Dr. Eric Hackert graduated from the University of Wisconsin in 1984 with a M.S. in Meteorology. He joined Center for Ocean-Land-Atmosphere Studies (COLA) at the University of Maryland (UMD) in 1985 where he helped to devise optimal interpolation techniques to assimilate in situ data into an early version of SODA. In May 1989, Eric moved to NASA/Goddard Space Flight Center and worked in the Laboratory for Hydrospheric Processes. In this capacity, he focused on dynamical ocean model development and validation, reduced-space Kalman filter data assimilation, wind sensitivity studies, and data analysis/validation of satellite altimetry. In October 2000, Eric joined Earth System Science Interdisciplinary Center (ESSIC) at the UMD. A main focus during 2000-2008 was the development of the Ensemble Reduced Order Kalman Filter data assimilation technique and subsequent completion of ocean observation sensitivity studies. During 2008-2014, he focused on full utilization of sea surface salinity (SSS) for oceanographic studies. In 2016, Eric received his Ph.D. in Oceanography through the Accomplished Scientist Program at the UMD. His research concentrated on determining the impact of Indian Ocean Sector on El Niño-Southern Oscillation (ENSO) predictability via the oceanic contribution, the atmospheric teleconnection, and via data assimilation. In addition, he confirmed that assimilation of Aquarius satellite SSS improved ENSO predictability.
Since joining the GMAO in Jan 2017, Eric has participated in the development of the ocean data assimilation system (ODAS) that is integrated with the current coupled forecast system. He has contributed to finalizing the optimal version of the reanalysis experiment and he has helped build code to initialize seasonal forecasts. Besides working on developing the ODAS, Eric is currently a principal investigator on the NASA Ocean Salinity Science Team with funding to explore the impacts of satellite SSS on ENSO prediction. He has found that Aquarius and SMAP SSS assimilation leads to more accurate representation of large-scale ocean waves and better ENSO forecasts. Eric will continue to develop and extend methods to assimilate ocean salinity observations into ocean models and use these results to advance scientific understanding of the Earth System. He will continue to study the coupled atmosphere-ocean dynamics of the El Niño-Southern Oscillation phenomenon.
Improving GEOS Seasonal to subseasonal prediction capability, adding SSS relaxation/assimilation, and working towards fully coupled (atmosphere/ocean) assimilation into GEOS_S2S-v3
Role of Sea Surface Salinity (SSS) and subsurface salinity assimilation into ocean/hybrid coupled models using the Ensemble Reduced Order Kalman Filter assimilation technique.
Tropical Pacific Observing System Experiments
Impact of the Indian Ocean on coupled ENSO predictions by both ocean teleconnections and atmospheric bridge
Satellite data analysis - ocean topography/altimetry, sea surface salinity and ocean vector winds
Dynamical ocean modeling, Ensemble Reduced-Order Kalman Filter data assimilation, hybrid coupled modeling, ocean model development and validation, and ocean data analysis
Reduced-space Kalman filter data assimilation into a reduced-gravity dynamical ocean model, observing system simulation experiments (OSSEs) for tropical array design
Satellite altimetry analysis and validation (Geosat to present), wind sensitivity studies, analysis of wind and hydrographic data.
OI data assimilation of hydrographic data into ocean model, quality control analysis on hydrographic data.
• June 2016: PhD Oceanography Atmospheric and Oceanic Sciences, Accomplished Scientist Program, University of Maryland, College Park (Advisor Busalacchi).
• December 1984: M.S. Meteorology, University of Wisconsin, Madison (Advisor Hastenrath).
• May 1982: B.S. Physical Sciences, University of Maryland, College Park.
1/2017
-
Present
Research Oceanographer, Research AST, Oceanographic Studies
GMAO/NASA,
Goddard Space Flight Center, Greenbelt, MD
9/2016
-
Present
Visiting Assistant Research Scientist
ESSIC University of Maryland,
College Park, MD.
10/2000
-
9/2016
Senior Faculty Specialist/Assistant Research Scientist
ESSIC University of Maryland,
College Park, MD.
5/1989
-
10/2000
Principal Scientist/Section Manager
Raytheon ITSS and Lab. for Hydrospheric Processes,
Goddard Space Flight Center, Greenbelt, MD.
2/1985
-
5/1989
Faculty Research Assistant
Center for Ocean, Land and Atmosphere, University of Maryland,
College Park, MD.
04/17/2017 -
04/16/2020
Impacts of Sea Surface Salinity on El Nino/Southern Oscillation Prediction,
NASA Ocean Salinity Science Team, NASA NRA #: NNH16ZDA001N-OSST
PI
;
0.47 FTE
Grant Amount: $402862
03/30/2016 -
03/29/2019
The Role of the Indian Ocean Sector in Prediction of the Coupled Indo-Pacific System,
NASA Physical Oceanography, NASA NRA #: NNX16AH62G
PI (Grant canceled due to leaving ESSIC)
;
0.58 FTE
Grant Amount: $648286
06/01/2012 -
05/31/2016
Role of Off-Equatorial Variability for Decadal Predictability of the Coupled Pacific System,
NASA Physical Oceanography, NASA NRA #: NNX13MA61G
Co-I, Institutional PI
;
0.42 FTE
Grant Amount: $439619
03/01/2009 -
02/28/2013
Spatio-Temporal Variability and Error Structure of Sea Surface Salinity in the Tropics,
NASA Ocean Salinity Science Team, NASA NRA #: NNX09AU74G
Co-I, Institutional PI
;
0.25 FTE
Grant Amount: $659,680
06/01/2008 -
05/31/2011
Application of Scatterometry, Satellite Sea Surface Temperature, and Altimetry Measurements to Improved Understanding and Prediction of Indo-Pacific Coupling,
NASA Physical Oceanography, NASA NRA #: NNX09AF41G
Co-I, Grant Manager
;
0.42 FTE
Grant Amount: $673,337
06/01/2007 -
05/31/2010
Implementation of Satellite Sea Surface Salinity Data into Ocean and Coupled Models,
NASA Physical Oceanography, NASA NRA #: NNX08AI76G
Co-I, Grant Manager
;
0.42 FTE
Grant Amount: $512,682
03/01/2020 -
02/28/2023
Towards Full Utilization of Satellite Sea Surface Salinity for El Niño/Southern Oscillation Prediction,
NASA, NASA NRA #: NNH19ZDA001N-OSST
PI
;
0.32-0.32 FTE
01/01/2020 -
12/31/2023
Effectively constraining both atmosphere and ocean components in an Integrated Earth System Analysis Data Assimilation System,
NASA Modeling and Prediction , NASA NRA #: NNH19ZDA001N-MAP
Co-I
;
0.1 FTE
Refereed
Molod, A. M., E. C. Hackert, Y. V. Vikhliaev, et al. 2020. "GEOS-S2S Version 2: The GMAO high resolution coupled model and assimilation system for seasonal prediction."
Journal of Geophysical Research,
125
(5):
[10.1029/2019JD031767]
Hackert, E. C., R. M. Kovach, A. J. Busalacchi, and J. Ballabrera-Poy. 2019. "Impact of Aquarius and SMAP Satellite Sea Surface Salinity Observations on Coupled El Niño/Southern Oscillation Forecasts."
Journal of Geophysical Research: Oceans,
0
(0):
[10.1029/2019JC015130]
Schollaert Uz, S., A. J. Busalacchi, T. M. Smith, et al. 2017. "Interannual and decadal variability in tropical Pacific chlorophyll from a statistical reconstruction: 1958-2008."
Journal of Climate,
30:
7293-7315
[10.1175/JCLI-D-16-0202.1]
Hackert, E. C., A. J. Busalacchi, J. Carton, et al. 2017. "The role of the Indian Ocean sector for prediction of the coupled Indo-Pacific system: Impact of atmospheric coupling."
Journal of Geophysical Research: Oceans,
122
(4):
2813-2829
[10.1002/2016jc012632]
Hackert, E., A. J. Busalacchi, and J. Ballabrera-Poy. 2014. "Impact of Aquarius sea surface salinity observations on coupled forecasts for the tropical Indo-Pacific Ocean."
Journal of Geophysical Research: Oceans,
119
(7):
4045-4067
[10.1002/2013jc009697]
Hackert, E., J. Ballabrera-Poy, A. J. Busalacchi, R.-H. Zhang, and R. Murtugudde. 2011. "Impact of sea surface salinity assimilation on coupled forecasts in the tropical Pacific."
Journal of Geophysical Research,
116
(C5):
C05009
[10.1029/2010jc006708]
Hackert, E., J. Ballabrera-Poy, A. J. Busalacchi, R.-H. Zhang, and R. Murtugudde. 2007. "Role of the initial ocean state for the 2006 El Niño."
Geophysical Research Letters,
34
(9):
[10.1029/2007gl029452]
Hackert, E., J. Ballabrera-Poy, A. J. Busalacchi, R.-H. Zhang, and R. Murtugudde. 2007. "Comparison between 1997 and 2002 El Niño events: Role of initial state versus forcing."
Journal of Geophysical Research,
112
(C1):
C01005
[10.1029/2006jc003724]
Hackert, E. C., A. J. Busalacchi, and R. Murtugudde. 2001. "A wind comparison study using an ocean general circulation model for the 1997-1998 El Niño."
Journal of Geophysical Research: Oceans,
106
(C2):
2345-2362
[10.1029/1999jc000055]
Hackert, E. C., R. N. Miller, and A. J. Busalacchi. 1998. "An optimized design for a moored instrument array in the tropical Atlantic Ocean."
Journal of Geophysical Research: Oceans,
103
(C4):
7491-7509
[10.1029/97jc03206]
Hackert, E. C., and S. Hastenrath. 1986. "Mechanisms of Java Rainfall Anomalies."
Monthly Weather Review,
114
(4):
745-757
[10.1175/1520-0493(1986)114<0745:mojra>2.0.co;2]
Invited
Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System
11
/
12
/
2018
Ocean Salinity Science Conference, Paris, FR
Other
Observing System Experiments for Evaluating the Impact of Satellite Sea Surface Salinity on Seasonal Predictions from the GMAO S2S System" and "Assessment of Sea Surface Salinity Products Using a Coupled ENSO Prediction Model"
9
/
17
/
2020
How Did We Do: Ocean Prediction of ENSO
6
/
20
/
2020
An Introduction to the NASA GMAO Coupled Atmosphere-Ocean System - GEOS-S2S Version 3 and "Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the NASA/GMAO Seasonal Forecast System"
2
/
12
/
2020
Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System
5
/
7
/
2019
OceanPredict'19 Conference, Halifax, NS
Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System
12
/
14
/
2018
Assessment of Sea Surface Salinity Products Using a Coupled ENSO Prediction Model
11
/
13
/
2018
Ocean Salinity Science Conference, Paris, FR
Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GEOS GMAO S2S Forecast System
9
/
20
/
2018
Second International Conference on Subseasonal to Decadal Prediction, at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, Sept. 20, 2018, author
Impact of Aquarius and SMAP Sea Surface Salinity Observations on Seasonal Predictions of the 2015 El Nino
5
/
3
/
2018
Bridging Sustained Observations and Data Assimilation for TPOS2020, Boulder, CO. May 3, 2018, author.
The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System
3
/
14
/
2018
Surface Ocean Lower Atmosphere Study (SOLAS) Workshop on Remote Sensing, Potomac, MD, Mar. 14 , 2018, author.
Impact of Aquarius and SMAP Sea Surface Salinity Observations on Seasonal Predictions of the 2015 El Nino
2
/
12
/
2018
AGU Ocean Sciences 2018, Portland, OR, Feb. 12, 2018 (poster) coauthor.
The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System
10
/
11
/
2017
Science Directors Seminar, GSFC, Greenbelt, MD
The Impact of Satellite Sea Surface Salinity for Prediction of the Coupled Indo-Pacific System
9
/
18
/
2017
Ocean Salinity Science Team Meeting, Crystal City, VA.
Validation of Aquarius and SMAP Sea Surface Salinity in the Tropics
9
/
18
/
2017
Ocean Salinity Science Team Meeting, Crystal City, VA (poster).
NASA GMAO Seasonal Prediction System (S2S V2.1)
6
/
29
/
2017
COST/Clivar Workshop on Ocean Reanalysis and Intercomparisons, Toulouse, FR.
The Beneficial Impact of Satellite Sea Surface Salinity Observations on El Niño/Southern Oscillation Predictions
8
/
2019
-
Present
What is the Science Question?
Can observing salinity from space improve our seasonal predictions of the El Niño phenomenon?
What are the findings?
Including satellite salinity measurements into the initialization of the ocean state significantly improves our ability to predict the coupled ocean/ atmosphere system. Satellite salinity helps to better define the structure and behavior of the upper layer of the ocean and how it interacts with the atmosphere (winds, precipitation, etc.)
What was the impact?
This inclusion allows us to extend useful predictions of El Niño/Southern Oscillation (ENSO) from 4 months to 7 months. This is very significant!
Why does it matter?
Being able to extend ENSO forecasts allows stakeholders to adequately prepare for environmental extremes like excessive rainfall over the southern U.S. or drought over Australia, Indonesia, and northeast Brazil. For example, having a confident El Niño forecast and given enough warning, planting drought resistant corn seeds in subsistence farming regions could save many lives.
Beneficial Impact on ENSO Predictions of Assimilating Satellite Sea Surface Salinity Observations in GEOS S2S
5
/
2019
-
Present
https://gmao.gsfc.nasa.gov/research/science_snapshots/2019/SSS_assim_ENSO.php
Assimilating satellite sea surface salinity (SSS) from NASA’s Aquarius and SMAP instruments improves the analyses of the near-surface density and the mixed layer depth (MLD). The deeper MLD in the initial conditions in April 2015 (top image) acts to dampen the ENSO Kelvin signal, resulting in improved seasonal forecasts for the 2015 El Niño (bottom).
Including SSS in the analyses increases salinity, causing higher near-surface density within the equatorial waveguide, leading in turn to a deeper MLD that dampens the ENSO signal in the forecasts due to the reduced efficiency of wind forcing on a relatively deeper mixed layer, producing a more realistic forecast of the El Niño event.
Validation of Aquarius and SMAP Sea Surface Salinity in the Tropics
10
/
2017
-
Present
https://gmao.gsfc.nasa.gov/research/science_snapshots/2017/ss_salinity_validation.php
Sea Surface Salinity (SSS) can help to identify the ocean-surface signature of large-scale changes in the hydrological cycle. One example of such a phenomenon is the changes associated with El Niño/Southern Oscillation (ENSO). Using data retrieved from NASA’s Aquarius and Soil Moisture Active/Passive (SMAP) satellites, we can now map global salinity patterns to help scientists better understand the water cycle and its link to climate variations and change, potentially leading to improvements in these processes in the models used to predict seasonal circulation anomalies and longer term changes in the oceans and atmosphere.
In collaboration with NASA’s Ocean Salinity Science Team, the latest versions of Aquarius and SMAP SSS data are being validated. The Aquarium Mission provided observations from September 2011 until June 2015; SMAP began operations in March 2015. Assessing the two data sets together allows researchers to determine if Aquarius and SMAP can be combined to produce a longer time series for use as an SSS climate data record. In this work, the most recent versions of the along-track (Level 2) Aquarius (Version 4.6.1) and SMAP (Version 3.0) SSS retrievals are evaluated against in-situ observations from the National Oceanographic Data Center (NODC) Global Temperature and Salinity Profile Programme (GTSPP). The satellite data uses all standard quality control except for the rain flag. The GTSPP data are made up of the “best” quality-controlled version and contains Argo, CTD, XBT, TAO, PIRATA, and RAMA profiles. Data are validated for Aquarius from August 2011 to June 2015 and for SMAP from March 2015 to April 2017, and the overlap period of the two satellites is from March to June 2015. Matchups are created from in situ observations on the same day and within 1o radius of the satellite data.
American Geophysical Union,
1989
-
Present
Editors Citation for Excellence in Refereeing, JGR Oceans, May 2008
Reviewer for Progress in Oceanography, JGR Oceans, Ocean Modeling, Bulletin of American Meteorology Society, Journal of Marine Research, Monthly Weather Review, Journal of Climate, Remote Sensing of Environment, and Scientific Reports .
NASA Panel Review Committee
Refereed
Molod, A. M., E. C. Hackert, Y. V. Vikhliaev, et al. 2020. "GEOS-S2S Version 2: The GMAO high resolution coupled model and assimilation system for seasonal prediction."
Journal of Geophysical Research
125
(5):
[10.1029/2019JD031767]
Hackert, E. C., R. M. Kovach, A. J. Busalacchi, and J. Ballabrera-Poy. 2019. "Impact of Aquarius and SMAP Satellite Sea Surface Salinity Observations on Coupled El Niño/Southern Oscillation Forecasts."
Journal of Geophysical Research: Oceans
0
(0):
[10.1029/2019JC015130]
Schollaert Uz, S., A. J. Busalacchi, T. M. Smith, et al. 2017. "Interannual and decadal variability in tropical Pacific chlorophyll from a statistical reconstruction: 1958-2008."
Journal of Climate
30
7293-7315
[10.1175/JCLI-D-16-0202.1]
Hackert, E. C., A. J. Busalacchi, J. Carton, et al. 2017. "The role of the Indian Ocean sector for prediction of the coupled Indo-Pacific system: Impact of atmospheric coupling."
Journal of Geophysical Research: Oceans
122
(4):
2813-2829
[10.1002/2016jc012632]
Hackert, E., A. J. Busalacchi, and J. Ballabrera-Poy. 2014. "Impact of Aquarius sea surface salinity observations on coupled forecasts for the tropical Indo-Pacific Ocean."
Journal of Geophysical Research: Oceans
119
(7):
4045-4067
[10.1002/2013jc009697]
Hackert, E., J. Ballabrera-Poy, A. J. Busalacchi, R.-H. Zhang, and R. Murtugudde. 2011. "Impact of sea surface salinity assimilation on coupled forecasts in the tropical Pacific."
Journal of Geophysical Research
116
(C5):
C05009
[10.1029/2010jc006708]
Hackert, E., J. Ballabrera-Poy, A. J. Busalacchi, R.-H. Zhang, and R. Murtugudde. 2007. "Role of the initial ocean state for the 2006 El Niño."
Geophysical Research Letters
34
(9):
[10.1029/2007gl029452]
Hackert, E., J. Ballabrera-Poy, A. J. Busalacchi, R.-H. Zhang, and R. Murtugudde. 2007. "Comparison between 1997 and 2002 El Niño events: Role of initial state versus forcing."
Journal of Geophysical Research
112
(C1):
C01005
[10.1029/2006jc003724]
Hackert, E. C., A. J. Busalacchi, and R. Murtugudde. 2001. "A wind comparison study using an ocean general circulation model for the 1997-1998 El Niño."
Journal of Geophysical Research: Oceans
106
(C2):
2345-2362
[10.1029/1999jc000055]
Hackert, E. C., R. N. Miller, and A. J. Busalacchi. 1998. "An optimized design for a moored instrument array in the tropical Atlantic Ocean."
Journal of Geophysical Research: Oceans
103
(C4):
7491-7509
[10.1029/97jc03206]
Hackert, E. C., and S. Hastenrath. 1986. "Mechanisms of Java Rainfall Anomalies."
Monthly Weather Review
114
(4):
745-757
[10.1175/1520-0493(1986)114<0745:mojra>2.0.co;2]
