Alfred Wegener Institute for Polar and Marine Research
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Combining sea-ice and ocean data assimilation with nudging atmospheric circulation in the AWI Coupled Prediction System
No full textOral presentation at EGU GA 2023 (EGU23 14227
Nudging allows direct evaluation of coupled climate models with in situ observations: a case study from the MOSAiC expedition
Get PDFComparing the output of general circulation models to observations is essential for assessing and improving the quality of models. While numerical weather prediction models are routinely assessed against a large array of observations, comparing climate models and observations usually requires long time series to build robust statistics. Here, we show that by nudging the large-scale atmospheric circulation in coupled climate models, model output can be compared to local observations for individual days. We illustrate this for three climate models during a period in April 2020 when a warm air intrusion reached the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the central Arctic. Radiosondes, cloud remote sensing and surface flux observations from the MOSAiC expedition serve as reference observations. The climate models AWI-CM1/ECHAM and AWI-CM3/IFS miss the diurnal cycle of surface temperature in spring, likely because both models assume the snowpack on ice to have a uniform temperature. CAM6, a model that uses three layers to represent snow temperature, represents the diurnal cycle more realistically. During a cold and dry period with pervasive thin mixed-phase clouds, AWI-CM1/ECHAM only produces partial cloud cover and overestimates downwelling shortwave radiation at the surface. AWI-CM3/IFS produces a closed cloud cover but misses cloud liquid water. Our results show that nudging the large-scale circulation to the observed state allows a meaningful comparison of climate model output even to short-term observational campaigns. We suggest that nudging can simplify and accelerate the pathway from observations to climate model improvements and substantially extends the range of observations suitable for model evaluation
Turbulent structure of the Arctic boundary layer in early summer driven by stability, wind shear and cloud-top radiative cooling: ACLOUD airborne observations
Get PDFAbstract. Clouds are assumed to play an important role in the Arctic amplification process. This motivated a
detailed investigation of cloud processes, including radiative and turbulent fluxes. Data from the aircraft campaign
ACLOUD were analyzed with a focus on the mean and turbulent structure of the cloudy boundary layer
over the Fram Strait marginal sea ice zone in late spring and early summer 2017. Vertical profiles of turbulence
moments are presented from contrasting atmospheric boundary layers (ABLs) from 4 d. They differ by the
magnitude of wind speed, boundary-layer height, stability, the strength of the cloud-top radiative cooling and
the number of cloud layers. Turbulence statistics up to third-order moments are presented, which were obtained
from horizontal-level flights and from slanted profiles. It is shown that both of these flight patterns complement
each other and form a data set that resolves the vertical structure of the ABL turbulence well. The comparison of
the 4 d shows that especially during weak wind, even in shallow Arctic ABLs with mixing ratios below 3 g kg-1,
cloud-top cooling can serve as a main source of turbulent kinetic energy (TKE).Well-mixed ABLs are generated
where TKE is increased and vertical velocity variance shows pronounced maxima in the cloud layer. Negative
vertical velocity skewness points then to upside-down convection. Turbulent heat fluxes are directed upward in
the cloud layer as a result of cold downdrafts. In two cases with single-layer stratocumulus, turbulent transport
of heat flux and of temperature variance are both negative in the cloud layer, suggesting an important role of
large eddies. In contrast, in a case with weak cloud-top cooling, these quantities are positive in the ABL due to
the heating from the surface.
Based on observations and results of a mixed-layer model it is shown that the maxima of turbulent fluxes are,
however, smaller than the jump of the net terrestrial radiation flux across the upper part of a cloud due to the
(i) shallowness of the mixed layer and (ii) the presence of a downward entrainment heat flux. The mixed-layer
model also shows that the buoyancy production of TKE is substantially smaller in stratocumulus over the Arctic
sea ice compared to subtropics due to a smaller surface moisture flux and smaller decrease in specific humidity
(or even humidity inversions) right above the cloud top.
In a case of strong wind, wind shear shapes the ABL turbulent structure, especially over rough sea ice, despite
the presence of a strong cloud-top cooling. In the presence of mid-level clouds, cloud-top radiative cooling and
thus also TKE in the lowermost cloud layer are strongly reduced, and the ABL turbulent structure becomes
governed by stability, i.e., by the surface–air temperature difference and wind speed. A comparison of slightly
unstable and weakly stable cases shows a strong reduction of TKE due to increased stability even though the
absolute value of wind speed was similar. In summary, the presented study documents vertical profiles of the
ABL turbulence with a high resolution in a wide range of conditions. It can serve as a basis for turbulence
closure evaluation and process studies in Arctic clouds
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
Get PDFArctic Ocean simulations in 19 global ocean-sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are evaluated in this paper. Our findings show no significant improvements in Arctic Ocean simulations from the previous Coordinated Ocean-ice Reference Experiments phase II (CORE-II) to the current OMIP. Large model biases and inter-model spread exist in the simulated mean state of the halocline and Atlantic Water layer in the OMIP models. Most of the OMIP models suffer from a too thick and deep Atlantic Water layer, a too deep halocline base, and large fresh biases in the halocline. The OMIP models qualitatively agree on the variability and change of the Arctic Ocean freshwater content; sea surface height; stratification; and volume, heat, and freshwater transports through the Arctic Ocean gateways. They can reproduce the changes in the gateway transports observed in the early 21st century, with the exception of the Bering Strait. We also found that the OMIP models employing the NEMO ocean model simulate relatively larger volume and heat transports through the Barents Sea Opening. Overall, the performance of the Arctic Ocean simulations is similar between the CORE2-forced OMIP-1 and JRA55-do-forced OMIP-2 experiments
Uniquely low stable iron isotopic signatures in deep marine sediments caused by Rayleigh distillation
Get PDFMicrobially mediated iron (Fe) reduction is suggested to be one of the earliest metabolic pathways on Earth and Fe(III)-reducing microorganisms might be key inhabitants of the deep and hot biosphere [1, 2]. Since microbial Fe cycling is typically accompanied by Fe isotope fractionation, stable Fe isotopes (δ56Fe) are used as tracer for microbial processes in modern and ancient marine sediments [3, 4]. Here we present Fe isotope data for dissolved and sequentially extracted sedimentary Fe pools from subseafloor sediments that were recovered during International Ocean Discovery Program Expedition 370 from a 1,180 m deep hole drilled in the Nankai Trough off Japan where temperatures of up to 120°C are reached at the sediment-basement interface. The expedition aimed at exploring the temperature limit of microbial life and identifying geochemical and microbial signatures that differentiate the biotic and abiotic realms [5, 6]. Dissolved Fe (Fe(II)aq) is isotopically light throughout the ferruginous sediment interval but some samples have exceptionally light δ56Fe values. Such light δ56Fe values have never been reported in natural marine environments and cannot be solely attributed to microbially mediated Fe(III) reduction. We show that the light δ56Fe values are best explained by a Rayleigh distillation model where Fe(II)aq is continuously removed from the pore water by diffusion and adsorption onto Fe (oxyhydr)oxide surfaces. While the microbially mediated Fe(II)aq release has ceased due to an increase in temperature beyond the threshold of mesophilic microorganisms, the abiotic diffusional and adsorptive Fe(II)aq removal continued, leading to uniquely light δ56Fe values. These findings have important implications for the interpretation of Fe isotope records especially in deep subseafloor sediments
Organic carbon in subsea permafrost: a globally significant but inert carbon pool Frederieke Miesner
Get PDFSubsea permafrost underlays 2.4 million km2 of the Arctic Shelf, an area equaling ~18% of the terrestrial permafrost region. Most of it was inundated at some point after the last glacial maximum and is in an advanced state of warming. How much organic carbon (OC) accumulated, how this carbon pool was affected by permafrost presence and degradation over time, how much carbon still remains today and how much of it may be mobilized are major unknowns in the global carbon
cycle. Recent estimates of OC decomposition from thawing submarine permafrost were as high as
8 Tg OC per year in methane alone. Here, we combine a numerical model of sedimentation and permafrost evolution with simplified carbon turnover to estimate accumulation and microbial decomposition of organic matter on the pan-Arctic shelf over the past four glacial cycles (450 kyr). Organic carbon decomposition is modeled with a reactivity continuum model using inversely determined parameters from incubation experiments and liquid water content within the permafrost as the limiting factor rather than temperature alone. We find that Arctic shelf permafrost is a long-term carbon sink storing 2822 (1518 - 4982) Pg OC, two to four times the amount stored in lowland permafrost. Although subsea permafrost is currently thawing, prior microbial decomposition and organic matter aging would limit decomposition rates to less than 48 Tg OC per year even if all frozen sediment deposited in the past 450 kyr thawed immediately. Since actual thaw rates are orders of magnitude lower, true emissions due to subsea permafrost thaw are also orders of magnitude lower than this. The OC pool in shelf permafrost is therefore largely immobilized. Compared to the organic matter in thawing permafrost large emissions are more likely derived from older and deeper sources as shelf’s frozen lid, the permafrost, becomes more permeable
The Way of Carbon - Composition and Transport of Organic Carbon in the Nearshore Zone of Herschel Island, Qikiqtaruk
Get PDFArctic permafrost coasts are greatly impacted by global climate change. Warming permafrost, decreasing sea ice extent and increasing sea temperature lead to greater coastal erosion. The carbon stored in the permafrost is then released into the nearshore zone, where it degrades, potentially leading to the release of greenhouse gas emissions (GHG) into the atmosphere.
Yet, the exact pathways of organic carbon (OC) in the nearshore zone are not completely understood. In order to fill this gap, we collected dissolved and particulate OC (DOC, POC) samples in the nearshore zone of Herschel Island, Qikiqtaruk.
The sampling was repeatedly carried out along a transect over a period of two weeks during the open water season in summer 2022. Water samples were collected at the surface and at several water depths. Subsequently, water samples were filtered through 47μm fiberglass filters and examined in the laboratory for suspended particulate matter, DOC, and POC. When possible, Van Veen Grab samples and short cores were taken at each sample location. The upper six centimeters of the short cores as well as the grab samples were analyzed for grain size, mercury, carbon and nitrogen content.
In addition to the water sampling, temperature, conductivity, salinity, and turbidity were measured at each sampling location with CTD and turbidity meter.
Initial data shows a gradient in temperature and turbidity in the water column, especially at the beginning of the sampling period, which coincided with the sea ice breakup. Hereby, values for Turbidity range from 3.81 to 205.00 FNU. The amount of DOC and POC in the water samples will give an indication on the variability of geochemical properties in the water column over time. This will allow us to determine and quantify the link between these properties and environmental forcing.
Keywords: Coastal Erosion, Carbon Pathways, Sediment Transport, Permafrost Coas
Adaptive dynamical networks
Get PDFIt is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields, in particular, for the models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In this review, we provide a detailed description of adaptive dynamical networks, show their applications in various areas of research, highlight their dynamical features and describe the arising dynamical phenomena, and give an overview of the available mathematical methods developed for understanding adaptive dynamical networks
Critical Drift in a Neuro-Inspired Adaptive Network
Get PDFIt has been postulated that the brain operates in a self-organized critical state that brings multiple benefits, such as optimal sensitivity to input. Thus far, self-organized criticality has typically been depicted as a one-dimensional process, where one parameter is tuned to a critical value. However, the number of adjustable parameters in the brain is vast, and hence critical states can be expected to occupy a high-dimensional manifold inside a high-dimensional parameter space. Here, we show that adaptation rules inspired by homeostatic plasticity drive a neuro-inspired network to drift on a critical manifold, where the system is poised between inactivity and persistent activity. During the drift, global network parameters continue to change while the system remains at criticality