Changes In Atmospheric Forcing Research Articles

The Stepwise Reduction of Multiyear Sea Ice Area in the Arctic Ocean Since 1980

AbstractThe loss of multiyear sea ice (MYI) in the Arctic Ocean is a significant change that affects all facets of the Arctic environment. Using a Lagrangian ice age product, we examine MYI loss and quantify the annual MYI area budget from 1980 to 2021 as the balance of export, melt, and replenishment. Overall, MYI area declined at 72,500 km2/yr; however, a majority of the loss occurred during two stepwise reductions that interrupt an otherwise balanced budget and resulted in the northward contraction of the MYI pack. First, in 1989, a change in atmospheric forcing led to a +56% anomaly in MYI export through Fram Strait. The second occurred from 2006 to 2008 with anomalously high melt (+25%) and export (+23%) coupled with low replenishment (−8%). In terms of trends, melt has increased since 1989, particularly in the Beaufort Sea, export has decreased since 2008 due to reduced MYI coverage north of Fram Strait, and replenishment has increased over the full time series due to a negative feedback that promotes seasonal ice survival at higher latitudes exposed by MYI loss. However, retention of older MYI has significantly declined, transitioning the MYI pack toward younger MYI that is less resilient than previously anticipated and could soon elicit another stepwise reduction. We speculate that future MYI loss will be driven by increased melt and reduced replenishment, both of which are enhanced with continued warming and will one day render the Arctic Ocean free of MYI, a change that will coincide with a seasonally ice‐free Arctic Ocean.

Wind‐Driven Seasonal Intrusion of Modified Circumpolar Deep Water Onto the Continental Shelf in Prydz Bay, East Antarctica

AbstractIntrusion of warm modified Circumpolar Deep Water (mCDW) is critical to heat transport onto the continental shelf around Antarctica, with substantial impacts on basal melting of ice shelves and sea ice production. We use hydrographic data collected in Prydz Bay, East Antarctica, and atmospheric and ocean reanalyses to investigate the seasonality of mCDW intrusions onto the East Antarctic continental shelf. Mooring measurements confirm that there is significant intrusion of mCDW over the inner continental shelf of Prydz Bay in March–July (austral autumn and early winter). The warming signal of intruded mCDW over the inner shelf is correlated with wind changes north of the shelf break, with a significant lag. This suggests that the autumn‐winter mCDW intrusions over the inner shelf are significantly affected by the wind regime north of the shelf break in January–May, when a southward displacement of the westerly winds occurs. The southward shift of westerly winds drives the shallowest depth of upwelled mCDW to move poleward and contributes more warm water to the shelf break. This results in the shoaling of mCDW near the shelf break in January–May and promotes mCDW intrusions onto the continental shelf. The dynamic barrier imposed on mCDW intrusions by the strong Antarctic Slope Front in January–May is offset by this shoaling of mCDW. This study indicates the strong sensitivity of continental shelves in East Antarctica to atmospheric forcing changes over the Southern Ocean.

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series

Abstract. Improving the quantification of soil thermal and physical properties is key to achieving a better understanding and prediction of soil hydro-biogeochemical processes and their responses to changes in atmospheric forcing. Obtaining such information at numerous locations and/or over time with conventional soil sampling is challenging. The increasing availability of low-cost, vertically resolved temperature sensor arrays offers promise for improving the estimation of soil thermal properties from temperature time series, and the possible indirect estimation of physical properties. Still, the reliability and limitations of such an approach need to be assessed. In the present study, we develop a parameter estimation approach based on a combination of thermal modeling, sliding time windows, Bayesian inference, and Markov chain Monte Carlo simulation to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution (i.e., down to 5 to 10 cm vertical resolution) from soil temperature time series. We provide the necessary framework to assess under which environmental conditions (soil temperature gradient, fluctuations, and trend), temperature sensor characteristics (bias and level of noise), and deployment geometries (sensor number and position) soil thermal diffusivity can be reliably inferred. We validate the method with synthetic experiments and field studies. The synthetic experiments show that in the presence of median diurnal fluctuations ≥ 1.5 ∘C at 5 cm below the ground surface, temperature gradients > 2 ∘C m−1, and a sliding time window of at least 4 d the proposed method provides reliable depth-resolved thermal diffusivity estimates with percentage errors ≤ 10 % and posterior relative standard deviations ≤ 5 % up to 1 m depth. Reliable thermal diffusivity under such environmental conditions also requires temperature sensors to be spaced precisely (with accuracy to a few millimeters), with a level of noise ≤ 0.02 ∘C, and with a bias defined by a standard deviation ≤ 0.01 ∘C. Finally, the application of the developed approach to field data indicates significant repeatability in results and similarity with independent measurements, as well as promise in using a sliding time window to estimate temporal changes in soil thermal diffusivity, as needed to potentially capture changes in bulk density or water content.

Recent divergent changes in Alaskan pinniped trophic position detected using compound-specific stable isotope analysis

Over the past century, Alaskan pinnipeds have experienced dramatic changes in abundance, but these changes have been highly variable across species and regions. In recent decades, changes in atmospheric forcing and sea surface temperature have been particularly pronounced in the Gulf of Alaska and eastern Bering Sea, impacting the food webs in which Alaskan pinnipeds forage. We used compound-specific stable isotope analysis of nitrogen in amino acids to estimate historic and modern trophic positions of harbor seals Phoca vitulina and Steller sea lions Eumetopias jubatus in the Gulf of Alaska and Bristol Bay. We applied a Bayesian hierarchical framework to determine whether shared trends through time exist across pinnipeds (classified by region and species) on decadal scales. Model results identified both shared trends through time and classification-specific decadal changes in pinniped trophic position. The largest change in trophic position occurred in the 2000s and 2010s and was observed in both Steller sea lions (median: 2.8) and harbor seals (median: 3.1) in the Gulf of Alaska, but not harbor seals in Bristol Bay or Iliamna Lake. Divergent trophic position patterns in the 2000s were identified in the western stock of Steller sea lions, which increased in trophic position, and sympatric harbor seals in the northern Gulf of Alaska, which decreased in trophic position. Our results indicate that these species have been experiencing unique food web conditions in recent decades in the Gulf of Alaska, likely in response to recent climate-induced ecological change in the region.

A Deep Learning Model for Forecasting Velocity Structures of the Loop Current System in the Gulf of Mexico

Despite the large efforts made by the ocean modeling community, such as the GODAE (Global Ocean Data Assimilation Experiment), which started in 1997 and was renamed as OceanPredict in 2019, the prediction of ocean currents has remained a challenge until the present day—particularly in ocean regions that are characterized by rapid changes in their circulation due to changes in atmospheric forcing or due to the release of available potential energy through the development of instabilities. Ocean numerical models’ useful forecast window is no longer than two days over a given area with the best initialization possible. Predictions quickly diverge from the observational field throughout the water and become unreliable, despite the fact that they can simulate the observed dynamics through other variables such as temperature, salinity and sea surface height. Numerical methods such as harmonic analysis are used to predict both short- and long-term tidal currents with significant accuracy. However, they are limited to the areas where the tide was measured. In this study, a new approach to ocean current prediction based on deep learning is proposed. This method is evaluated on the measured energetic currents of the Gulf of Mexico circulation dominated by the Loop Current (LC) at multiple spatial and temporal scales. The approach taken herein consists of dividing the velocity tensor into planes perpendicular to each of the three Cartesian coordinate system directions. A Long Short-Term Memory Recurrent Neural Network, which is best suited to handling long-term dependencies in the data, was thus used to predict the evolution of the velocity field in each plane, along each of the three directions. The predicted tensors, made of the planes perpendicular to each Cartesian direction, revealed that the model’s prediction skills were best for the flow field in the planes perpendicular to the direction of prediction. Furthermore, the fusion of all three predicted tensors significantly increased the overall skills of the flow prediction over the individual model’s predictions. The useful forecast period of this new model was greater than 4 days with a root mean square error less than 0.05 cm·s−1 and a correlation coefficient of 0.6.

Recent observations of superimposed ice and snow ice on sea ice in the northwestern Weddell Sea

Abstract. Recent low summer sea ice extent in the Weddell Sea raises questions about the contributions of dynamic and thermodynamic atmospheric and oceanic energy fluxes. The roles of snow, superimposed ice, and snow ice are particularly intriguing, as they are sensitive indicators of changes in atmospheric forcing and as they could trigger snow–albedo feedbacks that could accelerate ice melt. Here we present snow depth data and ice core observations of superimposed ice and snow ice collected in the northwestern Weddell Sea in late austral summer 2019, supplemented by airborne ice thickness measurements. Texture, salinity, and oxygen isotope analyses showed mean thicknesses of superimposed and snow ice of 0.11±0.11 and 0.22±0.22 m, respectively, or 3 % to 54 % of total ice thickness. Mean snow depths ranged between 0.46±0.29 m in the south to 0.05±0.06 m in the north, with mean and modal total ice thicknesses of 4.12±1.87 to 1.62±1.05 m and 3.9 to 0.9 m, respectively. These snow and ice properties are similar to results from previous studies, suggesting that the ice's summer surface energy balance and related seasonal transition of snow properties have changed little in past decades. This is supported by our additional analyses of the summer energy balance using atmospheric reanalysis data and by melt onset observations from satellite scatterometry showing few recent changes.

Surface and Atmospheric Driven Variability of the Single‐Layer Urban Canopy Model Under Clear‐Sky Conditions Over London

AbstractUrban canopy models (UCMs) are parametrization schemes that are used to improve weather forecasts in urban areas. The performance of UCMs depends on understanding potential uncertainty sources that can generally originate from the (a) urban surface parameters, (b) atmospheric forcing, and (c) physical description. Here, we investigate the relative importance of surface and atmospheric driven model sensitivities of the single‐layer urban canopy model when fully interactive with a 1‐D configuration of the Weather Research and Forecasting model (WRF). The impact of different physical descriptions in UCMs and other key parameterization schemes of WRF is considered. As a case study, we use a 54‐hr period with clear‐sky conditions over London. Our analysis is focused on the surface radiation and energy flux partitioning and the intensity of turbulent mixing. The impact of changes in atmospheric forcing and surface parameter values on model performance appears to be comparable in magnitude. The advection of potential temperature, aerosol optical depth, exchange coefficient and roughness length for heat, surface albedo, and the anthropogenic heat flux are the most influential. Some atmospheric forcing variations have similar impact on the key physical processes as changes in surface parameters. Hence, error compensation may occur if one optimizes model performance using a single variable or combinations that have potential for carryover effects (e.g., temperature). Process diagrams help differences to be understood in the physical description of different UCMs, boundary layer, and radiation schemes and between the model and the observations.

Effect of Climate Change on Precipitation Patterns in an Arid Region Using GCM Models: Case Study of Isfahan-Borkhar Plain

AbstractClimate change has major implications for a wide range of natural processes and phenomena, with precipitation patterns particularly sensitive to changes in atmospheric forcing. The arid and...

Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges

AbstractThe scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water storage product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low‐flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM‐simulated groundwater correlates strongly with 12‐month precipitation anomalies in low‐latitude and midlatitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional‐scale drought indicators, with discrepancies mainly in their estimated drought severity.

Summer hydrographic changes in the Baltic Sea, Kattegat and Skagerrak projected in an ensemble of climate scenarios downscaled with a coupled regional ocean\u2013sea ice\u2013atmosphere model

This model study investigates summer hydrographic changes in response to climate projections following the CMIP5 RCP8.5 scenario. We use the high resolution regional coupled ocean–sea ice–atmosphere model RCA4–NEMO to downscale an ensemble of five global climate projections with a main focus on the Baltic Sea and neighboring shelf basins to the west. We find consistently across the ensemble a northward shift in the mean summer position of the westerlies at the end of the twenty-first century compared to the twentieth century. Associated with this is an anomalous precipitation pattern marked by increased rainfall over northern Europe and dryer conditions over the continental central part. In response to these large-scale atmospheric changes, a strong freshening mainly resulting from a higher net precipitation over the year combined with higher annual mean runoff is registered for the Baltic Sea and adjacent seas. The strongest freshening takes place in the southern Skagerrak region where stronger winds enhance the cyclonic circulation and by this, recirculation of fresher waters from the Baltic Sea strengthens. In the Baltic Sea freshening leads to a reduction in basin averaged salinities between 0.6 and 2.3 g kg−1 throughout the ensemble. Likewise, the sea surface temperature response in the Baltic Sea varies between + 2.5 and + 4.7 K depending on the applied global model scenario. The climate induced changes in atmospheric forcing have further consequences for the large-scale circulation in the Baltic Sea. All ensemble members indicate a strengthening of the zonal, wind driven near surface overturning circulation in the southwestern Baltic Sea towards the end of the twenty-first century whereas the more thermohaline driven overturning at depth is reduced by ~ 25%. In the Baltic Proper, the meridional overturning shows no clear climate change signal. However, three out of five ensemble members indicate at least a northward expansion of the main overturning cell. In the Bothnian Sea, all ensemble members show a significant weakening of the meridional overturning. The entire ensemble consistently indicates a basin-wide intensification of the pycnocline (9–35%) for the Baltic Sea and a shallowing of the pycnocline depth in most regions as well. In the Baltic Sea, which is dominated by mesohaline conditions under the historical period, the changes in salinity at the end of the twenty-first century have turned wide areas to be dominated by oligohaline conditions as a result of climate change. Potential consequences for biogeochemical conditions and implications for biodiversity are discussed.

Climate and surface mass balance of coastal West Antarctica resolved by regional climate modelling

ABSTRACTWest Antarctic climate and surface mass balance (SMB) records are sparse. To fill this gap, regional atmospheric climate modelling is useful, providing that such models are employed at sufficiently high horizontal resolution and coupled with a snow model. Here we present the results of a high-resolution (5.5 km) regional atmospheric climate model (RACMO2) simulation of coastal West Antarctica for the period 1979–2015. We evaluate the results with available in situ weather observations, remote-sensing estimates of surface melt, and SMB estimates derived from radar and firn cores. Moreover, results are compared with those from a lower-resolution version, to assess the added value of the resolution. The high-resolution model resolves small-scale climate variability invoked by topography, such as the relatively warm conditions over ice-shelf grounding zones, and local wind speed accelerations. Surface melt and SMB are well reproduced by RACMO2. This dataset will prove useful for picking ice core locations, converting elevation changes to mass changes, for driving ocean, ice-sheet and coupled models, and for attributing changes in the West Antarctic Ice Sheet and shelves to changes in atmospheric forcing.

Potential effects of climate changes on soil–atmosphere interaction and landslide hazard

In the recent years, the scientific community is involved in an intense debate around the effects of global warming. In fact, this could determine valuable changes in atmospheric forcing that govern the soil–atmosphere interaction and, in turn, water budget in the subsoil, with unpredictable consequences, inter alia, on geohydrological hazards. An early and proper assessment of the magnitude of such phenomena would be of great importance in establishing the priorities and timing in adaptation strategies. The paper reports some results obtained through a simulation chain which accounts for the potential climatic changes induced by two different socioeconomic concentration scenarios in atmospheric forcing and consequent changes in soil moisture and, then, slope response. The analyses concern a site located in Southern Italy, representative of Mediterranean area, deemed an “hot spot” for future climate changes. It is shown that, beyond the variations induced by climate changes, soil nature and land cover could play a major role.

Variability of sea surface temperature in the southwestern Gulf of Mexico

The seasonal and interannual variability of sea surface temperature (SST) in the southwestern Gulf of Mexico (SGM) is related to changes in atmospheric forcing, subsurface water inputs, advection and surface currents. However, little is known about temperature variability in the gulf on decadal and multidecadal timescales. Temperature time series (1900–2010) were analysed in 36 2°×2° geographic quadrants that covered the SGM. A cluster analysis was applied to the data for the seasonal cycle and for the annual anomalies in each quadrant to describe SST variability, with a special focus on low frequencies (i.e. >10 years). Temperature anomalies were correlated with the identified cyclic components of the Atlantic Multidecadal Oscillation (AMO), and temperature variability in coastal quadrants of the gulf was described using multivariate analysis and harmonic analysys. There is a latitudinal separation of quadrants regading the seasonal cycle and a longitudinal separation in the total variability that is related to the Loop Current. The highest SST correlations were those related to a ~60-year cycle of the AMO and were found on the Yucatan shelf. The ~60-year variability is present in the entire gulf, but signals with periods shorter than ten years are more evident in the northern part. Extrapolation of the dominant sea surface temperature cycles in coastal areas of the gulf, shows that there will be a cooling event in the next 20 years.

Behaviour influences larval dispersal in shelf sea gyres: Nephrops norvegicus in the Irish Sea

The western Irish Sea seasonal gyre is widely believed to play an important role in the local retention of resident larvae. This mechanism could be particularly crucial for the larvae of the heavily fished crustacean Nephrops norvegicus (L.), as their sediment requirements highly restrict where they are able to settle. As recent research suggests that the gyre may be becoming less retentive due to changes in atmospheric forcing, it is now crucial to understand how the gyre influences dispersal. This investigation addresses the hypothesis that shelf sea gyres reinforce larval retention using a biophysical model with vertical migration, habitat selection and temperature-dependent pelagic larval duration (PLD) configured to match the behaviour of N. norvegicus larvae. The results of this study suggest that the gyre does increase the likelihood that passive larvae remain within the western Irish Sea, on the condition that the larvae remain fixed at the depth of peak gyral flow. Retention rates are significantly lower when vertical migration is introduced, and there is no evidence that the gyre promotes larval retention amongst either vertically migrating larvae, or larvae that require muddy sediments for successful settlement. By contrast, vertical migration is shown to be favourable for retention in the eastern Irish Sea. PLD varies by a factor of two according to release date and location. The simulations suggest that whilst some highly limited and almost entirely unidirectional larval exchange may occur, the distinct sites largely rely upon local recruitment.

Physical controls of variability in North Atlantic phytoplankton communities

The structure of marine phytoplankton communities in the North Atlantic Ocean varies considerably on seasonal, interannual, and longer timescales in response to environmental change. However, the causes of ecological variability on interannual and longer timescales remain uncertain. Here, using a half-century of observations, we compare changes in atmospheric forcing (surface wind speed and heat fluxes) and ocean surface properties (sea surface temperature, mixed layer depth, thermal stratification, and turbulent kinetic energy) with variability in total phytoplankton biomass and the abundances of diatoms and dinoflagellates, as measured by the Continuous Plankton Recorder survey. On seasonal timescales, there is a clear connection between observed changes in the physical environment and the phytoplankton assemblages. Strong turbulence, deep mixed layers, and weak stratification decrease diatom abundance in the subpolar gyre, but increase diatoms in the subtropical gyre, a pattern broadly consistent with growth limitation of phytoplankton in high and low latitudes by light and nutrients, respectively. In contrast, dinoflagellates prosper in stratified, weakly turbulent conditions in sampled portions of the subpolar and subtropical gyres. On interannual to multidecadal timescales, however, the links between observed ecological and physical changes are much weaker. The physical mechanisms that differentiate the fates of diatoms and dinoflagellates on seasonal timescales do not appear to control their longer-term variability, perhaps because year-to-year variability in the phytoplankton assemblages is greater than in the physical drivers. This suggests that other biological (e.g., zooplankton grazing, chaos in the plankton) or physical mechanisms (e.g., changes in ocean circulation) may play important regulatory roles.

Fluctuations of a Greenlandic tidewater glacier driven by changes in atmospheric forcing: observations and modelling of Kangiata Nunaata Sermia, 1859–present

Abstract. Many tidewater glaciers in Greenland are known to have undergone significant retreat during the last century following their Little Ice Age maxima. Where it is possible to reconstruct glacier change over this period, they provide excellent records for comparison to climate records, as well as calibration/validation for numerical models. These glacier change records therefore allow for tests of numerical models that seek to simulate tidewater glacier behaviour over multi-decadal to centennial timescales. Here we present a detailed record of behaviour from Kangiata Nunaata Sermia (KNS), SW Greenland, between 1859 and 2012, and compare it against available oceanographic and atmospheric temperature data between 1871 and 2012. We also use these records to evaluate the ability of a well-established one-dimensional flow-band model to replicate behaviour for the observation period. The record of terminus change demonstrates that KNS has advanced/retreated in phase with atmosphere and ocean climate anomalies averaged over multi-annual to decadal timescales. Results from an ensemble of model runs demonstrate that observed dynamics can be replicated. Model runs that provide a reasonable match to observations always require a significant atmospheric forcing component, but do not necessarily require an oceanic forcing component. Although the importance of oceanic forcing cannot be discounted, these results demonstrate that changes in atmospheric forcing are likely to be a primary driver of the terminus fluctuations of KNS from 1859 to 2012. We propose that the detail and length of the record presented makes KNS an ideal site for model validation exercises investigating links between climate, calving rates, and tidewater glacier dynamics.

Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity.

Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.

Properties of adjoint sea ice sensitivities to atmospheric forcing and implications for the causes of the long term trend of Arctic sea ice

Based on adjoint sensitivities of the coupled Massachusetts Institute of Technology ocean–sea ice circulation model, the potential influence of thermodynamic atmospheric forcing on the interannual variability of the September sea ice area (AREA) and volume (VOLUME) in the Arctic is investigated for the three periods 1980–1989, 1990–1999 and 2000–2009. Sensitivities suggest that only large forcing anomalies prior to the spring melting onset in May can influence the September sea ice characteristics while even small changes in the atmospheric variables during subsequent months can significantly influence September sea ice state. Specifically, AREA close to the ice edge in the Arctic seas is highly sensitive to thermodynamic atmospheric forcing changes from June to July. In contrast, VOLUME is highly sensitive to atmospheric temperature changes occurring during the same period over the central parts of the Arctic Ocean. A comparison of the sea ice conditions and sensitivities during three different periods reveals that, due to the strong decline of sea ice concentration and sea ice thickness, sea ice area became substantially more sensitive to the same amplitude thermodynamic atmospheric forcing anomalies during 2000–2009 relative to the earlier periods. To obtain a quantitative estimate of changes that can be expected from existing atmospheric trends, adjoint sensitivities are multiplied by monthly temperature differences between 1980s and two following decades. Strongest contributions of surface atmospheric temperature differences to AREA and VOLUME changes are observed during May and September. The strongest contribution from the downward long-wave heat flux to AREA changes occurs in September and to VOLUME changes in July–August. About 62 % of the AREA decrease simulated by the model can be explained by summing all contributions to the thermodynamic atmospheric forcing. The changing sea ice state (sensitivity) is found to enhance the decline and accounts for about one third of the explained reduction. For the VOLUME decrease, the explained fraction of the decrease is only about 37 %.

Decadal variability in an OGCM Southern Ocean: Intrinsic modes, forced modes and metastable states

An ocean general circulation model (OGCM) is used to identify a Southern Ocean southeast Pacific intrinsic mode of low frequency variability. Using CORE data a comprehensive suite of experiments were carried out to elucidate excitation and amplification responses of this intrinsic mode to low frequency forcing (ENSO,SAM) and stochastic forcing due to high frequency winds. Subsurface anomalies were found to teleconnect the Pacific and Atlantic regions of the Antarctic Circumpolar Current (ACC) thermocline. The Pacific region of the ACC is characterised by intrinsic baroclinic disturbances that respond to both SAM and ENSO, while the Atlantic sector of the ACC is sensitive to higher frequency winds that act to amplify thermocline anomalies propagating downstream from the Pacific. Non-stationary cluster analysis was used to identify the system’s dynamical regimes and characterise meta-stability, persistence and transitions between the respective states. This analysis reveals significant trends, indicating fundamental changes to the meta-stability of the ocean dynamics in response to changes in atmospheric forcing. Intrinsic variability in sea-ice concentration was found to be coupled to thermocline processes. Sea-ice variability localised in the Atlantic was most closely associated with high frequency weather forcing. The SAM was associated with a circumpolar sea-ice response whereas ENSO was found to be a major driver of sea-ice variability only in the Pacific. This simulation study identifies plausible mechanisms that determine the predictability of the Southern Ocean climate on multi-decadal timescales.

Climate change impact on thermal and oxygen regime of shallow lakes

ABSTRACTAmong the numerous processes that govern the functioning of a lake ecosystem, the regime of dissolved oxygen (DO) is of primary importance. The DO content is strongly affected by the temperature regime, mixing conditions and by the duration of the ice-covered period. These are formed due to atmospheric forcing and are, therefore, subject to variations in regional climate. Despite the large amount of data revealing the physical effect on the biological and chemical regimes in lakes, there is still insufficient understanding, both qualitative and quantitative, of how a lake ecosystem would be affected by changes in the lake temperature and mixing conditions due to changes in the atmospheric forcing. Below, the study of shallow lakes’ response to climatic changes using the coupled FLake–FLakeEco modelling system is presented. The results obtained reveal the extreme vulnerability of the lakes’ ecosystems to changes in atmospheric forcing. In ‘future’ climate the permanent existence of potentially dangerous anaerobic zones in shallow lakes is expected. The projected decreased oxygen concentrations are caused by: (1) the reduced oxygen flux from the atmosphere to the lakes due to increased temperature; and (2) strengthened density stratification of the water columns which would prevent aeration of the near-bottom layers.