Drought variability driven by interannual and decadal teleconnection patterns in monsoon regions of Southeast China 

2021 ◽  
Author(s):  
Kwok Pan Chun ◽  
Qing He ◽  
Bastien Dieppois ◽  
Benjamin Pohl ◽  
Ömer Yetemen ◽  
...  
Keyword(s):  
Coupled Model ◽  
Negative Phase ◽  
Cmip5 Models ◽  
Trade Wind ◽  
Drought Severity ◽  
Southeast China ◽  
Teleconnection Patterns ◽  
The Pacific ◽  
Drought Conditions ◽  
Asian Monsoons

<p>Drought conditions of Southeast China are associated with the sea surface temperature warm pool in the tropical Western Pacific, which is related to low-frequency hydroclimatic patterns and their teleconnections. Empirically, the moisture influx to the region is linked to the interannual and decadal teleconnections, including the Pacific Decadal Oscillation (PDO), the Pacific-Japan Oscillation (PJO) and the Silk Road Pattern (SRP). However, it is still unclear how those teleconnection patterns affect drought conditions in Southeast China via changes in monsoons’ dynamics or wave activities. In this study, we use ERA5 reanalysis over the 1950-2019 period to explore the impacts of the PDO, PJO and SRP on Asian monsoons’ dynamics and regional drought conditions over Southeast China, based on a self-calibrating Palmer Drought Severity Index (scPDSI). We specially use station data from the Greater Bay Area (GBA) which is a national key region for development in Southeast China which is affected by seasonal droughts in winters. Results indicate that drought conditions in Southeast China are significantly related to monsoons: the East Asia Monsoon (EAM), the Western North Pacific Monsoon (WNPM) and the Webster-Yang Monsoon (WYM), between 1950-2019. The strength of monsoons is modulated by PDO, PJO and SRP. A negative phase of SRP corresponds to a southward shift of the Asian westerly jet, strengthening winter Asian monsoons and causing drier conditions in the GBA. Similarly, a cold phase of PDO contributes to drier conditions in the GBA, by weakening Asian monsoons. For the negative phase of PJO, the trade wind of the Walker cell is weakened by the meridional pressure dipole over the West Pacific adjacent to the Southeast China coast. This pressure dipole reduces moisture influx to the continent by the weakened trade wind and leads to less precipitation over East China. Such three climate factors are also interacted through the modulations of monsoons and wave-activities. An extension of the Eliassen-Palm (EP) flux shows that the SRP relates to convective and dynamic wave-activities, which could explain changes in monsoons’ dynamics and drought conditions in Southeast China. To investigate the future drought conditions over Southeast China, bias-corrected historical and RCP8.5 scenarios are used for six of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models (i.e. ACCESS1, BCC, CNRM, IPSL, MPI, and GFDL) between 1861-2100. Among six models, IPSL and GFDL models reproduce the teleconnections well between changes in the monsoons and drought conditions over the GBA, for both historical simulations and future projections. Our results provide insights into the mechanisms of teleconnection patterns affecting drought monitoring and risk management in Southeast China. </p>

scholarly journals Precipitation in the Amazon and its relationship with moisture transport and tropical Pacific and Atlantic SST from the CMIP5 simulation

2015 ◽  
Vol 12 (1) ◽  
pp. 671-704 ◽  
Author(s):  
G. Martins ◽  
C. von Randow ◽  
G. Sampaio ◽  
A. J. Dolman
Keyword(s):  
Moisture Transport ◽  
General Circulation ◽  
Regional Analysis ◽  
Coupled Model ◽  
General Circulation Models ◽  
Moisture Convergence ◽  
Cmip5 Models ◽  
Wet Season ◽  
The Pacific ◽  
Eastern Edge

Abstract. Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in Amazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21 numerical simulations from CMIP5 during the present climate (1979–2005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of moisture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

ENSO Frequency Asymmetry and the Pacific Decadal Oscillation in Observations and 19 CMIP5 Models

2020 ◽  
Author(s):  
Fei Zheng ◽  
Renping Lin ◽  
Xiao Dong
Keyword(s):  
Monte Carlo ◽  
Observational Data ◽  
Pacific Decadal Oscillation ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Monte Carlo Test ◽  
The Pacific ◽  
Intercomparison Project ◽  
Sst Anomaly

<p>Using observational data and the pre-industrial simulations of 19 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the El Niño (EN) and La Niña (LN) events in positive and negative Pacific Decadal Oscillation (PDO) phases are examined. In the observational data, with EN (LN) events the positive (negative) SST anomaly in the equatorial eastern Pacific is much stronger in positive (negative) PDO phases than in negative (positive) phases. Meanwhile, the models cannot reasonably reproduce this difference. Besides, the modulation of ENSO frequency asymmetry by the PDO is explored. Results show that, in the observational data, EN is 300% more (58% less) frequent than LN in positive (negative) PDO phases, which is significant at the 99% confidence level using the Monte Carlo test. Most of the CMIP5 models exhibit results that are consistent with the observational data.</p>

Diversity of the Pacific–Japan Pattern among CMIP5 Models: Role of SST Anomalies and Atmospheric Mean Flow

2018 ◽  
Vol 31 (17) ◽  
pp. 6857-6877 ◽  
Author(s):  
Hainan Gong ◽  
Lin Wang ◽  
Wen Chen ◽  
Renguang Wu ◽  
Gang Huang ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Mean Flow ◽  
Central Pacific ◽  
The Pacific ◽  
Sea Surface Temperature Anomalies ◽  
Precipitation Anomalies

This study investigates the reproducibility of the spatial structure and amplitude of the observed Pacific–Japan (PJ) pattern in the phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. In particular, the role of sea surface temperature anomalies (SSTAs) and atmospheric mean flow in the diverse reproducibility of the PJ pattern among models is investigated. Based on the pattern correlation between simulated and observed PJ patterns, models are categorized into high and low correlation groups, referred to as HCG and LCG, respectively. The observed cold SSTAs in the western North Pacific (WNP) and equatorial central Pacific, organized convection and precipitation anomalies, and Rossby wave response are reproduced well in HCG models, whereas these features are not present in LCG models. The summer SSTAs are closely tied to the preceding El Niño–Southern Oscillation and its temporal evolution in the tropical Indo-Pacific Ocean in both observations and models, but the SSTAs in the Indian Ocean are weak in both HCG and LCG, implying a weak Indian Ocean capacitor effect. As a result, the reproducibility of the amplitude of the WNP center of the PJ pattern is mainly modulated by the SSTAs and local air–sea feedback over the WNP in the models. On the other hand, a model with stronger climatological southerly along the coast of East Asia tends to produce more realistic amplitude of the midlatitude center of the PJ pattern with clearer poleward wave-activity fluxes due to more efficient local barotropic energy conversion from the mean flow.

scholarly journals CMIP5 Projected Change in Northern Hemisphere Winter Cyclones with Associated Extreme Winds

2018 ◽  
Vol 31 (16) ◽  
pp. 6527-6542 ◽  
Author(s):  
Edmund Kar-Man Chang
Keyword(s):  
Northern Hemisphere ◽  
Surface Wind ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Near Surface ◽  
The Pacific ◽  
Projected Change ◽  
Good Proxy ◽  
Hemisphere Winter ◽  
Extreme Winds

Abstract In this study, 19 simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been analyzed to examine how winter cyclones producing extreme near-surface winds are projected to change. Extreme wind thresholds correspond to a top 5 or top 1 cyclone per winter month in the entire Northern Hemisphere (NH). The results show that CMIP5 models project a significant decrease in the number of such cyclones, with a 19-model mean decrease of about 17% for the entire NH toward the end of the twenty-first century, under the high-emission RCP8.5 scenario. The projected decrease is larger in the Atlantic (about 21%). Over the Pacific, apart from an overall decrease (about 13%), there is a northeastward shift in the extreme cyclone activity. Less decrease is found in the frequency of cyclones producing extreme winds at 850 hPa (about 5% hemisphere-wide), with models mainly projecting a northeastward shift in the Pacific. These results suggest that 850-hPa wind changes may not be a good proxy for near-surface wind changes. These results contrast with those for the Southern Hemisphere, in which the frequency of cyclones with extreme winds are projected to significantly increase in all four seasons.

scholarly journals Patterns of Precipitation Change and Climatological Uncertainty among CMIP5 Models, with a Focus on the Midlatitude Pacific Storm Track*

2015 ◽  
Vol 28 (19) ◽  
pp. 7857-7872 ◽  
Author(s):  
Baird Langenbrunner ◽  
J. David Neelin ◽  
Benjamin R. Lintner ◽  
Bruce T. Anderson
Keyword(s):  
Radiative Forcing ◽  
Storm Track ◽  
Coupled Model ◽  
Internal Variability ◽  
Empirical Orthogonal Functions ◽  
Cmip5 Models ◽  
Orthogonal Functions ◽  
Maximum Covariance Analysis ◽  
The Pacific ◽  
The Tropics

Abstract Projections of modeled precipitation (P) change in global warming scenarios demonstrate marked intermodel disagreement at regional scales. Empirical orthogonal functions (EOFs) and maximum covariance analysis (MCA) are used to diagnose spatial patterns of disagreement in the simulated climatology and end-of-century P changes in phase 5 of the Coupled Model Intercomparison Project (CMIP5) archive. The term principal uncertainty pattern (PUP) is used for any robust mode calculated when applying these techniques to a multimodel ensemble. For selected domains in the tropics, leading PUPs highlight features at the margins of convection zones and in the Pacific cold tongue. The midlatitude Pacific storm track is emphasized given its relevance to wintertime P projections over western North America. The first storm-track PUP identifies a sensitive region of disagreement in P increases over the eastern midlatitude Pacific where the storm track terminates, related to uncertainty in an eastward extension of the climatological jet. The second PUP portrays uncertainty in a zonally asymmetric meridional shift of storm-track P, related to uncertainty in the extent of a poleward jet shift in the western Pacific. Both modes appear to arise primarily from intermodel differences in the response to radiative forcing, distinct from sampling of internal variability. The leading storm-track PUPs for P and zonal wind change exhibit similarities to the leading uncertainty patterns for the historical climatology, indicating important and parallel sensitivities in the eastern Pacific storm-track terminus region. However, expansion coefficients for climatological uncertainties tend to be weakly correlated with those for end-of-century change.

scholarly journals Assessment of CMIP5 Models Based on the Interdecadal Relationship between the PDO and Winter Temperature in China

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 597 ◽  
Author(s):  
Xu ◽  
Li ◽  
Shen ◽  
Hu
Keyword(s):  
Correlation Coefficient ◽  
Spatial Correlation ◽  
Coupled Model ◽  
Research Unit ◽  
Winter Temperature ◽  
Cmip5 Models ◽  
Climatic Research Unit ◽  
The Pacific ◽  
Winter Temperatures ◽  
The Impact

In this study, the impact of the Pacific Decadal Oscillation (PDO) on the China winter temperature (CWT) was assessed on an interdecadal timescale, and the capacities of the 35 models of the fifth Coupled Model Intercomparison Project (CMIP5) were assessed by simulating the PDO-CWT teleconnection. The Met Office Hadley Centre’s sea ice and sea surface temperature (HadISST) were used as the observational data, and Climatic Research Unit (CRU) datasets provided long-term temperature data for the 1901–2005 period. By calculating the spatial correlation coefficient between the PDO index and winter temperature in China, thirteen CMIP5 models close to the HadISST datasets were selected for this study. These models were averaged as the good multi-model ensemble (GOODMME), and the PDO-CWT spatial correlation between the GOODMME and the observations was 0.80. Overall, the correlation coefficient between the PDO index and atmospheric circulation suggests that the GOODMME produces the same excellent results as do the observations. The results also verify the GOODMME’s superiority in simulating the impact of the PDO on winter temperatures in China. The possible mechanisms underlying the impact of the different phases of the PDO on the CWT are also described.

scholarly journals Madden–Julian Oscillation Pacific Teleconnections: The Impact of the Basic State and MJO Representation in General Circulation Models

2017 ◽  
Vol 30 (12) ◽  
pp. 4567-4587 ◽  
Author(s):  
Stephanie A. Henderson ◽  
Eric D. Maloney ◽  
Seok-Woo Son
Keyword(s):  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Teleconnection Pattern ◽  
Madden Julian Oscillation ◽  
Horizontal Structure ◽  
Teleconnection Patterns ◽  
Subtropical Jet ◽  
The Pacific ◽  
The Impact

Teleconnection patterns associated with the Madden–Julian oscillation (MJO) significantly alter extratropical circulations, impacting weather and climate phenomena such as blocking, monsoons, the North Atlantic Oscillation, and the Pacific–North American pattern. However, the MJO has been extremely difficult to simulate in many general circulation models (GCMs), and many GCMs contain large biases in the background flow, presenting challenges to the simulation of MJO teleconnection patterns and associated extratropical impacts. In this study, the database from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is used to assess the impact of model MJO and basic state quality on MJO teleconnection pattern quality, and a simple dry linear baroclinic model is employed to understand the results. Even in GCMs assessed to have good MJOs, large biases in the MJO teleconnection patterns are produced as a result of errors in the zonal extent of the Pacific subtropical jet. The horizontal structure of Indo-Pacific MJO heating in good MJO models is found to have modest impacts on the teleconnection pattern skill, in agreement with previous studies that have demonstrated little sensitivity to the location of tropical heating near the subtropical jet. However, MJO heating east of the date line can alter the teleconnection pathways over North America. Results show that GCMs with poor basic states can have equally low skill in reproducing the MJO teleconnection patterns as GCMs with poor MJO quality, suggesting that both the basic state and the MJO must be well represented in order to reproduce the correct teleconnection patterns.

scholarly journals Origins of Biases in CMIP5 Models Simulating Northwest Pacific Summertime Atmospheric Circulation Anomalies during the Decaying Phase of ENSO

2018 ◽  
Vol 31 (14) ◽  
pp. 5707-5729 ◽  
Author(s):  
Weichen Tao ◽  
Gang Huang ◽  
Renguang Wu ◽  
Kaiming Hu ◽  
Pengfei Wang ◽  
...  
Keyword(s):  
Atmospheric Circulation ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Tropical Indian Ocean ◽  
Shortwave Radiation ◽  
Cmip5 Models ◽  
Northwest Pacific ◽  
Circulation Anomalies ◽  
Atmospheric Circulation Anomalies ◽  
Sst Anomalies

Abstract The present study documents the biases of summertime northwest Pacific (NWP) atmospheric circulation anomalies during the decaying phase of ENSO and investigates their plausible reasons in 32 models from phase 5 of the Coupled Model Intercomparison Project. Based on an intermodel empirical orthogonal function (EOF) analysis of El Niño–Southern Oscillation (ENSO)-related 850-hPa wind anomalies, the dominant modes of biases are extracted. The first EOF mode, explaining 21.3% of total intermodel variance, is characterized by a cyclone over the NWP, indicating a weaker NWP anticyclone. The cyclone appears to be a Rossby wave response to unrealistic equatorial western Pacific (WP) sea surface temperature (SST) anomalies related to excessive equatorial Pacific cold tongue in the models. On one hand, the cold SST biases increase the mean zonal SST gradient, which further intensifies warm zonal advection, favoring the development and persistence of equatorial WP SST anomalies. On the other hand, they reduce the anomalous convection caused by ENSO-related warming, and the resultant increase in downward shortwave radiation contributes to the SST anomalies there. The second EOF mode, explaining 18.6% of total intermodel variance, features an anticyclone over the NWP with location shifted northward. The related SST anomalies in the Indo-Pacific sector show a tripole structure, with warming in the tropical Indian Ocean and equatorial central and eastern Pacific and cooling in the NWP. The Indo-Pacific SST anomalies are highly controlled by ENSO amplitude, which is determined by the intensity of subtropical cells via the adjustment of meridional and vertical advection in the models.

scholarly journals Climate Drift in the CMIP5 Models*

2013 ◽  
Vol 26 (21) ◽  
pp. 8597-8615 ◽  
Author(s):  
Alexander Sen Gupta ◽  
Nicolas C. Jourdain ◽  
Jaclyn N. Brown ◽  
Didier Monselesan
Keyword(s):  
Climate Models ◽  
Coupled Model ◽  
Deep Ocean ◽  
Internal Variability ◽  
Correction Method ◽  
Physical Models ◽  
Cmip5 Models ◽  
Steric Sea Level ◽  
Biogeochemical Models ◽  
The Difference

Abstract Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.

scholarly journals Evaluation of a High-Resolution SPI for Monitoring Local Drought Severity

2016 ◽  
Vol 55 (10) ◽  
pp. 2247-2262 ◽  
Author(s):  
Rebecca V. Cumbie-Ward ◽  
Ryan P. Boyles
Keyword(s):  
United States ◽  
High Resolution ◽  
Standardized Precipitation Index ◽  
Stage Iv ◽  
Drought Severity ◽  
Cluster Solution ◽  
Historical Distribution ◽  
Drought Conditions ◽  
Hydrologic Prediction ◽  
Strong Agreement

AbstractA standardized precipitation index (SPI) that uses high-resolution, daily estimates of precipitation from the National Weather Service over the contiguous United States has been developed and is referred to as HRD SPI. There are two different historical distributions computed in the HRD SPI dataset, each with a different combination of normals period (1971–2000 or 1981–2010) and clustering solution of gauge stations. For each historical distribution, the SPI is computed using the NCEP Stage IV and Advanced Hydrologic Prediction Service (AHPS) gridded precipitation datasets for a total of four different HRD SPI products. HRD SPIs are found to correlate strongly with independently produced SPIs over the 10-yr period from 2005 to 2015. The drought-monitoring utility of the HRD SPIs is assessed with case studies of drought in the central and southern United States during 2012 and over the Carolinas during 2007–08. A monthly comparison between HRD SPIs and independently produced SPIs reveals generally strong agreement during both events but weak agreement in areas where radar coverage is poor. For both study regions, HRD SPI is compared with the U.S. Drought Monitor (USDM) to assess the best combination of precipitation input, normals period, and station clustering solution. SPI generated with AHPS precipitation and the 1981–2010 PRISM normals and associated cluster solution is found to best capture the spatial extent and severity of drought conditions indicated by the USDM. This SPI is also able to resolve local variations in drought conditions that are not shown by either the USDM or comparison SPI datasets.

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