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Alexander Korablev Observed climatic changes in the Nordic Seas 1900-2009 OUTLINE Oceanographic database for the Nordic Seas Regional variability of thermohaline characteristics in selected regions from in situ observations Climatological horizontal fields for the Nordic Seas Summary Status October 2010 Oceanographic database for the Nordic Seas 60˚N — 82˚N 45˚W — 70˚E 1870 — 2010 456645 stations 45 sources 16000 AARI [13] AARIOD [24336] AARI_TGM [41207] AARIcr [565] ARGO [7711] 14000 AWI [137] AWI_CD [642] Cearex [2776] IGY 1957-58 ESIMO [557] ESOP [215] GSP [142] ICES2010 [14550] ICES_0207 [10255] ICES_0209 [3374] IMR [262] IMR9002 [32720] 10000 IOPAS_2008 [771] IOPAS [281] IORAS [272] IPY 3 2007-2009 IPY [309] 8000 6000 IPY 2 1932-33 Global Oceanographic Data Archeology and Rescue Project (GODAR) > 40000 stations added/corrected against original cruise reports Number of stations by source 12000 4000 ITP [163] LOGS [27] MAIA [9] Mike [11536] MMBI [386] NABOS [19] NANSEN [8] NOAA [516] NNDCD [2260] NPI [315] OCL [10826] Obninsk [24076] ODB_CA [140047] ODB_ICES [15920] Overflow [303] PNSEC [734] Report [7] 2000 RSHU [55] Tractor [311] VEINS [113] VEINS_H [14485] WHOI [215] 0 1900 WOD2001 [80190] 1910 1920 1930 1940 1950 1960 Years 1970 1980 1990 2000 2010 WOD2005 [11755] WOD2009 [1274] Time-depth diagrams for selected areas 1896 - 2009 ‘the strong of the event late 1960s and vertical exchange intensification’ ‘the late 1950searly 1960s warming event’ ‘The ‘The early 1920-1930s’ 20thcooling century warming low-salinity anomaly’ Negative Present salinity warm, anomaly salty andof low the density mid-1990s regime The Great Salinity Anomaly Example of estimated and mean fields (nearest neighborhood) (Intrinsic Kriging approach: details after ‘Thank You’ slide) Kriging Standard Deviations (KSD) provides estimation of interpolation quality for each field (depends on samples density) Standard Error of the mean provides quality of the climatological fields (depends on a variable variance and samples amount in a grid point) Example of estimated and mean fields (smoothing) MZ MIZ BZ FZ FZ It is dangerous to evaluate anomalies between estimated field and highly smoothed climatology field especially when they have been produced by different objective analysis methods with unknown errors of interpolation Temperature and salinity anomalies example (June 1976 at 50m relative to 1900-2009) Unsmoothed temperature anomalies Unsmoothed salinity anomalies Smoothed temperature anomalies Smoothed salinity anomalies GSA Propogation Now anomality of each monthly gridded field with data can be estimated relative to climatological field for selected period Climatological fields for 1900-2009 period in June at standard levels ? ? GS Gyre AW GS Gyre IS Gyre FZ AW EIC Reliable climatalogical fields may not be computed due to lack of observation over Greenland shelf LB Gyre Variability from in situ data and gridded fields. Comparison (June_d15) Spatial pattern of anomalies during stable regimes in the NS (June_d15 50m) Warm period around 1960 Strong atmospheric cooling The GSA propagation Low salinity anomaly Warm period since of the mid-1990s The late-1990s [1900-2009] climatological fields are generally warmer and saltier than [1957-1990] climatalogical fields at 50 m [1900-2009] - [1957-1990] (June_d15 50m) Strongest deviations, more than 1oC located in the Northern part of the NS, in BSO and Fram Strait regions Upper layer regimes and vertical exchange in the Nordic Seas T/S properties on 28.0 isopycnal surface (25-1000m) Strong atmospheric The GSA propagation cooling Low salinity anomaly of the mid-1990s 1.5 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 -0.1 -0.2 -0.3 -0.4 -0.5 -0.6 -0.7 -0.8 -0.9 -1 -1.5 75 70 65 60 -10 0 10 20 30 4 0.15 0.125 0.1 0.075 0.05 0.025 70 0 -0.025 -0.05 65 -0.075 -0.1 Convection intensification in the Nordic Seas 2 1 0 -1 -2 -3 -4 -0.125 60 -0.15 -10 0 10 20 30 40 cluster_1 (Polar Domain) cluster_4 (Arctic Domain) cluster_9 (Atlantic Domain) 3 40 75 Warm/salty period since the late-1990s 5 SAT_Anomalies_DJFM Warm period around 1960 -5 Mean SAT over the NS: Polar, Arctic and Atlantic Domains 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 YEARS Due to the upper layer salinity increase the NS are now potentially preconditioned for vertical exchange intensification if strong atmospheric cooling will occur. Similar to the late 1960s event. Mixed Layer temperature and salinity 2000-2010 (OWS ‘Mike’) Mean 1948-2009 AW low boundary ~380 m Winter convection ~170 m 0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 12 35.2 35.16 Salinity [psu] Temperature [°C] 11 10 9 8 6 2 3 4 5 6 7 month 8 9 10 4 6 8 10 12 2 4 Month 01dtd 02dtd 03dtd 05dtd 08dtd 1 35.08 35 2 Criterion 35.12 35.04 7 6 8 Month 35.2 4 35.16 Salinity [psu] MLD [m] Mixed Layer mean seasonal cycle (OWS ‘Mike’) 11 12 1 12 5 6 11 12 35.12 35.08 10 35.04 35 2 3 10 7 9 8 8 centered on winter Smirnov, A. Korablev, G. Alekseev and I. Esau Temporal and spatial changes in mixed layer properties and atmospheric net heat flux in the Nordic Seas. IOP Conf. Series: Earth and Environmental Science 13 (2010), doi:10/1088/1755-1315/13/1/012006 Simulated (MGO report, fig1 temperature/salinity anomalies versus observations ) Canadian Global Climate model Version 3 Ocean resolution 0.3o -> 1o Observed Temperature anomalies [oC] Observed Salinity anomalies [psu] Summary Oceanographic database for the Nordic Seas (including NA and Arctic) and time series were updated up to the beginning of 2010 Time series reveal variability is shaped by thermochaline anomalies propagation with different intensity, duration and spatial extent different stable upper layer regimes define intensity of the vertical exchange Monthly climatological fields based on non–stationary Intrinsic Kriging approach were computed for June 1900 – 2009 Reproduce spatial pattern and temporal variability reasonably well Show wide spread warming of the NS with acceleration in the northern parts Climatology for 1900-2009 period is generally warmer than for 1957-1990 Enhanced advection of sea ice and Polar water from Arctic affects heat fluxes over the NS and vertical mixing Quick comparison of simulated (CMIP3 models MGO report) and observed variability in the Norwegian Sea show substantial differences especially in the upper layer salinity regimes and deep water temperatures Thank you! Flowchart for horizontal fields gridding by Intrinsic Kriging Monthly or monthly centered samples at standard depth levels ODB Data Observed field: Data\in [irregular locations] Estimated field(internal): Estimated field(out): Data\grid Data\out [10x10 km] [0.25x0.25 deg] 1. Estimation Inversion problems are NSM disabled (selection duplicates Input: data\in within 1km) Drift trials: “no drift” “1 x y” “1 x y x2 xy y2” Covariance: Exp 250 NH: 250x250km; 3,16,3,3 Output model: t_mod; variable values with ksd at grid points ODB Climate 2. Interpolation into required grid (Linear Model Kriging) Input: grid\t_est grid\t_ksd Output: out\t_est out\t_ksd Filtering (optional) Kriging Input: data\in model: t_mod Extrapolation outside Output: grid\t_est data area is disabled grid\t_ksd (selection from Convex Hull) Filtering(optional) Notations ODB IK NSM NH KSD -Oceanographic DataBase - Intrinsic Kriging - non-stationary modeling -Neighborhood (ex: 50x50km 4,16,2,3) -ellipsoid distances: 50x50 -min number of samples: 4 -number of angular sectors: 16 -optimum number samples per sector: 2 -max number of consecutive empty sectors: 3 -Kriging Standard Deviation Grid for 60-82N, 45W-70E Observed Field ISATIS www.geovariances.com Mean (climatological) horizontal fields computing Output (ODBClimate application): ODB Climate Monthly ( or centered) gridded (0.25 deg) fields 1900-2009 at standard depth levels Mean at the grid points: arithmetic averaging for certain period (e.g. 1900-2009) Standard Error of the Mean: σ/N-2 Thresholds: ODB Climate KSD_SD: standard deviation of the KSD computed for all estimated fields QF: Quality flags were set at estimated values according to variable standard deviations computed for time series at grid nodes (>=3) Threshold values definition problem Output Expert control for each estimated field (-) From KSD total variance (3,4,5 σ) Time series consistency at grid nodes (1..5..9 SD) Time series at grid points (areas) Time/depth diagrams mean (climatological) fields for different periods anomality assessment for monthly or mean fields Additional quality control on observed data