Gregory J. McCabe

Evaluating the use of 'goodness-of-fit' measures in hydrologic and hydroclimatic model validation

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.

Pacific and Atlantic Ocean influences on multidecadal drought frequency in the United States

More than half (52%) of the spatial and temporal variance in multidecadal drought frequency over the conterminous United States is attributable to the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). An additional 22% of the variance in drought frequency is related to a complex spatial pattern of positive and negative trends in drought occurrence possibly related to increasing Northern Hemisphere temperatures or some other unidirectional climate trend. Recent droughts with broad impacts over the conterminous U.S. (1996, 1999–2002) were associated with North Atlantic warming (positive AMO) and northeastern and tropical Pacific cooling (negative PDO). Much of the long-term predictability of drought frequency may reside in the multidecadal behavior of the North Atlantic Ocean. Should the current positive AMO (warm North Atlantic) conditions persist into the upcoming decade, we suggest two possible drought scenarios that resemble the continental-scale patterns of the 1930s (positive PDO) and 1950s (negative PDO) drought.

Warming experiments underpredict plant phenological responses to climate change

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

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 SO1 and other indices of tropical El Nifio-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 SO1 and NIN03 are out-of-phase and PDO is negative. ENSO teleconnections are weak when SO1 and NIN03 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. Copyright 0 1999 Royal Meteorological Society.

Trends in Northern Hemisphere surface cyclone frequency and intensity

Abstract 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.

Comparison of Single and Multiple Flow Direction Algorithms for Computing Topographic Parameters in TOPMODEL

Single flow direction (sfd) and multiple flow direction (mfd) algorithms were used to compute the spatial and statistical distributions of the topographic index used in the watershed model TOPMODEL. An sfd algorithm assumes that subsurface flow occurs only in the steepest downslope direction from any given point; an mfd algorithm assumes that subsurface flow occurs in all downslope directions from any given point. The topographic index in TOPMODEL is In (a/tan/3), where In is the Napierian logarithm, a is the upslope area per unit contour length, and tan/3 is the slope gradient. The In (a/tan /3) distributions were computed from digital elevation model (DEM) data for locations with diverse topography in Arizona, Colorado, Louisiana, Nebraska, North Carolina, Oregon, Pennsylvania, Tennessee, Vermont, and Virginia. The means of the In (a/tan/3) distributions were higher when the mfd algorithm was used for computation compared to when the sfd algorithm was used. The variances and skews of the distributions were lower for the mfd algorithm compared to the sfd algorithm. The differences between the mfd and sfd algorithms in the mean, variance, and skew of the In (a/tan/3) distribution were almost identical for the various DEMs and were not affected by DEM resolution or watershed size. TOPMODEL model efficiency and simulated flow paths were affected only slightly when the In (a/tan/3) distribution was computed with the sfd algorithm instead of the mfd algorithm. Any difference in the model efficiency and simulated flow paths between the sfd and mfd algorithms essentially disappeared when the model was calibrated by adjusting subsurface hydraulic parameters.

Monitoring and Understanding Changes in Heat Waves, Cold Waves, Floods, and Droughts in the United States: State of Knowledge

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...

Primary Modes and Predictability of Year-to-Year Snowpack Variations in the Western United States from Teleconnections with Pacific Ocean Climate

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

Simulation of precipitation by weather type analysis

A method of precipitation simulation that incorporates climatological information has been developed. A Markovian-based model is used to generate temporal sequences of six daily weather types: high pressure; coastal return; maritime tropical return; frontal maritime tropical return; cold frontal overrunning; and warm frontal overrunning. Precipitation values are assigned to individual days by using observed statistical relations between weather types and precipitation characteristics. When this method was applied to an area in the Delaware River basin, the statistics describing average precipitation, extreme precipitation, and drought conditions for simulated precipitation closely matched those of the observed data. Potential applications of this weather type precipitation model include climatic change research and modeling of temperature and evapotranspiration.

Trends and Variability in Snowmelt Runoff in the Western United States

Abstract 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.