Ohc hfds rndt nh sh sum boxplot yr ensemble historicalghgaa r1i1p1 all text
ABSTRACT The largest contributor to the planetary energy imbalance is well-mixed greenhouse gases (GHGs), which are partially offset by poorly-mixed (and thus northern mid-latitude dominated) anthropogenic aerosols (AAs). To isolate the effects of GHGs and AAs, we analyze data from the CMIP5 historical (i.e. all natural and anthropogenic forcing) and single forcing (GHG-only and AA-only) experiments. Over the duration of the historical experiment (1861-2005) excess heat uptake at the top of the atmosphere and ocean surface occurs almost exclusively in the Southern Hemisphere, with AAs canceling the influence of GHGs in the Northern Hemisphere. This interhemispheric asymmetry in surface heat uptake is eliminated by a northward oceanic transport of excess heat, as there is little hemispheric difference in historical ocean heat storage after accounting for ocean volume. Data from the 1pctCO2 and RCP 8.5 experiments suggests that the future storage of excess heat will be skewed towards the Northern Hemisphere oceans. PLAIN LANGUAGE SUMMARY Climate change is fundamentally an energy balance problem. Due to the influence of greenhouse gas (GHG) emissions, the amount of solar energy absorbed by Earth is currently greater than the amount of energy radiated to space. This energy imbalance is partially offset by particulate matter released into the atmosphere from burning fossil fuels (anthropogenic aerosols; AAs), which is most concentrated in the northern mid-latitudes. In this study, model simulations of the historical and future climate are compared to single forcing simulations that apply only GHG or AA emissions. We find that the historical uptake of excess heat is strongly skewed towards the Southern Hemisphere because AAs cancel the influence of GHGs in the Northern Hemisphere. The oceanic storage of that heat shows little difference between the hemispheres due to a strong northward transport of excess heat. In future, the models suggest excess heat storage will skew towards the Northern Hemisphere. KEY POINTS - Single forcing simulations of the historical (1861-2005) climate suggest anthropogenic aerosols cause most excess heat uptake to occur in the Southern Hemisphere - This interhemispheric asymmetry in heat uptake is eliminated (after accounting for ocean volume) by a northward oceanic transport of excess heat - In future, the storage of excess heat will be skewed towards the Northern Hemisphere
Eof sf erainterim 500hpa monthly native sh zonal anom

Damien Irving

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The Pacific-South American (PSA) pattern is an important mode of climate variability in the mid-to-high southern latitudes. It is widely recognized as the primary mechanism by which the El Niño-Southern Oscillation (ENSO) influences the south-east Pacific and south-west Atlantic, and in recent years has also been suggested as a mechanism by which longer-term tropical sea surface temperature trends can influence the Antarctic climate. This study presents a novel methodology for objectively identifying the PSA pattern. By rotating the global coordinate system such that the equator (a great circle) traces the approximate path of the pattern, the identification algorithm utilizes Fourier analysis as opposed to a traditional Empirical Orthogonal Function approach. The climatology arising from the application of this method to ERA-Interim reanalysis data reveals that the PSA pattern has a strong influence on temperature and precipitation variability over West Antarctica and the Antarctic Peninsula, and on sea ice variability in the adjacent Amundsen, Bellingshausen and Weddell Seas. Identified seasonal trends towards the negative phase of the PSA pattern are consistent with warming observed over the Antarctic Peninsula during autumn, but are inconsistent with observed winter warming over West Antarctica. Only a weak relationship is identified between the PSA pattern and ENSO, which suggests that the pattern might be better conceptualized as preferred regional atmospheric response to various external (and internal) forcings.
Figure1

Damien Irving

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Southern Hemisphere mid-to-upper tropospheric planetary wave activity is characterized by the superposition of two zonally-oriented, quasi-stationary waveforms: zonal wavenumber one (ZW1) and zonal wavenumber three (ZW3). Previous studies have tended to consider these waveforms in isolation and with the exception of those studies relating to sea ice, little is known about their impact on regional climate variability. We take a novel approach to quantifying the combined influence of ZW1 and ZW3, using the strength of the hemispheric meridional flow as a proxy for zonal wave activity. Our methodology adapts the wave envelope construct routinely used in the identification of synoptic-scale Rossby wave packets and improves on existing approaches by allowing for variations in both wave phase and amplitude. While ZW1 and ZW3 are both prominent features of the climatological circulation, the defining feature of highly meridional hemispheric states is an enhancement of the ZW3 component. Composites of the mean surface conditions during these highly meridional, ZW3-like anomalous states (i.e. months of strong planetary wave activity) reveal large sea ice anomalies over the Amundsen and Bellingshausen Seas during autumn and along much of the East Antarctic coastline throughout the year. Large precipitation anomalies in regions of significant topography (e.g. New Zealand, Patagonia, coastal Antarctica) and anomalously warm temperatures over much of the Antarctic continent were also associated with strong planetary wave activity. The latter has potentially important implications for the interpretation of recent warming over West Antarctica and the Antarctic Peninsula.
Sf hus composite eraint 500hpa daily anom wrt all native reoriented queen maud
Below is the composite mean specific humidity and atmospheric circulation for each of the Antarctic Cloud Mass Meridional Transport (CMMT) regions over the entire study period (1 November 1992 – 31 October 2012). For this analysis, 6-hourly, 500 hPa specific humidity, zonal wind and meridional wind data from the European Centre for Medium-Range Weather Forecasts Interim Reanalysis \citep[ERA-Interim;][]{Dee2011} was downloaded for the period 1979–2016. Daily mean fields were calculated from the 6-hourly data and the wind fields were used to calculate the 500 hPa streamfunction. In order to calculate the streamfunction and specific humidity anomaly, the mean value for each day over the period 1979–2016 was calculated to produce a daily climatology, and then the corresponding climatological mean value was subtracted at each data time to obtain the anomaly data. When calculating the composite mean field for a given region, all days for which a CMMT event was recorded (i.e. at any time of the day) were used, regardless of whether the event was designated as a skirting event or not. While this is a rather coarse approach, I suspect a more detailed approach (e.g. it would be more correct to use the 6-hourly data and try to break down skirting events according to time spent in each region) would yield similar results. First impressions on recognizable structures in the composites: - The composite mean circulation for Ellsworth Land (Figure [fig:ellsworth]) resembles the Pacific-South American (PSA) pattern. The PSA pattern has traditionally been linked to convection in the tropical Pacific (and thus is routinely introduced as a mechanism by which ENSO can influence the high southern latitudes), however a couple of recent studies have challenged this assumption (they find it is instead an intrinsic feature of the mid-to-high latitude circulation that is largely independent of tropical forcing). This might explain why there was no strong association between CMMT events in Ellsworth Land and ENSO indices. - There are a limited number of seasons/regions that show a fairly coordinated zonal wave number 4 pattern around the hemisphere (e.g. Queen Maud Land in MAM; Figure [fig:queen_maud]). This wavenumber 4 variability is to be expected (Figure 4b of shows that zonal wavenumber 4 is dominant at daily timescales), but I’m actually not sure about the relationship between such coordinated daily timescale patterns and the well known monthly timescale features like the ZW3 pattern. (i.e. does a strong monthly mean ZW3 pattern consist of lots of daily mean fields that have a coordinated wavenumber 4 pattern? This might be true - I could possibly look into that if need be.) - In many seasons/regions (particularly for the annual plots) the streamfunction anomalies are strong in the vicinity of the region of interest but weak further afield (I’ve used an exaggerated number of contours in the plots to try and make sure we don’t miss any spatial structures, but if you use a more reasonable contour interval it becomes clearer that in many cases the far field anomalies are rather weak). This might be an interesting finding in itself, in that it suggests that there isn’t an obvious large-scale dynamical climate phenomena (e.g. ENSO, SAM, ZW3, PSA pattern, etc) associated with events in that season/region (i.e. perhaps local factors are much more important - future work could try and identify some of those local factors?) - It might be worth looking at the individual daily fields associated with some of the events to get a feel for if the composites are representative (i.e. if there is a lot of variability between events the composite mean might not be particularly representative)