Presentation is loading. Please wait.

Presentation is loading. Please wait.

Mixed Layer Depth in the Arctic Seas in observations and models

Published byAlexandra Johns Modified over 6 years ago

Similar presentations

Presentation on theme: "Mixed Layer Depth in the Arctic Seas in observations and models"— Presentation transcript:

1 Mixed Layer Depth in the Arctic Seas in observations and models
The seasonal cycle of Mixed Layer Depth in the Arctic Seas in observations and models Michael Steele Mark Wensnahan Jinlun Zhang Polar Science Center Applied Physics Laboratory University of Washington & NCAR, NOC, NPS, AWI…

2 Phytoplankton Growth = Primary Production depends on…
Michael Steele Polar Science Center / APL University of Washington Phytoplankton Growth = Primary Production depends on… light lead deep MLD: light deficit? shallow MLD: nutrient deficit? nutrients Skyllingstad & Denbo, 1998

3 Def’n: Mixed Layer Depth
Michael Steele Polar Science Center / APL University of Washington Def’n: Mixed Layer Depth MLD  Max “gradient method” …less common: requires smoothing more complicated etc  = 0.05 0.125  z 0.2 0.3  z Depth (m)  0-10m 2) 0-10m +  “increment method” …more common: easier! Sigma-theta (kg/m3)

4 Def’n: Mixed Layer Depth
Michael Steele Polar Science Center / APL University of Washington Def’n: Mixed Layer Depth MLD  Max “gradient method” …less common: requires smoothing more complicated etc  = 0.05 0.125  z 0.2 0.3  z Depth (m)  0-10m 2) 0-10m +  “increment method” …more common: easier! Sigma-theta (kg/m3)

5 Part 1: World Ocean Database’05 (Observed Profiles)

6 Profile data: obs. by month and 3-year bins
1980s & 90s CTD Bottles Profiling floats Buoys 1960s J F M A M J J A S O N D Month # obs

7 Profile data: obs. by month and 3-year bins
1980s & 90s late spring CTD Bottles Profiling floats Buoys 1960s summer J F M A M J J A S O N D Month # obs

8 # profiles per 100 km EASE grid cell
185,020 81,288 # profiles Good profiles Rejected profiles

9 Reasons for rejection # rejected 1 5 No data above 10 m
15 50 200 1000 No data above 10 m <4 pts in profile # rejected unstable profile No data below 10 m

10 Monthly MLD (m) >1000 m ~10 m March June September November 1000
400 150 75 25 10 >1000 m few data in Arctic Ocean September November ~10 m

11 Regional Means Russia Russia Alaska

12 Central Arctic Ocean cute lil’ sine wave ~25% MLD (m) St. Dev / MLD
120 80 40 % total % 2000 1990 1980 1970 1960 1950 MLD (m) cute lil’ sine wave 0.6 0.4 0.2 ~25% St. Dev / MLD J F M A M J J A S O N D J F M A M J J A S O N D Month Month

13 Greenland-Iceland-Norwegian Seas
120 80 40 % total % 2000 1990 1980 1970 1960 1950 MLD (m) 0.6 0.4 0.2 ~50% ! St. Dev / MLD J F M A M J J A S O N D J F M A M J J A S O N D Month Month

14 Part 2: PIOMAS Model & …some CCSM

15 PIOMAS: daily vs. monthly MLD
output 5 -5 -10 -15 -20 MLD  MLD using T,Smonth minus MLD using T,Sday MLD (m) -0.1 -0.2 -0.3 -0.4 -0.5 MLD MLDmon , MLDday Monthly mean output: underestimates MLD by < ~15 m or < ~50% J F M A M J J A S O N D Month

16 models have a larger seasonal cycle amplitude relative to WOD.
WOD vs. PIOMAS vs. CCSM Models: monthly means over > 50 years 20 40 60 80 Region 10: central Arctic Ocean WOD MLD (m) CCSM In most regions, models have a larger seasonal cycle amplitude relative to WOD. PIOMAS J F M A M J J A S O N D Month

17 models have a larger seasonal cycle amplitude relative to WOD.
WOD vs. PIOMAS vs. CCSM Models: monthly means over > 50 years 20 40 60 80 Region 10: central Arctic Ocean ? WOD MLD (m) CCSM In most regions, models have a larger seasonal cycle amplitude relative to WOD. Salt rejection in leads? refs: Smith, Nguyen, Jin PIOMAS J F M A M J J A S O N D Month

18 WOD vs. PIOMAS vs. CCSM PIOMAS CCSM WOD In Nordic Seas, (?!?)
monthly means 100 200 300 400 Region 7: GIN Sea PIOMAS MLD (m) CCSM WOD In Nordic Seas, (?!?) J F M A M J J A S O N D Month

19 PIOMAS vs. WOD vs. CCSM PIOMAS ~zE CCSM WOD In Nordic Seas, (?!?)
monthly means 100 200 300 400 Region 7: GIN Sea PIOMAS ~zE MLD (m) CCSM WOD In Nordic Seas, (?!?) 300 m! … but it’s all below the euphotic depth zE J F M A M J J A S O N D Month

20 Multi-year PIOMAS monthly means MLD (m) Region 1: Beaufort Sea
10 20 30 40 50 60 MLD (m) Region 1: Beaufort Sea

21 Summary To do list MLD stdev / MLD = 25-50%
Monthly model output underestimates MLD <~50% Not shown: MLD  stratification below the MLD To do list Optimal increment? More models Interannual variability

22 ESS + Laptev Seas

23 Beaufort Sea

24 PIOMAS (monthly model) vs. WOD (obs.)
80 40 60 Region 10: central Arctic Ocean MLD (m) J F M A M J J A S O N D Month

25 PIOMAS (monthly model) vs. WOD (obs.)
Region 7: GIN Sea

26 Data Sets WOD’05 Original profile data: require T & S
(early 1900s-present)  poor winter, central Arctic Ocean coverage PIOMAS Jinlun Zhang’s ice-ocean model (daily ) (monthly ) excellent coverage everywhere! CCSM & other models… (monthly…)

Download ppt "Mixed Layer Depth in the Arctic Seas in observations and models"

Similar presentations

1 ICES/NAFO Symposium Santander May 11 2011 Seasonal to interannual variability of temperature and salinity in the Nordic Seas: heat and freshwater budgets.

1 ICES/NAFO Symposium Santander May Seasonal to interannual variability of temperature and salinity in the Nordic Seas: heat and freshwater budgets.
Mixed layer depth variability and phytoplankton phenology in the Mediterranean Sea H. Lavigne 1, F. D’Ortenzio 1, M. Ribera d’Alcalà 2, H. Claustre 1 1.Laboratoire.

Mixed layer depth variability and phytoplankton phenology in the Mediterranean Sea H. Lavigne 1, F. D’Ortenzio 1, M. Ribera d’Alcalà 2, H. Claustre 1 1.Laboratoire.
Salt rejection, advection, and mixing in the MITgcm coupled ocean and sea-ice model AOMIP/(C)ARCMIP / SEARCH for DAMOCLES Workshop, Paris Oct 29-31, 2007.

Salt rejection, advection, and mixing in the MITgcm coupled ocean and sea-ice model AOMIP/(C)ARCMIP / SEARCH for DAMOCLES Workshop, Paris Oct 29-31, 2007.
Michael Steele Polar Science Center / APL University of Washington Oct 3, 2007 SASS Mtg, Alexandria, VA Collaborative Research: A Heat Budget Analysis.

Michael Steele Polar Science Center / APL University of Washington Oct 3, 2007 SASS Mtg, Alexandria, VA Collaborative Research: A Heat Budget Analysis.
Chukchi/Beaufort Seas Surface Wind Climatology, Variability, and Extremes from Reanalysis Data: 1979- 2009 Xiangdong Zhang, Jeremy Krieger, Paula Moreira,

Chukchi/Beaufort Seas Surface Wind Climatology, Variability, and Extremes from Reanalysis Data: Xiangdong Zhang, Jeremy Krieger, Paula Moreira,
Circulation in the “Freshwater Switchyard” of the Arctic Ocean Michael Steele Polar Science Center, APL/UW Peter Schlosser & Bill Smethie Lamont-Doherty.

Circulation in the “Freshwater Switchyard” of the Arctic Ocean Michael Steele Polar Science Center, APL/UW Peter Schlosser & Bill Smethie Lamont-Doherty.
Modeling Bowhead Whale Habitat: Integration of Ocean Models with Satellite, Biological Survey and Oceanographic Data Dan Pendleton, NOAA / NEAq Jinlun.

Modeling Bowhead Whale Habitat: Integration of Ocean Models with Satellite, Biological Survey and Oceanographic Data Dan Pendleton, NOAA / NEAq Jinlun.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Satellite Observations of Seasonal Sediment Plume in the Central East China.

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Satellite Observations of Seasonal Sediment Plume in the Central East China.
EGU 2012, Kristine S. Madsen, High resolution modelling of the decreasing Arctic sea ice Kristine S. Madsen, T.A.S. Rasmussen, J. Blüthgen and.

EGU 2012, Kristine S. Madsen, High resolution modelling of the decreasing Arctic sea ice Kristine S. Madsen, T.A.S. Rasmussen, J. Blüthgen and.
Ensemble-variational sea ice data assimilation Anna Shlyaeva, Mark Buehner, Alain Caya, Data Assimilation and Satellite Meteorology Research Jean-Francois.

Ensemble-variational sea ice data assimilation Anna Shlyaeva, Mark Buehner, Alain Caya, Data Assimilation and Satellite Meteorology Research Jean-Francois.
NABOS: observational program in the high Arctic Vladimir Ivanov IARC UAF, Fairbanks, Alaska, USA AARI, St. Petersburg, Russia Summer school onboard R/V.

NABOS: observational program in the high Arctic Vladimir Ivanov IARC UAF, Fairbanks, Alaska, USA AARI, St. Petersburg, Russia Summer school onboard R/V.
Arctic Sea Ice and the Ice-Albedo Feedback Harry Stern, Polar Science Center, University of Washington, Seattle Climate Complexity Workshop 2012 May 9,

Arctic Sea Ice and the Ice-Albedo Feedback Harry Stern, Polar Science Center, University of Washington, Seattle Climate Complexity Workshop 2012 May 9,
Climate Forecasting Unit Arctic Sea Ice Predictability and Prediction on Seasonal-to- Decadal Timescale Virginie Guemas, Edward Blanchard-Wrigglesworth,

Climate Forecasting Unit Arctic Sea Ice Predictability and Prediction on Seasonal-to- Decadal Timescale Virginie Guemas, Edward Blanchard-Wrigglesworth,
Dr. Lawson Brigham Deputy Director and Alaska office Director, US Arctic Research Commission PhD. (Cambridge, 2000) M.S. (Rensselear Polytechnic Inst.,

Dr. Lawson Brigham Deputy Director and Alaska office Director, US Arctic Research Commission PhD. (Cambridge, 2000) M.S. (Rensselear Polytechnic Inst.,
Stratification on the Eastern Bering Sea Shelf, Revisited C. Ladd 1, G. Hunt 2, F. Mueter 3, C. Mordy 2, and P. Stabeno 1 1 Pacific Marine Environmental.

Stratification on the Eastern Bering Sea Shelf, Revisited C. Ladd 1, G. Hunt 2, F. Mueter 3, C. Mordy 2, and P. Stabeno 1 1 Pacific Marine Environmental.
Introduction The environmental factors such as light, temperature and nutrients interact with each other in the marine environment and play a major role.

Introduction The environmental factors such as light, temperature and nutrients interact with each other in the marine environment and play a major role.
Nature’s Density Column. Nature creates its own density column Example: The Bering Sea As you discovered in your experiment, when ice melts it forms a.

Nature’s Density Column. Nature creates its own density column Example: The Bering Sea As you discovered in your experiment, when ice melts it forms a.
From Ocean Sciences at the Bedford Institute of Oceanography Temperature – Salinity for the Northwest.

From Ocean Sciences at the Bedford Institute of Oceanography Temperature – Salinity for the Northwest.
WHOI -- AOMIP 10/20/2009 Formation of the Arctic Upper Halocline in a Coupled Ocean and Sea-ice Model Nguyen, An T., D. Menemenlis, R. Kwok, Jet Propulsion.

WHOI -- AOMIP 10/20/2009 Formation of the Arctic Upper Halocline in a Coupled Ocean and Sea-ice Model Nguyen, An T., D. Menemenlis, R. Kwok, Jet Propulsion.
The Effect of Light Attenuation in Water Column on Sea Ice Simulations Jinlun Zhang PSC/APL/UW Polar Science Center Jinlun Zhang Synthesis of Primary Productivity.

The Effect of Light Attenuation in Water Column on Sea Ice Simulations Jinlun Zhang PSC/APL/UW Polar Science Center Jinlun Zhang Synthesis of Primary Productivity.

Similar presentations

Ads by Google