Monthly Rainfall Amounts Research Articles

Tropical Cyclonic Rainfall in China: Changing Properties, Seasonality, and Causes

AbstractUsing daily rainfall data from 1936 stations across China, this study investigated tropical cyclonic rainfall (TCR) changes during 1960–2014. The possible reasons behind TCR changes were examined using tracks and frequency of tropical cyclones (TCs) in both space and time. The highest annual TCR occur in coastal regions of east and southeast China (>500 mm/year). At monthly scale, August TCR can reach 150–250 mm in coastal regions. From the contribution viewpoint, TCR accounts for more than 40% of the monthly total rainfall and extreme rainfall events along the southeast coast of China. The contributions of TCR to the monthly rainfall amount decrease rapidly from coast to inland and are even faster for contributions of TCR to extreme rainfall. The distance inland from the shoreline with 250 km has been identified as the threshold, within that these contributions abruptly increase with decreasing distance from shoreline, and vice versa. In terms of extreme rainfall regimes, logistic and Poisson regressive techniques were used to identify the connections between TC‐induced extreme rainfall and El Niño–Southern Oscillation. Both these two regressions reveal that TC‐induced extreme rainfall tends to occur with higher frequency and magnitude in southeastern China (east and northeast coast of China) during La Niña (El Niño) years (El Niño). These consistent relations and remarkable spatial patterns can help to predict the occurrence of TC‐induced extreme rainfall events across eastern China.

Spatiotemporal trend analysis of changing rainfall characteristics in Guinea Savanna of Nigeria

This study attempt to examine the changing rainfall characteristics in Guinea Savanna of Nigeria. In view of the aim and targeted objectives, rainfall was carefully looked at on monthly and annual basis in brief and ecological spatial scales with data from 1980 to 2014. The study considered 12 stations which represent the area. Basic descriptive statistics like the mean, standard deviation, coefficient of variation including other inferential statistics such as linear regression, and standardized anomaly were successfully utilized. Variables analyzed include monthly and annual rainfall amount and number of rain days. Geostatistical analysis was employed mainly for spatial analysis in geographical information system (GIS) environment. Highest coefficient of variation of rainy days in Northern Guinea occurs in Yola 37% while highest in Ilorin in the Southern Guinea is 12.19%. The coefficient of determination (R2) of annual rainfall amount and rainy days were 66, 56, 63, 73 and 41% for Ibi, Abuja, Lokoja, Makurdi and Lafia respectively. It was generally discovered that rainfall shows variation temporally. The high variations of rainfall at higher latitudes reveal the unreliable nature of rainfall as one progresses towards Northern Guinea and vice versa. This results will enable policy makers and general public particularly farmers to understand the rainfall variability so as to adapt strategies like irrigation schemes for food security. This work will also help government to establish more effective meteorological stations at micro level to have dense network of stations for more accurate results.

Defining Philippine Climate Zones Using Surface and High-Resolution Satellite Data

Philippine climate zones traditionally were classified from a rain-gauge network, using the Modified Coronas Classification (MCC). MCC uses average monthly rainfall totals to define four climate zones: Types I-IV. Types I and III have wet and dry seasons, whereas Types II and IV have wet seasons but no dry seasons.The present study redefines Philippine climate zones by applying cluster analysis to the average monthly rainfall amounts from surface-based rain-gauge observations, and dense, high-resolution satellite data from the Tropical Rainfall Monitoring Mission (TRMM). To determine the optimal number of climate type clusters, both single-linkage hierarchical and K-means cluster analysis algorithms were used, together with known characteristics of Philippine rainfall distributions and attributes.Employing single linkage hierarchical and K-means methods in tandem identified six different Philippine climate types, which is two climate types more than the currently accepted MCC climate classification. Due to the far greater number of TRMM observations compared with the rain gauge network, the study provides more clearly defined cluster characteristics including the spatial and temporal variability of climate divisions. This study uses known meteorological factors contributing to the identification of six distinct climate types. This paper is intended to assist agricultural stakeholders with planning and decision-making.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998–2015), PERSIANN-CDR (1983–2015) and CHIRPS 2.0 (1981–2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze these datasets to better understand their similarities and differences in characterizing rainfall patterns across Chile. Monthly analysis showed that all satellite products highly overestimated rainfall in the arid North zone. However, there were no major difference between all three products from North to South-Central zones. Though, in the South zone, PERSIANN-CDR shows the lowest fit with high underestimation, while CHIRPS 2.0 and TMPA 3B43 v7 had better agreement with in situ measurements. The accuracy of satellite products were highly dependent on the amount of monthly rainfall with the best results found during winter seasons and in zones (Central to South) with higher amounts of precipitation. PERSIANN-CDR and CHIRPS 2.0 were used to derive SPI at time-scale of 1, 3 and 6 months, both satellite products presented similar results when it was compared in situ against satellite SPI's. Because of its higher spatial resolution that allows better characterizing of spatial variation in precipitation pattern, the CHIRPS 2.0 was used to mapping the SPI-3 over Chile. The results of this study show that in order to use the CHIRPS 2.0 and PERSIANN-CDR datasets in Chile to monitor spatial patterns in the rainfall and drought intensity conditions, these products should be calibrated to adjust for the overestimation/underestimation of rainfall geographically specially in the North zone and seasonally during the summer and spring months in the other zones.

Spatial and temporal characteristics of rainfall in a data-scarce region: case of Kinshasa and Bas-Congo in Democratic Republic of Congo

ABSTRACTThe aim of the present paper was to improve understanding of the rainfall dynamics in Bas-Congo and Kinshasa provinces, in Democratic Republic of Congo (DRC). The first objective of the study was achieved by analysing the spatial correlations of monthly, seasonal, annual and individual monthly rainfall amounts of Kinshasa and Bas-Congo. The second objective was achieved through investigating and quantifying the temporal trends and their spatial variations. The results demonstrated notably high average inter-station correlation of +0.63 for dry season series, followed by monthly rainfall series with an average inter-station correlation of +0.58. However, there was no station with a stable monthly rainfall regime, i.e. with mean precipitation concentration index lower than 10% (it varies between 14.2 and 21.9%). Moreover, Kinshasa experienced an increase of rainfall with an average annual rate of change of +4.59 mm/year for the period 1961–2006. The results will be helpful for efficient water resources management and for mitigating the adverse impacts of future extreme drought or flood occurrences.Editor M.C. Acreman Associate editor N. Verhoest

Independent Gamma Variables of McKay Distribution for Rainfall Model

The application of mathematical models of rainfall is crucial in order to have a better understanding in terms of rainfall characteristics. The rainfall models has been used widely to improve water management, to construct hydrological structures and as an input in climatological studies. In this study, the gamma distribution is used to fit the marginals of monthly rainfall data. The parameters of gamma distributions, shape and scale, are estimated using the maximum likelihood estimation method. Then the sum of monthly rainfall amount is modelled using the Mckay ditribution for independent gamma variables.

Effects of different vegetation restoration on soil water storage and water balance in the Chinese Loess Plateau

Large-scale vegetation restoration in the Chinese Loess Plateau has been initiated by the central government over the past decades to control soil and water loss. However, no guidelines are followed in plant species selection for vegetation restoration. We examined the effects of planting Pinus tabuliformis, Robinia pseudoacacia, Caragana korshinskii, and Hippophae rhamnoides on soil water dynamics and water stresses by measuring canopy interception, soil evaporation, plant transpiration, and surface runoff from May to September of 2009–2013 in the semi-arid loess hilly area. Results showed the following: (1) Water loss exceeded precipitation in most months during the growing seasons. The amount of soil water storage decreased within a 100cm depth in all land cover types from 2009 to 2013. Land cover examination showed that the slope of the decline trend of soil water storage for C. korshinskii was much lower than that of the other land cover types. However, P. tabuliformis exhibited the biggest decline slope among the four land cover types. (2) The ratio of actual evapotranspiration (ET) and pan evaporation (Ep) was low for all land cover types during the study period. The ET/Ep ratios followed the order (from highest to lowest) C. korshinskii>R. pseudoacacia>H. rhamnoides>P. tabuliformis. When the monthly rainfall amount was lower than 50mm, H. rhamnoides showed the lowest ET/Ep ratio among the four land cover types, but high ET/Ep ratio was observed in H. rhamnoides with large rainfall amount (>70mm). The current study suggested that P. tabuliformis plantation should not be the first choice for vegetation restoration in such a semiarid loess hilly area. H. rhamnoides is suitable for afforestation in areas with high levels of rainfall. C. korshinskii and R. pseudoacacia are highly recommended for vegetation restoration.

THE DYNAMICS OF THE CLIMATIC CONDITIONS OF THE TEREK-KUMA LOWLAND DURING 120 YEARS

Aim. This article is devoted to the analysis of climatic conditions of the territory of the Terek-Kuma Lowland. Data of the last 60 years (1951–2010) are compared with conditions of 1881–1935 (air temperature) and 1898–1948 (precipitation and relative humidity). Determination of tendencies in the age-old range, and for the last 60 years is given. Location. Terek-Kuma Lowland, Eastern Ciscaucasia, Russia. Methods. The following environmental parameters are characterized: the amount of monthly rainfall, average temperatures and humidity, evaporation, moisture ratio and the lack of moisture. Statistical characteristics (mean, variance, coefficient of variation) of annual precipitation, mean annual temperature and humidity, evaporation, lack of moisture are calculated. Separately, the same parameters were calculated for the warm (April – October) and cold (November – March) seasons. Significance of differences between them was assessed by the standard deviation ( α ) and the coefficient of variation ( Cv ). Results. Our analysis of the moisture conditions of the Terek-Kuma Lowland in the last 60 years has shown significant changes in key climate indicators in comparison with the corresponding (for the duration of observations) rates in preceding years. The average annual temperature for the period , including for the warm season (April – October), increased by 0.6 °C, annual precipitation decreased respectively by 29.6 and 35.9 mm. Coefficient of humidity (ratio of annual precipitation to evaporation) in the ambient range from 0.11 in 1898–1948 increased to 0.14 in 1951–2010. Conclusions. Aridity of the climate did not increase on this territory. In 1951–2010 coefficient of humidity increased to 0.14, and fits into the range for dry (arid) regions, while in 1898–1948 coefficient of humidity was 0.11 and it was an important characteristic of extra arid (very dry) areas.

The Relationship between Diurnal Temperature Range (DTR) and Rainfall over Northern Thailand

Since 1950, it has been found that the global diurnal temperature range (DTR), the difference between the minimum temperature (Tmin) and the maximum temperature (Tmax) of daily surface air temperature, has been temporally decreasing in several places all over the world. The aim of this study is to investigate the effect of DTR on the amount of total monthly rainfall (TRF) and the number of rainy days per month (RD), as well as to evaluate the possibility of using DTR as a parameter in the rainfall prediction process. The study area is in northern Thailand, which covers about one third of the total area of the country. The impact of DTR on rainfall over the studied area is evaluated from the relationship between DTR and TRF, as well as DTR and RD, by using long-term meteorological monthly data over 30 years (1978-2007). Besides, the relationships of RD, TRF, and the temperature of mean monthly Tmax and Tmin are also analysed. The significance of the correlation between the two parameters is identified by the coefficient of correlation. The possibility of using DTR is evaluated by estimating the relationships between DTR and a one month-lag time of RD and TRF. It is found that the DTR has a strong statistically significant ( > 99%) negative correlation with TRF and RD, as well as with the one month-lag time of TRF and RD. Therefore, it is possible to consider DTR as a significant parameter for rainfall prediction.

Assessment of Spatial and Temporal Variability of Rainfall Data Using Kriging, Mann Kendall Test and the Sen?s Slope Estimates in Jordan from 1980 to 2007

This study aims to examine the spatial and temporal variability of the mean annual rain in Jordan during a 28-year period (1980-2007). The used meteorological datasets are the monthly rainfall amounts (mm) and the annual rainfall recorded at twenty five meteorological stations of the Jordan Meteorological Department. The stations are uniformly distributed over Jordan territory. Various spatial and statistical tools were used to display and analyze the spatial and temporal variability of rainfall data. ArcGIS was used to produce the spatially distributed rainfall data by using Kriging interpolation method. The non-parametric Mann-Kendall test was used to determine whether there is a positive or negative trend in data with their statistical significance. Sen's method was also used to determine the magnitude of the trends. The findings of the analysis show that statistically significant negative trends (95% confidence level) appear mainly in three areas, while no significant trends (95% confidence level) are found in the remnant areas. Further analysis concerning the seasonal Rain Intensity (RI) is needed, because there are different seasonal patterns, taking into account that, convective rain in Jordan occurs mainly within the winter season.

Chemical Composition, Fluxes and Seasonal Variation of Acid Deposition in Carmen Island, Campeche, Mexico

Two hundred and seven rain events from April to October 2012 were collected in Carmen Island, Campeche, Mexico, and the concentration of 8 major ions with the pH of the rainwater was analyzed. Chemical composition variations as a result of seasonal patterns, meteorological conditions, and mixed local and regional sources contribution were assessed. In spite of the fact that nitrate and sulfate levels were higher than background hemispheric values, the average pH values were almost neutral. Carmen Island was under the influence of both, local and long-range transported emissions. Chemical composition showed a dilution effect as a result of the monthly rainfall amount. Ca2+ and Na+ were the most abundant ions, and these ions acted as acid neutralizers and buffered the acidity of the rain, suggesting that marine and crustal aerosols played an important role in the acid-base interactions. Wet deposition fluxes obtained were compared with reference values proposed as critical loads, fluxes obtained in this study did not exceed the critical values reported for sensitive ecosystems in Europe, indicating that this site has yet enough capacity to support acidity, nitrogen and sulfur deposition. However, it is necessary to obtain reference values characteristics for tropical regions.

Understanding the effect of climatology on monthly rainfall amounts in Australia using Tweedie GLMs

AbstractRainfall models are used to understand the effect of various climatological variables on rainfall amounts. The models also have potential uses in predicting and simulating rainfall. We use Tweedie generalized linear models to model monthly rainfall amounts and occurrence simultaneously with a set of predictors (sine term, cosine term, NINO 3.4, SOI and SOI phase). Models are fitted to the monthly rainfall data of 220 Australian stations with 4 stations as case studies. First, models with only sine and cosine terms (the base model) are fitted to model the cyclic pattern of rainfall data, and then one of the climatological variables is added each time in addition to the base model. On the basis of the BIC, the model with NINO 3.4 is preferred for most of the studied stations. Stations for which the model using the SOI is preferred appear in small clusters. Adding the climatological variables to the base model improves the fit of the model and makes substantial changes in the predicted mean monthly rainfall amount and probability of getting a dry month. The climatological variables have significant impacts on the amount of rainfall in most stations located on the eastern and northeastern regions of Australia. The models used lags one of the climatological covariates (i.e. value of the covariates of previous month with rainfall amount of a month) and are useful for one month lead rainfall prediction. Copyright © 2011 Royal Meteorological Society

The effect of typhoon induced rainfall on settling fluxes of particles and organic carbon in Yuanyang Lake, subtropical Taiwan

A sediment-trap monitoring program measured the fluxes of settling particles and organic carbon in Yuanyang Lake, northern Taiwan, from July 2004 to July 2006 and assessed their relations to the amounts of normal monthly and typhoon-event precipitation. The flux of settling particles varied from 0.7 mg cm −2 month −1 to 14.7 mg cm −2 month −1, and the monthly precipitation ranged from 56 mm to 1218 mm during the survey period. The contributions from typhoon-event precipitation to monthly rainfall amounts were generally larger than 70%. Higher inputs of both particulate and organic carbon into the lake were found during typhoon seasons. Of the annual settling particle loading of 14.9 tons year −1 to the lake floor, 69% occurred during the typhoon months, and 62% of the annual organic carbon loading of 2.3 tons year −1 happened during the typhoon months. These results show the importance of typhoon events on the fluxes of settling particles and organic carbon and their delivery to lakes.

Lessons learned from oxygen isotopes in modern precipitation applied to interpretation of speleothem records of paleoclimate from eastern Asia

Variability in oxygen isotope ratios collected from speleothems in Chinese caves is often interpreted as a proxy for variability of precipitation, summer precipitation, seasonality of precipitation, and/or the proportion of 18O to 16O of annual total rainfall that is related to a strengthening or weakening of the East Asian monsoon and, in some cases, to the Indian monsoon. We use modern reanalysis and station data to test whether precipitation and temperature variability over China can be related to changes in climate in these distant locales. We find that annual and rainy season precipitation totals in each of central China, south China, and east India have correlation length scales of ∼500km, shorter than the distance between many speleothem records that share similar long-term time variations in δ18O values. Thus the short distances of correlation do not support, though by themselves cannot refute, the idea that apparently synchronous variations in δ18O values at widely spaced (>500km) caves in China are due to variations in annual precipitation amounts. We also evaluate connections between climate variables and δ18O values using available instrumental measurements of δ18O values in precipitation. These data, from stations in the Global Network of Isotopes in Precipitation (GNIP), show that monthly δ18O values generally do not correlate well with either local precipitation amount or local temperature, and the degree to which monthly δ18O values do correlate with them varies from station to station. For the few locations that do show significant correlations between δ18O values and precipitation amount, we estimate the differences in precipitation amount that would be required to account for peak-to-peak differences in δ18O values in the speleothems from Hulu and Dongge caves, assuming that δ18O scales with the monthly amount of precipitation or with seasonal differences in precipitation. Insofar as the present-day relationship between δ18O values and monthly precipitation amounts can be applied to past conditions, differences of at least 50% in mean annual precipitation would be required to explain the δ18O variations on orbital time scales, which are implausibly large and inconsistent with published GCM results. Similarly, plausible amplitudes of seasonal cycles in amounts or in seasonal variations in δ18O values can account for less than half of the 4–5‰ difference between glacial and interglacial δ18O values from speleothems in China. If seasonal cycles in precipitation account for the amplitudes of δ18O values on paleoclimate timescales, they might do so by extending or contracting the durations of seasons (a frequency modulation of the annual cycle), but not by simply varying the amplitudes of the monthly rainfall amounts or monthly average δ18O values (amplitude modulation). Allowing that several processes can affect seasonal variability in isotopic content, we explore the possibility that one or more of the following processes contribute to variations in δ18O values in Chinese cave speleothems: different source regions of the precipitation, which bring different values of δ18O in vapor; different pathways between the moisture source and the paleorecord site along which exchange of 18O between vapor, surface water, and condensate might differ; a different mix of processes involving condensation and evaporation within the atmosphere; or different types of precipitation. Each may account for part of the range of δ18O values revealed by speleothems, and each might contribute to seasonal differences between past and present that do not scale with monthly or even seasonal precipitation amounts.

Predictive downscaling based on non-homogeneous hidden Markov models

Weather-state models have been shown to be effective in downscaling the synoptic atmospheric information to local daily precipitation patterns. We explore the ability of non-homogeneous hidden Markov models (NHMM) to downscale regional seasonal climate data to daily rainfall at a collection of gauging sites. The predictors used are: ensemble means of seasonal rainfall as forecast by the DEMETER and ECHAM models, and the preceding seasonal outgoing long-wave radiation (OLR). As the downscaling of seasonal GCM-based predictions lacks the ability to capture the intra-seasonal variability, we augment the seasonal GCM-driven inputs with statistically-driven predictions of the monthly rainfall amounts. The pooling effect of combining seasonal and monthly estimates of the regional rainfall enhances the capacity of the NHMM to simulate the stochastic characteristics of rainfall fields. The monthly rainfall prediction is derived from a wide range of climate precursors such as the El Niño-Southern Oscillation, local sea-level pressure, and sea-surface temperature. Application of the methodology to data from the Everglades National Park region in South Florida, USA is presented for the seasons May–July and August–September using a 22-year sequence of seasonal data from eight rainfall stations. The model skill in capturing the seasonal and intra-seasonal rainfall attributes at each station is demonstrated graphically and using simple statistical measures of efficiency. The hidden states derived from NHMM are qualitatively analysed and shown to correspond to the dominant synoptic-scale features of rainfall generating mechanisms, which reinforces the argument that physical processes are appropriately captured. Citation Khalil, A. F., Kwon, H.-H., Lall, U. & Kaheil, Y. H. (2010) Predictive downscaling based on non-homogeneous hidden Markov models. Hydrol. Sci. J. 55(3), 333–350.

Evaluation of the Effects of the Orbit Boost of the TRMM Satellite on PR Rain Estimates

The Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite, which was launched on 28 November 1997, has been collecting global rainfall data for more than 10 years. The monthly estmated-surface rainfall (e_SurfRain) amounts estimated by PR have decreased on average since the satellite altitude was changed from 350 km to 402.5 km in August 2001 to extend its lifetime. There is no significant decrease in e_SurfRain in the five angle bins around the nadir (near-nadir) or in rainfall amounts at a 2-km height. The major causes of the changes in rain estimates due to the orbit boost are (1) sensitivity degradation, owing to the increase of satellite altitude, (2) an increase in the range of surface clutter owing to the increase in the footprint size, and (3) a mismatch between the transmission and reception angles of adjacent radar beams for one in every 32 pulses. The decrease in the echo from a distributed target near the surface attributable to the change of the satellite altitude from 350 km to 402.5 km is 1.21 dB (= 20log(402.5/350)). From a simulation result, we estimate a decrease of 0.5% in surface-rainfall estimates due to the sensitivity degradation. Because the height of the clutter-free bottom increases at off-nadir angles due to the increase in the footprint size from 4.3 km to 5.0 km, the sampling range bins for near-surface rain have been raised, causing the PR to miss low-rain systems more often after the boost than before the boost. Although a beam-mismatch correction is executed in the current 1B21 algorithm, the correction algorithm still results in a negative bias in rain-rate estimates near the surface in the second half of the PR scan. The changes in the surface-rainfall estimates after the boost due to the second and third causes can be estimated as -2.5% and -2.9% by comparing the estimates at off-nadir bins with those at near-nadir bins with the assumption that the true rain rates measured at all angle bins should be the same, on average. It is concluded that the total effect of the orbit boost is a decrease of 5.9% (= 0.5 + 2.5 + 2.9%) in the e_SurfRain amounts in PR version 6 products.

Climate change impact on SWAT simulated streamflow in western Kenya

AbstractWeather and climate extremes such as droughts and floods have far reaching impacts in Kenya. They have had implications in a variety of sectors including agriculture, water resources, health, energy, and disaster management among others. Lake Victoria and its catchment support millions of people and any impact on its ability to support the livelihoods of the communities in this region is of major concern. Thus, the main objective of this study was to assess the potential future climatic changes on the Nzoia catchment in the Lake Victoria basin, and how they might affect streamflow. The Soil and Water Assessment Tool was used to investigate the impact of climatic change on streamflow of the study area. The model was set up using readily available spatial and temporal data, and calibrated against measured daily streamflow. Climate change scenarios were obtained from general circulation models.Results obtained showed increased amounts of annual rainfall for all the scenarios but with variations on a monthly basis. All—but one—global circulation models (GCMs) showed consistency in the monthly rainfall amounts. Rainfall was higher in the 2050s than in the 2020s. According to climate change scenarios, temperature will increase in this region, with the 2050s experiencing much higher increases than the 2020s with a monthly temperature change range of 0–1.7 °C. The range of change in mean annual rainfall of 2.4–23.2% corresponded to a change in streamflow of about 6–115%. The analysis revealed important rainfall–runoff linear relationships for certain months that could be extrapolated to estimate amounts of streamflow under various scenarios of change in rainfall. Streamflow response was not sensitive to changes in temperature. If all other variables, e.g. land cover, population growth etc., were held constant, a significant increase in streamflow may be expected in the coming decades as a consequence of increased rainfall amounts. Copyright © 2008 Royal Meteorological Society

Rainfall-Induced Changes in Actual Surface Backscattering Cross Sections and Effects on Rain-Rate Estimates by Spaceborne Precipitation Radar

Abstract In this study, the authors used Tropical Rainfall Measuring Mission precipitation radar (TRMM PR) data to investigate changes in the actual (attenuation corrected) surface backscattering cross section (σ0e) due to changes in surface conditions induced by rainfall, the effects of changes in σ0e on the path integrated attenuation (PIA) estimates by surface reference techniques (SRTs), and the effects on rain-rate estimates by the TRMM PR standard rain-rate retrieval algorithm. Over land, σ0e is statistically higher under rainfall than under no rainfall conditions (soil moisture effect) unless the land surface is densely covered by vegetation. Over ocean, the dependence of σ0e on the incident angle differs under rainfall and no-rainfall conditions (wind speed effect). The alongtrack spatial reference (ATSR) method, one of the SRTs used in the standard algorithm, partially considers these effects, while the temporal reference (TR) method, another SRT, never involves these effects; its PIA estimates thus have negative biases over land. In the hybrid spatial reference (HSR) method used over ocean, different incident angles create different biases in PIA estimates. If the TR method is replaced by the ATSR method, the monthly rainfall amount in July 2001 all over the land within the TRMM coverage increases by 0.70%. The bias in the HSR method over ocean can be mitigated by fitting a σ0–θ curve separately to smaller incident angles and to larger incident angles. This improvement increases or decreases the monthly rainfall amounts in individual incident angle regions by up to 10%.

The Recent Increase in the Heavy Rainfall Events in August over the Korean Peninsula

The characteristics of the rainfall events on the Korean peninsula have been investigated by means of regional and global observational data collected from 1954 to 2004 with an emphasis on extreme cases <TEX>$80\;mm\;day^{-1}$</TEX>. According to our analysis, long-term annual rainfall anomalies show an increasing trend. This trend is pronounced in the month of August, when both the amount of monthly rainfall and the frequency of extreme events increase significantly. Composite maps on August during the 8 wet years reveal warm SST anomalies over the eastern Philippine Sea which are associated with enhanced convection and vertical motion and intensified positive SLP over central Eurasia during August. The rainfall pattern suggests that the most significant increase in moisture supply over the southern parts of China and Korea in August is associated with positive SLP changes over Eurasia and negative SLP changes over the subtropical western Pacific off the east coast of south China. The frequent generation of typhoons over the warm eastern Philippine Sea and their tracks appear to influence the extreme rainfall events in Korea during the month of August. The typhoons in August mainly passed the western coast of Korea, resulting in the frequent occurrence of extreme rainfall events in this region. Furthermore, anomalous cyclonic circulations over the eastern Philippine Sea also promoted the generation of tropical cyclones. The position of pressure systems - positive SLP over Eurasia and negative SLP over the subtropical Pacific - in turn provided a pathway for typhoons. The moisture is then effectively transported further north toward Korea and east toward the southern parts of China during the extreme rainfall period.

Population dynamics of oriental fruit fly Bactrocera dorsalis (Diptera: Tephritidae) in Xishuangbanna, Yunnan Province, China

Annual monitoring of the population dynamics of the oriental fruit fly Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) in Xishuangbanna, southern Yunnan, was conducted by using methyl eugenol-baited traps in 1997, 2000, and 2003, and factors including temperature, rainfall, and host species with respect to the population fluctuation were analyzed systematically. The results showed that the fruit fly was present all year round in Xishuangbanna. Its population remained at a lower level from November to February, and increased from March until it reached a peak in June or July, depending on the rainfall that year. Afterward, the fly population declined remarkably until October. Temperature, rainfall, and host fruits were major factors comprehensively influencing the population fluctuation. The monthly mean temperature was in a range of temperatures suitable for development and reproduction of the fly. But the monthly mean minimum temperature from December to February was lower than the suitable temperature range, which was suggested a possible reason for the lower populations in winter months. Rainfall was another essential factor influencing the population fluctuations. The population was depressed when the monthly rainfall amount was lower than 50 mm, but increased when rainfall ranged from 100 mm to 200 mm. When the monthly rainfall amount was higher than 250 mm, the fruit fly population was reduced remarkably. The heavy rain in July and August explained the decreasing population. Mango, orange, pear, longan, and peach were found to be the main host species of the fly in Xishuangbanna. Among them, mango and longan were most preferred by the fly. Therefore, the planted areas, fruiting period, and production exerted essential effects on the fly population fluctuations, which were regarded as another major factor influencing the fly population in that area. Briefly, temperature, monthly rainfall, and the host species, through the way of their functions, the influence strength, as well as the period that they occurred comprehensively impacted the population fluctuations of the fruit fly in Xishuangbanna.