Chapter-1 Introduction

Size: px
Start display at page:

Download "Chapter-1 Introduction"

Transcription

1 Modeling of rainfall variability and drought assessment in Sabarmati basin, Gujarat, India Chapter-1 Introduction 1.1 General Many researchers had studied variability of rainfall at spatial as well as at temporal scale relating it with certain weather parameters. Mohapatra and Mohanty (2006) studied rainfall variability over Orissa in relation to low pressure system while Munot and Kothawale (2000) worked on intra-seasonal, inter-annual and decadal scale variability in summer monsoon rainfall over India. The large scale monsoon variability with respect to El-Nino Southern Oscillation (ENSO) had been studied by Kawamura et al (2005). In most of these studies focus was laid on understanding rainfall variability and effect on summer monsoon. Other researchers had studied rainfall and its variability with respect to temperature, crop cover, sea surface temperature, wind velocity and wind directions and weather dependent parameters. Most research contributions require several weather parameters and complex models while data availability for carrying out such research studies at regional and local scale is generally limited. Ghosh et al (2009) in his study on trend analysis of Indian Summer Monsoon Rainfall (ISMR) at different spatial scales found that the conventional method of representing ISMR using a single variable has some limitations and may result in an erroneous outcome for a few places. The results of local-scale studies may not match with those of large-scale analysis. India, being a developing country, is characterized by local-scale changes, viz., population 1

2 growth and urbanization, which have significant impacts on the summer monsoon rainfall pattern. These local changes are obviously not uniform all over India. Therefore, results at a finer scale considering spatial variability are more important and reliable for further use of rainfall data in hydrological applications, water resources management and agricultural water management. 1.2 Motivation for research work There is strong desire and scientific consensus to develop approaches, methods and models based on available data records which are efficient, quick and effective. This research aims to model rainfall variability and drought assessment for an arid basin in India with available data records. Preethi et al (2010) used coupled models to forecast seasonal and inter-annual prediction and found strong dependency of model simulating Indian summer monsoon on initial conditions. Rajeevan et al (2010) in his study used daily gridded rainfall for identifying active and break spells of Indian summer monsoon. Gopinath et al (1990) in his research for predicting ISMR found that rainfall anomaly can be computed knowing the position anomaly of Pacific Ocean Warm Pool (POWP). Gadgil et al (2004) showed a strong relationship between ISMR and a composite index based on ENSO and Equatorial Indian Ocean Oscillation (EQUINO). The variability of ISMR has been observed by Rahman et al (2010) using daily rainfall data from gauge and satellite. Makridakis et al (1978) has opined that rainfall amount and rainfall variability can be used for effective and efficient operations of water resource systems. The effect of rainfall distribution on crop productivity was studied by Wheeler et al. (2005) which showed simulated effect of evenly and unevenly distributed intra-seasonal rainfall. Other researchers such as Sarria -Dodd and Jolliffe, (2001) studied the importance of onset of rainy season (ORS) to determine the planting date. ORS is 2

3 important for crop growth, as planting too early may lead to crop failure whereas planting too late may results in reduced crop production. Hence, understanding of rainfall distribution and variability and prediction of monsoon onset few days ahead are vital for planning irrigation systems, operation of canal systems and assessing the impact of dry spells. The crop production uncertainty is generally defined by the variability of climate, therefore it is important to analyze rainfall variability. The crop yield depends on the rainfall amount and rain duration; hence the study of drought assessment process is essential. In general, drought is determined by comparing the departures and excess amount with the average rainfall over several years. The drought index is useful in identifying the occurrence, extent and severity of drought. Hence, the research attempt to develop a modified drought index for the Sabarmati basin. 1.3 Conventional Methods and their limitations The rainfall variability, distribution and frequency have been analyzed by several researchers using different methodologies. Several weather parameters like rainfall, temperature, evapo-transpiration, relative humidity and atmospheric pressure have been used to analyze the spatial and temporal variability of rainfall. The long term rainfall data are required for analyzing the variability, frequency and trends of rainfall. The statistical tools and soft computing models were used by researchers in the recent past. Several drought indices have been cited in the literature to classify deviation of rainfall from average rainfall. Each drought index has its own applications and limitations. There is no suitable drought index which can be used for every circumstance. Each drought index has parameters like rainfall, soil 3

4 moisture and temperature. Generally, rainfall parameter is most common to calculate drought index from monthly to yearly scale. Although, rainfall data alone may not reflect the range of drought related conditions, but they have been consistently used for field-level monitoring and contingency planning. The most common drought index is Standardized Precipitation Index (SPI), Percent of Normal (PN) and Effective Drought Index (EDI). Generally, all drought Indices use single weather parameter (mostly rainfall) for analysis and classification. PN is quite effective for comparing single season while SPI is useful for carrying out multiple time scale analysis. On the other hand, EDI is useful for carrying out daily scale analysis. Many researchers have used several weather and weather related parameters for predicting the onset of Monsoon. Different types of models like multiple regression models, Autoregressive Integrated Moving Average method (ARIMA), power (nonlinear) regression models and neural network models are used for generating predictions. The official forecast of the IMD is based on the 16 parameter power regression models. Many researchers used Time series methods, Casual methods and Judgemental method for forecasting of rainfall. Autoregressive Moving Average (ARMA), Exponential Smoothing, Extrapolation, Linear Prediction, Trend Estimation, Growth Curve and Box-Jenkins Approach are the methods of Time series modeling which require long term data. Soft computing technologies are the growing technologies for long term rainfall prediction which uses several Fuzzy, regression and neural network based models. 1.4 Objectives of the Study: The main aim of this study is to model rainfall variability, and assessment of drought in Sabarmati basin, Gujarat, India. Following are the objectives of the study. 4

5 1. To determine rainfall variability and rainfall distribution. 2. To develop modified drought index for Sabarmati basin. 3. To develop a reasonable onset definition for Sabarmati basin 4. To predict arrival of monsoon in a region based on arrival of monsoon in neighboring region. 1.5 Methodology: The research methodology has used models, methods and techniques for modeling rainfall variability and drought assessment in Sabarmati basin. The distribution and variability of rainfall has been analyzed using statistical tools. The drought assessment has been carried out by developing a modified drought index. The onset of monsoon has been defined using fuzzy logic approach and prediction of arrival of monsoon has been carried out using linear regression analysis. These techniques are rely on data driven models and statistical equations. The research frame work for the study area is presented below in Figure1.1 In this research study, meteorological and spatial data have been collected from the State Water Data Centre (SWDC), Gandhinagar. The geo-spatial data base for Sabarmati basin has been developed using basin map at 1:250,000 scale, topographical sheets at 1:50,000 scale and satellite imaginary. The satellite images for Landsat-7ETM+ was downloaded from USGS global land cover facility site http\ The images have been classified for land use and agricultural areas. The other data related to culturable area, agricultural yield were obtained from Director of Agriculture, Government of Gujarat. The statistical analysis of rainfall data for rainfall variability has been analyzed and regional classification of basin has been done. The rainfall variability was understood based on spatial, temporal and topographic features. The distribution 5

6 of rainfall and frequency of rainfall has been analyzed. It has been attempted to develop modified drought index which can describe both rainfall amount as well as rainfall duration, as earlier drought indices were based on rainfall amount only. The classification of drought condition has been done based on MDI and results were compared with past records. Figure 1.1 Flow chart on research methodology being adopted for modeling rainfall variability and drought assessment in Sabarmati basin, India A new definition for monsoon onset using a conceptual model has been proposed. It consists of three constraints consisting of total amount of rainfall during ten days period, successive number of rainy days and percentage of stations receiving the rainfall. The onset model uses artificial intelligence technique employing fuzzy logic approach for onset definition and prediction. 6

7 Linear regression equations have been developed to predict the arrival of monsoon in a region based on arrival of monsoon in neighboring region. The validity of time series based ARIMA models for rainfall forecasting have been also studied since long term data records for three stations were available Analysis on rainfall variability and distribution The spatial and temporal variability of monsoon are analyzed based on daily rainfall records for monsoon season for a period from 1 st May to 30 th October. An extended period has been considered to take into account early monsoon onset, late monsoon departure and climate change signals, if any. The available daily rainfall data have been converted into monthly and yearly rainfall records for rainfall amounts and number of rainy days. The few additional parameters such as rainfall departure, rainfall distribution, effect of terrain on rainfall and frequency of rainfall were also analyzed. Later, the yearly station rainfall anomalies were calculated using mean rainfall for the basin to determine the spatial and temporal variability of rainfall Drought Definition and Drought Indices A modified definition of drought index has been proposed based on standardized precipitation index (SPI) and number of rainy days. In the first step of analysis, two drought indices, namely SPI and PN has been computed and drought years has been analyzed. Later, a modified drought index has been computed using SPI and number of rainy days. SPI represents the probability of rainfall while the proposed modified drought index considers the rainfall amount and the duration. This modified index will be superior as it considers rainfall duration on which crop growth depends. Therefore, for the purpose of drought 7

8 planning this modified drought index will offer better insight on drought definition. The drought classes have been defined considering average SPI and average number of rainy days for a given station over long time period. Although none of the drought indices are superior, hence the need of new drought index was felt. Based on the new drought index calculated, drought years were identified and compared with the past records of available data Onset of rainy season The onset of monsoon has been defined considering three constraints namely, total amount of rainfall, number of rainy days and percentage of stations receiving rainfall. An artificial intelligence based fuzzy logic approach has been used to model the onset of rainy season. A fuzzy logic approach is important as it can incorporate the sternness of constraints which have to be fulfilled simultaneously. In this approach, each constraint is attached to a fuzzy membership function using triangular (subscript T) fuzzy numbers. The first two definition constraints are attached to a fuzzy membership function using triangular fuzzy numbers while the third constraint considers the threshold limit. For the first constraint dealing with total amount of rainfall within a 10 days spell, the triangular fuzzy numbers are (18, 25, + ) т. This means that membership grade of rainfall totals less than 18 mm is attached to zero & total larger than 25 mm to one. Between 18 & 25 mm the membership grade is linearly interpolated. For the second constraint dealing with number of rainy day, the triangular fuzzy numbers are (1, 3, + ) т. This means that membership grade of rainy days less than 1 is attached to zero & more than 3 to one. The membership grades between, 1, 1 and 3 are linearly interpolated and appropriate values are assigned. If 2 3 are membership grades for amount of rainfall, number of rainy days and 8

9 percentage of stations receiving rainfall then, the onset date is defined as the first * 1 * day of year where the product 2 3 exceeds a defined threshold value. The membership grades for the first two constraints have been computed with the help of software developed in FOXPRO. A filter was applied on onset date to make prediction relevance, in case the onset definition is beyond the stipulated monsoon duration. A Box-Jenkins approach of Time-series modeling has been used to predict the rainfall for three stations in Sabarmati basin as long term data is available. The ARIMA model of time-series with three parameters namely, p-number of auto regressive term, q- moving average and d-number of non seasonal differences, has been used. The ARIMA Model is tested for different values of parameters p, d and q. The time series models are calibrated for 40 years of period for Ahmedabad and Bhiloda rain gauge stations, and for 33 years for Vadagam station. Vadagam station has short daily rainfall data series available as compared to two other stations. The monthly forecasted rainfall time series is plotted against actual measured rainfall data series. In addition, the distribution of RMSE and SOR is also plotted for each model. The performance analysis of time series models are done using, root means square error (RMSE), sum of residuals (SOR), outliers in each time series, and normal probability plots (NPP). 1.6 Scope of Research work: This study is bounded in scope to the analysis of rainfall variability and assessment of drought in Sabarmati basin. In this study, the basic characteristics of rainfall have been analyzed to understand the rainfall variability at spatial and temporal scale. Regional classification of basin has been carried out. For understanding of drought condition, the study provides a new methodology to 9

10 develop a drought index. It also provides an approach to define the onset of monsoon in Sabarmati basin and prediction of arrival of monsoon in a region based on arrival of monsoon in neighboring region. 1.7 Organization of Thesis The structure of the thesis follows the below mentioned sequence to achieve the objectives of the study. In Chapter 1 the introductory background on the main theme, the research objectives, conceptual framework of the research and scope of research work are presented. The various chapters follow systematically analyze different issues on the basis of the framework. The chapter 2 reviews approaches, models, methods and techniques on modeling basin and station level rainfall variability and drought assessment. Initially, it describes factors influencing crop yield and drought and its dependence on other parameters. A literature review of earlier methods and models developed by researchers to analyze the rainfall variability, to define the onset of monsoon and its forecasting and to compute the drought indices for identifying the distribution, extent and severity of drought has been carried out. The brief over-view of study area as well as the availability and characteristics of data used is described in chapter 3. The chapter 4 describes about the analysis of rainfall done to find out the variability and distribution of rainfall at spatial and temporal level in the Sabarmati basin. In chapter 5, two drought indices using rainfall data are computed. The chapter also describes an approach to develop a modified drought index and to classify drought situation in Sabarmati basin. The Chapter 6 describes an approach based on fuzzy logic to define monsoon onset. It also covers the method used to predict the arrival of monsoon in a region based on arrival of monsoon in neighboring region. The chapter 7 presents summaries and conclusions of the research. It also outlines recommendations for further research. 10

Chapter-4 Analysis on Rainfall Variability and Distribution

Chapter-4 Analysis on Rainfall Variability and Distribution 4.1 Introduction Chapter-4 Analysis on ainfall Variability and Distribution The distribution pattern of rainfall in the state of Gujarat is most uneven and varies considerably from year to year and region

More information

THE STUDY OF NUMBERS AND INTENSITY OF TROPICAL CYCLONE MOVING TOWARD THE UPPER PART OF THAILAND

THE STUDY OF NUMBERS AND INTENSITY OF TROPICAL CYCLONE MOVING TOWARD THE UPPER PART OF THAILAND THE STUDY OF NUMBERS AND INTENSITY OF TROPICAL CYCLONE MOVING TOWARD THE UPPER PART OF THAILAND Aphantree Yuttaphan 1, Sombat Chuenchooklin 2 and Somchai Baimoung 3 ABSTRACT The upper part of Thailand

More information

Stochastic Hydrology. a) Data Mining for Evolution of Association Rules for Droughts and Floods in India using Climate Inputs

Stochastic Hydrology. a) Data Mining for Evolution of Association Rules for Droughts and Floods in India using Climate Inputs Stochastic Hydrology a) Data Mining for Evolution of Association Rules for Droughts and Floods in India using Climate Inputs An accurate prediction of extreme rainfall events can significantly aid in policy

More information

Analysis of Rainfall and Other Weather Parameters under Climatic Variability of Parbhani ( )

Analysis of Rainfall and Other Weather Parameters under Climatic Variability of Parbhani ( ) International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 06 (2018) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2018.706.295

More information

Analysis of meteorological measurements made over three rainy seasons in Sinazongwe District, Zambia.

Analysis of meteorological measurements made over three rainy seasons in Sinazongwe District, Zambia. Analysis of meteorological measurements made over three rainy seasons in Sinazongwe District, Zambia. 1 Hiromitsu Kanno, 2 Hiroyuki Shimono, 3 Takeshi Sakurai, and 4 Taro Yamauchi 1 National Agricultural

More information

Forecasting Drought in Tel River Basin using Feed-forward Recursive Neural Network

Forecasting Drought in Tel River Basin using Feed-forward Recursive Neural Network 2012 International Conference on Environmental, Biomedical and Biotechnology IPCBEE vol.41 (2012) (2012) IACSIT Press, Singapore Forecasting Drought in Tel River Basin using Feed-forward Recursive Neural

More information

South & South East Asian Region:

South & South East Asian Region: Issued: 10 th November 2017 Valid Period: December 2017 May 2018 South & South East Asian Region: Indonesia Tobacco Regions 1 A] Current conditions: 1] El Niño-Southern Oscillation (ENSO) ENSO Alert System

More information

SEASONAL CLIMATE OUTLOOK VALID FOR JULY-AUGUST- SEPTEMBER 2013 IN WEST AFRICA, CHAD AND CAMEROON

SEASONAL CLIMATE OUTLOOK VALID FOR JULY-AUGUST- SEPTEMBER 2013 IN WEST AFRICA, CHAD AND CAMEROON SEASONAL CLIMATE OUTLOOK VALID FOR JULY-AUGUST- SEPTEMBER 2013 IN WEST AFRICA, CHAD AND CAMEROON May 29, 2013 ABUJA-Federal Republic of Nigeria 1 EXECUTIVE SUMMARY Given the current Sea Surface and sub-surface

More information

DROUGHT ASSESSMENT USING SATELLITE DERIVED METEOROLOGICAL PARAMETERS AND NDVI IN POTOHAR REGION

DROUGHT ASSESSMENT USING SATELLITE DERIVED METEOROLOGICAL PARAMETERS AND NDVI IN POTOHAR REGION DROUGHT ASSESSMENT USING SATELLITE DERIVED METEOROLOGICAL PARAMETERS AND NDVI IN POTOHAR REGION Researcher: Saad-ul-Haque Supervisor: Dr. Badar Ghauri Department of RS & GISc Institute of Space Technology

More information

An objective criterion for the identification of breaks in Indian summer monsoon rainfall

An objective criterion for the identification of breaks in Indian summer monsoon rainfall ATMOSPHERIC SCIENCE LETTERS Atmos. Sci. Let. 16: 193 198 (2015) Published online 12 September 2014 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/asl2.536 An objective criterion for the

More information

Forecasting of meteorological drought using ARIMA model

Forecasting of meteorological drought using ARIMA model Indian J. Agric. Res., 51 (2) 2017 : 103-111 Print ISSN:0367-8245 / Online ISSN:0976-058X AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com/www.ijarjournal.com Forecasting of meteorological

More information

Prediction of Seasonal Rainfall Data in India using Fuzzy Stochastic Modelling

Prediction of Seasonal Rainfall Data in India using Fuzzy Stochastic Modelling Global Journal of Pure and Applied Mathematics. ISSN 0973-1768 Volume 13, Number 9 (2017), pp. 6167-6174 Research India Publications http://www.ripublication.com Prediction of Seasonal Rainfall Data in

More information

Summary and Conclusions

Summary and Conclusions 241 Chapter 10 Summary and Conclusions Kerala is situated in the southern tip of India between 8 15 N and 12 50 N latitude and 74 50 E and 77 30 E longitude. It is popularly known as Gods own country.

More information

Climate outlook, longer term assessment and regional implications. What s Ahead for Agriculture: How to Keep One of Our Key Industries Sustainable

Climate outlook, longer term assessment and regional implications. What s Ahead for Agriculture: How to Keep One of Our Key Industries Sustainable Climate outlook, longer term assessment and regional implications What s Ahead for Agriculture: How to Keep One of Our Key Industries Sustainable Bureau of Meteorology presented by Dr Jeff Sabburg Business

More information

El Niño 2015 Conference

El Niño 2015 Conference El Niño 2015 Conference Case Study: El Nino of 2015 and the Indian summer monsoon Sulochana Gadgil (on the basis of inputs from IMD) IRI, 17 November 2015 All-India rainfall: The mean monthly rainfall

More information

Drought Criteria. Richard J. Heggen Department of Civil Engineering University of New Mexico, USA Abstract

Drought Criteria. Richard J. Heggen Department of Civil Engineering University of New Mexico, USA Abstract Drought Criteria Richard J. Heggen Department of Civil Engineering University of New Mexico, USA rheggen@unm.edu Abstract Rainwater catchment is an anticipatory response to drought. Catchment design requires

More information

Zambia. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. C. McSweeney 1, M. New 1,2 and G.

Zambia. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. C. McSweeney 1, M. New 1,2 and G. UNDP Climate Change Country Profiles Zambia C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

Rainfall is the major source of water for

Rainfall is the major source of water for RESEARCH PAPER: Assessment of occurrence and frequency of drought using rainfall data in Coimbatore, India M. MANIKANDAN AND D.TAMILMANI Asian Journal of Environmental Science December, 2011 Vol. 6 Issue

More information

A High Resolution Daily Gridded Rainfall Data Set ( ) for Mesoscale Meteorological Studies

A High Resolution Daily Gridded Rainfall Data Set ( ) for Mesoscale Meteorological Studies National Climate Centre Research Report No: 9/2008 A High Resolution Daily Gridded Rainfall Data Set (1971-2005) for Mesoscale Meteorological Studies M. Rajeevan and Jyoti Bhate National Climate Centre

More information

TOOLS AND DATA NEEDS FOR FORECASTING AND EARLY WARNING

TOOLS AND DATA NEEDS FOR FORECASTING AND EARLY WARNING TOOLS AND DATA NEEDS FOR FORECASTING AND EARLY WARNING Professor Richard Samson Odingo Department of Geography and Environmental Studies University of Nairobi, Kenya THE NEED FOR ADEQUATE DATA AND APPROPRIATE

More information

Weather and climate outlooks for crop estimates

Weather and climate outlooks for crop estimates Weather and climate outlooks for crop estimates CELC meeting 2016-04-21 ARC ISCW Observed weather data Modeled weather data Short-range forecasts Seasonal forecasts Climate change scenario data Introduction

More information

Prediction of Monthly Rainfall of Nainital Region using Artificial Neural Network (ANN) and Support Vector Machine (SVM)

Prediction of Monthly Rainfall of Nainital Region using Artificial Neural Network (ANN) and Support Vector Machine (SVM) Vol- Issue-3 25 Prediction of ly of Nainital Region using Artificial Neural Network (ANN) and Support Vector Machine (SVM) Deepa Bisht*, Mahesh C Joshi*, Ashish Mehta** *Department of Mathematics **Department

More information

South & South East Asian Region:

South & South East Asian Region: Issued: 15 th December 2017 Valid Period: January June 2018 South & South East Asian Region: Indonesia Tobacco Regions 1 A] Current conditions: 1] El Niño-Southern Oscillation (ENSO) ENSO Alert System

More information

THE ROLE OF OCEAN STATE INDICES IN SEASONAL AND INTER-ANNUAL CLIMATE VARIABILITY OF THAILAND

THE ROLE OF OCEAN STATE INDICES IN SEASONAL AND INTER-ANNUAL CLIMATE VARIABILITY OF THAILAND THE ROLE OF OCEAN STATE INDICES IN SEASONAL AND INTER-ANNUAL CLIMATE VARIABILITY OF THAILAND Manfred Koch and Werapol Bejranonda Department of Geohydraulics and Engineering Hydrology, University of Kassel,

More information

FUTURE CARIBBEAN CLIMATES FROM STATISTICAL AND DYNAMICAL DOWNSCALING

FUTURE CARIBBEAN CLIMATES FROM STATISTICAL AND DYNAMICAL DOWNSCALING FUTURE CARIBBEAN CLIMATES FROM STATISTICAL AND DYNAMICAL DOWNSCALING Arnoldo Bezanilla Morlot Center For Atmospheric Physics Institute of Meteorology, Cuba The Caribbean Community Climate Change Centre

More information

Analysis of Meteorological drought condition for Bijapur region in the lower Bhima basin, India

Analysis of Meteorological drought condition for Bijapur region in the lower Bhima basin, India Analysis of Meteorological drought condition for Bijapur region in the lower Bhima basin, India Mamatha.K PG Student Department of WLM branch VTU, Belagavi Dr. Nagaraj Patil Professor and Head of the Department

More information

Seasonal Climate Outlook for South Asia (June to September) Issued in May 2014

Seasonal Climate Outlook for South Asia (June to September) Issued in May 2014 Ministry of Earth Sciences Earth System Science Organization India Meteorological Department WMO Regional Climate Centre (Demonstration Phase) Pune, India Seasonal Climate Outlook for South Asia (June

More information

To Predict Rain Fall in Desert Area of Rajasthan Using Data Mining Techniques

To Predict Rain Fall in Desert Area of Rajasthan Using Data Mining Techniques To Predict Rain Fall in Desert Area of Rajasthan Using Data Mining Techniques Peeyush Vyas Asst. Professor, CE/IT Department of Vadodara Institute of Engineering, Vadodara Abstract: Weather forecasting

More information

Antigua and Barbuda. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature

Antigua and Barbuda. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature UNDP Climate Change Country Profiles Antigua and Barbuda C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research

More information

University of Florida Department of Geography GEO 3280 Assignment 3

University of Florida Department of Geography GEO 3280 Assignment 3 G E O 3 2 8 A s s i g n m e n t # 3 Page 1 University of Florida Department of Geography GEO 328 Assignment 3 Modeling Precipitation and Elevation Solar Radiation Precipitation Evapo- Transpiration Vegetation

More information

Flood management in Namibia: Hydrological linkage between the Kunene River and the Cuvelai Drainage System: Cuvelai-Etosha Basin

Flood management in Namibia: Hydrological linkage between the Kunene River and the Cuvelai Drainage System: Cuvelai-Etosha Basin Flood management in Namibia: Hydrological linkage between the Kunene River and the Cuvelai Drainage System: Cuvelai-Etosha Basin By: Leonard Hango Department of Water Affairs and Forestry Ministry of Agriculture

More information

Study of Hydrometeorology in a Hard Rock Terrain, Kadirischist Belt Area, Anantapur District, Andhra Pradesh

Study of Hydrometeorology in a Hard Rock Terrain, Kadirischist Belt Area, Anantapur District, Andhra Pradesh Open Journal of Geology, 2012, 2, 294-300 http://dx.doi.org/10.4236/ojg.2012.24028 Published Online October 2012 (http://www.scirp.org/journal/ojg) Study of Hydrometeorology in a Hard Rock Terrain, Kadirischist

More information

Cape Verde. General Climate. Recent Climate. UNDP Climate Change Country Profiles. Temperature. Precipitation

Cape Verde. General Climate. Recent Climate. UNDP Climate Change Country Profiles. Temperature. Precipitation UNDP Climate Change Country Profiles C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

Drought risk assessment using GIS and remote sensing: A case study of District Khushab, Pakistan

Drought risk assessment using GIS and remote sensing: A case study of District Khushab, Pakistan 15 th International Conference on Environmental Science and Technology Rhodes, Greece, 31 August to 2 September 2017 Drought risk assessment using GIS and remote sensing: A case study of District Khushab,

More information

St Lucia. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. Precipitation

St Lucia. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. Precipitation UNDP Climate Change Country Profiles St Lucia C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

Chapter outline. Reference 12/13/2016

Chapter outline. Reference 12/13/2016 Chapter 2. observation CC EST 5103 Climate Change Science Rezaul Karim Environmental Science & Technology Jessore University of science & Technology Chapter outline Temperature in the instrumental record

More information

Will a warmer world change Queensland s rainfall?

Will a warmer world change Queensland s rainfall? Will a warmer world change Queensland s rainfall? Nicholas P. Klingaman National Centre for Atmospheric Science-Climate Walker Institute for Climate System Research University of Reading The Walker-QCCCE

More information

Grenada. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. Precipitation

Grenada. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. Precipitation UNDP Climate Change Country Profiles C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

SPI: Standardized Precipitation Index

SPI: Standardized Precipitation Index PRODUCT FACT SHEET: SPI Africa Version 1 (May. 2013) SPI: Standardized Precipitation Index Type Temporal scale Spatial scale Geo. coverage Precipitation Monthly Data dependent Africa (for a range of accumulation

More information

Contribution of Monthly and Regional Rainfall to the Strength of Indian Summer Monsoon

Contribution of Monthly and Regional Rainfall to the Strength of Indian Summer Monsoon VOLUME 144 M O N T H L Y W E A T H E R R E V I E W SEPTEMBER 2016 Contribution of Monthly and Regional Rainfall to the Strength of Indian Summer Monsoon YANGXING ZHENG AND M. M. ALI Center for Ocean Atmospheric

More information

Climate Change and Predictability of the Indian Summer Monsoon

Climate Change and Predictability of the Indian Summer Monsoon Climate Change and Predictability of the Indian Summer Monsoon B. N. Goswami (goswami@tropmet.res.in) Indian Institute of Tropical Meteorology, Pune Annual mean Temp. over India 1875-2004 Kothawale, Roopakum

More information

The New Normal or Was It?

The New Normal or Was It? The New Normal or Was It? by Chuck Coffey The recent drought has caused many to reflect upon the past and wonder what is in store for the future. Just a couple of years ago, few agricultural producers

More information

Effect of land use/land cover changes on runoff in a river basin: a case study

Effect of land use/land cover changes on runoff in a river basin: a case study Water Resources Management VI 139 Effect of land use/land cover changes on runoff in a river basin: a case study J. Letha, B. Thulasidharan Nair & B. Amruth Chand College of Engineering, Trivandrum, Kerala,

More information

Water Stress, Droughts under Changing Climate

Water Stress, Droughts under Changing Climate Water Stress, Droughts under Changing Climate Professor A.K.M. Saiful Islam Institute of Water and Flood Management Bangladesh University of Engineering and Technology (BUET) Outline of the presentation

More information

MDA WEATHER SERVICES AG WEATHER OUTLOOK. Kyle Tapley-Senior Agricultural Meteorologist May 22, 2014 Chicago, IL

MDA WEATHER SERVICES AG WEATHER OUTLOOK. Kyle Tapley-Senior Agricultural Meteorologist May 22, 2014 Chicago, IL MDA WEATHER SERVICES AG WEATHER OUTLOOK Kyle Tapley-Senior Agricultural Meteorologist May 22, 2014 Chicago, IL GLOBAL GRAIN NORTH AMERICA 2014 Agenda Spring Recap North America Forecast El Niño Discussion

More information

Drought Assessment under Climate Change by Using NDVI and SPI for Marathwada

Drought Assessment under Climate Change by Using NDVI and SPI for Marathwada Available online at www.ijpab.com ISSN: 2320 7051 Int. J. Pure App. Biosci. SPI: 6 (1): 1-5 (2018) Research Article Drought Assessment under Climate Change by Using NDVI and SPI for Marathwada A. U. Waikar

More information

SEASONAL RAINFALL FORECAST FOR ZIMBABWE. 28 August 2017 THE ZIMBABWE NATIONAL CLIMATE OUTLOOK FORUM

SEASONAL RAINFALL FORECAST FOR ZIMBABWE. 28 August 2017 THE ZIMBABWE NATIONAL CLIMATE OUTLOOK FORUM 2017-18 SEASONAL RAINFALL FORECAST FOR ZIMBABWE METEOROLOGICAL SERVICES DEPARTMENT 28 August 2017 THE ZIMBABWE NATIONAL CLIMATE OUTLOOK FORUM Introduction The Meteorological Services Department of Zimbabwe

More information

Chapter 4 Inter-Annual and Long-Term Variability

Chapter 4 Inter-Annual and Long-Term Variability Chapter 4 Inter-Annual and Long-Term Variability 4.1 General Rainfa\\ is the most imllortant weather element for India, a trollica\ country. Agriculture, hydro-electric power, industry and the economy

More information

Cuba. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. C. McSweeney 1, M. New 1,2 and G.

Cuba. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. C. McSweeney 1, M. New 1,2 and G. UNDP Climate Change Country Profiles Cuba C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

Chiang Rai Province CC Threat overview AAS1109 Mekong ARCC

Chiang Rai Province CC Threat overview AAS1109 Mekong ARCC Chiang Rai Province CC Threat overview AAS1109 Mekong ARCC This threat overview relies on projections of future climate change in the Mekong Basin for the period 2045-2069 compared to a baseline of 1980-2005.

More information

Key Finding: Long Term Trend During 2014: Rain in Indian Tradition Measuring Rain

Key Finding: Long Term Trend During 2014: Rain in Indian Tradition Measuring Rain Chapter 34 RAINFALL Key Finding: Long Term Trend Despite of theories suggesting increase in rainfall in Asian Region due to global warming, no significant trend has been observed at all India level (confirmed

More information

Tokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean-

Tokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean- Tokyo, 14 November 2016, TCC Training Seminar Tokyo Climate Center Website (TCC website) and its products -For monitoring the world climate and ocean- Yasushi MOCHIZUKI Tokyo Climate Center Japan Meteorological

More information

Malawi. General Climate. UNDP Climate Change Country Profiles. C. McSweeney 1, M. New 1,2 and G. Lizcano 1

Malawi. General Climate. UNDP Climate Change Country Profiles. C. McSweeney 1, M. New 1,2 and G. Lizcano 1 UNDP Climate Change Country Profiles Malawi C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

Possible Applications of Deep Neural Networks in Climate and Weather. David M. Hall Assistant Research Professor Dept. Computer Science, CU Boulder

Possible Applications of Deep Neural Networks in Climate and Weather. David M. Hall Assistant Research Professor Dept. Computer Science, CU Boulder Possible Applications of Deep Neural Networks in Climate and Weather David M. Hall Assistant Research Professor Dept. Computer Science, CU Boulder Quick overview of climate and weather models Weather models

More information

Mozambique. General Climate. UNDP Climate Change Country Profiles. C. McSweeney 1, M. New 1,2 and G. Lizcano 1

Mozambique. General Climate. UNDP Climate Change Country Profiles. C. McSweeney 1, M. New 1,2 and G. Lizcano 1 UNDP Climate Change Country Profiles Mozambique C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2.Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

CHAPTER 1 INTRODUCTION

CHAPTER 1 INTRODUCTION CHAPTER 1 INTRODUCTION Mean annual precipitation (MAP) is perhaps the most widely used variable in hydrological design, water resources planning and agrohydrology. In the past two decades one of the basic

More information

Behind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP

Behind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP Behind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP September 2012 Outline Mission Extended Range Outlooks (6-10/8-14)

More information

Water Balance in the Murray-Darling Basin and the recent drought as modelled with WRF

Water Balance in the Murray-Darling Basin and the recent drought as modelled with WRF 18 th World IMACS / MODSIM Congress, Cairns, Australia 13-17 July 2009 http://mssanz.org.au/modsim09 Water Balance in the Murray-Darling Basin and the recent drought as modelled with WRF Evans, J.P. Climate

More information

UPDATE OF REGIONAL WEATHER AND SMOKE HAZE November 2016

UPDATE OF REGIONAL WEATHER AND SMOKE HAZE November 2016 UPDATE OF REGIONAL WEATHER AND SMOKE HAZE November 2016 1. Review of Regional Weather Conditions in November 2016 1.1 Southwest Monsoon conditions prevailed on most days in October 2016 and the winds were

More information

Striving Sufficient Lead Time of Flood Forecasts via Integrated Hydro-meteorological Intelligence

Striving Sufficient Lead Time of Flood Forecasts via Integrated Hydro-meteorological Intelligence Striving Sufficient Lead Time of Flood Forecasts via Integrated Hydro-meteorological Intelligence Dong-Sin Shih Assistant Professor, National Chung Hsing University, Taiwan, Sep. 6, 2013 Outlines Introductions

More information

Sudan Seasonal Monitor 1

Sudan Seasonal Monitor 1 Sudan Seasonal Monitor 1 Sudan Seasonal Monitor Sudan Meteorological Authority Federal Ministry of Agriculture and Forestry Issue 1 June 2011 Early and advanced movement of IFT northward, implied significant

More information

Long term weather trends in Phaltan, Maharashtra. French intern at NARI, student from Ecole Centrale de Lyon, Ecully 69130, France.

Long term weather trends in Phaltan, Maharashtra. French intern at NARI, student from Ecole Centrale de Lyon, Ecully 69130, France. Long term weather trends in Phaltan, Maharashtra A. Jacob and Anil K. Rajvanshi French intern at NARI, student from Ecole Centrale de Lyon, Ecully 693, France. Director NARI, Nimbkar Agricultural Research

More information

Seasonal Climate Watch September 2018 to January 2019

Seasonal Climate Watch September 2018 to January 2019 Seasonal Climate Watch September 2018 to January 2019 Date issued: Aug 31, 2018 1. Overview The El Niño-Southern Oscillation (ENSO) is still in a neutral phase and is still expected to rise towards an

More information

An ENSO-Neutral Winter

An ENSO-Neutral Winter An ENSO-Neutral Winter This issue of the Blue Water Outlook newsletter is devoted towards my thoughts on the long range outlook for winter. You will see that I take a comprehensive approach to this outlook

More information

ANNUAL CLIMATE REPORT 2016 SRI LANKA

ANNUAL CLIMATE REPORT 2016 SRI LANKA ANNUAL CLIMATE REPORT 2016 SRI LANKA Foundation for Environment, Climate and Technology C/o Mahaweli Authority of Sri Lanka, Digana Village, Rajawella, Kandy, KY 20180, Sri Lanka Citation Lokuhetti, R.,

More information

Downscaling in Time. Andrew W. Robertson, IRI. Advanced Training Institute on Climate Variability and Food Security, 12 July 2002

Downscaling in Time. Andrew W. Robertson, IRI. Advanced Training Institute on Climate Variability and Food Security, 12 July 2002 Downscaling in Time Andrew W. Robertson, IRI Advanced Training Institute on Climate Variability and Food Security, 12 July 2002 Preliminaries Crop yields are driven by daily weather variations! Current

More information

UPDATE OF REGIONAL WEATHER AND SMOKE HAZE (May 2017)

UPDATE OF REGIONAL WEATHER AND SMOKE HAZE (May 2017) UPDATE OF REGIONAL WEATHER AND SMOKE HAZE (May 2017) 1. Review of Regional Weather Conditions in April 2017 1.1 Inter monsoon conditions, characterised by afternoon showers and winds that are generally

More information

Climate Change or Climate Variability?

Climate Change or Climate Variability? Climate Change or Climate Variability? Key Concepts: Greenhouse Gas Climate Climate change Climate variability Climate zones Precipitation Temperature Water cycle Weather WHAT YOU WILL LEARN 1. You will

More information

El Niño / Southern Oscillation

El Niño / Southern Oscillation El Niño / Southern Oscillation Student Packet 2 Use contents of this packet as you feel appropriate. You are free to copy and use any of the material in this lesson plan. Packet Contents Introduction on

More information

The Global Scope of Climate. The Global Scope of Climate. Keys to Climate. Chapter 8

The Global Scope of Climate. The Global Scope of Climate. Keys to Climate. Chapter 8 The Global Scope of Climate Chapter 8 The Global Scope of Climate In its most general sense, climate is the average weather of a region, but except where conditions change very little during the course

More information

Sudan Seasonal Monitor

Sudan Seasonal Monitor Sudan Seasonal Monitor Sudan Meteorological Authority Federal Ministry of Agriculture and Forestry Issue 5 August 2010 Summary Advanced position of ITCZ during July to most north of Sudan emerged wide

More information

MODELING RUNOFF RESPONSE TO CHANGING LAND COVER IN PENGANGA SUBWATERSHED, MAHARASHTRA

MODELING RUNOFF RESPONSE TO CHANGING LAND COVER IN PENGANGA SUBWATERSHED, MAHARASHTRA MODELING RUNOFF RESPONSE TO CHANGING LAND COVER IN PENGANGA SUBWATERSHED, MAHARASHTRA Abira Dutta Roy*, S.Sreekesh** *Research Scholar, **Associate Professor Centre for the Study of Regional Development,

More information

Summer 2018 Southern Company Temperature/Precipitation Forecast

Summer 2018 Southern Company Temperature/Precipitation Forecast Scott A. Yuknis High impact weather forecasts, climate assessment and prediction. 14 Boatwright s Loop Plymouth, MA 02360 Phone/Fax 508.927.4610 Cell: 508.813.3499 ClimateImpact@comcast.net Climate Impact

More information

DROUGHT IN MAINLAND PORTUGAL

DROUGHT IN MAINLAND PORTUGAL DROUGHT IN MAINLAND Ministério da Ciência, Tecnologia e Ensino Superior Instituto de Meteorologia, I. P. Rua C Aeroporto de Lisboa Tel.: (351) 21 844 7000 e-mail:informacoes@meteo.pt 1749-077 Lisboa Portugal

More information

Effect of El Niño Southern Oscillation (ENSO) on the number of leaching rain events in Florida and implications on nutrient management

Effect of El Niño Southern Oscillation (ENSO) on the number of leaching rain events in Florida and implications on nutrient management Effect of El Niño Southern Oscillation (ENSO) on the number of leaching rain events in Florida and implications on nutrient management C. Fraisse 1, Z. Hu 1, E. H. Simonne 2 May 21, 2008 Apopka, Florida

More information

Climate and the Atmosphere

Climate and the Atmosphere Climate and Biomes Climate Objectives: Understand how weather is affected by: 1. Variations in the amount of incoming solar radiation 2. The earth s annual path around the sun 3. The earth s daily rotation

More information

Colorado s 2003 Moisture Outlook

Colorado s 2003 Moisture Outlook Colorado s 2003 Moisture Outlook Nolan Doesken and Roger Pielke, Sr. Colorado Climate Center Prepared by Tara Green and Odie Bliss http://climate.atmos.colostate.edu How we got into this drought! Fort

More information

CHAPTER 2 DATA AND METHODS. Errors using inadequate data are much less than those using no data at all. Charles Babbage, circa 1850

CHAPTER 2 DATA AND METHODS. Errors using inadequate data are much less than those using no data at all. Charles Babbage, circa 1850 CHAPTER 2 DATA AND METHODS Errors using inadequate data are much less than those using no data at all. Charles Babbage, circa 185 2.1 Datasets 2.1.1 OLR The primary data used in this study are the outgoing

More information

The South Eastern Australian Climate Initiative

The South Eastern Australian Climate Initiative The South Eastern Australian Climate Initiative Phase 2 of the South Eastern Australian Climate Initiative (SEACI) is a three-year (2009 2012), $9 million research program investigating the causes and

More information

A Report on a Statistical Model to Forecast Seasonal Inflows to Cowichan Lake

A Report on a Statistical Model to Forecast Seasonal Inflows to Cowichan Lake A Report on a Statistical Model to Forecast Seasonal Inflows to Cowichan Lake Prepared by: Allan Chapman, MSc, PGeo Hydrologist, Chapman Geoscience Ltd., and Former Head, BC River Forecast Centre Victoria

More information

By: J Malherbe, R Kuschke

By: J Malherbe, R Kuschke 2015-10-27 By: J Malherbe, R Kuschke Contents Summary...2 Overview of expected conditions over South Africa during the next few days...3 Significant weather events (27 October 2 November)...3 Conditions

More information

Seasonal Climate Watch January to May 2016

Seasonal Climate Watch January to May 2016 Seasonal Climate Watch January to May 2016 Date: Dec 17, 2015 1. Advisory Most models are showing the continuation of a strong El-Niño episode towards the latesummer season with the expectation to start

More information

Weather and Climate Summary and Forecast August 2018 Report

Weather and Climate Summary and Forecast August 2018 Report Weather and Climate Summary and Forecast August 2018 Report Gregory V. Jones Linfield College August 5, 2018 Summary: July 2018 will likely go down as one of the top five warmest July s on record for many

More information

The Importance of Snowmelt Runoff Modeling for Sustainable Development and Disaster Prevention

The Importance of Snowmelt Runoff Modeling for Sustainable Development and Disaster Prevention The Importance of Snowmelt Runoff Modeling for Sustainable Development and Disaster Prevention Muzafar Malikov Space Research Centre Academy of Sciences Republic of Uzbekistan Water H 2 O Gas - Water Vapor

More information

ATMOSPHERIC MODELLING. GEOG/ENST 3331 Lecture 9 Ahrens: Chapter 13; A&B: Chapters 12 and 13

ATMOSPHERIC MODELLING. GEOG/ENST 3331 Lecture 9 Ahrens: Chapter 13; A&B: Chapters 12 and 13 ATMOSPHERIC MODELLING GEOG/ENST 3331 Lecture 9 Ahrens: Chapter 13; A&B: Chapters 12 and 13 Agenda for February 3 Assignment 3: Due on Friday Lecture Outline Numerical modelling Long-range forecasts Oscillations

More information

Seasonal forecasting of climate anomalies for agriculture in Italy: the TEMPIO Project

Seasonal forecasting of climate anomalies for agriculture in Italy: the TEMPIO Project Seasonal forecasting of climate anomalies for agriculture in Italy: the TEMPIO Project M. Baldi(*), S. Esposito(**), E. Di Giuseppe (**), M. Pasqui(*), G. Maracchi(*) and D. Vento (**) * CNR IBIMET **

More information

Climate Risk Profile for Samoa

Climate Risk Profile for Samoa Climate Risk Profile for Samoa Report Prepared by Wairarapa J. Young Samoa Meteorology Division March, 27 Summary The likelihood (i.e. probability) components of climate-related risks in Samoa are evaluated

More information

STATISTICAL DOWNSCALING OF DAILY PRECIPITATION IN THE ARGENTINE PAMPAS REGION

STATISTICAL DOWNSCALING OF DAILY PRECIPITATION IN THE ARGENTINE PAMPAS REGION STATISTICAL DOWNSCALING OF DAILY PRECIPITATION IN THE ARGENTINE PAMPAS REGION Bettolli ML- Penalba OC Department of Atmospheric and Ocean Sciences, University of Buenos Aires, Argentina National Council

More information

2003 Moisture Outlook

2003 Moisture Outlook 2003 Moisture Outlook Nolan Doesken and Roger Pielke, Sr. Colorado Climate Center Prepared by Tara Green and Odie Bliss http://climate.atmos.colostate.edu Through 1999 Through 1999 Fort Collins Total Water

More information

DROUGHT RISK EVALUATION USING REMOTE SENSING AND GIS : A CASE STUDY IN LOP BURI PROVINCE

DROUGHT RISK EVALUATION USING REMOTE SENSING AND GIS : A CASE STUDY IN LOP BURI PROVINCE DROUGHT RISK EVALUATION USING REMOTE SENSING AND GIS : A CASE STUDY IN LOP BURI PROVINCE K. Prathumchai, Kiyoshi Honda, Kaew Nualchawee Asian Centre for Research on Remote Sensing STAR Program, Asian Institute

More information

Suriname. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. C. McSweeney 1, M. New 1,2 and G.

Suriname. General Climate. Recent Climate Trends. UNDP Climate Change Country Profiles. Temperature. C. McSweeney 1, M. New 1,2 and G. UNDP Climate Change Country Profiles Suriname C. McSweeney 1, M. New 1,2 and G. Lizcano 1 1. School of Geography and Environment, University of Oxford. 2. Tyndall Centre for Climate Change Research http://country-profiles.geog.ox.ac.uk

More information

Effect of rainfall and temperature on rice yield in Puri district of Odisha in India

Effect of rainfall and temperature on rice yield in Puri district of Odisha in India 2018; 7(4): 899-903 ISSN (E): 2277-7695 ISSN (P): 2349-8242 NAAS Rating: 5.03 TPI 2018; 7(4): 899-903 2018 TPI www.thepharmajournal.com Received: 05-02-2018 Accepted: 08-03-2018 A Baliarsingh A Nanda AKB

More information

UPDATE OF REGIONAL WEATHER AND SMOKE HAZE (September 2017)

UPDATE OF REGIONAL WEATHER AND SMOKE HAZE (September 2017) UPDATE OF REGIONAL WEATHER AND SMOKE HAZE (September 2017) 1. Review of Regional Weather Conditions in August 2017 1.1 Southwest Monsoon conditions continued to prevail in the region in August 2017. The

More information

Fire Weather Drivers, Seasonal Outlook and Climate Change. Steven McGibbony, Severe Weather Manager Victoria Region Friday 9 October 2015

Fire Weather Drivers, Seasonal Outlook and Climate Change. Steven McGibbony, Severe Weather Manager Victoria Region Friday 9 October 2015 Fire Weather Drivers, Seasonal Outlook and Climate Change Steven McGibbony, Severe Weather Manager Victoria Region Friday 9 October 2015 Outline Weather and Fire Risk Environmental conditions leading to

More information

KEY WORDS: Palmer Meteorological Drought Index, SWAP, Kriging spatial analysis and Digital Map.

KEY WORDS: Palmer Meteorological Drought Index, SWAP, Kriging spatial analysis and Digital Map. PALMER METEOROLOGICAL DROUGHT CLASSIFICATION USING TECHNIQUES OF GEOGRAPHIC INFORMATION SYSTEM IN THAILAND S. Baimoung, W. Waranuchit, S. Prakanrat, P. Amatayakul, N. Sukhanthamat, A. Yuthaphan, A. Pyomjamsri,

More information

Seasonal Climate Watch June to October 2018

Seasonal Climate Watch June to October 2018 Seasonal Climate Watch June to October 2018 Date issued: May 28, 2018 1. Overview The El Niño-Southern Oscillation (ENSO) has now moved into the neutral phase and is expected to rise towards an El Niño

More information

Weather and Climate Summary and Forecast Summer 2017

Weather and Climate Summary and Forecast Summer 2017 Weather and Climate Summary and Forecast Summer 2017 Gregory V. Jones Southern Oregon University August 4, 2017 July largely held true to forecast, although it ended with the start of one of the most extreme

More information

New Zealand Climate Update No 221, October 2017 Current climate October 2017

New Zealand Climate Update No 221, October 2017 Current climate October 2017 New Zealand Climate Update No 221, October 2017 Current climate October 2017 October 2017 was characterised by higher than normal sea level pressure over New Zealand and the surrounding seas. This consistent

More information

2003 Water Year Wrap-Up and Look Ahead

2003 Water Year Wrap-Up and Look Ahead 2003 Water Year Wrap-Up and Look Ahead Nolan Doesken Colorado Climate Center Prepared by Odie Bliss http://ccc.atmos.colostate.edu Colorado Average Annual Precipitation Map South Platte Average Precipitation

More information

IMPACT OF CLIMATE CHANGE OVER THE ARABIAN PENINSULA

IMPACT OF CLIMATE CHANGE OVER THE ARABIAN PENINSULA IMPACT OF CLIMATE CHANGE OVER THE ARABIAN PENINSULA By: Talal Alharbi June, 29 2017 1 Motivation: In arid and semi-arid regions of the world the demand for fresh water resources is increasing due to: increasing

More information