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The SPARC Reanalysis Intercomparison Project (S-RIP):
A (Brief) Overview of the Interim Report
Jonathon Wright Tsinghua University, Beijing, China
Masatomo Fujiwara Hokkaido University, Sapporo, Japan
Gloria Manney NorthWest Research Associates, Socorro, New Mexico, USA
New Mexico Institute of Mining & Technology, Socorro, New Mexico, USA
Lesley Gray Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, UK
NERC National Centre for Atmospheric Science (NCAS), Leeds, UK
Craig Long Climate Prediction Center, NCEP/NOAA, College Park, Maryland, USA
Sean Davis Earth System Research Laboratory, NOAA, Boulder, Colorado, USA
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA
Michaela Hegglin Department of Meteorology, University of Reading, Reading, UK
The S-RIP Activity
Multiple studies have identified substantial differences amongst reanalyses with respect to key variables and diagnostics. For example: • Stratospheric winds and temperatures • Diabatic heating, residual circulation, dynamical consistency • Responses to internally generated and externally forced variability
(diurnal cycle, ENSO, QBO, volcanic eruptions, 11-year solar cycle) • Wave activity and mixing, both vertical and lateral • Transport model simulations of stratospheric water vapour, ozone, and
age of air • Stratosphere–troposphere coupling • Polar processes in the troposphere and stratosphere • Tropical cyclone activity and influences A working list of these and other studies can be found on the S-RIP website: http://s-rip.ees.hokudai.ac.jp/pubs/intercomp.html
Motivation
The S-RIP Activity Objectives
S-RIP is a coordinated SPARC-supported activity to: • compare all (or some of the newer) reanalysis data sets for key
diagnostics • identify and understand the causes of differences amongst reanalyses • provide guidance on the appropriate usage of various reanalysis
products in scientific studies • establish collaborative links between reanalysis centres and the
SPARC community • contribute to future improvements in reanalysis products S-RIP focuses on reanalysis outputs in the stratosphere, upper troposphere and lower mesosphere, and is closely connected with the SPARC Data Assimilation (SPARC-DA) activity
The S-RIP Report Interim Report
An S-RIP interim report (intended publication 2016) will include basic information: • Chapter 1: Introduction to the S-RIP activity
M. Fujiwara, G. Manney, L. Gray
• Chapter 2: Description of the reanalysis systems J. Wright, M. Fujiwara, C. Long
• Chapter 3: Climatology & interannual variability of dynamical variables C. Long, M. Fujiwara
• Chapter 4: Climatology & interannual variability of ozone and water vapor M. Hegglin, S. Davis
T & winds
O3 & H2O
3
4
equator winter hemispheresummer hemisphere
11 USLM
troposphere
stratosphere
mesosphere
ExUTLS7TTL8
6
Stratosphere–tropospherecoupling
QBO &tropical
variability 9
10
Polarprocesses
5
Brewer–Dobsoncirculation
The S-RIP Report Full Report
Interim Report Chapter 2: Description of the reanalysis systems
• Basic details: history, temporal coverage, reference publications, etc. • Forecast model descriptions:
• Model vintage, horizontal and vertical grids, model top • Key physical parametrizations: radiation, convective and non-convective clouds,
gravity wave drag, prognostic ozone • Boundary conditions: SSTs and sea ice, treatment of aerosols and trace gases,
total solar irradiance • Data assimilation strategies and implementations:
• Introduction to strategies used by recent and current reanalysis systems: 3D-Var, 3D-FGAT, 4D-Var, EnKF
• Key differences in implementation: first guess interpolation, IAU, assimilation windows, use of ensembles
• Input observations: • Conventional data: surface records, radiosondes, aircraft measurements • Satellite data: radiances, retrievals, atmospheric motion vectors • Common data screening criteria and bias correction strategies • Input observation timelines for the newest full-input reanalyses
• Common misconceptions and points of confusion • CFSR / CFSv2 transition and differences • Origins and usage of MERRA / MERRA-2 IAU products
Interim Report Chapter 2: Forecast model descriptions
example: vertical grid spacing
log-p altitude: z* = H ln(p0/p) surface pressure p0: 1000 hPa scale height H: 7 km
full grid zoomed grid
example product pressure levels (ERA-Interim / ERA-40)
Interim Report Chapter 2: Data assimilation strategies and implementations
JRA-25/JCDAS
NCEP R1 & R2 ERA-40 CFSR/CFSv2 MERRA & MERRA-2
JRA-55 ERA-Interim ERA-20C
20CR
example: strategies
Interim Report Chapter 2: Input observations
example: satellite radiances
Blue ERA-Interim
Purple JRA-55
Dark red MERRA
Light red MERRA-2
Green CFSR
Interim Report Chapter 3: Climatology and interannual variability of dynamic variables
• Approach • Construct a reanalysis ensemble mean (MERRA, ERA-Interim, JRA-55) • “Atlas” of climatologies and temporal evolution of temperature and winds • Evaluation against independent observations
• Temperature evaluation • Recent reanalyses agree well at and below 10 hPa, especially during the
ATOVS period (post-1998) • Biases in earlier reanalyses (JRA-25, ERA-40, NCEP R1/R2) are larger, more
persistent, and extend through a deeper vertical layer • All reanalyses contain temporal discontinuities associated with the transition
from TOVS (SSU+MSU) to ATOVS (AMSU), especially at p ≤ 10 hPa • CFSR also contains several discontinuities associated with production stream
changes and a warm bias in the upper stratosphere • JRA-55 contains a year-round cold bias in the upper stratosphere
• Zonal wind evaluation • Available independent observations are much more limited • Discrepancies are largest in the upper and middle stratosphere, especially in
the equatorial region (disagreements in phase and amplitude of QBO) • Large differences in the amplitude of the semi-annual oscillation (SAO) • General agreement in high latitudes at p > 10 hPa amongst newer reanalyses
Interim Report Chapter 3: Interannual variability of temperature anomalies (global)
Be very careful about using reanalyses for trend studies!
Figure 17
a)
b)
c)
d)
e)
f)
g)
h)
Interim Report Chapter 3: Climatology and interannual variability of temperature (10°S–10°N)
ensemble: ERA-Interim + JRA-55 + MERRA
(a) CFSR
(b) MERRA
(c) ERA-Interim
(d) JRA-55
(e) MERRA-2
seasonal cycle time series (1979–2014)
Interim Report Chapter 3: Climatology and interannual variability of zonal winds (10°S–10°N)
Figure 20
a)
b)
c)
d)
e)
f)
g)
h)
ensemble: ERA-Interim + JRA-55 + MERRA
(a) CFSR
(b) MERRA
(c) ERA-Interim
(d) JRA-55
(e) MERRA-2
seasonal cycle time series (1979–2014)
Interim Report Chapter 4: Climatology and interannual variability of ozone
• Treatment of ozone • All of the reanalysis systems except for NCEP R1 and R2 include some form of
prognostic ozone parametrization and analysis, but none of these include heterogeneous chemistry (use with caution for ozone hole studies)
• To date, only satellite ozone retrievals are assimilated (no ozonesondes) • Input observations vary widely, from total column only (JRA-25 and JRA-55) to
coarse-resolution profile information (ERA-40, MERRA, CFSR) to a broad selection of satellite products (ERA-Interim)
• ECMWF reanalyses use climatologies rather than analyses for radiation calculations
• Key conclusions and observational evaluation • Climatologies, annual cycles and interannual variability generally agree well
with observational data, despite some issues in JRA-25 and ERA-40 • Total column ozone is mostly captured by reanalyses, with some limitations
(e.g., no TCO data during polar night) • The ozone vertical distribution is weakly constrained by data assimilation, so
that mean biases in ozone products vary with height (10~50% in stratosphere) • QBO signals are vastly improved in JRA-55 relative to JRA-25 • All reanalyses fail to capture the “ozone valley” associated with the Asian
monsoon anticyclone
Interim Report Chapter 4: Seasonal cycles of UTLS ozone in three latitude bands
50 hPa
100 hPa
250 hPa
Interim Report Chapter 4: Climatology and interannual variability of water vapour
• Treatment of water vapour • Reanalysis WV is a function of dehydration, transport, and for some reanalyses
methane oxidation (ERA-40, ERA-Interim, ERA-20C), ice supersaturation (ERA-Interim and ERA-20C), and/or relaxation to climatology (MERRA and MERRA-2)
• Data assimilation has limited or no influence in the stratosphere (specification and treatment of the upper bound varies)
• Fields used for radiation calculations in the stratosphere often differ from reanalysis products
• Key conclusions and observational evaluation • Moderate agreement amongst reanalyses in the UTLS • Major issues in JRA-55 at mid–high latitudes and pressures less than 200 hPa • CFSR is very dry (with some negative mixing ratios) in the stratosphere • Comparison of transport simulations and tape recorder signals reveals several
important discrepancies in circulation and temperatures • Reanalysis stratospheric WV should not be used in scientific studies!
Interim Report Chapter 4: Climatology and interannual variability of water vapour
Differences relative to the SPARC Data Initiative multi-instrument mean
seasonal cycle
Common grid data
• Includes CFSR, ERA-Interim, JRA-25, JRA-55, MERRA, and MERRA-2 • Variables: temperature, zonal and meridional winds, ozone, specific
humidity, and geopotential height • Horizontal resolution: gridded 2.5°×2.5° and 2.5° zonal mean • Vertical levels: 1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150,
100, 70, 50, 30, 20, 10, 7, 5, 3, 2, 1, 0.7, 0.5, 0.3, 0.1 hPa (up to 1 hPa are the same as for CMIP5)
• Temporal resolution: monthly mean • Temporal coverage over two periods:
1. Full record that varies by reanalysis (e.g. 1958–2014 for JRA-55) 2. S-RIP common time period: 1979–2013
• Climatological seasonal cycles for 1981–2010 (all reanalyses in one file, along with ensemble mean)
• Ensemble mean excludes MERRA-2
Resources
Further details
• The S-RIP 2016 workshop will be held in Victoria, BC, Canada, on 19–21 October. The SPARC-DA workshop will be held at the same location on 17–19 October, with a one-day joint S-RIP/SPARC-DA session on 19 October. See http://s-rip.ees.hokudai.ac.jp/events/meeting2016/ for more details.
• A reanalysis session, “Evaluating Reanalysis: Learning about past weather and climate”, will be held at the 2016 AGU Fall Meeting in San Francisco, CA, USA during 12–16 December 2016. See https://agu.confex.com/agu/fm16/preliminaryview.cgi/Session13068 for more details.
Upcoming events
Further details
• The S-RIP website may be accessed at http://s-rip.ees.hokudai.ac.jp • Additional details about the project and the report • Contact information for project leads, chapter leads, and reanalysis centres • Links to reanalysis publications and resources
• A special issue entitled “The SPARC Reanalysis Intercomparison Project (S-RIP)” has been opened in ACP: • Review paper containing items from Chapters 1 and 2:
Fujiwara et al. (2016): Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2016-652
• Five other contributed papers to date • Contact Masatomo Fujiwara ([email protected]), Gloria Manney
([email protected]), Lesley Gray ([email protected]), or Jonathon Wright ([email protected])
Additional information
