scholarly journals Systematical Evaluation of Three Gridded Daily Precipitation Products Against Rain Gauge Observations Over Central Asia

2021 ◽  
Vol 9 ◽  
Author(s):  
Tuoliewubieke Dilinuer ◽  
Junqiang Yao ◽  
Jing Chen ◽  
Yong Zhao ◽  
Weiyi Mao ◽  
...  
Keyword(s):  
Central Asia ◽  
Time Scales ◽  
Daily Precipitation ◽  
Rain Gauge ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Climatic Regions ◽  
Arid Desert ◽  
Continental Climate

Understanding the precipitation variability and extreme precipitation over arid Central Asia (CA) has largely been hampered by the lack of daily precipitation observations. The gridded precipitation datasets over CA are large discrepancies. Here, three gauge-based gridded daily precipitation products from Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Global Precipitation Climatology Center (GPCC), and Climate Prediction Center Based Analysis of Global Daily Precipitation (CPC_global) were assessed and compared with 49 rain gauge daily observations precipitation (OBS) from January 1985 to December 2015 using different time-scales over CA and different climate regimes, specifically Northern CA with temperate continental climate (NCA), Southwestern CA with dry arid desert climate (SWCA), and Southeastern CA with Mediterranean continental climate (SECA). Four accuracy indices [correlation coefficient (R), Bias, root mean square error (RMSE), and relative bias (RBias)] were employed to evaluate the performance of the three products in depicting the spatiotemporal features of precipitation variation over CA at multiple time scales (including daily, monthly, seasonal, and yearly). The mean annual and daily precipitation of OBS and three gridded products exhibit the trend of a gradual precipitation decreased from SECA to NCA and SWCA. The best overall performance was obtained for APHRODITE and GPCC for daily and annual time-scale, whereas CPC shows noticeable underestimation precipitation in SECA. The monthly precipitation depicted distinct features with a bimodal pattern with a peak in March and another in December, include the SECA and SWCA regions. In contrast, precipitation was concentrated in summer with the peak in July over the NCA region. At monthly scale terms, APHRODITE was more accurate in the wet seasons (winter and spring months) in SWCA and SECA. Additionally, GPCC has fairly better capability in summer months in NCA. Considering the spatial distribution, the bias variability was largerly in mountainous areas than in the plains. Temporally, the bias largerly in the dry seasons than in the wet seasons. At the interannual variability scale, GPCC was capable of qualitatively increasing the CA (NCA and SECA) precipitation during the last 21 years, while APHRODITE underestimated the trends. The CPC overestimated the precipitation trends over all regions. This study can serve as a reference for selecting daily precipitation products with low densities of stations, complex topographies, and similar climatic regions.

scholarly journals Assessment of the influence of bias correction on meteorological drought projections for Poland

2015 ◽  
Vol 12 (10) ◽  
pp. 10331-10377 ◽  
Author(s):  
M. Osuch ◽  
R. J. Romanowicz ◽  
D. Lawrence ◽  
W. K. Wong
Keyword(s):  
Time Scales ◽  
Bias Correction ◽  
Climate Model ◽  
Precipitation Index ◽  
Future Climate Change ◽  
Multiple Time Scales ◽  
Climate Projections ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Standard Precipitation Index

Abstract. Possible future climate change effects on drought severity in Poland are estimated for six ENSEMBLE climate projections using the Standard Precipitation Index (SPI). The time series of precipitation represent six different RCM/GCM run under the A1B SRES scenario for the period 1971–2099. Monthly precipitation values were used to estimate the Standard Precipitation Index (SPI) for multiple time scales (1, 3, 6, 12 and 24 months) for a spatial resolution of 25 km × 25 km for the whole country. Trends in SPI were analysed using a Mann–Kendall test with Sen's slope estimator for each 25 km × 25 km grid cell for each RCM/GCM projection and timescale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded E-OBS precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the time scale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarise the mechanisms underlying the influence of bias correction on trends using a simple example of a linear bias correction procedure. In the case of precipitation the bias correction by QM does not change the direction of changes but can change the slope of trend. We also have noticed that the results for the same GCM, with differing RCMs, are characterized by similar pattern of changes, although this behaviour is not seen at all time scales and seasons.

scholarly journals Classificação de Eventos Extremos de Precipitação em Múltiplas Escalas de Tempo em Belém-PA: Utilizando o Índice de Precipitação Normalizada (Classification of Extreme Precipitation Events in Multiple Time Scales in Belém, PA: Using the Standardized ...)

2014 ◽  
Vol 7 (4) ◽  
pp. 628
Author(s):  
Sérgio Rodrigo Quadros dos Santos ◽  
Celia Campos Braga ◽  
Ana Paula Paes dos Santos ◽  
Thamiris Luiza De Oliveira Brandão Campos ◽  
José Ivaldo Barbosa de Brito
Keyword(s):  
Time Scales ◽  
Extreme Event ◽  
Standardized Precipitation Index ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Extreme Precipitation Events ◽  
The Standardized Precipitation Index ◽  
The City

O Índice de Precipitação Normalizada (SPI) é utilizado para quantificar o déficit e/ou excesso de precipitação nas múltiplas escalas de tempo. Ele tem se mostrado bastante útil no monitoramento da precipitação, principalmente pela sua flexibilidade, simplicidade de cálculo e interpretação. Desta forma este estudo tem como objetivo quantificar os eventos extremos secos e chuvosos na cidade de Belém-PA nas escalas de tempo de 3, 6 e 12 meses por meio do SPI. Para isto, utilizaram-se dados mensais de precipitação provenientes da estação meteorológicas de superfície do INMET no período de 1980-2011. Os resultados mostraram que a escala de tempo do SPI é inversamente proporcional à frequência dos eventos de chuva e seca. Os SPIs 3,6 e 12 mostraram mais eventos secos do que chuvosos para a cidade e a maioria dos eventos de chuva e seca estavam associados, principalmente, ao fenômeno ENOS. ABSTRACT The Standardized Precipitation Index (SPI) is used to quantify the deficit/ excess rainfall at multiple time scales. It has been very useful in monitoring of precipitation, mainly because of its flexibility, ease of calculation and interpretation. Thus this study aims to quantify the extreme wet and dry events in the city of Belém-PA in time scales of 3, 6 and 12 months by SPI. For this, we used monthly precipitation data from meteorological station at the INMET in the period 1980-2011. The results show that the timescale of the SPI is inversely proportional to the frequency of rain and dry events. The SPIs 3.6 and 12 showed driest events that rainy events to the city and most of the rainfall and drought events were associated, mainly, with the ENSO phenomenon. Key Words: Belem; SPI; Extreme Event.   

scholarly journals Climate change effects on drought severity

2008 ◽  
Vol 17 ◽  
pp. 23-29 ◽  
Author(s):  
A. Loukas ◽  
L. Vasiliades ◽  
J. Tzabiras
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Geographical Information ◽  
Multiple Time Scales ◽  
Drought Severity ◽  
Multiple Time ◽  
Monthly Precipitation ◽  
Climate Change Effects

Abstract. This paper evaluates climate change effects on drought severity in the region of Thessaly, Greece. The Standardized Precipitation Index (SPI) has been used for estimation of drought severity. A geographical information system is applied for the division of Thessaly region to twelve hydrological homogeneous areas based on their geomorphology. Mean monthly precipitation values from 50 precipitation stations of Thessaly for the hydrological period October 1960–September 1990 were used for the estimation of mean areal precipitation. These precipitation timeseries have been used for the estimation of Standardized Precipitation Index (SPI) for multiple time scales (1-, 3-, 6-, 9-, and 12-months) for each sub-basin or area. The outputs of Global Circulation Model CGCM2 were applied for two socioeconomic scenarios, namely, SRES A2 and SRES B2 for the assessment of climate change impact on droughts. The GCM outputs were downscaled to the region of Thessaly using a statistical methodology to estimate precipitation time series for two future periods 2020–2050 and 2070–2100. A method has been proposed for the estimation of annual cumulative drought severity-time scale-frequency curves. These curves integrate the drought severity and frequency for various types of drought. The SPI timeseries and annual weighted cumulative drought severity were estimated and compared with the respective timeseries and values of the historical period 1960–1990. The results showed that the annual drought severity is increased for all hydrological areas and SPI time scales, with the socioeconomic scenario SRES A2 being the most extreme.

SOME REMARKS ON THE MULTIPLE TIME SCALES OF DIFFUSION IN MINERALS AND MELTS

2018 ◽  
Author(s):  
Yan Liang ◽  
◽  
Daniele J. Cherniak ◽  
Chenguang Sun
Keyword(s):  
Time Scales ◽  
Multiple Time Scales ◽  
Multiple Time

scholarly journals Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World

2019 ◽  
Vol 11 (4) ◽  
pp. 1163 ◽  
Author(s):  
Melissa Bedinger ◽  
Lindsay Beevers ◽  
Lila Collet ◽  
Annie Visser
Keyword(s):  
Climate Change ◽  
Human Nature ◽  
Climate Change Adaptation ◽  
Time Scales ◽  
Spatial Scales ◽  
Local Context ◽  
Multiple Time Scales ◽  
Future Research ◽  
Multiple Time ◽  
Systems Research

Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.

scholarly journals A multistate model incorporating estimation of excess hazards and multiple time scales

2021 ◽  
Vol 40 (9) ◽  
pp. 2139-2154
Author(s):  
Caroline E. Weibull ◽  
Paul C. Lambert ◽  
Sandra Eloranta ◽  
Therese M. L. Andersson ◽  
Paul W. Dickman ◽  
...  
Keyword(s):  
Time Scales ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Multistate Model

scholarly journals Scale-dependent intrinsic entropies of complex time series

2016 ◽  
Vol 374 (2065) ◽  
pp. 20150204 ◽  
Author(s):  
Jia-Rong Yeh ◽  
Chung-Kang Peng ◽  
Norden E. Huang
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Spatial Scales ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Complex Time ◽  
Multi Scale ◽  
Mode Decomposition ◽  
Simulated Time ◽  
Simulated Time Series

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal’s complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease.

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