Explore the vast range of titles available.

Agriculture is one of the most climate-sensitive of all economic sectors. In many countries, such as the fourexamined in Looking Beyond the Horizon, the risks of climate change are an immediate and fundamentalproblem because the majority of the rural population depends either directly or indirectly on agriculture forits livelihood.The risks of climate change to agriculture cannot be eff ectively dealt with—and the opportunities cannot beeff ectively exploited—without a clear plan for aligning agricultural policies with climate change, developingthe capabilities of key agricultural institutions, and investing in infrastructure, support services, and on-farmimprovements. Developing such a plan ideally involves a combination of high-quality quantitative analysis;consultation with key stakeholders, particularly farmers and local agricultural experts; and investments inboth human and physical capital. The diverse experiences of Albania, the former Yugoslav Republic ofMacedonia, Moldova, and Uzbekistan, highlighted in this book, show that it is possible to develop a plan tomeet these objectives—one that is comprehensive and empirically driven as well as consultative and quickto develop.The approach of this volume is predicated on strong country ownership and participation, and is defi ned byits emphasis on \"win-win\" or \"no regrets\" solutions to the multiple challenges posed by climate change for thefarmers of Eastern Europe and Central Asia. The solutions are measures that increase resilience to futureclimate change, boost current productivity despite the greater climate variability already occurring, and limitgreenhouse gas emissions—also known as \"climate-smart agriculture.\"Looking Beyond the Horizon draws on the experiences of applying this approach to these four nations inEastern Europe and Central Asia with the goal of helping each country mainstream climate changeadaptation into its agricultural policies, programs, and investments. The book also highlights the projectedimpacts of climate change on agriculture in these countries through forecast variations in temperature andrainfall patterns, which are crucial to farming, and off ers a map for navigating the risks and realizingthe opportunities. Finally, a detailed e xplanation of the approach, as well as lessons learned from itsimplementation, is provided for those who would like to implement similar programs in other countries ofEurope, Central Asia, or anywhere else in the world.

\"China's Strategic Multilateralism: China sometimes plays a leadership role in addressing global challenges, but at other times it free-rides or even spoils efforts at cooperation. When will rising powers like China help to build and maintain international regimes that sustain cooperation on important issues, and when will they play less constructive roles? This study argues that the strategic setting of a particular issue area has a strong influence on whether and how a rising power will contribute to global governance. Two strategic variables are especially important: the balance of outside options that the rising power and established powers face, and whether contributions by the rising power are viewed as indispensable to regime success. Case studies of China's approach to security in Central Asia, nuclear proliferation, global financial governance, and climate change illustrate the logic of the theory, which has implications for contemporary issues such as China's growing role in development finance\"-- Provided by publisher.

The CORDEX-CORE initiative was developed with the aim of producing homogeneous regional climate model (RCM) projections over domains world wide. In its first phase, two RCMs were run at 0.22° resolution downscaling 3 global climate models (GCMs) from the CMIP5 program for 9 CORDEX domains and two climate scenarios, the RCP2.6 and RCP8.5. The CORDEX-CORE simulations along with the CMIP5 GCM ensemble and the most recently produced CMIP6 GCM ensemble are analyzed, with focus on several temperature, heat, wet and dry hazard indicators for present day and mid-century and far future time slices. The CORDEX-CORE ensemble shows a better performance than the driving GCMs for several hazard indices due to its higher spatial resolution. For the far future time slice the 3 ensembles project an increase in all temperature and heat indices analyzed under the RCP8.5 scenario. The largest increases are always shown by the CMIP6 ensemble, except for Tx > 35 °C, for which the CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected to increase by the RCM ensemble over the la Plata basin in South America, the Congo basin in Africa, east North America, north east Europe, India and Indochina, regions where a better performance is obtained, whereas the GCM ensembles show small or negligible signals. Compound hazard hotspots based on heat, drought and wet indicators are detected in each continent worldwide in region like Central America, the Amazon, the Mediterranean, South Africa and Australia, where a linear relation is shown between the heatwave and drought change signal, and region like Arabian peninsula, the central and south east Africa region (SEAF), the north west America (NWN), south east Asia, India, China and central and northern European regions (WCE, NEU) where the same linear relation is found for extreme precipitation and HW increases. Although still limited, the CORDEX-CORE initiative was able to produce high resolution climate projections with almost global coverage and can provide an important resource for impact assessment and climate service activities.

Mangrove forests are highly productive tidal saline wetland ecosystems found along sheltered tropical and subtropical coasts. Ecologists have long assumed that climatic drivers (i.e., temperature and rainfall regimes) govern the global distribution, structure, and function of mangrove forests. However, data constraints have hindered the quantification of direct climate—mangrove linkages in many parts of the world. Recently, the quality and availability of global-scale climate and mangrove data have been improving. Here, we used these data to better understand the influence of air temperature and rainfall regimes upon the distribution, abundance, and species richness of mangrove forests. Although our analyses identify global-scale relationships and thresholds, we show that the influence of climatic drivers is best characterized via regional range-limit-specific analyses. We quantified climatic controls across targeted gradients in temperature and/or rainfall within 14 mangrove distributional range limits. Climatic thresholds for mangrove presence, abundance, and species richness differed among the 14 studied range limits. We identified minimum temperature-based thresholds for range limits in eastern North America, eastern Australia, New Zealand, eastern Asia, eastern South America, and southeast Africa. We identified rainfall-based thresholds for range limits in western North America, western Gulf of Mexico, western South America, western Australia, Middle East, northwest Africa, east central Africa, and west-central Africa. Our results show that in certain range limits (e.g., eastern North America, western Gulf of Mexico, eastern Asia), winter air temperature extremes play an especially important role. We conclude that rainfall and temperature regimes are both important in western North America, western Gulf of Mexico, and western Australia. With climate change, alterations in temperature and rainfall regimes will affect the global distribution, abundance, and diversity of mangrove forests. In general, warmer winter temperatures are expected to allow mangroves to expand poleward at the expense of salt marshes. However, dispersal and habitat availability constraints may hinder expansion near certain range limits. Along arid and semiarid coasts, decreases or increases in rainfall are expected to lead to mangrove contraction or expansion, respectively. Collectively, our analyses quantify climate–mangrove linkages and improve our understanding of the expected global- and regional-scale effects of climate change upon mangrove forests.

We study the impact of recent global warming on extreme climatic events in Central Asia (CA) for 1901-2019 by comparing the composite representation of the observational climate with a hypothetical counterfactual one that does not include the long-term global warming trend. The counterfactual climate data are produced based on a simple detrending approach, using the global mean temperature (GMT) as the independent variable and removing the long-term trends from the climate variables of the observational data. This trend elimination is independent of causality, and the day-to-day variability in the counterfactual climate remains preserved. The analysis done in the paper shows that the increase in frequency and magnitude of extreme temperature and precipitation events can be attributed to global warming. Specifically, the probability of experiencing a +7 K temperature anomaly event in CA increases by up to a factor of seven in some areas due to global warming. The analysis reveals a significant increase in heatwave occurrences in Central Asia, with the observational climate dataset GSWP3-W5E5 (later called also factual) showing more frequent and prolonged extreme heat events than hypothetical scenarios without global warming. This trend, evident in the disparity between factual and counterfactual data, underscores the critical impact of recent climatic changes on weather patterns, highlighting the urgent need for robust adaptation and mitigation strategies. Additionally, using the self-calibrated Palmer drought severity index (scPDSI), the sensitivity of dry and wet events to the coupled precipitation and temperature changes is analyzed. The areas under dry and wet conditions are enhanced under the observational climate compared to a counterfactual scenario, especially over the largest deserts in CA. The expansion of the dry regions aligns well with the pattern of desert development observed in CA in recent decades.

This study investigates the attribution of climate change to trends in river discharge during six decades from 1955 until 2014 in 12 selected river catchments across six Central Asian countries located upstream of the main rivers. For this purpose, the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model) was firstly calibrated and validated for all study catchments. Attributing climate change to streamflow simulation trends was forced by factual (reanalysis) and counterfactual climate data (assuming the absence of anthropogenic influence) proposed in the framework of the ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) or ESM without anthropogenic forcing that were firstly tested and then compared. The trend analysis was performed for three variables: mean annual discharge and high flow (Q5) and low flow (Q95) indices. The results show that trends in the annual and seasonal discharge could be attributed to climate change for some of the studied catchments. In the three northern catchments (Derkul, Shagan, and Tobol), there are positive trends, and in two catchments (Sarysu and Kafirnigan), there are negative streamflow trends under the factual climate, which could be attributed to climate change. Also, our analysis shows that the average level of discharge in Murghab has increased during the historical study period due to climate change, despite the overall decreasing trend during this period. In addition, the study reveals a clear signal of shifting spring streamflow peaks in all catchments across the study area.

The climate is changing, and the Eastern Europe and Central Asia (ECA) region is vulnerable to the consequences. Many of the region's countries are facing warmer temperatures, a changing hydrology, and more extremes, droughts, floods, heat waves, windstorms, and forest fires. This book presents an overview of what adaptation to climate change might mean for Eastern Europe and Central Asia. It starts with a discussion of emerging best-practice adaptation planning around the world and a review of the latest climate projections. It then discusses possible actions to improve resilience organized around impacts on health, natural resources (water, biodiversity, and the coastal environment), the 'unbuilt' environment (agriculture and forestry), and the built environment (infrastructure and housing). The last chapter concludes with a discussion of two areas in great need of strengthening given the changing climate: disaster preparedness and hydro-meteorological services. This book has four key messages: a) contrary to popular perception, Eastern Europe and Central Asia face significant threats from climate change, with a number of the most serious risks already in evidence; b) vulnerability over the next 10 to 20 years is likely to be dominated by socioeconomic factors and legacy issues; c) even countries and sectors that stand to benefit from climate change are poorly positioned to do so; and d) the next decade offers a window of opportunity for ECA countries to make their development more resilient to climate change while reaping numerous co-benefits.

This study uses a new dataset on gauge locations and catchments to assess the impact of 21st-century climate change on the hydrology of 221 high-mountain catchments in Central Asia. A steady-state stochastic soil moisture water balance model was employed to project changes in runoff and evaporation for 2011–2040, 2041–2070, and 2071–2100, compared to the baseline period of 1979–2011. Baseline climate data were sourced from CHELSA V21 climatology, providing daily temperature and precipitation for each subcatchment. Future projections used bias-corrected outputs from four General Circulation Models under four pathways/scenarios (SSP1 RCP 2.6, SSP2 RCP 4.5, SSP3 RCP 7.0, SSP5 RCP 8.5). Global datasets informed soil parameter distribution, and glacier ablation data were integrated to refine discharge modeling and validated against long-term catchment discharge data. The atmospheric models predict an increase in median precipitation between 5.5% to 10.1% and a rise in median temperatures by 1.9 °C to 5.6 °C by the end of the 21st century, depending on the scenario and relative to the baseline. Hydrological model projections for this period indicate increases in actual evaporation between 7.3% to 17.4% and changes in discharge between + 1.1% to –2.7% for the SSP1 RCP 2.6 and SSP5 RCP 8.5 scenarios, respectively. Under the most extreme climate scenario (SSP5-8.5), discharge increases of 3.8% and 5.0% are anticipated during the first and second future periods, followed by a decrease of -2.7% in the third period. Significant glacier wastage is expected in lower-lying runoff zones, with overall discharge reductions in parts of the Tien Shan, including the Naryn catchment. Conversely, high-elevation areas in the Gissar-Alay and Pamir mountains are projected to experience discharge increases, driven by enhanced glacier ablation and delayed peak water, among other things. Shifts in precipitation patterns suggest more extreme but less frequent events, potentially altering the hydroclimate risk landscape in the region. Our findings highlight varied hydrological responses to climate change throughout high-mountain Central Asia. These insights inform strategies for effective and sustainable water management at the national and transboundary levels and help guide local stakeholders.

Pan Third Pole (PTP) region includes Tibet Plateau (TP), Central Asia (CA) and Southeast Asia (SEA) and it is one of the places on earth that are most sensitive to climate change. Meanwhile, PTP origins a series of large rivers such as Yangtze River, Yellow River and Lancang-Mekong River, which feed millions of people downstream. Therefore, climate change in PTP has significant impact on livings and water supply of local residents. In this study, 16 model predictions from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) and Climate Research Unit (CRU) observations are used to evaluate historical precipitation and temperature climatology changes in PTP region for the far (1901–1930), middle (1941–1970) and near history (1981–2010) respectively. In addition, Bayesian model averaging (BMA) approach is applied to obtain the multi-model weighted average prediction and the BMA values are further used to assess the climate variabilities in the near (2021–2050), middle (2046–2075) and far future (2071–2100) under four SSP-RCP scenarios. Results indicate that temperature is significantly underestimated by most CMIP6 models in TP especially IPSL-CM6A-LR and CanESM5 whereas precipitation is overestimated for CA and TP. Most CMIP6 models do not predict precipitation very well in SEA, the difference of annual total precipitation between the highest estimation from UKESM1-0-LL and the lowest estimation from CAMS-CSM1-0 is about 800 mm. Overall, BMA prediction is more reliable compared with individual models. In addition, Pan Third Pole region is projected to be warmer and wetter in the future and the trend is stronger under SSP5-8.5 scenario. The BMA predicted temperature uncertainty is larger for high latitude CA region whereas precipitation uncertainty is higher for low latitude SEA region.