scholarly journals Climatology and interannual variability of dynamic variables in multiple reanalyses evaluated by the SPARC Reanalysis Intercomparison Project (S-RIP)

2017 ◽  
Vol 17 (23) ◽  
pp. 14593-14629 ◽  
Author(s):  
Craig S. Long ◽  
Masatomo Fujiwara ◽  
Sean Davis ◽  
Daniel M. Mitchell ◽  
Corwin J. Wright
Keyword(s):  
Trend Detection ◽  
Data Sets ◽  
Temperature Structure ◽  
Climate Data ◽  
Quasi Biennial Oscillation ◽  
Temperature Bias ◽  
Independent Observations ◽  
Intercomparison Project ◽  
Reanalysis Intercomparison ◽  
Good Agreement

Abstract. Two of the most basic parameters generated from a reanalysis are temperature and winds. Temperatures in the reanalyses are derived from conventional (surface and balloon), aircraft, and satellite observations. Winds are observed by conventional systems, cloud tracked, and derived from height fields, which are in turn derived from the vertical temperature structure. In this paper we evaluate as part of the SPARC Reanalysis Intercomparison Project (S-RIP) the temperature and wind structure of all the recent and past reanalyses. This evaluation is mainly among the reanalyses themselves, but comparisons against independent observations, such as HIRDLS and COSMIC temperatures, are also presented. This evaluation uses monthly mean and 2.5° zonal mean data sets and spans the satellite era from 1979–2014. There is very good agreement in temperature seasonally and latitudinally among the more recent reanalyses (CFSR, MERRA, ERA-Interim, JRA-55, and MERRA-2) between the surface and 10 hPa. At lower pressures there is increased variance among these reanalyses that changes with season and latitude. This variance also changes during the time span of these reanalyses with greater variance during the TOVS period (1979–1998) and less variance afterward in the ATOVS period (1999–2014). There is a distinct change in the temperature structure in the middle and upper stratosphere during this transition from TOVS to ATOVS systems. Zonal winds are in greater agreement than temperatures and this agreement extends to lower pressures than the temperatures. Older reanalyses (NCEP/NCAR, NCEP/DOE, ERA-40, JRA-25) have larger temperature and zonal wind disagreement from the more recent reanalyses. All reanalyses to date have issues analysing the quasi-biennial oscillation (QBO) winds. Comparisons with Singapore QBO winds show disagreement in the amplitude of the westerly and easterly anomalies. The disagreement with Singapore winds improves with the transition from TOVS to ATOVS observations. Temperature bias characteristics determined via comparisons with a reanalysis ensemble mean (MERRA, ERA-Interim, JRA-55) are similarly observed when compared with Aura HIRDLS and Aura MLS observations. There is good agreement among the NOAA TLS, SSU1, and SSU2 Climate Data Records and layer mean temperatures from the more recent reanalyses. Caution is advised for using reanalysis temperatures for trend detection and anomalies from a long climatology period as the quality and character of reanalyses may have changed over time.

scholarly journals Climatology and Interannual Variability of Dynamic Variables in Multiple Reanalyses Evaluated by the SPARC Reanalysis Intercomparison Project (S-RIP)

2017 ◽  
Author(s):  
Craig S. Long ◽  
Masatomo Fujiwara ◽  
Sean Davis ◽  
Daniel M. Mitchell ◽  
Corwin J. Wright
Keyword(s):  
Trend Detection ◽  
Data Sets ◽  
Temperature Structure ◽  
Climate Data ◽  
Quasi Biennial Oscillation ◽  
Temperature Bias ◽  
Independent Observations ◽  
Intercomparison Project ◽  
Reanalysis Intercomparison ◽  
Good Agreement

Abstract. Abstract. Two of the most basic parameters generated from a reanalysis are temperature and winds. Temperatures in the reanalyses are derived from conventional (surface and balloon), aircraft, and satellite observations. Winds are both observed by conventional systems, cloud tracked, and derived from height fields which in turn are derived from the vertical temperature structure. In this paper we evaluate as part of the SPARC-Reanalysis Intercomparison Project (S-RIP) the temperature and wind structure of all the recent and past reanalyses. This evaluation is mainly between the reanalyses themselves, but comparisons against independent observations such as HIRDLS temperatures are also presented. This evaluation uses monthly mean and 2.5 degree zonal mean data sets and spans the satellite era from 1979–2014. There is very good agreement in temperature seasonally and latitudinally between the more recent reanalyses (CFSR, MERRA, ERA-Interim, JRA-55, and MERRA-2) between the surface and 10 hPa. At lower pressures there is increased variance between these reanalyses that changes with season and latitude. This variance also changes during the time span of these reanalyses with greater variance during the TOVS period (1979–1998) and less variance afterward in the ATOVS period (1999–2014). There is a distinct change in the temperature structure in the middle and upper stratosphere during this transition from TOVS to ATOVS systems. Zonal winds are in greater agreement than temperatures and this agreement extends to lower pressures than the temperatures. Older reanalyses (NCEP/NCAR, NCEP/DOE, ERA-40, JRA-25) have larger temperature and zonal wind disagreement from the more recent reanalyses. All reanalyses to date have issues analysing the Quasi-Biennial Oscillation (QBO) winds. Comparisons with Singapore QBO winds show disagreement in the amplitude of the westerly and easterly anomalies. The disagreement with Singapore winds improves with the transition from TOVS to ATOVS observations. Temperature bias characteristics determined via comparisons with a Reanalysis Ensemble Mean (MERRA, ERA-Interim, JRA-55) are similarly observed when compared with Aura/HIRDLS and Aura/MLS observations. There is good agreement between NOAA's TLS, SSU1 and SSU2 Climate Data Records and layer mean temperatures from the more recent reanalyses. Caution is advised for using reanalysis temperatures for trend detection.

scholarly journals Chemistry-climate model SOCOL: a validation of the present-day climatology

2005 ◽  
Vol 5 (6) ◽  
pp. 1557-1576 ◽  
Author(s):  
T. Egorova ◽  
E. Rozanov ◽  
V. Zubov ◽  
E. Manzini ◽  
W. Schmutz ◽  
...  
Keyword(s):  
Climate Model ◽  
Middle Atmosphere ◽  
Polar Vortex ◽  
Data Sets ◽  
Climate Data ◽  
Radiation Heating ◽  
Polar Night ◽  
Temperature Bias ◽  
Significant Temperature ◽  
Higher Temperature

Abstract. In this paper we document "SOCOL", a new chemistry-climate model, which has been ported for regular PCs and shows good wall-clock performance. An extensive validation of the model results against present-day climate data obtained from observations and assimilation data sets shows that the model describes the climatological state of the atmosphere for the late 1990s with reasonable accuracy. The model has a significant temperature bias only in the upper stratosphere and near the tropopause at high latitudes. The latter is the result of the rather low vertical resolution of the model near the tropopause. The former can be attributed to a crude representation of radiation heating in the middle atmosphere. A comparison of the simulated and observed link between the tropical stratospheric structure and the strength of the polar vortex shows that in general, both observations and simulations reveal a higher temperature and ozone mixing ratio in the lower tropical stratosphere for the case with stronger Polar night jet (PNJ) and slower Brewer-Dobson circulation as predicted by theoretical studies.

scholarly journals Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems

2017 ◽  
Vol 17 (2) ◽  
pp. 1417-1452 ◽  
Author(s):  
Masatomo Fujiwara ◽  
Jonathon S. Wright ◽  
Gloria L. Manney ◽  
Lesley J. Gray ◽  
James Anstey ◽  
...  
Keyword(s):  
Reanalysis Data ◽  
Research Community ◽  
Data Sets ◽  
Special Issue ◽  
Upper Troposphere ◽  
Climate Research ◽  
Wide Range ◽  
Underlying Causes ◽  
Intercomparison Project ◽  
Reanalysis Intercomparison

Abstract. The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This paper summarizes the motivation and goals of the S-RIP activity and extensively reviews key technical aspects of the reanalysis data sets that are the focus of this activity. The special issue The SPARC Reanalysis Intercomparison Project (S-RIP) in this journal serves to collect research with relevance to the S-RIP in preparation for the publication of the planned two (interim and full) S-RIP reports.

scholarly journals Numerical simulations of oceanic oxygen cycling in the FAMOUS Earth-System model: FAMOUS-ES, version 1.0

2014 ◽  
Vol 7 (1) ◽  
pp. 1453-1476
Author(s):  
J. H. T. Williams ◽  
I. J. Totterdell ◽  
P. R. Halloran ◽  
P. J. Valdes
Keyword(s):  
Climate Model ◽  
Coupled Model ◽  
System Model ◽  
Temperature Structure ◽  
Model Intercomparison ◽  
Oxygen Cycle ◽  
Surface Productivity ◽  
Intercomparison Project ◽  
Oxygen Cycling ◽  
Good Agreement

Abstract. Addition and validation of an oxygen cycle to the ocean component of the FAMOUS climate model are described. Surface validation is carried out with respect to HadGEM2-ES where good agreement is found and where discrepancies are mainly attributed to disagreement in surface temperature structure between the models. The agreement between the models at depth (where observations are also used in the comparison) in the Southern Hemisphere is less encouraging than in the Northern Hemisphere. This is attributed to a combination of excessive surface productivity in FAMOUS' equatorial waters (and its concomitant effect on remineralisation at depth) and its reduced overturning circulation compared to HadGEM2-ES. For the entire Atlantic basin FAMOUS has a circulation strength of 12.7 ± 0.4 Sv compared to 15.0 ± 0.9 for HadGEM2-ES. The HadGEM2-ES data used in this paper were obtained from the online database of the fifth Coupled Model Intercomparison Project, CMIP5 (Taylor et al., 2012).

scholarly journals Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems

2016 ◽  
Author(s):  
Masatomo Fujiwara ◽  
Jonathon S. Wright ◽  
Gloria L. Manney ◽  
Lesley J. Gray ◽  
James Anstey ◽  
...  
Keyword(s):  
Reanalysis Data ◽  
Research Community ◽  
Data Sets ◽  
Special Issue ◽  
Upper Troposphere ◽  
Climate Research ◽  
Wide Range ◽  
Underlying Causes ◽  
Intercomparison Project ◽  
Reanalysis Intercomparison

Abstract. The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This overview paper for the S-RIP special issue summarizes the motivation and goals of the S-RIP activity, and reviews key technical aspects of the reanalysis data sets that are the focus of the S-RIP report.

Direct phase determination in electron crystallography: small organic molecules

1992 ◽  
Vol 50 (2) ◽  
pp. 1166-1167
Author(s):  
Douglas L. Dorset
Keyword(s):  
Organic Molecules ◽  
Data Sets ◽  
Temperature Structure ◽  
3D Analysis ◽  
Intensity Data ◽  
Electron Crystallography ◽  
Phase Determination ◽  
Measured Intensity ◽  
3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

Systematic calculations of energy levels and transitions rates in Mo XXVIII

2020 ◽  
Vol 75 (8) ◽  
pp. 739-747
Author(s):  
Feng Hu ◽  
Yan Sun ◽  
Maofei Mei
Keyword(s):  
Energy Levels ◽  
Oscillator Strengths ◽  
Atomic Data ◽  
Data Sets ◽  
Electron Systems ◽  
Excitation Energies ◽  
Experimental Values ◽  
Qed Effects ◽  
Hyperfine Structures ◽  
Good Agreement

AbstractComplete and consistent atomic data, including excitation energies, lifetimes, wavelengths, hyperfine structures, Landé gJ-factors and E1, E2, M1, and M2 line strengths, oscillator strengths, transitions rates are reported for the low-lying 41 levels of Mo XXVIII, belonging to the n = 3 states (1s22s22p6)3s23p3, 3s3p4, and 3s23p23d. High-accuracy calculations have been performed as benchmarks in the request for accurate treatments of relativity, electron correlation, and quantum electrodynamic (QED) effects in multi-valence-electron systems. Comparisons are made between the present two data sets, as well as with the experimental results and the experimentally compiled energy values of the National Institute for Standards and Technology wherever available. The calculated values including core-valence correction are found to be in a good agreement with other theoretical and experimental values. The present results are accurate enough for identification and deblending of emission lines involving the n = 3 levels, and are also useful for modeling and diagnosing plasmas.

PWA OF πN SCATTERING WITH FIXED-t DISPERSION RELATIONS

2005 ◽  
Vol 20 (08n09) ◽  
pp. 1810-1813
Author(s):  
PEKKO PIIROLA ◽  
M. E. SAINIO
Keyword(s):  
Data Base ◽  
Forward Direction ◽  
Dispersion Relations ◽  
Data Sets ◽  
Coupling Constant ◽  
Partial Waves ◽  
Scattering Measurements ◽  
Pion Nucleon ◽  
Good Agreement

The πN scattering measurements from last couple of decades are not in very good agreement with each other. In fact, using the different data sets one finds different values for the pion-nucleon coupling constant. An analysis with theoretical constraints is the only way to produce accurate partial waves. In this analysis, the fixed-t dispersion relations are used to ensure analyticity in the invariant amplitudes and to decrease the effects of inaccuracies in the data base. Pietarinen's expansion is the method used to enforce the dispersion constraints. The strength of the analyticity constraints is illustrated with C± amplitudes in the forward direction.

Comparison of Small-Angle Neutron Scattering of δ' Precipitation in an Al–Li Alloy at a High-Flux Reactor and at a Pulsed-Neutron Source

1997 ◽  
Vol 30 (5) ◽  
pp. 602-606 ◽  
Author(s):  
G. Albertini ◽  
F. Carsughi ◽  
R. Coppola ◽  
R. K. Heenan ◽  
M. Stefanon
Keyword(s):  
Neutron Scattering ◽  
Small Angle ◽  
Small Angle Neutron Scattering ◽  
Size Distribution Function ◽  
Data Sets ◽  
Flux Reactor ◽  
Average Size ◽  
Pulsed Neutron ◽  
Pulsed Neutron Source ◽  
Good Agreement

Two different small-angle neutron scattering (SANS) facilities, the D11 camera at the Institut Laue–Langevin (ILL, Grenoble, France) and the LOQ time-of-flight diffractometer at the Rutherford Appleton Laboratory (RAL, Didcot, Oxon, England), were used in the investigations of δ′-Al3Li precipitation at 463 K in Al–Li 3% alloy. The results obtained from the steady-state reactor and from the pulsed source by using two different data-acquisition techniques and two different procedures for data analysis are compared. The SANS curves for the same set of samples investigated using the two different instruments are in good agreement within the experimental uncertainties. A check was also made on the metallurgically relevant quantities, namely the average size and the size-distribution function of the δ′ precipitates at the various stages of the ageing process, obtained from the two sets of SANS curves by applying the same numerical method. Good agreement was found between the results from the two data sets.

Data-model Comparison for the mid-Pliocene Warm Period

2021 ◽  
Author(s):  
Julia Tindall ◽  
Alan Haywood ◽  
Ulrich Salzmann ◽  
Aisling Dolan
Keyword(s):  
Data Model ◽  
Model Comparison ◽  
Surface Air Temperature ◽  
High Latitudes ◽  
Orbital Forcing ◽  
Local Site ◽  
Modern Analogue ◽  
Intercomparison Project ◽  
Global Mean ◽  
Good Agreement

<p>Modelling results from PlioMIP2 (the Pliocene Model Intercomparison Project Phase 2) focussing on MIS KM5c; ~3.205Ma, suggest that global mean surface air temperature was 1.7 – 5.2 °C higher than the preindustrial.  This warming was amplified at the poles and over land.  The results are in reasonable agreement with paleodata over the ocean.   </p><p>Over the land the situation is more complicated.  Model and data are in very good agreement at lower latitudes, however at high latitudes an initial data-model comparison shows much warmer mPWP temperatures from data than from models.   </p><p>Here we consider possible reasons for this data-model discord at high latitudes.  These include uncertainties in model boundary conditions (such as CO<sub>2 </sub>and orbital forcing), and whether there are local site-specific conditions which need to be accounted for.  We also show that the seasonal cycle in mPWP temperatures at these high latitude sites has no modern analogue.  This could lead to inaccuracies when comparing model derived mean annual temperatures with quantitative climatic estimates from palaeobotanical data using Nearest Living Relative methods.</p>

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