Detection of temperature inhomogeneities using observations of snow and rain. Gregor Vertačnik

Transcription

1 Detection of temperature inhomogeneities using observations of snow and rain Gregor Vertačnik Zagreb, 19 November 17

2 Introduction Quality of climate data homogenisation depends on network density and metadata Very old weather measurements sparse in space and lack of metadata One possible solution: coherent use of precipitation and temperature data Rain-to-snow temperature intersection quite stable in space and time

3 No major difference between the intersection in an Alpine valley and lowlands 1 9 Rat eče (86 m ASL), period: 1981/ 8 1/ 11 rain snow rain LOESS snow LOESS 8 number of day ys daily mean temperature ( C)

4 No major difference between the intersection in an Alpine valley and lowlands 1 9 Novo m est o ( m ASL), period: 1981/ 8 1/ 11 rain snow rain LOESS snow LOESS 8 s number of day daily mean temperature ( C)

5 Minor to moderate effect of 1-day timelag between temperature and precipitation data 1 9 Novo mesto ( m ASL), period: 1981/8 1/11, RR 1 day before rain snow rain LOESS snow LOESS 8 number of days daily mean temperature ( C)

6 Data Digitised archive of daily observations in Slovenia (late 19th century present) Daily mean temperature from three measurements (7, 1, 1 CET), adjusted to precipitation measurement interval Daily precipitation at 7 CET (amount, type) LOESS curve-fitting of rainfall/snowfall frequency: Winter months (December, January, February) Precipitation threshold 1 mm Width of temperature classes 1/1 C Smoothing width C

7 Analyis: case of Ljubljana Longest time series in Slovenia: with interruptions since 1818 officialy since March 185 modern-day standard observations since 198 Relatively abundant metadata Effect of city growth hard to estimate cautious use of the time series for regional climate change studies

8 numb ber of days Ljubljana, all cases, period: 185/ 53 16/ 17 rain snow rain LOESS snow LOESS daily mean t emperat ure ( C)

9 Example of poor measurement site number of days Ljubljana, period: 191/ Januar 1919 rain snow rain LOESS snow LOESS intersection at.9 C Station from 1895 till 19 in the central part of Ljubljana (Vegova ulica) Established by the Ljubljana hydrography section daily mean t emperat ure ( C)

10 Example of poor measurement site number of days Ljubljana, period: 191/ Januar 1919 rain snow rain LOESS snow LOESS intersection at.9 C Station from 1895 till 19 in the central part of Ljubljana (Vegova ulica) Established by the Ljubljana hydrography section daily mean t emperat ure ( C) A. Gavazzi writes that since Jan 16, 1919 measurement location is unsuitable, above cellar window of the central heating room Shift of rain-to-snow intersection for about 1.3 C number of days Ljubljana, period: 16 January 1919 December 19 intersection at. C daily mean temperat ure ( C) rain snow rain LOESS snow LOESS

11 Example of urbanisation around the site number of days Ljubljana, period: January / 7 intersection at. C rain snow rain LOESS snow LOESS Station from 198 onwards in Bežigrad Established by the Hydrometeorological institute Rural/suburban in early years daily mean t emperature ( C)

12 Example of urbanisation around the site number of days Ljubljana, period: January / 7 intersection at. C rain snow rain LOESS snow LOESS Station from 198 onwards in Bežigrad Established by the Hydrometeorological institute Rural/suburban in early years rain snow 7 8 daily mean t emperature ( C) rain LOESS The city of Ljubljana has expanded in recent decads Measurement site in a large urban area now Shift of rain-to-snow intersection for about.7 C number of days snow LOESS Ljubljana, period: 1993/ 9 16/ 17 intersection at 1.1 C daily mean temperature ( C)

13 Oldest data in Ljubljana (unofficial) number of days Ljubljana, period: / 7 intersection at C rain snow rain LOESS snow LOESS Measurements (in R) published as weekly tables in Laibacher Zeitung Period No metadata (observation times, location etc.) daily mean t emperat ure ( C)

14 Oldest data in Ljubljana (unofficial) number of days Ljubljana, period: / 7 intersection at C rain snow rain LOESS snow LOESS Measurements (in R) published as weekly tables in Laibacher Zeitung Period No metadata (observation times, location etc.) daily mean t emperat ure ( C) 1 Two different subperiods based on pressure inhomogeneities Very high intersection values ( C) Bias due to improper thermometer location number of days Ljubljana, period: 187/ / 39 intersection at.5 C daily mean temperature ( C) rain snow rain LOESS snow LOESS

15 Homogenised winter mean temperature time series Homogenisation based on intersection shifts Assumptions: Location changes not significant (i.e. from city-centre to a nearby village) Inhomogeneity size in fair weather and snowy/rainy weather approximately the same No significant inhomogeneities in precipitation type and amount measurements

16 5 Temperature anomaly for three winter timeseries, reference period: ano omaly ( C) Ljubljana Celje Kočevje Ljubljana H Celje H Kočevje H

17 5 3 Temperature anomaly for three winter timeseries, reference period: large inhomogeneities in early period ano omaly ( C) Ljubljana Celje Kočevje Ljubljana H Celje H Kočevje H

18 Is there any network bias in the early period?

19 Is there any network bias in the early period? 1-yr mean of all stations below 8 m ASL in interior Slovenia (mild continental climate) ure ( C) temperat yr mean intersection temperature for interior stations below 8 m ASL yr period

20 Is there any network bias in the early period? 1-yr mean of all stations below 8 m ASL in interior Slovenia (mild continental climate) Significant warm bias around ure ( C) temperat yr mean intersection temperature for interior stations below 8 m ASL warm bias yr period

21 Conclusions Method potentially useful for winter-time series in moderate climate

22 Conclusions Method potentially useful for winter-time series in moderate climate Requires homogenous block of around 1 years or more data

23 Conclusions Method potentially useful for winter-time series in moderate climate Requires homogenous block of around 1 years or more data Useful for medium to large inhomogeneities (> ~.5 C)

24 Conclusions Method potentially useful for winter-time series in moderate climate Requires homogenous block of around 1 years or more data Useful for medium to large inhomogeneities (> ~.5 C) Cannot account for true microclimate effect (hilltop versus frost hollow)

25 Conclusions Method potentially useful for winter-time series in moderate climate Requires homogenous block of around 1 years or more data Useful for medium to large inhomogeneities (> ~.5 C) Cannot account for true microclimate effect (hilltop versus frost hollow) Method may reveal network-wide temperature bias (i.e. early-period warm bias)

26 Sources Digital meteorological archive of Slovenian Environment Agency LOESS Smoothing in Excel package, Peltier Tech Blog:

27 Thankyouverymuchforyourattention!