scholarly journals Low-Frequency Climate Response and Fluctuation–Dissipation Theorems: Theory and Practice

2010 ◽  
Vol 67 (4) ◽  
pp. 1186-1201 ◽  
Author(s):  
Andrew J. Majda ◽  
Boris Gershgorin ◽  
Yuan Yuan
Keyword(s):  
Climate Change ◽  
Frequency Response ◽  
General Circulation ◽  
Ad Hoc ◽  
Low Frequency ◽  
Circulation Model ◽  
Theory And Practice ◽  
Climate Response ◽  
Fluctuation Dissipation ◽  
Test Models

Abstract The low-frequency response to changes in external forcing or other parameters for various components of the climate system is a central problem of contemporary climate change science. The fluctuation–dissipation theorem (FDT) is an attractive way to assess climate change by utilizing statistics of the present climate; with systematic approximations, it has been shown recently to have high skill for suitable regimes of an atmospheric general circulation model (GCM). Further applications of FDT to low-frequency climate response require improved approximations for FDT on a reduced subspace of resolved variables. Here, systematic mathematical principles are utilized to develop new FDT approximations on reduced subspaces and to assess the small yet significant departures from Gaussianity in low-frequency variables on the FDT response. Simplified test models mimicking crucial features in GCMs are utilized here to elucidate these issues and various FDT approximations in an unambiguous fashion. Also, the shortcomings of alternative ad hoc procedures for FDT in the recent literature are discussed here. In particular, it is shown that linear regression stochastic models for the FDT response always have no skill for a general nonlinear system for the variance response and can have poor or moderate skill for the mean response depending on the regime of the Lorenz 40-model and the details of the regression strategy. New nonlinear stochastic FDT approximations for a reduced set of variables are introduced here with significant skill in capturing the effect of subtle departures from Gaussianity in the low-frequency response for a reduced set of variables.

scholarly journals Future Changes in Drought Characteristics under Extreme Climate Change over South Korea

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Joo-Heon Lee ◽  
Hyun-Han Kwon ◽  
Ho-Won Jang ◽  
Tae-Woong Kim
Keyword(s):  
Climate Change ◽  
South Korea ◽  
General Circulation ◽  
Standardized Precipitation Index ◽  
Low Frequency ◽  
Circulation Model ◽  
Significance Test ◽  
Precipitation Index ◽  
Intergovernmental Panel ◽  
The Future

This study attempts to analyze several drought features in South Korea from various perspectives using a three-month standard precipitation index. In particular, this study aims to evaluate changes in spatial distribution in terms of frequency and severity of droughts in the future due to climate change, using IPCC (intergovernmental panel on climate change) GCM (general circulation model) simulations. First, the Mann-Kendall method was adopted to identify drought trends at the five major watersheds. The simulated temporal evolution of SPI (standardized precipitation index) during the winter showed significant drying trends in most parts of the watersheds, while the simulated SPI during the spring showed a somewhat different feature in the GCMs. Second, this study explored the low-frequency patterns associated with drought by comparing global wavelet power, with significance test. Future spectra decreased in the fractional variance attributed to a reduction in the interannual band from 2 to 8 years. Finally, the changes in the frequency and the severity under climate change were evaluated through the drought spell analyses. Overall features of drought conditions in the future showed a tendency to increase (about 6%) in frequency and severity of droughts during the dry season (i.e., from October to May) under climate change.

Predicting Climate Change through Response Operators in a Coupled General Circulation Model

2020 ◽  
Author(s):  
Valerio Lembo ◽  
Valerio Lucarini ◽  
Francesco Ragone
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Global Climate Models ◽  
Meridional Overturning Circulation ◽  
Climate System ◽  
Global Ocean ◽  
Climate Response ◽  
Ocean Heat Uptake

<p>Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Typically, an ensemble of simulations is performed considering a scenario of forcing, in order to analyse the response of the climate system to the specific forcing signal. Given that the the climate response spans a very large range of timescales, such a strategy often requires a dramatic amount of computational resources. In this paper we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest, going beyond the limitation of having to consider specific time patterns of forcing. We perform our study on a fully coupled GCM - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO<sub>2</sub> increase on a vast range of temporal scales. We specifically treat atmospheric  (surface temperature) and oceanic variables (strength of the Atlantic Meridional Overturning Circulation and of the Antarctic Circumpolar Current), as well as the global ocean heat uptake.</p>

“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 Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change

2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Transport Model ◽  
Circulation Model ◽  
Multiple Linear Regression Model ◽  
The United States ◽  
Chemical Transport Model ◽  
Modes Of Variability ◽  
The Us ◽  
Cyclone Frequency

Abstract. We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Atmospheric dynamics on terrestrial planets with eccentric orbits

2020 ◽  
Author(s):  
Ilai Guendelman ◽  
Yohai Kaspi
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Balance Model ◽  
Maximum Temperature ◽  
Climate Response ◽  
Eccentric Orbits ◽  
Orbital Configuration ◽  
Main Engine ◽  
Atmospheric Moisture Content ◽  
Parent Star

<p>The insolation a planet receives from its parent star is the main engine of the climate and depends on the planet's orbital configuration. Planets with non-zero obliquity and eccentricity experience seasonal insolation variations. As a result, the climate exhibits a seasonal cycle, with its strength depending on the orbital configuration and atmospheric characteristics. In this study, using an idealized general circulation model, we examine the climate response to changes in eccentricity for both zero and non-zero obliquity planets. In the zero obliquity case, a comparison between the seasonal response to changes in eccentricity and perpetual changes in the solar constant shows that the seasonal response strongly depends on the orbital period and radiative timescale. More specifically, using a simple energy balance model, we show the importance of the latitudinal structure of the radiative timescale in the climate response. We also show that the response strongly depends on the atmospheric moisture content. The combination of an eccentric orbit with non-zero obliquity is complex, as the insolation also depends on the perihelion position. Although the detailed response of the climate to variations in eccentricity, obliquity, and perihelion is involved, the circulation is constrained mainly by the thermal Rossby number and the maximum temperature latitude. Finally, we discuss the importance of different planetary parameters that affect the climate response to orbital configuration variations.</p>

scholarly journals Evaluation of Climate Change Impacts on Cotton Yield using Cropsyst and Regression Models

2018 ◽  
Vol 8 ◽  
pp. 1433-1451 ◽  
Author(s):  
Pantazis Georgiou ◽  
Panagiota Koukouli
Keyword(s):  
Climate Change ◽  
Regression Models ◽  
General Circulation ◽  
Management Practices ◽  
Potential Evapotranspiration ◽  
Circulation Model ◽  
Planting Date ◽  
Climate Variables ◽  
Cotton Yield ◽  
Cotton Production

The regional as well as the international crop production is expected to be influenced by climate change. This study describes an assessment of simulated potential cotton yield using CropSyst, a cropping systems simulation model, in Northern Greece. CropSyst was used under the General Circulation Model CGCM3.1/T63 of the climate change scenario SRES B1 for time periods of climate change 2020-2050 and 2070-2100 for two planting dates. Additionally, an appraisal of the relationship between climate variables, potential evapotranspiration and cotton yield was done based on regression models. Multiple linear regression models based on climate variables and potential evapotranspiration could be used as a simple tool for the prediction of crop yield changes in response to climate change in the future. The CropSyst simulation under SRES B1, resulted in an increase by 6% for the period 2020-2050 and a decrease by about 15% in cotton yield for 2070-2100. For the earlier planting date a higher increase and a slighter reduction was observed in cotton yield for 2020-2050 and 2070-2100, respectively. The results indicate that alteration of crop management practices, such as changing the planting date could be used as potential adaptation measures to address the impacts of climate change on cotton production.

scholarly journals Modeling and predicting suspended sediment load under climate change conditions: a new hybridization strategy

2021 ◽  
Author(s):  
Saeed Farzin ◽  
Mahdi Valikhan Anaraki
Keyword(s):  
Climate Change ◽  
Suspended Sediment ◽  
General Circulation ◽  
Sediment Load ◽  
Fuzzy Inference ◽  
Circulation Model ◽  
Support Vector ◽  
Suspended Sediment Load ◽  
Inference System ◽  
New Strategy

Abstract In the present study, for the first time, a new strategy based on a combination of the hybrid least-squares support-vector machine (LS-SVM) and flower pollination optimization algorithm (FPA), average 24 general circulation model (GCM) output, and delta change factor method has been developed to achieve the impacts of climate change on runoff and suspended sediment load (SSL) in the Lighvan Basin in the period (2020–2099). Also, the results of modeling were compared to those of LS-SVM and adaptive neuro-fuzzy inference system (ANFIS) methods. The comparison of runoff and SSL modeling results showed that the LS-SVM-FPA algorithm had the best results and the ANFIS algorithm had the worst results. After the acceptable performance of the LS-SVM-FPA algorithm was proved, the algorithm was used to predict runoff and SSL under climate change conditions based on ensemble GCM outputs for periods (2020–2034, 2035–2049, 2070–2084, and 2085–2099) under three scenarios of RCP2.6, RCP4.5, and RCP8.5. The results showed a decrease in the runoff in all periods and scenarios, except for the two near periods under the RCP2.6 scenario for runoff. The predicted runoff and SSL time series also showed that the SSL values were lower than the average observation period, except for 2036–2039 (up to an 8% increase in 2038).

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