Stefan Hagemann

Vulnerability of permafrost carbon to climate change: Implications for the global carbon cycle

ABSTRACT Thawing permafrost and the resulting microbial decomposition of previously frozen organic carbon (C) is one of the most significant potential feedbacks from terrestrial ecosystems to the atmosphere in a changing climate. In this article we present an overview of the global permafrost C pool and of the processes that might transfer this C into the atmosphere, as well as the associated ecosystem changes that occur with thawing. We show that accounting for C stored deep in the permafrost more than doubles previous high-latitude inventory estimates, with this new estimate equivalent to twice the atmospheric C pool. The thawing of permafrost with warming occurs both gradually and catastrophically, exposing organic C to microbial decomposition. Other aspects of ecosystem dynamics can be altered by climate change along with thawing permafrost, such as growing season length, plant growth rates and species composition, and ecosystem energy exchange. However, these processes do not appear to be able to compensate for C release from thawing permafrost, making it likely that the net effect of widespread permafrost thawing will be a positive feedback to a warming climate.

Sensitivity of Simulated Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere Model

Abstract The most recent version of the Max Planck Institute for Meteorology atmospheric general circulation model, ECHAM5, is used to study the impact of changes in horizontal and vertical resolution on seasonal mean climate. In a series of Atmospheric Model Intercomparison Project (AMIP)-style experiments with resolutions ranging between T21L19 and T159L31, the systematic errors and convergence properties are assessed for two vertical resolutions. At low vertical resolution (L19) there is no evidence for convergence to a more realistic climate state for horizontal resolutions higher than T42. At higher vertical resolution (L31), on the other hand, the root-mean-square errors decrease monotonically with increasing horizontal resolution. Furthermore, except for T42, the L31 versions are superior to their L19 counterparts, and the improvements become more evident at increasingly higher horizontal resolutions. This applies, in particular, to the zonal mean climate state and to the stationary wave patterns i...

Can climate trends be calculated from reanalysis data

Several global quantities are computed from the ERA40 reanalysis for the period 1958-2001 and explored for trends. These are discussed in the context of changes to the global observing system. Temperature, integrated water vapor (IWV), and kinetic energy are considered. The ERA40 global mean temperature in the lower troposphere has a trend of +0.11 K per decade over the period of 1979-2001, which is slightly higher than the MSU measurements, but within the estimated error limit. For the period 1958 2001 the warming trend is 0.14 K per decade but this is likely to be an artifact of changes in the observing system. When this is corrected for, the warming trend is reduced to 0.10 K per decade. The global trend in IWV for the period 1979-2001 is +0.36 mm per decade. This is about twice as high as the trend determined from the Clausius-Clapeyron relation assuming conservation of relative humidity. It is also larger than results from free climate model integrations driven by the same observed sea surface temperature as used in ERA40. It is suggested that the large trend in IWV does not represent a genuine climate trend but an artifact caused by changes in the global observing system such as the use of SSM/I and more satellite soundings in later years. Recent results are in good agreement with GPS measurements. The IWV trend for the period 1958-2001 is still higher but reduced to +0.16 mm per decade when corrected for changes in the observing systems. Total kinetic energy shows an increasing global trend. Results from data assimilation experiments strongly suggest that this trend is also incorrect and mainly caused by the huge changes in the global observing system in 1979. When this is corrected for, no significant change in global kinetic energy from 1958 onward can be found.

Multimodel estimate of the global terrestrial water balance: setup and first results

Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.58 spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr 21 (from 60 000 to 85 000 km 3 yr 21 ), and simulated runoff ranges from 290 to 457 mm yr 21 (from 42 000 to 66 000 km 3 yr 21 ). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degreeday approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact

Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

Significance Increasing concentrations of greenhouse gases in the atmosphere are widely expected to influence global climate over the coming century. The impact on drought is uncertain because of the complexity of the processes but can be estimated using outputs from an ensemble of global models (hydrological and climate models). Using an ensemble of 35 simulations, we show a likely increase in the global severity of drought by the end of 21st century, with regional hotspots including South America and Central and Western Europe in which the frequency of drought increases by more than 20%. The main source of uncertainty in the results comes from the hydrological models, with climate models contributing to a substantial but smaller amount of uncertainty. Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by bias-corrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty.

Reconstructing, Monitoring, and Predicting Multidecadal-Scale Changes in the North Atlantic Thermohaline Circulation with Sea Surface Temperature

Sea surface temperature (SST) observations in the North Atlantic indicate the existence of strong multidecadal variability with a unique spatial structure. It is shown by means of a new global climate model, which does not employ flux adjustments, that the multidecadal SST variability is closely related to variations in the North Atlantic thermohaline circulation (THC). The close correspondence between the North Atlantic SST and THC variabilities allows, in conjunction with the dynamical inertia of the THC, for the prediction of the slowly varying component of the North Atlantic climate system. It is shown additionally that past variations of the North Atlantic THC can be reconstructed from a simple North Atlantic SST index and that future, anthropogenically forced changes in the THC can be easily monitored by observing SSTs. The latter is confirmed by another state-ofthe-art global climate model. Finally, the strong multidecadal variability may mask an anthropogenic signal in the North Atlantic for some decades.

Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models

AbstractFuture climate model scenarios depend crucially on the models’ adequate representation of the hydrological cycle. Within the EU integrated project Water and Global Change (WATCH), special care is taken to use state-of-the-art climate model output for impacts assessments with a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, given the systematic errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed for correcting climate model output to produce long-term time series with a statistical intensity distribution close to that of the observations. As observations, global reanalyzed daily data of precipitation and temperature were used that were obtained in the WATCH project. Daily time series from three GCMs (GCMs) ECHAM5/Max Planck Institute Ocean Model (MPI-OM), Centre National de Recherches Me...

Climate model bias correction and the role of timescales

Abstract. It is well known that output from climate models cannot be used to force hydrological simulations without some form of preprocessing to remove the existing biases. In principle, statistical bias correction methodologies act on model output so the statistical properties of the corrected data match those of the observations. However, the improvements to the statistical properties of the data are limited to the specific timescale of the fluctuations that are considered. For example, a statistical bias correction methodology for mean daily temperature values might be detrimental to monthly statistics. Also, in applying bias corrections derived from present day to scenario simulations, an assumption is made on the stationarity of the bias over the largest timescales. First, we point out several conditions that have to be fulfilled by model data to make the application of a statistical bias correction meaningful. We then examine the effects of mixing fluctuations on different timescales and suggest an alternative statistical methodology, referred to here as a cascade bias correction method, that eliminates, or greatly reduces, the negative effects.

An Improved Land Surface Parameter Dataset for Global and Regional Climate Models

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Eavaluation of the hydrological cycle in the ECHAM5 model

Abstract This study investigates the impact of model resolution on the hydrological cycle in a suite of model simulations using a new version of the Max Planck Institute for Meteorology atmospheric general circulation model (AGCM). Special attention is paid to the evaluation of precipitation on the regional scale by comparing model simulations with observational data in a number of catchments representing the major river systems on the earth in different climate zones. It is found that an increased vertical resolution, from 19 to 31 atmospheric layers, has a beneficial effect on simulated precipitation with respect to both the annual mean and the annual cycle. On the other hand, the influence of increased horizontal resolution, from T63 to T106, is comparatively small. Most of the improvements at higher vertical resolution, on the scale of a catchment, are due to large-scale moisture transport, whereas the impact of local water recycling through evapotranspiration is somewhat smaller. At high horizontal a...