Hydrologic Advances in Space-Time Precipitation Modeling and Forecasting

1991 ◽  
pp. 47-65 ◽  
Author(s):  
Efi Foufoula-Georgiou ◽  
Konstantine P. Georgakakos
Keyword(s):  
Space Time ◽  
Modeling And Forecasting ◽  
Precipitation Modeling

scholarly journals PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA CURAH HUJAN EMPAT KABUPATEN DI PROVINSI JAWA TENGAH

2019 ◽  
Vol 8 (4) ◽  
pp. 418-427
Author(s):  
Eko Siswanto ◽  
Hasbi Yasin ◽  
Sudarno Sudarno
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Space Time ◽  
Series Data ◽  
Inverse Distance Weighted ◽  
Modeling And Forecasting ◽  
Distance Weighted ◽  
The Relationship ◽  
Inverse Distance

In many applications, several time series data are recorded simultaneously at a number of locations. Time series data from nearby locations often to be related by spatial and time. This data is called spatial time series data. Generalized Space Time Autoregressive (GSTAR) model is one of space time models used to modeling and forecasting spatial time series data. This study applied GTSAR model to modeling volume of rainfall four locations in Jepara Regency, Kudus Regency, Pati Regency, and Grobogan Regency. Based on the smallest RMSE mean of forecasting result, the best model chosen by this study is GSTAR (11)-I(1)12 with the inverse distance weighted. Based on GSTAR(11)-I(1)12 with the inverse distance weighted, the relationship between the location shown on rainfall Pati Regency influenced by the rainfall in other regencies. Keywords: GSTAR, RMSE, Rainfall

scholarly journals Space–Time Kriging of Precipitation: Modeling the Large-Scale Variation with Model GAMLSS

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2368
Author(s):  
Elias Silva de Medeiros ◽  
Renato Ribeiro de Lima ◽  
Ricardo Alves de Olinda ◽  
Leydson G. Dantas ◽  
Carlos Antonio Costa dos Santos
Keyword(s):  
Covariance Function ◽  
Large Scale ◽  
Precipitation Variability ◽  
Space Time ◽  
Monthly Precipitation ◽  
Distribution Of Zeros ◽  
New Techniques ◽  
Precipitation Estimates ◽  
The Government ◽  
Precipitation Modeling

Knowing the dynamics of spatial–temporal precipitation distribution is of vital significance for the management of water resources, in highlight, in the northeast region of Brazil (NEB). Several models of large-scale precipitation variability are based on the normal distribution, not taking into consideration the excess of null observations that are prevalent in the daily or even monthly precipitation information of the region under study. This research proposes a novel way of modeling the trend component by using an inflated gamma distribution of zeros. The residuals of this regression are generally space–time dependent and have been modeled by a space–time covariance function. The findings show that the new techniques have provided reliable and precise precipitation estimates, exceeding the techniques used previously. The modeling provided estimates of precipitation in nonsampled locations and unobserved periods, thus serving as a tool to assist the government in improving water management, anticipating society’s needs and preventing water crises.

Space, Time and Einstein

2002 ◽  
Author(s):  
J. B. Kennedy
Keyword(s):  
Space Time

Spinors and Space-Time

1984 ◽  
Author(s):  
Roger Penrose ◽  
Wolfgang Rindler
Keyword(s):  
Space Time

Do Writing Directions Influence How People Map Space onto Time?

2018 ◽  
Vol 77 (4) ◽  
pp. 173-184
Author(s):  
Wenxing Yang ◽  
Ying Sun
Keyword(s):  
Mental Representations ◽  
Space Time ◽  
Horizontal Axis ◽  
Causal Role ◽  
Writing Systems ◽  
Temporal Cognition ◽  
Japanese Speakers ◽  
Psychological Experiments ◽  
Vertical Up

Abstract. The causal role of a unidirectional orthography in shaping speakers’ mental representations of time seems to be well established by many psychological experiments. However, the question of whether bidirectional writing systems in some languages can also produce such an impact on temporal cognition remains unresolved. To address this issue, the present study focused on Japanese and Taiwanese, both of which have a similar mix of texts written horizontally from left to right (HLR) and vertically from top to bottom (VTB). Two experiments were performed which recruited Japanese and Taiwanese speakers as participants. Experiment 1 used an explicit temporal arrangement design, and Experiment 2 measured implicit space-time associations in participants along the horizontal (left/right) and the vertical (up/down) axis. Converging evidence gathered from the two experiments demonstrate that neither Japanese speakers nor Taiwanese speakers aligned their vertical representations of time with the VTB writing orientation. Along the horizontal axis, only Japanese speakers encoded elapsing time into a left-to-right linear layout, which was commensurate with the HLR writing direction. Therefore, two distinct writing orientations of a language could not bring about two coexisting mental time lines. Possible theoretical implications underlying the findings are discussed.

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