Results for “reanalyses” — Page 2

NASA NTRSDate not supplied

Broadening Systematic Reanalysis Intercomparisons in the SPARC-Reanalysis Intercomparison Project Phase 2 (S-RIP2): Chemical Reanalyses & Air Quality, Tropospheric Circulation, Extreme Events, and More

Reanalysis datasets are widely used to understand numerous atmospheric processes. 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, https://s-rip.github.io/) is a coordinated activity to compare key diagnostics among available reanalyses, identify differences among reanalyses and their underlying causes, provide guidance on appropriate usage of reanalyses in scientific studies, and contribute to future improvements in the reanalysis products via collaborations with reanalysis centers and data users. S-RIP Phase 1 (completed in early 2022) focused primarily on the upper troposphere through the middle atmosphere and processes linking these regions to the troposphere and surface. We look forward to broadening our efforts in Phase 2 (S-RIP2), with new foci including studies of tropospheric circulation, extreme weather events, and their links to the stratosphere, and focusing on evaluation of chemical reanalyses, both those with a stratosphere / upper troposphere focus and those that focus on air quality applications. This presentation will provide a summary of Phase 1 results and discussion of future directions for S-RIP2, emphasizing applications to composition and chemistry studies as well as fostering capacity building for Early Career Scientists.

Sean M Davis↗

NASA NTRS2017

Understanding Arctic Surface Temperature Differences in Reanalyses

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. A review of surface temperature differences is presented with a particular focus on differences in contemporary reanalyses. An important consideration is the significant differences in Arctic surfaces, including the central Arctic Ocean, the Greenland Ice Sheet, and non-glaciated land. While there is significant correlation among reanalyses in annual time series, there is substantial disagreement in mean values. For the period 1980-2013, the trend in annual temperature ranges from 0.3 to 0.7K per decade. Over the central Arctic Ocean, differences in mean values and trends are larger. Most of the uncertainty is associated with winter months. This is likely associated with the constraint imposed by melting processes (i.e. 0 deg. Celsius), rather than seasonal changes to the observing system.

Sea Ic↗

NASA NTRS2020

Revisiting the Relationship between Atlantic Dust and Tropical Cyclone Activity using Aerosol Optical Depth Reanalyses: 2003-2018

Previous studies have noted a relationship between African dust and Atlantic tropical cyclone (TC) activity. However, due to the limitations of past dust analyses, the strength of this relationship remains uncertain. The emergence of aerosol reanalyses, including the Navy Aerosol Analysis and Prediction System (NAAPS) aerosol optical depth (AOD) reanalysis, NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and ECMWF Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA), enables an investigation of the relationship between African dust and TC activity over the tropical Atlantic and Caribbean in a consistent temporal and spatial manner for 2003–2018. Although June–July–August (JJA) 550 nm dust AOD (DAOD) from all three reanalysis products correlates significantly over the tropical Atlantic and Caribbean, the difference in DAOD magnitude between products can be as large as 60 % over the Caribbean and 20 % over the tropical North Atlantic. Based on the three individual reanalyses, we have created an aerosol multi-reanalysis consensus (MRC). The MRC presents overall better root mean square error over the tropical Atlantic and Caribbean compared to individual reanalyses when verified with ground-based AErosol RObotic NETwork (AERONET) AOD measurements. Each of the three individual reanalyses and the MRC have significant negative correlations between JJA Caribbean DAOD and seasonal Atlantic accumulated cyclone energy (ACE), while the correlation between JJA tropical North Atlantic DAOD and seasonal ACE is weaker. Possible reasons for this regional difference are provided. A composite analysis of 3 high-JJA-Caribbean-DAOD years versus 3 low-JJA-Caribbean-DAOD years reveals large differences in overall Atlantic TC activity. We also show that JJA Caribbean DAOD is significantly correlated with large-scale fields associated with variability in interannual Atlantic TC activity including zonal wind shear, mid-level moisture, and sea surface temperature (SST), as well as the El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), implying confounding effects of these factors on the dust–TC relationship. We find that seasonal Atlantic DAOD and the AMM, the leading mode of coupled Atlantic variability, are inversely related and intertwined in the dust–TC relationship. Overall, DAOD in both the tropical Atlantic and Caribbean is negatively correlated with Atlantic hurricane frequency and intensity, with stronger correlations in the Caribbean than farther east in the tropical North Atlantic.

Dust particles↗

NASA NTRSDate not supplied

Evaluation of Water and Energy Cycles in Contemporary Atmospheric Reanalyses in US Basins

Global atmospheric reanalyses have become an important tool for climate studies, owing to the inclusion of observation driven model quantities that are not easily observed, if at all. This includes the study of regional water and energy budgets, despite the fact that the physical terms of the budgets do not balance, owing in large part to the influence of assimilated observations. Here, we focus on the regional water and energy budgets for key river basins in the US, related to the Humans and Hydroclimate in the US (H2US, a Global Energy and Watercycle EXchanges, GEWEX, regional hydroclimate project). Regional budgets and their residuals (related to the assimilated observations) from contemporary reanalyses will be evaluated and intercompared to assess the improvements over previous reanalyses and identify their strengths and weaknesses as contributions to H2US. When available, the observational analysis increments will be quantified directly, and as residuals when that information is missing. Early results show improvements over the Mississippi River basin water cycle closure, and reduced analysis increments. However, the energy analysis increments show non negligible seasonality. Results for the Colorado River basin and National Climate Assessment (NCA) regions will also be presented. The results will emphasize the need for reanalyses and models to produce complete budget equation terms.

Michael Bosilovich↗

NASA NTRS2016

Martian Polar Vortices: Comparison of Reanalyses

The structure and evolution of the Martian polar vortices is examined using two recently available reanalysis systems: version 1.0 of the Mars Analysis Correction Data Assimilation (MACDA) and a preliminary version of the Ensemble Mars Atmosphere Reanalysis System (EMARS). There is quantitative agreement between the reanalyses in the lower atmosphere, where Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) data are assimilated, but there are differences at higher altitudes reflecting differences in the free-running general circulation model simulations used in the two reanalyses. The reanalyses show similar potential vorticity (PV) structure of the vortices: There is near-uniform small PV equatorward of the core of the westerly jet, steep meridional PV gradients on the polar side of the jet core, and a maximum of PV located off of the pole. In maps of 30 sol mean PV, there is a near-continuous elliptical ring of high PV with roughly constant shape and longitudinal orientation from fall to spring. However, the shape and orientation of the vortex varies on daily time scales, and there is not a continuous ring of PV but rather a series of smaller scale coherent regions of high PV. The PV structure of the Martian polar vortices is, as has been reported before, very different from that of Earth's stratospheric polar vortices, but there are similarities with Earth's tropospheric vortices which also occur at the edge of the Hadley Cell, and have near-uniform small PV equatorward of the jet, and a large increase of PV poleward of the jet due to increased stratification.

Waugh, D. W.↗

NASA NTRS2017

From LIMS to OMPS-LP: Limb Ozone Observations for Future Reanalyses

High vertical resolution and accuracy of ozone data from satellite-borne limb sounders has made them an invaluable tool in scientific studies of the middle and upper atmosphere. However, it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses: of the major multidecadal reanalyses only ECMWF's (European Centre for Medium-Range Weather Forecasts') ERA (ECMWF Re-Analysis)-Interim/ERA5 and NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications-2) use limb ozone data. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 making these assimilated data sets useful for scientific research. In this presentation, we will show the results of test experiments assimilating retrieved ozone from the Limb Infrared Monitor of the Stratosphere (LIMS, 1978/1979) and Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP, 2012 to present). Our approach builds on the established assimilation methodology used for MLS in MERRA-2 and, in the case of OMPS-LP, extends the excellent record of MLS ozone assimilation into the post-EOS era in Earth observations. We will show case studies, discuss comparisons of the new experiments with MERRA-2, strategies for bias correction and the potential for combined assimilation of multiple limb ozone data types in future reanalyses for studies of multidecadal stratospheric ozone changes including trends.

Wargan, K.↗

NASA NTRS2019

Long-Term Ozone Variability and Trends from Reanalyses: Can It Be Done?

Stratospheric ozone concentrations have begun to show early signs of recovery following the implementation of the Montreal Protocol and its amendments as well as in response to decreasing upper-stratospheric temperatures. Secular trends in stratospheric ozone are modulated by considerable interannual variability and systematic changes in transport patterns that are expected under increasing concentrations of greenhouse gases, especially in the lower stratosphere. These factors necessitate the continued close monitoring of stratospheric ozone in upcoming decades, with a special focus on the lower stratosphere.As highly resolved data sets combining a plethora of observations with model simulations atmospheric reanalyses are, in principle, well suited for the task. All major reanalyses generate ozone output. However, significant spurious discontinuities that arise from step changes in the observing systems prevent a straightforward analysis of ozone trends and long-term variability. Building on our recent work, in this presentation we will demonstrate that trend detection is nonetheless possible using the ozone record from NASA's MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2) reanalysis bias-corrected using a chemistry model simulation as a transfer function. Next, we will outline several strategies to reduce artificial discontinuities in the ozone record in future NASA reanalyses. This discussion will be illustrated by an example of joint assimilation of bias-corrected ozone profiles from the Microwave Limb Sounder (MLS) on the Aura satellite (2004 to present) and the Ozone Mapping Profiler Suite Limb Profiler (OMPS-LP) sensors that are expected to operate on future NOAA platforms.

Wargan, Krzysztof↗

NASA NTRSDate not supplied

Trends in Asian Summer Monsoon Anticyclone Dynamical Diagnostics in Reanalyses

The area of the Asian summer monsoon anticyclone (ASMA), as defined by contours of Montgomery stream function (MSF) on isentropic surfaces, has been increasing over at least the last four decades. Here we analyze the relationship of the trend in ASMA area to trends in dynamical diagnostics in the ASM region, both inside and outside the ASMA, for 1979 through 2020 in the MERRA-2, JRA-55, and ERA5 reanalyses. Trends in geopotential height (GPH) and temperature (from which MSF is calculated) indicate that MSF increases are dominated by increasing temperature (GPH) at levels that are primarily in the troposphere (stratosphere). Trends in MSF, GPH, and temperature are much less clear within the ASMA circulation than those for the entire ASM region, suggesting that other mechanisms, besides the direct effects of increasing tropospheric temperatures, are at play. To further explore these results, we present trends in lapse rate and dynamical tropopause altitudes, easterly and westerly windspeeds bounding the ASMA, and potential vorticity. Overall, weak or inconsistent trends inside the ASMA in most diagnostics likely arise from a complex interplay of mechanisms in this region (which spans tropospheric/stratospheric and tropical/midlatitude conditions), and suggest that the previously reported area trends do not necessarily indicate an increase in “intensity" of the ASMA. In regions both with and without robust trends in dynamical diagnostics, trend results are typically consistent between the three reanalyses studied even when there are biases in the magnitudes of those diagnostics. This generally good agreement indicates that these reanalyses are suitable for more detailed studies needed to fully understand the mechanisms for trends in the ASMA.

Gloria Manney↗

NASA NTRS2016

Global Ocean Evaporation Increases Since 1960 in Climate Reanalyses: How Accurate Are They?

AGCMs w/ Specified SSTs (AMIPs) GEOS-5, ERA-20CM Ensembles Incorporate best historical estimates of SST, sea ice, radiative forcing Atmospheric "weather noise" is inconsistent with specified SST. Instantaneous Sfc fluxes can be wrong sign (e.g. Indian Ocean Monsoon, high latitude oceans). Averaging over ensemble members helps isolate SST-forced signal. Reduced Observational Reanalyses: NOAA 20CR V2C, ERA-20C, JRA-55C Incorporate observed Sfc Press (20CR), Marine Winds (ERA-20C) and rawinsondes (JRA-55C) to recover much of true synoptic or weather w/o shock of new sat obs. Comprehensive Reanalyses (MERRA-2) Full suite of observational constraints- both conventional and remote sensing. But... substantial uncertainties owing to evolving satellite observing system. Multi-source Statistically Blended OAFlux, LargeYeager Blend reanalysis, satellite, and ocean buoy information. While climatological biases are removed, non-physical trends or variations in components remain. Satellite Retrievals GSSTF3, SeaFlux, HOAPS3... Global coverage. Retrieved near sfc wind speed, & humidity used with SST to drive accurate bulk aerodynamic flux estimates. Satellite inter-calibration, spacecraft pointing variations crucial. Short record ( late 1987-present). In situ Measurements ICOADS, IVAD, Res Cruises VOS and buoys offer direct measurements. Sparse data coverage (esp south of 30S. Changes in measurement techniques (e.g. shipboard anemometer height).

Climate↗

NASA NTRS2018

Long-Term Ozone Variability and Trends from Reanalyses

Stratospheric ozone has a profound impact on radiation and chemistry over various spatial and temporal scales. The evolution of stratospheric ozone over the 21st century, however, is not well understood, especially in the lower stratosphere. Highly vertically resolved ozone data from satellite-borne limb sounders have proved to be invaluable for studying ozone in the middle and upper stratosphere but it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) making these assimilated data sets more useful for scientific research. In this presentation we demonstrate that multidecadal lower-stratospheric ozone variability and trends can be derived from NASA's MERRA-2 reanalysis ozone. In particular, the reanalysis ozone bias-corrected using a chemistry model simulation as a transfer function agrees very well with recently reprocessed long ozonesonde records. Ozone trends in the lower stratosphere will be discussed in the context of recent findings (Ball et al., 2018) and interpreted in connection with long-term circulation changes in the lower stratosphere. Next, we show that the use of ozone data retrieved from the next generation OMPS (Ozone Mapping Profiler Suite) instruments, including the OMPS Limb Profiler, can successfully extend the reanalyses into the future allowing comprehensive monitoring of global ozone and interpretation of its evolution during the critical period of expected ozone recovery and climate change from increasing concentration of greenhouse gases.

ozone↗

NASA NTRS1999

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the outgoing longwave radiation, and the large-scale circulation in the tropics. In particular, assimilating these data types reduce the state-dependent systematic errors in the assimilated products. The improved analysis also leads to a better short-range forecast, but the impact is modest compared with improvements in the time-averaged fields. These results suggest that, in the presence of biases and other errors of the forecast model, it is possible to improve the time-averaged "climate content" in the assimilated data without comparable improvements in the short-range forecast skill. Results of this experiment provide a useful benchmark for evaluating error covariance models for optimal use of these data types.

Hou, Arthur Y.↗

NASA NTRS1999

Improving Global Reanalyses and Short-Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗

NASA NTRS2000

Improving Global Reanalyses and Short Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗

NASA NTRS2007

The Spatiotemporal Structure of 20th Century Climate Variations in Observations and Reanalyses: Long-term Trend - Part 1

The dominant interannual El Nino-Southern Oscillation phenomenon (ENSO) and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENS0 signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, we develop an ENSO-removal method through which the ENS0 signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations, namely, the global warming trend (GW) and the Pacific pan-decadal variability (PDV), are isolated at middle and low latitudes in the climate parameter fields from observed and reanalyses datasets. Except for known GW characteristics, the warming that occurs in the Pacific basin (approximately 0.4K in the 2oth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on NCEP/NCAR and ERA-40 reanalyses, a comprehensive atmospheric structure associated with GW is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamic and water vapor fields. The dynamic field based on NCEP/NCAR reanalysis, which shows a change in the Walker Circulation, is consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in the ERA-40 reanalysis.

Chen, Junye↗

NASA NTRS2014

Evaluating Observation Influence on Regional Water Budgets in Reanalyses

The assimilation of observations in reanalyses incurs the potential for the physical terms of budgets to be balanced by a term relating the fit of the observations relative to a forecast first guess analysis. This may indicate a limitation in the physical processes of the background model, or perhaps inconsistencies in the observing system and its assimilation. In the MERRA reanalysis, an area of long term moisture flux divergence over land has been identified over the Central United States. Here, we evaluate the water vapor budget in this region, taking advantage of two unique features of the MERRA diagnostic output; 1) a closed water budget that includes the analysis increment and 2) a gridded diagnostic output data set of the assimilated observations and their innovations (e.g. forecast departures). In the Central United States, an anomaly occurs where the analysis adds water to the region, while precipitation decreases and moisture flux divergence increases. This is related more to a change in the observing system than to a deficiency in the model physical processes. MERRAs Gridded Innovations and Observations (GIO) data narrow the observations that influence this feature to the ATOVS and Aqua satellites during the 06Z and 18Z analysis cycles. Observing system experiments further narrow the instruments that affect the anomalous feature to AMSUA (mainly window channels) and AIRS. This effort also shows the complexities of the observing system, and the reactions of the regional water budgets in reanalyses to the assimilated observations.

Atmospheric Reanalysis↗

NASA NTRS2017

An Intercomparison of Changes Associated with Earth's Lower Tropospheric Temperature Using Traditional and AMIP-Style Reanalyses

Reanalyses have become an integral tool for evaluating regional and global climate variations, and an important component of this is modifications to the energy budget. Reductions in Arctic Sea ice extent has induced an albedo feedback, causing the Arctic to warm more rapidly than anywhere else in the world, referred to as "Arctic Amplification." This has been demonstrated by observations and numerous reanalyses, including the Modern Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). However, the Arctic Amplification signal is non-existent in a ten member ensemble of the MERRA-2 Atmospheric Model Intercomparison Project (M2AMIP) simulations, using the same prescribed climate forcing, including Sea Surface Temperature (SST) and ice. An evaluation of the temperature tendency within the lower troposphere due to radiation, moisture, and dynamics as well as the surface energy budget in MERRA-2 and M2AMIP will demonstrate that despite identical prescribed SSTs and sea ice in both versions, enhanced warming in the Arctic in MERRA-2 is in response to the analysis increment tendency due to temperature observations. Furthermore, the role of boundary conditions, model biases and changes in observing systems on the Arctic Amplification signal will be assessed. Literature on the topic of Arctic Amplification demonstrates that the enhanced warming begins in the mid-1990s. Anomalously warm Arctic SST in the early time period of MERRA-2 can mute the trend in Arctic lower troposphere temperature without the constraint of observations in M2AMIP. Additionally, MERRA-2 uses three distinct datasets of SST and sea ice concentration, which also plays a role.

Arcti↗

NASA NTRS2017

Towards A Representation of Vertically Resolved Ozone Changes in Reanalyses

The Solar Backscatter Ultraviolet Radiometer (SBUV) instruments on NASA and NOAA spacecraft provide a long-term record of total-column ozone and deep-layer partial columns since about 1980. These data have been carefully processed to extract long-term trends and offer a valuable resource for ozone monitoring. Studies assimilating limb-sounding observations in the Goddard Earth Observing System (GEOS) data assimilation system (DAS) demonstrate that vertical ozone gradients in the upper troposphere and lower stratosphere (UTLS) are much better represented than with the deep-layer SBUV observations. This is exemplified by the use of retrieved ozone from the EOS Microwave Limb Sounder (EOS-MLS) instrument in the MERRA-2 reanalysis, for the period after 2004. This study examines the potential for extending the use of limb-sounding observations at earlier times and into the future, so that future reanalyses may be more applicable to the study of long-term ozone changes.Historical data are available from NASA instruments: the Limb Infrared Monitor of the Stratosphere (LIMS: 1978-1979); the Upper Atmospheric Research Satellite (UARS: 1991-1995); Sounding of the Atmosphere using Broadband Emission Radiometry (SABER: 2000-onwards). For the post EOS-MLS period, the joint NASA-NOAA Ozone Monitoring and Profiling Suite Limb Profiler (OMPS-LP) instrument was launched on the Suomi-NPP platform in 201x and is planned for future platforms. This study will examine two aspects of these data pertaining to future reanalyses. First, the feasibility of merging the EOS-MLS and OMPS-LP instruments to provide a long-term record that extends beyond the potential lifetime of EOS-MLS. If feasible, this would allow for long-term monitoring of ozone recovery in a three-dimensional reanalysis context. Second, the skill of the GEOS DAS in ingesting historical data types will be investigated. Because these do not overlap with EOS-MLS, use will be made of system statistics and evaluation using independent datasets. Impacts of using a complete ozone chemistry module will also be considered.

ML↗

NASA NTRS2017

Influence of Mid-Latitude Cyclones on European Background Surface Ozone Investigated in Observations, MACC and MERRA-2 Reanalyses

The relationship between springtime mid-latitude cyclones and background ozone at two rural monitoring sites on the west coast of Europe -- Mace Head, Ireland and Monte Velho, Portugal -- is explored using a combination of observations and three reanalyses: 1) the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-Interim reanalysis, 2) the Monitoring Atmospheric Composition and Climate (MACC) reanalysis and 3) NASA's Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2) reanalysis. The ERA-Interim cyclone tracks are used here to establish the long-term relationship between cyclones and ozone observations (since 1988). The MACC reanalysis data set, which covers the period 2003-2012, is produced with the ECMWF integrated forecast system (IFS) model two-way coupled to a chemistry transport model (CTM). Since the MACC reanalysis uses a similar atmospheric model to ERA-Interim, MACC is used to explore the mechanisms within the case study cyclones that can influence surface ozone concentrations at Mace Head and Monte Velho. The MERRA-2 reanalysis also provides 3D distributions of ozone, although less ideal for analysis of surface ozone concentrations since MERRA-2 ozone under represents ozone variability outside the stratosphere as it does not have a detailed chemistry scheme or emission sources for the troposphere. The MERRA-2 reanalysis, which has the potential to identify more features within the cyclones as the resolution is higher than the MACC reanalysis, is used in conjunction with the MACC reanalysis to provide a measure of uncertainty to the case study analysis. We found the main source of high ozone to these two sites is from the stratosphere, which is well represented in both the MERRA-2 and the MACC reanalyses, either from direct injection into the cyclone or associated with aged airstreams from decaying downstream cyclones that can become entrained and descend toward the surface within new cyclones over the NA region.

MERRA-2↗