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S. Daniel Jacob and Chester J. Koblinsky

Abstract

The effect of precipitation on the upper-ocean response during a tropical cyclone passage is investigated using a numerical model in this paper. For realistic wind forcing and empirical rain rates based on satellite climatology, numerical simulations are performed with and without precipitation forcing to delineate the effects of freshwater forcing on the upper-ocean heat and salt budgets. Additionally, the performance of five mixing parameterizations is also examined for the two forcing conditions to understand the sensitivity of simulated ocean response. Overall, results from 15 numerical experiments are analyzed to quantify the precipitation effects on the oceanic mixed layer and the upper ocean. Simulated fields for the same mixing scheme with and without precipitation indicate a decrease in the upper-ocean cooling of about 0.2°–0.5°C. This is mainly due to reduced mixing of colder water from below induced by the increased stability of the added freshwater. The cooler rainwater contributes a maximum of approximately 10% to the total surface heat loss from the ocean. The rate of freshening due to precipitation exceeds the rate of mixing of the more saline water from below, leading to a change in sign of the mixed layer salinity response. As seen in earlier studies, large uncertainty exists in the simulated upper-ocean response due to the choice of mixing parameterization. Although the nature of simulated response remains similar for all the mixing schemes, the magnitude of freshening and cooling varies by as much as 0.5 psu and 1°C between the schemes to the right of the storm track. While changes in the mixed layer and in the top 100 m of heat and salt budgets are strongly influenced by the choice of mixing scheme, integrated budgets in the top 200 m are seen to be affected more by advection and surface fluxes. However, since the estimated surface fluxes depend upon the simulated sea surface temperature, the choice of mixing scheme is crucial for realistic coupled predictive models.

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Neil A. Jacobs, Daniel J. Mulally, and Alan K. Anderson

Abstract

A method for correcting the magnetic deviation error from planes using a flux valve heading sensor is presented. This error can significantly degrade the quality of the wind data reported from certain commercial airlines. A database is constructed on a per-plane basis and compared to multiple model analyses and observations. A unique filtering method is applied using coefficients derived from this comparison. Three regional airline fleets hosting the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor were analyzed and binned by error statistics. The correction method is applied to the outliers with the largest deviation, and the wind observational error was reduced by 22% (2.4 kt; 1 kt = 0.51 m s−1), 50% (8.2 kt), and 68% (20.5 kt) for each group.

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S. Daniel Jacob, Lynn K. Shay, Arthur J. Mariano, and Peter G. Black

Abstract

Upper-ocean heat and mass budgets are examined from three snapshots of data acquired during and after the passage of Hurricane Gilbert in the western Gulf of Mexico. Measurements prior to storm passage indicated a warm core eddy in the region with velocities of O(1) m s−1. Based upon conservation of heat and mass, the three-dimensional mixed layer processes are quantified from the data. During and subsequent to hurricane passage, horizontal advection due to geostrophic velocities is significant in the eddy regime, suggesting that prestorm oceanic variability is important when background flows have the same magnitude as the mixed layer current response. Storm-induced near-inertial currents lead to large vertical advection magnitudes as they diverge from and converge toward the storm track. Surface fluxes, estimated by reducing flight-level winds to 10 m, indicate a maximum wind stress of 4.2 N m−2 and a heat flux of 1200 W m−2 in the directly forced region. The upward heat flux after the passage of the storm has a maximum of 200 W m−2 corresponding to a less than 7 m s−1 wind speed.

Entrainment mixing across the mixed layer base is estimated using three bulk entrainment closure schemes that differ in their physical basis of parameterization. Entrainment remains the dominant mechanism in controlling the heat and mass budgets irrespective of the scheme. Depending on the magnitudes of friction velocity, surface fluxes and/or shear across the mixed layer base, the pattern and location of maximum entrainment rates differ in the directly forced region. While the general area of maximum entrainment is in the right-rear quadrant of the storm, shear-induced entrainment scheme predicts a narrow region of cooling compared to the the stress-induced mixing scheme and observed SST decreases. After the storm passage, the maximum contribution to the mixed layer dynamics is associated with shear-induced entrainment mixing forced by near-inertial motions up to the third day as indicated by bulk Richardson numbers that remained below criticality. Thus, entrainment based on a combination of surface fluxes, friction velocity and shear across the entrainment zone may be more relevant for three-dimensional ocean response studies.

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Lynn K. Shay, Arthur J. Mariano, S. Daniel Jacob, and Edward H. Ryan

Abstract

The three-dimensional hurricane-induced ocean response is determined from velocity and temperature profiles acquired in the western Gulf of Mexico between 14 and 19 September 1988 during the passage of Hurricane Gilbert. The asymmetric wind structure of Gilbert indicated a wind stress of 4.2 N m−2 at a radius of maximum winds (R max) of 60 km. Using observed temperature profiles and climatological temperature–salinity relationships, the background and storm-induced geostrophic currents (re: 750 m) were 0.1 m s−1 and 0.2 m s−1, respectively. A Loop Current warm core ring (LCWCR) was also located to the right of the storm track at 4–5 R max, where anticyclonically rotating near-surface and 100-m currents decreased from 0.9 m s−1 to 0.6 m s−1 at depth. The relative vorticity in the LCWCR was shifted below the local Coriolis parameter by about 6%.

In a storm-based coordinate system, alongtrack residual velocity profiles from 0 to 4 R max were fit to a dynamical model by least squares to isolate the near-inertial content over an e-folding timescale of four inertial periods (IP ≈ 30 h). Observed frequency shifts in the mixed layer currents ranged from 1.03 to 1.05f in agreement with both the backrotated velocity profiles at 1.04f relative to the storm profile (where maximum correlation coefficients were 0.8) and the predicted frequency shift from the mixed-layer Burger number. This frequency was increasingly blue shifted in the upper 100 m to 1.1f, decreasing toward f within the thermocline. Near-inertial currents rotated anticyclonically by 90°–180° in the upper ocean, providing the velocity shear for layer cooling and deepening observed on the right-hand side of the track. A summation of the first four baroclinic modes described up to 77% of this near-inertial current variability during the first 1.75 IP. However, the variance explained by this modal summation decreased to a minimum of 36% after 2.9 IP following passage due to phase separation between the first baroclinic mode and higher-order modes in the mixed layer. Although the response was complicated by the LCWCR, the evolving three-dimensional current structure can be described by linear, near-inertial wave dynamics.

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Jiawei Zhuang, Daniel J. Jacob, Judith Flo Gaya, Robert M. Yantosca, Elizabeth W. Lundgren, Melissa P. Sulprizio, and Sebastian D. Eastham

Abstract

Cloud computing platforms can provide fast and easy access to complex Earth science models and large datasets. This article presents a mature capability for running the GEOS-Chem global 3D model of atmospheric chemistry on the Amazon Web Services (AWS) cloud. GEOS-Chem users at any experience level can get immediate access to the latest, standard version of the model in a preconfigured software environment with all needed meteorological and other input data, and they can analyze model output data easily within the cloud using Python tools in Jupyter notebooks. Users with no prior knowledge of cloud computing are provided with easy-to-follow, step-by-step instructions. They can learn how to complete a demo project in less than one hour, and from there they can configure and submit their own simulations. The cloud is particularly attractive for beginning and occasional users who otherwise may need to spend substantial time configuring a local computing environment. Heavy users with their own local clusters can also benefit from the cloud to access the latest standard model and datasets, share simulation configurations and results, benchmark local simulations, and respond to surges in computing demand. Software containers allow GEOS-Chem and its software environment to be moved smoothly between cloud platforms and local clusters, so that the exact same simulation can be reproduced everywhere. Because the software requirements and workflows tend to be similar across Earth science models, the work presented here provides general guidance for porting models to cloud computing platforms in a user-accessible way.

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Katharine S. Law, Andreas Stohl, Patricia K. Quinn, Charles A. Brock, John F. Burkhart, Jean-Daniel Paris, Gerard Ancellet, Hanwant B. Singh, Anke Roiger, Hans Schlager, Jack Dibb, Daniel J. Jacob, Steve R. Arnold, Jacques Pelon, and Jennie L. Thomas

Given the rapid nature of climate change occurring in the Arctic and the difficulty climate models have in quantitatively reproducing observed changes such as sea ice loss, it is important to improve understanding of the processes leading to climate change in this region, including the role of short-lived climate pollutants such as aerosols and ozone. It has long been known that pollution produced from emissions at midlatitudes can be transported to the Arctic, resulting in a winter/spring aerosol maximum known as Arctic haze. However, many uncertainties remain about the composition and origin of Arctic pollution throughout the troposphere; for example, many climate–chemistry models fail to reproduce the strong seasonality of aerosol abundance observed at Arctic surface sites, the origin and deposition mechanisms of black carbon (soot) particles that darken the snow and ice surface in the Arctic is poorly understood, and chemical processes controlling the abundance of tropospheric ozone are not well quantified. The International Polar Year (IPY) Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, Climate, Chemistry, Aerosols and Transport (POLARCAT) core project had the goal to improve understanding about the origins of pollutants transported to the Arctic; to detail the chemical composition, optical properties, and climate forcing potential of Arctic aerosols; to evaluate the processes governing tropospheric ozone; and to quantify the role of boreal forest fires. This article provides a review of the many results now available based on analysis of data collected during the POLARCAT aircraft-, ship-, and ground-based field campaigns in spring and summer 2008. Major findings are highlighted and areas requiring further investigation are discussed.

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Gabriele G. Pfister, Sebastian D. Eastham, Avelino F. Arellano, Bernard Aumont, Kelley C. Barsanti, Mary C. Barth, Andrew Conley, Nicholas A. Davis, Louisa K. Emmons, Jerome D. Fast, Arlene M. Fiore, Benjamin Gaubert, Steve Goldhaber, Claire Granier, Georg A. Grell, Marc Guevara, Daven K. Henze, Alma Hodzic, Xiaohong Liu, Daniel R. Marsh, John J. Orlando, John M. C. Plane, Lorenzo M. Polvani, Karen H. Rosenlof, Allison L. Steiner, Daniel J. Jacob, and Guy P. Brasseur

ABSTRACT

To explore the various couplings across space and time and between ecosystems in a consistent manner, atmospheric modeling is moving away from the fractured limited-scale modeling strategy of the past toward a unification of the range of scales inherent in the Earth system. This paper describes the forward-looking Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA), which is intended to become the next-generation community infrastructure for research involving atmospheric chemistry and aerosols. MUSICA will be developed collaboratively by the National Center for Atmospheric Research (NCAR) and university and government researchers, with the goal of serving the international research and applications communities. The capability of unifying various spatiotemporal scales, coupling to other Earth system components, and process-level modularization will allow advances in both fundamental and applied research in atmospheric composition, air quality, and climate and is also envisioned to become a platform that addresses the needs of policy makers and stakeholders.

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