Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe

Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

A suite of climate change indices derived from daily temperature and precipitation data, with a primary focus on extreme events, were computed and analyzed. By setting an exact formula for each index and using specially designed software, analyses done in different countries have been combined seamlessly. This has enabled the presentation of the most up-to-date and comprehensive global picture of trends in extreme temperature and precipitation indices using results from a number of workshops held in data-sparse regions and high-quality station data supplied by numerous scientists world wide. Seasonal and annual indices for the period 1951-2003 were gridded. Trends in the gridded fields were computed and tested for statistical significance. Results showed widespread significant changes in temperature extremes associated with warming, especially for those indices derived from daily minimum temperature. Over 70% of the global land area sampled showed a significant decrease in the annual occurrence of cold nights and a significant increase in the annual occurrence of warm nights. Some regions experienced a more than doubling of these indices. This implies a positive shift in the distribution of daily minimum temperature throughout the globe. Daily maximum temperature indices showed similar changes but with smaller magnitudes. Precipitation changes showed a widespread and significant increase, but the changes are much less spatially coherent compared with temperature change. Probability distributions of indices derived from approximately 200 temperature and 600 precipitation stations, with near-complete data for 1901-2003 and covering a very large region of the Northern Hemisphere midlatitudes (and parts of Australia for precipitation) were analyzed for the periods 1901-1950, 1951-1978 and 1979-2003. Results indicate a significant warming throughout the 20th century. Differences in temperature indices distributions are particularly pronounced between the most recent two periods and for those indices related to minimum temperature. An analysis of those indices for which seasonal time series are available shows that these changes occur for all seasons although they are generally least pronounced for September to November. Precipitation indices show a tendency toward wetter conditions throughout the 20th century.

/pdf/global-observed-changes-in-daily-climate-extremes-of-50pijshpdk.pdf

Global observed changes in daily climate extremes of temperature and precipitation

There is a direct influence of global warming on precipitation. Increased heating leads to greater evaporation and thus surface drying, thereby increasing the intensity and duration of drought. However, the water holding capacity of air increases by about 7% per 1°C warming, which leads to increased water vapor in the atmosphere. Hence, storms, whether individual thunderstorms, extratropical rain or snow storms, or tropical cyclones, supplied with increased moisture, produce more intense precipitation events. Such events are observed to be widely occurring, even where total precipitation is decreasing: 'it never rains but it pours!' This increases the risk of flooding. The atmo- spheric and surface energy budget plays a critical role in the hydrological cycle, and also in the slower rate of change that occurs in total precipitation than total column water vapor. With modest changes in winds, patterns of precipitation do not change much, but result in dry areas becoming drier (generally throughout the subtropics) and wet areas becoming wetter, especially in the mid- to high latitudes: the 'rich get richer and the poor get poorer'. This pattern is simulated by climate mod- els and is projected to continue into the future. Because, with warming, more precipitation occurs as rain instead of snow and snow melts earlier, there is increased runoff and risk of flooding in early spring, but increased risk of drought in summer, especially over continental areas. However, with more precipitation per unit of upward motion in the atmosphere, i.e. 'more bang for the buck', atmo- spheric circulation weakens, causing monsoons to falter. In the tropics and subtropics, precipitation patterns are dominated by shifts as sea surface temperatures change, with El Nino a good example. The volcanic eruption of Mount Pinatubo in 1991 led to an unprecedented drop in land precipitation and runoff, and to widespread drought, as precipitation shifted from land to oceans and evaporation faltered, providing lessons for possible geoengineering. Most models simulate precipitation that occurs prematurely and too often, and with insufficient intensity, resulting in recycling that is too large and a lifetime of moisture in the atmosphere that is too short, which affects runoff and soil moisture.

/pdf/changes-in-precipitation-with-climate-change-3ofcyuiy76.pdf

Changes in precipitation with climate change

This chapter assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system. Changes are expressed with respect to a baseline period of 1986-2005, unless otherwise stated.

Chapter 12 - Long-term climate change: Projections, commitments and irreversibility

A significant effect of anthropogenic activities has already been detected in observed trends in temperature and mean precipitation. But to date, no study has formally identified such a human fingerprint on extreme precipitation — an increase in which is one of the central theoretical expectations for a warming climate. Seung-Ki Min and colleagues compare observations and simulations of rainfall between 1951 and 1999 in North America, Europe and northern Asia. They find a statistically significant effect of increased greenhouse gases on observed increases in extreme precipitation events over much of the Northern Hemisphere land area. A significant effect of anthropogenic activities has already been detected in observed trends in temperature and mean precipitation. But so far, no study has formally identified such a human fingerprint on extreme precipitation — an increase in which is one of the central theoretical expectations for a warming climate. This study compares observations and simulations and detects a statistically significant effect of increased greenhouse gases on observed increases in extreme precipitation events over much of the Northern Hemisphere land area. Extremes of weather and climate can have devastating effects on human society and the environment1,2. Understanding past changes in the characteristics of such events, including recent increases in the intensity of heavy precipitation events over a large part of the Northern Hemisphere land area3,4,5, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature—and that atmospheric water content is increasing in accord with this theoretical expectation6,7,8,9,10,11—it has been suggested that human-influenced global warming may be partly responsible for increases in heavy precipitation3,5,7. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model–model comparisons12,13,14,15. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavy precipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavy precipitation with warming16.

/pdf/human-contribution-to-more-intense-precipitation-extremes-3zggbqp3eg.pdf

Human contribution to more-intense precipitation extremes

The Indian summer (JJAS) shows high variability in both space and timescales. Changes in precipitation extremes play an important role on the regional scale due to their serious socio-economic consequences. This study, therefore, is mainly focused on understanding the variation of precipitation extremes during summer monsoon season in the presence of cyclonic disturbances forming over the Bay of Bengal (BOB), Arabian Sea, Land Area (LA) and Total. For this, several indices of observed precipitation extremes, in terms of frequencies, intensities and spell duration have been computed for the period 1951–2007 using daily APHRODITE data of 0.5° latitude × 0.5° longitude resolution. Correlation analysis reveals that a large part of the country exhibits positive relationship between the indices of precipitation extremes and frequency of cyclonic disturbances. Correlations with the indices of frequencies defined as seasonal count of days when rainfall exceeds 30, 20 and 10 mm show that spatial extent and strength of the positive relationship decreases with increase in threshold values. Disturbances forming over BOB play dominant role in precipitation during Indian summer monsoon.

Precipitation extremes during Indian summer monsoon: role of cyclonic disturbances

Assessment of regional downscaling simulations for long term mean, excess and deficit Indian Summer Monsoons

Long-term (1901–2010) district data have been used to examine the observed variability and trends in rainfall during the south-west monsoon season (June–September) and north-east monsoon season (October–December) over India. South-west monsoon rainfall averaged over the country as a whole does not show any significant long-term trend during the period 1901–2010, suggesting that south-west monsoon system is stable. However, there is a significant multi-decadal epochal variability over the country and the four homogenous regions over India. The recent decades from 1971 onwards are found to be drier than normal with the recent decade 2001–2010 being the driest. Rainfall during the month of July shows a decreasing trend over most parts of the central India. However, rainfall during June and August shows increasing trend over the central and south-western parts of the country. Significant decreasing trends are observed in the seasonal rainfall over three subdivisions, and significant increasing trends are observed over eight other subdivisions. The analysis of the north-east monsoon (October–December) rainfall over the five met-subdivisions of Peninsular India reveals no significant long-term trend. However, the presence of decadal variability in north-east monsoon rainfall is clearly observed.

Observed Variability and Long-Term Trends of Rainfall Over India

Thunderstorms are of much importance in tropics, as this region is considered to have central role in the convective overturn of the atmosphere and play an important role in rainfall activity. It is well known that El Nino and La Nina are well associated with significant climate anomalies at many places around the globe. Therefore, an attempt is made in this study to analyze variability in thunderstorm days and rainfall activity over Indian region and its association with El Nino and La Nina using data of thunderstorm day’s for 64 stations well distributed all over India for the period 1981–2005 (25 years). It is seen that thunderstorm activity is higher and much variable during pre-monsoon (MAM) and southwest monsoon (JJAS) than the rest of the year. Positive correlation coefficients (CCs) are seen between thunderstorms and rainfall except for the month of June during which the onset of the southwest monsoon sets over the country. CCs during winter months are highly correlated. Composite anomalies in thunderstorms during El Nino and La Nina years suggest that ENSO conditions altered the patterns of thunderstorm activity over the country. Positive anomalies are seen during pre-monsoon (MAM) and southwest monsoon months (JAS) during La Nina years. Opposite features are seen in southwest monsoon during El Nino periods, but El Nino favors thunderstorm activity during pre-monsoon months. There is a clear contrast between the role of ENSO during southwest monsoon and post-monsoon on thunderstorm activity over the country. Time series of thunderstorms and precipitation show strong association with similarities in their year-to-year variation over the country.

J. V. Revadekar

Papers

Precipitation extremes during Indian summer monsoon: role of cyclonic disturbances

Assessment of regional downscaling simulations for long term mean, excess and deficit Indian Summer Monsoons

Observed Variability and Long-Term Trends of Rainfall Over India

About the variability in thunderstorm and rainfall activity over India and its association with El Niño and La Niña

Variability in AIRS CO2 during active and break phases of Indian summer monsoon.