Differential Signal of Change Among Multiple Components of West African Rainfall

Mapping Intimacies ◽

10.21203/rs.3.rs-825136/v1 ◽

2021 ◽

Author(s):

Omon Aigbovboise Obarein ◽

Cameron C. Lee

Keyword(s):

Rainfall Intensity ◽

Climate Models ◽

Grid Point ◽

Congo Basin ◽

Annual Rainfall ◽

Reanalysis Dataset ◽

Rainfall Frequency ◽

Hourly Rainfall ◽

Long Term Changes

Abstract Rainfall components likely differ in the magnitude and direction of their long-term changes for any given location, and some rainfall components may carry a greater regional signal of change than rainfall totals. This study evaluates the magnitude of change of multiple rainfall components relative to other components, and the greatest regions of change across all rainfall components in West Africa. Hourly rainfall data from the ERA5 reanalysis dataset was used to derive twelve rainfall components, which were evaluated for long-term means, interannual variability, and long-term changes. For rainfall totals and rainfall intensity, the central Sahel is witnessing increasing trends while the western Sahel is experiencing significant decreasing trends. In general, decreasing trends predominate in the study domain, especially in the northwestern Congo Basin, where annual rainfall is decreasing by 120mm per decade. Importantly, rainfall frequency accounts for 49% of all significant grid-point trends for the whole domain. In contrast, rainfall totals account for 26% of all combined significant trends across the domain, while rainfall intensity (12.6%), rainy season length (9.5%), and seasonality (3.3%) account for the remaining signals of change. Most of the changes among the rainfall components are in the Tropical Wet and Dry regions (59% of all significant trends); the Saharan and Equatorial regions account for the least changes. This study finds evidence that rainfall frequency is changing more across the regions compared to rainfall totals and should be explored as rainfall inputs in climate models to potentially improve regional predictions of future rainfall.

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Long-term changes in annual rainfall patterns in southern Israel

Theoretical and Applied Climatology ◽

10.1007/bf00868190 ◽

1994 ◽

Vol 49 (2) ◽

pp. 59-67 ◽

Cited By ~ 35

Author(s):

T. Ben-Gai ◽

A. Bitan ◽

A. Manes ◽

P. Alpert

Keyword(s):

Annual Rainfall ◽

Long Term Changes ◽

Rainfall Patterns

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Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin

Remote Sensing ◽

10.3390/rs12040638 ◽

2020 ◽

Vol 12 (4) ◽

pp. 638 ◽

Cited By ~ 1

Author(s):

Koen Hufkens ◽

Thalès de Haulleville ◽

Elizabeth Kearsley ◽

Kim Jacobsen ◽

Hans Beeckman ◽

...

Keyword(s):

Tropical Forest ◽

Forest Cover ◽

Congo Basin ◽

Spatial And Temporal Patterns ◽

Smallholder Farming ◽

Aboveground Carbon ◽

Decadal Scale ◽

Long Term Changes ◽

The Impact

Given the impact of tropical forest disturbances on atmospheric carbon emissions, biodiversity, and ecosystem productivity, accurate long-term reporting of Land-Use and Land-Cover (LULC) change in the pre-satellite era (<1972) is an imperative. Here, we used a combination of historical (1958) aerial photography and contemporary remote sensing data to map long-term changes in the extent and structure of the tropical forest surrounding Yangambi (DR Congo) in the central Congo Basin. Our study leveraged structure-from-motion and a convolutional neural network-based LULC classifier, using synthetic landscape-based image augmentation to map historical forest cover across a large orthomosaic (~93,431 ha) geo-referenced to ~4.7 ± 4.3 m at submeter resolution. A comparison with contemporary LULC data showed a shift from previously highly regular industrial deforestation of large areas to discrete smallholder farming clearing, increasing landscape fragmentation and providing opportunties for substantial forest regrowth. We estimated aboveground carbon gains through reforestation to range from 811 to 1592 Gg C, partially offsetting historical deforestation (2416 Gg C), in our study area. Efforts to quantify long-term canopy texture changes and their link to aboveground carbon had limited to no success. Our analysis provides methods and insights into key spatial and temporal patterns of deforestation and reforestation at a multi-decadal scale, providing a historical context for past and ongoing forest research in the area.

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Long-Term Changes of Aquatic Invasive Plants and Implications for Future Distribution: A Case Study Using a Tank Cascade System in Sri Lanka

Climate ◽

10.3390/cli9020031 ◽

2021 ◽

Vol 9 (2) ◽

pp. 31

Author(s):

Champika S. Kariyawasam ◽

Lalit Kumar ◽

Benjamin Kipkemboi Kogo ◽

Sujith S. Ratnayake

Keyword(s):

Sri Lanka ◽

Climate Variability ◽

Annual Rainfall ◽

Trend Test ◽

P Value ◽

Positive Trend ◽

Cascade System ◽

Landsat Images ◽

Long Term Changes

Climate variability can influence the dynamics of aquatic invasive alien plants (AIAPs) that exert tremendous pressure on aquatic systems, leading to loss of biodiversity, agricultural wealth, and ecosystem services. However, the magnitude of these impacts remains poorly known. The current study aims to analyse the long-term changes in the spatio-temporal distribution of AIAPs under the influence of climate variability in a heavily infested tank cascade system (TCS) in Sri Lanka. The changes in coverage of various features in the TCS were analysed using the supervised maximum likelihood classification of ten Landsat images over a 27-year period, from 1992 to 2019 using ENVI remote sensing software. The non-parametric Mann–Kendall trend test and Sen’s slope estimate were used to analyse the trend of annual rainfall and temperature. We observed a positive trend of temperature that was statistically significant (p value < 0.05) and a positive trend of rainfall that was not statistically significant (p values > 0.05) over the time period. Our results showed fluctuations in the distribution of AIAPs in the short term; however, the coverage of AIAPs showed an increasing trend in the study area over the longer term. Thus, this study suggests that the AIAPs are likely to increase under climate variability in the study area.

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Tropical Rainfall Intensifies While the Doldrums Narrow

Eos ◽

10.1029/2016eo051571 ◽

2016 ◽

Vol 97 ◽

Author(s):

Sarah Stanley

Keyword(s):

Rainfall Intensity ◽

Tropical Rainfall ◽

Long Term Changes

Scientists show long-term changes in the Intertropical Convergence Zone's location, extent, and rainfall intensity.

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Estimation of the annual rainfall erosivity index based on hourly rainfall data in a tropical region

Soil and Water Research ◽

10.17221/25/2020-swr ◽

2020 ◽

Author(s):

Ming-Hsi Lee ◽

I-Ping Hsu

Keyword(s):

Kinetic Energy ◽

Soil Loss ◽

Rainfall Intensity ◽

Rainfall Data ◽

Annual Rainfall ◽

Tropical Region ◽

Rainfall Erosivity ◽

Data Set ◽

Data Accumulation ◽

Hourly Rainfall

The annual mean rainfall erosivity (R) indicates the potential soil loss caused by the precipitation and runoff and is used to predict the soil loss from agricultural hillslopes. R is calculated from rainfall stations with continuously recording rainfall databases. However, many short-term real-time rainfall databases that also relate to the rainfall intensity are not readily available around Taiwan, with the hourly rainfall data being predominantly available. The annual mean rainfall erosivity calculated by the 10-min rainfall data accumulation converted to the 30-min rainfall data (R10_30) can be estimated using the annual mean rainfall erosivity calculated by the 10-min rainfall data accumulation convert to the hourly rainfall data (R10_60) that are calculated from the kinetic energy calculated by the 10-min rainfall data accumulation converted to the hourly rainfall data (E60j). The maximum 60-min rainfall intensity calculated by the 10-min rainfall data accumulation converted to the hourly rainfall data (I60j) has been established in rainfall stations throughout southern Taiwan. The 10-min rainfall data set consists of 15 221 storm events from 2002 to 2017 monitored by 51 rainfall stations located in the tropical regions in Taiwan. According to the results of this study, the average conversion factors of the kinetic energy (1.04), rainfall erosivity (1.47), and annual mean rainfall erosivity (1.30) could be estimated based on the 10-min rainfall data.

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Assessing the sources of uncertainty associated with the calculation of rainfall kinetic energy and erosivity – application to the Upper Llobregat Basin, NE Spain

Hydrology and Earth System Sciences ◽

10.5194/hess-15-679-2011 ◽

2011 ◽

Vol 15 (3) ◽

pp. 679-688 ◽

Cited By ~ 17

Author(s):

G. Catari ◽

J. Latron ◽

F. Gallart

Keyword(s):

Kinetic Energy ◽

Temporal Variability ◽

Rainfall Intensity ◽

Spatial Scales ◽

Annual Rainfall ◽

Rainfall Erosivity ◽

Sources Of Uncertainty ◽

Eastern Pyrenees ◽

Erosion Modelling

Abstract. The diverse sources of uncertainty associated with the calculation of rainfall kinetic energy and rainfall erosivity, calculated from precipitation data, were investigated at a range of temporal and spatial scales in a mountainous river basin (504 km2) in the south-eastern Pyrenees. The sources of uncertainty analysed included both methodological and local sources of uncertainty and were (i) tipping-bucket rainfall gauge instrumental errors, (ii) the efficiency of the customary equation used to derive rainfall kinetic energy from intensity, (iii) the efficiency of the regressions obtained between daily precipitation and rainfall erosivity, (iv) the temporal variability of annual rainfall erosivity values, and the spatial variability of (v) annual rainfall erosivity values and (vi) long-term erosivity values. The differentiation between systematic (accuracy) and random (precision) errors was taken into account in diverse steps of the analysis. The results showed that the uncertainty associated with the calculation of rainfall kinetic energy from rainfall intensity at the event and station scales was as high as 30%, because of insufficient information on rainfall drop size distribution. This methodological limitation must be taken into account for experimental or modelling purposes when rainfall kinetic energy is derived solely from rainfall intensity data. For longer temporal scales, the relevance of this source of uncertainty remained high if low variability in the types of rain was supposed. Temporal variability of precipitation at wider spatial scales was the main source of uncertainty when rainfall erosivity was calculated on an annual basis, whereas the uncertainty associated with long-term erosivity was rather low and less important than the uncertainty associated with other model factors such as those in the RUSLE, when operationally used for long-term soil erosion modelling.

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Decadal changes in mean annual rainfall drive long-term changes in bush-encroached southern African savannas

Austral Ecology ◽

10.1111/aec.12358 ◽

2016 ◽

Vol 41 (6) ◽

pp. 690-700 ◽

Cited By ~ 5

Author(s):

Munyaradzi D. Shekede ◽

Amon Murwira ◽

Mhosisi Masocha ◽

Fadzai M. Zengeya

Keyword(s):

Annual Rainfall ◽

Mean Annual Rainfall ◽

Long Term Changes

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Inconsistencies between Long-Term Trends in Storminess Derived from the 20CR Reanalysis and Observations

Journal of Climate ◽

10.1175/jcli-d-12-00309.1 ◽

2013 ◽

Vol 26 (3) ◽

pp. 868-874 ◽

Cited By ~ 96

Author(s):

Oliver Krueger ◽

Frederik Schenk ◽

Frauke Feser ◽

Ralf Weisse

Keyword(s):

Twentieth Century ◽

Climate Variability ◽

Climate Models ◽

Reanalysis Dataset ◽

Northeast Atlantic ◽

Long Term Trends ◽

Storm Index ◽

Global Reanalysis ◽

Long Term Trend

Abstract Global atmospheric reanalyses have become a common tool for both validation of climate models and diagnostic studies, such as assessing climate variability and long-term trends. Presently, the Twentieth Century Reanalysis (20CR), which assimilates only surface pressure reports, sea ice, and sea surface temperature distributions, represents the longest global reanalysis dataset available covering the period from 1871 to the present. Currently the 20CR dataset is extensively used for the assessment of climate variability and trends. Here, the authors compare the variability and long-term trends in northeast Atlantic storminess derived from 20CR and from observations. A well-established storm index derived from pressure observations over a relatively densely monitored marine area is used. It is found that both variability and long-term trends derived from 20CR and from observations are inconsistent. In particular, both time series show opposing trends during the first half of the twentieth century: both storm indices share a similar behavior only for the more recent periods. While the variability and long-term trend derived from the observations are supported by a number of independent data and analyses, the behavior shown by 20CR is quite different, indicating substantial inhomogeneities in the reanalysis, most likely caused by the increasing number of observations assimilated into 20CR over time. The latter makes 20CR likely unsuitable for the identification of trends in storminess in the earlier part of the record, at least over the northeast Atlantic. The results imply and reconfirm previous findings that care is needed in general when global reanalyses are used to assess long-term changes.

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Farmers’ Perceptions of Climate Change, Long-term Variability and Trends in Rainfall in Apac District, Northern Uganda

10.21203/rs.3.rs-450998/v1 ◽

2021 ◽

Author(s):

Francis Atube ◽

Geoffrey M. Malinga ◽

Martine Nyeko ◽

Daniel M. Okello ◽

Basil Mugonola ◽

...

Keyword(s):

Climate Change ◽

Abrupt Change ◽

Smallholder Farmers ◽

Change Points ◽

Annual Rainfall ◽

The Past ◽

Rainfall Trends ◽

Long Term Changes ◽

Cropping Seasons

Abstract Background: Climate change poses a serious threat to agricultural livelihoods and food security of smallholder farmers in Sub Saharan Africa. Understanding long-term rainfall trends of variability and extremes at local scales and perceptions regarding long-term changes in climate variables is important in planning appropriate adaptation measures to climate change. This paper examines the perception of farmers in Apac district regarding long-term changes in climate variables and analyzes the trend of occurrence in seasonal and annual rainfall in Apac district, northern Uganda. A cross-sectional survey design was employed to collect data on perception of farmers regarding long-term changes in climate from 260 randomly selected small-holder farmers’ households across two sub-counties in Apac district by the administration of semi-structured questionnaires in February 2018. Monthly rainfall data sets from the Uganda Meteorological Authority (UMA) for the period 1980 to 2019 for the Apac district were also used to analyze trends of occurrences in seasonal and annual rainfall in the study area. The nonparametric Sequential Mann-Kendall (SMK) and Sequential SMK tests were employed at a 5% significance level to detect trends and abrupt change points in mean seasonal rainfall. Results: The majority of the respondents (87%) perceived a decrease in precipitation over the past 39 years. The plot of forward regression u(ti) values and backward regression u’(ti) values showed interactions indicating rainfall trends: rainfall lower and upper limits and abrupt change points in the different cropping seasons. Analysis of historical series of mean monthly and annual rainfall showed an abrupt change in rainfall in March, April, May (MAM) season in 1982. Although the September, October and November (SON) season did not show an abrupt significant change, there was a significant (p<0.05) increase in rainfall above the upper limit from 1994 to date. Conclusion: The mean seasonal rainfall for MAM and SON cropping seasons in the Apac district were highly variable from different time points within the past 39 years (1980-2019), while JJA did not realize a significant change in rainfall within the same study period. Thus, the two cropping seasons (MAM and SON) in the district experienced remarkable variations in rainfall. This, therefore, provides a basis for Government to strengthen the provision of an effective climate tailored agricultural advisory service to aid farmers’ adaptation planning at the local level and to assist smallholder farmers and land-use managers in developing effective adaptation management strategies to the effects of climate change.

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