Recycling of moisture in Europe: contribution of evaporation to variability in very wet and dry years

Evaporation is a key parameter in the regional atmospheric water cycle. Precipitation recycling is defined as the contribution of water that evaporates from a region to precipitation within the same region. We apply a dynamic precipitation recycling model, which includes a dynamic moisture storage term, to calculate the warm season variability of the precipitation recycling over central Europe at a daily time scale for 2003 (dry) and 2006 (wet). <br><br> For the central part of Europe advection is the most important contributor to precipitation. In dry spells in both years 2003 and 2006, when moisture of advective origin diminishes, local evaporation becomes an important contributor to precipitation (negative feedback). In two dry periods (June 2003 and July 2006) where there is enough moisture storage in the soil to continue evaporation, precipitation recycling is enhanced. In case studies we follow the path of an air column for days with high precipitation recycling to discuss the role of moisture recycling in land-atmosphere interactions. For 2 days with enough moisture availability (28 May 2003 and 5 July 2006) moisture particles stay long in the study area due to weak winds. By following the paths we show that the air is transported over land for a very long distance before it precipitates. It thus takes a considerable amount of time to traverse the region and capture moisture of evaporative origin. However, we hypothesize that the precipitation falling on those days still originates (partly) from oceanic sources, but that the triggering of precipitation may itself be a result of enhanced instability induced by soils, which still have sufficient moisture storage. In dry periods with enough moisture available precipitation recycling acts as a mechanism to keep the precipitation at a stable level. <br><br> In August 2003 evaporation is affecting the precipitation recycling due to the lack of water availability caused by the dryness of the preceding spring and summer season. According to a Granger Causality test the evaporation in 2003 exerts the strongest causal impact on the precipitation recycling ratio. For the case study of 10 August 2003, the atmosphere is too dry to generate precipitation with exception of the mountainous regions due to orographical lifting

Influence of drainage status on soil and water chemistry, litter decomposition and soil respiration in central Amazonian forests on sandy soils

Central Amazonian rainforest landscape supports a mosaic of tall terra firme rainforest and ecotone campinarana, riparian and campina forests, reflecting topography-induced variations in soil, nutrient and drainage conditions. Spatial and temporal variations in litter decomposition, soil and groundwater chemistry and soil CO2 respiration were studied in forests on sandy soils, whereas drought sensitivity of poorly-drained valley soils was investigated in an artificial drainage experiment. Slightly changes in litter decomposition or water chemistry were observed as a consequence of artificial drainage. Riparian plots did experience higher litter decomposition rates than campina forest. In response to a permanent lowering of the groundwater level from 0.1 m to 0.3 m depth in the drainage plot, topsoil carbon and nitrogen contents decreased substantially. Soil CO2 respiration decreased from 3.7±0.6 µmol m-2 s-1 before drainage to 2.5±0.2 and 0.8±0.1 µmol m-2 s-1 eight and 11 months after drainage, respectively. Soil respiration in the control plot remained constant at 3.7±0.6 µmol m-2 s-1. The above suggests that more frequent droughts may affect topsoil carbon and nitrogen content and soil respiration rates in the riparian ecosystem, and may induce a transition to less diverse campinarana or short-statured campina forest that covers areas with strongly-leached sandy soil

Mass conservation above slopes in the regional atmospheric modelling system (RAMS)

This paper examines the mass balance in calculations with the Regional Atmospheric Modelling System (RAMS). An error is pointed out that concerns the calculation of the surface fluxes on slopes. This error affects all the prognostic variables in RAMS when sloping terrain is involved. Here we explain how the error can be corrected. To study the impact of the error, we compared simulations with the uncorrected and corrected model. The model contains C

A summer climate regime over Europe modulated by the North Atlantic Oscillation

Recent summer heat waves in Europe were found to be preceded by precipitation deficits in winter. Numerical studies suggest that these phenomena are dynamically linked by land-atmosphere interactions. However, there exists as yet no complete observational evidence that connects summer climate variability to winter precipitation and the relevant circulation patterns. In this paper, we investigate the functional responses of summer mean and maximum temperature (June–August, <i>T</i><sub>mean</sub> and <i>T</i><sub>max</sub>) as well as soil moisture proxied by the self-calibrating Palmer drought severity index (<i>scPDSI</i>) to preceding winter precipitation (January–March, <i>P</i><sub>JFM</sub>) for the period 1901–2005. All the analyzed summer fields show distinctive responses to <i>P</i><sub>JFM</sub> over the Mediterranean. We estimate that 10 ~ 15% of the interannual variability of <i>T</i><sub>max</sub> and <i>T</i><sub>mean</sub> over the Mediterranean is statistically forced by <i>P</i><sub>JFM</sub>. For the <i>scPDSI</i> this amounts to 10 ~ 25%. Further analysis shows that these responses are highly correlated to the North Atlantic Oscillation (NAO) regime over the Mediterranean. We suggest that NAO modulates European summer temperature by controlling winter precipitation that initializes the moisture states that subsequently interact with temperature. This picture of relations between European summer climate and NAO as well as winter precipitation suggests potential for improved seasonal prediction of summer climate for particular extreme events

On observational and modelling strategies targeted at regional carbon exchange over continents

Estimating carbon exchange at regional scales is paramount to understanding feedbacks between climate and the carbon cycle, but also to verifying climate change mitigation such as emission reductions and strategies compensating for emissions such as carbon sequestration. This paper discusses evidence for a number of important shortcomings of current generation modelling frameworks designed to provide regional scale budgets from atmospheric observations. Current top-down and bottom-up approaches targeted at deriving consistent regional scale carbon exchange estimates for biospheric and anthropogenic sources and sinks are hampered by a number of issues: we show that top-down constraints using point measurements made from tall towers, although sensitive to larger spatial scales, are however influenced by local areas much more strongly than previously thought. On the other hand, classical bottom-up approaches using process information collected at the local scale, such as from eddy covariance data, need up-scaling and validation on larger scales. We therefore argue for a combination of both approaches, implicitly providing the important local scale information for the top-down constraint, and providing the atmospheric constraint for up-scaling of flux measurements. Combining these data streams necessitates quantifying their respective representation errors, which are discussed. The impact of these findings on future network design is highlighted, and some recommendations are given

The Kyoto Article 3.3 and 3.4 toolbox (KAT); January 2000

The KAT model provides a spreadsheet-based framework to calculate carbon sequestration in the commitment period (2008-2012) under Article 3.3 and 3.4 activities of the Kyoto protocol for the EU15 countries and selected Annex 1 countries. Any combination of 3.3 scenarios, 3.4 activities and sub-rules on Articles 3.3 and 3.4 based on policy proposals can be chosen. The carbon sequestration is calculated and presented in graphs and tables both in absolute values and in percentages of the1990 emissions. The user can interactively choose between a literature database and a database that consists of data submitted by countries under the UNFCC regulations

A comparison of different inverse carbon flux estimation approaches for application on a regional domain

We have implemented six different inverse carbon flux estimation methods in a regional carbon dioxide (CO<sub>2</sub>) flux modeling system for the Netherlands. The system consists of the Regional Atmospheric Mesoscale Modeling System (RAMS) coupled to a simple carbon flux scheme which is run in a coupled fashion on relatively high resolution (10 km). Using an Ensemble Kalman filter approach we try to estimate spatiotemporal carbon exchange patterns from atmospheric CO<sub>2</sub> mole fractions over the Netherlands for a two week period in spring 2008. The focus of this work is the different strategies that can be employed to turn first-guess fluxes into optimal ones, which is known as a fundamental design choice that can affect the outcome of an inversion significantly. <br><br> Different state-of-the-art approaches with respect to the estimation of net ecosystem exchange (NEE) are compared quantitatively: (1) where NEE is scaled by one linear multiplication factor per land-use type, (2) where the same is done for photosynthesis (GPP) and respiration (<i>R</i>) separately with varying assumptions for the correlation structure, (3) where we solve for those same multiplication factors but now for each grid box, and (4) where we optimize physical parameters of the underlying biosphere model for each land-use type. The pattern to be retrieved in this pseudo-data experiment is different in nearly all aspects from the first-guess fluxes, including the structure of the underlying flux model, reflecting the difference between the modeled fluxes and the fluxes in the real world. This makes our study a stringent test of the performance of these methods, which are currently widely used in carbon cycle inverse studies. <br><br> Our results show that all methods struggle to retrieve the spatiotemporal NEE distribution, and none of them succeeds in finding accurate domain averaged NEE with correct spatial and temporal behavior. The main cause is the difference between the structures of the first-guess and true CO<sub>2</sub> flux models used. Most methods display overconfidence in their estimate as a result. A commonly used daytime-only sampling scheme in the transport model leads to compensating biases in separate GPP and <i>R</i> scaling factors that are readily visible in the nighttime mixing ratio predictions of these systems. <br><br> Overall, we recommend that the estimate of NEE scaling factors should not be used in this regional setup, while estimating bias factors for GPP and <i>R</i> for every grid box works relatively well. The biosphere parameter inversion performs good compared to the other inversions at simultaneously producing space and time patterns of fluxes and CO<sub>2</sub> mixing ratios, but non-linearity may significantly reduce the information content in the inversion if true parameter values are far from the prior estimate. Our results suggest that a carefully designed biosphere model parameter inversion or a pixel inversion of the respiration and GPP multiplication factors are from the tested inversions the most promising tools to optimize spatiotemporal patterns of NEE

Fluctuation regimes of soil moisture in ERA-40 re-analysis data

Soil moisture variability is analysed in the re-analysis data ERA-40 of the European Centre for Medium-Range Weather Forecasts (ECMWF) which includes four layers within 189 cm depth. Short-term correlations are characterised by an e-folding time scale assuming an exponential decay, whilst long-term memory is described by power law decays with exponents determined by detrended fluctuation analysis. On a global scale, the short-term variability varies congruently with long-term memory in the surface layer. Key climatic regions (Europe, Amazon and Sahara) reveal that soil moisture time series are non-stationary in arid regions and in deep layers within the time horizon of ERA-40. The physical processes leading to soil moisture variability are linear according to an analysis of volatility (the absolute differences), which is substantiated by surrogate data analysis preserving the long-term memory