Fast versus slow response in climate change: implications for the global hydrological cycle

Recent studies have shown that changes in global mean precipitation are larger for solar forcing than for CO2 forcing of similar magnitude.In this paper, we use an atmospheric general circulation model to show that the differences originate from differing fast responses of the climate system. We estimate the adjusted radiative forcing and fast response using Hansen's ``fixed-SST forcing'' method.Total climate system response is calculated using mixed layer simulations using the same model. Our analysis shows that the fast response is almost 40% of the total response for few key variables like precipitation and evaporation. We further demonstrate that the hydrologic sensitivity, defined as the change in global mean precipitation per unit warming, is the same for the two forcings when the fast responses are excluded from the definition of hydrologic sensitivity, suggesting that the slow response (feedback) of the hydrological cycle is independent of the forcing mechanism. Based on our results, we recommend that the fast and slow response be compared separately in multi-model intercomparisons to discover and understand robust responses in hydrologic cycle. The significance of this study to geoengineering is discussed.

Forest policies and programs affecting vulnerability and adaptation to climate change

Due to large scale afforestation programs and forest conservation legislations, India's total forest area seems to have stabilized or even increased. In spite of such efforts, forest fragmentation and degradation continues, with forests being subject to increased pressure due to anthropogenic factors. Such fragmentation and degradation is leading to the forest cover to change from very dense to moderately dense and open forest and 253 km(2) of very dense forest has been converted to moderately dense forest, open forest, scrub and non-forest (during 2005-2007). Similarly, there has been a degradation of 4,120 km(2) of moderately dense forest to open forest, scrub and non-forest resulting in a net loss of 936 km(2) of moderately dense forest. Additionally, 4,335 km(2) of open forest have degraded to scrub and non-forest. Coupled with pressure due to anthropogenic factors, climate change is likely to be an added stress on forests. Forest sector programs and policies are major factors that determine the status of forests and potentially resilience to projected impacts of climate change. An attempt is made to review the forest policies and programs and their implications for the status of forests and for vulnerability of forests to projected climate change. The study concludes that forest conservation and development policies and programs need to be oriented to incorporate climate change impacts, vulnerability and adaptation.

A macroeconomic analysis of adaptation to climate change impacts on forests in India

We examine the potential for adaptation to climate change in Indian forests, and derive the macroeconomic implications of forest impacts and adaptation in India. The study is conducted by integrating results from the dynamic global vegetation model IBIS and the computable general equilibrium model GRACE-IN, which estimates macroeconomic implications for six zones of India. By comparing a reference scenario without climate change with a climate impact scenario based on the IPCC A2-scenario, we find major variations in the pattern of change across zones. Biomass stock increases in all zones but the Central zone. The increase in biomass growth is smaller, and declines in one more zone, South zone, despite higher stock. In the four zones with increases in biomass growth, harvest increases by only approximately 1/3 of the change in biomass growth. This is due to two market effects of increased biomass growth. One is that an increase in biomass growth encourages more harvest given other things being equal. The other is that more harvest leads to higher supply of timber, which lowers market prices. As a result, also the rent on forested land decreases. The lower prices and rent discourage more harvest even though they may induce higher demand, which increases the pressure on harvest. In a less perfect world than the model describes these two effects may contribute to an increase in the risk of deforestation because of higher biomass growth. Furthermore, higher harvest demands more labor and capital input in the forestry sector. Given total supply of labor and capital, this increases the cost of production in all the other sectors, although very little indeed. Forestry dependent communities with declining biomass growth may, however, experience local unemployment as a result.

Assessing Indian cities for vulnerability to climate change

This paper critically evaluates the vulnerability of Indian cities to climate change in the context of sustainable development. City-scale indicators are developed for multiple dimensions of security and vulnerability. Factor analysis is employed to construct a vulnerability ranking of 46 major Indian cities. The analysis reveals that high aggregate levels of wealth do not necessarily make a city less vulnerable. Two, cities with diversified economic opportunities could adapt better to the new risks posed by climate change, than cities with unipolar opportunities. Three, highly polluted cities are more vulnerable to the health impacts of climate change, and cities with severe groundwater depletion will find it difficult to cope with increased rainfall variability. Policy and sustainability issues are discussed for these results.

Fast and slow climate responses to CO2 and solar forcing: A linear multivariate regression model characterizing transient climate change

Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

Integrated modelling approaches to analysis of climate change impacts on forests and forest management

This paper reviews integrated economic and ecological models that address impacts and adaptation to climate change in the forest sector. Early economic model studies considered forests as one out of many possible impacts of climate change, while ecological model studies tended to limit the economic impacts to fixed price-assumptions. More recent studies include broader representations of both systems, but there are still few studies which can be regarded fully integrated. Full integration of ecological and economic models is needed to address forest management under climate change appropriately. The conclusion so far is that there are vast uncertainties about how climate change affects forests. This is partly due to the limited knowledge about the global implications of the social and economical adaptation to the effects of climate change on forests.

Climate change and forests in India

Forests play a critical role in addressing climate change concerns in the broader context of global change and sustainable development. Forests are linked to climate change in three ways. i) Forests are a source of greenhouse gas (GHG) emissions: ii) Forests offer mitigation opportunities to stabilise GHG concentrations: iii) Forests are impacted by climate change. This paper reviews studies related to climate change and forests in India: first, the studies estimating carbon inventory for the Indian land use change and forestry sector (LUCF), then the different models and mitigation potential estimates for the LUCF sector in India. Finally it reviews the studies on the impact of climate change on forest ecosystems in India, identifying the implications for net primary productivity and bio-diversity. The paper highlights data, modelling and research gaps relevant to the GHG inventory, mitigation potential and vulnerability and impact assessments for the forest sector in India.

Reservoir performance under uncertainty in hydrologic impacts of climate change

Relatively few studies have addressed water management and adaptation measures in the face of changing water balances due to climate change. The current work studies climate change impact on a multipurpose reservoir performance and derives adaptive policies for possible futurescenarios. The method developed in this work is illustrated with a case study of Hirakud reservoir on the Mahanadi river in Orissa, India,which is a multipurpose reservoir serving flood control, irrigation and power generation. Climate change effects on annual hydropower generation and four performance indices (reliability with respect to three reservoir functions, viz. hydropower, irrigation and flood control, resiliency, vulnerability and deficit ratio with respect to hydropower) are studied. Outputs from three general circulation models (GCMs) for three scenarios each are downscaled to monsoon streamflow in the Mahanadi river for two future time slices, 2045-65 and 2075-95. Increased irrigation demands, rule curves dictated by increased need for flood storage and downscaled projections of streamflow from the ensemble of GCMs and scenarios are used for projecting future hydrologic scenarios. It is seen that hydropower generation and reliability with respect to hydropower and irrigation are likely to show a decrease in future in most scenarios, whereas the deficit ratio and vulnerability are likely to increase as a result of climate change if the standard operating policy (SOP) using current rule curves for flood protection is employed. An optimal monthly operating policy is then derived using stochastic dynamic programming (SDP) as an adaptive policy for mitigating impacts of climate change on reservoir operation. The objective of this policy is to maximize reliabilities with respect to multiple reservoir functions of hydropower, irrigation and flood control. In variations to this adaptive policy, increasingly more weightage is given to the purpose of maximizing reliability with respect to hydropower for two extreme scenarios. It is seen that by marginally sacrificing reliability with respect to irrigation and flood control, hydropower reliability and generation can be increased for future scenarios. This suggests that reservoir rules for flood control may have to be revised in basins where climate change projects an increasing probability of droughts. However, it is also seen that power generation is unable to be restored to current levels, due in part to the large projected increases in irrigation demand. This suggests that future water balance deficits may limit the success of adaptive policy options. (C) 2010 Elsevier Ltd. All rights reserved.

Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Impact of climate change at species level: a case study of teak in India

In this study, we model the long-term effect of climate change on commercially important teak (Tectona grandis) and its productivity in India. This modelling assessment is based on climate projections of the regional climate model of the Hadley Center (HadRM3) and the dynamic vegetation model, IBIS. According to the model projections, 30% of teak grids in India are vulnerable to climate change under both A2 and B2 SRES scenarios because the future climate may not be optimal for teak at these grids. However, the net primary productivity and biomass are expected to increase because of elevated levels of CO2. Given these directions of likely impacts, it is crucial to further investigate the climate change impacts on teak and incorporate such findings into long-term teak plantation programs. This study also demonstrates the feasibility and limitations of assessing the impact of projected climate change at the species level in the tropics.

Climate change and Indian forests

An assessment of the impact of projected climate change on forest ecosystems in India based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the global dynamic vegetation model IBIS for A1B scenario is conducted for short-term (2021-2050) and long-term (2071-2100) periods. Based on the dynamic global vegetation modelling, vulnerable forested regions of India have been identified to assist in planning adaptation interventions. The assessment of climate impacts showed that at the national level, about 45% of the forested grids is projected to undergo change. Vulnerability assessment showed that such vulnerable forested grids are spread across India. However, their concentration is higher in the upper Himalayan stretches, parts of Central India, northern Western Ghats and the Eastern Ghats. In contrast, the northeastern forests, southern Western Ghats and the forested regions of eastern India are estimated to be the least vulnerable. Low tree density, low biodiversity status as well as higher levels of fragmentation, in addition to climate change, contribute to the vulnerability of these forests. The mountainous forests (sub-alpine and alpine forest, the Himalayan dry temperate forest and the Himalayan moist temperate forest) are susceptible to the adverse effects of climate change. This is because climate change is predicted to be larger for regions that have greater elevations.

Climate change vulnerability profiles for North East India

Climate change vulnerability profiles are developed at the district level for agriculture, water and forest sectors for the North East region of India for the current and projected future climates. An index-based approach was used where a set of indicators that represent key sectors of vulnerability (agriculture, forest, water) is selected using the statistical technique principal component analysis. The impacts of climate change on key sectors as represented by the changes in the indicators were derived from impact assessment models. These impacted indicators were utilized for the calculation of the future vulnerability to climate change. Results indicate that majority of the districts in North East India are subject to climate induced vulnerability currently and in the near future. This is a first of its kind study that exhibits ranking of districts of North East India on the basis of the vulnerability index values. The objective of such ranking is to assist in: (i) identifying and prioritizing the most vulnerable sectors and districts; (ii) identifying adaptation interventions, and (iii) mainstreaming adaptation in development programmes.

Importance of carbon dioxide physiological forcing to future climate change

An increase in atmospheric carbon dioxide (CO2) concentration influences climate both directly through its radiative effect (i.e., trapping longwave radiation) and indirectly through its physiological effect (i.e., reducing transpiration of land plants). Here we compare the climate response to radiative and physiological effects of increased CO2 using the National Center for Atmospheric Research (NCAR) coupled Community Land and Community Atmosphere Model. In response to a doubling of CO2, the radiative effect of CO2 causes mean surface air temperature over land to increase by 2.86 ± 0.02 K (± 1 standard error), whereas the physiological effects of CO2 on land plants alone causes air temperature over land to increase by 0.42 ± 0.02 K. Combined, these two effects cause a land surface warming of 3.33 ± 0.03 K. The radiative effect of doubling CO2 increases global runoff by 5.2 ± 0.6%, primarily by increasing precipitation over the continents. The physiological effect increases runoff by 8.4 ± 0.6%, primarily by diminishing evapotranspiration from the continents. Combined, these two effects cause a 14.9 ± 0.7% increase in runoff. Relative humidity remains roughly constant in response to CO2-radiative forcing, whereas relative humidity over land decreases in response to CO2-physiological forcing as a result of reduced plant transpiration. Our study points to an emerging consensus that the physiological effects of increasing atmospheric CO2 on land plants will increase global warming beyond that caused by the radiative effects of CO2.

Climate forcing and response to idealized changes in surface latent and sensible heat

Land use and land cover changes affect the partitioning of latent and sensible heat, which impacts the broader climate system. Increased latent heat flux to the atmosphere has a local cooling influence known as `evaporative cooling', but this energy will be released back to the atmosphere wherever the water condenses. However, the extent to which local evaporative cooling provides a global cooling influence has not been well characterized. Here, we perform a highly idealized set of climate model simulations aimed at understanding the effects that changes in the balance between surface sensible and latent heating have on the global climate system. We find that globally adding a uniform 1 W m(-2) source of latent heat flux along with a uniform 1 W m(-2) sink of sensible heat leads to a decrease in global mean surface air temperature of 0.54 +/- 0.04 K. This occurs largely as a consequence of planetary albedo increases associated with an increase in low elevation cloudiness caused by increased evaporation. Thus, our model results indicate that, on average, when latent heating replaces sensible heating, global, and not merely local, surface temperatures decrease.