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  • 1
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    GEOMAR
    In:  [Software]
    Publication Date: 2021-11-09
    Description: With this script, the Meridional Overturning Circulation (MOC) can be computed from NEMO ocean-model output for the whole globe or the Atlantic (AMOC), Indic (IMOC) and Pacific (PMOC) subbasins. The MOC is computable in z- and sigma coordinates. Moreover, for nested configurations, it is possible to combine data from both host and nest grids. Finally, it is possible to take into account of that the ORCA model grid is curvilinear north of 20°N: it is possible to compute the northward velocity component from the velocity field in x- and y- directions and to sum up the meridional flux over latitudional bands instead of in x-direction. When both steps are applied, the resulting MOC shows however strong variability in meridional direction. It needs to be clarified, whether this is realistic or not. The software is provided in the form of the jupyter notebook "MOC.ipynb" which includes more informations on the possibilites of the computations and an extensive appendix section with comparisons to computations with cdftools, as well as with details on the computation of the MOC including nest data and taking the curvilinearity of the grid into account. Necessary python modules are listed at the beginning of the document.
    Type: Software , NonPeerReviewed
    Format: archive
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  • 2
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    GEOMAR
    In:  GEOMAR, Kiel, Germany, 17 pp.
    Publication Date: 2021-11-04
    Description: CMSY++ is an advanced state-space Bayesian method for stock assessment that estimates fisheries reference points (MSY, Fmsy, Bmsy) as well as status or relative stock size (B/Bmsy) and fishing pressure or exploitation (F/Fmsy) from catch and (optionally) abundance data, a prior for resilience or productivity (r), and broad priors for the ratio of biomass to unfished biomass (B/k) at the beginning, an intermediate year, and the end of the time series. For the purpose of this User Guide, the whole package is referred to as CMSY++ whereas the part of the method that deals with catch-only data is referred to as CMSY (catch MSY), and the part of the method that requires additional abundance data is referred to as BSM (Bayesian Schaefer Model). Both methods are based on a modified Schaefer surplus production model (see paper cited above for more details). The main advantage of BSM, compared to other implementations of surplus production models, is the focus on informative priors and the acceptance of short and incomplete (i.e., fragmented, with missing years) abundance data. This document provides a simple step-by-step guide for researchers who want to apply CMSY++ to their own data.
    Type: Report , NonPeerReviewed
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  • 3
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    GEOMAR
    In:  GEOMAR, Kiel, Germany, 2 pp.
    Publication Date: 2021-10-29
    Description: MSM89 – Bridgetown/Barbados – Bridgetown/Barbados 2. Wochenbericht – MARIA S. MERIAN - MSM89 20.-26.01.2020
    Type: Report , NonPeerReviewed
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  • 4
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    GEOMAR
    In:  GEOMAR, Kiel, Germany, 2 pp.
    Publication Date: 2021-10-29
    Description: MSM89 – Bridgetown/Barbados – Bridgetown/Barbados 1. Wochenbericht – MARIA S. MERIAN - MSM89 14.-19.01.2020
    Type: Report , NonPeerReviewed
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  • 5
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    GEOMAR
    In:  GEOMAR, Kiel, Germany, 2 pp.
    Publication Date: 2021-10-29
    Description: MSM89 – Bridgetown/Barbados – Bridgetown/Barbados 3. Wochenbericht – MARIA S. MERIAN - MSM89 27.01.-02.02.2020
    Type: Report , NonPeerReviewed
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  • 6
    Publication Date: 2021-10-06
    Description: Tillage erosion causes substantial soil redistribution that can exceed water erosion especially in hummocky landscapes under highly mechanized large field agriculture. Consequently, truncated soil profiles can be found on hill shoulders and top slopes, whereas colluvial material is accumulated at footslopes, in depressions, and along downslope field borders. We tested the hypothesis that soil erosion substantially affects in‐field patterns of the enhanced vegetation index (EVI) of different crop types on landscape scale. The interrelation between the EVI (RAPIDEYE satellite data; 5 m spatial resolution) as a proxy for crop biomass and modeled total soil erosion (tillage and water erosion modeled using SPEROS‐C) was analyzed for the Quillow catchment (size: 196 km2) in Northeast Germany in a wet versus normal year for four crop types (winter wheat, maize, winter rapeseed, winter barley). Our findings clearly indicate that eroded areas had the lowest EVI values, while the highest EVI values were found in depositional areas. The differences in the EVI between erosional and depositional sites are more pronounced in the analyzed normal year. The net effect of total erosion on the EVI compared to areas without pronounced erosion or deposition ranged from −10.2% for maize in the normal year to +3.7% for winter barley in the wet year. Tillage erosion has been identified as an important driver of soil degradation affecting in‐field crop biomass patterns in a hummocky ground moraine landscape. While soil erosion estimates are to be made, more attention should be given toward tillage erosion.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: 631.4 ; agroscapelab Quillow ; crop biomass patterns ; EVI ; remote sensing ; tillage erosion
    Type: map
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  • 7
    Publication Date: 2021-07-20
    Description: The connection between weather extremes and Rossby wave packets (RWP) has been increasingly documented in recent years. RWP propagation and characteristics can modulate the midlatitude weather, setting the scene for temperature and precipitation extremes and controlling the geographical area affected. Several studies on extreme precipitation events (EPEs) in the Alpine area reported, as the main triggering factor, a meridionally elongated upper‐level trough as part of an incoming Rossby wave packet. In this work, we investigate a wide number of EPEs occurring between 1979 and 2015 in northern‐central Italy. The EPEs are subdivided into three categories (Cat1, Cat2, Cat3) according to thermodynamic conditions over the affected region. It is found that the three categories differ not only in terms of the local meteorological conditions, but also in terms of the evolution and properties of precursor RWPs. These differences cannot be solely explained by the apparent seasonality of the flow; therefore, the relevant physical processes in the RWP propagation of each case are further investigated. In particular, we show that RWPs associated with the strongest EPEs, namely the ones falling in Cat2, undergo a substantial amplification over the western North Atlantic due to anomalous ridge‐building 2 days before the event; arguably due to diabatic heating sources. This type of development induces a downstream trough which is highly effective in focusing water vapour transport toward the main orographic barriers of northern‐central Italy and favouring the occurrence of EPEs.
    Description: The EPEs are subdivided into three categories (Cat1, Cat2, Cat3) according to thermodynamic conditions over the affected region. The three categories not only differ locally but also in the evolution of precursor RWPs as visible in the composite Hovmöller plots. RWPs associated with the strongest EPEs, the ones falling in Cat2, undergo a substantial amplification over the west North Atlantic due to anomalous ridge‐building 2 days before the event. This type of development induces a downstream trough which is highly effective in focusing water vapour transport toward the Apennines and the Alps.
    Description: Ludwig‐Maximilians‐Universität München http://dx.doi.org/10.13039/501100005722
    Description: German Research Foundation (DFG)
    Description: Transregional Collaborative Research Centre
    Keywords: 551.6 ; atmospheric rivers ; extreme precipitation ; integrated water vapour transport ; large‐scale forcing ; potential vorticity ; Rossby wave packets
    Type: article
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  • 8
    Publication Date: 2021-07-16
    Description: Rural communities in the drylands of sub‐Saharan Africa (SSA) derive their livelihoods primarily from their natural resource base. Unprecedented changes in these environments over the past few decades are likely to intensify in the future and land users need to develop sustainable adaptation strategies. This study aims to identify land‐use and land‐cover (LULC) changes and their drivers in a sub‐Saharan dryland, between 1986 and 2017, by integrating local knowledge and remote sensing. Local knowledge and environmental perception are used as the basis for defining LULC classes and for training and validation of change detection. This study detects significant LULC changes in 41% of the investigated area, and identifies bush encroachment into former pastures as the dominant LULC change with an increase of woodland by 39% and a decrease of grassland by 74%. This process is perceived as severe degradation by local respondents and is linked to changing management regimes and unreliable rainfall patterns. Deforestation and woodland thinning account for 44% of the detected changes, and can be traced back to increased habitation and farming, although the local community also identifies charcoal production as a driving factor. The integration of remote sensing and local knowledge provides a holistic view on LULC change in Pokot Central, Kenya and offers a solid base for site‐specific and actor‐centred management approaches necessary for sustainable pathways of drylands. Our results emphasize the need to include local actors in the development of adaptation strategies and management guidelines for drylands.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: Heidelberg University, Graduiertenförderung
    Keywords: 631.37 ; Kenya ; LANDSAT ; land‐use and land‐cover change ; local knowledge ; Pokot Central ; remote sensing
    Type: article
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  • 9
    Publication Date: 2021-07-04
    Description: In this paper, we present a characterization of Antarctic sea ice based on the classification of annual sea ice concentration (SIC) data from 1979 to 2018. A clustering algorithm was applied to provide a climatological description of significant annual cycles of SIC and their spatial distribution around the Southern Ocean. Based on these classification results, we investigate the variability of SIC cycles on decadal and inter‐annual time scales. First, we discuss significant spatial shifts of SIC cycles during 1979–1998 and 1999–2018. In the Weddell Sea and in large parts of the Ross Sea, we observed higher SIC during the summer season, and an extension of sea ice cover in winter compared to the long‐term average. Second, we introduce the Climatological Sea Ice Anomaly Index (CSIAI), which is an annual measure for year‐round sea ice anomalies of the Southern Ocean and its regional sub‐sectors. By relating selected years of significant sea ice conditions (1981, 2007 and 2014) with atmospheric influences, we demonstrate that the CSIAI is very useful for assessing inter‐annular Antarctic SIC variability. Positive and negative sea ice anomalies can be qualitatively explained by atmospheric circulation anomalies in the years 1981 and 2007. However, in 2014, the year with the largest observed sea ice extent in our time series, we found that this positive sea ice anomaly was surprisingly not associated with a stationary and inter‐seasonally persistent pattern of circulation anomaly. This suggests that sub‐seasonal to seasonal circulation anomalies and ocean‐related processes favoured the formation of the sea ice maximum in 2014. With this study we provide additional information on the long‐term annual SIC variability around Antarctica. Furthermore, our classification approach and its results have potential for application in the evaluation of sea ice model results.
    Description: In this paper, we present a characterization of Antarctic sea ice based on the classification of annual sea ice concentration cycles in the period 1979 to 2018. Furthermore, we discuss spatial shifts between 1979–1998 and 1999–2018 and are able to explain significant annual sea ice anomalies by atmospheric circulation anomalies.
    Description: DLR Management Board: Young Investigator Group Leader Program. F.R. was funded by the Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: 551.31 ; passive microwave data ; sea ice climatology ; sea ice trends ; sea ice variability
    Type: article
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  • 10
    Publication Date: 2021-07-04
    Description: The spatiotemporal variability of precipitation is of vital importance to Mediterranean ecology and economy, but pre‐instrumental changes are not well understood. Here, we present a millennial‐length June–July precipitation reconstruction derived from a network of 22 Pinus heldreichii high‐elevation sites in the Pindus Mountains of northwestern Greece. Tree‐ring width chronologies from these sites cohere exceptionally well over the past several hundred years (r1467–2015 = 0.64) revealing coherence at inter‐annual to centennial timescales across the network. The network mean calibrates significantly against instrumental June–July precipitation over the past 40 years (r1976–2015 = 0.71), even though no high‐elevation observational record is available representing the moist conditions at the treeline above 1,900 m a.s.l. For the final reconstruction, the instrumental target data are adjusted to provide realistic estimates of high‐elevation summer rainfall back to 729 CE. The reconstruction contains substantially more low‐frequency variability than other high‐resolution hydroclimate records from the eastern Mediterranean including extended dry periods from 1,350 to 1,379 CE (39 ± 4.5 mm) and 913 to 942 (40 ± 8.4 mm), and moist periods from 862 to 891 (86 ± 11 mm) and 1,522 to 1,551 (80 ± 3.5 mm), relative to the long‐term mean of 61 mm. The most recent 30‐year period from 1986 to 2015 is characterized by above average June–July precipitation (73 ± 2 mm). Low‐frequency changes in summer precipitation are likely related to variations in the position and persistence of storm tracks steering local depressions and causing extensive rainfall (or lack thereof) in high‐elevation environments of the Pindus Mountains.
    Description: Associated with a strengthening of circum‐global sub‐tropical high‐pressure belts, climate models unequivocally predict a decrease of Mediterranean precipitation, accompanied by an increase of extreme events in the upcoming decades. Long‐term desiccation will amplify evaporative demand challenging plant metabolism and foster an even greater need to irrigate Mediterranean crops. We place these recent hydroclimate dynamics into a long‐term context and explore the feasibility of reconstructing low‐frequency precipitation variability by employing a large network of high‐elevation Pinus heldreichii sites from northwestern Greece.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Keywords: 551.6 ; climate reconstruction ; Mediterranean ; Pindus Mountains ; pine ; tree‐rings ; Valia Calda
    Type: article
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