scholarly journals Reexamination of the Late Pliocene Climate over China Using a 25-km Resolution General Circulation Model

2019 ◽  
Vol 32 (3) ◽  
pp. 897-916 ◽  
Author(s):  
Qing Yan ◽  
Ting Wei ◽  
Zhongshi Zhang

Simulations of past warm climate provide an opportunity to better understand how the climate system may respond to increased greenhouse gas emissions. Using the ~25-km-resolution Community Atmosphere Model, version 4 (CAM4), we examine climate change over China in the Late Pliocene warm period (3.264–3.025 Ma) and further explore the influences of different sea surface temperature (SST) forcings and model horizontal resolutions. Initial evaluation shows that the high-resolution CAM4 performs well in capturing the climatological distribution of present-day temperature, precipitation, and low-level monsoon circulations over China. Based on the standard Pliocene Research, Interpretation and Synoptic Mapping (version 4; PRISM4) boundary conditions, CAM4 predicts an increase of annual mean temperature by ~0.5°C over China in the Late Pliocene relative to the preindustrial era, with the greatest warming in northwest China but cooling in southwest China. Enhanced annual mean precipitation is observed in the Late Pliocene over most of China except for northwest China where precipitation is decreased. The East Asian summer (winter) monsoon is intensified (weakened) in the Late Pliocene as suggested by geological evidence, which is attributed to the enhanced (reduced) land–sea thermal contrast. The East Asian monsoon domain exhibits a northwestward expansion in the Late Pliocene, especially over the Tibetan Plateau. Additionally, our results indicate that the modeled climate change is sensitive to the Late Pliocene SST forcings and model resolution. Particularly, different SST forcings [PRISM4-based vs Pliocene Model Intercomparison Project (PlioMIP)-based SSTs] affect the modeled phase change of summer monsoon and the associated precipitation change, while model resolution (~25 vs 400 km) mainly impacts precipitation change.

2021 ◽  
pp. 1-36
Author(s):  
Soo-Hyun Seok ◽  
Kyong-Hwan Seo

AbstractRecent studies have highlighted that a primary mechanism of the East Asian summer monsoon (EASM) is the fluid dynamical response to the Tibetan Plateau (TP), that is, orographically forced Rossby waves. With this mechanism in mind, this study explores how changes in the location of the TP affect the EASM precipitation. Specifically, the TP is moved in the four cardinal directions using idealized general circulation model experiments. The results show that the monsoon aspects are entirely determined by the location of the TP. Interestingly, the strongest EASM precipitation occurs when the TP is situated near its current location, a situation in which downstream southerlies are well developed from the surface to aloft. However, southerlies into the EASM region weaken as the TP moves, which in turn reduces the precipitation. Nevertheless, as long as it moves in the east–west direction, the TP is likely to force the stationary waves that induce precipitation over the mid-latitudes (not necessarily over East Asia). In contrast, moving the TP well north of its original location does not induce strong monsoon flows over the EASM region, resulting in the driest case. Meanwhile, although the southward movement of the TP triggers downstream southerlies to some extent, it does not lead to an increase in the precipitation. Overall, these results show that the location of the TP is crucial in determining the EASM precipitation, and the latter is much more sensitive to the displacement of the TP in the meridional direction than in the zonal direction.


2020 ◽  
Vol 33 (18) ◽  
pp. 7945-7965 ◽  
Author(s):  
J. C. H. Chiang ◽  
W. Kong ◽  
C. H. Wu ◽  
D. S. Battisti

AbstractThe East Asian summer monsoon is unique among summer monsoon systems in its complex seasonality, exhibiting distinct intraseasonal stages. Previous studies have alluded to the downstream influence of the westerlies flowing around the Tibetan Plateau as key to its existence. We explore this hypothesis using an atmospheric general circulation model that simulates the intraseasonal stages with fidelity. Without a Tibetan Plateau, East Asia exhibits only one primary convective stage typical of other monsoons. As the plateau is introduced, the distinct rainfall stages—spring, pre-mei-yu, mei-yu, and midsummer—emerge, and rainfall becomes more intense overall. This emergence coincides with a pronounced modulation of the westerlies around the plateau and extratropical northerlies penetrating northeastern China. The northerlies meridionally constrain the moist southerly flow originating from the tropics, leading to a band of lower-tropospheric convergence and humidity front that produces the rainband. The northward migration of the westerlies away from the northern edge of the plateau leads to a weakening of the extratropical northerlies, which, coupled with stronger monsoonal southerlies, leads to the northward migration of the rainband. When the peak westerlies migrate north of the plateau during the midsummer stage, the extratropical northerlies disappear, leaving only the monsoon low-level circulation that penetrates northeastern China; the rainband disappears, leaving isolated convective rainfall over northeastern China. In short, East Asian rainfall seasonality results from the interaction of two seasonally evolving circulations—the monsoonal southerlies that strengthen and extend northward, and the midlatitude northerlies that weaken and eventually disappear—as summer progresses.


2017 ◽  
Vol 30 (9) ◽  
pp. 3343-3365 ◽  
Author(s):  
Wenwen Kong ◽  
Leif M. Swenson ◽  
John C. H. Chiang

The Holocene East Asian summer monsoon (EASM) was previously characterized as a trend toward weaker monsoon intensity paced by orbital insolation. It is demonstrated here that this evolution is more accurately characterized as changes in the transition timing and duration of the EASM seasonal stages (spring, pre-mei-yu, mei-yu, midsummer), and tied to the north–south displacement of the westerlies relative to Tibet. To this end, time-slice simulations across the Holocene are employed using an atmospheric general circulation model. Self-organizing maps are used to objectively identify the transition timing and duration of the EASM seasonal stages. Compared to the late Holocene, an earlier onset of mei-yu and an earlier transition from mei-yu to midsummer in the early to mid-Holocene are found, resulting in a shortened mei-yu and prolonged midsummer stage. These changes are accompanied by an earlier northward positioning of the westerlies relative to Tibet. Invoking changes to seasonal transitions also provides a more satisfactory explanation for two key observations of Holocene East Asian climate: the “asynchronous Holocene optimum” and changes to dust emissions. A mechanism is proposed to explain the altered EASM seasonality in the simulated early to mid-Holocene. The insolation increase over the boreal summer reduces the pole–equator temperature gradient, leading to northward-shifted and weakened westerlies. The meridional position of the westerlies relative to the Tibetan Plateau determines the onset of mei-yu and possibly the onset of the midsummer stage. The northward shift in the westerlies triggers earlier seasonal rainfall transitions and, in particular, a shorter mei-yu and longer midsummer stage.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Rui Ito ◽  
Tosiyuki Nakaegawa ◽  
Izuru Takayabu

AbstractEnsembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble.


2009 ◽  
Vol 22 (10) ◽  
pp. 2639-2658 ◽  
Author(s):  
Grant Branstator ◽  
Frank Selten

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.


2012 ◽  
Vol 12 (6) ◽  
pp. 3131-3145 ◽  
Author(s):  
A. P. K. Tai ◽  
L. J. Mickley ◽  
D. J. Jacob ◽  
E. M. Leibensperger ◽  
L. Zhang ◽  
...  

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.


2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  

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.


2018 ◽  
Vol 8 ◽  
pp. 1433-1451 ◽  
Author(s):  
Pantazis Georgiou ◽  
Panagiota Koukouli

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.


Author(s):  
Saeed Farzin ◽  
Mahdi Valikhan Anaraki

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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