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USGS2019

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↗
USGS2020

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↗
USGS2020

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↗
USGS2021

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↗
USGS2026

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↗
USGS2002

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↗
USGS2022

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↗
USGS2002

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↗
USGS2002

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↗
USGS2019

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↗
USGS2005

An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa

Periodic epidemics of malaria are a major public health problem for many sub-Saharan African countries. Populations in epidemic prone areas have a poorly developed immunity to malaria and the disease remains life threatening to all age groups. The impact of epidemics could be minimized by prediction and improved prevention through timely vector control and deployment of appropriate drugs. Malaria Early Warning Systems are advocated as a means of improving the opportunity for preparedness and timely response. Rainfall is one of the major factors triggering epidemics in warm semi-arid and desert-fringe areas. Explosive epidemics often occur in these regions after excessive rains and, where these follow periods of drought and poor food security, can be especially severe. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization. The Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics recommended that a simple indicator of changes in epidemic risk in regions of marginal transmission, consisting primarily of rainfall anomaly maps, could provide immediate benefit to early warning efforts. In response to these recommendations, the Famine Early Warning Systems Network produced maps that combine information about dekadal rainfall anomalies, and epidemic malaria risk, available via their Africa Data Dissemination Service. These maps were later made available in a format that is directly compatible with HealthMapper, the mapping and surveillance software developed by the WHO's Communicable Disease Surveillance and Response Department. A new monitoring interface has recently been developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of the current rainfall estimates by comparing them to previous seasons and climatological averages. These resources are available at no cost to the user and are updated on a routine basis.

Malaria Journal↗
USGS2025

Assessing gap-filled Landsat land surface temperature time-series data using different observational datasets

Landsat Analysis Ready Data (ARD)-based time-series present challenges in monitoring surface urban heat islands (SUHI) due to rapid changes in land surface temperature (LST) compared to cloud-free satellite observations. This research investigates the use of a spatiotemporal gap-filling model as a feasible and cost-effective solution to produce Landsat time-series LST products with both high spatial resolution and temporal frequency. The study identified and filled Landsat ARD thermal times-series data gaps due to missing data, cloud and shadow effects, and data quality. The accuracy of Landsat gap-filled products was assessed using randomly selected clear observations of Landsat and uncertainty products from the gap-filling model and was evaluated using various existing temperature datasets, including climate data from NOAA Global Historical Climate Network station observations, Daily Surface Weather and Climatological Summaries (DAYMET), and LST including MODIS, VIIRS and ECOSTRESS. The result suggests that the gap-filled Landsat LST has significant correlations with existing datasets including field observation and remote sensing data derived from other sensors that have similar monthly and seasonal variation patterns. The uncertainty maps show spatial distributions of uncertainty for gap-filled pixels that have high or low uncertainties. The Landsat gap-filled time-series datasets can be used to measure annual, seasonal, or even monthly landscape thermal conditions, which are useful for SUHI and relevant research, and to perform multi-decade time-series LST change analysis under climate change conditions.

International Journal of Remote Sensing↗
USGS2020

Relocated aftershocks and background seismicity in eastern Indonesia shed light on the 2018 Lombok and Palu earthquake sequences

High seismicity rates in eastern Indonesia occur due to the complex interaction of several tectonic plates which resulted in two deadly, destructive earthquake sequences that occurred in Lombok Island and the city of Palu, Sulawesi in 2018. The first sequence began in July with an M w 6.4 event near Lombok, culminating in an M w 7.0 event 8 d later. This was then followed by a nearby M w 6.9 event 12 d later. Approximately 1000 km to the northeast, a separate sequence began several weeks later near Palu where an M w 7.5 event occurred that triggered a tsunami. In this study, we present hypocentre relocations for both earthquake sequences as well as all other regional earthquakes in eastern Indonesia. The relocations were performed using a teleseismic double-difference relocation method and arrival times for P and S waves from stations at local, regional, and teleseismic distances. The catalogue and phase data were taken from the Agency for Meteorology, Climatology and Geophysics (BMKG) of Indonesia and the International Seismological Centre (ISC) for the period of April 2009 through November 2018. The relocated catalogue provides an improved view of seismicity in eastern Indonesia over the study period, sharpening locations and interpretations of seismogenic features throughout the region. In the Lombok area, the relocated earthquakes clearly show a backarc thrust to the north of the Sunda-Banda Arc transition zone. The relocated aftershocks show that the destructive M w 7.0 and M w 6.9 earthquakes of the Lombok sequence ruptured two different regions: The M w 7.0 earthquake propagated westward, whereas the M w 6.9 earthquake propagated eastward. The entire sequence of Lombok earthquakes was most likely started by the M w 6.4 event as the initial event or foreshock, which then triggered backarc thrusts on both sides. Several weeks later and far to the northeast, the M w 7.5 Palu earthquake occurred along the Palu-Koro Fault, filling a seismic gap that had not ruptured in an M w 6.0 event or larger since at least 1900. The distribution of aftershocks indicates that the northern part of the Palu-Koro Fault has lower relative seismicity rates than the southern part at shallow depths, and that off fault aftershocks are mostly located to the east of the Palu-Koro Fault.

Lombok, Palu↗