A novel framework to harmonise satellite data series for climate applications

Fundamental and thematic climate data records derived from satellite observations provide unique information for climate monitoring and research. Since any satellite operates over a limited period of time only, creating a climate data record requires the combination of space-borne measurements from a series of several (often similar) satellite sensors. A simple combination of calibrated measurements from several sensors, however, can produce an inconsistent climate data record. This is particularly true of older, historic sensors whose behavior in space was often different from their behavior during pre-launch calibration in the laboratory. More scientific value can be derived from considering the series of historical and present satellites as a whole. Here we consider harmonisation as a process that obtains new calibration coefficients for revised sensor calibration models by comparing calibrated measurements over appropriate satellite-to-satellite match-ups, such as simultaneous nadir overpasses. When we perform a comparison of two sensors, however, we must consider that those sensors are not observing exactly the same Earth radiance. This is in part due to differences in exact location and time tolerated by the match-up process itself, but also due to differences in the spectral response functions of the two instruments, even when nominally observing the same spectral band. To derive a harmonised data set we do not aim to correct for spectral response function differences, but to reconcile the calibration of different sensors given their estimated spectral response function differences. Here we present the concept of a framework that establishes calibration coefficients and their uncertainty and error covariance for an arbitrary number of sensors in a metrologically-rigorous manner. We describe harmonisation and its mathematical formulation as an inverse problem. Solving this problem is challenging when some hundreds of millions of match-ups are involved and the errors of fundamental sensor measurements are correlated. We solve the harmonisation problem as marginalised errors in variables regression. The algorithm involves computation of first and second order partial derivatives, for which the corresponding computer source code is generated by Automatic Differentiation. Finally we present re-calibrated AVHRR radiances from a series of 10 sensors. It is shown that the new time series have much less match-up differences while being consistent with uncertainty statistics

Depth-resolved particle associated microbial respiration in the northeast Atlantic

Atmospheric levels of carbon dioxide are tightly linked to the depth at which sinking particulate organic carbon (POC) is remineralised in the ocean. Rapid attenuation of downward POC flux typically occurs in the upper mesopelagic (top few hundred metres of the water column), with much slower loss rates deeper in the ocean. Currently, we lack understanding of the processes that drive POC attenuation, resulting in large uncertainties in the mesopelagic carbon budget. Attempts to balance the POC supply to the mesopelagic with respiration by zooplankton and microbes rarely succeed. Where a balance has been found, depth-resolved estimates reveal large compensating imbalances in the upper and lower mesopelagic. In particular, it has been suggested that respiration by free-living microbes and zooplankton in the upper mesopelagic are too low to explain the observed flux attenuation of POC within this layer. We test the hypothesis that particle-associated microbes contribute significantly to community respiration in the mesopelagic, measuring particle-associated microbial respiration of POC in the northeast Atlantic through shipboard measurements on individual marine snow aggregates collected at depth (36–500 m). We find very low rates of both absolute and carbon-specific particle-associated microbial respiration (< 3 % d−1), suggesting that this term cannot solve imbalances in the upper mesopelagic POC budget. The relative importance of particle-associated microbial respiration increases with depth, accounting for up to 33 % of POC loss in the mid-mesopelagic (128–500 m). We suggest that POC attenuation in the upper mesopelagic (36–128 m) is driven by the transformation of large, fast-sinking particles to smaller, slow-sinking and suspended particles via processes such as zooplankton fragmentation and solubilisation, and that this shift to non-sinking POC may help to explain imbalances in the mesopelagic carbon budget

Increasing of entanglement entropy from pure to random quantum critical chains

It is known that the entropy of a block of spins of size $L$ embedded in an infinite pure critical spin chain diverges as the logarithm of $L$ with a prefactor fixed by the central charge of the corresponding conformal field theory. For a class of strongly random spin chains, it has been shown that the correspondent block entropy still remains universal and diverges logarithmically with an "effective" central charge. By computing the entanglement entropy for a family of models which includes the $N$-states random Potts chain and the $Z_N$ clock model, we give some definitive answer to some recent conjectures about the behaviour of the effective central charge. In particular, we show that the ratio between the entanglement entropy in the pure and in the disordered system is model dependent and we provide a series of critical models where the entanglement entropy grows from the pure to the random case.Comment: 4 pages, 2 eps figures, added reference

High export via small particles before the onset of the North Atlantic spring bloom

Sinking organic matter in the North Atlantic Ocean transfers 1-3 Gt carbon year?1 from the surface ocean to the interior. The majority of this exported material is thought to be in form of large, rapidly sinking particles that aggregate during or after the spring phytoplankton bloom. However, recent work has suggested that intermittent water column stratification resulting in the termination of deep convection can isolate phytoplankton from the euphotic zone, leading to export of small particles. We present depth profiles of large (&gt;0.1mm equivalent spherical diameter, ESD) and small (&lt;0.1mm ESD) sinking particle concentrations and fluxes prior to the spring bloom at two contrasting sites in the North Atlantic (61°30N, 11°00W and 62°50N, 02°30W) derived from the Marine Snow Catcher and the Video Plankton Recorder. The downward flux of organic carbon via small particles ranged from 23-186 mg C m?2 d?1, often constituting the bulk of the total particulate organic carbon flux. We propose that these rates were driven by two different mechanisms: In the Norwegian Basin, small sinking particles likely reached the upper mesopelagic by disaggregation of larger, faster sinking particles. In the Iceland Basin, a storm deepened the mixed layer to &gt;300m depth, leading to deep mixing of particles as deep as 600m. Subsequent re-stratification could trap these particles at depth and lead to high particle fluxes at depth without the need for aggregation (‘mixed layer pump'). Overall we suggest that pre-bloom fluxes to the mesopelagic are significant, and the role of small sinking particles requires careful consideration. <br/

High export via small particles before the onset of the North Atlantic spring bloom

Sinking organic matter in the North Atlantic Ocean transfers 1-3 Gt carbon year?1 from the surface ocean to the interior. The majority of this exported material is thought to be in form of large, rapidly sinking particles that aggregate during or after the spring phytoplankton bloom. However, recent work has suggested that intermittent water column stratification resulting in the termination of deep convection can isolate phytoplankton from the euphotic zone, leading to export of small particles. We present depth profiles of large (>0.1mm equivalent spherical diameter, ESD) and small (300m depth, leading to deep mixing of particles as deep as 600m. Subsequent re-stratification could trap these particles at depth and lead to high particle fluxes at depth without the need for aggregation (‘mixed layer pump'). Overall we suggest that pre-bloom fluxes to the mesopelagic are significant, and the role of small sinking particles requires careful consideration

Testing variational estimation of process parameters and initial conditions of an earth system model

We present a variational assimilation system around a coarse resolution Earth System Model (ESM) and apply it for estimating initial conditions and parameters of the model. The system is based on derivative information that is efficiently provided by the ESM's adjoint, which has been generated through automatic differentiation of the model's source code. In our variational approach, the length of the feasible assimilation window is limited by the size of the domain in control space over which the approximation by the derivative is valid. This validity domain is reduced by non-smooth process representations. We show that in this respect the ocean component is less critical than the atmospheric component. We demonstrate how the feasible assimilation window can be extended to several weeks by modifying the implementation of specific process representations and by switching off processes such as precipitation