Spatial and temporal patterns of indicators of climate change and variability in the Arab world in the past four decades.

A comprehensive assessment of the spatial and temporal patterns of the most common indicators of climate change and variability in the Arab world in the past four decades was carried out. Monthly maximum and minimum air temperature and precipitation amount data for the period 1980-2018 were obtained from the CHELSA project with a resolution of 1 km2, which is suitable for detecting local geographic variations in climatic patterns. This data was analyzed using a seasonal-Kendall metric, followed by Sen's slope analysis. The findings indicate that almost all areas of the Arab world are getting hotter. Maximum air temperatures increased by magnitudes varying from 0.027 to 0.714 °C/decade with a mean of 0.318 °C/decade while minimum air temperatures increased by magnitudes varying from 0.030 to 0.800 °C/decade with a mean of 0.356 °C/decade. Most of the Arab world did not exhibit clear increasing or decreasing precipitation trends. The remaining areas showed either decreasing or increasing precipitation trends. Decreasing trends varied from -0.001 to -1.825 kg m-2/decade with a mean of -0.163 kg m-2/decade, while increasing trends varied from 0.001 to 4.286 kg m-2/decade with a mean of 0.366 kg m-2/decade. We also analyzed country-wise data and identified areas of most vulnerability in the Arab world.

TRMM 3B43 Product-Based Spatial and Temporal Anatomy of Precipitation Trends: Global Perspective.

This study harnessed some of the many opportunities provided by the TRMM 3B43 data in order to generate maps illustrating the spatial and temporal distribution of significant linear rates of change of annual total precipitation for the surface of earth bounded by latitudes 50° S and 50° N for the years 1998-2018 by applying pixel-based simple linear regression. These maps are valuable for many applications and should enhance our understanding of the global precipitation patterns and trigger more research in order to explain what has not been explained. It has been found that the whole study area had a mean significant linear rate of change of - 0.4 mm/year. Nearly half of its area had significant linear rates of increase with a mean of 8.5 mm/year while the other half had significant linear rates of decrease with mean of - 7.6 mm/year. Landmass alone can be divided into nearly two halves; the first had significant linear rates of increase with a mean of 5.2 mm/year while the second had significant linear rates of decrease with mean of - 7.0 mm/year. Water areas alone also can nearly be divided into two halves; the first showed significant linear rates of increase with a mean of 9.6 mm/year while the second showed significant linear rates of decrease with mean of - 7.8 mm/year. Grouping the whole study area into six climatic zones and 21 administrative land and water regions and applying pixel-based Tukey test showed that the obtained significant linear rates of change varied significantly among these climatic and administrative regions.

Spatial and temporal characteristics of cancer in the period from 2004 to 2013 in the Hashemite Kingdom of Jordan.

Cancer in Jordan is a major public health problem and the second leading cause of death after heart disease. This study aimed at studying the spatial and temporal characteristics of cancer in Jordan and its 12 governorates for the period 2004-2013 to establish a baseline for future research and identification of cancer risk factors paving the way for developing a cancer control plan in the country. Numerical and graphical summaries, time-series additive seasonal decomposition, the method of least squares, and spacetime scan statistics were applied in a geographic information systems environment. Although the results indicate that the cancer incidence in Jordan is comparatively low, it is increasing over time. In the 10-year study period, a total of 44,741 cases was reported with a mean annual crude incidence rate of 68.4 cases/100,000, mean annual age-adjusted incidence rate of 111.9 cases/100,000, and a monthly rate increase of 1.2 (cases/100,000)/month. This study also revealed that the spatial and temporal characteristics of cancer vary among the governorates. Amman, which includes the capital city and hosts more than one-third of the population of the country, reported 61.0% of the total number of cases. Amman also reported the highest annual crude incidence rate (105.3 cases/100,000), the highest annual age-adjusted incidence rate (160.6 cases/100,000), and the highest rate of increase (0.7 (cases/100,000)/month) forming a high-rate cluster. Excluding the three governorates Amman, Balqa, and Ma'daba, low-rate clusters were found with regard to the remaining governorates. All governorates, except Irbid and Mafraq, showed significant rates of increase of cancer incidence. However, no clear seasonality pattern with respect to cancer incidence was discerned.

Exploring recent spatial patterns of cutaneous leishmaniasis and their associations with climate in some countries of the Middle East using geographical information systems.

This study explores the spatial trends of cutaneous leishmaniasis (CL) and characterises the relationships between the observed spatial patterns and climate in Jordan, Syria, Iraq and Saudi Arabia in 2009. Areal interpolation revealed the presence of four major hotspots of relatively high incidence rates covering most parts of Syria, central parts of Iraq, and north-western, central, south-eastern and south-western parts of Saudi Arabia. The severity of these hotspots was seen to decrease from high to low latitudes. The spatial patterns could be partly linked to precipitation (the higher the precipitation, the higher the incidence rates) and to a lesser degree to temperature (the lower the temperature, the higher the incidence rates). No significant relationship was deduced between the observed spatial patterns of incidence rates and humidity. However, these three climatic factors could be used jointly as explanatory variables (ceteris paribus) to explain part of the spatial variations of the CL incidence rates in the study area by applying geographically weighted regression.