Gad Levy

Arctic Ice Dynamics Joint Experiment (AIDJEX) assumptions revisited and found inadequate

[1] This paper revisits the Arctic Ice Dynamics Joint Experiment (AIDJEX) assumptions about pack ice behavior with an eye to modeling sea ice dynamics. The AIDJEX assumptions were that (1) enough leads were present in a 100 km by 100 km region to make the ice isotropic on that scale; (2) the ice had no tensile strength; and (3) the ice behavior could be approximated by an isotropic yield surface. These assumptions were made during the development of the AIDJEX model in the 1970s, and are now found inadequate. The assumptions were made in part because of insufficient large-scale (10 km) deformation and stress data, and in part because of computer capability limitations. Upon reviewing deformation and stress data, it is clear that a model including deformation on discontinuities and an anisotropic failure surface with tension would better describe the behavior of pack ice. A model based on these assumptions is needed to represent the deformation and stress in pack ice on scales from 10 to 100 km, and would need to explicitly resolve discontinuities. Such a model would require a different class of metrics to validate discontinuities against observations.

Boundary layer roll statistics from SAR

The Atmospheric Boundary Layer (ABL) mean flow frequently consists of an organized secondary circulation in the form of counter rotating rolls embedded in it. Theory predicts this is the case for a range of thermodynamic conditions. Although generally associated with the formation of “cloud streets”, numerical and theoretical studies suggest that rolls should be present whenever there is sufficient shear to organize the convection, including cloud free conditions. Through their association with clouds and their modification of the mean low level flow, ABL rolls alter air-sea interaction processes, surface energy fluxes, and the earth radiational balance. Despite their potential importance to climate there exist no prior studies that can establish the extent and statistical frequency of roll occurrence. Synthetic Aperture Radar (SAR) can detect ABL roll signature on the ocean surface. A first regional climate scale attempt to construct ABL roll frequency statistics from the RADARSAT SAR observations is described.

Statistical, Physical, and Computational Aspects of Massive Data Analysis and Assimilation in Atmospheric Applications

Abstract The goals and procedures of the most data-intensive operations in atmospheric sciences, including data assimilation and fusion, are introduced. We explore specific problems that result from the expansion in observing systems from conventional to satellite borne and the corresponding transition from small, medium, and large datasets to massive datasets. The satellite data, their volumes, heterogeneity, and structure are described in specific examples. We illustrate that the atmospheric data analysis and assimilation procedures and the satellite data pose unique problems that do not exist in other applications and are not easily addressed by existing methods and tools. Existing solutions are presented and their performance with massive datasets is critically evaluated. We conclude that since the problems are interdisciplinary, a comprehensive solution must be interdisciplinary as well. We note that components of such a solution already exist in statistics, atmospheric, and computational sciences, b...

Simulated response of the marine atmospheric boundary layer in the western Pacific warm pool region to surface flux forcing

The atmospheric boundary layer (ABL) response to surface fluxes and prescribed advective and radiative forcings is tested in a column ABL model. Observations are used to run an ABL model in a marine tropical convective regime. The influence of surface fluxes and prescribed advective and radiative forcings potential temperature and specific humidity throughout the ABL is examined. The manner by which the different ABL processes interact with each other is investigated in light of recently demonstrated sensitivity of the simulated general circulation to flux parameterizations. Simulated near-surface temperature and sensible heat fluxes are in close agreement with observations, with both the advection and the sensible heat flux contributing approximately equally to ABL warming. Simulated near-surface humidity and humidity profiles are dryer than observed. The model exhibits very vigorous nonlocal ABL mixing that self-regulates the flux response in its surface flux formulation by reducing humidity gradients and subsequent evaporation. The total time-averaged simulated heat flux for two surface flux parameterizations tested is within the Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Experiment (TOGA-COARE) required accuracy. When decoupled from model response, the ABL model formulation overpredicts (underpredicts) latent heat fluxes modestly. ABL depth is dominated by nonlinear terms involving interaction between different surface fluxes and the ABL turbulent mixing and between these fluxes and advective and radiative forcing. Simulations in coarse vertical resolution typical of General Circulation Models (GCMs) result in significant ABL deepening and drying over observed values but also in better agreement between the time-averaged simulated and observed surface heat fluxes.

Air-sea fluxes from satellite sensors: calibration, time, space, and scale transitions

A number of spaceborne microwave sensors have been launched in the last decade, significantly increasing the quantity and quality of observations over the oceans that can be used to study air-sea interactions. These observations, when combined with conventional in-situ observations and model output, can be used to improve air-sea flux estimates and for model initialization and parameterization. However, because of the different characteristics, sampling frequency and resolution, and sensor accuracy, the calibration of satellite observations against in-situ observations is discussed. Special attention is paid to time, space, and scale transitions, and to formulating a velocity scale for use in large scale models. Specifically, the paper reviews recent observational and modeling studies that show that a considerable subgrid air-sea flux may be generated by directional variability in the near surface wind field. It then describes: (i) temporal-spatial conversion methods that allow proper calibration of satellite observations against in-situ data and synergistic use of heterogeneous data sets for estimating flux enhancement; and (ii) resolution dependent velocity scale terms that can be formulated from scatterometer observations and incorporate in General Circulation Models bulk formulas.

Space and time aliasing structure in mean polar-orbiting satellite data

Monthly mean wind fields from the European Remote Sensing Satellite (ERS-1) scatterometer are calculated and presented. A banded structure which resembles the satellite subtrack is clearly and consistently apparent in the isotachs as well as the u- and v-components of the wind with a typical variation (amplitude) of 4 ms/sup -1/. An experiment is designed to trace the cause of the banded structure; the European Centre for Medium Range Weather Forecasting (ECMWF) surface wind analyses are used to form a control (synoptic) set and a simulated scatterometer wind set sampled with the ERS-1 temporal/spatial sampling pattern. Both sets are used to create monthly averages. The banded structures appear in the simulated scatterometer set but do not appear in the control set. It is concluded that the source of the banded structure is in the spatial and temporal sampling of the polar-orbiting satellite. The nature of the problem and some means to control it are discussed. The problem is rather complicated and involves multiple time and space scales, over and under sampling in space, aliasing of time to space domain, and intraseasonal variability which is preferentially sampled. Therefore, common means of controlling the undesirable effects of aliasing address only part of the problem. While some of these control methods produce visually pleasing results, they may bias the true mean.<<ETX>>

Surface Pressure Maps From Scatterometer Data

The ability to determine surface pressure fields from satellite scatterometer data was shown by Brown and Levy (1986). The surface winds are used to calculate the gradient winds above the planetary boundary layer, and these are directly related to the pressure gradients. There are corrections for variable stratification, variable surface roughness, horizontal inhomogeneity, humidity and baroclinity. The SEASAT scatterometer (SASS) data has been used in a systematic study of 50 synoptic weather events (regions of approximately 1000 X 1000km). The preliminary statistics of agreement with national weather service surface pressure maps are calculated. The resulting surface pressure maps can be used together with SASS winds and SMMR water vapor and liquid water analyses to provide good front and storm system analyses. The pressure fields will also allow corrections to oceanic geostrophic flow determined from satellite altimeter soundings.