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GEOS-5 Seasonal Forecast System

Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9 month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

GEOS-5↗

Assessment of the Advanced Very High Resolution Radiometer (AVHRR) for Snowfall Retrieval in High Latitudes Using CloudSat and Machine Learning

Precipitation retrieval is a challenging topic, especially in high latitudes (HL), and current precipitation products face ample challenges over these regions. This study investigates the potential of the Advanced Very High Resolution Radiometer (AVHRR) for snowfall retrieval in HL using CloudSat radar information and machine learning (ML). With all the known limitations, AVHRR observations should be considered for HL snowfall retrieval because 1) AVHRR data have been continuously collected for about four decades on multiple platforms with global coverage, and similar observations will likely continue in the future; 2) current passive microwave satellite precipitation products have several issues over snow and ice surfaces; and 3) good coincident observations between AVHRR and CloudSat are available for training ML algorithms. Using ML, snowfall rate was retrieved from AVHRR’s brightness temperature and cloud probability, as well as auxiliary information provided by numerical reanalysis. The results indicate that the ML-based retrieval algorithm is capable of detection and estimation of snowfall with comparable or better statistical scores than those obtained from the Atmospheric Infrared Sounder (AIRS) and two passive microwave sensors contributing to the Global Precipitation Measurement (GPM) mission constellation. The outcomes also suggest that AVHRR-based snowfall retrievals are spatially and temporally reasonable and can be considered as a quantitatively useful input to the merged precipitation products that require frequent sampling or long-term records.

Mohammad Reza↗

RINA: An interactive system for the rapid interpretation of NASTRAN results

RINA is a general post-processor system which performs data reduction, post processing and post analysis of NASTRAN results. RINA can be run in either batch or time-sharing mode. The system, which is an expansion of the NASDAT program, performs the following tasks: (1) scan of extreme values for displacements, forces, stresses and margins of safety, (2) computations of envelopes for displacements, forces, stresses and margins of safety, (3) computations of allowables and margins of safety; and (4) generation of NASTRAN tables needed for reanalysis computations. Usage of all these options provides the analyst with an efficient tool for the study and interpretation of NASTRAN analysis results and their presentation for project documentation.

Raibstone, A. I.↗

Interactions Between Thresholds and Spatial Discretizations of Snow: Insights From Estimates of Wolverine Denning Habitat in the Colorado Rocky Mountains

Thresholds can be used to interpret environmental data in a way that is easily communicated and useful for decision making purposes. However, thresholds are often developed for specific data products and time periods, changing findings when the same threshold is applied to datasets or periods with different characteristics. Here, we test the impact of different spatial discretizations of snow on annual estimates of wolverine denning opportunities in the Colorado Rocky Mountains, defined using a snow water equivalent (SWE) threshold (0.20 m) and threshold date (15 May) from previous habitat assessments. Annual potential wolverine denning area (PWDA) was thresholded from a 36-year (1985 – 2020) snow reanalysis model with three different spatial discretizations: 1) 480 m grid cells (D480), 2) 90 m grid cells (D90), and 3) 480 m grid cells with implicit representations of subgrid snow spatial heterogeneity (S480). Relative to the D480 and S480 discretizations, D90 resolved shallower snow deposits on slopes between 3050 and 3350 m elevation, decreasing PWDA by 10%, on average. In years with warmer and/or drier winters, S480 discretizations with subgrid representations of snow heterogeneity increased PWDA, even within grid cells where mean 15 May SWE was less than the SWE threshold. These simulations increased PWDA by upwards of 30% in low snow years, as compared to the D480 and D90 simulations without subgrid snow heterogeneity. Despite PWDA sensitivity to different snow spatial discretizations, PWDA was controlled more by annual variations in winter precipitation and temperature. However, small changes to the SWE threshold (± 0.07 m) and threshold date (± 2 weeks) also affected PWDA by as much as 82%. Across these threshold ranges, PWDA was approximately 18% more sensitive to the SWE threshold than the threshold date. However, the sensitivity to the threshold date was larger in years with late spring snowfall, when PWDA depended on whether modeled SWE was thresholded before, during, or after spring snow accumulation. Our results demonstrate that snow thresholds are useful but may not always provide a complete picture of the annual variability in snow-adapted wildlife denning opportunities. Studies thresholding spatiotemporal datasets could be improved by including 1) information about the fidelity of thresholds across multiple spatial discretizations, and 2) uncertainties related to ranges of realistic thresholds.

Justin M. Pflug↗

Development and Evaluation of Ensemble Consensus Precipitation Estimates over High Mountain Asia

Precipitation estimates are highly uncertain in complex regions such as High-Mountain Asia (HMA), where ground measurements are very difficult to obtain, and atmospheric dynamics poorly understood. Though gridded products derived from satellite-based observations and/or reanalysis can provide temporally and spatially distributed estimates of precipitation, there are significant inconsistencies in these products. As such, to date, there is little agreement in the community on the best and most accurate gridded precipitation product in HMA, which is likely area dependent because of HMA’s strong heterogeneities and complex orography. Targeting these gaps, this article presents the development of a consensus ensemble precipitation product using three gridded precipitation datasets (the Integrated Multi-satellitE Retrieals for Global Precipitation Measurement IMERG, the Climate Hazards group Infrared Precipitation with Stations CHIRPS, and the ECMWF Reanalysis ERA5) with a localized probability matched mean (LPM) approach. We evaluate the performance of the LPM estimate along with a simple ensemble mean (EM) estimate to overcome the differences and disparities of the three selected constituent products on long-term averages and trends in HMA. Our analysis demonstrates that LPM reduces the high biases embedded in the ensemble members and provides more realistic spatial patterns compared to EM. LPM is also a good alternative for merging data products with different spatio-temporal resolutions. By filtering disparities among the individual ensemble members, LPM overcomes the problem of a certain product performing well only in a particular area and provides a consensus estimate with plausible temporal trends.

Fadji Z Maina↗

The Influence of Prescribed Boundary Conditions on Near-Surface Temperature over the Arctic in the MERRA-2 Atmospheric Model

An accurate historical record of evolving Arctic conditions is integral to furthering our understanding of climate processes and to providing a foundation for predicting future climate scenarios in northern high latitudes. Atmospheric reanalyses are seen as an important source of information on the recent past for the data-sparse Arctic region. An assessment of near-surface Arctic air temperatures finds significant discrepancies among the various modern reanalyses. An important point is the treatment of surface boundary conditions: specifically, the sea ice cover and sea surface temperatures (SSTs) over the Arctic Ocean. Reanalyses use different methodologies and data sources for SSTs and sea ice concentration boundary forcing. Notably, the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) both use boundary forcing derived from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) over an extended, overlapping period of time. This allows for an examination of differences between the two systems while both concurrently employ the same fractional sea ice coverage. To further understand these differences, an ensemble of AMIP-style simulations using the MERRA-2 atmospheric model - but without data assimilation - shows considerable differences in Arctic temperatures as compared to reanalyses, particularly in autumn and winter months. Results from the AMIP simulations suggest that the surface representation over sea ice used in the MERRA-2 model provides an intrinsic warm bias and obfuscates Arctic Amplification, an established feature present in observations and reanalyses. An additional ensemble of AMIP-style simulations using the MERRA-2 atmospheric model was performed using boundary conditions derived from the ERA-Interim reanalysis. An in-depth comparison of surface temperatures over the Arctic from the two reanalyses and two AMIP-style ensembles will be presented, along with an assessment of the effects of the varying Arctic temperature time series on the atmospheric general circulation and energy budget.

Collow, Allison B. Marquardt↗

Comparison of Observed Longwave, Shortwave Irradiance and Surface Temperature from “MOSAiC” to CERES Radiative Transfer Calculations and Inputs

As atmospheric temperatures rise due to increased anthropogenic forcing, the effect is expected to be larger over the arctic than midlatitude and tropics, known as polar amplification. A multi-national program, the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was ran between Sept 2019 and Oct 2020. The project deployed scientific instruments on board the German research vessel Polarstern with the ship remaining across a year to observe all aspects of polar climate. The US DOE deployed the ARM AMF2 aboard the ship along with several off-ship sites for extended spatial observations. Of particular importance was the measurement of the energetics of the ice/ocean/atmosphere interactions through observations of surface irradiance and surface temperatures. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project produces the SYN1deg Edition 4 data product. This product provides high quality, hourly, globally gridded and temporally complete maps of top of atmosphere (TOA), in atmosphere, and surface irradiances. TOA fluxes are derived from CERES instruments and geostationary satellites. In addition, TOA, in atmosphere, and surface irradiances are computed using the Langley Fu and Liou radiative transfer model. The radiative transfer model is run hourly at 1 degree ~equal area spatial resolution. Meteorological profiles are provided by Global Modeling and Assimilation Office’s GEOS-541 reanalysis product. Cloud properties are derived solely from Terra and Aqua MODIS imagers northward of 60°. Here we compare SYN1deg hourly calculations of surface irradiance to observations from the AMF2 to validate the products estimates of surface irradiance in this challenging area. Along with the irradiance comparisons we take a close look at the surface temperature record in the GEOS-541 product and compare it over both time and space to several surface observations provided by MOSAiC. Along with the comparison to the re-analysis record we will compare these observed surface temperatures to those derived from the AIRS product, which is known to have some difficulty in extreme high latitude areas. The goals of this study are 1) understand computed surface downward irradiance and temperature error separated by surface type (e.g. sea ice or open water) and by season, and 2) error covariance in spatial and temporal space. We seek to use this information to extrapolate the error from the MOSAiC domain to a larger arctic region.

David A Rutan↗

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael G Bosilovich↗

Evaluation of Regional Water and Energy Balance in Contemporary Reanalyses

Regional to continental water and energy balance in reanalyses provide crucial information on the climate and climate variations in that region and can contrast other regions. Reanalyses are a valuable tool in piecing together the complete balance owing to the incorporation of the budgets in the background model and the assimilation of observation. On the other hand, the background model has its own biases and observational assimilation can lead to non-negligible tendencies within the budgets, and these can vary over space and time. Here, we will compare the balance within several reanalyses and how they have evolved over recent decades. Several observational data products will provide reference points in the comparison. In addition, a recent project has integrated observations of the water and energy budgets in an optimization that aims to reduce the imbalance of regional budgets in using observational terms from disparate sources. In evaluating the regional balances, we will incorporate, when available, the water and energy convergence terms as well as their analysis increments (which may be diagnosed as residuals). The reanalyses considered here include: Japanese Reanalyses for Three Quarters Century (JRA3Q), ECMWF Reanalysis version 5 (ERA5), Modern Era Retrospective-analysis for Research and Applications version 2 (MERRA-2) and the NCEP Reanalysis II (NCEPR2). NCEPR2 is representative of the late 90s technology, while the others represent the contemporary climate reanalyses presently available. We will discuss the regional balances over key river basins (e.g. Mississippi and Amazon), and a range of continents including those well observed (North America and Europe) and those with fewer consistent observations (e.g. Africa). These contrasting regions show the degree of advancement in reanalyses and expose areas in need of improvement. The results also demonstrate the usefulness of producing complete atmospheric water and energy budgets as part of the diagnostic output.

Michael Bosilovich↗

Version 2.0 AERONET Dust Aerosol properties, Constraints and Application to Asian Dust Observations

In November 2006, AERONET released Version 2 of the Dubovik and King sky radiance and optical depth inversion. Reanalysis of the entire AERONET database revealed marked differences in aerosol properties in arid and semi arid regions with dust dominated aerosols. The change will be illustrated through sensitivity analysis and examples from the UAE2 (United Arab Emirates Unified Aerosol Experiment) field campaign. Properties of dust dominated aerosols will be presented from regional AERONET sites in China showing variations in dust aerosol properties. The constraints and limitations of the AERONET inversion will be presented that will facilitate analysis by the user community of these data.

Holben, Brent↗

The Influence of Sea ice on Arctic Cloud Properties: What Can We Learn by Applying a In Situ Observational Strategy to Satellite Data?

Sea ice is declining because of anthropogenic climate change. This change alters many aspects of the Arctic climate system, including the way that the surface and atmosphere interact. Atmosphere-surface coupling processes represent an important cloud feedback mechanism that can alter the Arctic surface energy budget. For the Arctic, it has been hypothesized that a reduction in sea ice cover could lead to an increase in clouds. If this process were to occur as originally hypothesized, sea ice loss in all seasons would lead to an increase in clouds. Recent observational studies find a cloud response to sea ice loss in non-summer months and no cloud response in summer months. However, previous studies rely on inter-annual variability and reanalysis to control for the influence of meteorology, reducing the confidence in the resulting conclusions. We adopt a phenomenological, event-based approach that does not need to use meteorological reanalysis. The approach analyzes cloud properties derived from CALIPSO-CloudSat over sea ice and adjacent ice-free footprints by compositing individual satellite ground tracks that cross the Arctic sea ice edge. The underlying assumption, which we verify, is that footprints that are close to each other in space and time experience similar large-scale meteorological conditions. Our results show larger cloud fraction and more cloud liquid water over ice-free than over sea ice footprints and provide additional evidence for a seasonal dependence of cloud-sea ice coupling that is in line with previous work. We find a different result where the maximum cloud property differences between sea ice and ice-free ocean occurs in spring, not fall as earlier studies suggest. We argue that these cloud differences between sea ice and ice-free ocean are primarily caused by the influence of the surface type on the thermodynamic stability of the lower troposphere and not principally from an increase in surface evaporation. In addition, we explore the sensitivity of these results to marginal ice zone width, season, Atlantic vs. Pacific sector, and the cloud property dependence on the distance from the sea ice edge. Overall, our results provide further evidence that cloud-sea ice coupling processes are not offsetting the observed surface energy budget perturbation due to sea ice loss in summer; thus, the cloud response to declining sea ice appears to contribute to amplified Arctic warming.

Patrick C Taylor↗

Image-Subtraction Photometry of Variable Stars in the Globular Clusters NGC 6388 and NGC 6441

We have applied Alard's image subtraction method (ISIS v2.1) to the observations of the globular clusters NGC 6388 and NGC 6441 previously analyzed using standard photometric techniques (DAOPHOT, ALLFRAME). In this reanalysis of observations obtained at CTIO, besides recovering the variables previously detected on the basis of our ground-based images, we have also been able to recover most of the RR Lyrae variables previously detected only in the analysis of Hubble Space Telescope WFPC2 observations of the inner region of NGC 6441. In addition, we report five possible new variables not found in the analysis of the EST observations of NGC 6441. This dramatically illustrates the capabilities of image subtraction techniques applied to ground-based data to recover variables in extremely crowded fields. We have also detected twelve new variables and six possible variables in NGC 6388 not found in our previous groundbased studies. Revised mean periods for RRab stars in NGC 6388 and NGC 6441 are 0.676 day and 0.756 day, respectively. These values are among the largest known for any galactic globular cluster. Additional probable type II Cepheids were identified in NGC 6388, confirming its status as a metal-rich globular cluster rich in Cepheids.

Corwin, Michael T.↗

Wind Forcing of the North Sea Pole Tide

The Chandler wobble of the earth's rotation has a period near 14 months and sets up the 0.5 cm amplitude pole tide in the deep oceans, However, the pole tide is anomalously large in the North Sea, where the amplitude increases sharply up to 3 cm along the continental coast. It is shown here that the sea levels are well correlated with winds at the pole tide frequency. The Princeton Ocean Model is used to investigate the response of the North Sea to wind forcing. The barotropic numerical ocean model depicts realistic coastlines and bathymetry at 5 ft x 5 ft resolution, with 97 x 73 grid points. The monthly mean wind fields for the 40-year period (1958-1997) from the National Centers for Atmospheric Prediction (NCEP) reanalysis were used to force the model. The winds were converted to stress with a neutral drag coefficient that varied linearly with windspeed (instead of using the NCEP windstress). A 5-day simulation was made for each month until the resulting flow regime came into equilibrium, and model water levels at various station locations were saved for comparison with tidal-gauge observed sea levels from the Permanent Service for Mean Sea Level (PSMSL). The comparison is made for 10 North Sea stations with high quality tide gauge data. We find: (1) good agreement in annual and semi-annual phases and in the trend of amplitude w.r.t. latitude; (2) more importantly for this study, the model-predicted and observed non-seasonal sea level variations show a very significant temporal correlation as well as spectral coherence. However, a large amplitude difference exists between the two sets -- the overall amplitude variability of the observed is generally a factor of 2-3 larger than the model prediction (this same phenomenon has been reported in ocean circulation studies, although the cause is not yet clear.) Our results indicate that the wind forcing is the main cause of the observed large pole tide in the North Sea.

OConnor, W.↗

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↗

The Reanalysis for Stratospheric Trace-gas Studies

In order to re-examine trace gas transport in the middle atmosphere for the period May 1991 until April 1995, a "reanalysis" is being performed using an up-to-date version of the DAO's "GEOS" assimilation system. The Reanalysis for Stratospheric Trace-gas Studies (ReSTS) is intended to provide state-of-the-art estimates of the atmosphere during a period when the Upper Atmospheric Research Satellite provided a high density of trace-gas observations, and when the aerosol loading from the eruption of Mount Pinatubo contaminated the lower stratosphere, at the same time performing a natural tracer transport experiment. This study will present the first results from ReSTS, focussing on the improvements over the meteorological analyses produced by the then-operational GEOS-1 data assimilation system; emphasis will be placed on the improved representations of physical processes between GEOS-1 and the current GEOS-4 systems, highlighting the transport properties of the datasets. Alongside the production of a comprehensive atmospheric dataset, important components of ReSTS include performing sensitivity studies to the formulation of the assimilation system (including the representation of physical processes in the GCM, such as feedbacks between ozone/aerosols and meteorology) and to the inclusion of additional data types (including limb-sounding temperature data alongside the TOVS observations). Impacts of some of these factors on the analyzed meteorology and transport will be discussed. Of particular interest are attempts to determine the relative importance of various steps in the assimilation process to the quality of the final analyses.

Pawson, Steven↗

TESS Revisits WASP-12: Updated Orbital Decay Rate and Constraints on Atmospheric Variability

After observing WASP-12 in the second year of the primary mission, the Transiting Exoplanet Survey Satellite (TESS) revisited the system in late 2021 during its extended mission. In this paper, we incorporate the new TESS photometry into a reanalysis of the transits, secondary eclipses, and phase curve. We also present a new Ks-band occultation observation of WASP-12b obtained with the Palomar/Wide-field Infrared Camera instrument. The latest TESS photometry spans three consecutive months, quadrupling the total length of the TESS WASP-12 light curve and extending the overall time baseline by almost two years. Based on the full set of available transit and occultation timings, we find that the orbital period is shrinking at a rate of −29.81 ± 0.94 ms yr−1. The additional data also increase the measurement precision of the transit depth, orbital parameters, and phase-curve amplitudes. We obtain a secondary eclipse depth of 466 ± 35 ppm, a 2σ upper limit on the nightside brightness of 70 ppm, and a marginal 6°.2 ± 2°.8 eastward offset between the dayside hotspot and the substellar point. The voluminous TESS data set allows us to assess the level of atmospheric variability on timescales of days, months, and years. We do not detect any statistically significant modulations in the secondary eclipse depth or day–night brightness contrast. Likewise, our measured Ks-band occultation depth of 2810 ± 390 ppm is consistent with most ∼2.2 μm observations in the literature.

Ian Wong↗

Assessing the Altitude and Dispersion of Volcanic Plumes Using MISR Multi-angle Imaging from Space: Sixteen Years of Volcanic Activity in the Kamchatka Peninsula, Russia

Volcanic eruptions represent a significant source of atmospheric aerosols and can display local, regional and global effects, impacting earth systems and human populations. In order to assess the relative impacts of these events, accurate plume injection altitude measurements are needed. In this work, volcanic plumes generated from seven Kamchatka Peninsula volcanoes (Shiveluch, Kliuchevskoi, Bezymianny, Tolbachik, Kizimen, Karymsky and Zhupanovsky), were identified using over 16 years of Multi-angle Imaging SpectroRadimeter (MISR) measurements. Eighty-eight volcanic plumes were observed by MISR, capturing 3-25% of reported events at individual volcanoes. Retrievals were most successful where high intensity events persisted over a period of weeks to months. Compared with existing ground and airborne observations, and alternative satellite-based reports compiled by the Global Volcanism Program (GVP), MISR plume height retrievals showed general consistency; the comparison reports appear to be skewed towards the region of highest concentration observed in MISR-constrained vertical plume extent. The report observations display less discrepancy with MISR toward the end of the analysis period, with improvements in the suborbital data likely the result of the deployment of new instrumentation. Conversely, the general consistency of MISR plume heights with conventionally reported observations supports the use of MISR in the ongoing assessment of volcanic activity globally, especially where other types of volcanic plume observations are unavailable. Differences between the northern (Shiveluch, Kliuchevskoi, Bezymianny and Tolbachik) and southern (Kizimen, Karymsky and Zhupanovsky) volcanoes broadly correspond to the Central Kamchatka Depression (CKD) and Eastern Volcanic Front (EVF), respectively, geological sub-regions of Kamchatka distinguished by varying magma composition. For example, by comparison with reanalysis-model simulations of local meteorological conditions, CKD plumes generally were less constrained by mid-tropospheric (< 6 km) layers of vertical stability above the boundary layer, suggesting that these eruptions were more energetic than those in the EVF

Kamchatka↗

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

The Modern-Era Retrospective analysis for Research and Applications (MERRA) is a state-ofthe-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields ("MERRA-Land") generated by re-running a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ERA-Interim (ERA-I) reanalysis. MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 US stations) are comparable and significantly greater than that of MERRA. Throughout the northern hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 US basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

Reichle, Rolf H.↗