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R. Onken, J. Fischer, and J. D. Woods

Abstract

We present and compare results from a two-dimensional numerical frontogenesis model and a field experiment in the eddy field of the North Atlantic Current in order to illustrate and explain the shape and generation mechanisms of frontal finestructure.

The frontogenesis model has been presented in detail in an earlier paper by Bleck et al. We have added to this model simple initial temperature and salinity fields, which are treated as passive tracers on isopycnals. Integrating the model for three days produces an asymmetry of the thermohaline gradient field and the familiar slope of the frontal surface details of which depend on the initial conditions. An analysis of the terms of the tracer advection equation reveals that the asymmetry is due to the divergence of the cross-jet agestrophic mass flux induced by vortex stretching, whereas the slope of the frontal surface is caused by the cross-jet advection of the thermohaline gradient.

Within the eddy field of the North Atlantic Current we observed regions of confluent flow in which mesoscale fronts have been formed, exhibiting dynamical and thermohaline properties similar to those predicted by the model. By applying the model results we construct a dynamically consistent picture of the cross-front circulation, which leads to the observed thermohaline structure. A method is proposed which allows to estimate the magnitude of the cross-frontal flow solely from the finestructure of passive scalar gradients.

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Valentijn R. N. Pauwels and Eric F. Wood

Abstract

One of the governing scientific objectives of the Boreal Ecosystem–Atmosphere Study (BOREAS) is the development of methods for applying process models over large spatial scales using remote sensing and other integrative modeling techniques. This paper presents the first step in a modeling strategy that focuses on scaling a point model up to the BOREAS regional scale. The objective of this paper is to compare the effect of differences in spatial resolution of land cover data to land–atmosphere model results relative to the effect of differences in land cover sensors and classification schemes. The analysis suggests that the uncertainty in model results arises mainly from the uncertainty in the land cover classification and that the lack of spatial resolution has a lower effect. Overall, an uncertainty of approximately 15% in modeled energy and water balance fluxes and states has to be assigned because of the uncertainty in land cover classification.

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M. J. Roberts and R. A. Wood

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This paper describes a series of four experiments, each run for 10 years at 1° × 1° resolution on a North Atlantic domain, designed to illuminate the sensitivity of a Bryan–Cox-type ocean model to changes in the representation of the ridges that restrict the flow of dense, deep water out of the Greenland–Iceland–Norway (GIN) basin. In reality, much of the outflow takes place through narrow sills, which are subgrid-scale in the model, and small changes in the model topography to reflect these sills have a large impact on the outflow and on the compensating inflow of warm North Atlantic water. The circulation of the GIN basin is dramatically changed depending on the amount of this inflow; with no inflow, the basin cools and freshens, as would be expected, whereas with too much inflow, it becomes warm, salty, and homogeneous to great depths.

Moreover, the small changes in topography have wider implications for the simulation. The presence or absence of dense overflows has a great impact on the mixed layer development in the subpolar gyre, with mixed layer depths differing by more than 500 m between two of the cases. This has implications for the formation of subpolar mode water, which is nearly shut off in the two cases with significant overflow.

The meridional overturning in the model in year 10 increases by over 50% at its peak between the cases with no dense overflow and those with the greatest overflow, and this partly explains a change in peak heat transport, which increases by around 50% in the cases with significant overflow.

The results in this paper imply that careful “tuning” of the model topography is necessary in ocean/climate models in order to get a reasonable simulation of the conveyor belt and of North Atlantic Deep Water formation.

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Craig R. Ferguson and Eric F. Wood

Abstract

The lack of observational data for use in evaluating the realism of model-based land–atmosphere feedback signal and strength has been deemed a major obstacle to future improvements to seasonal weather prediction by the Global Land–Atmosphere Coupling Experiment (GLACE). To address this need, a 7-yr (2002–09) satellite remote sensing data record is exploited to produce for the first time global maps of predominant coupling signals. Specifically, a previously implemented convective triggering potential (CTP)–humidity index (HI) framework for describing atmospheric controls on soil moisture–rainfall feedbacks is revisited and generalized for global application using CTP and HI from the Atmospheric Infrared Sounder (AIRS), soil moisture from the Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E), and the U.S. Climate Prediction Center (CPC) merged satellite rainfall product (CMORPH). Based on observations taken during an AMSR-E-derived convective rainfall season, the global land area is categorized into four convective regimes: 1) those with atmospheric conditions favoring deep convection over wet soils, 2) those with atmospheric conditions favoring deep convection over dry soils, 3) those with atmospheric conditions that suppress convection over any land surface, and 4) those with atmospheric conditions that support convection over any land surface. Classification maps are produced using both the original and modified frameworks, and later contrasted with similarly derived maps using inputs from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective Analysis for Research and Applications (MERRA). Both AIRS and MERRA datasets of CTP and HI are validated using radiosonde observations. The combinations of methods and data sources employed in this study enable evaluation of not only the sensitivity of the classification schemes themselves to their inputs, but also the uncertainty in the resultant classification maps. The findings are summarized for 20 climatic regions and three GLACE coupling hot spots, as well as zonally and globally. Globally, of the four-class scheme, regions for which convection is favored over wet and dry soils accounted for the greatest and least extent, respectively. Despite vast differences among the maps, many geographically large regions of concurrence exist. Through its ability to compensate for the latitudinally varying CTP–HI–rainfall tendency characteristics observed in this study, the revised classification framework overcomes limitations of the original framework. By identifying regions where coupling persists using satellite remote sensing this study provides the first observationally based guidance for future spatially and temporally focused studies of land–atmosphere interactions. Joint distributions of CTP and HI and soil moisture, rainfall occurrence, and depth demonstrate the relevance of CTP and HI in coupling studies and their potential value in future model evaluation, rainfall forecast, and/or hydrologic consistency applications.

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R. Paul Lawson, Sarah Woods, and Hugh Morrison

Abstract

The rapid glaciation of tropical cumulus clouds has been an enigma and has been debated in the literature for over 60 years. Possible mechanisms responsible for the rapid freezing have been postulated, but until now direct evidence has been lacking. Recent high-speed photography of electrostatically suspended supercooled drops in the laboratory has shown that freezing events produce small secondary ice particles. Aircraft observations from the Ice in Clouds Experiment–Tropical (ICE-T), strongly suggest that the drop-freezing secondary ice production mechanism is operating in strong, tropical cumulus updraft cores. The result is the production of small ice particles colliding with large supercooled drops (hundreds of microns up to millimeters in diameter), producing a cascading process that results in rapid glaciation of water drops in the updraft. The process was analyzed from data collected using state-of-the-art cloud particle probes during 54 Learjet penetrations of strong cumulus updraft cores over open ocean in a temperature range from 5° to −20°C. Repeated Learjet penetrations of an updraft core containing 3–5 g m−3 supercooled liquid showed an order-of-magnitude decrease in liquid mass concentration 3 min later at an elevation 1–1.5 km higher in the cloud. The aircraft observations were simulated using a one-dimensional cloud model with explicit bin microphysics. The model was initialized with drop and ice particle size distributions observed prior to rapid glaciation. Simulations show that the model can explain the observed rapid glaciation by the drop-freezing secondary ice production process and subsequent riming, which results when large supercooled drops collide with ice particles.

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L. C. Jackson and R. A. Wood

Abstract

Different strategies have been proposed in previous studies for monitoring the Atlantic meridional overturning circulation (AMOC). As well as arrays to directly monitor the AMOC strength, various fingerprints have been suggested to represent an aspect of the AMOC based on properties such as temperature and density. The additional value of fingerprints potentially includes the ability to detect a change earlier than a change in the AMOC itself, the ability to extend a time series back into the past, and the ability to detect crossing a threshold. In this study we select metrics that have been proposed as fingerprints in previous studies and evaluate their ability to detect AMOC changes in a number of scenarios (internal variability, weakening from increased greenhouse gases, weakening from hosing and hysteresis) in the eddy-permitting coupled climate model HadGEM3-GC2. We find that the metrics that perform best are the temperature metrics based on large-scale differences, the large-scale meridional density gradient, and the vertical density difference in the Labrador Sea. The best metric for monitoring the AMOC depends somewhat on the processes driving the change. Hence the best strategy would be to consider multiple fingerprints to provide early detection of all likely AMOC changes.

Open access
Craig R. Ferguson and Eric F. Wood

Abstract

The skill of instantaneous Atmospheric Infrared Sounder (AIRS) retrieved near-surface meteorology, including surface skin temperature (Ts), air temperature (Ta), specific humidity (q), and relative humidity (RH), as well as model-derived surface pressure (P surf) and 10-m wind speed (w), is evaluated using collocated National Climatic Data Center (NCDC) in situ observations, offline data from the North American Land Data Assimilation System (NLDAS), and geostationary remote sensing (RS) data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). Such data are needed for RS-based water cycle monitoring in areas without readily available in situ data. The study is conducted over the continental United States and Africa for a period of more than 6 years (2002–08). For both regions, it provides for the first time the geographic distribution of AIRS retrieval performance. Through conditional sampling, attribution of retrieval errors to scene atmospheric and surface conditions is performed. The findings support previous assertions that performance degrades with cloud fraction and that (positive) bias enhances with altitude. In general AIRS is biased warm and dry. In certain regions, strong AIRS–NCDC correlation suggests that bias-driven errors, which can be substantial, are correctable. The utility of the error characteristics for prescribing the input-induced uncertainty of RS retrieval models is demonstrated through two applications: a microwave soil moisture retrieval algorithm and the Penman–Monteith evapotranspiration model. An important side benefit of this study is the verification of NLDAS forcing.

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Kevin R. Wood and James E. Overland

A unique glimpse of the Arctic from a period before the present era of climate warming is found in the records of the first International Polar Year (IPY) of 1882–83. Inspired by the Austrian scientist and explorer Carl Weyprecht, the purpose of the IPY was to discover the fundamental laws governing global meteorological and geophysical phenomena. It was understood that new discoveries would depend upon a program of simultaneous observations that encompassed the polar regions. The collection and analysis of the first series of coordinated meteorological observations ever obtained in the Arctic was one of the principal objects of the IPY. The field program was successfully completed and a vast body of data was collected, but afterward it fell into obscurity with little analysis completed.

We have analyzed for the first time the synchronous meteorological observations recorded during the first IPY. This analysis contributes to the goal of the upcoming fourth IPY scheduled for 2007–08: to understand the climate changes currently unfolding in the Arctic/Antarctic within the context of the past. We found that surface air temperature (SAT) and sea level pressure (SLP) observed during 1882–83 were within the limits of recent climatology, but with a slight skew toward colder temperatures, and showed a wide range of variability from place to place over the course of the year, which is a feature typical of the Arctic climate today. Monthly SAT, SLP, and associated phenological anomalies were regionally coherent and consistent with patterns of variability in the atmospheric circulation such as the North Atlantic Oscillation (NAO). Evidence of a strong NAO signature in the observed SAT anomalies during the first IPY highlights the impact of large-scale atmospheric circulation patterns on regional climate variability in the Arctic, both today and in the past.

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Yangang Liu, Peter H. Daum, R. McGraw, and R. Wood

Abstract

Existing Sundqvist-type parameterizations, which only consider dependence of the autoconversion rate on cloud liquid water content, are generalized to explicitly account for the droplet concentration and relative dispersion of the cloud droplet size distribution as well. The generalized Sundqvist-type parameterization includes the more commonly used Kessler-type parameterization as a special case, unifying the two different types of parameterizations for the autoconversion rate. The generalized Sundqvist-type parameterization is identical with the Kessler-type parameterization presented in Part I beyond the autoconversion threshold, but exhibits a more realistic, smooth transition in the vicinity of the autoconversion threshold (threshold behavior) in contrast to the discontinuously abrupt transition embodied in the Kessler-type parameterization. A new Sundqvist-type parameterization is further derived by applying the expression for the critical radius derived from the kinetic potential theory to the generalized Sundqvist-type parameterization. The new parameterization eliminates the need for defining the driving radius and for prescribing the critical radius associated with Kessler-type parameterizations. The two-part structure of the autoconversion process raises questions regarding model-based empirical parameterizations obtained by fitting simulation results from detailed collection models with a single function.

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Yinghui Liu, Jeffrey R. Key, Steve Vavrus, and Cian Woods

Abstract

Northward fluxes of moisture and sensible heat into the Arctic affect the atmospheric stability, sea ice and snow cover, clouds, and surface energy budget. Intense moisture fluxes into the Arctic are called moisture intrusions; some can lead to basinwide increases in downward longwave radiation (DLR) at the surface, called downward infrared (IR) events. Using the ERA-Interim reanalysis from 1990 to 2016, this study investigated the time evolution of cloud amount and cloud properties and their impact on the surface radiation fluxes in response to Arctic moisture intrusions and downward IR events during winter for better understanding of the Arctic moisture intrusions. A composite analysis revealed several key features: moisture intrusions produce more clouds and higher cloud liquid and ice water content; positive cloud amount anomalies can persist for over 10 days over the Arctic Ocean during downward IR events; positive high-level and middle-level cloud anomalies are evident in the early stage, and positive low-level cloud anomalies are evident in the late stage. Greater clear-sky DLR and longwave cloud radiative forcing (CRF) over the Arctic Ocean accompany the greater all-sky DLR during the downward IR events. Greater clear-sky DLR can be attributed to higher air temperatures and higher total column water vapor, while greater longwave CRF is the result of larger cloud amount and cloud water content. Longwave CRF anomalies account for approximately 40% of the all-sky DLR anomalies.

Open access