Effects of fluctuating daily surface fluxes on the time-mean oceanic circulation

The effect of fluctuating daily surface fluxes on the time-mean oceanic circulation is studied using an empirical flux model. The model produces fluctuating fluxes resulting from atmospheric variability and includes oceanic feedbacks on the fluxes. Numerical experiments were carried out by driving an ocean general circulation model with three different versions of the empirical model. It is found that fluctuating daily fluxes lead to an increase in the meridional overturning circulation (MOC) of the Atlantic of about 1 Sv and a decrease in the Antarctic circumpolar current (ACC) of about 32 Sv. The changes are approximately 7% of the MOC and 16% of the ACC obtained without fluctuating daily fluxes. The fluctuating fluxes change the intensity and the depth of vertical mixing. This, in turn, changes the density field and thus the circulation. Fluctuating buoyancy fluxes change the vertical mixing in a non-linear way: they tend to increase the convective mixing in mostly stable regions and to decrease the convective mixing in mostly unstable regions. The ACC changes are related to the enhanced mixing in the subtropical and the mid-latitude Southern Ocean and reduced mixing in the high-latitude Southern Ocean. The enhanced mixing is related to an increase in the frequency and the depth of convective events. As these events bring more dense water downward, the mixing changes lead to a reduction in meridional gradient of the depth-integrated density in the Southern Ocean and hence the strength of the ACC. The MOC changes are related to more subtle density changes. It is found that the vertical mixing in a latitudinal strip in the northern North Atlantic is more strongly enhanced due to fluctuating fluxes than the mixing in a latitudinal strip in the South Atlantic. This leads to an increase in the density difference between the two strips, which can be responsible for the increase in the Atlantic MOC

Fingerprints of changes in annual and seasonal precipitation from CMIP5 models over land and ocean

By comparing annual and seasonal changes in precipitation over land and ocean since 1950 simulated by the CMIP5 (Coupled Model Intercomparison Project, phase 5) climate models in which natural and anthropogenic forcings have been included, we find that clear global-scale and regional-scale changes due to human influence are expected to have occurred over both land and ocean. These include moistening over northern high latitude land and ocean throughout all seasons and over the northern subtropical oceans during boreal winter. However we show that this signal of human influence is less distinct when considered over the relatively small area of land for which there are adequate observations to make assessments of multi-decadal scale trends. These results imply that extensive and significant changes in precipitation over the land and ocean may have already happened, even though, inadequacies in observations in some parts of the world make it difficult to identify conclusively such a human fingerprint on the global water cycle. In some regions and seasons, due to aliasing of different kinds of variability as a result of sub sampling by the sparse and changing observational coverage, observed trends appear to have been increased, underscoring the difficulties of interpreting the apparent magnitude of observed changes in precipitation

Impact of ocean in-situ observations on ECMWF sub-seasonal forecasts

We assess for the first time the impact of in-situ ocean observations on European Centre for Medium-Range Weather Forecasts (ECMWF) sub-seasonal forecasts of both ocean and atmospheric conditions. A series of coupled reforecasts have been conducted for the period 1993-2015, in which different sets of ocean observations were withdrawn in the production of the ocean initial conditions. Removal of all ocean in-situ observations in the initial conditions leads to significant degradation in the forecasts of ocean surface and subsurface mean state at lead times from week 1 to week 4. The negative impact is predominantly caused by the removal of the Argo observing system in recent decades. Changes in the mean state of atmospheric variables are comparatively small but significant in the forecasts of lower and upper atmospheric circulation over large regions. Our results highlight the value of continuous, real-time in-situ observations of the surface and subsurface ocean for coupled forecasts in the sub-seasonal range

Have greenhouse gases intensified the contrast between wet and dry regions?

While changes in land precipitation during the last 50 years have been attributed in part to human influences, results vary by season, are affected by data uncertainty and do not account for changes over ocean. One of the more physically robust responses of the water cycle to warming is the expected amplification of existing patterns of precipitation minus evaporation. Here, precipitation changes in wet and dry regions are analyzed from satellite data for 1988–2010, covering land and ocean. We derive fingerprints for the expected change from climate model simulations that separately track changes in wet and dry regions. The simulations used are driven with anthropogenic and natural forcings combined, and greenhouse gas forcing or natural forcing only. Results of detection and attribution analysis show that the fingerprint of combined external forcing is detectable in observations and that this intensification of the water cycle is partly attributable to greenhouse gas forcing

Impact of the ocean in-situ observations on the ECMWF seasonal forecasting system

This study aims to evaluate the impact of the in-situ ocean observations on seasonal forecasts. A series of seasonal reforecasts have been conducted for the period 1993-2015, in which different sets of ocean observations were withdrawn in the production of the ocean initial conditions, while maintaining a strong constrain in sea surface temperature (SST). By comparing the different reforecast sets, it is possible to assess the impact on the forecast of ocean and atmospheric variables. Results show that the in-situ observations have profound and significant impacts on the mean state of forecast ocean and atmospheric variables, which can be classified into different categories: i) impact due to local air-sea interaction, as direct consequence of changes in the mixed layer in the ocean initial conditions, and visible in the early stages of the forecasts; ii) changes due to different ocean dynamical balances, most visible in the Equatorial Pacific in forecasts initialized in May, which amplify and evolve with forecast lead time; iii) changes to the atmospheric circulation resulting from changes in large scale SST gradients; these are non-local, mediated by the atmospheric bridge, and they are obvious from the visible impact of the removing in-situ observations on the Atlantic basin only in the global atmospheric circulation; iv) changes in the atmospheric tropical deep convection associated with the structure of the warm pools. The ocean observations have also a significant impact on the representation of the trends of the ocean initial conditions, which affect the trends in the seasonal forecasts of ocean and atmospheric variables. The impact of the ocean observing system in the Atlantic and extratropics appears dominated by Argo, but this is not the case in the Tropical Pacific, where the other ocean observing systems play a role in constraining the ocean state

A numerical model study of the effects of interannual timescale wave propagation on the predictability of the Atlantic meridional overturning circulation

We investigate processes leading to uncertainty in forecasts of the Atlantic meridional overturning circulation (AMOC). A climate model is used to supply initial conditions for ensemble simulations in which members initially have identical ocean states but perturbed atmosphere states. Baroclinic transports diverge on interannual timescales even though the ocean is not eddy-permitting. Interannual fluctuations of the model AMOC in the subtropical gyre are caused by westward propagating Rossby waves. Divergence of the predicted AMOC with time occurs because the waves develop different phases in different ensemble members predominantly due to differences in eastern boundary windstress curl. These windstress fluctuations communicate with interior ocean transports via modifications to the vertical velocity and the vortex stretching term dw/dz. Consequently, errors propagate westwards resulting in longer predictability times in the interior ocean compared with the eastern boundary. Another source of divergence is transport anomalies propagating along the Gulf Stream (and other boundary currents). The propagation mechanism seems to be predominantly advection by mean currents, and we show that the arrival of westward propagating waves can trigger development of these anomalies. The mean state of the AMOC has a small effect on interannual predictability in the subtropical gyre, most likely because eastern boundary windstress curl predictability is not strongly dependent on the state of the AMOC in the subtropics. Eastern boundary windstress curl was more predictable at 45{degree sign}N when the AMOC was in a strongly decreasing state, but, unlike at 30{degree sign}N, no mechanism was found linking windstress curl fluctuations with deep transports

Assessment of AtlantOS impact

Assessment of the impact of AtlantOS in situ observing system for Copernicus Marine Service and seasonal predictio

The impact of salinity perturbations on the future uptake of heat by the Atlantic Ocean

Anthropogenic ocean heat uptake is a key factor in determining climate change and sea-level rise. There is considerable uncertainty in projections of freshwater forcing of the ocean, with the potential to influence ocean heat uptake. We investigatethis by adding either -0.1 Sv or +0.1 Sv freshwater to the Atlantic in global climate model simulations, simultaneously imposing an atmospheric CO2 increase. The resulting changes in the Atlantic meridional overturning circulation are roughly equal and opposite (±2Sv). The impact of the perturbation on ocean heat content is more complex, although it is relatively small (~5%) compared to the total anthropogenic heat uptake. Several competing processes either accelerate or retard warming at different depths. Whilst positive freshwater perturbations cause an overall heating of the Atlantic, negative perturbations produce insignificant net changes in heat content. The processes active in our model appear robust, although their net result is likely model- and experiment-dependent

Capability of the variogram to quantify the spatial patterns of surface fluxes and soil moisture simulated by land surface models

Up to now, relatively little effort has been dedicated to the quantitative assessment of the differences in spatial patterns of model outputs. In this paper, we employed a variogram-based methodology to quantify the differences in the spatial patterns of root-zone soil moisture, net radiation, and latent and sensible heat fluxes simulated by three land surface models (SURFEX/ISBA, JULES and CHTESSEL) over three European geo- graphic domains – namely, UK, France and Spain. The model output spatial patterns were quantified through two metrics derived from the variogram: i) the variogram sill, which quantifies the degree of spatial variability of the data; and ii) the variogram integral range, which represents the spatial length scale of the data. The higher seasonal variation of the spatial variability of sensible and latent heat fluxes over France and Spain, compared to the UK, is related to a more frequent occurrence of a soil-moisture-limited evapotranspiration regime during summer dry spells in the south of France and Spain. The small differences in spatial variability of net radiation between models indicate that the spatial patterns of net radiation are mostly driven by the climate forcing data set. However, the models exhibit larger differences in latent and sensible heat flux spatial variabilities, which are related to their differences in i) soil and vegetation ancillary datasets and ii) physical process representation. The highest discrepancies in spatial patterns between models are observed for soil moisture, which is mainly related to the type of soil hydraulic function implemented in the models. This work demonstrates the capability of the variogram to enhance our understanding of the spatiotemporal structure of the uncertainties in land surface model outputs. Therefore, we strongly encourage the implementation of the variogram metrics in model intercomparison exercises

Seasonal Arctic sea ice forecasting with probabilistic deep learning.

Anthropogenic warming has led to an unprecedented year-round reduction in Arctic sea ice extent. This has far-reaching consequences for indigenous and local communities, polar ecosystems, and global climate, motivating the need for accurate seasonal sea ice forecasts. While physics-based dynamical models can successfully forecast sea ice concentration several weeks ahead, they struggle to outperform simple statistical benchmarks at longer lead times. We present a probabilistic, deep learning sea ice forecasting system, IceNet. The system has been trained on climate simulations and observational data to forecast the next 6 months of monthly-averaged sea ice concentration maps. We show that IceNet advances the range of accurate sea ice forecasts, outperforming a state-of-the-art dynamical model in seasonal forecasts of summer sea ice, particularly for extreme sea ice events. This step-change in sea ice forecasting ability brings us closer to conservation tools that mitigate risks associated with rapid sea ice loss