Seasonal precipitation forecasts over China using monthly large-scale oceanic-atmospheric indices

Peng, Zhaoliang; Wang, Q.J.; Bennett, James; Pokhrel, Prafulla; Wang, Ziru

doi:10.1016/j.jhydrol.2014.08.012

Cited by 39 publications

(27 citation statements)

References 47 publications

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“…The results revealed that the precipitation of the river basin was significantly influenced by climate fluctuation phases, which were also proved by Cañón et al []. The correlation relationships can be used to predict rainfall on the monthly, seasonal, and annual scales if a lag structure can be found between precipitation and the climate indices [ He and Guan , ; Peng et al , ].…”

Section: Introductionmentioning

confidence: 53%

A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates

Wang

et al. 2015

JGR Atmospheres

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Many drought indices were proposed to describe drought characteristics, but only few had considered environmental changes. In an attempt to incorporate climate change into meteorological drought index, a nonstationary Gamma distribution with climate indices as covariates was developed for fitting precipitation data and then used for calculating a Nonstationary Standardized Precipitation Index (NSPI) in this study. The performances of the NSPI were compared with those of the traditional Standardized Precipitation Index (SPI), showing that the NSPI capable of taking climate variations into account is more robust than the traditional SPI. Focusing on the Luanhe River basin, historical drought events were described and assessed based on the NSPI and traditional SPI. Moreover, drought characteristics, including drought frequency, peak, duration, and magnitude, were calculated by using the two indices. The results in this study indicated that NSPI using climate indices as covariates could capture drought characteristics in the Luanhe River basin, and this new drought index provides a new concept for constructing the drought index that can effectively adapt to a changing environment.

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Section: Introductionmentioning

confidence: 53%

A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates

Wang

et al. 2015

JGR Atmospheres

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“…Svensson et al 2015;Palin et al 2016;Clark et al 2017), and is often used already in China (e.g. Xiao et al 2012;Wang et al 2013;Peng et al 2014;Wang et al 2015;Xing et al 2016). Research is ongoing to understand the predictability of larger-scale drivers in GloSea5, and how they can be used to improve sector-specific forecasts.…”

Section: Discussionmentioning

confidence: 99%

Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector

Bett

Thornton

Lockwood

et al. 2017

Journal of Applied Meteorology and Climatology

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We assess the skill and reliability of forecasts of winter and summer temperature, wind speed and irradiance over China, using the GloSea5 seasonal forecast system. Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. We find that although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skilfully forecast around the coast of the South China Sea, related to skilful forecasts of the El Niño-Southern Oscillation. Such information could improve seasonal estimates of offshore wind power generation. Similarly, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar power estimation. Much of China shows skill in summer temperatures, which derives from an upward trend. However, the region around Beijing retains this skill even when detrended. This temperature skill could be helpful in managing summer energy demand. While both the strengths and limitations of our results will need to be considered when developing seasonal climate services in the future, the outlook for such service development in China is promising. This document is c Crown

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“…Statistical relationships between large-scale climate phenomena and precipitation at more local scales have long been used to produce seasonal forecasts across China, and for the Yangtze in particular (e.g. Zhu et al, 2008, Kwon et al, 2009, Zou et al, 2010, Ke et al, 2011, Liu and Fan, 2012, Tung et al, 2013, Peng et al, 2014, Li and Lin, 2015, Wu and Yu, 2016, Xing et al, 2016, Zhang et al, 2016b.…”

Section: Introductionmentioning

confidence: 99%

Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

Bett¹,

Scaife²,

Li³

et al. 2018

Adv. Atmos. Sci.

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The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/2016 provided a valuable opportunity to test the application of a dynamical forecast system.This paper therefore presents a case study of a real time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations.

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Seasonal precipitation forecasts over China using monthly large-scale oceanic-atmospheric indices

Cited by 39 publications

References 47 publications

A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates

A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates

Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector

Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

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