Description: The significant climate feedback of stratospheric water vapor (SWV) necessitates quantitative estimates of SWV budget changes. Model simulations driven by the newest European Centre for Medium‐Range Weather Forecast reanalysis ERA5, satellite observations from the Stratospheric Water and OzOne Satellite Homogenized data set, Microwave Limb Sounder, and in situ frost point hygrometer observations from Boulder all show substantial and persistent stratospheric moistening after a sharp drop in water vapor at the turn of the millennium. This moistening occurred mainly during 2000–2006 and SWV abundances then remained high over the last decade. We find strong positive trends in the Northern Hemisphere and weak negative trends over the South Pole, mainly during austral winter. Moistening of the tropical stratosphere after 2000 occurred during late boreal winter/spring, reached values of ∼0.2 ppm/decade, was well correlated with a warming of the cold point tropopause by ∼0.4 K/decade and can only be partially attributed to El Nino‐Southern Oscillation and volcanic eruptions.

Description: Plain Language Summary: Water vapor is an effective greenhouse gas. Human‐induced climate change has led to warmer air in the troposphere, which consequently can hold more moisture, thus enhancing the greenhouse effect. The long‐term change in stratospheric water vapor (SWV) is less clear and currently under debate. Using satellite observations, balloon soundings and model simulations, we find an increase of SWV after 2000. This moistening occurred mainly during 2000–2006 and the stratospheric moisture content then remained high over the last decade. The increase of SWV is stronger in the Northern than in the Southern Hemisphere. Over the South Pole, a weak decrease was found. Moistening of the tropical stratosphere occurred mainly during late winter and spring, and was in line with warming of the tropical tropopause, the coldest region that separates the troposphere and stratosphere. Natural causes such as volcanic eruptions cannot completely explain this stratospheric moistening.

Description: Key Points: Stratospheric moistening after 2000 is clearly detectable in ERA5‐driven simulations, satellite and in situ observations. Hemispheric asymmetry is found with strong positive trends in the Northern Hemisphere and weak negative trends over the South Pole. Moistening of the lower tropical stratosphere is only partially caused by El Nino‐Southern Oscillation and volcanic eruptions.

Description: https://doi.org/10.5067/Aura/MLS/DATA2508

Description: https://doi.org/10.5067/GLOSSAC-L3-V2.0

Description: https://doi.org/10.5067/GLOSSAC-L3-V2.0

Description: Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 31 (2018): 7751-7769, doi:10.1175/JCLI-D-18-0184.1.

Description: Decadal variability of the subsurface ocean heat content (OHC) in the Indian Ocean is investigated using a coupled climate model experiment, in which observed eastern tropical Pacific sea surface temperature (EPSST) anomalies are specified. This study intends to understand the contributions of external forcing relative to those of internal variability associated with EPSST, as well as the mechanisms by which the Pacific impacts Indian Ocean OHC. Internally generated variations associated with EPSST dominate decadal variations in the subsurface Indian Ocean. Consistent with ocean reanalyses, the coupled model reproduces a pronounced east–west dipole structure in the southern tropical Indian Ocean and discontinuities in westward-propagating signals in the central Indian Ocean around 100°E. This implies distinct mechanisms by which the Pacific impacts the eastern and western Indian Ocean on decadal time scales. Decadal variations of OHC in the eastern Indian Ocean are attributed to 1) western Pacific surface wind anomalies, which trigger oceanic Rossby waves propagating westward through the Indonesian Seas and influence Indonesian Throughflow transport, and 2) zonal wind anomalies over the central tropical Indian Ocean, which trigger eastward-propagating Kelvin waves. Decadal variations of OHC in the western Indian Ocean are linked to conditions in the Pacific via changes in the atmospheric Walker cell, which trigger anomalous wind stress curl and Ekman pumping in the central tropical Indian Ocean. Westward-propagating oceanic Rossby waves extend the influence of this anomalous Ekman pumping to the western Indian Ocean.

Description: This research was supported by the Independent Research and Development Program at WHOI to CCU, an NSF OCE PO grant (NSF OCE- 1242989) to Young-Oh Kwon, NOAA CP CVP grants (NA15OAR4310176 and NA17OAR4310255) to Hyodae Seo, and a research grant fromtheMinistry of Science and Technology of the People’s Republic of China to Tsinghua University (2017YFA0603902).

Description: 2019-02-13

Description: Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 31 (2018): 4157-4174, doi:10.1175/JCLI-D-17-0654.1.

Description: Decadal variabilities in Indian Ocean subsurface ocean heat content (OHC; 50–300 m) since the 1950s are examined using ocean reanalyses. This study elaborates on how Pacific variability modulates the Indian Ocean on decadal time scales through both oceanic and atmospheric pathways. High correlations between OHC and thermocline depth variations across the entire Indian Ocean Basin suggest that OHC variability is primarily driven by thermocline fluctuations. The spatial pattern of the leading mode of decadal Indian Ocean OHC variability closely matches the regression pattern of OHC on the interdecadal Pacific oscillation (IPO), emphasizing the role of the Pacific Ocean in determining Indian Ocean OHC decadal variability. Further analyses identify different mechanisms by which the Pacific influences the eastern and western Indian Ocean. IPO-related anomalies from the Pacific propagate mainly through oceanic pathways in the Maritime Continent to impact the eastern Indian Ocean. By contrast, in the western Indian Ocean, the IPO induces wind-driven Ekman pumping in the central Indian Ocean via the atmospheric bridge, which in turn modifies conditions in the southwestern Indian Ocean via westward-propagating Rossby waves. To confirm this, a linear Rossby wave model is forced with wind stresses and eastern boundary conditions based on reanalyses. This linear model skillfully reproduces observed sea surface height anomalies and highlights both the oceanic connection in the eastern Indian Ocean and the role of wind-driven Ekman pumping in the west. These findings are also reproduced by OGCM hindcast experiments forced by interannual atmospheric boundary conditions applied only over the Pacific and Indian Oceans, respectively.

Description: This research was supported by a scholarship from the China Scholarship Council (CSC) to X. J., a research fellowship by the Alexander von Humboldt Foundation to C. C. U., an NSF OCE PO Grant (OCE- 1242989) to Y.-O. K., the ONR Young Investigator Award (N00014-15-1-2588) to H. S., and a research grant from the Ministry of Science and Technology of the People’s Republic of China to Tsinghua University (2017YFA0603902).

Description: 2018-10-30

Description: Decadal variabilities in Indian Ocean subsurface ocean heat content (OHC; 50–300 m) since the 1950s are examined using ocean reanalyses. This study elaborates on how Pacific variability modulates the Indian Ocean on decadal time scales through both oceanic and atmospheric pathways. High correlations between OHC and thermocline depth variations across the entire Indian Ocean Basin suggest that OHC variability is primarily driven by thermocline fluctuations. The spatial pattern of the leading mode of decadal Indian Ocean OHC variability closely matches the regression pattern of OHC on the interdecadal Pacific oscillation (IPO), emphasizing the role of the Pacific Ocean in determining Indian Ocean OHC decadal variability. Further analyses identify different mechanisms by which the Pacific influences the eastern and western Indian Ocean. IPO-related anomalies from the Pacific propagate mainly through oceanic pathways in the Maritime Continent to impact the eastern Indian Ocean. By contrast, in the western Indian Ocean, the IPO induces wind-driven Ekman pumping in the central Indian Ocean via the atmospheric bridge, which in turn modifies conditions in the southwestern Indian Ocean via westward-propagating Rossby waves. To confirm this, a linear Rossby wave model is forced with wind stresses and eastern boundary conditions based on reanalyses. This linear model skillfully reproduces observed sea surface height anomalies and highlights both the oceanic connection in the eastern Indian Ocean and the role of wind-driven Ekman pumping in the west. These findings are also reproduced by OGCM hindcast experiments forced by interannual atmospheric boundary conditions applied only over the Pacific and Indian Oceans, respectively.

Description: 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.

Description: 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.

Description: The tropical tropopause layer (TTL) is the transition region between the well-mixed convective troposphere and the radiatively controlled stratosphere with air masses showing chemical and dynamical properties of both regions. The representation of the TTL in meteorological reanalysis data sets is important for studying the complex interactions of circulation, convection, trace gases, clouds, and radiation. In this paper, we present the evaluation of climatological and long-term TTL temperature and tropopause characteristics in the reanalysis data sets ERA-Interim, ERA5, JRA-25, JRA-55, MERRA, MERRA-2, NCEP-NCAR (R1), and CFSR. The evaluation has been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The most recent atmospheric reanalysis data sets (ERA-Interim, ERA5, JRA-55, MERRA-2, and CFSR) all provide realistic representations of the major characteristics of the temperature structure within the TTL. There is good agreement between reanalysis estimates of tropical mean temperatures and radio occultation data, with relatively small cold biases for most data sets. Temperatures at the cold point and lapse rate tropopause levels, on the other hand, show warm biases in reanalyses when compared to observations. This tropopause-level warm bias is related to the vertical resolution of the reanalysis data, with the smallest bias found for data sets with the highest vertical resolution around the tropopause. Differences in the cold point temperature maximize over equatorial Africa, related to Kelvin wave activity and associated disturbances in TTL temperatures. Interannual variability in reanalysis temperatures is best constrained in the upper TTL, with larger differences at levels below the cold point. The reanalyses reproduce the temperature responses to major dynamical and radiative signals such as volcanic eruptions and the quasi-biennial oscillation (QBO). Long-term reanalysis trends in temperature in the upper TTL show good agreement with trends derived from adjusted radiosonde data sets indicating significant stratospheric cooling of around −0.5 to −1 K per decade. At 100 hPa and the cold point, most of the reanalyses suggest small but significant cooling trends of −0.3 to −0.6 K per decade that are statistically consistent with trends based on the adjusted radiosonde data sets. Advances of the reanalysis and observational systems over the last decades have led to a clear improvement in the TTL reanalysis products over time. Biases of the temperature profiles and differences in interannual variability clearly decreased in 2006, when densely sampled radio occultation data started being assimilated by the reanalyses. While there is an overall good agreement, different reanalyses offer different advantages in the TTL such as realistic profile and cold point temperature, continuous time series, or a realistic representation of signals of interannual variability. Their use in model simulations and in comparisons with climate model output should be tailored to their specific strengths and weaknesses.

Description: The S-RIP activity focuses predominantly on reanalyses, although some chapters include diagnostics from operational analyses when appropriate. Many of the chapters focus primarily on newer reanalysis systems that assimilate upper-air measurements and produce data at relatively high resolution (i.e., ERA-Interim, JRA55, MERRA, MERRA-2, and CFSR). The ERA5 reanalysis, which was released during the latter stages of the activity, is not fully evaluated but is included in some intercomparisons. Selected long-term reanalyses that assimilate only surface meteorological observations (e.g., NOAA-CIRES 20CR, ERA-20C, and CERA-20C) are also evaluated where appropriate. Some chapters include comparisons with older reanalyses (NCEP-NCAR R1, NCEP-DOE R2, ERA-40, and JRA-25/JCDAS), because these products have been extensively used in the past and are still being used for some studies, and because such comparisons can provide insight into the potential shortcomings of past research results. Other chapters only include a subset of these reanalysis data sets, since some reanalyses have already been shown to perform poorly for certain diagnostics or do not extend high enough (e.g., pressures less than 10hPa) in the atmosphere. At the beginning of each chapter an explanation is given as to why specific reanalysis data sets were included or excluded. The minimum intercomparison period is 1980-2010. This period starts with the availability of MERRA-2 shortly after the advent of high-frequency remotely sensed data in late 1978 and ends with the transition between CFSR and CFSv2. Some chapters also consider the pre-satellite era before 1979 and/or include results for more recent years. Some chapters use shorter intercomparison periods for some diagnostics due to limitations in the observational record available for comparison and/or computational resources.