Center Merged Analysis Of Precipitation Research Articles

Climatology of the global summer monsoon rainy seasons: Revisited from a high-resolution satellite climate data record

Reliable information on the monsoon rainfall at finer spatiotemporal scales has always been crucial for applications in hydrometeorology, water resource management, disaster prevention, and assessment of numerical model outputs. Here, the spatial-temporal characteristics of the summer monsoon rainy seasons worldwide are revisited using a global, high-resolution, bias-corrected satellite rainfall climate data record. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides 0.25° rainfall estimates for the latitude band 60°S–60°N from 1983 to the near present. The global monsoon regimes are defined based on the annual rainfall range and the summer rainfall ratio. The onset, peak, and withdrawal of the rainy season are then determined using a concise yet pertinent rainfall parameter with universal objective criteria.Overall, six major summer monsoon regimes of the globe, the Asian Monsoon, Indonesian–Australian monsoon, North African monsoon, South African monsoon, North American and South American monsoon, are all reasonably represented by PERSIANN-CDR. The progression patterns of climatological onset, peak, and withdrawal phases of these monsoons are consistent with those reported by previous global and regional monsoon studies. Furthermore, compared with other coarser resolution satellite rainfall estimates such as the Climate Prediction Center Merged Analysis of Precipitation (CMAP), the present result is clearly in better agreement with that obtained from ground-based observations since it allows the determination of more detailed information associated with local-scale factors such as the sharp land-sea contrast, local surface heating, and topography effects. However, some “spots”, particularly over complex topography lacking ground truth validations, are revealed to have rainy season characteristics that differ substantially from those over the surrounding areas and have not been fully described by published literature. These distinct features need to be confirmed by further regional monsoon studies.

Magnitude Agreement, Occurrence Consistency, and Elevation Dependency of Satellite-Based Precipitation Products over the Tibetan Plateau

Satellite remote sensing is a practical technique to estimate global precipitation with adequate spatiotemporal resolution in ungauged regions. However, the performance of satellite-based precipitation products is variable and uncertain for the Tibetan Plateau (TP) because of its complex terrain and climate conditions. In this study, we evaluated the abilities of nine widely used satellite-based precipitation products over the Eastern Tibetan Plateau (ETP) and quantified precipitation dynamics over the entire TP. The evaluation was carried out from three aspects, i.e., magnitude agreement, occurrence consistency, and elevation dependency, from grid-cell to regional scales. The results show that the nine satellite-based products exhibited different agreement with gauge-based reference data with median correlation coefficients ranging from 0.15 to 0.95. Three products (climate hazards group infrared precipitation with stations (CHIRPS), multi-source weighted-ensemble precipitation (MSWEP), and tropical rainfall measuring mission multi-satellite precipitation analysis (TMPA)) generally presented the best performance with the reference data, even in complex terrain regions, given their root mean square errors (RMSE) of less than 25 mm/mon. The climate prediction center merged analysis of precipitation (CMAP) product has relatively coarse spatial resolution, but it also exhibited good performance with a bias of less than 20% in watershed scale. Two other products (precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system (PER-CCS) and climate prediction center morphing technique-raw (CMORPH-RAW)) overestimated precipitation with median RMSEs of 87 mm/mon and 45 mm/mon, respectively. All the precipitation products generally exhibited better agreement with the reference data for rainy season and lower-elevation regions. All of the products captured precipitation occurrence well, with hit event over 60%, and similar percentages of missed and false event. According to the evaluation, the four products (CHIRPS, MSWEP, TMPA, and CMAP) revealed that the annual precipitation over the TP fluctuated between 333 mm/yr and 488 mm/yr during the period 2003 to 2015. The study indicates the importance of integration of multiple data sources and post-processing (e.g., gauge data fusion and elevation correction) for satellite-based products and have implications for selection of suitable precipitation products for hydrological modeling and water resources assessment for the TP.

Temporal and Spatial Evolution Features of Precipitable Water in China during a Recent 65-Year Period (1951–2015)

Water vapor in the atmosphere is not only an important greenhouse gas, but also an important factor that significantly affects the variations of global climate and water circulation. This study utilized the National Centers for Environmental Prediction (NCEP) and Climate Prediction Center Merged Analysis of Precipitation (CMAP) reanalysis data to probe the temporal and spatial distribution features of atmospheric precipitable water (PW) in China during a recent 65-year period (1951–2015), and the relationship between PW and actual precipitation was also studied. The temporal and spatial distribution characteristics of PW in China presented an overall decreasing spatial trend from the southeast to northwest direction. The spatial distribution pattern of the first eigenvector demonstrated that the PW in China shows nationwide variation features with a varying amount of PW across different regions. The year 1967 was further identified as an important transition period for the temporal and spatial distribution characteristics of the PW. We also found that the PW had inherent variability of around 30 years. Regarding the relationship with precipitation, PW was most closely correlated with precipitation in the northeastern region and the upper northwestern region in China. Different regions displayed different efficiencies for converting PW to precipitation. The conclusions are useful for understanding the long-term water vapor evolution and its potential effects on precipitation in China.

Correlation between the Onset of the East Asian Subtropical Summer Monsoon and the Eastward Propagation of the Madden–Julian Oscillation

Abstract Using the daily outgoing longwave radiation (OLR), the pentad Climate Prediction Center Merged Analysis of Precipitation (CMAP), and the 6-h Climate Forecast System Reanalysis (CFSR) dataset from 1979 to 2010, a composite analysis along with space–time wave filtering is performed to examine the linkage between the Madden–Julian oscillation (MJO) and the onset of the East Asian subtropical summer monsoon (EASSM) (over 20°–30°N, 110°–120°E). The onset of the EASSM is shown to be best characterized by the reversal of the mean meridional wind shear related to the rapid reestablishment of the South Asian high (SAH) over the southern Indochinese Peninsula in the upper troposphere. The mean date of EASMM onset is near the end of April, which is about a month earlier than the typical onset of the East Asian summer monsoon. Further analysis indicates that the onset of the EASSM and the reestablishment of SAH are often associated with the arrival of the wet phase of the tropical MJO over the central and eastern Indian Ocean.

Seasonal intercomparison of observational rainfall datasets over India during the southwest monsoon season

The Indian monsoon is an important component of Earth's climate system, accurate forecasting of its mean rainfall being essential for regional food and water security. Accurate measurement of the rainfall is essential for various water-related applications, the evaluation of numerical models and detection and attribution of trends, but a variety of different gridded rainfall datasets are available for these purposes. In this study, six gridded rainfall datasets are compared against the India Meteorological Department (IMD) gridded rainfall dataset, chosen as the most representative of the observed system due to its high gauge density. The datasets comprise those based solely on rain gauge observations and those merging rain gauge data with satellite-derived products. Various skill scores and subjective comparisons are carried out for the Indian region during the south-west monsoon season (June to September). Relative biases and skill metrics are documented at all-India and sub-regional scales. In the gauge-based (land-only) category, Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) and Global Precipitation Climatology Center (GPCC) datasets perform better relative to the others in terms of a variety of skill metrics. In the merged category, the Global Precipitation Climatology Project (GPCP) dataset is shown to perform better than the Climate Prediction Center Merged Analysis of Precipitation (CMAP) for the Indian monsoon in terms of various metrics, when compared with the IMD gridded data. Most of the datasets have difficulty in representing rainfall over orographic regions including the Western Ghats mountains, in north-east India and the Himalayan foothills. The wide range of skill scores seen among the datasets and even the change of sign of bias found in some years are causes of concern. This uncertainty between datasets is largest in north-east India. These results will help those studying the Indian monsoon region to select an appropriate dataset depending on their application and focus of research.

Comparison of Downscaled Precipitation Data over a Mountainous Watershed: A Case Study in the Heihe River Basin

Abstract Development of an accurate precipitation dataset is of primary importance for regional hydrological process studies and water resources management. Here, four regional precipitation products are evaluated for the Heihe River basin (HRB): 1) a spatially and temporally disaggregated Climate Prediction Center Merged Analysis of Precipitation (CMAP) at 0.25° spatial resolution (DCMAP); 2) a fusion product obtained by merging China Meteorological Administration station data and Tropical Rainfall Measuring Mission precipitation data at 0.1° spatial resolution supported by the Institute of Tibetan Plateau Research (ITP), Chinese Academy of Sciences (ITP-F); 3) a disaggregated CMAP downscaled by a statistical meteorological model tool at 1-km spatial resolution (DCMAP–MicroMet); and 4) a Weather Research and Forecasting (WRF) Model simulation with 5-km resolution (WRF-P). The validation metrics include spatial pattern, temporal pattern, error analysis with respect to observation data, and precipitation event verification indicators. The results indicate that 1) precipitation from the DCMAP product may not be suitable for water cycle studies at the watershed scale because of its coarser spatial resolution and 2) ITP-F, WRF-P, and DCMAP–MicroMet precipitation products generally show similar spatial–temporal patterns in HRB but have varying performances between different subbasins.

The boreal summer intraseasonal oscillation simulated by four Chinese AGCMs participating in the CMIP5 project

The performances of four Chinese AGCMs participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) in the simulation of the boreal summer intraseasonal oscillation (BSISO) are assessed. The authors focus on the major characteristics of BSISO: the intensity, significant period, and propagation. The results show that the four AGCMs can reproduce boreal summer intraseasonal signals of precipitation; however their limitations are also evident. Compared with the Climate Prediction Center Merged Analysis of Precipitation (CMAP) data, the models underestimate the strength of the intraseasonal oscillation (ISO) over the eastern equatorial Indian Ocean (IO) during the boreal summer (May to October), but overestimate the intraseasonal variability over the western Pacific (WP). In the model results, the westward propagation dominates, whereas the eastward propagation dominates in the CMAP data. The northward propagation in these models is tilted southwest-northeast, which is also different from the CMAP result. Thus, there is not a northeast-southwest tilted rain belt revolution off the equator during the BSISO’s eastward journey in the models. The biases of the BSISO are consistent with the summer mean state, especially the vertical shear. Analysis also shows that there is a positive feedback between the intraseasonal precipitation and the summer mean precipitation. The positive feedback processes may amplify the models’ biases in the BSISO simulation.

Modelling the effect of soil moisture variability on summer precipitation variability over East Asia

ABSTRACTThe potential role of surface soil moisture (SSM) in improving the simulation of interannual East Asian summer precipitation is investigated using a coupled land‐atmosphere climate model, the Community Atmosphere Model version 3 (CAM3). Forced by specified observational sea surface temperature (SST), two ensemble simulations for 22 boreal‐summer seasons (1979–2000) are conducted, one with interannually varying SSM (SSMinter) forcing and another with climatological SSM (SSMclim) forcing. Results show that, relative to the SSMclim run, interannual variability of East Asian summer precipitation is better simulated in the SSMinter run over the mid‐ and high‐latitudes of East Asia, especially in northwest China, where the correlation coefficient between precipitation simulated and observed from the Climate Prediction Center Merged Analysis of Precipitation (CMAP) is increased from 0.12 to 0.56 during 1979–2000. Meanwhile, positive relationships between anomalies of local soil evaporation and summer precipitation in northwest China can be better reproduced in the SSMinter run than in the SSMclim run. Possible mechanisms for the improved simulations of the interannual summer precipitation variability in northwest China are analysed; the improvement is resulted from the reasonable reproduction of anomalous atmospheric circulation in Siberia and Iranian plateau.

Study on the changes in the East Asian precipitation in the mid‐1990s using a high‐resolution global downscaled atmospheric data set

AbstractA high‐resolution global atmospheric data set (DA126) is used to understand the East Asian summer precipitation variability. It is found that a fine resolution of the DA126 precipitation data is able to reveal the detailed structures of the rainfall variability over East Asia and southern China in comparison with global analysis precipitation data sets such as the Climate Prediction Center Merged Analysis of Precipitation (CMAP). The first two empirical orthogonal functions (EOFs) of the DA126 precipitation data over East Asia accurately reflect a decadal shift in rainfall over southern China in the mid‐1990s. Furthermore, the first EOF‐related precipitation of the DA126 is related to the tropical Pacific sea surface temperature (SST) variability (i.e., El Niño/Southern Oscillation), and the second EOF‐related precipitation is associated with the Indian Ocean SST variability. Consequently, the tropical Pacific and the Indian Ocean SSTs have different associations with the East Asian monsoon precipitation variability. However, it is difficult to find such a relationship in the first two EOFs of the CMAP data set over East Asia. Using the DA126 precipitation data set, our further analysis indicates that warming of both the tropical Pacific and the Indian Ocean causes an increase in the rainfall anomaly over southern China after the mid‐1990s, which results in a decadal shift in the rainfall anomaly after the mid‐1990s. In addition, the first EOF‐related precipitation is associated with both the Pacific‐Japan‐like (PJ‐like) pattern and the Eurasian‐like pattern. In contrast, the second EOF‐related precipitation is only associated with the PJ‐like wave trains from the western Pacific to East Asia.

Quality Control and Analysis of Global Gauge-Based Daily Precipitation Dataset from 1980 to 2009

A series of quality control (QC) procedures were performed on a gauge-based global daily precipitation dataset from the Global Telecommunication System (GTS) for the period 1980–2009. A new global daily precipitation (NGDP) dataset was constructed by applying those QC procedures to eliminate erroneous records. The NGDP dataset was evaluated using the NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) and the Global Precipitation Climatology Project (GPCP) precipitation datasets. The results showed that the frequency distribution and spatial distribution pattern of NGDP had a nice match with those from the CMAP and GPCP datasets. The global mean correlation coefficients with the CMAP and GPCP data increased from 0.24 for original GTS precipitation data to about 0.70 for NGDP data. Correspondingly, the root mean square errors (RMSE) decreased from 12 mm per day to 1 mm per day. The interannual variabilities of NGDP monthly precipitation are consistent with the CMAP and GPCP datasets in Asia. Meanwhile, the seasonal variabilities for most land areas on the Earth of NGDP dataset are also consistent with the CMAP and GPCP precipitation products. CitationNie, S.-P., Y. Luo, W.-P. Li, et al., 2012: Quality control and analysis of global gauge-based daily precipitation dataset from 1980 to 2009. Adv. Clim. Change Res., 3(1), doi: 10.3724/SP.J.1248.2012.00045.

Analysis of precipitation climatology simulated by high resolution coupled global models over the South America

The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.

Global Energy and Water Budgets in MERRA

Abstract Reanalyses, retrospectively analyzing observations over climatological time scales, represent a merger between satellite observations and models to provide globally continuous data and have improved over several generations. Balancing the earth’s global water and energy budgets has been a focus of research for more than two decades. Models tend to their own climate while remotely sensed observations have had varying degrees of uncertainty. This study evaluates the latest NASA reanalysis, the Modern Era Retrospective-Analysis for Research and Applications (MERRA), from a global water and energy cycles perspective, to place it in context of previous work and demonstrate the strengths and weaknesses. MERRA was configured to provide complete budgets in its output diagnostics, including the incremental analysis update (IAU), the term that represents the observations influence on the analyzed states, alongside the physical flux terms. Precipitation in reanalyses is typically sensitive to the observational analysis. For MERRA, the global mean precipitation bias and spatial variability are more comparable to merged satellite observations [the Global Precipitation and Climatology Project (GPCP) and Climate Prediction Center Merged Analysis of Precipitation (CMAP)] than previous generations of reanalyses. MERRA ocean evaporation also has a much lower value, which is comparable to independently derived estimate datasets. The global energy budget shows that MERRA cloud effects may be generally weak, leading to excess shortwave radiation reaching the ocean surface. Evaluating the MERRA time series of budget terms, a significant change occurs that does not appear to be represented in observations. In 1999, the global analysis increments of water vapor changes sign from negative to positive and primarily lead to more oceanic precipitation. This change is coincident with the beginning of Advanced Microwave Sounding Unit (AMSU) radiance assimilation. Previous and current reanalyses all exhibit some sensitivity to perturbations in the observation record, and this remains a significant research topic for reanalysis development. The effect of the changing observing system is evaluated for MERRA water and energy budget terms.

Regionalization of Present-Day Precipitation in the Greater Monsoon Region of Asia*

Abstract The spatial domain of the Asian monsoon has been defined by the intensity, seasonal concentration, and annual range of precipitation. Monsoon subdomains, such as the Indian monsoon, East Asian monsoon, and western North Pacific monsoon, have also been identified based on seasonal wind reversals as well as the timing and source of monsoon moisture. However, precipitation across the Asian monsoon region is heterogeneous and spatially complex and may have influences farther north than commonly assumed, particularly if scientists consider records of past variability spanning the current interglacial period. This paper presents an additional means of identifying the Asian monsoon domain and monsoon subsystems using an empirical orthogonal function (EOF)-based regionalization of gridded precipitation values. Regions of unique precipitation variability for the Asian monsoon region are determined using monthly precipitation anomalies from the Climate Prediction Center Merged Analysis of Precipitation (CMAP) gridded precipitation dataset from 1979 to 2009. From these regions, an area of Asian monsoon influence extending from the Arabian Sea eastward to the western North Pacific Ocean is defined, similar to other studies. One key difference is that this region of monsoon influence penetrates farther north into the Tibetan Plateau and northern China. Thus, paleoclimate observations of wetter conditions in these northern arid regions may suggest an intensification of monsoon moisture, rather than a northward shift in the boundary of the monsoon. In contrast, the Arabian Peninsula, largely removed from monsoon precipitation today, likely saw a shift of monsoon influence inland earlier in the Holocene. Also identified are different subdomains of distinct precipitation variability in southeastern Asia, the western North Pacific, and the East Asian monsoon region of northeastern China that agree with previous studies. Not identified in the paper is a single Indian summer monsoon region. Instead, the Arabian Sea was found to have unique precipitation variability relative to the Indian subcontinent. Summers with enhanced precipitation over the Arabian Sea coincide with decreased summer precipitation in the western North Pacific. This relationship is likely a result of the El Niño–Southern Oscillation (ENSO)-induced development of the Philippine Sea anticyclone. Local and remote sea surface temperatures were generally found to covary with regional precipitation, but not all regions respond similarly to the remote climate variability associated with ENSO. There is some evidence that the EOF-defined regions were stable … through the Holocene, although additional regionalization analyses of paleorecords and model simulations of past precipitation variability are needed to reconstruct past regions of coherent precipitation variability.

GRACE and AMSR‐E‐based estimates of winter season solid precipitation accumulation in the Arctic drainage region

Solid precipitation plays a major role in controlling the winter hydrological cycle and spring discharge in the Arctic region. However, it has not been well documented due to sharply decreasing numbers of precipitation gauges, gauge measurement biases, as well as limitations of conventional satellite methods in high latitudes. In this study, we document the winter season solid precipitation accumulation in the Arctic region using the latest new satellite measurements from the Gravity Recovery and Climate Experiment (GRACE) and the Advanced Microwave Scanning Radiometer‐Earth Observing System (AMSR‐E). GRACE measures the winter total water (mainly from snow water equivalent (SWE)) storage change through gravity changes while AMSR‐E measures the winter SWE through passive microwave measurements. The GRACE and AMSR‐E measurements are combined with in situ and numerical model estimates of discharge and evapotranspiration to estimate the winter season solid precipitation accumulation in the Arctic region using the water budget equation. These two satellite‐based estimates are then compared to the conventional estimates from two global precipitation products, such as the Global Precipitation Climatology Project (GPCP) and Climate Prediction Center's Merged Analysis of Precipitation (CMAP), and three reanalyses, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, the European Centre for Medium‐Range Weather Forecasts' ERA‐Interim, and the Japan Meteorological Agency's Climate Data Assimilation System (JCDAS) reanalysis. The GRACE‐based estimate is very close to the GPCP and ERA‐Interim estimates. The AMSR‐E‐based estimate is the most different from the other estimates. This GRACE‐based measurement of winter season solid precipitation accumulation can provide a new valuable benchmark to understand the hydrological cycle, to validate and evaluate the model simulation, and to improve data assimilation in the Arctic region.

Impact of the Madden–Julian Oscillation on Wintertime Precipitation in Canada

Abstract Based on the adjusted daily total precipitation data at Canadian stations and the Climate Prediction Center Merged Analysis of Precipitation (CMAP) data during the most recent 30 Northern Hemisphere winters, the connection between the tropical convection of the Madden–Julian oscillation (MJO) and the intraseasonal variability of precipitation in Canada is investigated. The dominant convection patterns associated with the MJO are represented by the two leading modes of the empirical orthogonal function (EOF) analysis that is applied to the pentad outgoing longwave radiation (OLR) in the equatorial Indian Ocean and western Pacific. The first EOF mode is characterized by a single convection center near the Maritime Continent, whereas the second EOF has an east–west dipole structure with enhanced precipitation over the Indian Ocean and reduced convective activity over the tropical western Pacific. Lagged regression analysis reveals significant precipitation anomalies in Canada associated with the tropical convection of the MJO. Above-normal precipitation starts to occur in the west coast of Canada one pentad after a positive EOF2 phase. In the next two pentads, positive precipitation anomalies extend to a large area of south Canada. At the same time, the northeast region experiences reduced precipitation. For strong MJO events when the principal component of EOF2 exceeds its standard deviation, the precipitation anomaly in the west coast of Canada can reach about 20%–30% of its standard deviation of pentad-to-pentad variability. A linearized global primitive equation model is utilized to assess the cause of the intraseasonal variability in the Northern Hemisphere extratropics and its influence on North American weather associated with the tropical heating of the MJO.

Assessing High-Latitude Winter Precipitation from Global Precipitation Analyses Using GRACE

Abstract This study compares cold-season, high-latitude precipitation estimates from two global, merged satellite–gauge precipitation analyses—Global Precipitation Climatology Project (GPCP) and Climate Prediction Center Merged Analysis of Precipitation (CMAP)—to total water storage anomalies produced from the Gravity Recovery and Climate Experiment (GRACE). In general, spatial patterns and interannual variability are highly correlated between the datasets, although significant differences are also observed. Differences vary by region but typically increase at higher latitudes. Furthermore, results indicate that the gauge undercatch correction used by GPCP may be overestimated. These comparisons may be useful for assessing precipitation estimates over large regions, where in situ gauge networks may be sparse.

Empirical Analysis of Intraseasonal Climate Variability over the Greater Horn of Africa

Abstract This study examines the intraseasonal climate variability over the Greater Horn of Africa (GHA) during the rainy season of October–December (OND). The investigation is primarily based on empirical orthogonal function (EOF) analysis of the pentad Climate Prediction Center Merged Analysis of Precipitation (CMAP) data for the period 1979–2001. The EOF analysis reveals two dominant modes of intraseasonal variability for the OND season: mixed El Niño–Southern Oscillation–Indian Ocean dipole (ENSO-IOD) and a decadal mode. The leading mode is associated with ENSO–IOD covariability. Case studies of several intraseasonal ENSO–IOD events within the recent decades indicate that during the warm (positive) events pentad rainfall is consistently above normal during the entire season despite fluctuations between pentads. However, case study analyses of negative ENSO–IOD events show that the negative cases are not mirror images of the warm events. The negative events exhibit pronounced wet and dry spells superimposed on the consistent dry anomaly background conditions. There is no large signal regarding the onset for either case, but the withdrawal of the positive (negative) events is anomalously wet (dry). The second mode of variability is associated with a decadal shift in the rainfall with the northern (southern) GHA becoming wetter (drier) in the recent decade. The decadal change in individual pentads can be quite different across the season and has a tendency to manifest itself through extreme events. The analysis underscores the need to exercise caution when applying seasonal-average-based statistics to infer the long-term behavior on subseasonal time scales. Additional analyses further confirm the decadal rainfall shift using four different rainfall datasets. Averaging the datasets to help aid in removing bias of individual datasets shows that, on average, northern (southern) portions of GHA are 29% (19%) wetter (drier) in the recent decade.

Tropical western Pacific warm pool and maritime continent precipitation rates and their contrasting relationships with the Walker Circulation

The Cenozoic reorganization of islands in the Maritime Continent region of the tropical western Pacific may have increased the amount of land surface area, changed the distribution of sea surface temperature (SST), and consequently provided a necessary condition for the onset of the Walker Circulation. Precipitation rates over the Maritime Continent, measured with the Tropical Rainfall Measurement Mission (TRMM) satellite and generated from the Climate Prediction Center Merged Analysis of Precipitation (CMAP), correlate positively with a variety of measures of the Walker Circulation's strength (surface easterlies and high‐level westerlies over the western Pacific) and hence with La Niña conditions. Similarly measured precipitation rates over the western Pacific warm pool correlate positively with the strength of tropical zonal circulation shifted to the east, and thus a weakened Walker Circulation and stronger El Niño‐like conditions. Areas of high precipitation rates correlate with areas of ascent in the atmosphere and with high SST. Condensation associated with precipitation over the warm pool provides about twice the amount of latent heating as that over the Maritime Continent largely because the surface area of the warm pool is about 1.9 times larger than that of the Maritime Continent. These results support the conjecture that tectonic expansion and reorganization of the Maritime Continent may have led to a strengthening of the Walker Circulation, and may be related to a change in tropical Pacific climate from a permanent and zonally uniform (El Niño‐like) state in Pre‐Ice Age time to the present day El Niño‐Southern Oscillation (ENSO) state.

Role of SST over the Indian Ocean in Influencing the Intraseasonal Variability of the Indian Summer Monsoon

Intraseasonal variability (10-60 days) of sea surface temperature (SST) over the north Indian Ocean and its influence on regional precipitation variability over the Indian subcontinent are examined. SST, cloud liquid water and precipitation over the Indian Ocean of the Tropical Rainfall Measuring Mission (TRMM), precipitation of Climate Prediction Center Merged Analysis of Precipitation (CMAP), and low-level atmospheric parameters of National Center for Environmental Prediction (NCEP) II reanalysis are utilized for this study. Western Ghats (WG) in the southwest and the Ganges-Mahanadi Basin (GB) in the northeast of the Indian subcontinent are observed to be the regions of maximum precipitation with large standard deviations of the intraseasonal variability. Active (break) phases of precipitation occur in these regions by the northward propagation of positive (negative) precipitation anomalies over the Arabian Sea and the Bay of Bengal. Latitude-time plots during the active phase of the WG region shows that the positive SST anomalies over the Arabian Sea formed by suppressed surface latent heat flux and increased downward shortwave radiation flux lead the positive precipitation anomalies. Surface air temperature anomalies follow the SST anomalies and then destabilize the lower atmosphere between 1000 hPa and 700 hPa. These results indicate that, in the northward propagating dynamical surface convergence, underlying SST anomalies tend to form a favorable condition for convective activity and may sustain enhanced precipitation over the convergence region. This results in enhanced precipitation anomalies over the WG region that move further northeastward and merge with the northward propagating precipitation anomalies from the Bay of Bengal, enhancing the active phase of the GB region.

Comparing 20 years of precipitation estimates from different sources over the world ocean

The paper compares ten different global precipitation data sets over the oceans and discusses their respective strengths and weaknesses in ocean regions where they are potentially important to the salinity and buoyancy budgets of surface waters. Data sets (acronyms of which are given in Section 2) are categorised according to their source of data, which are (1) in situ for Center for Climatic Research (Legates and Willmott, 1990; Archive of Precipitation Version 3.01, http://climate.geog.udel.edu/~climate), Southampton Oceanography Centre (SOC) (Josey et al., J Clim 12:2856–2880, 1999) and University of Wisconsin-Milwaukee (UWM) (Da Silva et al. 1994); (2) satellite for Microwave Sounding Unit (MSU) (Spencer, J Clim 6:1301–1326, 1993), TOPEX (Quartly et al., J Geophys Res 104:31489–31516, 1999), and Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS) (Bauer and Schluessel, J Geophys Res 98:20737–20759, 1993); (3) atmospheric forecast model re-analyses for European Centre for Medium-range Weather Forecast (ECMWF) (Gibson et al. 1997) and National Center for Environmental Prediction (NCEP) (Kalnay et al., Bull Am Meteorol Soc 77:437–471, 1996); and (4) composite for Global Precipitation Climatology Project (GPCP) (satellites and rain gauges, Huffman et al., Bull Am Meteorol Soc 78(1):5–20, 1997) and Climate Prediction Center Merged Analysis of Precipitation (CMAP) (satellites, rain gauges and atmospheric forecast model, Xie and Arkin, Bull Am Meteorol Soc 78(11):2539–2558, 1997). Although there is no absolute field of reference, composite data sets are often considered as the best estimates. First, a qualitative comparison is carried out, which provides for each data set, a description of the geographical distribution of the climatological mean precipitation field. A more careful comparison between data sets is undertaken over periods they have in common. First, six among the ten data sets (SOC, UWM, ECMWF, NCEP, MSU and CMAP) are compared over their common period of 14 years, from 1980 to 1993. Then CMAP is compared to GPCP over the 1988–1995 period and to HOAPS over the 1992–1998 period. Usual diagnostics, like comparison of the precipitation patterns exhibited in the annual climatological means of zonal averages and global budget, are used to investigate differences between the various precipitation fields. In addition, precipitation rates are spatially integrated over 16 regional boxes, which are representative of the major ocean gyres or large-scale ocean circulation patterns. Seasonal and inter-annual variations are studied over these boxes in terms of time series anomalies or correlation coefficients. The analysis attempts to characterise differences and biases according to the original source of data (i.e. in situ or satellite, etc.). Qualitative agreement can be observed in all climatologies, which reproduce the major characteristics of the precipitation patterns over the oceans. However, great disagreements occur in terms of quantitative values and regional patterns, especially in regions of high precipitation. However, a better agreement is generally found in the northern hemisphere. The most significant differences, observed between data sets in the mean seasonal cycles and interannual variations, are discussed. A major result of the paper, which was not expected a priori, is that differences between data sets are much more dependent upon the ocean region that is considered than upon the origin of the data sets (in situ vs satellite vs model, etc.). Our analysis did not provide enough objective elements, which would allow us to clearly recommend a given data set as reference or best estimate. However, composite data sets (GPCP, and especially CMAP), because they never appeared to be really “off” when compared to other data sets, may represent the best recent data set available. CMAP would certainly be our first choice to drive an ocean GCM.