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Abstract The Sierras de Córdoba (SDC) range in Argentina is a hotspot of deep moist convection initiation (CI). Radar climatology indicates that 44% of daytime CI events that occur near the SDC in spring and summer seasons and that are not associated with the passage of a cold front or an outflow boundary involve a northerly low-level jet (LLJ), and these events tend to preferentially occur over the southeast quadrant of the main ridge of the SDC. To investigate the physical mechanisms acting to cause CI, idealized convection-permitting numerical simulations with a horizontal grid spacing of 1 km were conducted using Cloud Model 1 (CM1). The sounding used for initializing the model featured a strong northerly LLJ, with synoptic conditions resembling those in a previously postulated conceptual model of CI over the region, making it a canonical case study. Differential heating of the mountain caused by solar insolation in conjunction with the low-level northerly flow sets up a convergence line on the eastern slopes of the SDC. The southern portion of this line experiences significant reduction in convective inhibition, and CI occurs over the SDC southeast quadrant. The simulated storm soon acquires supercellular characteristics, as observed. Additional simulations with varying LLJ strength also show CI over the southeast quadrant. A simulation without background flow generated convergence over the ridgeline, with widespread CI across the entire ridgeline. A simulation with mid- and upper-tropospheric westerlies removed indicates that CI is minimally influenced by gravity waves. We conclude that the low-level jet is sufficient to focus convection initiation over the southeast quadrant of the ridge. 

Soil moisture–precipitation (SM–PPT) feedbacks at the mesoscale represent a major challenge for numerical weather prediction, especially for subtropical regions that exhibit large variability in surface SM. How does surface heterogeneity, specifically mesoscale gradients in SM and land surface temperature (LST), affect convective initiation (CI) over South America? Using satellite data, we track nascent, daytime convective clouds and quantify the underlying antecedent (morning) surface heterogeneity. We find that convection initiates preferentially on the dry side of strong SM/LST boundaries with spatial scales of tens of kilometers. The strongest alongwind gradients in LST anomalies at 30-km length scale underlying the CI location occur during weak background low-level wind (<2.5 m s⁻¹), high convective available potential energy (>1500 J kg⁻¹), and low convective inhibition (<250 J kg⁻¹) over sparse vegetation. At 100-km scale, strong gradients occur at the CI location during convectively unfavorable conditions and strong background flow. The location of PPT is strongly sensitive to the strength of the background flow. The wind profile during weak background flow inhibits propagation of convection away from the dry regions leading to negative SM–PPT feedback whereas strong background flow is related to longer life cycle and rainfall hundreds of kilometers away from the CI location. Thus, the sign of the SM–PPT feedback is dependent on the background flow. This work presents the first observational evidence that CI over subtropical South America is associated with dry soil patches on the order of tens of kilometers. Convection-permitting numerical weather prediction models need to be examined for accurately capturing the effect of SM heterogeneity in initiating convection over such semiarid regions.

 

Abstract Sierras de Córdoba (Argentina) is characterized by the occurrence of extreme precipitation events during the austral warm season. Heavy precipitation in the region has a large societal impact, causing flash floods. This motivates the forecast performance evaluation of 24-h accumulated precipitation and vertical profiles of atmospheric variables from different numerical weather prediction (NWP) models with the final aim of helping water management in the region. The NWP models evaluated include the Global Forecast System (GFS), which parameterizes convection, and convection-permitting simulations of the Weather Research and Forecasting (WRF) Model configured by three institutions: University of Illinois at Urbana–Champaign (UIUC), Colorado State University (CSU), and National Meteorological Service of Argentina (SMN). These models were verified with daily accumulated precipitation data from rain gauges and soundings during the RELAMPAGO-CACTI field campaign. Generally all configurations of the higher-resolution WRFs outperformed the lower-resolution GFS based on multiple metrics. Among the convection-permitting WRF Models, results varied with respect to rainfall threshold and forecast lead time, but the WRFUIUC mostly performed the best. However, elevation-dependent biases existed among the models that may impact the use of the data for different applications. There is a dry (moist) bias in lower (upper) pressure levels which is most pronounced in the GFS. For Córdoba an overestimation of the northern flow forecasted by the NWP configurations at lower levels was encountered. These results show the importance of convection-permitting forecasts in this region, which should be complementary to the coarser-resolution global model forecasts to help various users and decision-makers. 

This study compared drop size distribution (DSD) measurements on the surface, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter Dm, and normalized droplet concentration Nw) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader Nw distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h−1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of Nw in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution. 

The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteen-disdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logNw), the mean volume diameter (D0), the mean mass diameter (Dm), the shape parameter (μ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logNw, lower D0, and higher μ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D0: the lower values of D0 were associated with higher values of logNw and were found more frequently during the afternoon, while the higher D0 were associated with lower logNw and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logNw-D0 and LWC-D0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case. 

Abstract This article provides an overview of the Advanced Study Institute: Field Studies of Convection in Argentina (ASI-FSCA) program, a 3-week dynamic and collaborative hands-on experience that allowed 16 highly motivated and diverse graduate students from the U.S. to participate in the 2018-19 Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. This program is unique as it represents the first effort to integrate an intensive Advanced Study Institute with a field campaign in atmospheric science. ASI-FSCA activities and successful program outcomes for five key elements are described: (1) Intensive field research with field campaign instrumentation platforms; (2) Recruitment of diverse graduate students who would not otherwise have opportunities to participate in intensive field research; (3) Tailored curriculum focused on scientific understanding of cloud and mesoscale processes and professional/academic development topics; (4) Outreach to local K-12 schools and the general public; and (5) Building a collaborative international research network to promote weather and climate research. These five elements served to increase motivation and improve confidence and self-efficacy of students to participate in scientific research and field work with goals of increasing retention and a sense of belonging in STEM graduate programs and advancing the careers of students from underrepresented groups as evidenced by a formal program evaluation effort. Given the success of the ASI-FSCA program, our team strongly recommends considering this model for expanding the opportunities for a broader and more diverse student community to participate in dynamic and intensive field work in atmospheric science. 

Abstract Some of the most intense convective storms on Earth initiate near the Sierras de Córdoba mountain range in Argentina. The goal of the RELAMPAGO field campaign was to observe these intense convective storms and their associated impacts. The intense observation period (IOP) occurred during November–December 2018. The two goals of the hydrometeorological component of RELAMPAGO IOP were 1) to perform hydrological streamflow and meteorological observations in previously ungauged basins and 2) to build a hydrometeorological modeling system for hindcast and forecast applications. During the IOP, our team was able to construct the stage–discharge curves in three basins, as hydrological instrumentation and personnel were successfully deployed based on RELAMPAGO weather forecasts. We found that the flood response time in these river locations is typically between 5 and 6 h from the peak of the rain event. The satellite-observed rainfall product IMERG-Final showed a better representation of rain gauge–estimated precipitation, while IMERG-Early and IMERG-Late had significant positive bias. The modeling component focuses on the 48-h simulation of an extreme hydrometeorological event that occurred on 27 November 2018. Using the Weather Research and Forecasting (WRF) atmospheric model and its hydrologic component WRF-Hydro as an uncoupled hydrologic model, we developed a system for hindcast, deterministic forecast, and a 60-member ensemble forecast initialized with regional-scale atmospheric data assimilation. Critically, our results highlight that streamflow simulations using the ensemble forecasting with data assimilation provide realistic flash flood forecast in terms of timing and magnitude of the peak. Our findings from this work are being used by the water managers in the region. 

Abstract During the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations-Cloud, Aerosol, and Complex Terrain Interactions (RELAMPAGO-CACTI) field experiments in 2018–19, an unprecedented number of balloon-borne soundings were collected in Argentina. Radiosondes were launched from both fixed and mobile platforms, yielding 2712 soundings during the period 15 October 2018–30 April 2019. Approximately 20% of these soundings were collected by highly mobile platforms, strategically positioned for each intensive observing period, and launching approximately once per hour. The combination of fixed and mobile soundings capture both the overall conditions characterizing the RELAMPAGO-CACTI campaign, as well as the detailed evolution of environments supporting the initiation and upscale growth of deep convective storms, including some that produced hazardous hail and heavy rainfall. Episodes of frequent convection were characterized by sufficient quantities of moisture and instability for deep convection, along with deep-layer vertical wind shear supportive of organized or rotating storms. A total of 11 soundings showed most unstable convective available potential energy (MUCAPE) exceeding 6000 J kg −1 , comparable to the extreme instability observed in other parts of the world with intense deep convection. Parameters used to diagnose severe-storm potential showed that conditions were often favorable for supercells and severe hail, but not for tornadoes, primarily because of insufficient low-level wind shear. High-frequency soundings also revealed the structure and evolution of the boundary layer leading up to convection initiation, convectively generated cold pools, the South American low-level jet (SALLJ), and elevated nocturnal convection. This sounding dataset will enable improved understanding and prediction of convective storms and their surroundings in subtropical South America, as well as comparisons with other heavily studied regions such as the central United States that have not previously been possible.