Editing IPCC:AR6/SRCCL/Chapter-2 (section)

=== 2.5.1 Impacts of historical and future anthropogenic land cover changes ===

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The studies reported below focus essentially on modelling experiments, as there is no direct observation of how historical land use changes have affected the atmospheric dynamics and physics at the global and regional scales. Moreover, the climate modelling experiments only assess the impacts of anthropogenic land cover changes (e.g., deforestation, urbanisation) and neglect the effects of changes in land management (e.g., irrigation, use of fertilisers, choice of species varieties among managed forests or crops). Because of this restricted accounting for land use changes, we will use the term ‘land cover changes’ in Sections 2.5.1.1 and 2.5.1.2.

Each section starts by describing changes at the global scale and regional scale, and ends with what we know about the impacts of those scenarios on extreme weather events, whenever the information is available.

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<span id="impacts-of-global-historical-land-cover-changes-on-climate"></span>
==== 2.5.1.1 Impacts of global historical land cover changes on climate ====

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'''''At the global level'''''

The contribution of anthropogenic land cover changes to the net global warming throughout the 20th century has been derived from few model-based estimates that account simultaneously for biogeochemical and biophysical effects of land on climate (Table 2.4). The simulated net change in mean global annual surface air temperature, averaged over all the simulations, is a small warming of 0.078 ± 0.093°C, ranging from small cooling simulated by two models (–0.05°C and –0.02°C respectively in Brovkin et al. (2004) <sup>[[#fn:r988|988]]</sup> and Simmons and Matthews (2016) <sup>[[#fn:r989|989]]</sup> , to larger warming simulated by three models (&gt;+0.14°C; Shevliakova et al. 2013 <sup>[[#fn:r990|990]]</sup> ; Pongratz et al. 2010 <sup>[[#fn:r991|991]]</sup> ; Matthews et al. 2004 <sup>[[#fn:r992|992]]</sup> ). When starting from the Holocene period, He et al. (2014) <sup>[[#fn:r993|993]]</sup> estimated an even larger net warming effect of anthropogenic land cover changes (+0.72°C).

This net small warming signal results from the competing effects of biophysical cooling ( ''medium confidence'' ) and biogeochemical warming ( ''very high confidence'' ) (Figure 2.14 <sup>[[#fn:1|1]]</sup> ). The global biophysical cooling alone has been estimated by a larger range of climate models and is –0.10 ± 0.14°C; it ranges from –0.57°C to +0.06°C (e.g., Zhang et al. 2013a <sup>[[#fn:r994|994]]</sup> ; Hua and Chen 2013 <sup>[[#fn:r995|995]]</sup> ; Jones et al. 2013b <sup>[[#fn:r996|996]]</sup> ; Simmons and Matthews 2016 <sup>[[#fn:r997|997]]</sup> ) (Table A2.1). This cooling is essentially dominated by increases in surface albedo: historical land cover changes have generally led to a dominant brightening of land as discussed in AR5 (Myhre et al. 2013 <sup>[[#fn:r998|998]]</sup> ). Reduced incoming longwave radiation at the surface from reduced evapotranspiration and thus less water vapour in the atmosphere has also been reported as a potential contributor to this cooling (Claussen et al. 2001 <sup>[[#fn:r999|999]]</sup> ). The cooling is, however, dampened by decreases in turbulent fluxes, leading to decreased loss of heat and water vapour from the land through convective processes. Those non-radiative processes are well-known to often oppose the albedo- induced surface temperature changes (e.g., Davin and de Noblet- Ducoudre (2010) <sup>[[#fn:r1000|1000]]</sup> , Boisier et al. (2012) <sup>[[#fn:r1001|1001]]</sup> ).

Historical land cover changes have contributed to the increase in atmospheric CO <sub>2</sub> content (Section 2.3) and thus to global warming (biogeochemical effect, ''very high confidence'' ). The global mean biogeochemical warming has been calculated from observation- based estimates (+0.25 ± 0.10°C) (e.g., Li et al. (2017a) <sup>[[#fn:r1002|1002]]</sup> , Avitabile et al. (2016) <sup>[[#fn:r1003|1003]]</sup> , Carvalhais et al. (2014) <sup>[[#fn:r1004|1004]]</sup> , Le Quéré et al. (2015) <sup>[[#fn:r1005|1005]]</sup> ), or estimated from DGVMs (+0.24 ± 0.12°C) (Peng et al. 2017 <sup>[[#fn:r1006|1006]]</sup> ; Arneth et al. 2017 <sup>[[#fn:r1007|1007]]</sup> ; Pugh et al. 2015 <sup>[[#fn:r1008|1008]]</sup> ; Hansis et al. 2015 <sup>[[#fn:r1009|1009]]</sup> ) and global climate models (+0.20 ± 0.05°C) (Pongratz et al. 2010 <sup>[[#fn:r1010|1010]]</sup> ; Brovkin et al. 2004 <sup>[[#fn:r1011|1011]]</sup> ; Matthews et al. 2004 <sup>[[#fn:r1012|1012]]</sup> ; Simmons and Matthews 2016 <sup>[[#fn:r1013|1013]]</sup> ).

The magnitude of these simulated biogeochemical effects may, however, be underestimated as they do not account for a number of processes such as land management, nitrogen/phosphorus cycles, changes in the emissions of CH <sub>4</sub> , N <sub>2</sub> O and non-GHG emissions from land (Ward et al. 2014 <sup>[[#fn:r1014|1014]]</sup> ; Arneth et al. 2017 <sup>[[#fn:r1015|1015]]</sup> ; Cleveland et al. 2015 <sup>[[#fn:r1016|1016]]</sup> ; Pongratz et al. 2018 <sup>[[#fn:r1017|1017]]</sup> ). Two studies have accounted for those compounds and found a global net positive radiative forcing in response to historical anthropogenic land cover changes, indicating a net surface warming (Mahowald et al. 2017 <sup>[[#fn:r1018|1018]]</sup> ; Ward et al. 2014 <sup>[[#fn:r1019|1019]]</sup> ). However, first the estimated biophysical radiative forcing in those studies only accounts for changes in albedo and not for changes in turbulent fluxes. Secondly, the combined estimates also depend on other several key modelling estimates such as climate sensitivity, CO <sub>2</sub> fertilisation caused by land use emissions, possible synergistic effects, validity of radiative forcing concept for land forcing. The comparison with the other above-mentioned modelling studies is thus difficult.

In addition, most of those estimates do not account for the evolution of natural vegetation in unmanaged areas, while observations and numerical studies have reported a greening of the land in boreal regions resulting from both extended growing season and poleward migration of tree lines (Lloyd et al. 2003 <sup>[[#fn:r1020|1020]]</sup> ; Lucht et al. 1995 <sup>[[#fn:r1021|1021]]</sup> ; Section 2.2). This greening enhances global warming via a reduction of surface albedo (winter darkening of the land through the snow- albedo feedbacks; e.g., Forzieri et al. 2017 <sup>[[#fn:r1022|1022]]</sup> ). At the same time, cooling occurs due to increased evapotranspiration during the growing season, along with enhanced photosynthesis, in essence, increased CO <sub>2</sub> sink (Qian et al. 2010 <sup>[[#fn:r1023|1023]]</sup> ). When feedbacks from the poleward migration of treeline are accounted for, together with the biophysical effects of historical anthropogenic land cover change, the biophysical annual cooling (about –0.20°C to –0.22°C on land, –0.06°C globally) is significantly dampened by the warming (about +0.13°C) resulting from the movements of natural vegetation (Strengers et al. 2010 <sup>[[#fn:r1024|1024]]</sup> ). Accounting simultaneously for both anthropogenic and natural land cover changes reduces the cooling impacts of historical land cover change in this specific study.

'''''At the regional level'''''

The global and annual estimates reported above mask out very contrasted regional and seasonal differences. Biogeochemical effects of anthropogenic land cover change on temperature follow the spatial patterns of GHG-driven climate change with stronger warming over land than ocean, and stronger warming in northern high latitudes than in the tropics and equatorial regions (Arctic amplification). Biophysical effects on the contrary are much stronger where land cover has been modified than in their surroundings (see Section 2.5.4 for a discussion on non-local effects). Very contrasted regional temperature changes can thus result, depending on whether biophysical processes dampen or exacerbate biogeochemical impacts.

Figure 2.15 compares, for seven climate models, the biophysical effects of historical anthropogenic land cover change in North America and Eurasia (essentially cooling) to the regional warming resulting from the increased atmospheric CO <sub>2</sub> content since pre- industrial times (De Noblet-Ducoudré et al. 2012 <sup>[[#fn:r1025|1025]]</sup> ; comparing 1973–2002 to 1871–1900). It shows a dominant biophysical cooling effect of changes in land cover, at all seasons, as large as the regional footprint of anthropogenic global warming. Averaged over all agricultural areas of the world (Pongratz et al. 2010 <sup>[[#fn:r1026|1026]]</sup> ) reported a 20th century biophysical cooling of –0.10°C, and Strengers et al. (2010) <sup>[[#fn:r1027|1027]]</sup> reported a land induced cooling as large as –1.5°C in western Russia and eastern China between 1871 and 2007. There is thus ''medium confidence'' that anthropogenic land cover change has dampened warming in many regions of the world over the historical period.

Very few studies have explored the effects of historical land cover changes on seasonal climate. There is, however, evidence that the seasonal magnitude and sign of those effects at the regional level are strongly related to soil-moisture/evapotranspiration and snow regimes, particularly in temperate and boreal latitudes (Teuling et al. 2010 <sup>[[#fn:r1028|1028]]</sup> ; Pitman and de Noblet-Ducoudré 2012 <sup>[[#fn:r1029|1029]]</sup> ; Alkama and Cescatti 2016 <sup>[[#fn:r1030|1030]]</sup> ). Quesada et al. (2017a) <sup>[[#fn:r1031|1031]]</sup> showed that atmospheric circulation changes can be significantly strengthened in winter for tropical and temperate regions. However, the lack of studies underlines the need for a more systematic assessment of seasonal, regional and other- than-mean-temperature metrics in the future.

'''''Effects on extremes'''''

The effect of historical deforestation on extreme temperature trends is intertwined with the effect of other climate forcings, thus making it difficult to quantify based on observations. Based on results from four climate models, the impact of historical anthropogenic land cover change on temperature and precipitation extremes was found to be locally as important as changes arising from increases in atmospheric CO <sub>2</sub> and sea-surface temperatures, but with a lack of model agreement on the sign of changes (Pitman et al. 2012 <sup>[[#fn:r1032|1032]]</sup> ). In some regions, the impact of land cover change masks or amplifies the effect of increased CO <sub>2</sub> on extremes (Avila et al. 2012 <sup>[[#fn:r1033|1033]]</sup> ; Christidis et al. 2013 <sup>[[#fn:r1034|1034]]</sup> ). Using an observational constraint for the local biophysical effect of land cover change applied to a set of CMIP5 climate models, Lejeune et al. (2018) <sup>[[#fn:r1035|1035]]</sup> found that historical deforestation increased extreme hot temperatures in northern mid-latitudes. The results also indicate a stronger impact on the warmest temperatures compared to mean temperatures. Findell et al. (2017) <sup>[[#fn:r1036|1036]]</sup> reached similar conclusions, although using only a single climate model. Importantly, the climate models involved in these three studies did not consider the effect of management changes, which have been shown to be important, as discussed in Section 2.5.2.

Based on the studies discussed above, there is limited evidence but high agreement that land cover change affects local temperature extremes more than mean values. Observational studies assessing the role of land cover on temperature extremes are still very limited (Zaitchik et al. 2006 <sup>[[#fn:r1037|1037]]</sup> ; Renaud and Rebetez 2008 <sup>[[#fn:r1038|1038]]</sup> ), but suggest that trees dampen seasonal and diurnal temperature variations at all latitudes, and even more so in temperate regions compared to short vegetation (Chen et al. 2018 <sup>[[#fn:r1039|1039]]</sup> ; Duveiller et al. 2018 <sup>[[#fn:r1040|1040]]</sup> ; Li et al. 2015a <sup>[[#fn:r1041|1041]]</sup> ; Lee et al. 2011 <sup>[[#fn:r1042|1042]]</sup> ). Furthermore, trees also locally dampen the amplitude of heat extremes (Renaud and Rebetez 2008 <sup>[[#fn:r1043|1043]]</sup> ; Zaitchik et al. 2006 <sup>[[#fn:r1044|1044]]</sup> ) although this result depends on the forest type, coniferous trees providing less cooling effect than broadleaf trees (Renaud et al. 2011 <sup>[[#fn:r1045|1045]]</sup> ; Renaud and Rebetez 2008 <sup>[[#fn:r1046|1046]]</sup> ).

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<span id="table-2.4"></span>
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'''Table 2.4'''

<span id="change-in-mean-global-annual-surface-air-temperature-resulting-from-anthropogenic-land-cover-change-over-the-historical-period."></span>
'''Change in mean global annual surface air temperature resulting from anthropogenic land cover change over the historical period.'''

This historical period varies from one simulation to another (middle column).

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{| class="wikitable"
|-

Reference of the study

Time period

Mean global annual change in surface air temperature (°C)

|-

Simmons and Matthews (2016)

1750–2000

–0.02

|-

Shevliakova et al. (2013)

1861–2005

+0.17

|-

Pongratz et al. (2010)

1900–2000

+0.14

|-

Matthews et al. (2004)

1700–2000

+0.15

|-

Brovkin et al. (2004)

1850–2000

–0.05

|-

Mean ± standard deviation

0.078 ± 0.093

|}
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'''Figure 2.14'''

<span id="changes-in-mean-global-annual-surface-air-temperature-ºc-in-response-to-historical-and-future-anthropogenic-land-cover-changes-as-estimated-from-a-range-of-studies.-see-table-a2.1-in-the-appendix-for-detailed-information.-temperature-changes-resulting-from-biophysical-processes-e.g.-changes-in-physical-land-surface-characteristics-such-as-albedo-evapotranspiration-and-roughness-length"></span>
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'''Changes in mean global annual surface air temperature (ºC) in response to historical and future anthropogenic land cover changes as estimated from a range of studies. See Table A2.1 in the Appendix for detailed information. Temperature changes resulting from biophysical processes (e.g., changes in physical land surface characteristics such as albedo, evapotranspiration and roughness length) […]'''
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[[File:08e4c0dfc6985de239e57e8cfecc576b Figure-2.14-1024x724.jpg]]

Changes in mean global annual surface air temperature (ºC) in response to historical and future anthropogenic land cover changes as estimated from a range of studies. See Table A2.1 in the Appendix for detailed information. Temperature changes resulting from biophysical processes (e.g., changes in physical land surface characteristics such as albedo, evapotranspiration and roughness length) are illustrated using blue symbols and temperature changes resulting from biogeochemical processes (e.g., changes in atmospheric CO <sub>2</sub> composition) use red symbols. Future changes are shown for three distinct scenarios: RCP8.5, RCP4.5 and RCP2.6. The markers ‘filled circle’, ‘filled cross’ and ‘filled triangle down’ represent estimates from global climate models, DGVMs and observations respectively. When the number of estimates is sufficiently large, box plots are overlaid; they show the ensemble minimum, first quartile (25th percentile), median, third quartile (75th percentile), and the ensemble maximum. Scatter points beyond the box plot are the outliers. Details about how temperature change is estimated from DGVMs and observations is provided in the Appendix. Numbers on the right-hand side give the mean and the range of simulated mean global annual warming from various climate models

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'''Figure 2.15'''

<span id="simulated-changes-in-mean-surface-air-temperature-ºc-between-the-pre-industrial-period-18701900-and-the-present-day-19722002-for-all-seasons-and-for-a-north-america-and-b-eurasia.source-de-noblet-ducoudré-et-al.-2012.-brown-boxes-are-the-changes-simulated-in-response-to-increased-atmospheric-ghg-content-between-both-time-periods-and-subsequent-changes-in-sea-surface"></span>
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'''Simulated changes in mean surface air temperature (ºC) between the pre-industrial period (1870–1900) and the present-day (1972–2002) for all seasons and for (A) North America and (B) Eurasia.Source: De Noblet-Ducoudré et al. (2012). Brown boxes are the changes simulated in response to increased atmospheric GHG content between both time periods and subsequent changes in sea-surface […]'''
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[[File:f4afc1705c5c633841db1ca2f70ea59f Figure-2.15-1024x481.jpg]]

Simulated changes in mean surface air temperature (ºC) between the pre-industrial period (1870–1900) and the present-day (1972–2002) for all seasons and for (A) North America and (B) Eurasia.Source: De Noblet-Ducoudré et al. (2012) <sup>[[#fn:r1047|1047]]</sup> . Brown boxes are the changes simulated in response to increased atmospheric GHG content between both time periods and subsequent changes in sea-surface temperature and sea-ice extent (SST/CO <sub>2</sub> ). The CO <sub>2</sub> changes accounted for include emissions from all sources, including land use. Blue boxes are the changes simulated in response to the biophysical effects of historical land cover changes. The box-and-whisker plots have been drawn using results from seven climate models and ensembles of 10 simulations per model and time period. The bottom and top of each grey box are the 25th and 75th percentiles, and the horizontal line within each box is the 50th percentile (the median). The whiskers (straight lines) indicate the ensemble maximum and minimum values. Seasons are respectively December-January-February (DJF), March-April-May (MAM), June-July-August (JJA) and September-October-November (SON). North America and Eurasia are extended regions where land-use changes are the largest between the two time periods considered (their contours can be found in Figure 1 of De Noblet-Ducoudré et al. (2012).

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<span id="impacts-of-future-global-land-cover-changes-on-climate"></span>
==== 2.5.1.2 Impacts of future global land cover changes on climate ====

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'''''At the global level'''''

The most extreme CMIP5 emissions scenario, RCP8.5, has received the most attention in the literature with respect to how projected future anthropogenic land use land cover changes (Hurtt et al. 2011 <sup>[[#fn:r1048|1048]]</sup> ) will affect the highest levels of global warming.

Seven model-based studies have examined both the biophysical and biogeochemical effects of anthropogenic changes in land cover, as projected in RCP8.5, on future climate change (Simmons and Matthews 2016 <sup>[[#fn:r1049|1049]]</sup> ; Davies-Barnard et al. 2014 <sup>[[#fn:r1050|1050]]</sup> ; Boysen et al. 2014 <sup>[[#fn:r1051|1051]]</sup> ) (Table 2.5). They all agree on a biogeochemical warming, ranging from +0.04°C to +0.35°C, in response to land cover change. Two models predict an additional biophysical warming, while the others agree on a biophysical cooling that dampens (or overrules) the biogeochemical warming. Using a wider range of global

climate models, the biogeochemical warming ( ''high confidence'' ) is +0.20 ± 0.15°C whereas it is +0.28 ± 0.11°C when estimated from DGVMs (Pugh et al. 2015 <sup>[[#fn:r1052|1052]]</sup> ; Stocker et al. 2014 <sup>[[#fn:r1053|1053]]</sup> ). This biogeochemical warming is compensated for by a biophysical cooling ( ''medium confidence'' ) of –0.10 ± 0.14°C (Quesada et al. 2017a <sup>[[#fn:r1054|1054]]</sup> ; Davies-Barnard et al. 2015 <sup>[[#fn:r1055|1055]]</sup> ; Boysen et al. 2014 <sup>[[#fn:r1056|1056]]</sup> ). The estimates of temperature changes resulting from anthropogenic land cover changes alone remain very small compared to the projected mean warming of +3.7°C by the end of the 21st century (ranging from 2.6°C–4.8°C depending on the model and compared to 1986–2005; Figure 2.14).

Two other projected land cover change scenarios have been examined (RCP4.5 and RCP2.6; Table 2.5; Figure 2.14) but only one climate modelling experiment has been carried out for each, to estimate the biophysical impacts on climate of those changes (Davies-Barnard et al. 2015 <sup>[[#fn:r1057|1057]]</sup> ). For RCP2.6, ESMs and DGVMs agree on a systematic biogeochemical warming resulting from the imposed land cover changes, ranging from +0.03 to +0.28°C (Brovkin et al. 2013 <sup>[[#fn:r1058|1058]]</sup> ), which is significant compared to the projected mean climate warming of +1°C by the end of the 21st century (ranging from 0.3°C–1.7°C depending on the models, compared to 1986–2005). A very small amount of biophysical cooling is expected from the one estimate. For RCP4.5, biophysical warming is expected from only one estimate, and results from a projected large forestation in the temperate and high latitudes. There is no agreement on the sign of the biogeochemical effect: there are as many studies predicting cooling as warming, whichever the method to compute those effects (ESMs or DGVMs).

Previous scenarios – Special Report on Emission Scenarios (SRES) results of climate studies using those scenarios were reported in AR4 – displayed larger land use changes than the more recent ones (RCP,AR5). There is ''low confidence'' from some of those previous scenarios (SRES A2 and B1) of a small warming effect (+0.2 to +0.3°C) of anthropogenic land cover change on mean global climate, this being dominated by the release of CO <sub>2</sub> in the atmosphere from land conversions (Sitch et al. 2005 <sup>[[#fn:r1059|1059]]</sup> ). This additional warming remains quite small when compared to the one resulting from the combined anthropogenic influences (+1.7°C for SRES B1 and +2.7°C for SRES A2). A global biophysical cooling of –0.14°C is estimated in response to the extreme land cover change projected in SRES A2, a value that far exceeds the impacts of historical land use changes (–0.05°C) calculated using the same climate model (Davin et al. 2007 <sup>[[#fn:r1060|1060]]</sup> ). The authors derived a biophysical climatic sensitivity to land use change of about –0.3°C W.m <sup>–2</sup> for their model, whereas a warming of about 1°C W.m <sup>–2</sup> is obtained in response to changes in atmospheric CO <sub>2</sub> concentration.

Those studies generally do not report on changes in atmospheric variables other than surface air temperature, thereby limiting our ability to assess the effects of anthropogenic land cover changes on regional climate (Sitch et al. 2005 <sup>[[#fn:r1061|1061]]</sup> ). However, small reductions reported in rainfall via changes in biophysical properties of the land, following the massive tropical deforestation in SRES A2 (+0.5 and +0.25 mm day <sup>–1</sup> respectively in the Amazon and Central Africa). They also report opposite changes – that is, increased rainfall of about 0.25 mm day <sup>–1</sup> across the entire tropics and subtropics, triggered by biogeochemical effects of this same deforestation.

'''''At the regional level'''''

In regions that will undergo land cover changes, dampening of the future anthropogenic warming can be as large as –26% while enhancement is always smaller than 9% within RCP8.5 by the end of the 21st century (Boysen et al. 2014 <sup>[[#fn:r1062|1062]]</sup> ). Voldoire (2006) <sup>[[#fn:r1063|1063]]</sup> shows that, by 2050, and following the SRES B2 scenario, the contribution of land cover changes to the total temperature change can be as large as 15% in many boreal regions, and as large as 40% in south-western tropical Africa. Feddema et al. (2005) <sup>[[#fn:r1064|1064]]</sup> simulate large decreases in the diurnal temperature range in the future (2050 and 2100 in SRES B1 and A2) following tropical deforestation in both scenarios. In the Amazon, for example, the diurnal temperature range is lowered by 2.5°C due to increases in minimum temperature, while little change is obtained for the maximum value.

There is thus ''medium evidence'' that future anthropogenic land cover change will have a significant effect on regional temperature via biophysical effects in many regions of the world. There is, however, ''no agreement'' on whether warming will be dampened or enhanced, and there is ''no agreement'' on the sign of the contribution across regions.

There are very few studies that go beyond analysing the changes in mean surface air temperature. Some studies attempted to look at global changes in rainfall and found no significant influence of future land cover changes (Brovkin et al. 2013 <sup>[[#fn:r1065|1065]]</sup> ; Sitch et al. 2005 <sup>[[#fn:r1066|1066]]</sup> ; Feddema et al. 2005 <sup>[[#fn:r1067|1067]]</sup> ). Quesada et al. (2017a <sup>[[#fn:r1068|1068]]</sup> , b <sup>[[#fn:r1069|1069]]</sup> ) however carried out a systematic multi-model analysis of the response of a number of atmospheric, radiative and hydrological variables (e.g., rainfall, sea level pressure, geopotential height, wind speed, soil-moisture, turbulent heat fluxes, shortwave and longwave radiation, cloudiness) to RCP8.5 land cover scenario. In particular, they found a significant reduction of rainfall in six out of eight monsoon regions studied (Figure 2.16) of about 1.9–3% (which means more than –0.5 mm day <sup>–1</sup> in some areas) in response to future anthropogenic land cover changes. Including those changes in global climate models reduces the projected increase in rainfall by about 9–41% in those same regions, when all anthropogenic forcings are accounted for (30% in the global monsoon region as defined by Wang and Ding (2008 <sup>[[#fn:r1070|1070]]</sup> )). In addition, they found a shortening of the monsoon season of one to four days. They conclude that the projected future increase in monsoon rains may be overestimated by those models that do not yet include biophysical effects of land cover changes. Overall, the regional hydrological cycle was found to be substantially reduced and wind speed significantly strengthened in response to regional deforestation within the tropics, with magnitude comparable to projected changes with all forcings (Quesada et al. 2017b <sup>[[#fn:r1071|1071]]</sup> ).

'''''Effects on extremes'''''

Results from a set of climate models have shown that the impact of future anthropogenic land cover change on extreme temperatures can be of similar magnitude as the changes arising from half a degree global mean annual surface temperature change (Hirsch et al. 2018 <sup>[[#fn:r1072|1072]]</sup> ). However, this study also found a lack of agreement between models with respect to the magnitude and sign of changes, thus making land cover change a factor of uncertainty in future climate projections.

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<span id="table-2.5"></span>
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'''Table 2.5'''

<span id="change-in-mean-global-annual-surface-air-temperature-resulting-from-anthropogenic-land-cover-changes-projected-for-the-future-according-to-three-different-scenarios-rcp8.5-rcp4.5-and-rcp2.6."></span>
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 '''Change in mean global annual surface air temperature resulting from anthropogenic land cover changes projected for the future, according to three different scenarios: RCP8.5, RCP4.5 and RCP2.6.'''

Temperature changes resulting from biophysical and biogeochemical effects of land cover change are examined.
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[[File:06f33ed15db05e99f31259a8e97d2ea1 table-2.5.png]]

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<span id="figure-2.16"></span>
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'''Figure 2.16'''

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'''Changes in monsoon rainfall in RCP8.5 scenario resulting from projected changes in anthropogenic land cover, in eight monsoon regions (%, blue bars). Differences are calculated between the end of the 21st century (2071–2100) and the end of the 20th century (1976–2005), and the percent change is calculated with reference to 1976–2005. Grey bars refer to […]'''
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[[File:b7f35600beedd6a93242d3be3b32c1ff Figure-2.16-1024x659.jpg]]

Changes in monsoon rainfall in RCP8.5 scenario resulting from projected changes in anthropogenic land cover, in eight monsoon regions (%, blue bars). Differences are calculated between the end of the 21st century (2071–2100) and the end of the 20th century (1976–2005), and the percent change is calculated with reference to 1976–2005. Grey bars refer to the relative contribution of land-cover changes (in %) to future rainfall projections: it is the ratio between the change in rainfall responding to land cover changes and the one responding to all anthropogenic changes (Quesada et al. 2017b <sup>[[#fn:r1073|1073]]</sup> ). Negative values mean that changes in land cover have an opposite effect (dampening) on rainfall compared to the effects of all anthropogenic changes. Monsoon regions have been defined following Yim et al. (2014) <sup>[[#fn:r1074|1074]]</sup> . The changes have been simulated by five climate models (Brovkin et al. 2013) <sup>[[#fn:r1075|1075]]</sup> . Results are shown for December-January-February for southern hemisphere regions, and for June-July-August for northern hemisphere regions. Statistical significance is given by green tick marks and circles: one, two and three blue tick marks are displayed for the regions where at least 80% of the climate models have regional changes significant at the 66th, 75th and 80th confidence level, respectively; green circles are added when the regional values are also significant at 90th confidence level. Note that future land cover change impacts on South American monsoon are neither significant nor robust among models, along with very small future projected changes in South American monsoon rainfall.

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