Quality Evaluation of the 0.01° Multi-Source Fusion Precipitation Product and Its Application in Extreme Precipitation Event

High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the development of modern meteorological business. The 0.01° multi-source fusion precipitation product is the latest precipitation product developed by the National Meteorological Information Center to meet the above needs. Taking the hourly precipitation observation data of 2400 national automatic stations as the evaluation base, independent and non-independent test methods are used to evaluate the 0.01° multi-source fusion precipitation product in 2020. The product quality differences between the 0.01° precipitation product and the 0.05° precipitation product are compared, and their application in extreme precipitation events are analyzed. The results show that, in the independent test, the product quality of the 0.01° precipitation product and the 0.05° precipitation product are basically the same, which is better than that of each single input data source, and the product quality in winter and spring is slightly lower than that in summer, and both products have better quality in the east in China. The evaluation results of the 0.01° precipitation product in the non-independent test are far better than that of the 0.05° product. The root mean square error and the correlation coefficient of the 0.01° multi-source fusion precipitation product are 0.169 mm/h and 0.995, respectively. In the extreme precipitation case analysis, the 0.01° precipitation product, which is more consistent with the station observation values, effectively improves the problem that the extreme value of the 0.05° product is lower than that of station observation values and greatly improves the accuracy of the precipitation extreme value in the product. The 0.01° multi-source fusion precipitation product has better spatial continuity, a more detailed description of precipitation spatial distribution and a more accurate reflection of precipitation extreme values, which will better provide precipitation data support for refined meteorological services, major activity support, disaster prevention and reduction, etc.

Assessment of precipitation extremes in CMIP6 decadal hindcasts over India

<p>A skillful decadal precipitation prediction (DPP) is valuable for sustainable development, which currently face many challenges.Deriving reliable information from DPP is still a challenge because of the difficulties linked with precipitation predictions and coarse spatial resolution by General Circulation Models (GCMs) not able to be in a straight line appropriate for impact assessment.This study examines the decadal hindcast simulations of precipitation extreme over seven sub regions of India from different ocean-atmosphere coupled models from the Coupled Model Intercomparison Project(CMIP6) by applying quantile mapping approach.Each decadal hindcast consists of predictions for a 10-year period from the initial climate states of 1961 to 2014/2018 and the assessment of skill is carried out lead-wise from 1 to 10 for different season and different regions over India (both raw and bias corrected). The potential skill of precipitation extreme is examined in terms of  extreme precipitation index (EPIs) i.e.cumulative wet days (CWD), cumulative dry days (CDD), precipitation events between P1020(10 and 20 mm),P20P40(20 and 40 mm), PG40(>40 mm) and  annual maximum 1 & 5 day precipitation (Rx1day and Rx5day). The promising results revealed that the skills of DPPs are enhanced after the bias adjustment and the data product can be used as a key input for impacts assessments in the region.</p><p> </p>

Spatial and temporal variability of precipitation extreme indices in arid and semi-arid regions of Iran for the last half-century

Precipitation variability analysis, on different spatial and temporal scales, has been of great concern during the past century because of the attention given to global climate change by the scientific community. According to some recent studies, the Iranian territory has been experienced a precipitation variability, especially in the last 50 years, and the arid and semi-arid areas seem to be more affected. The present study aims to analyze precipitation extreme indices over a wide time interval and a wide area, detecting potential trends and assessing their significance. The investigation is based on a wide range of daily and multi-day precipitation statistics encompassing basic characteristics and heavy precipitation. Two different methods of trend analysis and statistical testing are applied, depending on the nature of the statistics. Linear regression is used for statistics with a continuous value range, and logistic regression is used for statistics with a discrete value range. The trends are calculated on annual and seasonal bases for the years 1951–2007. Statistical analysis of the database highlight that a clear trend signal is found with a high number of sites with a statistically significant trend. In winter, significant increases are found for all statistics related to precipitation strength and occurrence. In spring, statistically, significant increases are found only for the statistics related to heavy precipitation, whereas precipitation frequency and occurrence statistics show little systematic change. The trend signal is strongest in highlands and mountainous terrains. In autumn and summer, the heavy and basic precipitation statistics did not show statistically significant trends.

Valoração Econômica de Danos Causados por Inundações na Cidade de Manaus nos Últimos 20 Anos (1999-2018)

A cidade de Manaus, a mais populosa na Amazônia brasileira, sofre com inundações que afetam a qualidade de vida de sua população. Analisar o prejuízo causado por essa problemática pode auxiliar na tomada de decisões sobre investimentos que trarão melhorias à qualidade de vida de seus habitantes. Neste trabalho foi feita uma estimativa de danos oriundos de Eventos Extremos de Precipitação (EEP) ocorridos em residências da cidade, no período de 1999 a 2018. Os EEP foram selecionados a partir da combinação entre os dados do Instituto Nacional de Meteorologia - INMET e as notícias registradas na mídia local, resultando em um total de 31 eventos nos últimos 20 anos. Notou-se que a ocorrência dos EEP é influenciada pela posição da Zona de Convergência Intertropical (ZCIT) e pelo fenômeno La Niña. Para estimar os danos foi utilizada a Avaliação Monetária Material Meio Ambiente (AMA), que depende do cálculo do Índice de Pegada da Água (IPA). Por sua vez, o IPA foi calculado tomando por base a altura que a água alcançou após uma chuva ocorrida na cidade. De posse do valor do índice, fez-se o cálculo dos danos ocorridos nos últimos 20 anos, onde obteve-se como resultado o custo de R$ 6.905.311.148,00, um preço bastante relevante que indica perdas significativas para a população.Economic Valuation of Damage Caused by Flooding in the City of Manaus over the last 20 Years (1999-2018) A B S T R A C TThe city of Manaus, the most populous on the Brazilian Amazon, suffers with inundations that affects its inhabitants’ life quality. To analyze the negative impacts caused by this issue may help on the decision-making process about investments that will bring improvement to the citizens life quality. This paper shows an estimation of damages caused by Precipitation Extreme Events (EEP) that happened on residences of the city during the period of 1999 until 2018. The EEP were selected by the combination of data provided by the National Meteorology Institute – INMET and the reports registered on the local media, resulting in 31 events found on the last 20 years. It was noticed that the occurrence of EEP is influenced by the Intertropical Convergence Zone (ITCZ) and by the La Niña Phenomenon. In order to estimate the damages, it was used the Environment Material Monetary Assessment (AMA), which depends on the calculation of the Water Footprint Index (IPA). The IPA was calculated with the information of how height the water got from accumulating after a rain event occurred on the city. With the Index’s value it was calculated the losses occurred on the past 20 years, resulting in a cost of R$ 6,905,311,148.00, a relevant price that indicates to significant losses to the population.Keywords: Precipitation, Extreme Events, Damage Assessment.

Observed Changes in Temperature and Precipitation Extremes Over the Yarlung Tsangpo River Basin during 1970–2017

Twenty-five climate indices based on daily maximum and minimum temperature and precipitation at 15 meteorological stations were examined to investigate changes in temperature and precipitation extremes over the Yarlung Tsangpo River Basin (1970–2017). The trend-free prewhitening (TFPW) Mann–Kendall test and Pettitt’s test were used to identify trends and abrupt changes in the time series, respectively. The results showed widespread significant changes in extreme temperature indices associated with warming, most of which experienced abrupt changes in the 1990s. Increases in daily minimum and maximum temperature were detected, and the magnitude of daily minimum temperature change was greater than that of the daily maximum temperature, revealing an obvious decrease in the diurnal temperature range. Warm days and nights became more frequent, whereas fewer cold days and nights occurred. The frequency of frost and icing days decreased, while summer days and growing season length increased. Moreover, cold spell length shortened, whereas warm spell length increased. Additionally, changes in the precipitation extreme indices exhibited much less spatial coherence than the temperature indices. Spatially, mixed patterns of stations with positive and negative trends were found, and few trends in the precipitation extreme indices at individual stations were statistically significant. Generally, precipitation extreme indices showed a tendency toward wetter conditions, and the contribution of extreme precipitation to total precipitation has increased. However, no significant regional trends and abrupt changes were detected in total precipitation or in the frequency and duration of precipitation extremes.

Observed Trends and Changes in Temperature and Precipitation Extreme Indices over Myanmar

Projected increase in frequency and severity of extreme events are important threat brought by climate change. Thus, there is a need to understand the dynamics and magnitude of climate extreme at local and regional level. This study examines the patterns of annual trends and changes of extreme daily temperature and precipitation in Myanmar for the period of 1981 to 2015 using the RClimDex 1.1 software. The trends of maximum and minimum temperature show significant warming trends (p < 0.001) across Myanmar. From 2009 to 2015, the maximum temperature anomaly has continuously increased by 0.5 °C for all years except 2011. The larger rise in both maximum and minimum temperature observed after 2000 suggests that, overall, days and nights are becoming hotter for the entirety of Myanmar over this recent period. Furthermore, our works also show that the temperature extreme indices of warm days and warm nights have increased, whereas the frequency of cool days and cool nights have decreased. Our analysis also reveals that increasing trends in precipitation anomaly were not significant during 1981–2015. On the contrary, slight increasing trends towards wetter conditions were observed with a rate of 76.52 mm/decade during the study period. The other precipitation extreme indicators—namely, annual total precipitation (PRCPTOT), heavy precipitation days (R20mm), extreme wet days precipitation (R99p), and consecutive wet days (CWD)—are consistent with warming trends. Additionally, the relationship between inter-annual variability in the climate extremes indices and Oceanic Niño Index (ONI) patterns was also examined with a focus on the influence of the El Niño-Southern Oscillation (ENSO) phenomenon.