A compound reconstructed prediction model for nonstationary climate processes

Wang, Geli; Yang, Pan

doi:10.1002/joc.1158

Cited by 15 publications

(7 citation statements)

References 18 publications

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“…Recently, based on some climate observations, the concept of a "climate hierarchy" that implied climate is a cascade phenomenon originating from different hierarchies was proposed [6][7][8][9]. Techniques termed "compound reconstruction" and "segregated prediction" were applied to predict non-stationary time series; technically, though, these approximated the non-stationary contributions of the signals into stationary components.…”

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confidence: 99%

A novel approach in predicting non-stationary time series by combining external forces

et al. 2011

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In this paper, we investigate a novel technique that reconstructs the observed time series and incorporates driving forces. Furthermore, to illustrate and test the technique, we consider a couple of predictive experiments using ideal time series provided by the logistic and Lorenz systems with specific driving forces. The preliminary results show this approach can improve prediction proficiency to some extent, and the external forces play a similar role to that of state variables. Short-term prediction is one of the difficult issues in climate change studies. Because of the complexity of short-term climate processes and lack of general knowledge underpinning its mechanisms, proficiency in prediction remains at a stand-still [1,2]. As for climate change in the 21st century, global warming is the most important factor, with many studies devoted to the topic. The possible causes range from change in natural forces (such as solar activity and volcanic emission) to human activities (such as green-house gases, sulfate emission in aerosols, and land use). In addition, the internal variability of climate systems should not be ignored either. However, no matter the cause of climate change, global warming in fact gives notice that climate processes are non-stationary. So far many climate predictive theories formulated in statistics and in nonlinear science are based on the hypothesis that the process is stationary, thus ergodicity theory can be used under such conditions to reconstruct the dynamics from an observed time series and establish predictive equations constructed from it.This reconstruction is at variance with the basic behavior of climate process. As is well-known for any weather or climate system, it is impossible to state the initial conditions incontrovertible. In fact, except for global warming, recent work has addressed the proper characterization of non-stationarity using weather and climate data. For instance, Tsonis [3] analyzed low-frequency (decadal to multi-decadal) variation in global precipitation over the past century and found that fluctuations about the global mean have increased significantly, implying that the second-order moment of the precipitation has changed on those scales, or that global precipitation process is non-stationary in the past century. In another case, Trenberth [4] found that the observed winter Pacific mean sea-level pressure underwent an abrupt change towards the end of the 70s; such a change in regime highlights the decline in the stationary behavior of the system. They noted that the behavior of these quantities is non-stationary. Most real world time series have some degree of non-stationarity due to external perturbations of the observed system [5].However, there is as yet no general theory about nonstationary processes. What scientists can do for the moment

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confidence: 99%

A novel approach in predicting non-stationary time series by combining external forces

et al. 2011

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“…AZC has important influences on the weather processes in Asia. The Asian Zonal Circulation Index (AZCI) is defined as the mean geopotential height gradient over the region (45°–65°N, 60°–150°E) at 500 hPa and is often used to show the intensity of zonal circulation over Asia (Wang and Yang, ). The region was divided into three subregions by an interval (30°) of longitude at the parallel circle.…”

Section: Methodsmentioning

confidence: 99%

Spatial and temporal variations of summer hot days and heat waves and their relationships with large‐scale atmospheric circulations across Northeast China

Wang

et al. 2018

Intl Journal of Climatology

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This study investigated the recent and future spatiotemporal changes in summer hot days (HDs) and heat waves (HWs) and their relationships with large‐scale atmospheric circulations over Northeast China (NEC). We used daily maximum temperature data from 109 meteorological stations for the period 1961–2013 across NEC and the output of 11 general circulation models from Coupled Model Intercomparison Project Phase 5 under RCP4.5 and RCP8.5 emission scenarios. We found that the frequencies and intensities of summer HDs and HWs overall increased in the last 53 years. The increases mainly occurred in the northeastern Inner Mongolia, the north part of the Heilongjiang Province, and southern Changbai Mountains. The during time periods between the start and end dates of HDs were lengthened from 1961 to 2013 in the eastern Inner Mongolia, the northeastern Heilongjiang Province, and the southern Liaoning Province. Our results showed that HDs and HWs exhibited significant increasing trends from 2006 to 2100 under RCP4.5 and RCP8.5 emission scenarios. Generally, more frequent and intense summer HDs and HWs would happen in NEC over the 21st century. Especially, the northwest of NEC and the south and middle of Da Hinggan Mountains would experience the most frequent and intense HDs and HWs. The variations in atmospheric circulation in summers with abnormal frequency of HDs and HWs were driven by Asian Zonal Circulation and Western Pacific Subtropical High simultaneously. An anticyclonic circulation anomaly prevailing over the west of NEC and the higher summer surface sea temperature in Japan Sea resulted in more frequent HDs and HWs across NEC. This study may help to understand future changes in HDs and HWs and provide references for water resources management and policy‐making in agriculture and forestry.

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“…Physics controlling snow cover and snow water equivalent, i.e. precipitation and processes of climate are nonstationary [39,40]. A factor in nonstationarity is telecomnection processes at the global scale such as the El Niño/Southern Oscillation (ENSO) [41,42].…”

Section: Methodsmentioning

confidence: 99%

Multi-Satellite and Sensor Derived Trends and Variation of Snow Water Equivalent on the High-Latitudes of the Northern Hemisphere

Muskett¹

2012

IJG

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Utilizing more than 30 years of satellite-microwave sensor derived snow water equivalent data on the high-latitudes of the northern hemisphere we investigate regional trends and variations relative to elevation. On the low-elevation tundra regions encircling the Arctic we find high statistically significant trends of snow water equivalent. Across the high Arctic Siberia and Far East Russia through North America and northern Greenland we find increasing trends of snow water equivalent with local region variations in strength. Yet across the high Arctic of western Russia through Norway we find decreasing trends of snow water equivalent of varying strength. Power density spectra identify significant power at quasi-biennial and associated lunar nodal cycles. These cycles of the upper atmosphere circulation, ENSO and ocean circulation perturbations from tides forms the causative linkage between increasing snow water equivalent on low-elevation tundra landscapes and decreasing coastal sea ice cover as part of the Arctic system energy and mass cycles

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A compound reconstructed prediction model for nonstationary climate processes

Cited by 15 publications

References 18 publications

A novel approach in predicting non-stationary time series by combining external forces

A novel approach in predicting non-stationary time series by combining external forces

Spatial and temporal variations of summer hot days and heat waves and their relationships with large‐scale atmospheric circulations across Northeast China

Multi-Satellite and Sensor Derived Trends and Variation of Snow Water Equivalent on the High-Latitudes of the Northern Hemisphere

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