A state-of-the-art daily precipitation analysis for Brazil for the period 1961-present is used to examine the annual cycle and variability of daily precipitation over the country. Emphasis is placed on daily precipitation statistics (including frequency of occurrence, intensity and geographic distribution). The NCEP/NCAR Reanalysis is used to examine the large-scale circulation features associated with extreme precipitation events. A classification of El Niño-Southern Oscillation (ENSO) is used together with the daily precipitation analysis to diagnose relationships between ENSO phase and precipitation.
Accurate and complete estimates of precipitation are critical to a wide variety of problems ranging from understanding the water budget to improved monitoring and prediction of climate. Most areas of the globe are not adequately sampled, either by in situ or remote sensing. The Americas are covered by a relatively dense array of in situ raingauge data. The relatively good coverage allows us to focus on improving the quality of the analysis of precipitation on a range of space and time scales.
The Climate Prediction Center (CPC) has undertaken a comprehensive program to improve the analysis of gauge-based precipitation over the Americas on a range of space and time scales. The goal of this activity is to develop improved daily, monthly and seasonal gauge-only precipitation analysis products and applications in support of climate monitoring, climate prediction, and applied research. The approach has been incremental, by first focusing on the U.S. and then by expanding this effort to include the remainder of North, Central and South America. Several gridded daily analysis products are currently available:
Real-Time Daily Analyses Historical Reanalysis
United States (1996-present) United States (1948-1998+; daily)
Mexico (2001-present) United States (1948-present; hourly)
South America (2000-present) Mexico (1948-2000; daily)
Brazil (1961-1999; daily)
Canada (1961-1996; daily)
The overall goal of this effort is to couple real-time analyses for all of the Americas (12Z-12Z) to historical reanalyses for all of the Americas, so that current anomalies can be placed in the proper historical context. The real-time daily analysis for the United States and the historical daily reanalysis are documented in Higgins et al. (2000). The United States hourly precipitation reanalysis is documented in Higgins et al (1996). Improving the analysis of precipitation requires careful consideration of the quality of the input observations. The Climate Prediction Center routinely produces quality controlled gauge-only precipitation analyses for the U.S. as part of its effort to monitor current and past conditions and to provide improved climate forecasts for the U.S. The U.S. precipitation quality control (QC) system and analysis is discussed in detail in Higgins et al. (2000). To the extent possible similar QC procedures are used for all of our real-time and historical analyses (see section 2.2).
In this study we report on our activities over South America. Emphasis is placed on a historical daily reanalysis for Brazil. Daily precipitation statistics (including the frequency of wet days and the geographical distribution of precipitation extremes) are examined by month.
In addition, we use the daily analysis to examine relationships between ENSO and precipitation throughout the country.
The data source and details of the near-real-time and historical daily South American precipitation analyses are described in section 2. A climatology of South American precipitation is presented in section 3. Daily precipitation statistics (including frequency of wet days and daily precipitation extremes) are presented in section 4. The linkage between ENSO and daily precipitation is emphasized in section 5.
2.0 South American Precipitation Analyses
Historical daily precipitation data were obtained from the Brazilian National Agency for Electric Energy (ANEEL). These data were used to produce gridded daily analyses with a latitude-longitude resolution of 1 degree for the period 1960-1997. A daily climatology was then computed for the period 1979-1995, which corresponds to the period having the greatest number of station reports.
Monthly precipitation totals, taken from the Climate Anomaly Monitoring System (Ropelewski et al., 1985) archive were used to supplement the ANEEL data in computing long-term mean monthly and seasonal precipitation totals for all of South America.
The real-time gridded daily precipitation analyses are computed in collaboration with the Brazilian Center for Weather Prediction and Climate Studies (CPTEC). CPTEC receives real-time precipitation data from regional rainfall networks and automated data collection platforms in Brazil, and from the Global Telecommunication System for the entire continent of South America.
2.2 Near-Real-Time daily analysis
The daily analyses are gridded at a horizontal resolution of (lat, lon)=(1°x1°) over the domain (110o W - 30o W, 60o S - 15o N) using a Cressman (1959) scheme with modifications (Glahn et al. 1985; Charba et al. 1992). The input data set for the near-real-time analysis is discussed in the previous subsection. The analysis on Day 1 is valid for the 24-hour window from 1200Z on day 0 to 1200Z on day 1; a typical station distribution and daily precipitation analysis are shown in Figs. 1a and 1b respectively. Currently the daily analysis is available within ~16 hrs of real time.
Several types of QC are currently applied to the real-time gauge data including a "duplicate station check" which eliminates duplicates and key punch errors from the raingauge reports and a "buddy check" to eliminate error reports on extreme values. In the near future we will invoke a standard deviation check, which compares the daily raingauge data against a gridded daily climatology (this is done routinely for our daily analyses over the U.S.). Other types of QC that are routinely applied to the U.S. data, such as NEXRAD radar QC and satellite QC are not applied. See Higgins et al. (2000) for details of these QC procedures. All QC flags are inserted back into the gauge data archive for future reference.
The near-real-time precipitation analysis has been used to develop a number of additional products and applications. Precipitation products currently available at CPC include a daily precipitation analysis and associated station map (e.g. Fig. 1), monthly totals (accumulations and anomalies), and 30 day animations of 7 day precipitation accumulations. All of these products are disseminated on a daily basis via the CPC Web Site (http://www.cpc.ncep.noaa.gov/products/precip/ realtime/SA/index.html). These products are undergoing continuous improvement. The near-real-time analyses are also used by several other CPC projects, including "Monitoring Weather & Climate" (http://www.cpc.ncep.noaa.gov/products/precip/CWlink/index.html)
2.3 Historical daily reanalysis
Hydrologic anomalies cross monthly boundaries and occur at sub-monthly time scales. Thus, it is necessary to have a near-real-time daily precipitation analysis that is "well-connected" to a historical precipitation analysis, in order to place current anomalies in the proper historical context. Towards this end, we are developing a multi-year daily precipitation analysis for South America using the available gauge data. At the present time we have a multi-year (1960-present) daily precipitation analysis for Brazil. This analysis has been used to generate a daily precipitation climatology (1979-1995) for Brazil that we will report on here. Because of the small sample size (17 years), the daily climatology is very noisy. Therefore we computed a smoothed daily climatology using 30-day-running-mean procedure. For the remaining countries in South America our daily precipitation data bases are under development, and not nearly as extensive as the one for Brazil. For that reason, in this study we use Climate Anomaly Monitoring System (CAMS) data, which is monthly, to fill in the climatology for countries outside of Brazil.
In the following subsections we present some statistics that illustrate the quality of the analysis product (for Brazil only) at various temporal scales. The analysis is compared to the existing climatology mentioned above.
The characteristics of the analysis scheme used for the precipitation analysis are identical to those in our operational near-real-time analysis (section 2.1). The daily analyses are gridded at a horizontal resolution of (lat, lon) = (1°x1°) over the domain 80oW - 30oW, 40oS - 10oN using a Cressman (1959) scheme with modifications (Glahn et al. 1985; Charba et al. 1992). The analysis on Day 1 is valid for the 24-hour window from 1200Z on day 0 to 1200Z on day 1.
The gridded daily precipitation data set is available from the Climate Prediction Center at the National Centers for Environmental Prediction. Information about data access and data format can be obtained by contacting the authors at
Climate Prediction Center
NOAA/NWS/NCEP
World Weather Building, Room 605
5200 Auth Road
Camp Springs, MD 20746
or through anonymous ftp at ftp://ftp.ncep.noaa.gov/pub/precip/wd52ws/brazil/.
The classification of El Niño and La Niña events used in this study is identical to that used by the Climate Prediction Center and found on their website:
http://www.cpc.ncep.noaa.gov/research_papers/ncep_cpc_atlas/8/ensoyrs.txt
The classification is based on the pattern and magnitude of SST anomalies in the tropical Pacific.
Composites keyed to El Niño (La Niña) episodes are based on the moderate and strong events, indicated as W+ and W (C+ and C) in the CPC classification, respectively.
3.0 South American Climatology
The mean (1979-1995) annual precipitation totals based on the daily precipitation analysis for Brazil and the monthly precipitation analysis for the remainder of South America is shown in Fig. 2. In an annual mean sense the wettest part of the continent is over northwestern Brazil, where annual precipitation amounts average in excess of 2450 mm. The driest areas of the continent are along the west coast and in southern Argentina. In several of the driest regions (e.g. southern Argentina) there is a limited amount of CAMS data, which may contribute to significant errors in the analysis in these regions. This situation will improve once our daily analyses are completed for these regions.
Figure 3 shows the annual cycle of mean (1979-1995) monthly precipitation over Brazil, the 925-hPa winds (vectors) and 200-hPa streamlines (dark lines). The center of maximum rainfall (above 300 mm month-1) gradually migrates from a position over western Brazil near 10°S during the southern hemisphere warm season (December-February) to just north of the equator during the southern hemispheric cold season (June -July); this is accompanied by the weakening of the upper level monsoon anticyclone over the region and by the shift of lower level winds carrying moisture from northeasterlies (from the deep tropics) to southeasterlies (from the mid-latitudes). The area of heaviest precipitation decreases substantially during the transition from warm to cold seasons while the area of light precipitation (<25 mm/month) over the Amazon Basin gradually expands starting in April. During the transition from cold to warm seasons the precipitation gradually reintensifies over western Brazil and the remainder of the Amazon Basin.
4.0 Daily statistics for Brazil
The pattern of mean annual frequency of measurable (> 1 mm day-1) daily precipitation in Brazil (Fig. 4) is similar in many respects to the pattern of mean annual precipitation amount (Fig. 2). The highest frequencies (greater than 85% of the days) occur in the northwest while the lowest frequencies (less than 25% of the days) occur in the east-central portion of the country.
An examination of the mean monthly frequency of measurable daily precipitation (> 1 mm day-1) in Brazil (Fig. 5) shows a considerable annual cycle in the frequency of wet days. This is particularly apparent in central Brazil, where frequencies exceed 80% of the days during the southern hemisphere summer, but drop to less than 25% of the days during the southern hemisphere winter, while little or no seasonality is observed over the southern areas of the country. The annual cycle is much weaker over northwestern Brazil, where frequencies exceed 75% throughout the year. Geographic patterns of the monthly frequency of daily precipitation ( > 10 mm day-1 and > 25 mm day-1 in Figs. 6 and 7, respectively) resemble those for the frequency of measurable daily precipitation (Fig. 5). However, peak frequencies in western Brazil drop to about 50% (10%) of the days in Fig. 6 (Fig. 7). The vast majority of wet days in northwestern Brazil have light precipitation throughout the annual cycle. However, a disproportionate fraction of wet days in southern Brazil have heavy precipitation.
Since the standard deviation of daily precipitation is affected by the underlying march of the annual cycle, the daily climatology based on 1979-1995 has been removed from the daily data prior to the analysis. The standard deviation of daily mean precipitation (Fig. 8) shows a very different pattern for the southern hemisphere rainy season (roughly November to April) as compared to the dry season (roughly May-October). During the rainy season the variability is large (the standard deviation exceeds 4 mm day-1) over much of the country. During the dry season the variability is greatly reduced, particularly during the heart of the southern hemisphere cold season when the standard deviation averages less than 1 mm day-1 over much of the east-central portion of the country. Interestingly, during the southern hemisphere cold season the variability is largest over southern Brazil, where mid-latitude fronts provide a focusing mechanism for heavy precipitation episodes.
Daily accumulations of precipitation were ranked (locally) for the period 1979-1995 (by month) and the heavy precipitation days were defined as those in the upper 10% of the daily distribution. For these calculations we used daily precipitation timeseries for wet days (a wet day is defined as the day when precipitation at a particular grid of interest is greater than 1 mm day-1). Geographical maps of the threshold precipitation amount for ranked daily precipitation at the 90th percentile (Fig. 9) illustrate the marked difference in the annual cycle of heavy precipitation events for different regions of the country. Heavy precipitation events over central Brazil are 20-30 times wetter during the rainy season than during the dry season. On the other hand, wet days at the 90th percentile over western, northern and southern Brazil have a much weaker annual cycle. Heavy precipitation events over western Brazil have roughly 2 times more precipitation during the southern hemisphere summer as during the southern hemisphere winter. Heavy precipitation events over southern Brazil are slightly wetter during southern hemisphere winter. The annual cycle of the percentage of total rainfall due to heavy precipitation days at and above the 90th percentile (Fig. 10) has its largest amplitude in areas where the annual cycle in threshold precipitation amount (Fig. 9) is smallest.
Fig. 11 shows the geographic map of the threshold precipitation amounts for ranked 3-day precipitation events at the 90th percentile. In some areas the 3-day accumulated rainfall amounts may exceed 60 mm, which can produce flooding. Products like this could be used in conjunction with local flash flood guidance numbers to determine whether a particular 3-day precipitation event forecast is likely to produce flooding.
5.0 Linkage between ENSO and precipitation in Brazil
A classification of La Niña and El Niño episodes devised by CPC is used to examine how ENSO is related to the daily precipitation in Brazil. Precipitation composites (Fig.12) are constructed for the differences between moderate/strong El Niño (warm) and La Niña (cold) episodes, with the remaining years being classified as ENSO-neutral. The composite patterns show significant variations from season to season. For instance, during the southern hemisphere warm season (JFM), the El Niño episodes feature enhanced precipitation in northwestern and southeastern Brazil and reduced rainfall in northeastern Brazil. During the southern hemisphere cold season (JAS), however, a large area in northern Brazil experiences anomalously dry conditions during El Niño episodes; this large area includes northwestern Brazil where the climatological maximum in precipitation in this season is found.
The above features are generally in agreement with results from previous studies (e.g. Kousky et al. 1984; Ropelewski and Halpert 1987; Aceituno 1988; Kousky and Ropelewski 1989; Kiladis and Diaz 1989; Marengo 1995; Grimm et al.. 1998). It should be noted, however, that detailed study of the relationship between ENSO and precipitation in Brazil is not the main focus of this paper. We present this initial result here as an additional way to evaluate the quality of this historical data set. At the present time, there are certain areas in which we currently lack sufficient data coverage (in space and time) which prohibit us from further study of the detailed structure of the relationship(Fig. 13). To construct a useful data set like this requires considerable effort with our international partners. This data set will be updated as new data sources become available.
This work was partially supported by the NOAA Office of Global Programs under the PACS/GAPP Project "Real-time Monitoring of the American Monsoons for PACS/GAPP" (W. Higgins, PI) and the GEWEX Americas Prediction Project (GAPP) Project "Improved US Precipitation QC System and Analysis" (W. Higgins, PI).
Aceituno, P., 1988: On the functioning of the Southern Oscillation in the South American sector.
Mon. Wea. Rev., 116, 505-525.
Cayan, D., K. Redmond, and L. Riddle, 1996: Accentuated ENSO effects on extreme hydrologic
events over the western United States. Preprints, Proc. 21st Annual Climate Diagnostics and
Prediction Workshop, Huntsville, AL, Amer. Meteor. Soc., 324-325.
Charba, J. P., A. W. Harrell III and A. C. Lackner III, 1992: A monthly precipitation amount
climatology derived from published atlas maps: Development of a digital data base. TDL
Office Note 92-7, NOAA, U.S. Department of Commerce, 20 pp.
Cressman, G. P., 1959: An operational objective analysis system. Mon. Wea. Rev., 87, 367-374.
Gandin, L. S., 1963: Objective analysis of meteorological fields. Gidrometeor. Isdat., Leningrad.
[Israel Program for Scientific Translations, Jerusalem, 1965, 242 pp.]
Gershunov, A., and T. Barnett, 1998: ENSO influence on intraseasonal extreme rainfall and
temperature frequencies in the contiguous United States: Observations and model results.
J. Climate, 7, 1575-1586.
Glahn, H. R., T. L. Chambers, W. S. Richardson, and H. P. Perrotti, 1985: Objective map
analysis for the local AFOS MOS Program. NOAA Technical Memorandum NWS TDL 75,
NOAA, U. S. Department of Commerce, 34 pp.
Grimm, A. M., S. E. T. Ferraz, and J. Gomes, 1998: Precipitation anomalies in southern Brazil
associated with El Niño and La Niña events. J. Climate, 11, 2863-2880.
Higgins, R. W., J. E. Janowiak and Y. Yao, 1996: A gridded hourly precipitation data base for the United States (1963-1993). NCEP/Climate Prediction Center ATLAS No. 1., 47 pp.
Higgins, R. W., W. Shi, E. Yarosh and R. Joyce , 2000: Improved United States Precipitation
Quality Control System and Analysis. NCEP/Climate Prediction Center Atlas No. 7, NOAA,
U. S. Department of Commerce (For an electronic version of this atlas, click here)
Kiladis, G. N., and H. F. Diaz, 1989: Global climatic anomalies associated with extremes in the
Southern Oscillation. J. Climate, 2, 1069-1090.
Kousky, V. E., M. T. Kayano, and I. F. A. Cavalcanti, 1984: A review of the Southern Oscillation:
Oceanic-atmospheric circulation changes and related rainfall anomalies. Tellus, 36A, 490-502.
-------------, and C. F. Ropelewski, 1989: Extremes in the Southern Oscillation and their relationship to precipitation anomalies with emphasis on the South American region. Revista Brasileira de Meteorologia, 4, 351-363.
Marengo, J. A., 1995: Interannual variability of deep convection over the tropical South American
sector as deduced from ISCCP C2 data. Int. J. Climatol., 15, 995-1010.
Ropelewski, C. F., J. E. Janowiak and M. S. Halpert, 1985: The analysis and display of real time surface climate data. Mon. Wea. Rev., 113, 1101-1106.
Ropelewski, C. F., and M. S. Halpert, 1987: Global and regional scale precipitation patterns
associated with the El Niño/ Southern Oscillation. Mon. Wea. Rev., 115, 1606-1626.
Figure 1. (a) Typical station distribution for daily reporting stations in South America. The data sources are described in section 2.1. (b) Daily precipitation analysis (Units: mm) based on 24-hr accumulations for the period from 1200Z March 28, 2001 - 1200Z March 29, 2001. The analysis is gridded at a horizontal resolution of (lat,lon)=(1°,1°).
Figure 2. The mean (1979-1995) annual precipitation totals (units: mm) based on the daily precipitation analysis for Brazil and the monthly precipitation analysis for the remainder of South America.
Figure 3. The annual cycle of mean (1979-1995) monthly precipitation (units: mm month-1) (shadded), 925-hPa winds (units: m s-1) (vectors) and 200-hPa streamlines (dark lines) over Brazil.
Figure 4. Mean (1979-1995) annual frequency of measurable daily precipitation (> 1 mm day-1) in Brazil, expressed as a percentage of the total number of days in a year.
Figure 5. Mean (1979-1995) monthly frequency of measurable daily precipitation (> 1 mm day-1) in Brazil, expressed as a percentage of the total number of days in a month.
Figure 6. Mean (1979-1995) monthly frequency of daily precipitation (> 10 mm day-1) in Brazil, expressed as a percentage of the total number of days in a month.
Figure 7. Mean (1979-1995) monthly frequency of daily precipitation (> 25 mm day-1) in Brazil, expressed as a percentage of the total number of days in a month.
Figure 8. Standard deviation of daily precipitation (1979-1995) (units: mm day-1) by month in Brazil.
Figure 9. Threshold precipitation amount (units: mm day-1) for ranked daily precipitation at the 90th percentile by month in Brazil. Results are based on daily data for the period 1979-1995.
Figure 10. Percentage of total rainfall due to heavy precipitation days at and above 90th percentile by month in Brazil. Results are based on daily data for the period 1979-1995.
Figure 11. Threshold precipitation amount (units: mm) for ranked 3-day precipitation events at the 90th percentile by month in Brazil. Results are based on daily data for the period 1979-1995.
Figure 12. Composites of precipitation differences (units: mm day-1) between ENSO warm (El Niño) episodes cold (La Niña) episodes for JFM, AMJ, JAS and OND seasons, 1970-1997. Based on our ENSO classification, we identified 4 cold and 4 warm episodes for the JFM season; 2 cold and 6 warm episodes for the AMJ season; 2 cold and 5 warm episodes for the JAS season and 4 cold and 7 warm episodes for the OND season.
Figure 13. Number of daily precipitation (non-missing)reports for Brazil