Thomas Laepple

Improved albedo formulation for chemistry transport models based on satellite observations and assimilated snow data and its impact on tropospheric photochemistry

[1]xa0Present parameterizations of the UV surface albedo in global chemistry transport models are generally based on a crude land cover classification and do not account for interannual variations of the snow-covered surface or the large variability in the albedo of snow-covered surfaces. We developed an improved scheme based on 2 years of Moderate-Resolution Imaging Spectroradiometer (MODIS) albedo data, a fine-resolution MODIS land cover map, Global Ozone Monitoring Experiment (GOME) albedo data, and daily assimilated snow cover maps from the European Centre for Medium-Range Weather Forecasts or the National Centers for Environmental Prediction. The new parameterization improves the calculation of photolysis frequencies in particular in the subarctic region as shown by a comparison of the calculated ratio of upwelling and downwelling actinic fluxes with spectral measurements from the Tropospheric Ozone Production About Spring Equinox (TOPSE) campaign (January–May 2000). The impact of surface albedo changes on tropospheric photochemistry has been investigated using the global MOZART-2 chemistry transport model. Compared with the original model version, the surface albedo changes alter the tropospheric oxidizing capacity (OH concentrations) between −20 and +200% locally and +5% in the global annual mean. About half of this change results from a new value adapted for the ocean UV albedo. Locally, NOx concentrations were found to decrease by up to 40% and were most pronounced where the snow boundary crosses the high-emission regions in Europe, North America, and Asia. The interannual variability of snow and sea ice cover can lead to changes in the global tropospheric OH-concentration of 0.5%, which is of similar magnitude compared with the impacts of varying water vapor, transport, ozone column, and emissions as discussed in previous studies.

Layering of surface snow and firn at Kohnen Station, Antarctica - noise or seasonal signal?

The density of firn is an important property for monitoring and modeling the ice sheet as well as to model the pore close-off and thus to interpret ice core-based greenhouse gas records. One feature, which is still in debate, is the potential existence of an annual cycle of firn density in low-accumulation regions. Several studies describe or assume seasonally successive density layers, horizontally evenly distributed, as seen in radar data. On the other hand, high-resolution density measurements on firn cores in Antarctica and Greenland showed no clear seasonal cycle in the top few meters. A major caveat of most existing snow-pit and firn-core based studies is that they represent one vertical profile from a laterally heterogeneous density field. To overcome this, we created an extensive dataset of horizontal and vertical density data at Kohnen Station, Dronning Maud Land on the East Antarctic Plateau. We drilled and analyzed three 90u2009m long firn cores as well as 160 one meter long vertical profiles from two elongated snow trenches to obtain a two dimensional view of the density variations. The analysis of the 45u2009m wide and 1u2009m deep density fields reveals a seasonal cycle in density. However, the seasonality is overprinted by strong stratigraphic noise, making it invisible when analyzing single firn cores. Our density dataset extends the view from the local ice-core perspective to a hundred meter scale and thus supports linking spatially integrating methods such as radar and seismic studies to ice and firn cores.

Northeast Siberian ice wedges confirm Arctic winter warming over the past two millennia

Arctic climate has experienced major changes over the past millennia that are not fully understood in terms of their controls and seasonality. Stable isotope data from ice wedges in permafrost provide unique information on past winter climate. Recently, an ice-wedge record from the Lena River Delta suggested for the first time that Siberian winter temperatures increased throughout the Holocene, contradicting most other Arctic palaeoclimate reconstructions which are likely biased towards the summer. However, the representativeness of this single record and the spatial extent of its reconstructed winter warming signal is unclear. Here, we present a new winter temperature record based on paired stable oxygen (δ18O) and radiocarbon age data spanning the last two millennia from the Oyogos Yar coast in northeast Siberia. The record confirms the long-term winter warming signal as well as the unprecedented temperature rise in recent decades. This confirmation demonstrates that winter warming over the last millennia is a coherent feature in the northeastern Siberian Arctic, supporting the hypothesis of an insolation-driven seasonal Holocene temperature evolution followed by a strong warming likely related to anthropogenic forcing.

Sedproxy: a forward model for sediment archived climate proxies

Climate reconstructions based on proxy records recovered from marine sediments, such as alkenone records or geochemical parameters measured on foraminifera, play an important role in our understanding of the climate system. They provide information about the state of the ocean ranging back hundreds to millions of years and form the backbone of paleo-oceanography. However, there are many sources of uncertainty associated with the signal recovered from sediment-archived proxies. These include seasonal or depth-habitat biases in the recorded signal; a frequency-dependent reduction in the amplitude of the recorded signal due to bioturbation of the sediment; aliasing of high-frequency climate variation onto a nominally annual, decadal, or centennial resolution signal; and additional sample processing and measurement error introduced when the proxy signal is recovered. Here we present a forward model for sediment-archived proxies that jointly models the above processes so that the magnitude of their separate and combined effects can be investigated. Applications include the interpretation and analysis of uncertainty in existing proxy records, parameter sensitivity analysis to optimize future studies, and the generation of pseudo-proxy records that can be used to test reconstruction methods. We provide examples, such as the simulation of individual foraminifera records, that demonstrate the usefulness of the forward model for paleoclimate studies. The model is implemented as an open-source R package, sedproxy, to which we welcome collaborative contributions. We hope that use of sedproxy will contribute to a better understanding of both the limitations and potential of marine sediment proxies to inform researchers about earth’s past climate.