CPC) Merged Analysis Of Precipitation Research Articles

Increase in the pre‐monsoon rainfall over the Indian summer monsoon region

AbstractExamination of the Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) rainfall datasets, both available for the past 31 years (1979–2009), suggests that rainfall has increased considerably over the pre‐monsoon rainfall belts of the Bay of Bengal (BoB) and Southeast Arabian Sea (SEA) during May. The rainfall rate has increased by 83.9% (94.5%) over SEA and 54.6% (19.6%) over BoB in the GPCP (CMAP) dataset during the study period. During the study period, the atmospheric temperature has increased over north/northwestern parts of the Indian summer monsoon region in May, which has possibly caused more rain by enhancing the meridional pressure gradient. Copyright © 2010 Royal Meteorological Society

Climate Adjustments over Africa Accompanying the Indian Monsoon Onset

Abstract Rainfall and circulation changes accompanying the Indian monsoon onset are examined, focusing on the African continent and neighboring areas. The Indian Meteorological Department official monsoon onset dates over Kerala (MOK; on average on 1 June) are used. Composites are formed at a pentad (5 days) time scale to compare pre- and postonset conditions. Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) data for 1979–2007 indicate that a substantial rainfall decrease over several parts of Africa is associated with MOK. Significant rainfall anomalies, after removal of the mean seasonal cycle, are found in eastern Africa and the nearby western Indian Ocean. Indian monsoon onset dates over the period 1958–2001 are correlated at 0.55 with the cessation dates of the March–May rainy season (the long rains) averaged over Kenya and northern Tanzania. The rainy season cessation leads the onset by 12 days, on average. An early cessation of the March–May rains tends to precede an early onset over India. Over East Africa, the rainfall decrease is associated with a strengthening of the southerly winds (Somali jet) shortly before MOK, enhancing wind divergence and wind shear. A weaker rainfall signal is noted over western Africa and the Gulf of Guinea. MOK coincides with a pause in the progression of the West African monsoon. The pause is associated with anomalous descent over the Sahel, culminating two to three pentads after MOK. Composite maps further indicate that MOK is followed over much of the African continent by a sea level pressure rise and, between India and North Africa, a westward propagation of easterly wind and positive geopotential height anomalies. Many of these signals are associated with Madden–Julian oscillations, but independent features, suggesting Rossby wave propagation over North Africa, are also found to connect MOK and West Africa. Overall, these results are indicative of a large-scale adjustment of the atmospheric dynamics across both eastern and western Africa in conjunction with the monsoon onset over India.

A Joint Estimate of the Precipitation Climate Signal in Europe Using Eight Regional Models and Five Observational Datasets

Abstract This paper presents an analysis of the precipitation climate signal in Europe emerging from a simulation of heterogeneous regional climate models (RCMs) using five observational datasets as the reference for present day climate conditions. Current climate simulations, as well as those from the A2 family of scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES-A2), from eight RCMs involved in the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE) project have been cross-compared with data from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP), the Global Precipitation Climatology Centre (GPCC), the Climate Prediction Center (CPC), and the CPC Merged Analysis of Precipitation (CMAP) databases for Europe. The RCMs used are HIRHAM, the Climate High Resolution Model (CHRM), the Rossby Centre Atmosphere–Ocean (RCAO) model, the GKSS Climate Version of the Local Model (CLM), the Hadley Center RCM (HadRM3H), the Atmospheric Hydrostatic Regional Model (REMO), the Prognostic Model at the Mesoscale (PROMES), and the regional coupled ocean–atmosphere–ice model (RACMO). The comparison shows that the climate signal has to be interpreted depending on the reference data used. Although each validation dataset has its own relative merits and shortcomings, it is known that all of the datasets present variable uncertainties and error sources, which impedes consideration of a single dataset as the only valid representation of actual precipitation. Hence, it is suggested that a robust joint estimate of changes in future precipitation might include the uncertainties of both the RCMs and those of the observational datasets. After accounting for the difference between observed and simulated precipitation in the present climate, the analysis of such joint estimates reveals significant agreement in the climate signal for most of Europe. This lends confidence to the idea that the RCMs are able to correctly simulate future changes in precipitation.

A Monsoon-Like Southwest Australian Circulation and Its Relation with Rainfall in Southwest Western Australia

Abstract Using the NCEP–NCAR reanalysis, the 40-yr ECMWF Re-Analysis (ERA-40), and precipitation data from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Australian Bureau of Meteorology, the variability and circulation features influencing southwest Western Australia (SWWA) winter rainfall are investigated. It is found that the climate of southwest Australia bears a strong seasonality in the annual cycle and exhibits a monsoon-like atmospheric circulation, which is called the southwest Australian circulation (SWAC) because of its several distinct features characterizing a monsoonal circulation: the seasonal reversal of winds, alternate wet and dry seasons, and an evident land–sea thermal contrast. The seasonal march of the SWAC in extended winter (May–October) is demonstrated by pentad data. An index based on the dynamics’ normalized seasonality was introduced to describe the behavior and variation of the winter SWAC. It is found that the winter rainfall over SWWA has a significant positive correlation with the SWAC index in both early (May–July) and late (August–October) winter. In weaker winter SWAC years, there is an anticyclonic anomaly over the southern Indian Ocean resulting in weaker westerlies and northerlies, which are not favorable for more rainfall over SWWA, and the opposite combination is true in the stronger winter SWAC years. The SWAC explains not only a large portion of the interannual variability of SWWA rainfall in both early and late winter but also the long-term drying trend over SWWA in early winter. The well-coupled SWAC–SWWA rainfall relationship seems to be largely independent of the well-known effects of large-scale atmospheric circulations such as the southern annular mode (SAM), El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), and ENSO Modoki (EM). The result offers qualified support for the argument that the monsoon-like circulation may contribute to the rainfall decline in early winter over SWWA. The external forcing of the SWAC is also explored in this study.

Low‐frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets

Evidence is presented of a reduction in relative humidity over low‐latitude and midlatitude land areas over a period of about 10 years leading up to 2008, based on monthly anomalies in surface air temperature and humidity from comprehensive European Centre for Medium‐Range Weather Forecasts reanalyses (ERA‐40 and ERA‐Interim) and from Climatic Research Unit and Hadley Centre analyses of monthly station temperature data (CRUTEM3) and synoptic humidity observations (HadCRUH). The data sets agree well for both temperature and humidity variations for periods and places of overlap, although the average warming over land is larger for the fully sampled ERA data than for the spatially and temporally incomplete CRUTEM3 data. Near‐surface specific humidity varies similarly over land and sea, suggesting that the recent reduction in relative humidity over land may be due to limited moisture supply from the oceans, where evaporation has been limited by sea surface temperatures that have not risen in concert with temperatures over land. Continental precipitation from the reanalyses is compared with a new gauge‐based Global Precipitation Climatology Centre (GPCC) data set, with the combined gauge and satellite products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC), Merged Analysis of Precipitation (CMAP), and with CPC's independent gauge analysis of precipitation over land (PREC/L). The reanalyses agree best with the new GPCC and latest GPCP data sets, with ERA‐Interim significantly better than ERA‐40 at capturing monthly variability. Shifts over time in the differences among the precipitation data sets make it difficult to assess their longer‐term variations and any link with longer‐term variations in humidity.

Climate simulations with a new air‐sea turbulent flux parameterization in the National Center for Atmospheric Research Community Atmosphere Model (CAM3)

This study examines climate simulations with the National Center for Atmospheric Research Community Atmosphere Model version 3 (NCAR CAM3) using a new air‐sea turbulent flux parameterization scheme. The current air‐sea turbulent flux scheme in CAM3 consists of three basic bulk flux equations that are solved simultaneously by an iterative computational technique. We recently developed a new turbulent flux parameterization scheme where the Obukhov stability length is parameterized directly by using a bulk Richardson number, an aerodynamic roughness length, and a heat roughness length. Its advantages are that it (1) avoids the iterative process and thus increases the computational efficiency, (2) takes account of the difference between z0m and z0h and allows large z0m/z0h, and (3) preserves the accuracy of iteration. An offline test using Tropical Ocean–Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment (TOGA COARE) data shows that the original scheme overestimates the surface fluxes under very weak winds but the new scheme gives better results. Under identical initial and boundary conditions, the original CAM3 and CAM3 coupled with the new turbulent flux scheme are used to simulate the global distribution of air‐sea surface turbulent fluxes, and precipitation. Comparisons of model outputs against the European Remote Sensing Satellites (ERS), the Objectively Analyzed air‐sea Fluxes (OAFlux), and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) show that: (1) the new scheme produces more realistic surface wind stress in the North Pacific and North Atlantic trade wind belts and wintertime extratropical storm track regions; (2) the latent heat flux in the Northern Hemisphere trade wind zones shows modest improvement in the new scheme, and the latent heat flux bias in the western boundary current region of the Gulf Stream is reduced; and (3) the simulated precipitation in the new scheme is closer to observation in the Asian monsoon region.

Comparison of Precipitation Datasets over the Tropical South American and African Continents

Abstract Six rainfall datasets are compared over the Amazon basin, Northeast Brazil, and the Congo basin. These datasets include three gauge-only precipitation products from the Climate Prediction Center (CPC), Global Precipitation Climatology Center (GPCC), and Brazilian Weather Forecast and Climate Studies Center (CLMNLS), and three combined gauge and satellite precipitation datasets from the CPC Merged Analysis of Precipitation (CMAP), Global Precipitation Climatology Project (GPCP), and Tropical Rainfall Measuring Mission (TRMM) product. The pattern of the annual precipitation is consistently represented by these data, despite the differences in methods and periods of averaging. Quantitatively, the differences in annual precipitation among these datasets are 5% more than the Amazon domain (0°–15°S, 50°–70°W), 22% more than Northeast Brazil (5°–10°S, 35°–45°W), and 11% more than the Congo domain (5°N–10°S, 15°–30°E). Over the Amazon domain the rainfall variation is well correlated between CPC, TRMM, GPCP, and GPCC (r 2 > 0.9) except for the northwestern Amazon, whereas CMAP and CLMNLS were different from these four datasets. Over the Congo basin, the coefficient of determination between these rainfall datasets is generally below 0.7. The empirical orthogonal functions analysis suggests large discrepancies in interannual and decadal variations of rainfall among these datasets, especially for the Congo basin and for the South American region after 1998. In general, CMAP, GPCC, TRMM, and GPCP significantly agree over the tropical areas in South America.

Tropical Atlantic Variability Modes (1979–2002). Part I: Time-Evolving SST Modes Related to West African Rainfall

AbstractThis work presents a description of the 1979–2002 tropical Atlantic (TA) SST variability modes coupled to the anomalous West African (WA) rainfall during the monsoon season. The time-evolving SST patterns, with an impact on WA rainfall variability, are analyzed using a new methodology based on maximum covariance analysis. The enhanced Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, which includes measures over the ocean, gives a complete picture of the interannual WA rainfall patterns for the Sahel dry period. The leading TA SST pattern, related to the Atlantic El Niño, is coupled to anomalous precipitation over the coast of the Gulf of Guinea, which corresponds to the second WA rainfall principal component. The thermodynamics and dynamics involved in the generation, development, and damping of this mode are studied and compared with previous works. The SST mode starts at the Angola/Benguela region and is caused by alongshore wind anomalies. It then propagates westward via Rossby waves and damps because of latent heat flux anomalies and Kelvin wave eastward propagation from an off-equatorial forcing. The second SST mode includes the Mediterranean and the Atlantic Ocean, showing how the Mediterranean SST anomalies are those that are directly associated with the Sahelian rainfall. The global signature of the TA SST patterns is analyzed, adding new insights about the Pacific–Atlantic link in relation to WA rainfall during this period. Also, this global picture suggests that the Mediterranean SST anomalies are a fingerprint of large-scale forcing.This work updates the results given by other authors, whose studies are based on different datasets dating back to the 1950s, including both the wet and the dry Sahel periods.

Tropical Atlantic Variability Modes (1979–2002). Part II: Time-Evolving Atmospheric Circulation Related to SST-Forced Tropical Convection

Abstract The ways in which deep convection over the tropical Atlantic affects the midlatitude climate variability through meridional circulation, planetary wave teleconnection, and wave–mean flow interaction is examined for the 1979–2002 period, by following the North Atlantic anomalous rainfall evolution from summer to late winter. In this way, the first two covariability modes between anomalous summer tropical Atlantic sea surface temperature (SST) and anomalous summer–late-winter precipitation over the North Atlantic basin are analyzed using the same methodology of extended maximum covariance analysis developed for Part I. This work updates the results given by other authors, whose studies are based on different datasets dating back to the 1950s. To this end, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, which includes measures over the ocean, is used to give a complete picture of the interannual rainfall patterns for the last decades. The first mode, which accounts for more than 40% of the squared covariance fraction (SCF), involves SST anomalies related to the equatorial mode or Atlantic Niño. Its atmospheric response shows variations of the Atlantic Hadley and Ferrel circulations, reinforcing the direct and indirect circulation cells, respectively, displacements of the Atlantic Walker circulation, and the excitation of Rossby waves, which are trapped in the North African–Asian jet. The second mode, which accounts for 15% of the SCF, is associated with the summer horseshoe and winter tripole SST patterns. The related atmospheric circulation anomalies include direct thermal forcing (altering the local Hadley cell), perturbations in the ITCZ, and wavelike responses from the Caribbean region. The method used in this work highlights the seasonal dependence of the modes, in contrast to previous work that neglects to take into account the month-to-month evolution of these modes. The results add new and valuable information to the understanding of these modes from the important period back to the 1980s.

Differing Estimates of Observed Bangladesh Summer Rainfall

Abstract The differences in boreal summer (June–August) monthly-mean rainfall estimates over the Indian Ocean region in five research-quality products are examined for the period 1979–2003. Two products derived from the merged satellite and surface observations are considered: the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Global Precipitation Climatology Project (GPCP). In addition, three products derived solely from rain gauge observations are considered: the Chen et al. product; the Indian Meteorological Department (IMD) product; and a new, objectively analyzed product based on the Climate Anomaly Monitoring System (CAMS) dataset. Significant discrepancies have been found between the different products across the entire Indian Ocean region, with the greatest disagreement over Burma and neighboring Bangladesh. These differences appear to be primarily due to the absence of reported rain gauge data for Burma and differences in the algorithms used to merge the satellite microwave emission and scattering data in coastal regions. Representations of rainfall across much of the eastern Indian Ocean region would likely be improved by the identification and inclusion of reporting stations from Burma and a refinement of the techniques used for merging microwave data. The differences among the five products are sufficient to affect both quantitative and qualitative conclusions drawn about rainfall, particularly over Bangladesh and Burma. Consequently, the results of precipitation studies in this region will depend, in some cases, on the choice of the data product, including such basic questions as to whether a given summer was wet or dry. Of particular note is that the apparent relationship between rainfall and ENSO can depend on the choice of the data product.

Northern Annular Mode Effects on the Land Surface Phenologies of Northern Eurasia

Abstract Land surface phenology (LSP) is the spatiotemporal development of the vegetated land surface as revealed by synoptic sensors. Modeling LSP across northern Eurasia reveals the magnitude, significance, and spatial pattern of the influence of the northern annular mode. Here the authors fit simple LSP models to two normalized difference vegetation index (NDVI) datasets and calculate the Spearman rank correlations to link the start of the observed growing season (SOS) and the timing of the peak NDVI with the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) indices. The relationships between the northern annular mode and weather station data, accumulated precipitation derived from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, accumulated growing degree-days (AGDDs) derived from the NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) reanalysis, and the number of snow days from the National Snow and Ice Data Center are investigated. The analyses confirm strong relationships between the temporal behavior of temperature and precipitation and large-scale climatic variability across Eurasia. The authors find widespread influence of the northern annular mode (NAM) on the land surface phenologies across northern Eurasia affecting 200–300 Mha. The tundra ecoregions were especially impacted with significant results for about a quarter of the biome. The influence of the AO was also extensive (>130 Mha) for the boreal forests. The AO appears to affect the Asian part of northern Eurasia more strongly than the NAO, especially for the NDVI peak position as a function of AGDD. Significant responses of vegetation timing to NAO and AO in northeastern Russia have not been as well documented as the seasonal advancement in Europe. The two Advanced Very High Resolution Radiometer NDVI datasets yield fields of LSP model parameter estimates that are more similar in dates of peak position than in dates for SOS and more similar for AO than for NAO. As a result, the authors conclude that peak position appears to be a more robust characteristic of land surface phenology than SOS to link vegetation dynamics to variability and change in regional and global climates.

Spatial patterns of Tropospheric Biennial Oscillation and its numerical simulation

In order to investigate the spatial patterns of the Tropospheric Biennial Oscillation (TBO) on the global scale, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) monthly averaged precipitation and the Climate Diagnostics Center (CDC) monthly outgoing long-wave radiation (OLR) and SST are used in conjunction with TBO bandpass-filtering. The results indicate active biennial variability in the tropical eastern-central Pacific regions. It is evident that observations reflect the biennial component of the ENSO rather than the TBO itself. Since some studies have pointed out that the TBO is a broad-scale phenomenon differing from the ENSO, to investigate the pure TBO the ENSO signal must be excluded. The Scale Interaction Experiment-FRCGC (SINTEX-F) coupled general circulation model (CGCM) developed at Japan Frontier Research Center for Global Change (FRCGC) can capture both the ENSO and the biennial signals. Air-sea interactions in the tropical eastern-central Pacific are decoupled to eliminate the effects of ENSO in a experiment by SINTEX-F and the results show that biennial variability still exists even without ENSO. It seems to mean that the TBO and ENSO are independent from each other. Furthermore, the model results indicate that the two key regions are southwest Sumatra and the tropical western Pacific for the TBO cycle.

Global summer monsoon rainy seasons

AbstractA concise and objective definition of monsoon rainy season characteristics is proposed for worldwide monsoon regions. The result highlights six major summer monsoon rainy season domains and the mean dates of the local onset, peak and withdrawal phases of the summer monsoon rainy season. The onset phases occur progressively later poleward in the continental domains but primarily eastward in the oceanic monsoon regions. The rainy season retreats equatorward over the continental and oceanic monsoon regions. The length of the rainy season decreases poleward and shorter rainy season can also be found over the outskirts of warm water. Some exceptions exist in terms of the characteristics of rainy season, e.g. the westward advance of rainy season over North Africa and an apparently prolonged rainy season in the Korean peninsula. The results here are basically compatible with those obtained in previous studies on regional monsoons.A definition of the seasonal wind overturning is proposed. Combining rainfall and winds, we stratify the global monsoon into strong and weak categories. The strong monsoons are typically in the regions with both concentration of summer rainfall and annual reversal of low‐level winds, while the weak monsoon features only a contrasting wet–dry season. Seemingly, some mid‐latitude regions with wind reversals are not monsoonal because of the reversals being opposite to the monsoon overturning and the rainfall patterns being more or less Mediterranean.The comparison between the monsoon domains derived from Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the 40‐year European Centre for Medium‐Range Weather Forecasts Re‐Analysis (ERA‐40), the Japanese 25‐year Reanalysis (JRA‐25) and National Centers for Environmental Prediction (NCEP) datasets show good capabilities of the reanalyses in demarcation of the major monsoon rainy season domains in the tropics and subtropics. But the reanalyses are less realistic in the mid‐latitudes of Eurasia and North America. The result here provides the simple yet objective definitions of monsoon domain, onset, peak and withdrawal which are useful for validation of GCMs. Copyright © 2008 Royal Meteorological Society

Annual variations in water storage and precipitation in the Amazon Basin

We combine satellite gravity data from the gravity recovery and climate experiment (GRACE) and precipitation measurements from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center’s (CPC) Merged Analysis of Precipitation (CMAP) and the Tropical Rainfall Measuring Mission (TRMM), over the period from mid-2002 to mid-2006, to investigate the relative importance of sink (runoff and evaporation) and source (precipitation) terms in the hydrological balance of the Amazon Basin. When linear and quadratic terms are removed, the time-series of land water storage variations estimated from GRACE exhibits a dominant annual signal of 250 mm peak-to-peak, which is equivalent to a water volume change of ~1,800 km3. A comparison of this trend with accumulated (i.e., integrated) precipitation shows excellent agreement and no evidence of basin saturation. The agreement indicates that the net runoff and evaporation contributes significantly less than precipitation to the annual hydrological mass balance. Indeed, raw residuals between the de-trended water storage and precipitation anomalies range from ±40 mm. This range is consistent with stream-flow measurements from the region, although the latter are characterized by a stronger annual signal than our residuals, suggesting that runoff and evaporation may act to partially cancel each other.

Assessing a Satellite-Era Perspective of the Global Water Cycle

Abstract The capability of a global data compilation, largely satellite based, is assessed to depict the global atmospheric water cycle’s mean state and variability. Monthly global precipitation estimates from the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) span from 1979 to 1999. Monthly global Special Sensor Microwave Imager (SSM/I)-based bulk aerodynamic ocean evaporation estimates span from June 1987 to December 1999. Global terrestrial evapotranspiration rates are estimated over a multidecade period (1975–99) using a global land model simulation forced by bias-corrected reanalysis data. Monthly total precipitable water (TPW) from the NASA Global Water Vapor Project (NVAP) spans from 1988 to 1999. The averaged annual global precipitation (P) and evaporation (E) estimates are out of balance by 5% or 24 000 (metric) gigatons (Gton) of water, which exceeds the uncertainty of global mean annual precipitation (∼±1%). For any given year, the annual flux imbalance can be on the order of 10% (48 000 Gton of water). However, observed global TPW interannual variations suggest a water flux imbalance on the order of 0.01% (48 Gton of water)—a finding consistent with a general circulation model (GCM) simulation. Variations in observationally based global P and E rates show weak monthly and interannual consistency, and depending on the choice of ocean evaporation data, the mean annual cycle of global E − P can be up to 5 times larger to that of TPW. The global ocean annual evaporation rates have as much as a ∼1% yr−1 increase during the period analyzed (1988–99), which is consistent in sign with most transient CO2 GCM simulations, but at least an order of magnitude larger. The ocean evaporation trends are driven by trends in SSM/I-retrieved near-surface atmospheric humidity and wind speed, and the largest year-to-year changes are coincident with transitions in the SSM/I fleet. In light of (potential) global water cycle changes in GCM projections, the ability to consistently detect or verify these changes in nature rests upon one or more of the following: quantification of global evaporation uncertainty, at least a twofold improvement in consistency between the observationally based global precipitation and evaporation variations, a two order of magnitude rectification between annual variations of E − P and precipitable water as well as substantial improvements in the consistency of their seasonal cycles, a critical reevaluation of intersatellite calibration for the relevant geophysical quantities used for ocean evaporation estimates, and the continuation of a dedicated calibration in this regard for future satellite transitions.

A maximum entropy analysis of global monthly series of rainfall from merged satellite data

This Letter presents the results of analysing a global, satellite‐based monthly precipitation database on a 2.5° latitude‐longitude grid for the 22‐year period from 1979 to 2001 using a direct maximum entropy spectral analysis method. The NOAA Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) database is used to calculate the rainfall cycles for ∼10 000 time series covering the whole Earth. It is shown that several cycles other than the annual or seasonal cycles affect the rainfall distribution of many areas, in particular western Europe.

Revisiting the Possible Links between the Quasi-Biennial Oscillation and the Indian Summer Monsoon Using NCEP R-2 and CMAP Fields

AbstractIn the past the stratospheric quasi-biennial oscillation (QBO) has sometimes been proposed to explain the tendency for the Indian summer monsoon (ISM) to alternate between strong and weak years. In this study, NCEP Reanalysis-2 (R-2) and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) fields are statistically analyzed to assess the relationship between equatorial zonal winds in the stratosphere and ISM. In a first step, it is shown that zonal winds at 15 hPa during the preceding winter (January–February) are the best stratospheric predictor of the summer rainfall over the Indian subcontinent as a whole. This relationship mainly holds for August and September, or the late ISM. Surprisingly, the QBO pattern is not significantly associated with the rainfall variability during June–July or the early ISM. CMAP and NCEP R-2 fields corroborate these findings and show that westerly QBO years are associated with a deepening of the monsoon trough over the Gangetic plains and decreased convective activity in the eastern equatorial Indian region. However, further statistical analysis shows that the QBO–ISM link is complex since a westerly QBO phase at 15 hPa in boreal winter leads to a weaker monsoon surface circulation with, in particular, a weakening of the Somali jet at the beginning of the monsoon, but a much stronger circulation in September. At that time, the Tibetan high is reinforced, the tropical easterly jet at 200 hPa is stronger over India, and the local reversed Hadley circulation is also strengthened north of the equator. The mechanisms by which the QBO may affect ISM have been explored through, in particular, correlations between stratospheric winds and tropopause temperature and pressure fields. The results provide support for an out-of-phase behavior of convective activity between the Indian subcontinent and the equatorial Indian Ocean induced by the QBO phase, especially during the late ISM. During a westerly QBO phase, convective activity is, in September, enhanced over India, which brings higher precipitation, compared to the east phase. This work also suggests that the winter QBO at 15 hPa could have some skill in foreshadowing the late ISM.

Sudan‐Sahel rainfall onset: Definition of an objective index, types of years, and experimental hindcasts

Using rainfall estimates from the 5‐day version of CPC Merged Analysis of Precipitation (CMAP) and Global Precipitation Climatology Project data along with multiscale spatial key descriptors of atmospheric dynamics from National Center for Environmental Prediction/Department of Energy reanalysis 2 (NCEP/DOE), we first define a West African monsoon onset index to determine its successive dates of occurrence over the period 1979–2004 (28–29 June in mean with a standard deviation of 8.5 days). Then we focus on the three main types of time evolutions of that index at the moment of the monsoon onset in terms of precipitation, pressure, temperature, and winds at different levels to detect the most robust associated signals and select on the mid‐May, mid‐June period different sets of potential predictors for onset dates. Basically, late (early) onsets are preceded by more (less) rainfall southward to the equator by the end of May, then by a clear decrease (increase) of the normal northward cross‐equatorial gradient in mid‐June. Finally, we present experimental cross‐validated hindcasts of the dates of onset always based on four predictors using both reanalyzed atmospheric data and observed rainfall estimates. Accurate forecasting schemes are obtained, especially with CMAP rainfall (time tendencies and cross‐equatorial gradients) over the Gulf of Guinea. In this context the hindcasted series are highly significant when compared to observations (75% of explained common variance with the sole rainfall predictors) and can reach 82% of variance when a zonal wind descriptor of regional scale is added. Basically, a late (early) onset is preceded by more (less) rainfall southward to the equator by the end of May, then by a clear decrease (increase) of the normal northward cross‐equatorial gradient by mid‐June.

A Climatological Monsoon Break in Rainfall over Indochina—A Singularity in the Seasonal March of the Asian Summer Monsoon

Abstract This study investigated the climatological pentad mean annual cycle of rainfall in Thailand and the associated atmospheric circulation fields. The data used included two different data of rainfall: rain gauge data for Thailand from the Thai Meteorological Department and satellite-derived rainfall data from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP). Climatological mean pentad values of rainfall taken over 50 yr clearly show a distinct climatological monsoon break (CMB) occurring over Thailand in late June. The occurrence of the CMB coincides with a drastic change of large-scale monsoon circulation in the seasonal march. The CMB is a significant singularity in the seasonal march of the Southeast Asia monsoon, which divides the rainy season into the early monsoon and the later monsoon over the Indochina Peninsula. A quasi-stationary ridge dynamically induced by the north–south-oriented mountain range in Indochina is likely to cause the CMB. The formation of the strong ridge over the mountain ranges of Indochina is preceded by a sudden enhancement (northward expansion) of the upstream monsoon westerlies along a latitudinal band between 15° and 20°N in late June. The CMB also has an impact downstream. The orographically induced stationary Rossby waves enhance the cyclonic circulation to the lee of Indochina, and over the South China Sea. The enhancement of cyclonic circulation may be responsible for the summer monsoon rains peaking in late June over the South China Sea and the western North Pacific, and in the baiu front.

Rainfall Estimation in the Sahel. Part II: Evaluation of Rain Gauge Networks in the CILSS Countries and Objective Intercomparison of Rainfall Products

Abstract This study investigates the accuracy of various precipitation products for the Sahel. A first set of products is made of three ground-based precipitation estimates elaborated regionally from the gauge data collected by Centre Regional Agrometeorologie–Hydrologie–Meteorologie (AGRHYMET). The second set is made of four global products elaborated by various international data centers. The comparison between these two sets covers the period of 1986–2000. The evaluation of the entire operational network of the Sahelian countries indicates that on average the monthly estimation error for the July–September period is around 12% at a spatial scale of 2.5° × 2.5°. The estimation error increases from south to north and remains below 10% for the area south of 15°N and west of 11°E (representing 42% of the region studied). In the southern Sahel (south of 15°N), the rain gauge density needs to be at least 10 gauges per 2.5° × 2.5° grid cell for a monthly error of less than 10%. In the northern Sahel, this density increases to more than 20 gauges because of the large intermittency of rainfall. In contrast, for other continental regions outside Africa, some authors have found that only five gauges per 2.5° × 2.5° grid cell are needed to give a monthly error of less than 10%. The global products considered in this comparison are the Climate Prediction Center (CPC) merged analysis of precipitation (CMAP), Global Precipitation Climatology Project (GPCP), Global Precipitation Climatology Center (GPCC), and Geostationary Operational Environmental Satellite (GOES) precipitation index (GPI). Several methods (scatterplots, distribution comparisons, root-mean-square error, bias, Nash index, significance test for the mean, variance, and distribution function, and the standard deviation approach for the kriging interval) are first used for the intercomparison. All of these methods lead to the same conclusion that CMAP is slightly the better product overall, followed by GPCC, GPCP, and GPI, with large errors for GPI. However, based on the root-mean-square error, it is found that the regional rainfall product obtained from the synoptic network is better than the four global products. Based on the error function developed in a companion paper, an approach is proposed to take into account the uncertainty resulting from the fact that the reference values are not the real ground truth. This method was applied to the most densely sampled region in the Sahel and led to a significant decrease of the raw evaluation errors. The reevaluated error is independent of the gauge references.