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Freezing rain can cause severe impacts, particularly when it persists for many hours. In this paper, we present the climatology of long-duration (6 or more hours) freezing rain events in the United States and Canada from 1979 to 2016. We identify three focus regions from this climatology and examine the archetypal thermodynamic evolution of events in each region using surface and radiosonde observations. Long-duration events occur most frequently in the northeastern United States and southeastern Canada, where freezing rain typically begins as lower-tropospheric warm-air advection develops the warm layer aloft. This warm-air advection and the latent heat of fusion released when rain freezes at the surface erode the cold layer, and freezing rain transitions to rain once the surface temperature reaches 0°C. In the southeastern United States, a larger percentage of events are of long duration than elsewhere in North America. Weak surface cold-air advection and evaporative cooling in the particularly dry onset cold layers there prevent surface temperatures from rising substantially during events. Finally, the south-central United States has a regional maximum in the occurrence of the top 1% of events by duration (18 or more hours), despite the relative rarity of freezing rain there. These events are associated with particularly warm/deep onset warm layers, with persistent low-level cold-air advection maintaining the cold layer. The thermodynamic evolutions we have identified highlight characteristics that are key to supporting persistent freezing rain in each region and may warrant particular attention from forecasters tasked with predicting these events. [ABSTRACT FROM AUTHOR]

Extreme precipitation can have significant adverse impacts on infrastructure and property, human health, and local economies. This paper examines recent changes in extreme precipitation in the northeast United States. Daily station data from 58 stations missing less than 5% of days for the years 1979–2014 from the U.S. Historical Climatology Network were used to analyze extreme precipitation, defined as the top 1% of days with precipitation. A statistically significant (95% confidence level) increasing trend of the threshold for the top 1% of extreme precipitation events was found (0.3 mm yr−1). This increasing trend was due to both an increase in the frequency of extreme events and the magnitude of extreme events. Rainfall events ≥ 150 mm (24-h accumulation) increased in frequency from 6 events between 1979 and 1996 to 25 events between 1997 and 2014, a 317% increase. The annual daily maximum precipitation, or the highest recorded precipitation amount in a given year, increased by an average of 1.6 mm yr−1, a total increase of 58.0 mm. Decreasing trends in extreme precipitation were observed east of Lake Erie during the warm season. Increasing trends in extreme precipitation were most robust during the fall months of September, October, and November, and particularly at locations further inland. The analysis showed that increases in events that were tropical in nature, or associated with tropical moisture, led to the observed increase in extreme precipitation during the fall months. [ABSTRACT FROM AUTHOR]

Hydrologists and other users need to know the uncertainty of the satellite rainfall datasets across the range of time--space scales over the whole domain of the dataset. Here, ''uncertainty'' refers to the general concept of the ''deviation'' of an estimate from the reference (or ground truth) where the deviation may be defined in multiple ways. This uncertainty information can provide insight to the user on the realistic limits of utility, such as hydrologic predictability, which can be achieved with these satellite rainfall datasets. However, satellite rainfall uncertainty estimation requires ground validation (GV) precipitation data. On the other hand, satellite data will be most useful over regions that lack GV data, for example developing countries. This paper addresses the open issues for developing an appropriate uncertainty transfer scheme that can routinely estimate various uncertainty metrics across the globe by leveraging a combination of spatially dense GV data and temporally sparse surrogate (or proxy) GV data, such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and the Global Precipitation Measurement (GPM) mission dual-frequency precipitation radar. The TRMM Multisatellite Precipitation Analysis (TMPA) products over the United States spanning a record of 6 yr are used as a representative example of satellite rainfall. It is shown that there exists a quantifiable spatial structure in the uncertainty of satellite data for spatial interpolation. Probabilistic analysis of sampling offered by the existing constellation of passive microwave sensors indicate that transfer of uncertainty for hydrologic applications may be effective at daily time scales or higher during the GPM era. Finally, a commonly used spatial interpolation technique (kriging), which leverages the spatial correlation of estimation uncertainty, is assessed at climatologic, seasonal, monthly, and weekly time scales. It is found that the effectiveness of kriging is sensitive to the type of uncertainty metric, time scale of transfer, and the density of GV data within the transfer domain. Transfer accuracy is lowest at weekly time scales with the error doubling from monthly to weekly. However, at very low GV data density (<20%% of the domain), the transfer accuracy is too low to show any distinction as a function of the time scale of transfer. [ABSTRACT FROM AUTHOR]

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 global coupled climatic model has been used to generate a 10 000-yr simulation of “present” climate. The resultant dataset has been used to investigate a number of aspects of extremes associated with annual mean rainfall. Multimillennial time series of normalized rainfall amounts for selected points are used to highlight secular variability, spatial variations, and the differences between pluvial and drought conditions. Global distributions are also presented for selected rainfall characteristics, including the frequency of occurrence of specified rainfall anomalies with annual durations, the frequency of occurrence of 5-yr sequences of specified rainfall anomalies, and the maximum and minimum normalized rainfall amounts attained in the simulation. Such features cannot be obtained from observations because of their limited duration. A case study is also made of a megadrought over the southwestern United States, together with an analysis of the associated causal mechanisms. Given the exclusion of all external forcing from the model, it is concluded that the extreme annual mean rainfall extremes presented in the paper are attributable to stochastic events. [ABSTRACT FROM AUTHOR]

A method is presented to obtain the climatology of extreme wind speeds coincident with the occurrence of rain. The simultaneous occurrence of wind and rain can force water through building wall components such as windows, resulting in building damage and insured loss. To quantify this hazard, extreme value distributions are fit to peak 3-s wind speed data recorded during 1-min intervals with specific reported rain intensities. This improves upon previous attempts to quantify the wind-driven rain hazard that computed wind speed and rainfall-intensity probabilities independently and used hourly data that cannot assure the simultaneous occurrence of peak wind that represents only a several-second interval within the hour and rain that is accumulated over the entire hour. The method is applied across the southeastern United States, where the wind-driven rain hazard is most pronounced. For the lowest rainfall intensities, the computed wind speed extremes agree with published values that ignore rainfall occurrence. Such correspondence is desirable for aligning the rain-intensity-dependent wind speed return periods with established extreme wind statistics. Maximum 50-yr return-period wind speeds in conjunction with rainfall intensities ≥0.254 mm min−1 exceed 45 m s−1 in a swath from Oklahoma to the Gulf Coast and at stations along the immediate Atlantic coast. For rainfall intensities >2.54 mm min−1 maximum, 50-yr return-period wind speeds decrease to 35 m s−1 but occur over a similar area. The methodology is also applied to stations outside the Southeast to demonstrate its applicability for incorporating the wind-driven rain hazard in U.S. building standards. Significance Statement: Rainfall driven horizontally by strong winds can penetrate building components and cladding. If unmanaged, this can directly damage the building and its contents and become a substantial component of insured losses to buildings. A climatology of wind-driven rain is developed from recently available 1-min weather observations that better represent the joint occurrence of the extremes that define wind-driven rain occurrence than hourly data. This work is a first implementation of 1-min data into extreme-value statistical models, providing a basis for including wind-driven rain in United States building codes. This inclusion would be most significant in the hurricane-prone regions of the southeastern United States. The omission of wind-driven rain in U.S. building codes contrasts to its inclusion in Europe and Canada. [ABSTRACT FROM AUTHOR]

Each year flash floods cause considerable property damage and loss of life, yet the heavy precipitation events responsible for flash floods remain extremely difficult to forecast, especially during summer. This paper presents synoptic analog models for use in the shod-range prediction of summertime extreme rainstorms in Minnesota. To develop these analog models, forty-three heavy rain events that occurred from 1974-78 first were classified into four similar categories on the basis of the spatial properties of their rainfall distributions. Next, composite fields of surface and upper-air parameters were prepared for each of the four categories, and features on the composite maps that contributed most to the occurrence of heavy rainfall were incorporated into synoptic analog models. The analog models reveal that the typical circulation patterns for the four rainfall types vary significantly and that the spatial characteristics of extreme rainstorms are determined by the synoptic-scale circulation regime in which the rainstorms form. This interrelationship between the spatial characteristics and atmospheric circulation can be used to improve subjective forecasts of location and areal extent of extreme rainstorms. The results of this study also indicate that the preparation of synoptic analog models for local areas can improve our understanding of the climatology of heavy precipitation. [ABSTRACT FROM AUTHOR]

Spatial and temporal differences in the processes that transform precipitation into runoff are a common source of error in watershed models. For large watersheds, spatial disaggregation of the drainage area can improve efforts to model the precipitation-runoff relationship when the model employs physically explainable variables to represent horizontal and vertical variations in moisture fluxes and storages. The paper presents the conceptual structure of a hydroclimatic model that simulates the runoff process as four functionally discrete subsystems linked in series. Moisture inputs are routed through each subsystem employing environmentally dictated rules and readily available data. Dividing the basin into homogeneous subunits addresses the problem of horizontal heterogeneity. Residence times for two groundwater storage subsystems are calculated by an optimization algorithm included in the model. Modeled hydroclimatic characteristics for the Deschutes River Basin in Oregon illustrate the ability of the model to reveal important spatial and temporal differences in the runoff process. Sectors representing 20 percent of the basin area contribute 57 percent of modeled groundwater recharge and 61 percent of total modeled runoff for the watershed, but some other sectors make a relatively small quantitative contribution to basin runoff. Moisture exchange processes in the basin display explicit seasonal characteristics that explain the surprisingly large proportion of annual precipitation allocated to groundwater recharge and the dampening of the seasonal moisture input by the groundwater storages. This knowledge of the basin runoff process provides a rational basis for formulating water management strategies for the watershed. [ABSTRACT FROM AUTHOR]

Attribution of extreme events is a challenging science and one that is currently undergoing considerable evolution. In this paper are 19 analyses by 18 different research groups, often using quite different methodologies, of 12 extreme events that occurred in 2012. In addition to investigating the causes of these extreme events, the multiple analyses of four of the events, the high temperatures in the United States, the record low levels of Arctic sea ice, and the heavy rain in northern Europe and eastern Australia, provide an opportunity to compare and contrast the strengths and weaknesses of the various methodologies. The differences also provide insights into the structural uncertainty of event attribution, that is, the uncertainty that arises directly from the differences in analysis methodology. In these cases, there was considerable agreement between the different assessments of the same event. However, different events had very different causes. Approximately half the analyses found some evidence that anthropogenically caused climate change was a contributing factor to the extreme event examined, though the effects of natural fluctuations of weather and climate on the evolution of many of the extreme events played key roles as well. [ABSTRACT FROM AUTHOR]

This research applies an automated mesoscale convective system (MCS) segmentation, classification, and tracking approach to composite radar reflectivity mosaic images that cover the contiguous United States (CONUS) and span a relatively long study period of 22 years (1996–2017). These data afford a novel assessment of the seasonal and interannual variability of MCSs. Additionally, hourly precipitation data from 16 of those years (2002–17) are used to systematically examine rainfall associated with radar-derived MCS events. The attributes and occurrence of MCSs that pass over portions of the CONUS east of the Continental Divide (ECONUS), as well as five author-defined subregions—North Plains, High Plains, Corn Belt, Northeast, and Mid-South—are also examined. The results illustrate two preferred regions for MCS activity in the ECONUS: 1) the Mid-South and Gulf Coast and 2) the Central Plains and Midwest. MCS occurrence and MCS rainfall display a marked seasonal cycle, with most of the regions experiencing these events primarily during the warm season (May–August). Additionally, MCS rainfall was responsible for over 50% of annual and seasonal rainfall for many locations in the ECONUS. Of particular importance, the majority of warm-season rainfall for regions with high agricultural land use (Corn Belt) and important aquifer recharge properties (High Plains) is attributable to MCSs. These results reaffirm that MCSs are a significant aspect of the ECONUS hydroclimate. [ABSTRACT FROM AUTHOR]

Over the last six to seven decades, there has been a substantial increase in atmospheric research to better understand the dynamics and evolution of atmospheric blocking events. It is well known that atmospheric blocking serves as a catalyst for increasing the frequency of atmospheric flow regime stagnation and forecast unpredictability. This study built upon the results of previous work by expanding upon the findings of various climatologies and case studies. This work analyzes specific trends observed in association with atmospheric blocking predominantly across the central and eastern Pacific Ocean. Such trends include the relationship between the size, duration, and onset position of atmospheric blocking events and the frequency, duration, and intensity of heavy rainfall events across the central United States. A strong focus is placed on examining the duration and spatial extent of atmospheric blocking which has been found to influence the intensity of heavy rainfall events. The goal is to further bridge the gap between the location and duration of blocking highs and the intensity, duration, and frequency of heavy rainfall events which occur downstream of such blocking events. [ABSTRACT FROM AUTHOR]

Factors responsible for extreme monthly rainfall over Texas and Oklahoma during May 2015 are assessed. The event had a return period of at least 400 years, in contrast to the prior record, which was roughly a 100-yr event. The event challenges attribution science to disentangle factors because it occurred during a strong El Niño, a natural pattern of variability that affects the region's springtime rains, and during the warmest global mean temperatures since 1880. Effects of each factor are diagnosed, as is the interplay between El Niño dynamics and human-induced climate change. Analysis of historical climate simulations reveals that El Niño was a necessary condition for monthly rains to occur having the severity of May 2015. The model results herein further reveal that a 2015 magnitude event, whether conditioned on El Niño or not, was made neither more intense nor more likely to be due to humaninduced climate change over the past century. The intensity of extreme May rainfall over Texas and Oklahoma, analogous to the 2015 event, increases by roughly 5% by the latter half of the twenty-first century. No material changes occur in either El Niño-related teleconnections or in overall atmospheric dynamics during extreme May rainfall over the twenty-first century. The increased severity of Texas/Oklahoma May rainfall events in the future is principally due to thermodynamic driving, although much less than implied by simple Clausius-Clapeyron scaling arguments given a projected 23% increase in atmospheric precipitable water vapor. Other thermodynamic factors are identified that act in opposition to the increase in atmospheric water vapor, thereby reducing the effectiveness of overall thermodynamic driving of extreme May rainfall changes over Texas and Oklahoma. [ABSTRACT FROM AUTHOR]

Rain-on-snow (ROS) events have caused severe floods in mountainous areas in the recent past. Because of the complex interactions of physical processes, it is still difficult to accurately predict the effect of snow cover on runoff formation for an upcoming ROS event. In this study, a detailed physics-based energy balance snow cover model (SNOWPACK) was used to assess snow cover processes during more than 1000 historical ROS events at 116 locations in the Swiss Alps. The simulations of the mass and energy balance, liquid water flow, and the temporal evolution of structural properties of the snowpack were used to analyze runoff formation characteristics during ROS events. Initial liquid water content and snow depth at the onset of rainfall were found to influence the temporal dynamics, intensities, and cumulative amount of runoff. The meteorological forcing is modulated by processes within the snowpack, leading to an attenuation of runoff intensities for intense and short rain events and an amplifying effect for longer rain events. The timing of runoff generation relative to the rainfall seems to be strongly dependent on initial liquid water content, snow depth, and rainfall intensities. As these snowpack and meteorological conditions usually exhibit a strong seasonality, cumulative runoff generation during ROS also varies seasonally. ROS events with intensified snowpack runoff were found to be most common during late snowmelt season, with several such events also occurring in late autumn. These results demonstrate the strong influence of initial snowpack properties on runoff formation during ROS events in the Swiss Alps. [ABSTRACT FROM AUTHOR]

A 2D video disdrometer (2DVD) probe was used to gather detailed drop measurements over a 770-min rain event. Accumulated totals of the rainfall and of the number of drops for each square centimeter showed persistent, significant correlated structures across the approximately 11 cm × 11 cm grid of the 2DVD. This is surprising because larger-scale studies suggest that the values in each square centimeter should be highly correlated with very little variation. Nevertheless, this correlation remains strikingly similar to what is observed at a coarser resolution, suggesting that it somehow scales with spatial resolution. However, because the correlation functions are not power laws, the origin of this scaling must be due to a factor other than fractal geometry. Analysis reveals that this occurs because of a filtering effect such that as the domain size (or resolution of a remote sensor) becomes finer, it is only the smaller wavelengths that contribute most to the variance so that the correlation function also scales. Consequently, correlated finescale structures can apparently occur even over 10 cm. This fine structure was also found for the kinetic energy and impact power of the rain, important for understanding the initiation of soil erosion. The patterns in the integrated parameters appeared to arise almost exclusively from patterns in the total number of drops with patterns in the drop sizes playing an insignificant role. Therefore, in future studies of rain it is recommended that the total number of drops be retained as a crucial variable. [ABSTRACT FROM AUTHOR]

An analysis of three predecessor rain events (PREs) that occurred ahead of North Atlantic tropical cyclone (TC) Ike and east Pacific TC Lowell during 10-15 September 2008 is presented. The three PREs produced all-time daily record rainfall at many locations, including Lubbock, Texas (189.5 mm); Wichita, Kansas (262 mm); and Chicago-O'Hare, Illinois (169 mm), on 11-13 September, respectively. PRE 1 organized over Texas on 10 September with moisture from a stalled frontal boundary and the Bay of Campeche, and matured with moisture from TC Lowell. PRE 2 organized over the Texas Panhandle on 11 September with moisture from the Bay of Campeche, and developed and matured over Kansas and Missouri with moisture from TC Lowell. PRE 3 developed over Texas on 11 September, merged with and absorbed PRE 2 over Kansas and Missouri, and matured as it ingested moisture from TC Ike. All three PREs matured in the equatorward entrance region of an intensifying subtropical jet stream (STJ). Heavy rainfall with the three PREs occurred along a plume of moist air characterized by high precipitable water values that extended poleward over the central United States near the juxtaposition of the nose of a low-level jet, a region of lower-tropospheric forcing for ascent along a surface baroclinic zone, and the STJ equatorward entrance region. The cumulative upscale effect of persistent deep convection from the three PREs enhanced and 'locked in' a favorable upper-tropospheric flow pattern conducive to ridge development over the Ohio Valley and STJ intensification over the central U.S. and Great Lakes region. [ABSTRACT FROM AUTHOR]

Using 13 yr of data from the Tropical Rainfall Measuring Mission (TRMM) satellite, a regional climatology of monsoonal precipitation is created for portions of the southwest United States. The climatology created using precipitation features defined from the TRMM precipitation radar (PR) shows that the population of features includes a large number of small, weak features that do not produce much rain and are very shallow. A lesser percentage of large, stronger features contributes most of the region's rainfall. Dividing the features into categories based on the median values of volumetric rainfall and maximum height of the 30-dB Z echo is a useful way to visualize the population of features, and the categories selected reflect the life cycle of monsoonal convection. An examination of the top rain-producing features at different elevations reveals that extreme features tend to occur at lower elevations later in the day. A comparison with the region studied in the North American Monsoon Experiment (NAME) shows that similar diurnal patterns occur in the Sierra Madre Occidental region of Mexico. The population of precipitation features in both regions is similar, with the NAME region producing slightly larger precipitation systems on average than the southwest United States. Both regions on occasion demonstrate the pattern of convection initiating at high elevations and moving downslope while growing upscale through the afternoon and evening; however, there are also days on which convection remains over the high terrain. [ABSTRACT FROM AUTHOR]

Physical processes responsible for the abnormally wet condition in the Central Intermountain West (CIW) of the United States in June 2009 were investigated. It was illustrated that persistent rainy conditions over the CIW during June 2009 were associated with a pronounced circumglobal teleconnection pattern, which is characterized as a short Rossby wave train along the jet stream waveguide with a wave number 5 structure. The ascending motion and moisture flux convergence over the CIW associated with the cyclonic action center over the US West Coast in the teleconnection wave train could be essential for the persistent local rainfall during June 2009. Further analysis suggested that the June 2009 circulation pattern is consistent with a prevailing mode of the summer circumglobal teleconnection pattern. The findings in this study provide information for improved understanding of the early summer rainfall regime in the CIW. [ABSTRACT FROM AUTHOR]

Case studies have shown that heavy precipitation events and rapid cyclogenesis in the extratropics can be fueled by moist and warm tropical air masses. Often the tropical moisture export (TME) occurs through a longitudinally confined region in the subtropics. Here a comprehensive climatological analysis of TME is constructed on the basis of seven-day forward trajectories started daily from the tropical lower troposphere using 6-hourly 40-yr ECMWF Re-Analysis (ERA-40) data from the 23-year period 1979–2001. The objective TME identification procedure retains only those trajectories that reach a water vapor flux of at least 100 g kg-1 m s-1 somewhere north of 35°N. The results show four distinct activity maxima with different seasonal behavior: (i) The “pineapple express,” which connects tropical moisture sources near Hawaii with precipitation near the North American west coast, has a marked activity maximum in boreal winter. (ii) TME over the west Pacific is largest in summer, partly related to the East Asian monsoon and the mei-yu–baiu front. This region alone is responsible for a large portion of TME across 35°N. (iii) The narrow activity maximum over the Great Plains of North America is rooted over the Gulf of Mexico and the Caribbean Sea and has a clear maximum in summer and spring. (iv) TME over the western North Atlantic shows the smallest annual cycle with a maximum in winter and autumn. The interannual variability of (i) and (iv) is significantly modulated by El Niño. Over the African–European–Asian region, high orographic barriers impede TME. A typical TME trajectory evolution is poleward and quasi-horizontal in the subtropics and then more eastward and upward in the southern midlatitudes, where TME contributes up to 60% to climatological precipitation. The TME dataset presented here can serve as a basis for future studies on extreme events. [ABSTRACT FROM AUTHOR]

Partial-duration maximum precipitation series from Historical Climatology Network stations are used as a basis for assessing trends in extreme-precipitation recurrence-interval amounts. Two types of time series are analyzed: running series in which the generalized extreme-value (GEV) distribution is fit to separate overlapping 30-yr data series and lengthening series in which more recent years are iteratively added to a base series from the early part of the record. Resampling procedures are used to assess both trend and field significance. Across the United States, nearly two-thirds of the trends in the 2-, 5-, and 10-yr return-period rainfall amounts, as well as the GEV distribution location parameter, are positive. Significant positive trends in these values tend to cluster in the Northeast, western Great Lakes, and Pacific Northwest. Slopes are more pronounced in the 1960–2007 period when compared with the 1950–2007 interval. In the Northeast and western Great Lakes, the 2-yr return-period precipitation amount increases at a rate of approximately 2% per decade, whereas the change in the 100-yr storm amount is between 4% and 9% per decade. These changes result primarily from an increase in the location parameter of the fitted GEV distribution. Collectively, these increases result in a median 20% decrease in the expected recurrence interval, regardless of interval length. Thus, at stations across a large part of the eastern United States and Pacific Northwest, the 50-yr storm based on 1950–79 data can be expected to occur on average once every 40 yr, when data from the 1950–2007 period are considered. [ABSTRACT FROM AUTHOR]

Data obtained from NOAA's Geostationary Operational Environmental Satellite (GOES) and NASA's Tropical Rainfall Measuring Mission (TRMM) satellites were used to investigate the relationships between topography, large-scale circulation, and the climatology of precipitation and cloudiness in the Andes—specifically over Peru and the Altiplano Plateau—at diurnal, seasonal, and interannual time scales. The spatial variability of cloudiness was assessed through empirical orthogonal function (EOF) analysis of GOES brightness temperatures. Results indicate that landform is the principal agent of the space–time variability of moist atmospheric processes in the Andes, with the first mode explaining up to 70% of all observed variability. These results substantiate the differences between “continental” (Andes and Himalayas) and “maritime” (Western Cordillera) orographic precipitation regimes, reflecting the degree to which upwind landmasses modulate moisture transport toward and across mountain barriers. GOES brightness temperatures show that afternoon convective activity during the rainy season is more intense on wet hydrometeorological years such as 2001, whereas the space–time structure of nighttime cloudiness at the foothills and outlets of deep interior valleys does not change during the monsoon and from one year to another independently of large-scale conditions. This suggests that daytime cloud formation and precipitation is strongly dependent on large-scale moisture transport. Interactions between mesoscale and ridge–valley circulations, which are locked to the topography, determine the space–time organization of clouds and precipitation at nighttime. This leads to strong clustering of precipitation features associated with enhanced convection at high elevations along the ridges and near the headwaters of the major river systems in the TRMM data. [ABSTRACT FROM AUTHOR]

Precipitation recycling is one of the key mechanisms linking the land surface and atmospheric dynamics. This work explores the physical mechanisms that modulate precipitation recycling variability at the daily-to-intraseasonal time scales in the central U.S. plains ecoregion using a set of land–atmosphere variables derived from the North American Regional Reanalysis dataset. Recycling estimates are performed using the Dynamic Recycling Model, which allows for analysis at shorter time scales than the previous bulk recycling models. In the central U.S. plains ecoregion local evapotranspiration only becomes an important contributor to precipitation when moisture of advective origin, the largest contributor to precipitation, diminishes. Consequently, the recycling ratio is negatively correlated to precipitation. The dominant mechanism is a negative feedback, which ensures that, even when precipitation is low, evapotranspiration continues to feed moisture into the overlying atmosphere and contribute to rainfall. Consequently, in the central U.S. plains, precipitation recycling acts as a mechanism for ecoclimatological stability through local negative feedbacks. Additionally, the zonal and meridional winds and moisture fluxes were also found to be important drivers of recycling variability. As winds decrease, the air has more time to traverse the region and capture moisture of evaporative origin. Evapotranspiration variability is not an important driver for recycling ratio variability in the central U.S. plains. Only during the extremely dry 1988 summer drought, when soil moisture storage was depleted, did the recycling ratio variability closely follow evapotranspiration. [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) are a dominant climatological feature of the central United States and are responsible for a substantial fraction of warm season rainfall. Yet very little is known about the predictability of MCSs. To help alleviate this situation, a series of ensemble simulations of an MCS are performed on a two-dimensional, storm-scale (Δx = 1 km) model. Ensemble member perturbations in wind speed, relative humidity, and instability are based on current 24-h forecast errors from the North American Model (NAM). The ensemble results thus provide an upper bound on the predictability of mesoscale convective systems within realistic estimates of environmental uncertainty, assuming successful convective initiation. The simulations are assessed by considering an ensemble member a success when it reproduces a convective system of at least 20 km in length (roughly the size of two convective cells) within 100 km on either side of the location of the MCS in the control run. By that standard, MCSs occur roughly 70% of the time for perturbation magnitudes consistent with 24-h forecast errors. Reducing the perturbations for all fields to one-half the 24-h error values increases the MCS success rate to over 90%. The same improvement in forecast accuracy would lead to a 30%–40% reduction in maximum surface wind speed uncertainty and a roughly 20% reduction in the uncertainty in maximum updraft strength, and initially slower growth in the uncertainty in the size of the MCS. However, the occurrence of MCSs drops below 50% as the midlayer mean relative humidity falls below 65%. The response of the model to reductions in forecast errors for instability, moisture, and wind speed is not consistent and cannot be easily generalized, but each can have a substantial impact on forecast uncertainty. [ABSTRACT FROM AUTHOR]

Raindrop collision and breakup is a stochastic process that affects the evolution of drop size distributions (DSDs) in precipitating clouds. Low and List have remained the obligatory reference on this matter for almost three decades. Based on a limited number of drop sizes (10), Low and List proposed generalized parameterizations of collisional breakup across the raindrop spectra that are standard building blocks for numerical models of rainfall microphysics. Here, recent laboratory experiments of drop collision at NASA’s Wallops Island Facility (NWIF) using updated high-speed imaging technology with the objective of assessing the generality of Low and List are reported. The experimental fragment size distributions (FSDs) for the collision of selected drop pairs were evaluated against explicit simulations using a dynamical microphysics model (Prat and Barros, with parameterizations based on Low and List updated by McFarquhar). One-to-one comparison of the FSDs shows similar distributions; however, the model was found to underestimate the fragment numbers observed in the smallest diameter range (e.g., D < 0.2 mm), and to overestimate the number of fragments produced when small drops (diameter DS ≥ 1mm) and large drops (diameter DL ≥ 3mm) collide. This effect is particularly large for fragments in the 0.5–1.0-mm range, and more so for filament breakup (the most frequent type of breakup observed in laboratory conditions), reflecting up to 30% uncertainty in the left-hand side of the FSD (i.e., the submillimeter range). For coalescence, the NWIF experiments confirmed the drop collision energy cutoff (ET) estimated by Low and List (i.e., ET > 5.0 μJ). Finally, the digital imagery of the laboratory experiments was analyzed to determine the characteristic time necessary to reach stability in relevant statistical properties. The results indicate that the temporal separation between particle (i.e., single hydrometeor) and population behavior, that is, the characteristic time scale to reach homogeneity in the NWIF raindrop populations, is 160 ms, which provides a lower bound to the governing time scale in population-based microphysical models. [ABSTRACT FROM AUTHOR]

A revised framework is presented that quantifies observed changes in the climate of the contiguous United States through analysis of a revised version of the U.S. Climate Extremes Index (CEI). The CEI is based on a set of climate extremes indicators that measure the fraction of the area of the United States experiencing extremes in monthly mean surface temperature, daily precipitation, and drought (or moisture surplus). In the revised CEI, auxiliary station data, including recently digitized pre-1948 data, are incorporated to extend it further back in time and to improve spatial coverage. The revised CEI is updated for the period from 1910 to the present in near–real time and is calculated for eight separate seasons, or periods. Results for the annual revised CEI are similar to those from the original CEI. Observations over the past decade continue to support the finding that the area experiencing much above-normal maximum and minimum temperatures in recent years has been on the rise, with infrequent occurrence of much below- normal mean maximum and minimum temperatures. Conversely, extremes in much below-normal mean maximum and minimum temperatures indicate a decline from about 1910 to 1930. An increasing trend in the area experiencing much above-normal proportion of heavy daily precipitation is observed from about 1950 to the present. A period with a much greater-than-normal number of days without precipitation is also noted from about 1910 to the mid-1930s. Warm extremes in mean maximum and minimum temperature observed during the summer and warm seasons show a more pronounced increasing trend since the mid-1970s. Results from the winter season show large variability in extremes and little evidence of a trend. The cold season CEI indicates an increase in extremes since the early 1970s yet has large multidecadal variability. [ABSTRACT FROM AUTHOR]

The modulation of El Niño and La Niña responses by the long-term sea surface temperature (SST) warming trend in the Indian–Western Pacific (IWP) Oceans has been investigated using a large suite of sensitivity integrations with an atmospheric general circulation model. These model runs entail the prescription of anomalous SST conditions corresponding to composite El Niño or La Niña episodes, to SST increases associated with secular warming in IWP, and to combinations of IWP warming and El Niño/La Niña. These SST forcings are derived from the output of coupled model experiments for climate settings of the 1951–2000 and 2001–50 epochs. Emphasis is placed on the wintertime responses in 200-mb height and various indicators of surface climate in the North American sector. The model responses to El Niño and La Niña forcings are in agreement with the observed interannual anomalies associated with warm and cold episodes. The wintertime model responses in North America to IWP warming bear a distinct positive (negative) spatial correlation with the corresponding responses to La Niña (El Niño). Hence, the amplitude of the combined responses to IWP warming and La Niña is notably higher than that to IWP warming and El Niño. The model projections indicate that, as the SST continues to rise in the IWP sector during the twenty-first century, the strength of various meteorological anomalies accompanying La Niña (El Niño) will increase (decrease) with time. The response of the North American climate and the zonal mean circulation to the combined effects of IWP forcing and La Niña (El Niño) is approximately equal to the linear sum of the separate effects of IWP warming and La Niña (El Niño). The summertime responses to IWP warming bear some similarity to the meteorological anomalies accompanying extended droughts and heat waves over the continental United States. [ABSTRACT FROM AUTHOR]

Summer simulations over the contiguous United States and Mexico with the Regional Atmospheric Modeling System (RAMS) dynamically downscaling the NCEP–NCAR Reanalysis I for the period 1950–2002 (described in Part I of the study) are evaluated with respect to the three dominant modes of global SST. Two of these modes are associated with the statistically significant, naturally occurring interannual and interdecadal variability in the Pacific. The remaining mode corresponds to the recent warming of tropical sea surface temperatures. Time-evolving teleconnections associated with Pacific SSTs delay or accelerate the evolution of the North American monsoon. At the period of maximum teleconnectivity in late June and early July, there is an opposite relationship between precipitation in the core monsoon region and the central United States. Use of a regional climate model (RCM) is essential to capture this variability because of its representation of the diurnal cycle of convective rainfall. The RCM also captures the observed long-term changes in Mexican summer rainfall and suggests that these changes are due in part to the recent increase in eastern Pacific SST off the Mexican coast. To establish the physical linkage to remote SST forcing, additional RAMS seasonal weather prediction mode simulations were performed and these results are briefly discussed. In order for RCMs to be successful in a seasonal weather prediction mode for the summer season, it is required that the GCM provide a reasonable representation of the teleconnections and have a climatology that is comparable to a global atmospheric reanalysis. [ABSTRACT FROM AUTHOR]

Fifty-three years of the NCEP–NCAR Reanalysis I are dynamically downscaled using the Regional Atmospheric Modeling System (RAMS) to generate a regional climate model (RCM) climatology of the contiguous United States and Mexico. Data from the RAMS simulations are compared to the recently released North American Regional Reanalysis (NARR), as well as observed precipitation and temperature data. The RAMS simulations show the value added by using a RCM in a process study framework to represent North American summer climate beyond the driving global atmospheric reanalysis. Because of its enhanced representation of the land surface topography, the diurnal cycle of convective rainfall is present. This diurnal cycle largely governs the transitions associated with the evolution of the North American monsoon with regards to rainfall, the surface energy budget, and surface temperature. The lower frequency modes of convective rainfall, though weaker, account for rainfall variability at a remote distance from elevated terrain. As in previous studies with other RCMs, RAMS precipitation is overestimated compared to observations. The Great Plains low-level jet (LLJ) is also well represented in both RAMS and NARR, but the Baja LLJ and associated gulf surges are not. [ABSTRACT FROM AUTHOR]

Lake-effect snowstorms are important parts of the climate of the U.S. Upper Midwest, with significant economic and societal impacts on communities close to the Great Lakes. Some impacts, particularly those on air and ground transportation, depend critically on the time of day that lake-effect precipitation occurs. This study utilizes hourly precipitation data collected near Lakes Superior and Michigan to determine the diurnal behavior of lake-effect precipitation frequency. Precipitation data from approximately 200 lake-effect days during 1988–93, identified by a previous study based on visible satellite data, are examined. A distinct morning maximum and afternoon/evening minimum in lake-effect precipitation frequency was observed, with the largest variations at sites within the snowbelt regions. The relative importance of several factors known to influence lake-effect precipitation development was examined to gain insight into the physical mechanisms controlling the diurnal evolution of lake-effect precipitation. [ABSTRACT FROM AUTHOR]

Utilizes results from each of the mesoscale convective complex (MCC) summaries compiled between 1978 and 1999 for the U.S. in order to develop a more complete climatology, or description of long-term means and interannual variation, of these storms. Indication that during the warm season, significant portions of the Great Plains receive, on average, between 8 percent and 18 percent of their total precipitation from MCC rainfall.

In this work, recent (1948-2001) rainfall data in a southwestern California station (San Diego) and a northwestern Baja California station (Ensenada) within a region called Mediterranean California, around 33°N, 117°W, are studied. Cumulative annual means are used as indicators of climatological variability; but the entire datasets are analyzed by modeling the histogram of each set as a Weibull distribution probability density function, f. The climatology of both stations, defined simply as the arithmetic average, is compared with their theoretical mean; that is, the first moment of f. It is assumed that this comparison would be indicative of the reliability of the available rainfall climatologies. If these assumptions hold, in particular if the data is indeed Weibull distributed, it can be concluded that the climatological annual mean precipitation in this region is slightly overestimated at this time. [ABSTRACT FROM AUTHOR]

The article discusses the climatic cycles and treegrowths in the U.S. It highlights the ecologist interest in the correlation of treegrowth rainfall. According to that author, in dry climates, the ring thickness is proportional to the amount of rainfall in the year with an accuracy of seventy percent. It says that the trees were tabulated in groups of 10 or more, but a remarkable correspondence exists between individual trees of each group. It also says that double rings in the arid regions were found to be correlated with deficient winter snowfall, so that the tree had not enough water to continue forming its summer wood, and passed to forming autumn wood before the summer rains enabled it to start a fresh zone of wide elements.