scholarly journals Choices in the Verification of S2S Forecasts and Their Implications for Climate Services

2020 ◽  
Vol 148 (10) ◽  
pp. 3995-4008
Author(s):  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
Verónica Torralba ◽  
Nicola Cortesi ◽  
Francisco J. Doblas-Reyes
Keyword(s):  
Skill Score ◽  
Climate Services ◽  
Near Surface ◽  
Weather Forecasts ◽  
Probabilistic Evaluation ◽  
Skill Scores ◽  
Medium Range ◽  
The Impact ◽  
Start Dates

AbstractSubseasonal predictions bridge the gap between medium-range weather forecasts and seasonal climate predictions. This time scale is crucial for operations and planning in many sectors such as energy and agriculture. For users to trust these predictions and efficiently make use of them in decision-making, the quality of predicted near-surface parameters needs to be systematically assessed. However, the method to follow in a probabilistic evaluation of subseasonal predictions is not trivial. This study aims to offer an illustration of the impact that the verification setup might have on the calculation of the skill scores, thus providing some guidelines for subseasonal forecast evaluation. For this, several forecast verification setups to calculate the fair ranked probability skill score for tercile categories have been designed. These setups use different number of samples to compute the fair RPSS as well as different ways to define the climatology, characterized by different time periods to average (week or month). These setups have been tested by evaluating 2-m temperature in ECMWF-Ext-ENS 20-yr hindcasts for all of the initializations in 2016 against the ERA-Interim reanalysis. Then, the implications on skill score values of each of the setups are analyzed. Results show that to obtain a robust skill score several start dates need to be employed. It is also shown that a constant monthly climatology over each calendar month may introduce spurious skill score associated with the seasonal cycle. A weekly climatology bears similar results to a monthly running-window climatology; however, the latter provides a better reference climatology when bias adjustment is applied.

scholarly journals Addressing model error through atmospheric stochastic physical parametrizations: impact on the coupled ECMWF seasonal forecasting system

2014 ◽  
Vol 372 (2018) ◽  
pp. 20130290 ◽  
Author(s):  
Antje Weisheimer ◽  
Susanna Corti ◽  
Tim Palmer ◽  
Frederic Vitart
Keyword(s):  
Time Scales ◽  
Weather Prediction ◽  
Seasonal Forecasting ◽  
Near Surface ◽  
Weather Forecasts ◽  
European Centre ◽  
Medium Range ◽  
Forecasting System ◽  
The Impact ◽  
Stochastically Perturbed

The finite resolution of general circulation models of the coupled atmosphere–ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere–ocean climate system in operational forecast mode, and the latest seasonal forecasting system—System 4—has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981–2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden–Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid-latitude circulation regimes over the Pacific–North America region.

Impact of non-Arctic observations on the AROME-Arctic regional model

2020 ◽  
Author(s):  
Rogerr Randriamampianina
Keyword(s):  
Regional Model ◽  
Satellite Observations ◽  
Lateral Boundary ◽  
Regional Data ◽  
Weather Forecasts ◽  
Lateral Boundary Conditions ◽  
Skill Scores ◽  
Medium Range ◽  
Considerable Impact ◽  
The Impact

<p>In the framework of the Applicate project (https://applicate.eu), ECMWF (European Centre for Medium-Range Weather Forecasts) performed global (Bormann et al. 2019) and Arctic (Lawrence et al. 2019) observing system experiments. Use of the results of these experiments as lateral boundary conditions (LBC) for our regional model opens opportunity to study the following: 1) the impact of observations through regional data assimilation (DA); 2) the impact of observations that are assimilated in a global model through LBC in a regional model; 3) the impact of global loss of observations in a regional model; and 4) the impact of non-Arctic observations in an Arctic regional model.</p><p>In the framework of the Alertness project, we performed experiments for the two special observation periods (SOP) 1 and 2 and found considerable impact (significant for some cases) of both conventional and satellite observations through both regional DA and LBC. So far, the impact of non-Arctic observations on our Arctic regional model AROME-Arctic analyses and forecasts was checked during SOP1 with microwave radiance only. The impact was found to be positive, especially on day-2 forecasts.</p><p>In this presentation, the impact of other non-Arctic observations (conventional and satellite) on our regional model AROME-Arctic will be discussed through different forecast skill scores verification.</p>

scholarly journals Application of φ-IASI to IASI: retrieval products evaluation and radiative transfer consistency

2009 ◽  
Vol 9 (22) ◽  
pp. 8771-8783 ◽  
Author(s):  
G. Masiello ◽  
C. Serio ◽  
A. Carissimo ◽  
G. Grieco ◽  
M. Matricardi
Keyword(s):  
Water Vapour ◽  
Forward Model ◽  
Continuum Absorption ◽  
Weather Forecasts ◽  
Time Profiles ◽  
Spectral Residual ◽  
Atmospheric Sounding ◽  
Medium Range ◽  
Temperature Water

Abstract. Retrieval products for temperature, water vapour and ozone have been obtained from spectral radiances measured by the Infrared Atmospheric Sounding Interferometer flying onboard the first European Meteorological Operational satellite. These products have been used to check the consistency of the forward model and its accuracy and the expected retrieval performance. The study has been carried out using a research-oriented forward-inverse methodology, called φ-IASI, that the authors have specifically developed for the new sounding interferometer. The performance of the forward-inversion strategy has been assessed by comparing the retrieved profiles to profiles of temperature, water vapour and ozone obtained by co-locating in space and time profiles from radiosonde observations and from the European Centre for Medium-Range Weather Forecasts analysis. Spectral residuals have also been computed and analyzed to assess the quality of the forward model. Two versions of the high-resolution transmission molecular absorption database have been used, which mostly differ for ozone absorption line parameters, line and continuum absorption of both CO2 and H2O molecules. Their performance has been assessed by inter-comparing the results, and a consistent improvement in the spectral residual has been found when using the most updated release.

scholarly journals An assessment of the accuracy of the RTTOV fast radiative transfer model using IASI data

2009 ◽  
Vol 9 (2) ◽  
pp. 9491-9535 ◽  
Author(s):  
M. Matricardi
Keyword(s):  
Radiative Transfer ◽  
Regression Coefficients ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Weather Forecasts ◽  
Medium Range ◽  
Forecasting System ◽  
Relative Differences ◽  
Temperature Water

Abstract. IASI measurements of spectral radiances made between the 1 April 2008 and the 15 April 2008 are compared with simulations performed using the RTTOV fast radiative transfer model utilizing regression coefficients based on different line-by-line models. The comparisons are performed within the framework of the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System using fields of temperature, water vapour and ozone obtained from short-range forecasts. Simulations are performed to assess the accuracy of the RTTOV computations and investigate relative differences between the line-by-line models and the quality of the spectroscopic databases on which the RTTOV coefficients are based.

scholarly journals Impact of the sea surface temperature forcing on hindcasts of Madden-Julian Oscillation events using the ECMWF model

2012 ◽  
Vol 9 (4) ◽  
pp. 2535-2559
Author(s):  
E. de Boisséson ◽  
M. A. Balmaseda ◽  
F. Vitart ◽  
K. Mogensen
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Phase Relationship ◽  
Sea Surface ◽  
Madden Julian Oscillation ◽  
Weather Forecasts ◽  
Skill Scores ◽  
The Mean ◽  
Ecmwf Model ◽  
The Impact

Abstract. This paper explores the sensitivity of the prediction of Madden Julian Oscillation (MJO) events to different aspects of the sea surface temperature (SST) in the European Centre for Medium-range Weather Forecasts (ECMWF) model. The impact of temporal resolution of SST on the MJO is first evaluated via a set of monthly hindcast experiments. The experiments are conducted with an atmosphere forced by persisted SST anomalies, monthly and weekly SSTs. Skill scores are clearly degraded when weekly SSTs are replaced by monthly values or persisted anomalies. The new high resolution OSTIA SST daily reanalysis would in principle allow to establish the impact of daily versus weekly SST values on the MJO prediction. It is found however that OSTIA SSTs provide lower skill scores than the weekly product. Further experiments show that this loss of skill cannot be attributed to either the mean state or the daily frequency of OSTIA SSTs. Additional diagnostics show that the phase relationship between OSTIA SSTs and tropical convection is not optimal with repspect to observations. Such result suggests that capturing the correct SST-convection phase relationship is a major challenge for the MJO predictions.

scholarly journals Technical and operational characteristics of GPS radiosounding system in the upper air network of IMD

MAUSAM ◽  
2021 ◽  
Vol 62 (3) ◽  
pp. 403-416
Author(s):  
GAJENDRA KUMAR ◽  
RANJU MADAN ◽  
K.C. SAIKRISHNAN ◽  
S.K. KUNDU ◽  
P.K. JAIN
Keyword(s):  
Global Positioning System ◽  
Weather Forecasting ◽  
Quality Change ◽  
Weather Forecasts ◽  
National Centre ◽  
Operational Characteristics ◽  
Global Positioning ◽  
Medium Range ◽  
Black List

In recent years, the upper air radiosounding system based on Global Positioning System (GPS) is used as an effective method. GPS receiving device in a Radiosonde improves observation accuracy, allowing simplification of ground equipment. To get improved quality of upper air data, ten stations have been upgraded with new upper air systems based on GPS. This paper describes the upper air radiosounding system that adopts the GPS. After the introduction of GPS Radiosonde in the network at 10 places, data quality has improved substantially at these stations, which has been validated by National Centre for Medium Range Weather Forecasting (NCMRWF) and European Centre for Medium-Range Weather Forecasts (ECMWF). In all cases the quality change has been remarkable and as a result black list tag is removed by ECMWF for the Indian GPS stations.

scholarly journals Ensemble Model of Precipitation Change Over Indonesia Caused by El Nino Modoki

2021 ◽  
Vol 4 (1) ◽  
pp. 72
Author(s):  
Ida Bagus Mandhara Brasika
Keyword(s):  
El Niño ◽  
El Nino ◽  
Skill Score ◽  
Ensemble Model ◽  
Single Model ◽  
Model Quality ◽  
El Niño Modoki ◽  
Squared Error ◽  
The Impact

The aim of this research is to understand the impact of El Nino Modoki into Indonesian precipitation and how ensemble models can simulate this changing. Ensemble model has been recognized as a method to improve the quality of model and/or prediction of climate phenomenon. Every model has their own algorithm which causes strength and weakness in many aspects. Ensemble will improve the quality of simulation while reducing the weakness. However, the combination of models for ensembles is differ for each event and/or location. Here we utilize the Squared Error Skill Score (SESS) method to examine each model quality and to compare the ensemble model with the single model. El Nino Modoki is a unique phenomenon. It remains debatable amongst scientists, many features of this phenomenon are unfold. So, it is important to find out how El Nino Modoki has changed precipitation over Indonesia. To verify the changing precipitation, the composite of precipitation on El Nino Modoki Year is divided with the composite of all years. Last, validating ensemble model with Satellite-gauge precipitation dataset. El Nino Modoki decreases precipitation in most of Indonesian regions. The ensemble, while statistically promising, has failed to simulate precipitation in some region.

scholarly journals Sensitivity, Structure, and Dynamics of Singular Vectors Associated with Hurricane Helene (2006)

2012 ◽  
Vol 69 (2) ◽  
pp. 675-694 ◽  
Author(s):  
Simon T. K. Lang ◽  
Sarah C. Jones ◽  
Martin Leutbecher ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds
Keyword(s):  
Three Dimensional ◽  
Growth Dynamics ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Singular Vectors ◽  
Medium Range ◽  
Flow Features ◽  
Forecasting System ◽  
Diabatic Processes ◽  
The Impact

Abstract The sensitivity of singular vectors (SVs) associated with Hurricane Helene (2006) to resolution and diabatic processes is investigated. Furthermore, the dynamics of their growth are analyzed. The SVs are calculated using the tangent linear and adjoint model of the integrated forecasting system (IFS) of the European Centre for Medium-Range Weather Forecasts with a spatial resolution up to TL255 (~80 km) and 48-h optimization time. The TL255 moist (diabatic) SVs possess a three-dimensional spiral structure with significant horizontal and vertical upshear tilt within the tropical cyclone (TC). Also, their amplitude is larger than that of dry and lower-resolution SVs closer to the center of Helene. Both higher resolution and diabatic processes result in stronger growth being associated with the TC compared to other flow features. The growth of the SVs in the vicinity of Helene is associated with baroclinic and barotropic mechanisms. The combined effect of higher resolution and diabatic processes leads to significant differences of the SV structure and growth dynamics within the core and in the vicinity of the TC. If used to initialize ensemble forecasts with the IFS, the higher-resolution moist SVs cause larger spread of the wind speed, track, and intensity of Helene than their lower-resolution or dry counterparts. They affect the outflow of the TC more strongly, resulting in a larger downstream impact during recurvature. Increasing the resolution or including diabatic effects degrades the linearity of the SVs. While the impact of diabatic effects on the linearity is small at low resolution, it becomes large at high resolution.

Impact of a multi-layer snow scheme on near-surface weather forecasts

2020 ◽  
Author(s):  
Gabriele Arduini ◽  
Gianpaolo Balsamo ◽  
Emanuel Dutra ◽  
Jonathan J. Day ◽  
Irina Sandu ◽  
...  
Keyword(s):  
Snow Depth ◽  
Positive Impact ◽  
Radiative Properties ◽  
Polar Regions ◽  
Snow Layer ◽  
Near Surface ◽  
Weather Forecasts ◽  
Surface Weather ◽  
Weather Parameters ◽  
The Impact

<p>Snow cover properties have a large impact on the partitioning of surface energy fluxes and thereby on near-surface weather parameters. Snow schemes of intermediate complexity have been widely used for hydrological and climate studies, whereas their impact on typical weather forecast time-scales has received less attention. A new multi-layer snow scheme is implemented in the ECMWF Integrated Forecasting System (IFS) and its impact on snow and 2-metre temperature forecasts is evaluated. The new snow scheme is evaluated offline at well instrumented field sites and compared to the current single-layer scheme. The new scheme largely improves the representation of snow depth for most of the sites considered, reducing the root-mean-square-error averaged over all sites by more than 30%. The improvements are due to a better description of snow density in thick and cold snowpacks, but also due to an improved representation of sporadic melting episodes thanks to the inclusion of a thin top snow layer with a low thermal inertia. The evaluation of coupled 10-day weather forecasts shows an improved representation of snow depth at all lead times, demonstrating a positive impact at the global scale. Regarding the impact on weather parameters, the use of the multi-layer snow scheme improves the simulated daily minimum 2-metre temperature, by decreasing the positive bias and improving the amplitude of the diurnal cycle over snow-covered regions. The analysis indicates that a more realistic representation of snow processes is essential to improve the simulation of low temperature extremes at high latitudes, where snow is a key component of the climate system. The work also highlights that other errors in polar regions still need to be addressed, such as cloud radiative properties, despite the improvements in the responsiveness of snow-covered surfaces with respect to the atmospheric forcing.</p>

scholarly journals Representation of model error in a convective-scale ensemble prediction system

2014 ◽  
Vol 21 (1) ◽  
pp. 19-39 ◽  
Author(s):  
L. H. Baker ◽  
A. C. Rudd ◽  
S. Migliorini ◽  
R. N. Bannister
Keyword(s):  
Model Error ◽  
Ensemble Prediction ◽  
Initial Condition ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
Near Surface ◽  
Skill Scores ◽  
The Uk ◽  
Parameter Values ◽  
The Impact

Abstract. In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office's 24-member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model's parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits "jumpiness" in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.

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