Extent of diurnal cycle of rainfall and its intra seasonal variation over coastal Tamil Nadu during north east monsoon season

The diurnal variation of north east monsoon rainfall of coastal Tamil Nadu represented by four coastal stations Chennai Nungambakkam (Nbk), Chennai Meenambakkam (Mbk), Nagapattinam (Npt) and Pamban (Pbn) was studied in detail based on hourly rainfall data of rainy days only, for the period 1 Oct-31 Dec for the 47/48 year period 1969-2016/2017. Mean Octet rainfall and its anomaly were computed for the 8 octets 00-03,…., 21-24 hrs of the day and the anomaly was tested for statistical significance. Various analysis for the individual months of Oct, Nov, Dec and the entire period Oct-Dec were separately conducted. The basic technique of evolutionary histogram analysis supplemented by harmonic analysis of octet mean rainfall anomaly was used to detect the diurnal cycle signal. Two indices named as diurnal variation of rainfall index and coefficient of mean absolute octet rainfall anomaly representing the intensity of diurnal variation in dimensionless numbers were defined, computed and interpreted. The analysis based on the above techniques revealed that the diurnal signal which shows an early morning maximum and late afternoon minimum of octet rainfall is well defined in Oct, decreases in Nov and further decreases in Dec for all the 4 stations. Though the diurnal variation manifests a well defined pattern in Dec the signal is not statistically significant in most cases. For Nbk and Mbk there is a weak secondary peak of octet rainfall anomaly occurring in the forenoon and afternoon respectively in Oct and Dec suggesting the presence of semi-diurnal variation of rainfall. Stationwise, the diurnal signal is most well defined for each month/season in Pbn followed by Npt, Nbk and then Mbk. The physical causes behind the diurnal signal and its decrease as the north east monsoon season advances from Oct to Dec have been deliberated. The well known feature of nocturnal maximum of oceanic convection influencing a coastal station with maritime climate and the higher saturation at the lower levels of the upper atmosphere in the early morning hours have been advanced as some of the causes. For the much more complex feature of decrease of diurnal signal with the advancement of the season, the decrease of minimum surface temperature over coastal Tamil Nadu from Oct to Dec causing an early morning conceptual land breeze has been shown as one of the plausible causes based on analysis of temperature and wind. Scope for further work based on data from automatic weather stations, weather satellites and Doppler Weather Radars has been discussed.

Time-series analysis and statistical forecasting of daily rainfall in Kupang, East Nusa Tenggara, Indonesia: a pilot study

This pilot study presents a novel statistical time-series approach for analyzing daily rainfall data in Kupang, East Nusa Tenggara, Indonesia. By using the piecewise cubic hermite interpolation algorithm, we succeeded in filling in the null values in the daily rainfall time series. We then analyzed the monthly average and its pattern using the continuous wavelet transform (CWT) algorithm, which shows the strong annual pattern of rainfall in this region. In addition, we use the rainfall anomaly index (RAI) function to standardize daily rainfall as an indicator of dry/wet conditions in this region. Then we also use the daily RAI time-series objects from 1978 to 2020 for modeling and predicting daily RAI over the next year. The result is the root mean squared error (RMSE) of 0.8424041040593219. This Prophet model is also able to capture the linear trend of increasing drought throughout the study time period and the annual pattern of wet/dry conditions which is in accordance with previous study by Aldrian and Susanto (2003).

Recent Climate Change in the Lake Kyoga Basin, Uganda: An Analysis Using Short-Term and Long-Term Data with Standardized Precipitation and Anomaly Indexes

Climate change (CC) is now a global challenge due to uncertainties on the drivers and the multifaceted nature of its impacts. It impacts many sectors such as agriculture, water supply, and global economies through temperature and precipitation, affecting many livelihoods. Although there are global, regional, and national studies on CC, their application to determine local CC occurence mitigation and adaptation measures is not ideal. Therefore, this study aimed to determine climate change trends in Lake Kyoga Basin using standardized precipitation and anomaly indexes. Short-term (39 years, 1981–2020) and long-term (59 years, 1961–2020) monthly data from eight strategic meteorological stations were acquired from the Uganda National Meteorological Authority and supplemented with satellite and model reanalysis climate datasets. Change in precipitation was determined by SPI-6, while SAI determined change in temperature. The Mann–Kendall test was used to determine the trend significance. Whereas two (Serere and Lira) long-term data stations showed significant changes in precipitation, all the short-term data stations showed a significant increasing trend. Decadal relative rainfall anomaly increased from 85.6–105 in 1981–1990 to 92.0–120.9 in 2011–2020, while mean temperature anomaly increased from 0.2–0.6 °C to 1.0–1.6 °C in the same period. The frequency of severe wet weather events was more than for dry weather events in many stations, indicating an increase in precipitation. Maximum, mean, and minimum temperatures increased, with resultant warmer nights. The findings showed that the Lake Kyoga basin is experiencing climate change, with both temperature and rainfall increasing spatially and temporarily. Climate change affects agriculture, which is the main economic activity, and causes the destruction of infrastructure from floods, landslides, and mudslides. The results of this study are helpful in pointing out climate change-affected areas, and hence for designing mitigation and adaption strategies for local communities by policy and decision-makers from relevant stakeholders.

An alternative index to NINO3.4 for predicting monthly rainfall anomaly in East Java

ENSO and NINO3.4 index are known to have some relation with Indonesian monthly rainfall anomaly. There is a gap between scientific studies on one hand and forecasting operational problems on the other hand since previous studies are not giving enough attention to the N+1,2,3 concept. The concept is about giving three next month rainfall anomaly prediction rather than connecting ENSO index with three-monthly rainfall anomaly. Here we propose an alternative index for ENSO. The median of categorical gridded rainfall anomaly of East Java is used as a general representation. Plots of correlation between the median and anomaly sea surface temperature from ReynSmithOIv2 are used to determine locus candidate to be compared with NINO3.4. The Near Maritime Continent (NMC) index is selected and proven to have a significant average difference in correlation between based on bootstrap technique. Verification of prediction used in this study is simulation-based and only uses binary hit-miss final result. Prediction is generated by simple linear regression with three lag times (2,3, and 4). Verification based on three categories shows that NMC’s hits are higher than NINO.34 in lag-2 and lag-3. In lag-2, NMC’s verification is 57.5% compared to only 38.7% for NINO3.4. However, NINO3.4 is a still better predictor in lag-4. Radar charts of monthly verifications are also developed.

Trend Analysis of Temperature and Rainfall across Agro Climatic Zones of Karnataka-A Semi Arid State in India

The study was carried out for ten Agro climatic zones in Karnataka state in India. The temperature and rainfall data were used for analysis from 1979-2019 which is about 40 years. Understanding spatiotemporal rainfall pattern, Rainfall Anomaly Index which is drought indicator technique was used to classify the positive and negative severities in rainfall anomalies. The RAI ranges below 0.2 are considered as dry zone. The analysis resulted that, all zones are falls in category of dry zone with range of 0.2 to 0.4. For past five years, North Eastern Transition Zone was noted maximum times falling in the range of RAI below 0.2 and near to zero. Statistical techniques like linear trend estimation, R square was used for trend estimation across annual, seasonal to identify the variation in the temperature across different zones. The meaningful statistically significant achieves when there is r2≥0.65 and p≤0.05. It was analysed that, hilly Zone experienced decreased trend in both minimum and maximum temperature in all seasons which ultimately reflected in annual temperature to decrease with high R square values.

The Impact of the Interaction between Madden-Julian Oscillation and Cold Surge, on Rainfall over Western Indonesia

The Madden-Julian Oscillation and Cold Surge phenomena have been known to cause increased rainfall, with the capacity to trigger hydrometeorological disasters, in western Indonesia. However, further investigations are required regarding the interaction between these phenomena on rainfall pattern. Therefore, this study aims to analyze the interaction between MJO and CS over western Indonesia, particularly by using land-based rainfall observation data from multiple stations, as previous studies were dominated by the use of gridded data from remote observations. This study utilized in-situ observation data obtained from 4329 weather observations and rain stations between 1989 and 2018. Subsequently, quality control performed based on data availability exceeding 70% over a 30-year period resulted in 303 selected stations to be used for further analysis. Meanwhile, the RMM index, as well as reanalysis data of mean sea level pressure and 925 hPa meridional wind, were also applied for MJO and CS identification. According to the composite analysis, the effect of CS on MJO phases tends to increase precipitation by about 50%, over western Indonesia, with maximum increase ranging from 200 to 400% over the northeastern coast of Sumatra, around Karimata Strait (Riau Islands and West Kalimantan), as well as the northern coast of Java. These areas are exposed to the sea and have direct access to the wind-terrain interaction. In addition, the highest rainfall anomaly due to the MJO-CS interaction occurs around Karimata Strait, followed by northern Sumatra and Java, with spatially averaged rainfall anomaly reaching 5 mm/day over the area.

Minor Seanonal Rainfall Variability over Southern Ghana

Rainfall variability has resulted in extreme events like devastating floods and droughts which is the main cause of human vulnerability to precipitation in West Africa. Attempts have been made by previous studies to understand rainfall variability over Ghana but these have mostly focused on the major rainy season of April-July, leaving a gap in our understanding of the variability in the September-November season which is a very important aspect of the Ghanaian climate system. The current study seeks to close this knowledge gap by employing statistical tools to quantify variabilities in rainfall amounts, rain days, and extreme precipitation indices in the minor rainfall season over Ghana. We find extremely high variability in rainfall with a Coefficient of variation (CV) between 25.3% and 70.8%, and moderate to high variability in rain days (CV=14.0% - 48.8%). Rainfall amount was found to be higher over the middle sector (262.7 mm – 400.2 mm) but lowest over the east coast (125.2 mm – 181.8 mm). Analysis of the second rainfall season using the Mankandell Test presents a non-significant trend of rainfall amount and extreme indices (R10, R20, R99p, and R99p) for many places in southern Ghana. Rainfall Anomaly Indices show that the middle sector recorded above normal precipitation which is the opposite for areas in the transition zone. The result of this work provides a good understanding of rainfall in the minor rainfall season and may be used for planning purposes.

Meteorological sub-divisions of India : Assessment of coherence, homogeneity and recommended redelineation

The data on mean rainfall and mean rainfall anomaly of the meteorological sub-divisions of India, on different time-scales, is extensively used for monitoring the progress of the monsoon as well as applications and research. As such, it is important to ensure that the sub-divisional means are meaningful representations of the rainfall and the rainfall anomaly at districts/stations within the sub-division. Hence, the criteria to be satisfied for an appropriate delineation of a meteorological sub-division are high levels of coherence and homogeneity. In this paper we present an assessment of the coherence and homogeneity of the current meteorological sub-divisions, for rainfall on the seasonal scale, by analysis of monthly district average rainfall for the period 1901-2015 during the summer monsoon for all the states, except Tamil Nadu for which June-December data are considered. Since, earlier studies have shown that some of the sub-divisions of Karnataka and Maharashtra are neither coherent nor homogeneous, the problem of redelineation of the sub-divisions of these states is first addressed. We have assumed that the number of coherent zones in a state is the same as the number of current sub-divisions. Identification of coherent zones is achieved by successive application of the K-means (KM) clustering method to the seasonal rainfall of the districts, considering correlation of seasonal rainfall between districts as a measure of similarity. For these two states we find that some of the districts are not coherent and homogeneous. So we have repeated the exercise with analysis of a dense station network. The coherent zones identified from analysis of district data as well as station data, are found to be homogeneous as well and we have recommended that they become the new sub-divisions of the states. The new sub-divisions suggested for Karnataka, which are coherent and homogeneous, are: (i) Karnataka Western coast and Ghats (which includes districts/stations in the current sub-division of Coastal Karnataka as well as some from the sub-divisions of interior Karnataka) (ii) Karnataka northern plateau and (iii) Karnataka southern plateau. Of the current sub-divisions of Maharashtra, Marathwada and Vidarbha satisfy the criteria of coherence and homogeneity and can be retained as such. The current Madhya Maharashtra sub-division does not satisfy the criteria of coherence and homogeneity. We have derived a modified version of Madhya Maharashtra by allocation of some districts/stations of Western Ghats from the existing sub-division of Madhya Maharashtra to the existing sub-division of Konkan and Goa to generate a modified version of Konkan and Goa. These modified versions are coherent and homogeneous. Thus the suggested sub-divisions of Maharashtra are (i) modified version of Konkan and Goa (which could have been renamed as Konkan, Ghats and Goa but we have retained the old name) and (ii) modified version of Madhya Maharashtra, along with the current sub-divisions of (iii) Marathwada and (iv) Vidarbha. We have shown that the sub-divisions of all the other states of mainland India, are homogeneous and reasonably coherent and recommend that they should be retained as such.