EVALUATION OF CONE OF UNCERTAINTY IN TROPICAL CYCLONE TRACK FORECAST OVER NORTH INDIAN OCEAN ISSUED BY INDIA METEOROLOGICAL DEPARTMENT

India Meteorological Department(IMD) introduced cone of uncertainty(COU) in cyclonic disturbances(CDs) alongwith the 72 hr track forecast over the north India Ocean(NIO) in 2009. The track forecast for CDs is issued for +6, +12, +18, +24, +36, +48, +60 and +72 hrs time period from the stage of deep depression onwards. An attempt is made to evaluate COU forecast issued by IMD during 2009-2011(3 years). The size of the cone is deduced from climatological track forecast errors. The accuracy of COU forecast has been analysed with respect to basin of formation, season of formation, intensity and type of track(climatological/straight moving and recurving/looping type) of CDs by calculating percentage of total number of forecasts in each category lying within COU. The observed track lies within the forecast COU in about 60% of the cases over the NIO. The accuracy of COU forecast is about 66% in post-monsoon season and about 50% in pre-monsoon season. The observed track lies within the forecast COU in 90% cases of climatological/straight moving CDs and 39% cases of recurving/looping CDs. The observed track lies within COU forecast in about 71% cases of severe cyclonic storm and 37% cases of cyclonic storm/deep depression.

Meteorological impacts on evapotranspiration in different climatic zones of Pakistan

Arid regions are highly vulnerable and sensitive to drought. The crops cultivated in arid zones are at high risk due to the high evapotranspiration and water demands. This study analyzed the changes in seasonal and annual evapotranspiration（ET） during 1951–2016 at 50 meteorological stations located in the extremely arid, arid, and semi-arid zones of Pakistan using the Penman Monteith（PM） method. The results show that ET is highly sensitive and positively correlated to temperature, solar radiation, and wind speed whereas vapor pressure is negatively correlated to ET. The study also identifies the relationship of ET with the meteorological parameters in different climatic zones of Pakistan. The significant trend analysis of precipitation and temperature（maximum and minimum） are conducted at 95% confidence level to determine the behaviors of these parameters in the extremely arid, arid, and semi-arid zones. The mean annual precipitation and annual mean maximum temperature significantly increased by 0.828 mm/a and 0.014℃/a in the arid and extremely arid zones, respectively. The annual mean minimum temperature increased by 0.017℃/a in the extremely arid zone and 0.019℃/a in the arid zone, whereas a significant decrease of 0.007℃/a was observed in the semi-arid zone. This study provides probabilistic future scenarios that would be helpful for policy-makers, agriculturists to plan effective irrigation measures towards the sustainable development in Pakistan.

Towards Increasing Data Availability for Meteorological Services: Inter-Comparison of Meteorological Data from a Synoptic Weather Station and Two Automatic Weather Stations in Kenya

Meteorological data is useful for varied applications and sectors ranging from weather and climate forecasting, landscape planning to disaster management among others. However, the availability of these data requires a good network of manual meteorological stations and other support systems for its collection, recording, processing, archiving, communication and dissemination. In sub-Saharan Africa, such networks are limited due to low investment and capacity. To bridge this gap, the National Meteorological Services in Kenya and few others from African countries have moved to install a number of Automatic Weather Stations (AWSs) in the past decade including a few additions from private institutions and individuals. Although these AWSs have the potential to improve the existing observation network and the early warning systems in the region, the quality and capacity of the data collected from the stations are not well exploited. This is mainly due to low confidence, by data users, in electronically observed data. In this study, we set out to confirm that electronically observed data is of comparable quality to a human observer recorded data, and can thus be used to bridge data gaps at temporal and spatial scales. To assess this potential, we applied the simple Pearson correlation method and other statistical tests and approaches by conducting inter-comparison analysis of weather observations from the manual synoptic station and data from two Automatic Weather Stations (TAHMO and 3D-PAWS) co-located at KMD Headquarters to establish existing consistencies and variances in several weather parameters. Results show there is comparable consistency in most of the weather parameters between the three stations. Strong associations were noted between the TAHMO and manual station data for minimum (r = 0.65) and maximum temperatures (r = 0.86) and the maximum temperature between TAHMO and 3DPAWS (r = 0.56). Similar associations were indicated for surface pressure (r = 0.99) and RH (r > 0.6) with the weakest correlations occurring in wind direction and speed. The Shapiro test for normality assumption indicated that the distribution of several parameters compared between the 3 stations were normally distributed (p > 0.05). We conclude that these findings can be used as a basis for wider use of data sets from Automatic Weather Stations in Kenya and elsewhere. This can inform various applications in weather and climate related decisions.

Agrometeorological wheat yield prediction in rainfed Potohar region of Pakistan

The reliable early estimates of production had always been the prime concerns of growers on one hand and planners as well as policy makers for import/export on the other hand. This study represents a linear regression model making use of meteorological parameters at critical stages of crop’s life cycle to predict the wheat yield about two months earlier than the harvesting. A statistical based software “Statistical Package for Social Sciences” (SPSS) and MS-excel were employed as working tools. Decadal (ten days) agrometeorological data for Rabi season (for the period 1993-2011) being observed at Regional Agromet Centre, Rawalpindi have been utilized. The parameters studied for correlation were mainly rainfall (amount and days), air temperature (minimum, maximum, mean), heat units (on phenological basis), relative humidity, wind speed, sunshine duration, reference crop evapotran-spiration etc. Finally, minimum temperature, sunshine duration and rainfall amount in January (tillering and stem extension phase) proved to be the reliable predictors for the final yield. The correlation coefficients for these parameters on individual basis resulted within the acceptable range where as in aggregate it remained 0.87, an optimistic value.

The estimate of sea ice resources quantity in the Bohai Sea based on NOAA/AVHRR data

The research on sea ice resources is the academic base of sea ice exploitation in the Bohai Sea. According to the ice-water spectrum differences and the correlation between ice thickness and albedo, this paper comes up with a sea ice thickness inversion model based on the NOAA/AVHRR data. And then a sea ice resources quantity （SIQ） time series of Bohai Sea is established from 1987 to 2009. The results indicate that the average error of inversion sea ice thickness is below 30%. The maximum sea ice resources quantity is about 6×109 m3 and the minimum is 1.3×109 m3. And a preliminary analysis has been made on the errors of the estimate of sea ice resources quantity （SIQ）.

DIAGNOSIS OF WAVE ACTIVITY OVER RAINBAND OF LANDFALL TYPHOON

A generalized wave-activity density, which is defined as an absolute value of production of three-dimensional vorticity vector perturbation and gradient of general potential temperature perturbation, is introduced and its wave-activity law is derived in Cartesian coordinates. Constructed in an agoestrophic and nonhydrostatie dynamical framework, the generalized wave-activity law may be applicable to diagnose mesoscale weather systems leading to heavy rainfall. The generalized wave-activity density and wave-activity flux divergence were calculated with the objective analysis data to investigate the character of wave activity over heavy-rainfall regions. The primary dynamical processes responsible for disturbance associated with heavy rainfall were also analyzed. It was shown that the generalized wave-activity density was closely correlated to the observed 6-h accumulative rainfall. This indicated that the wave activity or disturbance was evident over the frontal and landfall-typhoon heavy-rainfall regions in middle and lower troposphere. For the landfall-typhoon rainband, the portion of generalized wave-activity flux divergence, denoting the interaction between the basic-state cyclonic circulation of landfall typhoon and mesoscale waves, was the primary dynamic process responsible for the evolution of generalized wave-activity density.

Evaluation of Simulated CO_2 Concentrations from the CarbonTracker-Asia Model Using In-situ Observations over East Asia for 2009–2013

The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).

A research progress review on regional extreme events

An extreme （weather and climate） event does not only mean that an extreme occurs at a location, but more generally it can impact a certainarea and last a certain period of time, which is defined as a regional extreme event （REE） with a certain impacted area and duration. The conceptof REE has been defined to allow mainly objective assessment of the events without a pre-determined boundary and duration. This paper reviewsthe studies on REEs published during the past 20 years, especially recent years. Mainly in view of methodology, these studies can be divided intothree types studies focusing on spatial simultaneity, studies focusing on temporal persistence, and studies identifying REEs. The methodsidentifying REEs include two kinds, e.g., type-I methods stressing REE＇s temporal persistence within a relatively certain area and type-IImethods focusing on catching a complete REE. Identification methods proposed in this paper could provide valuable information for variouspurposes, such as real-time monitoring, estimating long-term changes, mechanism diagnosis, forecasting study and even attribution analysis.Research on REEs is important for objectively defining extreme weather and climate events, which depends on the spatial and temporal scales ofinterest. Such an objective definition will support ongoing climate monitoring and improve the assessment of how regional extreme events havechanged over time.

Integrated water vapor during active and break spells of monsoon and its relationship with temperature,precipitation and precipitation efficiency over a tropical site

Global Positioning System(GPS)measurements of integrated water vapor(IWV)for two years(2014 and 2015)are presented in this paper.Variation of IWV during active and break spells of Indian summer monsoon has been studied for a tropical station Hyderabad(17.4°N,78.46°E).The data is validated with ECMWF Re-Analysis(ERA)91 level data.Relationships of IWV with other atmospheric variables like surface temperature,rain,and precipitation efficiency have been established through cross-correlation studies.A positive correlation coefficient is observed between IWV and surface temperature over two years.But the coefficient becomes negative when only summer monsoon months(June,July,August,and September)are considered.Rainfall during these months cools down the surface and could be the reason for this change in the correlation coefficient.Correlation studies between IWV-precipitation,IWVprecipitation efficiency(P.E),and precipitation-P.E show that coefficients are-0.05,-0.10 and 0.983 with 95%confidence level respectively,which proves that the efficacy of rain does not depend only on the level of water vapor.A proper dynamic mechanism is necessary to convert water vapor into the rain.The diurnal variations of IWV during active and break spells have been analyzed.The amplitudes of diurnal oscillation and its harmonics of individual spell do not show clear trends but the mean amplitudes of the break spells are approximately double than those of the active spells.The amplitudes of diurnal,semidiurnal and ter-diurnal components during break spells are 1.08 kg/m^(2),0.52 kg/m;and 0.34 kg/m;respectively.The corresponding amplitudes during active spells are 0.68 kg/m^(2),0.41 kg/m;and 0.23 kg/m;.

Parameter Calibration of SWMM Model Based on Optimization Algorithm

For the challenge of parameter calibration in the process of SWMM(storm water management model)model application,we use particle Swarm Optimization(PSO)and Sequence Quadratic Programming(SQP)in combination to calibrate the parameters and get the optimal parameter combination in this research.Then,we compare and analyze the simulation result with the other two respectively using initial parameters and parameters obtained by PSO algorithm calibration alone.The result shows that the calibration result of PSO-SQP combined algorithm has the highest accuracy and shows highly consistent with the actual situation,which provides a scientific and effective new idea for parameter calibration of SWMM model,moreover,has practical guidance for flood control and disaster mitigation.

Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

Monthly Forecast of Indian Southwest Monsoon Rainfall Based on NCEP’s Coupled Forecast System

The monthly forecast of Indian monsoon rainfall during June to September is investigated by using the hindcast data sets of the National Centre for Environmental Prediction (NCEP)’s operational coupled model (known as the Climate Forecast System) for 25 years from 1981 to 2005 with 15 ensemble members each. The ensemble mean monthly rainfall over land region of India from CFS with one month lead forecast is underestimated during June to September. With respect to the inter-annual variability of monthly rainfall it is seen that the only significant correlation coefficients (CCs) are found to be for June forecast with May initial condition and September rainfall with August initial conditions. The CFS has got lowest skill for the month of August followed by that of July. Considering the lower skill of monthly forecast based on the ensemble mean, all 15 ensemble members are used separately for the preparation of probability forecast and different probability scores like Brier Score (BS), Brier Skill Score (BSS), Accuracy, Probability of Detection (POD), False Alarm Ratio (FAR), Threat Score (TS) and Heidke Skill Score (HSS) for all the three categories of forecasts (above normal, below normal and normal) have been calculated. In terms of the BS and BSS the skill of the monthly probability forecast in all the three categories are better than the climatology forecasts with positive BSS values except in case of normal forecast of June and July. The “TS”, “HSS” and other scores also provide useful probability forecast in case of CFS except the normal category of July forecast. Thus, it is seen that the monthly probability forecast based on NCEP CFS coupled model during the southwest monsoon season is very encouraging and is found to be very useful.

Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC（Environmental Policy Integrated Climate） model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was ＆lt;0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.

A Preliminary Study on Rainfall Pattern before and after the January 26, 2001 Bhuj Earthquake (<i>M_w</i>7.7) over Kachchh Region of Western Peninsular, India

Under the influence of great debate on relation between earthquake and rainfall, some scientists have carried out detailed study and now commonly accepted that heavy rainfall can trigger earthquake at the faults or fractures depending upon the local geology. Here, an attempt is made to check relation between earthquake and rainfall with different scientific approaches. We have attempted to critically examine the relation between the Bhuj earthquake-aftershocks sequence and the rainfall pattern over the region as large earthquake (Mw 7.7) has occurred on January 26, 2001 in Kachchh region of western peninsular shield of India and the aftershocks are being reported till the date. We have analyzed rainfall data for 20 years, i.e. 10 years before and 10 years after the main shock of January 26, 2001, recorded by three meteorological observatories in the Kachchh region. We have studied annual total rainfall for two decades, annual rainfall departures from the climate normals, number of rainy days and number of heavy rainfall days during the period for all the three meteorological observatories of Kachchh region. We have found significant increase in all the measured rainfall parameters i.e. annual total rainfall, number of rainy days and number of heavy rainfall days over the Kachchh region during last decade i.e., from 2001 to 2010 after the main shock. Numbers of negative departures have been decreased during the last decade compared to previous decade. Thus rainfall pattern over Kachchh region is being changed. This increase in rainfall activity over Kachchh region may have been influenced by large earthquake and continuing aftershock activities over the region.

Application of Omori’s Decay Law to the 2001 Bhuj Aftershock Sequence for Kachchh Region of Western India

In the present study, the temporal behavior of 2001 Bhuj aftershock sequence in Kachchh region of western peninsular India is studied by the modified Omori law. The Omori law parameters p, c and K are determined with the standard errors by the maximum likelihood estimates using ZMAP algorithm in MatLab environment. The entire aftershock sequence is analyzed by diving it into three separate series with respect to time to weigh up the bigger earthquake of magnitude M 5.7 occurring on March 7, 2006 at Gedi fault. This study helps to understand the cumulative effect of the aftershocks generated by this bigger earthquake of the mainshock sequence. The results of this analysis are discussed with other studies of the different earthquake sequence for the different parts of the world and suggest that all the three series of Bhuj aftershock sequence follow the Omori relation. Values of parameter p vary significantly from series 1 to series 3, i.e., p-value varies significantly with time. Similarly, other two Omori law parameters K and c are also found to change significantly with time. These parameters are useful to describe temporal behavior of aftershocks and to forecast aftershock activity in time domain. Aftershock decay rate provides insight into stress release processes after the mainshock, thus helping to understand the heterogeneity of the fault zone properties and evaluate time-dependent seismic hazard analysis over the region.

Rainfall Estimation using Image Processing and Regression Model on DWR Rainfall Product for Delhi-NCR Region

Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.

Understanding the Evolution and Socio-Economic Impacts of the Extreme Rainfall Events in March-May 2017 to 2020 in East Africa

This study aimed at assessing the evolution, distribution and the socio-economic impacts of extreme rainfall over East Africa during the March, April and May (MAM) rainfall season focusing on assessing the trends and contribution of MAM rainfall in mean annual rainfall across the region. It employed Principal Component Analysis (PCA) methods to capture the patterns and variability of MAM rainfall. The PCA results indicated that the first Principal Component (PC) describe 17% of the total variance, while the first six PCs account only 53.5% of the total variance in MAM rainfall, underscoring the complexity of rainfall forcing factors in the region. It has been observed that MAM rainfall accounts about 30% - 60% of the mean annual rainfall in most parts of the region, signifying its importance in agriculture, water, energy and other socio-economic sectors. MAM has been characterized by increasing variability with varying trend patterns across the region. The MAM rainfall trend is not homogeneous across the region;some areas are experiencing a slight decreasing rainfall trend, while other areas are experiencing a slight increasing rainfall trend. The observed trend dynamics is consistent with the global trend patterns in precipitation as depicted in recent Intergovernmental Panel on Climate Change (IPCC) reports. Over the last five years MAM rainfall season have been characterized by record-breaking extremes. On 8th May 2017, Tanga and Mombasa meteorological stations recorded 316 mm and 235.1 mm of rainfall in 24 hours respectively, which are the highest amounts for these respective stations, since their establishment. Record highest 24 hours rainfall amounting to 134.9 mm and 119.4 mm were also observed at Buginyanya and Kawanda meteorological stations in Uganda on 18th March 2018 and 7th May 2020. On 6th May 2020, Byimana meteorological station in Rwanda, also observed 140.6 mm of rainfall in 24 hours, the highest since its establishment. These extremes have caused multiple losses of life and property, and severe damages to infrastructure. Unfortunately, the frequency and intensity of these extremes are projected to increase under a changing regional climate patterns. It is therefore important that more studies are carried out to enhance understanding about the evolution, dynamics and predictability of these extremes in East Africa region.

Physical properties of three short period close binaries:KIC 2715417,KIC 6050116 and KIC 6287172

We present the physical parameters of three short period close binaries using data observed from the Kepler Space Telescope. All of these observations were taken in a single bandpass(which approximates the Johnson V-band). Our three systems are KIC 2715417, KIC 6050116 and KIC 6287172. The first system, KIC 2715417, is considered a semi-detached system with the secondary component filling its Roche lobe. The second system, KIC 6050116, is an overcontact system, while the third system, KIC 6287172, belongs to ellipsoidal variables as deduced from the Roche lobe geometry. For photometric analysis, we used the PHOEBE software package, which is based on the Wilson-Devinney code. Due to lack of spectroscopic data, the photometric mass ratios are determined from the analyses of light curves using the q-search method. The absolute parameters are determined using three different methods(Harmanec, Maceroni &Van'tVeer and Gazeas & Niarchos).

Comparison of trends and frequencies of drought in central North China and sub- Saharan Africa from 1901 to 2010

This study compares the trends and frequencies of drought between central North China(CNC) and(SSA) for the periods 1901–2010 and 1951–2010. The Standardized Precipitation Evapotranspiration Index(SPEI) and Self-Calibrating Palmer Drought Severity Index(sc-PDSI) are used to assess the drought trends and frequencies. In general, the results exhibit downward trends of drought index values and upward trends of drought frequencies over CNC and SSA. A high rate of the trends' slopes for the drought index and a low rate of the frequencies' slopes is found over CNC with respect to SPEI and sc-PDSI. Furthermore, some abrupt changes are revealed after applying the sequential Mann–Kendall test to detect change points. These findings offer insight into the trends and frequencies of drought over the regions studied. Further analysis needs to be undertaken to understand the mechanisms underlying the occurrence of drought in these areas.

Impact of climate change on agriculture during winter season over Pakistan

This study has been carried out to investigate the impact of climate change over Pakistan and its surrounding areas (60° - 80°E and 20°- 40° N) during winter seasons (December-February). Variability in three meteorological parameters such as: rainfall;air temperature;and moisture transport, has been investigated. Global Pre- cipitation Climatology Center (GPCC) data for precipitation and National Centre for Environ- mental Prediction (NCEP) reanalysis data for computation of Moisture Flux Convergence (MFC) and temperature have been used for the period of 49 years (1961 to 2009). The study period has been divided into three phases on basis of pre- cipitation anomaly i.e., before climate change scenario (1961-1985), transition period (1986- 1999) and after climate change scenario (2000- 2009).Variability in precipitation has been ob- served in three different ways such as, slightly increase in magnitudes, decrease in rainy days and shifting of precipitation pattern towards south of the country. Moisture transport from the surrounding has decreased with increase in precipitation which is indirectly associated with decreases in mass deposit on the glaciers. In- crease in temperature is more prominent over upper and lower part as compared to the central parts of the country. Uncertainty in precipitation has also been observed. Shift of precipitation over southern parts showed positive impact over agriculture sector. As a result, Rabi crop yield has increased during last decade over southern parts of the country.