scholarly journals Winter Weather Regimes in Southeastern China and its Intraseasonal Variations

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 271 ◽  
Author(s):  
Yongdi Wang ◽  
Shuanggen Jin ◽  
Xinyu Sun ◽  
Fei Wang
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Model Simulation ◽  
Cold Wave ◽  
Wind Fields ◽  
Intraseasonal Variation ◽  
Southeastern China ◽  
Large Scale Circulation ◽  
Optimal Value

Extreme precipitation has often occurred in Southeastern China, while the possible mechanism is not clear. In order to bridge the scale gap between large-scale circulation and extreme precipitation, in this paper, the k-means clustering technique—a common method of weather-type (WT) analysis—was applied to regional 850-hPa wind fields. The reasonable determination of k values can make the later WT analyses more reliable. Thus, the Davies–Bouldin (BD) criterion index is used in the clustering process, and the optimal value of the k was determined. Then, we obtain and analyze the frequency, persistence, and progression of WTs. The rule of transitions from one WT to another may help explain some of the physical processes in winter. We found a special evolutionary chain (WT3→WT1→WT2→WT5→WT3) that can be used to explain the cold wave weather process in winter. Different WTs in the evolutionary chain correspond well to different stages of the cold wave weather process (gestation (WT3), outbreak (WT1), eastward withdrawal (WT2), and extinction (WT5)). In addition, we found that there are obvious differences in precipitation between December and February. After reassembling five kinds of WTs, two modes are formed: dry WTs and wet WTs. Our research shows that the intraseasonal variation of precipitation can be attributed to the fluctuation between the wet and dry WTs, and the different phases of teleconnection can correspond well with it. For example, the relative frequencies of wet WTs are higher in February. These WTs correspond to the positive phase of the WP and ENSO, the negative phase of the EA and EU, and the strong MJO state of the second, third, and eighth phase. Our work has well established the relationship between synoptic scale and large-scale circulation, which provides a reference for climate model simulation and future climate prediction.

scholarly journals Improved Physical Processes in a Regional Climate Model and Their Impact on the Simulated Summer Monsoon Circulations over East Asia

2008 ◽  
Vol 21 (5) ◽  
pp. 963-979 ◽  
Author(s):  
Yoo-Bin Yhang ◽  
Song-You Hong
Keyword(s):  
Boundary Layer ◽  
Summer Monsoon ◽  
Large Scale ◽  
Climate Model ◽  
Asian Summer Monsoon ◽  
Regional Climate ◽  
Analysis Data ◽  
Cumulus Parameterization ◽  
Intraseasonal Variation ◽  
Thermal Roughness Length

Abstract This paper documents the sensitivity of the modeled evolution of the East Asian summer monsoon (EASM) to physical parameterization using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). To this end, perfect boundary condition experiments driven by analysis data are designed for August 2003 to investigate the individual role of the surface processes, boundary layer, and convection parameterization on the simulated monsoon. Also, 10-yr June–August (JJA) simulations from 1996 to 2005 are performed to evaluate the overall impacts of these revisions on the simulated EASM climatology. The one-month simulation for August 2003 reveals that the experiment with a realistic distribution of land use conditions and vegetation and smaller thermal roughness length simulates higher temperature and geopotential height. On the other hand, in the experiment with an improved boundary layer scheme, the rainfall amount is slightly decreased due to reduced vertical mixing. The simulation with revised subgrid-scale processes in the cumulus parameterization scheme reproduces a rainband over the subtropics, which is weakly simulated by the default package. The overall large-scale distribution from the experiment, which includes all three revised physics processes, shows the same direction as that of the revised convection run in the middle and upper troposphere, but is improved further when other newly enhanced processes are combined. These improvements are also achieved in a 10-yr summer simulation. It is distinct that the revised physics package improves the large-scale patterns by strengthening the intensity of the North Pacific high and reducing the intensity of the lower-level jet, which are critical components in the EASM. The general patterns of the interannual and intraseasonal variation of precipitation are also improved, in particular, over land.

scholarly journals Dry and moist dynamics shape regional patterns of extreme precipitation sensitivity

2020 ◽  
Vol 117 (16) ◽  
pp. 8757-8763 ◽  
Author(s):  
Ji Nie ◽  
Panxi Dai ◽  
Adam H. Sobel
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Regional Scale ◽  
Vertical Motion ◽  
Precipitable Water ◽  
Small Scale ◽  
Climate Projections ◽  
Regional Patterns

Responses of extreme precipitation to global warming are of great importance to society and ecosystems. Although observations and climate projections indicate a general intensification of extreme precipitation with warming on global scale, there are significant variations on the regional scale, mainly due to changes in the vertical motion associated with extreme precipitation. Here, we apply quasigeostrophic diagnostics on climate-model simulations to understand the changes in vertical motion, quantifying the roles of dry (large-scale adiabatic flow) and moist (small-scale convection) dynamics in shaping the regional patterns of extreme precipitation sensitivity (EPS). The dry component weakens in the subtropics but strengthens in the middle and high latitudes; the moist component accounts for the positive centers of EPS in the low latitudes and also contributes to the negative centers in the subtropics. A theoretical model depicts a nonlinear relationship between the diabatic heating feedback (α) and precipitable water, indicating high sensitivity of α (thus, EPS) over climatological moist regions. The model also captures the change of α due to competing effects of increases in precipitable water and dry static stability under global warming. Thus, the dry/moist decomposition provides a quantitive and intuitive explanation of the main regional features of EPS.

Large-scale patterns of lake ice phenology and climate: model simulation and observations

2000 ◽  
Vol 27 (5) ◽  
pp. 2815-2815
Author(s):  
S. E. Walsh ◽  
S. J. Vavrus ◽  
J. A. Foley ◽  
R. H. Wynne
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Model Simulation ◽  
Lake Ice ◽  
Climate Model Simulation ◽  
Ice Phenology

Forcings of mass-balance variability in Karakoram-Himalaya

2020 ◽  
Author(s):  
Pankaj Kumar ◽  
Vladimir A. Ryabchenko ◽  
Aaquib Javed ◽  
Dmitry V. Sein ◽  
Md. Farooq Azam
Keyword(s):  
Mass Balance ◽  
Large Scale ◽  
Climate Model ◽  
Model Simulation ◽  
Large Fraction ◽  
Water Security ◽  
Spatiotemporal Variability ◽  
Glacier Mass Balance ◽  
Russian Science ◽  
The Impact

<p>Glacier retreat is a key indicator of climate variability and change. Karakoram-Himalaya (KH) glaciers are the source of several perennial rivers protecting water security of a large fraction of the global population. The region is highly vulnerable to climate change impacts, hence the sensitivity of KH glaciers to regional microclimate, especially the impact of individual parameters forcing have been not quantified yet. The present study, using a coupled dynamical glacier-climate model simulation results, analyses the modelled interannual variability of mass-balance for the period 1989-2016. It is validated against available observations to quantify for the first time the sensitivity of the glaciers mass-balance to the individual forcing over KH. The snowfall variability emerges as the key factor, explaining ~60% of the variability of regional glacier mass balance. We provide insight into the recent divergent glacier response over the Karakoram Himalaya. The results underline the need for careful measurements and model representations of snowfall spatiotemporal variability, one of the HK's least-studied meteorological variables, to capture the large-scale, but region-specific, glacier changes at the third pole.</p><p> </p><p> </p><p> </p><p>Acknowledgement:</p><p>The work was supported by Indian project no. DST/INT/RUS/RSF/P-33/G, and the Russian Science Foundation (Project 19-47-02015).</p>

scholarly journals Simulated pre-industrial climate in Bergen Climate Model (version 2): model description and large-scale circulation features

2009 ◽  
Vol 2 (2) ◽  
pp. 197-212 ◽  
Author(s):  
O. H. Otterå ◽  
M. Bentsen ◽  
I. Bethke ◽  
N. G. Kvamstø
Keyword(s):  
Sea Ice ◽  
Observational Data ◽  
Mixed Layer ◽  
Large Scale ◽  
Climate Model ◽  
Ocean Model ◽  
Meridional Overturning Circulation ◽  
Model Description ◽  
Sea Ice Extent ◽  
Large Scale Circulation

Abstract. The Bergen Climate Model (BCM) is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large-scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressure distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean model have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

A Comparison of CMIP3 Simulations of Precipitation over North America with Observations: Daily Statistics and Circulation Features Accompanying Extreme Events

2013 ◽  
Vol 26 (10) ◽  
pp. 3209-3230 ◽  
Author(s):  
Anthony M. DeAngelis ◽  
Anthony J. Broccoli ◽  
Steven G. Decker
Keyword(s):  
North America ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Southern Mexico ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract Climate model simulations of daily precipitation statistics from the third phase of the Coupled Model Intercomparison Project (CMIP3) were evaluated against precipitation observations from North America over the period 1979–99. The evaluation revealed that the models underestimate the intensity of heavy and extreme precipitation along the Pacific coast, southeastern United States, and southern Mexico, and these biases are robust among the models. The models also overestimate the intensity of light precipitation events over much of North America, resulting in fairly realistic mean precipitation in many places. In contrast, heavy precipitation is simulated realistically over northern and eastern Canada, as is the seasonal cycle of heavy precipitation over a majority of North America. An evaluation of the simulated atmospheric dynamics and thermodynamics associated with extreme precipitation events was also conducted using the North American Regional Reanalysis (NARR). The models were found to capture the large-scale physical mechanisms that generate extreme precipitation realistically, although they tend to overestimate the strength of the associated atmospheric circulation features. This suggests that climate model deficiencies such as insufficient spatial resolution, inadequate representation of convective precipitation, and overly smoothed topography may be more important for biases in simulated heavy precipitation than errors in the large-scale circulation during extreme events.

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