The results from three approaches are very similar. The approaches are evaluated at 65 benchmarks (BMs covered around Qingdao where the tide gauge is used to observe the local mean sea level of China. This combination is performed through three approaches: The first one is based on the theory of Molodensky, and the second one compares levelled heights and geopotential values derived from the GGMs, while the third one analyses the differences between GPS/Levelling and GGMs geoid undulations. The geoid undulations derived from the GGM (Global Geopotential Models. ![]() This estimation is based on the combination of ellipsoidal heights, levelled heights (referring to the CVD, and some physical parameters, such as geopotential values, gravity values, and geoid undulations. Estimation the W0LVD of China is based on the computation of the mean geopotential offset between the value W0 = 62636856.0 m 2s− 2, selected as reference in this study, and the unknown geopotential value W0LVD. The relative operating characteristic (ROC) indicates that the highest scores for the above- and below-normal precipitation categories are, respectively, for February and April and the lowest scores found for December.Įvaluation of the geopotential value W0LVD of Chinaĭirectory of Open Access Journals (Sweden)įull Text Available Estimation of the zero- height geopotential value W0LVD for the CVD (China Vertical Datum plays a fundamental role in the connection of traditional height reference systems into a global height system. The Pearson correlation between the area averaged of the observed and predicted precipitation over the study area for Jan, Feb, March, April, November, and December months are statistically significant at the 5% significance level and are 0.78, 0.80, 0.82, 0.74, 0.79, and 0.61, respectively. The 850 hPa geopotential height pattern over the Red Sea, Saudi Arabia, and Persian Gulf is found to be the major pattern related to Iranian monthly precipitation. The optimal number of principal components and canonical variables to be retained in the CCA equations is determined using the highest average cross-validated Kendall's tau value. Principal component analysis (PCA) as a pre-filter is used for data reduction for both explanatory and response variables before applying CCA. The monthly geopotential height reanalysis dataset over an area between 10° N and 60° N and from 20° E to 80° E is utilized as the explanatory variable in the CCA. The monthly precipitation dataset for 50 synoptic stations distributed in different climate regions of Iran is considered as the response variable in the CCA. ![]() Canonical correlation analysis (CCA) is used to set up the statistical linkage between the 850 hPa geopotential height large-scale circulation and monthly precipitation over Iran for the period 1968-2010. This paper investigates the linkage between large-scale atmospheric circulation and monthly precipitation during November to April over Iran. Shirvani, Amin Fadaei, Amir Sabetan Landman, Willem A. ![]() The linkage between geopotential height and monthly precipitation in Iran National Aeronautics and Space Administration — ML 2GPH is the EOS Aura Microwave Limb Sounder (MLS) standard product for geopotential height derived from radiances measured by the 118 and 240 GHz radiometers.
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