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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]

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]

In this paper, the authors analyze simulations of present and future climates in the western United States performed with four regional climate models (RCMs) nested within two global ocean–atmosphere climate models. The primary goal here is to assess the range of regional climate responses to increased greenhouse gases in available RCM simulations. The four RCMs used different geographical domains, different increased greenhouse gas scenarios for future-climate simulations, and (in some cases) different lateral boundary conditions. For simulations of the present climate, RCM results are compared to observations and to results of the GCM that provided lateral boundary conditions to the RCM. For future-climate (increased greenhouse gas) simulations, RCM results are compared to each other and to results of the driving GCMs. When results are spatially averaged over the western United States, it is found that the results of each RCM closely follow those of the driving GCM in the same region in both present and future climates. This is true even though the study area is in some cases a small fraction of the RCM domain. Precipitation responses predicted by the RCMs in many regions are not statistically significant compared to interannual variability. Where the predicted precipitation responses are statistically significant, they are positive. The models agree that near-surface temperatures will increase, but do not agree on the spatial pattern of this increase. The four RCMs produce very different estimates of water content of snow in the present climate, and of the change in this water content in response to increased greenhouse gases. [ABSTRACT FROM AUTHOR]

NW flow snowfall (NWFS) events are common occurrences at higher elevations (1500 to >2000 m a.s.l.) and on windward slopes in the Southern Appalachian Mountain region of the south-eastern USA. The spatial patterns of NWFS are strongly controlled by topography, resulting in pronounced spatial variability. The strong topographic and low-level convective forcing, coupled with low temperatures and strong winds, increases societal impacts. This paper analyzes the relationships between NWFS and various topographic and geographic (TOPO/GEOG) variables in the Southern Appalachians. We identified NWFS events on the basis of low-level wind direction, extracted values for the TOPO/GEOG variables from Digital Elevation Models (DEMs), and developed statistical relationships between NWFS and the TOPO/GEOG variables. Using a multivariate regression model and GIS techniques, we also mapped mean annual NWFS across the region. Results indicate that elevation and NW exposure are most strongly correlated with NWFS; however, the strength of these relationships is mediated by temperature. In the colder NWFS events, the relative importance of elevation is diminished, while NW exposure and distance to a NW slope are relatively more important. Additionally, we demonstrate that multivariate regression modeling in conjunction with GIS techniques can be an effective way to map snowfall patterns associated with specific wind directions, particularly when a strong topographic control is evident. [ABSTRACT FROM AUTHOR]

Impacts modelers and stakeholders use publicly available data sets of downscaled climate projections to assess and design infrastructure for changes in future rainfall extremes. If differences across data sets exist, infrastructure resilience decisions could change depending on which single data set is used. We assess changes in U.S. rainfall extremes from 2044–2099 compared with 1951–2005 based on 227 projections under RCP4.5 and RCP8.5 from five widely used data sets. We show there are large differences in the change magnitude and its spatial structure between data sets. At the continental scale, the data sets show different increases, with high‐end extremes (e.g. 100‐year event) generally increasing more (between 10% and 50%) than low‐end extremes (e.g. 5‐year). These differences largely contribute to the overall uncertainty for small average recurrence intervals (ARIs) extremes (2‐ to 10‐year), while uncertainties due to short record length dominate large ARIs (25‐ to 100‐year). The results indicate that robust infrastructure planning should consider these uncertainties to enable resilient infrastructure under climate change. Plain Language Summary: Observed extreme rainfall magnitudes have increased since 1950, and climate model projections indicate that these increases will continue throughout the 21st century in many areas in the US. Adapting and designing infrastructure for climate change requires future extreme rainfall projections at high resolutions. Global climate model (GCM) output resolution is generally much coarser, and methods have been developed to create relevant climate information at regional scales. Multiple open data sets exist that provide downscaled projections of future rainfall extremes. We analyze changes in future daily extremes using five widely used data sets in climate change impacts assessments and decision making. We found large differences between data sets in how much and where extreme events will intensify by the end of the 21st century. This and other sources of uncertainty need to be considered when designing resilient infrastructure. Key Points: Extreme daily rainfall changes for the United States from five widely used public downscaled climate projection data sets are comparedLarge differences in magnitude and spatial patterns of projected extreme precipitation changes exist between data setsHigh‐end extremes (e.g., 100‐year event) increase 10–50 % faster than low‐end extremes (e.g., 2‐year event) at the continental scale [ABSTRACT FROM AUTHOR]

Coastal ecosystems are dependent on terrestrial freshwater export which is affected by both climate trends and natural climate variability. However, the relative role of these factors is not clear. Here, both climate trends and internal climate variabilities at different time scales are related to variations in terrestrial freshwater export into the eastern United States ( U.S.) coastal region. For the recent 35-year period, the intensified hydro-meteorological processes (annual precipitation or evapotranspiration) may explain the observed streamflow variability in the northeast. However, in the southeast, streamflow is positively correlated with climate variability induced by the Pacific Ocean conditions (El Nino-Southern Oscillation [ENSO] and Pacific Decadal Oscillation) rather than Atlantic Ocean conditions (Atlantic Multi-decadal Oscillation and North Atlantic Oscillation). The centroid location for volume of terrestrial freshwater export integrated along the eastern U.S. has a positive temporal trend and is negatively correlated with ENSO conditions, suggesting the northward trend in freshwater export to U.S. eastern coast may be disturbed by the natural climate variability, especially ENSO conditions, i.e., the center of freshwater mass moves southward (northward) during El Nino (La Nina) years. The results indicate the spatial and temporal variations in freshwater export from the eastern U.S. are affected by both climate change and inter-annual climate variability during the recent 35-year period (1980-2014). [ABSTRACT FROM AUTHOR]

Changes in extreme temperatures, heat waves, and heavy rainfall events have adverse effects on human health, air quality, and water resources. With aerosol-only (AER) and greenhouse gas-only (GHG) simulations from 1860 to 2005 in the GFDL CM3 chemistry-climate model, aerosol-induced versus greenhouse gas-induced changes in temperature (summer) and precipitation (all seasons) extremes over the United States are investigated. Small changes in these extremes in the all forcing simulations reflect cancellations between the effects of increasing anthropogenic aerosols and greenhouse gases. In AER, extreme high temperatures and the number of days with temperatures above the 90th percentile decline over most of the United States. The strongest response occurs in the western United States (−2.0°C and −14 days, regionally averaged) and the weakest response occurs in the southeastern United States (−0.6°C and −4.8 days). An opposite-signed response pattern occurs in GHG (+2.3°C and +11.5 days over the western United States and +1.6°C and +7.2 days over the southeastern United States). The similar spatial response patterns in AER versus GHG suggest a preferred regional mode of response that is largely independent of the type of forcing. Extreme precipitation over the eastern United States decreases in AER, particularly in winter, and increases over the eastern and central United States in GHG, particularly in spring. Over the twenty-first century under the representative concentration pathway 8.5 (RCP8.5) emissions scenario, the patterns of extreme temperature and precipitation associated with greenhouse gas forcing dominate. [ABSTRACT FROM AUTHOR]

ABSTRACT Snow cover amount and duration have a large role in both the natural and anthropogenic systems of the Northeast United States. Any changes in the climatology of the amount, duration, and timing of the snowpack may have long-lasting environmental and economic consequences. At present, the principal tools used to examine future climatic changes are general circulation models; however, they do not provide information at the scales required for investigating many of the impacts in which snow plays a major role. In order to address this gap, a statistical downscaling methodology for simulating climatological snow cover parameters was developed. The methodology utilizes the Statistical DownScaling Model to construct climate change scenarios at daily time scales that are subsequently evaluated based on their ability to reproduce seasonal snow cover statistics. Two different observational datasets (station and gridded) were used as predictands and empirical relationships were created between the predictands and regional scale predictors. The methodology was tested at 20 locations across the Northeast and was then applied to output from HadCM3 under the A2 and B2 emissions scenarios. The methodology performed well at capturing key properties of station-based snow cover over a range of climates and was found to perform better than the technique used in previous work in the Northeast. By the end of the century, the projections revealed characteristics that are consistent with declining snow cover, yet there are likely to be regional variations in the next several decades, especially when elevation is considered. [ABSTRACT FROM AUTHOR]

Precipitation over the southwestern United States exhibits distinctive seasonality, and contrasting ocean–atmospheric dynamics are involved in the interannual variability of cool- and warm-season totals. Tree-ring chronologies based on annual-ring widths of conifers in the southwestern United States are well correlated with accumulated precipitation and have previously been used to reconstruct cool-season and annual precipitation totals. However, annual-ring-width chronologies cannot typically be used to derive a specific record of summer monsoon-season precipitation. Some southwestern conifers exhibit a clear anatomical transition from the earlywood and latewood components of the annual ring, and these exactly dated subannual ring components can be measured separately and used as unique proxies of cool- and warm-season precipitation and their associated large-scale ocean–atmospheric dynamics. Two 2139-yr-long reconstructions of cool- (November–May) and early-warm season (July) precipitation have been developed from ancient conifers and relict wood at El Malpais National Monument, New Mexico. Both reconstructions have been verified on independent precipitation data and reproduce the spatial correlation patterns detected in the large-scale SST and 500-mb height fields using instrumental precipitation data from New Mexico. Above-average precipitation in the cool-season reconstruction is related to El Niño conditions and to the positive phase of the Pacific decadal oscillation. Above-average precipitation in July is related to the onset of the North American monsoon over New Mexico and with anomalies in the 500-mb height field favoring moisture advection into the Southwest from the North Pacific, the Gulf of California, and the Gulf of Mexico. Cool- and warm-season precipitation totals are not correlated on an interannual basis in the 74-yr instrumental or 2139-yr reconstructed records, but wet winter–spring extremes tend to be followed by dry conditions in July and very dry winters tend to be followed by wet Julys in the reconstructions. This antiphasing of extremes could arise from the hypothesized cool- to early-warm-season change in the sign of large-scale ocean–atmospheric forcing of southwestern precipitation, from the negative land surface feedback hypothesis in which winter–spring precipitation and snow cover reduce surface warming and delay the onset of the monsoon, or perhaps from an interaction of both large-scale and regional forcing. Episodes of simultaneous interseasonal drought (“perfect” interseasonal drought) persisted for a decade or more during the 1950s drought of the instrumental era and during the eighth- and sixteenth-century droughts, which appear to have been two of the most profound droughts over the Southwest in the past 1400 yr. Simultaneous interseasonal drought is doubly detrimental to dry-land crop yields and is estimated to have occurred during the mid-seventeenth-century famines of colonial New Mexico but was less frequent during the late-thirteenth-century Great Drought among the Anasazi, which was most severe during the cool season. [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]

An examination of five temperature and five precipitation extreme indicators reveals an increase in both temperature and precipitation extremes over the 1926–2000 period in the northeast United States, with most of this increase occurring over the past four decades. Empirical orthogonal function (EOF) analysis of winter frost days (FD) and warm nights (TN90) and also winter consecutive dry days (CDD) and very wet days (R95T) over the 1950–2000 period reveals that some of the variability associated with changes in these extremes may be explained by variations in the Arctic Oscillation (AO), El Niño–Southern Oscillation (ENSO), and Pacific–North American (PNA) pattern. The most prominent feature of these results was the high correlation between the leading EOF of frost days and warm nights and the AO. Winter composites of temperature and precipitation extreme indicators were examined for different phases of the AO and ENSO during the 1926–2000 period. Overall, the AO is a better predictor of winter warm nights, while the ENSO is a better predictor of consecutive dry days in the northeast 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]

The article discusses the photographic documentation of poor observation sites within the U.S. Historical Climate Reference Network (USHCN) with respect to monitoring long-term surface air temperature trends. The objectives of the USHCN are outlined. The primary source of surface observations used to construct the long-term global surface temperature analyses has been National Oceanic and Atmospheric Administration stations, which include first-order stations and a subset of NOAA Cooperative Observer Program sites that compose the USHCN. The COOP Network has long served as the main climate observation network in the U.S., with once daily measurements of temperature, precipitation and sometimes snowfall made by depth volunteers using equipment supplied and maintained by NOAA.

There is an increasing interest in examining long-term trends in measures of snow climatology. An examination of the U.S. daily snowfall records for 1900–2004 revealed numerous apparent inconsistencies. For example, long-term snowfall trends among neighboring lake-effect stations differ greatly from insignificant to +100% century-1. Internal inconsistencies in the snow records, such as a lack of upward trends in maximum seasonal snow depth at stations with large upward trends in snowfall, point to inhomogeneities. Nationwide, the frequency of daily observations with a 10:1 snowfall-to-liquid-equivalent ratio declined from 30% in the 1930s to a current value of around 10%, a change that is clearly due to observational practice. There then must be biases in cold-season liquid-equivalent precipitation, or snowfall, or both. An empirical adjustment of snow-event, liquid-equivalent precipitation indicates that the potential biases can be statistically significant. Examples from this study show that there are nonclimatic issues that complicate the identification of and significantly change the trends in snow variables. Thus, great care should be taken in interpretation of time series of snow-related variables from the Cooperative Observer Program (COOP) network. Furthermore, full documentation of optional practices should be required of network observers so that future users of these data can properly account for such practices. [ABSTRACT FROM AUTHOR]

In 1997, during the late stages of production of NCEP-NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km-45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979-2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP-Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability. [ABSTRACT FROM AUTHOR]

The NCEP–NCAR reanalysis together with the outgoing longwave radiation anomalies (OLRAs) and a gridded daily precipitation over the United States were used to analyze precipitation over California on intraseasonal timescales. The intraseasonal (10–90 days) filtered OLRAs were subjected to singular spectrum analysis, which identifies nonlinear oscillations in noisy time series. There are two dominant oscillatory modes associated with California rainfall with periods near 36–40 and 20–25 days. The 36–40-day mode is related to the Madden–Julian Oscillation (MJO) in the Tropics. Enhanced tropical convection propagates from the western Pacific to the central Pacific. A three-cell pattern with negative OLRAs in California and positive anomalies in the eastern Pacific and the Pacific Northwest starts to develop 4 days later and rainfall starts in California. Anomalies associated with the 20–25-day mode are responsible for alternating wet and dry episodes over California with periods shorter than the timescales of the MJO. The 20–25-day mode is the leading mode in the 7–30-day band and is related to tropical convection in the Pacific. In the extratropics, cloud bands propagate northward along the west coast of North America from the eastern Pacific just north of the ITCZ through California to the Pacific Northwest. The 200-hPa streamfunction anomaly composites associated with the 20–25-day mode reveal a westward propagating wave train dominated by a zonal wavenumber 2. This mode has a spatial structure similar to the traveling pattern described by Branstator. [ABSTRACT FROM AUTHOR]

Heavy precipitation is one of the most significant natural hazards in the United States today. Knowledge of the climatography, including; the temporal characteristics, of this phenomenon is necessary in order to better plan, design for, and predict this hazard. In this study, cluster analysis is used to simplify and clarify the spatial patterns in the time of day heavy precipitation most frequently occurs. Regions with similar diurnal properties are delineated, and the substantial seasonal fluctuations in the regional patterns are traced. Of particular interest is the expansion during the cool season and contraction during the warm season of the nocturnal precipitation regime in the central United States. [ABSTRACT FROM AUTHOR]

The variability of Pennsylvania winter climate is shown to be the result of mechanisms working on two distinctly different time scales: interdecadal and interannual. Interdecadal variability is associated with hemispheric changes in large-scale atmospheric circulation regimes. During periods of zonal flow, Pennsylvania temperatures are above normal, while meridional flow is associated with below-normal temperatures. Precipitation is near normal during zonal regimes, but can be either very dry (as it was in the 1960s) or abnormally wet (like the 1970s) with meridional flow, depending on the exact placement of the deepened trough over the eastern United States. Imbedded in the interdecadal fluctuations is interannual variability which is related to two important Northern Hemisphere teleconnection patterns: the Pacific/North American (PNA) and North Atlantic Oscillation (NAO) patterns. Interannual changes in the atmospheric circulation, as expressed by indices of the two teleconnections, explain 50 percent of the variance in Pennsylvania winter temperature, but only 14 percent of the precipitation variance. It is argued that knowledge of such relationships provides a basis for refining and better interpreting models of greenhouse gas-induced climatic change. [ABSTRACT FROM AUTHOR]