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Author(s): Jones, HM; Mecray, EL; Birkel, SD; Conlon, KC; Kinney, PL; Silva, VBS; Solecki, W; Surgeon Rogers, TM

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. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood.

In this study, the authors document the extent to which the precipitation statistics of the new CFS reanalysis (CFSR) represent an improvement over the earlier reanalyses: the NCEP–NCAR reanalysis (R1) and the NCEP–DOE Second Atmospheric Model Intercomparison Project (AMIP-II) reanalysis (R2). An intercomparison between the CFSR, R1, R2, and observations over South America was made for the period 1979–2006. The CFSR shows notable improvements in the large-scale precipitation patterns compared with the previous reanalyses (R1 and R2). In spite of these improvements, the CFSR has substantial biases in intensity and frequency of occurrence of rainfall events. Over west-central Brazil, the core region of the South American monsoon system (SAMS), the CFSR displays a dry bias during the onset phase of the SAMS wet season and a wet bias during the peak and decay phases of the SAMS wet season. The CFSR also displays a dry bias along the South American coast near the mouth of the Amazon and along the east coast of northeastern Brazil. A wet bias exists in all seasons over southeast Brazil and over the Andes Mountains.

A comparison of the statistics of daily precipitation over the conterminous United States is carried out using gridded station data and three generations of reanalysis products in use at the National Centers for Environmental Prediction (NCEP). The reanalysis products are the NCEP–NCAR reanalysis (Kalnay et al.), the NCEP–Department of Energy (DOE) reanalysis (Kanamitsu et al.), and the NCEP Climate Forecast System (CFS) reanalysis (Saha et al.). Several simple measures are used to characterize relationships between the observations and the reanalysis products, including bias, precipitation probability, variance, and correlation. Seasonality is accounted for by examining these measures for four nonoverlapping seasons, using daily data in each case. Relationships between daily precipitation and El Niño–Southern Oscillation (ENSO) phase are also considered. It is shown that the CFS reanalysis represents a clear improvement over the earlier reanalysis products, though significant biases remain. Comparisons of the error patterns in the reanalysis products provide a suitable basis for confident conversion of the Climate Prediction Center (CPC) operational monitoring and prediction products to the new generation of analyses based on CFS.

An intercomparison of the statistics of daily precipitation within seasonal climate over the conterminous United States is carried out using gridded station data and output from the NCEP Climate Forecast System (CFS). Differences in the occurrence of daily precipitation between the observations and a set of CFS reforecasts are examined as a function of forecast lead time for 1982–2005. Difference patterns show considerable evolution depending on season and lead time, with positive biases in CFS at most locations and leads except along the southern tier of states during the spring and summer months. An examination of differences in daily precipitation statistics by ENSO phase and in the frequencies of wet and dry spells is also conducted using a longer period of gridded daily station data (1948–2006) and a pair of 100-yr CFS coupled simulations. These comparisons expose additional details of the regional and seasonal dependence of the bias in the CFS simulations and reforecasts over the conterminous United States. The analysis motivates additional synoptic studies aimed at improving the linkage between daily precipitation and related circulation features in CFS. Prospects for using this information to develop more reliable ensemble-based probabilistic forecasts in real time at leads of 2–4 weeks (e.g., risks of heavy rain events) are also considered.

A gauge-only precipitation data quality control and analysis system has been developed for monitoring precipitation at NOAA’s Climate Prediction Center (CPC). Over the past 10 yr the system has been used to develop and deliver many different precipitation products over the United States, Mexico, and Central and South America. Here the authors describe how the system has been applied to develop improved gridded daily precipitation analyses over Brazil. Consistent with previous studies, comparisons between the the gridded analyses and station observations reveal fewer dry days, a greater number of low precipitation days, and fewer extreme precipitation events in the gridded analyses. Even though the gridded analysis system reduces the number of dry days and increases the number of wet days, there is still a good correlation between time series of the gridpoint precipitation values and observations. Retrospective analyses are important for computing basic statistics such as mean daily/monthly rainfall, extremes, and probabilities of wet and dry days. The CPC gridded precipitation analyses can be used in hydrologic and climate variability studies dealing with large spatial-scale anomaly patterns, such as those related to ENSO. The analyses can also be used as a benchmark for evaluating model simulations, serve as a basis for real-time monitoring, and provide statistics on the occurrence of large-scale heavy rainfall events and dry periods.

The circulation features associated with intense precipitation events over the La Plata Basin (LPB) during the austral summers of 2001/02 and 2002/03 are investigated using the Eta Model runs generated at the University of Maryland. Based on the main mode of variability over LPB, two regions were selected: (i) the region of Brazil that is at the core of the South American summer monsoon system (SAMS) and (ii) the central region of LPB in southeastern South America (SESA). First, a comparison between the 24-h total precipitation in the Eta Model and the 24-h observed precipitation was made. Results show that the Eta Model captures well the temporal variability of precipitation events in both regions, although a positive bias is noticed over SAMS. Likewise, the model reproduces the distribution of precipitation rate over SESA, but not over SAMS. Nevertheless, the distribution of the moisture flux convergence intensity, which represents the dynamical forcing, is closer in shape to the observed precipitation distribution, suggesting that the model can be a useful tool in identifying the forcing for heavy precipitation events over both regions. Composites of atmospheric and surface variables were constructed for intense precipitation events during austral summer over both regions. Intense rainfall over the central La Plata Basin (SESA) is linked to an amplified upper-tropospheric midlatitude wave pattern in which rainfall occurs just east of an enhanced cyclonic circulation. Accompanying this circulation pattern, an enhanced low-level jet (LLJ) transports warm, moist air from the Amazon toward the region, contributing to an increase in the thermal contrast over SESA. The combined patterns of thermal and dynamical variables suggest that large-scale systems, like frontal systems, are important in producing intense rainfall events. The SAMS region events have a similar upper-level structure as in SESA, but they are longer lived. In this case, the moisture fluxes are determined by an eastward shift of the LLJ, but also directly from the Amazon Basin to the north. As expected, precipitation events produce large increases of simulated runoff. The largest impact is on the SESA region, affecting the streamflow of the Paraná, Paraguay, and Uruguay, the three main rivers of the LPB.

This chapter concerns the validation of high resolution (mostly 0.25°, daily and three-hourly) precipitation products over the United States. A synthesis of relevant studies is followed by comparisons of high resolution estimates based on satellites and models, with in situ ground validation data over the US. All the comparisons use multiple satellite estimates as well as model data (from the NCEP GFS). First, daily results are shown from the ongoing, web-based, real-time International Precipitation Working Group validation activity over the US. Next, validation data from 15 sub-daily gauges over Kansas and Oklahoma are used to assess the performance of three-hourly precipitation estimates, with attention to the distribution of precipitation. Finally, results from the comparison of several products against data collected from the North American Monsoon Experiment are given. Results show that existing high resolution products have great skill over many areas of the US, even at the three-hourly time-scale. Significant issues still exist over orography and results are seasonally dependent.

[1] Three objective techniques used to obtain gauge-based daily precipitation analyses over global land areas are assessed. The objective techniques include the inverse-distance weighting algorithms of Cressman (1959) and Shepard (1968), and the optimal interpolation (OI) method of Gandin (1965). Intercomparisons and cross-validation tests are conducted to examine their performance over various parts of the globe where station network densities are different. The gauge data used in the examinations are quality controlled daily precipitation reports from roughly 16,000 stations over the global land areas that have been collected by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). Data sources include daily summary files from the Global Telecommunication System (GTS), and the CPC unified daily gauge data sets over the contiguous United States (CONUS), Mexico, and South America. All three objective techniques are capable of generating useful daily precipitation analyses with biases of generally less than 1% over most parts of the global land areas. The OI method consistently performs the best among the three techniques for almost all situations (regions, seasons, and network densities). The Shepard scheme compares reasonably well with the OI, while the Cressman method tends to generate smooth precipitation fields with wider raining areas relative to the station observations. The quality of the gauge-based analyses degrades as the network of station observations becomes sparser, although the OI technique exhibits relatively stable performance statistics over regions covered by fewer gauges.