Reanalyses Suitable for Characterizing Long-Term Trends

Reanalyses are, by a substantial margin, the most utilized climate data products, and they are applied in a myriad of different contexts. Despite their popularity, there are substantial concerns about their suitability for the monitoring of long-term climate trends. This has led to calls for a truly “climate quality” reanalysis that retains long-term trend fidelity. The authors contend that for such a reanalysis to be achieved, a substantial rethinking of the current strategy for producing reanalysis products is required. First, the problem must be defined clearly. Second, the methodology that is employed must be reconsidered so as to minimize potential nonclimatic artifacts and robustly ascertain the inevitable residual uncertainty. Finally, a set of validation data and metrics must be constructed that the community can use to compare and unambiguously assess the claims of climate quality. The purpose of this essay is very much to initiate discussions to this end rather than to prescribe solutions.

[1]  S. Sherwood,et al.  Robust Tropospheric Warming Revealed by Iteratively Homogenized Radiosonde Data , 2008 .

[2]  Carl A. Mears,et al.  Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders , 2009 .

[3]  S. Hagemann,et al.  Can climate trends be calculated from reanalysis data , 2004 .

[4]  M. Webb,et al.  Quantification of modelling uncertainties in a large ensemble of climate change simulations , 2004, Nature.

[5]  Peter W. Thorne,et al.  Revisiting radiosonde upper air temperatures from 1958 to 2002 , 2005 .

[6]  Jean-Noël Thépaut,et al.  An improved general fast radiative transfer model for the assimilation of radiance observations , 2004 .

[7]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[8]  Atmospheric Reanalyses and Climate Variations , 2008 .

[9]  E. Källén,et al.  Vertical structure of recent Arctic warming , 2008, Nature.

[10]  Jeffrey S. Whitaker,et al.  Feasibility of a 100-Year Reanalysis Using Only Surface Pressure Data , 2006 .

[11]  A. Hollingsworth,et al.  The response of numerical weather prediction systems to fgge level iib data. Part I: Analyses , 1985 .

[12]  Andrew C. Lorenc,et al.  Objective quality control of observations using Bayesian methods. Theory, and a practical implementation , 1988 .

[13]  John R. Christy,et al.  UNCERTAINTIES IN CLIMATE TRENDS Lessons from Upper-Air Temperature Records , 2005 .

[14]  C. Danforth,et al.  Estimating and Correcting Global Weather Model Error , 2007 .

[15]  K. Koltermann,et al.  How much is the ocean really warming? , 2007 .

[16]  J. Willis,et al.  Recent cooling of the upper ocean , 2006 .

[17]  Arlindo da Silva,et al.  Data assimilation in the presence of forecast bias , 1998 .

[18]  S. Kobayashi,et al.  The JRA-25 Reanalysis , 2007 .

[19]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[20]  V. John,et al.  Temperature and humidity biases in global climate models and their impact on climate feedbacks , 2007 .

[21]  L. Bengtsson,et al.  FGGE 4-dimensional Data Assimilation at ECMWF , 1982 .

[22]  Nils Wedi,et al.  Comparison of trends and low-frequency variability in CRU, ERA-40, and NCEP//NCAR analyses of surface air temperature , 2004 .

[23]  Paul Poli,et al.  Diagnosis of observation, background and analysis‐error statistics in observation space , 2005 .

[24]  D. Dee,et al.  Variational bias correction of satellite radiance data in the ERA‐Interim reanalysis , 2009 .

[25]  E. Kalnay,et al.  Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter , 2009 .

[26]  Christopher M. Danforth,et al.  Accounting for Model Errors in Ensemble Data Assimilation , 2009 .

[27]  Elizabeth C. Kent,et al.  Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century , 2003 .

[28]  L. Haimberger,et al.  Recent Arctic warming vertical structure contested , 2008, Nature.

[29]  Leopold Haimberger,et al.  Toward Elimination of the Warm Bias in Historic Radiosonde Temperature Records—Some New Results from a Comprehensive Intercomparison of Upper-Air Data , 2008 .

[30]  D. Dee.  On-line Estimation of Error Covariance Parameters for Atmospheric Data Assimilation , 1995 .

[31]  P. Thorne.  Arctic tropospheric warming amplification? , 2008, Nature.

[32]  Leopold Haimberger,et al.  Critically Reassessing Tropospheric Temperature Trends from Radiosondes Using Realistic Validation Experiments , 2009 .

[33]  Thomas C. Peterson,et al.  Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC): A new data set of large‐area anomaly time series , 2005 .

[34]  Russell S. Vose,et al.  Overview of the Integrated Global Radiosonde Archive , 2006 .

[35]  Richard B. Rood,et al.  An assimilated dataset for Earth science applications , 1993 .

[36]  Q. Fu,et al.  Arctic warming aloft is data set dependent , 2008, Nature.