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The concentration of CO2 in the atmosphere is sensitive to changes in the depth at which sinking particulate organic matter is remineralized: often described as a change in the exponent “b” of the Martin curve. Sediment trap observations from deep and intermediate depths suggest there is a spatially heterogeneous pattern of b, particularly varying with latitude, but disagree over the exact spatial patterns. Here we use a biogeochemical model of the phosphorus cycle coupled with a steady-state representation of ocean circulation to explore the sensitivity of preformed phosphate and atmospheric CO2 to spatial variability in remineralization depths. A Latin hypercube sampling method is used to simultaneously vary the Martin curve independently within 15 different regions, as a basis for a regression-based analysis used to derive a quantitative measure of sensitivity. Approximately 30 % of the sensitivity of atmospheric CO2 to changes in remineralization depths is driven by changes in the subantarctic region (36 to 60∘ S) similar in magnitude to the Pacific basin despite the much smaller area and lower export production. Overall, the absolute magnitude of sensitivity is controlled by export production, but the relative spatial patterns in sensitivity are predominantly constrained by ocean circulation pathways. The high sensitivity in the subantarctic regions is driven by a combination of high export production and the high connectivity of these regions to regions important for the export of preformed nutrients such as the Southern Ocean and North Atlantic. Overall, regionally varying remineralization depths contribute to variability in CO2 of between around 5 and 15 ppm, relative to a global mean change in remineralization depth. Future changes in the environmental and ecological drivers of remineralization, such as temperature and ocean acidification, are expected to be most significant in the high latitudes where CO2 sensitivity to remineralization is also highest. The importance of ocean circulation pathways to the high sensitivity in subantarctic regions also has significance for past climates given the importance of circulation changes in the Southern Ocean.

We analyze the response of different ionospheric equivalent current modes to variations in the interplanetary magnetic field (IMF) components By and Bz. Each mode comprises a fixed spatial pattern whose amplitude varies in time, identified by a month‐by‐month empirical orthogonal function separation of surface measured magnetic field variance. Here we focus on four sets of modes that have been previously identified as DPY, DP2, NBZ, and DP1. We derive the cross‐correlation function of each mode set with either IMF By or Bz for lags ranging from −10 to +600 mins with respect to the IMF state at the bow shock nose. For all four sets of modes, the average correlation can be reproduced by a sum of up to three linear responses to the IMF component, each centered on a different lag. These are interpreted as the statistical ionospheric responses to magnetopause merging (15‐ to 20‐min lag) and magnetotail reconnection (60‐min lag) and to IMF persistence. Of the mode sets, NBZ and DPY are the most predictable from a given IMF component, with DP1 (the substorm component) the least predictable. The proportion of mode variability explained by the IMF increases for the longer lags, thought to indicate conductivity feedbacks from substorms. In summary, we confirm the postulated physical basis of these modes and quantify their multiple reconfiguration timescales.

We present 17 velocity records derived from in situ stand-alone single-frequency Global Positioning System (GPS) receivers placed on eight marine-terminating ice sheet outlet glaciers in South, West and North Greenland, covering varying parts of the period summer 2009 to summer 2012. Common to all the observed glacier velocity records is a pronounced seasonal variation, with an early melt season maximum generally followed by a rapid mid-melt season deceleration. The GPS-derived velocities are compared to velocities derived from radar satellite imagery over six of the glaciers to illustrate the potential of the GPS data for validation purposes. Three different velocity map products are evaluated, based on ALOS/PALSAR data, TerraSAR-X/Tandem-X data and an aggregate winter TerraSAR-X data set. The velocity maps derived from TerraSAR-X/Tandem-X data have a mean difference of 1.5% compared to the mean GPS velocity over the corresponding period, while velocity maps derived from ALOS/PALSAR data have a mean difference of 9.7%. The velocity maps derived from the aggregate winter TerraSAR-X data set have a mean difference of 9.5% to the corresponding GPS velocities. The data are available from the GEUS repository at doi:10.5280/GEUS000001.