ALBERT

Description: The Standardized Precipitation Index (SPI) is a widely accepted drought index. Its calculation algorithm normalizes the index via a distribution function. Which distribution function to use is still disputed within the literature. This study illuminates that long-standing dispute and proposes a solution that ensures the normality of the index for all common accumulation periods in observations and simulations. We compare the normality of SPI time series derived with the gamma, Weibull, generalized gamma, and the exponentiated Weibull distribution. Our normality comparison is based on a complementary evaluation. Actual compared to theoretical occurrence probabilities of SPI categories evaluate the absolute performance of candidate distribution functions. Complementary, the Akaike information criterion evaluates candidate distribution functions relative to each other while analytically punishing complexity. SPI time series, spanning 1983–2013, are calculated from the Global Precipitation Climatology Project's monthly precipitation dataset, and seasonal precipitation hindcasts are from the Max Planck Institute Earth System Model. We evaluate these SPI time series over the global land area and for each continent individually during winter and summer. While focusing on regional performance disparities between observations and simulations that manifest in an accumulation period of 3 months, we additionally test the drawn conclusions for other common accumulation periods (1, 6, 9, and 12 months). Our results suggest that calculating SPI with the commonly used gamma distribution leads to deficiencies in the evaluation of ensemble simulations. Replacing it with the exponentiated Weibull distribution reduces the area of those regions where the index does not have any skill for precipitation obtained from ensemble simulations by more than one magnitude. The exponentiated Weibull distribution maximizes also the normality of SPI obtained from observational data and a single ensemble simulation. We demonstrate that calculating SPI with the exponentiated Weibull distribution delivers better results for each continent and every investigated accumulation period, irrespective of the heritage of the precipitation data. Therefore, we advocate the employment of the exponentiated Weibull distribution as the basis for SPI.

Description: We investigate changes in the seasonal cycle of the Atlantic Ocean meridional heat transport (OHT) in a climate projection experiment with the Max Planck Institute Earth System Model (MPI-ESM) performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). Specifically, we compare a Representative Concentration Pathway (RCP) RCP 8.5 climate change scenario, covering the simulation period from 2005 to 2300, to a historical simulation, covering the simulation period from 1850 to 2005. In RCP 8.5, the OHT declines by 30–50 % in comparison to the historical simulation in the North Atlantic by the end of the 23rd century. The decline in the OHT is accompanied by a change in the seasonal cycle of the total OHT and its components. We decompose the OHT into overturning and gyre component. For the OHT seasonal cycle, we find a northward shift of 5° and latitude-dependent shifts between 1 and 6 months that are mainly associated with changes in the meridional velocity field. We find that the changes in the OHT seasonal cycle predominantly result from changes in the wind-driven surface circulation, which projects onto the overturning component of the OHT in the tropical and subtropical North Atlantic. This leads in turn to latitude-dependent shifts between 1 and 6 months in the overturning component. In comparison to the historical simulation, in the subpolar North Atlantic, in RCP 8.5 we find a reduction of the North Atlantic Deep Water formation and changes in the gyre heat transport result in a strongly weakened seasonal cycle with a weakened amplitude by the end of the 23rd century.

Description: The multiple correlation and/or regression information that two competing forecast systems have on the same observations is decomposed into four components, adapting the method of multivariate information decomposition of Williams and Beer (2010), Wibral et al. (2015), and Lizier et al. (2018). Their concept is to divide source information about a target into total, (target) redundant or shared, and unique information from each source. It is applied here to the comparison of forecast systems using classic regression. Additionally, non-target redundant or shared information is newly defined that resumes the redundant information of the forecasts which is not observed. This provides views that go beyond classic correlation differences. These five terms share the same units and can be directly compared to put prediction results into perspective. The redundance terms in particular provide a new view. All components are given as maps of explained variance on the observations and for the non-target redundance on the models, respectively. Exerting this concept to lagged damped persistence is shown to be related to directed information entropy. To emphasize the benefit of the toolkit on all timescales, two analysis examples are provided. Firstly, two forecast systems of the German decadal prediction system of “Mittelfristige Klimaprognose”, namely the pre-operational version and a special version using ensemble Kalman filter for the ocean initialization, are compared. The analyses reveal the clear added value of the latter and provide an as yet unseen map of their non-target redundance. Secondly, 4 d lead forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) are compared to a simple autoregressive and/or damped persistence model. The analysis of the information partition on this timescale shows that interannual changes in damped persistence, seen as target redundance changes between forecasts and damped persistence models, are balanced by associated changes in the added value of the dynamic forecasts in the extratropics but not in the tropics.

Description: We investigate the effect of a projected reduction in the Atlantic Ocean meridional heat transport (OHT) on changes in its seasonal cycle. We analyze a climate projection experiment with the Max-Planck Institute Earth System Model (MPI-ESM) performed for the Coupled Model Intercomparison Project phase 5 (CMIP5). In the RCP8.5 climate change scenario, the OHT declines in MPI-ESM in the North Atlantic by 30–50 % by the end of the 23rd century. The decline in the OHT is accompanied by a change in the seasonal cycle of the total OHT and its components. We decompose the OHT into overturning and gyre component. For the total OHT seasonal cycle, we find a northward shift of 5 degrees and latitude dependent temporal shifts of 1 to 6 months that are mainly associated with changes in the meridional velocity field. We find that the shift in the OHT seasonal cycle predominantly results from changes in the wind-driven surface circulation which projects onto the overturning component of the OHT in the tropical and subtropical North Atlantic. This leads to latitude dependent shifts of 1 to 6 months in the overturning component. In the subpolar North Atlantic, we find that the reduction of the North Atlantic Deep Water formation in RCP8.5 and changes in the gyre heat transport result in a strongly weakened seasonal cycle with a weakened seasonal amplitude by the end of the 23rd century and thus changes the OHT seasonal cycle in the SPG.

Description: Predicting the ambient environmental conditions in the coming several years to one decade is of key relevance for elucidating how deep-sea habitats, like for example sponge habitats, in the North Atlantic will evolve under near-future climate change. However, it is still not well known to what extent the deep-sea environmental properties can be predicted in advance. A regional downscaling prediction system is developed to assess the potential predictability of the North Atlantic deep-sea environmental factors. The large-scale climate variability predicted with the coupled Max Planck Institute Earth System Model with low-resolution configuration (MPI-ESM-LR) is dynamically downscaled to the North Atlantic by providing surface and lateral boundary conditions to the regional coupled physical-ecosystem model HYCOM-ECOSMO. Model results of two physical fields (temperature and salinity) and two biogeochemical fields (concentrations of silicate and oxygen) over 21 sponge habitats are taken as an example to assess the ability of the downscaling system to predict the interannual to decadal variations of the environmental properties based on ensembles of retrospective predictions over the period from 1985 to 2014. The ensemble simulations reveal skillful predictions of the environmental conditions several years in advance with distinct regional differences. In areas closely tied to large-scale climate variability and ice dynamics, both the physical and biogeochemical fields can be skillfully predicted more than 4 years ahead, while in areas under strong influence of upper oceans or open boundaries, the predictive skill for both fields is limited to a maximum of 2 years. The simulations suggest higher predictability for the biogeochemical fields than for the physical fields, which can be partly attributed to the longer persistence of the former fields. Predictability is improved by initialization in areas away from the influence of Mediterranean outflow and areas with weak coupling between the upper and deep oceans. Our study highlights the ability of the downscaling regional system to predict the environmental variations at deep-sea benthic habitats on time scales of management relevance. The downscaling system therefore will be an important part of an integrated approach towards the preservation and sustainable exploitation of the North Atlantic benthic habitats.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in [citation], doi:[doi]. Frajka-Williams, E., Ansorge, I. J., Baehr, J., Bryden, H. L., Chidichimo, M. P., Cunningham, S. A., Danabasoglu, G., Dong, S., Donohue, K. A., Elipot, S., Heimbach, P., Holliday, N. P., Hummels, R., Jackson, L. C., Karstensen, J., Lankhorst, M., Le Bras, I. A., Lozier, M. S., McDonagh, E. L., Meinen, C. S., Mercier, H., Moat, B., I., Perez, R. C., Piecuch, C. G., Rhein, M., Srokosz, M. A., Trenberth, K. E., Bacon, S., Forget, G., Goni, G., Kieke, D., Koelling, J., Lamont, T., McCarthy, G. D., Mertens, C., Send, U., Smeed, D. A., Speich, S., van den Berg, M., Volkov, D., & Wilson, C. Atlantic meridional overturning circulation: Observed transport and variability. Frontiers in Marine Science, 6, (2019): 260, doi:10.3389/fmars.2019.00260.

Description: The Atlantic Meridional Overturning Circulation (AMOC) extends from the Southern Ocean to the northern North Atlantic, transporting heat northwards throughout the South and North Atlantic, and sinking carbon and nutrients into the deep ocean. Climate models indicate that changes to the AMOC both herald and drive climate shifts. Intensive trans-basin AMOC observational systems have been put in place to continuously monitor meridional volume transport variability, and in some cases, heat, freshwater and carbon transport. These observational programs have been used to diagnose the magnitude and origins of transport variability, and to investigate impacts of variability on essential climate variables such as sea surface temperature, ocean heat content and coastal sea level. AMOC observing approaches vary between the different systems, ranging from trans-basin arrays (OSNAP, RAPID 26°N, 11°S, SAMBA 34.5°S) to arrays concentrating on western boundaries (e.g., RAPID WAVE, MOVE 16°N). In this paper, we outline the different approaches (aims, strengths and limitations) and summarize the key results to date. We also discuss alternate approaches for capturing AMOC variability including direct estimates (e.g., using sea level, bottom pressure, and hydrography from autonomous profiling floats), indirect estimates applying budgetary approaches, state estimates or ocean reanalyses, and proxies. Based on the existing observations and their results, and the potential of new observational and formal synthesis approaches, we make suggestions as to how to evaluate a comprehensive, future-proof observational network of the AMOC to deepen our understanding of the AMOC and its role in global climate.

Description: OSNAP is funded by the US National Science Foundation (NSF, OCE-1259013), UK Natural Environment Research Council (NERC, projects: OSNAP NE/K010875/1, Extended Ellett Line and ACSIS); China's national key research and development projects (2016YFA0601803), the National Natural Science Foundation of China (41521091 and U1606402) and the Fundamental Research Funds for the Central Universities (201424001); the German Ministry BMBF (RACE program); Fisheries and Oceans Canada (DFO: AZOMP). Additional support was received from the European Union 7th Framework Programme (FP7 2007–2013: NACLIM 308299) and the Horizon 2020 program (Blue-Action 727852, ATLAS 678760, AtlantOS 633211), and the French Centre National de la Recherche Scientifique (CNRS). RAPID and MOCHA moorings at 26°N are funded by NERC and NSF (OCE1332978). ABC fluxes is funded by the NERC RAPID-AMOC program (grant number: NE/M005046/1). Florida Current cable array is funded by the US National Oceanic and Atmospheric Administration (NOAA). The Meridional Overturning Variability Experiment (MOVE) was funded by the NOAA Climate Program Office-Ocean Observing and Monitoring Division, and initially by the German Federal Ministry of Education and Research (BMBF). SAMBA 34.5°S is funded by the NOAA Climate Program Office-Ocean Observing and Monitoring Division (100007298), the French SAMOC project (11–ANR-56-004), from Brazilian National Council for Scientific and Technological development (CNPq: 302018/2014-0) and Sao Paulo Research Foundation (FAESP: SAMOC-Br grants 2011/50552-4 and 2017/09659-6), the South African DST-NRF-SANAP program and South African Department of Environmental Affairs. The Line W project was funded by NSF (grant numbers: OCE-0726720, 1332667, and 1332834), with supplemental contributions from Woods Hole Oceanographic Institution (WHOI)'s Ocean and Climate Change Institute. The Oleander Program is funded by NOAA and NSF (grant numbers: OCE1536517, OCE1536586, OCE1536851). The 47°N array NOAC is funded by the BMBF (grant numbers: 03F0443C, 03F0605C, 03F0561C, 03F0792A). The Senate Commission of Oceanography from the DFG granted shiptime and costs for travel, transports and consumables. JB's work is funded by DFG under Germany's Excellence Strategy (EXC 2037 Climate, Climatic Change, and Society, Project Number: 390683824), contribution to the Center for Earth System Research and Sustainability (CEN) of Universitat Hamburg. LCJ was funded by the Copernicus Marine Environment Monitoring Service (CMEMS: 23-GLO-RAN LOT 3). MSL was supported by the Overturning in the Subpolar North Atlantic Program (NSF grant: OCE-1259013). GDM was supported by the Blue-Action project (European Union's Horizon 2020 research and innovation programme, grant number: 727852). HM was supported by CNRS. RH acknowledges financial support by the BMBF as part of the cooperative projects RACE (03F0605B, 03F0824C). The National Centre for Atmospheric Research (NCAR) is sponsored by NSF under Cooperative Agreement No. 1852977. JKO was supported by NASA Headquarters under the NASA Earth and Space Science Fellowship Program (Grant NNX16AO39H).