Abstract

Independent measurements of Jovian cloud motions confirm previously published results on the general structure of Jupiter's zonal mean circulation. The new results are based on Voyager 2 images and measurement techniques which are different from those used in previous studies. The latitudes of the zonal jets agree with previous results, but there are some differences in the measured speed of the jets which exceed uncertainty estimates. These differences may be due to differences in sampling strategies. The structure of the zonal mean meridional velocity profile has still not been clearly resolved: mean meridional velocities generally differ from zero by no more than their estimated uncertainty. An analysis of successive measurements of the same cloud targets shows that most of the variance of individual velocity measurements is due to true variability of the winds. In agreement with the previous results the curvature of the zonal velocity profile is consistent with barotropic instability within most easterly jets, although the cloud morphologies visible in the images do not confirm that large-scale instabilities actually exist in these regions. Baroclinic effects may also be important in these regions. Large differences among independent estimates of eddy momentum transport indicate that this quantity has yet to be reliably determined.

Abstract

Ensemble experiments are performed with five coupled atmosphere–ocean models to investigate the potential for initial-value climate forecasts on interannual to decadal time scales. Experiments are started from similar model-generated initial states, and common diagnostics of predictability are used. We find that variations in the ocean meridional overturning circulation (MOC) are potentially predictable on interannual to decadal time scales, a more consistent picture of the surface temperature impact of decadal variations in the MOC is now apparent, and variations of surface air temperatures in the North Atlantic Ocean are also potentially predictable on interannual to decadal time scales, albeit with potential skill levels that are less than those seen for MOC variations. This intercomparison represents a step forward in assessing the robustness of model estimates of potential skill and is a prerequisite for the development of any operational forecasting system.

Abstract

The 2017 North Atlantic hurricane season was extremely active, with 17 named storms (1981–2010 median is 12.0), 10 hurricanes (median is 6.5), 6 major hurricanes (median is 2.0), and 245% of median accumulated cyclone energy (ACE) occurring. September 2017 generated more Atlantic named storm days, hurricane days, major hurricane days, and ACE than any other calendar month on record. The season was destructive, with Harvey and Irma devastating portions of the continental United States, while Irma and Maria brought catastrophic damage to Puerto Rico, Cuba, and many other Caribbean islands. Seasonal forecasts increased from calling for a slightly below-normal season in April to an above-normal season in August as large-scale environmental conditions became more favorable for an active hurricane season. During that time, the tropical Atlantic warmed anomalously while a potential El Niño decayed in the Pacific. Anomalously high SSTs prevailed across the tropical Atlantic, and vertical wind shear was anomalously weak, especially in the central tropical Atlantic, from late August to late September when several major hurricanes formed. Late-season hurricane activity was likely reduced by a convectively suppressed phase of the Madden–Julian oscillation. The large-scale steering flow was different from the average over the past decade with a strong subtropical high guiding hurricanes farther west across the Atlantic. The anomalously high tropical Atlantic SSTs and low vertical wind shear were comparable to other very active seasons since 1982.

Abstract

The equatorial Pacific is a region with strong negative feedbacks. Yet coupled general circulation models (GCMs) have exhibited a propensity to develop a significant SST bias in that region, suggesting an unrealistic sensitivity in the coupled models to small energy flux errors that inevitably occur in the individual model components. Could this “hypersensitivity” exhibited in a coupled model be due to an underestimate of the strength of the negative feedbacks in this region? With this suspicion, the feedbacks in the equatorial Pacific in nine atmospheric GCMs (AGCMs) have been quantified using the interannual variations in that region and compared with the corresponding calculations from the observations. The nine AGCMs are the NCAR Community Climate Model version 1 (CAM1), the NCAR Community Climate Model version 2 (CAM2), the NCAR Community Climate Model version 3 (CAM3), the NCAR CAM3 at T85 resolution, the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Atmospheric Model, the Hadley Centre Atmospheric Model (HadAM3), the Institut Pierre Simon Laplace (IPSL) model (LMDZ4), the Geophysical Fluid Dynamics Laboratory (GFDL) AM2p10, and the GFDL AM2p12. All the corresponding coupled runs of these nine AGCMs have an excessive cold tongue in the equatorial Pacific.

The net atmospheric feedback over the equatorial Pacific in the two GFDL models is found to be comparable to the observed value. All other models are found to have a weaker negative net feedback from the atmosphere—a weaker regulating effect on the underlying SST than the real atmosphere. Except for the French (IPSL) model, a weaker negative feedback from the cloud albedo and a weaker negative feedback from the atmospheric transport are the two leading contributors to the weaker regulating effect from the atmosphere. The underestimate of the strength of the negative feedbacks by the models is apparently linked to an underestimate of the equatorial precipitation response. All models have a stronger water vapor feedback than that indicated in Earth Radiation Budget Experiment (ERBE) observations. These results confirm the suspicion that an underestimate of the regulatory effect from the atmosphere over the equatorial Pacific region is a prevalent problem. The results also suggest, however, that a weaker regulatory effect from the atmosphere is unlikely solely responsible for the hypersensitivity in all models. The need to validate the feedbacks from the ocean transport is therefore highlighted.

Abstract

The Atlantic meridional overturning circulation (AMOC) makes the strongest oceanic contribution to the meridional redistribution of heat. Here, an observation-based, 48-month-long time series of the vertical structure and strength of the AMOC at 26.5°N is presented. From April 2004 to April 2008, the AMOC had a mean strength of 18.7 ± 2.1 Sv (1 Sv ≡ 10⁶ m³ s⁻¹) with fluctuations of 4.8 Sv rms. The best guess of the peak-to-peak amplitude of the AMOC seasonal cycle is 6.7 Sv, with a maximum strength in autumn and a minimum in spring. While seasonality in the AMOC was commonly thought to be dominated by the northward Ekman transport, this study reveals that fluctuations of the geostrophic midocean and Gulf Stream transports of 2.2 and 1.7 Sv rms, respectively, are substantially larger than those of the Ekman component (1.2 Sv rms). A simple model based on linear dynamics suggests that the seasonal cycle is dominated by wind stress curl forcing at the eastern boundary of the Atlantic. Seasonal geostrophic AMOC anomalies might represent an important and previously underestimated component of meridional transport and storage of heat in the subtropical North Atlantic. There is evidence that the seasonal cycle observed here is representative of much longer intervals. Previously, hydrographic snapshot estimates between 1957 and 2004 had suggested a long-term decline of the AMOC by 8 Sv. This study suggests that aliasing of seasonal AMOC anomalies might have accounted for a large part of the inferred slowdown.

The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system.

The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided by different countries and organizations. The system has been designed with advanced quality control and monitoring components, and can produce 1 mon of reanalysis per day on a Cray YMP/8 supercomputer. Different types of output archives are being created to satisfy different user needs, including a “quick look” CD-ROM (one per year) with six tropospheric and stratospheric fields available twice daily, as well as surface, top-of-the-atmosphere, and isentropic fields. Reanalysis information and selected output is also available on-line via the Internet (http//:nic.fb4.noaa.gov:8000). A special CDROM, containing 13 years of selected observed, daily, monthly, and climatological data from the NCEP/NCAR Reanalysis, is included with this issue. Output variables are classified into four classes, depending on the degree to which they are influenced by the observations and/or the model. For example, “C” variables (such as precipitation and surface fluxes) are completely determined by the model during the data assimilation and should be used with caution. Nevertheless, a comparison of these variables with observations and with several climatologies shows that they generally contain considerable useful information. Eight-day forecasts, produced every 5 days, should be useful for predictability studies and for monitoring the quality of the observing systems.

The 40 years of reanalysis (1957–96) should be completed in early 1997. A continuation into the future through an identical Climate Data Assimilation System will allow researchers to reliably compare recent anomalies with those in earlier decades. Since changes in the observing systems will inevitably produce perceived changes in the climate, parallel reanalyses (at least 1 year long) will be generated for the periods immediately after the introduction of new observing systems, such as new types of satellite data.

NCEP plans currently call for an updated reanalysis using a state-of-the-art system every five years or so. The successive reanalyses will be greatly facilitated by the generation of the comprehensive database in the present reanalysis.

Abstract

Emission rates and properties of ice nucleating particles (INPs) are required for proper representation of aerosol–cloud interactions in atmospheric models. Few investigations have quantified marine INP emissions, a potentially important INP source for remote oceanic regions. Previous studies have suggested INPs in sea spray aerosol (SSA) are linked to oceanic biological activity. This proposed link was explored in this study by measuring INP emissions from nascent SSA during phytoplankton blooms during two mesocosm experiments. In a Marine Aerosol Reference Tank (MART) experiment, a phytoplankton bloom was produced with chlorophyll-a (Chl a) concentrations reaching 39 μg L⁻¹, while Chl a concentrations more representative of natural ocean conditions were obtained during the Investigation into Marine Particle Chemistry and Transfer Science (IMPACTS; peak Chl a of 5 μg L⁻¹) campaign, conducted in the University of California, San Diego, wave flume. Dynamic trends in INP emissions occurred for INPs active at temperatures > −30°C. Increases in INPs active between −25° and −15°C lagged the peak in Chl a in both studies, suggesting a consistent population of INPs associated with the collapse of phytoplankton blooms. Trends in INP emissions were also compared to aerosol composition, abundances of microbes, and enzyme activity. In general, increases in INP concentrations corresponded to increases in organic species in SSA and the emissions of heterotrophic bacteria, suggesting that both microbes and biomolecules contribute to marine INP populations. INP trends were not directly correlated with a single biological marker in either study. Direct measurements of INP chemistry are needed to accurately identify particles types contributing to marine INP populations.

Abstract

The Community Climate System Model version 3 (CCSM3) has recently been developed and released to the climate community. CCSM3 is a coupled climate model with components representing the atmosphere, ocean, sea ice, and land surface connected by a flux coupler. CCSM3 is designed to produce realistic simulations over a wide range of spatial resolutions, enabling inexpensive simulations lasting several millennia or detailed studies of continental-scale dynamics, variability, and climate change. This paper will show results from the configuration used for climate-change simulations with a T85 grid for the atmosphere and land and a grid with approximately 1° resolution for the ocean and sea ice. The new system incorporates several significant improvements in the physical parameterizations. The enhancements in the model physics are designed to reduce or eliminate several systematic biases in the mean climate produced by previous editions of CCSM. These include new treatments of cloud processes, aerosol radiative forcing, land–atmosphere fluxes, ocean mixed layer processes, and sea ice dynamics. There are significant improvements in the sea ice thickness, polar radiation budgets, tropical sea surface temperatures, and cloud radiative effects. CCSM3 can produce stable climate simulations of millennial duration without ad hoc adjustments to the fluxes exchanged among the component models. Nonetheless, there are still systematic biases in the ocean–atmosphere fluxes in coastal regions west of continents, the spectrum of ENSO variability, the spatial distribution of precipitation in the tropical oceans, and continental precipitation and surface air temperatures. Work is under way to extend CCSM to a more accurate and comprehensive model of the earth's climate system.

Abstract

The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and related land surface variables from 31 March 2015 to present with ~2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O − F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of ~0.37 K for the O − F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O − F residuals (under ~3 K), the soil moisture increments (under ~0.01 m³ m⁻³), and the surface soil temperature increments (under ~1 K). Typical instantaneous values are ~6 K for O − F residuals, ~0.01 (~0.003) m³ m⁻³ for surface (root zone) soil moisture increments, and ~0.6 K for surface soil temperature increments. The O − F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O − F autocorrelations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

The multination, high-resolution field study of Meteorology And Diffusion Over Non-Uniform Areas (MADONA) was conducted by scientists from the United States, the United Kingdom, Germany, Denmark, Sweden, and the Netherlands at Porton Down, Salisbury, Wiltshire, United Kingdom, during September and October 1992. The host of the field study was the Chemical and Biological Defence Establishment (CBDE, now part of Defence Evaluation and Research Agency) at Porton Down. MADONA was designed and conducted for high-resolution meteorological data collection and diffusion experiments using smoke, sulphurhexaflouride (SF₆), and propylene gas during unstable, neutral, and stable atmospheric conditions in an effort to obtain terrain-influenced meteorological fields, dispersion, and concentration fluctuation measurements using specialized sensors and tracer generators. Thirty-one days of meteorological data were collected during the period 7 September–7 October and 27 diffusion experiments were conducted from 14 to 23 September 1992. Puffs and plumes of smoke and SF₆ were released simultaneously for most of the experiments to gauge the resultant diffusion and concentration behavior. Some 44 meteorological and aerosol sensors and four source generators were used during each day of the field study. This array of sensors included 14 towers of wind cups and vanes, 10 sonic anemometer/thermometers, one boundary layer sonde, two lidar, one ion sensor, the CBDE Weather Station, and several one-of-a-kind sensors. Simulations of airflow and diffusion over the MADONA topography (a 9 km by 7.5 km area) were made with a variety of models. Wind fields and wind-related parameters were simulated with several high-resolution (microalpha scale) wind flow models. A tally of the various data-gathering activities indicates that the execution of MADONA was highly successful. Preliminary use of the datasets shows the high quality and depth of the MADONA database. This well-documented database is suitable for the evaluation and validation of short-range/near-field wind and diffusion models/codes. The database was originally placed on CD-ROM in a structured way by CBDE, Porton Down. The database is now available from the Risø National Laboratory, Denmark.