Journal articles on the topic 'Atmospheric reanalyses'
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1
Kumar, Arun, Li Zhang, and Wanqiu Wang. "Sea Surface Temperature–Precipitation Relationship in Different Reanalyses." Monthly Weather Review 141, no. 3 (March 1, 2013): 1118–23. http://dx.doi.org/10.1175/mwr-d-12-00214.1.
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Abstract The focus of this investigation is how the relationship at intraseasonal time scales between sea surface temperature and precipitation (SST–P) varies among different reanalyses. The motivation for this work was spurred by a recent report that documented that the SST–P relationship in Climate Forecast System Reanalysis (CFSR) was much closer to that in the observation than it was for the older generation of reanalyses [i.e., NCEP–NCAR reanalysis (R1) and NCEP–Department of Energy (DOE) reanalysis (R2)]. Further, the reason was attributed either to the fact that the CFSR is a partially coupled reanalysis, while R1 and R2 are atmospheric-alone reanalyses, or that R1 and R2 use the observed weekly-averaged SST. The authors repeated the comparison of the SST–P relationship among R1, R2, and CFSR, as well as two recent generations of atmosphere-alone reanalyses, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the ECMWF Re-Analysis Interim (ERA-Interim). The results clearly demonstrate that the differences in the SST–P relationship at intraseasonal time scales across different reanalyses are not due to whether the reanalysis system is coupled or atmosphere alone, but are due to the specification of different SSTs. The SST–P relationship in different reanalyses, when computed against a single SST for the benchmark, demonstrates a relationship that is common across all of the reanalyses and observations.
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Zib, Behnjamin J., Xiquan Dong, Baike Xi, and Aaron Kennedy. "Evaluation and Intercomparison of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic Using BSRN Surface Observations." Journal of Climate 25, no. 7 (March 28, 2012): 2291–305. http://dx.doi.org/10.1175/jcli-d-11-00147.1.
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Abstract With continual advancements in data assimilation systems, new observing systems, and improvements in model parameterizations, several new atmospheric reanalysis datasets have recently become available. Before using these new reanalyses it is important to assess the strengths and underlying biases contained in each dataset. A study has been performed to evaluate and compare cloud fractions (CFs) and surface radiative fluxes in several of these latest reanalyses over the Arctic using 15 years (1994–2008) of high-quality Baseline Surface Radiation Network (BSRN) observations from Barrow (BAR) and Ny-Alesund (NYA) surface stations. The five reanalyses being evaluated in this study are (i) NASA's Modern-Era Retrospective analysis for Research and Applications (MERRA), (ii) NCEP's Climate Forecast System Reanalysis (CFSR), (iii) NOAA's Twentieth Century Reanalysis Project (20CR), (iv) ECMWF's Interim Reanalysis (ERA-I), and (v) NCEP–Department of Energy (DOE)'s Reanalysis II (R2). All of the reanalyses show considerable bias in reanalyzed CF during the year, especially in winter. The large CF biases have been reflected in the surface radiation fields, as monthly biases in shortwave (SW) and longwave (LW) fluxes are more than 90 (June) and 60 W m−2 (March), respectively, in some reanalyses. ERA-I and CFSR performed the best in reanalyzing surface downwelling fluxes with annual mean biases less than 4.7 (SW) and 3.4 W m−2 (LW) over both Arctic sites. Even when producing the observed CF, radiation flux errors were found to exist in the reanalyses suggesting that they may not always be dependent on CF errors but rather on variations of more complex cloud properties, water vapor content, or aerosol loading within the reanalyses.
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Hertzog, Albert, Claude Basdevant, and François Vial. "An Assessment of ECMWF and NCEP–NCAR Reanalyses in the Southern Hemisphere at the End of the Presatellite Era: Results from the EOLE Experiment (1971–72)." Monthly Weather Review 134, no. 11 (November 1, 2006): 3367–83. http://dx.doi.org/10.1175/mwr3256.1.
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Abstract This article estimates the biases and standard deviations of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and the 50-yr National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) Reanalysis (NN50) in the upper troposphere and lower stratosphere in 1971–72. These estimates are obtained by comparing the reanalyzed temperatures and winds with EOLE observations, a dataset collected during 480 superpressure-ballon flights in the Southern Hemisphere (SH). Dedicated algorithms have been developped to control the quality of this dataset and a stringent selection has been performed on the observations. None of the atmospheric centers has assimilated the EOLE dataset, which is therefore fully independent from the reanalyses. It is furthermore argued that the statistics obtained in this study at the end of the presatellite era may be representative of the reanalysis accuracy since 1957. The results of these comparisons indicate that NN50 tends to be a few degrees colder than the observations in the SH subpolar latitudes, while ERA-40 is less hit by this cold-pole issue. Both reanalyses, on the other hand, are found to be warmer than the observations by about 1 K in the subtropics. In contrast, the wind comparisons only exhibit nonsignificant or small reanalysis biases, even though the reanalyzed subtropical jet is slightly displaced equatorward with respect to the observations. The ability of reanalyses to capture the atmospheric synoptic-scale variability in the upper troposphere is assessed by computing the standard deviations of the reanalysis minus observation differences. The ERA-40 and NN50 standard deviations show a maximum (i.e., a poorer reanalysis accuracy) in the SH storm track. However, ERA-40 standard deviations are found to be much larger than NN50 standard deviations. The standard deviations also exhibit a marked decrease above the continents, stressing the heterogeneity of the atmospheric observation network during the presatellite era. Finally, in contrast with previous studies, the reanalysis accuracy does not appear to be better during summer than during winter.
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Fujiwara, Masatomo, Jonathon S. Wright, Gloria L. Manney, Lesley J. Gray, James Anstey, Thomas Birner, Sean Davis, et al. "Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems." Atmospheric Chemistry and Physics 17, no. 2 (January 31, 2017): 1417–52. http://dx.doi.org/10.5194/acp-17-1417-2017.
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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.
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Song, Hua, and Minghua Zhang. "Changes of the Boreal Winter Hadley Circulation in the NCEP–NCAR and ECMWF Reanalyses: A Comparative Study." Journal of Climate 20, no. 20 (October 15, 2007): 5191–200. http://dx.doi.org/10.1175/jcli4260.1.
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Abstract Both the ECMWF and the NCEP–NCAR reanalyses show a strengthening of the atmospheric Hadley circulation in boreal winter over the last 50 years, but the intensification is much stronger in the ECMWF than in the NCEP–NCAR reanalysis. This study focuses on the difference of these trends in the two reanalyses. It is shown that trends in the Hadley circulation in the two reanalyses differ mainly over the tropical western Pacific. This difference is found to be consistent with respective trends of the atmospheric transport of moist static energy, longwave cloud radiative forcing, and upper-level clouds in the two reanalyses. Two independent datasets of upper-level cloud cover and sea level pressure from ship-based measurements are then used to evaluate the reanalyses over the tropical western Pacific. They are found to be more consistent with the trends in the NCEP–NCAR reanalysis than those in the ECMWF reanalysis. The results suggest a weakening of the vertical motion associated with the Hadley circulation in the tropical western Pacific.
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King, Austin T., and Aaron D. Kennedy. "North American Supercell Environments in Atmospheric Reanalyses and RUC-2." Journal of Applied Meteorology and Climatology 58, no. 1 (January 2019): 71–92. http://dx.doi.org/10.1175/jamc-d-18-0015.1.
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AbstractA suite of modern atmospheric reanalyses is analyzed to determine how they represent North American supercell environments. This analysis is performed by comparing a database of Rapid Update Cycle (RUC-2) proximity soundings with profiles derived from the nearest grid point in each reanalysis. Parameters are calculated using the Sounding and Hodograph Analysis and Research Program in Python (SHARPpy), an open-source Python sounding-analysis package. Representation of supercell environments varies across the reanalyses, and the results have ramifications for climatological studies that use these datasets. In particular, thermodynamic parameters such as the convective available potential energy (CAPE) show the widest range in biases, with reanalyses falling into two camps. The North American Regional Reanalysis (NARR) and the Japanese 55-year Reanalysis (JRA-55) are similar to RUC-2, but other reanalyses have a substantial negative bias. The reasons for these biases vary and range from thermodynamic biases at the surface to evidence of convective contamination. Overall, it is found that thermodynamic biases feed back to other convective parameters that incorporate CAPE directly or indirectly via the effective layer. As a result, significant negative biases are found for indices such as the supercell composite parameter. These biases are smallest for NARR and JRA-55. Kinematic parameters are more consistent across the reanalyses. Given the issues with thermodynamic properties, better segregation of soundings by storm type is found for fixed-layer parameters than for effective-layer shear parameters. Although no reanalysis can exactly reproduce the results of earlier RUC-2 studies, many of the reanalyses can broadly distinguish between environments that are significantly tornadic versus nontornadic.
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Lader, Rick, Uma S. Bhatt, John E. Walsh, T. Scott Rupp, and Peter A. Bieniek. "Two-Meter Temperature and Precipitation from Atmospheric Reanalysis Evaluated for Alaska." Journal of Applied Meteorology and Climatology 55, no. 4 (April 2016): 901–22. http://dx.doi.org/10.1175/jamc-d-15-0162.1.
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AbstractAlaska is experiencing effects of global climate change that are due, in large part, to the positive feedback mechanisms associated with polar amplification. The major risk factors include loss of sea ice and glaciers, thawing permafrost, increased wildfires, and ocean acidification. Reanalyses, integral to understanding mechanisms of Alaska’s past climate and to helping to calibrate modeling efforts, are based on the output of weather forecast models that assimilate observations. This study evaluates temperature and precipitation from five reanalyses at monthly and daily time scales for the period 1979–2009. Monthly data are evaluated spatially at grid points and for six climate zones in Alaska. In addition, daily maximum temperature, minimum temperature, and precipitation from reanalyses are compared with meteorological-station data at six locations. The reanalyses evaluated in this study include the NCEP–NCAR reanalysis (R1), North American Regional Reanalysis (NARR), Climate Forecast System Reanalysis (CFSR), ERA-Interim, and the Modern-Era Retrospective Analysis for Research and Applications (MERRA). Maps of seasonal bias and standard deviation, constructed from monthly data, show how the reanalyses agree with observations spatially. Cross correlations between the monthly gridded and daily station time series are computed to provide a measure of confidence that data users can assume when selecting reanalysis data in a region without many surface observations. A review of natural hazards in Alaska indicates that MERRA is the top reanalysis for wildfire and interior-flooding applications. CFSR is the recommended reanalysis for North Slope coastal erosion issues and, along with ERA-Interim, for heavy precipitation in southeastern Alaska.
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Sang, Xiaozhuo, Xiu-Qun Yang, Lingfeng Tao, Jiabei Fang, and Xuguang Sun. "Evaluation of synoptic eddy activities and their feedback onto the midlatitude jet in five atmospheric reanalyses with coarse versus fine model resolutions." Climate Dynamics 58, no. 5-6 (September 27, 2021): 1363–81. http://dx.doi.org/10.1007/s00382-021-05965-9.
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AbstractInteraction between synoptic eddy and mean flow plays a crucial role in maintaining midlatitude westerly jet. In this study, climatologies of synoptic eddy activities and their feedback onto midlatitude jet for 1980–2016 are evaluated and compared through analyzing daily data from five atmospheric reanalyses with different resolutions including one coarse-resolution reanalysis (NCEP2) and four fine-resolution reanalyses (ERA-Interim, JRA-55, MERRA-2, and CFSR). Horizontal resolutions of the atmospheric models generating those reanalyses are approximately equivalent to 210, 79, 60, 50, and 38 km, respectively. Results show that the eddy activities and their feedback onto the midlatitude jet in those fine-resolution reanalyses are consistently and significantly stronger than those in the coarse-resolution reanalysis (NCEP2). The maximal relative increases that are found to occur primarily in the midlatitudes of the Southern Hemisphere are estimated to be up to 55% for the baroclinicity, 53% for the eddy energetics, 59% for the eddy forcing, and even 85% for the eddy feedback onto the mean flow. Those increases are reasonably conjectured to be related to increased model resolutions, since the synoptic eddy genesis is proportional to the low-level atmospheric meridional temperature gradient which is sensitive to the meridional resolution of atmospheric models. Although the coarse-resolution reanalysis resolves synoptic eddies insufficiently and thus underestimates their feedback onto the mean flow, the magnitudes of eddy-driven jets are almost the same among five reanalyses, implying a mismatch between the eddy feedback and the eddy-driven jet in the coarse-resolution reanalysis. Therefore, the results of this study imply the importance of using fine-resolution reanalyses in accurately understanding the midlatitude synoptic eddy–mean flow interaction.
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Hynčica, Martin, and Radan Huth. "Modes of Atmospheric Circulation Variability in the Northern Extratropics: A Comparison of Five Reanalyses." Journal of Climate 33, no. 24 (December 15, 2020): 10707–26. http://dx.doi.org/10.1175/jcli-d-19-0904.1.
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AbstractModes of low-frequency circulation variability in the Northern Hemisphere extratropics are compared between five reanalyses. Circulation modes are detected by rotated principal component analysis (PCA) of monthly mean 500-hPa geopotential heights between 1957 and 2002, separately for individual seasons. The quantification of differences between reanalyses is based on the percentage of grid points (approximately corresponding to the percentage of area) where the spatial representations of a mode (loadings) significantly differ between reanalyses. The differences between surface-input reanalyses (20CRv2c, ERA-20C) and full-input reanalyses (NCEP-1, ERA-40, JRA-55) are larger than differences within the reanalysis groups in all seasons except for autumn. The causes of the differences are of two kinds. First, the differences may be inherent to PCA: namely, the spatial structure of the modes may be sensitive to the number of components rotated. This concerns only a few modes. Second, the differences may reflect real correlation structures in reanalysis data. We demonstrate that the differences concentrate in three or fewer modes in each season. The reanalysis most different from the rest is 20CRv2c, with the differences concentrating over the southern half of Asia and in the subtropical belt over the Pacific and adjacent southwestern North America. The 20CRv2c reanalysis disagrees from other reanalyses there predominantly before the 1980s, which points to the impact of insufficient amount of assimilated observations. On the contrary, ERA-20C exhibits a higher agreement with full-input reanalyses, which is why we recommend it for studies of atmospheric circulation over the entire twentieth century.
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Millán, Luis F., Gloria L. Manney, and Zachary D. Lawrence. "Reanalysis intercomparison of potential vorticity and potential-vorticity-based diagnostics." Atmospheric Chemistry and Physics 21, no. 7 (April 7, 2021): 5355–76. http://dx.doi.org/10.5194/acp-21-5355-2021.
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Abstract. Global reanalyses from data assimilation systems are among the most widely used datasets in weather and climate studies, and potential vorticity (PV) from reanalyses is invaluable for many studies of dynamical and transport processes. We assess how consistently modern reanalyses represent potential vorticity (PV) among each other, focusing not only on PV but also on process-oriented dynamical diagnostics including equivalent latitude calculated from PV and PV-based tropopause and stratospheric polar vortex characterization. In particular we assess the National Centers for Environmental Prediction Climate Forecast System Reanalysis/Climate Forecast System, version 2 (CFSR/CFSv2) reanalysis, the European Centre for Medium-Range Weather Forecasts Interim (ERA-Interim) reanalysis, the Japanese Meteorological Agency's 55-year (JRA-55) reanalysis, and the NASA Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). Overall, PV from all reanalyses agrees well with the reanalysis ensemble mean, providing some confidence that all of these recent reanalyses are suitable for most studies using PV-based diagnostics. Specific diagnostics where some larger differences are seen include PV-based tropopause locations in regions that have strong tropopause gradients (such as around the subtropical jets) or are sparse in high-resolution data (such as over Antarctica), and the stratospheric polar vortices during fall vortex formation and (especially) spring vortex breakup; studies of sensitive situations or regions such as these should examine PV from multiple reanalyses.
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Davis, Sean M., Michaela I. Hegglin, Masatomo Fujiwara, Rossana Dragani, Yayoi Harada, Chiaki Kobayashi, Craig Long, et al. "Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP." Atmospheric Chemistry and Physics 17, no. 20 (October 26, 2017): 12743–78. http://dx.doi.org/10.5194/acp-17-12743-2017.
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Abstract. Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as "observations" for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields.The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses.In contrast to O3, reanalysis estimates of stratospheric WV are not directly constrained by assimilated data. Observations of atmospheric humidity are typically used only in the troposphere, below a specified vertical level at or near the tropopause. The fidelity of reanalysis stratospheric WV products is therefore mainly dependent on the reanalyses' representation of the physical drivers that influence stratospheric WV, such as temperatures in the tropical tropopause layer, methane oxidation, and the stratospheric overturning circulation. The lack of assimilated observations and known deficiencies in the representation of stratospheric transport in reanalyses result in much poorer agreement amongst observational and reanalysis estimates of stratospheric WV. Hence, stratospheric WV products from the current generation of reanalyses should generally not be used in scientific studies.
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Lynch, Peng, Jeffrey S. Reid, Douglas L. Westphal, Jianglong Zhang, Timothy F. Hogan, Edward J. Hyer, Cynthia A. Curtis, et al. "An 11-year global gridded aerosol optical thickness reanalysis (v1.0) for atmospheric and climate sciences." Geoscientific Model Development 9, no. 4 (April 21, 2016): 1489–522. http://dx.doi.org/10.5194/gmd-9-1489-2016.
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Abstract. While stand alone satellite and model aerosol products see wide utilization, there is a significant need in numerous atmospheric and climate applications for a fused product on a regular grid. Aerosol data assimilation is an operational reality at numerous centers, and like meteorological reanalyses, aerosol reanalyses will see significant use in the near future. Here we present a standardized 2003–2013 global 1 × 1° and 6-hourly modal aerosol optical thickness (AOT) reanalysis product. This data set can be applied to basic and applied Earth system science studies of significant aerosol events, aerosol impacts on numerical weather prediction, and electro-optical propagation and sensor performance, among other uses. This paper describes the science of how to develop and score an aerosol reanalysis product. This reanalysis utilizes a modified Navy Aerosol Analysis and Prediction System (NAAPS) at its core and assimilates quality controlled retrievals of AOT from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Multi-angle Imaging SpectroRadiometer (MISR) on Terra. The aerosol source functions, including dust and smoke, were regionally tuned to obtain the best match between the model fine- and coarse-mode AOTs and the Aerosol Robotic Network (AERONET) AOTs. Other model processes, including deposition, were tuned to minimize the AOT difference between the model and satellite AOT. Aerosol wet deposition in the tropics is driven with satellite-retrieved precipitation, rather than the model field. The final reanalyzed fine- and coarse-mode AOT at 550 nm is shown to have good agreement with AERONET observations, with global mean root mean square error around 0.1 for both fine- and coarse-mode AOTs. This paper includes a discussion of issues particular to aerosol reanalyses that make them distinct from standard meteorological reanalyses, considerations for extending such a reanalysis outside of the NASA A-Train era, and examples of how the aerosol reanalysis can be applied or fused with other model or remote sensing products. Finally, the reanalysis is evaluated in comparison with other available studies of aerosol trends, and the implications of this comparison are discussed.
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Gerber, Edwin P., and Patrick Martineau. "Quantifying the variability of the annular modes: reanalysis uncertainty vs. sampling uncertainty." Atmospheric Chemistry and Physics 18, no. 23 (December 4, 2018): 17099–117. http://dx.doi.org/10.5194/acp-18-17099-2018.
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Abstract. The annular modes characterize the dominant variability of the extratropical circulation in each hemisphere, quantifying vacillations in the position of the tropospheric jet streams and the strength of the stratospheric polar vortices. Their representation in all available reanalysis products is assessed. Reanalysis uncertainty associated with limitations in the ability to constrain the circulation with available observations, i.e., the inter-reanalysis spread, is contrasted with sampling uncertainty associated with the finite length of the reanalysis records. It is shown that the annular modes are extremely consistent across all modern reanalyses during the satellite era (ca. 1979 onward). Consequently, uncertainty in annular mode variability, e.g., the coupling between the stratosphere and troposphere and the variation in the amplitude and timescale of jet variations throughout the annual cycle, is dominated by sampling uncertainty. Comparison of reanalyses based on conventional (i.e., nonsatellite) or surface observations alone with those using all available observations indicates that there is limited ability to characterize the Southern Annular Mode (SAM) in the presatellite era. Notably, prior to 1979, surface-input reanalyses better capture the SAM at near-surface levels than full-input reanalyses. For the Northern Annular Mode, however, there is evidence that conventional observations are sufficient, at least from 1958 onward. The addition of 2 additional decades of records substantially reduces sampling uncertainty in several key measures of annular mode variability, demonstrating the value of more historic reanalyses. Implications for the assessment of atmospheric models and the strength of coupling between the surface and upper atmosphere are discussed.
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Inness, Antje, Melanie Ades, Anna Agustí-Panareda, Jérôme Barré, Anna Benedictow, Anne-Marlene Blechschmidt, Juan Jose Dominguez, et al. "The CAMS reanalysis of atmospheric composition." Atmospheric Chemistry and Physics 19, no. 6 (March 20, 2019): 3515–56. http://dx.doi.org/10.5194/acp-19-3515-2019.
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Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis is the latest global reanalysis dataset of atmospheric composition produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), consisting of three-dimensional time-consistent atmospheric composition fields, including aerosols and chemical species. The dataset currently covers the period 2003–2016 and will be extended in the future by adding 1 year each year. A reanalysis for greenhouse gases is being produced separately. The CAMS reanalysis builds on the experience gained during the production of the earlier Monitoring Atmospheric Composition and Climate (MACC) reanalysis and CAMS interim reanalysis. Satellite retrievals of total column CO; tropospheric column NO2; aerosol optical depth (AOD); and total column, partial column and profile ozone retrievals were assimilated for the CAMS reanalysis with ECMWF's Integrated Forecasting System. The new reanalysis has an increased horizontal resolution of about 80 km and provides more chemical species at a better temporal resolution (3-hourly analysis fields, 3-hourly forecast fields and hourly surface forecast fields) than the previously produced CAMS interim reanalysis. The CAMS reanalysis has smaller biases compared with most of the independent ozone, carbon monoxide, nitrogen dioxide and aerosol optical depth observations used for validation in this paper than the previous two reanalyses and is much improved and more consistent in time, especially compared to the MACC reanalysis. The CAMS reanalysis is a dataset that can be used to compute climatologies, study trends, evaluate models, benchmark other reanalyses or serve as boundary conditions for regional models for past periods.
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Stryhal, Jan, and Radan Huth. "Classifications of Winter Euro-Atlantic Circulation Patterns: An Intercomparison of Five Atmospheric Reanalyses." Journal of Climate 30, no. 19 (September 1, 2017): 7847–61. http://dx.doi.org/10.1175/jcli-d-17-0059.1.
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Abstract Atmospheric reanalyses have been widely used to study large-scale atmospheric circulation and its links to local weather and to validate climate models. Only little effort has so far been made to compare reanalyses over the Euro-Atlantic domain, with the exception of a few studies analyzing North Atlantic cyclones. In particular, studies utilizing automated classifications of circulation patterns—one of the most popular methods in synoptic climatology—have paid little or no attention to the issue of reanalysis evaluation. Here, five reanalyses [ERA-40; NCEP-1; JRA-55; Twentieth Century Reanalysis, version 2 (20CRv2); and ECMWF twentieth-century reanalysis (ERA-20C)] are compared as to the frequency of occurrence of circulation types (CTs) over eight European domains in winters 1961–2000. Eight different classifications are used in parallel with the intention to eliminate possible artifacts of individual classification methods. This also helps document how substantial effect a choice of method can have if one quantifies differences between reanalyses. In general, ERA-40, NCEP-1, and JRA-55 exhibit a fairly small portion of days (under 8%) classified to different CTs if pairs of reanalyses are compared, with two exceptions: over Iceland, NCEP-1 shows disproportionately high frequencies of CTs with cyclones shifted south- and eastward; over the eastern Mediterranean region, ERA-40 and NCEP-1 disagree on classification of about 22% of days. The 20CRv2 is significantly different from other reanalyses over all domains and has a clearly suppressed frequency of zonal CTs. Finally, validation of 32 CMIP5 models over the eastern Mediterranean region reveals that using different reanalyses can considerably alter errors in the CT frequency of models and their rank.
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Pinheiro, Henri Rossi, Kevin Ivan Hodges, and Manoel Alonso Gan. "An intercomparison of subtropical cut-off lows in the Southern Hemisphere using recent reanalyses: ERA-Interim, NCEP-CFRS, MERRA-2, JRA-55, and JRA-25." Climate Dynamics 54, no. 1-2 (December 24, 2019): 777–92. http://dx.doi.org/10.1007/s00382-019-05089-1.
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AbstractFour recent reanalysis products ERA-Interim, NCEP-CFSR, MERRA-2 and JRA-55 are evaluated and compared to an older reanalysis JRA-25, to quantify their confidence in representing Cut-off lows (COLs) in the Southern Hemisphere. The climatology of COLs based on the minima of 300-hPa vorticity ($$\xi_{300}$$ξ300) and 300-hPa geopotential ($$Z_{300}$$Z300) provides different perspectives of COLs and contributes to the understanding of the discrepancies observed in the literature regarding their numbers and seasonality. The COLs compare better among the newest reanalyses than compared to the older reanalysis JRA-25. The difference in number between the latest reanalyses are generally small for both $$\xi_{300}$$ξ300 and, with more COLs identified in $$\xi_{300}$$ξ300 than in $$Z_{300}$$Z300 for all reanalyses. The spatial differences observed between the newest reanalyses are mainly due to differences in the track lengths, which is larger in ERA-Interim and JRA-55 than in NCEP-CFSR and MERRA-2, resulting in disparities in the track density. This is likely due to the difference in the assimilation data system used in each reanalysis product. The largest differences in intensities occur in the $$\xi_{300}$$ξ300, because this field is very sensitive to the reanalysis resolution. The mean separation distance of the COLs that match between the latest reanalyses are generally small, while the older JRA-25 has a broader distribution and larger number of matches with relatively large distances, indicating larger uncertainties in location of COLs. The results show significant improvements for the most recent reanalyses compared to the older JRA-25 reanalysis, indicating a progress in representing the COL properties.
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Sakazaki, Takatoshi, Masatomo Fujiwara, and Masato Shiotani. "Representation of solar tides in the stratosphere and lower mesosphere in state-of-the-art reanalyses and in satellite observations." Atmospheric Chemistry and Physics 18, no. 2 (February 1, 2018): 1437–56. http://dx.doi.org/10.5194/acp-18-1437-2018.
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Abstract. Atmospheric solar tides in the stratosphere and the lower mesosphere are investigated using temperature data from five state-of-the-art reanalysis data sets (MERRA-2, MERRA, JRA-55, ERA-Interim, and CFSR) as well as TIMED SABER and Aura MLS satellite measurements. The main focus is on the period 2006–2012 during which the satellite observations are available for direct comparison with the reanalyses. Diurnal migrating tides, semidiurnal migrating tides, and nonmigrating tides are diagnosed. Overall the reanalyses agree reasonably well with each other and with the satellite observations for both migrating and nonmigrating components, including their vertical structure and the seasonality. However, the agreement among reanalyses is more pronounced in the lower stratosphere and relatively weaker in the upper stratosphere and mesosphere. A systematic difference between SABER and the reanalyses is found for diurnal migrating tides in the upper stratosphere and the lower mesosphere; specifically, the amplitude of trapped modes in reanalyses is significantly smaller than that in SABER, although such difference is less clear between MLS and the reanalyses. The interannual variability and the possibility of long-term changes in migrating tides are also examined using the reanalyses during 1980–2012. All the reanalyses agree in exhibiting a clear quasi-biennial oscillation (QBO) in the tides, but the most significant indications of long-term changes in the tides represented in the reanalyses are most plausibly explained by the evolution of the satellite observing systems during this period. The tides are also compared in the full reanalyses produced by the Japan Meteorological Agency (i.e., JRA-55) and in two parallel data sets from this agency: one (JRA-55C) that repeats the reanalysis procedure but without any satellite data assimilated and one (JRA-55AMIP) that is a free-running integration of the model constrained only by observed sea surface temperatures. Many aspects of the tides are closer in JRA-55C and JRA-55AMIP than these are to the full reanalysis JRA-55, demonstrating the importance of the assimilation of satellite data in representing the diurnal variability of the middle atmosphere. In contrast to the assimilated data sets, the free-running model has no QBO in equatorial stratospheric mean circulation and our results show that it displays no quasi-biennial variability in the tides.
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Lima, Daniela C. A., Pedro M. M. Soares, Alvaro Semedo, and Rita M. Cardoso. "A Global View of Coastal Low-Level Wind Jets Using an Ensemble of Reanalyses." Journal of Climate 31, no. 4 (February 2018): 1525–46. http://dx.doi.org/10.1175/jcli-d-17-0395.1.
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Global reanalyses are powerful tools to study the recent climate. They are built by combining forecast models with observations through data assimilation, which provide complete spatial and temporal information of observable and unobservable parameters. The reanalyses constitute very valuable three-dimensional data of the atmosphere, which make it possible to investigate a panoply of atmospheric processes, such as coastal low-level jets (CLLJs). In the present study, three global reanalyses, the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), the Japanese 55-year Reanalysis (JRA-55), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), are used to build an ensemble of reanalyses for a period encompassing 1980–2016 with 6-hourly output. A detailed global climatology of CLLJs is presented based on this ensemble of reanalyses. This reanalysis ensemble makes it possible to explore the ability of reanalysis to represent the CLLJs mitigating its uncertainty and adding robustness. The annual and diurnal cycle as well as the interannual variability are analyzed in order to evaluate the temporal variability of frequency of occurrence of CLLJ. The ensemble mean displays a good representation of the seasonal spatial variability of frequency of occurrence of coastal jets. The Oman and Benguela CLLJs show, respectively, a decrease and increase of frequency of occurrence in the studied period, which are statistically significant during boreal summer and austral spring. The coastal jets have higher mean frequencies of occurrences during late afternoon and early evening. During the season where each CLLJ has higher mean frequency of occurrence, the Oman CLLJ is the most intense and occurs at higher altitudes.
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Rohrer, Marco, Stefan Brönnimann, Olivia Martius, Christoph C. Raible, Martin Wild, and Gilbert P. Compo. "Representation of Extratropical Cyclones, Blocking Anticyclones, and Alpine Circulation Types in Multiple Reanalyses and Model Simulations." Journal of Climate 31, no. 8 (March 20, 2018): 3009–31. http://dx.doi.org/10.1175/jcli-d-17-0350.1.
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Abstract Atmospheric circulation types, blockings, and cyclones are central features of the extratropical flow and key to understanding the climate system. This study intercompares the representation of these features in 10 reanalyses and in an ensemble of 30 climate model simulations between 1980 and 2005. Both modern, full-input reanalyses and century-long, surface-input reanalyses are examined. Modern full-input reanalyses agree well on key statistics of blockings, cyclones, and circulation types. However, the intensity and depth of cyclones vary among them. Reanalyses with higher horizontal resolution show higher cyclone center densities and more intense cyclones. For blockings, no strict relationship is found between frequency or intensity and horizontal resolution. Full-input reanalyses contain more intense blocking, compared to surface-input reanalyses. Circulation-type classifications over central Europe show that both versions of the Twentieth Century Reanalysis dataset contain more easterlies and fewer westerlies than any other reanalysis, owing to their high pressure bias over northeast Europe. The temporal correlation of annual circulation types over central Europe and blocking frequencies over the North Atlantic–European domain between reanalyses is high (around 0.8). The ensemble simulations capture the main characteristics of midlatitudinal atmospheric circulation. Circulation types of westerlies to northerlies over central Europe are overrepresented. There are too few blockings in the higher latitudes and an excess of cyclones in the midlatitudes. Other characteristics, such as blocking amplitude and cyclone intensity, are realistically represented, making the ensemble simulations a rich dataset to assess changes in climate variability.
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Long, Craig S., Masatomo Fujiwara, Sean Davis, Daniel M. Mitchell, and Corwin J. Wright. "Climatology and interannual variability of dynamic variables in multiple reanalyses evaluated by the SPARC Reanalysis Intercomparison Project (S-RIP)." Atmospheric Chemistry and Physics 17, no. 23 (December 7, 2017): 14593–629. http://dx.doi.org/10.5194/acp-17-14593-2017.
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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.
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Kawatani, Yoshio, Kevin Hamilton, Kazuyuki Miyazaki, Masatomo Fujiwara, and James A. Anstey. "Representation of the tropical stratospheric zonal wind in global atmospheric reanalyses." Atmospheric Chemistry and Physics 16, no. 11 (June 2, 2016): 6681–99. http://dx.doi.org/10.5194/acp-16-6681-2016.
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Abstract. This paper reports on a project to compare the representation of the monthly-mean zonal wind in the equatorial stratosphere among major global atmospheric reanalysis data sets. The degree of disagreement among the reanalyses is characterized by the standard deviation (SD) of the monthly-mean zonal wind and this depends on latitude, longitude, height, and the phase of the quasi-biennial oscillation (QBO). At each height the SD displays a prominent equatorial maximum, indicating the particularly challenging nature of the reanalysis problem in the low-latitude stratosphere. At 50–70 hPa the geographical distributions of SD are closely related to the density of radiosonde observations. The largest SD values are over the central Pacific, where few in situ observations are available. At 10–20 hPa the spread among the reanalyses and differences with in situ observations both depend significantly on the QBO phase. Notably the easterly-to-westerly phase transitions in all the reanalyses except MERRA are delayed relative to those directly observed in Singapore. In addition, the timing of the easterly-to-westerly phase transitions displays considerable variability among the different reanalyses and this spread is much larger than for the timing of the westerly-to-easterly phase changes. The eddy component in the monthly-mean zonal wind near the Equator is dominated by zonal wavenumber 1 and 2 quasi-stationary planetary waves propagating from midlatitudes in the westerly phase of the QBO. There generally is considerable disagreement among the reanalyses in the details of the quasi-stationary waves near the Equator. At each level, there is a tendency for the agreement to be best near the longitude of Singapore, suggesting that the Singapore observations act as a strong constraint on all the reanalyses. Our measures of the quality of the reanalysis clearly show systematic improvement over the period considered (1979–2012). The SD among the reanalysis declines significantly over the record, although the geographical pattern of SD remains nearly constant.
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Kim, Ji-Eun, and M. Joan Alexander. "Tropical Precipitation Variability and Convectively Coupled Equatorial Waves on Submonthly Time Scales in Reanalyses and TRMM." Journal of Climate 26, no. 10 (May 8, 2013): 3013–30. http://dx.doi.org/10.1175/jcli-d-12-00353.1.
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Abstract Tropical precipitation characteristics are investigated using the Tropical Rainfall Measuring Mission (TRMM) 3-hourly estimates, and the result is compared with five reanalyses including the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Applications (MERRA), National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) reanalysis (NCEP1), NCEP–U.S. Department of Energy (DOE) reanalysis (NCEP2), and NCEP–Climate Forecast System Reanalysis (CFSR). Precipitation characteristics are evaluated in terms of the mean, convectively coupled equatorial wave activity, frequency characteristics, diurnal cycle, and seasonality of regional precipitation variability associated with submonthly scale waves. Generally the latest reanalyses such as ERA-Interim, MERRA, and CFSR show better performances than NCEP1 and NCEP2. However, all the reanalyses are still different from observations. Besides the positive mean bias in the reanalyses, a spectral analysis revealed that the reanalyses have overreddened spectra with persistent rainfall. MERRA has the most persistent rainfall, and CFSR appears to have the most realistic variability. The diurnal cycle in NCEP1 is extremely exaggerated relative to TRMM. The low-frequency waves with the period longer than 3 days are relatively well represented in ERA-Interim, MERRA, and CFSR, but all the reanalyses have significant deficiencies in representing convectively coupled equatorial waves and variability in the high-frequency range.
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Uma, Kizhathur Narasimhan, Siddarth Shankar Das, Madineni Venkat Ratnam, and Kuniyil Viswanathan Suneeth. "Assessment of vertical air motion among reanalyses and qualitative comparison with very-high-frequency radar measurements over two tropical stations." Atmospheric Chemistry and Physics 21, no. 3 (February 11, 2021): 2083–103. http://dx.doi.org/10.5194/acp-21-2083-2021.
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Abstract. Vertical wind (w) is one of the most important meteorological parameters for understanding a range of different atmospheric phenomena. Very few direct measurements of w are available so that most of the time one must depend on reanalysis products. In the present study, assessment of w among selected reanalyses (ERA-Interim, ERAi; ERA fifth generation, ERA5; Modern-Era Retrospective analysis for Research and Applications, version 2, MERRA-2; National Center for Atmospheric Research and Depart- ment of Energy reanalysis, NCEP–DOE (R-2); and Japanese 55-year reanalysis, JRA-55) and qualitative comparison of those datasets with VHF radar measurements over the convectively active regions Gadanki, India (13.5∘ N, 79.2∘ E), and Kototabang, Indonesia (0∘ S, 100.2∘ E), are presented for the first time in the troposphere and lower stratosphere. The magnitude of w derived from reanalyses is 10 %–50 % less than that from the radar observations. Radar measurements of w show downdrafts below 8 and 10 km and updrafts above 8–10 km over both locations. Intercomparison between the ensemble of reanalyses with respect to individual reanalysis shows that ERAi, MERRA-2 and JRA-55 compare well with the ensemble compared to ERA5 and NCEP–DOE (R-2). There is no significant improvement in w due to the effect of different spatial sampling for reanalysis data around the Gadanki station. Directional tendency shows that the percentage of updrafts captured is reasonably good, but downdrafts are not well captured by all reanalyses. Thus, caution is advised when using w from reanalyses.
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Wright, Jonathon S., Xiaoyi Sun, Paul Konopka, Kirstin Krüger, Bernard Legras, Andrea M. Molod, Susann Tegtmeier, Guang J. Zhang, and Xi Zhao. "Differences in tropical high clouds among reanalyses: origins and radiative impacts." Atmospheric Chemistry and Physics 20, no. 14 (July 29, 2020): 8989–9030. http://dx.doi.org/10.5194/acp-20-8989-2020.
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Abstract. We examine differences among reanalysis high-cloud products in the tropics, assess the impacts of these differences on radiation budgets at the top of the atmosphere and within the tropical upper troposphere and lower stratosphere (UTLS), and discuss their possible origins in the context of the reanalysis models. We focus on the ERA5 (fifth-generation European Centre for Medium-range Weather Forecasts – ECMWF – reanalysis), ERA-Interim (ECMWF Interim Reanalysis), JRA-55 (Japanese 55-year Reanalysis), MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2), and CFSR/CFSv2 (Climate Forecast System Reanalysis/Climate Forecast System Version 2) reanalyses. As a general rule, JRA-55 produces the smallest tropical high-cloud fractions and cloud water contents among the reanalyses, while MERRA-2 produces the largest. Accordingly, long-wave cloud radiative effects are relatively weak in JRA-55 and relatively strong in MERRA-2. Only MERRA-2 and ERA5 among the reanalyses produce tropical-mean values of outgoing long-wave radiation (OLR) close to those observed, but ERA5 tends to underestimate cloud effects, while MERRA-2 tends to overestimate variability. ERA5 also produces distributions of long-wave, short-wave, and total cloud radiative effects at the top of the atmosphere that are very consistent with those observed. The other reanalyses all exhibit substantial biases in at least one of these metrics, although compensation between the long-wave and short-wave effects helps to constrain biases in the total cloud radiative effect for most reanalyses. The vertical distribution of cloud water content emerges as a key difference between ERA-Interim and other reanalyses. Whereas ERA-Interim shows a monotonic decrease of cloud water content with increasing height, the other reanalyses all produce distinct anvil layers. The latter is in better agreement with observations and yields very different profiles of radiative heating in the UTLS. For example, whereas the altitude of the level of zero net radiative heating tends to be lower in convective regions than in the rest of the tropics in ERA-Interim, the opposite is true for the other four reanalyses. Differences in cloud water content also help to explain systematic differences in radiative heating in the tropical lower stratosphere among the reanalyses. We discuss several ways in which aspects of the cloud and convection schemes impact the tropical environment. Discrepancies in the vertical profiles of temperature and specific humidity in convective regions are particularly noteworthy, as these variables are directly constrained by data assimilation, are widely used, and feed back to convective behaviour through their relationships with thermodynamic stability.
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Hodges, K. I., R. W. Lee, and L. Bengtsson. "A Comparison of Extratropical Cyclones in Recent Reanalyses ERA-Interim, NASA MERRA, NCEP CFSR, and JRA-25." Journal of Climate 24, no. 18 (September 15, 2011): 4888–906. http://dx.doi.org/10.1175/2011jcli4097.1.
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Abstract Extratropical cyclones are identified and compared using data from four recent reanalyses for the winter periods in both hemispheres. Results show the largest differences occur between the older lower resolution 25-yr Japanese Reanalysis (JRA-25) when compared with the newer high resolution reanalyses, particularly in the Southern Hemisphere (SH). Spatial differences between the newest reanalyses are small in both hemispheres and generally not significant except in some common regions associated with cyclogenesis close to orography. Differences in the cyclone maximum intensitites are generally related to spatial resolution except in the NASA Modern Era Retrospective-Analysis for Research and Applications (NASA MERRA), which has larger intensities for several different measures. Matching storms between reanalyses shows the number matched between the ECMWF Interim Re-Analysis (ERA-Interim) and the other reanalyses is similar in the Northern Hemisphere (NH). In the SH the number matched between JRA-25 and ERA-Interim is lower than in the NH; however, for NASA MERRA and the NCEP Climate Forecast System Reanalysis (NCEP CFSR), the number matched is similar to the NH. The mean separation of the identically same cyclones is typically less than 2° geodesic in both hemispheres for the latest reanalyses, whereas JRA-25 compared with the other reanalyses has a broader distribution in the SH, indicating greater uncertainty. The instantaneous intensity differences for matched storms shows narrow distributions for pressure, while for winds and vorticity the distributions are much broader, indicating larger uncertainty typical of smaller-scale fields. Composite cyclone diagnostics show that cyclones are very similar between the reanalyses, with differences being related to the intensities, consistent with the intensity results. Overall, results show NH cyclones correspond well between reanalyses, with a significant improvement in the SH for the latest reanalyses, indicating a convergence between reanalyses for cyclone properties.
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Kim, Young-Ha, George N. Kiladis, John R. Albers, Juliana Dias, Masatomo Fujiwara, James A. Anstey, In-Sun Song, et al. "Comparison of equatorial wave activity in the tropical tropopause layer and stratosphere represented in reanalyses." Atmospheric Chemistry and Physics 19, no. 15 (August 9, 2019): 10027–50. http://dx.doi.org/10.5194/acp-19-10027-2019.
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Abstract. Equatorial Kelvin and mixed Rossby–gravity (MRG) waves in the tropical tropopause layer and stratosphere represented in recent reanalyses for the period of 1981–2010 are compared in terms of spectral characteristics, spatial structures, long-term variations, and their forcing of the quasi-biennial oscillation (QBO). For both wave types, the spectral distributions are broadly similar among most of the reanalyses, while the peak amplitudes exhibit considerable spread. The longitudinal distributions and spatial patterns of wave perturbations show reasonable agreement between the reanalyses. A few exceptions to the similarity of the spectral shapes and spatial structures among them are also noted. While the interannual variations of wave activity appear to be coherent for both the Kelvin and MRG waves, there is substantial variability in long-term trends among the reanalyses. Most of the reanalyses which assimilate satellite data exhibit large increasing trends in wave variance (∼15 %–50 % increase in 30 years at 100–10 hPa), whereas one reanalysis (Japanese 55-year Reanalysis assimilating conventional observations only; JRA-55C) produced without satellite data does not. Several discontinuities are found around 1998 in the time series of the Kelvin and MRG wave variances, which manifest in different ways depending on the reanalysis, and are indicative of impacts of the transition of satellite measurements during that year. The equatorial wave forcing of the QBO, estimated by the Eliassen–Palm (EP) flux divergence, occurs in similar phase-speed ranges in the lower stratosphere among the reanalyses. However, the EP flux and its divergence are found to be dependent on the zonal-mean winds represented in reanalyses, exhibiting different magnitudes, altitudes, and phase-speed ranges of the Kelvin wave forcing between the reanalyses, especially at 20–10 hPa. In addition, at around 20 hPa, a wave signal which appears only in easterly mean winds with westward phase speeds is found and discussed.
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Walsh, John E., William L. Chapman, and Diane H. Portis. "Arctic Cloud Fraction and Radiative Fluxes in Atmospheric Reanalyses." Journal of Climate 22, no. 9 (May 1, 2009): 2316–34. http://dx.doi.org/10.1175/2008jcli2213.1.
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Abstract Arctic radiative fluxes, cloud fraction, and cloud radiative forcing are evaluated from four currently available reanalysis models using data from the North Slope of Alaska (NSA) Barrow site of the Atmospheric Radiation Measurement Program (ARM). A primary objective of the ARM–NSA program is to provide a high-resolution dataset of direct measurements of Arctic clouds and radiation so that global climate models can better parameterize high-latitude cloud radiative processes. The four reanalysis models used in this study are the 1) NCEP–NCAR global reanalysis, 2) 40-yr ECMWF Re-Analysis (ERA-40), 3) NCEP–NCAR North American Regional Reanalysis (NARR), and 4) Japan Meteorological Agency and Central Research Institute of Electric Power Industry 25-yr Reanalysis (JRA25). The reanalysis models simulate the radiative fluxes well if/when the cloud fraction is simulated correctly. However, the systematic errors of climatological reanalysis cloud fractions are substantial. Cloud fraction and radiation biases show considerable scatter, both in the annual mean and over a seasonal cycle, when compared to those observed at the ARM–NSA. Large seasonal cloud fraction biases have significant impacts on the surface energy budget. Detailed comparisons of ARM and reanalysis products reveal that the persistent low-level cloud fraction in summer is particularly difficult for the reanalysis models to capture creating biases in the shortwave radiation flux that can exceed 160 W m−2. ERA-40 is the best performer in both shortwave and longwave flux seasonal representations at Barrow, largely because its simulation of the cloud coverage is the most realistic of the four reanalyses. Only two reanalyses (ERA-40 and NARR) capture the observed transition from positive to negative surface net cloud radiative forcing during a 2–3-month period in summer, while the remaining reanalyses indicate a net warming impact of Arctic clouds on the surface energy budget throughout the entire year. The authors present a variable cloud radiative forcing metric to diagnose the erroneous impact of reanalysis cloud fraction on the surface energy balance. The misrepresentations of cloud radiative forcing in some of the reanalyses are attributable to errors in both simulated cloud amounts and the models’ radiative response to partly cloudy conditions.
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Chang, Liang, Shiqiang Wen, Guoping Gao, Zhen Han, Guiping Feng, and Yang Zhang. "Assessment of Temperature and Specific Humidity Inversions and Their Relationships in Three Global Reanalysis Products over the Arctic Ocean." Journal of Applied Meteorology and Climatology 60, no. 4 (April 2021): 493–511. http://dx.doi.org/10.1175/jamc-d-20-0079.1.
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AbstractCharacteristics of temperature inversions (TIs) and specific humidity inversions (SHIs) and their relationships in three of the latest global reanalyses—the European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-I), the Japanese 55-year Reanalysis (JRA-55), and the ERA5—are assessed against in situ radiosonde (RS) measurements from two expeditions over the Arctic Ocean. All reanalyses tend to detect many fewer TI and SHI occurrences, together with much less common multiple TIs and SHIs per profile than are seen in the RS data in summer 2008, winter 2015, and spring 2015. The reanalyses generally depict well the relationships among TI characteristics seen in RS data, except for the TIs below 400 m in summer, as well as above 1000 m in summer and winter. The depth is simulated worst by the reanalyses among the SHI characteristics, which may result from its sensitivity to the uncertainties in specific humidity in the reanalyses. The strongest TI per profile in RS data exhibits more robust dependency on surface conditions than the strongest SHI per profile, and the former is better presented by the reanalyses than the latter. Furthermore, all reanalyses have difficulties simulating the relationships between TIs and SHIs, together with the correlations between the simultaneous inversions. The accuracy and vertical resolution in the reanalyses are both important to properly capture occurrence and characteristics of the Arctic inversions. In general, ERA5 performs better than ERA-I and JRA-55 in depicting the relationships among the TIs. However, the representation of SHIs is more challenging than TIs in all reanalyses over the Arctic Ocean.
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Lawrence, Zachary D., Gloria L. Manney, and Krzysztof Wargan. "Reanalysis intercomparisons of stratospheric polar processing diagnostics." Atmospheric Chemistry and Physics 18, no. 18 (September 25, 2018): 13547–79. http://dx.doi.org/10.5194/acp-18-13547-2018.
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Abstract. We compare herein polar processing diagnostics derived from the four most recent “full-input” reanalysis datasets: the National Centers for Environmental Prediction Climate Forecast System Reanalysis/Climate Forecast System, version 2 (CFSR/CFSv2), the European Centre for Medium-Range Weather Forecasts Interim (ERA-Interim) reanalysis, the Japanese Meteorological Agency's 55-year (JRA-55) reanalysis, and the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). We focus on diagnostics based on temperatures and potential vorticity (PV) in the lower-to-middle stratosphere that are related to formation of polar stratospheric clouds (PSCs), chlorine activation, and the strength, size, and longevity of the stratospheric polar vortex. Polar minimum temperatures (Tmin) and the area of regions having temperatures below PSC formation thresholds (APSC) show large persistent differences between the reanalyses, especially in the Southern Hemisphere (SH), for years prior to 1999. Average absolute differences of the reanalyses from the reanalysis ensemble mean (REM) in Tmin are as large as 3 K at some levels in the SH (1.5 K in the Northern Hemisphere – NH), and absolute differences of reanalysis APSC from the REM up to 1.5 % of a hemisphere (0.75 % of a hemisphere in the NH). After 1999, the reanalyses converge toward better agreement in both hemispheres, dramatically so in the SH: average Tmin differences from the REM are generally less than 1 K in both hemispheres, and average APSC differences less than 0.3 % of a hemisphere. The comparisons of diagnostics based on isentropic PV for assessing polar vortex characteristics, including maximum PV gradients (MPVGs) and the area of the vortex in sunlight (or sunlit vortex area, SVA), show more complex behavior: SH MPVGs showed convergence toward better agreement with the REM after 1999, while NH MPVGs differences remained largely constant over time; differences in SVA remained relatively constant in both hemispheres. While the average differences from the REM are generally small for these vortex diagnostics, understanding such differences among the reanalyses is complicated by the need to use different methods to obtain vertically resolved PV for the different reanalyses. We also evaluated other winter season summary diagnostics, including the winter mean volume of air below PSC thresholds, and vortex decay dates. For the volume of air below PSC thresholds, the reanalyses generally agree best in the SH, where relatively small interannual variability has led to many winter seasons with similar polar processing potential and duration, and thus low sensitivity to differences in meteorological conditions among the reanalyses. In contrast, the large interannual variability of NH winters has given rise to many seasons with marginal conditions that are more sensitive to reanalysis differences. For vortex decay dates, larger differences are seen in the SH than in the NH; in general, the differences in decay dates among the reanalyses follow from persistent differences in their vortex areas. Our results indicate that the transition from the reanalyses assimilating Tiros Operational Vertical Sounder (TOVS) data to advanced TOVS and other data around 1998–2000 resulted in a profound improvement in the agreement of the temperature diagnostics presented (especially in the SH) and to a lesser extent the agreement of the vortex diagnostics. We present several recommendations for using reanalyses in polar processing studies, particularly related to the sensitivity to changes in data inputs and assimilation. Because of these sensitivities, we urge great caution for studies aiming to assess trends derived from reanalysis temperatures. We also argue that one of the best ways to assess the sensitivity of scientific results on polar processing is to use multiple reanalysis datasets.
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Bosilovich, Michael G., Junye Chen, Franklin R. Robertson, and Robert F. Adler. "Evaluation of Global Precipitation in Reanalyses." Journal of Applied Meteorology and Climatology 47, no. 9 (September 1, 2008): 2279–99. http://dx.doi.org/10.1175/2008jamc1921.1.
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Abstract Retrospective-analysis (or reanalysis) systems merge observations and models to provide global four-dimensional earth system data encompassing many physical and dynamical processes. Precipitation is one critical diagnostic that is not only sensitive to the observing system and model physics, but also reflects the general circulation. Climate records of observed precipitation through a merged satellite and gauge dataset provide a reference for comparison, though not without their own uncertainty. In this study, five reanalyses precipitation fields are compared with two observed data products to assess the strengths and weaknesses of the reanalyses. Taylor diagrams show the skill of the reanalyses relative to the reference dataset. While there is a general sense that the reanalyses precipitation data are improving in recent systems, it is not always the case. In some ocean regions, NCEP–NCAR reanalysis spatial patterns are closer to observed precipitation than NCEP–Department of Energy. The 40-yr ECMWF reanalysis (ERA-40) produces reasonable comparisons over Northern Hemisphere continents, but less so in the tropical oceans. On the other hand, the most recent reanalysis, the Japanese 25-yr reanalysis (JRA-25), shows good comparisons in both the Northern Hemisphere continents and the tropical oceans but contains distinct variation according to the available observing systems. The statistics and methods used are also tested on short experiments from a data assimilation system proposed to perform a satellite-era reanalysis.
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Bao, Xinghua, and Fuqing Zhang. "How Accurate Are Modern Atmospheric Reanalyses for the Data-Sparse Tibetan Plateau Region?" Journal of Climate 32, no. 21 (September 25, 2019): 7153–72. http://dx.doi.org/10.1175/jcli-d-18-0705.1.
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Abstract More than 6000 independent radiosonde observations from three major Tibetan Plateau experiments during the warm seasons (May–August) of 1998, 2008, and 2015–16 are used to assess the quality of four leading modern atmospheric reanalysis products (CFSR/CFSv2, ERA-Interim, JRA-55, and MERRA-2), and the potential impact of satellite data changes on the quality of these reanalyses in the troposphere over this data-sparse region. Although these reanalyses can reproduce reasonably well the overall mean temperature, specific humidity, and horizontal wind profiles against the benchmark independent sounding observations, they have nonnegligible biases that can be potentially bigger than the analysis-simulated mean regional climate trends over this region. The mean biases and mean root-mean-square errors of winds, temperature, and specific humidity from almost all reanalyses are reduced from 1998 to the two later experiment periods. There are also considerable differences in almost all variables across different reanalysis products, though these differences also become smaller during the 2008 and 2015–16 experiments, in particular for the temperature fields. The enormous increase in the volume and quality of satellite observations assimilated into reanalysis systems is likely the primary reason for the improved quality of the reanalyses during the later field experiment periods. Besides differences in the forecast models and data assimilation methodology, the differences in performance between different reanalyses during different field experiment periods may also be contributed by differences in assimilated information (e.g., observation input sources, selected channels for a given satellite sensor, quality-control methods).
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Millán, Luis F., and Gloria L. Manney. "An assessment of ozone mini-hole representation in reanalyses over the Northern Hemisphere." Atmospheric Chemistry and Physics 17, no. 15 (August 4, 2017): 9277–89. http://dx.doi.org/10.5194/acp-17-9277-2017.
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Abstract. An ozone mini-hole is a synoptic-scale region with strongly decreased total column ozone resulting from dynamical processes. Using total column measurements from the Ozone Monitoring Instrument and ozone profile measurements from the Microwave Limb Sounder, we evaluate the accuracy of mini-hole representation in five reanalyses. This study provides a metric of the reanalyses' ability to capture dynamically driven ozone variability. The reanalyses and the measurements show similar seasonal variability and geographical distributions of mini-holes; however, all of the reanalyses underestimate the number of mini-holes and their area, and in many reanalyses their location displays an eastward bias. The reanalyses' underestimation of mini-hole number ranges from about 34 to about 83 %. The mini-hole vertical representation in the reanalyses agrees well with that in the MLS measurements and, furthermore, is consistent with previously reported mechanisms for mini-hole formation. The skill of the reanalyses is not closely tied to the ozone fields assimilated, suggesting that the dynamics of the reanalysis models are more important than the assimilated ozone fields to reproducing ozone mini-holes.
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Marquardt Collow, Allison B., Richard I. Cullather, and Michael G. Bosilovich. "Recent Arctic Ocean Surface Air Temperatures in Atmospheric Reanalyses and Numerical Simulations." Journal of Climate 33, no. 10 (May 15, 2020): 4347–67. http://dx.doi.org/10.1175/jcli-d-19-0703.1.
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AbstractSurface air temperatures have recently increased more rapidly in the Arctic than elsewhere in the world, but large uncertainty remains in the time series and trend. Over the data-sparse sea ice zone, the retrospective assimilation of observations in numerical reanalyses has been thought to offer a possible, but challenging, avenue for adequately reproducing the historical time series. Focusing on the central Arctic Ocean, output is analyzed from 12 reanalyses with a specific consideration of two widely used products: the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and the European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim, hereafter ERA-I). Among the reanalyses considered, a trend of 0.9 K decade−1 is indicated but with an uncertainty of 6%, and a large spread in mean values. There is a partitioning among those reanalyses that use fractional sea ice cover and those that employ a threshold, which are colder in winter by an average of 2 K but agree more closely with in situ observations. For reanalyses using fractional sea ice cover, discrepancies in the ice fraction in autumn and winter explain most of the differences in air temperature values. A set of experiments using the MERRA-2 background model using MERRA-2 and ERA-I sea ice and sea surface temperature indicates significant effects of boundary condition differences on air temperatures, and a preferential warm bias inherent in the MERRA-2 model sea ice representation. Differences between experiments and reanalyses suggest the available observations apply a significant constraint on reanalysis mean temperatures.
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Ayarzagüena, Blanca, Froila M. Palmeiro, David Barriopedro, Natalia Calvo, Ulrike Langematz, and Kiyotaka Shibata. "On the representation of major stratospheric warmings in reanalyses." Atmospheric Chemistry and Physics 19, no. 14 (July 26, 2019): 9469–84. http://dx.doi.org/10.5194/acp-19-9469-2019.
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Abstract. Major sudden stratospheric warmings (SSWs) represent one of the most abrupt phenomena of the boreal wintertime stratospheric variability, and constitute the clearest example of coupling between the stratosphere and the troposphere. A good representation of SSWs in climate models is required to reduce their biases and uncertainties in future projections of stratospheric variability. The ability of models to reproduce these phenomena is usually assessed with just one reanalysis. However, the number of reanalyses has increased in the last decade and their own biases may affect the model evaluation. Here we compare the representation of the main aspects of SSWs across reanalyses. The examination of their main characteristics in the pre- and post-satellite periods reveals that reanalyses behave very similarly in both periods. However, discrepancies are larger in the pre-satellite period compared to afterwards, particularly for the NCEP-NCAR reanalysis. All datasets reproduce similarly the specific features of wavenumber-1 and wavenumber-2 SSWs. A good agreement among reanalyses is also found for triggering mechanisms, tropospheric precursors, and surface response. In particular, differences in blocking precursor activity of SSWs across reanalyses are much smaller than between blocking definitions.
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Lee, Dong Eun, and Michela Biasutti. "Climatology and Variability of Precipitation in the Twentieth-Century Reanalysis." Journal of Climate 27, no. 15 (July 29, 2014): 5964–81. http://dx.doi.org/10.1175/jcli-d-13-00630.1.
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Abstract The performance of the Twentieth-Century Reanalysis (20CR) in reproducing observed monthly mean precipitation over the global domain is compared to that of comprehensive reanalyses that also assimilate upper-air and satellite observations [the Climate Forecast System Reanalysis (CFSR), ECMWF Interim Re-Analysis (ERA-Interim), and NCEP–U.S. Department of Energy reanalysis (NCEP2)] and to that of an atmospheric general circulation model (GCM) ensemble simulation [Global Ocean Global Atmosphere (GOGA)] that is forced with observed sea surface temperature (SST). Wintertime rainfall variability in the midlatitude continents and storm tracks is captured with great accuracy, similar to the comprehensive reanalyses, but summertime rainfall is not, probably in consequence of the greater importance of convection in the summer season. Over the tropics, the accuracy of all reanalyses is much less than over the midlatitudes. Over tropical land, the performance of 20CR is better than NCEP2 and similar to ERA-Interim and CFSR, but over the tropical oceans the most recent reanalyses perform significantly better. Across the twentieth century, the clearest gain from the assimilation of a denser observational dataset is the expansion of the area of good skill. A comparison of the accuracy and ensemble spread in the 20CR and GOGA ensembles highlights regions where SST forcing is a stronger source of skill than data assimilation for 20CR. In contrast, for some tropical regions such as the Sahel, the assimilation of sea level pressure is effective in constraining precipitation values—but model biases in the teleconnections with global SST limit the performance of 20CR.
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Chung, C. E., H. Cha, T. Vihma, P. Räisänen, and D. Decremer. "On the possibilities to use atmospheric reanalyses to evaluate the warming structure in the Arctic." Atmospheric Chemistry and Physics 13, no. 22 (November 18, 2013): 11209–19. http://dx.doi.org/10.5194/acp-13-11209-2013.
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Abstract. There has been growing interest in the vertical structure of the recent Arctic warming. We investigated temperatures at the surface, 925, 700, 500 and 300 hPa levels in the Arctic (north of 70° N) using observations and four reanalyses: ERA-Interim, CFSR, MERRA and NCEP II. For the period 1979–2011, the layers at 500 hPa and below show a warming trend in all seasons in all the chosen reanalyses and observations. Restricting the analysis to the 1998–2011 period, however, all the reanalyses show a cooling trend in the Arctic-mean 500 hPa temperature in autumn, and this also applies to both observations and the reanalyses when restricting the analysis to the locations with available IGRA radiosoundings. During this period, the surface observations mainly representing land areas surrounding the Arctic Ocean reveal no summertime trend, in contrast with the reanalyses whether restricted to the locations of the available surface observations or not. In evaluating the reanalyses with observations, we find that the reanalyses agree better with each other at the available IGRA sounding locations than for the Arctic average, perhaps because the sounding observations were assimilated into reanalyses. Conversely, using the reanalysis data only from locations matching available surface (air) temperature observations does not improve the agreement between the reanalyses. At 925 hPa, CFSR deviates from the other three reanalyses, especially in summer after 2000, and it also deviates more from the IGRA radiosoundings than the other reanalyses do. The CFSR error in summer T925 is due mainly to underestimations in the Canadian-Atlantic sector between 120° W and 0°. The other reanalyses also have negative biases in this longitude band.
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Kaspar, Frank, Deborah Niermann, Michael Borsche, Stephanie Fiedler, Jan Keller, Roland Potthast, Thomas Rösch, Thomas Spangehl, and Birger Tinz. "Regional atmospheric reanalysis activities at Deutscher Wetterdienst: review of evaluation results and application examples with a focus on renewable energy." Advances in Science and Research 17 (July 6, 2020): 115–28. http://dx.doi.org/10.5194/asr-17-115-2020.
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Abstract. Based on the numerical weather prediction model COSMO of Germany's national meteorological service (Deutscher Wetterdienst, DWD), regional reanalysis datasets have been developed with grid spacing of up to 2 km. This development started as a fundamental research activity within the Hans-Ertel-Centre for Weather Research (HErZ) at the University of Bonn and the University of Cologne. Today, COSMO reanalyses are an established product of the DWD and have been widely used in applications on European and national German level. Successful applications of COSMO reanalyses include renewable energy assessments as well as meteorological risk estimates. The COSMO reanalysis datasets are now publicly available and provide spatio-temporal consistent data of atmospheric parameters covering both near-surface conditions and vertical profiles. This article reviews the status of the COSMO reanalyses, including evaluation results and applications. In many studies, evaluation of the COSMO reanalyses point to an overall good quality and often an added value compared to different contemporary global reanalysis datasets. We further outline current plans for the further development and application of regional reanalyses in the HErZ research group Cologne/Bonn in collaboration with the DWD.
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Fu, Xiouhua, Bin Wang, June-Yi Lee, Wanqiu Wang, and Li Gao. "Sensitivity of Dynamical Intraseasonal Prediction Skills to Different Initial Conditions." Monthly Weather Review 139, no. 8 (August 2011): 2572–92. http://dx.doi.org/10.1175/2011mwr3584.1.
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AbstractPredictability of intraseasonal oscillation (ISO) relies on both initial conditions and lower boundary conditions (or atmosphere–ocean interaction). The atmospheric reanalysis datasets are commonly used as initial conditions. Here, the biases of three reanalysis datasets [the NCEP reanalysis 1 and 2 (NCEP-R1 and -R2) and the ECMWF Re-Analysis Interim (ERA-Interim)] in describing ISO were briefly revealed and the impacts of these biases as initial conditions on ISO prediction skills were assessed. A signal-recovery method is proposed to improve ISO prediction.Although all three reanalyses underestimate the intensity of the equatorial eastward-propagating ISO, the overall quality of the ERA-Interim is better than the NCEP-R1 and -R2. When these reanalyses are used as initial conditions in the ECHAM4-University of Hawaii hybrid coupled model (UH-HCM), skillful ISO prediction reaches only about 1 week for both the 850-hPa zonal winds (U850) and rainfall over Southeast Asia and the global tropics. An enhanced nudging of the divergence field is shown to significantly improve the initial conditions, resulting in an extension of the skillful rainfall prediction by 2–4 days and U850 prediction by 5–10 days.After recovering the ISO signals in the original reanalyses, the resultant initial conditions contain ISO strength closer to the observed, whereas the rainfall spatial pattern correlation in the ERA-Interim reanalysis drops. The resultant ISO prediction skills, however, are consistently extended for all the NCEP and ERA-Interim reanalyses. Using these signal-recovered reanalyses as initial conditions, the boreal summer ISO prediction skill measured with the Wheeler–Hendon index reaches 14 days. The U850 and rainfall prediction skills, respectively, reach 23 and 18 days over Southeast Asia. It is also found that small-scale synoptic weather disturbances in initial conditions generally increase ISO prediction skills. Both the UH-HCM and NCEP Climate Forecast System (CFS) suffer the prediction barrier over the Maritime Continent.
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Gossart, A., S. Helsen, J. T. M. Lenaerts, S. Vanden Broucke, N. P. M. van Lipzig, and N. Souverijns. "An Evaluation of Surface Climatology in State-of-the-Art Reanalyses over the Antarctic Ice Sheet." Journal of Climate 32, no. 20 (September 16, 2019): 6899–915. http://dx.doi.org/10.1175/jcli-d-19-0030.1.
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Abstract In this study, we evaluate output of near-surface atmospheric variables over the Antarctic Ice Sheet from four reanalyses: the new European Centre for Medium-Range Weather Forecasts ERA-5 and its predecessor ERA-Interim, the Climate Forecast System Reanalysis (CFSR), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The near-surface temperature, wind speed, and relative humidity are compared with datasets of in situ observations, together with an assessment of the simulated surface mass balance (approximated by precipitation minus evaporation). No reanalysis clearly stands out as the best performing for all areas, seasons, and variables, and each of the reanalyses displays different biases. CFSR strongly overestimates the relative humidity during all seasons whereas ERA-5 and MERRA-2 (and, to a lesser extent, ERA-Interim) strongly underestimate relative humidity during winter. ERA-5 captures the seasonal cycle of near-surface temperature best and shows the smallest bias relative to the observations. The other reanalyses show a general temperature underestimation during the winter months in the Antarctic interior and overestimation in the coastal areas. All reanalyses underestimate the mean near-surface winds in the interior (except MERRA-2) and along the coast during the entire year. The winds at the Antarctic Peninsula are overestimated by all reanalyses except MERRA-2. All models are able to capture snowfall patterns related to atmospheric rivers, with varying accuracy. Accumulation is best represented by ERA-5, although it underestimates observed surface mass balance and there is some variability in the accumulation over the different elevation classes, for all reanalyses.
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Donat, Markus G., Jana Sillmann, Simon Wild, Lisa V. Alexander, Tanya Lippmann, and Francis W. Zwiers. "Consistency of Temperature and Precipitation Extremes across Various Global Gridded In Situ and Reanalysis Datasets." Journal of Climate 27, no. 13 (July 2014): 5019–35. http://dx.doi.org/10.1175/jcli-d-13-00405.1.
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Changes in climate extremes are often monitored using global gridded datasets of climate extremes based on in situ observations or reanalysis data. This study assesses the consistency of temperature and precipitation extremes between these datasets. Both the temporal evolution and spatial patterns of annual extremes of daily values are compared across multiple global gridded datasets of in situ observations and reanalyses to make inferences on the robustness of the obtained results. While normalized time series generally compare well, the actual values of annual extremes of daily data differ systematically across the different datasets. This is partly related to different computational approaches when calculating the gridded fields of climate extremes. There is strong agreement between extreme temperatures in the different in situ–based datasets. Larger differences are found for temperature extremes from the reanalyses, particularly during the presatellite era, indicating that reanalyses are most consistent with purely observational-based analyses of changes in climate extremes for the three most recent decades. In terms of both temporal and spatial correlations, the ECMWF reanalyses tend to show greater agreement with the gridded in situ–based datasets than the NCEP reanalyses and Japanese 25-year Reanalysis Project (JRA-25). Extreme precipitation is characterized by higher temporal and spatial variability than extreme temperatures, and there is less agreement between different datasets than for temperature. However, reasonable agreement between the gridded observational precipitation datasets remains. Extreme precipitation patterns and time series from reanalyses show lower agreement but generally still correlate significantly.
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Zhou, Chunlüe, and Kaicun Wang. "Contrasting Daytime and Nighttime Precipitation Variability between Observations and Eight Reanalysis Products from 1979 to 2014 in China." Journal of Climate 30, no. 16 (August 2017): 6443–64. http://dx.doi.org/10.1175/jcli-d-16-0702.1.
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Daytime (0800–2000 Beijing time) and nighttime (2000–0800 Beijing time) precipitation at approximately 2100 stations in China from 1979 to 2014 was used to evaluate eight current reanalyses. Daytime, nighttime, and nighttime–daytime contrast of precipitation were examined in aspects of climatology, seasonal cycle, interannual variability, and trends. The results show that the ECMWF interim reanalysis (ERA-Interim), ERA-Interim/Land, Japanese 55-year Reanalysis (JRA-55), and NCEP Climate Forecast System Reanalysis (CFSR) can reproduce the observed spatial pattern of nighttime–daytime contrast in precipitation amount, exhibiting a positive center over the eastern Tibetan Plateau and a negative center over southeastern China. All of the reanalyses roughly reproduce seasonal variations of nighttime and daytime precipitation, but not always nighttime–daytime contrast. The reanalyses overestimate drizzle and light precipitation frequencies by greater than 31.5% and underestimate heavy precipitation frequencies by less than −30.8%. The reanalyses successfully reproduce interannual synchronizations of daytime and nighttime precipitation frequencies and amounts with an averaged correlation coefficient r of 0.66 against the observed data but overestimate their year-to-year amplitudes by approximately 64%. The trends in nighttime, daytime, and nighttime–daytime contrast of the observed precipitation amounts are mainly dominated by their frequencies ( r = 0.85). Less than moderate precipitation frequency has exhibited a significant downward trend (−2.5% decade−1 during nighttime and −1.7% decade−1 during daytime) since 1979, which is roughly captured by the reanalyses. However, only JRA-55 captures the observed trend of nighttime precipitation intensity (2.4% decade−1), while the remaining reanalyses show negative trends. Overall, JRA-55 and CFSR provide the best reproductions of the observed nighttime–daytime contrast in precipitation intensity, although they have considerable room for improvement.
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Huang, Yiyi, Xiquan Dong, Baike Xi, Erica K. Dolinar, Ryan E. Stanfield, and Shaoyue Qiu. "Quantifying the Uncertainties of Reanalyzed Arctic Cloud and Radiation Properties Using Satellite Surface Observations." Journal of Climate 30, no. 19 (September 6, 2017): 8007–29. http://dx.doi.org/10.1175/jcli-d-16-0722.1.
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Abstract Reanalyses have proven to be convenient tools for studying the Arctic climate system, but their uncertainties should first be identified. In this study, five reanalyses (JRA-55, 20CRv2c, CFSR, ERA-Interim, and MERRA-2) are compared with NASA CERES–MODIS (CM)-derived cloud fractions (CFs), cloud water paths (CWPs), top-of-atmosphere (TOA) and surface longwave (LW) and shortwave (SW) radiative fluxes over the Arctic (70°–90°N) over the period of 2000–12, and CloudSat–CALIPSO (CC)-derived CFs from 2006 to 2010. The monthly mean CFs in all reanalyses except JRA-55 are close to or slightly higher than the CC-derived CFs from May to September. However, wintertime CF cannot be confidently evaluated until instrument simulators are implemented in reanalysis products. The comparison between CM and CC CFs indicates that CM-derived CFs are reliable in summer but not in winter. Although the reanalysis CWPs follow the general seasonal variations of CM CWPs, their annual means are only half or even less than the CM-retrieved CWPs (126 g m−2). The annual mean differences in TOA and surface SW and LW fluxes between CERES EBAF and reanalyses are less than 6 W m−2 for TOA radiative fluxes and 16 W m−2 for surface radiative fluxes. All reanalyses show positive biases along the northern and eastern coasts of Greenland as a result of model elevation biases or possible CM clear-sky retrieval issues. The correlations between the reanalyses and CERES satellite retrievals indicate that all five reanalyses estimate radiative fluxes better than cloud properties, and MERRA-2 and JRA-55 exhibit comparatively higher correlations for Arctic cloud and radiation properties.
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Hodges, Kevin, Alison Cobb, and Pier Luigi Vidale. "How Well Are Tropical Cyclones Represented in Reanalysis Datasets?" Journal of Climate 30, no. 14 (July 2017): 5243–64. http://dx.doi.org/10.1175/jcli-d-16-0557.1.
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Tropical cyclones (TCs) are identified and tracked in six recent reanalysis datasets and compared with those from the IBTrACS best-track archive. Results indicate that nearly every cyclone present in IBTrACS over the period 1979–2012 can be found in all six reanalyses using a tracking and matching approach. However, TC intensities are significantly underrepresented in the reanalyses compared to the observations. Applying a typical objective TC identification scheme, it is found that the largest uncertainties in TC identification occur for the weaker storms; this is exacerbated by uncertainties in the observations for weak storms and lack of consistency in operational procedures. For example, certain types of storms, such as tropical depressions, subtropical cyclones, and monsoon depressions, are not included in the best-track data for all reporting agencies. There are definite improvements in how well TCs are represented in more recent, higher-resolution reanalyses; in particular MERRA-2 is comparable with the NCEP-CFSR and JRA-55 reanalyses, which perform significantly better than the older MERRA reanalysis.
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Schenkel, Benjamin A., and Robert E. Hart. "An Examination of Tropical Cyclone Position, Intensity, and Intensity Life Cycle within Atmospheric Reanalysis Datasets." Journal of Climate 25, no. 10 (May 14, 2012): 3453–75. http://dx.doi.org/10.1175/2011jcli4208.1.
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Abstract The following study examines the position and intensity differences of tropical cyclones (TCs) among the Best-Track and five atmospheric reanalysis datasets to evaluate the degree to which reanalyses are appropriate for studying TCs. While significant differences are found in both reanalysis TC intensity and position, the representation of TC intensity within reanalyses is found to be most problematic owing to its underestimation beyond what can be attributed solely to the coarse grid resolution. Moreover, the mean life cycle of normalized TC intensity within reanalyses reveals an underestimation of both prepeak intensification rates as well as a delay in peak intensity relative to the Best-Track. These discrepancies between Best-Track and reanalysis TC intensity and position can further be described through correlations with such parameters as Best-Track TC age, Best-Track TC intensity, Best-Track TC location, and the extended Best-Track TC size. Specifically, TC position differences within the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), ECMWF Interim Re-Analysis (ERA-I), and Modern Era Retrospective-Analysis for Research and Applications (MERRA) exhibit statistically significant correlations (0.27 ≤ R ≤ 0.38) with the proximity of TCs to observation dense areas in the North Atlantic (NATL) and western North Pacific (WPAC). Reanalysis TC intensity is found to be most strongly correlated with Best-Track TC size (0.53 ≤ R ≤ 0.70 for maximum 10-m wind speed; −0.71 ≤ R ≤ −0.53 for minimum mean sea level pressure) while exhibiting smaller, yet significant, correlations with Best-Track TC age, Best-Track TC intensity, and Best-Track TC latitude. Of the three basins examined, the eastern North Pacific (EPAC) has the largest reanalysis TC position differences and weakest intensities possibly due to a relative dearth of observations, the strong nearby terrain gradient, and the movement of TCs away from the most observation dense portion of the basin over time. The smaller mean Best-Track size and shorter mean lifespan of Best-Track EPAC TCs may also yield weaker reanalysis TC intensities. Of the five reanalyses, the smaller position differences and stronger intensities found in the Climate Forecast System Reanalysis (CFSR) and Japanese 25-year Reanalysis (JRA-25) are attributed to the use of vortex relocation and TC wind profile retrievals, respectively. The discrepancies in TC position between the Best-Track and reanalyses combined with the muted magnitude of TC intensity and its partially nonphysical life cycle within reanalyses suggests that caution should be exercised when utilizing these datasets for studies that rely either on TC intensity (raw or normalized) or track. Finally, several cases of nonphysical TC structure also argue that further work is needed to improve TC representation while implying that studies focusing solely on TC intensity and track do not necessarily extend to other aspects of TC representation.
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Di Luca, Alejandro, Jason P. Evans, Acacia Pepler, Lisa Alexander, and Daniel Argüeso. "Resolution Sensitivity of Cyclone Climatology over Eastern Australia Using Six Reanalysis Products*." Journal of Climate 28, no. 24 (January 15, 2015): 9530–49. http://dx.doi.org/10.1175/jcli-d-14-00645.1.
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Abstract The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences.
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Bukovsky, Melissa S., and David J. Karoly. "A Brief Evaluation of Precipitation from the North American Regional Reanalysis." Journal of Hydrometeorology 8, no. 4 (August 1, 2007): 837–46. http://dx.doi.org/10.1175/jhm595.1.
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Abstract Several aspects of the precipitation climatology from the North American Regional Reanalysis (NARR) are analyzed and compared with two other reanalyses and one set of gridded observations over a domain encompassing the United States. The spatial distribution, diurnal cycle, and annual cycle of precipitation are explored to establish the reliability of the reanalyses and to judge their usefulness. While the NARR provides a much improved representation of precipitation over that of the other reanalyses examined, some inaccuracies are found and have been highlighted as a warning to potential users of the data.
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Essou, Gilles R. C., Florent Sabarly, Philippe Lucas-Picher, François Brissette, and Annie Poulin. "Can Precipitation and Temperature from Meteorological Reanalyses Be Used for Hydrological Modeling?" Journal of Hydrometeorology 17, no. 7 (July 1, 2016): 1929–50. http://dx.doi.org/10.1175/jhm-d-15-0138.1.
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Abstract This paper investigates the potential of reanalyses as proxies of observed surface precipitation and temperature to force hydrological models. Three global atmospheric reanalyses (ERA-Interim, CFSR, and MERRA), one regional reanalysis (NARR), and one global meteorological forcing dataset obtained by bias-correcting ERA-Interim [Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] were compared to one gridded observation database over the contiguous United States. Results showed that all temperature datasets were similar to the gridded observation over most of the United States. On the other hand, precipitation from all three global reanalyses was biased, especially in summer and winter in the southeastern United States. The regional reanalysis precipitation was closer to observations since it indirectly assimilates surface precipitation. The WFDEI dataset was generally less biased than the reanalysis datasets. All datasets were then used to force a global conceptual hydrological model on 370 watersheds of the Model Parameter Estimation Experiment (MOPEX) database. River flows were computed for each watershed, and results showed that the flows simulated using NARR and gridded observations forcings were very similar to the observed flows. The simulated flows forced by the global reanalysis datasets were also similar to the observations, except in the humid continental and subtropical climatic regions, where precipitation seasonality biases degraded river flow simulations. The WFDEI dataset led to better river flows than reanalysis in the humid continental and subtropical climatic regions but was no better than reanalysis—and sometimes worse—in other climatic zones. Overall, the results indicate that global reanalyses have good potential to be used as proxies to observations to force hydrological models, especially in regions with few weather stations.
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Trenberth, Kevin E., John T. Fasullo, and Jessica Mackaro. "Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses." Journal of Climate 24, no. 18 (September 15, 2011): 4907–24. http://dx.doi.org/10.1175/2011jcli4171.1.
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Abstract An assessment is made of the global energy and hydrological cycles from eight current atmospheric reanalyses and their depiction of changes over time. A brief evaluation of the water and energy cycles in the latest version of the NCAR climate model referred to as CCSM4 is also given. The focus is on the mean ocean, land, and global precipitation P; the corresponding evaporation E; their difference corresponding to the surface freshwater flux E–P; and the vertically integrated atmospheric moisture transports. Using the model-based P and E, the time- and area-average E–P for the oceans, P–E for land, and the moisture transport from ocean to land should all be identical but are not close in most reanalyses, and often differ significantly from observational estimates of the surface return flow based on net river discharge into the oceans. Their differences reveal outstanding issues with atmospheric models and their biases, which are manifested as analysis increments in the reanalyses. The NCAR CCSM4, along with most reanalysis models, the exception being MERRA, has too-intense water cycling (P and E) over the ocean although ocean-to-land transports are very close to observed. Precipitation from reanalyses that assimilate moisture from satellite observations exhibits large changes identified with the changes in the observing system, as new and improved temperature and water vapor channels are assimilated and, while P improves after about 2002, E–P does not. Discrepancies among hydrological cycle components arise from analysis increments that can add or subtract moisture. The large-scale moisture budget divergences are more stable in time and similar across reanalyses than model-based estimates of E–P. Results are consistent with the view that recycling of moisture is too large in most models and the lifetime of moisture is too short. For the energy cycle, most reanalyses have spurious imbalances of ~10 W m−2 within the atmosphere, and ~5–10 W m−2 in net fluxes into the surface and to space. Major improvements are needed in model treatment and assimilation of moisture, and surface fluxes from reanalyses should only be used with great caution.
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Rienecker, Michele M., Max J. Suarez, Ronald Gelaro, Ricardo Todling, Julio Bacmeister, Emily Liu, Michael G. Bosilovich, et al. "MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications." Journal of Climate 24, no. 14 (July 15, 2011): 3624–48. http://dx.doi.org/10.1175/jcli-d-11-00015.1.
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Abstract The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).
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Coburn, Jacob J. "Assessing Wind Data from Reanalyses for the Upper Midwest." Journal of Applied Meteorology and Climatology 58, no. 3 (March 2019): 429–46. http://dx.doi.org/10.1175/jamc-d-18-0164.1.
Full textAbstract:
AbstractWind is an important atmospheric variable that is receiving increased attention as the world seeks to shift from carbon-based fuels in order to mitigate climate change. This has resulted in increased need for more temporally and spatially continuous wind information, which is often met through the use of reanalysis data. However, limited work has been done to assess the long-term accuracy of the wind data against observations in the context of specific applications. This study focuses on the representation of daily and monthly average 10-m wind speed data in the upper Midwest by six global reanalysis datasets. The accuracy of the datasets was assessed using several measures of skill, as well as the associated wind speed distributions and long-term trends. While it was found that higher resolution and complexity in more recent generations of reanalyses produced more accurate simulations of wind in the region, important biases remained. High variability in the observed data resulted in lower correlations at the monthly time scale. As with previous research, linear trends calculated from the reanalyzed wind speeds were significantly underestimated compared to observed trends. While it is expected that future improvements in model resolution, physics, and data assimilation will further improve wind representation in reanalyses, accounting for the differences between the available datasets and their associated biases will be important for potential applications of the output, particularly wind resource assessment.