Configuration and hindcast quality assessment of a brazilian global sub‐seasonal prediction system

This paper presents the Center for Weather Forecast and Climate Studies (CPTEC) developments for configuring a global sub-seasonal prediction system and assessing its ability in producing retrospective predictions (hindcasts) for meteorological conditions of the following 4 weeks. Six Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) configurations were tested in terms of vertical resolution, deep convection and boundary layer parameterizations, as well as soil moisture initialization. The aim was to identify the configuration with best performance when predicting weekly accumulate precipitation, weekly mean 2-meter temperature (T2M) and the Madden and Julian Oscillation (MJO) daily evolution. Hindcasts assessment was performed for 12 extended austral summers (November to March - 1999/2000 to 2010/2011) with two start dates for each month for the six configurations and two ensemble approaches. The first approach, referred to as Multiple Configurations Ensemble (MCEN), was formed of one ensemble member from each of the six configurations. The second, referred to as Initial Condition Ensemble (ICEN), was composed of six ensemble members produced with the chosen configuration as the best using an Empirical Orthogonal Function (EOF) perturbation methodology. The chosen configuration presented high correlation and low root mean squared error (RMSE) for precipitation and T2M anomaly predictions at the first week and these indices degraded as lead time increased, maintaining moderate performance up to week 4 over the tropical Pacific and northern South America. For MJO predictions, this configuration crossed the 0.5 bivariate correlation threshold in 18 days. The ensemble approaches improved the correlation and RMSE of precipitation and T2M anomalies. ICEN improved precipitation and T2M predictions performance over eastern South America at week 3 and over northern South America at week 4. Improvements were also noticed for MJO predictions. The time to cross the above mentioned threshold increased to 21 days for MCEN and to 20 days for ICEN

Evaluation of climate simulations produced with the Brazilian Global Atmospheric Model version 1.2

This paper presents an evaluation of climate simulations produced by the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) of the Center for Weather Forecast and Climate Studies (CPTEC). The model was run over the 1975-2017 period at two spatial resolutions, corresponding to ~180 and ~100 km, both with 42 vertical levels, following most of the Atmospheric Model Intercomparison Project (AMIP) protocol. In this protocol, observed sea surface temperatures (SSTs) are used as boundary conditions for the atmospheric model. Four ensemble members were run for each of the two resolutions. A series of diagnostics was computed for assessing the model's ability to represent the top of the atmosphere (TOA) radiation, atmospheric temperature, circulation and precipitation climatological features. The representation of precipitation interannual variability, El Niño-Southern Oscillation (ENSO) precipitation teleconnections, the Madden and Julian Oscillation (MJO) and daily precipitation characteristics was also assessed. The model at both resolutions reproduced many observed temperature, atmospheric circulation and precipitation climatological features, despite several identified biases. The model atmosphere was found to be more transparent than the observations, leading to misrepresentation of cloud-radiation interactions. The net cloud radiative forcing, which produces a cooling effect on the global mean climate at the TOA, was well represented by the model. This was found to be due to the compensation between both weaker longwave cloud radiative forcing (LWCRF) and shortwave cloud radiative forcing (SWCRF) in the model compared to the observations. The model capability to represent inter-annual precipitation variability at both resolutions was found to be linked to the adequate representation of ENSO teleconnections. However, the model produced weaker than observed convective activity associated with the MJO. Light daily precipitation over the southeast of South America and other climatologically similar regions was diagnosed to be overestimated, and heavy daily precipitation underestimated by the model. Increasing spatial resolution helped to slightly reduce some of the diagnosed biases. The performed evaluation identified model aspects that need to be improved. These include the representation of polar continental surface and sea ice albedo, stratospheric ozone, low marine clouds, and daily precipitation features, which were found to be larger and last longer than the observed features

A perspective for advancing climate prediction services in Brazil

The Climate Science for Service Partnership Brazil (CSSP-Brazil) project provides Brazil and UK partners the opportunity to address important challenges faced by the climate modeling community, including the need to develop subseasonal and seasonal prediction and climate projection services. This paper provides an overview of the climate modeling and prediction research conducted through CSSP-Brazil within the context of a framework to advance climate prediction services in Brazil that includes a research-to-services (R2S) and a services-to-research (S2R) feedback pathway. The paper also highlights plans to advance scientific understanding and capability to produce beneficial climate knowledge and new products to improve climate prediction services to support decisions in various industries in Brazil. Policy-relevant outcomes from climate modeling and prediction exercises illustrated in this paper include supporting stakeholders with climate information provided from weeks to months ahead for (a) improving water management strategies for human consumption, navigation, and agricultural and electricity production; (b) defining crop variety and calendars for food production; and (c) diversifying energy production with alternatives to hydropower

Analise da capacidade do modelo global operacional do CPTEC/COLA em simular a evolucao de ciclogenese de meso-escala usando alta resolucao: estudo de caso

It is analysed the performance of a high resolution version of the operational CPTEC/COLA (T170L28) global model in simulating the mesoscale cyclogenese over the Southest Brazil and adjoining sea. The model is run with two kinds of deep convection: Kuo, modified by Anthes, and Relaxed Arakawa-Schubert. It is selected a case study during the period of 13 to 15 April 2000, in which the mesoscale cyclone becames very strong over the warmer sea-water at the coast of Rio Grande do Sul state. The Kuo scheme seems to be the better to simulate the trajectory of the cyclone, the diabatic heating and the surface winds in high resolution than in the lower (T062L28), while the relaxed Arakawa-Schubert scheme altough give good results for the magnitude of the surface winds, the trajectory and the diabatic heating is not very well simulated even for high resolution.Pages: 3514-352

Capacidade do modelo global operacional do CPTEC/COLA T062L28 em simular a evolucao de ciclogenese de meso-escala: estudo de caso

It is analyzed the performance of the operational CPTEC/COLA T062L28 global model in simulating the mesoscale cyclogenese over the Southeast Brazil and adjoining sea. The model is run with two kinds of deep convection: Kuo, modified by Anthes, and Relaxed Arakawa-Schubert. It is selected a case study during the period of 13 to 15 April 2000, in which the mesoscale cyclone becomes very strong over the warmer sea-water at the coast of Rio Grande do Sul state. The Kuo scheme seems to be the better to simulate the trajectory of the cyclone and the diabatic heating and the relaxed Arakawa-Schubert scheme shows better results for the magnitude of the surface winds.Pages: 3608-361

O sistema de previsao de tempo global por ensemble do CPTEC

Lorenz (1963,1965,1969) observed that atmospheric equations are sensitive to initial conditions, in other words they are chaotic. The ensemble weather prediction was originated from this new conception of the atmosphere since the initial conditions used for models have intrinsic uncertainties. Basically, the ensemble weather prediction consists to produce perturbed initial conditions and to run for several times the same model from this perturbed initial conditions. In October 2001, the Center for Weather Forecast and Climate Studies (CPTEC) started the operational ensemble weather forecasting. In this paper the CPTEC ensemble weather prediction system, the metodology for construction of perturbed initial conditions and some products that are being generated from this system are shown.Pages: 3341-335

Radiancias no Hemisferio Sul a partir de um modelo de transferencia radiativa

The radiance information is obtained from TIROS Operational Vertical Sounder (TOVS), that gives this information for the area where the satellite is passing, and in the South Hemisphere it passes only two times a day, and the area of the information is very limited. This is a problem for assimilation because we need the values of radiance for all the area we are going to do the prediction. The fast model for radiative transference with the consideration of the effects of clouds can give information of radiance for all area under interest. These values can be used for retrievals or for to direct assimilation in the model Numerical Weather Prediction. We showed some fields of radiance for two channels obtained with the fast model of radiative transference

Experiments with EOF-Based perturbation method to ensemble weather forecasting in middle latitudes

The atmosphere is an example of system that presents sensitivity to the initial conditions. The importance of the initial conditions for the numerical simulation errors is explained by the theory known as chaos. Briefly, the chaos is related to the sensitivity that some non-linear dynamic systems present to the initial conditions as they evolve in the time, i.e. slightly different initial conditions may produce remarkable distinct solutions. Thus, still that model was perfect, as the real initial state of the atmosphere is not completely known, there are inevitably errors in the model analysis that will grow up with the integration time, leading to reduction of forecast quality and maintaining the impossibility of evaluate the future atmospheric conditions indefinitely. The ensemble weather forecasting approach represents a way to consider these aspects in the atmosphere prediction. The ensemble weather forecasting started operationally at the Center for Weather Forecast and Climate Studies (CPTEC) in October 2001. It is used the EOF-based perturbations method (Zhang and Krishnamurti, 1999), as modified by Coutinho (1999), to generate the perturbed initial conditions. Essentially, the method is based on: a) random perturbations are added to control initial condition to generate random perturbed initial condition; b) the full model is integrated for 36 hours starting from the control and from the perturbed initial conditions saving results each 3 hours; c) a time series is constructed for the successive differences between control and perturbed forecasts; d) an empirical orthogonal functions analysis (EOF) is performed for the time series of difference fields in order to obtain the fastest growing perturbation; e) the eigenmode associated to the largest eigenvalue is considered as the fastest growing mode; f) the fastest growing mode is normalized to pre-fixed amplitudes; g) the optimum ensemble of initial conditions is generated by adding (subtracting) this fastest eigenmode to (from) the control analysis. Currently, two runs are performed starting from 00 and 12 GMT analysis. Each run represents a set of fifteen forecasts (one control plus fourteen perturbed). The CPTEC spectral global model in a T126L28 resolution, which means a horizontal grid with about 100 km x 100 km near to Equator and 28 levels in the vertical, is used for the predictions. Coutinho (1999) used the EOF method to evaluate the tropical unstable modes and found that EOF perturbations grow up faster than random perturbations applied to the same area. In this work the EOF method is applied to extratropical latitudes in order to evaluate the extratropical perturbation characteristics and their impact in the ensemble weather forecasting. Preliminary results indicate that ensemble mean performance and ensemble spread are improved when compared to the version with tropical EOF. These results are encouraging and may contribute to improve the method used at the CPTEC.Pages: 1829-183