scholarly journals Regional Patterns of Tropical Indo-Pacific Climate Change: Evidence of the Walker Circulation Weakening

2012 ◽  
Vol 25 (5) ◽  
pp. 1689-1710 ◽  
Author(s):  
Hiroki Tokinaga ◽  
Shang-Ping Xie ◽  
Axel Timmermann ◽  
Shayne McGregor ◽  
Tomomichi Ogata ◽  
...  
Keyword(s):  
Climate Change ◽  
Indian Ocean ◽  
General Circulation ◽  
Surface Wind ◽  
Circulation Model ◽  
Walker Circulation ◽  
Tropical Eastern Pacific ◽  
Maritime Continent ◽  
Regional Patterns ◽  
The Walker Circulation

Regional patterns of tropical Indo-Pacific climate change are investigated over the last six decades based on a synthesis of in situ observations and ocean model simulations, with a focus on physical consistency among sea surface temperature (SST), cloud, sea level pressure (SLP), surface wind, and subsurface ocean temperature. A newly developed bias-corrected surface wind dataset displays westerly trends over the western tropical Pacific and easterly trends over the tropical Indian Ocean, indicative of a slowdown of the Walker circulation. This pattern of wind change is consistent with that of observed SLP change showing positive trends over the Maritime Continent and negative trends over the central equatorial Pacific. Suppressed moisture convergence over the Maritime Continent is largely due to surface wind changes, contributing to observed decreases in marine cloudiness and land precipitation there. Furthermore, observed ocean mixed layer temperatures indicate a reduction in zonal contrast in the tropical Indo-Pacific characterized by larger warming in the tropical eastern Pacific and western Indian Ocean than in the tropical western Pacific and eastern Indian Ocean. Similar changes are successfully simulated by an ocean general circulation model forced with the bias-corrected wind stress. Whereas results from major SST reconstructions show no significant change in zonal gradient in the tropical Indo-Pacific, both bucket-sampled SSTs and nighttime marine air temperatures (NMAT) show a weakening of the zonal gradient consistent with the subsurface temperature changes. All these findings from independent observations provide robust evidence for ocean–atmosphere coupling associated with the reduction in the Walker circulation over the last six decades.

scholarly journals Changing the Climate Sensitivity of an Atmospheric General Circulation Model through Cloud Radiative Adjustment

2012 ◽  
Vol 25 (19) ◽  
pp. 6567-6584 ◽  
Author(s):  
Andrei P. Sokolov ◽  
Erwan Monier
Keyword(s):  
Climate Change ◽  
Climate Sensitivity ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Climate Projections ◽  
Regional Patterns ◽  
Adjustment Method ◽  
Wide Range ◽  
Perturbed Physics

Abstract Conducting probabilistic climate projections with a particular climate model requires the ability to vary the model’s characteristics, such as its climate sensitivity. In this study, the authors implement and validate a method to change the climate sensitivity of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 3 (CAM3), through cloud radiative adjustment. Results show that the cloud radiative adjustment method does not lead to physically unrealistic changes in the model’s response to an external forcing, such as doubling CO2 concentrations or increasing sulfate aerosol concentrations. Furthermore, this method has some advantages compared to the traditional perturbed physics approach. In particular, the cloud radiative adjustment method can produce any value of climate sensitivity within the wide range of uncertainty based on the observed twentieth century climate change. As a consequence, this method allows Monte Carlo–type probabilistic climate forecasts to be conducted where values of uncertain parameters not only cover the whole uncertainty range, but cover it homogeneously. Unlike the perturbed physics approach that can produce several versions of a model with the same climate sensitivity but with very different regional patterns of change, the cloud radiative adjustment method can only produce one version of the model with a specific climate sensitivity. As such, a limitation of this method is that it cannot cover the full uncertainty in regional patterns of climate change.

scholarly journals Effects of Climatological Model Biases on the Projection of Tropical Climate Change

2015 ◽  
Vol 28 (24) ◽  
pp. 9909-9917 ◽  
Author(s):  
Zhen-Qiang Zhou ◽  
Shang-Ping Xie
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Walker Circulation ◽  
Tropical Climate ◽  
Equatorial Pacific ◽  
Model Biases ◽  
Tropical Climate Change

Abstract Climate models suffer from long-standing biases, including the double intertropical convergence zone (ITCZ) problem and the excessive westward extension of the equatorial Pacific cold tongue. An atmospheric general circulation model is used to investigate how model biases in the mean state affect the projection of tropical climate change. The model is forced with a pattern of sea surface temperature (SST) increase derived from a coupled simulation of global warming but uses an SST climatology derived from either observations or a coupled historical simulation. The comparison of the experiments reveals that the climatological biases have important impacts on projected changes in the tropics. Specifically, during February–April when the climatological ITCZ displaces spuriously into the Southern Hemisphere, the model overestimates (underestimates) the projected rainfall increase in the warmer climate south (north) of the equator over the eastern Pacific. Furthermore, the global warming–induced Walker circulation slowdown is biased weak in the projection using coupled model climatology, suggesting that the projection of the reduced equatorial Pacific trade winds may also be underestimated. This is related to the bias that the climatological Walker circulation is too weak in the model, which is in turn due to a too-weak mean SST gradient in the zonal direction. The results highlight the importance of improving the climatological simulation for more reliable projections of regional climate change.

“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 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.

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