scholarly journals Oceanic drivers and empirical prediction of interannual rainfall variability in late summer over Northeast China

2021 ◽  
Author(s):  
Junhu Zhao ◽  
Han Zhang ◽  
Jinqing Zuo ◽  
Liu Yang ◽  
Jie Yang ◽  
...  
2021 ◽  
Author(s):  
Junhu Zhao ◽  
Han Zhang ◽  
Jinqing Zuo ◽  
Liu Yang ◽  
Jie Yang ◽  
...  

Abstract Northeast China (NEC) is located between the subtropical monsoon and temperate-frigid monsoon regions and exhibits two successive rainy seasons with different natures: the northeast cold vortex rainy season in early summer (May–June) and the monsoon rainy season in late summer (July–August). Summer rainfall over NEC (NECR) has a fundamental influence on society, yet its successful seasonal prediction remains a long-term scientific challenge to current dynamical models. The poor NECR prediction skill is partly attributed to the large NECR variability at both the interannual and interdecadal time scales. Here, we focus on the oceanic drivers of the late summer NECR variability and associated physical processes at interannual time scale. Then, we establish an empirical prediction model to predict the interannual variability of summer NECR at one-month lead time (in June). The analysis of observations spanning 40 years (1963–2002) reveals three physically and synergistically influencing predictors of the late summer NECR interannual variability. Above-normal NECR is preceded in the previous spring by (a) warm sea surface temperature (SST) anomalies in the tropical northern Indian Ocean, (b) a positive thermal contrast tendency in the tropical West–East Pacific SST, and (c) a positive tendency of the North Atlantic tripolar SST. These precursors enhance the anomalous low-level anticyclone over the Northwest Pacific and southerly anomalies over NEC in late summer, which are beneficial to enhancing NECR. An empirical prediction model built on these three predictors achieves a forecast temporal correlation coefficient (TCC) skill of 0.72 for 1961–2019, and a 17-year (2003–2019) independent forecast shows a significant TCC skill of 0.70. The skill is substantially higher than that of five state-of-the-art dynamical models and their ensemble mean for 1979–2019 (TCC=0.24). These results suggest that the proposed empirical model is a very meaningful approach for the prediction of NECR, although the dynamical prediction of NECR has considerable room for improvement.


2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.


2017 ◽  
Vol 50 (5-6) ◽  
pp. 2283-2283
Author(s):  
Isela L. Vásquez P. ◽  
Lígia Maria Nascimento de Araujo ◽  
Luiz Carlos Baldicero Molion ◽  
Mariana de Araujo Abdalad ◽  
Daniel Medeiros Moreira ◽  
...  

2013 ◽  
Vol 52 (6) ◽  
pp. 1303-1317 ◽  
Author(s):  
Christian Seiler ◽  
Ronald W. A. Hutjes ◽  
Pavel Kabat

AbstractBolivia is facing numerous climate-related threats, ranging from water scarcity due to rapidly retreating glaciers in the Andes to a partial loss of the Amazon forest in the lowlands. To assess what changes in climate may be expected in the future, 35 global circulation models (GCMs) from the third and fifth phases of the Coupled Model Intercomparison Project (CMIP3/5) were analyzed for the Bolivian case. GCMs were validated against observed surface air temperature, precipitation, and incoming shortwave (SW) radiation for the period 1961–90. Weighted ensembles were developed, and climate change projections for five emission scenarios were assessed for 2070–99. GCMs revealed an overall cold, wet, and positive-SW-radiation bias and showed no substantial improvement from the CMIP3 to the CMIP5 ensemble for the Bolivian case. Models projected an increase in temperature (2.5°–5.9°C) and SW radiation (1%–5%), with seasonal and regional differences. In the lowlands, changes in annual rainfall remained uncertain for CMIP3 whereas CMIP5 GCMs were more inclined to project decreases (−9%). This pattern also applied to most of the Amazon basin, suggesting a higher risk of partial biomass loss for the CMIP5 ensemble. Both ensembles agreed on less rainfall (−19%) during drier months (June–August and September–November), with significant changes in interannual rainfall variability, but disagreed on changes during wetter months (January–March). In the Andes, CMIP3 GCMs tended toward less rainfall (−9%) whereas CMIP5 tended toward more (+20%) rainfall during parts of the wet season. The findings presented here may provide inputs for studies of climate change impact that assess how resilient human and natural systems are under different climate change scenarios.


Geology ◽  
2018 ◽  
Vol 46 (8) ◽  
pp. 731-734 ◽  
Author(s):  
Philip J. Hopley ◽  
Graham P. Weedon ◽  
Chris M. Brierley ◽  
Christopher Thrasivoulou ◽  
Andy I.R. Herries ◽  
...  

Abstract Interannual variability of African rainfall impacts local and global communities, but its past behavior and response in future climate projections are poorly understood. This is primarily due to short instrumental records and a lack of long high-resolution palaeoclimate proxy records. Here we present an annually resolved 91,000 year Early Pleistocene record of hydroclimate from the early hominin-bearing Makapansgat Valley, South Africa. Changes in speleothem annual band thickness are dominated by precession over four consecutive orbital cycles with strong millennial-scale periodicity. The frequency of interannual variability (2.0–6.5 yr oscillations) does not change systematically, yet its amplitude is modulated by the orbital forcing. These long-term characteristics of interannual variability are reproduced with transient climate model simulations of water balance for South Africa from the Late Pleistocene to Recent. Based on these results, we suggest that the frequency of interannual variations in southern African rainfall is likely to be stable under anthropogenic warming, but that the size of year-to-year variations may increase. We see an orbitally forced increase in the amplitude of interannual climate variability between 1.8 Ma and 1.7 Ma coincident with the first evidence for the Acheulean stone tool technology.


2010 ◽  
Vol 49 (5) ◽  
pp. 1032-1043 ◽  
Author(s):  
Daniel Vila ◽  
Ralph Ferraro ◽  
Hilawe Semunegus

Abstract Global monthly rainfall estimates have been produced from more than 20 years of measurements from the Defense Meteorological Satellite Program series of Special Sensor Microwave Imager (SSM/I). This is the longest passive microwave dataset available to analyze the seasonal, annual, and interannual rainfall variability on a global scale. The primary algorithm used in this study is an 85-GHz scattering-based algorithm over land, while a combined 85-GHz scattering and 19/37-GHz emission is used over ocean. The land portion of this algorithm is one of the components of the blended Global Precipitation Climatology Project rainfall climatology. Because previous SSM/I processing was performed in real time, only a basic quality control (QC) procedure had been employed to avoid unrealistic values in the input data. A more sophisticated, statistical-based QC procedure on the daily data grids (antenna temperature) was developed to remove unrealistic values not detected in the original database and was employed to reprocess the rainfall product using the current version of the algorithm for the period 1992–2007. Discrepancies associated with the SSM/I-derived monthly rainfall products are characterized through comparisons with various gauge-based and other satellite-derived rainfall estimates. A substantial reduction in biases was observed as a result of this QC scheme. This will yield vastly improved global rainfall datasets.


2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Marcela Hebe González ◽  
María Laura Cariaga ◽  
María de los Milagros Skansi

The Chaco plain region in Argentina is located in the north of the country and east of Los Andes where the main activity is the agriculture. As such activity is highly affected by interannual rainfall variability, the influence of some of the principal atmospheric and oceanic forcing is investigated in this paper. Results show that the factors which affect precipitation highly depend on the season and the subregion. The position of the South Atlantic Height and the sea surface temperature in the coast of southern Brazil and Buenos Aires seem to be the factors that affect rainfall, all over the year. The El Niño-Southern Oscillation phenomenon affects summer and spring rainfall and the Southern Annular Mode involves spring precipitation but both only in the east of the study region. Furthermore, enhanced convection in Central Brazil, mainly influences autumn and spring rainfall.


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