scholarly journals Estimating the Local Time of Emergence of Climatic Variables Using an Unbiased Mapping of GCMs: An Application in Semiarid and Mediterranean Chile

2019 ◽  
Vol 20 (8) ◽  
pp. 1635-1647 ◽  
Author(s):  
Cristián Chadwick ◽  
Jorge Gironás ◽  
Sebastián Vicuña ◽  
Francisco Meza
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Statistical Power ◽  
Signal To Noise Ratio ◽  
Circulation Model ◽  
Climatic Conditions ◽  
Climate Change Signal ◽  
Signal To Noise ◽  
Adaptation Measures ◽  
Precipitation And Temperature

Abstract The time at which climate change signal can be clearly distinguished from noise is known as time of emergence (ToE) and is typically detected by a general circulation model (GCM) signal-to-noise ratio exceeding a certain threshold. ToE is commonly estimated at large scales from GCMs, although management decisions and adaptation strategies are implemented locally. This paper proposes a methodology to estimate ToE for both precipitation and temperature at local scales (i.e., river basin). The methodology considers local climatic conditions and unbiased GCM projections to estimate ToE by using the statistical power to find when the climate significantly differs from the historical one. The method suggests that ToE for temperature already occurred in three Chilean basins (Limarí, Maipo, and Maule). However, in terms of precipitation, an earlier ToE is clearly identified for the Maule basin, indicating that risk assessment and adaptation measures should be implemented first in this basin.

scholarly journals Calibrating Climate Change Time-Slice Projections with Estimates of Seasonal Forecast Reliability

2016 ◽  
Vol 29 (10) ◽  
pp. 3831-3840 ◽  
Author(s):  
M. Matsueda ◽  
A. Weisheimer ◽  
T. N. Palmer
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Circulation Model ◽  
Seasonal Forecast ◽  
Time Slice ◽  
Climate Change Signal ◽  
Seasonal Forecasts ◽  
Low Resolution ◽  
Climate Change Projections ◽  
Resolution Model

Abstract In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users.

scholarly journals Recent Trends and Long-Range Forecasts of Water Resources of Northeast Iraq and Climate Change Adaptation Measures

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1562 ◽  
Author(s):  
Nahlah Abbas ◽  
Saleh Wasimi ◽  
Nadhir Al-Ansari ◽  
Sultana Nasrin Baby
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
General Circulation ◽  
Swat Model ◽  
Research Work ◽  
Circulation Model ◽  
Green Water ◽  
Change Analysis ◽  
Adaptation Measures ◽  
The Relationship

Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than generally reported elsewhere. The relationship between climate change and its effect on water resources of a region has been sparsely addressed in published literature. To fill that gap this research work first investigates if there has been a significant change in climate in the region, which has been found to be true. In the next stage, the research projects future climatic scenarios of the region based on six oft-used General Circulation Model (GCM) ensembles, namely CCSM4, CSIRO-Mk3.6.0, GFDL-ESM2M, MEROC5, HadGEM2-ES, and IPSL-CM5A-LR. The relationship between climate change and its impact on water resources is explored through the application of the popular, widely used SWAT model. The model depicts the availability of water resources, classified separately as blue and green waters, for near and distant futures for the region. Some of the findings are foreboding and warrants urgent attention of planners and decision makers. According to model outputs, the region may experience precipitation reduction of about 12.6% and 21% in near (2049–2069) and distant (2080–2099) futures, respectively under RCP8.5. Those figures under RCP4.5 are 15% and 23.4%, respectively and under RCP2.6 are 12.2% and 18.4%, respectively. As a consequence, the blue water may experience decreases of about 22.6% and 40% under RCP8.5, 25.8% and 46% under RCP4.5, and 34.4% and 31% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. Green water, by contrast, may reduce by about 10.6% and 19.6% under RCP8.5, by about 14.8% and 19.4% under RCP4.5, and by about 15.8% and 14.2% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. The research further investigates how the population are adapting to already changed climates and how they are expected to cope in the future when the shift in climate is expected to be much greater.

scholarly journals Performance of Pattern-Scaled Climate Projections under High-End Warming. Part I: Surface Air Temperature over Land

2018 ◽  
Vol 31 (14) ◽  
pp. 5667-5680 ◽  
Author(s):  
Timothy J. Osborn ◽  
Craig J. Wallace ◽  
Jason A. Lowe ◽  
Dan Bernie
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Actual Performance ◽  
Mean Square Errors

Pattern scaling is widely used to create climate change projections to investigate future impacts. We consider the performance of pattern scaling for emulating the HadGEM2-ES general circulation model (GCM) paying particular attention to “high end” warming scenarios and to different choices of GCM simulations used to diagnose the climate change patterns. We demonstrate that evaluating pattern-scaling projections by comparing them with GCM simulations containing unforced variability gives a significantly less favorable view of the actual performance of pattern scaling. Using a four-member initial-condition ensemble of HadGEM2-ES simulations, we infer that the root-mean-square errors of pattern-scaled monthly temperature changes over land are less than 0.25°C for global warming up to approximately 3.5°C. Some regional errors are larger than this and, for this GCM, there is a tendency for pattern scaling to underestimate warming over land. For warming above 3.5°C, the pattern-scaled projection errors grow but remain small relative to the climate change signal. We investigate whether patterns diagnosed by pooling GCM experiments from several scenarios are suitable for emulating the GCM under a high-end warming scenario. For global warming up to 3.5°C, pattern scaling using this pooled pattern closely emulates GCM simulations. For warming beyond 3.5°C, pattern-scaling performance is notably improved by using patterns diagnosed only from the high-forcing representative concentration pathway 8.5 (RCP8.5) scenario. Assessments of climate change impacts under high-end warming using pattern-scaling projections could be improved by using change patterns diagnosed from pooled scenarios for projections up to 3.5°C above preindustrial levels and patterns diagnosed from only strong forcing simulations for projecting beyond that. Similar findings are obtained for five other GCMs.

scholarly journals STOCHASTIC TYPHOON MODEL AND ITS APPLICATION TO FUTURE TYPHOON PROJECTION

2011 ◽  
Vol 1 (32) ◽  
pp. 16 ◽  
Author(s):  
Tomohiro Yasuda ◽  
Hajime Mase ◽  
Shoji Kunitomi ◽  
Nobuhito Mori ◽  
Yuta Hayashi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Circulation Model ◽  
Stochastic Modelling ◽  
Climate Scenario ◽  
Future Climate ◽  
Statistical Characteristics ◽  
Climate Change Signal ◽  
Change Scenario ◽  
Climate Conditions

This study presents a stochastic typhoon model (STM) for estimating the characteristics of typhoons in the present and future climate conditions. Differences of statistical characteristics between present and future typhoons were estimated from projections by an Atmospheric General Circulation Model (AGCM) under a climate change scenario and are taken into account in the stochastic modelling of future typhoons as a climate change signal. From the STM results which utilize the Monte Carlo simulation, it was found that the frequency of typhoon landfall in Osaka bay area, Japan, will decrease, although the mean value of atmospheric central pressure of typhoon will not change significantly. The arrival probability of stronger typhoons will increase in the future climate scenario.

Testing the simulation skill of hydrological models under transient climate conditions for European case studies

2020 ◽  
Author(s):  
Ernesto Pasten-Zapata ◽  
Paul Royer-Gaspard ◽  
Rafael Pimentel ◽  
Torben O. Sonnenborg ◽  
Anthony Lemoine ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Hydrological Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Climatic Conditions ◽  
Climate Change Scenarios ◽  
Hydrological Models ◽  
Climate Conditions

<p>Commonly, the analysis of climate change impacts on hydrology involves a series of steps that begin with a General Circulation Model followed by the application of a downscaling or bias correction method and then coupling the climate outputs to a hydrological model. Nevertheless, frequently the hydrological models employed in these analyses are not tested to assess their skill to simulate the hydrology of a catchment under changing climate regimes. We evaluate such skill by applying a Differential Split Sampling Test (DSST) using the available observations. The models are calibrated during the three most extreme dry (or wet) years and evaluated on the three most wet (or dry) years. The DSST is applied on three catchments located across Europe: Denmark, France and Spain. This spatial distribution allows us to evaluate the method on diverse climatic and hydrological regimes. Furthermore, the DSST is applied to three different models in each of the catchments and case-specific metrics are evaluated to determine the practical usefulness of the models. Based on the DSST results, we assign a weight to the hydrological models and drive them with six Euro-CORDEX Regional Climate Models to assess climate change scenarios for the case-specific metrics. This methodology allows us to increase the confidence of our projections considering the hydrological model uncertainty for transient climatic conditions.</p>

Climate change and winter damage to fruit trees in eastern Canada

2004 ◽  
Vol 84 (4) ◽  
pp. 1113-1125 ◽  
Author(s):  
P. Rochette ◽  
G. Bélanger ◽  
Y. Castonguay ◽  
A. Bootsma ◽  
D. Mongrain
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Circulation Model ◽  
Fruit Trees ◽  
Fruit Production ◽  
Climatic Conditions ◽  
Eastern Canada ◽  
Spring Frost ◽  
Annual Minimum Temperature ◽  
Agricultural Regions

Climatic conditions during the cold season represent a serious constraint to fruit production in eastern Canada. Meteorological models predict that temperatures of winter months will increase by 2 to 6°C by 2050. The possible impact of climate change on fruit trees in eastern Canada was assessed using agroclimatic indices expressing the risks associated with known causes of damage during fall, winter, and spring. Indices were calculated for 15 agricultural regions in eastern Canada for recent (1961–1990) and future periods (2010–2039 and 2040–2069) using temperature and precipitation data predicted by the Canadian Global General Circulation Model (CGCMI). Averaged across all agricultural regions, the first fall frost in 2040–2069 would be delayed by 16 d while the last spring frost (≤-2°C) would be advanced by 15 d. By 2040 to 2069, the risks of damage to fruit trees by early winter frosts in eastern Canada are likely to decrease because the shorter photoperiod at the time of the first fall frost would result in a longer hardening period. Milder winter temperatures will also reduce the cold stress as the accumulation of cold degree-days (<-15°C) would be reduced and the annual minimum temperature would be increased in all regions of eastern Canada. More frequent winter thaw events, however, would result in a loss of hardiness and in a thinner snow cover that would increase the plant vulnerability to subsequent extreme sub-freezing temperatures. The risk of damage to flower buds by a late frost would increase in southern Ontario, remain almost unchanged in the Maritimes and Ottawa Valley-southern Québec regions, and decrease in the Continental North. The projected climate change should allow for the introduction of new varieties and species where fruit trees are currently grown and for an extension further north of the commercial production in eastern Canada. Key words: Overwintering, fruit production, climatic indices, winter injury, spring frost

Ensemble climate simulations using a fully coupled ocean–troposphere–stratosphere general circulation model

2007 ◽  
Vol 365 (1857) ◽  
pp. 2089-2101 ◽  
Author(s):  
H Huebener ◽  
U Cubasch ◽  
U Langematz ◽  
T Spangehl ◽  
F Niehörster ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Storm Track ◽  
Circulation Model ◽  
Climate Change Signal ◽  
Intergovernmental Panel ◽  
Wave Forcing ◽  
Transient Simulations

Long-term transient simulations are carried out in an initial condition ensemble mode using a global coupled climate model which includes comprehensive ocean and stratosphere components. This model, which is run for the years 1860–2100, allows the investigation of the troposphere–stratosphere interactions and the importance of representing the middle atmosphere in climate-change simulations. The model simulates the present-day climate (1961–2000) realistically in the troposphere, stratosphere and ocean. The enhanced stratospheric resolution leads to the simulation of sudden stratospheric warmings; however, their frequency is underestimated by a factor of 2 with respect to observations. In projections of the future climate using the Intergovernmental Panel on Climate Change special report on emissions scenarios A2, an increased tropospheric wave forcing counteracts the radiative cooling in the middle atmosphere caused by the enhanced greenhouse gas concentration. This leads to a more dynamically active, warmer stratosphere compared with present-day simulations, and to the doubling of the number of stratospheric warmings. The associated changes in the mean zonal wind patterns lead to a southward displacement of the Northern Hemisphere storm track in the climate-change signal.

scholarly journals Mediterranean Olive Orchards under Climate Change: A Review of Future Impacts and Adaptation Strategies

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 56
Author(s):  
Helder Fraga ◽  
Marco Moriondo ◽  
Luisa Leolini ◽  
João A. Santos
Keyword(s):  
Climate Change ◽  
Mediterranean Basin ◽  
Olive Tree ◽  
Climatic Conditions ◽  
Adaptation Strategies ◽  
Adaptation Measures ◽  
The Mediterranean ◽  
Projected Changes ◽  
The Mediterranean Basin ◽  
Impacts Of Climate Change

The olive tree (Olea europaea L.) is an ancient traditional crop in the Mediterranean Basin. In the Mediterranean region, traditional olive orchards are distinguishable by their prevailing climatic conditions. Olive trees are indeed considered one of the most suitable and best-adapted species to the Mediterranean-type climate. However, new challenges are predicted to arise from climate change, threatening this traditional crop. The Mediterranean Basin is considered a climate change “hotspot,” as future projections hint at considerable warming and drying trends. Changes in olive tree suitability have already been reported over the last few decades. In this context, climate change may become particularly challenging for olive growers. The growing evidence for significant climate change in the upcoming decades urges adaptation measures to be taken. To effectively cope with the projected changes, both short and long-term adaptation strategies must be timely planned by the sector stakeholders and decision-makers to adapt for a warmer and dryer future. The current manuscript is devoted to illustrating the main impacts of climate change on olive tree cultivation in the Mediterranean Basin, by reviewing the most recent studies on this subject. Additionally, an analysis of possible adaptation strategies against the potentially negative impacts of climate change was also performed.

“Modes of Variability” and Climate Change

2009 ◽  
Vol 22 (10) ◽  
pp. 2639-2658 ◽  
Author(s):  
Grant Branstator ◽  
Frank Selten
Keyword(s):  
Climate Change ◽  
Stochastic Model ◽  
General Circulation ◽  
Climate Changes ◽  
Circulation Model ◽  
Meridional Wind ◽  
Model Atmosphere ◽  
Linear Pattern ◽  
Modes Of Variability ◽  
Mean State

Abstract A 62-member ensemble of coupled general circulation model (GCM) simulations of the years 1940–2080, including the effects of projected greenhouse gas increases, is examined. The focus is on the interplay between the trend in the Northern Hemisphere December–February (DJF) mean state and the intrinsic modes of variability of the model atmosphere as given by the upper-tropospheric meridional wind. The structure of the leading modes and the trend are similar. Two commonly proposed explanations for this similarity are considered. Several results suggest that this similarity in most respects is consistent with an explanation involving patterns that result from the model dynamics being well approximated by a linear system. Specifically, the leading intrinsic modes are similar to the leading modes of a stochastic model linearized about the mean state of the GCM atmosphere, trends in GCM tropical precipitation appear to excite the leading linear pattern, and the probability density functions (PDFs) of prominent circulation patterns are quasi-Gaussian. There are, on the other hand, some subtle indications that an explanation for the similarity involving preferred states (which necessarily result from nonlinear influences) has some relevance. For example, though unimodal, PDFs of prominent patterns have departures from Gaussianity that are suggestive of a mixture of two Gaussian components. And there is some evidence of a shift in probability between the two components as the climate changes. Interestingly, contrary to the most prominent theory of the influence of nonlinearly produced preferred states on climate change, the centroids of the components also change as the climate changes. This modification of the system’s preferred states corresponds to a change in the structure of its dominant patterns. The change in pattern structure is reproduced by the linear stochastic model when its basic state is modified to correspond to the trend in the general circulation model’s mean atmospheric state. Thus, there is a two-way interaction between the trend and the modes of variability.

scholarly journals Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction

2013 ◽  
Vol 17 (6) ◽  
pp. 2147-2159 ◽  
Author(s):  
E. P. Maurer ◽  
T. Das ◽  
D. R. Cayan
Keyword(s):  
Bias Correction ◽  
General Circulation ◽  
Daily Precipitation ◽  
Extreme Values ◽  
Circulation Model ◽  
The United States ◽  
Historical Period ◽  
Late 20Th Century ◽  
Precipitation And Temperature ◽  
Gcm Biases

Abstract. When correcting for biases in general circulation model (GCM) output, for example when statistically downscaling for regional and local impacts studies, a common assumption is that the GCM biases can be characterized by comparing model simulations and observations for a historical period. We demonstrate some complications in this assumption, with GCM biases varying between mean and extreme values and for different sets of historical years. Daily precipitation and maximum and minimum temperature from late 20th century simulations by four GCMs over the United States were compared to gridded observations. Using random years from the historical record we select a "base" set and a 10 yr independent "projected" set. We compare differences in biases between these sets at median and extreme percentiles. On average a base set with as few as 4 randomly-selected years is often adequate to characterize the biases in daily GCM precipitation and temperature, at both median and extreme values; 12 yr provided higher confidence that bias correction would be successful. This suggests that some of the GCM bias is time invariant. When characterizing bias with a set of consecutive years, the set must be long enough to accommodate regional low frequency variability, since the bias also exhibits this variability. Newer climate models included in the Intergovernmental Panel on Climate Change fifth assessment will allow extending this study for a longer observational period and to finer scales.

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