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Statistical climatology
Jsurnal of Statistical PXanningand Inference 6 (1982)201-202 North-Hotland Publishing Company
201
S, IKEDA, E. SUZUKI, E. UCHIDA and M.M. YOSHINO, editors (Elsevies Scientific Publishing Company, New York, 1980)x + 388 pp. $68.25
This book is the proceedix of the First International Cor&rence on Statistical Chmatology held at the Inte niversity Seminar House, Hachioji, Tokyo, Japan, from November 29 through December 1, 1979. Statistical climatology is a fascinating field requiring a broad spectrum of analysis procedares involving both statistics and applied probability. The inherent stochastic behavior of a climate demands the use of statistical and probabilistic techniques. The thirty articles of this book indicate the scope of statistical and probabilistic techniques needed in this field. While many of the articles do have a direct bearing on climatologicai questions, a specific concern is the imagination required in understanding hgw some of the articles do relate to climatology per se. It seems imperative (at least from my point of view) that a statistician actually wanting to sell a product to climatologists (which at least appears part of t!ris book’s purpose) must show advantages attained with hi:; These advantages: should be demonstrated by an exampie (Le., with real ch clearly indicates (i) that the product is superior to previously existing e products, or (ii) that the product accomplishes something that was not previously possible. Statistical climatology is an exciting field involving real problems which require new meaningful and innovative statistica: techniques. The discussion of a statistical problem which might involve a data oriented field (such as climatology) does not provide much motivation or interest to a elima:;ologist. The :&ove does describe my concern regarding this book, To indicate the diversity of topics considered in the many interesting arti&s of the following list of article titles and authors is presented: ‘A summarized this bo theoretical Ijistributions fitted to climatic factors and Markov chain review models of weather sequences’, E. Suzuki; ‘A generalized circular dist:sibution’, W. ly of generalized log istic S~eyers and J$ Va sacker; ‘Sort prop d.stributions’, R.R. Davidson: ‘Some stati for chmatological data’, ta and S. Panchapakesan; ’ reoryof estimation of’the loca-ion and scale parameters based on a set r of selected samp1.e riate aJram&-v 9
/$02.75 0 1982 North-Holland
202
of Bayes decision for normal mean under nonstandard prior: Unknown precision’, AK. Band; ‘Some results on exchangeability and majorization in statistics’, A.M. Abouammoh; ‘Prediction ot’ a future ordered observation based on a sample from Gan, MS. Hak and M.M. Ah; ‘Testing homothe exponential population’, E. geneity of varia;tRceof a series of linear models’, Y.P. Chaubey; ‘Some properties of generalized ridge estimators in finear regression models’, T,D. Dwivedi, J.M. Lowerre and V.K. Srivastava; “Selection of the number of re ression parameters in small sample cases’, R, Shibata; ‘Modelling weather data as a Markov chain’, L. Billard and M.R. Meshkani; ‘On red noise and quasi-periodicity in the time series of atmospheric temperature’, O,M. Essenwanger; ‘Detection of changes in the parameters of periodic or pseudo-periodic systems when the change times are unknown’, LB. MacNeill; ‘Precipitation simulation process with Markov chain modeling’, O.P. Bishnoi and K.K. Saxena; ‘Statistical prediction of clim logical extreme value and return period in the case of small samples’, E. Suzuki . Miyata and S. Mongo; ‘On the use of exponential smoothirlg for the estimation of climatic e!ements’, M, Ogawara; ‘An optimum linear restriction in the estimation problem for a generalized linear mode! and its application to climatic data’, E. Suzuki, T. Oohashi and S. Hongo; ‘Application of the discriminant aslalysis in meteorology’, G. Der-MeEreditchian; ‘Regional classification cf East African rainfall stations into homogen:L.ousgroups using the method of principal component analysis’, L. Ogalio; ‘On a mathematical mode1 of carbon dioxide concentrations in the mid troposphere’, J. Gould, F.A. Ahrens and CS, i-long; ‘Some new worldwide cloud cover models’, S.T. Bean and P.-N. Somerville; ‘Variability of northern hemisphere mean surface air temperature during recent two hundred years’, R. Yamamoto; ‘The four-year cycle in atmospheric and solar phenomena’, K. Takaharshi; ‘Classification of monsoon climates and stability of their moisture regime’, VP. Subrahmanyam and H.S. Ram Mohan; ‘Suitable probability model for severe cycloniz storms striking the coast around the Bay of Bengal’, D.A. Mooley; ‘Rainfall intensity-duration-return period equations and nomographs of India’, R. B&u, K.G. Tejwani, MC. Agarwal and L.S. Bhushan; ‘Probability model for the calamitous behaviour of the summer monsoon over In ia’, D.A. Mooley and B. Parthasarathy; and ‘Problems in statistical climatology*, M.M. Yoshino. This list also demonstrates the substantial need for statistical and probabilistic expertise in au extremely ilnportant field.
201
S, IKEDA, E. SUZUKI, E. UCHIDA and M.M. YOSHINO, editors (Elsevies Scientific Publishing Company, New York, 1980)x + 388 pp. $68.25
This book is the proceedix of the First International Cor&rence on Statistical Chmatology held at the Inte niversity Seminar House, Hachioji, Tokyo, Japan, from November 29 through December 1, 1979. Statistical climatology is a fascinating field requiring a broad spectrum of analysis procedares involving both statistics and applied probability. The inherent stochastic behavior of a climate demands the use of statistical and probabilistic techniques. The thirty articles of this book indicate the scope of statistical and probabilistic techniques needed in this field. While many of the articles do have a direct bearing on climatologicai questions, a specific concern is the imagination required in understanding hgw some of the articles do relate to climatology per se. It seems imperative (at least from my point of view) that a statistician actually wanting to sell a product to climatologists (which at least appears part of t!ris book’s purpose) must show advantages attained with hi:; These advantages: should be demonstrated by an exampie (Le., with real ch clearly indicates (i) that the product is superior to previously existing e products, or (ii) that the product accomplishes something that was not previously possible. Statistical climatology is an exciting field involving real problems which require new meaningful and innovative statistica: techniques. The discussion of a statistical problem which might involve a data oriented field (such as climatology) does not provide much motivation or interest to a elima:;ologist. The :&ove does describe my concern regarding this book, To indicate the diversity of topics considered in the many interesting arti&s of the following list of article titles and authors is presented: ‘A summarized this bo theoretical Ijistributions fitted to climatic factors and Markov chain review models of weather sequences’, E. Suzuki; ‘A generalized circular dist:sibution’, W. ly of generalized log istic S~eyers and J$ Va sacker; ‘Sort prop d.stributions’, R.R. Davidson: ‘Some stati for chmatological data’, ta and S. Panchapakesan; ’ reoryof estimation of’the loca-ion and scale parameters based on a set r of selected samp1.e riate aJram&-v 9
/$02.75 0 1982 North-Holland
202
of Bayes decision for normal mean under nonstandard prior: Unknown precision’, AK. Band; ‘Some results on exchangeability and majorization in statistics’, A.M. Abouammoh; ‘Prediction ot’ a future ordered observation based on a sample from Gan, MS. Hak and M.M. Ah; ‘Testing homothe exponential population’, E. geneity of varia;tRceof a series of linear models’, Y.P. Chaubey; ‘Some properties of generalized ridge estimators in finear regression models’, T,D. Dwivedi, J.M. Lowerre and V.K. Srivastava; “Selection of the number of re ression parameters in small sample cases’, R, Shibata; ‘Modelling weather data as a Markov chain’, L. Billard and M.R. Meshkani; ‘On red noise and quasi-periodicity in the time series of atmospheric temperature’, O,M. Essenwanger; ‘Detection of changes in the parameters of periodic or pseudo-periodic systems when the change times are unknown’, LB. MacNeill; ‘Precipitation simulation process with Markov chain modeling’, O.P. Bishnoi and K.K. Saxena; ‘Statistical prediction of clim logical extreme value and return period in the case of small samples’, E. Suzuki . Miyata and S. Mongo; ‘On the use of exponential smoothirlg for the estimation of climatic e!ements’, M, Ogawara; ‘An optimum linear restriction in the estimation problem for a generalized linear mode! and its application to climatic data’, E. Suzuki, T. Oohashi and S. Hongo; ‘Application of the discriminant aslalysis in meteorology’, G. Der-MeEreditchian; ‘Regional classification cf East African rainfall stations into homogen:L.ousgroups using the method of principal component analysis’, L. Ogalio; ‘On a mathematical mode1 of carbon dioxide concentrations in the mid troposphere’, J. Gould, F.A. Ahrens and CS, i-long; ‘Some new worldwide cloud cover models’, S.T. Bean and P.-N. Somerville; ‘Variability of northern hemisphere mean surface air temperature during recent two hundred years’, R. Yamamoto; ‘The four-year cycle in atmospheric and solar phenomena’, K. Takaharshi; ‘Classification of monsoon climates and stability of their moisture regime’, VP. Subrahmanyam and H.S. Ram Mohan; ‘Suitable probability model for severe cycloniz storms striking the coast around the Bay of Bengal’, D.A. Mooley; ‘Rainfall intensity-duration-return period equations and nomographs of India’, R. B&u, K.G. Tejwani, MC. Agarwal and L.S. Bhushan; ‘Probability model for the calamitous behaviour of the summer monsoon over In ia’, D.A. Mooley and B. Parthasarathy; and ‘Problems in statistical climatology*, M.M. Yoshino. This list also demonstrates the substantial need for statistical and probabilistic expertise in au extremely ilnportant field.