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In this work the sensitivity of summer Probabilistic Quantitative Precipitation Forecasts (PQPF) to alternative ensemble generation methods over southeastern South America is examined. A perturbed initial condition ensemble using the breeding technique, a multimodel ensemble and a pragmatic ensemble based on spatial shifts of the forecast fields have been used to generate calibrated PQPF over the selected region and the results were evaluated using the Brier Skill Score. Results show that calibrated PQPF quality exhibits sensitivity to the ensemble system used and this sensitivity is mainly related with the resolution component of the Brier Skill Score. For the 24 h lead time, the pragmatic approach shows surprisingly good results while for the 48 h lead time, the best results are obtained with the multimodel ensemble. The combination of the spatial shift technique with the multimodel and with the perturbed initial conditions ensemble has also been evaluated and resulted in an increase of the PQPF skill at all lead times. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Different techniques for obtaining probabilistic quantitative precipitation forecasts (PQPFs) over South America are tested during the 2002-2003 warm season. They have been applied to a regional ensemble system which uses the breeding technique to generate initial and boundary conditions perturbations. This comparison involves seven algorithms and also includes experiments to select an adequate size for the training period. Results show that the sensitivity to different calibration strategies is small with the exception of the rank histogram algorithm. The inclusion of the ensemble spread or the use of different ensemble members for the computation of probabilities shows almost no improvement with respect to probabilistic forecasts computed using the ensemble mean. This is basically due to the strong relationship between precipitation error and its amount. Copyright © 2011 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The Weather and Research Forecast model is tested over South America in different configurations to identify the one that gives the best estimates of observed surface variables. Systematic, nonsystematic, and total errors are computed for 48-h forecasts initialized with the NCEP Global Data Assimilation System (GDAS). There is no unique model design that best fits all variables over the whole domain, and nonsystematic errors for all configurations differ little from one another; such differences are in most cases smaller than the observed day-to-day variability. An ensemble mean consisting of runs with different parameterizations gives the best skill for the whole domain. Surface variables are highly sensitive to the choice of land surface models. Surface temperature is well represented by the Noah land model, but dewpoint temperature is best estimated by the simplest land surface model considered here, which specifies soil moisture based on climatology. This underlines the need for better understanding of humid processes at the subgrid scale. Surface wind errors decrease the intensity of the low-level jet, reducing expected heat and moisture advection over southeast South America (SESA), with negative precipitation errors over SESA and positive biases over the South Atlantic convergence zone (SACZ). This pattern of errors suggests feedbacks between wind errors, precipitation, and surface processes as follows: an increase of precipitation over the SACZ produces compensating descent in SESA, with more stable stratification, less rain, less soil moisture, and decreased rain. This is a clear example of how local errors are related to regional circulation, and suggests that improvement of model performance requires not only better parameterizations at the subgrid scales, but also improved regional models. [ABSTRACT FROM AUTHOR]

The impact of changes in soil moisture in subtropical Argentina in rainfall distribution and low-level circulation is studied with a state-of-the-art regional model in a downscaling mode, with different scenarios of soil moisture for a 10-day period. The selected case (starting 29 January 2003) was characterized by a northwestern Argentina low event associated with well-defined low-level northerly flow that extended east of the Andes over subtropical latitudes. Four tests were conducted at 40-km horizontal resolution with 31 sigma levels, decreasing and increasing the soil moisture initial condition by 50% over the entire domain, and imposing a 50% reduction over northwest Argentina and 50% increase over southeast South America. A control run with NCEP/Global Data Assimilation System (GDAS) initial conditions was used to assess the impact of the different soil moisture configurations. It was found that land surface interactions are stronger when soil moisture is decreased, with a coherent reduction of precipitation over southern South America. Enhanced northerly winds result from an increase in the zonal gradient of pressure at low levels. In contrast, when soil moisture is increased, smaller circulation changes are found, although there appears to be a local feedback effect between the land and precipitation. The combined effects of changes in the circulation and in local stratification induced by soil wetness modifications, through variations in evaporation and Convective Available Potential Energy (CAPE), are in agreement with what has been found by other studies, resulting in coherent modifications of precipitation when variations of CAPE and moisture flux convergence mutually reinforce. [ABSTRACT FROM AUTHOR]

In this work, the quality of several probabilistic quantitative precipitation forecasts (PQPFs) is examined. The analysis is focused over South America during a 2-month period in the warm season. Several ways of generating and calibrating the PQPFs have been tested, using different ensemble systems and single-model runs. Two alternative calibration techniques (static and dynamic) have been tested. To take into account different precipitation regimes, PQPF performance has been evaluated over two regions: the northern part of South America, characterized by a tropical regime, and the southern part, where synoptic-scale forcing is stronger. The results support the adoption of such area separation, since differences in the precipitation regimes produce significant differences in PQPF performance. The more skillful PQPFs are the ones obtained after calibration. PQPFs derived from the ensemble mean also show higher skill and better reliability than those derived from the single ensemble members. The performance of the PQPFs derived from both ensemble systems is similar over the southern part of the region; however, over the northern part the superensemble approach seems to achieve better results in both reliability and skill. Finally, the impact of using Climate Prediction Center morphing technique (CMORPH) estimates to calibrate the precipitation forecast has been explored since the more extensive coverage of this dataset would allow its use over areas where the rain gauge coverage is insufficient. Results suggest that systematic biases present in the CMORPH estimates produce only a slight degradation of the resulting PQPF. [ABSTRACT FROM AUTHOR]

Previous studies suggest that the enhanced meridional extent of some South American low-level jet events (known as Chaco jets) is a consequence of a positive feedback between the low-level wind and strong convection that is usually observed at their exit region. To assess how this interaction takes place, a Chaco low-level jet event observed between 18 and 19 December 2002 (i.e., during the South America Low-Level Jet Experiment) and the associated mesoscale convective system that evolved at its exit region have been selected to perform numerical experiments where diabatic heating effects associated with phase changes can be quantified. This case study has also been used to analyze the diurnal oscillations related to planetary boundary layer (PBL) mechanisms in order to describe whether the observed evolution of the low-level wind can be explained either by PBL-related forcing or by the interaction with convection. The sensitivity experiments confirm that there is a positive feedback at low levels between convection and the northerly wind flow that becomes accelerated and also aids in the identification of a strong coupling between organized convection and the upper-level circulation, resulting in an increase of the upper-level jet strength downstream of the simulated precipitation area. A conceptual model of how these systems (i.e., convection, low- and upper-level jets) mutually interact is proposed, which differs from coupling mechanisms documented for the Great Plains low-level jet. [ABSTRACT FROM AUTHOR]

Specification of suitable initial conditions to accurately forecast high-impact weather events associated with intense thunderstorms still poses a significant challenge for convective-scale forecasting. Radar data assimilation has been showing encouraging results to produce an accurate estimate of the state of the atmosphere at the mesoscale, as it combines high-spatiotemporal-resolution observations with convection-permitting numerical weather prediction models. However, many open questions remain regarding the configuration of state-of-the-art data assimilation systems at the mesoscale and their potential impact upon short-range weather forecasts. In this work, several observing system simulation experiments of a mesoscale convective system were performed to assess the sensitivity of the local ensemble transform Kalman filter to both relaxation-to-prior spread (RTPS) inflation and horizontal localization of the error covariance matrix. Realistic large-scale forcing and model errors have been taken into account in the simulation of reflectivity and Doppler velocity observations. Overall, the most accurate analyses in terms of RMSE were produced with a relatively small horizontal localization cutoff radius (;3.6–7.3 km) and large RTPS inflation parameter (;0.9–0.95). Additionally, the impact of horizontal localization on short-range ensemble forecast was larger compared to inflation, almost doubling the lead times up to which the effect of using a more accurate state to initialize the forecast persisted. [ABSTRACT FROM AUTHOR]

Low visibility events are sometimes associated with delays and accidents related with air and land transportation. An accurate forecast of low visibility events can help to reduce the economical and human life losses associated with this phenomenon. This work contributes to the improvement of visibility forecast proposing a dynamic-statistical model that generates probabilistic visibility forecasts. This model combines retrospective forecast generated with a global model and in-situ observations. The proposed model is used to generate probabilistic visibility forecasts for Ezeiza airport between December 1984 and January 2011. Results show that combining in-situ observations and numerical model outputs increases the skill of the probabilistic forecasts with respect to the probabilistic forecast that are based only on observations or only on numerical model outputs. Considering the dependence of systematic numerical model errors with the time of the year produce an additional increase in the forecast skill. [ABSTRACT FROM AUTHOR]

A climatology of the South American low-level jet east of the Andes (SALLJ) is developed using the 1950– 2000 circulation and moisture fields from the NCEP–NCAR reanalyses and available upper-air observations made in Bolivia and Paraguay since 1998. Upper- and low-level circulation fields were derived for seasonal means and SALLJ composites during the warm and cold seasons. The Bonner criterion 1 was applied for sites in central Bolivia and downstream near northern Paraguay, to determine the spatial and temporal characteristics of the SALLJ. On the circulation characteristics, SALLJ composites during the warm season show the enhanced low-level meridional moisture transport coming from equatorial South America as well as an upper-level wave train emanating from the west Pacific propagating toward South America. The intensification of the warm season SALLJ follows the establishment of an upper-level ridge over southern Brazil and a trough over most of Argentina. The circulation anomalies at upper and lower levels suggest that the intensification of the SALLJ would lead to an intensification of the South Atlantic convergence zone (SACZ) later on and to the penetration of cold fronts with an area of enhanced convection ahead at the exit region of the SALLJ. Regarding the time variability, the SALLJ seems to occur all year long, bringing tropical moist air masses from the Amazon into southern Brazil–northern Argentina more frequently in the warm season, and bringing tropical maritime air, which is less humid than the tropical air masses coming from the subtropical Atlantic high, more frequently during the cold season. SALLJs are detected mostly during the warm season to the north of ∼20°S, while to the south the SALLJs seem to occur all year long. The diurnal cycle shows that SALLJs are more frequent and intense between 0600 and 1200 UTC for the warm season north of 20°S, while at the region downstream the maximum is detected between 0000 and 0600 UTC during the cold season. At interannual time scales, even though there is a weak tendency for stronger and more frequent warm season SALLJ episodes in years with anomalously warm surface waters in the tropical Pacific, it cannot be affirmed with a large degree of certainty that there is a strong relationship between the occurrence of El Niño events and the number and/ or intensity of SALLJ episodes. However, the 1998 El Niño featured more frequent and intense warm season jet episodes than occurred during the 1999 La Niña, and this has been demonstrated by the reanalyses, the available Pan American Climate Studies-Sound Network (PACS-SONET) upper-air observations, and by other studies using independent datasets and regional modeling. [ABSTRACT FROM AUTHOR]

The article reports on the Climate-System Historical Forecast Project (CHFP) started by the World Climate Research Programme's orking Group on Subseasonal to Interdecadal Prediction (WGSIP) in June 2007. The CHFP invites leading centers to contribute their sets of forecasts conducted for dates in the past to a common database.

This paper describes the lessons learned from the implementation of a regional ensemble data assimilation and forecast system during the intensive observing period of the Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign (central Argentina, November–December 2018). This system is based on the coupling of the Weather Research and Forecasting (WRF) model and the Local Ensemble Transform Kalman Filter (LETKF). It combines multiple data sources both global and locally available like high-resolution surface networks, AMDAR data from local aircraft flights, soundings, AIRS retrievals, high-resolution GOES-16 wind estimates, and local radar data. Hourly analyses with grid spacing of 10 km are generated along with warm-start 36-h ensemble-forecasts, which are initialized from the rapid refresh analyses every three hours. A preliminary evaluation shows that a forecast error reduction is achieved due to the assimilated observations. However, cold-start forecasts initialized from the Global Forecasting System Analysis slightly outperform the ones initialized from the regional assimilation system discussed in this paper. The system uses a multi-physics approach, focused on the use of different cumulus and planetary boundary layer schemes allowing us to conduct an evaluation of different model configurations over central Argentina. We found that the best combinations for forecasting surface variables differ from the best ones for forecasting precipitation, and that differences among the schemes tend to dominate the forecast ensemble spread for variables like precipitation. Lessons learned from this experimental system are part of the legacy of the RELAMPAGO field campaign for the development of advanced operational data assimilation systems in South America. • A LETKF-WRF system was run successfully in real-time to support RELAMPAGO operations. • A reduction in forecast error was shown due to data assimilation cycles. • 60-member RRR analyses and forecasts are available for the research community. [ABSTRACT FROM AUTHOR]