ABSTRACT

In the 21st century, climate change is considered one of the greatest environmental threats to the world, and it has greater negative impacts on human society and the natural environment. All the IPCC's reports concluded that we should prepare scenarios and strategies for under the conditions of forthcoming global change. This study presents the projections of future changes under HadCM3 A2a and HadCM3 B2a SRES scenarios using the statistical downscaling model (SDSM) in the period (2020-2099) and their link to the planning of sustainable development in Libya. Results of downscaling show that the SDSM model can be well acceptable regard its performance. The result of the SDSM model showed great reliability of SDSM in ascertaining changes for the periods; (2020-2039), (2040-2059), (2060-2079) and (2080-2099), relative to 1961–1990. Trend analysis in Libya showed an increase in average annual and monthly temperature, compared to the baseline period for both HadCM3A2a and HadCM3B2a scenarios in both the dry and wet seasons. Thus, there is likely to be a significant warming in local surface temperature, which is enough for a significant change on the energy balance and is likely to affect water availability. The SDSM is well to help decision-makers understand the expectations of the change in extreme temperatures in the future and its environmental and economic impacts and social in Libya.

Keywords: Statistical downscaling model, SDSM, Intergovernmental Panel on Climate Change IPCC, General circulation model, GCM, HadCM3 Hadley Climate Model version, Temperature, Libya.

Abstract

All the IPCC's five reports between 1990 and 2013 concluded that we cannot expect stable climate in the future and we should prepare scenarios and strategies for the survival of humankind under the conditions of forthcoming global change. The study describes the application of statistical downscaling method (SDSM) to downscale maximum temperature data. In order to explore the SDSM method, the Kufra station in Libya has been selected as a study site to test the methodology for maximum temperature. The study included calibration and validate with large-scale atmospheric variables encompassing NCEP reanalysis data, the future estimation due to a climate scenario, which are HadCM3 A2 and HadCM3 B2. Results of downscaling show that during the calibration and validation stage, the SDSM model can be well acceptable regard its performance in the downscaling of daily maximum temperature.

Trend analysis in the study area showed an increase in average annual and monthly maximum temperature, compared to the baseline period for both HadCM3A2a and HadCM3B2a scenarios in both the dry and wet seasons. The average annual maximum temperature in Kufra area is predicted to increase by 1. 3°C and 1.4°C by the 2020s (2011-2040) under the A2 and B2 scenarios respectively. By the 2050s (2041-2070) the increase is predicted to be 1.4°C, 1.7°C under the both A2 and B2 scenarios. By the 2080s, (2071-2099) the average annual maximum temperature is predicted to increase by 1.9 °C and 1.4°C under A2 and B2.

However, there is likely to be a significant warming in local surface temperature, which is enough for a significant change on the energy balance and is likely to impact water availability.

Keywords: - SDSM Statistical downscaling model, IPCC Intergovernmental Panel on Climate Change, GCM General Circulation model, SERS Special Report on the Emission Scenarios, HadCM3 Hadley Climate Model version.

ABSTRACT

In the 21st century, climate change is considered to be one of the greatest environmental

threats to the world, and the changes in climate extremes are estimated to have greater

negative impacts on human society and the natural environment than the changes in mean

climate.

All the IPCC's five reports between 1990 and 2013 concluded that we cannot expect stable

climate in the future and we should prepare scenarios and strategies for the survival of

humankind under the conditions of forthcoming global change.

This study presents the projections of future changes in maximum temperature events under

A2 and B2 SRES scenarios using the statistical downscaling model (SDSM) in the Zlitan

Area–Libya.

In order to explore the SDSM method, at Zlitan station in Libya has been selected as a study

site to test the methodology for maximum temperature. The study included calibration and

validate with large-scale atmospheric variables encompassing NCEP reanalysis data, the

future estimation due to a climate scenario, which are HadCM3 A2 and HadCM3 B2 . Results

of downscaling show that during the calibration and validation stage, the SDSM model can be

well acceptable regard its performance in the downscaling of daily maximum temperature.

The result of climate projection reveals that the SDSM model showed great reliability of

SDSM in ascertaining changes for the periods 2011–2040, 2041–2070 and 2071–2099,

• relative to 1961–1990 and it has very good ability to replicate the historical maximum

temperature for the observed period. Trend analysis in the study area showed an increase in

average annual and monthly maximum temperature, compared to the baseline period for both

HadCM3A2a and HadCM3B2a scenarios in both the dry and wet seasons.

However, this increase is higher in dry months than wet months for all future time horizons

and for both HadCM3A2a and HadCM3B2a scenarios. Thus there is likely to be a significant

warming in local surface temperature, which is enough for a significant change on the energy

balance and is likely to impact water availability.

Keywords: - Statistical downscaling model, SDSM, Intergovernmental Panel on Climate

Change IPCC, General circulation model, GCM, Special Report on the Emission Scenarios,

SERS, HadCM3 Hadley Research Center’s Hadley Climate Model version, Maximum

• temperature, Zlitan area, Libya.

АННОТАЦИЯ:

Through the last three decades, the Normalized Difference Vegetation Index (NDVI) has been widely used for vegetation mapping and monitoring land-cover change in semi-arid regions. In Libya semi-arid lands occupy many parts in the north part of country that is near the Mediterranean Sea. The aim of paper is to use remote sensing technique (NDVI) for monitoring vegetation degradation in Al-Jabal Al-Akhdar region in Libya. The Pathfinder AVHRR Land (PAL), SPOT Apparent green cover percentage data and MODIS Vegetation index are used to monitor the vegetation cover change in the study area. The paper explain the possibility of use only long term NOAA-AVHRR NDVI time-series data, without need to any precipitation data, for assessing desertification conditions in Al-Jabal Al-Akhdar region. According to annual rainfall the northern parts of the area receives the greatest amount of rainfall towards the Mediterranean Sea, which occurs between October and May, it agreed well with the spatial pattern of NDVI within monthly averaged of vegetation that start increasing rapidly and reached a greater amount during spring (March-May), and decreased during June to September...

Abstract

There is much discussion in the scientific literature and concern in the wider community about climate

change, recent climate analyses indicate that the magnitude of 21st Century warming is likely to have been the

largest of any century for the last 1000 years over the northern hemisphere. All the IPCC's four reports between

1990 and 2007 concluded that we cannot expect stable climate in the future and we should prepare scenarios

and strategies for the survival of humankind under the conditions of forthcoming global change. In this study,

the applicability of the statistical downscaling model (SDSM) in downscaling temperature in Misurata area -

Libya, was investigated. The investigation includes the calibration of the SDSM model by using large-scale

atmospheric variables encompassing NCEP reanalysis data, the validation of the model were measured daily

temperature data (1961-1990) using independent period of the NCEP reanalysis data and the general circulation

model (GCM) outputs of scenarios A2 and B2 of the HadCM3 model. The model is calibrated and applied at a

daily time series, even though the output is monthly and the prediction of the future regional maximum and

minimum temperature scenarios for three time windows: 2011-2040, 2041-2070 and 2071-2099. The results showed

that: The statistical downscaling model (SDSM) was able to describe the basic statistical properties of daily

minimum and maximum temperature in the period of record, suggesting that it could be used to predict future

trends. Trend analysis in the study area showed an increase in average annual and monthly temperature,

compared to the baseline period for both HadCM3A2a and HadCM3B2a scenarios in both the dry and wet

seasons. However, this increase is higher in dry months than wet months for all future time horizons and for

both HadCM3A2a and HadCM3B2a scenarios. Thus there is likely to be a significant warming in local surface

temperature, which is enough for a significant change on the energy balance and is likely to impact water

availability.

Key words: Statistical downscaling model SDSM Intergovernmental Panel on Climate Change

IPCC General circulation model GCM Special Report on the Emission Scenarios SERS

Maximum and minimum temperature Misurata area Libya

Abstract

Most of Arabic countries are located within the arid and semi-arid zones, which are characterised by the scarcity and the high spatial and temporary variability of rainfall .The influence of rainfall patterns on natural vegetation cover is significant and can be monitored and assessed using NDVI indices derived from remote sensing data. The literature stresses on the wide use of NDVI to study the changes in vegetation cover, because of the sensitivity of vegetation to the Red and Infra-red spectrum. In this paper the SPOT Apparent Green Cover Percentage data and MODIS Vegetation index are used to monitor the vegetation cover change in North western Libya. The aim of this study is to establish the spatial and temporal changes in vegetation cover and their relation to the rainfall pattern. The data and method: The utilized data for research included multi-temporal remotely sensed data (Spot, MODIS, and Landsat ETM), climatic data (ground stations and satellite data) and digital maps (DEM, slope, flow direction and basins). The satellite images were firstly pre-processed. This included the importing of different format images into a standard format of the ERDAS IMAGINE 9.1. Then the dataset were geometrically corrected into the WGS84 latitude/longitude geographic co-ordinate system. The study area was then subseted using a vector file representing the area boundary (AOI). The multibands were stacked to create time series, the NDVI equation was used to convert the DN values into NDVI values.