Climate diagnostics of three major drought events in the Amazon and illustrations of their seasonal precipitation predictions

n/

Subseasonal prediction performance for austral summer South American rainfall

Skilful and reliable predictions of week-to-week rainfall variations in South America, two to three weeks ahead, are essential to protect lives, livelihoods and ecosystems. We evaluate forecast performance for weekly rainfall in extended austral summer (November-March) in four contemporary subseasonal systems, including a new Brazilian model, at 1-5 week leads for 1999-2010. We measure performance by the correlation coefficient (in time) between predicted and observed rainfall; we measure skill by the Brier Skill Score for rainfall terciles against a climatological reference forecast. We assess unconditional performance (i.e., regardless of initial condition) and conditional performance based on the initial phase of the Madden-Julian Oscillation (MJO) and the El Nino--Southern Oscillation (ENSO). All models display substantial mean rainfall biases, including dry biases in Amazonia and wet biases near the Andes, which are established by Week 1 and vary little thereafter. Unconditional performance extends to Week 2 in all regions except for Amazonia and the Andes, but to Week 3 only over northern, northeastern and southeastern South America. Skill for upper- and lower-tercile rainfall extends only to Week 1. Conditional performance is not systematically or significantly higher than unconditional performance; ENSO and MJO events provide limited "windows of opportunity" for improved S2S predictions that are region- and model-dependent. Conditional performance may be degraded by errors in predicted ENSO and MJO teleconnections to regional rainfall, even at short lead times

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

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

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes