European Centre For Medium-Range Weather Forecasts Operational Analyses Research Articles

WIRA-C: a compact 142-GHz-radiometer for continuous middle-atmospheric wind measurements

Abstract. Ground-based microwave wind radiometry provides a method to measure horizontal wind speeds at altitudes between 35 and 75 km as has been shown by various previous studies. No other method is capable of continuously delivering wind measurements in this altitude region. As opposed to lidar systems, microwave radiometers operate autonomously and independent of daylight and clouds.In this paper, we present the WIRA-C (Wind Radiometer for Campaigns) instrument that observes the 142.17504 GHz rotational transition line of ozone with a high spectral resolution using a low noise single side band heterodyne receiver. Because the emitting molecules are drifting with the wind, the line is Doppler shifted. Together with the pressure broadening effect, this allows the retrieval of altitude resolved wind profiles.The novel WIRA-C instrument represents the newest development in microwave wind radiometry and implements many improvements over its predecessor, the WIRA instrument. The main improvements include the compact structure, lower noise and an advanced retrieval setup. This paper describes the instrument and the data processing with a focus on the retrieval that takes into account a three-dimensional atmosphere and has never been used in ground-based radiometry before. The retrieval yields profiles of horizontal wind speeds with a 12 h time resolution and a vertical resolution of 10 km for zonal and 10 to 15 km for meridional wind speeds. We give an error estimate that accounts for the thermal noise on the measured spectra and additionally estimate systematic errors using Monte Carlo methods.WIRA-C has been continuously measuring horizontal wind speeds for 1 year at the Maïdo observatory on Réunion (21.4° S, 55.9° E). We present the time series of this campaign and compare our measurements to model data from the European Centre for Medium-range Weather Forecasts (ECMWF) and coincident measurements of the co-located Rayleigh–Mie Doppler wind lidar. We find a good agreement between our measurements and the ECMWF operational analysis for the time series, where many features are present in both datasets. The wind profiles of the coincident WIRA-C and lidar observations are consistent and agree within their respective uncertainties for the lidar measurements with long integration times.

Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses

Abstract. The accuracy of trajectory calculations performed by Lagrangian particle dispersion models (LPDMs) depends on various factors. The optimization of numerical integration schemes used to solve the trajectory equation helps to maximize the computational efficiency of large-scale LPDM simulations. We analyzed global truncation errors of six explicit integration schemes of the Runge–Kutta family, which we implemented in the Massive-Parallel Trajectory Calculations (MPTRAC) advection module. The simulations were driven by wind fields from operational analysis and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279L137 spatial resolution and 3 h temporal sampling. We defined separate test cases for 15 distinct regions of the atmosphere, covering the polar regions, the midlatitudes, and the tropics in the free troposphere, in the upper troposphere and lower stratosphere (UT/LS) region, and in the middle stratosphere. In total, more than 5000 different transport simulations were performed, covering the months of January, April, July, and October for the years 2014 and 2015. We quantified the accuracy of the trajectories by calculating transport deviations with respect to reference simulations using a fourth-order Runge–Kutta integration scheme with a sufficiently fine time step. Transport deviations were assessed with respect to error limits based on turbulent diffusion. Independent of the numerical scheme, the global truncation errors vary significantly between the different regions. Horizontal transport deviations in the stratosphere are typically an order of magnitude smaller compared with the free troposphere. We found that the truncation errors of the six numerical schemes fall into three distinct groups, which mostly depend on the numerical order of the scheme. Schemes of the same order differ little in accuracy, but some methods need less computational time, which gives them an advantage in efficiency. The selection of the integration scheme and the appropriate time step should possibly take into account the typical altitude ranges as well as the total length of the simulations to achieve the most efficient simulations. However, trying to summarize, we recommend the third-order Runge–Kutta method with a time step of 170 s or the midpoint scheme with a time step of 100 s for efficient simulations of up to 10 days of simulation time for the specific ECMWF high-resolution data set considered in this study. Purely stratospheric simulations can use significantly larger time steps of 800 and 1100 s for the midpoint scheme and the third-order Runge–Kutta method, respectively.

The Impact of Atmospheric Modeling Errors on GRACE Estimates of Mass Loss in Greenland and Antarctica

AbstractSystematic errors in Gravity Recovery and Climate Experiment (GRACE) monthly mass estimates over the Greenland and Antarctic ice sheets can originate from low‐frequency biases in the European Centre for Medium‐Range Weather Forecasts (ECMWF) Operational Analysis model, the atmospheric component of the Atmospheric and Ocean Dealising Level‐1B (AOD1B) product used to forward model atmospheric and ocean gravity signals in GRACE processing. These biases are revealed in differences in surface pressure between the ECMWF Operational Analysis model, state‐of‐the‐art reanalyses, and in situ surface pressure measurements. While some of these errors are attributable to well‐understood discrete model changes and have published corrections, we examine errors these corrections do not address. We compare multiple models and in situ data in Antarctica and Greenland to determine which models have the most skill relative to monthly averages of the dealiasing model. We also evaluate linear combinations of these models and synthetic pressure fields generated from direct interpolation of pressure observations. These models consistently reveal drifts in the dealiasing model that cause the acceleration of Antarctica's mass loss between April 2002 and August 2016 to be underestimated by approximately 4 Gt yr−2. We find similar results after attempting to solve the inverse problem, recovering pressure biases directly from the GRACE Jet Propulsion Laboratory RL05.1 M mascon solutions. Over Greenland, we find a 2 Gt yr−1 bias in mass trend. While our analysis focuses on errors in Release 05 of AOD1B, we also evaluate the new AOD1B RL06 product. We find that this new product mitigates some of the aforementioned biases.

Tropopause sharpening by data assimilation

AbstractData assimilation was recently suggested to smooth out the sharp gradients that characterize the tropopause inversion layer (TIL) in systems that did not assimilate TIL‐resolving observations. We investigate whether this effect is present in the ERA‐Interim reanalysis and the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational forecast system (which assimilate high‐resolution observations) by analyzing the 4D‐Var increments and how the TIL is represented in their data assimilation systems. For comparison, we also diagnose the TIL from high‐resolution GPS radio occultation temperature profiles from the COSMIC satellite mission, degraded to the same vertical resolution as ERA‐Interim and ECMWF operational analyses. Our results show that more recent reanalysis and forecast systems improve the representation of the TIL, updating the earlier hypothesis. However, the TIL in ERA‐Interim and ECMWF operational analyses is still weaker and farther away from the tropopause than GPS radio occultation observations of the same vertical resolution.

A perspective on the fundamental quality of GPS radio occultation data

Abstract. Radio occultation (RO) is a promising source of observation for weather and climate applications. However, the uncertainties arising from imperfect retrieval algorithms may weaken the overall confidence in the data and discourage their use. As an alternative approach of assessing the quality of RO data while avoiding the nuisance of retrieval errors, this study proposes to use minimally processed data (measurement) instead of derived RO data. This study compares measured phase paths with their model counterparts, simulated with an effective ray tracer for which the refractive indices along the complete ray path linking the transmitter and the receiver are realistically specified. The comparison of phase measurements with the European Centre for Medium-Range Weather Forecasts (ECMWF) data made in the observation space shows that the RO measurements are of sufficient accuracy to uncover regional-scale systematic errors in ECMWF's operational analysis and the 45-year reanalysis (ERA40), and to clearly depict the error growth of short-term ERA40 forecasts. In the southern hemispheric stratosphere, in particular, the RO measurements served as a robust reference against which both of the two analyses were significantly biased in opposite directions even though they were produced by the same center using virtually the same set of data. The measurement and ECMWF analyses showed a close agreement in the standard deviation except for the regions and heights that the quality of the ECMWF data is controversial. This confirms the high precision of RO measurements and also indicates that the main problem of the ECMWF analyses lies in their systematic error.

Optimization of NWP model closure parameters using total energy norm of forecast error as a target

Abstract. We explore the use of dry total energy norm in improving numerical weather prediction (NWP) model forecast skill. The Ensemble Prediction and Parameter Estimation System (EPPES) is utilized to estimate ECHAM5 atmospheric GCM (global circulation models) closure parameters related to clouds and precipitation. The target criterion in the optimization is the dry total energy norm of 3-day forecast error with respect to the ECMWF (European Centre for Medium-Range Weather Forecasts) operational analyses. The results are summarized as follows: (i) forecast error growth in terms of energy norm is slower in the optimized than in the default model up to day 10 forecasts (and beyond), (ii) headline forecast skill scores are improved in the training sample as well as in independent samples, (iii) the decrease of the forecast error energy norm at day three is mainly because of smaller kinetic energy error in the tropics, and (iv) this impact is spread into midlatitudes at longer ranges and appears as a smaller forecast error of potential energy. The interpretation of these results is that the parameter optimization has reduced the model error so that the forecasts remain longer in the vicinity of the analyzed state.

Comparisons of atmospheric data and reduction methods for the analysis of satellite gravimetry observations

The Gravity Recovery and Climate Experiment (GRACE) derived gravity solutions contain errors mostly due to instrument noise, anisotropic spatial sampling, and temporal aliasing. Improving the quality of satellite gravimetry observations, in terms of using more sensitive sensors and/or increasing the spatial isotropy, has been discussed in the context of the designed scenarios of future satellite gravimetry missions. Temporal aliasing caused by incomplete reducing of background models, however, is still a factor that affects the quality of the gravity field solutions. This paper specifically explores the possible physical, geometrical, and numerical modifications of the three‒dimensional (3‒D) integration approach to eliminate the high‒frequency atmospheric effects from satellite gravimetry observations. The new modified 3‒D approach is then applied to compute new sets of atmospheric dealiasing products, using atmospheric fields from the European Centre for Medium‒Range Weather Forecasts (ECMWF) operational analysis model and ERA‒Interim reanalysis. Impacts of modifications are compared to the prelaunch baseline and the current error‒curve of GRACE as well as an error‒curve of a Bender‒type multiorbit satellite configuration. Specifically, we found that using latitude‒dependent radius, latitude‒ and altitude‒dependent gravity accelerations along with numerical modifications have a considerable impact on the 3‒D integral. Comparing the new products to those of GRACE Atmosphere and Ocean Dealiasing level‒1B shows a nonnegligible difference with respect to the prelaunch baseline of GRACE and a possible Bender‒type mission up to harmonic degrees 13 and 50, respectively. A big difference is also found between the derived dealiasing products from ECMWF operational analysis and ERA‒Interim indicating the importance of input parameters on the final atmospheric dealiasing products.

NWP model forecast skill optimization via closure parameter variations

AbstractWe apply a recently developed method, the Ensemble Prediction and Parameter Estimation System (EPPES), to demonstrate how numerical weather prediction (NWP) model closure parameters can be optimized. As proof of concept, we tune the medium‐range forecast skill of the ECMWF model HAMburg version (ECHAM5) atmospheric general circulation model using an ensemble prediction system (EPS) emulator. Initial state uncertainty is represented in the EPS emulator by applying the initial state perturbations generated at the European Centre for Medium‐range Weather Forecasts (ECMWF). Model uncertainty is represented in the emulator via parameter variations at the initial time. We vary four closure parameters related to parametrizations of subgrid‐scale physical processes of clouds and precipitation. With this set‐up, we generate ensembles of 10‐day global forecasts with the ECHAM5 model at T42L31 resolution twice a day over a period of three months. The cost function in the optimization is formulated in terms of standard forecast skill scores, verified against the ECMWF operational analyses. A summarizing conclusion of the experiments is that the EPPES method is able to find ECHAM5 model closure parameter values that correspond to smaller values of the cost function. The forecast skill score improvements verify positively in dependent and independent samples. The main reason is the reduced temperature bias in the tropical lower troposphere. Moreover, the optimization improved the top‐of‐atmosphere radiation flux climatology of the ECHAM5 model, as verified against the Clouds and the Earth's Radiant Energy System (CERES) radiation data over a 6‐year period, while the simulated tropical cloud cover was reduced, thereby increasing a negative bias as verified against the International Satellite Cloud Climatology Project (ISCCP) data.

Properties of the average distribution of equatorial Kelvin waves investigated with the GROGRAT ray tracer

Abstract. Kelvin waves excited by tropospheric convection are considered to be one of the main drivers of the stratospheric quasi-biennial oscillation (QBO). In this paper we combine several measured data sets with the Gravity wave Regional Or Global RAy Tracer (GROGRAT) in order to study the forcing and vertical propagation of Kelvin waves. Launch distributions for the ray tracer at tropospheric altitudes are deduced from space-time spectra of European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses, as well as outgoing longwave radiation (OLR) and rainfall data measured by the Tropical Rainfall Measuring Mission (TRMM) satellite. The resulting stratospheric Kelvin wave spectra are compared to ECMWF operational analyses and temperature measurements of the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite instrument. Questions addressed are: the relative importance of source variability versus wind modulation, the relative importance of radiative and turbulent damping versus wave breaking, and the minimum altitude where freely propagating waves dominate the spectrum.

Analysis of planetary boundary layer fluxes and land‐atmosphere coupling in the regional climate model CLM

Land‐atmosphere interactions and associated boundary layer processes are crucial elements of the climate system and play a major role in several feedback processes, in particular for extreme events. In this article, we provide a detailed validation of land surface processes and land‐atmosphere interactions in the climate version of the Lokal Modell (CLM), a regional climate model that has been recently developed and is now used by a wide research community. For the evaluation of the model, we use observations from the FLUXNET network and meteorological data. Moreover, we also compare the performance of the CLM with that of its driving data set, the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational analysis, and simulations of the Inter‐Continental Transferability Study (ICTS). The results show that most of the land‐atmosphere coupling characteristics are consistent in CLM and the observations. Nonetheless, the analysis also allows identification of specific weaknesses of the CLM such as an underestimation of the incoming surface shortwave radiation due to cloud cover overestimation, leading to an underestimation of the sensible heat flux. The comparisons with the ECMWF operational analysis and the ICTS models suggest, however, that all models have biases of comparable magnitude. This study demonstrates the utility of flux observations for diagnosing biases in land‐atmosphere exchanges and interactions in current climate models and highlights perspectives for our improved understanding of the relevant processes.

Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA) against CERES Tropical Deep Convective Cloud Object Observations

Abstract This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis (EOA) and 40-yr ECMWF Re-Analysis (ERA-40) are validated against those obtained from Earth Observing System satellite cloud object data for the January–August 1998 and March 2000 periods. These properties include the ice water path (IWP), cloud-top height and temperature, cloud optical depth, and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud object type for the January–August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud-top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The less sophisticated data assimilation technique and the lack of snow water content information in ERA-40, not the larger horizontal grid spacing, are also responsible for the disagreements with observed pdfs of cloud physical properties, although the detection rates of cloud object occurrence are improved for small-size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights on grid-cell dynamics.

A review of the temporal and spatial variability of Arctic and Antarctic atmospheric circulation based upon ERA-40

A survey of the spatial and temporal behavior of the atmospheric general circulation as it relates to both polar regions is presented. The review is based on the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year reanalysis (ERA-40), updated using ECMWF operational analyses. The analysis spans 1960–2005 in the Northern Hemisphere, but is restricted to 1979–2005 in the Southern Hemisphere because of difficulties experienced by ERA-40 prior to the modern satellite era. The seasonal cycle of atmospheric circulation is illustrated by focusing on winter and summer. The huge circulation contrasts between the land-dominated Northern Hemisphere and the ocean-dominated Southern Hemisphere stand out. The intensification of the North Atlantic Oscillation/Northern Annular Mode and the Southern Annular Mode in DJF is highlighted and likely due to warming of the tropical Indian Ocean. The Arctic frontal zone during northern summer and the semi-annual oscillation throughout the year in the Southern Hemisphere are prominent features of the high latitude circulation in the respective hemispheres. Rotated principal component analysis (RPCA) is used to describe the primary modes of temporal variability affecting both polar regions, especially the links with the tropical forcing. The North Atlantic Oscillation is a key modulator of the atmospheric circulation in the North Atlantic sector, especially in winter, and is the dominant control on the moisture transport into the Arctic Basin. The Pacific-South American teleconnection patterns are primary factors in the high southern latitude circulation variability throughout the year, especially in the Pacific sector of Antarctica where the majority of moisture transport into the continent occurs.

Anomalies in the tropics associated with the heavy rainfall in east asia during the summer of 1998

The summer of 1998 was characterised by a severe flood in East Asia. The possible linkages were examined among the anomalies in the tropics that may be associated with the severe flood. The anomalies of 1998 are obtained by removing the climatology, which is the average of the ECMWF (European Centre for Medium Range Weather Forecasts) Re—Analysis (ERA) data over 15 years from 1979 to 1993, from the corresponding fields of 1998, which are obtained from the ECMWF operational analyses. In comparison to the results of Nitta (1990), it was found that there are considerable similarities in the atmospheric circulation anomalies between the summers of 1998 and 1988, in the tropics as well as in middle—high latitudes. It was shown that the atmospheric convection is slightly suppressed over the tropical western Pacific. In general, the suppressed convection corresponds to a negative anomaly of SST in the warm pool region. In the summers of 1998 and 1988, however, there are positive anomalies of SSTs in the tropical western Pacific, corresponding to the suppressed convection over there. This slightly suppressed convection may not provide a viable forcing mechanism for the severe flood in East Asia. It was postulated that the zonal wind anomalies in the tropics, in addition to the atmospheric convection over the tropical western Pacific, influence the position and intensity of the North Pacific subtropical high. In both summers of 1998 and 1988, while the stronger convection occurs over the warmer tropical Indian Ocean, the suppressed convection corresponds to the positive anomalies of SSTs in the tropical western Pacific. A possible explanation was given for the broken relationship between SSTs and OLR, (Outgoing Longwave Radiation) by analyzing the large—scale atmospheric circulation anomalies in the tropics. The heat fluxes at the surface in the warm pool of the tropical western Pacific and tropical Indian Ocean were also examined by using the ERA–15 data. To avoid the inconsistency between the ERA–15 and the operational analyses, the anomalies of the heat fluxes at the surface in the warm pool region in the summer of 1988, instead of the summer of 1998, were examined. The anomalous latent heat flux and the net solar radiation flux are the main reason for the positive anomalies of SSTs in the tropical Indian Ocean and in the tropical western Pacific, respectively. The suppressed convection over the tropical western Pacific allows more solar radiation fluxes downward at the surface, which would increase the SSTs.

ECMWF Analyses and Reanalyses Depiction of ENSO Signal in Antarctic Precipitation*

The El Nino-Southern Oscillation (ENSO) signal in Antarctic precipitation is evaluated using European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses and ECMWF 15-yr (1979-93) reanalyses. Operational and reanalysis datasets indicate that the ENSO teleconnection with Antarctic precipitation is man- ifested through a close positive correlation between the Southern Oscillation index and West Antarctic sector (758-908S, 1208W-1808) precipitation from the early 1980s to 1990, and a close negative correlation after 1990. However, a comparison between the operational analyses and reanalyses shows significant differences in net precipitation (P 2 E) due to contrasts in the mean component of moisture flux convergence into the West Antarctic sector. These contrasts are primarily due to the mean winds, which differ significantly between the operational analyses and the reanalyses for the most reliable period of overlap (1985-93). Some of the differences in flow pattern are attributed to an error in the reanalysis assimilation of Vostok station data that suppresses the geopotential heights over East Antarctica. Reanalysis geopotential heights are also suppressed over the Southern Ocean, where there is a known cold bias below 300 hPa. Deficiencies in ECMWF reanalyses result in a weaker ENSO signal in Antarctic precipitation and cause them to miss the significant upward trend in precipitation found in recent operational analyses. Ice-core analyses reflect both an upward trend in ice accumulation and the ENSO teleconnection correlation pattern seen in the operational analyses. This study confirms the results of a previous study using ECMWF operational analyses that was the first to find a strong correlation pattern between the moisture budget over the West Antarctic sector and the Southern Oscillation index.

Soil‐moisture nudging experiments with a single‐column version of the ECMWF model

AbstractThe soil‐moisture nudging technique suggests using model forecast errors in near‐surface air temperature and relative humidity to re‐initialize (update) soil moisture in atmospheric models. This study investigates the application of soil‐moisture nudging using a single‐column version of the European Centre for Medium‐Range Weather Forecasts (ECMWF) model. the model was applied at 16 sites selected to sample a range of climates and land covers across the globe, with atmospheric forcing taken from the ECMWF operational analysis for 15 June 1994 and 15 December 1994. When observation errors are set to zero, the Optimal Interpolation technique for deriving estimates of nudging coefficients shows computational instability because strong correlation between near‐surface temperature and near‐surface relative humidity forecast errors makes the coefficient matrix of the linear equations ill‐posed. Therefore, Principal Component Analysis (PCA) is used as a pre‐processor to identify the independent and dependent components of temperature and relative humidity errors. With PCA, the soilmoisture nudging coefficients appropriate to the dominant principal component become stable and effective for correcting soil moisture within days. Such coefficients, when derived for the northern hemisphere summer over the 16 sites, are sufficiently consistent to propose using their all‐site, daily‐average values in a globally applicable soil‐moisture analysis scheme. Tests of this method at the First ISLSCP (International Satellite Land Surface Climatology Program) Field Experiment (FIFE) site confirm that soil‐moisture nudging can provide good estimates of near‐surface weather variables and surface fluxes in a numerical weather prediction (NWP) model which gives poor simulation of precipitation (thereby poor soil moisture). However, the PCA method is unable to give an accurate determination of the location of the soil moisture within soil layers that are accessible to the atmosphere. Further, these tests show that, if the NWP model has good simulation of precipitation but poor simulation of surface radiation, soil‐moisture nudging could wrongly vary the soil moisture so as to provide good estimates of the surface sensible‐heat flux, but poor estimates of surface latent‐heat flux. an approach to distinguish error sources from surface radiation and soil moisture is necessary for further improvement.