Steven A. Mauget

Multidecadal Regime Shifts in U.S. Streamflow, Precipitation, and Temperature at the End of the Twentieth Century

Abstract Intra- to multidecadal variation in annual streamflow, precipitation, and temperature over the continental United States are evaluated here through the calculation of Mann–Whitney U statistics over running-time windows of 6–30-yr duration. When this method is demonstrated on time series of nationally averaged annual precipitation and mean temperature during 1896–2001, it reveals that 8 of the 10 wettest years occurred during the last 29 yr of that 106-yr period, and 6 of the 10 warmest years during the last 16. Both of these results indicate highly significant departures from long-term stationarity in U.S. climate at the end of the twentieth century. The effects of increased wetness are primarily evident in the central and eastern United States, while evidence of warmth is found throughout the Rocky Mountain region and in the West. Analysis of annual streamflow records across the United States during 1939–98 shows broadly consistent effects. Initial evidence of the recent wet regime is most appar...

Intra- to Multidecadal Climate Variability over the Continental United States: 1932–99

Abstract Trend analysis is used frequently in climate studies, but it is vulnerable to a number of conceptual shortcomings. This analysis of U.S. climate division data uses an alternate approach. The method used here subjects time series of annual average temperature and total precipitation to tests of Mann–Whitney U statistics over moving sampling windows of intra- to multidecadal (IMD) duration. In applying this method to time series of nationally averaged annual rainfall, a highly significant incidence of wet years is found after the early 1970s. When applied to individual climate divisions this test provides the basis for a climate survey method that is more robust than linear trend analysis, and capable of objectively isolating the timing and location of major IMD climate events over the United States. From this survey, four such periods emerge between 1932 and 1999: the droughts of the 1930s and 1950s, a cool 1964–79 period, and wet–warm time windows at the end of the century. More circumstantial co...

LOW FREQUENCY STREAMFLOW REGIMES OVER THE CENTRAL UNITED STATES: 1939-1998

Intra- to multi-decadal (6–30 year) streamflow regimes over the central United States during the late 20th century are identified and investigated here through a two-stage analysis. The first stage ranks mean annual flow rates during 1939–1998, calculates Mann–Whitney Ustatistics from samples of those rankings over running time windows, and then tests those U statistics for significance. This analysis of the records of 42 Hydro-Climatic Data Network stations over the Great Plains and Midwest reveals consistent patterns of highly ranked annual streamflow during time windows at the end of the century, with most beginning during the late 1960s and early 1970s and ending in either 1997 or 1998. Many of these stations are located in a critical agricultural region known as the Corn Belt. The second stage of analysis compares both the duration of abnormal flow periods and the frequency of hydrological surplus and drought conditions during the high flow years indicated by the first stage, relative to the remaining years of 1939–1998. Among gage stations in the climatologically drier western Corn Belt during the 1980s and 1990s there is a clear tendency toward extended periods of above normal flow, which results in more than a doubling in the average annual frequency of hydrological surplus days relative to previous years. These stations also show more than a 50% reduction in the average annual frequency of hydrological drought days relative to previous years. Similar but less pronounced shifts in hydrological regime are evident in the central and eastern Corn Belt, and in the Mississippi River at Vicksburg during 1973–1998. These results indicate that many areas of the central United States have shifted toward a climate regime of relative hydrological surplus during the closing decades of the 20th century.

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenarios forced signal, but is likely inconsistent with the steepest emission scenarios forced signal.

Evaluating Modeled Intra- to Multidecadal Climate Variability Using Running Mann-Whitney Z Statistics

An analysis method previously used to detect observed intra- to multidecadal (IMD) climate regimes was adapted to compare observed and modeled IMD climate variations. Pending the availability of the more appropriate phase 5 Coupled Model Intercomparison Project (CMIP-5) simulations, the method is demonstrated using CMIP-3 model simulations. Although the CMIP-3 experimental design will almost certainly prevent these model runs from reproducing features of historical IMD climate variability, these simulations allow for the demonstration of the method and illustrate how the models and observations disagree. This method samples a time series’s data rankings over moving time windows, converts those ranking sets to a Mann‐Whitney U statistic, and then normalizes the U statistic into a Z statistic. By detecting optimally significant IMD ranking regimes of arbitrary onset and varying duration, this process generates time series of Z values that are an adaptively low-passed and normalized transformation of the original time series. Principal component (PC) analysis of the Z series derived from observed annual temperatures at 92 U.S. grid locations during 1919‐2008 shows two dominant modes: a PC1 mode with cool temperatures before the late 1960s and warm temperatures after the mid-1980s, and a PC2 mode indicating a multidecadal temperature cycle over the Southeast. Using a graphic analysis of a Z error metric that compares modeled and observed Z series,thethreeCMIP-3modelsimulationstestedhereareshowntoreproducethePC1modebutnotthePC2 mode. By providing a way to compare grid-level IMD climate response patterns in observed and modeled data, this method can play a useful diagnostic role in future model development and decadal climate forecasting.

Optimal Ranking Regime Analysis of Intra- to Multidecadal U.S. Climate Variability. Part II: Precipitation and Streamflow*

AbstractIn Part I of this paper, the optimal ranking regime (ORR) method was used to identify intradecadal to multidecadal (IMD) regimes in U.S. climate division temperature data during 1896–2012. Here, the method is used to test for annual and seasonal precipitation regimes during that same period. Water-year mean streamflow rankings at 125 U.S. Hydro-Climatic Data Network gauge stations are also evaluated during 1939–2011. The precipitation and streamflow regimes identified are compared with ORR-derived regimes in the Pacific decadal oscillation (PDO), the Atlantic multidecadal oscillation (AMO), and indices derived from gridded SST anomaly (SSTA) analysis data. Using a graphic display approach that allows for the comparison of IMD climate regimes in multiple time series, an interdecadal cycle in western precipitation is apparent after 1980, as is a similar cycle in northwestern streamflow. Before 1980, IMD regimes in northwestern streamflow and annual precipitation are in approximate antiphase with the...

A web application for cotton irrigation management on the U.S. Southern High Plains. Part I: Crop yield modeling and profit analysis

Irrigated cotton (Gossypium Hirsutum L.) production is a central part of west Texas agriculture that depends on the essentially non-renewable water resource of the Ogallala aquifer. Web-based decision support tools that estimate the profit effects of irrigation for cotton under varying lint price, production cost, and well capacity conditions could help to optimize the agricultural value of the Ogallalas water. The crop modeling and profit analysis component of such a support tool is demonstrated here. This web application is based on a database of modeled yields generated from the meteorological records of four weather stations under un-irrigated (dryland) conditions and under center pivot irrigation with 12 total irrigation (TI) levels spanning deficit to full irrigation conditions. The application converts the databases dryland and irrigated yield outcomes into corresponding values of profit per hectare based on user-defined yield values and production costs. Given the resulting values of dryland and irrigated profit per unit area and the additional constraints of a users well capacity and center pivot area, the application also calculates the profit effects of dividing center pivot area into dryland and irrigated production under the 12 irrigation levels.

A Two-Tier Statistical Forecast Method for Agricultural and Resource Management Simulations

Abstract Simple phase schemes to predict seasonal climate based on leading ENSO indicators can be used to estimate the value of forecast information in agriculture and watershed management, but may be limited in predictive skill. Here, a simple two-tier statistical method is used to hindcast seasonal precipitation over the continental United States, and the resulting skill is compared with that of ENSO phase systems based on Nino-3 sea surface temperature anomaly (SSTA) and Southern Oscillation index (SOI) persistence. The two-tier approach first predicts Nino-3 winter season SSTA, and then converts those predictions to categorical precipitation hindcasts via a simple phase translation process. The hindcasting problem used to make these comparisons is relevant to winter wheat production over the central United States. Thus, given the state of seasonal SOI and Nino-3 indicators defined before August, the goal is to predict the tercile category of the following November–March precipitation. Generally, it wa...

Optimal Ranking Regime Analysis of Intra- to Multidecadal U.S. Climate Variability. Part I: Temperature*

AbstractThe optimal ranking regime (ORR) method was used to identify intradecadal to multidecadal (IMD) time windows containing significant ranking sequences in U.S. climate division temperature data. The simplicity of the ORR procedure’s output—a time series’ most significant nonoverlapping periods of high or low rankings—makes it possible to graphically identify common temporal breakpoints and spatial patterns of IMD variability in the analyses of 102 climate division temperature series. This approach is also applied to annual Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) climate indices, a Northern Hemisphere annual temperature (NHT) series, and divisional annual and seasonal temperature data during 1896–2012. In addition, Pearson correlations are calculated between PDO, AMO, and NHT series and the divisional temperature series. Although PDO phase seems to be an important influence on spring temperatures in the northwestern United States, eastern temperature regimes in a...

Optimal Ranking Regime Analysis of U.S. Summer Temperature and Degree-Days: 1895-2015

AbstractThe optimal ranking regime (ORR) method was applied to mean summer maximum (TMXS) and mean summer minimum (TMNS) temperature and to cumulative summer cooling degree-days (CDDS) calculated f...