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Gianpaolo Balsamo
,
Anton Beljaars
,
Klaus Scipal
,
Pedro Viterbo
,
Bart van den Hurk
,
Martin Hirschi
, and
Alan K. Betts

Abstract

The Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) is used operationally in the Integrated Forecast System (IFS) for describing the evolution of soil, vegetation, and snow over the continents at diverse spatial resolutions. A revised land surface hydrology (H-TESSEL) is introduced in the ECMWF operational model to address shortcomings of the land surface scheme, specifically the lack of surface runoff and the choice of a global uniform soil texture. New infiltration and runoff schemes are introduced with a dependency on the soil texture and standard deviation of orography. A set of experiments in stand-alone mode is used to assess the improved prediction of soil moisture at the local scale against field site observations. Comparison with basin-scale water balance (BSWB) and Global Runoff Data Centre (GRDC) datasets indicates a consistently larger dynamical range of land water mass over large continental areas and an improved prediction of river runoff, while the effect on atmospheric fluxes is fairly small. Finally, the ECMWF data assimilation and prediction systems are used to verify the effect on surface and near-surface quantities in the atmospheric-coupled mode. A midlatitude error reduction is seen both in soil moisture and in 2-m temperature.

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Bart van den Hurk
,
Martin Hirschi
,
Christoph Schär
,
Geert Lenderink
,
Erik van Meijgaard
,
Aad van Ulden
,
Burkhardt Rockel
,
Stefan Hagemann
,
Phil Graham
,
Erik Kjellström
, and
Richard Jones

Abstract

Simulations with seven regional climate models driven by a common control climate simulation of a GCM carried out for Europe in the context of the (European Union) EU-funded Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project were analyzed with respect to land surface hydrology in the Rhine basin. In particular, the annual cycle of the terrestrial water storage was compared to analyses based on the 40-yr ECMWF Re-Analysis (ERA-40) atmospheric convergence and observed Rhine discharge data. In addition, an analysis was made of the partitioning of convergence anomalies over anomalies in runoff and storage. This analysis revealed that most models underestimate the size of the water storage and consequently overestimated the response of runoff to anomalies in net convergence. The partitioning of these anomalies over runoff and storage was indicative for the response of the simulated runoff to a projected climate change consistent with the greenhouse gas A2 Synthesis Report on Emission Scenarios (SRES). In particular, the annual cycle of runoff is affected largely by the terrestrial storage reservoir. Larger storage capacity leads to smaller changes in both wintertime and summertime monthly mean runoff. The sustained summertime evaporation resulting from larger storage reservoirs may have a noticeable impact on the summertime surface temperature projections.

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Martina Weiss
,
Paul A. Miller
,
Bart J. J. M. van den Hurk
,
Twan van Noije
,
Simona Ştefănescu
,
Reindert Haarsma
,
Lambertus H. van Ulft
,
Wilco Hazeleger
,
Philippe Le Sager
,
Benjamin Smith
, and
Guy Schurgers

Abstract

In this study, the impact of coupling and initializing the leaf area index from the dynamic vegetation model Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) is analyzed on skill of decadal predictions in the fully coupled atmosphere–land–ocean–sea ice model, the European Consortium Earth System Model (EC-Earth). Similar to the impact of initializing the model with the observed oceanic state, initializing the leaf area index (LAI) fields obtained from an offline LPJ-GUESS simulation forced by the observed atmospheric state leads to a systematic drift. A different treatment of the water and soil moisture budget in LPJ-GUESS is a likely cause of this drift. The coupled system reduces the cold bias of the reference model over land by reducing LAI (and the associated evaporative cooling), particularly outside the growing season. The coupling with the interactive vegetation module implies more degrees of freedom in the coupled model, which generates more noise that can mask a portion of the extra signal that is generated. The forecast reliability improves marginally, particularly early in the forecast. Ranked probability skill scores are also improved slightly in most areas analyzed, but the signal is not fully coherent over the forecast interval because of the relatively low number of ensemble members. Methods to remove the LAI drift and allow coupling of other variables probably need to be implemented before significant forecast skill can be expected.

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Alexis Berg
,
Benjamin R. Lintner
,
Kirsten Findell
,
Sonia I. Seneviratne
,
Bart van den Hurk
,
Agnès Ducharne
,
Frédérique Chéruy
,
Stefan Hagemann
,
David M. Lawrence
,
Sergey Malyshev
,
Arndt Meier
, and
Pierre Gentine

Abstract

Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture–atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature–precipitation correlations using simulations from the Global Land–Atmosphere Coupling Experiment–phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950–2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture–atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature–precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature–precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture–atmosphere interactions.

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Ned Haughton
,
Gab Abramowitz
,
Andy J. Pitman
,
Dani Or
,
Martin J. Best
,
Helen R. Johnson
,
Gianpaolo Balsamo
,
Aaron Boone
,
Matthias Cuntz
,
Bertrand Decharme
,
Paul A. Dirmeyer
,
Jairui Dong
,
Michael Ek
,
Zichang Guo
,
Vanessa Haverd
,
Bart J. J. van den Hurk
,
Grey S. Nearing
,
Bernard Pak
,
Joe A. Santanello Jr.
,
Lauren E. Stevens
, and
Nicolas Vuichard

Abstract

The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave radiation, surface air temperature, and relative humidity. These results are explored here in greater detail and possible causes are investigated. It is examined whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation, and whether a lack of energy conservation in flux tower data gives the empirical models an unfair advantage in the intercomparison. It is demonstrated that energy conservation in the observational data is not responsible for these results. It is also shown that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, evidence is presented that suggests that the nature of this partitioning problem is likely shared among all contributing LSMs. While a single candidate explanation for why land surface models perform poorly relative to empirical benchmarks in PLUMBER could not be found, multiple possible explanations are excluded and guidance is provided on where future research should focus.

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EC-Earth

A Seamless Earth-System Prediction Approach in Action

Wilco Hazeleger
,
Camiel Severijns
,
Tido Semmler
,
Simona Ştefănescu
,
Shuting Yang
,
Xueli Wang
,
Klaus Wyser
,
Emanuel Dutra
,
José M. Baldasano
,
Richard Bintanja
,
Philippe Bougeault
,
Rodrigo Caballero
,
Annica M. L. Ekman
,
Jens H. Christensen
,
Bart van den Hurk
,
Pedro Jimenez
,
Colin Jones
,
Per Kållberg
,
Torben Koenigk
,
Ray McGrath
,
Pedro Miranda
,
Twan van Noije
,
Tim Palmer
,
José A. Parodi
,
Torben Schmith
,
Frank Selten
,
Trude Storelvmo
,
Andreas Sterl
,
Honoré Tapamo
,
Martin Vancoppenolle
,
Pedro Viterbo
, and
Ulrika Willén
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