scholarly journals Temporal and Spatial Variations of Precipitation Change from Southeast to Northwest China during the Period 1961–2017

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2622
Author(s):  
Zhu Li ◽  
Honghu Liu
Keyword(s):  
Daily Precipitation ◽  
Global Climate ◽  
Heavy Rain ◽  
Northwest China ◽  
Annual Rainfall ◽  
Trend Test ◽  
Spatiotemporal Variations ◽  
Light Rain ◽  
Daily Precipitation Data ◽  
Northwest Region

Global climate change is significant, and the spatiotemporal variations of precipitation associated with it are pronounced. Based on the daily precipitation data from 10 weather stations located from southeast to northwest across China from 1961–2017, the Mann–Kendall trend test was generally applied to analyze the spatiotemporal variations of precipitation. The factors influencing the precipitation changes were investigated. The results revealed that (1) the annual, summer, and winter rainfall amount (RA) exhibited increasing rates of 16.36, 12.31, and 2.49 mm/10 year, respectively. The change rates of annual rainfall days (RD) were 2.68 day/10 year in the northwest region and −1.88 day/10 year in the southeast. The annual and seasonal daily precipitation on rainy days (RP) exhibited an increasing trend. (2) All of the RA, RD, and RP values initially increased, then decreased, and then slightly increased from Southeast to Northwest China. These results proved that the RA increased with the increase of light rain in Northwest China and heavy rain in Southeast China. In addition, changes in the monsoon have altered the rate at which RA, RD, and RP vary with distance from the sea. These findings may help to provide suggestions for the rational spatial utilization of water resources in China.

scholarly journals Spatial and Temporal Patterns of Rainfall Erosivity in the Tibetan Plateau

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 200 ◽  
Author(s):  
Zhijia Gu ◽  
Detai Feng ◽  
Xingwu Duan ◽  
Kuifang Gong ◽  
Yawen Li ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Tibetan Plateau ◽  
Global Climate ◽  
Summer Rainfall ◽  
Annual Rainfall ◽  
Trend Test ◽  
Rainfall Erosivity ◽  
The Tibetan Plateau ◽  
Spatial And Temporal Patterns ◽  
Daily Precipitation Data

The Tibetan Plateau is influenced by global climate change which results in frequent melting of glaciers and snow, and in heavy rainfalls. These conditions may increase the risk of soil erosion, but prediction is not feasible due to scarcity of rainfall data in the high altitudes of the region. In this study, daily precipitation data from 1 January 1981 to 31 December 2015 were selected for 38 meteorological stations in the Tibetan Plateau, and annual and seasonal rainfall erosivity were calculated for each station. Additionally, we used the Mann–Kendall trend test, Sen’s slope, trend coefficient, and climate tendency rate indicators to detect the temporal variation trend of rainfall erosivity. The results showed that the spatial distribution of rainfall erosivity in the Tibetan Plateau exhibited a significant decreasing trend from southeast to northwest. The average annual rainfall erosivity is 714 MJ·mm·ha−1·h−1, and varies from 61 to 1776 MJ·mm·ha−1·h−1. Rainfall erosivity was mainly concentrated in summer and autumn, accounting for 67.5% and 18.5%, respectively. In addition, annual, spring, and summer rainfall erosivity were increasing, with spring rainfall erosivity highly significant. Temporal and spatial patterns of rainfall erosivity indicated that the risk of soil erosion was relatively high in the Hengduan mountains in the eastern Tibetan Plateau, as well as in the Yarlung Zangbo River Valley and its vicinity.

scholarly journals Spatio-temporal evolution characteristics of precipitation in the north and south of Qin-ba Mountain area in recent 43 years

2020 ◽  
Vol 13 (17) ◽  
Author(s):  
Zhigang Cheng ◽  
Xiaoxiao Chen ◽  
Yueyue Zhang ◽  
Liya Jin
Keyword(s):  
Heavy Rain ◽  
Kendall Test ◽  
Mountain Range ◽  
Mountain Area ◽  
Light Rain ◽  
Precipitation Concentration ◽  
The North ◽  
Grade Classification ◽  
Daily Precipitation Data ◽  
North And South

Abstract Using the daily precipitation data at 89 stations during 1975–2017 in the Qin-ba Mountain area, variation characteristics of different-grade precipitation in the north and south of the Qin-ba Mountain area are analyzed by the linear regression, Mann-Kendall test, and correlation analysis, based on the precipitation grade classification standard proposed by Dai Aiguo and the division of the geo-ecological boundary in mountain range presented by Kang Muyi. The results are as follows: (1) Light rain occurs most frequently, and the percentage of light rain in the north is twice that of the southern region. Rainstorms are the most rare. Precipitation above 800 mm mainly occurs south of the study area, and the result is consistent with the boundary between the north and south of the precipitation. (2) The beginning of precipitation mainly occurs in early April. The high precipitation concentration (PCD) in the north is an important reason for the debris flow disaster. The north-south precipitation concentration period (PCP) is about 1 month ahead of the central part. (3) In the past 43 years, the overall precipitation in the Qin-ba Mountain area has shown a decreasing trend, with the frequency of light rain and the percentage of heavy rain decreasing year by year. (4) The frequency of light rain is negatively correlated with other frequencies. In addition, the fewer days of precipitation, the later the precipitation concentration period (PCP) occurs, which means that the disaster occurs later.

scholarly journals Changes in Climate Extremes over North Thailand, 1960–2099

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Mohammad Badrul Masud ◽  
Peeyush Soni ◽  
Sangam Shrestha ◽  
Nitin K. Tripathi
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Annual Rainfall ◽  
Trend Test ◽  
Daily Maximum ◽  
Climate Extreme ◽  
The Future ◽  
North Thailand ◽  
Extreme Indices

This study analyzes 24 climate extreme indices over North Thailand using observed data for daily maximum and minimum temperatures and total daily rainfall for the 1960–2010 period, and HadCM3 Global Climate Model (GCM) and PRECIS Regional Climate Model simulated data for the 1960–2100 period. A statistical downscaling tool is employed to downscale GCM outputs. Variations in and trends of historical and future climates are identified using the nonparametric Mann-Kendall trend test and Sen’s slope. Temperature extreme indices showed a significant rising trend during the observed period and are expected to increase significantly with an increase in summer days and tropical nights in the future. A notable decline in the number of cool days and nights is also expected in the study area while the number of warm days and nights is expected to increase. There was an insignificant decrease in total annual rainfall, number of days with rainfall more than 10 and 20 mm. However, the annual rainfall is projected to increase by 9.65% in the future 2011–2099 period compared to the observed 1960–2010 period.

scholarly journals Precipitation downscaling using random cascades: a case study in Italy

2010 ◽  
Vol 26 ◽  
pp. 39-44 ◽  
Author(s):  
B. Groppelli ◽  
D. Bocchiola ◽  
R. Rosso
Keyword(s):  
Climate Model ◽  
Daily Precipitation ◽  
Spatial Clustering ◽  
Global Climate ◽  
Global Climate Model ◽  
Expectation Maximization Algorithm ◽  
Recursive Estimation ◽  
Climatic Forcing ◽  
Daily Precipitation Data ◽  
Spatial Correlation Structure

Abstract. We present a Stochastic Space Random Cascade (SSRC) approach to downscale precipitation from a Global Climate Model (hereon, GCMs) for an Italian Alpine watershed, the Oglio river (1440 km2). The SSRC model is locally tuned upon Oglio river for spatial downscaling (approx. 2 km) of daily precipitation from the NCAR Parallel Climate Model. We use a 10 years (1990–1999) series of observed daily precipitation data from 25 rain gages. Scale Recursive Estimation coupled with Expectation Maximization algorithm is used for model estimation. Seasonal parameters of the multiplicative cascade are accommodated by statistical distributions conditioned upon climatic forcing, based on regression analysis. The main advantage of the SSRC is to reproduce spatial clustering, intermittency, self-similarity of precipitation fields and their spatial correlation structure, with low computational burden.

scholarly journals Indices of trends of climatic changes for the states of the Bahia and Sergipe by means of daily precipitacion indices and its relation with SST'S of the Pacific and Atlantic

2011 ◽  
Vol 26 (4) ◽  
pp. 541-554 ◽  
Author(s):  
Winícius dos Santos Araújo ◽  
José Ivaldo Barbosa de Brito
Keyword(s):  
Climate Changes ◽  
Daily Precipitation ◽  
Global Climate ◽  
Precipitation Data ◽  
Global Climate Changes ◽  
The Pacific ◽  
Daily Precipitation Data ◽  
Annual Scale ◽  
Relationship Of ◽  
Sst Anomalies

The objective of this study was to investigate statistically the precipitation variability in annual scale from the states of the Bahia and Sergipe using daily precipitation data. From that, indexes of detection of climate changes were calculated to evaluate the relationship of the most significant indexes with the sea surface temperature (SST) anomalies of the Pacific and Atlantic oceans. The daily precipitation data used were for a period of 45 years of 75 meteorological stations supplied by the old net of the SUDENE available in the DSA and data of the of the SST anomalies obtained from NOAA. Influence of SST of the Pacific and Atlantic oceans on the precipitation of the studied area is evidenced. A decrease of CWD was verified; increase was observed in the number days with rain; therefore, the amount of annual total precipitation increased. Several stations presented positive or negative tendencies in all examined indexes, consequently, they are also related to regional aspects. Therefore, it is not possible to affirm that the climate alterations noted in the study area are due to the global climate changes.

scholarly journals Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm

2019 ◽  
Vol 12 (1) ◽  
pp. 71 ◽  
Author(s):  
Simone Lolli ◽  
Gemine Vivone ◽  
Jasper R. Lewis ◽  
Michaël Sicard ◽  
Ellsworth J. Welton ◽  
...  
Keyword(s):  
Climate Models ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Heavy Rain ◽  
Detection Algorithm ◽  
Processing Technique ◽  
Global Climate Models ◽  
Mitigation Strategies ◽  
Image Processing Technique ◽  
Light Rain

Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for low-intensity precipitation) within global scale models is crucial. In addition to improving our modeling of the hydrological cycle, this will reduce the associated uncertainty of global climate models in correctly forecasting future scenarios, and will enable the application of mitigation strategies. In this manuscript we present a proof of concept algorithm to automatically detect precipitation from lidar measurements obtained from the National Aeronautics and Space Administration Micropulse lidar network (MPLNET). The algorithm, once tested and validated against other remote sensing instruments, will be operationally implemented into the network to deliver a near real time (latency <1.5 h) rain masking variable that will be publicly available on MPLNET website as part of the new Version 3 data products. The methodology, based on an image processing technique, detects only light precipitation events (defined by intensity and duration) such as light rain, drizzle, and virga. During heavy rain events, the lidar signal is completely extinguished after a few meters in the precipitation or it is unusable because of water accumulated on the receiver optics. Results from the algorithm, in addition to filling a gap in light rain, drizzle, and virga detection by radars, are of particular interest for the scientific community as they help to fully characterize the aerosol cycle, from emission to deposition, as precipitation is a crucial meteorological phenomenon accelerating atmospheric aerosol removal through the scavenging effect. Algorithm results will also help the understanding of long term aerosol–cloud interactions, exploiting the multi-year database from several MPLNET permanent observational sites across the globe. The algorithm is also applicable to other lidar and/or ceilometer network infrastructures in the framework of the Global Aerosol Watch (GAW) aerosol lidar observation network (GALION).

scholarly journals Assessing the Potential Impacts of Climate Changes on Rainfall and Evapotranspiration in the Northwest Region of Bangladesh

Climate ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 94 ◽  
Author(s):  
Fazlul Karim ◽  
Mohammed Mainuddin ◽  
Masud Hasan ◽  
Mac Kirby
Keyword(s):  
Climate Models ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Climate Models ◽  
Annual Rainfall ◽  
Emission Scenarios ◽  
Rabi Season ◽  
Kharif Season ◽  
Almost All ◽  
Northwest Region

Changes in the natural climate is a major concern for food security across the world, including Bangladesh. This paper presents results from an analysis on quantitative assessment of changes in rainfall and potential evapotranspiration (PET) in the northwest region of Bangladesh, which is a major agricultural hub in the country. The study was conducted using results from 28 global climate models (GCMs), based on IPCC’s 5th assessment report (AR5) for two emission scenarios. Projections were made over the period of 2045 to 2075 for 16 administrative districts in the study area, and the changes were estimated at annual, seasonal and monthly time scale. More projections result in an increase in rainfall than decrease, while almost all projections show an increase in PET. Although annual rainfall is generally projected to increase, some projections show a decrease in some months, especially in December and January. Across the region, the average change projected by the 28 GCMs for the moderate emission was an increase of 235 mm (12.4%) and 44 mm (3.4%) for rainfall and PET, respectively. Increases in rainfall and PET are slightly higher (0.6% and 0.2%, respectively) under high emission scenarios. Increases in both rainfall and PET were projected for two major cropping seasons, Kharif (May-Oct) and Rabi (Nov-Apr). Projections of rainfall show increase in the range of 160 to 250 mm (with an average of 200 mm) during the Kharif season. Although an increase is projected in the Rabi season, the amount is very small (~10mm). It is important to note that rainfall increases mostly in the Kharif season, but PET increases for both Kharif and Rabi seasons. Contrary to rainfall, increase in PET is higher during Rabi season. This information is crucial for better adaptation under increased water demand for agricultural and domestic use.

scholarly journals High-Resolution North Sulawesi Drought Hazzard Mapping Based on Consecutive Dry Days (CDD)

2021 ◽  
Vol 893 (1) ◽  
pp. 012018
Author(s):  
A M Setiawan ◽  
A A Syafrianno ◽  
R Rahmat ◽  
Supari
Keyword(s):  
High Resolution ◽  
Global Climate ◽  
Annual Rainfall ◽  
Hazard Map ◽  
The North ◽  
North Sulawesi ◽  
Drought Hazard ◽  
Geostatistical Approach ◽  
Daily Precipitation Data ◽  
Consecutive Dry Days

Abstract North Sulawesi is one of the Province in northern Indonesia with high spatial annual rainfall variations and influenced by global climate anomaly that can lead to extreme events and disaster occurrence, such as flood, landslide, drought, etc. The purpose of this study is to generate high-resolution meteorological hazard map based on long-term historical consecutive dry days (CDD) over the North Sulawesi region. CDD was calculated based on observed daily precipitation data from Indonesia Agency for Meteorology, Climatology, and Geophysics (BMKG) surface observation station network (CDDobs) and the daily-improved Climate Hazards group Infrared Precipitation with Stations (CHIRPS) version 2.0 (CDDCHIRPS) during 1981 – 2010 period. The Japanese 55-year Reanalysis (JRA-55) data obtained from iTacs (Interactive Tool for Analysis of the Climate System) with the same time scale period also used to explain physical – dynamical atmospheric properties related to drought hazard over this region. The Geostatistical approach using regression kriging method was applied as spatial interpolation technique to generate high resolution gridded (0.05° × 0.05°) drought hazard map. This method combines a regression of CDDobs as dependent variable (target variable) on CDDCHIRPS as predictors with kriging of the prediction residuals. The results show that most of the areas were categorized as medium drought hazard level with CDD values ranging from 80-100 days. Meanwhile, small islands around main Sulawesi island such as Sangihe and Karakelong island are dominated by low drought hazard levels with CDD values ranging from 50-60 days. The highest levels of drought hazard area are located in South Bolaang Mongondow Regency.

scholarly journals Microphysical Characteristics of Rainfall Observed by a 2DVD Disdrometer during Different Seasons in Beijing, China

2021 ◽  
Vol 13 (12) ◽  
pp. 2303
Author(s):  
Li Luo ◽  
Jia Guo ◽  
Haonan Chen ◽  
Meilin Yang ◽  
Mingxuan Chen ◽  
...  
Keyword(s):  
Rain Rate ◽  
Heavy Rain ◽  
Occurrence Frequency ◽  
Total Rainfall ◽  
Axis Ratio ◽  
Seasonal Differences ◽  
Mean Values ◽  
Light Rain ◽  
Beijing China ◽  
Maximum Occurrence

The seasonal variations of raindrop size distribution (DSD) and rainfall are investigated using three-year (2016–2018) observations from a two-dimensional video disdrometer (2DVD) located at a suburban station (40.13°N, 116.62°E, ~30 m AMSL) in Beijing, China. The annual distribution of rainfall presents a unimodal distribution with a peak in summer with total rainfall of 966.6 mm, followed by fall. Rain rate (R), mass-weighted mean diameter (Dm), and raindrop concentration (Nt) are stratified into six regimes to study their seasonal variation and relative rainfall contribution to the total seasonal rainfall. Heavy drizzle/light rain (R2: 0.2~2.5 mm h−1) has the maximum occurrence frequency throughout the year, while the total rainfall in summer is primarily from heavy rain (R4: 10~50 mm h−1). The rainfall for all seasons is contributed primarily from small raindrops (Dm2: 1.0~2.0 mm). The distribution of occurrence frequency of Nt and the relative rainfall contribution exhibit similar behavior during four seasons with Nt of 10~1000 m−3 registering the maximum occurrence and rainfall contributions. Rainfall in Beijing is dominated by stratiform rain (SR) throughout the year. There is no convective rainfall (CR) in winter, i.e., it occurs most often during summer. DSD of SR has minor seasonal differences, but varies significantly in CR. The mean values of log10Nw (Nw: mm−1m−3, the generalized intercept parameter) and Dm of CR indicate that the CR during spring and fall in Beijing is neither continental nor maritime, at the same time, the CR in summer is close to the maritime-like cluster. The radar reflectivity (Z) and rain rate (?) relationship (Z = ?R?) showed seasonal differences, but were close to the standard NEXRAD Z-R relationship in summer. The shape of raindrops observed from 2DVD was more spherical than the shape obtained from previous experiments, and the effect of different axis ratio relations on polarimetric radar measurements was investigated through T-matrix-based scattering simulations.

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