Editing IPCC:AR6/SRCCL/SPM (section)

== A People, land and climate in a warming world ==

<div id="article-800-2-block-1"></div>

'''A.1        '''<br />
'''Land provides the principal basis for human livelihoods and well-being including the supply of food, freshwater and multiple other ecosystem services, as well as biodiversity. Human use directly affects more than 70% ( ''likely'' 69–76%) of the global, ice-free land surface ( ''high confidence'' ). Land also plays an important role in the climate system. (Figure SPM.1) {1.1, 1.2, 2.3, 2.4}'''

A.1.1<br />
People currently use one quarter to one third of land’s potential net primary production  <sup>[[#fn:10|10]]</sup> for food, feed, fibre, timber and energy. Land provides the basis for many other ecosystem functions and services, <sup>[[#fn:11|11]]</sup> including cultural and regulating services, that are essential for humanity ( ''high confidence'' ). In one economic approach, the world’s terrestrial ecosystem services have been valued on an annual basis to be approximately equivalent to the annual global Gross Domestic Product  <sup>[[#fn:12|12]]</sup> ''(medium confidence'' ). (Figure SPM.1) {1.1, 1.2, 3.2, 4.1, 5.1, 5.5}

A.1.2<br />
Land is both a source and a sink of GHGs and plays a key role in the exchange of energy, water and aerosols between the land surface and atmosphere. Land ecosystems and biodiversity are vulnerable to ongoing climate change, and weather and climate extremes, to different extents. Sustainable land management can contribute to reducing the negative impacts of multiple stressors, including climate change, on ecosystems and societies (high confidence). (Figure SPM.1) {1.1, 1.2, 3.2, 4.1, 5.1, 5.5}

A.1.3<br />
Data available since 1961  <sup>[[#fn:13|13]]</sup> show that global population growth and changes in per capita consumption of food, feed, fibre, timber and energy have caused unprecedented rates of land and freshwater use ( ''very high confidence'' ) with agriculture currently accounting for ca. 70% of global fresh-water use ( ''medium confidence'' ). Expansion of areas under agriculture and forestry, including commercial production, and enhanced agriculture and forestry productivity have supported consumption and food availability for a growing population ( ''high confidence'' ). With large regional variation, these changes have contributed to increasing net GHG emissions ( ''very high confidence'' ), loss of natural ecosystems (e.g., forests, savannahs, natural grasslands and wetlands) and declining biodiversity ( ''high confidence'' ). (Figure SPM.1) {1.1, 1.3, 5.1, 5.5}

A.1.4<br />
Data available since 1961 shows the per capita supply of vegetable oils and meat has more than doubled and the supply of food calories per capita has increased by about one third ( ''high confidence'' ). Currently, 25–30% of total food produced is lost or wasted ( ''medium confidence'' ). These factors are associated with additional GHG emissions ( ''high confidence'' ). Changes in consumption patterns have contributed to about two billion adults now being overweight or obese ( ''high confidence'' ). An estimated 821 million people are still undernourished ( ''high confidence'' ). (Figure SPM.1) {1.1, 1.3, 5.1, 5.5}

A.1.5<br />
About a quarter of the Earth’s ice-free land area is subject to human-induced degradation ( ''medium confidence'' ). Soil erosion from agricultural fields is estimated to be currently 10 to 20 times (no tillage) to more than 100 times (conventional tillage) higher than the soil formation rate ( ''medium confidence'' ). Climate change exacerbates land degradation, particularly in low-lying coastal areas, river deltas, drylands and in permafrost areas ( ''high confidence'' ). Over the period 1961–2013, the annual area of drylands in drought has increased, on average by slightly more than 1% per year, with large inter-annual variability. In 2015, about 500 (380-620) million people lived within areas which experienced desertification between the 1980s and 2000s. The highest numbers of people affected are in South and East Asia, the circum Sahara region including North Africa, and the Middle East including the Arabian Peninsula ( ''low confidence'' ). Other dryland regions have also experienced desertification. People living in already degraded or desertified areas are increasingly negatively affected by climate change ( ''high confidence'' ). (Figure SPM.1) {1.1, 1.2, 3.1, 3.2, 4.1, 4.2, 4.3}

<div id="article-800-2-block-2"></div>

<span id="figure-spm.1"></span>
<!-- START IMG -->
<!-- IMG TITLE -->
'''Figure SPM.1'''

<span id="a-representation-of-the-land-use-and-observed-climate-change-covered-in-this-assessment-report.-panels-a-f-show-the-status-and-trends-in-selected-land-use-and-climate-variables-that-represent-many-of-the-core-topics-covered-in-this-report.-the-annual-time-series-in-b-and-d-f-are-based-on-the-most-comprehensive-available"></span>
<!-- IMG CAPTION -->
'''A representation of the land use and observed climate change covered in this assessment report. Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D-F are based on the most comprehensive, available […]'''
<!-- IMG FILE -->
[[File:720509405e4f4330a7f9b5e0bdf605a3 SPM1-approval-v7-USletter-791x1024.png]]

A representation of the land use and observed climate change covered in this assessment report. Panels A-F show the status and trends in selected land use and climate variables that represent many of the core topics covered in this report. The annual time series in B and D-F are based on the most comprehensive, available data from national statistics, in most cases from FAOSTAT which starts in 1961. Y-axes in panels D-F are expressed relative to the starting year of the time series (rebased to zero). Data sources and notes: '''A''' : The warming curves are averages of four datasets {2.1, Figure 2.2, Table 2.1} '''B''' : N <sub>2</sub> O and CH <sub>4</sub> from agriculture are from FAOSTAT; Net CO <sub>2</sub> emissions from FOLU using the mean of two bookkeeping models (including emissions from peatland fires since 1997). All values expressed in units of CO <sub>2</sub> -eq are based on AR5 100-year Global Warming Potential values without climate-carbon feedbacks (N <sub>2</sub> O=265; CH <sub>4</sub> =28). (Table SPM.1) {1.1, 2.3} '''C''' : Depicts shares of different uses of the global, ice-free land area for approximately the year 2015, ordered along a gradient of decreasing land-use intensity from left to right. Each bar represents a broad land cover category; the numbers on top are the total percentage of the ice-free area covered, with uncertainty ranges in brackets. Intensive pasture is defined as having a livestock density greater than 100 animals/km². The area of ‘forest managed for timber and other uses’ was calculated as total forest area minus ‘primary/intact’ forest area. {1.2, Table 1.1, Figure 1.3} '''D''' : Note that fertiliser use is shown on a split axis. The large percentage change in fertiliser use reflects the low level of use in 1961 and relates to both increasing fertiliser input per area as well as the expansion of fertilised cropland and grassland to increase food production. {1.1, Figure 1.3} '''E''' : Overweight population is defined as having a body mass index (BMI) &gt; 25 kg m <sup>-2</sup> ; underweight is defined as BMI &lt; 18.5 kg m <sup>-2</sup> . {5.1, 5.2} '''F''' : Dryland areas were estimated using TerraClimate precipitation and potential evapotranspiration (1980-2015) to identify areas where the Aridity Index is below 0.65. Population data are from the HYDE3.2 database. Areas in drought are based on the 12-month accumulation Global Precipitation Climatology Centre Drought Index. The inland wetland extent (including peatlands) is based on aggregated data from more than 2000 time series that report changes in local wetland area over time. {3.1, 4.2, 4.6}

<!-- END IMG -->
<div id="article-800-2-block-3"></div>

'''A.2'''

'''Since the pre-industrial period, the land surface air temperature has risen nearly twice as much as the global average temperature ( ''high confidence'' ). Climate change, including increases in frequency and intensity of extremes, has adversely impacted food security and terrestrial ecosystems as well as contributed to desertification and land degradation in many regions ( ''high confidence'' ). {2.2, 3.2, 4.2, 4.3, 4.4, 5.1, 5.2, Executive Summary Chapter 7, 7.2}'''

A.2.1<br />
Since the pre-industrial period (1850-1900) the observed mean land surface air temperature has risen considerably more than the global mean surface (land and ocean) temperature (GMST) ( ''high confidence'' ). From 1850-1900 to 2006-2015 mean land surface air temperature has increased by 1.53°C ( ''very likely'' range from 1.38°C to 1.68°C) while GMST increased by 0.87°C ( ''likely'' range from 0.75°C to 0.99°C). (Figure SPM.1) {2.2.1}

A.2.2<br />
Warming has resulted in an increased frequency, intensity and duration of heat-related events, including heatwaves  <sup>[[#fn:14|14]]</sup> in most land regions ( ''high confidence'' ). Frequency and intensity of droughts has increased in some regions (including the Mediterranean, west Asia, many parts of South America, much of Africa, and north-eastern Asia) ( ''medium confidence'' ) and there has been an increase in the intensity of heavy precipitation events at a global scale ( ''medium confidence'' ). {2.2.5, 4.2.3, 5.2}

A.2.3<br />
Satellite observations  <sup>[[#fn:15|15]]</sup> have shown vegetation greening  <sup>[[#fn:16|16]]</sup> over the last three decades in parts of Asia, Europe, South America, central North America, and southeast Australia. Causes of greening include combinations of an extended growing season, nitrogen deposition, Carbon Dioxide (CO <sub>2</sub> ) fertilisation  <sup>[[#fn:17|17]]</sup> , and land management ( ''high confidence'' ). Vegetation browning  <sup>[[#fn:18|18]]</sup> has been observed in some regions including northern Eurasia, parts of North America, Central Asia and the Congo Basin, largely as a result of water stress ( ''medium confidence'' ). Globally, vegetation greening has occurred over a larger area than vegetation browning ( ''high confidence'' ). {2.2.3, Box 2.3, 2.2.4, 3.2.1, 3.2.2, 4.3.1, 4.3.2, 4.6.2, 5.2.2}

A.2.4<br />
The frequency and intensity of dust storms have increased over the last few decades due to land use and land cover changes and climate-related factors in many dryland areas resulting in increasing negative impacts on human health, in regions such as the Arabian Peninsula and broader Middle East, Central Asia ( ''high confidence'' ).  <sup>[[#fn:19|19]]</sup> {2.4.1, 3.4.2}

A.2.5<br />
In some dryland areas, increased land surface air temperature and evapotranspiration and decreased precipitation amount, in interaction with climate variability and human activities, have contributed to desertification. These areas include Sub-Saharan Africa, parts of East and Central Asia, and Australia. ( ''medium confidence'' ) {2.2, 3.2.2, 4.4.1}

A.2.6<br />
Global warming has led to shifts of climate zones in many world regions, including expansion of arid climate zones and contraction of polar climate zones ( ''high confidence'' ). As a consequence, many plant and animal species have experienced changes in their ranges, abundances, and shifts in their seasonal activities ( ''high confidence'' ). {2.2, 3.2.2, 4.4.1}

A.2.7<br />
Climate change can exacerbate land degradation processes ( ''high confidence'' ) including through increases in rainfall intensity, flooding, drought frequency and severity, heat stress, dry spells, wind, sea-level rise and wave action, and permafrost thaw with outcomes being modulated by land management. Ongoing coastal erosion is intensifying and impinging on more regions with sea-level rise adding to land use pressure in some regions ( ''medium confidence'' ). {4.2.1, 4.2.2, 4.2.3, 4.4.1, 4.4.2, 4.9.6, Table 4.1, 7.2.1, 7.2.2}

A.2.8<br />
Climate change has already affected food security due to warming, changing precipitation patterns, and greater frequency of some extreme events ( ''high confidence'' ). Studies that separate out climate change from other factors affecting crop yields have shown that yields of some crops (e.g., maize and wheat) in many lower-latitude regions have been affected negatively by observed climate changes, while in many higher-latitude regions, yields of some crops (e.g., maize, wheat, and sugar beets) have been affected positively over recent decades ( ''high confidence'' ). Climate change has resulted in lower animal growth rates and productivity in pastoral systems in Africa ( ''high confidence'' ). There is robust evidence that agricultural pests and diseases have already responded to climate change resulting in both increases and decreases of infestations ( ''high confidence'' ). Based on indigenous and local knowledge, climate change is affecting food security in drylands, particularly those in Africa, and high mountain regions of Asia and South America.  <sup>[[#fn:20|20]]</sup> {5.2.1, 5.2.2, 7.2.2}


'''A.3'''<br />
'''Agriculture, Forestry and Other Land Use (AFOLU) activities accounted for around 13% of CO <sub>2</sub> , 44% of methane (CH <sub>4</sub> ), and 81% of nitrous oxide (N <sub>2</sub> O) emissions from human activities globally during 2007-2016, representing 23% (12.0 ± 2.9 GtCO <sub>2</sub> eq yr <sup>-1</sup> ) of total net anthropogenic emissions of GHGs ( ''medium confidence'' ).  <sup>[[#fn:21|21]]</sup>   The natural response of land to human-induced environmental change caused a net sink of around 11.2 GtCO <sub>2</sub> yr <sup>-1</sup> during 2007–2016 (equivalent to 29% of total CO2 emissions) ( ''medium confidence)'' ; the persistence of the sink is uncertain due to climate change ( ''high confidence'' ). If emissions associated with pre- and post-production activities in the global food system  <sup>[[#fn:22|22]]</sup> are included, the emissions are estimated to be 21–37% of total net anthropogenic GHG emissions ( ''medium confidence'' ). {2.3, Table 2.2, 5.4}'''

A.3.1<br />
Land is simultaneously a source and a sink of CO <sub>2</sub> due to both anthropogenic and natural drivers, making it hard to separate anthropogenic from natural fluxes ( ''very high confidence'' ).  Global models estimate net CO <sub>2</sub> emissions of 5.2 ± 2.6 GtCO <sub>2</sub> yr <sup>-1</sup> ( ''likely'' range) from land use and land-use change during 2007–2016. These net emissions are mostly due to deforestation, partly offset by afforestation/reforestation, and emissions and removals by other land use activities ( ''very high confidence'' ).  <sup>[[#fn:23|23]]</sup> There is no clear trend in annual emissions since 1990 ( ''medium confidence'' ). (Figure SPM.1, Table SPM.1) {1.1, 2.3, Table 2.2, Table 2.3}

A.3.2<br />
The natural response of land to human-induced environmental changes such as increasing atmospheric CO <sub>2</sub> concentration, nitrogen deposition, and climate change, resulted in global net removals of 11.2 ± 2.6 GtCO <sub>2</sub> yr <sup>–1</sup> ( ''likely'' range) during 2007–2016. The sum of the net removals due to this response and the AFOLU net emissions gives a total net land-atmosphere flux that removed 6.0 ± 3.7 GtCO <sub>2</sub> yr <sup>-1</sup> during 2007–2016 ( ''likely'' range). Future net increases in CO <sub>2</sub> emissions from vegetation and soils due to climate change are projected to counteract increased removals due to CO <sub>2</sub> fertilisation and longer growing seasons ( ''high confidence'' ). The balance between these processes is a key source of uncertainty for determining the future of the land carbon sink. Projected thawing of permafrost is expected to increase the loss of soil carbon ( ''high confidence'' ). During the 21 <sup>st</sup> century, vegetation growth in those areas may compensate in part for this loss ( ''low confidence'' ). (Table SPM.1) {Box 2.3, 2.3.1, 2.5.3, 2.7, Table 2.3}

A.3.3<br />
Global models and national GHG inventories use different methods to estimate anthropogenic CO <sub>2</sub> emissions and removals for the land sector. Both produce estimates that are in close agreement for land-use change involving forest (e.g., deforestation, afforestation), and differ for managed forest. Global models consider as managed forest those lands that were subject to harvest whereas, consistent with IPCC guidelines, national GHG inventories define managed forest more broadly. On this larger area, inventories can also consider the natural response of land to human-induced environmental changes as anthropogenic, while the global model approach (Table SPM.1) treats this response as part of the non-anthropogenic sink. For illustration, from 2005 to 2014, the sum of the national GHG inventories net emission estimates is 0.1 ± 1.0 GtCO <sub>2</sub> yr <sup>-1</sup> , while the mean of two global bookkeeping models is 5.2 ± 2.6 GtCO <sub>2</sub> yr <sup>-1</sup> ( ''likely'' range). Consideration of differences in methods can enhance understanding of land sector net emission estimates and their applications. {2.4.1, 2.7.3, Fig 2.5, Box 2.2}

<div id="article-800-2-block-4"></div>

<span id="table-spm.1"></span>
<!-- START IMG -->
<!-- TABLE IMG -->
<!-- IMG TITLE -->
'''Table SPM.1'''

<span id="net-anthropogenic-emissions-due-to-agriculture-forestry-and-other-land-use-afolu-and-non-afolu-panel-1-and-global-food-systems-average-for-20072016-1-panel-2.-positive-values-represent-emissions-negative-values-represent-removals."></span>
<!-- IMG CAPTION -->
'''Net anthropogenic emissions due to Agriculture, Forestry, and other Land Use (AFOLU) and non-AFOLU (Panel 1) and global food systems (average for 2007–2016) <sup>1</sup> (Panel 2). Positive values represent emissions; negative values represent removals.'''
<!-- IMG FILE -->
[[File:edd426175bc57b28e31d38fb0f9ce3b7 08112019_Table_Erata_3_Open-sans-1024x564.png]]

Data sources and notes:<br />
1 Estimates are only given until 2016 as this is the latest date when data are available for all gases.<br />
2 Net anthropogenic flux of CO2 due to land cover change such as deforestation and afforestation, and land management including wood harvest and regrowth, as well as peatland burning, based on two bookkeeping models as used in the Global Carbon Budget and for AR5. Agricultural soil carbon stock change under the same land use is not considered in these models. {2.3.1.2.1, Table 2.2, Box 2.2}<br />
3 Estimates show the mean and assessed uncertainty of two databases, FAOSTAT and USEPA. 2012 {2.3, Table 2.2}<br />
4 Based on FAOSTAT. Categories included in this value are ‘net forest conversion’ (net deforestation), drainage of organic soils (cropland and grassland), biomass burning (humid tropical forests, other forests, organic soils). It excludes ‘forest land’ (forest management plus net forest expansion), which is primarily a sink due to afforestation. Note: Total FOLU emissions from FAOSTAT are 2.8 (±1.4) GtCO2 yr-1 for the period 2007–2016. {Table 2.2, Table 5.4}<br />
5 CO2 emissions induced by activities not included in the AFOLU sector, mainly from energy (e.g., grain drying), transport (e.g., international trade), and industry (e.g., synthesis of inorganic fertilisers) part of food systems, including agricultural production activities (e.g., heating in greenhouses), pre-production (e.g., manufacturing of farm inputs) and post-production (e.g., agri-food processing) activities. This estimate is land based and hence excludes emissions from fisheries. It includes emissions from fibre and other non-food agricultural products since these are not separated from food use in databases. The CO2 emissions related to food system in other sectors than AFOLU are 6–-13% of total anthropogenic CO2 emissions. These emissions are typically low in smallholder subsistence farming. When added to AFOLU emissions, the estimated share of food systems in global anthropogenic emissions is 21–-37%. {5.4.5, Table 5.4}<br />
6 Total non-AFOLU emissions were calculated as the sum of total CO2eq emissions values for energy, industrial sources, waste and other emissions with data from the Global Carbon Project for CO2, including international aviation and shipping and from the PRIMAP database for CH4 and N2O averaged over 2007–2014 only as that was the period for which data were available. {2.3, Table 2.2}.<br />
7 The natural response of land to human-induced environmental changes is the response of vegetation and soils to environmental changes such as increasing atmospheric CO2 concentration, nitrogen deposition, and climate change. The estimate shown represents the average from Dynamic Global Vegetation Models {2.3.1.2, Box 2.2, Table 2.3}<br />
8 All values expressed in units of CO2eq are based on AR5 100-year Global Warming Potential (GWP) values without climate-carbon feedbacks (N2O = 265; CH4 = 28). Note that the GWP has been used across fossil fuel and biogenic sources of methane. If a higher GWP for fossil fuel CH4 (30 per AR5) were used, then total anthropogenic CH4 emissions expressed in CO2eq would be 2% greater.<br />
9 This estimate is land based and hence excludes emissions from fisheries and emissions from aquaculture (except emissions from feed produced on land and used in aquaculture), and also includes non-food use (e.g. fibre and bioenergy) since these are not separated from food use in databases. It excludes non-CO2 emissions associated with land use change (FOLU category) since these are from fires in forests and peatlands.<br />
10 Emissions associated with food loss and waste are included implicitly, since emissions from the food system are related to food produced, including food consumed for nutrition and to food loss and waste. The latter is estimated at 8–10% of total anthropogenic emissions in CO2eq. {5.5.2.5}<br />
11 No global data are available for agricultural CO2 emissions.

<!-- END IMG -->
<div id="article-800-2-block-5"></div>

A.3.4<br />
Global AFOLU emissions of methane in the period 2007–2016 were 161 ± 43 MtCH <sub>4</sub> yr <sup>-1</sup> (4.5 ± 1.2 GtCO <sub>2</sub> eq yr <sup>-1</sup> ) ( ''medium confidence'' ). The globally averaged atmospheric concentration of CH <sub>4</sub> shows a steady increase between the mid-1980s and early 1990s, slower growth thereafter until 1999, a period of no growth between 1999–2006, followed by a resumption of growth in 2007 ( ''high confidence'' ). Biogenic sources make up a larger proportion of emissions than they did before 2000 ( ''high confidence'' ). Ruminants and the expansion of rice cultivation are important contributors to the rising concentration ( ''high confidence'' ). (Figure SPM.1) {Table 2.2, 2.3.2, 5.4.2, 5.4.3}

A.3.5<br />
Anthropogenic AFOLU N <sub>2</sub> O emissions are rising, and were 8.7 ± 2.5 MtN <sub>2</sub> O yr <sup>-1</sup> (2.3 ± 0.7 GtCO <sub>2</sub> eq yr <sup>-1</sup> ) during the period 2007-2016. Anthropogenic N <sub>2</sub> O emissions {Figure SPM.1, Table SPM.1} from soils are primarily due to nitrogen application including inefficiencies (over-application or poorly synchronised with crop demand timings) ( ''high confidence'' ). Cropland soils emitted around 3 MtN <sub>2</sub> O yr <sup>-1</sup> (around 795 MtCO <sub>2</sub> eq yr <sup>-1</sup> ) during the period 2007–2016 ( ''medium confidence'' ). There has been a major growth in emissions from managed pastures due to increased manure deposition ( ''medium confidence'' ). Livestock on managed pastures and rangelands accounted for more than one half of total anthropogenic N <sub>2</sub> O emissions from agriculture in 2014 ( ''medium confidence'' ). {Table 2.1, 2.3.3, 5.4.2, 5.4.3}

A.3.6<br />
Total net GHG emissions from AFOLU emissions represent 12.0 ± 2.9 GtCO <sub>2</sub> eq yr <sup>-1</sup> during 2007–2016. This represents 23% of total net anthropogenic emissions {Table SPM.1}.  <sup>[[#fn:24|24]]</sup> Other approaches, such as global food system, include agricultural emissions and land use change (i.e., deforestation and peatland degradation), as well as outside farm gate emissions from energy, transport and industry sectors for food production. Emissions within farm gate and from agricultural land expansion contributing to the global food system represent 16–27% of total anthropogenic emissions ( ''medium confidence'' ). Emissions outside the farm gate represent 5–10% of total anthropogenic emissions ( ''medium confidence'' ). Given the diversity of food systems, there are large regional differences in the contributions from different components of the food system ( ''very high confidence'' ). Emissions from agricultural production are projected to increase ( ''high confidence'' ), driven by population and income growth and changes in consumption patterns ( ''medium confidence'' ). {5.5, Table 5.4}

'''A.4        '''<br />
'''Changes in land conditions, <sup>[[#fn:25|25]]</sup> either from land-use or climate change, affect global and regional climate ( ''high confidence'' ). At the regional scale, changing land conditions can reduce or accentuate warming and affect the intensity, frequency and duration of extreme events. The magnitude and direction of these changes vary with location and season ( ''high confidence'' ). {Executive Summary Chapter 2, 2.3, 2.4, 2.5, 3.3}'''

A.4.1<br />
Since the pre-industrial period, changes in land cover due to human activities have led to both a net release of CO <sub>2</sub> contributing to global warming ( ''high confidence'' ), and an increase in global land albedo  <sup>[[#fn:26|26]]</sup>  causing surface cooling ( ''medium confidence'' ). Over the historical period, the resulting net effect on globally averaged surface temperature is estimated to be small ( ''medium confidence'' ). {2.4, 2.6.1, 2.6.2}

A.4.2<br />
The likelihood, intensity and duration of many extreme events can be significantly modified by changes in land conditions, including heat related events such as heatwaves ( ''high confidence'' ) and heavy precipitation events ( ''medium confidence'' ). Changes in land conditions can affect temperature and rainfall in regions as far as hundreds of kilometres away ( ''high confidence'' ). {2.5.1, 2.5.2, 2.5.4, 3.3, Cross-Chapter Box 4 in Chapter 2}

A.4.3<br />
Climate change is projected to alter land conditions with feedbacks on regional climate. In those boreal regions where the treeline migrates northward and/or the growing season lengthens, winter warming will be enhanced due to decreased snow cover and albedo while warming will be reduced during the growing season because of increased evapotranspiration ( ''high confidence'' ). In those tropical areas where increased rainfall is projected, increased vegetation growth will reduce regional warming ( ''medium confidence'' ). Drier soil conditions resulting from climate change can increase the severity of heat waves, while wetter soil conditions have the opposite effect ( ''high confidence'' ). {2.5.2, 2.5.3}

A.4.4<br />
Desertification amplifies global warming through the release of CO <sub>2</sub> linked with the decrease in vegetation cover ( ''high confidence'' ). This decrease in vegetation cover tends to increase local albedo, leading to surface cooling ( ''high confidence'' ). {3.3}

A.4.5<br />
Changes in forest cover, for example from afforestation, reforestation and deforestation, directly affect regional surface temperature through exchanges of water and energy ( ''high confidence'' ).  <sup>[[#fn:27|27]]</sup> Where forest cover increases in tropical regions cooling results from enhanced evapotranspiration ( ''high confidence'' ). Increased evapotranspiration can result in cooler days during the growing season ( ''high confidence'' ) and can reduce the amplitude of heat related events ( ''medium confidence'' ). In regions with seasonal snow cover, such as boreal and some temperate regions, increased tree and shrub cover also has a wintertime warming influence due to reduced surface albedo ( ''high confidence'' ).  <sup>[[#fn:28|28]]</sup> {2.3, 2.4.3, 2.5.1, 2.5.2, 2.5.4}

A.4.6

Both global warming and urbanisation can enhance warming in cities and their surroundings (heat island effect), especially during heat related events, including heat waves ( ''high confidence'' ). Night-time temperatures are more affected by this effect than daytime temperatures ( ''high confidence'' ). Increased urbanisation can also intensify extreme rainfall events over the city or downwind of urban areas ( ''medium confidence'' ). {2.5.1, 2.5.2, 2.5.3, 4.9.1, Cross-Chapter Box 4 in Chapter 2}

<div id="article-800-2-block-6" class="box"></div>

<span id="box-spm.1-shared-socio-economic-pathways-ssps"></span>