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Atmosphere
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Climate Reanalysis
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Climate Reanalysis

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 13138

Special Issue Editors

Prof. Dr. Chunlei Liu

E-Mail Website
Guest Editor
South China Sea Institute of Marine Meteorology, Guangdong Ocean University, Zhanjiang 524088, China
Interests: climate change; Earth system energy budget change; water cycle change; tropical cyclone
Special Issues, Collections and Topics in MDPI journals
Dr. Todd R. Jones

E-Mail Website
Guest Editor
Department of Meteorology, University of Reading, Reading RG6 6BB, UK
Interests: numerical weather prediction; atmospheric modelling; tropical convection; convective parameterisation

Special Issue Information

Dear Colleagues,

We would like to invite you to contribute to a Special Issue of Atmosphere dedicated to research results based on climatological reanalyses of the Earth’s atmosphere and oceans. Continual improvements in geophysical modelling, observation, and data assimilation techniques have given rise to a number of more spatially and temporally complete and physically consistent reanalysis datasets produced by institutions such as ECMWF, NASA, JMA, NOAA, NCEP, CMEMS, GFDL, and ZMAW. Many such sophisticated, synthetic representations of the Earth system now incorporate hundreds of state variables, with the horizontal resolution as high as 0.25 × 0.25°, enabling the detailed study of global and regional climate phenomena on timescales up to a century or more. Reanalysis products have proven to be popular tools in weather and climate research and monitoring, as well as in practical commercial applications in areas such as insurance, energy, hydrology, and agriculture. At the same time, challenges remain; systematic model biases, observational inconsistencies, and assimilation deficiencies are known to affect the reliability of climate statistics and the nature of physical processes represented in the reanalysis products. 

This Special Issue aims to (1) highlight improvements in our understanding of geophysical climate processes and phenomena made possible by recent advances in the state of climate reanalyses and to (2) call attention to key areas where our understanding remains incomplete and could be developed by further progress in reanalysis techniques. As such, we welcome research topics concerning new developments and applications of all types of reanalyses, as well as those addressing their evaluation and intercomparison. 

While a broad range of ideas are welcome, topics specifically encouraged include:

  • Earth energy budget and water cycle change—accuracy in the representation of TOA and surface fluxes and energy transport; precipitation and ITCZ variation; understanding the energy constraint to precipitation;
  • Atmosphere–ocean–cryosphere coupled variability and change—effect of surface and boundary layer on the atmosphere, ENSO variation, etc.;
  • Land–atmosphere coupling, including biosphere–atmosphere coupling—soil moisture, vegetation dynamics, drought, heatwave, cloud formation, convection, land cover change, aerosols, process understanding;
  • Interactions between scales—multiscale interactions, boundary layer, ocean, and atmosphere;
  • Tropical–extratropical interactions—deep convection, overturning circulation, Rossby wavetrains, ENSO, MJO, teleconnection;
  • Troposphere–stratosphere interactions, including the interplay between chemistry and dynamics—mass and chemical transport, gravity wave, ozone intrusion, large and small scales.

Manuscripts may present original research or review previous work and summarise the current state of the science.

Dr. Chunlei Liu
Dr. Todd R. Jones
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Earth energy budget change
  • Water cycle change
  • Climate change
  • Global warming
  • Climate dynamics
  • Atmospheric dynamics
  • Tropical–extratropical interactions
  • Arctic–midlatitude interactions
  • Troposphere–stratosphere coupling
  • Coupled variability
  • Atmospheric and ocean reanalyses
  • Atmospheric, oceanic, and cryospheric observation
  • Land–atmosphere coupling
  • Biosphere–atmosphere coupling

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

13 pages, 414 KiB  
Article
Which Reanalysis Dataset Should We Use for Renewable Energy Analysis in Ireland?
by Eadaoin Doddy Clarke, Seánie Griffin, Frank McDermott, João Monteiro Correia and Conor Sweeney
Atmosphere 2021, 12(5), 624; https://doi.org/10.3390/atmos12050624 - 13 May 2021
Cited by 24 | Viewed by 4270
Abstract
Attention should always be given to which reanalysis dataset to use when preparing analysis for a project. The accuracies of three reanalysis datasets, two global (ERA5 and MERRA-2) and one high-resolution regional reanalysis (MÉRA), are assessed by comparison with observations at seven weather [...] Read more.
Attention should always be given to which reanalysis dataset to use when preparing analysis for a project. The accuracies of three reanalysis datasets, two global (ERA5 and MERRA-2) and one high-resolution regional reanalysis (MÉRA), are assessed by comparison with observations at seven weather observing stations around Ireland. Skill scores are calculated for the weather variables at these stations that are most relevant to the renewable energy sector: 10 m wind for wind power; surface shortwave radiation (SW) and 2 m temperature for photovoltaic power generation. The choice of which reanalysis dataset to use is important when future planning depends on this data. The newer ERA5 generally outperforms the other two reanalyses. However, this is not always true, and the best performing reanalysis dataset often depends on the variable of interest and location. As errors are significant for these reanalysis datasets, consideration should also be given to datasets specifically tailored to renewable energy resource modelling. Full article
(This article belongs to the Special Issue Climate Reanalysis)
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19 pages, 2915 KiB  
Article
Biases of Global Tropopause Altitude Products in Reanalyses and Implications for Estimates of Tropospheric Column Ozone
by Lingyun Meng, Jane Liu, David W. Tarasick and Yingjie Li
Atmosphere 2021, 12(4), 417; https://doi.org/10.3390/atmos12040417 - 24 Mar 2021
Cited by 2 | Viewed by 2732
Abstract
Accuracy of global tropopause altitude products from reanalyses is important to applications of the products, including the derivation of tropospheric column ozone (TCO). Here, monthly biases in lapse-rate tropopause pressure (PLRT) in two reanalyses, NCEP/NCAR and MERRA-2, and associated implications for [...] Read more.
Accuracy of global tropopause altitude products from reanalyses is important to applications of the products, including the derivation of tropospheric column ozone (TCO). Here, monthly biases in lapse-rate tropopause pressure (PLRT) in two reanalyses, NCEP/NCAR and MERRA-2, and associated implications for estimating TCO are examined, based on global radiosonde observations over 1980–2017 at 689 stations. Our analysis suggests that the global mean PLRT is underestimated by −2.3 hPa in NCEP/NCAR and by −0.9 hPa in MERRA-2, mainly attributable to large negative biases around the subtropics (~20°–50°) in both hemispheres, with generally positive biases at other latitudes. Overall, NCEP/NCAR outperforms MERRA-2 in the Northern Hemisphere but underperforms MERRA-2 in the Southern Hemisphere. PLRT biases in the two reanalyses vary more evidently with latitude than with longitude. From winter to summer, the peaks of negative PLRT biases around the subtropics shift poleward by ~10°. Approximately, 70% of the reanalysis PLRT biases are within −10–10 hPa. Consequently, a negative (positive) PLRT bias induces a positive (negative) TCO bias. In absolute magnitude, the mean ozonesonde TCO bias attributable to PLRT biases is ~0.2, ~0.8 and ~1.2 Dobson Units (DU) if a PLRT bias is within 0–5, 10–15, and 10–15 hPa. Using a global ozone climatology, we estimate that the global mean bias in TCO induced by the PLRT biases in both reanalyses is positive, being 0.64 DU (or 2.2%) for NCEP/NCAR and 0.28 DU (or 1.1%) for MERRA-2. Full article
(This article belongs to the Special Issue Climate Reanalysis)
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11 pages, 2657 KiB  
Article
Elevation-Dependent Trend in Diurnal Temperature Range in the Northeast China during 1961–2015
by Yanyu Zhang, Xiangjin Shen and Gaohua Fan
Atmosphere 2021, 12(3), 319; https://doi.org/10.3390/atmos12030319 - 28 Feb 2021
Cited by 11 | Viewed by 2978
Abstract
The diurnal temperature range (DTR) is considered a signature of observed climate change, which is defined as the difference between the maximum (Tmax) and minimum temperatures (Tmin). It is well known that the warming rate of mean temperature is [...] Read more.
The diurnal temperature range (DTR) is considered a signature of observed climate change, which is defined as the difference between the maximum (Tmax) and minimum temperatures (Tmin). It is well known that the warming rate of mean temperature is larger at high elevations than at low elevations in northeast China. However, it is still uncertain whether DTR trend is greater at high elevations. This study examined the spatiotemporal variation in DTR and its relationship with elevation in northeast China based on data from 68 meteorological stations from 1961 to 2015. The results show that there was a significant declining trend (0.252 °C/decade) in DTR from 1961 to 2015 due to the fact that Tmin increased at a faster rate than Tmax. Seasonally, DTR in northeast China showed a decreasing trend with the largest decrease rate in spring (−0.3167 °C/decade) and the smallest decrease rate in summer (−0.1725 °C/decade). The results of correlation analysis show that there was a significant positive correlation between the annual DTR trend and elevation in northeast China. This is due to the fact that increasing elevation has a significant warming effect on Tmax. Seasonally, there were significant positive correlations between the DTR trend and elevation in all seasons. The elevation gradient of DTR trend was the greatest in winter (0.392 °C/decade/km) and the lowest in autumn (0.209 °C/decade/km). In spring, summer, and autumn, increasing elevation has a significant warming effect on Tmax, leading to a significant increase of the DTR trend with increasing elevation. However, in winter, increasing elevation has a significant cooling effect on Tmin, resulting in a significant increase of the DTR trend with increasing elevation. Full article
(This article belongs to the Special Issue Climate Reanalysis)
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25 pages, 2044 KiB  
Article
Long-Term Variability of Relationships between Potential Large-Scale Drivers and Summer Precipitation in North China in the CERA-20C Reanalysis
by Lan Dai and Jonathon S. Wright
Atmosphere 2021, 12(1), 81; https://doi.org/10.3390/atmos12010081 - 7 Jan 2021
Cited by 3 | Viewed by 2389
Abstract
Although much progress has been made in identifying the large-scale drivers of recent summer precipitation variability in North China, the evolution of these drivers over longer time scales remains unclear. We investigate multidecadal and interannual variability in North China summer precipitation in the [...] Read more.
Although much progress has been made in identifying the large-scale drivers of recent summer precipitation variability in North China, the evolution of these drivers over longer time scales remains unclear. We investigate multidecadal and interannual variability in North China summer precipitation in the 110-year Coupled ECMWF Reanalysis of the Twentieth Century (CERA-20C), considering changes in regional moisture and surface energy budgets along with nine circulation indices linked to anomalous precipitation in this region. The CERA-20C record is separated into three distinct periods according to the running climatology of summer precipitation: 1901–1944 (neutral), 1945–1979 (wet), and 1980–2010 (dry). CERA-20C reproduces expected relationships between large-scale drivers and regional summer precipitation anomalies well during 1980–2010, but these relationships generally do not extend to earlier periods. For example, a strong relationship with the Eurasian teleconnection pattern only emerges in the late 1970s, while correlations with the El Niño-Southern Oscillation and the Pacific–Japan pattern change sign in the mid-twentieth century. We evaluate two possible reasons for this nonstationarity: (1) the underlying atmospheric model may require strong data assimilation constraints to capture large-scale circulation influences on North China, or (2) large-scale drivers inferred from recent records may be less general than expected. Our analysis indicates that both factors contribute to the identified nonstationarity in CERA-20C, with implications for the reliability of seasonal forecasts and climate projections based on current models. Full article
(This article belongs to the Special Issue Climate Reanalysis)
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