The geographical pattern of near-term surface warming simulated by the CMIP5 (Coupled Model Intercomparison Project Phase 5) models is consistent with previous IPCC reports in a number of key aspects according to Kirtman et al. (2013). Kirtman et al.
(2013) state that predictions for averages of temperature, over large regions of the planet and for the global mean, exhibit positive skill when verified against observations for forecast periods up to ten years. Near term changes in global mean surface air temperature will likely be in the range 0.3 to 0.7°C. This projection is valid for the four RCP (Representative Concentration Pathway) scenarios and assumes there will be no major volcanic eruptions or secular changes in total solar irradiance before 2035.
In Kirtman et al. (2013), cold episodes were projected to decrease significantly in a future warmer climate and it was considered very likely that heat waves would be more intense, more frequent and last longer towards the end of the 21st century. These conclusions have generally been confirmed in subsequent studies addressing both global scales (Caesar and Lowe, 2012; Orlowsky and Seneviratne, 2012; Sillmann et al., 2013b) and regional scales (Cattiaux et al., 2012; Wang et al., 2012). In the SREX assessment it is reported that increases in the number of warm days and nights and decreases in the number of cold days and nights are virtually certain on the global scale. Additionally it is projected that the mean global mean surface air temperature for the period 2016–2035 will be more than 1°C above the mean for 1850–1900, and very unlikely that it will be more than 1.5°C above the 1850–1900 mean, Kirtman et al. (2013).
It must be emphasized that detection and attribution studies have previously shown that temperature extremes have already increased in many regions, consistent with climate
UNIVERSITAT ROVIRA I VIRGILI
CLIMATE CHANGE ANALYSIS FOR GUINEA CONAKRY WITH HOMOGENIZED DAILY DATASET.
Abdoul Aziz Barry Dipòsit Legal: T 262-2015
35 Climate change analysis for Guinea Conakry with homogenized daily dataset change projections, and analyses of CMIP5 global projections showed that this trend will continue and become more notable. Furthermore, the CMIP5 model ensemble exhibits a significant decrease in the frequency of cold nights, an increase in the frequency of warm days and nights and an increase in the duration of warm spells (Sillmann et al., 2013b).
These changes are particularly evident in global mean projections and; they are also remarkably insensitive to the emission scenario considered (Caesar and Lowe, 2012).
To summarize, in most land regions and in the near-term, the frequency of warm days and warm nights will thus likely continue to increase, while that of cold days and cold nights will likely continue to decrease.
According to AR5, projections of precipitation over some land areas exhibit positive skill.
The frequency and intensity of heavy precipitation events over land will likely increase on average in the near term. However, this trend will not be apparent in all regions because of natural variability and possible influences of anthropogenic aerosols.
AR4 projections of the spatial patterns of precipitation change in response to GHG forcing showed consistency between models on the largest scales but large uncertainty on smaller scales. The consistent pattern was characterized by increases at high latitudes and in wet regions, including the maxima in mean precipitation found in the tropics, and decreases in dry regions including large parts of the subtropics. Large uncertainties in the sign of projected change were seen especially in regions located on the borders between regions of increases and regions of decreases. Tebaldi et al. (2011) and Power et al.
(2012) highlighted the fact that if models agree that the projected change is small in some sense relative to internal variability, then agreement on the sign of the change is not expected. This recognition led to the identification of sub-regions within the border regions, where models agree that projected changes are either zero or small concluded Power et al. (2012). Power et al. (2012) stated that the consensus among models on precipitation projections is more widespread than might have been inferred on the basis of the projections described in the AR4 (Kirtman et al., 2013).
The general pattern of wet-get-wetter (Allan et al., 2010) and dry-get-drier has been confirmed, although with deviations in some dry regions at present that are projected to become wetter by some models, e.g. East Africa. It has been demonstrated that the wet-get-wetter pattern implies an enhanced seasonal precipitation range between wet and dry
UNIVERSITAT ROVIRA I VIRGILI
CLIMATE CHANGE ANALYSIS FOR GUINEA CONAKRY WITH HOMOGENIZED DAILY DATASET.
Abdoul Aziz Barry Dipòsit Legal: T 262-2015
2. Background
Climate change analysis for Guinea Conakry with homogenized daily dataset 36 seasons in the tropics, and enhanced inter-hemispheric precipitation gradients (Kirtman et al., 2013).
In the near term, and on regional or smaller scales, the magnitude of projected changes in mean precipitation was small compared to the magnitude of natural internal variability in AR4 (Kirtman et al., 2013). Deser et al. (2012) and Power et al. (2012) confirmed this result and provided more quantification.
In addition to the response to GHG forcing, forcing from natural and anthropogenic aerosols may exert significant impacts on regional patterns of precipitation change as well as on global mean temperature (Bollasina et al., 2011; Yue et al., 2011; Fyfe et al., 2012).
For the 21st century, the AR4 and the SREX concluded that heavy precipitation events were likely to increase in many areas of the globe (Kirtman et al., 2013). Since AR4, a larger number of additional studies have been published using global and regional climate models (Hanel and Buishand, 2011; Heinrich and Gobiet, 2011; Meehl et al., 2012).
For the near term, CMIP5 global projections confirm a clear tendency for increases in heavy precipitation events in the global mean, but there are significant variations across regions (Sillmann et al., 2013b). Past observations have also shown that interannual and decadal variability in mean and heavy precipitation are large, and are in addition strongly affected by internal variability e.g. El Niño, volcanic forcing and anthropogenic aerosol loads. In general models have difficulties in representing these variations, particularly in the tropics. Thus the frequency and intensity of heavy precipitation events will likely increase over many land areas in the near term, but this trend will not be apparent in all regions, because of natural variability and possible influences of anthropogenic aerosols.
Simulations with regional climate models demonstrate that the response in terms of heavy precipitation events to anthropogenic climate change may become evident in some but not all regions in the near term (Kirtman et al., 2013).
Previous work reviewed in AR4 has established that extreme precipitation events may increase substantially stronger than mean precipitation amounts (Kirtman et al., 2013).
Models project near-term increases in the duration, intensity and spatial extent of heat waves and warm spells. These changes may proceed at a different rate than the mean warming. For example, several studies project that European high-percentile summer
UNIVERSITAT ROVIRA I VIRGILI
CLIMATE CHANGE ANALYSIS FOR GUINEA CONAKRY WITH HOMOGENIZED DAILY DATASET.
Abdoul Aziz Barry Dipòsit Legal: T 262-2015
37 Climate change analysis for Guinea Conakry with homogenized daily dataset temperatures warm faster than mean temperatures (Kirtman et al., 2013). On regional scales, mean projected changes are almost everywhere smaller than the estimated standard deviation of natural internal variability according to Kirtman et al. (2013).
Seneviratne et al. (2012) assessed that model projections indicated an increase in droughts, in particular in subtropical and mid-latitude areas (Christensen et al., 2007). An increase in dry spells length and frequency was considered very likely over the Mediterranean region, southern areas of Australia, and New Zealand and likely over most subtropical regions, with little change over northern Europe. Continental drying and the associated risk of drought were considered likely to increase in summer over many mid-latitude continental interiors, in boreal spring, and dry periods of the annual cycle over Central America.
On the global scale, Burke and Brown (2008) provided an analysis of projected changes in drought based on four indices using two model ensembles: one based on a GCM expressing uncertainty in parameter space, and a multi-model ensemble of 11 GCM simulations from CMIP3. Their analysis revealed that SPI (Standardized Precipitation Index), based solely on precipitation, showed little change in the proportion of the land surface stricken by drought, but all the other indices, which include a measure of the atmospheric demand for moisture, showed a statistically significant increase of drought with the extension of the drought stricken area by 5 to 45 %. This study also highlighted large uncertainties in regional changes in drought (IPCC, 2012).