Forecasting the week 3/4 period presents many challenges, resulting in a need for improvements to forecast skill. At this distance from initial conditions, numerical models struggle to present skillful forecasts of temperature, precipitation, and associated extremes. One approach to address this is to utilize more predictable large-scale circulation regimes to make forecasts of temperature and precipitation anomalies, using the association between the regimes and surface weather obtained from reanalysis products. This study explores the utility of k-means cluster analysis on geopotential heights and their ability to make skillful regime predictions in the week 3/4 period. Using 14-day running means of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) 500-hPa geopotential heights for the wintertime December-February (DJF) period, circulation regimes are identified using k-means clustering. Each period is assigned a cluster number, allowing the compositing of any reanalysis or observation variable to form cluster maps. Maps of 500-hPa height, 2-m temperature, precipitation, and storm-track anomalies are some of the variables composited. The utility of these relationships in a dynamical forecast setting is tested via Global Ensemble Forecast System v12 (GEFSv12) hindcasts and real-time ensemble suite forecasts. Week 3/4 deterministic and probabilistic experimental forecasts are then derived from cluster assignments using several methods. We fi nd, via a conditional skill analysis, forecasts strongly correlated with a cluster exhibit greater skill for both dynamical model and cluster-derived forecasts. Our preliminary results represent a step forward to aid forecasters make more skillful assessments of the circulation regime and its associated surface weather for this challenging forecast time scale. SIGNIFICANCE STATEMENT: Our paper links the local statistics of 14-day precipitation and temperature within the United States to very broad preferred patterns of winds and pressure over the wide Pacific-North American region. Such patterns, known as "circulation regimes," provide the background that heavily influences local surface conditions. We fi nd that forecasts for which midatmospheric anomalies are closely aligned with one or more circulation regimes are better at predicting the U.S. weather probabilities than other week 3-4 forecasts. A tool based on this fi nding identifi es forecasts for which confidence is higher. Future work will be designed to further exploit the links between circulation regimes and weather to improve the accuracy of week 3-4 forecasts.

The US drought monitor (USDM) has been widely used as an observational reference for evaluating land surface model (LSM) simulation of drought. This study investigates potential caveats in such evaluation when the USDM and LSMs use different base periods and drought indices to identify drought. The retrospective national water model (NWM) v2.0 simulation (1993–2018) was used to exemplify the evaluation, supplemented by North American land data assimilation system phase 2 (NLDAS-2). Over their common period (2000–2018), in distinct contrast with the USDM which shows high drought occurrence (>50%) in the western half of the continental US (CONUS) and the southeastern US with low occurrence (<30%) elsewhere, the NWM and NLDAS-2 based on soil moisture percentiles (SMPs) consistently show higher drought occurrence (30%–40%) in the central and southeastern US than the rest of the CONUS. Much of the differences between the LSMs and USDM, particularly the strong LSM underestimation of drought occurrence in the western and southeastern US, are not attributed to the LSM deficiencies, but rather the lack of long-term drought in the LSM simulations due to their relatively short lengths. Specifically, the USDM integrates drought indices with century-long periods of record, which enables it to capture both short-term (<6 months) drought and long-term (⩾6 months) drought, whereas the relatively short retrospective simulations of the LSMs allows them to adequately capture short-term drought but not long-term drought. In addition, the USDM integrates many drought indices whereas the NWM results are solely based on the SMP, further adding to the inconsistency. The high occurrence of long-term drought in the western and southeastern US in the USDM is further found to be driven collectively by the post-2000 long-term warm sea surface temperature (SST) trend, cold Pacific decadal oscillation and warm Atlantic multi-decadal oscillation, all of which are typical leading patterns of global SST variability that can induce drought conditions in the western, central, and southeastern US. Our findings highlight the effects of the above caveats and suggest that LSM evaluation should stay qualitative when the caveats are considerable.

p. 9 4. Summary pp. 9-10 5. References p. 10

The El Nino Southern Oscillation (ENSO) climate-variability phenomenon greatly affects water availability in the Southeast United States. For example, it is well known that La Nina conditions bring drought to this region. In the past decade, several severe droughts have adversely impacted the water resources of many communities in this region, especially those that rely on surface-water systems. Because small- to mid-size communities are most vulnerable to climate variability, this study was undertaken to develop a climate variability-based community water deficit index (CWDI) for use by water managers in these communities. Although currently available drought indices can be useful tools for monitoring and forecasting purposes, they are not suitable for use in water-supply systems for small- to mid-size communities. The CWDI was conceptualized keeping in mind that it should (1)forecast hydrologic drought, (2)operate at a high spatial resolution, and (3)address both water supply and demand during droughts. The system dynamics-modeling software Structured Thinking Experiential Learning Laboratory with Animation was used to develop the modeling framework to estimate CWDI by evaluating differences in a community water supply and demand, and thus help forecast the severity of an impending drought. Another important feature of the CWDI is its ability to evaluate how drought-management policies can affect the severity of drought. The CWDI was tested in two small- to mid-size communities of this region (Auburn, Alabama, and Griffin, Georgia). The results indicate that the index not only can monitor drought in the studied water-supply systems, but can also forecast ENSO-induced hydrologic droughts in the region and can be used in drought planning. (C) 2013 American Society of Civil Engineers.

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There is increased pressure on the water resources of the southeastern United States due to the rapidly growing population of the region. This pressure is further exacerbated by the severe seasonal to interannual climate variability this region experiences, most of which has been attributed to the El Niño Southern Oscillation (ENSO). Understanding the regional impacts of ENSO on precipitation and streamflow is a valuable tool for water resource managers in the region. This study was undertaken to develop a clear picture of the effect of ENSO on observed precipitation and streamflow anomalies in Alabama to help managers in the state with decision making. The effect of ENSO on precipitation in eight climate divisions of Alabama was assessed using 59 years (1950 to 2008) of monthly historical data. In addition, eight unimpaired streams (one in each climate division) were selected to study the relationship between ENSO and streamflow. Results indicate a significant relationship between ENSO and precipitation as well as between ENSO and streamflow. However, different parts of the state respond differently to ENSO. For precipitation, it was found that the relationship is significant during winter months with dry conditions being associated with La Niña in the southern climate divisions. A fairly strong relationship was also found during other months. Streamflows show high variability and positive correlation during winter months in the southern climate divisions. The results obtained can provide a basis for water resource managers in Alabama to incorporate climate variability caused by ENSO in their decision making related to soil and water conservation.

The National Centers for Environmental Prediction (NCEP) recently completed the latest, and partially coupled, atmosphere-ocean-sea ice model-based climate forecast system reanalysis (CFSR) for the 1979 to current satellite era. In the reanalysis, the observed CO2 concentration and the volcanic aerosols were also prescribed. This paper provides an initial overview of the tropospheric variability in the CFSR by comparing it against available previous reanalyses. CFSR's monthly mean zonal and meridional component of wind U and V, temperature T, and geopotential height H at pressure levels up to 100 mb are compared against those of three other readily available reanalyses NCEP/R1, NCEP/R2 and ERA40 for the period from 1979 to 2008 (2002 for ERA40) and also against modern reanalyses such as JRA, MERRA, and C20. At any given time (analysis hour, day, or month), for the globe as a whole, CFSR analysis agrees reasonably well with the other reanalyses. The CFSR's new coupled model and assimilation system makes use of the recent advances in these areas and hence is possibly an improvement to NCEP's previous reanalyses R1 and R2, which are 15 and 10 years old, respectively. For these long-term climate variability measures the analysis indicates that the CFSR was generally the outlier, with much stronger easterly trades, cooler tropospheric temperatures, and lower geopotential heights during much of the earlier part of the analysis period (1979-similar to 1998). Consequently, real-time monitoring of many of the ENSO-related climate wind indices in the equatorial Pacific or the wind shear index in the tropical North Atlantic from CFSR may be problematic in the context of historical variability.

Several large-scale climate patterns influenced climate conditions and weather patterns across the globe during 2010. The transition from a warm El Niño phase at the beginning of the year to a cool La Niña phase by July contributed to many notable events, ranging from record wetness across much of Australia to historically low Eastern Pacific basin and near-record high North Atlantic basin hurricane activity. The remaining five main hurricane basins experienced below- to well-below-normal tropical cyclone activity. The negative phase of the Arctic Oscillation was a major driver of Northern Hemisphere temperature patterns during 2009/10 winter and again in late 2010. It contributed to record snowfall and unusually low temperatures over much of northern Eurasia and parts of the United States, while bringing above-normal temperatures to the high northern latitudes. The February Arctic Oscillation Index value was the most negative since records began in 1950. The 2010 average global land and ocean surface temperature was among the two warmest years on record. The Arctic continued to warm at about twice the rate of lower latitudes. The eastern and tropical Pacific Ocean cooled about 1°C from 2009 to 2010, reflecting the transition from the 2009/10 El Niño to the 2010/11 La Niña. Ocean heat fluxes contributed to warm sea surface temperature anomalies in the North Atlantic and the tropical Indian and western Pacific Oceans. Global integrals of upper ocean heat content for the past several years have reached values consistently higher than for all prior times in the record, demonstrating the dominant role of the ocean in the Earth's energy budget. Deep and abyssal waters of Antarctic origin have also trended warmer on average since the early 1990s. Lower tropospheric temperatures typically lag ENSO surface fluctuations by two to four months, thus the 2010 temperature was dominated by the warm phase El Niño conditions that occurred during the latter half of 2009 and early 2010 and was second warmest on record. The stratosphere continued to be anomalously cool. Annual global precipitation over land areas was about five percent above normal. Precipitation over the ocean was drier than normal after a wet year in 2009. Overall, saltier (higher evaporation) regions of the ocean surface continue to be anomalously salty, and fresher (higher precipitation) regions continue to be anomalously fresh. This salinity pattern, which has held since at least 2004, suggests an increase in the hydrological cycle. Sea ice conditions in the Arctic were significantly different than those in the Antarctic during the year. The annual minimum ice extent in the Arctic—reached in September—was the third lowest on record since 1979. In the Antarctic, zonally averaged sea ice extent reached an all-time record maximum from mid-June through late August and again from mid-November through early December. Corresponding record positive Southern Hemisphere Annular Mode Indices influenced the Antarctic sea ice extents. Greenland glaciers lost more mass than any other year in the decade-long record. The Greenland Ice Sheet lost a record amount of mass, as the melt rate was the highest since at least 1958, and the area and duration of the melting was greater than any year since at least 1978. High summer air temperatures and a longer melt season also caused a continued increase in the rate of ice mass loss from small glaciers and ice caps in the Canadian Arctic. Coastal sites in Alaska show continuous permafrost warming and sites in Alaska, Canada, and Russia indicate more significant warming in relatively cold permafrost than in warm permafrost in the same geographical area. With regional differences, permafrost temperatures are now up to 2°C warmer than they were 20 to 30 years ago. Preliminary data indicate there is a high probability that 2010 will be the 20th consecutive year that alpine glaciers have lost mass. Atmospheric greenhouse gas concentrations continued to rise and ozone depleting substances continued to decrease. Carbon dioxide increased by 2.60 ppm in 2010, a rate above both the 2009 and the 1980–2010 average rates. The global ocean carbon dioxide uptake for the 2009 transition period from La Niña to El Niño conditions, the most recent period for which analyzed data are available, is estimated to be similar to the long-term average. The 2010 Antarctic ozone hole was among the lowest 20% compared with other years since 1990, a result of warmer-than-average temperatures in the Antarctic stratosphere during austral winter between mid-July and early September.

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice m...

The Climate Prediction Center has used atmospheric temperatures for data analysis from the National Centers for Environmental Prediction (NCEP) model since 1979. Unfortunately, model changes have adversely affected the stability of the climatologic fields, introducing time-varying biases in the anomaly patterns of the Climate Diagnostic Data Base (CDDB). Fortunately, NCEP has addressed this issue by rerunning a state-of-the-art model using fixed assimilation, parameterization, and physics in order to derive a true climatology and anomalies. The authors compare the previous CDDB temperatures with those derived from the stable reanalysis. Results show major improvements for climate diagnostics and monitoring. Also compared are the reanalysis temperatures with brightness temperature T-b observed by the Microwave Sounding Units (MSU), flown aboard the National Oceanic and Atmospheric Administration (NOAA) series of polar-orbiting satellites (TIROS-N to NOAA-14). This MSU dataset has a precision of about 0.02 degrees C globally, and it is available from December 1978. Therefore, the 17 levels of the reanalysis level temperature were weighted to simulate the MSU T-b in order to measure its precision over the 17-yr record. Global time series of the spatial correlations between full fields approach 1.0 throughout the entire record, whereas correlations for the anomaly fields can drop below 0.8 during the high sun season in the Northern Hemisphere. In 1994 the correlations drop below 0.65, which is the largest difference between the two datasets. An EOF on the global T-b differences from both datasets identified a relative drift beginning in 1991. The maximum loading was in the tropical Pacific, although it also extended over the tropical Indian Ocean and the Asian landmass. Results indicate that the reanalysis anomalies are getting progressively colder, relative to the MSU, during the early 1990s. The authors associate this drift with the changes in satellite retrievals and a reduction of Soviet Union data during its breakup. Additional sources of bias may be associated with aerosol contamination after the Mt. Pinotuba eruption and/or drift in the NOAA-11 sensor. Although there is a relative offset in the anomalies, the reanalysis temperatures have a better correspondence with the radiosonde network after 1990. Therefore it appears that the bias is associated with an improvement in the reanalysis input data during the last several years. Since changes in the datasets assimilated into the model can introduce a slight bias, new procedures should be developed to minimizes these effects in any future reanalysis. Finally, although the reanalysis has a slight drift in the later years, the comparison with the MSU spatial anomalies generally showed excellent results. The reanalysis represents a substantial improvement over the CDDB for monitoring climate variability.

We developed methods of forecasting cotton (Gossypium hirsutum L. var. hirsutum) yields at a county level 3 mo before harvest for the states of Alabama and Georgia. Cotton yield historical records for 57 counties were obtained from NASS and detrended using a low‐pass spectral filter. A Canonical Correlation Analysis regression‐based model was annually recalibrated to incorporate the year‐by‐year accumulating data: (i) April–June (during vegetative growth) observed rainfall for the forecasting year, and (ii) July–September (during reproductive growth) global‐scaled 2‐m mean temperatures for years before the forecasting year, beginning with 1970. We produced two types of forecasts: short range and medium range. The short‐range near‐term yield forecast (just before initiating harvest in the region) used gridded assimilated observed 2‐m mean temperatures obtained from the NCEP‐NCAR CDAS Reanalysis data. The medium‐range forecast (3 mo before harvest) used 2‐m mean temperature retrospective forecasts from the operational NOAA/NWS/NCEP Climate Forecasts System coupled global circulation model. The short‐range, near‐term forecast performance was measured by leave‐one‐out cross‐validation and retroactive validation, whereas medium‐range forecast performance used the previous two methods plus a proposed coral‐reef validation method. The agreement between short‐range near‐term forecast and actual cotton yield was statistically significant at the 0.05 level in 31 out of 57 counties. For 48% of these 31 counties, the agreements between medium‐range forecasts and actual cotton yields were statistically significant at the 0.05 level. The goodness‐of‐fit index for those 15 counties was 0.51 and the RMSE ranged from 13 to 31% of the annual yield.

A hybrid dynamical-statistical model is developed for predicting Atlantic seasonal hurricane activity. The model is built upon the empirical relationship between the observed interannual variability of hurricanes and the variability of sea surface temperatures (SSTs) and vertical wind shear in 26-yr (1981-2006) hindcasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS).The number of Atlantic hurricanes exhibits large year-to-year fluctuations and an upward trend over the 26 yr. The latter is characterized by an inactive period prior to 1995 and an active period afterward. The interannual variability of the Atlantic hurricanes significantly correlates with the CFS hindcasts for August-October (ASO) SSTs and vertical wind shear in the tropical Pacific and tropical North Atlantic where CFS also displays skillful forecasts for the two variables. In contrast, the hurricane trend shows less of a correlation to the CFS-predicted SSTs and vertical wind shear in the two tropical regions. Instead, it strongly correlates with observed preseason SSTs in the far North Atlantic. Based on these results, three potential predictors for the interannual variation of seasonal hurricane activity are constructed by averaging SSTs over the tropical Pacific (TPCF; 5 degrees S-5 degrees N, 170 degrees E-130 degrees W) and the Atlantic hurricane main development region (MDR; 10 degrees-20 degrees N, 20 degrees-80 degrees W), respectively, and vertical wind shear over the MDR, all of which are from the CFS dynamical forecasts for the ASO season. In addition, two methodologies are proposed to better represent the long-term trend in the number of hurricanes. One is the use of observed preseason SSTs in the North Atlantic (NATL; 55 degrees-65 degrees N, 30 degrees-60 degrees W) as a predictor for the hurricane trend, and the other is the use of a step function that breaks up the hurricane climatology into a generally inactive period (1981-94) and a very active period (1995-2006). The combination of the three predictors for the interannual variation, along with the two methodologies for the trend, is explored in developing an empirical forecast system for Atlantic hurricanes.A cross validation of the hindcasts for the 1981-2006 hurricane seasons suggests that the seasonal hurricane forecast with the TPCF SST as the only CFS predictor is more skillful in inactive hurricane seasons, while the forecast with only the MDR SST is more skillful in active seasons. The forecast using both predictors gives better results. The most skillful forecast uses the MDR vertical wind shear as the only CFS predictor. A comparison with forecasts made by other statistical models over the 2002-07 seasons indicates that this hybrid dynamical-statistical forecast model is competitive with the current statistical forecast models.

Abstract Interannual and multidecadal extremes in Atlantic hurricane activity are shown to result from a coherent and interrelated set of atmospheric and oceanic conditions associated with three leading modes of climate variability in the Tropics. All three modes are related to fluctuations in tropical convection, with two representing the leading multidecadal modes of convective rainfall variability, and one representing the leading interannual mode (ENSO). The tropical multidecadal modes are shown to link known fluctuations in Atlantic hurricane activity, West African monsoon rainfall, and Atlantic sea surface temperatures, to the Tropics-wide climate variability. These modes also capture an east–west seesaw in anomalous convection between the West African monsoon region and the Amazon basin, which helps to account for the interhemispheric symmetry of the 200-hPa streamfunction anomalies across the Atlantic Ocean and Africa, the 200-hPa divergent wind anomalies, and both the structure and spatial scale ...

The State of the Climate 2005 report summarizes global and regional climate conditions and places them, where possible, into the context of historical records. Descriptions and analyses of notable climatic anomalies, both global and regional, also are presented. According to the Smith and Reynolds global land and ocean surface temperature dataset in use at the NOAA National Climatic Data Center (NCDC), the globally averaged annual mean surface temperature in 2005 was the warmest since the inception of consistent temperature observations in 1880. Unlike the previous record positive anomaly of 1998 (+0.50 degrees C), the 2005 global anomaly of 6.53 degrees C above the 1961-90 mean occurred in the absence of a strong El Nino signal. The record ranking of 2005 was corroborated by a dataset maintained at NASA, while United Kingdom archives placed 2005 second behind 1998. However, statistically, the 2005 global temperature anomaly could not be differentiated from either 1998 or any of the past four years. The majority of the top 10 warmest years on record have occurred in the past decade, and 2005 continues a marked upward trend in globally averaged temperature since the mid-1970s. Lower-tropospheric temperature was the second warmest on record, with northern polar regions the warmest at 1.3 degrees C above the 1979-98 mean. Unlike air temperatures, globally averaged precipitation was near normal relative to the 1961-90 period mean value. The global 2005 anomaly was just -0.87 mm. Over the past 25 years, only 7 years have had above-normal precipitation. Additionally, in 2005, only September-November experienced a positive anomaly. Northern Hemisphere snow cover extent was 0.9 million km(2) below the 36-year average (fifth lowest) and Arctic sea ice extent was record lowest in all months of 2005 except May, resulting in a record lowest annual average Arctic sea ice extent for the year and continuing a roughly 8% yr(-1) decline in ice extent. Carbon dioxide (CO2) concentrations rose to a global average of 378.9 parts per million (ppm); about 2 ppm over the value from 2004. This record CO2 concentration in 2005 continues a trend toward increased atmospheric CO2 since the preindustrial era values of around 280 ppm. The globally aver,aged methane (CH4) concentration in 2005 was 1774.8 parts per billion (ppb), or 2.8 ppb less than in 2004. Stratospheric ozone over Antarctica reached a minimum of 110 Dobson units (DU) on 29 September. This represented the 10th lowest minimum level in the 20 years of,measurement of stratospheric ozone. In the global ocean, sea level was above the 1993-2001 base period mean and rose at a rate of 2.9 +/- 0.4 mm yr(-1). The largest positive anomalies were in the Tropics and Southern Hemisphere. Globally averaged sea,surface temperature (SST) also was above normal in 2005 (relative to the 1971-2002 mean), reflecting the general warming trend in SST observed since 1971. In the Tropics only a-weak warm phase of El Nino materialized, but dissipated by March. A relatively active Madden-Julian oscillation (MJO) resulted in the disruption of normal convective patterns in the tropical Pacific and generated several Kelvin waves in the oceanic mixed layer. In the Atlantic Ocean basin, there was record tropical storm activity, with 27* named storms (15 hurricanes). Three became category 5 storms on the Saffir-Simpson scale, and Hurricane Wilma set a new record for the lowest pressure (882 hPa) recorded in the basin. Both Hurricanes Stan and Katrina had exceptional death tolls, and Katrina became the costliest storm on record. Below-normal tropical storm activity in several other basins resulted in near-normal conditions globally in 2005. Regionally, annual and monthly averaged temperatures were above normal across most of the world. Australia experienced its warmest year on record, as well is its hottest April. For both Russia and Mexico 2005 was the second warmest year on record. Intermittent and delayed monsoons in Africa and East Asia resulted in below-normal precipitation in many areas. Drought continued in much,of the Greater Horn of Africa and developed in the central United States. Record severe drought occurred over both the Iberian Peninsula and-western Amazonia in 2005. In the Amazon, river levels dropped by as much as 11 m between May and September. Conversely, heavy snows early in 2005 combined with a warm boreal spring to generate widespread flooding in areas of southwest Asia. Canada experienced its wettest year on record in 2005, with flooding in Alberta, Manitoba, and Ontario. In July, the South Asian monsoon delivered a record 944.2 mm of precipitation over 24 h to areas around Mumbai, India.

The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP-NCAR reanalysis data.The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub) tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found.In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere-ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to.There are several signs of enthusiasm in the community about using "trends" (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years' averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in "explaining" variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century.