This article reviews past and current reanalysis activities at the European Centre for Medium-Range Weather Forecasts (ECMWF) and describes plans for developing future reanalyses of the coupled ...climate system. Global reanalyses of the atmosphere, ocean, land surface, and atmospheric composition have played an important role in improving and extending the capabilities of ECMWF's operational forecasting systems. The potential role of reanalysis in support of climate change services in Europe is driving several interesting new developments. These include the production of reanalyses that span a century or more and the implementation of a coupled data assimilation capability suitable for climate reanalysis. Although based largely on ECMWF's achievements, capabilities, and plans, the article serves more generally to provide a review of pertinent issues affecting past and current reanalyses and a discussion of the major challenges in moving to more fully coupled systems.
The Plumbing of Land Surface Models Best, M. J.; Abramowitz, G.; Johnson, H. R. ...
Journal of hydrometeorology,
06/2015, Letnik:
16, Številka:
3
Journal Article
Recenzirano
Odprti dostop
The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. ...Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically basedmodels and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.
The coupling between land surface and the atmosphere is a key feature in Earth System Modeling for exploiting the predictability of slowly evolving geophysical variables (e.g., soil moisture or ...vegetation state), and for correctly representing rapid variations within the diurnal cycle, particularly relevant in data assimilation applications. In this study, land surface temperature (LST) estimated from Meteosat Second Generation (MSG) is used to assess the European Centre for Medium‐Range Weather Forecasts (ECMWF) skin temperature, which can be interpreted as a radiative temperature of the model surface. It is shown that the ECMWF model tends to slightly overestimate skin temperature during nighttime and underestimate daytime values. Such underestimation of daily amplitudes is particularly pronounced in (semiarid) arid regions, suggesting a misrepresentation of surface energy fluxes in those areas. The LST estimated from MSG is used to evaluate the impact of changes in some of the ECMWF model surface parameters. The introduction of more realistic model vegetation is shown to have a positive but limited impact on skin temperature: long integration leads to an equilibrium state where changes in the latent heat flux and soil moisture availability compensate each other. Revised surface roughness lengths for heat and momentum, however, lead to overall positive impact on daytime skin temperature, mostly due to a reduction of sensible heat flux. This is particularly relevant in nonvegetated areas, unaffected by model vegetation. The reduction of skin conductivity, a parameter which controls the heat transfer to ground by diffusion, is shown to further improve the model skin temperature.
Key Points
Remote sensing land surface temperature used to assess ECMWF skin temperature
Use of monthly LAI has limited impact on model skin temperature
Revised surface roughness lengths reduce skin temperature bias in arid regions
Quantification of global land evapotranspiration (ET) has long been associated with large uncertainties due to the lack of reference observations. Several recently developed products now provide the ...capacity to estimate ET at global scales. These products, partly based on observational data, include satellite based products, land surface model (LSM) simulations, atmospheric reanalysis output, estimates based on empirical upscaling of eddycovariance flux measurements, and atmospheric water balance datasets. The LandFlux-EVAL project aims to evaluate and compare these newly developed datasets. Additionally, an evaluation of IPCC AR4 global climate model (GCM) simulations is presented, providing an assessment of their capacity to reproduce flux behavior relative to the observations based products. Though differently constrained with observations, the analyzed reference datasets display similar large-scale ET patterns. ET from the IPCC AR4 simulations was significantly smaller than that from the other products for India (up to 1 mm/d) and parts of eastern South America, and larger in the western USA, Australia and China. The inter-product variance is lower across the IPCC AR4 simulations than across the reference datasets in several regions, which indicates that uncertainties may be underestimated in the IPCC AR4 models due to shared biases of these simulations.
In situ soil moisture measurements from 2007 to 2010 for 196 stations from five networks across the world (United States, France, Spain, China, and Australia) are used to determine the reliability of ...three soil moisture products: (i) a revised version of the ECMWF Interim Re-Analysis (ERA-Interim; ERA-Land); (ii) a revised version of the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis from NASA(MERRA-Land); and (iii) a new, microwave-based multisatellite surface soil moisture dataset (SM-MW). Evaluation of the time series and anomalies from a moving monthly mean shows a good performance of the three products in capturing the annual cycle of surface soil moisture and its short-term variability. On average, correlations (95% confidence interval) are 0.66 (±0.038), 0.69 (±0.038), and 0.60 (±0.061) for ERA-Land, MERRA-Land, and SM-MW. The two reanalysis products also capture the root-zone soil moisture well; on average, correlations are 0.68 (±0.035) and 0.73 (±0.032) for ERA-Land and MERRA-Land, respectively. Global trends analysis for 1988–2010 suggests a decrease of surface soil moisture contents (72% of significant trends are negative, i.e., drying) for ERA-Land and an increase in surface soil moisture (59% of significant trends are positive, i.e., wetting) for MERRA-Land. As the spatial extent and fractions of significant trends in both products differ, the trend reflected in the majority of grid points within different climate classes was investigated and compared to that of SM-MW. The latter is dominated by negative significant trends (73.2%) and is more in line with ERA-Land. For both reanalysis products, trends for the upper layer of soil are confirmed in the root-zone soil moisture (first meter of soil).
The influence of the snowpack on wintertime atmospheric teleconnections has received renewed attention in recent years, partially for its potential impact on seasonal predictability. Many ...observational and model studies have indicated that the autumn Eurasian snow cover in particular, influences circulation patterns over the North Pacific and North Atlantic. We have performed a suite of coupled atmosphere-ocean simulations with the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecast system to investigate the impact of accurate snow initialisation. Pairs of 2-month ensemble forecasts were started every 15 days from the 15th of October through the 1st of December in the years 2004–2009, with either realistic initialization of snow variables based on re-analyses, or else with “scrambled” snow initial conditions from an alternate autumn date and year. Initially, in the first 15 days, the presence of a thicker snowpack cools surface temperature over the continental land masses of Eurasia and North America. At a longer lead of 30-day, it causes a warming over the Arctic and the high latitudes of Eurasia due to an intensification and westward expansion of the Siberian High. It also causes a cooling over the mid-latitudes of Eurasia, and lowers sea level pressures over the Arctic. This “warm Arctic—cold continent” difference means that the forecasts of near-surface temperature with the more realistic snow initialization are in closer agreement with re-analyses, reducing a cold model bias over the Arctic and a warm model bias over mid-latitudes. The impact of realistic snow initialization upon the forecast skill in snow depth and near-surface temperature is estimated for various lead times. Following a modest skill improvement in the first 15 days over snow-covered land, we also find a forecast skill improvement up to the 30-day lead time over parts of the Arctic and the Northern Pacific, which can be attributed to the realistic snow initialization over the land masses.
Soil Moisture Analyses at ECMWF Albergel, C.; de Rosnay, P.; Balsamo, G. ...
Journal of hydrometeorology,
10/2012, Letnik:
13, Številka:
5
Journal Article
Recenzirano
Odprti dostop
In situ soil moisture from 117 stations across the world and under different biome and climate conditions are used to evaluate two soil moisture products from the European Centre for Medium-Range ...Weather Forecasts (ECMWF)—namely, the operational analysis and the interim reanalysis ECMWF Re-Analysis Interim (ERA-Interim). ECMWF’s operational Integrated Forecasting System (IFS) is based on a continuous effort to improve the analysis and modeling systems, resulting in frequent updates (a few times a year). The ERA-Interim reanalysis is produced by a fixed IFS version (for the main component of the atmospheric model and data assimilation). It has the advantage of being consistent over the whole period from 1979 onward and by design, reanalysis products are more suitable than their operational counterparts for use in climate studies. Although the two analyses show good skills in capturing surface soil moisture variability, they tend to overestimate soil moisture, particularly for dry land. Over the 2008–10 period, averaged statistical scores (correlation, bias, and root-mean-square difference) are 0.70, −0.081 m³ m−3, and 0.113 m³ m−3for the operational product and 0.63, −0.079 m³ m−3, and 0.121 m³ m−3for ERA-Interim. Compared to the scheme used in ERA-Interim, the current model used in the IFS has an improved match to soil moisture that is attributed to recent changes in the IFS. Indeed, major upgrades recently implemented in the operational land surface analysis and modeling system improve the surface and the root-zone soil moisture analyses.
A global intercomparison of 12 monthly mean land surface heat flux products for the period 1993-1995 is presented. The intercomparison includes some of the first emerging global satellite-based ...products (developed at Paris Observatory, Max Planck Institute for Biogeochemistry, University of California Berkeley, University of Maryland, and Princeton University) and examples of fluxes produced by reanalyses (ERA-Interim, MERRA, NCEP-DOE) and off-line land surface models (GSWP-2, GLDAS CLM/ Mosaic/Noah). An intercomparison of the global latent heat flux (Q(sub le)) annual means shows a spread of approx 20 W/sq m (all-product global average of approx 45 W/sq m). A similar spread is observed for the sensible (Q(sub h)) and net radiative (R(sub n)) fluxes. In general, the products correlate well with each other, helped by the large seasonal variability and common forcing data for some of the products. Expected spatial distributions related to the major climatic regimes and geographical features are reproduced by all products. Nevertheless, large Q(sub le)and Q(sub h) absolute differences are also observed. The fluxes were spatially averaged for 10 vegetation classes. The larger Q(sub le) differences were observed for the rain forest but, when normalized by mean fluxes, the differences were comparable to other classes. In general, the correlations between Q(sub le) and R(sub n) were higher for the satellite-based products compared with the reanalyses and off-line models. The fluxes were also averaged for 10 selected basins. The seasonality was generally well captured by all products, but large differences in the flux partitioning were observed for some products and basins.
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