Abstract

The European summer of 2003 is used as a case study to analyze the land surface role in augmenting the local temperature anomalies. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and the 40-yr ECMWF Re-Analysis (ERA-40) climate, it is shown that in the months preceding the extreme summer events, positive anomalies in the surface shortwave radiation and a large precipitation deficit indicated an impending dry summer in early June. The use of soil water analysis values as possible predictors for drought is currently limited by the systematic attenuation of its seasonal cycle. Several numerical simulations with the ECMWF atmospheric model have been used to explore the atmospheric model sensitivity to the initial soil water conditions. The atmospheric response to large initial perturbations in the root zone extends up to month 2 and is nonlinear, and larger for drier regimes. Perturbations to the whole soil depth increase the amplitude of the atmospheric anomaly and extend its duration up to 3 months. The response of large initial dry soil anomalies greatly exceeds the impact of the ocean boundary forcing. Results from numerical simulations indicate the possible benefit of using perturbations in the initial soil water conditions, commensurate with soil moisture uncertainties, in the generation of the seasonal forecast ensembles.

Abstract

In many operational numerical weather prediction applications, the soil moisture analysis is based on the modeled first-guess and screen-level variables; that is, 2-m temperature and 2-m relative humidity. A set of two global 61-day analysis/forecast experiments based on the Integrated Forecast System at the European Centre for Medium-Range Weather Forecasts (ECMWF) has been performed for June and July 2002. Analyses and forecasts based on the operational Optimal Interpolation (OI) scheme are compared against results obtained from an open loop system, in which soil moisture evolves freely. It is found that soil moisture assimilation or analysis has a significant impact on the model atmosphere. Temperature forecasts for the Northern Hemisphere up to a level of 700 hPa and up to nine days were significantly improved when the operational analysis was used. A comparison of volumetric soil moisture against in situ observations from the Oklahoma Mesonet reveals, however, that the operational OI system fails to improve both the analysis and the subsequent forecast of soil moisture itself. In addition, the system is not able to correct soil moisture for errors introduced through wrong precipitation in the background forecasts. Biweekly observations from the Illinois Climate Network support these findings. This study confirms the long assumed (but rarely proven) characteristics of analysis schemes using screen-level variables: The observations are efficient in improving the turbulent surface fluxes and consequently the weather forecast on large geographical domains. The quality of the resulting soil moisture profile is often not sufficient for hydrological or agricultural applications.

Abstract

The liquid and frozen hydrological budgets and the surface energy budget from seven subbasins of the Mackenzie River are analyzed using hourly integrals from the operational European Centre for Medium-Range Forecasts model from September 1996 to August 1998. The model budgets give estimates of precipitation (rainfall and snowfall), surface evaporation (of water and snow), runoff, and melt terms in the spring. On a basin scale and monthly timescale, the model precipitation correlates well with observations but has a 40% positive bias. On an annual basis, evaporation has a 60% positive bias. Although the annual runoff for the Mackenzie as a whole is close to the annual stream flow, this condition is not true for the subbasins. In the liquid water budget, nudging of soil water compensates for basin errors in runoff. The model snow budget is not closed because each new snow analysis depends heavily on climatological means. The surface energy balance on the basin scale also is analyzed. Although the model gradients of net radiation probably are realistic, the model evaporation bias means that sensible heat flux is negatively biased, especially in spring.

Abstract

A comparison of clear-sky radiances of the Meteosat window channel with the European Centre for Medium-Range Weather Forecasts (ECMWF) model results is presented, aiming to assess both the model's performance and the quality of the observations. The comparison is made for four periods covering the seasonal cycle and for the Meteosat-7 (Africa and southern Europe) and Meteosat-5 (Middle East and the Indian subcontinent) disks. Results show 1) an underestimation of the diurnal cycle of model brightness temperature in clear-sky conditions with a cool bias during daytime of up to 7–8 K and 2) a much smaller and less widespread warm bias at night. Although such discrepancies are sensitive to surface characteristics (e.g., vegetation type, terrain elevation, and slope), problems in the model surface-to–boundary layer coupling are identified as the most likely model deficiency associated with the underestimation of diurnal amplitudes of skin temperature. A conditional error analysis also reveals strong error stratification with the model cloud cover and with the percent of clear-sky pixels associated with the Meteosat data, suggesting great care should be taken when using Meteosat clear-sky observations, particularly in the ITCZ and adjacent areas.

Abstract

Snow water equivalent and snow extent are key parameters for the earth's energy and water budget. In this study, the current operational snow-depth analysis (2D spatial Cressman interpolation) at the European Centre for Medium-Range Weather Forecasts (ECMWF), which relies on real-time observations of snow depth, the short-range forecast, and snow-depth climatic data, is presented. The operational product is compared with satellite-derived snow cover. It is found that the total area of grid boxes affected by snow is approximately 10% larger in the analysis than in the National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) snow-extent product. The differences are persistent in time and space and cover the entire Northern Hemisphere. They comprise areas with intermittent and/or patchy snow cover, for example, the Tibetan Plateau, the edges of snow fields, and areas with a low density of observations, which are difficult to capture in the current operational analysis. A modified snow analysis is presented, in which the operational NESDIS snow product is incorporated. The current analysis and the revised analysis are compared with high-resolution snow-cover datasets derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and independent ground-based snow-depth observations from the Meteorological Service of Canada. Using the NOAA/NESDIS snow-extent dataset in the operational analysis leads to a more realistic description of the actual snow extent.

Abstract

A new version of the ECMWF land surface parameterization scheme is described. It has four prognostic layers in the soil for temperature and soil moisture, with a free drainage and a zero heat flux condition at the bottom as a boundary condition. The scheme has been extensively tested in stand-alone mode with the help of long observational time series from three different experiments with different climatological regimes: the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment in the United States, Cabauw in the Netherlands, and the Amazonian Rainforest Meteorological Experiment in Brazil. The emphasis is on seasonal timescales because it was felt that the main deficiencies in the old ECMWF land surface scheme were related to its capability of storing precipitation in spring and making it available for evaporation later in the year. It is argued that the stand-alone testing is particularly important, because it allows one to isolate problems in the land surface scheme without having to deal with complicated interactions in the full three-dimensional model.

Abstract

Three different complexity snow schemes implemented in the ECMWF land surface scheme Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) are evaluated within the EC-EARTH climate model. The snow schemes are (i) the original HTESSEL single-bulk-layer snow scheme, (ii) a new snow scheme in operations at ECMWF since September 2009, and (iii) a multilayer version of the previous. In offline site simulations, the multilayer scheme outperforms the single-layer schemes in deep snowpack conditions through its ability to simulate sporadic melting events thanks to the lower thermal inertial of the uppermost layer. Coupled atmosphere–land/snow simulations performed by the EC-EARTH climate model are validated against remote sensed snow cover and surface albedo. The original snow scheme has a systematic early melting linked to an underestimation of surface albedo during spring that was partially reduced with the new snow schemes. A key process to improve the realism of the near-surface atmospheric temperature and at the same time the soil freezing is the thermal insulation of the snowpack (tightly coupled with the accuracy of snow mass and density simulations). The multilayer snow scheme outperforms the single-layer schemes in open deep snowpack (such as prairies or tundra in northern latitudes) and is instead comparable in shallow snowpack conditions. However, the representation of orography in current climate models implies limitations for accurately simulating the snowpack, particularly over complex terrain regions such as the Rockies and the Himalayas.

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.

Abstract

Average surface energy and water budgets, subsurface variables, and atmospheric profiles were computed online with an hourly timescale from the ECMWF reanalysis for five subbasins of the Mississippi River from 1985–93. The results for the Arkansas–Red River basin are discussed on diurnal, 5-day, monthly, seasonal, and interannual timescales, and compared with the observed basin-scale precipitation and streamflow. The model shows the seasonal and interannual variability of precipitation, evaporation, and soil water. The annual range of soil water is typically 100 mm, and the interannual range is somewhat smaller. The model has a significant spinup of about 29% in precipitation from the analysis cycle to a 12–24-h forecast. The spinup of the model “large-scale” precipitation is 39%, double that of the spinup of the model “convective” precipitation of 18%. When compared with 5-day and monthly basin averages of hourly rain gauge observations (corrected for a probable 10% low bias), the precipitation in the reanalysis is low by 20%–25%, while the 12–24-h forecast precipitation is high by about 5%; so the model precipitation estimates the bracket observations. The nudging of soil water in the analysis cycle, based on 0–6-h forecast errors in low-level humidity, plays an important role in the model liquid hydrology. It prevents the downward interannual drift of soil water, associated with a shortfall of precipitation in the analysis cycle, while allowing interannual variations of soil water. However, the nudging appears to be trying to compensate for other errors in the model: such as errors in the diurnal cycle of low-level mixing ratio and in the seasonal cycle of evaporation. Evaporation in the model is probably high in winter, and on an annual basis may have a small high bias in comparison to a basin evaporation estimate derived from observed precipitation and streamflow. An internal inconsistency of 7% in the evaporation term in the model surface energy and subsurface water budgets is also found, dating from an earlier model version. The coupling of soil water in the model to evaporative fraction and the low-level thermodynamics is similar to that observed. The model runoff, which is all deep runoff from the base soil layer, is low by a factor of 2, when compared to observed streamflow on an annual basis. The model diurnal cycle of precipitation has a near-noon maximum, while that observed is late afternoon and evening. This is probably related to the model error in the diurnal cycle of mixing ratio and boundary layer depth. Overall the ECMWF reanalysis gives a valuable description of the surface energy and water balance of the Arkansas–Red River basin on timescales longer than the diurnal.

Abstract

Ocean waves are generated by wind and, as a consequence, there is a considerable transfer of momentum from atmosphere to ocean. This momentum transfer depends, however, on the stage of development of the ocean waves. Ocean waves that are just generated by wind ("young” windsea) are usually steeper and are capable of extracting more momentum from the air flow than older waves that are more gently sloped.

In this paper the consequences are discussed of the sea-state-dependent momentum transfer on the seasonal climate of the European Centre for Medium-Range Weather Forecasts (ECMWF) model. Here 15 simulations of the 1990/91 winter season were performed. Because of the large variability in the extratropics, results of the ensemble mean are presented. They show that the sea-state-dependent momentum transfer has a definite impact on atmospheric and wave climate in both hemispheres.

In certain aspects, there is an improvement in the coupled climate when compared to the analyzed climate. We mention the favorable changes over the Eurasian continent in the mean 500-hPa height field and high-frequency variability. The blocking frequency over the North Pacific has shown an unfavorable reduction, however. The reduction of mean surface wind speed over the Southern Ocean seems favorable in view of the positive error in wind speed in the 10-day ECMWF forecast when verified against the analysis.