Bosilovich, Michael G.

Roberts, Jason B.

Robertson, Franklin R.

NASA Technical Reports Server

Consistency Checks
Reanalysis Ensemble                       LSM Ensemble P-ET
Reanalysis Ensemble JOFURO3 E – GPCP P
JOFURO3 E - Wentz V7 P 
Global Ocean Evaporation
SeaFlux-2 HOAPS4 IFREMER4 JOFURO3 OAFlux
• Low-frequency behavior and trends are much greater in
IFREMER4 and HOAPS4 and contrast strongly with OAFlux.
JOFURO3 correlates best to reanalyses.
• SeaFlux algorithm extreme sensitivity to: (1) Earth
Incidence Angle variability and (2) single sensor algorithm
training data coverage.
Ocean / Land Moisture Transport: Estimates from 
Reanalyses, Satellites and Land Surface Models
Franklin R. Robertson1 , Michael G. Bosilovich2 and Jason B. Roberts1
1NASA / Marshall Space Flight Center, Earth Science Office, 320 Sparkman Dr., Huntsville, AL 35805, USA 2NASA / GSFC Global Modeling and Assimilation Office, 880 Greenbelt, Rd, Greenbelt, MD 20771 
Page 3
What are the causes of 
water cycle variations?
Are variations in the global 
and regional water cycle predictable?
How are water and 
nutrient cycles linked?
NEWS Integrated Water and Energy Cycle Research Challenge:
Document and enable improved, observationally-based, predictions of water and energy 
cycle consequences of Earth system variability and change.
The NEWS challenge is global in scale and requires the integration of NASA system components to make 
decisive progress toward the NEWS challenge in an end-to-end program
Time–Dependent Flux Variability over Ocean / Land Domains
Quantities area averaged over 60oN/S Land and Ocean Regions
(units: mm/day, fluxes;  kgm-2, climatology)
Summary Points:
(1) Reanalysis vertically-integrated moisture flux divergence estimates shopw strong
consistency with LSM P-ET estimates, (2) ENSO warm and cold SST events provide primary
interannual signal modulating land ocean moisture exchange, (3) Satellite P - E estimates
over ocean exhibit significantly stronger interannual signals than either reanalyses or
LSMs. Known intercalibration issues with satellite evaporation retrievals are a likely driver.
Alternative Global Ocean Global Ocean Mean Calculation 
§ Changes in ocean evaporation 
anomalies are balanced by precipitation changes and transports to / from land. 
(Atmospheric storage is small on the scales of interest.)
§ Use GPCP v2.3 precipitation (ocean, land and (P-ET)’ from observationally 
constrained Land Surface Models (Robertson et al. 2016; GLEAM 3.0a ET, Martens 
et al. [2016, GMDD]).
E 'OC = P 'OC + P − ET( )'LANDarea∫ δa.
Global SST anomalies  
(rhs scale; shaded, deg C)
Diagnosed Ocean  
Evaporation Anomalies 
60 N/S (12-mo smooth; mm/d)
E: GPCP Ocn Precip + LSM P-ET
GPCP Ocn Precip only (dotted)
E: GPCP Ocn, Land Precip + 
GLEAM 3.0a P-ET
!"# !$∇ & '( )*+,"# = !./01 !$−∇ & '( )*+,./01
3456 = 7456 +!/9:/ 7 −3; <=>?6 +,
@A@B = !$−∇ & '()*+3 −7
Atmospheric 
Reanalyses
•Atmospheric Reanalyses
•Passive Microwave Satellite (Ocean)
•Observationally Constrained Land 
Surface Models
Issues & Challenge:
Vertically-integrated atmospheric transport of moisture
between ocean and land is a fundamental component of the
physical climate system linking the hydrologic and energy
cycles of the planet as well as determining fresh water
availability to the biosphere.
For land / ocean domains and monthly time scales,
vertically-integrated moisture convergence ∫$ −∇ & '( )* ~
P-E; thus, (i) direct estimates of this transport from
reanalysis wind and moisture fields, (ii) E and P from
satellite retrievals and, (iii) E and P from observationally
constrained land surface models relatively independent
information on land /ocean moisture exchange.
Land Surface Model P-ET 
WaterGAP (GPCC precip) Princeton MEaSUREs
GLEAM / MSWEP Earth2Observe
Climatological Annual Cycles (1980-2015)
• On ENSO time scales a strong anti-correlation is present
(warm SSTsà P-ET) and implied reduction in transport of
moisture to land. P-ET also leads global SST maximum.
• P-ET maximum is in NH winter as ET is at a minimum.
Global Ocean Precipitation
GPCP  RSS V7  GPROF 10.2  HOAPS4
Climatological Annual Cycles (1980-2015)
• Strong correlation between oceanic P and SST on ENSO
time scales with more (less) P sequestered over oceans
during warm (cold) events.
• GPROF10.2 and HOAPS4 likely have regime-dependent
sensitivity to frozen precipitation.
Reanalysis                     Global Oceans    
MERRA-2  ERA-I JRA-55
Climatological Annual Cycles (1980-2015)
• Systematic anomalous export of moisture from ocean to
land (land to ocean) during transition to ENSO cold (warm)
events. Moisture export leads global SST minimum.
• Maximum moisture export to land in late NH Winter.
• MERRA-2 climatological values appear biased high.
!$∇ & '()*
!$∇ & '()*
!$∇ & '()*
• Significant agreeme t exists b tween
reanalysis export of moisture from
ocean to land and land P-ET
diagnosed from observationally-
constrained Land Surface Models.
• Warm (cold) ENSO events retard
(enhance) this export.
• Satellite retrievals of E-P over the
global oceans, while consistent in
terms of interannual signals, exhibit
much greater amplitudes. (HOAPS4
and IFREMER E values yield even
more extreme results.
• Known systematic biases in satellite
Qs-qa signals used in bulk formula
retrievals are a major source of the
large amplitude E-P signals.
Global SST anomalies  
(rhs scale; shaded, deg C)
Global SST anomalies  
(rhs scale; shaded, deg C)
Global SST anomalies  
(rhs scale; shaded, deg C)
Global SST anomalies  
(rhs scale; shaded, deg C)
Global SST anomalies  
(rhs scale; shaded, deg C)
Global SST anomalies  
(rhs scale; shaded, deg C)
Atmospheric Moisture Budget and
Complementary Data Sources
Climatological Mean Water Cycle
NASA / GSFC
https://ntrs.nasa.gov/search.jsp?R=20190000319 2019-08-30T05:12:08+00:00Z


Ocean / Land Moisture Transport: Estimates from Reanalyses, Satellites and Land Surface Models

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