1. GPI RAS 1 Arctic region

2. GPI RAS 2 Arctic region

3. GPI RAS 3 Arctic region

4. GPI RAS Remote sensing of Arctic fiords by Raman Lidar Remote sensing of Arctic fiords by Raman Lidar : ЗАДЕЛ – РЕЗУЛЬТАТЫ - ПЕРСПЕКТИВЫ ЛИДАРОВ В АРКТИКЕ –НОЧЬ – НЕТ ВИДЕО-ФОТО РЕГИСТРАЦИИ С.М. Першин pershin@kapella.gpi.ru Prokhorov General Physics Institute Russian Academy of Sciences

5. GPI RAS 5 Remote sensing of Arctic fiords and freshwater reservoir by Raman Lidar S.M. Pershin, My colleagues A.F. Bunkin M.Ya. Grishin V.K. Klinkov V.N. Lednev, E.G. Morozov A.V. Marchenko Prokhorov General Physics Institute Russian Academy of Sciences

6. GPI RAS 6 Motivation Arctic is the “weather kitchen” Arctic is the prospective region as an oil province and shortest transportation route from Passific Ocean to Europe and needs in ecological and weather monitoring by different technique Lidar remote sensing technique is the most effective among others

7. GPI RAS 7 Remote sensing for Arctic region (Why we need remote sensing?) Arctic region: Global climate changes Oil/gas production Temperature map of Arctic region Parameters 1.seawater temperature 2.seawater salinity 3.seawater phytoplankton concentration 4.seawater organic substances concentration 5.seawater optical properties 6.seawater contamination 7.ice thickness 8.ice surface roughness 9.ice optical properties 10.snow cover optical and thermodynamic properties automatic monitoring of ocean surface by remote sensing technique Satellite image of Arctic region Oil spills image Global climate modeling

8. GPI RAS Палеоклиматические данные (ледяные керны со станции «Восток»-Антарктида) по изменению температуры поверхности Земли и концентрации СО 2 и СН 4 в ее атмосфере за последние примерно 420 000 лет. Zakharov V.I.

9. GPI RAS 1) Человеческая жизнедеятельность меняет состав атмосферы, в особенности наблюдается очень активный рост концентрации парниковых газов IPCC 2013: нет сомнения в том, что 2) Потепление происходит  Наибольшая часть в наблюдаемом росте средней глобальной температуры с середины 20-го века, наиболее вероятно, обусловлена ростом концентрации парниковых газов из-за человеческих факторов.  Остается много неопределенностей Carbon dioxide (СO 2 ) + 39 % Methane (CH 4 ) +150 % Nitrous oxide( N 2 O) + 20% 3) Потепление будет продолжаться 2010

10. GPI RAS Температурная разница между 2010 /1970 (Hansen et al., 2011) Глобальное потепление в среднем на 0.66 ; и более чем в два раза в Арктике

11. GPI RAS Upper Ocean heat ContentN.H. Spring snow cover Global average sea level Arctic sea ice minimum extent

12. GPI RAS A1B типичный« сценарий высокой эмиссии » к (2090 – 2099), Прогнозируемый рост среднегодовой температуры составит 2.8°C В большей части суши ~ 3.5° C ; in Arctic > 7°C ;

13. GPI RAS Естественные причины ( солнечная активность, вулканы ) Наблюдения Человеческая активность Парниковые газы и аэрозоль Наибольшая часть в наблюдаемом росте средней глобальной температуры с середины 20-го века, наиболее вероятно, обусловлена ростом концентрации парниковых газов из-за человеческих факторов Les activités humaines ont-elles déjà influencé le climat ?

14. GPI RAS 14 The first Lidar of RAS on Mars surface was delivered by NASA launcher (project Mars Surveyor Lander – 99) Weight – 940 g Consumption 0.2-5W Т = – 100 +50 0 С Data volume 2kB per set 36 kB/12 sets per sol Range 750 meters resolution 10 m

15. GPI RAS Lidar-rangefinder in Arctic

16. GPI RAS 16 Remote measurements of temperature (Why we need Lidar remote sensing?) Remote temperature measurements: Spaceborne radiometer radars Airborne microwave scatterometers Airborne laser scatterometers * A. V. Soloviev and R. Lukas, Deep-Sea Res. Part I, 44, 1055–1076 (1997) ! 1 0 С low-speed wind* temperature detection in 30 μ m surface layer 5 definitions of temperature Alternatives: 1. thermocouple measurements 2. temperature measurements by Raman spectroscopy (laser remote sensing) 30 um vs 0.5-10 m

17. GPI RAS 17 Temperature dependence of Raman OH-band Raman spectra for distilled water from -33 0 C to +160 0 C А B Hare D.E. and Sorensen C.M., J. Chem. Phys. 1990, 93(10), 6954 water molecule Raman spectroscopy

18. GPI RAS 18 OH Raman spectrum in water vs temperature Raman scattering spectra of OH band in water and ice S. M. Pershin, et.al., Quantum Electron. 40, 1146–1148 (2010) А B Hare D.E. and Sorensen C.M., J. Chem. Phys. 1992, 96(1), 13

19. GPI RAS 19 Temperature measurements by Raman OH-band profile S. Pershin, et.al., Quant. Electr. 40, 1146 (2010) OH-band center vs temperaureOH-band peak fitting vs temperature A B R= BABA Becucci M., et.al., Appl.Opt., 38, 928 (1999)

20. GPI RAS 20 Compact Raman LIDAR Specification* Mass: ~20 kg Dimensions: 60x40x20 cm Power: 300 W Details Laser: DPSSL laser Nd:YVO 4 (Laser Compact), 527 nm, 5 ns, 1 kHz, 200 m J/pulse Detection system: Spectrograph (Spectra Physics MS127i) Spectral range 500 – 750 nm Spectral resolution 0.1 nm + ICCD detector (Andor iStar) Gate 5 ns Delay 0 - 1 s with step 0.25 ns A. Bunkin, S. Pershin et al., Appl. Opt. 51, 5477 (2012)

21. GPI RAS 21 Lidar, optical scheme

22. GPI RAS 22 “Viking Exploring” crew. Svalbard ( Spitsbergen, supporting by A. Marchenko )

23. GPI RAS 23 Compact Raman Lidar onboard a)compact LIDAR installed in ship’s cabin b) measurements with aluminum mirror

24. GPI RAS 24 Svalbard Fjords and GPS ship route 1. “open” Ice Fjord; 2. Akseloya Island at depths shallower ~20 m; 3. floating ice study in “closed” fjords, i.e., Van Mijen and Rinders Fjord

25. GPI RAS 25 Fiords temperature mapping by Raman Lidar b) temperature ( black squares ) by Raman system and by the CTD- profiler (red triangles) c) expedition route and mapping points are marked (red squares) A.Bunkin, V. Klinkov, V. Lednev, A. Marchenko, E. Morozov, S. Pershin, and R. Yulmetov, Remote sensing of ice in Svalbard fjords by compact Raman lidar, Appl. Opt. 51, 5477 (2012)

26. GPI RAS 26 Russian team from AGAT, Vladivostok http://msuauv.ru Maritime State University General view of the Russian ROBOSUB

27. GPI RAS 27 Raman Spectra for Ice and Water is different the idea is based on the difference of water and ice Raman and Rayleigh signal

28. GPI RAS 28 Ice Snow layer Underwater ice thickness measurement in front of icebreaker water

29. 1. A. F. Bunkin, V. K. Klinkov, V. A. Lukyanchenko, and S. M. Pershin, Ship Wake detection by Raman lidar, Appl.Opt., 2011, 50(4), pp. A86-A89 2. A.F. Bunkin, V.K. Klinkov, V.N. Lednev, D.L. Lushnikov, A.V. Marchenko, E.G. Morozov, S.M. Pershin, and R.N. Yulmetov, Remote sensing of seawater and drifting ice in Svalbard fjords by compact Raman LIDAR // Applied Optics, 2012, 51(22), pp. 5477 – 5485, 3. S.M. Pershin, A.F. Bunkin, V.K.Klinkov, V.N. Lednev, D. Lushnikov, E.G. Morozov, and R.N. Yul’metov, Remote Sensing of Arctic Fjords by Raman Lidar: Heat Transfer Screening by Layer of Glacier’s Relict Water // Physics of Wave Phenomena, 2012, 20(3), pp. 212-222 4. A.F. Bunkin, V.K. Klinkov, V.N. Lednev, S.M. Pershin, and R.N. Yulmetov,, http://www.gpi.ru/trudgpi.phphttp://www.gpi.ru/trudgpi.php 5. S.M. Pershin, V.N. Lednev, V.K. Klinkov, R. N. Yulmetov, and A.F. Bunkin, Ice thickness measurements by Raman scattering // Opt. Lett. 2014, 39, pp. 2573-2575; Papers

30. GPI RAS 30 Conclusions Compact Raman LIDAR has been developed in GPI RAS for remote sensing of Arctic region The new technique for express temperature, chlorophyll and ice thickness measurements by Raman spectroscopy was suggested and tested The new phenomenon was observed: Fiords heat screening by Layer of Glacier’s Relict melted water flows above sea water Lidar sensing of an algal bloom in freshwater reservoir was carried out, quantified and mapped

31. GPI RAS 31 Arctic region Thank you for attention S. PERSHIN et al., Applied Optics, 54(19), 5943 (2015)

32. GPI RAS 32 Thanks for your attention.

33. GPI RAS 33 Outline Laser remote sensing: principals and capabilities Unmanned aircraft vehicle’s (UAV) facilities for remote sensing Raman&Rayleigh scattering technique with underwater LidarIce thickness measurements by Raman&Rayleigh scattering technique with underwater Lidar

34. GPI RAS 34 Platforms: Laser remote sensing in 70-90 s mirror telescope Helicopter Kamov-32 for lLIDAR Result * no systematic expeditions * a few flights per year Laser remote sensing drawbacks: heavy equipment (>300 kg) high power consumption (> 3 kW) expansive vehicle rental fee Lidar system installed in helicopter ( developed at GPI RAS in 1992)

35. GPI RAS 35 Modern approach: Compact LIDAR for UAV Future of remote sensing: micro UAV with installed lidar? Unmanned aircraft vehicle’s (UAV) facilities for remote sensing: payload mass power heavy (>1000 kg, 24 h) <100 kg <800 W midi (50-1000 kg, <12 h )<20 kg <100 W mini (5-50 kg, 1-4 h)<2 kg <10 W micro (<1 kg, 1 h)<100 g <0.1 W

36. GPI RAS 36 Ice thickness measurements just now Conventional techniques : 1. drilling (a, b) - human costs -long duration for measurements - ( 10 holes for 1 m depth equals >1 hour ) - low accuracy of temperature measurements 2. electro-magnetic antenna (c) - expansive equipment - poor accuracy for remote sensing - no temperature measurements a)a) b)b) c)c) Optical technique using is forbidden by snow layer

37. GPI RAS 37 Seawater echo-spectrum: main idea ice snow layer water

38. GPI RAS 38 Compact Raman LIDAR Specification* Mass: ~20 kg Dimensions: 60x40x20 cm Power: 300 W Details Laser: DPSSL laser Nd:YVO 4 (Laser Compact), 527 nm, 5 ns, 1 kHz, 200  J/pulse Detection system: Spectrograph (Spectra Physics MS127i) Spectral range 500 – 750 nm Spectral resolution 0.1 nm + ICCD detector (Andor iStar) Gate 5 ns Delay 0 - 1 s with step 0.25 ns * A.F. Bunkin et. al., Appl. Opt. 51, 5477-5485 (2012)

39. GPI RAS 39 Ice and Water Raman spectra

40. GPI RAS 40 Ice thickness measurements by LIDAR in lab

41. GPI RAS 41 Ice thickness measurement by elastic scattering ice water laser beam Conclusion: elastic scattering is not convenient for ice–water interface detection n water = 1.333 n ice = 1.309 Elastic scattering (“ice bathymetry”)

42. GPI RAS 42 Ice thickness measurements by Raman scattering a) Raman spectra of OH-band for ice (black triangles) and water (red circus) and corresponding fitting curves b) Ice thickness measurements by Raman OH-band center (blue circus) Raman scattering a) ice water laser beam b) Conclusion: Raman OH-band center shift is convenient for ice–water interface detection

43. GPI RAS 43 Conclusions A new optic technique for express ice thickness measurements by Raman spectroscopy was suggested for the first time to the best of our knowledge Compact Raman LIDAR has been developed in GPI RAS for remote sensing of ocean together with AGAT-concern Light weight and low power consumption make possible to install the device on any vehicle like unmanned aircraft or submarine or underwater robotics platforms S. PERSHIN, V. LEDNEV, R. YULMETOV, V. KLINKOV, A. BUNKIN, Applied Optics, 54(19), 5943 (2015)

44. GPI RAS 44 Optical technique is forbidden by snow layer compact LIDAR for ice thickness and temperature measurements mass: < 2 kg power: < 20 W conditions: -50 to +50 0 C Capabilities Ice thickness measurements: distance to object 0 – 600 m thickness range 0 – 100 m thickness accuracy ± 1 cm Ice temperature profile: sample dimensions 0 – 100 m temperature accuracy ± 0.5 o C spatial resolution 5 cm key features: single photon counting and time-of-flight measurements 0 – 450 m with accuracy 1 cm ice LIDAR water eye-safe LIDAR

45. GPI RAS 45 LIDAR: principles and signals LIght Detecting And Ranging Laser matter interaction: elastic scattering (surface, particles or bubbles, sea floor) Raman scattering (H 2 O molecules, dissolved salts ) fluorescence (distributed organic material, chlorophyll a)

46. GPI RAS 46 Thank you for your attention

47. GPI RAS 47 Lidar Remote Sensing Applications: 1. Bathymetry 2. Temperature measurements 3. Ecology monitoring (oil leaks detection or other contaminations) 4. Biology applications (chlorophyll concentrations)

48. GPI RAS 48 Ice mechanics Ice properties: thickness temperature density age and history ice mechanical properties port and ocean engineering

49. GPI RAS 49 Snow Characterization by Raman spectra Raman spectra for different snow layers (a) and detailed OH-band profile (b): fresh snow (black), snow cover (red) and old snow (blue)

50. GPI RAS 50 Ice thickness measurements by Raman&Rayleigh scattering technique with compact Lidar S.M. Pershin, V.N. Lednev,, R.N. Yulmetov, A.F. Bunkin and M.Ya. Grishin Prokhorov General Physics Institute Russian Academy of Sciences

51. GPI RAS 51 Bathymetry by LIDAR LIDAR bathymetry 1. express mapping 2. ground and underwater mapping 3. no needs for water contact