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Extensive and severe droughts have substantial effects on water supplies, agriculture, and aquatic ecosystems. To better understand these droughts, we used tree-ring-based reconstructions of the Palmer drought severity index (PDSI) for the period 1475–2017 to examine droughts that covered at least 33% of the conterminous United States (CONUS). We identified 37 spatially extensive drought events for the CONUS and examined their spatial and temporal patterns. The duration of the extensive drought events ranged from 3 to 12 yr and on average affected 43% of the CONUS. The recent (2000–08) drought in the southwestern CONUS, often referred to as the turn-of-the-century drought, is likely one of the longest droughts in the CONUS during the past 500 years. A principal components analysis of the PDSI data from 1475 through 2017 resulted in three principal components (PCs) that explain about 48% of the variability of PDSI and are helpful to understand the temporal and spatial variability of the 37 extensive droughts in the CONUS. Analyses of the relations between the three PCs and well-known climate indices, such as indices of El Niño–Southern Oscillation, indicate statistically significant correlations; however, the correlations do not appear to be large enough (all with an absolute value less than 0.45) to be useful for the development of drought prediction models. Significance Statement To better understand the variability of spatially extensive U.S. droughts through time and across space, we examined tree-ring-based reconstructions of a relative dryness/wetness index for the period 1475–2017. We identified 37 extensive drought events with durations that ranged from 3 to 12 years and that on average affected 43% of the conterminous United States. Also, three of the seven longest droughts occurred after 1900. Because associations between indices of climatic conditions and drought are weak, use of climatic indices for predictive models of drought seems tenuous.

The Colorado River basin (CRB) supplies water to approximately 40 million people and is essential to hydropower generation, agriculture, and industry. In this study, a monthly water balance model is used to compute hydroclimatic water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff) for the period 1901–2014 across the entire CRB. The time series of monthly runoff is aggregated to compute water-year runoff and then used to identify drought periods in the basin. For the 1901–2014 period, eight basinwide drought periods were identified. The driest drought period spanned years 1901–04, whereas the longest drought period occurred during 1943–56. The eight droughts were primarily driven by winter precipitation deficits rather than warm temperature anomalies. In addition, an analysis of prehistoric drought for the CRB—computed using tree-ring-based reconstructions of the Palmer drought severity index—indicates that during some past centuries drought frequency was higher than during the twentieth century and that some centuries experienced droughts that were much longer than those during the twentieth century. More frequent or longer droughts than those that occurred during the twentieth century, combined with continued warming associated with climate change, may lead to substantial future water deficits in the CRB.

Across the Upper Missouri River Basin, the recent drought of 2000 to 2010, known as the “turn-of-the-century drought,” was likely more severe than any in the instrumental record including the Dust Bowl drought. However, until now, adequate proxy records needed to better understand this event with regard to long-term variability have been lacking. Here we examine 1,200 y of streamflow from a network of 17 new tree-ring–based reconstructions for gages across the upper Missouri basin and an independent reconstruction of warm-season regional temperature in order to place the recent drought in a long-term climate context. We find that temperature has increasingly influenced the severity of drought events by decreasing runoff efficiency in the basin since the late 20th century (1980s) onward. The occurrence of extreme heat, higher evapotranspiration, and associated low-flow conditions across the basin has increased substantially over the 20th and 21st centuries, and recent warming aligns with increasing drought severities that rival or exceed any estimated over the last 12 centuries. Future warming is anticipated to cause increasingly severe droughts by enhancing water deficits that could prove challenging for water management.

Land‐use and climate change are significantly affecting stream ecosystems, yet understanding of their long‐term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land‐use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin‐wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land‐use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project ‐ Phase 5 (CMIP5) and a watershed‐wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land‐use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed‐wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land‐use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed‐wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%–26.2% of stream kilometers, dependent on land‐use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land‐use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions., Maps showing small NHDplusV2 catchments (

Flood variability due to changes in climate is a major economic and social concern. Climate drivers can affect the amount and distribution of flood-generating precipitation through seasonal shifts in storm tracks. An understanding of how the drivers may change in the future is critical for identifying the regions where the magnitude of floods may change. Here we show the regions in the conterminous U.S. where seasonal changes in global-scale climate oscillations have driven a large part of the variability of flood magnitude. The regions are cohesive across multiple watershed boundaries suggesting that variability in floods is driven by regional climate influences. Correlations with climate indices indicate that floods in the western and southern U.S. are most affected by global-scale climate. The regions provide a useful approach for characterizing flood variability and for attributing climatic drivers on flood variability and magnitude.

The National Park Service (NPS) manages hundreds of parks in the United States, and many contain important aquatic ecosystems and/or threatened and endangered aquatic species vulnerable to hydro-climatic change. More effective management of park resources under future hydro-climatic uncertainty requires information on both baseline conditions and the range of projected future conditions. A monthly water balance model was used to assess baseline (1981&ndash, 1999) conditions and a range of projected future hydro-climatic conditions in 374 NPS parks. General circulation model outputs representing 214 future climate simulations were used to drive the model. Projected future changes in air temperature (T), precipitation (p), and runoff (R) are expressed as departures from historical baselines. Climate simulations indicate increasing T by 2030 for all parks with 50th percentile simulations projecting increases of 1.67 &deg, C or more in 50% of parks. Departures in 2030 p indicate a mix of mostly increases and some decreases, with 50th percentile simulations projecting increases in p in more than 70% of parks. Departures in R for 2030 are mostly decreases, with the 50th percentile simulations projecting decreases in R in more than 50% of parks in all seasons except winter. Hence, in many NPS parks, R is projected to decrease even when p is projected to increase because of increasing T in all parks. Projected changes in future hydro-climatic conditions can also be assessed for individual parks, and Rocky Mountain National Park and Congaree National Park are used as examples.

The accuracy of statistically downscaled (SD) general circulation model (GCM) simulations of monthly surface climate for historical conditions (1950–2005) was assessed for the conterminous United States (CONUS). The SD monthly precipitation (PPT) and temperature (TAVE) from 95 GCMs from phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) were used as inputs to a monthly water balance model (MWBM). Distributions of MWBM input (PPT and TAVE) and output [runoff (RUN)] variables derived from gridded station data (GSD) and historical SD climate were compared using the Kolmogorov–Smirnov (KS) test For all three variables considered, the KS test results showed that variables simulated using CMIP5 generally are more reliable than those derived from CMIP3, likely due to improvements in PPT simulations. At most locations across the CONUS, the largest differences between GSD and SD PPT and RUN occurred in the lowest part of the distributions (i.e., low-flow RUN and low-magnitude PPT). Results indicate that for the majority of the CONUS, there are downscaled GCMs that can reliably simulate historical climatic conditions. But, in some geographic locations, none of the SD GCMs replicated historical conditions for two of the three variables (PPT and RUN) based on the KS test, with a significance level of 0.05. In these locations, improved GCM simulations of PPT are needed to more reliably estimate components of the hydrologic cycle. Simple metrics and statistical tests, such as those described here, can provide an initial set of criteria to help simplify GCM selection.

Winter snowfall and accumulation is an important component of the surface water supply in the western United States. In these areas, increasing winter temperatures T associated with global warming can influence the amount of winter precipitation P that falls as snow S. In this study we examine long-term trends in the fraction of winter P that falls as S (Sfrac) for 175 hydrologic units (HUs) in snow-covered areas of the western United States for the period 1951–2014. Because S is a substantial contributor to runoff R across most of the western United States, we also examine long-term trends in water-year runoff efficiency [computed as water-year R/water-year P (Reff)] for the same 175 HUs. In that most S records are short in length, we use model-simulated S and R from a monthly water balance model. Results for Sfrac indicate long-term negative trends for most of the 175 HUs, with negative trends for 139 (~79%) of the HUs being statistically significant at a 95% confidence level (p = 0.05). Additionally, results indicate that the long-term negative trends in Sfrac have been largely driven by increases in T. In contrast, time series of Reff for the 175 HUs indicate a mix of positive and negative long-term trends, with few trends being statistically significant (at p = 0.05). Although there has been a notable shift in the timing of R to earlier in the year for most HUs, there have not been substantial decreases in water-year R for the 175 HUs.

Despite the importance of the Missouri River for navigation, recreation, habitat, hydroelectric power, and agriculture, relatively little is known about the basic hydroclimatology of the Missouri River basin (MRB). This is of particular concern given the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, observed and modeled hydroclimatic data and estimated natural flow records in the MRB are used to 1) assess the major source regions of MRB flow, 2) describe the climatic controls on streamflow in the upper and lower basins , and 3) investigate trends over the instrumental period. Analyses indicate that 72% of MRB runoff is generated by the headwaters in the upper basin and by the lowest portion of the basin near the mouth. Spring precipitation and temperature and winter precipitation impacted by changes in zonal versus meridional flow from the Pacific Ocean play key roles in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. Although increases in precipitation in the lower basin are currently overriding the effects of warming temperatures on total MRB flow, the upper basin’s long-term trend toward decreasing flows, reduction in snow versus rain fraction, and warming spring temperatures suggest that the upper basin may less often provide important flow supplements to the lower basin in the future.

The upper Colorado River basin (UCRB) is one of the primary sources of water for the western United States, and increasing temperatures likely will elevate the risk of reduced water supply in the basin. Although variability in water-year precipitation explains more of the variability in water-year UCRB streamflow than water-year UCRB temperature, since the late 1980s, increases in temperature in the UCRB have caused a substantial reduction in UCRB runoff efficiency (the ratio of streamflow to precipitation). These reductions in flow because of increasing temperatures are the largest documented temperature-related reductions since record keeping began. Increases in UCRB temperature over the past three decades have resulted in a mean UCRB water-year streamflow departure of −1306 million m3 (or −7% of mean water-year streamflow). Additionally, warm-season (April through September) temperature has had a larger effect on variability in water-year UCRB streamflow than the cool-season (October through March) temperature. The greater contribution of warm-season temperature, relative to cool-season temperature, to variability of UCRB flow suggests that evaporation or snowmelt, rather than changes from snow to rain during the cool season, has driven recent reductions in UCRB flow. It is expected that as warming continues, the negative effects of temperature on water-year UCRB streamflow will become more evident and problematic.

Analysis of the water balance of the southwestern United States (SWUS) during 1900 through 2018 was used to evaluate the magnitude of the turn-of-the-century (TOC) drought in the SWUS. Results indicate that the warm season (April through September) soil moisture and runoff during the TOC drought were among the lowest values of the 1900 through 2018 period. Additionally, increases in temperature were identified as a significant driver of low soil moisture and runoff conditions during the warm season. In contrast, during the cool seasons (October through March) and the water year (October 1 through September 30) during the TOC drought, soil moisture and runoff did not indicate extremely dry conditions even though temperatures were the highest of the 1900 through 2018 period.

A parameter regionalization scheme to transfer parameter values and model uncertainty information from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash–Sutcliffe Efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

This empirical study examines the influence of precipitation, temperature, and antecedent soil moisture on upper Colorado River basin (UCRB) water year streamflow over the past century. While cool season precipitation explains most of the variability in annual flows, temperature appears to be highly influential under certain conditions, with the role of antecedent fall soil moisture less clear. In both wet and dry years, when flow is substantially different than expected given precipitation, these factors can modulate the dominant precipitation influence on streamflow. Different combinations of temperature, precipitation, and soil moisture can result in flow deficits of similar magnitude, but recent droughts have been amplified by warmer temperatures that exacerbate the effects of relatively modest precipitation deficits. Since 1988, a marked increase in the frequency of warm years with lower flows than expected, given precipitation, suggests continued warming temperatures will be an increasingly important influence in reducing future UCRB water supplies.

Paleohydrologic reconstructions of water-year streamflow for 105 sites across the western United States (West) were used to compute the likelihood (risk) of regime (wet/dry state) shifts given the length of time in a specific regime and for a specified time in the future. The spatial variability of risks was examined and indicates that regime shift risks are variable across the West. The Pacific-Northwest region is associated with low risks of regime shifts, indicating persistence controlled by prevalent low frequency variability in flow (periods above 64 years). Other areas in the West indicate higher risks compared to the Pacific-Northwest due to flow variability in the mid-to-high frequencies (periods of 32 to 16 years). Understanding risks of regime shifts provides critical information for improved management of water supplies, particularly during periods of extended low flows. The method presented here has global applicability as a decision-making framework for risk-based planning and management.

Monthly precipitation (P) and potential evapotranspiration (PET) from the CRUTS3.1 data set are used to compute monthly P minus PET (PMPE) for the land areas of the globe. The percent of the global land area with annual sums of PMPE less than zero are used as an index of global drought (%drought) for 1901 through 2009. Results indicate that for the past century %drought has not changed, even though global PET and temperature (T) have increased. Although annual global PET and T have increased, annual global P also has increased and has mitigated the effects of increased PET on %drought.

Spatial and temporal patterns in annual and seasonal minimum, mean, and maximum daily streamflow values were examined for a set of 516 reference stream gauges located throughout the conterminous United States for the period 1951–2009. Cluster analysis was used to classify the stream gauges into 14 groups based on similarity in their temporal patterns of streamflow. The results indicated that the temporal patterns in flow metrics (1) have strong spatial coherence within each region, (2) are similar among the three annual flow metrics and the four seasonal flow metrics within each region, (3) indicate some small magnitude trends over time, and (4) are only weakly associated with well-known climate indices. We conclude that most of the temporal variability in flow is unpredictable in terms of relations to climate indices and infer that, for the most part, future changes in flow characteristics cannot be predicted by these indices.

Singular value decomposition (SVD) is used to identify the variability common to global sea surface temperatures (SSTs) and water-balance-modeled water-year (WY) runoff in the conterminous United States (CONUS) for the 1900–2012 period. Two modes were identified from the SVD analysis; the two modes explain 25% of the variability in WY runoff and 33% of the variability in WY SSTs. The first SVD mode reflects the variability of the El Niño–Southern Oscillation (ENSO) in the SST data and the hydroclimatic effects of ENSO on WY runoff in the CONUS. The second SVD mode is related to variability of the Atlantic multidecadal oscillation (AMO). An interesting aspect of these results is that both ENSO and AMO appear to have nearly equivalent effects on runoff variability in the CONUS. However, the relatively small amount of variance explained by the SVD analysis indicates that there is little covariation between runoff and SSTs, suggesting that SSTs may not be a viable predictor of runoff variability for most of the conterminous United States.

Paleohydrologic records can provide unique, long-term perspectives on streamflow variability and hydroclimate for use in water resource planning. Such long-term records can also play a key role in placing both present day events and projected future conditions into a broader context than that offered by instrumental observations. However, relative to other major river basins across the western United States, a paucity of streamflow reconstructions has to date prevented the full application of such paleohydrologic information in the Upper Missouri River Basin. Here we utilize a set of naturalized streamflow records for the Upper Missouri and an expanded network of tree-ring records to reconstruct streamflow at thirty-one gaging locations across the major headwaters of the basin. The reconstructions explain an average of 68% of the variability in the observed streamflow records and extend available records of streamflow back to 886 CE on average. Basin-wide analyses suggest unprecedented hydroclimatic variability over the region during the Medieval period, similar to that observed in the Upper Colorado River Basin, and show considerable synchrony of persistent wet-dry phasing with the Colorado River over the last 1200 years. Streamflow estimates in individual sub-basins of the Upper Missouri demonstrate increased spatial variability in discharge during the Little Ice Age (∼1400–1850 CE) compared with the Medieval Climate Anomaly (∼800–1400 CE). The network of streamflow reconstructions presented here fills a major geographical void in paleohydrologic understanding and now allows for a long-term assessment of hydrological variability over the majority of the western U.S.

Singular value decomposition is used to identify the common variability in first leaf dates (FLDs) and 1 April snow water equivalent (SWE) for the western United States during the period 1900–2012. Results indicate two modes of joint variability that explain 57% of the variability in FLD and 69% of the variability in SWE. The first mode of joint variability is related to widespread late winter–spring warming or cooling across the entire west. The second mode can be described as a north–south dipole in temperature for FLD, as well as in cool season temperature and precipitation for SWE, that is closely correlated to the El Niño–Southern Oscillation. Additionally, both modes of variability indicate a relation with the Pacific–North American atmospheric pattern. These results indicate that there is a substantial amount of common variance in FLD and SWE that is related to large-scale modes of climate variability.

Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale “memory” in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood.

[1] We used a first-order, monthly snow model and observations to disentangle seasonal influences on 20th century,regional snowpack anomalies in the Rocky Mountains of western North America, where interannual variations in cool-season (November–March) temperatures are broadly synchronous, but precipitation is typically antiphased north to south and uncorrelated with temperature. Over the previous eight centuries, regional snowpack variability exhibits strong, decadally persistent north-south (N-S) antiphasing of snowpack anomalies. Contrary to the normal regional antiphasing, two intervals of spatially synchronized snow deficits were identified. Snow deficits shown during the 1930s were synchronized north-south by low cool-season precipitation, with spring warming (February–March) since the 1980s driving the majority of the recent synchronous snow declines, especially across the low to middle elevations. Spring warming strongly influenced low snowpacks in the north after 1958, but not in the south until after 1980. The post-1980, synchronous snow decline reduced snow cover at low to middle elevations by ~20% and partly explains earlier and reduced streamflow and both longer and more active fire seasons. Climatologies of Rocky Mountain snowpack are shown to be seasonally and regionally complex, with Pacific decadal variability positively reinforcing the anthropogenic warming trend.

Several studies document lengthening of the frost-free season within the conterminous United States (U.S.) over the past century, and report trends in spring and fall frost timing that could stem from hemispheric warming. In the absence of warming, theory and case studies link anomalous frost timing to atmospheric circulation anomalies. However, recent efforts to relate a century of observed changes in U.S. frost timing to various atmospheric circulations yielded only modest correlations, leaving the relative importance of circulation and warming unclear. Here, we objectively partition the U.S. into four regions and uncover atmospheric circulations that account for 25–48% of spring and fall-frost timing. These circulations appear responsive to historical warming, and they consistently account for more frost timing variability than hemispheric or regional temperature indices. Reliable projections of future variations in growing season length depend on the fidelity of these circulation patterns in global climate models., Over the past century, the frost-free season in the US has lengthened. Here, Strong and McCabe show that most of the variability of spring and fall-frost timing is determined by atmospheric circulation patterns and needs to be considered in future projections of growing season length.

Mean global surface air temperature (SAT) and sea surface temperature (SST) display substantial variability on timescales ranging from annual to multi-decadal. We review the key recent literature on connections between global SAT and SST variability. Although individual ocean influences on SAT have been recognized, the combined contributions of worldwide SST variability on the global SAT signal have not been clearly identified in observed data. We analyze these relations using principal components of detrended SST, and find that removing the underlying combined annual, decadal, and multi-decadal SST variability from the SAT time series reveals a nearly monotonic global warming trend in SAT since about 1900.

Disparate ecological datasets are often organized into databases post hoc and then analyzed and interpreted in ways that may diverge from the purposes of the original data collections. Few studies, however, have attempted to quantify how biases inherent in these data (for example, species richness, replication, climate) affect their suitability for addressing broad scientific questions, especially in under-represented systems (for example, deserts, tropical forests) and wild communities. Here, we quantitatively compare the sensitivity of species first flowering and leafing dates to spring warmth in two phenological databases from the Northern Hemisphere. One—PEP725—has high replication within and across sites, but has low species diversity and spans a limited climate gradient. The other—NECTAR—includes many more species and a wider range of climates, but has fewer sites and low replication of species across sites. PEP725, despite low species diversity and relatively low seasonality, accurately captures the magnitude and seasonality of warming responses at climatically similar NECTAR sites, with most species showing earlier phenological events in response to warming. In NECTAR, the prevalence of temperature responders significantly declines with increasing mean annual temperature, a pattern that cannot be detected across the limited climate gradient spanned by the PEP725 flowering and leafing data. Our results showcase broad areas of agreement between the two databases, despite significant differences in species richness and geographic coverage, while also noting areas where including data across broader climate gradients may provide added value. Such comparisons help to identify gaps in our observations and knowledge base that can be addressed by ongoing monitoring and research efforts. Resolving these issues will be critical for improving predictions in understudied and under-sampled systems outside of the temperature seasonal mid-latitudes.

Detrended, modelled first leaf dates for 856 sites across North America for the period 1900-2008 are used to examine how the El Nino Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) separately and together might influence the timing of spring. Although spring (mean March through April) ENSO and PDO signals are apparent in first leaf dates, the signals are not statistically significant (at a 95% confidence level (p

A monthly snow accumulation and melt model was used with monthly Precipitation-elevation Regressions on Independent Slopes Model (PRISM) temperature and precipitation data to generate time series of 1 April snow water equivalent (SWE) for 1900 through 2008 in the western United States. Averaged across the western United States, SWE generally was higher than long-term (1900–2008) average conditions during the periods 1900–25, 1944–55, and 1966–82; SWE was lower than long-term average conditions during the periods 1926–43, 1957–65, and 1984–2008. During the period 1900–2008, the temporal pattern in winter precipitation exhibited wetter-than-average and drier-than-average decadal-scale periods with no long-term increasing or decreasing trend. Winter temperature generally was below average from 1900 to the mid-1950s, close to average from the mid-1950s to the mid-1980s, and above average from the mid-1980s to 2008. In general, periods of higher-than-average SWE have been associated with higher precipitation and lower temperature. Since about 1980, western U.S. winter temperatures have been consistently higher than long-term average values, and the resultant lower-than-average SWE values have been only partially offset by periods of higher-than-average precipitation. The post-1980 lower-than-average SWE conditions in the western United States are unprecedented within the context of twentieth-century climate and estimated SWE.

Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905–2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Niño–Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Atlantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.

Low-elevation glaciers in coastal regions of Alaska, the Canadian Arctic, individual ice caps around the Greenland ice sheet, and the Patagonia Ice Fields have an aggregate glacier area of about 332 × 103 km2 and account for approximately 42% of all the glacier area outside the Greenland and Antarctic ice sheets. They have shown volume loss, especially since the end of the 1980s, increasing from about 45% in the 1960s to nearly 67% in 2003 of the total wastage from all glaciers on Earth outside those two largest ice sheets. Thus, a disproportionally large contribution of coastal glacier ablation to sea level rise is evident. We examine cumulative standardized departures (1961–2000 reference period) of glacier mass balances and air temperature data in these four coastal regions. Analyses indicate a strong association between increases in glacier volume losses and summer air temperature at regional and global scales. Increases in glacier volume losses in the coastal regions also coincide with an ac...

The timing of snowmelt runoff (SMR) for 84 rivers in the western United States is examined to understand the character of SMR variability and the climate processes that may be driving changes in SMR timing. Results indicate that the timing of SMR for many rivers in the western United States has shifted to earlier in the snowmelt season. This shift occurred as a step change during the mid-1980s in conjunction with a step increase in spring and early-summer atmospheric pressures and temperatures over the western United States. The cause of the step change has not yet been determined.

Snowpack, as measured on 1 April, is the primary source of warm-season streamflow for most of the western United States and thus represents an important source of water supply. An understanding of climate factors that influence the variability of this water supply and thus its predictability is important for water resource management. In this study, principal component analysis is used to identify the primary modes of 1 April snowpack variability in the western United States. Two components account for 61% of the total snowpack variability in the western United States. Relations between these modes of variability and indices of Pacific Ocean climate

Examination of historical climate records indicates a significant relation between the El Nino/Southern Oscillation (ENSO) and seasonal temperature and precipitation in Louisiana. In this study, a 40 yr record of twice daily (06:00 and 15:00 h local time) weather types are used to study the effects of ENSO variability on the local climate at New Orleans, Louisiana. Tropical Pacific sea- surface temperatures (SSTs) for the NINO3.4 region are used to define ENSO events (i.e. El Nino and La Nina events), and daily precipitation and temperature data for New Orleans are used to define weather-type precipitation and temperature properties. Data for winters (December through Febru- ary) 1962-2000 are analyzed. The 39 winters are divided into 3 categories; winters with NINO3.4 SST anomalies 1°C (El Nino events), and neu- tral conditions (all other years). For each category, weather-type frequencies and properties (i.e. pre- cipitation and temperature) are determined and analyzed. Results indicate that El Nino events pri- marily affect precipitation characteristics of weather types at New Orleans, whereas the effects of La Nina events are most apparent in weather-type frequencies. During El Nino events, precipitation for some of the weather types is greater than during neutral and La Nina conditions and is related to increased water vapor transport from the Tropics to the Gulf of Mexico. The changes in weather-type frequencies during La Nina events are indicative of a northward shift in storm tracks and/or a decrease in storm frequency in southern Louisiana.

Observed (1895-1999) trends in climatic moisture conditions in the conterminous United States (US) characterized by (1) annual precipitation minus annual potential evapotranspira- tion (PMPE), (2) annual surplus (water that eventually becomes streamflow), and (3) annual deficit (the amount of water that must be supplied by irrigation to grow vegetation at an optimum rate) are examined. The sensitivity of moisture conditions across the conterminous US to increases in temper- ature also are examined. Results indicate that there have been statistically significant trends in PMPE, annual surplus, and annual deficit for some parts of the conterminous US. Most of the signifi- cant trends in PMPE have been increasing trends primarily in the eastern US. Annual surplus also has increased over the eastern US, whereas the magnitudes of annual deficit have decreased. For the conterminous US as a whole, there has been a statistically significant increase in PMPE and annual surplus; however, there is no significant trend in annual deficit. Results also indicate that PMPE and annual deficit in the warmest regions of the conterminous US are most sensitive to increases in tem- perature. The high sensitivity of PMPE and annual deficit in these regions to increases in tempera- ture is related to the relation between temperature and the saturation vapor pressure of air. The increases in potential evapotranspiration for a given change in temperature are larger for high tem- peratures than for low temperatures. The regions with the highest sensitivity of annual surplus to increases in temperature are the humid regions of the country. In these regions, annual surplus is large and increased potential evapotranspiration, resulting from increased temperature, has a signif- icant effect on reducing annual surplus. In the dry regions of the country, annual surplus is so low that increases in potential evapotranspiration only result in small decreases in annual surplus.

One of the hypothesized effects of global warming from increasing concentrations of greenhouse gases is a change in the frequency and/or intensity of extratropical cyclones. In this study, winter frequencies and intensities of extratropical cyclones in the Northern Hemisphere for the period 1959–97 are examined to determine if identifiable trends are occurring. Results indicate a statistically significant decrease in midlatitude cyclone frequency and a significant increase in high-latitude cyclone frequency. In addition, storm intensity has increased in both the high and midlatitudes. The changes in storm frequency correlate with changes in winter Northern Hemisphere temperature and support hypotheses that global warming may result in a northward shift of storm tracks in the Northern Hemisphere.

Snow-water equivalent (SWE) data measured at several hundred montane sites in the western United States are used to examine the historic effects of El Nino and La Nina events on seasonal snowpack evolution in the major subbasins in the Columbia and Colorado River systems. Results are used to predict annual runoff. In the Columbia River Basin, there is a general tendency for decreased SWE during El Nino years and increased SWE in La Nina years. However, the SWE anomalies for El Nino years are much less pronounced. This occurs in part because midlatitude circulation anomalies in El Nino years are located 35° east of those in La Nina years. This eastward shift is most evident in midwinter, at which time, SWE anomalies associated with El Nino are actually positive in coastal regions of the Columbia River Basin. In the Colorado River Basin, mean anomalies in SWE and annual runoff during El Nino years depict a transition between drier-than-average conditions in the north, and wetter-than-average conditions in the southwest. Associations during La Nina years are generally opposite those in El Nino years. SWE anomalies tend to be more pronounced in spring in the Lower Colorado River Basin. Our predictions of runoff reveal modest skill for scenarios using only historic El Nino and La Nina information. Predictions based on the water stored in the seasonal snowpack are, in almost all cases, much higher than those based on El Nino-Southern Oscillation (ENSO) information alone. However, combining observed midwinter snow conditions with information on seasonal snowpack evolution associated with ENSO improves predictions for basins in which ENSO signals exhibit strong seasonality.

The hydrologic concepts needed in a water-balance model to estimate the spatial varia- tion in mean annual runoff for the 344 climate divisions in the conterminous United States (U.S.) were determined. The concepts that were evaluated were the climatic supply of water (precipitation), cli- matic demand for water (potential evapotranspiration), seasonality in supply and demand, and soil- moisture-storage capacity. Most (91%) of the spatial variability in mean annual runoff for the climate divisions in the conterminous U.S. was explained by the spatial variability of mean annual precipitation minus mean annual potential evapotranspiration. When soil-moisture-storage capacity and seasonality in supply and demand were added to the water balance, the explained variance in mean annual runoff increased slightly, and the error in estimated mean annual runoff decreased significantly. Adding soil- moisture-storage capacity and seasonality in supply and demand provided the most improvement in areas where seasonal supply and demand are out of phase.

Correlation and correlation-based measures (e.g., the coefficient of determination) have been widely used to evaluate the “goodness-of-fit” of hydrologic and hydroclimatic models. These measures are oversensitive to extreme values (outliers) and are insensitive to additive and proportional differences between model predictions and observations. Because of these limitations, correlation-based measures can indicate that a model is a good predictor, even when it is not. In this paper, useful alternative goodness-of-fit or relative error measures (including the coefficient of efficiency and the index of agreement) that overcome many of the limitations of correlation-based measures are discussed. Modifications to these statistics to aid in interpretation are presented. It is concluded that correlation and correlation-based measures should not be used to assess the goodness-of-fit of a hydrologic or hydroclimatic model and that additional evaluation measures (such as summary statistics and absolute error measures) should supplement model evaluation tools.

One of the most severe outbreaks of yellow fever, a viral disease transmitted by the Aedes aegypti mosquito, affected the southern United States in the summer of 1878. The economic and human toll was enormous, and the city of Memphis, Tennessee, was one of the most affected. The authors suggest that as a consequence of one of the strongest El Nino episodes on record—that which occurred in 1877-78—exceptional climate anomalies occurred in the United States (as well as in many other parts of the world), which may have been partly responsible for the widespread nature and severity of the 1878 yellow fever outbreak. This study documents some of the extreme climate anomalies that were recorded in 1877 and 1878 in parts of the eastern United States, with particular emphasis on highlighting the evolution of these anomalies, as they might have contributed to the epidemic. Other years with major outbreaks of yellow fever in the eighteenth and nineteenth centuries also occurred during the course of El Nino...

Artículo -- Universidad de Costa Rica. Centro de Investigaciones Geofísicas, 2014 The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamflow changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamflows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record. Universidad de Costa Rica. Centro de Investigaciones Geofísicas Lamont-Doherty Earth Observatory of Columbia University UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)

Phenological events - defined points in the life cycle of a plant or animal - have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues. The ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. Here, we evaluated evidence for phylogenetic conservatism - the tendency for closely related species to share similar ecological and biological attributes - in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing ̃4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the set of included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites. We show that more closely related species tend to flower and leaf at similar times. By contrasting mean flowering times within and across sites, however, we illustrate that it is not the time of year that is conserved, but rather the phenological responses to a common set of abiotic cues. Our findings suggest that species cannot be treated as statistically independent when modelling phenological responses. Synthesis. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories. © 2013 British Ecological Society.