scholarly journals Reassessing Statistical Downscaling Techniques for Their Robust Application under Climate Change Conditions

2013 ◽  
Vol 26 (1) ◽  
pp. 171-188 ◽  
Author(s):  
J. M. Gutiérrez ◽  
D. San-Martín ◽  
S. Brands ◽  
R. Manzanas ◽  
S. Herrera
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Lower Troposphere ◽  
Temperature Inversion ◽  
Max Planck ◽  
Near Surface ◽  
Climate Conditions

Abstract The performance of statistical downscaling (SD) techniques is critically reassessed with respect to their robust applicability in climate change studies. To this end, in addition to standard accuracy measures and distributional similarity scores, the authors estimate the robustness of the methods under warming climate conditions working with anomalous warm historical periods. This validation framework is applied to intercompare the performances of 12 different SD methods (from the analog, weather typing, and regression families) for downscaling minimum and maximum temperatures in Spain. First, a calibration of these methods is performed in terms of both geographical domains and predictor sets; the results are highly dependent on the latter, with optimum predictor sets including near-surface temperature data (in particular 2-m temperature), which appropriately discriminate cold episodes related to temperature inversion in the lower troposphere. Although regression methods perform best in terms of correlation, analog and weather generator approaches are more appropriate for reproducing the observed distributions, especially in case of wintertime minimum temperature. However, the latter two families significantly underestimate the temperature anomalies of the warm periods considered in this work. This underestimation is found to be critical when considering the warming signal in the late twenty-first century as given by a global climate model [the ECHAM5–Max Planck Institute (MPI) model]. In this case, the different downscaling methods provide warming values with differences in the range of 1°C, in agreement with the robustness significance values. Therefore, the proposed test is a promising technique for detecting lack of robustness in statistical downscaling methods applied in climate change studies.

scholarly journals Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

2013 ◽  
Vol 6 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Conditions ◽  
Southeastern Us ◽  
The Us ◽  
Ozone Levels

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF) model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM) to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

scholarly journals Downscaling a global climate model to simulate climate change impacts on US regional and urban air quality

2013 ◽  
Vol 6 (2) ◽  
pp. 2517-2549 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Climate Conditions ◽  
Southeastern Us ◽  
The Us

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (Western US, Texas, Northeastern, and Southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (northeast). We also find that daily peak temperatures tend to increase in most major cities in the US which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

scholarly journals How Can Climate Change Affect the UNESCO Cultural Heritage Sites in Panama?

Geosciences ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 296 ◽  
Author(s):  
Chiara Ciantelli ◽  
Elisa Palazzi ◽  
Jost von Hardenberg ◽  
Carmela Vaccaro ◽  
Francesca Tittarelli ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Construction Materials ◽  
Horizontal Resolution ◽  
Damage Functions ◽  
Near Surface ◽  
Heritage Sites ◽  
The Impact

This work investigates the impact of long-term climate change on heritage sites in Latin America, focusing on two important sites in the Panamanian isthmus included in the World Heritage List: the monumental site of Panamá Viejo (16th century) and the Fortresses of Portobelo and San Lorenzo (17th to 18th centuries). First of all, in order to support the conservation and valorisation of these sites, a characterisation of the main construction materials utilized in the building masonries was performed together with an analysis of the meteoclimatic conditions in their vicinity as provided by monitoring stations recording near-surface air temperature, relative humidity, and rainfall amounts. Secondly, the same climate variables were analysed in the historical and future simulations of a state-of-the-art global climate model, EC-Earth, run at high horizontal resolution, and then used with damage functions to make projections of deterioration phenomena on the Panamanian heritage sites. In particular, we performed an evaluation of the possible surface recession, biomass accumulation, and deterioration due to salt crystallisation cycles on these sites in the future (by midcentury, 2039–2068) compared to the recent past (1979–2008), considering a future scenario of high greenhouse gas emissions.

scholarly journals Synergistic impacts of global warming and thermohaline circulation collapse on amphibians

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Julián A. Velasco ◽  
Francisco Estrada ◽  
Oscar Calderón-Bustamante ◽  
Didier Swingedouw ◽  
Carolina Ureta ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Thermohaline Circulation ◽  
Climate Model ◽  
Global Climate ◽  
Extinction Risk ◽  
Meridional Overturning Circulation ◽  
Mitigation Strategies ◽  
Amphibian Species ◽  
Climate Conditions

AbstractImpacts on ecosystems and biodiversity are a prominent area of research in climate change. However, little is known about the effects of abrupt climate change and climate catastrophes on them. The probability of occurrence of such events is largely unknown but the associated risks could be large enough to influence global climate policy. Amphibians are indicators of ecosystems’ health and particularly sensitive to novel climate conditions. Using state-of-the-art climate model simulations, we present a global assessment of the effects of unabated global warming and a collapse of the Atlantic meridional overturning circulation (AMOC) on the distribution of 2509 amphibian species across six biogeographical realms and extinction risk categories. Global warming impacts are severe and strongly enhanced by additional and substantial AMOC weakening, showing tipping point behavior for many amphibian species. Further declines in climatically suitable areas are projected across multiple clades, and biogeographical regions. Species loss in regional assemblages is extensive across regions, with Neotropical, Nearctic and Palearctic regions being most affected. Results underline the need to expand existing knowledge about the consequences of climate catastrophes on human and natural systems to properly assess the risks of unabated warming and the benefits of active mitigation strategies.

scholarly journals Cirrus clouds in a global climate model with a statistical cirrus cloud scheme

2010 ◽  
Vol 10 (12) ◽  
pp. 5449-5474 ◽  
Author(s):  
M. Wang ◽  
J. E. Penner
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Lower Troposphere ◽  
Circulation Model ◽  
Cirrus Clouds ◽  
Cloud Formation ◽  
Cirrus Cloud ◽  
Ice Crystal ◽  
Homogeneous Freezing

Abstract. A statistical cirrus cloud scheme that accounts for mesoscale temperature perturbations is implemented in a coupled aerosol and atmospheric circulation model to better represent both subgrid-scale supersaturation and cloud formation. This new scheme treats the effects of aerosol on cloud formation and ice freezing in an improved manner, and both homogeneous freezing and heterogeneous freezing are included. The scheme is able to better simulate the observed probability distribution of relative humidity compared to the scheme that was implemented in an older version of the model. Heterogeneous ice nuclei (IN) are shown to decrease the frequency of occurrence of supersaturation, and improve the comparison with observations at 192 hPa. Homogeneous freezing alone can not reproduce observed ice crystal number concentrations at low temperatures (<205 K), but the addition of heterogeneous IN improves the comparison somewhat. Increases in heterogeneous IN affect both high level cirrus clouds and low level liquid clouds. Increases in cirrus clouds lead to a more cloudy and moist lower troposphere with less precipitation, effects which we associate with the decreased convective activity. The change in the net cloud forcing is not very sensitive to the change in ice crystal concentrations, but the change in the net radiative flux at the top of the atmosphere is still large because of changes in water vapor. Changes in the magnitude of the assumed mesoscale temperature perturbations by 25% alter the ice crystal number concentrations and the net radiative fluxes by an amount that is comparable to that from a factor of 10 change in the heterogeneous IN number concentrations. Further improvements on the representation of mesoscale temperature perturbations, heterogeneous IN and the competition between homogeneous freezing and heterogeneous freezing are needed.

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

scholarly journals The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high-resolution global climate model data

2018 ◽  
Vol 18 (11) ◽  
pp. 2991-3006 ◽  
Author(s):  
Matthew D. K. Priestley ◽  
Helen F. Dacre ◽  
Len C. Shaffrey ◽  
Kevin I. Hodges ◽  
Joaquim G. Pinto
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Large Scale ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Geographic Region ◽  
Near Surface ◽  
Short Period

Abstract. Extratropical cyclones are the most damaging natural hazard to affect western Europe. Serial clustering occurs when many intense cyclones affect one specific geographic region in a short period of time which can potentially lead to very large seasonal losses. Previous studies have shown that intense cyclones may be more likely to cluster than less intense cyclones. We revisit this topic using a high-resolution climate model with the aim to determine how important clustering is for windstorm-related losses. The role of windstorm clustering is investigated using a quantifiable metric (storm severity index, SSI) that is based on near-surface meteorological variables (10 m wind speed) and is a good proxy for losses. The SSI is used to convert a wind footprint into losses for individual windstorms or seasons. 918 years of a present-day ensemble of coupled climate model simulations from the High-Resolution Global Environment Model (HiGEM) are compared to ERA-Interim reanalysis. HiGEM is able to successfully reproduce the wintertime North Atlantic/European circulation, and represent the large-scale circulation associated with the serial clustering of European windstorms. We use two measures to identify any changes in the contribution of clustering to the seasonal windstorm loss as a function of return period. Above a return period of 3 years, the accumulated seasonal loss from HiGEM is up to 20 % larger than the accumulated seasonal loss from a set of random resamples of the HiGEM data. Seasonal losses are increased by 10 %–20 % relative to randomized seasonal losses at a return period of 200 years. The contribution of the single largest event in a season to the accumulated seasonal loss does not change with return period, generally ranging between 25 % and 50 %. Given the realistic dynamical representation of cyclone clustering in HiGEM, and comparable statistics to ERA-Interim, we conclude that our estimation of clustering and its dependence on the return period will be useful for informing the development of risk models for European windstorms, particularly for longer return periods.

scholarly journals Uncovering the shortcomings of a weather typing method

2020 ◽  
Vol 24 (5) ◽  
pp. 2671-2686 ◽  
Author(s):  
Els Van Uytven ◽  
Jan De Niel ◽  
Patrick Willems
Keyword(s):  
Statistical Downscaling ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Precipitation Amount ◽  
Winter Season ◽  
Added Value ◽  
Typing Method ◽  
Weather Typing ◽  
Precipitation Changes

Abstract. In recent years many methods for statistical downscaling of the precipitation climate model outputs have been developed. Statistical downscaling is performed under general and method-specific (structural) assumptions but those are rarely evaluated simultaneously. This paper illustrates the verification and evaluation of the downscaling assumptions for a weather typing method. Using the observations and outputs of a global climate model ensemble, the skill of the method is evaluated for precipitation downscaling in central Belgium during the winter season (December to February). Shortcomings of the studied method have been uncovered and are identified as biases and a time-variant predictor–predictand relationship. The predictor–predictand relationship is found to be informative for historical observations but becomes inaccurate for the projected climate model output. The latter inaccuracy is explained by the increased importance of the thermodynamic processes in the precipitation changes. The results therefore question the applicability of the weather typing method for the case study location. Besides the shortcomings, the results also demonstrate the added value of the Clausius–Clapeyron relationship for precipitation amount scaling. The verification and evaluation of the downscaling assumptions are a tool to design a statistical downscaling ensemble tailored to end-user needs.

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