The importance of long-term Arctic weather station data for setting the research stage for climate change studies

The importance of long-term Arctic weather station data for setting the research stage for climate change studies Taneil Uttal NOAA/Earth Systems Research Laboratory Boulder, Colorado

Things to get out of this lecture There are a handful of Arctic weather stations with very long records that are also the site of new observatories Change across the Arctic is very regional and seasonal details can get lost in averages and synthetic data recreations may only be detected with station records The Arctic has seasons that have a steep latitudinal dependence for some parameters direct observations may still surpass any advanced technological methods for acquiring data Russia is a treasure trove of long-term Arctic data records work is being done now on calibrating historical records to modern sensors

Barrow Tiksi Alert Eureka

http://www.giss.nasa.gov/research/news/20110113/ There are large areas in the Arctic without weather stations. NASA GISS approaches the problem by filling in gaps with data from the nearest land stations. The Climatic Research Unit at the University of East Anglia, which works jointly with the Met Office Hadley Centre, leaves much of the region out of its global temperature analysis. (Image credit: NASA Earth Observatory/Robert Simmon) Coverage is irregular, so the existing station records are important.

Tiksi and Barrow are at the same latitude but have very different amplitudes in the annual temperature cycles. Eureka gets colder in winter than Alert despite being further south. Important differences in the number of days/year with temperature above -10C Tiksi Tiksi 24 degrees C Barrow 17 degrees C 120 days Same Latitude but different temperature amplitudes Alert Eureka 95 days

Temperature Trends by Month Barrow Tiksi Alert Eureka Hmmm when we started this we expected cooling in the Canadian Archipelago, strong warming in Siberia and not much change in Alaska

Things to get out of this lecture There are a few Arctic weather stations with records very long records Change across the Arctic is very regional and seasonal details can get lost in averages and synthetic data recreations may only be detected with station records The Arctic has seasons that have a steep latitudinal dependence for some parameters direct observations may still surpass any advanced technological methods for acquiring data Russia is a treasure trove of long-term Arctic data records work is being done now on calibrating historical records to modern sensors

March-April-May MAM Seasons June-July-August JJA Sept-Oct-Nov SON Dec-Jan-Feb DJF

I took a trip to Eureka in March 2006 and the temperatures were -40 C (+/- 3 degrees) For eight days straight and my feet were COLD. It did not seem like spring

Record warmth in 2005 is notable, because global temperature has not received any boost from a tropical El Niño this year. The prior record year, 1998, on the contrary, was lifted 0.2 C above the trend line by the strongest El Niño of the past century. We believe that the remarkable Arctic warmth of 2005 is real, and the inclusion of estimated arctic temperatures is the primary reason for our rank of 2005 as the warmest year. Hansen et al analysis (2005) Update: Jan. 12, 2006 Dr. James Hansen ( NASA)

Trends in Nordic and Arctic Temperature Extremes and Ranges HEIKKI TUOMENVIRTA Finnish Meteorological Institute, Helsinki, Finland HANS ALEXANDERSSON Swedish Meteorological and Hydrological Institute, Norrkoping, Sweden ACHIM DREBS Finnish Meteorological Institute, Helsinki, Finland POVL FRICH* Danish Meteorological Institute, Copenhagen, Denmark PER OYVIND NORDLI Norwegian Meteorological Institute, Oslo, Norway J. Clim, 2000, Vol 13, pp 977-990 In Fenno-Scandia, the reliable long-term mean maximum and minimum temperatures show cooling in winter and warming in spring and summer during the period 1910 95.

Comparison of winter trends

Comparison of spring and fall trends

Temperature Change over 55 years (1948-2002) Temperature Change over 27 years (1975-2002) Classic DJF-MAM- JJA-SON Proposed ONDJFMA- MAY-JJA- Sep Winter 0.54 0.89 Classic DJF-MAM- JJA-SON Proposed ONDJFMA- MAY-JJA- Sep Winter 0.58 2.77 Spring 0.23-0.83 Spring 3.04 1.61 Summer -0.13-0.13 Summer 0.9 0.9 Fall 1.44 0.9 Fall 4.8 2.79

Oct-Nov-Dec-Jan-Feb-Mar-Apr ONDJFMA June-July-August JJA May M September S

Things to get out of this lecture There are a few Arctic weather stations with records very long records Change across the Arctic is very regional and seasonal details can get lost in averages and synthetic data recreations may only be detected with station records The Arctic has seasons that have a steep latitudinal dependence for some parameters direct observations may still surpass any advanced technological methods for acquiring data Continuity of observation techniques is important Russia is a treasure trove of long-term Arctic data records work is being done now on calibrating historical records to modern sensors

Now it is assumed we have better Instruments and methods For data archival

Subjective surface observer estimates of cloud cover may be better than satellite estimates of cloud cover There are MANY papers showing that model and satellite measurements agree poorly with surface measurements

Figure from R. Stone http://www.esrl.noaa.gov/gmd/grad/westernarctic.html Temperature Trend Cloud Amount Trend This is an example of very qualitative data indicating a clear mechanisms of positive cloud forcing in the winter and negative cloud forcing in the summer Thanks Ryan Eastman!

Eureka -

In addition, to accuracy issues, The more advanced and sophisticated methods of measurement do not have the 70+ year records yet Area (Grid) averages will have a hard time catching extreme local events

Trend coefficients of total (1) and low (2) cloudiness Tenth/year 0.04 0.02 0.00-0.02 Significant trend Insignificant 50 40 30 20 10-0.04 1 3 5 month 7 9 11 Tenth/year 0.04 0.02 0.00-0.02 0 50 40 30 20 10 1 3 5 7 9 11-0.04 1 3 5 7 9 11 0 1 3 5 7 9 11 month From A. Makshtas Arctic and Antarctic Research Institutes St Petersburg

Wind roses in Tiksi (1934 2006) SCALE, % 0 10 16 22 28 34 40 46 52 58 64 70 76 82 88 94 1 00 CALM 3 5 7 9 11 13 15 17 19 21 23 25 27 30 VELOSITY, m/s JANUARY FEBRUARY MARCH APRIL MAY JUNE JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DESEMBER

Tiksi January Winds 1932-1939 1940-1949 1950-1959 1960-1969 1970-1979 1980-1989 1990-1999 2000-2009

Barrow Tiksi Alert Eureka winter spring summer fall year Upper air data show a long-term trend of lower tropospheric heating and upper troposphere/low stratosphere cooling at all 34 stations for all seasons except winter. Particularly strong positive trends of winter upper air temperatures have been observed at Eureka and Alert. The smaller warming trend in the Tiksi in lower atmosphere agrees with the surface data.

T 1000 mb -22-24 -26-28 -30-32 T 850 mb -18-20 -22-24 -26 Climate of free atmosphere in Tiksi -34-36 -38 1940 1950 1960 1970 1980 1990 2000 Year -42-44 -46-48 -50 T 400 mb T 50 mb -28-30 -32 1930 1940 1950 1960 1970 1980 1990 2000 2010 Year -45-50 -55-60 -65 The strong warming in low troposphere and cooling in upper troposphere and low stratosphere, especially during summer, is one of the main peculiarities of climate in the Tiksi region -52-70 -54-75 14-56 1930 1940 1950 1960 1970 1980 1990 2000 2010 Year -80 1950 1960 1970 1980 1990 2000 2010 Year 12 12 10 10 8 January T 1000 mb 8 6 4 T 850 mb 6 4 2 0-2 July 2 1930 1940 1950 1960 1970 1980 1990 2000 2010 Year -22-24 -4 1930 1940 1950 1960 1970 1980 1990 2000 2010 Year -34-36 -38-26 T 400 mb -28 T 50 mb -40-42 -30-44 -32-46 -34 1930 1940 1950 1960 1970 1980 1990 2000 2010 Year -48 1940 1950 1960 1970 1980 1990 2000 2010 Year

Interannual variability of data of fast and drifting ice formation and destruction 320 300 280 Julian day 260 240 220 Date of fast ice destruction Date of drifting ice total melting Date of freezing begining Date of beginning fast ice formation 200 180 160 1930 1940 1950 1960 1970 1980 1990 2000 2010 Year

Tiksi Sea Ice Thickness

Snow thickness calculated with data about snow precipitation 0.7 0.6 Snow thickness, m 0.5 0.4 0.3 0.2 0.1 0.0 1940 1942 1944 1946 1948 1950 1952 1954 1956 1958 1960 Year

In Tiksi, comparison of Russia radiation instruments and modern Baseline Surface Radiation Network (BSRN) instruments is in progress

Modern measurements can be used to backwards calibrate existing records

Network of Stations around Tiksi

Russian Drifting Station.

Time History of the NP stations

The Arctic and Antarctic Research Institute in St. Petersburg Russia has web accessible data archives..

http://research.iarc.uaf.edu/~igor/research/data/airtemppres.php

http://cdiac.ornl.gov/epubs/ndp/ndp026d/ndp026d.html

Surface Temperature from meteorological stations is not a radiative temperature related to heat content! Not a great metric for climate change