NOAA Climate Prediction Center

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 model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system. CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research. Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.

In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979–2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP–Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability.

Abstract The second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled reanalysis was made over a 32-yr period (1979–2010), which provided the initial conditions to carry out a comprehensive reforecast over 29 years (1982–2010). This was done to obtain consistent and stable calibrations, as well as skill estimates for the operational subseasonal and seasonal predictions at NCEP with CFSv2. The operational implementation of the full system ensures a continuity of the climate record and provides a valuable up-to-date dataset to study many aspects of predictability on the seasonal and subseasonal scales. Evaluation of the reforecasts show that the CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days (dramatically improving subseasonal forecasts), nearly doubles the skill of seasonal forecasts of 2-m temperatures over the United States, and significantly improves global SST forecasts over its predecessor. The CFSv2 not only provides greatly improved guidance at these time scales but also creates many more products for subseasonal and seasonal forecasting with an extensive set of retrospective forecasts for users to calibrate their forecast products. These retrospective and real-time operational forecasts will be used by a wide community of users in their decision making processes in areas such as water management for rivers and agriculture, transportation, energy use by utilities, wind and other sustainable energy, and seasonal prediction of the hurricane season.

A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors derived from geostationary satellite infrared data. The Climate Prediction Center morphing method (CMORPH) uses motion vectors derived from half-hourly interval geostationary satellite IR imagery to propagate the relatively high quality precipitation estimates derived from passive microwave data. In addition, the shape and intensity of the precipitation features are modified (morphed) during the time between microwave sensor scans by performing a time-weighted linear interpolation. This process yields spatially and temporally complete microwave-derived precipitation analyses, independent of the infrared temperature field. CMORPH showed substantial improvements over both simple averaging of the microwave estimates and over techniques that blend microwave and infrared information but that derive estimates of precipitation from infrared data when passive microwave information is unavailable. In particular, CMORPH outperforms these blended techniques in terms of daily spatial correlation with a validating rain gauge analysis over Australia by an average of 0.14, 0.27, 0.26, 0.22, and 0.20 for April, May, June–August, September, and October 2003, respectively. CMORPH also yields higher equitable threat scores over Australia for the same periods by an average of 0.11, 0.14, 0.13, 0.14, and 0.13. Over the United States for June–August, September, and October 2003, spatial correlation was higher for CMORPH relative to the average of the same techniques by an average of 0.10, 0.13, and 0.13, respectively, and equitable threat scores were higher by an average of 0.06, 0.09, and 0.10, respectively.

The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1 1 lat/long grid from currently available observational data. Where possible (40N-40S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR T b ) are compared with a threshold and all ''cold'' pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite Precipitation Index, but for the TMPI the IR T b threshold and conditional rain rate are set locally by month from Special Sensor Microwave Imager-based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite-gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television and Infrared Observation Satellite Operational Vertical Sounder (TOVS) precipitation. The frequency of rain days in the TOVS is scaled down to match that in the TMPI at the data boundaries, and the resulting nonzero TOVS values are scaled locally to sum to the SG (which is a globally complete monthly product).

Results are presented from the second phase of the multiinstitution North American Land Data Assimilation System (NLDAS‐2) research partnership. In NLDAS, the Noah, Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic land surface models (LSMs) are executed over the conterminous U.S. (CONUS) in realtime and retrospective modes. These runs support the drought analysis, monitoring and forecasting activities of the National Integrated Drought Information System, as well as efforts to monitor large‐scale floods. NLDAS‐2 builds upon the framework of the first phase of NLDAS (NLDAS‐1) by increasing the accuracy and consistency of the surface forcing data, upgrading the land surface model code and parameters, and extending the study from a 3‐year (1997–1999) to a 30‐year (1979–2008) time window. As the first of two parts, this paper details the configuration of NLDAS‐2, describes the upgrades to the forcing, parameters, and code of the four LSMs, and explores overall model‐to‐model comparisons of land surface water and energy flux and state variables over the CONUS. Focusing on model output rather than on observations, this study seeks to highlight the similarities and differences between models, and to assess changes in output from that seen in NLDAS‐1. The second part of the two‐part article focuses on the validation of model‐simulated streamflow and evaporation against observations. The results depict a higher level of agreement among the four models over much of the CONUS than was found in the first phase of NLDAS. This is due, in part, to recent improvements in the parameters, code, and forcing of the NLDAS‐2 LSMs that were initiated following NLDAS‐1. However, large inter‐model differences still exist in the northeast, Lake Superior, and western mountainous regions of the CONUS, which are associated with cold season processes. In addition, variations in the representation of sub‐surface hydrology in the four LSMs lead to large differences in modeled evaporation and subsurface runoff. These issues are important targets for future research by the land surface modeling community. Finally, improvement from NLDAS‐1 to NLDAS‐2 is summarized by comparing the streamflow measured from U.S. Geological Survey stream gauges with that simulated by four NLDAS models over 961 small basins.

The Drought Monitor was started in spring 1999 in response to a need for improved information about the status of drought across the United States. It serves as an example of interagency cooperation in a time of limited resources. The Drought Monitor process also illustrates the creative use of Internet technologies to disseminate authoritative information about drought and to receive regional and local input that is in turn incorporated into the product. This paper describes the Drought Monitor and the interactive process through which it is created.

Abstract The Climate Forecast System (CFS), the fully coupled ocean–land–atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004, is described and evaluated in this paper. The CFS provides important advances in operational seasonal prediction on a number of fronts. For the first time in the history of U.S. operational seasonal prediction, a dynamical modeling system has demonstrated a level of skill in forecasting U.S. surface temperature and precipitation that is comparable to the skill of the statistical methods used by the NCEP Climate Prediction Center (CPC). This represents a significant improvement over the previous dynamical modeling system used at NCEP. Furthermore, the skill provided by the CFS spatially and temporally complements the skill provided by the statistical tools. The availability of a dynamical modeling tool with demonstrated skill should result in overall improvement in the operational seasonal forecasts produced by CPC. The atmospheric component of the CFS is a lower-resolution version of the Global Forecast System (GFS) that was the operational global weather prediction model at NCEP during 2003. The ocean component is the GFDL Modular Ocean Model version 3 (MOM3). There are several important improvements inherent in the new CFS relative to the previous dynamical forecast system. These include (i) the atmosphere–ocean coupling spans almost all of the globe (as opposed to the tropical Pacific only); (ii) the CFS is a fully coupled modeling system with no flux correction (as opposed to the previous uncoupled “tier-2” system, which employed multiple bias and flux corrections); and (iii) a set of fully coupled retrospective forecasts covering a 24-yr period (1981–2004), with 15 forecasts per calendar month out to nine months into the future, have been produced with the CFS. These 24 years of fully coupled retrospective forecasts are of paramount importance to the proper calibration (bias correction) of subsequent operational seasonal forecasts. They provide a meaningful a priori estimate of model skill that is critical in determining the utility of the real-time dynamical forecast in the operational framework. The retrospective dataset also provides a wealth of information for researchers to study interactive atmosphere–land–ocean processes.

Abstract A new gauge-based analysis of daily precipitation has been constructed on a 0.5° latitude–longitude grid over East Asia (5°–60°N, 65°–155°E) for a 26-yr period from 1978 to 2003 using gauge observations at over 2200 stations collected from several individual sources. First, analyzed fields of daily climatology are computed by interpolating station climatology defined as the summation of the first six harmonics of the 365-calendar-day time series of the mean daily values averaged over a 20-yr period from 1978 to 1997. These fields of daily climatology are then adjusted by the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) monthly precipitation climatology to correct the bias caused by orographic effects. Gridded fields of the ratio of daily precipitation to the daily climatology are created by interpolating the corresponding station values using the optimal interpolation method. Analyses of total daily precipitation are finally calculated by multiplying the daily climatology by the daily ratio. Cross-validation tests indicated that this gauge-based analysis has high quantitative quality with a negligible bias and a correlation coefficient of ∼0.6 for comparisons between withdrawn station data and the analysis at a 0.05° latitude–longitude grid box. The quality of the analysis increases with the gauge network density. The mean distribution and annual cycle of this new gauge analysis present similar patterns but with more detailed structures and slightly larger magnitude compared to other published monthly gauge analyses over the region. The East Asia gauge analysis is applied to verify the performance of five satellite-based precipitation estimates. This examination reveals the regionally and seasonally dependent performance of the satellite products with the best statistics observed for relatively wet regions. Further improvements of the daily gauge analysis are underway to increase the gauge network density and to refine the algorithm to better deal with the orographic effects especially over South and Southeast Asia.

Abstract El Niño–Southern Oscillation (ENSO) is a naturally occurring mode of tropical Pacific variability, with global impacts on society and natural ecosystems. While it has long been known that El Niño events display a diverse range of amplitudes, triggers, spatial patterns, and life cycles, the realization that ENSO’s impacts can be highly sensitive to this event-to-event diversity is driving a renewed interest in the subject. This paper surveys our current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions.

The new Version 2.3 of the GPCP Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross calibration of satellite data inputs and updates to the gauge analysis. Over ocean, changes starting in 2003 result in an overall precipitation increase of 1.8% after 2009. Updating the gauge analysis to its final, high quality version increases the global land total by 1.8% for the post-2002 period. These changes correct a small, incorrect dip in the estimated global precipitation over the last decade in the earlier Version 2.2. The GPCP analysis is also used to describe global precipitation for 2017. The general La Nina pattern for 2017 is noted and the evolution from the early 2016 El Nino pattern is described. The 2017 global value is one of the highest for the 19792017 period, exceeded only by 2016 and 1998 (both El Nino years) and reinforces the small positive trend. Results for 2017 also reinforce significant trends in precipitation intensity (on a monthly scale) in the tropics. These results for 2017 indicate the value of the GPCP analysis for climate monitoring in addition to research.

Abstract An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge.

In this study, the authors apply the NCEP–NCAR reanalysis and other observations to depict the association of the Asian–Pacific–American climate with the East Asian jet stream (EAJS). With an emphasis on boreal winter seasons and on interannual timescales, they analyze the variations of the EAJS and their relationships with El Niño–Southern Oscillation (ENSO) and extratropical North Pacific sea surface temperature (SST), and assess the relative connections of the EAJS and ENSO to the anomalies of atmospheric circulation, surface temperature, and precipitation in the Asian–Pacific–American region. It is found that the EAJS is coupled to a teleconnection pattern spanning the entire Asian–Pacific–American region with the strongest signals over east Asia and the western Pacific. This pattern differs significantly from that associated with ENSO, which influences the earth's climate extensively with a strongest impact on the climate over the central Pacific and east. A strong EAJS is associated with an intensification of the weather and climate systems in Asia and over the Pacific such as deepening of the east Asian trough and the Aleutian low and strengthening of the east Asian winter monsoon. It is linked to colder and drier conditions in east Asia and stronger convection over the tropical Asia–Australia sector. Compared with ENSO, the EAJS seems to link to the climate signals of Asia and the Pacific more strongly. An intensified EAJS is also associated with anomalies of temperature and precipitation in North America due to the related changes in stationary wave patterns. While the EAJS does not strongly link to the tropical central-eastern Pacific SST, it is significantly associated with the extratropical North Pacific SST, more specifically the second most dominant mode of the empirical orthogonal function analysis of the SST. In addition, a strong (weak) EAJS seems to follow a large (small) meridional gradient of the western Pacific SST associated with warming (cooling) in the Tropics–subtropics and cooling (warming) in the extratropics.

Central Great Plains precipitation deficits during May–August 2012 were the most severe since at least 1895, eclipsing the Dust Bowl summers of 1934 and 1936. Drought developed suddenly in May, following near-normal precipitation during winter and early spring. Its proximate causes were a reduction in atmospheric moisture transport into the Great Plains from the Gulf of Mexico. Processes that generally provide air mass lift and condensation were mostly absent, including a lack of frontal cyclones in late spring followed by suppressed deep convection in the summer owing to large-scale subsidence and atmospheric stabilization. Seasonal forecasts did not predict the summer 2012 central Great Plains drought development, which therefore arrived without early warning. Climate simulations and empirical analysis suggest that ocean surface temperatures together with changes in greenhouse gases did not induce a substantial reduction in sum mertime precipitation over the central Great Plains during 2012. Yet, diagnosis of the retrospective climate simulations also reveals a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade, most probably due to natural decadal variability. As a consequence, the probability of the severe summer Great Plains drought occurring may have increased in the last decade compared to the 1980s and 1990s, and the so-called tail risk for severe drought may have been heightened in summer 2012. Such an extreme drought event was nonetheless still found to be a rare occurrence within the spread of 2012 climate model simulations. The implications of this study's findings for U.S. seasonal drought forecasting are discussed.

The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hailstorms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make using the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical link- ages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multidecadal trends in the areal percentage of the contiguous United States impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the United States as a whole since 1950.

Mountain ranges, deserts, ice fields and oceans generally act as barriers to the movement of land-dependent animals, often profoundly shaping migration routes. We used satellite telemetry to track the southward flights of bar-tailed godwits (Limosa lapponica baueri), shorebirds whose breeding and non-breeding areas are separated by the vast central Pacific Ocean. Seven females with surgically implanted transmitters flew non-stop 8,117-11,680 km (10153+/-1043 s.d.) directly across the Pacific Ocean; two males with external transmitters flew non-stop along the same corridor for 7,008-7,390 km. Flight duration ranged from 6.0 to 9.4 days (7.8+/-1.3 s.d.) for birds with implants and 5.0 to 6.6 days for birds with externally attached transmitters. These extraordinary non-stop flights establish new extremes for avian flight performance, have profound implications for understanding the physiological capabilities of vertebrates and how birds navigate, and challenge current physiological paradigms on topics such as sleep, dehydration and phenotypic flexibility. Predicted changes in climatic systems may affect survival rates if weather conditions at their departure hub or along the migration corridor should change. We propose that this transoceanic route may function as an ecological corridor rather than a barrier, providing a wind-assisted passage relatively free of pathogens and predators.

Abstract A new ENSO SST index is documented that is strongly correlated to the core ENSO phenomenon. The SST anomaly in much of the east‐central and eastern tropical Pacific is closely related to ENSO. However, the anomaly from approximately the centre of the eastern half of the equatorial Pacific westward to near the date line is suggested to be most strongly ENSO‐related when data spanning the most recent several decades are used. This is the case both with respect to (1) strength of association with other oceanic/atmospheric ENSO‐related anomalies (both simultaneously and as a time‐delayed predictand), and (2) impact on remote worldwide climate anomalies. This observational insight was lacking in the early 1980s when the four “Niño” regions were developed. While a firmer dynamical foundation for this regional preference still needs to be established, the region straddling Niño 3 and Niño 4 may be regarded as an appropriate general SST index of the ENSO state by researchers, diagnosticians and forecasters. A dataset of this index, called “Niño 3.4” (5°N‐5°S, 120–170°W), is maintained on the Internet, shown in the Climate Diagnostics Bulletin, and provided in the Appendix of this note.

Key features of the U.S. summer precipitation regime are examined within the context of the evolving North American monsoon system. The focus is on the antecedent and subsequent atmospheric conditions over the conterminous United States relative to the onset of monsoon precipitation over the southwestern United States, which typically begins in early July. The onset of the monsoon in this region is determined using a precipitation index, based on daily observed precipitation for a 31-yr (1963–94) period. Lagged composites of the observed precipitation and various fields from the NCEP–NCAR reanalysis for the period 1979–94 provide a comprehensive picture of atmospheric conditions during the evolution of the U.S. warm season precipitation regime. The summer precipitation regime is characterized by an out-of-phase relationship between precipitation over the Southwest and the Great Plains–northern tier and an in-phase relationship between precipitation over the Southwest and the East Coast. Changes in the upper-tropospheric wind and divergence fields (mean vertical motion) are broadly consistent with the evolution of this precipitation pattern. Enhanced upper-tropospheric divergence in the vicinity and south of the upper-tropospheric monsoon high coincides with enhanced upper-tropospheric easterlies and Mexican monsoon rainfall after onset. Over the Great Plains and along the northern tier, the middle- and upper-tropospheric flow is more convergent and rainfall diminishes after onset to the north and east of the monsoon high. The frequency of occurrence of the Great Plains low-level jet (LLJ) and southerly moisture transport change little during the evolution. However, LLJ-related precipitation is controlled by changes in the large-scale flow related to the North American monsoon system. There is increased upper-tropospheric divergence and precipitation after onset in the vicinity of an “induced” trough over the eastern United States. The pattern of evaporation minus precipitation from the NCEP–NCAR reanalysis shows broad consistency with the divergence of the vertically integrated flux of water vapor during the monsoon, although the resolution in the NCEP–NCAR reanalysis is inadequate to yield quantitatively accurate regional estimates of these fields. In agreement with earlier studies, the NCEP–NCAR reanalysis indicates that most of the moisture below 850 hPa over the desert Southwest comes from the northern Gulf of California, while most of the moisture at and above 850 hPa arrives from over the Gulf of Mexico.

Long-term trends and interannual variations of circulation anomalies in the Southern Hemisphere are examined using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis from 1949 to 1998. The changes in planetary circulation regimes are linked to global sea surface temperature anomalies (SSTAs). Empirical orthogonal function (EOF) analysis was performed on 500-hPa height anomalies. The leading mode EOF1 shows a strong zonal symmetry with a phase reversal between height anomalies in high and midlatitudes. Apart from zonal symmetry, a zonal wavenumber 3 is evident with three centers located in three southern oceans. In the low-frequency band with fluctuations longer than 60 months, EOF1 is associated with the second rotated EOF mode of SSTAs with positive loadings over three southern oceans and negative loadings in the North Pacific and the North Atlantic. The next two modes are the Pacific–South American (PSA) patterns. They depict wave-3 patterns in quadrature with each other and a well-defined wave train from the tropical Pacific to Argentina with large amplitudes in the Pacific–South American sector. On decadal timescales, the abrupt warming over the central and eastern Pacific is related to the strengthening of PSA1. In the interannual band, PSA1 is associated with the low-frequency part of El Niño–Southern Oscillation (ENSO) variability with the dominant period of 40–48 months. PSA2 is associated with the quasi-biennial component of ENSO variability with a period of 26 months.

A gauge‐based analysis of hourly precipitation is constructed on a 0.25° latitude/longitude grid over China for a 3 year period from 2005 to 2007 by interpolating gauge reports from ∼2000 stations collected and quality controlled by the National Meteorological Information Center of the China Meteorological Administration. Gauge‐based precipitation analysis is applied to examine the performance of six high‐resolution satellite precipitation estimates, including Joyce et al.'s (2004) Climate Prediction Center Morphing Technique (CMORPH) and the arithmetic mean of the microwave estimates used in CMORPH; Huffman et al.'s (2007) Tropical Rainfall Measuring Mission (TRMM) precipitation product 3B42 and its real‐time version 3B42RT; Turk et al.'s (2004) Naval Research Laboratory blended product; and Hsu et al.'s (1997) Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Network (PERSIANN). Our results showed the following: (1) all six satellite products are capable of capturing the overall spatial distribution and temporal variations of precipitation reasonably well; (2) performance of the satellite products varies for different regions and different precipitation regimes, with better comparison statistics observed over wet regions and for warm seasons; (3) products based solely on satellite observations present regionally and seasonally varying biases, while the gauge‐adjustment procedures applied in TRMM 3B42 remove the large‐scale bias almost completely; (4) CMORPH exhibits the best performance in depicting the spatial pattern and temporal variations of precipitation; and (5) both the relative magnitude and the phase of the warm season precipitation over China are estimated quite well, but the early morning peak associated with the Mei‐Yu rainfall over central eastern China is substantially under‐estimated by all satellite products.