scholarly journals Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations

2007 ◽  
Vol 34 (2) ◽  
Author(s):  
Rowan T. Sutton ◽  
Buwen Dong ◽  
Jonathan M. Gregory
Keyword(s):  
Climate Change ◽  
Ipcc Ar4 ◽  
Sea Warming

scholarly journals Linking IPCC AR4 & AR5 frameworks for assessing vulnerability and risk to climate change in the Indian Bengal Delta

2020 ◽  
Vol 7 ◽  
pp. 100110 ◽  
Author(s):  
Shouvik Das ◽  
Amit Ghosh ◽  
Sugata Hazra ◽  
Tuhin Ghosh ◽  
Ricardo Safra de Campos ◽  
...  
Keyword(s):  
Climate Change ◽  
Bengal Delta ◽  
Ipcc Ar4

Phenological changes in Europe are still attributable to climate change induced warming

2020 ◽  
Author(s):  
Annette Menzel ◽  
Ye Yuan ◽  
Michael Matiu ◽  
Tim H Sparks ◽  
Helfried Scheifinger ◽  
...  
Keyword(s):  
Climate Change ◽  
Wild Species ◽  
Plant Traits ◽  
Temperature Response ◽  
Early Spring ◽  
Wild Plants ◽  
Phenological Changes ◽  
Species Groups ◽  
Mean Trend ◽  
Ipcc Ar4

<p>During 1971-2000 phenological responses of wild species in spring and summer matched the warming pattern in Europe, whereas timing of farming activities as well as autumnal leaf colouring did not mirror climate change to the same extent (Menzel et al. GCB 2006). These findings were a backbone of the corresponding global attribution study of the IPCC AR4 (Rosenzweig et al. 2007, 2008). Two decades of warming later, however, new phenological findings suggest that especially a lack of chilling and / or increasing influence of photoperiod may have lowered the phenological temperature response and that adaptation in agricultural management is taking place. We therefore updated the GCB 2006 study by asking three questions: What drives the inherent variation of trends? Can we now detect a warming signal in “false” agricultural (i.e. those being directly or indirectly determined by farmers’ management) and autumn phases? Is there still an attributable warming signal in phenology?</p><p>The complete phenological dataset of Germany, Austria and Switzerland (1951-2018, ~97.000 times series, corresponding to 96.3% of PEP725 data) was analysed. We determined linear trends, studied their variation by plant traits / phenogroups, across season and time, and followed IPCC methodology for attributing phenological changes to warming patterns.</p><p>For spring and summer phases of wild plants we found more (significantly) advancing trends (~90% and ~60% sign.) which were stronger in early spring, at higher elevations, but smaller for non-woody insect-pollinated species. Although mean trend strength decreased, changes in spring were strongly attributable to warming in spring and winter. We had similar but less strong findings for agricultural crops in these seasons. In contrast only ~75% of phenological phases set by farmers’ decisions were advancing, however this was the only phenological group for which the mean advance increased, indicating adaptation. Equally trends in farming phases in spring and summer were attributable to warming in winter and summer, respectively. Leaf coloring and fall was now predominantly delayed (57%) which was attributable to winter and spring warming, too.</p><p>Thus, this update of the GCB2006 study demonstrates that there is still a significant and attributable phenological change pattern in Europe, in which number of (significant) trends pointing into the direction of warming increased, but mean trend strength mostly decreased, probably due to a lack of chilling and smaller forcing trends. More attention should be paid to the inherent variability of trends with traits / species groups, season and time triggering divers (e.g. ecological) consequences of these phenological shifts. Still existing differences between the generative period of crops and wild species as well as between the farming season and the general growing season call for more research in this area.</p>

scholarly journals Potential effects of climate change on inundation patterns in the Amazon Basin

2013 ◽  
Vol 17 (6) ◽  
pp. 2247-2262 ◽  
Author(s):  
F. Langerwisch ◽  
S. Rost ◽  
D. Gerten ◽  
B. Poulter ◽  
A. Rammig ◽  
...  
Keyword(s):  
Climate Change ◽  
Amazon Basin ◽  
Climate Models ◽  
Climate Projections ◽  
Flooding Regime ◽  
Key Factor ◽  
Inundation Duration ◽  
Flooded Area ◽  
Global Vegetation ◽  
Ipcc Ar4

Abstract. Floodplain forests, namely the Várzea and Igapó, cover an area of more than 97 000 km2. A key factor for their function and diversity is annual flooding. Increasing air temperature and higher precipitation variability caused by climate change are expected to shift the flooding regime during this century, and thereby impact floodplain ecosystems, their biodiversity and riverine ecosystem services. To assess the effects of climate change on the flooding regime, we use the Dynamic Global Vegetation and Hydrology Model LPJmL, enhanced by a scheme that realistically simulates monthly flooded area. Simulation results of discharge and inundation under contemporary conditions compare well against site-level measurements and observations. The changes of calculated inundation duration and area under climate change projections from 24 IPCC AR4 climate models differ regionally towards the end of the 21st century. In all, 70% of the 24 climate projections agree on an increase of flooded area in about one third of the basin. Inundation duration increases dramatically by on average three months in western and around one month in eastern Amazonia. The time of high- and low-water peak shifts by up to three months. Additionally, we find a decrease in the number of extremely dry years and in the probability of the occurrence of three consecutive extremely dry years. The total number of extremely wet years does not change drastically but the probability of three consecutive extremely wet years decreases by up to 30% in the east and increases by up to 25% in the west. These changes implicate significant shifts in regional vegetation and climate, and will dramatically alter carbon and water cycles.

The use of the land-sea warming contrast under climate change to improve impact metrics

2013 ◽  
Vol 117 (4) ◽  
pp. 951-960 ◽  
Author(s):  
Manoj M. Joshi ◽  
Andrew G. Turner ◽  
Chris Hope
Keyword(s):  
Climate Change ◽  
Sea Warming

scholarly journals Lessons Learned from IPCC AR4: Scientific Developments Needed to Understand, Predict, and Respond to Climate Change

2009 ◽  
Vol 90 (4) ◽  
pp. 497-514 ◽  
Author(s):  
Sarah J. Doherty ◽  
Stephan Bojinski ◽  
Ann Henderson-Sellers ◽  
Kevin Noone ◽  
David Goodrich ◽  
...  
Keyword(s):  
Climate Change ◽  
Lessons Learned ◽  
Ipcc Ar4

Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju Basin, Korea

2011 ◽  
Vol 401 (1-2) ◽  
pp. 90-105 ◽  
Author(s):  
Deg-Hyo Bae ◽  
Il-Won Jung ◽  
Dennis P. Lettenmaier
Keyword(s):  
Climate Change ◽  
Ipcc Ar4
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