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Robertino ha scritto:sta miseramente fallendo la mia ipotesi di break più consistente intorno al 23, del resto nel cuore della stagione ho osato troppo, chiedo scusa

Matteo TV ha scritto:

Robertino ha scritto:sta miseramente fallendo la mia ipotesi di break più consistente intorno al 23, del resto nel cuore della stagione ho osato troppo, chiedo scusa

Matteo il nord non può lamentarsi. Tra gfs e volendo pure gem ci sarebbero precipitazioni quasi ogni giorno.

luca90 ha scritto:

Robertino ha scritto:

ventomoderato ha scritto: hai la memoria corta. Io parlavo di estate in decadenza a breve. Era un'idea. Bravo sfotti pure.

ah a breve, ok ok, no perchè ho letto di anomalie di +10 gradi, a parte che potrebbero essere dati sbagliati anche quelli eh

A me ha fatto ridere

Fanta pauroso

Non ho tempo di tradurla per chi eventualmente fatica con l'inglese ma l'uomo ha inventato Google e fortunatamente anche un buonissimo traduttore.


"
THE DATA SET
The data used to produce the climate bulletins consists of a data set of secular records, coming from the historical Italian Meteorological Observatories, set up in Brunetti et al (2006) updated with data from the Global Surface Summery of Day (GSOD), which comprises Italian Air Force and ENAV station data.
At present day, many of the historical Italian Meteorological Observatories are closed and for those still working it is difficult to obtain data in an automatic and near real time way. For this reason, the historical Observatories records, when possible, were merged with the modern Air Force network to get a series wich is updatable in near real time and automatically via GSOD Network managed by NCDC/NOAA.
The whole data set (both merged and not merged series) has been homogenized with statistical techniques to eliminate all the non-climatic signals due to station history (changes in the instruments, instruments/station relocation, changes in the observations riles, and so on). See Brunetti et al. (2006) for details about data homogenization and Venema et al. (2012) for details about the performances of the mostly used homogenization techniques.
The homogenization is a necessary step to provide time series with a long-term signal as close as possible to the real climate signal.
The figures show the data set with different symbols for stations wich are updated in near real time and stations not updated.

CONVERSION INTO ANOMALIES
Stations are located at different elevations and absolute temperature and precipitation values present strong spatial gradients. For this reason, changes in data availability can lead to biases when averaging among station series of different length.
An example: if we average the temperature records of three stations with different mean temperature values (e.g. one station located at sea leve, one at 1000m asl and the third one at 2000m asl) and with station records having different lengths, the resulting average series will be positively biased when the coldest station has no data and negatively biased when the warmest station has no data.
To avoid biases that could result from these problems, monthly temperature and precipitation series are reduced to anomalies (deviation from the mean for temperature and ratio for precipitation) from the period with best coverage (1971-2000).
Because many stations do not have complete records for the 1971-2000 period, a gap-filling technique have been developed to estimate 1971-2000 averages from neighbouring records (see Brunetti et al., 2006).
The station records converted into anomalies are then interpolated onto a regular grid.

THE NATIONAL MEAN SERIES
The national mean seires were obtained by averaging all grid boxes over the italian territory and not the station anomalies.
The reason is as follows:
The availability of station data is typically not sufficient to ensure an even distribution of stations throughout a network. But by averaging station anomalies within regions of similar size (grid boxes) and then calculating the average of all the grid box averages, a more representative region-wide anomaly can be calculated.
This makes grid box averaging superior to simply taking the average of all stations in the domain. A network of 1000 stations could theoretically have 700 stations in the northern half of the domain and 300 stations in the southern half. A simple average of the stations could easily create a bias in the domain-wide average to those stations in the north."


ps, basterebbe a volte fare una semplice e rapida ricerca per comprendere come funzionano le mappe di un Ente Scientifico.

Buona serata a tutti.

Mi aspettavo una risposta diversa da quello che già so luca, a prescindere da tutto il dato pluvio sul Lazio centrale è totalmente sballato e non veritiero, lo dimostra anche la carta del noaa postata da robertino e naturalmente ho dei motivi se dico qualcosa del genere

Matteo TV ha scritto:Fanta pauroso

certi scenari sempre a 250 ore e oltre. Come le altre super ondate di caldo viste da gfs e per fortuna ridotte o posticipate...

Rio ha scritto:
Vedrete che quando l'AMO virerà di segno torneremo ad avvicinarci molto alla media estiva 71-'00

IMadeYouReadThis ha scritto:

Rio ha scritto:
Vedrete che quando l'AMO virerà di segno torneremo ad avvicinarci molto alla media estiva 71-'00

L'oracolo schernitore

freddopungente ha scritto:Mi aspettavo una risposta diversa da quello che già so luca, a prescindere da tutto il dato pluvio sul Lazio centrale è totalmente sballato e non veritiero, lo dimostra anche la carta del noaa postata da robertino e naturalmente ho dei motivi se dico qualcosa del genere

Mi associo

Rio ha scritto:

IMadeYouReadThis ha scritto:

Rio ha scritto:
Vedrete che quando l'AMO virerà di segno torneremo ad avvicinarci molto alla media estiva 71-'00

L'oracolo schernitore

Di sicuro l'Amo negativo qualche effetto favorevoke lo porterà per forza di cose.. Perô ritornare su quei valori é dura ( ma mai dire mai a questo punto)

luca90 ha scritto:Non ho tempo di tradurla per chi eventualmente fatica con l'inglese ma l'uomo ha inventato Google e fortunatamente anche un buonissimo traduttore.


"
THE DATA SET
The data used to produce the climate bulletins consists of a data set of secular records, coming from the historical Italian Meteorological Observatories, set up in Brunetti et al (2006) updated with data from the Global Surface Summery of Day (GSOD), which comprises Italian Air Force and ENAV station data.
At present day, many of the historical Italian Meteorological Observatories are closed and for those still working it is difficult to obtain data in an automatic and near real time way. For this reason, the historical Observatories records, when possible, were merged with the modern Air Force network to get a series wich is updatable in near real time and automatically via GSOD Network managed by NCDC/NOAA.
The whole data set (both merged and not merged series) has been homogenized with statistical techniques to eliminate all the non-climatic signals due to station history (changes in the instruments, instruments/station relocation, changes in the observations riles, and so on). See Brunetti et al. (2006) for details about data homogenization and Venema et al. (2012) for details about the performances of the mostly used homogenization techniques.
The homogenization is a necessary step to provide time series with a long-term signal as close as possible to the real climate signal.
The figures show the data set with different symbols for stations wich are updated in near real time and stations not updated.

CONVERSION INTO ANOMALIES
Stations are located at different elevations and absolute temperature and precipitation values present strong spatial gradients. For this reason, changes in data availability can lead to biases when averaging among station series of different length.
An example: if we average the temperature records of three stations with different mean temperature values (e.g. one station located at sea leve, one at 1000m asl and the third one at 2000m asl) and with station records having different lengths, the resulting average series will be positively biased when the coldest station has no data and negatively biased when the warmest station has no data.
To avoid biases that could result from these problems, monthly temperature and precipitation series are reduced to anomalies (deviation from the mean for temperature and ratio for precipitation) from the period with best coverage (1971-2000).
Because many stations do not have complete records for the 1971-2000 period, a gap-filling technique have been developed to estimate 1971-2000 averages from neighbouring records (see Brunetti et al., 2006).
The station records converted into anomalies are then interpolated onto a regular grid.

THE NATIONAL MEAN SERIES
The national mean seires were obtained by averaging all grid boxes over the italian territory and not the station anomalies.
The reason is as follows:
The availability of station data is typically not sufficient to ensure an even distribution of stations throughout a network. But by averaging station anomalies within regions of similar size (grid boxes) and then calculating the average of all the grid box averages, a more representative region-wide anomaly can be calculated.
This makes grid box averaging superior to simply taking the average of all stations in the domain. A network of 1000 stations could theoretically have 700 stations in the northern half of the domain and 300 stations in the southern half. A simple average of the stations could easily create a bias in the domain-wide average to those stations in the north."


ps, basterebbe a volte fare una semplice e rapida ricerca per comprendere come funzionano le mappe di un Ente Scientifico.

Buona serata a tutti.

Ciao Luca...come va? Spero tutto bene! Ogni tanto faccio qualche apparizione....però vi leggo sempre! Qui sta facendo un'estate calda si...ma molto dinamica! La sera poi si sta bene e anche la notte ! Buona serata

Telecuscino ha scritto:

Rio ha scritto:

IMadeYouReadThis ha scritto:

L'oracolo schernitore

Di sicuro l'Amo negativo qualche effetto favorevoke lo porterà per forza di cose.. Perô ritornare su quei valori é dura ( ma mai dire mai a questo punto)

@Telecuscino ciao

Perchè sei tu ... posto, come hai detto bisogna aver fiducia e forse è un piccolo passo...


NOAA

https://www.esrl.noaa.gov/psd/data/corr ... .long.data


Colorado State University

aggiornamento-index-amo-atlantic-multi- ... 43814.html

Matteo come ti dicevo durante il live il run appena uscito non è dei peggiori per le prime 192 ore, certo mi ribeccherei nei prossimi giorni la +20, i 34 35 gradi e la tanta afa, però poi si nota qualche spago ipotizzare pioggia e scendere, si fa per dire, verso la "fresca" +17 +18, di questi tempi c'è di peggio. Eppure ci credevo un po sul break verso il 23, ma ormai speranze al lumicino

spaghi completi, si vede solo l'ufficiale nel fanta esuberante, la media resta calda ma non esagerata, vedremo un po