Search

Total column H2O is measured by two remote sensing techniques at the Altzomoni Atmospheric Observatory (19°12′N, 98°65′W, 4000 m above sea level), a high-altitude, tropical background site in central Mexico. A ground-based solar absorption FTIR spectrometer that is part of the Network for Detection of Atmospheric Composition Change (NDACC) is used to retrieve water vapor in three spectral regions (6074–6471, 2925–2941, and 1110–1253 cm−1) and is compared to data obtained from a global positioning system (GPS) receiver that is part of the TLALOCNet GPS-meteorological network. Strong correlations are obtained between the coincident hourly means from the three FTIR products and small relative bias and correction factors could be determined for each when compared to the more consistent GPS data. Retrievals from the 2925–2941 cm−1 spectral region have the highest correlation with GPS [coefficient of determination (R2) = 0.998, standard deviation (STD) = 0.18 cm (78.39%), mean difference = 0.04 cm (8.33%)], although the other products are also highly correlated [R2 ≥ 0.99, STD ≤ 0.20 cm (

Forecasting mesoscale convective systems (MCSs) and precipitation over complex terrain is an ongoing challenge even for convective permitting numerical models. Here, we show the value of combining mesoscale constraints to improve short-term MCS forecasts for two events during the North American monsoon season in 2013, including: 1) the initial specification of moisture, via GPS-precipitable water vapor (PWV) data assimilation (DA), 2) kinematics via modification of cumulus parameterization, and 3) microphysics via modification of cloud microphysics parameterization. A total of five convective-permitting Weather Research Forecasting (WRF) model experiments is conducted for each event to elucidate the impact of these constraints. Results show that combining GPS-PWV DA with a modified Kain-Fritsch scheme and double moment microphysics provides relatively the best forecast of both North American monsoon MCSs and convective precipitation in terms of timing, location, and intensity relative to available precipitation and cloud-top temperature observations. Additional examination on the associated reflectivity, vertical wind field, equivalent potential temperature, and hydrometeor distribution of MCS events show the added value of each individual constraint to forecast performance.

Lower tropospheric thermal structure greatly affects atmospheric boundary-layer (ABL) stability and mixing processes with the free troposphere. In particular, in polluted urban zones, ABL stratification becomes a key variable in air quality research. This study focuses on generating a climatology (1990–2017) of the seasonal variability of ABL thermal structure in Mexico City by way of radiosonde analysis. Thermal inversion intensity and frequency are shown to be greater during winter and spring, a behaviour which coincides with greater pollutant concentrations. Higher concentrations are found during the dry season (November to May) than during the rainy months. In addition, significantly higher than normal surface pollutant concentrations are found on days with simple thermal inversion layers as well as during multilayer inversion days. Furthermore, stable layers, determined by potential temperature, are found throughout the year but more frequently during winter, whereas stable layers based on the virtual potential temperature prevail all year. In regions of complex terrain, such multiple stable layers have also been identified by previous authors. Additionally, the most unstable surface layers (in which the bulk Richardson number ( $${Ri}_{\mathrm {B}}$$ ) is small) develop during the rainy season, whereas during winter there are more levels in the vertical column with higher $${Ri}_{\mathrm {B}}$$ values. Although the Mexico City ABL and pollution episodes have been widely studied, this represents the first long-term investigation to consider the thermal stability of the ABL. Therefore, the present study provides a baseline for further research employing different observational techniques and high-resolution numerical models.

The 2014–15 Observations and Modeling of the Green Ocean Amazon (GOAmazon) field campaign over the central Amazon near Manaus, Brazil, occurred in coordination with the larger Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) project across Brazil. These programs provide observations of convection over the central Amazon on diurnal to annual time scales. In this study, we address the question of how Kelvin waves, observed in satellite observations of deep cloud cover over the GOAmazon region during the 2014–15 time period, modulate the growth, type, and organization of convection over the central Amazon. The answer to this question has implications for improved predictability of organized systems over the region and representation of convection and its growth on local to synoptic scales in global models. Our results demonstrate that Kelvin waves are strong modulators of synoptic-scale low- to midlevel free-tropospheric moisture, integrated moisture convergence, and surface heat fluxes. These regional modifications of the environment impact the local diurnal cycle of convection, favoring the development of mesoscale convective systems. As a result, localized rainfall is also strongly modulated, with the majority of rainfall in the GOAmazon region occurring during the passage of these systems.

We assess the impact of GPS precipitable water vapor (GPS-PWV) data assimilation (DA) on short-range North American monsoon (NAM) precipitation forecasts, across 38 days with weak synoptic forcing, during the NAM GPS Hydrometeorological Network field campaign in 2017 over northwest Mexico. Utilizing an ensemble-based data assimilation technique, the GPS-PWV data retrieved from 18 observation sites are assimilated every hour for 12 hours into a 30-member ensemble convective-permitting (2.5 km) Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model. As the assimilation of the GPS-PWV improves the initial condition of WRF by reducing the root mean square error and bias of PWV across 1200-1800 UTC, this also leads to an improvement in capturing nocturnal convection of mesoscale convective systems (MCSs; after 0300 UTC) and to an increase by 0.1 mm h-1 in subsequent precipitation during the 0300-0600 UTC period relative to no assimilation of the GPS-PWV (NODA) over the area with relatively more observation sites. This response is consistent with observed precipitation from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final Precipitation product. Moreover, compared to the NODA, we find that the GPS-PWV DA decreases cloud top temperature, increases most unstable convective available energy and surface dewpoint temperature, and thus creates a more favorable condition for convective organization in the region.

Convective processes in the atmosphere over the Maritime Continent and their diurnal cycles have important repercussions for the circulations in the tropics and beyond. In this work, we present a new dataset of precipitable water vapor (PWV) obtained from the Sumatran GPS Array (SuGAr), a dense network of GPS stations principally for examining seismic and tectonic activity along the western coast of Sumatra and several offshore islands. The data provide an opportunity to examine the characteristics of convection over the area in greater detail than before. In particular, our results show that the diurnal cycle of PWV on Sumatra has a single late afternoon peak, while that offshore has both a midday and a nocturnal peak. The SuGAr data are in good agreement with GPS radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, as well as with imaging spectrometer data from the Ozone Measuring Instrument (OMI). A comparison between SuGAr and the NASA Water Vapor Project (NVAP), however, shows significant differences, most likely due to discrepancies in the temporal and spatial resolutions. To further understand the diurnal cycle contained in the SuGAr data, we explore the impact of the Madden–Julian oscillation (MJO) on the diurnal cycle with the aid of the Weather Research and Forecasting (WRF) Model. Results show that the daily mean and the amplitude of the diurnal cycle appear smaller during the suppressed phase relative to the developing/active MJO phase. Furthermore, the evening/nighttime peaks of PWV offshore appear later during the suppressed phase of the MJO compared to the active phase.

Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of the seasonal patterns of isoprene fluxes and the associated mechanistic controls is still limited, especially in Amazonian evergreen forests. In this paper, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest site with meteorological observations and with tower-mounted camera leaf phenology to improve our understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas the lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature cannot totally explain isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf age class (e.g., leaf ages of 3–5 months) exhibits the highest correlation with observed isoprene flux seasonality (R2=0.59, p). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm by utilizing results from the camera-derived leaf phenology that provided LAI categorized into three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations in isoprene fluxes (R2=0.52, p). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and identifying forest adaptive mechanisms that underlie seasonal variation in isoprene emissions in Amazonia.

A lightning–precipitation relationship (LPR) is studied at high temporal and spatial resolution (5 min and 5 km). As a proof of concept of these methods, precipitation data are retrieved from the National Severe Storms Laboratory (NSSL) NMQ product for southern Arizona and western Texas while lightning data are provided by the National Lightning Detection Network (NLDN). A spatial- and time-invariant (STI) linear model that considers spatial neighbors and time lags is proposed. A data denial analysis is performed over Midland, Texas (a region with good sensor coverage), with this STI model. The LPR is unchanged and essentially equal, regardless of the domain (denial or complete) used to obtain the STI model coefficients. It is argued that precipitation can be estimated over regions with poor sensor coverage (i.e., southern Arizona) by calibrating the LPR over well-covered domains that are experiencing similar storm conditions. To obtain a lightning-estimated precipitation that dynamically updates the model coefficients in time, a Kalman filter is applied to the STI model. The correlation between the observed and estimated precipitation is statistically significant for both models, but the Kalman filter provides a better precipitation estimation. The best demonstration of this application is a heavy-precipitation, high-frequency lightning event in southern Arizona over a region with poor radar and rain gauge coverage. By calibrating the Kalman filter over a data-covered domain, the lightning-estimated precipitation is considerably greater than that estimated by radar alone. Therefore, for regions where both rain gauge and radar data are compromised, lightning provides a viable alternative for improving QPE.

Long-term changes in North American monsoon (NAM) precipitation intensity in the southwestern United States are evaluated through the use of convective-permitting model simulations of objectively identified severe weather events during “historical past” (1950–70) and “present day” (1991–2010) periods. Severe weather events are the days on which the highest atmospheric instability and moisture occur within a long-term regional climate simulation. Simulations of severe weather event days are performed with convective-permitting (2.5 km) grid spacing, and these simulations are compared with available observed precipitation data to evaluate the model performance and to verify any statistically significant model-simulated trends in precipitation. Statistical evaluation of precipitation extremes is performed using a peaks-over-threshold approach with a generalized Pareto distribution. A statistically significant long-term increase in atmospheric moisture and instability is associated with an increase in extreme monsoon precipitation in observations and simulations of severe weather events, corresponding to similar behavior in station-based precipitation observations in the Southwest. Precipitation is becoming more intense within the context of the diurnal cycle of convection. The largest modeled increases in extreme-event precipitation occur in central and southwestern Arizona, where mesoscale convective systems account for a majority of monsoon precipitation and where relatively large modeled increases in precipitable water occur. Therefore, it is concluded that a more favorable thermodynamic environment in the southwestern United States is facilitating stronger organized monsoon convection during at least the last 20 years.

Bias and spread in Coupled Model Intercomparison Project Phase 5 simulated vertical specific humidity (q) structure are examined and related to both precipitation and column water vapor (cwv) near Manaus, Brazil, site of the recent Green Ocean Amazon (GOAmazon) campaign. Simulated seasonal-mean q profiles are typically too dry, especially at low levels and during the local dry season, consistent with previously identified surface hydroclimate biases in the Amazon. Multimodel empirical orthogonal function analysis of the models’ monthly climatological q profiles indicates two significant modes of ensemble spread in moisture vertical structure, with the leading mode peaked at low levels and the second mode in the lower free troposphere (LFT). While both modes project onto simulated cwv spread, only the first projects on precipitation, suggesting inconsistent sensitivity of simulated rainfall to LFT moisture. Relative to observations, models with high cwv and low-level moisture errors tend to exhibit high precipitation error.

This paper examines the ability of the Weather Research and Forecasting model forecast to simulate moisture and precipitation during the North American Monsoon GPS Hydrometeorological Network field campaign that took place in 2017. A convective-permitting model configuration performs daily weather forecast simulations for northwestern Mexico and southwestern United States. Model precipitable water vapor (PWV) exhibits wet biases greater than 0.5 mm at the initial forecast hour, and its diurnal cycle is out of phase with time, compared to observations. As a result, the model initiates and terminates precipitation earlier than the satellite and rain gauge measurements, underestimates the westward propagation of the convective systems, and exhibits relatively low forecast skills on the days where strong synoptic-scale forcing features are absent. Sensitivity analysis shows that model PWV in the domain is sensitive to changes in initial PWV at coastal sites, whereas the model precipitation and moisture flux convergence (QCONV) are sensitive to changes in initial PWV at the mountainous sites. Improving the initial physical states, such as PWV, potentially increases the forecast skills.

Purpose of Review: Understanding the details of the impact of global warming on the North and South America monsoons is of key importance for the well-being of a great number of inhabitants of the Americas. This review deals with the latest research on this topic. Recent Findings: Combined multiple datasets, high-resolution global climate models and regional convection–permitting models provide new insights on the evolution of the North and South American monsoons under global warming, suggesting a precipitation reduction in the North American Monsoon, the southward shift of the core of the South American Monsoon, and precipitation reduction in the Amazon Basin. These changes are accompanied by increased frequency of extreme precipitation events in both monsoon regions. Summary: Uncertainty in the response mechanisms to global warming remains high, especially for the North American monsoon. To make progress, the evaluation of local and remote drives is critical, for which we need a combined use of regional and global models.

The economic activities of the Sonora strongly depend on groundwater extraction, which is generally of recent meteoric origin. Understanding the hydrological functioning in this semi-arid region, located in northwestern Mexico, is crucial for integrated water management in a changing climate. This study presents a spatio-temporal analysis of the isotopic composition (δ18O, δ2 H, d-excess) during the 2018 rainy season in the Sonora River Basin (SRB), a region influenced by the characteristic weather conditions of the North American Monsoon (NAM). The basin is located in the central region of Sonora and covers an area of approximately 27,000 km2 . Precipitation was collected using six passive totalizers, distributed spatially from the coast of the Gulf of California up to 1,425 m asl inland. The rainfall isotopic composition is comparable with the Global Meteoric Water Line (GMWL) and with the records of the Global Isotope Network in Precipitation (GNIP) in Chihuahua, Mexico, between 1962 and 1988, and Tucson, Arizona (2018). The temporal variability of rainfall isotope ratios was Δ18O = 7.4‰ and Δ2 H = 49.8‰, with a clear depletion pattern (low δ18O) as the monsoon rainy season progressed. The isotopic lapse rate was found to be − 1.0‰ in δ18O per km of elevation as a result of the topography relief and rainout effects within the basin. The influence of tropical cyclones such as Hurricane Sergio (October 2018) provided the opportunity to isolate the effects of a tropical storm with respect to the deep convective precipitation, typical of the NAM systems over northwest Mexico Las actividades económicas de Sonora dependen en gran medida de la extracción de agua subterránea, que generalmente es de origen meteórico reciente. Comprender el funcionamiento hidrológico en esta región semiárida, ubicada en el noroeste de México, es crucial para la gestión integral del agua en un clima cambiante. Este estudio presenta un análisis espacio-temporal de la composición isotópica (δ18O, δ2 H, d-exceso) durante la temporada de lluvias 2018 en la Cuenca del Río Sonora (SRB), una región influenciada por las condiciones climáticas características del Monzón de América del Norte ( NAM). La cuenca está ubicada en la región central de Sonora y cubre un área de aproximadamente 27,000 km2. La precipitación se recogió utilizando seis totalizadores pasivos, distribuidos espacialmente desde la costa del Golfo de California hasta 1.425 m snm tierra adentro. La composición isotópica de las precipitaciones es comparable con la Línea de Agua Meteórica Global (GMWL) y con los registros de la Red Global de Isótopos en Precipitación (GNIP) en Chihuahua, México, entre 1962 y 1988, y Tucson, Arizona (2018). La variabilidad temporal de las proporciones de isótopos de lluvia fue Δ18O = 7.4 ‰ y Δ2 H = 49.8 ‰, con un patrón de agotamiento claro (bajo δ18O) a medida que avanzaba la temporada de lluvias monzónicas. Se encontró que la tasa de caída isotópica era de - 1.0 ‰ en δ18O por km de elevación como resultado del relieve de la topografía y los efectos de la lluvia dentro de la cuenca. La influencia de ciclones tropicales como el huracán Sergio (octubre de 2018) brindó la oportunidad de aislar los efectos de una tormenta tropical con respecto a la precipitación convectiva profunda, típica de los sistemas NAM sobre el noroeste de México. Universidad Nacional Autónoma de México, México Universidad Nacional, Costa Rica Comité Estatal de Sanidad Vegetal de Sonora, México Escuela de Química

Almost one-half of the annual precipitation in the southwestern United States occurs during the North American monsoon (NAM). Given favorable synoptic-scale conditions, organized monsoon thunderstorms may affect relatively large geographic areas. Through an objective analysis of atmospheric reanalysis and observational data, the dominant synoptic patterns associated with NAM extreme events are determined for the period from 1993 to 2010. Thermodynamically favorable extreme-weather-event days are selected on the basis of atmospheric instability and precipitable water vapor from Tucson, Arizona, rawinsonde data. The atmospheric circulation patterns at 500 hPa associated with the extreme events are objectively characterized using principal component analysis. The first two dominant modes of 500-hPa geopotential-height anomalies of the severe-weather-event days correspond to type-I and type-II severe-weather-event patterns previously subjectively identified by Maddox et al. These patterns reflect a positioning of the monsoon ridge to the north and east or north and west, respectively, from its position in the “Four Corners” region during the period of the climatological maximum of monsoon precipitation from mid-July to mid-August. An hourly radar–gauge precipitation product shows evidence of organized, westward-propagating convection in Arizona during the type-I and type-II severe weather events. This new methodological approach for objectively identifying severe weather events may be easily adapted to inform operational forecasting or analysis of gridded climate data.

Northwestern Mexico experiences large variations in water vapor on seasonal time scales in association with the North American monsoon, as well as during the monsoon associated with upper-tropospheric troughs, mesoscale convective systems, tropical easterly waves, and tropical cyclones. Together these events provide more than half of the annual rainfall to the region. A sufficient density of meteorological observations is required to properly observe, understand, and forecast the important processes contributing to the development of organized convection over northwestern Mexico. The stability of observations over long time periods is also of interest to monitor seasonal and longer-time-scale variability in the water cycle. For more than a decade, the U.S. Global Positioning System (GPS) has been used to obtain tropospheric precipitable water vapor (PWV) for applications in the atmospheric sciences. There is particular interest in establishing these systems where conventional operational meteorological networks are not possible due to the lack of financial or human resources to support the network. Here, we provide an overview of the North American Monsoon GPS Transect Experiment 2013 in northwestern Mexico for the study of mesoscale processes and the impact of PWV observations on high-resolution model forecasts of organized convective events during the 2013 monsoon. Some highlights are presented, as well as a look forward at GPS networks with surface meteorology (GPS-Met) planned for the region that will be capable of capturing a wider range of water vapor variability in both space and time across Mexico and into the southwestern United States.

The relationships between the onset of tropical deep convection, column water vapor (CWV), and other measures of conditional instability are analyzed with 2 yr of data from the DOE Atmospheric Radiation Measurement (ARM) Mobile Facility in Manacapuru, Brazil, as part of the Green Ocean Amazon (GOAmazon) campaign, and with 3.5 yr of CWV derived from global positioning system meteorology at a nearby site in Manaus, Brazil. Important features seen previously in observations over tropical oceans—precipitation conditionally averaged by CWV exhibiting a sharp pickup at high CWV, and the overall shape of the CWV distribution for both precipitating and nonprecipitating points—are also found for this tropical continental region. The relationship between rainfall and CWV reflects the impact of lower-free-tropospheric moisture variability on convection. Specifically, CWV over land, as over ocean, is a proxy for the effect of free-tropospheric moisture on conditional instability as indicated by entraining plume calculations from GOAmazon data. Given sufficient mixing in the lower troposphere, higher CWV generally results in greater plume buoyancies through a deep convective layer. Although sensitivity of buoyancy to other controls in the Amazon is suggested, such as boundary layer and microphysical processes, the CWV dependence is consistent with the observed precipitation onset. Overall, leading aspects of the relationship between CWV and the transition to deep convection in the Amazon have close parallels over tropical oceans. The relationship is robust to averaging on time and space scales appropriate for convective physics but is strongly smoothed for averages greater than 3 h or 2.5°.

Transient inverted troughs (IVs) are a trigger for severe weather during the North American monsoon (NAM) in the southwest contiguous United States (CONUS) and northwest Mexico. These upper-tropospheric disturbances enhance the synoptic-scale and mesoscale environment for organized convection, increasing the chances for microbursts, straight-line winds, blowing dust, and flash flooding. This work considers changes in the track density climatology of IVs between 1951 and 2010. IVs are tracked as potential vorticity (PV) anomalies on the 250-hPa surface from a regional climate model that dynamically downscales the NCEP–NCAR Reanalysis 1. Late in the NAM season, a significant increase in IV track density over the 60-yr period is observed over Southern California and western Arizona, coupled with a slight decrease over northwest Mexico. Changes in precipitation are evaluated on days when an IV is observed and days without an IV, using high-resolution model-simulated precipitation estimates and CPC gridded precipitation observations. Because of changes in the spatial distribution of IVs during the 1951–2010 analysis period, which are associated with a strengthening of the monsoon ridge, it is suggested that IVs have played a lesser role in the initiation and organization of monsoon convection in the southwest CONUS during recent warm seasons.

During the North American monsoon global positioning system (GPS) Transect Experiment 2013, daily convective-permitting WRF simulations are performed in northwestern Mexico and the southern Arizona border region using the operational Global Forecast System (GFS) and North American Mesoscale Forecast System (NAM) models as lateral boundary forcing and initial conditions. Compared to GPS precipitable water vapor (PWV), the WRF simulations display a consistent moist bias in the initial specification of PWV leading to convection beginning 3–6 h early. Given appreciable observed rainfall, days are classified as strongly and weakly forced based only on the presence of an inverted trough (IV); gulf surges did not noticeably impact the development of mesoscale convective systems (MCSs) and related convection in northwestern Mexico. Strongly forced days display higher modeled precipitation forecast skill than weakly forced days in the slopes of the northern Sierra Madre Occidental (SMO) away from the crest, especially toward the west where MCSs account for the greatest proportion of all monsoon-related precipitation. A case study spanning 8–10 July 2013 illustrates two consecutive days when nearly identical MCSs evolved over northern Sonora. Although a salient MCS is simulated on the strongly forced day (9–10 July 2013) when an IV is approaching the core monsoon region, a simulated MCS is basically nonexistent on the weakly forced day (8–9 July 2013) when the IV is farther away. The greater sensitivity to the initial specification of PWV in the weakly forced day suggests that assimilation of GPS-derived PWV for these types of days may be of greatest value in improving model precipitation forecasts.

The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial–temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km × 100 km) networks: 1) a 1-yr (April 2011–April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized.

In this work, the trends of total suspended particulate matter (TSP) were analyzed during a period of 12 years (2000–2012) on the basis of meteorological parameters. The results of historical trends of TSP show that post-monsoon dust emission seems to be connected to rainfall distribution in the urban environment. Particulate matter is dominated by plagioclase, quartz, calcite, and montmorillonite phases with barium sulfate, and particles enriched in Cu, Fe, and Ce. Elemental composition and principal component analysis allow the identification of two major sources for metals incorporated in geogenic dust: cement, and traffic. Geochemical analysis of non-mobile trace elements show a similar signature as local cement brands in TSP filters, but it remains unknown if such a signature is related to cement production, erosion of buildings, or construction activities. La–Ce geochemical tracers show that geogenic dust is an important media of transportation for traffic, and cement-related contaminants. This work highlights the importance of monsoon season precipitation in dust generation in arid urban environments, and it could contribute to regional studies including the southwestern US regarding the dust emission processes and transport of pollutants across the trans-boundary.

Deep atmospheric convection, which covers a large range of spatial scales during its evolution, continues to be a challenge for models to replicate, particularly over land in the tropics. Specifically, the shallow-to-deep convective transition and organization on the mesoscale are often not properly represented in coarse-resolution models. High-resolution models offer insights on physical mechanisms responsible for the shallow-to-deep transition. Model verification, however, at both coarse and high resolution requires validation and, hence, observational metrics, which are lacking in the tropics. Here a straightforward metric derived from the Amazon Dense GNSS Meteorological Network (~100 km × 100 km) is presented based on a spatial correlation decay time scale during convective evolution on the mesoscale. For the shallow-to-deep transition, the correlation decay time scale is shown to be around 3.5 h. This novel result provides a much needed metric from the deep tropics for numerical models to replicate.

CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.

Author(s): Serr, YL; Haase, JS; Adams, DK; Fu, Q; Ackerman, TP; Alexander, MJ; Arellano, A; Back, L; Emanuel, K; Kuang, Z; Mapes, B; Neelin, D; Raymond, D; Sobel, AH; Staten, PW; Subramanian, A; Thompson, DWJ; Vecchi, G; Wood, R; Zuidema, P

Lightning and deep convective precipitation have long been studied as closely linked variables, the former being viewed as a proxy, or estimator, of the latter. However, to date, no single methodology or algorithm exists for estimating lightning-derived precipitation in a gridded form. This paper, the third in a series, details the specific algorithm where convective rainfall was estimated with cloud-to-ground lightning occurrences from the U.S. National Lightning Detection Network (NLDN), for the North American Monsoon region. Specifically, the authors present the methodology employed in their previous studies to get this estimation, noise test, spatial and temporal neighbors and the algorithm of the Kalman filter for dynamically derived precipitation from lightning.

The Bodele Depression (Chad) in the central Sahara/Sahel region of Northern Africa is the most important source of mineral dust to the atmosphere globally. The Bodele Depression is purportedly the largest source of Saharan dust reaching the Amazon Basin by transatlantic transport. Here, we have undertaken a comprehensive study of surface sediments from the Bodele Depression and dust deposits (Chad, Niger) in order to characterize geochemically and isotopically (Sr, Nd and Pb isotopes) this dust source, and evaluate its importance in present and past African dust records. We similarly analyzed sedimentary deposits from the Amazonian lowlands in order to assess postulated accumulation of African mineral dust in the Amazon Basin, as well as its possible impact in fertilizing the Amazon rainforest. Our results identify distinct sources of different ages and provenance in the Bodele Depression versus the Amazon Basin, effectively ruling out an origin for the Amazonian deposits, such as the Belterra Clay Layer, by long-term deposition of Bodele Depression material. Similarly, no evidence for contributions from other potential source areas is provided by existing isotope data (Sr, Nd) on Saharan dusts. Instead, the composition of these Amazonian deposits is entirely consistent with derivation from in-situ weathering and erosion of the Precambrian Amazonian craton, with little, if any, Andean contribution. In the Amazon Basin, the mass accumulation rate of eolian dust is only around one-third of the vertical erosion rate in shield areas, suggesting that Saharan dust is “consumed” by tropical weathering, contributing nutrients and stimulating plant growth, but never accumulates as such in the Amazon Basin. The chemical and isotope compositions found in the Bodele Depression are varied at the local scale, and have contrasting signatures in the “silica-rich” dry lake-bed sediments and in the “calcium-rich” mixed diatomites and surrounding sand material. This unexpected finding implies that the Bodele Depression material is not “pre-mixed” at the source to provide a homogeneous source of dust. Rather, different isotope signatures can be emitted depending on subtle vagaries of dust-producing events. Our characterization of the Bodele Depression components indicate that the Bodele “calcium-rich” component, identified here, is most likely released via eolian processes of sand grain saltation and abrasion and may be significant in the overall global budget of dusts carried out by the Harmattan low-level jet during the winter.

[1] In the tropics, understanding the shallow-to-deep transition and organization of convection on the mesoscale is made difficult due the paucity of long-term high spatial/temporal resolution data. In this paper, data from the world's first long-term equatorial Global Navigational Satellite System meteorological station in Manaus (Central Amazon) is used to create a new metric, a water vapor convergence time scale, to characterize the temporal evolution of deep convection over a tropical continental region. From 3.5 years of data, 320 convective events were analyzed using a compositing analysis. Results reveal two characteristic time scales of water vapor convergence; an 8 h time scale of weak convergence and 4 h timescale of intense water vapor convergence associated with the shallow-to-deep convection transition. The 4 h shallow-to-deep transition time scale is particularly robust, regardless of convective intensity, seasonality, or nocturnal versus daytime convection. This new result provides a useful metric for both high resolution and global climate models to replicate.

We assessed the temporal evolution of vegetation activity of mangroves in the Southeastern coastal of the Gulf of California (Mexico) through a multi-temporal analysis of Landsat TM images from 1990 to 2010 where time series of the Normalized Difference Vegetation Index (NDVI) were obtained. A multivariate regression analysis showed the presence of statistically significant negative trends of NDVI (low vegetation activity) in the coverage of mangrove forest, mangrove forest with pickleweed, and pickleweed; however, we did not found any meteorological variable (built time series of average minimum and maximum temperatures, and of accumulated rainfall) that controlled the observed trends. A pixel-by-pixel spatially distributed analysis of the temporal trends of NDVI, complemented by digitalization through photo interpretation of the shrimp farms present in the study area, showed a spatial relationship between the zones of greatest loss of vegetation activity (1990–2010) and the areas with greater proliferation of shrimp farms in the study area. Our study demonstrated the applicability of NDVI for the environmental assessment of mangroves. The relationship between changes in remote sensing indices and environmental variables allows for an efficient evaluation of the main environmental impacts, which can be used for coastal planning and management., The research was supported by the Mexican Secretary of Natural Resources and Environment (SEMARNAT-CONACYT; grant number SEMARNAT-2002-C01-0147). SM-B and RJM are students of Academic Program of Geoinformatics (UACJ).

A dense Global Navigation Satellite System (GNSS) meteorological network (∼20 stations) in the central Amazon Basin in Brazil is being developed for long-term studies of deep convection/water vapor interactions and feedback. In this article, the network is described and preliminary results are presented: GNSS-derived precipitable water vapor is useful for tracking water vapor advection and in identifying convective events and water vapor convergence timescales. Upon network completion (early 2011), 3D water vapor field analyses and participation in the intensive field campaign GPM-CHUVA will provide unique data sets for initializing, constraining or validating high-resolution models or refining convective parameterizations. Copyright  2011 Royal Meteorological Society

Apresenta-se uma revisão de literatura sobre convecção naAmazônia, com foco na sua parametrização em modelos numéricos. Estudos baseados em dados observacionais obtidos durante campanhas de campo são examinados. As características básicas da convecção profunda na Amazônia, sua variabilidade temporal e geográfica são discutidas, com foco nas dificuldades que as parametrizações de convecção têm em capturar essa variabilidade, particularmente o ciclo diurno. O papel de variáveis termodinâmicas, como: CAPE e CIN é discutido por serem variáveis críticas na compreensão das deficiências em se reproduzir adequadamente o ciclo diurno da convecção. Outros elementos da física dos modelos, relevantes para parametrizações convectivas, particularmente aquelas relacionadas com os fluxos de energia da superfície e com o desenvolvimento da camada limite são também considerados. A interação de convecção rasa com radiação é apresentada. Superparametrização, como ferramenta para representação explícita da convecção, é revisada, uma vez que representa uma possível futura direção para a representação da convecção em modelos numéricos. Na conclusão fazem-se várias sugestões para estudos futuros, visando assim um melhor o entendimento de processos convectivos e a sua parametrização.

The relationship between atmospheric stability, measured as CAPE, and deep precipitating convection has been widely studied but is not definitive. In the maritime tropics, CAPE and precipitation are usually inversely correlated. In continental convection (i.e., midlatitude and tropical), no consistent relationship has been found. In this study of the semiarid Southwest, a moderate positive correlation exists, approaching 0.6. Correlations based on radiosonde data are found to be sensitive to the parcel level of origin. The strongest correlations are found by modifying the preconvective morning sounding with the maximum reported surface temperature, assuming well-mixed adiabatic layers to the level of free convection with pseudoadiabatic ascent. These results show that the upper bounds on parcel instability correlate best with precipitation. Furthermore, the CAPE–precipitation relationship is argued to depend on the convective regime being considered. The North American monsoon convective regime requires essentially only moisture advection interacting with the strong surface sensible heating over complex topography. Elimination of strong convective inhibition through intense surface sensible heating in the presence of sufficient water vapor leads to the positive CAPE–precipitation relationship on diurnal time scales. These results are discussed in light of contradictory results from other continental and maritime regions, which demonstrate negative correlations.

We employ the heat engine framework to derive a simple method for assessing the strength of irreversible processes in global climate models (GCMs). Using the explicit energy budget of an idealized GCM, we show that the thermodynamic efficiencies based on the net heating rate and frictional work rate provides a measure of physical and numerical irreversibilities present in either open (e.g., the Hadley circulation) or closed (e.g., the general circulation) circulations. In addition, we show that the Carnot efficiency is useful for assessing the maximum possible efficiency attained by closed circulations. Comparison of the work-based efficiency with that based on the net heating rate and the Carnot efficiency provides a gauge of how close to reversible and ideal the circulations are. A series of experiments with the idealized GCM demonstrate the usefulness of our method and show the sensitivity of an essentially reversible model to changes in physical and numerical parameters such as rotation period and resolution.

A recent article by J. I. Yano has indicated that there is an inconsistency in the original formulation of the quasi-equilibrium theory of Arakawa and Schubert. He argues that this inconsistency results from a contradiction in the two asymptotic limits of the theory; that is, the fractional area covered by convection, and the ratio of the convective adjustment and large-scale timescales cannot simultaneously go to zero, σ → 0 and τADJ/τLS → 0. Yano cites the heat engine theory proposed by Renno and Ingersoll as “formally establishing” this contradiction. It is demonstrated in this paper that the quasi-equilibrium framework originally developed by Arakawa and Schubert is perfectly consistent with the heat engine theory for steady-state convection, that is, when the timescale associated with the large-scale forcing τLS approximates the effective adjustment timescale of the large-scale ensemble of convective clouds τEFF. Indeed, the quasi-equilibrium framework states that, on the large scale, the at...

The North American monsoon is an important feature of the atmospheric circulation over the continent, with a research literature that dates back almost 100 years. The authors review the wide range of past and current research dealing with the meteorological and climatological aspects of the North American monsoon, highlighting historical development and major research themes. The domain of the North American monsoon is large, extending over much of the western United States from its region of greatest influence in northwestern Mexico. Regarding the debate over moisture source regions and water vapor advection into southwestern North America, there is general agreement that the bulk of monsoon moisture is advected at low levels from the eastern tropical Pacific Ocean and the Gulf of California, while the Gulf of Mexico may contribute some upper-level moisture (although mixing occurs over the Sierra Madre Occidental). Surges of low-level moisture from the Gulf of California are a significant part of intrase...

A multiple lapse time window analysis was applied to three-component broadband seismograms recorded at five TERRAscope stations in southern California to separate scattering and intrinsic attenuation. Seismic energies were integrated over three consecutive lapse time intervals: 0–15, 15–30, and 30–45 s (measured from the S arrival) for approximately 30 earthquakes with hypocentral distances of less than 70 km from each station. Using the fundamental separability of source, site, and path effects for coda waves, the integrated energies for different magnitude earthquakes were normalized to a common source size at each station, and the effect of near-site amplification is removed. Subsequently, we constructed a group of geometric spreading-corrected normalized energy-distance curves for each station region over frequency bands 0.5–1, 1–2, 2–4, and 4–8 Hz for all five stations. Two more frequency bands, 8–16 and 16–32 Hz, were added at stations PAS and SVD, for which higher sample rate data were available. A theoretical model of body wave energy propagation in a randomly heterogeneous elastic medium was employed to interpret the observation. Two parameters describe the medium in this model. These are the scattering attenuation coefficient ηs and the intrinsic attenuation coefficient ηi. By assuming that scattering is isotropic and including all orders of multiple scattering, this model predicts the spatial and temporal distribution of seismic energy. A two-step least squares fitting procedure was used to find the best fitting model parameters. The result shows the following: (1) the seismic albedo, B0 = ηs/(ηi + ηs), increases with decreasing frequency for all station regions. The difference in B0 among stations is frequency dependent, and the difference disappears at 6.0 Hz. (2) Significant differences exist for the scattering attenuation coefficient ηs and seismic albedo B0 among stations at lower frequencies. Stations on or close to the fault zone(s), such as PAS, PFO, and SVD, show a stronger scattering at frequencies of 0.75 and 1.5 Hz, whereas station ISA, located far away from any major active faults, shows the lowest scattering. (3) The coda Q−1 determined from the decay rate of coda waves lies, in general, between the intrinsic Q−1 and total Q−1, sometimes closer to the former than the latter, and sometimes opposite, depending on the frequency and station.

A mobile seismic array of seven stations was deployed at 11 sites along the fault trace of the M7.4 Landers earthquake of June 28, 1992, with a maximum offset of 1 km from the trace. We found a distinct wave train with a relatively long period following the S waves that shows up only when both the stations and the events are close to the fault trace. This wave train is interpreted as a seismic guided wave trapped in a low-velocity fault zone. To study the distribution of amplitude of the guided waves with distance from the fault trace and also their attenuation with travel distance along the fault zone, we eliminated source and recording site effects by the coda normalization method. The normalized amplitudes of guided waves show a spectral peak at 3–4 Hz, which decays sharply with distance from the fault trace. Spectral amplitudes at high frequencies (8–15 Hz) show an opposite trend, increasing with distance from the fault trace. The normalized amplitudes of guided waves at 3–4 Hz also show a systematic decrease with hypocentral distance along the fault zone, from which we infer an apparent Q of 50. In order to confirm the existence of the guided waves, a dense array of 31 stations was deployed at one of the 11 sites. The resultant records revealed unequivocal evidence for the existence of guided waves associated with the fault zone. By modeling the waveforms as S waves trapped in a low-velocity waveguide sandwiched between two homogeneous half-spaces with velocity Vs = 3.0 km/s, we infer a waveguide width of about 180 m, a shear velocity of 2.0–2.2 km/s, and a Q of ∼50. Hypocenters of aftershocks with clear guided waves show a systematic distribution both laterally and with depth delineating the extent of the low-velocity fault zone in three dimensions. We find that the zone extends to a depth of at least 10 km. This zone apparently continues to the south across the Pinto Mountain fault because guided waves are observed at stations north of the Pinto Mountain fault for earthquakes with epicenters south of it. On the other hand, the zone appears to be discontinuous at the fault bend located about 20 km north of the mainshock epicenter; guided waves were observed for stations and epicenters which are located on the same sides of the fault bend but not for those on the opposite sides.

Understanding the complex interactions between water vapor fields and deep convection on the mesoscale requires observational networks with high spatial (kilometers) and temporal (minutes) resolution. In the equatorial tropics, where deep convection dominates the vertical distribution of the most important greenhouse substance—water—these mesoscale networks are nonexistent. Global Navigational Satellite System (GNSS) meteorological networks offer high temporal/spatial resolution precipitable water vapor, but infrastructure exigencies are great. The authors report here on very accurate precipitable water vapor (PWV) values calculated from a GNSS receiver installed on a highly nonideal Amazon rain forest flux tower. Further experiments with a mechanically oscillating platform demonstrate that errors and biases of approximately 1 mm (2%–3% of PWV) can be expected when compared with a stable reference GNSS receiver for two different geodetic grade receivers/antennas and processing methods [GPS-Inferred Positioning System (GIPSY) and GAMIT]. The implication is that stable fixed antennas are unnecessary for accurate calculation of precipitable water vapor regardless of processing techniques or geodetic grade receiver.

The North American monsoon (NAM) is a dominant feature of the climate of northwest Mexico and the southwest United States. The annual monsoon, which usually lasts from July to September, contributes more than half of the yearly precipitation for much of the region. Thunderstorms brought on by the monsoon are routinely responsible for severe weather, including flooding, hail, wind, dust storms, and lightning. Tropical storms and hurricanes during the NAM season can also wreak havoc on a much larger scale.

This study entails an examination of GPS PWV for two tropical regimes, the North American Monsoon and the Amazon Basin. It is demonstrated that GPS PWV can provide useful data for data poor convective regions. Their use include indentifying dynamical features associated with deep convection in addition to providing an observational constraint on numerical models where water vapor data are lacking. Results are shown from field campaigns (The North American Monsoon Experiment) and from a new observational site in the Amazon Basin.