SEARCH · Geology Reports

Results for “International Journal of Climatology”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

USGS2012

A refined index of model performance: a rejoinder

Willmott et al. [Willmott CJ, Robeson SM, Matsuura K. 2012. A refined index of model performance. International Journal of Climatology , forthcoming. DOI:10.1002/joc.2419.] recently suggest a refined index of model performance ( d r ) that they purport to be superior to other methods. Their refined index ranges from − 1.0 to 1.0 to resemble a correlation coefficient, but it is merely a linear rescaling of our modified coefficient of efficiency ( E 1 ) over the positive portion of the domain of d r . We disagree with Willmott et al. ( 2012 ) that d r provides a better interpretation; rather, E 1 is more easily interpreted such that a value of E 1 = 1.0 indicates a perfect model (no errors) while E 1 = 0.0 indicates a model that is no better than the baseline comparison (usually the observed mean). Negative values of E 1 (and, for that matter, d r < 0.5) indicate a substantially flawed model as they simply describe a ‘level of inefficacy’ for a model that is worse than the comparison baseline. Moreover, while d r is piecewise continuous, it is not continuous through the second and higher derivatives. We explain why the coefficient of efficiency ( E or E 2 ) and its modified form ( E 1 ) are superior and preferable to many other statistics, including d r , because of intuitive interpretability and because these indices have a fundamental meaning at zero. We also expand on the discussion begun by Garrick et al. [Garrick M, Cunnane C, Nash JE. 1978. A criterion of efficiency for rainfall-runoff models. Journal of Hydrology 36 : 375-381.] and continued by Legates and McCabe [Legates DR, McCabe GJ. 1999. Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resources Research 35 (1): 233-241.] and Schaefli and Gupta [Schaefli B, Gupta HV. 2007. Do Nash values have value? Hydrological Processes 21 : 2075-2080. DOI: 10.1002/hyp.6825.]. This important discussion focuses on the appropriate baseline comparison to use, and why the observed mean often may be an inadequate choice for model evaluation and development.

International Journal of Climatology↗

USGS2018

Assessing recovery and change in West Africa's rainfall regime from a 161-year record

The Sahel region is known for the multi-decadal occurrence of severe drought that commenced in the late 1960s. A still open question is whether or not the region's rainfall has returned to “normal.” This paper provides a compelling answer to that question by examining the longest and most comprehensive gauge series for the region ever published. It extends from 1854 to 2014 and is based on 602 gauge records. A comparative series for the Guinea Coast region to the south is also presented, as the two regions collectively provide insight into the long-term variability of the West African monsoon. In contrast to many previous studies, here the question of recovery and regime change is not restricted to the core of the Sahelian rainy season (July–September), but is separately discussed also for the coastal phase (April–May), transition phase (June), Sahelian phase (July–September) and the second transition phase (October–November) of the West African monsoon. These analyses suggest that full recovery from the droughts of the 1970s and 1980s has not occurred that a major change in the rainfall regime occurred around 1968 and that since that time large-scale teleconnections have also changed markedly. The shift post-1968 is evident in all phases of the monsoon except the coastal phase, in which a change to drier conditions occurred a decade later. Overall, recovery has been greater in the east than in the west, creating a change in the climatological east–west rainfall gradient. The drier post-1968 conditions appear to be associated with a general weakening of the intensity of the West African monsoon and only a small southwards displacement of the rainfall maximum. These changes have strong implications for the future of this region and for seasonal prediction.

International Journal of Climatology↗

USGS2000

Effects of temperature anomalies on the Palmer Drought Severity Index in the central United States

The purpose of this study is to improve our understanding of temperature and precipitation effects on the Palmer Drought Severity Index (PDSI). Both theoretical and observational analyses were applied to separate and compare temperature and precipitation effects on PDSI. The results showed that because of the dependence of PDSI on the ‘climatologically appropriate rainfall’, which is a function of time and varies with surface air temperature, the PDSI can be equally affected by temperature and precipitation, when both have similar magnitudes of anomalies. Calculations using observational data further illustrated the temperature influence on PDSI in different climate regions in the central United States. The temperature effect on PDSI complicates the usage of the index in interpreting precipitation anomalies and its application in inferring precipitation variations, particularly from reconstructed PDSI.

International Journal of Climatology↗

USGS2011

The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

International Journal of Climatology↗

USGS2018

Changing station coverage impacts temperature trends in the Upper Colorado River Basin

Over the Upper Colorado River Basin (UCRB), temperatures in widely used gridded data products do not warm as much as mean temperatures from a stable set of U.S. Historical Climatology Network (USHCN) stations, located at generally lower elevations, in most months of the year. This is contrary to expectations of elevation-dependent warming, which suggests that warming increases with elevation. These findings could reflect 1) a genuine absence of elevation-dependent warming in the region, 2) systematic non-climatic influences on either the USHCN stations or high elevation stations, including known inhomogeneities related to changes in the time of observation and instrumentation, or 3) suppression of an elevation-dependent warming signal introduced by changes in the station network. While we cannot categorically dismiss the first two possibilities, we show here that over portions of the 20th century, gridded temperatures warm less than USHCN temperatures and the difference cannot be explained by accounting for known inhomogeneities. These analyses suggest that changing station coverage in the UCRB has influenced trends in gridded temperature estimates that incorporate changing suites of stations over time. Specifically, increases in the number of high-elevation stations in the UCRB may have led to an underestimation of elevation-dependent warming, particularly during the spring and summer. This phenomenon is unlikely limited to this specific basin, and may be present in other high-elevation watersheds across the western U.S.

Upper Colorado River Basin↗

USGS2003

The collaborative historical African rainfall model: description and evaluation

In Africa the variability of rainfall in space and time is high, and the general availability of historical gauge data is low. This makes many food security and hydrologic preparedness activities difficult. In order to help overcome this limitation, we have created the Collaborative Historical African Rainfall Model (CHARM). CHARM combines three sources of information: climatologically aided interpolated (CAI) rainfall grids (monthly/0.5° ), National Centers for Environmental Prediction reanalysis precipitation fields (daily/1.875° ) and orographic enhancement estimates (daily/0.1° ). The first set of weights scales the daily reanalysis precipitation fields to match the gridded CAI monthly rainfall time series. This produces data with a daily/0.5° resolution. A diagnostic model of orographic precipitation, VDELB—based on the dot-product of the surface wind V and terrain gradient (DEL) and atmospheric buoyancy B —is then used to estimate the precipitation enhancement produced by complex terrain. Although the data are produced on 0.1° grids to facilitate integration with satellite-based rainfall estimates, the ‘true’ resolution of the data will be less than this value, and varies with station density, topography, and precipitation dynamics. The CHARM is best suited, therefore, to applications that integrate rainfall or rainfall-driven model results over large regions. The CHARM time series is compared with three independent datasets: dekadal satellite-based rainfall estimates across the continent, dekadal interpolated gauge data in Mali, and daily interpolated gauge data in western Kenya. These comparisons suggest reasonable accuracies (standard errors of about half a standard deviation) when data are aggregated to regional scales, even at daily time steps. Thus constrained, numerical weather prediction precipitation fields do a reasonable job of representing large-scale diurnal variations.

International Journal of Climatology↗

USGS2008

Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States

Spatial climate data sets of 1971–2000 mean monthly precipitation and minimum and maximum temperature were developed for the conterminous United States. These 30‐arcsec (∼800‐m) grids are the official spatial climate data sets of the U.S. Department of Agriculture. The PRISM (Parameter‐elevation Relationships on Independent Slopes Model) interpolation method was used to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States. PRISM calculates a climate–elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell. Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain. Surface stations used in the analysis numbered nearly 13 000 for precipitation and 10 000 for temperature. Station data were spatially quality controlled, and short‐period‐of‐record averages adjusted to better reflect the 1971–2000 period. PRISM interpolation uncertainties were estimated with cross‐validation (C‐V) mean absolute error (MAE) and the 70% prediction interval of the climate–elevation regression function. The two measures were not well correlated at the point level, but were similar when averaged over large regions. The PRISM data set was compared with the WorldClim and Daymet spatial climate data sets. The comparison demonstrated that using a relatively dense station data set and the physiographically sensitive PRISM interpolation process resulted in substantially improved climate grids over those of WorldClim and Daymet. The improvement varied, however, depending on the complexity of the region. Mountainous and coastal areas of the western United States, characterized by sparse data coverage, large elevation gradients, rain shadows, inversions, cold air drainage, and coastal effects, showed the greatest improvement. The PRISM data set benefited from a peer review procedure that incorporated local knowledge and data into the development process.

International Journal of Climatology↗

USGS1996

Global distribution of plant-extractable water capacity of soil

Plant-extractable water capacity of soil is the amount of water that can be extracted from the soil to fulfill evapotranspiration demands. It is often assumed to be spatially invariant in large-scale computations of the soil-water balance. Empirical evidence, however, suggests that this assumption is incorrect. In this paper, we estimate the global distribution of the plant-extractable water capacity of soil. A representative soil profile, characterized by horizon (layer) particle size data and thickness, was created for each soil unit mapped by FAO (Food and Agriculture Organization of the United Nations)/Unesco. Soil organic matter was estimated empirically from climate data. Plant rooting depths and ground coverages were obtained from a vegetation characteristic data set. At each 0.5°×0.5° grid cell where vegetation is present, unit available water capacity (cm water per cm soil) was estimated from the sand, clay, and organic content of each profile horizon, and integrated over horizon thickness. Summation of the integrated values over the lesser of profile depth and root depth produced an estimate of the plant-extractable water capacity of soil. The global average of the estimated plant-extractable water capacities of soil is 8ċ6cm (Greenland, Antarctica and bare soil areas excluded). Estimates are less than 5, 10 and 15 cm—over approximately 30, 60, and 89 per cent of the area, respectively. Estimates reflect the combined effects of soil texture, soil organic content, and plant root depth or profile depth. The most influential and uncertain parameter is the depth over which the plant- extractable water capacity of soil is computed, which is usually limited by root depth. Soil texture exerts a lesser, but still substantial, influence. Organic content, except where concentrations are very high, has relatively little effect.

International Journal of Climatology↗

USGS1999

Decadal variations in the strength of ENSO teleconnections with precipitation in the western United States

Changing patterns of correlations between the historical average June-November Southern Oscillation Index (SOI) and October-March precipitation totals for 84 climate divisions in the western US indicate a large amount of variability in SOI/precipitation relations on decadal time scales. Correlations of western US precipitation with SOI and other indices of tropical El Nino-Southern Oscillation (ENSO) processes were much weaker from 1920 to 1950 than during recent decades. This variability in teleconnections is associated with the character of tropical air-sea interactions as indexed by the number of out-of-phase SOI/tropical sea surface temperature (SST) episodes, and with decadal variability in the North Pacific Ocean as indexed by the Pacific Decadal Oscillation (PDO). ENSO teleconnections with precipitation in the western US are strong when SOI and NINO3 are out-of-phase and PDO is negative. ENSO teleconnections are weak when SOI and NINO3 are weakly correlated and PDO is positive. Decadal modes of tropical and North Pacific Ocean climate variability are important indicators of periods when ENSO indices, like SOI, can be used as reliable predictors of winter precipitation in the US.

International Journal of Climatology↗

USGS2006

Midwestern streamflow, precipitation, and atmospheric vorticity influenced by Pacific sea-surface temperatures and total solar-irradiance variations

A solar effect on streamflow in the Midwestern United States is described and supported in a six-step physical connection between total solar irradiance (TSI), tropical sea-surface temperatures (SSTs), extratropical SSTs, jet-stream vorticity, surface-layer vorticity, precipitation, and streamflow. Variations in the correlations among the individual steps indicate that the solar/hydroclimatic mechanism is complex and has a time element (lag) that may not be constant. Correct phasing, supported by consistent spectral peaks between 0.092 and 0.096 cycles per year in all data sets within the mechanism is strong evidence for its existence. A significant correlation exists between total solar irradiance and the 3-year moving average of annual streamflow for Iowa (R = 0.67) and for the Mississippi River at St Louis, Missouri (R = 0.60), during the period 1950-2000. Published in 2005 by John Wiley & Sons, Ltd.

International Journal of Climatology↗

USGS2006

Multidecadal climate variability of global lands and oceans

Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperature (SSTs). The PDSI and SST data for 1925-2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Published in 2006 by John Wiley & Sons, Ltd.

International Journal of Climatology↗

USGS2006

Shifting covariability of North American summer monsoon precipitation with antecedent winter precipitation

Previous research has suggested that a general inverse relation exists between winter precipitation in the southwestern United states (US) and summer monsoon precipitation. In addition, it has been suggested that this inverse relation between winter precipitation and the magnitude of the southwestern US monsoon breaks down under certain climatic conditions that override the regional winter/monsoon precipitation relations. Results from this new study indicate that the winter/monsoon precipitation relations do not break down, but rather shift location through time. The strength of winter/monsoon precipitation relations, as indexed by 20-year moving correlations between winter precipitation and monsoon precipitation, decreased in Arizona after about 1970, but increased in New Mexico. The changes in these correlations appear to be related to an eastward shift in the location of monsoon precipitation in the southwestern US. This eastward shift in monsoon precipitation and the changes in correlations with winter precipitation also appear to be related to an eastward shift in July/August atmospheric circulation over the southwestern US that resulted in increased monsoon precipitation in New Mexico. Results also indicate that decreases in sea-surface temperatures (SSTs) in the central North Pacific Ocean also may be associated with th changes in correlations between winter and monsoon precipitation. Copyright ?? 2006 Royal Meteorological Society.

International Journal of Climatology↗

USGS2006

Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications

Evaluating a range of scenarios that accurately reflect precipitation variability is critical for water resource applications. Inputs to these applications can be provided using location- and interval-specific probability distributions. These distributions make it possible to estimate the likelihood of rainfall being within a specified range. In this paper, we demonstrate the feasibility of fitting cell-by-cell probability distributions to grids of monthly interpolated, continent-wide data. Future work will then detail applications of these grids to improved satellite-remote sensing of drought and interpretations of probabilistic climate outlook forum forecasts. The gamma distribution is well suited to these applications because it is fairly familiar to African scientists, and capable of representing a variety of distribution shapes. This study tests the goodness-of-fit using the Kolmogorov–Smirnov (KS) test, and compares these results against another distribution commonly used in rainfall events, the Weibull. The gamma distribution is suitable for roughly 98% of the locations over all months. The techniques and results presented in this study provide a foundation for use of the gamma distribution to generate drivers for various rain-related models. These models are used as decision support tools for the management of water and agricultural resources as well as food reserves by providing decision makers with ways to evaluate the likelihood of various rainfall accumulations and assess different scenarios in Africa.

International Journal of Climatology↗

USGS2008

Trends and spatial distribution of annual and seasonal rainfall in Ethiopia

As a country whose economy is heavily dependent on low-productivity rainfed agriculture, rainfall trends are often cited as one of the more important factors in explaining various socio-economic problems such as food insecurity. Therefore, in order to help policymakers and developers make more informed decisions, this study investigated the temporal dynamics of rainfall and its spatial distribution within Ethiopia. Changes in rainfall were examined using data from 134 stations in 13 watersheds between 1960 and 2002. The variability and trends in seasonal and annual rainfall were analysed at the watershed scale with data (1) from all available years, and (2) excluding years that lacked observations from at least 25% of the gauges. Similar analyses were also performed at the gauge, regional, and national levels. By regressing annual watershed rainfall on time, results from the one-sample t -test show no significant changes in rainfall for any of the watersheds examined. However, in our regressions of seasonal rainfall averages against time, we found a significant decline in June to September rainfall (i.e. Kiremt) for the Baro-Akobo, Omo-Ghibe, Rift Valley, and Southern Blue Nile watersheds located in the southwestern and central parts of Ethiopia. While the gauge level analysis showed that certain gauge stations experienced recent changes in rainfall, these trends are not necessarily reflected at the watershed or regional levels.

International Journal of Climatology↗

USGS2011

Millennial precipitation reconstruction for the Jemez Mountains, New Mexico, reveals changing drought signal

Drought is a recurring phenomenon in the American Southwest. Since the frequency and severity of hydrologic droughts and other hydroclimatic events are of critical importance to the ecology and rapidly growing human population of this region, knowledge of long-term natural hydroclimatic variability is valuable for resource managers and policy-makers. An October–June precipitation reconstruction for the period AD 824–2007 was developed from multi-century tree-ring records of Pseudotsuga menziesii (Douglas-fir), Pinus strobiformis (Southwestern white pine) and Pinus ponderosa (Ponderosa pine) for the Jemez Mountains in Northern New Mexico. Calibration and verification statistics for the period 1896–2007 show a high level of skill, and account for a significant portion of the observed variance (>50%) irrespective of which period is used to develop or verify the regression model. Split-sample validation supports our use of a reconstruction model based on the full period of reliable observational data (1896–2007). A recent segment of the reconstruction (2000–2006) emerges as the driest 7-year period sensed by the trees in the entire record. That this period was only moderately dry in precipitation anomaly likely indicates accentuated stress from other factors, such as warmer temperatures. Correlation field maps of actual and reconstructed October–June total precipitation, sea surface temperatures and 500-mb geopotential heights show characteristics that are similar to those indicative of El Niño–Southern Oscillation patterns, particularly with regard to ocean and atmospheric conditions in the equatorial and north Pacific. Our 1184-year reconstruction of hydroclimatic variability provides long-term perspective on current and 20th century wet and dry events in Northern New Mexico, is useful to guide expectations of future variability, aids sustainable water management, provides scenarios for drought planning and as inputs for hydrologic models under a broader range of conditions than those provided by historical climate records.

New Mexico↗

USGS2011

Century-scale variability in global annual runoff examined using a water balance model

A monthly water balance model (WB model) is used with CRUTS2.1 monthly temperature and precipitation data to generate time series of monthly runoff for all land areas of the globe for the period 1905 through 2002. Even though annual precipitation accounts for most of the temporal and spatial variability in annual runoff, increases in temperature have had an increasingly negative effect on annual runoff after 1980. Although the effects of increasing temperature on runoff became more apparent after 1980, the relative magnitude of these effects are small compared to the effects of precipitation on global runoff.

International Journal of Climatology↗

USGS2006

General circulation model simulations of winter and summer sea-level pressures over North America

Temporal variability of synoptic-scale circulation is a dominant factor in regional temporal climate variations. In the midlatitudes, temporal variability of synoptic-scale circulation has been found to be related to temporal variations in regional air temperature and precipitation. General circulation model (GCM) simulations of long-term changes in synoptic-scale circulation may be useful in assessing the effects of climate change on regional air temperature and precipitation. Atmospheric pressure is an important component of synoptic-scale circulation. In this paper, observed sea-level pressures were used to evaluate winter and summer sea-level pressures over North America simulated by the Goddard Institute for Space Studies (GISS) and the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation models. The objective of the study is to determine how similar the spatial and temporal distributions of GCM-simulated daily sea-level pressures over North America are to observed distributions. Overall, both models are better at reproducing observed within-season variance of winter and summer sea-level pressures than they are at simulating the magnitude of mean winter and summer sea-level pressures. Results indicate that winter sea-level pressures are better simulated by the GISS model than by the GFDL model. The GFDL model simulates anomalously high winter sea-level pressures over north-eastern North America. In summer, the GISS model underestimates sea-level pressures, whereas the GFDL model overestimates sea-level pressures over most of North America. Kolmogorov-Smirnov tests indicate that much of the error in model simulations can be attributed to differences between simulated and observed means. Comparisons of spatial correlation matrices of observed and simulated sea-level pressures indicate that GCMs simulate spatial variability of sea-level pressures that is similar to observed. These results suggest that GCMs are able to simulate major components of synoptic-scale circulation over North America, especially for winter.

International Journal of Climatology↗

USGS2007

Relationships between 700 hPa height anomalies and 1 April snowpack accumulations in the western USA

Relationships between atmospheric circulation and the temporal and spatial distributions of snowpack accumulations in the western USA are examined. Winter mean 700 hPa height anomalies, representing the average atmospheric circulation during the snow season, are compared with snowpack measurements made on or about 1 April at 311 snowcourse 7stations in the western USA during the winters of 1947–1948 through 1986–1987. Correlation and anomaly pattern analysis are used to identify relations between atmospheric circulation and the temporal and spatial distributions of snowpack accumulations, and to quantify the degree to which the temporal and spatial variability in snowpack accumulations can be attributed to variations in atmospheric circulation. Results indicate that winter mean 700 hPa height anomalies account for a statistically significant portion of both the temporal and spatial variability in the snowpack accumulations. In general, above-average snowpack accumulations are associated with negative 700 hPa height anomalies over the eastern North Pacific Ocean and the western USA. These anomalies are indicative of anomalous cyclonic circulation, which produces an anomalous westerly flow of moist air from the eastern North Pacific Ocean into the western USA and increases winter precipitation and snowpack accumulations. Below-average snowpack accumulations at most of the snowcourse stations are associated with positive 700 hPa height anomalies over the western USA. These positive anomalies indicate anomalous anticyclonic circulation which prevents the intrusion of moist air from the eastern North Pacific Ocean into the western USA, increases subsidence, and decreases winter precipitation. Five winter mean 700 hPa height anomaly patterns also were identified that explain the spatial variability in snowpack accumulations.

International Journal of Climatology↗