
Nikolaos Roukounakis ◽  
Maria Tombrou ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Statistical Downscaling ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Horizontal Resolution ◽  
Correction Function ◽  
Climate Projections ◽  
Spatial And Temporal Variability ◽  
Athens Area

<p>The available state-of-the art Regional Climate Model (RCM) simulations from the Euro-Cordex initiative have an horizontal resolution of about 12km which although is adequate for assessing regional climate change impacts is still coarse for studying the climate change impacts in an urban environment such as the Greater Athens Area (GAA). To this aim we propose a hybrid dynamical-statistical downscaling approach that produces high resolution, in the order of 1km, climate change projections for two future periods and under two RCP scenarios. To produce the higher resolution climate projections we combine the results of the Weather Research and Forecasting model (WRF) - Version 3.9.1 -including a single-layer urban canopy model to represent the urban tile- with available RCMs simulations obtained from the Euro-Cordex database.</p><p>Initially an annual WRF, ERA interim driven, simulation for a year identified as a “representative year” for the period 1971-2000 in the GAA is performed at an horizontal resolution of 1km. Subsequently the spatial signal of the WRF simulation is passed to the ERA interim driven RCM simulations for the period 1971-2000 using the unbiasing bias adjusting method which maintains the absolute trend as well as the variability of the RCM simulated data at all time scales. In a second step the donwscaled RCM evaluation simulations are used to bias adjust the transient RCM simulations using the empirical quantile method (EQM). EQM works by matching the transient simulations empirical cumulative distributions to the evaluation ones. This is achieved by establishing a quantile-dependent correction function between them during the reference period. The correction functions are then applied to both the historical and the future periods.</p><p>In this study we present the results for temperature and precipitation but the methodology can be extended to other variables of interest assuming that the WRF and the evaluation RCM simulations adequately reproduce their spatial and temporal variability, respectively.</p>

scholarly journals Climate Change Impacts Assessment on Wine-Growing Bioclimatic Transition Areas

Agriculture ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 605
Author(s):  
Alba Piña-Rey ◽  
Estefanía González-Fernández ◽  
María Fernández-González ◽  
Mª. Nieves Lorenzo ◽  
Fco. Javier Rodríguez-Rajo
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Change Impacts ◽  
Mediterranean Area ◽  
Cultural Practice ◽  
Climatic Conditions ◽  
Study Region ◽  
Bioclimatic Indices ◽  
Northwestern Spain ◽  
The Mediterranean

Viticultural climatic indices were assessed for the evaluation of the meteorological variations in the requirements of wine cultivars. The applied bioclimatic indices have been widely used to provide an initial evaluation of climate change impacts on grapevine and to delineate wine regions and suitable areas for planting around the world. The study was carried out over a period of 16 years (from 2000 to 2015) in five Designation of Origin areas in Northwestern Spain located in the Eurosiberian region, the transition zone between the Eurosiberian and the Mediterranean areas, and in the Mediterranean area. In addition, the high-resolution meteorological dataset “Spain02” was applied to the bioclimatic indices for the period 1950–2095. To further assess the performance of “Spain02”, Taylor diagrams were elaborated for the different bioclimatic indices. A significant trend to an increase of the Winkler, Huglin, Night Cold Index and GSS Indices was detected in the North-western Spain, whereas slight negative trends for BBLI and GSP Indices were observed. To analyze future projections 2061–2095, data from the high-resolution dynamically downscaled daily climate simulations from EURO-CORDEX project were used. To further assess the performance of Spain02, Taylor diagrams were elaborated for the different bioclimatic indices. A trend to an increase of the Winkler, Huglin, Night Cold Index and GSP Indices was detected in Northwestern Spain, whereas slight negative trends for BBLI and GSP Indices were observed. Our results showed that climatic conditions in the study region could variate for the crop in the future, more for Mediterranean than Eurosiberian bioclimatic area. Due to an advance in the phenological events or the vintage data, more alcohol-fortified wines and variations in the acidity level of wines could be expected in Northwestern Spain, these processes being most noticeable in the Mediterranean area. The projections for the BBLI and GSP Indices will induce a decrease in the pressure of the mildew attacks incidence in the areas located at the Eurosiberian region and the nearest transition zones. Projections showed if the trend of temperature increase continues, some cultural practice variations should be conducted in order to preserve the grape cultivation suitability in the studied area.

scholarly journals Statistical downscaling of precipitation and temperature in north‐central Chile: an assessment of possible climate change impacts in an arid Andean watershed

2010 ◽  
Vol 55 (1) ◽  
pp. 41-57 ◽  
Author(s):  
Maxime Souvignet ◽  
Hartmut Gaese ◽  
Lars Ribbe ◽  
Nicole Kretschmer ◽  
Ricardo Oyarzún
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Climate Change Impacts ◽  
North Central ◽  
Central Chile ◽  
Precipitation And Temperature

scholarly journals RCP 8.5 Ghana. High-end climate change impacts on crop production

2020 ◽  
Author(s):  
Sylvia Tramberend ◽  
Günther Fischer ◽  
Harrij van Velthuizen
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Crop Production ◽  
Agricultural Sector ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Development Planning ◽  
Sub Saharan Africa ◽  
Sub Saharan

<p>Climate change threatens vulnerable communities in sub-Saharan Africa who face significant challenges for adaptation. Agriculture provides the livelihood for the majority of population. High-resolution assessments of the effects of climate change on crop production are urgently needed for targeted adaptation planning. In Ghana, next to food needs, agriculture plays an important role on international cocoa markets. To this end, we develop and apply a National Agro-Ecological Zoning system (NAEZ Ghana) to analyze the impacts of high-end (RCP8.5) global warming on agricultural production potentials until the end of this century. NAEZ Ghana uses an ensemble of the CORDEX Africa Regional Climate Model, a regional soil map, to assess development trends of crop production potentials for 19 main crops. Results highlight differential impacts across the country. Especially due to the significant increase in the number of days exceeding high-temperature thresholds, rain-fed production of several food and export crops could be reduced significantly compared to the historical 30-year average (1981-2010). Plantain production, an important food crop, could achieve under climate change less than half of its current potential already in the 2050s and less than 10% by the 2080s. Suitable areas for cocoa production decrease strongly resulting in only one third of production potential compared to today. Other crops with detrimental effects of climate change include oil palm, sugarcane, coffee, and rubber. Production of maize, sorghum, and millet cope well with a future warmer climate. The NAEZ Ghana database provides valuable high-resolution information to support agricultural sector development planning and climate change adaptation strategies. The expansion of irrigation development will play a central role in some areas. This requires further research on Ghana’s linkages between food, water, and energy, taking into account climate and socio-economic changes.</p>

Assessing climate change impacts on European wind energy from ENSEMBLES high-resolution climate projections

2014 ◽  
Vol 128 (1-2) ◽  
pp. 99-112 ◽  
Author(s):  
Isabelle Tobin ◽  
Robert Vautard ◽  
Irena Balog ◽  
François-Marie Bréon ◽  
Sonia Jerez ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Wind Energy ◽  
Climate Change Impacts ◽  
Climate Projections

Assessment of climate change impacts on energy capacity planning in Ontario, Canada using high-resolution regional climate model

2020 ◽  
Vol 274 ◽  
pp. 123026
Author(s):  
Shuo Wang ◽  
Jinxin Zhu ◽  
Gordon Huang ◽  
Brian Baetz ◽  
Guanhui Cheng ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Regional Climate Model ◽  
Capacity Planning ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Energy Capacity

Linking atmospheric circulation to daily rainfall patterns across the Murrumbidgee River Basin

2003 ◽  
Vol 48 (7) ◽  
pp. 233-240 ◽  
Author(s):  
S.P. Charles ◽  
B.C. Bates ◽  
N.R. Viney
Keyword(s):  
Climate Change ◽  
Atmospheric Circulation ◽  
River Basin ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Rainfall Variability ◽  
Daily Rainfall ◽  
Climate Change Impacts ◽  
River Health ◽  
Climate Model Simulations

The hydrological cycle in Australia covers an extraordinary range of climatic and hydrologic regimes. It is now widely accepted that Australian hydrology is significantly different from all other regions and continents with the partial exception of southern Africa. Rainfall variability is very high in almost all regions with respect to amount and the lengths of wet and dry spells. These factors are keys to the behaviour and health of Australian aquatic ecosystems and water resources. Thus assessment of how rainfall may change under a potential future climate is critical. For a case study of the Murrumbidgee River Basin (MRB), a statistical downscaling model that links broad scale atmospheric circulation to multi-site, daily precipitation is assessed using observed data. This model can be driven with climate model simulations to produce rainfall scenarios at the scale required by impacts models. These can then be used in probabilistic risk assessments of climate change impacts on river health. These issues will be discussed in the context of assessing the potential impacts of precipitation changes due to projected climate change on river health.

Some Pitfalls in Statistical Downscaling of Future Climate

2018 ◽  
Vol 99 (4) ◽  
pp. 791-803 ◽  
Author(s):  
John R. Lanzante ◽  
Keith W. Dixon ◽  
Mary Jo Nath ◽  
Carolyn E. Whitlock ◽  
Dennis Adams-Smith
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Added Value ◽  
Historical Period ◽  
Perfect Model

AbstractStatistical downscaling (SD) is commonly used to provide information for the assessment of climate change impacts. Using as input the output from large-scale dynamical climate models and observation-based data products, SD aims to provide a finer grain of detail and to mitigate systematic biases. It is generally recognized as providing added value. However, one of the key assumptions of SD is that the relationships used to train the method during a historical period are unchanged in the future, in the face of climate change. The validity of this assumption is typically quite difficult to assess in the normal course of analysis, as observations of future climate are lacking. We approach this problem using a “perfect model” experimental design in which high-resolution dynamical climate model output is used as a surrogate for both past and future observations.We find that while SD in general adds considerable value, in certain well-defined circumstances it can produce highly erroneous results. Furthermore, the breakdown of SD in these contexts could not be foreshadowed during the typical course of evaluation based on only available historical data. We diagnose and explain the reasons for these failures in terms of physical, statistical, and methodological causes. These findings highlight the need for caution in the use of statistically downscaled products and the need for further research to consider other hitherto unknown pitfalls, perhaps utilizing more advanced perfect model designs than the one we have employed.

A High-Resolution Climate Model for the U.S. Pacific Northwest: Mesoscale Feedbacks and Local Responses to Climate Change*

2008 ◽  
Vol 21 (21) ◽  
pp. 5708-5726 ◽  
Author(s):  
Eric P. Salathé ◽  
Richard Steed ◽  
Clifford F. Mass ◽  
Patrick H. Zahn
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Snow Cover ◽  
Pacific Northwest ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Model ◽  
Mesoscale Model ◽  
Global Model ◽  
Temperature And Precipitation

Abstract Simulations of future climate scenarios produced with a high-resolution climate model show markedly different trends in temperature and precipitation over the Pacific Northwest than in the global model in which it is nested, apparently because of mesoscale processes not being resolved at coarse resolution. Present-day (1990–99) and future (2020–29, 2045–54, and 2090–99) conditions are simulated at high resolution (15-km grid spacing) using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) system and forced by ECHAM5 global simulations. Simulations use the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 emissions scenario, which assumes a rapid increase in greenhouse gas concentrations. The mesoscale simulations produce regional alterations in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land–water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. Warming is significantly amplified through snow–albedo feedback in regions where snow cover is lost. Increased onshore flow in the spring reduces the daytime warming along the coast. Precipitation increases in autumn are amplified over topography because of changes in the large-scale circulation and its interaction with the terrain. The robustness of the modeling results is established through comparisons with the observed and simulated seasonal variability and with statistical downscaling results.

scholarly journals Climate Change Impacts on Streamflow in Taiwan Catchments Based on Statistical Downscaling Data

2016 ◽  
Vol 27 (5) ◽  
pp. 741-755 ◽  
Author(s):  
Yun-Ju Chen ◽  
Jung-Lien Chu ◽  
Ching-Pin Tung ◽  
Keh Chia Yeh
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Climate Change Impacts
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