MODELING AND PREDICTING THE MONO RIVER OVERFLOW UPSTREAM OF THE NANGBETO DAM IN WEST AFRICA USING MULTIPLICATIVE DETERMINIST MODEL

The variation and non-control of the overflow of the Mono River adversely affects the performance of the Nangbetohydropower plant to the point thatitcan no longermeet the increasinglyincreaseddemand for electricity. This studypresents the development of an operational model for forecastingdaily river flows for the plants water retention. The overflow of the Mono River at the upstreamhydroelectric dam from 1991 to 2019 wasanalyzed and modeled by the deterministicprocesswith R software in order to makepredictions. First, the flow serieswasanalyzed by the ARIMA model (18, 1, 2) then by a multiplicative model afterremoving the seasonal trends fromtheseseries by the movingaveragemethod. The calculatederror of the results of said model revealsthat the deterministic model integrates the input generationprocesseswith an error of the order of . Finally, an annual flow forecasting program has been developed as a planning tool for the operation of the dam, in order to meet production needs and to plan water releases.

Recent climatology and trends in surface humidity over India for 1969-2007

Annual and seasonal trends in specific humidity, relative humidity and dry bulb temperature based upon 215 stations across India are studied. The results of trend analysis show evidence of an increase in air moisture content over India during 1969-2007 with more than 90% stations showing increasing trends in specific humidity. Climatological means of specific humidity and relative humidity for the country are 14.1 g/kg and 63.9% respectively and trends are significantly increasing for all periods except for relative humidity in monsoon season. Annual trends in specific humidity, relative humidity and dry bulb temperature are +0.23 g/kg per decade, +0.85% per decade and +0.04° C per decade respectively. Seasonal trends in specific humidity, relative humidity and dry bulb temperature are statistically significant and highest in summer (+0.30 g/kg per decade), winter (+1.49% per decade) and monsoon (+0.11° C per decade) respectively. Spatially, the increasing trends in specific humidity and relative humidity are more coherent over north, northwest, central and southeast India. Spatial patterns of trends in relative humidity and dry bulb temperature are complementary and strongly correlated. Relative humidity trends are consistently decreasing over Jammu and Kashmir and northeast India. Increasing trends in summer season relative humidity and monsoon season dry bulb temperature over large parts of the country contribute significantly to upward trend in human discomfort. The spatial patterns of discomfort index show that the aerial extent of uncomfortable conditions increases both north and westwards as season progresses from summer to monsoon.

Changes in total cloud cover over India based upon 1961-2007 surface observations

Based upon 172 well distributed surface meteorological stations over India, annual and seasonal trends in total cloud cover and associated climatic variables diurnal temperature range and rainy days are investigated for 1961-2007. The data analysis indicates a general decrease in total cloud cover over most parts of India during winter, summer and monsoon. On monthly scale, statistically significant decrease in total cloud cover has occurred during April (3% per decade), June to September (2% per decade) and December (5% per decade). Seasonally, the declining trends in total cloud cover are significant for summer and monsoon (2% per decade). Spatial analysis of trends suggests coherent decrease in total cloud cover over central India (all seasons) and south peninsula (except post monsoon). All India averaged monthly, annual and seasonal trends in diurnal temperature range and rainy days are mixed and weak. Spatially, trends in diurnal temperature range are decreasing over north and increasing over south peninsula while trends in rainy days are decreasing over large number of stations during winter and monsoon and increasing in summer and post monsoon seasons. However, the sizes of the same trend regions show considerable variability between seasons. Monsoon season total cloud cover and Nino3.4 sea surface temperature anomalies are significantly negatively correlated over all regions of the country except northeast indicating a strong relationship between them.

Trends in pluviometric precipitation and climatic water balance in the hydrographic region of Paraguaçu – BA

Trend analysis of hydroclimatic data is essential in the development of water resources management, as it can envisage changes in the pattern of behaviour, helping develop strategies for adaptation in the face of imminent climate change. This study aimed to investigate possible annual and seasonal trends in rainfall and climatological water balance in the hydrographic region of Paraguaçu - BA. From the historical series of precipitation, deficiency and water surpluses, between 1989 and 2018, two analysis scenarios were conducted: the first to verify the annual and seasonal trends of each station, using the traditional Mann-Kendall (MK) methods and Sen’s estimator; and the second for each sub-region of Paraguaçu, by comparing MK with the Innovative Trend Analysis (ITA). The results of the annual series, regardless of the methodology adopted, point to negative trends in rainfall, positive trends in deficit and negative trends in water surplus. Seasonally, in the autumn and winter seasons, generally considered to be drought, there were more trends of increasing rainfall and decreasing water deficiency. A comparison between the MK and ITA models showed that both have similar results for indicating trends in the sub-regions of Paraguaçu. However, the ITA has shown a higher number of significant trends.

15-year variability of desert dust optical depth on global and regional scales

This study aims to investigate global, regional and seasonal temporal dust changes as well as the effect of dust particles on total aerosol loading using the ModIs Dust AeroSol (MIDAS) fine-resolution dataset. MIDAS delivers dust optical depth (DOD) at fine spatial resolution (0.1∘×0.1∘) spanning from 2003 to 2017. Within this study period, the dust burden increased across the central Sahara (up to 0.023 yr−1) and Arabian Peninsula (up to 0.024 yr−1). Both regions observed their highest seasonal trends in summer (up to 0.031 yr−1). On the other hand, declining DOD trends are encountered in the western (down to −0.015 yr−1) and eastern (down to −0.023 yr−1) Sahara, the Bodélé Depression (down to −0.021 yr−1), the Thar (down to −0.017 yr−1) and Gobi (down to −0.011 yr−1) deserts, and the Mediterranean Basin (down to −0.009 yr−1). In spring, the most negative seasonal trends are recorded in the Bodélé Depression (down to −0.038 yr−1) and Gobi Desert (down to −0.023 yr−1), whereas they are in the western (down to −0.028 yr−1) and the eastern Sahara (down to −0.020 yr−1) and the Thar Desert (down to −0.047 yr−1) in summer. Over the western and eastern sector of the Mediterranean Basin, the most negative seasonal trends are computed at summer (down to −0.010 yr−1) and spring (down to −0.006 yr−1), respectively. The effect of DOD on the total aerosol optical depth (AOD) change is determined by calculating the DOD-to-AOD trend ratio. Over the Sahara the median ratio values range from 0.83 to 0.95, whereas in other dust-affected areas (Arabian Peninsula, southern Mediterranean, Thar and Gobi deserts) the ratio value is approximately 0.6. In addition, a comprehensive analysis of the factors affecting the sign, the magnitude and the statistical significance of the calculated trends is conducted. Firstly, the implications of the implementation of the geometric mean instead of the arithmetic mean for trend calculations are discussed, revealing that the arithmetic-based trends tend to overestimate compared to the geometric-based trends over both land and ocean. Secondly, an analysis interpreting the differences in trend calculations under different spatial resolutions (fine and coarse) and time intervals is conducted.