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Relations between winter precipitation and atmospheric circulation simulated by the Geophysical Fluid Dynamics Laboratory general circulation model

General circulation model (GCM) simulations of atmospheric circulation are more reliable than GCM simulations of temperature and precipitation. In this study, temporal correlations between 700 hPa height anomalies simulated winter precipitation at eight locations in the conterminous United States are compared with corresponding correlations in observations. The objectives are to 1) characterize the relations between atmospheric circulation and winter precipitation simulated by the GFDL, GCM for selected locations in the conterminous USA, ii) determine whether these relations are similar to those found in observations of the actual climate system, and iii) determine if GFDL-simulated precipitation is forced by the same circulation patterns as in the real atmosphere. -from Authors

International Journal of Climatology↗

Influences of the El Niño Southern Oscillation and the Pacific Decadal Oscillation on the timing of the North American spring

Detrended, modelled first leaf dates for 856 sites across North America for the period 1900–2008 are used to examine how the El Niño 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 < 0.05)) for most sites. The most significant ENSO/PDO signal in first leaf dates occurs for El Niño and positive PDO conditions. An analysis of the spatial distributions of first leaf dates for separate and combined ENSO/PDO conditions features a northwest–southeast dipole that is significantly (at p < 0.05) different than the distributions for neutral conditions. The nature of the teleconnection between Pacific SST's and first leaf dates is evident in comparable composites for detrended sea level pressure (SLP) in the spring months. During positive ENSO/PDO, there is an anomalous flow of warm air from the southwestern US into the northwestern US and an anomalous northeasterly flow of cold air from polar regions into the eastern and southeastern US. These flow patterns are reversed during negative ENSO/PDO. Although the magnitudes of first leaf date departures are not necessarily significantly related to ENSO and PDO, the spatial patterns of departures are significantly related to ENSO and PDO. These significant relations and the long-lived persistence of SSTs provide a potential tool for forecasting the tendencies for first leaf dates to be early or late.

International Journal of Climatology↗

Climatic trends over Ethiopia: regional signals and drivers

This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year −1 and downward trends in rainfall of − 0.4 mm month −1 year −1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.

International Journal of Climatology↗

Spring onset variations and trends in the continental United States: past and regional assessment using temperature-based indices

Phenological data are simple yet sensitive indicators of climate change impacts on ecosystems, but observations have not been made routinely or extensively enough to evaluate spatial and temporal patterns across most continents, including North America. As an alternative, many studies use weather-based algorithms to simulate specific phenological responses. Spring Indices (SI) are a set of complex phenological models that have been successfully applied to evaluate variations and trends in the onset of spring across the Northern Hemisphere’s temperate regions. To date, SI models have been limited by only producing output in locations where both the plants’ chilling and warmth requirements are met. Here, we develop an extended form of the SI (abbreviated SI-x) that expands their application into the subtropics by ignoring chilling requirements while still retaining the utility and accuracy of the original SI (now abbreviated SI-o). The validity of the new indices is tested, and regional SI anomalies are explored across the data-rich continental United States. SI-x variations from 1900 to 2010 show an abrupt and sustained delay in spring onset of about 4–8 d (around 1958) in parts of the Southeast and southern Great Plains, and a comparable advance of 4–8 d (around 1984) in parts of the northern Great Plains and the West. Atmospheric circulation anomalies, linked to large-scale modes of variability, exert modest but significant roles in the timing of spring onset across the United States on interannual and longer timescales. The SI-x are promising metrics for tracking spring onset variations and trends in mid-latitudes, relating them to relevant ecological, hydrological, and socioeconomic phenomena, and exploring connections between atmospheric drivers and seasonal timing.

International Journal of Climatology↗

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

International Journal of Climatology↗

Climate change and water resources in a tropical island system: Propagation of uncertainty from statistically downscaled climate models to hydrologic models

Many tropical islands have limited water resources with historically increasing demand, all potentially affected by a changing climate. The effects of climate change on island hydrology are difficult to model due to steep local precipitation gradients and sparse data. This work uses 10 statistically downscaled general circulation models (GCMs) under two greenhouse gas emission scenarios to evaluate the uncertainty propagated from GCMs in projecting the effects of climate change on water resources in a tropical island system. The assessment is conducted using a previously configured hydrologic model, the Precipitation Runoff Modelling System (PRMS) for Puerto Rico. Projected climate data and their modelled hydrologic variables versus historical measurements and their modelled hydrologic variables are found to have empirical distribution functions that are statistically different with less than 1 year of daily data aggregation. Thus, only annual averages of the projected hydrologic variables are employed as completely bias‐corrected model outputs. The magnitude of the projected total flow decreases in the four regions covering Puerto Rico, but with a large range of uncertainty depending on the makeup of the GCM ensemble. The multi‐model mean projected total flow decreases by 49–88% of historical amounts from the 1960s to the 2090s for the high emissions scenarios and by 39–79% for the low emissions scenarios. Subsurface flow contributions decreased the least and groundwater flow contributions decreased the most across the island. At locations critical to water supply for human use, projected streamflow is shown to decrease substantially below projected withdrawals by 2099.

Puerto Rico↗

Variability of runoff-based drought conditions in the conterminous United States

In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.

International Journal of Climatology↗

Assessment of uncertainty in multi-model means of downscaled south Florida precipitation for projected (2019-2099) climate

South Florida resource management, particularly the Everglades restoration effort, is beginning to consider projections of precipitation from multiple climate models for decision-making. Because precipitation changes can significantly affect the Everglades ecosystem, characterization of precipitation projection uncertainty is important for resource management decisions, and reduction of uncertainty is desired for better decision-making. Though uncertainty of precipitation projections has been characterized for many regions, uncertainty has not been sufficiently quantified for south Florida. This study builds upon prior results for projected Florida precipitation by adding recent climate model simulations, seasonal and spatial information, and uncertainty quantification and reduction. We identify the multi-model mean change in south Florida precipitation and characterize the uncertainty of 37 statistically downscaled Coupled Model Intercomparison Project Phase 5 models. For 2019−45, there is a likely (over 60% of ensemble members) increase in south Florida annual mean precipitation owing to a likely to very likely (near 90% of ensemble members) increase in dry season (November, December, January) precipitation, while wet season (June, July, August) shows a more likely than not (over 50% of ensemble members) decrease in precipitation in southern region and increase in precipitation in northern region. As south Florida agencies are on the verge of including precipitation projections in their upcoming planning horizon, this information will aid south Florida practitioners in decisions influenced by future rainfall.

South Florida↗

Using seasonal rainfall clusters to explain the interannual variability of the rain belt over the Greater Horn of Africa

The seasonal cycle of rainfall over the Greater Horn of Africa (GHA) is dominated by the latitudinal migration and activity of the tropical rain belt (TRB). The TRB exhibits high interannual variability in the GHA and the reasons for the recent dry period in the Long Rains (March–May) are poorly understood. In addition, few studies have addressed the rainfall fluctuations during the Msimu Rains (Dec.–Mar.) in the southern GHA region. Interannual variations of the seasonal cycle of the TRB between 1981 and 2018 were analysed using two statistical indices. The Rainfall Cluster Index (RCI) describes the seasonal cycle as a succession of six characteristic rainfall patterns, while the Seasonal Location Index (SLI) captures the latitudinal location of the TRB. The SLI and RCI depict the full seasonal cycle of the TRB supporting interpretations of the interannual variations and trends. The Msimu Rains are dominated by two clusters with opposite rainfall characteristics between the Congo Basin and Tanzania. The associated anomalies in moisture flux and divergence indicate variations in the location of the TRB originating from an interplay between low‐level air flows from the Atlantic and Indian Oceans and tropical and subtropical teleconnections. The peak period of the Long Rains shows a complex composition of five clusters, which is tightly connected to intraseasonal and interannual variability of latitudinal locations of the TRB. A persistent location of the TRB near the equator, evidenced in a frequent occurrence of a cluster related to an anomalously weak Walker circulation, is associated with wet conditions over East Africa. Dry Long Rains are associated with strong and frequent latitudinal variations of the TRB position with a late onset and intermittent rainfall. These results offer new opportunities to understand recent variability and trends in the GHA region.

International Journal of Climatology↗

High‐resolution dynamically downscaled rainfall and temperature projections for ecological life zones within Puerto Rico and for the U.S. Virgin Islands

The weather research and forecasting (WRF) model and a combination of the regional spectral model (RSM) and the Japanese Meteorological Agency Non‐Hydrostatic Model (NHM) were used to dynamically downscale selected CMIP5 global climate models to provide 2‐km projections with hourly model output for Puerto Rico and the U.S. Virgin Islands. Two 20‐year time slices were downscaled for historical (1986–2005) and future (2041–2060) periods following RCP8.5. Projected changes to mean and extreme temperature and precipitation were quantified for Holdridge life zones within Puerto Rico and for the U.S. Virgin Islands. The evaluation reveals a persistent cold bias for all islands in the U.S. Caribbean, a dry bias across Puerto Rico, and a wet bias on the windward side of mountains within the U.S. Virgin Islands. Despite these biases, model simulations show a robust drying pattern for all islands that is generally larger for Puerto Rico (25% annual rainfall reduction for some life zones) than the U.S. Virgin Islands (12% island average). The largest precipitation reductions are found during the more convectively active afternoon and evening hours. Within Puerto Rico, the model uncertainty increases for the wetter life zones, especially for precipitation. Across the life zones, both models project unprecedented maximum and minimum temperatures that may exceed 200 days annually above the historical baseline with only small changes to the frequency of extreme rainfall. By contrast, in the U.S. Virgin Islands, there is no consensus on the location of the largest drying relative to the windward and leeward side of the islands. However, the models project the largest increases in maximum temperature on the southern side of St. Croix and in higher elevations of St. Thomas and St. John.

Puerto Rico↗

Multi-year hydroclimatic droughts and pluvials across the conterminous United States

Time series of water‐year runoff for 2,109 hydrologic units (HUs) across the conterminous United States (CONUS) for the 1900 through 2014 period were used to identify drought and pluvial (i.e., wet) periods. Characteristics of the drought and pluvial events including frequency, duration, and severity were examined and compared. Additionally, a similar analysis was performed using gridded tree‐ring reconstructions of the Palmer Drought Severity Index (PDSI) for the period 1475 through 2005 to place the drought and pluvial characteristics determined using water‐year runoff for 1900 through 2014 in the context of multi‐century climate variability. The temporal and spatial variability of droughts and pluvials determined using runoff for the 1900 through 2014 period indicated that most drought events in the CONUS occurred before about 1970, whereas most pluvial periods occurred after about 1970. This change in the frequencies of drought and pluvial events around 1970 was largely related to an increase in fall (October through December) precipitation across much of the central United States. Also, the duration and severity of droughts and pluvials identified using runoff for the 1900 through 2014 period generally were not significantly different from the drought and pluvial characteristics identified using the PDSI for the 1475 through 2005 period.

International Journal of Climatology↗

Tropicalization of the temperate zone: Spatiotemporal variability of winter warming and declining freeze days across the United States

We investigate changes in cool-season and winter daily minimum (T min ) and maximum (T max ) temperatures, and the occurrence of freeze days, from 1952 to 2024 across the conterminous United States (CONUS). Emphasis is placed on the tropical-temperate transition zone (TTTz) in the southeastern CONUS. During winter, ~70% of the land area exhibited T min warming rates exceeding those of T max . The countywide coldest T min became milder across 57% of the CONUS, while the coldest T max showed little change and even cooled east of the Rocky Mountains in the central CONUS. Across the TTTz, 75% of freeze days occur within a ~25–100-day window, often fewer than 75 days in the southernmost areas. Approximately 80% of counties exhibited significant contractions in freeze-day concentration, with the largest and most spatially consistent changes occurring in the Southeast, primarily driven by later start dates. Roughly 85% of the CONUS experienced a significant decline in freeze days, with the largest relative declines in regions where average winter T min is above freezing, while parts of the Pacific Northwest showed no significant change. An analysis of freeze day isopleths (30, 45, 60 and 75 days) across 20-year periods showed that the mean latitude of freeze days has migrated poleward substantially. Between 101° W and 79° W in the TTTz, the 30 freeze-day isopleth for the late period (2005–2024) was, on average, 122 km (~1.1° latitude) farther north than in the early period (1952–1971). Generally, the largest latitudinal shifts and percentage losses in freeze days occurred across low-elevation, low-relief regions at lower latitudes (e.g., the Mississippi River Valley), with abrupt shifts occurring near topographic gradients. Regions with sharp elevational gradients (e.g., Balcones Escarpment, Ouachita Mountains and Tennessee Valley) exhibited smaller temporal changes, likely reflecting the barrier-like influence of higher terrain on the poleward retreat of freeze days.

conterminous United States↗

Problems in evaluating regional and local trends in temperature: An example from eastern Colorado, USA

We evaluated long-term trends in average maximum and minimum temperatures, threshold temperatures, and growing season in eastern Colorado, USA, to explore the potential shortcomings of many climate-change studies that either: (1) generalize regional patterns from single stations, single seasons, or a few parameters over short duration from averaging dissimilar stations: or (2) generalize an average regional pattern from coarse-scale general circulation models. Based on 11 weather stations, some trends were weakly regionally consistent with previous studies of night-time temperature warming. Long-term (80 + years) mean minimum temperatures increased significantly (P < 0.2) in about half the stations in winter, spring, and autumn and six stations had significant decreases in the number of days per year with temperatures ??? - 17.8 ??C (???0??F). However, spatial and temporal variation in the direction of change was enormous for all the other weather parameters tested, and, in the majority of tests, few stations showed significant trends (even at P < 0.2). In summer, four stations had significant increases and three stations had significant decreases in minimum temperatures, producing a strongly mixed regional signal. Trends in maximum temperature varied seasonally and geographically, as did trends in threshold temperature days ???32.2??C (???90??F) or days ???37.8??C (???100??F). There was evidence of a subregional cooling in autumn's maximum temperatures, with five stations showing significant decreasing trends. There were many geographic anomalies where neighbouring weather stations differed greatly in the magnitude of change or where they had significant and opposite trends. We conclude that sub-regional spatial and seasonal variation cannot be ignored when evaluating the direction and magnitude of climate change. It is unlikely that one or a few weather stations are representative of regional climate trends, and equally unlikely that regionally projected climate change from coarse-scale general circulation models will accurately portray trends at sub-regional scales. However, the assessment of a group of stations for consistent more qualitative trends (such as the number of days less than - 17.8??C, such as we found) provides a reasonably robust procedure to evaluate climate trends and variability. Copyright ?? 2002 Royal Meteorological Society.

International Journal of Climatology↗

A hydrologic perspective of major U.S. droughts

Drought is a recurring natural hazard that has substantial human and environmental impacts. Given continued global warming and associated climate change, there is concern that droughts could become more severe and longer lasting. To better monitor and understand drought development and persistence, it is helpful to understand the development and climatic drivers of past droughts. In this study we use monthly runoff percentiles to identify five major drought events in the conterminous United States (CONUS) from 1901 through 2020. For each drought event we examined spatial patterns of departures of mean monthly precipitation, temperature, soil moisture storage, and runoff for 2,107 hydrologic units (HUs) across the CONUS. Results indicated that precipitation deficits have been the primary driver of past major-drought events and temperature a secondary driver, even of the most recent drought event (September 1999 through September 2015) when positive temperature anomalies occurred over most of the CONUS. Additionally, negative soil moisture storage departures were more negative than runoff departures during the five drought events we examined, which emphasizes the importance of measuring both runoff and soil moisture to monitor drought conditions. We also examined the use of statistical persistence to develop short-term (i.e., 1 month) forecasts of runoff drought conditions in the CONUS by developing autoregressive integrated moving average (ARIMA) models for each HU. Results indicated that persistence can be used to predict short-term changes in the spatial pattern of drought and the areal extent of drought, but that predictions of runoff magnitude for any particular site are often poor.

International Journal of Climatology↗

Assessing satellite-derived start-of-season measures in the conterminous USA

National Oceanic and Atmospheric Administration (NOAA)-series satellites, carrying advanced very high-resolution radiometer (AVHRR) sensors, have allowed moderate resolution (1 km) measurements of the normalized difference vegetation index (NDVI) to be collected from the Earth's land surfaces for over 20 years. Across the conterminous USA, a readily accessible and decade-long data set is now available to study many aspects of vegetation activity in this region. One feature, the onset of deciduous plant growth at the start of the spring season (SOS) is of special interest, as it appears to be crucial for accurate computation of several important biospheric processes, and a sensitive measure of the impacts of global change. In this study, satellite-derived SOS dates produced by the delayed moving average (DMA) and seasonal midpoint NDVI (SMN) methods, and modelled surface phenology (spring indices, SI) were compared at widespread deciduous forest and mixed woodland sites during 1990&ndash;93 and 1995&ndash;99, and these three measures were also matched to native species bud-break data collected at the Harvard Forest (Massachusetts) over the same time period. The results show that both SOS methods are doing a modestly accurate job of tracking the general pattern of surface phenology, but highlight the temporal limitations of biweekly satellite data. Specifically, at deciduous forest sites: (1) SMN SOS dates are close in time to SI first bloom dates (average bias of +0.74 days), whereas DMA SOS dates are considerably earlier (average bias of &minus;41.24 days) and also systematically earlier in late spring than in early spring; (2) SMN SOS tracks overall yearly trends in deciduous forests somewhat better than DMA SOS, but with larger average error (MAEs 8.64 days and 7.37 days respectively); and (3) error in both SOS techniques varies considerably by year. Copyright &copy; 2002 Royal Meteorological Society.

International Journal of Climatology↗

Historical changes in lake ice-out dates as indicators of climate change in New England, 1850-2000

Various studies have shown that changes over time in spring ice-out dates can be used as indicators of climate change. Ice-out dates from 29 lakes in New England (USA) with 64 to 163 years of record were assembled and analysed for this study. Ice-out dates have become significantly earlier in New England since the 1800s. Changes in ice-out dates between 1850 and 2000 were 9 days and 16 days in the northern/mountainous and southern regions of New England respectively. The changes in the ice-out data over time were very consistent within each of the two regions of New England, and more consistent than four air-temperature records in each region. The ice-out dates of the two regions had a different response to changes in air temperature. The inferred late winter-early spring air-temperature warming in both regions of New England since 1850, based on linear regression analysis, was about 1.5 ??C. Published in 2002 by John Wiley & Sons, Ltd.

International Journal of Climatology↗

Subhourly mesoscale analysis of the 2011-2017 North American monsoon near its northwest boundary

The North American Monsoon (NAM) delivers precipitation to the southwestern USA during the warm-dry summer season. The seasonal extent of NAM precipitation is highly variable and is likely to change under future climate change. Our objective was to determine how large scale monsoonal patterns as well as local variables influence precipitation events near the NAM northwest boundary. Intra- and inter-annual changes in the northwest sector of the NAM were represented by subhourly weather data collected on the Sheep Range (2300 m asl), in the Mojave Desert of southern Nevada, during 2011-2017. Our study site is part of the Nevada Climate-ecohydrological Assessment Network (NevCAN), an automated observing system established in early 2011. Three seasons were classified using the subhourly weather data including: 1) cool season, 2) early warm season, 3) and late warm season, where the transition between early and late warm season was marked by the day when in situ dewpoint temperature first exceeded 9.4 ºC. Based on analysis of covariance (ANCOVA), dewpoint temperature had the greatest relationship with total hourly precipitation, followed by vapor pressure deficit, solar radiation, and air temperature. The only significant interaction term was between hour of the day and dewpoint temperature, highlighting the importance of dewpoint temperature for afternoon thunderstorms, which are typical of monsoonal precipitation. Besides in situ meteorological variables, we also analyzed NCEP/NCAR vertically integrated water vapor transport (IVT) and long-term 800-m PRISM precipitation time series. Regional composites were developed for IVT for the three seasons. Water vapor in the cool and early warm season originated mostly from the Pacific Ocean, while a transition in IVT to a NAM pattern occurred in the late warm season. Overall, this highly instrumented yet remote site was representative of NAM precipitation, despite noticeable variability in its timing and amount.

Nevada↗