Ola Persson

Surface Heat Budget of the Arctic Ocean

A summary is presented of the Surface Heat Budget of the Arctic Ocean (SHEBA) project, with a focus on the field experiment that was conducted from October 1997 to October 1998. The primary objective of the field work was to collect ocean, ice, and atmospheric datasets over a full annual cycle that could be used to understand the processes controlling surface heat exchanges—in particular, the ice–albedo feedback and cloud–radiation feedback. This information is being used to improve formulations of arctic ice–ocean–atmosphere processes in climate models and thereby improve simulations of present and future arctic climate. The experiment was deployed from an ice breaker that was frozen into the ice pack and allowed to drift for the duration of the experiment. This research platform allowed the use of an extensive suite of instruments that directly measured ocean, atmosphere, and ice properties from both the ship and the ice pack in the immediate vicinity of the ship. This summary describes the project goal...

Toward Quantifying the Increasing Role of Oceanic Heat in Sea Ice Loss in the New Arctic

AbstractThe loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated ...

Investigation of Microphysical Parameterizations of Snow and Ice in Arctic Clouds during M-PACE through Model–Observation Comparisons

In this study the Weather Research Forecast model is used with 1-km horizontal grid spacing to investigate the microphysical properties of Arctic mixed-phase stratocumulus. Intensive measurements taken during the Department of Energy Atmospheric Radiation Measurement Program Mixed-Phase Arctic Cloud Experiment (M-PACE) on the North Slope of Alaska, during 9‐12 October 2004, are used to verify the microphysical characteristics of the model’s simulation of mixed-phase clouds (MPCs). A series of one- and two-moment bulk microphysical cloud schemes are tested to identify how the treatment of snow and ice affects the maintenance of cloud liquid water at low temperatures. The baseline two-moment simulation results in realistic liquid water paths and in size distributions of snow reasonably similar to observations. With a one-moment simulation for which the size distribution intercept parameter for snow is fixed at values taken from the two-moment simulation, reasonable snow size distributions are again obtained but the cloud liquid water is reduced because the one-moment scheme couples the number concentration to the mixing ratio. The one-moment scheme with the constant snow intercept parameter set to a value typical of midlatitude frontal clouds results in a substantial underprediction of the liquid water path. In the simulations, the number concentration of small ice crystals is found to be underestimated by an order of magnitude. A sensitivity test with the concentration of ice particles larger than 53 mm increased to the observed value results in underprediction of the liquid water path. If ice (not snow) is the primary driver for the depletion of cloud liquid water, then the results of this study suggest that the feedbacks among ice‐snow‐cloud liquid water may be misrepresented in the model.

The Sensitivity of Springtime Arctic Mixed-Phase Stratocumulus Clouds to Surface-Layer and Cloud-Top Inversion-Layer Moisture Sources

AbstractIn this study, a series of idealized large-eddy simulations is used to understand the relative impact of cloud-top and subcloud-layer sources of moisture on the microphysical–radiative–dynamical feedbacks in an Arctic mixed-phase stratocumulus (AMPS) cloud system. This study focuses on a case derived from observations of a persistent single-layer AMPS cloud deck on 8 April 2008 during the Indirect and Semi-Direct Aerosol Campaign near Barrow, Alaska. Moisture and moist static energy budgets are used to examine the potential impact of ice in mixed-phase clouds, specific humidity inversions coincident with temperature inversions as a source of moisture for the cloud system, and the presence of cloud liquid water above the mixed-layer top. This study demonstrates that AMPS have remarkable insensitivity to changes in moisture source. When the overlying air is dried initially, radiative cooling and turbulent entrainment increase moisture import from the surface layer. When the surface layer is dried in...

Doppler Correction of Wave Frequency Spectra Measured by Underway Vessels

Abstract“Sea State and Boundary Layer Physics of the Emerging Arctic Ocean” is an ongoing Departmental Research Initiative sponsored by the Office of Naval Research (http://www.apl.washington.edu/project/project.php?id=arctic_sea_state). The field component took place in the fall of 2015 within the Beaufort and Chukchi Seas and involved the deployment of a number of wave instruments, including a downward-looking Riegl laser rangefinder mounted on the foremast of the R/V Sikuliaq. Although time series measurements on a stationary vessel are thought to be accurate, an underway vessel introduces a Doppler shift to the observed wave spectrum. This Doppler shift is a function of the wavenumber vector and the velocity vector of the vessel. Of all the possible relative angles between wave direction and vessel heading, there are two main scenarios: 1) vessel steaming into waves and 2) vessel steaming with waves. Previous studies have considered only a subset of cases, and all were in scenario 1. This was likely t...

Episodic Reversal of Autumn Ice Advance Caused by Release of Ocean Heat in the Beaufort Sea

High-resolution measurements of the air-ice-ocean system during an October 2015 event in the Beaufort Sea demonstrate how stored ocean heat can be released to temporarily reverse seasonal ice advance. Strong on-ice winds over a vast fetch caused mixing and release of heat from the upper ocean. This heat was sufficient to melt large areas of thin, newly formed pancake ice; an average of 10 MJ/m2 was lost from the upper ocean in the study area, resulting in ∼3-5 cm pancake sea ice melt. Heat and salt budgets create a consistent picture of the evolving air-ice-ocean system during this event, in both a fixed and ice-following (Lagrangian) reference frame. The heat lost from the upper ocean is large compared with prior observations of ocean heat flux under thick, multi-year Arctic sea ice. In contrast to prior studies, where almost all heat lost goes into ice melt, a significant portion of the ocean heat released in this event goes directly to the atmosphere, while the remainder (∼30-40%) goes into melting sea ice. The magnitude of ocean mixing during this event may have been enhanced by large surface waves, reaching nearly 5 m at the peak, which are becoming increasingly common in the autumn Arctic Ocean. The wave effects are explored by comparing the air-ice-ocean evolution observed at short and long fetches, and a common scaling for Langmuir turbulence. After the event, the ocean mixed layer was deeper and cooler, and autumn ice formation resumed.

Arctic Climate Connections Curriculum: A Model for Bringing Authentic Data Into the Classroom

ABSTRACT Science education can build a bridge between research carried out by scientists and relevant learning opportunities for students. The Broader Impact requirements for scientists by funding agencies facilitate this connection. We propose and test a model curriculum development process in which scientists, curriculum developers, and classroom educators work together to scaffold the use of authentic, unprocessed scientific data for high school students. We outline a three-module curriculum structure that facilitates these goals. This curriculum engages students in the collection, description, visualization, and interpretation of data; develops understanding of the nature of science; includes prompts to develop higher-order thinking skills; builds knowledge of regional relevance of climate change in students; uses active learning techniques; and can be easily integrated with the Next Generation Science Standards. The curriculum was reviewed and tested in the classroom. To shed further light on the curriculum development process, we gathered reflection data from the scientists, curriculum developers, and educators. Scientists appreciated the collaborative process in which they contributed their expertise without requiring a large time commitment or strong expertise in science education. The curriculum developers viewed the modular structure as helpful in breaking complicated scientific concepts into teachable steps. Classroom educators appreciated the detailed description and step-by-step instructions to navigate data analysis tools like Excel or Google Earth. Initial classroom implementation of the curriculum by 11 teachers with over 1,100 students showed high levels of interest in the topic and engagement. Further work is needed to assess efficacy of the curriculum through classroom observations and measures of student learning.

Advancing Science and Services during the 2015-16 El Niño: The NOAA El Niño Rapid Response Field Campaign

AbstractForecasts by mid-2015 for a strong El Nino during winter 2015/16 presented an exceptional scientific opportunity to accelerate advances in understanding and predictions of an extreme climat...

Overview of the Arctic Sea State and Boundary Layer Physics Program

A large collaborative program has studied the coupled air‐ice‐ocean‐wave processes occurring in the Arctic during the autumn ice advance. The program included a field campaign in the western Arctic during the autumn of 2015, with in situ data collection and both aerial and satellite remote sensing. Many of the analyses have focused on using and improving forecast models. Summarizing and synthesizing the results from a series of separate papers, the overall view is of an Arctic shifting to a more seasonal system. The dramatic increase in open water extent and duration in the autumn means that large surface waves and significant surface heat fluxes are now common. When refreezing finally does occur, it is a highly variable process in space and time. Wind and wave events drive episodic advances and retreats of the ice edge, with associated variations in sea ice formation types (e.g., pancakes, nilas). This variability becomes imprinted on the winter ice cover, which in turn affects the melt season the following year.

Calibrating a Viscoelastic Sea Ice Model for Wave Propagation in the Arctic Fall Marginal Ice Zone: CALIBRATING WAVE-IN-ICE MODEL FOR MIZ

This paper presents a wave-in-ice model calibration study. Data used were collected in the thin ice of the advancing autumn marginal ice zone of the western Arctic Ocean in 2015, where pancake ice was found to be prevalent. Multiple buoys were deployed in seven wave experiments; data from four of these experiments are used in the present study. Wave attenuation coefficients are calculated utilizing wave energy decay between two buoys measuring simultaneously within the ice covered region. Wavenumbers are measured in one of these experiments. Forcing parameters are obtained from simultaneous in-situ and remote sensing observations, as well as forecast/hindcast models. Cases from three wave experiments are used to calibrate a viscoelastic model for wave attenuation/dispersion in ice cover. The calibration is done by minimizing the difference between modeled and measured complex wavenumber, using a multi-objective genetic algorithm. The calibrated results are validated using two methods. One is to directly apply the calibrated viscoelastic parameters to one of the wave experiments not used in the calibration and then compare the attenuation from the model with measured data. The other is to use the calibrated viscoelastic model in WAVEWATCH III® over the entire western Beaufort Sea and then compare the wave spectra at two remote sites not used in the calibration. Both validations show reasonable agreement between the model and the measured data. The completed viscoelastic model is believed to be applicable to the fall marginal ice zone dominated by pancake ice.