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precipitacion_1983-2019.txt
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precipitacion_1983-2019.txt
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HOMOGEN() APPLICATION OUTPUT (From R's contributed package 'climatol' 4.1.0)
=========== Homogenization of precipitacion, 1983-2019. (Sat Jun 8 23:33:20 2024)
Parameters: varcli=precipitacion, anyi=1983, anyf=2019, test=snht, nref=10 10 4, std=NA, swa=NA, ndec=1, niqd=4 1, dz.max=0.01, dz.min=-0.01, cumc=NA, wd=0 0 100, inht=25, sts=5, maxdif=0.05, maxite=999, force=FALSE, wz=0.001, mindat=NA, onlyQC=FALSE, annual=mean, ini=NA, na.strings=NA, vmin=NA, vmax=NA, hc.method=ward.D2, nclust=300, cutlev=NA, grdcol=#666666, mapcol=#666666, expl=FALSE, metad=FALSE, sufbrk=m, tinc=NA, tz=utc, rlemin=NA, rlemax=NA, cex=1.1, uni=NA, raway=TRUE, graphics=TRUE, verb=TRUE, logf=TRUE, snht1=NA, snht2=NA, gp=NA
Data matrix: 444 data x 6 stations
Warning: excessive run lengths diagnostic skiped because IQR=0
-------------------------------------------
Stations in the 2 clusters :
$`1`
[1] 1 2 3 4 5
$`2`
[1] 6
---------------------------------------------
Computing inter-station distances ... 1 2 3 4 5
========== STAGE 1 (SNHT on overlapping temporal windows) ===========
Calculation of missing data with outlier removal
(Suggested data replacements are provisional)
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
22004(5) 2009-09-01: 33.4 -> 120.2 (-5.44)
22046(6) 2017-02-01: 145.6 -> 3.1 (9.39)
Performing shift analysis on the 6 series...
========== STAGE 2 (SNHT on the whole series) =======================
Calculation of missing data with outlier removal
(Suggested data replacements are provisional)
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
(No detected outliers)
Performing shift analysis on the 6 series...
22067(2) breaks at 2017-05-01 (27.4)
Update number of series: 6 + 1 = 7
Calculation of missing data with outlier removal
(Suggested data replacements are provisional)
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
(No detected outliers)
Performing shift analysis on the 7 series...
========== STAGE 3 (Final calculation of all missing data) ==========
Computing inter-station weights... (done)
Calculation of missing data with outlier removal
(Suggested data replacements are provisional)
The following lines will have one of these formats:
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
Iteration Max_data_difference (Station_code)
2 0.573 (22067-2)
3 0.275 (22067-2)
4 0.14 (22067)
5 0.127 (22067)
6 0.116 (22067)
7 0.107 (22067)
8 0.099 (22067)
9 0.092 (22067)
10 0.086 (22067-2)
11 0.082 (22067-2)
12 0.077 (22067-2)
13 0.072 (22067-2)
14 0.068 (22067-2)
15 0.064 (22067-2)
16 0.06 (22067-2)
17 0.056 (22067-2)
18 0.052 (22067-2)
19 0.049 (22067-2)
Prescribed convergence reached
Last series readjustment (please, be patient...)
======== End of the homogenization process, after 1.94 secs
----------- Final calculations :
SNHT: Standard normal homogeneity test (on anomaly series)
Min. 1st Qu. Median Mean 3rd Qu. Max.
5.600 6.400 8.200 8.643 9.650 14.600
RMSE: Root mean squared error of the estimated data
Min. 1st Qu. Median Mean 3rd Qu. Max.
3.674 12.597 13.944 12.549 14.724 15.585
POD: Percentage of original data
Min. 1st Qu. Median Mean 3rd Qu. Max.
7.00 55.00 66.00 60.43 70.50 99.00
SNHT RMSE POD Code Name
1 7.2 13.9 75 22058 Santa Teresa
2 8.2 3.7 7 22067 La Venta
3 14.6 14.1 66 22063 Queretaro (DGE)
4 5.6 15.3 56 22070 Plantel 7
5 5.6 15.6 99 22004 El Batan
6 9.5 12.6 66 22046 Nogales
7 9.8 12.6 54 22067-2 La Venta-2
Frequency distribution tails of residual anomalies and SNHT
Left tail of standardized anomalies:
0.1% 0.2% 0.5% 1% 2% 5% 10%
-4.1 -3.5 -3.0 -2.6 -2.2 -1.5 -1.1
Right tail of standardized anomalies:
90% 95% 98% 99% 99.5% 99.8% 99.9%
1.0 1.7 2.7 3.4 3.9 4.5 5.3
Right tail of SNHT on windows of 120 terms with up to 4 references:
90% 95% 98% 99% 99.5% 99.8% 99.9%
21.9 24.1 25.4 25.9 26.1 26.2 26.3
Right tail of SNHT with up to 4 references:
90% 95% 98% 99% 99.5% 99.8% 99.9%
11.7 13.2 14.0 14.3 14.5 14.5 14.6
----------- Generated output files: -------------------------
precipitacion_1983-2019.txt : Text output of the whole process
precipitacion_1983-2019_out.csv : List of corrected outliers
precipitacion_1983-2019_brk.csv : List of corrected breaks
precipitacion_1983-2019.pdf : Diagnostic graphics
precipitacion_1983-2019.rda : Homogenization results. Postprocess with (examples):
dahstat('precipitacion',1983,2019) # averages
dahstat('precipitacion',1983,2019,stat='tnd') #OLS trends and p-values
dahstat('precipitacion',1983,2019,stat='series') #homogenized series
dahgrid('precipitacion',1983,2019,grid=YOURGRID) #homogenized grids
... (See other options in the package documentation)