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Augustin Pajou: Royal Sculptor, – – MetPublications – The Metropolitan Museum of Art

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The celebration of Great Men, a quintessential part of eighteenth-century French patronage, is here examined with lively insight. The volume is lavishly illustrated and contains a detailed chronology, a wintre history of the artist’s critical reputation, an exhaustive bibliography, and a complete index. James David Draper is Henry R. Among his other publications is Clodionwith Anne L. Burchard, Wolf.

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Some of these extreme seasons are confirmed by other data sources. Documentary data normally provide information on extreme events. In a first step, it is possible to obtain a catalogue of episodes like droughts, intense rainfall, snowfall, or hailstorms. In our case, there is no overlapping period between documentary and instrumental data, so a different methodology must be applied.

Rodrigo proposed an alternative methodology to indices, trying to overcome the problem of the lack of an overlapping period. This method was tested using climate model paleo simulations Rodrigo et al.

If p 10 and p 90 are the percentiles 10 and 90 of a climatic series X of a mean value u and standard deviation SD, we can find corresponding normalized values q 10 and q 90 :. The normality hypothesis is the simplest choice, and it is valid for the series of temperature and rainfall in the four seasons of the year, except in the case of summer rainfall Rodrigo et al. From Eq. The basic idea is to accept that threshold values p i obtained from the instrumental observations are also valid for defining extreme values in the past, that is, we accept that during a past extreme season the value of the climate variable X was lower higher than p 10 p Percentiles 10 and 90 are commonly used to define the frequency of extreme indices, such as cold nights or warm days, and correspond to moderately extreme events Zhang et al.

These numbers are used to estimate q i Eq. The hypothesis here is that climatic changes are revealed not only by changes in the mean value of the variables, but also in the frequency and intensity of extreme events. Therefore, if we know the frequency of extremes during a given period, and accepting the normality hypothesis, we can determine the mean value and standard deviation of the climate variable corresponding to that period.

This methodology does not try to provide the year-to-year variability but the general characteristics of the studied period. This is a weakness of the analysis, although it is possible to reconstruct this interannual variability when documentary and instrumental periods are consecutive Rodrigo et al.

However, this methodology has advantages in comparison with the standard indices methodology. In addition, ordinal indices are often based on the impact of the events on the socioeconomic infrastructures for example, destruction of bridges during a river flood or loss of harvests , and these impacts may change in different periods.

The risk here is to consider as heavy extremes certain events that show the vulnerability of the system more than the extreme character of climate variables. The method followed is not based on the severity of the phenomena and, in consequence, at least to a certain degree, avoids these problems.

In second place, it does not need an overlapping period with instrumental data, which are necessary to calibrate and validate indices and to reconstruct a climate variable. There is a third problem of a statistical nature: the calibration of indices is normally done using a regression procedure between proxy data indices and instrumental data during an overlapping period.

With this method, in principle, it is not necessary to introduce this mathematical artifact. The reconstruction of SD and u depends on the values p i previously established as threshold values to define extreme seasons. These values may be established using the percentiles 10 and 90 corresponding to a given reference period.

Therefore, the reconstruction is strongly dependent on the chosen reference period. A possible solution is to select as reference period a period in which there are different climatic situations. Here we use the period —, which contains years characterized by a weak warming signal first decades , and years with a clear warming signal last decades of the 20th century.

All the series are homogeneous and do not present missing data or gaps. Table 2 shows the percentiles 10 and 90 of seasonal mean temperature and accumulated precipitation in Granada corresponding to the complete period — To calibrate the method, the complete series was divided into year running periods, the first one being —, the second one —, and the last — This procedure was adopted to obtain a large empirical sample.

For each individual period, the mean value u and the standard deviation SD were calculated and compared with the corresponding values u and SD estimated from the numbers n 10 and n 90 of extreme seasons. Correlation coefficients between estimated and observed values, as well as the root-mean-squared error RMSE , were calculated.

RMSE is used in forecasts verification and can also be thought as a typical magnitude for forecast errors Wilks, Values of RMSE were used to provide an estimate of the uncertainties that are associated with the reconstruction methodology. Table 3 shows the results of this calibration. According to correlation coefficient values, the method offers better results for the mean value u standard deviation SD of temperature rainfall.

These differences may be due to deviations from normality in the case of rainfall, particularly in summer. As an example, Fig. Figure 3 Calibration of the reconstruction method for autumn rainfall in Granada from to Table 3 Calibration of the reconstruction methodology using year moving series from to The method was applied to the period —, using the data of Table 1 as n i and percentiles p i of the reference period Table 2.

Figures 4 and 5 and Table 4 show the reconstruction of seasonal temperature and accumulated rainfall distribution functions, accepting the normality hypothesis. Only in the case of summer rainfall was the reconstruction not accomplished because of the absence of extreme wet seasons Table 1 and the non-normal character of summer rainfall. RMSE values previously estimated are used as error margins. Results are compared with the corresponding values of two year periods in the 20th century — — and — — when the warming signal is very different.

To obtain a best view of this comparison, Table 5 shows the statistics corresponding to these periods. According to these results, seasonal mean temperatures during — were very similar to those during —, even slightly warmer, and lower except in summer than temperatures during — around 0.

Standard deviations of temperature during — were similar to — and smaller than that of —, suggesting smaller variability in the past. Total rainfall shows values very similar in autumn for the three periods: slightly wetter conditions in spring during — and — and slightly wetter conditions in winter of — in comparison with — The variability of rainfall in is similar to that in —, except in spring, characterized during — by drier conditions.

Table 4 Reconstruction of the period — in Granada. Table 5 Statistics of the periods — and — in Granada. Figure 4 Distribution functions of seasonal temperatures of — and comparison with — a and — b. Figure 5 Distribution functions of seasonal rainfall of — and comparison with — a, c, e and — b, d, f.

Chapter IV of the book fols. It is the first compilation of early instrumental meteorological data in Spain, so far as we know. It begins in December and ends in February Unfortunately, we have not found documentary sources with these nine years of data, and we have to be content with the available information. In addition, information is not presented tabulated but as monthly summaries, indicating characteristic values or corresponding to critical moments, and it does not cover in detail all the days of the period.

Sometimes, he adds comments on winds and other meteorological events fog, cloudiness , and he indicates the number of rainy days of some months.

So, for instance, for August he indicates that. August began with warm weather; on day 2, the thermometer indicated 34, and there was a southerly wind. On day 8, the thermometer increased by two lines, from 38 to 40, during the total lunar eclipse, which was at 1 o’clock. Day 14 seemed to be the warmest day of the year; however the thermometer indicated 37, and from day 18 onwards there were slight northerly winds and the temperature decreased to This information was tabulated for analysis and may be found in Rodrigo a, NavarreteData.

There is no information about the installation of the instruments or the exact time at which readings were taken, and in the case of temperature, the scale does not correspond to any of the better-known scales that were introduced later for instance, the Reamur scale. In chap. Figure 6 shows the measurements recorded by Navarrete from December to February The sensitivity or resolution of the scale is 0. Figure 6 Temperatures measured and scale defined by Navarrete with the Florentine thermometer.

Cornelia Reiter. Costello, Jane. DAgostino, Paola. Metropolitan Museum Journal , Vol. Daskalakis Mathews, Annie-Christine. Dauterman, Carl Christian. Davidson, Marshall B. Dawson, Aileen. De Montebello, Philippe. De la Croix, P. Dean, Bashford. Dennis, Faith. The Passions of Jean-Baptiste Carpeaux. Draper, James David, and Guilhelm Scherf. Augustin Pajou: Royal Sculptor, — Olson, and Burkard von Roda. Playing with Fire: European Terracotta Models, — Draper, James David. The Arts Under Napoleon.

Eames, Clare. Eisler, Colin T. Eisler, Colin, and James Parker. Fahy, Everett. Farina, Viviana. Faxon, Alicia Craig. Feingold, Lawrence. Font, Lourdes M. Friedmann, Herbert, and Howard Hibbard. Ostoia, and Margaret R.

Galitz, Kathryn Calley. Gardner, Albert TenEyck. Gardner, Elizabeth E. Gazzard, Katherine. Gill, Kathryn. Gillies, Linda. Gordon, Alden R. Grace, Priscilla. Grancsay, Stephen V. Gregory H. Centeno, Janet G. Douglas, Christina Hagelskamp, John T. Haynes, Robyn E. Hodgkins, Edward A. Kennedy, Sarah Kleiner, Michele D. Thomas, and Anna Vila. Griswold, William.

Hackenbroch, Yvonne. Hale, Charlotte. Harris, John. Hauser, Walter. Haverkamp Begemann, Egbert. The Robert Lehman Collection.

Hecht, Johanna. Heckscher, Morrison H. Hibbard, Howard. Hollein, Max. Gifts of Art: The Met’s th Anniversary. Hunter-Stiebel, Penelope. Husband, Timothy, and John Goldsmith Phillips. Impey, O. Ives, Colta Feller. Picturesque Ideas on the Flight into Egypt. Ives, Colta, and Susan Alyson Stein. Goya in The Metropolitan Museum of Art. Ivins, W. How Prints Look: Photographs with a Commentary.

Ivins, William Mills. The Unseen Rembrandt. Kahr, Madlyn Millner. Kanter, Laurence B. Karpinski, Caroline, A. Hyatt Mayor, and Edith A. Hyatt Mayor, and John J. Karpinski, Caroline. Kaufmann, Thomas DaCosta. Kessler, Hans-Ulrich. London: The Society, Knauer, Elfriede Regina. Smith, and Dirk Syndram. Koeppe, Wolfram. Making Marvels: A Picture Album.

Kugler, Georg. La Rocca, Donald J. How to Read European Armor. LaRocca, Donald J. Laing, Alastair, et al. Pierre-Paul Prud’hon. Lawrence, Elizabeth N.

Le Bourhis, Katell, ed. Le Corbeiller, Clare. China Trade Porcelain: Patterns of Exchange. Eighteenth-Century Italian Porcelain. Gold Boxes: The Wrightsman Collection. Leopold, Jan Hendrik. Liedtke, Walter A. Vermeer and the Delft School. Liedtke, Walter. Frans Hals: Style and Substance.

The Milkmaid by Johannes Vermeer. Logan, Anne-Marie S. Logan, Anne-Marie, and Michiel C. Peter Paul Rubens: The Drawings. Logan, Carolyn. Lorenz, Hellmut. Liechtenstein Palaces in Vienna from the Age of the Baroque. Lowenthal, Rayanne. Mahon, Denis. Mann, Vivian B. A Court Jews Silver Cup. Martin, Richard. Massar, Phyllis Dearborn. Mayor, A. Goya: 67 Drawings. McCluer, Kate. McGregor, Jack R. McKendry, John J. McKim-Smith, Gridley.

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Volume 38, Number 3, Winter Issue View. Table of Contents. View Formatted Version. Wolf, Th. Engelen pp. Logue, Peter David Blanck pp. Jackson pp. DeLaet pp. Adler pp. Burnham pp. Seaver pp. Smith pp. Kselman pp. Hanson pp. Ringrose pp.