ALBERT

Description: Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we adapt model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Description: Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Description: Data assimilation was recently suggested to smooth out the sharp gradients that characterize the tropopause inversion layer (TIL) in systems that did not assimilate TIL-resolving observations. We investigate whether this effect is present in the ERA-Interim reanalysis and the European Centre for Medium-Range Weather Forecasts (ECMWF) operational forecast system (which assimilate high-resolution observations) by analyzing the 4D-Var increments and how the TIL is represented in their data assimilation systems. For comparison, we also diagnose the TIL from high-resolution GPS radio occultation temperature profiles from the COSMIC satellite mission, degraded to the same vertical resolution as ERA-Interim and ECMWF operational analyses. Our results show that more recent reanalysis and forecast systems improve the representation of the TIL, updating the earlier hypothesis. However, the TIL in ERA-Interim and ECMWF operational analyses is still weaker and farther away from the tropopause than GPS radio occultation observations of the same vertical resolution.

Description: Changes in Earth rotation are strongly related to fluctuations in the angular momentum of the atmosphere, and therefore contain integral information about the atmospheric state. Here we investigate the extent to which observed Earth rotation parameters can be used to evaluate and potentially constrain atmospheric models. This is done by comparing the atmospheric excitation function, computed geophysically from reanalysis data and climate model simulations constrained only by boundary forcings, to the excitation functions inferred from geodetic monitoring data. Model differences are assessed for subseasonal variations, the annual and semiannual cycles, interannual variations, and decadal-scale variations. Observed length-of-day anomalies on the subseasonal timescale are simulated well by the simulations that are constrained by meteorological data only, whereas the annual cycle in length-of-day is simulated well by all models. Interannual length-of-day variations are captured fairly well as long as a model has realistic, time-varying SST boundary conditions and QBO forcing. Observations of polar motion are most clearly relatable to atmospheric dynamics on subseasonal to annual timescales, though angular momentum budget closure is difficult to achieve even for data-constrained atmospheric simulations. Closure of the angular momentum budget on decadal timescales is difficult and strongly dependent on estimates of angular momentum fluctuations due to core-mantle interactions in the solid Earth.

Description: It has been found in recent years that the atmosphere excites changes in the rotation of the Earth, i.e. the wobble of the rotational pole (polar motion) and the rate of rotation of the Earth (i.e. changes in the length-of-day, or LOD), by the exchange of angular momentum between the atmosphere and solid Earth. These changes range from subdaily to decadal timescales, and while very small, can be observed at high precision by space geodetic techniques. Observations of polar motion and LOD reflect the atmosphere’s total angular momentum, and thus represent an integral measure of the atmospheric state. They can therefore be used to observationally constrain atmospheric models. Here we present the application of this constraint to simulations of NCAR’s Community Climate Model 5 (CAM5) using an Ensemble Square Root Filter, implemented within the Data Assimilation Research Testbed (DART).We present a set of perfect-model experiments wherein observations of thee Earth rotation parameters are assimilated daily. Since the observations represent spatial integrals, each set of observations does not correspond to a unique state-space solution, which means that the three parameters are unable to fully constrain the state. However, the spread of the ensemble around the true state is significantly reduced as the assimilation progresses, showing that the application of a spatial-integral observations can constrain the modeled dynamics in a way that is complementary to standard meteorological observations.