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Bart J. J. M. van den Hurk and Erik van Meijgaard

Abstract

Land–atmosphere interaction at climatological time scales in a large area that includes the West African Sahel has been explicitly explored in a regional climate model (RegCM) simulation using a range of diagnostics. First, areas and seasons of strong land–atmosphere interaction were diagnosed from the requirement of a combined significant correlation between soil moisture, evaporation, and the recycling ratio. The northern edge of the West African monsoon area during June–August (JJA) and an area just north of the equator (Central African Republic) during March–May (MAM) were identified. Further analysis in these regions focused on the seasonal cycle of the lifting condensation level (LCL) and the convective triggering potential (CTP), and the sensitivity of CTP and near-surface dewpoint depressions HIlow to anomalous soil moisture. From these analyses, it is apparent that atmospheric mechanisms impose a strong constraint on the effect of soil moisture on the regional hydrological cycle.

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Bart van den Hurk, Janneke Ettema, and Pedro Viterbo

Abstract

This study aims at stimulating the development of soil moisture data assimilation systems in a direction where they can provide both the necessary control of slow drift in operational NWP applications and support the physical insight in the performance of the land surface component. It addresses four topics concerning the systematic nature of soil moisture data assimilation experiments over Europe during the growing season of 2000 involving the European Centre for Medium-Range Weather Forecasts (ECMWF) model infrastructure. In the first topic the effect of the (spinup related) bias in 40-yr ECMWF Re-Analysis (ERA-40) precipitation on the data assimilation is analyzed. From results averaged over 36 European locations, it appears that about half of the soil moisture increments in the 2000 growing season are attributable to the precipitation bias. A second topic considers a new soil moisture data assimilation system, demonstrated in a coupled single-column model (SCM) setup, where precipitation and radiation are derived from observations instead of from atmospheric model fields. For many of the considered locations in this new system, the accumulated soil moisture increments still exceed the interannual variability estimated from a multiyear offline land surface model run. A third topic examines the soil water budget in response to these systematic increments. For a number of Mediterranean locations the increments successfully increase the surface evaporation, as is expected from the fact that atmospheric moisture deficit information is the key driver of soil moisture adjustment. In many other locations, however, evaporation is constrained by the experimental SCM setup and is hardly affected by the data assimilation. Instead, a major portion of the increments eventually leave the soil as runoff. In the fourth topic observed evaporation is used to evaluate the impact of the data assimilation on the forecast quality. In most cases, the difference between the control and data assimilation runs is considerably smaller than the (positive) difference between any of the simulations and the observations.

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Mxolisi E. Shongwe, Geert Jan van Oldenborgh, Bart van den Hurk, and Maarten van Aalst

Abstract

Probable changes in mean and extreme precipitation in East Africa are estimated from general circulation models (GCMs) prepared for the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4). Bayesian statistics are used to derive the relative weights assigned to each member in the multimodel ensemble. There is substantial evidence in support of a positive shift of the whole rainfall distribution in East Africa during the wet seasons. The models give indications for an increase in mean precipitation rates and intensity of high rainfall events but for less severe droughts. Upward precipitation trends are projected from early this (twenty first) century. As in the observations, a statistically significant link between sea surface temperature gradients in the tropical Indian Ocean and short rains (October–December) in East Africa is simulated in the GCMs. Furthermore, most models project a differential warming of the Indian Ocean during boreal autumn. This is favorable for an increase in the probability of positive Indian Ocean zonal mode events, which have been associated with anomalously strong short rains in East Africa. On top of the general increase in rainfall in the tropics due to thermodynamic effects, a change in the structure of the Eastern Hemisphere Walker circulation is consistent with an increase in East Africa precipitation relative to other regions within the same latitudinal belt. A notable feature of this change is a weakening of the climatological subsidence over eastern Kenya. East Africa is shown to be a region in which a coherent projection of future precipitation change can be made, supported by physical arguments. Although the rate of change is still uncertain, almost all results point to a wetter climate with more intense wet seasons and less severe droughts.

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Siswanto, Geert Jan van Oldenborgh, Gerard van der Schrier, Geert Lenderink, and Bart van den Hurk
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Bart J. J. M. van den Hurk, Wim G. M. Bastiaanssen, Henk Pelgrum, and Erik van Meijgaard

Abstract

In this study, a simple method is described and tested for deriving initial soil moisture fields for numerical weather prediction purposes using satellite imagery. Recently, an algorithm was developed to determine surface evaporation maps from high- and low-resolution satellite data, which does not require information on land use and synoptic data. A correction to initial soil moisture was calculated from a comparison between the evaporation fields produced by a numerical weather prediction model and the satellite algorithm. As a case study, the method was applied to the Iberian Peninsula during a 7-day period in the summer of 1994. Two series of short-term forecasts, initialized from a similar initial soil moisture field, were run in parallel: a control run in which soil moisture evolved freely and an experimental run in which soil moisture was updated daily using the simple assimilation procedure. The simple assimilation resulted in a decrease of the bias of temperature and specific humidity at 2-m height during the daytime and a small decrease of the root-mean-square error of these quantities. The results show that the surface evaporation maps, derived from the satellite data, contain a signal that may be used to assimilate soil moisture in numerical weather prediction models.

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Dirk Meetschen, Bart J. J. M. van den Hurk, Felix Ament, and Matthias Drusch

Abstract

High-quality fields of surface radiation fluxes are required for the development of Land Data Assimilation Systems. A fast offline integration scheme was developed to modify NWP model cloud fields based on Meteosat visible and infrared observations. From the updated cloud fields, downward shortwave and longwave radiation at the surface are computed using the NWP radiative transfer model.

A dataset of 15 months covering Europe was produced and validated against measurements of ground stations on a daily basis. In situ measurements are available for 30 stations in the Netherlands and two Baseline Surface Radiation Network (BSRN) stations in Germany and France. The accuracy of shortwave surface radiation is increased when the integration system is applied. The rms error in the model forecast is found to be 32 and 42 W m−2 for the period from October 1999 to December 2000 for the two BSRN stations. These values are reduced to 21 and 25 W m−2 through the application of the integration scheme. During the summer months the errors are generally larger than in winter. Because of an integrated monitoring of surface albedo, the performance of the scheme is not affected by snow cover. The errors in the longwave radiation field of the original NWP model are already small. However, they are slightly reduced by applying the integration scheme.

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Adriaan J. Teuling, Remko Uijlenhoet, Bart van den Hurk, and Sonia I. Seneviratne

Abstract

Integration of simulated and observed states through data assimilation as well as model evaluation requires a realistic representation of soil moisture in land surface models (LSMs). However, soil moisture in LSMs is sensitive to a range of uncertain input parameters, and intermodel differences in parameter values are often large. Here, the effect of soil parameters on soil moisture and evapotranspiration are investigated by using parameters from three different LSMs participating in the European Land Data Assimilation System (ELDAS) project. To prevent compensating effects from other than soil parameters, the effects are evaluated within a common framework of parsimonious stochastic soil moisture models. First, soil parameters are shown to affect soil moisture more strongly than the average evapotranspiration. In arid climates, the effect of soil parameters is on the variance rather than the mean, and the intermodel flux differences are smallest. Soil parameters from the ELDAS LSMs differ strongly, most notably in the available moisture content between the wilting point and the critical moisture content, which differ by a factor of 3. The ELDAS parameters can lead to differences in mean volumetric soil moisture as high as 0.10 and an average evapotranspiration of 10%–20% for the investigated parameter range. The parsimonious framework presented here can be used to investigate first-order parameter sensitivities under a range of climate conditions without using full LSM simulations. The results are consistent with many other studies using different LSMs under a more limited range of possible forcing conditions.

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Bart van den Hurk, Martin Best, Paul Dirmeyer, Andy Pitman, Jan Polcher, and Joe Santanello

No abstract available.

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Lennert B. Stap, Bart J. J. M. van den Hurk, Chiel C. van Heerwaarden, and Roel A. J. Neggers

Abstract

Observations have shown that differences in surface energy fluxes over grasslands and forests are amplified during heat waves. The role of land–atmosphere feedbacks in this process is still uncertain. In this study, a single-column model (SCM) is used to investigate the difference between forest and grassland in their energy response to heat waves. Three simulations for the period 2005–11 were carried out: a control run using vegetation characteristics for Cabauw (the Netherlands), a run where the vegetation is changed to 100% forest, and a run with 100% short grass as vegetation. A surface evaporation tendency equation is used to analyze the impact of the land–atmosphere feedbacks on evapotranspiration and sensible heat release under normal summer and heat wave conditions with excessive shortwave radiation.

Land–atmosphere feedbacks modify the contrast in surface energy fluxes between forest and grass, particularly during heat wave conditions. The surface resistance feedback has the largest positive impact, while boundary layer feedbacks generally tend to reduce the contrast. Overall, forests give higher air temperatures and drier atmospheres during heat waves. In offline land surface model simulations, the difference between forest and grassland during heat waves cannot be diagnosed adequately owing to the absence of boundary layer feedbacks.

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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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