averaged over the entire ice sheet was 68%. Albedo in July 2015 was as much as 15%–20% below average along the northwestern ice sheet and along the west coast, where a large increase in melting days was observed in 2015. Over the entire summer, however, the albedo anomaly along the southwestern ice sheet margin coast was positive, consistent with a relatively shorter melt season and with the presence of summer snow accumulation.

GRACE satellite data (Velicogna et al. 2014) are used to estimate monthly changes in the total mass of the Greenland Ice Sheet, including mass gain due to accumulation and summer losses due to runoff and calving (Fig. 5.10). Between the beginning of September 2014 and the beginning of September 2015 GRACE recorded a $174 \pm 45$ Gt (Gt $\equiv 10^9$ tons) mass loss, versus an average September-to-September loss of $278 \pm 35$ Gt for the 2002–15 period. As a comparison, the 2013–14 September-to-September loss was $236 \pm 45$ Gt

(7% of the total loss of ~3500 Gt since the beginning of the GRACE record in 2002) and that for 2011–12 was $638 \pm 45$ Gt (18% of the total loss). The relatively modest loss for the 2014–15 period is consistent with reduced melting over the southwest portion of the ice sheet and increased summer snowfall.

Glacier front classification in LANDSAT and AS-TER imagery (after Jensen et al. 2016) reveals that 45 of the widest and fastest flowing marine-terminating glaciers retreated at a slower rate in 2013–15 than in the 1999–2012 period (Fig. 5.11). Between the end of the 2014 melt season and the end of the 2015 melt season, 22 of the 45 glaciers retreated, but the advance of 9 relatively wide glaciers resulted in the lowest

annual net area loss in the 16-year period of observations (1999–2015), being –16.5 km² or 7.7 times lower than the annual average area change trend of –127 km² yr⁻¹ (Fig. 5.11). Specifically, Petermann Glacier advanced by 0.68 km across a width of 17.35 km, and Kangerdlugssuaq Glacier advanced by 1.68 km across a width of 6.01 km.

f. *Glaciers and ice caps outside Greenland*—G. Wolken, M. Sharp, L. M. Andreassen, A. Arendt, D. Burgess, J. G. Cogley, L. Copland, J. Kohler, S. O’Neel, M. Pelto, L. Thomson, and B. Wouters

Mountain glaciers and ice caps cover an area of over 400 000 km² in the Arctic and are a leading contributor to global sea level change (Gardner et al. 2011, 2013; Jacob et al. 2012). They gain mass by snow accumulation and lose mass by surface melt runoff, and by iceberg calving where they terminate in water (ocean or lake). The total mass balance (ΔM) is defined as the difference between annual snow accumulation and annual mass losses (by iceberg calving plus surface melt runoff). Of the 27 glaciers currently monitored, however, only three (Kongsvegen, Hansbreen, and Devon Ice Cap NW) lose any mass by iceberg calving into the ocean. For all glaciers discussed here, the climatic mass balance is reported ($B_{clim}$, the difference between annual snow accumulation and annual runoff). $B_{clim}$ is a widely used index of how glaciers respond to climate variability and change.

<figure><img src="image_202.png" /><figcaption>FIG. 5.11. Cumulative net area change (km², left y-axis and square miles, right y-axis) of 45 of the widest and fastest-flowing marine-terminating glaciers of the Greenland Ice Sheet (Box and Hansen 2015; Jensen et al. 2016). The linear regression is dashed.</figcaption></figure>

<figure><img src="image_203.png" /><figcaption>FIG. 5.10. Cumulative change in the total mass (Gt) of the Greenland Ice Sheet between Apr 2002 and Sep 2015 estimated from GRACE measurements. The square symbols denote Apr values for reference.</figcaption></figure>
$B_{\text{clim}}$ measurements for mass balance year 2014/15 are available for only 9 of the 26 glaciers that are monitored across the Arctic (three each in Alaska and Svalbard, and one in Norway), and some of these are still provisional. Therefore, we focus on the 2013/14 $B_{\text{clim}}$ measurements, which are available for 21 glaciers (WGMS 2015b). These glaciers are located in Alaska (three), Arctic Canada (four), Iceland (seven), Svalbard (three), Norway (three), and Sweden (one; Fig. 5.12; Table 5.1). For these glaciers as a group, the mean $B_{\text{clim}}$ in 2013/14 was negative. However, five glaciers [one each in Arctic Canada (Meighen Ice Cap) and Iceland (Dyngjujökull) and three in Svalbard (Midre Lovenbreen, Austre Broggerbreen, and Kongsvegen)] had positive balances.

For the Arctic as a whole, 2013/14 was the 17th most negative mass balance year on record (the first record dates from 1946) and the 12th most negative year since 1989 (i.e., the median for the 25-year period), when annual measurements of at least 20 glaciers began. This balance year continues the increasingly negative trend of cumulative regional climatic mass balances, calculated by summing the annual mean mass balances for all glaciers in each reporting region of the Arctic (Fig. 5.13). For Svalbard, 2013/14 was among the least negative mass balance years on record, and the climatic balances of each of its three glaciers were among the 3–9 most positive since 1987. Local meteorological observations suggest that the positive balances in Svalbard were attributable to high winter (October–May) precipitation, especially at low elevations, that was followed by a relatively cool summer (June–August). Melt suppression over Svalbard, as well as the Russian Arctic Archipelagos and the northernmost islands of Arctic Canada, was likely linked to negative 850-hPa air temperature anomalies in June–September. In contrast, in 2013/14 the mean measured climatic balance of glaciers in Alaska was the fifth most negative since 1966, with Lemon Creek and Wolverine glaciers registering their third and fourth most negative years on record, respectively. The negative balances of Alaska, Iceland, and northern Scandinavia glaciers in 2013/14 were most likely linked to melt increases caused by positive air temperature anomalies at the 850-hPa level in July–September that exceeded +2.5°C in northern Norway and Sweden (data from NCEP–NCAR reanalysis). Indeed, in 2014, many locations in northern Scandinavia reported their highest summer air temperatures since records began (Overland et al. 2015).

Among the nine glaciers for which 2014/15 $B_{\text{clim}}$ measurements have been reported, the balances of glaciers in Alaska, Svalbard, and northern Norway

<figure><img src="image_204.png" /><figcaption>**Fig. 5.12.** Locations (green circles) of 27 Arctic glaciers with long-term records of annual climatic mass balance ($B_{\text{clim}}$). See Table 5.1 for glacier names. Regions outlined in yellow are the Randolph Glacier Inventory (RGI) regions of the Arctic (Pfeffer et al. 2014). In regions where individual glaciers are located too close together to be identifiable on the map, their numbers are shown at the edge of the RGI region in which they occur. Red shading indicates glaciers and ice caps, including ice caps in Greenland outside the ice sheet. Yellow shading shows the solution domains for regional mass balance estimates for Alaska, Arctic Canada, Russian Arctic, and Svalbard derived using gravity data from the GRACE satellites (see Fig. 5.3).</figcaption></figure>

<figure><img src="image_205.png" /><figcaption>**Fig. 5.13.** Cumulative climatic mass balances ($B_{\text{clim}}$ in kg m⁻²) for glaciers in five regions of the Arctic and for the Arctic as a whole (Pan–Arctic). Mean balances are calculated for glaciers monitored in each region in each year and these means are summed over the period of record. Note that the period of monitoring varies between regions and that the number and identity of glaciers monitored in a given region may vary between years.</figcaption></figure>
<table><caption>TABLE 5.1. Measured annual climatic mass balance (B<sub>clim</sub>) of glaciers in Alaska, the Canadian Arctic, Iceland, Svalbard, and northern Scandinavia for 2013/14 and 2014/15, along with the 1980–2010 mean and standard deviation for each glacier (column 3). Mass balance data are from the World Glacier Monitoring Service (2015; 2016), with corrections to Svalbard data provided by J. Kohler and to Alaska data provided by S. O’Neel, and with updates from the Norwegian Water Resources and Energy Directorate (NVE) database. Numbers in column 1 identify glacier locations in Fig. 5.1. Note that 2014/15 results may be based upon data collected before the end of the 2015 melt season and may be subject to revision.</caption><thead><tr><th>Region</th><th>Glacier (Record length, years)</th><th>Mean Climatic Balance 1980–2010 (kg m<sup>-2</sup> yr<sup>-1</sup>)</th><th>Standard Deviation of Climatic Mass Balance 1980–2010 (kg m<sup>-2</sup> yr<sup>-1</sup>)</th><th>Climatic Balance 2013/14 (kg m<sup>-2</sup> yr<sup>-1</sup>)</th><th>Climatic Balance 2014/15 (kg m<sup>-2</sup> yr<sup>-1</sup>)</th></tr></thead><tbody><tr><td colspan="6"><strong>Alaska</strong></td></tr><tr><td>1</td><td>Wolverine (50)</td><td>-285</td><td>1205</td><td>-1950</td><td>-1130</td></tr><tr><td>3</td><td>Lemon Creek (63)</td><td>-584</td><td>709</td><td>-1825</td><td>-2270</td></tr><tr><td>2</td><td>Gulkana (50)</td><td>-505</td><td>738</td><td>-220</td><td>-1440</td></tr><tr><td colspan="6"><strong>Arctic Canada</strong></td></tr><tr><td>7</td><td>Devon Ice Cap (54)</td><td>-153</td><td>176</td><td>-246</td><td></td></tr><tr><td>5</td><td>Meighen Ice Cap (53)</td><td>-173</td><td>284</td><td>+57</td><td></td></tr><tr><td>4</td><td>Melville South Ice Cap (52)</td><td>-295</td><td>369</td><td>-159</td><td></td></tr><tr><td>6</td><td>White (52)</td><td>-239</td><td>260</td><td>-417</td><td></td></tr><tr><td colspan="6"><strong>Iceland</strong></td></tr><tr><td>8</td><td>Langjökull S. Dome (18)</td><td>-1448</td><td>817</td><td>-1950</td><td></td></tr><tr><td>9</td><td>Hofsjökull E (24)</td><td>-602</td><td>1009</td><td>-990</td><td></td></tr><tr><td>9</td><td>Hofsjökull N (25)</td><td>-606</td><td>787</td><td>-950</td><td></td></tr><tr><td>9</td><td>Hofsjökull SW (24)</td><td>-978</td><td>947</td><td>-990</td><td></td></tr><tr><td>14</td><td>Köldukvislarjökull (22)</td><td>-529</td><td>738</td><td>-887</td><td></td></tr><tr><td>10</td><td>Tungnaarjökull (23)</td><td>-1170</td><td>873</td><td>-1535</td><td></td></tr><tr><td>13</td><td>Dyngjujökull (17)</td><td>-133</td><td>912</td><td>+170</td><td></td></tr><tr><td>12</td><td>Brúarjökull (22)</td><td>-367</td><td>660</td><td>-34</td><td></td></tr><tr><td>11</td><td>Eyjabakkajökull (23)</td><td>-867</td><td>813</td><td>-353</td><td></td></tr><tr><td colspan="6"><strong>Svalbard</strong></td></tr><tr><td>17</td><td>Midre Lovenbreen (48)</td><td>-356</td><td>305</td><td>+30</td><td>-450</td></tr><tr><td>16</td><td>Austre Broggerbreen (49)</td><td>-469</td><td>342</td><td>+10</td><td>-610</td></tr><tr><td>15</td><td>Kongsvegen (29)</td><td>-70</td><td>378</td><td>+140</td><td>-160</td></tr><tr><td>18</td><td>Hansbreen (26)</td><td>-431</td><td>512</td><td>-227</td><td></td></tr><tr><td colspan="6"><strong>Northern Scandinavia</strong></td></tr><tr><td>20</td><td>Engabreen (45)</td><td>+463</td><td>1091</td><td>-892</td><td>+668</td></tr><tr><td>21</td><td>Langfjordjøkelen (25)</td><td>-927</td><td>781</td><td>-780</td><td>-800</td></tr><tr><td>22</td><td>Marmaglaciaren (23)</td><td>-430</td><td>525</td><td></td><td></td></tr><tr><td>23</td><td>Rabots Glaciar (29)</td><td>-394</td><td>560</td><td></td><td></td></tr><tr><td>24</td><td>Riukojietna (26)</td><td>-592</td><td>805</td><td></td><td></td></tr><tr><td>25</td><td>Storglaciaren (68)</td><td>-113</td><td>698</td><td>-890</td><td></td></tr><tr><td>26</td><td>Tarfalaglaciaren (18)</td><td>-212</td><td>1101</td><td></td><td></td></tr><tr><td>27</td><td>Rundvassbreen (8)</td><td>-777</td><td></td><td>-790</td><td>-20</td></tr></tbody></table>

(Langfjordjøkelen) were negative, while those of glaciers in central Norway were near balance (Rundvassbreen) or positive (Engabreen). The pattern of negative balances in Alaska and Svalbard is also captured in time series of regional total stored water estimates (Fig. 5.14), derived using GRACE satellite

gravimetry available since 2003. Annual storage changes are proxy for changes in the regional annual glacier mass balance (ΔM) for the heavily glacierized regions of the Arctic (Luthcke et al. 2013). Measurements of ΔM in 2014/15 for all the glaciers and ice caps in Arctic Canada and the Russian Arctic also
show a negative mass balance year. The GRACE-derived time series clearly show a continuation of negative trends in ΔM for all measured regions in the Arctic. These measurements of B_clim and ΔM are consistent with anomalously warm (up to +1.5°C) June–August air temperatures over Alaska, Arctic Canada, the Russian Arctic, and Svalbard in 2015 (section 5b), and anomalously cool temperatures in northern Scandinavia, particularly in June and July (up to –2°C).

g. Terrestrial snow cover—C. Derksen, R. Brown, L. Mudryk, and K. Luojus

The Arctic (land areas north of 60°N) is always completely snow-covered in winter and almost snow free in summer, so the transition seasons of autumn and spring are significant when characterizing variability and change. The timing of spring snowmelt is particularly significant because the transition from highly reflective snow cover to the low albedo of snow-free ground is coupled with increasing solar radiation during the lengthening days of the high-latitude spring. The 2015 spring melt season provided continued evidence of earlier snowmelt across the terrestrial Arctic. There is increased awareness of the impact of these changes on the Arctic climate system, the freshwater budget, other components of the cryosphere (such as permafrost and associated geochemical cycles), and Arctic ecosystems (Callaghan et al. 2011).

Snow cover extent (SCE) anomalies (relative to the 1981–2010 reference period) for the 2015 Arctic spring (April, May, June) were computed separately for the North American and Eurasian sectors of the Arctic from the NOAA snow chart Climate Data Record, maintained at Rutgers University (Estilow et al. 2015; http://climate.rutgers.edu/snowcover/). Consistent with nearly all spring seasons of the past decade, both May and June SCE anomalies were strongly negative in 2015 (Fig. 5.15); June SCE in both the North American and Eurasian sectors of the Arctic was the second lowest in the snow chart record, which extends back to 1967.

<figure><img src="image_206.png" /></figure>

FIG. 5.14. Cumulative changes in regional total stored water for 2003–15 (Gt), derived using GRACE satellite gravimetry. Annual storage changes are proxy for changes in the regional annual glacier mass balance (ΔM). The estimated uncertainty in regional mass changes is 10 Gt yr⁻¹ for the Gulf of Alaska, 8 Gt yr⁻¹ for the Canadian Arctic, 8 Gt yr⁻¹ for the Russian Arctic, and 4 Gt yr⁻¹ for Svalbard. These errors include the formal error of the least squares fit and the uncertainties in the corrections for glacial isostatic adjustment, Little Ice Age, and terrestrial hydrology.

<figure><img src="image_207.png" /></figure>

FIG. 5.15. Monthly Arctic snow cover extent standardized (and thus unitless) anomaly time series (with respect to 1981–2010) from the NOAA snow chart Climate Data Record for (a) Apr, (b) May, and (c) Jun 1967–2015 (solid lines denote 5-yr moving average); (d) % change decade⁻¹ in spring snow cover extent for running time series starting in 1979 (1979–98, 1979–99, 1979–2000, etc.).
For the fifth time in the past six years (2010–15), Arctic SCE in June was below 3 million km² despite never falling below this threshold in the previous 43 years of the snow chart data record (1967–2008). Figure 5.15d shows the changing rate of SCE loss across the Arctic since 1998 via calculations over running time periods since 1979, the first year of the satellite passive microwave record used to track sea ice extent. The April and May SCE reductions have remained relatively consistent year over year, ranging between –1% and –2% decade⁻¹ (April; insignificant at 95%) and –3% and –5% per decade⁻¹ (May; significant at 99%). A significant rate of June SCE loss was identified over the first 20 years (nearly –16% for 1979–98) due to rapid reductions in the 1980s, which then plateaued due to a period of stable spring snow cover during the 1990s. Since 2005, the rate of June SCE loss has increased again, reaching almost 18% decade⁻¹ for the period 1979–2015 (compared to the 1981–2010 mean June SCE). Since 2011, the rate of June snow cover loss has exceeded the much publicized rate of September sea ice loss (section 5c).

There are complex interactions between regional variability in the onset of snow cover in the autumn, subsequent winter season snow accumulation patterns (which themselves are driven by the complex interplay of temperature and precipitation anomalies), and continental-scale spring SCE anomalies (shown in Fig. 5.15). Snow cover duration (SCD) departures (relative to the 1998–2010 period) derived from the NOAA daily Interactive Multi-sensor Snow and Ice Mapping System (IMS) snow cover product (Helfrich et al. 2007) suggest earlier snow cover onset in the autumn over much of the Arctic for the 2014/15 snow year (Fig. 5.16a). This is consistent with premelt April snow depth anomalies (relative to the 1999–2010 average), derived from the Canadian Meteorological Centre (CMC) daily gridded global snow depth analysis (Brasnett 1999), which were largely positive over much of the Arctic land surface (25.1% and 33.7%, respectively, for the North American and Eurasian sectors of the Arctic). There was a notable east-west snow depth gradient across Eurasia in April 2015 with above-average snow depth in eastern Siberia and below-average snow depth across western Siberia and northern Europe. The North American Arctic was characterized by a more latitudinal gradient of deeper-than-normal snow depth north of the boreal tree line and shallower-than-normal snow depth across the boreal forest. Note that the CMC results shown in Figs. 5.17a–c mask out anomalies over high elevation areas (in the Canadian Arctic Archipelago, Baffin Island, coastal Alaska) known to be affected by

a bias toward higher winter snow depths since 2006 due to changes in the resolution of the precipitation forcing used as part of the CMC analysis. Strong positive surface temperature anomalies over central Siberia, Alaska, and the western Canadian Arctic in May (which persisted into June; section 5b) were associated with rapid reductions in regional snow depth reflected in the May and June depth anomalies (Figs. 5.17b,c) and earlier than normal snowmelt in these regions (Fig. 5.16b), which drove the negative continental-scale SCE anomalies in May and June (Figs. 5.16b,c).

<figure><img src="image_208.png" /><figcaption>FIG. 5.16. Snow cover duration departures (with respect to 1998–2010) from the NOAA IMS data record for the (a) 2014 autumn season and (b) 2015 spring season.</figcaption></figure>
<figure><img src="image_209.png" /><figcaption>FIG. 5.17. Snow depth anomaly (% of 1999–2010 average) from the CMC snow depth analysis for (a) Apr, (b) May, and (c) Jun 2015.</figcaption></figure>

h. *River discharge*—R. M. Holmes, A. I. Shiklomanov, S. E. Tank, J. W. McClelland, and M. Tretiakov

River discharge integrates hydrologic processes occurring throughout the surrounding landscape. Consequently, changes in the discharge of large rivers can be a sensitive indicator of widespread changes in watersheds (Rawlins et al. 2010; Holmes et al. 2013). Changes in river discharge also impact coastal and ocean chemistry, biology, and circulation. This interaction is particularly strong in the Arctic, given the relative volume of river discharge to ocean volume. Rivers in this region transport >10% of the global river discharge into the Arctic Ocean, which represents only ~1% of the global ocean volume (Aagaard and Carmack 1989; McClelland et al. 2012).

In this section, annual river discharge values since 2011 are presented for the eight largest Arctic rivers, and recent observations are compared to a 1980–89 reference period (the first decade with data from all eight rivers). Six of the rivers lie in Eurasia and two are in North America. Together, the watersheds of these rivers cover 70% of the $16.8 \times 10^6$ km² pan-Arctic drainage area and, as such, account for the majority of riverine freshwater inputs to the Arctic Ocean (Fig. 5.18). Discharge data for the six Eurasian rivers are analyzed through 2015, whereas data from the Yukon and Mackenzie Rivers in North America are only available through 2014. Most of these data are now available through the Arctic Great Rivers Observatory (www.arcticgreatrivers.org).

A long-term increase in Arctic river discharge has been well documented and may be linked to increasing precipitation associated with global warming (Peterson et al. 2002; McClelland et al. 2006; Shiklomanov and Lammers 2009; Overeem and

Sytvitski 2010; Rawlins et al. 2010). The long-term discharge trend is greatest for rivers of the Eurasian Arctic and constitutes the strongest evidence of intensification of the Arctic freshwater cycle (Rawlins et al. 2010).

In 2015, the combined discharge of 2051 km³ for the six largest Eurasian Arctic rivers was 15% greater than the 1980–89 average (Fig. 5.19; Table 5.2), and the peak discharge occurred earlier than the average over the same period (Fig. 5.20). This is the fourth highest combined discharge value since measurements began in 1936. The four highest values have

<figure><img src="image_210.png" /><figcaption>FIG. 5.18. Map showing the watersheds of the eight rivers featured in this section. The blue dots show the location of the discharge monitoring stations and the red line shows the boundary of the pan-Arctic watershed.</figcaption></figure>
<table><caption>TABLE 5.2. Annual discharge for 2012, 2013, and 2014 for the eight largest Arctic rivers, compared to long-term and decadal averages back to the start of observations. Values for 2015 are provided for the six Eurasian rivers. Red values indicate provisional data, which are subject to modification before official data are released.</caption><thead><tr><th colspan="10">Discharge (km³ yr⁻¹)</th></tr><tr><th></th><th>Yukon</th><th>Mackenzie</th><th>Pechora</th><th>S. Dvina</th><th>Ob'</th><th>Yenisey</th><th>Lena</th><th>Kolyma</th><th>Sum</th></tr></thead><tbody><tr><td>2015</td><td></td><td></td><td>123</td><td>80</td><td>527</td><td>654</td><td>585</td><td>82</td><td></td></tr><tr><td>2014</td><td>227</td><td>272</td><td>116</td><td>91</td><td>448</td><td>640</td><td>607</td><td>86</td><td>2487</td></tr><tr><td>2013</td><td>213</td><td>311</td><td>82</td><td>97</td><td>372</td><td>527</td><td>600</td><td>80</td><td>2282</td></tr><tr><td>2012</td><td>232</td><td>306</td><td>103</td><td>117</td><td>300</td><td>458</td><td>665</td><td>59</td><td>2240</td></tr><tr><td>Average 2010–15</td><td>212</td><td>293</td><td>108</td><td>93</td><td>409</td><td>594</td><td>583</td><td>75</td><td>2366</td></tr><tr><td>Average 2000–09</td><td>207</td><td>305</td><td>124</td><td>103</td><td>415</td><td>640</td><td>603</td><td>78</td><td>2475</td></tr><tr><td>Average 1990–99</td><td>217</td><td>275</td><td>117</td><td>111</td><td>405</td><td>613</td><td>532</td><td>68</td><td>2338</td></tr><tr><td>Average 1980–89</td><td>206</td><td>273</td><td>108</td><td>100</td><td>376</td><td>582</td><td>549</td><td>68</td><td>2262</td></tr><tr><td>Average 1970–79</td><td>184</td><td>292</td><td>108</td><td>94</td><td>441</td><td>591</td><td>529</td><td>65</td><td>2304</td></tr><tr><td>Average 1960–69</td><td></td><td>273</td><td>112</td><td>98</td><td>376</td><td>546</td><td>535</td><td>73</td><td></td></tr><tr><td>Average 1950–59</td><td></td><td></td><td>110</td><td>108</td><td>380</td><td>566</td><td>511</td><td>74</td><td></td></tr><tr><td>Average 1940–49</td><td></td><td></td><td>102</td><td>100</td><td>424</td><td>578</td><td>498</td><td>72</td><td></td></tr><tr><td>Average for Period of Record</td><td>206</td><td>286</td><td>111</td><td>100</td><td>401</td><td>589</td><td>540</td><td>71</td><td>2305</td></tr></tbody></table>

all occurred in the past 14 years. Overall, the most recent data indicate a continuing long-term increase in Eurasian Arctic river discharge, at a rate of 3.5% ± 2.1% decade⁻¹ since 1976. Looking more closely at recent years, Eurasian Arctic river discharge generally declined between 2007 and 2012 and then began to increase again in 2013. Values for 2012 (1702 km³), 2013 (1759 km³), and 2014 (1989 km³) were 5% less, 1% less, and 2% greater than the 1980–89 period, respectively. The short-term variability in Eurasian Arctic river discharge is consistent with previous increases and decreases over 4–6 year intervals in the past (Fig. 5.19).

For the North American Arctic rivers considered here (Yukon and Mackenzie), the combined discharge declined each year from 2012 (538 km³) to 2014 (499 km³), yet in each of those years the combined discharge was greater than the long-term average (493 km³ year⁻¹; Fig. 5.19; Table 5.2). Thus, as discussed for Eurasian rivers, these most recent data indicate a longer-term pattern of increasing river discharge (Fig. 5.19). At a rate of 2.6% ± 1.7% decade⁻¹ since 1976, the overall trends of increasing discharge are remarkably similar for the North American

and Eurasian rivers. (Increases per decade follow a Mann–Kendall trend analysis; error bounds are 95% confidence intervals for the trend.)

<figure><img src="image_211.png" /><figcaption>FIG. 5.19. Long-term trends in annual discharge for Eurasian and North American Arctic rivers. The Eurasian rivers are Severnaya Dvina, Pechora, Ob', Yenisey, Lena, and Kolyma. The North American rivers are Yukon and Mackenzie. Note the different scales for the Eurasian and North American river discharge; discharge from the former is 3–4 times greater than the latter. Reference lines show long-term means for the Eurasian (1812 km³ yr⁻¹, 1936–2015) and North American (493 km³ yr⁻¹, 1976–2014) rivers.</figcaption></figure>
<figure><img src="image_212.png" /><figcaption>FIG. 5.20. Combined daily discharge for the six Eurasian Arctic rivers in 2015 compared to the 1980–89 average.</figcaption></figure>

Considering the eight Eurasian and North Ameri-
can Arctic rivers together, their combined discharge
in 2014 (2487 km³) was 10% greater than the average
discharge for 1980–89. Comparing 2014 to 2012, the
combined discharge of these eight rivers was almost
250 km³ greater in 2014. For perspective, 250 km³ is
approximately 14 times the annual discharge of the
Hudson River, the largest river on the east coast of
the United States.

i. *Terrestrial permafrost*—V. E. Romanovsky, S. L. Smith, K. Isaksen, N. I. Shiklomanov, D. A. Streletskiy, A. L. Kholodov, H. H. Christiansen, D. S. Drozdov, G. V. Malkova, and S. S. Marchenko

Permafrost is defined as soil, rock, and any other
subsurface earth material that exists at or below 0°C
continuously for two or more consecutive years. On
top of permafrost is the active layer, which thaws
during the summer and freezes again the following
winter. The mean annual temperature of permafrost
and the active layer thickness (ALT) are good indica-
tors of changing climate and therefore designated as
essential climate variables (Smith and Brown 2009;
Biskaborn et al. 2015) by the Global Climate Observ-
ing System Program of the World Meteorological
Organization. Changes in permafrost temperatures
and ALT at undisturbed locations in Alaska, Canada,
Russia, and the Nordic region (Fig. 5.21) are reported
here. Regional variability in permafrost temperature
records, described below, indicates more substantial
permafrost warming since 2000 in higher latitudes
than in the subarctic. This is in general agreement
with the pattern of average air temperature anomalies.

In 2015, record high temperatures at 20-m depth
were measured at all permafrost observatories on the
North Slope of Alaska (Barrow, West Dock, Franklin
Bluffs, Happy Valley, and Galbraith Lake in Fig. 5.22a;
Romanovsky et al. 2015). The permafrost temperature
increase in 2015 was substantial and comparable to
the highest rate of warming observed in this region
so far, which occurred during the period 1995–2000;
20-m depth temperatures in 2015 were from 0.10°C
to 0.17°C higher than those in 2014 (Fig. 5.22a)

on the North Slope. Since 2000, temperature at
20-m depth in this region has increased between
0.21°C and 0.66°C decade⁻¹ (Fig. 5.22a; Table 5.3).
Permafrost temperatures in Interior Alaska were
higher in 2015 than 2014 at all sites (Old Man,
College Peat, Birch Lake, Gulkana, and Healy
in Fig. 5.22b), except for Coldfoot. Notably, this
warming followed slight cooling of 2007–13 (Fig.
5.22b). However, the recent warming in the interior
(see section 5b; Fig. 5.2) was not strong enough to
bring permafrost temperatures back to the record
highs observed between the mid-1990s and the mid-
2000s except at Gulkana (Fig. 5.22b; Table 5.3).

In northwestern Canada, temperatures in warm
permafrost of the central Mackenzie Valley (Nor-
man Wells and Wrigley in Fig. 5.22b) were similar
in 2014/15 to those observed the previous year.

<figure><img src="image_213.png" /><figcaption>FIG. 5.21. Location of the permafrost monitoring sites shown in Fig. 5.22 superimposed on average air temperature anomalies during 2000–14 (with respect to the 1971–2000 mean) from the NCEP–NCAR re-analysis (Kalnay et al. 1996) (Source: NOAA/ESRL.) Sites shown in Fig. 5.22 are (a) Barrow (Ba), West Dock (WD), KC-07 (KC), Deadhorse (De), Franklin Bluffs (FB), Galbraith Lake (GL), Happy Valley (HV), Norris Ck (No); (b) College Peat (CP), Old Man (OM), Chandalar Shelf (CS), Birch Lake (BL), Coldfoot (Co), Norman Wells (NW), Wrigley 2 (Wr), Healy (He), Gulakana (Gu), Wrigley 1 (Wr); (c) Eureka EUK4 (Eu), Alert BH2 (Al), Alert BH5 (Al), Resolute (Re), Alert BHI (Al), Arctic Bay (AB), Pond Inlet (PI), Pangnirtung (Pa); (d) Janssonhaugen (Ja), Urengoy #15-10 (Ur), Juv-vashøe (Ju), Tarfarelyggen (Ta), Bolvansky #59 (Bo), Bolvansky #65 (Bo), Urengoy #15-06 (Ur), Bolvansky #56 (Bo), Iskoras Is-B-2 (Is).</figcaption></figure>
<figure><img src="image_214.png" /></figure>

FIG. 5.22. Time series of mean annual ground temperature at depths of 9–26 m below the surface at selected measurement sites that fall roughly into the Adaptation Actions for a Changing Arctic Project (AMAP 2015) priority regions: (a) cold continuous permafrost of NW North America (Beaufort–Chukchi region); (b) discontinuous permafrost in Alaska and northwestern Canada; (c) cold continuous permafrost of eastern and high Arctic Canada (Baffin Davis Strait); (d) continuous to discontinuous permafrost in Scandinavia, Svalbard, and Russia/Siberia (Barents region). Temperatures are measured at or near the depth of penetration of the seasonal ground temperature variations. Data series are updated from Christiansen et al. 2010; Romanovksy et al. 2015; Smith et al. 2015; Ednie and Smith 2015.

<table><caption>TABLE 5.3. Change in mean annual ground temperature (MAGT; °C decade⁻¹) for sites shown in Fig. 5.22, for which data are available for 2015 († indicates discontinuous permafrost regions). For sites with records initiated prior to 2000, the rate for the entire available record is provided along with the rate for the period after 2000. (Note records for some sites only began after 2007 as shown in Fig. 5.22).</caption><thead><tr><td>Region</td><td>Sites</td><td>Entire Record</td><td>Since 2000</td></tr></thead><tbody><tr><td>Central Mackenzie Valley †</td><td>Norman Wells (NW), Wrigley (Wr)</td><td>+0.1 to +0.2</td><td>&lt;+0.1 to +0.2</td></tr><tr><td>Northern Mackenzie Valley</td><td>Norris Ck (No), KC-07(KC)</td><td>NA</td><td>+0.4 to +0.7</td></tr><tr><td>Baffin Island</td><td>Pond Inlet (PI)</td><td>NA</td><td>+0.7</td></tr><tr><td>High Canadian Arctic</td><td>Resolute (Re), Eureka (Eu)</td><td>NA</td><td>+0.4 to +0.7</td></tr><tr><td>High Canadian Arctic</td><td>Alert (Al), BH5, BHI, BH2</td><td>+0.53, +0.3 to +0.4</td><td>+1.2, +0.7 to +0.9</td></tr><tr><td>Alaskan Arctic plain</td><td>West Dock (WD), Deadhorse (De), Franklin Bluffs (FB), Barrow (Ba)</td><td>+0.33 to +0.81</td><td>+0.36 to +0.66</td></tr><tr><td>Northern foothills of the Brooks Range, Alaska</td><td>Happy Valley (HV), Galbraith Lake (GL)</td><td>+0.25 to +0.37</td><td>+0.21 to +0.35</td></tr><tr><td>Southern foothills of the Brooks Range, Alaska †</td><td>Coldfoot (Co), Chandalar Shelf (CS), Old Man (OM)</td><td>+0.07 to +0.31</td><td>+0.13 to +0.18</td></tr><tr><td>Interior Alaska †</td><td>College Peat (CP), Birch Lake (BL), Gulkana (Gu), Healy (He)</td><td>+0.03 to +0.15</td><td>-0.05 to +0.02</td></tr><tr><td>North of West Siberia</td><td>Urengoy 15-06 and 15-10 (Ur)</td><td>+0.31 to +0.47</td><td>+0.1 to +0.19</td></tr><tr><td>Russian European North</td><td>Bolvansky 56, 59, and 65 (Bo)</td><td>+0.18 to +0.46</td><td>+0.1 to +0.83</td></tr><tr><td>Svalbard</td><td>Janssonhaugen (Ja)</td><td>+0.7</td><td>+0.7</td></tr><tr><td>Northern Scandinavia †</td><td>Tarfalarggen (Ta), Iskoras Is-B-2 (Is)</td><td>NA</td><td>+0.1 to +0.4</td></tr><tr><td>Southern Norway †</td><td>Juvvasshøe (Ju)</td><td>+0.2</td><td>+0.2</td></tr></tbody></table>
Permafrost in this region has gener-
ally warmed since the mid-1980s,
with less warming observed since
2000 (Table 5.3), corresponding to a
period of steady air temperatures. In
contrast, greater recent warming has
been observed in the colder permafrost
of the northern Mackenzie (Norris
Ck, KC-07 in Fig. 5.22a and Table
5.3) with 2014/15 temperatures higher
than those recorded over the previous
5-7 years, reflecting an increase in
air temperatures over the last decade
(Fig. 5.21).

Mean temperatures for 2014/15
in the upper 25 m of the ground at
Alert, northernmost Ellesmere Island
in the high Canadian Arctic, were
among the highest recorded since 1978
(Fig. 5.22c). Since 2010, temperatures
have changed little or even declined,
consistent with lower air temperatures
since 2010 (Smith et al. 2015). However,

higher permafrost temperature at 15-m depth in 2014/15 compared to 2013/14 appears to reflect an increase in air temperature since 2013. Since 2000, Alert permafrost temperatures have increased at a higher rate (Table 5.3) than that for the entire record (Smith et al. 2015), consistent with air temperature anomaly patterns (Fig. 5.21). Short records, from other high Arctic sites in the Queen Elizabeth Islands (Resolute and Eureka) and on Baffin Island (Pond Inlet) in the eastern Arctic, indicate some cooling of permafrost since 2012/13 at 10–15-m depth (Fig. 5.22c). However, a general warming trend is observed (Table 5.3) with higher temperatures in 2014/15 than in 2008/09 when measurements began.

Similar to northern Alaska and the Canadian
high Arctic, permafrost temperature has increased
by 1–2°C in northern Russia during the last 30 to
35 years. In the Russian European North and in the
western Siberian Arctic, for example, temperatures
at 10-m depth have increased by ~0.4°C to 0.6°C de-
cade⁻¹ since the late 1980s at colder permafrost sites
(in Fig. 5.22d, Bolvansky #59, Urengoy #15-5, and
#15-10). Less warming has been observed at warm
permafrost sites (Table 5.3; in Fig. 5.22d, sites Bolvan-
sky #56 and Urengoy #15-6; Drozdov et al. 2015).

In the Nordic countries (including Svalbard),
regional warming and thawing of permafrost have
been observed recently (Christiansen et al. 2010;
Isaksen et al. 2011; Farbrot et al. 2013). Since 2000,
temperature at 20-m depth has increased between

0.1°C and 0.7°C decade⁻¹ (Fig. 5.22d; Table 5.3) with lower rates of increase occurring at sites in the discontinuous permafrost zone that are affected by latent heat exchange at temperatures close to 0°C. Higher temperature increases occurred at colder permafrost sites on Svalbard and in northern Scandinavia. In southern Norway permafrost was warmer in 2015 compared to 2014, a warming that followed a period of cooling between 2011 and 2014.

Active layer thickness [determined by probing ac-
cording to Brown et al. (2000) and Shiklomanov et al.
(2012)] at North Slope and Alaska Interior locations
was on average greater in 2015 than in 2014 (Fig. 5.23).
An increase in the thickness of the ALT indicates
warming surface temperature. Of 26 North Slope sites
observed in 2015, only nine had ALT values within
1 cm of those observed in 2014, while the majority of
sites had greater ALT values than in 2014. The aver-
age ALT in 2015 for the 20 North Slope sites with
records of at least 10 years was 0.51 m, which is 3 cm
higher than the 1995–2013 average. In the interior
of Alaska, three of the four active sites reported an
ALT increase in 2015. The most pronounced change
occurred at a site where surface cover was burned in
2010. Here ALT was 1.78 m in 2015, which is 0.10 m
greater than the 2014 value and 1.23 m greater than
the prefire 1990–2010 average.

Records from 25 sites with thaw tubes in the Mack-
enzie Valley, northwestern Canada, indicate that ALT
in 2014 (the most recent year data are available) was

<figure><img src="image_215.png" /><figcaption>Fig. 5.23. Long-term active-layer change from selected sites in six different Arctic regions as observed by the Circumpolar Active Layer Monitoring project (Shiklomanov et al. 2012). The data are presented as annual percentage deviations from the mean value for the period of observations. Thaw depth observations from the end of the thawing season were used. Only sites with at least 10 years of continuous thaw depth observations are shown in the figure. Solid red lines show mean values. Dashed black lines represent maximum and minimum values. In the Nordic countries (not shown here) active layer records (1996–2015) indicate a general increase in ALT since 1999. Maximum ALT was observed in 2011 followed by a period of thinner active layers.</figcaption></figure>
on average about 4% greater than the 2003–12 mean (Fig. 5.23). Although ALT in this region has generally increased since 2008 (Duchesne et al. 2015), there has been a decrease since 2012.

In Russia, active layer observations were con-
ducted at 44 sites in 2015. Since 2009, a progressive
increase in ALT is evident for western Siberian loca-
tions (Fig. 5.23), with a substantial increase in 2015
of 0.05–0.20 m. Locations in the Russian European
North have been characterized by almost monotonic
thickening of the active layer over the 1999–2012 peri-
od. However, after reaching its maximum in 2012, the
ALT decreased for three consecutive years (Fig. 5.23).
In central Siberia (Low Yenisey region) ALT increased
by 0.07–0.10 m, while ALT in the East Siberian region
(Yakutsk) was largely unchanged from 2014 values. In
northeastern Siberia, ALT in 2015 was 4% lower than
the 2014 peak values. Similarly, in Chukotka (Russian
Far East) 2015 ALT values were on average 2% lower
than in 2014 (Fig. 5.23).

However, ALT was still greater in 2012–15 than
the long-term average value. The summer of 2014 was
particularly warm in the Nordic countries and con-
tributed to the thickest active layer measured to date
at some places. On Svalbard (Janssonhaugen) ALT
increased by 10% in 2015 compared to the 2000–14
mean and was the highest in the entire 1998–2015
observational record.

j. *Ozone and UV radiation*—G. Bernhard, I. Ialongo, J.-U. Grooß, J. Hakkarainen, B. Johnsen, G.L. Manney, V. Fioletov, A. Heikkilä, K. Lakkala

The minimum Arctic daily total ozone column (TOC) measured by satellites (Levelt et al. 2006) in March 2015 was 389 Dobson Units (DU). Measurements from March are used for assessing the temporal evolution of Arctic ozone because chemically induced loss of ozone typically peaks in the month of March (WMO 2014). The March 2015 value was 17 DU (5%) above the average of 372 DU for the period of available measurements (1979–2014) and 23 DU (6%) above the average for the past decade, 2005–14 (Fig. 5.24). The record low was 308 DU in 2011. Figure 5.24 also indicates that the Arctic ozone interannual variability is large: the standard deviation for the period 1979–2014 is 35 DU. This large variability is caused by dynamical effects that affect vortex size and longevity, transport of ozone into the lower stratosphere, and stratospheric chemistry via its sensitivity to temperature (e.g., Tegtmeier et al. 2008; WMO 2014).

Between December 2014 and April 2015, ozone
concentrations measured at an altitude of 20 km
by the Microwave Limb Sounder (MLS) aboard the

<figure><img src="image_216.png" /><figcaption>FIG. 5.24. Time series of area-averaged minimum total ozone (DU) for Mar in the Arctic, calculated as the minimum of daily average column ozone poleward of 63° equivalent latitude (Butchart and Remsberg 1986). Open circles represent years in which the polar vortex broke up before Mar. Ozone in those years was relatively high due to mixing with air from lower latitudes and higher altitudes and a lack of significant chemical ozone depletion. Red and green lines indicate the average TOC for 1979–2014 and 2005–14, respectively. [Sources: Data are adapted from Müller et al. (2008) and WMO (2014), updated using ERA-Interim reanalysis data (Dee et al. 2011). Ozone data from 1979 to 2012 are based on the combined total column ozone database version 2.8 produced by Bodeker Scientific (www.bodekerscientific.com/data/total-column-ozone). Data for 2013–15 are from OMI.]</figcaption></figure>

Aura satellite were the highest in the MLS record, which started in August 2004 (Manney et al. 2015). The altitude of 20 km is representative of the lower stratosphere (altitude range of 15 km to 25 km) where chemical destruction of ozone is typically observed in spring when temperatures drop below –78°C (equal to about –108°F or 195 K). Chemically induced loss of ozone was minimal in the spring of 2015 because of a minor sudden stratospheric warming (SSW) event in early January. This event caused lower stratospheric temperatures to rise above the critical temperature for the formation of polar stratospheric clouds, which is a prerequisite for heterogeneous chemical reactions that destroy ozone. A second reason for the abnormally high ozone concentrations observed in 2015 was larger-than-usual transport of ozone-rich air into the lower stratosphere from higher altitudes, as observed by MLS (Manney et al. 2015). As a consequence, TOCs in the spring of 2015 were relatively high (Figs. 5.24, 5.25b).

Spatial deviations of monthly average TOCs from
historical (2005–14) means were estimated with
measurements by the Ozone Monitoring Instrument
(OMI), which is collocated from MLS on the Aura
satellite (Figs. 5.25a, 5.25b). Monthly average TOCs
for March 2015 exceeded historical means by more
than 10% over Iceland, southern Greenland, the Davis
Strait between Greenland and Canada, and eastern
Canada (Fig. 5.25a). In contrast, TOCs over most of
Siberia were 2.5%–7.5% below the 2005–14 average
<figure><img src="image_217.png" /></figure>

**FIG. 5.25.** Anomalies of total ozone column and the noontime UV index in 2015 relative to 2005–14 means. TOC anomaly for (a) Mar and (b) Apr. UVI anomaly for (c) Mar and (d) Apr (first value in parenthesis). Data are based on measurements from the OMI. Monthly means calculated from OMTO3 Level 3 total ozone products (Bhartia and Wellemeyer 2002) that are provided in 1° × 1° spatial gridding. (c) and (d) also indicate UVI anomalies measured by ground-based instruments at 12 locations (second value presented). Gray shading indicates areas where no OMI data are available.

with somewhat larger negative departures east of Moscow. Monthly average TOCs for April 2015 were above 2005–2014 means over almost the entire Arctic (Fig. 5.25b). Positive TOC anomalies between 10% and 20% were observed at the North Pole, northern Greenland, and the Canadian Arctic Archipelago.

UV radiation is quantified with the UV index (UVI), a measure of the ability of UV radiation to cause erythema (sunburn) in human skin (WHO 2002). In addition to its inverse dependence on TOC, the UVI depends greatly on the sun angle, cloud cover, and surface albedo (Weatherhead et al. 2005). In the Arctic, the UVI ranges from 0 to about 7, with

sites closest to the North Pole having the smallest peak radiation and UVI values <4 all year. UVI values <5 indicate low to moderate risk of erythema (WHO 2002).

Maps shown in Figs. 5.25c,d quantify differences of monthly average noontime UVIs from historical (2005–14) means for March and April and are based on observations derived from OMI. The OMI UV algorithm uses a surface albedo climatology (Tanskanen et al. 2003) that does not change from year to year. At places where the actual surface albedo deviates greatly from the OMI albedo climatology (e.g., when snowmelt occurred earlier than usual), OMI UVI data may be biased by more than 50%, although differences in absolute values rarely exceed 2 UVI units (Bernhard et al. 2015). Figures 5.25c,d therefore also compare UVI anomalies measured by OMI and ground-based instruments deployed throughout the Arctic and Scandinavia. Anomalies derived from the two datasets agree to within ±12% at all locations, with the exception of Andøya for April (OMI overestimates the actual anomaly by 16%) and Jokioinen for March (overestimate by 27% or 0.3 UVI units). The large discrepancy for Jokioinen can be explained by early snowmelt on 9 March while the OMI climatology assumes snow cover through the month of March. Persistent cloud cover in the second half of March also contributed to this discrepancy.

Monthly average noontime UVIs for March 2015 were below the 2005–14 means in a belt stretching from the Greenland Sea and Iceland in the east to Hudson Bay and the Canadian Arctic Archipelago in the west (Fig. 5.25c). This region roughly agrees with the region where TOCs were abnormally high in March 2015 (Fig. 5.25a), but UVI anomalies show a larger spatial variability than TOCs because of their added dependence on cloud cover. Monthly average noontime UVIs for April 2015 were 5%–15% below the 2005–14 means over almost the entire Arctic (Fig. 5.25d), consistent with the positive ozone anomalies observed in this month (Fig. 5.25b).
## 6. ANTARCTICA—S. Stammerjohn, Ed.

### a. Overview—S. Stammerjohn

In strong contrast to 2014, 2015 was marked by low regional variability in both atmospheric and oceanic anomalies, at least for the first half of the year. The Antarctic-wide distribution of anomalies coincided with a strong positive southern annular mode (SAM) index. However, by October; the high-latitude response to El Niño became evident, but the associated anomalies were rather atypical compared to the mean response from six previous El Niño events. Simultaneously, a somewhat tardy but unusually large and persistent Antarctic ozone hole developed. These springtime conditions imparted strong regional contrasts late in the year, particularly in the West Antarctic sector. Other noteworthy Antarctic climate events from 2015 are below:

* For most of the year surface pressure was lower and temperatures were cooler than the 1981–2010 climatology, along with stronger-than-normal circumpolar westerly winds, slightly higher-than-normal precipitation over the ocean areas, and mostly shorter-than-normal melt seasons on the continent. These anomalies were consistent with the positive SAM index registered in all months except October. February had a record high SAM index value of +4.92 (13% higher than the previous high value recorded over 1981–2010).

* There was an abrupt but short-lived switch in the mean surface temperature anomaly for the continent (from cold to warm) and a weakening of the negative surface pressure anomaly in October 2015. These atmospheric circulation changes coincided with the emerging high-latitude response to El Niño, the ozone hole, and a shift in the SAM index from positive to negative.

* The 2015 Antarctic ozone hole was amongst the largest in areal coverage and most persistent, based on the record of ground and satellite observations starting in the 1970s. This very large ozone hole was caused by unusually weak stratospheric wave dynamics, resulting in a colder- and stronger-than-normal stratospheric polar vortex. The persistently below-normal temperatures enabled larger ozone depletion by human-produced chlorine and bromine compounds, which are still at fairly high levels despite their continuing decline resulting from the Montreal Protocol and its Amendments.

* Although the 2015 El Niño produced strong atmospheric circulation anomalies in the South Pacific, thus affecting temperatures and sea ice

in the West Antarctic sector, its impact across the rest of Antarctica was weaker due to an atypical teleconnection pattern.

* There was a continuation of near-record high Antarctic sea ice extent and area for the first half of 2015, with 65 sea ice extent and 46 sea ice area daily records attained by July. However, at mid-year, there was a reversal of the sea ice anomalies, shifting from record high levels in May to record low levels in August. This was then followed by a period of near-average circumpolar sea ice (relative to the 36-year satellite record).

* Together with unusually high sea ice extent, particularly in the West Antarctic sector, SSTs were also cooler than average, in contrast to warmer-than-normal SSTs equatorward of the polar front. South of the polar front, sea surface height anomalies were negative, consistent with the mostly positive SAM index. Compared to 2014, there was a small decrease in sea level detected around the continental margin as well, leading to a slight increase in the estimated volume transport of the Antarctic Circumpolar Current. These changes are, however, superimposed on longer-term increases in sea level and a potential small decrease in volume transport. The 2015 deep ocean observations at 140°E indicate a continued freshening of Antarctic Bottom Water, relative to observations in the late 1960s and more frequent observations since the 1980s.

Details on the state of Antarctica's climate in 2015 and other climate-related aspects of the Antarctic region are provided below, starting with the atmospheric circulation, surface observations on the continent (including precipitation and seasonal

<figure><img src="image_218.png" /><figcaption>FIG. 6.1. Map of stations and other regions used throughout the chapter.</figcaption></figure>
melt), ocean observations (including sea ice and ocean circulation), and finally the Antarctic ozone hole. Newly included this year is the southern high latitude response to El Niño (Sidebar 6.1) and the state of Antarctic ecosystems in the face of climate perturbations (Sidebar 6.2). Place names used in this chapter are provided in Fig. 6.1.

b. Atmospheric circulation—K. R. Clem, S. Barreira, and R. L. Fogt

The 2015 atmospheric anomalies across Antarctica were dominated by below-average surface temperatures over much of coastal and interior Antarctica from January to September, particularly across the Antarctic Peninsula and the surrounding Weddell and Bellingshausen Seas. Negative pressure anomalies in the Antarctic troposphere during the first half of the year weakened in August, while the stratosphere poleward of 60°S became very active beginning in June with strong negative pressure and temperature anomalies and an amplification of the stratospheric vortex. Using a station-based SAM index (normalized difference in zonal mean sea level pressure between 40°S and 65°S; Marshall 2003), the generally low pressure conditions gave rise to positive SAM index values, which were observed in every month except October during 2015. Figure 6.2 depicts a vertical cross section of the geopotential height anomalies (Fig. 6.2a) and temperature anomalies (Fig. 6.2b) averaged over the polar cap (60°–90°S), as well as the circumpolar zonal wind anomalies (Fig. 6.2c) averaged over 50°–70°S and the Marshall (2003) SAM index average for each month.

Climatologically, the year was split into four time periods (denoted by vertical red lines in Fig. 6.2) that were selected based on periods of similar temperature and pressure anomalies (Fig. 6.3). The composite anomalies (contours) and standard deviations (from the 1981–2010 climatological average; shading) for each of the time periods are shown in Fig. 6.3; surface pressure anomalies are displayed in the left column and 2-m temperature anomalies in the right column.

During January–March, the large-scale circulation was marked with negative geopotential height (Fig. 6.2a) and surface pressure (Fig. 6.3a) anomalies over Antarctica and positive surface pressure anomalies over much of the middle latitudes. The Marshall SAM index was strongly positive, and reached a record monthly mean high value during February [+4.92; Fig. 6.2; Marshall (2003); SAM index values start in 1957]. At this time, the circumpolar zonal winds exceeded 2 m s⁻¹ (>1.5 standard deviations) above the climatological average throughout the

<figure><img src="image_219.png" /><figcaption>FIG. 6.2. Area-weighted averaged climate parameter anomalies for the southern polar region in 2015 relative to 1981–2010: (a) polar cap (60°–90°S) averaged geopotential height anomalies (contour interval is 50 m up to ±200 m with additional contour at ±25 m, and 100 m contour interval after ±200 m); (b) polar cap averaged temperature anomalies (contour interval is 1°C up to ±4°C with additional contour at ±0.5°C, and 2°C contour interval after ±4°C); (c) circumpolar (50°–70°S) averaged zonal wind anomalies (contour interval is 2 m s⁻¹ with additional contour at ±1 m s⁻¹). Shading represents standard deviation of anomalies from the 1981–2010 climatological average. (Source: ERA-Interim reanalysis.) Red vertical bars indicate the four separate climate periods used for compositing in Fig. 6.2; the dashed lines near Dec 2014 and Dec 2015 indicate circulation anomalies wrapping around the calendar year. Values from the Marshall (2003) SAM index are shown below panel (c) in black (positive values) and red (negative values).</figcaption></figure>

troposphere and lower stratosphere (Fig. 6.2c). Much of the coastal Antarctic 2-m temperatures were below average (Fig. 6.3b), with the exception of areas of the Ross Ice Shelf and Wilkes Land (~90°E–180°). Positive temperature anomalies were observed throughout much of the stratosphere over the polar cap (Fig. 6.2b).

Positive SAM index values continued during April but weakened in May. This was due to a strong positive surface pressure anomaly southwest of Australia, while the remainder of the middle latitudes experi-
<figure><img src="image_220.png" /></figure>

FIG. 6.3. (left) Surface pressure anomalies and (right) 2-m temperature anomalies relative to 1981–2010 for (a) and (b) Jan–Mar 2015; (c) and (d) Apr–May 2015; (e) and (f) Jun–Sep 2015; and (g) and (h) Oct–Dec 2015. Contour interval for (a), (c), (e), and (g) is 2 hPa; contour interval for (b) and (h) is 1°C and contour interval for (d) and (f) contour interval is 2°C. Shading represents standard deviations of anomalies relative to the selected season from the 1981–2010 average. (Source: ERA-Interim reanalysis.)

enced negative surface pressure anomalies with a weakening of the circumpolar zonal winds in May (Fig. 6.2c). Much of East Antarctica was colder than average, particularly offshore along coastal Queen Maud Land (30°W–0°) and portions of the Ross Sea westward towards Mirny station (~90°E), while the Amundsen Sea and the Ronne-Filchner Ice Shelf were slightly warmer than average (Fig. 6.3d).

During June–September, negative polar-cap averaged geopotential height anomalies and positive circumpolar zonal wind anomalies were observed

throughout the troposphere and stratosphere. Strong positive surface pressure anomalies occurred over the South Pacific, southwest of Australia, and over the South Atlantic, while strong negative surface pressure anomalies occurred over the Weddell Sea (Fig. 6.3e); these conditions led to positive SAM index values through September. Antarctic 2-m temperatures were primarily below average (Fig. 6.3f), with anomalies over the Antarctic Peninsula, Bellingshausen Sea, and eastern Amundsen Sea more than 2.5 standard deviations below the climatological average.

By October–December, positive surface pressure and 2-m temperature anomalies developed over interior East Antarctica, with the strongest warming noted over Queen Maud Land, while the Drake Passage and coastal Wilkes Land remained colder than average (Figs. 6.3g,h). A strong negative surface pressure anomaly was observed south of New Zealand and a strong positive surface pressure anomaly was observed in the southeastern South Pacific, likely tied to the strengthening of the El Niño conditions in the tropical Pacific. These circulation anomalies over the South Pacific brought cold, southerly flow to the coastal and offshore regions of Wilkes Land and the offshore region of the northwestern Antarctic Peninsula, respectively. Meanwhile, the stratosphere over the polar cap became very active after September. Negative temperature and geopotential height anomalies of 1–2 standard deviations below the climatological average propagated down through the stratosphere from October to December. A marked strengthening of the stratospheric circumpolar vortex occurred in response to the stratospheric cooling, with positive zonal wind anomalies exceeding 1–2 standard deviations above the climatological average throughout the stratosphere to finish the year. Over this time period (October–December) the SAM index values also weakened, and a negative value was observed in October 2015, coincident with the weaker and more regional nature of the near-surface conditions (Fig. 6.3).

c. Surface manned and automatic weather station observations—S. Colwell, L. M. Keller, M. A. Lazzara, A. Setzer, R. L. Fogt, and T. Scambos

The circulation anomalies described in section 6b are discussed here in terms of observations at staffed and automatic weather stations (AWS). Climate data that depict regional conditions are displayed for four staffed stations (Bellingshausen on the Antarctic Peninsula, Halley in the Weddell Sea, Mawson in the Indian Ocean sector, and Amundsen-Scott at the South Pole; Figs. 6.4a–d) and two AWSs (Byrd in West
<figure><img src="image_221.png" /><figcaption>**FIG. 6.4.** 2015 Antarctic climate anomalies at six representative stations [four staffed (a)–(d) and two automatic (e)–(f)]. Monthly mean anomalies for temperature (°C) and surface pressure (hPa) are shown, with + denoting record anomalies for a given month at each station in 2015. All anomalies are based on differences from 1981–2010 averages, except for Gill, which is based on averages during 1985–2013. Observational data start in 1968 for Bellingshausen, 1957 for Halley and Amundsen-Scott, 1954 for Mawson, 1985 for Gill AWS, and 1981 for Byrd AWS.</figcaption></figure>

Antarctica and Gill on the Ross Ice Shelf; Figs. 6.4e,f). To better understand the statistical significance of records and anomalies discussed in this section, references can be made to the spatial anomaly maps in Fig. 6.3 (the shading indicates the number of standard deviations the anomalies are from the mean).

Monthly mean temperatures at Bellingshausen station (Fig 6.4a) on the western side of the Antarctic Peninsula were similar to the 1981–2010 mean at the start and end of the year, but from May to September, the values were consistently lower than the mean. Midway down on the west side of the Antarctic Peninsula, the temperatures at Rothera (not shown) followed a similar pattern. In the Weddell Sea region, the monthly mean temperatures at Halley (Fig. 6.4b) and Neumayer (not shown) were within ±2°C of the

1981–2010 mean, with the exception of June and July at Halley. In June, the mean monthly value nearly matched the lowest recorded mean monthly value and included a new record for the extreme daily minimum value, which was –56.2°C. The anomalously cold conditions in June were followed by a respite to anomalously warm conditions in July that were then followed by below- to near-average temperatures for the rest of the year.

Around the coast of East Antarctica, all of the Australian stations had near-average temperatures at the start and end of the year and colder-than-average temperatures from April to August, except for Casey (not shown) in June when the temperature was slightly higher than average. Davis (not shown) and Mawson (Fig. 6.4c) both had very low monthly mean temperatures in

May (a record low at Mawson). Temperatures at Mawson were also anomalously low again in July. At Amundsen-Scott station (Fig. 6.4d), the monthly mean temperatures were close to the long-term means with the exception of October and November when they were warmer than average.

In the Antarctic Peninsula, an all-time record warm air temperature for the continent may have been set at Esperança on 24 March, reaching +17.5°C during an intense foehn wind event that spanned much of the northeastern Peninsula. Temperatures rose as much as 30°C within 48 hours as an intense high pressure region over the Drake Passage and strong low pressure over the northwestern Weddell Sea drove strong downslope winds all along eastern Graham Land. An automated sensor at Foyn Point in
the Larsen B embayment recorded still higher values briefly, at +18.7°C on the 24th, and several other weather stations in the region surpassed +17°C on 23 and 24 March.

Temperatures at the AWS locations provide a broader view of weather records and trends for the continent. For the Ross sector, Possession Island (not shown) reported a record low temperature of -21.9°C (greater than 2 standard deviations from the 1981-2010 mean) in September and then tied its record high mean temperature of 1.7°C in December. Otherwise, temperatures at Possession Island were above normal for February, August, October, November, and December and below normal for the rest of the months (no report for July). The Ross Ice Shelf region (e.g., Gill AWS, Fig. 6.4f) had generally above-normal temperatures from January through March and again in August, but these warm periods were interspersed by colder-than-normal temperatures, especially in April, July, and September. In West Antarctica, Byrd AWS (Fig. 6.4e) was colder than normal for March-April, June-August, and November-December and was warmer than normal otherwise. At Relay Station (not shown) on the Polar Plateau, temperatures were above normal through May, below normal for June-September, and then 5°C above normal in October. On the other side of the Polar Plateau, Dome C II (not shown) did not operate from May through part of September, but October and November had above-normal temperatures.

While stations over Antarctica generally did not report record temperature anomalies, many staffed and unstaffed stations reported record low pressure anomalies in at least one month. The pressure data from all staffed stations showed lower-than-average pressures for all months except October (Figs. 6.4a-d) and January at the Bellingshausen station (Fig. 6.4a). On the Ross Ice Shelf, almost every month had below-normal pressure with a record low anomaly reported for February for Possession Island (-6.7 hPa), Marble Point (-9.2 hPa, greater than 2 standard deviations below normal), Ferrell (-9.9 hPa, about 2 standard deviations below normal), and Gill AWS (-10.5 hPa, greater than 2 standard deviations below normal; the latter shown in Fig. 6.4f). The record low pressure anomalies ranged from -6.7 to -10.5 hPa. Possession Island was only above normal for May, and Marble Point had slightly above-normal pressure for October. Relay Station also had a record low pressure anomaly in February (-5.1 hPa), and pressures were below normal through the whole year until October. The record low pressure anomalies observed in February on both the Ross Ice Shelf and at Relay Station also coincided

with the record high SAM index value (Fig. 6.2c). Byrd AWS (Fig. 6.4e) in West Antarctica reported record low pressures in March and November (803.7 and 799.8 hPa, respectively), with only four other months reporting pressure anomalies less than 6 hPa below normal. There were also a few reported wind speed records (not shown), but most stations generally reported only slightly above or below normal wind speeds over the course of the year. Marble Point had a record low monthly mean wind speed of 2.4 m s⁻¹ in March, and Gill reported a record low wind speed of 1.5 m s⁻¹ in April (both more than 2 standard deviations below normal). Relay Station had a record high monthly mean wind speed of 9.1 m s⁻¹ in April (greater than 2 standard deviations above normal).

d. Net precipitation (P-E)—D. H. Bromwich and S.-H. Wang

Precipitation minus evaporation/sublimation (P-E) closely approximates the surface mass balance over Antarctica, except for the steep coastal slopes (e.g., Bromwich et al. 2011; Lenaerts and van den Broeke 2012). Precipitation variability is the dominant term for P-E changes at regional and larger scales over the Antarctic continent. There are few precipitation gauge measurements for Antarctica, and those are compromised by blowing snow. In addition, over the interior Antarctic plateau, snowfall amounts are often less than the minimum gauge resolution. As a result, precipitation and evaporation fields from the Japanese 55-year Reanalysis (JRA-55; Kobayashi et al. 2015) were examined to assess Antarctic net precipitation (P-E) behavior for 2015. JRA-55, the second generation of JRA, is produced with a low-resolution version of the Japan Meteorological Agency's (JMA) operational data assimilation system as of December 2009, which incorporated many improvements achieved since JRA-25 (Onogi et al. 2007), including a revised longwave radiation scheme, four-dimensional data assimilation, bias correction for satellite radiances, and assimilation of newly available homogenized observations. These improvements have resulted in better fits to observations, reduced analysis increments and improved forecast results (Kobayashi et al. 2015). The model is run at a spatial resolution of TL319 (~0.5625° or 55 km) and at 60 vertical levels from the surface up to 0.1 hPa. In comparison to other long-term global reanalyses (e.g., NCEP1 and NCEP2), JRA has higher horizontal and vertical model resolution, uses a greater number of observations, and has a more advanced model configuration (e.g., Bromwich et al. 2007; Kang and Ahn 2015).

Figure 6.5 shows the JRA-55 2015 and 2014 annual anomalies of P-E and mean sea level pressure
(MSLP) departures from the 1981–2010 average. In general, annual *P*–*E* anomalies (Figs. 6.5a,b) over the high interior of the continent are small (within ±50 mm yr⁻¹), but larger anomalies can be observed along the coast, consistent with the low and high snow accumulation in these regions. At higher latitudes (≥ 60°S) JRA-55 is quantitatively similar to JRA-25 and ERA-I (European Centre for Medium-Range Weather Forecasts Interim reanalysis) *P*–*E* results (Bromwich and Wang 2014, 2015). The excessively high positive anomalies of JRA-25 over the Southern Ocean north of 60°S (that were noted in last year’s report) are not present in JRA-55. JRA-55 also shows better overall agreement with ERA-I than JRA-25 during 2013 and 2014.

Based on JRA-55, the 2014 negative anomalies located at eastern Queen Maud Land (between 15° and 80°E) are weaker in 2015, and positive anomalies are observed over Enderby Land and the Amery Ice Shelf. The strong negative features between American Highland and Wilkes Land (between 80° and 150°E) observed in 2014 were replaced by weak positive anomalies in 2015, except near the Budd Coast region (near 115°E) where negative anomalies were observed again. The George V Coast and Ross Sea had positive anomalies in 2015, in contrast to 2014 conditions. The small positive anomalies over the western Ross Sea seen in 2014 were replaced by negative anomalies in 2015. Strong positive anomalies over the Amundsen and Bellingshausen Seas (between 150° and 75°W) in 2014 were weaker but remained positive in 2015. Small negative anomaly centers were present along

the West Antarctic coastline in 2015. Both sides of the Antarctic Peninsula have similar anomaly patterns to 2014, but were weaker. The negative *P*–*E* anomaly center over the Weddell Sea in 2014 was replaced by a positive one in 2015.

These annual *P*–*E* anomaly features were generally consistent with the mean atmospheric circulation implied by the MSLP anomalies (Figs. 6.5c,d). In 2015 the MSLP anomalies surrounding Antarctica were less localized than in 2014 (Figs. 6.5c,d). The MSLP

<figure><img src="image_222.png" /><figcaption>FIG. 6.5. JRA-55 (a–d) annual *P*–*E* and MSLP anomalies: (a) 2015 *P*–*E* anomalies (mm month⁻¹); (b) 2014 *P*–*E* anomalies (mm month⁻¹); (c) 2015 MSLP anomalies (hPa); and (d) 2014 MSLP anomalies (hPa). All anomalies are departures from the 1981–2010 mean. (e) Monthly total *P*–*E* (mm; dashed green) for the West Antarctic sector bounded by 75°–90°S, 120°W–180°, along with the SOI (dashed dark blue, from NOAA Climate Prediction Center) and SAM [dashed light blue, from Marshall (2003)] indices since 2010. In (a) and (b), Antarctic regions with greater than ±30% change are hatched; sloping denotes negative values and horizontal denotes positive. Centered annual running means are plotted as solid lines.</figcaption></figure>
pattern in 2015 consisted of large negative pressure anomalies over Antarctica (or high latitudes) and a ring of positive pressure anomalies at midlatitudes, which resulted in positive SAM index values recorded for most of 2015 (Figs. 6.2c, 6.5e). This MSLP pattern tended to induce higher precipitation from the Southern Ocean into Antarctica. The positive MSLP anomaly over the Ronne Ice Shelf and the Weddell Sea in 2014 was replaced by a strong negative anomaly center at the tip of the Antarctic Peninsula in 2015. Enhanced cyclonic flows induced more inflow from the ocean and resulted in higher precipitation anomalies into the Weddell Sea and Queen Maud Land. A strong negative anomaly center at the southern Indian Ocean (near 105°E) in 2014 was replaced by large positive anomalies, with weak negative anomalies along the coast of East Antarctica. Combined with cyclonic flow produced by negative anomalies over Weddell Sea, it produced higher precipitation along Queen Mary Coast (between 60° and 125°E) in 2015. The large positive anomaly center in 2014 over the South Pacific Ocean (near 120°W) was enhanced in 2015. In combination with the expanded and strengthened negative anomalies over the western Ross Sea region, above-normal precipitation was observed in the Ross Sea and Amundsen Sea regions (Fig. 6.5a).

Earlier studies show that almost half of the moisture transport into Antarctica occurs in the West Antarctic sector. Here, there is also large interannual variability in moisture transport in response to atmospheric circulation patterns associated with extreme ENSO events (e.g., Bromwich et al. 2004) and high SAM index values (e.g., Fogt et al. 2011). As the seasons progressed from 2014 to 2015, the negative MSLP anomalies over the Ross Sea weakened (Figs. 6.3a,c, 6.5d), while a positive MSLP anomaly deepened offshore of 60°S (Figs. 6.5c,d). A positive anomaly then appeared in the Bellingshausen Sea and strengthened in later months of 2015 (Figs. 6.3e,g). These anomaly features are consistent with a simultaneously strong El Niño event and a positive SAM index. Figure 6.5e shows the time series of average monthly total P-E over Marie Byrd Land-Ross Ice Shelf (75°-90°S, 120°W-180°) and the monthly Southern Oscillation index (SOI) and SAM indices (with 12-month running means). It is clear that the SOI and SAM index were

positively associated with each other, but negatively associated with P-E, in most months from 2010 to mid-2011. From then on, the SOI and SAM index were negatively associated through 2015. From 2014 into 2015, the SOI became more negative (indicating El Niño conditions in the tropical Pacific), while the SAM index became more positive. The atmospheric circulation pattern associated with a positive SAM index modulated the high latitude response to El Niño, and the associated MSLP anomalies were located farther north than normal (Sidebar 6.1). The end result was near-normal precipitation over Marie Byrd Land-Ross Ice Shelf (Fig. 6.5e), in contrast to higher-than-normal precipitation during previous El Niño events (e.g., Bromwich et al. 2004).

e. Seasonal melt extent and duration—L. Wang and H. Liu

Seasonal surface melt on the Antarctic continent during 2014/15 was estimated from daily measurements of passive microwave brightness temperature using data acquired by the Special Sensor Microwave-Imager Sounder (SSMIS) onboard the Defense Meteorological Satellite Program (DMSP) F17 satellite. The data were preprocessed and provided by the U.S. National Snow and Ice Data Center (NSIDC) in level-3 EASE-Grid format (Armstrong et al. 1994) and were analyzed using a wavelet transform-based edge

<figure><img src="image_223.png" /><figcaption>**FIG. 6.6.** Estimated surface melt for the 2014/15 austral summer (a) melt start day, (b) melt end day, (c) melt duration (days), and (d) melt duration anomalies (days) relative to 1981–2010. (Data source: DMSP SSMIS daily brightness temperature observations.)</figcaption></figure>
During 2015, a strong El Niño developed and intensified in the tropical Pacific. Like much of the globe, Antarctica is influenced during ENSO events by a series of atmospheric Rossby waves emanating from the tropical Pacific, extending to high latitudes over the South Pacific Ocean near West Antarctica (Turner 2004). This pattern has been widely referred to as the Pacific South American pattern, and during an El Niño event, positive pressure anomalies are typical off the coast of West Antarctica (Mo and Ghil 1987; Karoly 1989).

Despite the 2015/16 El Niño's emergence as a strong event in the Pacific by midyear, its impact near Antarctica was not at all typical. However, true to form, in September–December (SOND) 2015, the high-latitude South Pacific was marked by a strong positive pressure anomaly and associated counterclockwise near-surface flow (Figs. SB6.1a, 6.3g). The southerly flow in the vicinity of the Antarctic Peninsula partially explains the persistence of below-average temperatures across the Antarctic Peninsula in the latter half of 2015 (compare Figs. 6.3f,h with Fig. 6.4a). Elsewhere, the pattern of response was quite different from recent strong El Niño events (Fig. SB6.1b). The southern Pacific positive pressure anomaly, although much stronger than the El Niño average, was displaced northward. While this had consistent temperature

and wind impacts across the Antarctic Peninsula and the South Pacific, much of the rest of West Antarctica was not strongly impacted in 2015 as is typical during other strong El Niño events (compare Fig. SB6.1b with Fig. 6.3e,g and Byrd AWS data in Fig. 6.4e). The northward displacement of the high pressure anomaly in 2015 is most likely due to the fact that much of 2015, with the exception of October, was marked by a positive SAM index (compare Fig. 6.2c). Because the SAM index monitors the strength and/or position of the circumpolar jet, which is known to influence extratropical Rossby wave propagation and breaking (L'Heureux and Thompson 2006; Fogt et al. 2011; Gong et al. 2010, 2013), the strengthened jet in 2015 was not so favorable for Rossby wave propagation into the higher (>60°) southern latitudes. Thus, the South Pacific teleconnection was displaced farther north than normal (based on Fig. SB6.1b). Historically, many of the strongest El Niño events occurred during negative SAM index values

<figure><img src="image_224.png" /></figure>

FIG. SB6.1. (a) SOND MSLP (contoured) and 10-m wind anomalies (vectors) from the 1981–2010 climatological mean. Shading represents the number of standard deviations the 2015 SOND MSLP anomalies were from the climatological mean; wind vectors are only shown if at least one component was a standard deviation outside the climatological mean. (b) MSLP (contoured) and 10-m wind (vectors) anomaly composite for the six strongest El Niño events in SOND since 1979 (in rank order: 1997, 1982, 1987, 2002, 2009, 1991), with shading (from lightest to darkest shades) indicating composite mean anomalies (of MSLP and winds) significantly different from zero at *p* < 0.10, *p* < 0.05, *p* < 0.01, respectively, based on a two-tailed Student's t test. The shading therefore indicates where the El Niño composite mean is significantly different from the 1981–2010 climatology. (Source: ERA-Interim reanalysis.)

(Fogt et al. 2011) in contrast to the 2015 El Niño event. Nonetheless, because of its influence on meridional flow over the ice edge at the time of maximum sea ice extent (Figs. SB6.1a, 6.8c), the end of 2015 was marked by strong regional sea ice extent anomalies in the West Antarctic sector (Figs. 6.8c,d, 6.9c–e), which were opposite in sign to the long-term trends in sea ice extent in that region (Fig. 6.8e).

In summary, the 2015 El Niño indeed produced strong atmospheric circulation impacts in the South Pacific, which are consistent with the below-average temperatures across the Antarctic Peninsula and sea ice extent anomalies in the Bellingshausen, Amundsen, and Ross Seas. However, because the teleconnection was displaced farther north than normal, its impact across the rest of Antarctica was much weaker than was the case for previous strong El Niño events.
detection method (Liu et al. 2005). The algorithm delineates each melt event in the time series by tracking its onset and end dates, with the onset day of the first melt event being the start day of the melt season (Fig. 6.6a) and the end day of the last melt event being the end day of the melt season (Fig. 6.6b). The melt duration is then the total number of melting days per pixel during the defined melt season (excluding any refreezing events that may have occurred during this period; Fig. 6.6c). The melt extent and melt index are metrics useful for quantifying the interannual variability in surface melt (Zwally and Fiegles 1994; Liu et al. 2006). Melt extent (km²) is the total area that experienced surface melt for at least one day, while the melt index (day·km²) is the product of duration and melt extent and describes the spatiotemporal variability of surface melting. The anomaly map (Fig. 6.6d) was created by referencing the mean melt duration computed over 1981–2010 (see also Fig. 3 in Liu et al. 2006).

The spatial pattern of the melt duration map in austral summer 2014/15 (Fig. 6.6c) was similar to previous years (Wang et al. 2014). Areas with extended melt duration (>45 day duration in orange-red) were the Antarctic Peninsula area, including the Larsen and Wilkins ice shelves, and parts of coastal East Antarctica, including the Shackleton ice shelf and other smaller ice shelves east of there. Areas with moderate melt duration (16–45 day duration in green-yellow) included much of coastal Queen Maud Land and the Amery, West, and Abbot ice shelves; short-term melt (<16 day duration in blues) occurred on the coast of Marie Byrd Land, including Ross ice shelf and portions of Queen Maud Land near the Filchner Ice Shelf.

<figure><img src="image_225.png" /><figcaption>**FIG. 6.7.** (a) Melt index (10⁶ day·km²) from 1978/79 to 2014/15, showing a slight negative trend (*p* not significant at 95%). (b) Melt extent (10⁶ km²) from 1978/79 to 2014/15, also showing a negative trend (*p* significant at 99%). A record low melt was observed during 2008/09. The year on the x-axis corresponds to the start of the austral summer melt season, e.g., 2008 corresponds to summer (DFJ) 2008/09.</figcaption></figure>

The melt index for the entire Antarctic continent has continued to drop since the 2012/13 season (Fig. 6.7a; Wang et al. 2014). The estimated melt index of the 2014/15 season is 29 252 500 day·km² in comparison to 39 093 125 day·km² in 2013/14 and 51 335 000 day·km² in the 2012/13 season. The melt extent of the 2014/15 season (Fig. 6.7b), however, is 1 058 750 km², slightly greater than last year at 1 043 750 km². The melt anomaly map in Fig. 6.6d shows the melt season was generally shorter than the historical average. Therefore, austral summer 2014/15 is classified as a low melt year for Antarctica. The 2014/15 melt extent and index numbers were almost equivalent to those observed during austral summer 2011/12 (944 375 km² and 29 006 250 day·km², respectively). Figure 6.7 shows a nearly significant (*p* = 0.05) negative trend (311 900 day·km² yr⁻¹) in melt index and a significant (*p* < 0.01) negative trend (14 200 km² yr⁻¹) in melt extent over 1978/79 to 2014/15, highlighted by the record low melt season observed during austral summer 2008/09. The negative trends in melt index and melt extent are consistent with previous reports (Liu et al. 2006; Tedesco 2009a,b).

f. Sea ice extent, concentration, and duration—P. Reid, R. A. Massom, S. Stammerjohn, S. Barreira, J. L. Lieser, and T. Scambos

Net sea ice areal extent was well above average during the first few months of 2015 (Fig. 6.8a). Monthly record extents were observed in January (7.46 × 10⁶ km²), April (9.06 × 10⁶ km²), and May (12.1 × 10⁶ km²). The January extent marked the highest departure from average for any month since records began in 1979, at 2.39 × 10⁶ km² above the 1981–2010 mean of 5.07 × 10⁶ km², or nearly 50% greater. These early season records follow on from the record high extent and late retreat of sea ice in 2014 (Reid et al. 2015). During the first half of 2015, there were 65 individual days of record daily sea ice extent, the last occurring on 11 July, and 46 record-breaking days of sea ice area within the first half of the year. However, the expansion of sea ice slowed so dramatically midyear that although sea ice area was at a record high level in May, it was at a record low level in August, just 83 days later (Fig. 6.8a). Close-to-average net sea ice extent levels were then observed in the latter half of 2015.

The record high net sea ice extent in January was dominated by strong positive regional anomalies in sea ice concentration and extent in the Ross and Weddell Seas (Figs. 6.8b, 6.9c,e) and across East Antarctica (~75°–140°E). This was counterbalanced by strong negative ice concentration and extent anomalies that were present in the Bellingshausen–Amundsen Seas (Figs. 6.8b, 6.9d). All three regions
of more extensive sea ice coincided with anomalously cool SSTs adjacent to the sea ice. Low atmospheric pressure anomalies were also present in the Weddell and Ross-Amundsen Seas (Fig. 6.3a). Interestingly, at this time colder-than-normal SSTs were present just to the north of the Bellinghausen-Amundsen Seas, possibly entrained within the ACC but not adjacent to the ice edge itself (and thus removed from the area experiencing below-normal ice extent).

As shown in Fig. 6.8a, there was a substantial and rapid decrease in the net ice extent (and area) anomaly from late January to early February, in large part due to changes in the eastern Ross (reflected in Fig. 6.9c) and western Amundsen (not shown) Seas. This rapid regional “collapse” followed lower-than-normal sea ice concentrations in the central pack ice during the latter part of 2014 (see Reid et al. 2015). In spite of this, net sea ice extent and area continued to track well above average or at record high levels between February and May. The Indian Ocean sector between ~60° and 110°E, the western Ross Sea, and the Weddell Sea showed particularly high or increasing sea ice extents during the February to May period as reflected in the regionwide daily anomaly series (Figs. 6.9a,c,e, respectively), with early-season areal expansion spurred on by colder-than-normal SSTs (not shown) and surface air temperatures (Figs. 6.3b,d).

June saw the beginning of a major change in the large-scale atmospheric pattern at higher southern latitudes, with lower-than-normal atmospheric pressure over the Antarctic continent and a strong atmospheric wave-3 pattern evolving (Fig. 6.3e). This coincided with warmer-than-normal SSTs in lower latitudes of the Indian and Pacific Oceans (the latter associated with the developing El Niño) and their influence on

<figure><img src="image_226.png" /></figure>

<figure><img src="image_227.png" /></figure>

<figure><img src="image_228.png" /></figure>

<figure><img src="image_229.png" /><figcaption>**FIG. 6.8.** (a) Plot of daily anomalies from the 1981–2010 mean of daily Southern Hemisphere sea ice extent (red line) and area (blue line) for 2015. Blue banding represents the range of daily values of extent for 1981–2010, while the thin black lines represent ±2 standard deviations of extent. Numbers at the top are monthly mean extent anomalies (× 10⁶ km²). Sea ice concentration anomaly (%) maps for (b) Jan and (c) Sep 2015 relative to the monthly means for 1981–2010, along with monthly mean SST anomalies (Reynolds et al. 2002; Smith et al. 2008). These maps are also superimposed with monthly mean contours of 500-hPa geopotential height anomaly (Kalnay et al. 1996; NCEP). Bell is Bellinghausen Sea, AIS is Amery Ice Shelf. (d) Sea ice duration anomaly for 2015/16 and (e) duration trend (Stammerjohn et al. 2008). Both the climatology (for computing the anomaly) and trend are based on 1981/82 to 2010/11 data (Cavalieri et al. 1996, updated yearly), while the 2015/16 duration-year data are from the NASA Team NRTSI dataset (Maslanik and Stroeve 1999).</figcaption></figure>

the distribution of atmospheric jets (Yuan 2004) and hence cyclonicity at higher southern latitudes. The abrupt change in hemispheric atmospheric circulation began a regional redistribution of patterns of sea ice areal expansion (Fig. 6.9). On one hand, there was
<figure><img src="image_230.png" /></figure>

FIG. 6.9. Plots of daily anomalies (× 10⁶ km²) from the 1981–2010 mean of daily Southern Hemisphere sea ice extent (red line) and area (blue line) for 2015 for the sectors: (a) Indian Ocean; (b) western Pacific Ocean; (c) Ross Sea; (d) Bellingshausen–Amundsen Seas; and (e) Weddell Sea. The blue banding represents the range of daily values for 1981–2010 and the thin red line represents ±2 std dev. Based on satellite passive-microwave ice concentration data (Cavalieri et al. 1996, updated yearly).

a reduction in the rate of expansion in the western Weddell and Ross Seas and much of East Antarctica (~30°E–180°). In other regions (i.e., the eastern Weddell and Ross Seas and Bellingshausen and Amundsen Seas), however, a likely combination of wind-driven ice advection and enhanced thermodynamics (colder-than-normal atmospheric temperatures, and in the Bellingshausen and Amundsen Seas region colder-than-normal SSTs) led to strongly positive sea ice extent anomalies. The anomalous ice extent patterns in the Ross Sea and Bellingshausen–Amundsen Seas were opposite to the trends observed over the last few decades of greater/lesser sea ice extent in those two regions respectively (Holland 2014). The net result of this redistribution in regional ice extent

anomalies was that net circumpolar sea ice extent and area dropped dramatically at the beginning of July (Fig. 6.8a). This general regional ice anomaly pattern then persisted to the end of September (Fig. 6.8c).

Another switch in large-scale regional sea ice extent anomalies occurred in October in response to the dissipation of the atmospheric wave-3 pattern and subsequent increase in negative pressure anomalies centered on ~0° and ~170°W and a broad ridge of positive pressure anomalies centered on ~55°S, 90°W (Fig. 6.3g). Positive sea ice extent anomalies were associated with a combination of cold SSTs in the Bellingshausen–Amundsen Seas and cool atmospheric temperatures in the western Ross and Weddell Seas and far eastern East Antarctic. Negative anomalies were associated with relatively warm atmospheric temperatures to the east of the low pressure systems (Fig. 6.3h). At the same time, sea ice extent in the far eastern Weddell Sea and Indian Ocean sector (~0° to ~60°E) was well below average (Fig. 6.9a) and remained so for the rest of the year. This is attributable to the very low sea ice extent in the western Weddell Sea in the previous months (July–September as mentioned above), leading to lower-than-normal eastward advection of sea ice in the eastern limb of the Weddell Gyre (see Kimura and Wakatsuchi 2011). Similarly, a lack of eastward zonal advection of sea ice from the western Ross Sea resulted in lower-than-normal sea ice extent in the eastern Ross Sea (~150° to ~120°W). On a smaller scale, in late October through mid-November several intense low pressure systems caused a temporary expansion of the sea ice edge (~50% above the long-term average) between ~60° and 90°E.

The net result of the seasonal sea ice anomalies described is summarized by the anomaly pattern in the annual ice season duration (Fig. 6.8d). The longer-than-normal annual ice season in the outer pack ice of the eastern Amundsen, Bellingshausen, and western Weddell Seas (120°W–0°) was due both to an anomalously early autumn ice-edge advance and later spring ice-edge retreat. In contrast, the longer annual ice season in the inner pack ice zones of the western Weddell Sea and East Antarctic sector (~80°–120°E) was the result of anomalously high summer sea ice concentrations (Fig. 6.8b) that initiated an anomalously early autumn ice edge advance in those two regions. The shorter-than-normal annual ice season in the eastern Ross and western Amundsen Seas (160°–120°W) was mostly due to an anomalously early ice edge retreat in spring associated with the increased negative pressure anomalies centered on 170°W and lack of zonal ice advection from the west. Though of lesser magnitude, similar spring factors
(the low pressure at 0° and lack of zonal ice advection from the west) were also implicated in the shorter-than-normal ice season in the far eastern Weddell Sea and western Indian Ocean sector between 10° and 40°E. The contrast in spring-summer anomaly patterns between the Bellingshausen-Amundsen Seas and eastern Ross Sea (Figs. 6.8c, 6.9c,d) is a somewhat typical response to El Niño and as such is opposite to the sea ice response to the atmospheric circulation pattern associated with a strong positive SAM index (and is also opposite to the long-term trend in annual ice season duration; Fig. 6.8e). However, and as described in Sidebar 6.1, the high-latitude response to this year's El Niño was spatially muted relative to past El Niños due to the damping effect of the circulation anomalies associated with a mostly positive SAM index during this time.

g. *Southern Ocean*—J.-B. Sallée, M. Mazloff, M. P. Meredith, C. W. Hughes, S. Rintoul, R. Gomez, N. Metzl, C. Lo Monaco, S. Schmidtko, M. M. Mata, A. Wählin, S. Swart, M. J. M. Williams, A. C. Naveria-Garabata, and P. Monteiro

The horizontal circulation of the Southern Ocean, which allows climate signals to propagate across the major ocean basins, is marked by eddies and the meandering fronts of the Antarctic Circumpolar Current (ACC). In 2015, large observed anomalies of sea surface height (SSH; Fig. 6.10a) contributed to variations in the horizontal ocean circulation. While many of these anomalies are typical of interannual variability, there were several regions where the 2015 anomaly was noteworthy due either to its extreme magnitude or its spatial coherence: north of the ACC in the Southwest Indian Ocean (~20°–90°E); in the entire South Pacific (~150°E–60°W), specifically the mid-Pacific basin around 120°W; and the anomalous negative SSH anomalies stretching around much of the Antarctic south of the ACC, especially over the Weddell Sea (0°–60°W). A large part of the 2015 SSH anomalies in the mid-Pacific, around Australia, and around South America was likely attributable to the strong El Niño event in 2015, though the low around Antarctica appears unrelated to ENSO variations (Sallée et al. 2008).

It is not straightforward to convert these large-scale SSH anomalies into anomalies of circumpolar volume transport. The best indicator of such variations is bottom pressure averaged on the Antarctic continental slope (Hughes et al. 2014), but such observations on the narrow slope regions are not available. Instead, the focus is on sea level averaged over this strip (Hogg et al. 2015). Figure 6.10d reveals that recent years have shown a resumption of the steady

rise in sea level in this region. A slight sea level fall in 2015 compared to 2014 remains consistent with this trend given the increase from 2014 to 2015 in eastward winds as represented by the SAM index (Fig. 6.10e), which is known to be associated with a fall in sea level (Aoki 2002; Hughes et al. 2003). A conversion from sea level to zonally averaged circumpolar transport, which is well established for periods of up to five years, is shown in Fig. 6.10e. This confirms the association with the atmospheric structures related to SAM but is suggestive of an additional source of variability associated with major El Niño (e.g., 2009/10, 2015/16) and La Niña (e.g., 1998/99, 1999/2000) events, when zonally averaged circumpolar transport anomalies became more negative (decreased transport) and positive (increased transport), respectively.

The horizontal circulation and vertical water-mass circulation are dynamically linked through a series of processes including surface water-mass transformation associated with air-sea-ice interactions. The characteristics of the lightest and densest of the Southern Ocean water masses are now described to provide an assessment of the vertical circulation and its contribution to ventilating the world's oceans. The ocean surface mixed layer is the gateway for air-sea exchanges and provides a conduit for the sequestration of heat or carbon dioxide from the atmosphere into the ocean's interior, which is ultimately mediated by the physical characteristics of the mixed layer.

The 2015 mixed layer temperature anomaly pattern revealed a distinct north-south dipole delimited by the ACC (Figs. 6.10b,c). Mixed layer conditions in Antarctic waters were very cold, whereas the mixed layers north of the ACC were warmer than average. This pattern persisted throughout both summer and winter, though with a reduced magnitude in winter. While the warm signal in the mid-Pacific was consistent with the influence of the 2015 El Niño event (Vivier et al. 2010), the cold signal south of the ACC was not. It was consistent, however, with the atmospheric circulation pattern associated with a positive SAM index that included increased northward Ekman transport of relatively cool and fresh Antarctic surface waters. In agreement, the southeast Pacific sector was fresher than the climatological average conditions, though other regions showed little homogeneity in salinity anomaly (not shown).

Mixed layer temperatures have a strong influence on air-sea CO₂ fluxes and ocean pH. Overall, the Southern Ocean is a net carbon sink. This sink decreased during the 1990s, but since 2002 has increased, reaching a maximum of about 1.3 Pg C yr⁻¹ in 2011 (Pg = 10¹⁵g; Landschutzer et al. 2015) and was
<figure><img src="image_231.png" /></figure>

FIG. 6.10. (a) 2015 anomaly of sea surface height (cm) with respect to the 1993–2014 mean (produced from the Aviso SSH merged and gridded product). The trend at each location has been removed. (b) Time series (gray) of sea level anomaly (cm; produced from the Aviso SSH merged and gridded product) representative of a narrow region along the Antarctic coast (see Hogg et al. 2015) smoothed at different time scales. (c) Estimate of annual mean ACC transport anomaly (Sv, black line) derived from sea level (Hogg et al. 2015) with SAM index (Marshall et al. 2003) superimposed (dashed orange line). (d) 2015 anomaly of mixed layer temperature (°C) in summer (Jan–Apr) with respect to the climatological mean (2000–2014; computed from all available Argo observations). (e) Same as (d) but for the winter anomaly (Jul–Sep). In (a, d, e), the two black lines represent the mean location of the two main fronts of the ACC (Orsi et al. 1995). (f) Evolution of the Southern Ocean carbon sink (Pg C yr⁻¹) south of 35°S, showing the flux derived from an interpolation method (Landschutzer et al. 2015) based on surface ocean pCO₂ data from SOCAT-V3 (black solid line) and from SOCAT-V2 (black dotted line; Bakker et al. 2014). Positive values refer to a flux from air to ocean (i.e., ocean acts as a sink). (g) Evolution of pH in the Antarctic surface water (around 56°S, solid square) and subantarctic surface water (around 40°S, hollow square) in the South Indian Ocean; only repeat summer stations are used. (h) Potential temperature (°C, black line) and salinity (dashed orange line) of Antarctic Bottom Water at 140°E for 1969–2015; only repeat summer stations are used. Potential temperature and salinity are averaged over the deepest 100 m of the water column for stations between 63.2° and 64.4°S, in the core of the AABW over the lower continental slope (average pressure of 3690 dbar). The vertical dashed line indicates the date of the calving of the Mertz Glacier Tongue. Note that time axis in (h) is different from (b), (c), (f), and (g).

likely stronger than 1 Pg C yr⁻¹ in 2015 (Fig. 6.10f). South of the ACC, the increase of the sink is explained by the cooling of the surface layer in summer (Fig. 6.10b) and the stability of the CO₂ concentrations in winter (Munro et al. 2015). The ocean carbon uptake leads to a decrease in pH, the so-called ocean acidification. A global assessment of surface water pH in 2015 is not possible due to scarcity of observations, so we present the evolution of pH in the South Indian sector, which has been monitored since 1985 (Fig. 6.10g). A rapid pH change was identified in 1985–2001 (−0.03 decade⁻¹) but has stabilized since 2002 (Fig. 6.10g), a signal probably associated with a shift in climate forcing (e.g., neutral state of SAM in 2000s; Fig. 6.10e).

The bottom layers of the Southern Ocean are also undergoing substantial changes. Linear trends of deep ocean change constructed from repeat sections between 1992 and 2005 reveal abyssal warming, with the strongest warming close to Antarctica (Purkey and Johnson 2010; Talley et al. 2016). Antarctic Bottom Water (AABW) is also contracting in volume and freshening (Purkey and Johnson 2012, 2013; Shimada et al. 2012; Jullion et al. 2013; van Wijk and Rintoul 2014; Katsumata et al. 2014; Meredith et al. 2014). These changes reflect the response of AABW source regions to changes in surface climate and ocean-ice shelf interaction and to downstream propagation of the signal by wave and advective processes (Jacobs and Giulivi 2010; van Wijk and Rintoul 2014; Johnson et al. 2014).

As with pH, observations of the deep ocean remain scarce, preventing a global assessment of the state of the abyssal ocean in 2015. However, repeat occupa-
tions of hydrographic sections at 140°E provide a record of variations in AABW properties immediately downstream of a primary source of bottom water (Fig. 6.10h). Potential temperature shows significant variability but no long-term trend between 1969 and 2015. In contrast, the long-term trend in salinity (~ -0.01 decade⁻¹; Fig. 6.10h) exceeds interannual variability. Calving of the Mertz Glacier Tongue in 2010 reduced the area of the Mertz polynya and thereby reduced the amount of sea ice and dense water formed in the polynya (Tamura et al. 2012; Shadwick et al. 2013), which likely contributed to the AABW variations observed after 2010.

h. **Antarctic ozone hole**—E. R. Nash, S. E. Strahan, N. Kramarova, C. S. Long, M. C. Pitts, P. A. Newman, B. Johnson, M. L. Santee, I. Petropavlovskikh, and G. O. Braathen

The 2015 Antarctic ozone hole was among the largest and most persistent ever observed, based upon the record of ground and satellite measurements starting in the 1970s. Figure 6.11a displays the daily areal coverage of the Antarctic ozone hole during 2015 (blue line) compared to the 1986–2014 climatology (white line). The ozone hole area is defined as the area covered by total column ozone values less than 220 Dobson Units (DU). For 2015, area values greater than 5 million km² first appeared in late August, ap-

<figure><img src="image_232.png" /></figure>

**FIG. 6.11.** (a) Area coverage of the Antarctic ozone hole as defined by total column ozone values less than 220 DU and (b) daily total column ozone minimum values in the Antarctic region from TOMS/OMI for 2014 (red line) and 2015 (blue line). The average of the daily values (thick white line), the record maximum and minimum sizes (thin black lines), and the percentiles (gray regions and legend in a) are based on a climatology from 1986–2014. The black arrows indicate the dates of the ozone maps on the right side.

proximately two weeks later than typical. The ozone hole usually reaches its largest size by mid-September, but in 2015 the maximum size occurred on 2 October at 28.2 million km². The ozone hole then persisted at this large size (>20 million km²) until 15 November, setting daily records during much of October and November. The development of ozone depletion over time (daily minimum values; Fig. 6.11b) indicates that the ozone minimum was reached near 2 October; ozone then remained near record low values until early December. The late start, persistent large area, and low ozone minima were caused by unusually weak stratospheric wave dynamics.

NOAA ozonesondes are launched regularly over South Pole station. In early October 2015, the 12–20-km column ozone was close to the long-term mean (Fig. 6.12a), while ozone increases thereafter were delayed compared to the long-term record. The minimum 12–20-km column ozone in 2015 was the fourth lowest at 7.2 DU, measured on 21 October (ozone hole image Fig. 6.11a). The ozonesonde total column minimum was 112 DU on 15 October. The ozonesonde of 8 December 2015 (ozone hole image Fig. 6.11b) showed record low total column ozone for early December, highlighting the abnormally late breakup of the hole.

One of the key factors controlling the severity of the Antarctic ozone hole is stratospheric temperature. Lower temperatures allow more polar stratospheric cloud (PSC) formation, exacerbating ozone depletion. Southern Hemisphere stratospheric dynamical conditions were anomalous in spring 2015. The lower stratospheric polar cap temperatures from the NCEP-DOE Reanalysis 2 for 2015 (Fig. 6.12b, blue line) were near the climatological average through August, but were below climatology during September–November.

The 100-hPa eddy heat flux is a measure of wave propagation into the stratosphere. A smaller (larger) magnitude leads to colder- (warmer-) than-average temperatures. The heat flux was generally below average for July–October (Fig. 6.12c), especially in October. As a result, temperatures warmed at a slower rate in September–October (Fig. 6.12b), and the vortex eroded more slowly than in previous years. Consequently, the ozone hole was persistent, and stratospheric ozone levels at South Pole remained below average during October–November (Fig. 6.12a).

The 2015 ozone hole broke up on 21 December, about two weeks later than average. The breakup is identified as the date when total ozone values below 220 DU disappear (see Fig. 6.11). Ozone hole breakup is tightly correlated with the stratospheric polar vor-
<figure><img src="image_233.png" /></figure>

FIG. 6.12. (a) Column ozone from NOAA South Pole ozonesondes measured over the 12–20-km (~160–40-hPa) range. (b) NCEP–DOE Reanalysis 2 of lower stratospheric temperature (60°–90°S, 50-hPa). (c) NCEP–DOE Reanalysis 2 of zonal mean eddy heat flux (45°–75°S, 100 hPa). The blue lines show the 2015 values and the red lines show 2014. The average of the daily values (thick white line), the record maximum and minimum sizes (thin black lines), and the percentiles [(gray regions and legend in (b)] are based on a climatology from (a) 1986–2014 and (b), (c) 1979–2014.

tex breakup, which is driven by wave events propagating upward into the stratosphere, thus enabling transport of ozone-rich air from midlatitudes. The 2015 ozone hole broke up late because of weak wave driving in October–November (Fig. 6.12c).

Levels of chlorine and bromine continue to decline in the stratosphere, and improvement of ozone conditions over Antarctica is expected. Ozone depletion is estimated using equivalent effective stratospheric chlorine (EESC)—a combination of inorganic chlorine ($Cl_y$) and bromine. Using a mean age of air of 5.2

years, EESC shows a 2000–02 peak of 3.8 ppb, with a projected decrease in 2015 of 9% to 3.45 ppb as a result of the Montreal Protocol. This is a 20% drop towards the 1980 (“pre-ozone hole”) level of 2.03 ppb. NASA *Aura* satellite Microwave Limb Sounder (MLS) $N_2O$ measurements can be used to estimate Antarctic stratospheric $Cl_y$ levels (Strahan et al. 2014). Antarctic EESC has a small annual decrease (<1% yr$^{-1}$), but interannual variations in transport to the Antarctic vortex cause $Cl_y$ to vary by up to ±8% with respect to expected levels. Similar to 2014, the 2015 Antarctic stratospheric $Cl_y$ was higher than recent years and similar to levels found in 2008 and 2010.

MLS lower stratospheric chlorine and ozone observations in the vortex were consistent with the

<figure><img src="image_234.png" /></figure>

FIG. 6.13. Time series of 2014 (red line) and 2015 (blue line) Antarctic vortex-averaged: (a) HCl, (b) CIO, and (c) ozone from *Aura* MLS (updated from Manney et al. 2011). These MLS averages are made inside the polar vortex on the 440-K isentropic surface (~18 km or 65 hPa). The gray shading shows the range of Antarctic values for 2004–14. (d) Time series of 2014 (red line) and 2015 (blue line) CALIPSO PSC volume (updated from Pitts et al. 2009). The gray shading shows the range for 2006–14, and the black line is the average.
Ice exerts a dominant control on the function and structure of polar ecosystems. Depending on the organism, it provides habitat and foraging platforms, or serves as a barrier to food and the flow of nutrients (Fountain et al. 2012). Polar ecosystems, both terrestrial and marine, have evolved and adapted to pervasive ice conditions, so when air temperatures rise above the melting threshold, the normal balance of water and ice shifts dramatically, resulting in a series of cascading effects that propagate through the entire ecosystem. The effects may persist for years to decades (J. Priscu 2016, manuscript submitted to *BioScience*).

In Antarctica, the differences between marine and terrestrial ecosystems could not be more extreme. These two biomes are the focus of two NSF-funded Long Term Ecological Research (LTER) programs: the Palmer LTER (or PAL), which is studying the rapidly changing marine ecosystem west of the Antarctic Peninsula (Ducklow et al. 2013), and the McMurdo Dry Valleys LTER (or MCM), which is studying the terrestrial ecosystem in the Dry Valley polar desert (Freckman and Virginia 1997). Established in the early 1990s, these two Antarctic sites collect baseline measurements to develop process-level understanding, thus providing necessary context for evaluating ecological responses to climate events.

The marine ecosystem surrounding Antarctica includes the coastal and continental shelf region that is influenced by seasonal sea ice cover, as well as the permanently open ocean zone poleward of the Antarctic Circumpolar Current (Treguer and Jacques 1992). Primary production in these regions is dominantly by phytoplankton. Although considerable regional and seasonal variability exists, Antarctic food webs are typically supported by diatoms with variable contributions by other types of phytoplankton. Diatom-based food webs are typically characterized by highly variable but sometimes vast swarms of Antarctic krill. Krill in turn are the principal food for the conspicuous large predators of Antarctic seas, including penguins and other seabirds, seals, and whales (Hardy 1967).

This general picture has served as the paradigm for the Antarctic marine ecosystem for decades, but it appears to be changing, at least in the rapidly warming (Smith et al. 1996) western Antarctic Peninsula region (WAP) of the Bellingshausen Sea. Ecological change along the WAP was first marked by catastrophic declines in Adélie penguins (Fig. SB6.2a; Fraser and Hofmann 2003; Bestelmeyer et al. 2011). The principal cause of ecological change is decreasing sea ice cover in the WAP and greater Bellingshausen Sea—both its extent and duration (Fig. 6.8e; Stammerjohn

et al. 2012). Diatom blooms, krill recruitment, and penguin breeding success are all dependent on the extent of sea ice and the timing of its retreat (Saba et al. 2014; Montes-Hugo et al. 2009). Other changes in the freshwater system are also known to influence the marine ecosystem. Glacial discharge and melt, for example, have the capacity to increase ocean stratification and add bio-available micronutrients, such as iron, to the productive upper

<figure><img src="image_235.png" /></figure>

FIG. SB6.2. (a) The number of breeding pairs of Adélie and Gentoo penguins near Palmer Station, 1976–2013. The Gentoo is a subpolar, ice-tolerant invasive species that has colonized the polar region as sea ice cover has declined and water temperatures have increased. The first Gentoo pairs were observed at this location in 1994. (b) Monthly mean composite anomaly map of 500-hPa geopotential height centered over Antarctica for Sep 2001 to Feb 2002 relative to the mean calculated over Sep to Feb 1980–2001. BH and LP denote blocking high pressure and low-pressure anomalies, respectively. The yellow X is close to Palmer Station and the yellow circle is close to McMurdo Station. (From Massom et al. 2006.)
layers (Boyd and Ellwood 2010; Hawkings et al. 2014). Changes in any of these environment variables can lead to functionally extinct species and a reorganization of the marine ecosystem (e.g., Sailley et al. 2013).

Antarctic terrestrial ecosystems, at least those that inhabit the largest ice-free areas of the Antarctic continent, the Dry Valleys (78°S, 162°E), exist in a landscape that includes glaciers, perennially ice-covered lakes, seasonal meltwater streams, and arid soils (Ugolini and Bockhiem 2008). No vascular plants or vertebrates inhabit the region, and food webs are dominated by bacteria, cyanobacteria, fungi, yeasts, protozoa, and a few taxa of metazoan invertebrates (Freckman and Virginia 1997). Glacial meltwater is the primary source of water, which flows in ephemeral streams and conveys water, solutes, sediment, and organic matter to the lakes (Fountain et al. 1998; McKnight et al. 1999). Streams flow for up to 12 weeks in the austral summer providing a habitat for microbial mats abundant in streambeds stabilized by stone pavement (McKnight et al. 1998). Perennial water environments include ice-covered lakes in the Dry Valleys of Antarctica; they maintain biological activity year-round with food webs dominated by phytoplankton and bacteria (Laybourn-Parry 1997).

The two LTER sites are separated by about 3800 km (Fig. 6.1). On annual time scales, air temperatures at these two sites are inversely related (A. Fountain et al. 2016, manuscript submitted to *BioScience*; M. Obryk et al. 2016, manuscript submitted to *BioScience*) due mostly to the circulation anomalies associated with the SAM index (Trenberth et al. 2007). On decadal time scales, the lower-latitude PAL site is also experiencing rising air temperatures (+3°C increase in annual temperatures over 1958–2014), while the higher-latitude MCM site is experiencing a more modest change [+1°C over the same time period; A. Fountain et al. (2016), manuscript submitted to *BioScience*].

However, in the austral spring/summer of 2001/02, a hemisphere-wide atmospheric circulation anomaly caused

unusually high temperatures across the entire continent (Fig. SB6.2b; Massom et al. 2006), which had long-lasting impacts.

At MCM, the rapid melting of glacial ice caused streams to flow at record levels, eroding stream banks and rapidly raising lake levels (Foreman et al. 2004). The stream waters transported unusually high concentrations of sediments and nutrients to the ice-covered lakes. Phytoplankton chlorophyll-a concentrations reached record high levels that austral summer but also remained at elevated levels for almost a decade. Elevated soil moisture caused a reorganization of species composition in the soils that was still evident seven years later (Barrett et al. 2008).

At PAL, warm, moist northwesterly winds caused a rapid and early ice edge retreat in early spring (September–October 2001) that subsequently compacted and piled the ice against the Peninsula. Snowfall was also anomalously high during this time (Massom et al. 2006). Abundances of krill species were higher than normal, likely due to the high productivity associated with the compacted sea ice inshore (Steinberg et al. 2015). The positive chlorophyll-a anomaly in 2001/02 corresponded to a statistically significant krill recruitment event (evidenced in Adélie penguin diet samples) the following year (Saba et al. 2014). However, it was the catastrophic late-season snowfalls and subsequent flooding that caused the largest single-season decline in Adélie penguin breeding success in 30 years (Fraser et al. 2013). There was a devastating loss of an entire breeding cohort, an effect that is still evident 10 years later.

The climate event of 2001/02 illustrates the extreme sensitivity of polar ecosystems and also illustrates how an anomalous event can induce connectivity across different regional climates. As exemplified here, a relatively small but critical change in the temporal and spatial distributions of ice and water exhibited dramatic and persistent ecological responses, the implications of which are still being studied.

late start of the 2015 ozone hole (Fig. 6.11a). The ref-ormation of hydrogen chloride (HCl; Fig. 6.13a) and decrease of chlorine monoxide (ClO; Fig. 6.13b) oc-curred late in 2015. The 440-K potential temperature ozone levels (Fig. 6.13c) were higher than average in July–September, but declined to very low values by mid-October, consistent with Fig. 6.12a.

Heterogeneous chemical reactions on PSC surfaces convert reservoir chlorine (e.g., HCl) into reactive

forms (e.g., ClO) for catalytic ozone loss. The PSC volume (Fig. 6.13d), as measured by the *Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)*, generally followed the average (black line) for the entire season. However, the October 2015 volume of 5.6 million km³ ranked highest of all 10 years, consistent with the persistent and large October ozone hole (Fig. 6.11a).

Satellite column observations over Antarctica (not shown) show some indications that ozone loss
has diminished since the late-1990s. Averaged daily minima over 21 September–16 October (ozone hole maximum period) have increased since 1998 at a rate of 1.2 DU yr⁻¹ (90% confidence level). The 2015 ozone hole area, averaged over 7 September–13 October, was estimated at 25.6 million km², the fourth largest over the 1979–2015 record. Since 1998, this area is decreasing at a rate of –0.09 million km² yr⁻¹, but this trend is not statistically significant. The decline of chlorine concentrations should eventually

be manifested in smaller and shallower Antarctic ozone holes. However, unambiguous attribution of the ozone hole improvement to the Montreal Protocol cannot yet be made because of relatively large year-to-year transport, wave activity, temperature variability, and observational uncertainty. Further information on the ozone hole, with data from satellites, ground instruments, and balloon instruments, can be found at www.wmo.int/pages/prog/arep/gaw/ozone/index.html.
**a. Overview**

This chapter provides summaries of the 2015 tem-
perature and precipitation conditions across seven
broad regions: North America, Central America and
the Caribbean, South America, Africa, Europe, Asia,
and Oceania. In most cases, summaries of notable
weather events are also included. Local scientists
provided the annual summary for their respective
regions and, unless otherwise noted, the source of the
data used is typically the agency affiliated with the au-
thors. Please note that different nations, even within
the same section, may use unique periods to define
their normals. Section introductions will typically
define the prevailing practices for that section, and
exceptions will be noted within the text. In a similar
way, many contributing authors use languages other
than English as their primary professional language.
To minimize additional loss of fidelity through re-
interpretation after translation, editors have been
conservative and careful to preserve the voice of the
author. In some cases, this may result in abrupt transi-
tions in style from section to section.

b. North America

This section is divided into three subsections:
Canada, the United States, and Mexico. Information
for each country has been provided by local scientists,
and the source of the data is from the agency affili-
ated with the authors. Where available, anomalies are
reported using a 1981-2010 base period; however,
due to the different data sources, some anomalies are
reported using other base periods. These are noted
in the text.

<figure><img src="image_236.png" /><figcaption>FIG. 7.1. Annual average temperature anomalies (°C) for Canada for 1948-2015 (base period: 1961-90). The red line is the 11-yr running mean. (Source: Environment and Climate Change Canada.)</figcaption></figure>

In Canada, 2015 was characterized by higher-than-
average temperatures stretching from the central
regions to the Pacific Coast and lower- and drier-
than-average temperatures in the northeastern region
of the country. Anomalies in this section are reported
with respect to the 1961-90 base period.

(i) Temperature

The annual average temperature in 2015 for Canada was 1.3°C above the 1961-90 average, based on preliminary data. This marks the 11th warmest year since nationwide records began in 1948. The warmest year on record for Canada was 2010, at 3.0°C above average, and 4 of the 10 warmest years have occurred during the last decade. The national annual average temperature has increased 1.6°C over the past 68 years (Fig. 7.1). In 2015, annual departures >+2.5°C were recorded in the Yukon and western Northwest Territories, while annual departures <-0.5°C were observed in northern Quebec, Labrador, and Baffin Island (Fig. 7.2a).

Seasonally, winter (December–February) 2014/15
was 1.0°C above average and the 27th warmest
since 1948. Warmer-than-average conditions were

<figure><img src="image_237.png" /><figcaption>FIG. 7.2. Annual (a) average temperature anomalies (°C) and (b) total precipitation anomalies in Canada (% departure; base period: 1961–90). (Source: Environment and Climate Change Canada.)</figcaption></figure>
observed in Yukon, Northwest Territories, British Columbia, Alberta, and Saskatchewan. Most of Ontario, Quebec, and the Atlantic provinces experienced cooler-than-average conditions. During spring (March-May), the same pattern of warmer-than-average conditions in the western and central regions and cooler-than-average conditions in the eastern regions of the country continued. The nationally averaged temperature for spring 2015 was 1.3°C above the 1961-90 average and the 14th warmest in the 68-year period of record.

Summer (June-August) was 1.0°C above average and the sixth warmest since 1948. British Columbia and northern Nunavut (a territory in the northeast of the country) experienced warmer-than-average conditions. Southern Ontario was the only region with slightly cooler-than-average temperature conditions during summer. Summer temperatures across the remainder of the country were near-average.

During autumn (September-November), the pattern changed with the central regions of the country, from Saskatchewan through the Maritimes, and the northern territories all experiencing warmer-than-average conditions, while British Columbia, Alberta, northern Quebec, and Newfoundland and Labrador experienced near-average conditions. The nationally averaged temperature was 1.7°C above the 1961-90 average; the sixth warmest autumn since 1948.

### (ii) Precipitation

Canada as a whole experienced slightly drier-than-average precipitation in 2015. Based on preliminary data, it was the 20th driest year since nationwide records began in 1948, with nationally averaged precipitation 97% of the 1961-90 average. Drier-than-average conditions were observed for eastern Nunavut, northern Quebec and Labrador, in central British Columbia, and Alberta, whereas only the area over the Canadian Arctic Archipelago experienced wetter-than-average conditions (Fig. 7.2b).

Seasonally, winter 2014/15 was the 13th driest since 1948, and nationally averaged precipitation was 90% of the 1961-90 average, with most of the country experiencing drier-than-average conditions. However, wetter-than-average conditions were observed over much of Nunavut and the Atlantic provinces. Spring 2015 was the 10th driest in the 68-year period of record with nationally averaged precipitation 89% of average. Drier-than-average conditions continued across much of the country, with some wetter-than-average conditions in the western Canadian Arctic Archipelago.

Summer 2015 was the 17th wettest since 1948, and national average precipitation was 105% of average. Wetter-than-average conditions were mainly observed in the northwestern regions of the country whereas drier-than-average conditions occurred in British Columbia and Alberta. Autumn 2015 was the 26th wettest since 1948, with nationally averaged precipitation 103% of average. Drier-than-average conditions for the season were experienced in the Yukon, northern British Columbia, most of Quebec, and over Baffin Island in the north. Wetter-than-average conditions were observed in the Prairie Provinces (Alberta, Saskatchewan, and Manitoba) and in the rest of Nunavut for the autumn months.

### (iii) Notable events

Winter got off to a slow start for the Maritimes, but conditions changed in January. Snow fell from several storms, often just a few days apart. Atlantic Canada was continually battered through February and March with storm after storm, leaving behind snow amounts not seen in decades. Numerous records were set over the 2014/15 winter in the Maritimes. Halifax International Airport in Nova Scotia recorded total snow accumulation from January to May of 371 cm (normal is 59 cm). The previous snowiest such period at any Halifax station was 330 cm in 1972. Saint John, New Brunswick, received more than double its normal snowfall—495 cm (normal is 240 cm)—its snowiest winter on record. Moncton, New Brunswick, broke the 5-meter level at 507 cm (normal is 325 cm). In Charlottetown, Prince Edward Island, the snowiest city in Canada this winter, an April snowstorm helped set a new record for the most snow in one winter—551 cm—12 cm more than the previous record in 1971/72.

The wildfire season in Canada began early, ended late, and was extremely active, especially in the West. The national wildland fire season was above average for both number of fires and hectares burned, about four times the 15-year average (2001–15) and three times the 25-year average (1991–2015), respectively. Wildfires began in northern Saskatchewan in March. Residents from several communities near La Ronge and La Loche began evacuating to centers in the south. Hot temperatures and dry thunderstorms in May and June contributed to even more volatile fire conditions, with more than 13 000 people evacuated in what was the largest evacuation in Saskatchewan's history. In total, 1.8 million hectares burned in Saskatchewan, six times the provincial average. In Alberta, wildfires burned hot and fast in June when half the province came under a fire advisory. British
Columbia reported more than 1800 wildfires that burned an estimated 300 000 hectares and cost more than 287 million U.S. dollars to fight. The 20-year (1996–2015) average number of fires is about 1050 with an average 43 280 hectares burned. Conditions in British Columbia included extreme heat near 40°C, widespread and persistent dryness, large amounts of dry lightning, and gusty winds, which all contributed to the extreme fire season.

2) UNITED STATES—J. Crouch, R. R. Heim Jr., and C. Fenimore

The annual average temperature in 2015 for the contiguous United States (CONUS) was 12.4°C, or 0.9°C above the 1981–2010 average—the second warmest year since records began in 1895, behind 2012 (Fig. 7.3). The annual CONUS temperature over the 121-year period of record is increasing at an average rate of 0.1°C per decade. The nationally averaged precipitation total during 2015 was 111% of average, the third wettest year in the 121-year historical record. The annual CONUS precipitation is increasing at an average rate of 4.1 mm per decade. Outside of the CONUS, Alaska had its 2nd warmest and 15th wettest year since records began in 1925. The statewide temperature was 1.6°C above average, while the precipitation total was 108% of average. Complete U.S. temperature and precipitation maps are available at www.ncdc.noaa.gov/cag/.

(i) Temperature

During early 2015, record warmth spanned the western United States with record and near-record cold temperatures in the Midwest and Northeast. The last few months of 2015, particularly December, brought much-above-average temperatures to

<figure><img src="image_238.png" /><figcaption>FIG. 7.3. Annual mean temperature anomalies (°C) for the contiguous United States for 1895–2015 based on the 1981–2010 average. The red line is the 10-year running mean. (Source: NOAA/NCEI.)</figcaption></figure>

<figure><img src="image_239.png" /></figure>

<figure><img src="image_240.png" /><figcaption>FIG. 7.4. (a) Annual average temperature anomalies (°C) and (b) % of average annual total precipitation in the contiguous United States (base period: 1981–2010). (Source: NOAA/NCEI.)</figcaption></figure>

the East, with near-average temperatures across the West. This pattern resulted in all 48 states in the CONUS observing an above-average annual temperature (Fig. 7.4a). Florida, Montana, Oregon, and Washington (state) each had their warmest year on record. Twenty-three additional states across the West, Great Plains, Gulf Coast, and East Coast each had annual temperatures that ranked in the highest 10th percentile of their historical records.

The winter (December–February) 2014/15 CONUS temperature was 0.4°C above average, ranking in the warmest third of the historical record. Record and near-record warmth were observed in the West, with six states observing record high seasonal temperatures. Below-average temperatures occurred in the East; February was particularly cold, with 24 states observing one of their 10 coldest months on record and numerous cities, including Chicago, Illinois, and Buffalo, New York, being record cold. The CONUS spring (March–May) temperature was 0.7°C above average, the 11th warmest on record. Much-above-average temperatures were observed across the West and Southeast—Florida observed its warmest spring
on record. The summer (June–August) CONUS tem-
perature was 0.5°C above average, the 12th warmest
on record. Above-average temperatures continued in
the Southeast and West, where California, Oregon,
and Washington were record warm, while parts of
the Midwest were cooler than average. The autumn
(September–November) temperature was 1.5°C
above average, the warmest such period on record
for the CONUS. Every state had an above-average
autumn temperature: 40 states observed one of their
10 warmest on record, with Florida record warm.
December ended the year with a record high monthly
temperature for the CONUS that was 3.0°C above
average. Twenty-nine states across the East were
record warm, while near-average temperatures were
observed across the West.

(ii) Precipitation

During 2015, much of the central and eastern CO-
NUS were wetter than average, while parts of the West
and Northeast were drier than average (Fig. 7.4b).
Fourteen states had an annual precipitation total
that was within their wettest 10th percentiles. Okla-
homa and Texas were both record wet with 145% and
143% of average annual precipitation, respectively.
Drought conditions that began in 2010 in both states
were eradicated during 2015. California, which was
plagued by drought during all of 2015, had its 13th
driest year on record; end-of-year precipitation par-
tially erased early year deficits. At the beginning of
2015, the CONUS moderate to exceptional drought
footprint was 28.7%; it peaked at 37.8% in May and
ended the year at 18.7%. This end-of-year drought
footprint was the smallest for the CONUS since
December 2010.

The CONUS winter precipitation was 90% of
average, ranking in the driest third of the historical
record (29th driest). Despite near-average precipita-
tion in the West, record warmth caused much of the
high-elevation precipitation to fall as rain and not
snow. The below-average mountain snowpack and
subsequent below-average spring and summer run-
off contributed to near-record low reservoir levels,
worsening drought, and a record-breaking wildfire
season. Spring was the 10th wettest on record for the
CONUS, with 117% of average precipitation. Record
and near-record precipitation totals were observed in
the southern Great Plains and Central Rockies, with
below-average precipitation along both coasts. May
was an extraordinarily wet month for the CONUS
with 112.8 mm of precipitation, 147% of average,
the wettest among all months on record. Much of
the precipitation fell across the Southern Plains. The

summer precipitation for the CONUS was 108% of
average, the 16th wettest on record. Above-average
precipitation was observed across the Ohio Valley,
where record rain fell during June and July. For au-
tumn, the CONUS precipitation total was 111% of av-
erage and the 15th wettest on record. Above-average
precipitation was observed across the South and along
the East Coast. South Carolina had its wettest autumn
on record with 603.5 mm of rainfall, 321% of average.
December was record wet for the CONUS, at 160%
of average, becoming the only month in the 121-year
period of record that was simultaneously wettest and
warmest for its respective month.

(iii) Notable events

Tornado activity during 2015 was below average for the fourth consecutive year, with a total of 1177 confirmed tornadoes, compared to the 1991–2010 annual average of 1253. Despite the below-average number of tornadoes, there were 36 tornado-related fatalities, with most occurring during a deadly outbreak in December across the Southern Plains and Lower Mississippi Valley.

Wildfires burned nearly 4.1 million hectares
across the United States during 2015, surpassing 2006
for the most acreage burned since record keeping
began in 1960. The most costly wildfires occurred in
California, where over 2500 structures were destroyed
in the Valley and Butte wildfires in September.

Numerous major precipitation events impacted dif-
ferent regions of the CONUS in 2015. Heavy snowfall
during late winter and early spring set a new seasonal
record for Boston, Massachusetts, with 281 cm of snow.
In early October, an upper-level low interacted with
moisture from Hurricane Joaquin offshore in the
Atlantic to produce rainfall totals exceeding 500 mm
in parts of North and South Carolina. In the Southern
Plains, late-spring rainfall and summer and autumn
rains associated with the remnants of east Pacific tropi-
cal cyclones (see section 4e3) caused several significant
flooding events. On 30 October, the remnants of Hur-
ricanes Patricia dumped 389.7 mm of rain on Austin,
Texas, 146.3 mm of which fell in a single hour.

3) MEXICO—R. Pascual Ramírez, A. Albanil Encarnación, and J. L. Rodríguez Solís

In Mexico, the annual temperature for 2015 tied
with 2014 as the highest since national temperature re-
cords began in 1971. The nationally averaged precipita-
tion total was ninth highest since precipitation records
began in 1941, with the most notable accumulations
during February and March.
<figure><img src="image_241.png" /><figcaption>FIG. 7.5. Annual mean temperature anomalies (°C, blue) for Mexico (base period: 1981–2010). A linear trend is depicted by the red line. (Source: National Meteorological Service of Mexico.)</figcaption></figure>

### (i) Temperature

The 2015 mean temperature for Mexico was 22.1°C, which was 1.1°C above the 1981–2010 average, tying with 2014 as the warmest year since national records began in 1971 and surpassing the previous record of 21.9°C set in 2006 and 2013 (Fig. 7.5). This was also the 12th consecutive year with an above-average annual temperature.

The first three months of the year were near-average; however, the rest of the year was characterized by above-average temperatures and, in some instances, the daily mean, maximum, and minimum temperatures were close to two standard deviations above average (Fig. 7.6). The mean temperature for July–September was 2.3°C above average—the warmest such period on record, surpassing the previous record set in 2013 and 2014 and making the last three years the three warmest for the July–September period on record.

Regionally, the mean temperature in 2015 was below average in northern Baja California, areas of Chiuhua and its borders with Coahuila and Durango, between Colima and Jalisco, the central region (which includes the states of Mexico, Puebla, and Veracruz), and Oaxaca, while the rest of the country observed near-average to above-average temperatures. Eight states had their warmest year since records began in 1971: Campeche, Quintana Roo, and Yucatan in the Yucatan Peninsula; Nayarit, Jalisco, Michoacán, and Guerrero in the west; and Morelos in the central portion of the country. Conversely, the state of Veracruz observed one of its 20 coldest years on record (Fig. 7.7a).

Frost days, defined as daily minimum temperatures ≤0°C, is typical in Mexico during October–March, while hot days—daily maximum temperatures ≥40°C—are typical during April–September. During January–March 2015, only 26.0% of the country, mostly confined to the central region,

<figure><img src="image_242.png" /><figcaption>FIG. 7.6. Nationwide daily temperatures (°C) for Mexico. Shaded areas represent the ±2 std. dev. (base period: 1981–2010). Solid lines represent daily values for the three temperature parameters and dotted lines are the climatology. (Source: National Meteorological Service of Mexico.)</figcaption></figure>

<figure><img src="image_243.png" /><figcaption>FIG. 7.7. Annual (a) mean temperature anomalies (°C) and (b) precipitation anomalies (% of normal) observed in 2015 over Mexico (base period: 1981–2010). (Source: National Meteorological Service of Mexico.)</figcaption></figure>

experienced frost conditions (compared to the January–March average of 43.3%). Similarly, during October–December 2015, only 28.1% of the country, mainly in the northern areas, observed frost conditions, compared to the October–December average of 38.2%. During April–June, 20.2% of the country, mainly across northwestern and southern Mexico, observed hot days (compared to the average of 41.8%),
while 16.7% of the country, mainly in the northern regions, recorded hot days during July–September (much below the average of 29.6%).

### (ii) Precipitation

Above-average rainfall was observed across the north-central region in 2015, while below-average conditions were present across northern Baja California, the South Pacific (coastal areas of Guerrero, Oaxaca, and Chiapas), Veracruz, and the northern Yucatan Peninsula (Fig. 7.7b). The 2015 national rainfall total of 872.0 mm (110.8% of normal) was the ninth highest annual total since national records began in 1941.

March was exceptionally wet. Two winter storms and four frontal passages led to the rainiest March since records began in 1941, with 69.6 mm of rain, providing 8.0% of the annual rainfall for the year compared to a normal contribution (14.7 mm) close to 2.0%. September, which climatologically provides the greatest amount to the annual rainfall total (18.5%), added 132.7 mm in 2015, which represents 15.2% of 2015 annual rainfall.

Nine hurricanes, which all formed in the eastern North Pacific basin (see section 4e3), impacted the nation's western coastal region, leaving, in most cases, significant rainfall. The most activity occurred in September when Tropical Storm Kevin, Hurricane Linda, Hurricane Marty, and Tropical Depression 16-E brought heavy rain to northwestern and southwestern parts of the nation.

Overall, Aguascalientes (central Mexico) and Colima (western Mexico) had their wettest year on record, while Baja California Sur and Chihuahua had their second wettest. Meanwhile, the rainfall deficits were remarkable along the South Pacific coast, with Oaxaca having its second driest year since national records began in 1941.

### (iii) Notable events

An EF3 tornado struck Ciudad Acuña, Coahuila, on the morning of 25 May, causing at least 14 deaths and 290 injuries and destroying 750 homes. This was only the second tornado to reach EF3 intensity over the past 15 years, following the tornado in Piedras Negras on 24 April 2007, also in the state of Coahuila.

Hurricane Patricia was the strongest hurricane on record in the eastern North Pacific basin and one of the most intense to strike Mexico. It developed on 20 October and reached Category 5 hurricane strength on the Saffir–Simpson scale, with maximum sustained winds of 174 kt (88 m s⁻¹) and a minimum pressure of 879 mb (see section 3e4). Patricia was only the second tropical cyclone to make landfall in Mexico on the Pacific

coastal shores as a Category 5 storm since records began in the Pacific basin in 1949. The previous Category 5 landfall was in October 1959, when Hurricane No. 12 made landfall in the Tenacatita Bay, Jalisco, similar to Patricia's trajectory.

## c. Central America and the Caribbean

### i) CENTRAL AMERICA—J. A. Amador, H. G. Hidalgo, E. J. Alfaro, A. M. Durán-Quesada, and B. Calderón

For this region, nine stations from five countries were analyzed (Fig. 7.8). Stations on the Caribbean slope are: Philip Goldson International Airport, Belize; Puerto Barrios, Guatemala; Puerto Lempira, Honduras; and Puerto Limón, Costa Rica. Stations located on the Pacific slope are: Tocumen International Airport and David, Panama; Liberia, Costa Rica; Choluteca, Honduras; and Puerto San Jose, Guatemala. For 2015, the NOAA/NCEI GHCN daily precipitation dataset showed a considerable amount of missing data. For some stations, the daily rainfall amount was incomplete, whereas in other cases the value was flagged because it did not pass a quality control test. Precipitation historical records for the above-mentioned stations were recovered from Central American national weather services (NWS). The station climatology (1981–2010) and anomalies for 2015 were recalculated using NWS data by filling the gaps in the daily data records of the NOAA/NCEI database (especially those considered initially as zero based on the flags listed in the metadata of this database). In some stations (e.g., David and Choluteca), differences in precipitation totals between NWS data and the NOAA/NCEI dataset were as high as 420 and 560 mm, respectively, for 2015. In the station climatology, the largest differences were found in David and Liberia (490 and 820 mm, respectively). Previous years' station climatology from the NOAA/NCEI database and procedures used for all variables can be found in Amador et al. (2011).

### (i) Temperature

Mean temperature (Tm) frequency distributions for the nine stations are shown in Fig. 7.8. Most stations, with the exception of Limon and Liberia, experienced a higher frequency of above-average daily mean temperatures in 2015. There was a near-normal negative skewness in Tm at Philip Goldson (Tm1) and Puerto Barrios (Tm2) on the Caribbean slope and a near-average number of cold surges during the winter months. Stations in Panama (Tm5 and Tm6) and Honduras (Tm8) show a shift to the right of the Tm distribution with a higher frequency of warm Tm values during 2015.
<figure><img src="image_244.png" /><figcaption>FIG. 7.8. Mean surface temperature (Tm) frequency (F; days) and accumulated pentad precipitation (P; mm) time series are shown for nine stations (blue dots) in Central America: (1) Philip Goldson International Airport, Belize; (2) Puerto Barrios, Guatemala; (3) Puerto Lempira, Honduras; (4) Puerto Limón, Costa Rica; (5) Tocumen International Airport, Panamá; (6) David, Panamá; (7) Liberia, Costa Rica; (8) Choluteca, Honduras; and (9) Puerto San José, Guatemala. The blue solid line represents the 1981–2010 average values and the red solid line shows 2015 values. Vertical dashed lines depict the mean temperature for 2015 (red) and the 1981–2010 period (blue). Vectors indicate July wind anomalies at 925 hPa (1981–2010 base period). Shading depicts regional elevation (m). (Source: NOAA/NCEI and Central American NWS.)</figcaption></figure>

### (ii) Precipitation

Annual precipitation totals were below normal at all stations on the Pacific slope (Fig. 7.8). At Liberia and Choluteca, the values were extremely low (in the tail of the distribution at the *p* = 0.05 level), and these areas experienced a long dry spell that extended past pentad 50 (beginning of September). Subsequent rains helped increase the accumulations later in the year, but they were not sufficient to move out of the “extremely dry” classification. A similar type of variation also occurred in Tocumen, where lack of precipitation caused an extremely dry condition until around pentad 47 (third week of August), but subsequent rains led to a close-to-normal annual total. The other stations in the Pacific slope (David and Puerto San José) showed no or little indication

of this “late-rains” effect. Stations on the Caribbean slope observed relatively normal accumulations at the end of the year. Puerto Limón was extremely wet most of the time from the beginning of the year to pentad 40 (third week of July). A subsequent reduction of rainfall at this station resulted in moderately wetter-than-normal conditions for the year as a whole.

Low-level moisture appeared sensitive to ENSO conditions. Regional rainfall resembled conditions associated with the development of the El Niño event in 2015. Near-surface moisture flux convergence anomalies were computed based on ERA Interim reanalysis data. Results (not shown) reveal that wetter-than-normal conditions in late 2014 evolved into drier-than-normal after spring 2015.
<table><caption>TABLE 7.1. Summary of events and impacts, including number of fatalities (f), missing people (m), and affected people (a) by country and specific region. [(Sources for the Guatemala landslide in October 2015: www.redhum.org/documento_detail/17300 and the Pacific slope of Central America: OCHA-ROLAC (in Spanish: Oficina de Coordinación de Asuntos Humanitarios-Oficina Regional para América Latina y el Caribe, reliefweb.int/sites/reliefweb.int/files/resources/Crisis%20por%20sequia%20en%20America%20Central%20en%202015.pdf)]</caption><thead><tr><th>Country(ies)</th><th>Dates (2015)</th><th>Hydrometeorological Conditions</th><th>Fatalities (f) Missing People (m) Affected People (a)</th><th>Specific Region</th></tr></thead><tbody><tr><td>Panamá</td><td>22 Sep</td><td>Extreme below-average rains</td><td>Unknown number of affected farmers, 2500 cattle died</td><td>Azuero Peninsula</td></tr><tr><td rowspan="2">Costa Rica</td><td>27-28 Oct</td><td>Floods</td><td>4f</td><td>Central Valley</td></tr><tr><td>19 Nov</td><td>Floods</td><td>1f</td><td>Alajuela and Corredores</td></tr><tr><td>Nicaragua</td><td>2-14 Jun</td><td>Heavy rainfall and floods associated with low pressure systems</td><td>6f, 35000a</td><td>Managua</td></tr><tr><td>El Salvador</td><td>15-20 Oct</td><td>Floods and landslides</td><td>4f, more than 210a</td><td>San Cayetano, Zaragoza, San Miguel, Luis de Moscoso</td></tr><tr><td rowspan="4">Honduras</td><td>07-15 Jun</td><td>Heavy rainfall, landslides and floods</td><td>2f, 2m, 300a</td><td>Tegucigalpa</td></tr><tr><td>16-18 Oct</td><td>Floods</td><td>8f</td><td>Central Honduras</td></tr><tr><td>7-8 Dec</td><td>Floods and landslides</td><td>3f</td><td>Northern Honduras</td></tr><tr><td>15 Dec</td><td>Landslides</td><td>1f</td><td>Cuculmeca</td></tr><tr><td rowspan="3">Guatemala</td><td>7 Jun</td><td>Floods and landslides</td><td>8000a</td><td>Departments of Guatemala, Sacatepéquez, Santa Inés, and San Miguel Petapa</td></tr><tr><td>8 Aug</td><td>Floods associated with a tropical wave</td><td>5f</td><td>Caribbean slope</td></tr><tr><td>13 Oct</td><td>Landslides</td><td>274f, 353m</td><td>El Cambray II Community, and Santa Catalina Pinula</td></tr><tr><td>Pacific Slope of Central America</td><td>Up to 6 Oct</td><td>Extreme below-average rains</td><td>An estimated 3.5 million people affected, with more than 2 million in need of food, medical, and sanitary assistance</td><td>Azuero Peninsula, Panama; Guanacaste, Costa Rica; Pacific slopes of Nicaragua, El Salvador, Honduras, and Guatemala</td></tr></tbody></table>
### (iii) Notable events

Tropical storm activity during 2015 was below average for the Caribbean basin (6°–24°N, 60°–92°W). There were three named storms: Danny, Erika, and Joaquin. Joaquin became a hurricane and reached major hurricane status in early October. No significant impacts were reported for Central America associated with any of these tropical systems. Stronger-than-average Caribbean low-level jet (CLLJ; Amador 1998), 925-hPa winds during July (vectors in Fig. 7.8) were consistent with El Niño (Amador et al. 2006). Central America experienced contrasting hydro-meteorological conditions between the Pacific and Caribbean slopes from January to May. The impacts were severe, but different, across the region (Table 7.1).

2) **CARIBBEAN**—T. S. Stephenson, M. A. Taylor, A. R. Trotman, S. Etienne—LeBlanc, A. O. Porter, M. Hernández, D. Boudet, C. Fonseca, J. M. Spence, A. Shaw, A. P. Aaron-Morrison, K. Kerr, G. Tamar, D. Destin, C. Van Meerbeeck, V. Marcellin, A. C. Joseph, S. Willie, R. Stennett-Brown, and J. D. Campbell

Prevailing El Niño conditions were associated with below-normal annual rainfall and above-normal annual mean temperatures over much of the region (Fig. 7.9). Abundant dry and dusty air from the Sahara Desert in Africa also contributed to the dry weather for the year, particularly during the first six months. The base period for comparisons is 1981–2010.

### (i) Temperature

Some Caribbean countries, including Anguilla, Barbados, Cayman Islands, Cuba, Dominican Republic, St. Kitts and Nevis, St. Maarten, and St. Lucia, experienced above-normal to record temperatures during 2015. The average annual temperatures were the highest on record since 1951 for Cuba (26.6°C)

and second highest since 1946 for Piarco, Trinidad (27.4°C). Other temperature extremes for Piarco include the highest mean maximum temperature since 1946 for October (33.6°C) and November (32.7°C) and the second highest for August (33.6°C). V. C. Bird International Airport, Antigua, recorded its second-highest maximum temperature of 34.6°C (on 30 September) since records began in 1971 and observed a high mean minimum temperature of 24.5°C for the year, tying the record set in 2001 and 2002. Sangster International Airport, Jamaica, recorded its highest mean maximum temperature for May (33.0°C) since 1973, and Crown Point, Tobago, set records for August (33.2°C), September (33.9°C), and November (33.0°C) since records began in 1969. During October–December, record high mean maximum temperatures were observed in Freeport, Bahamas (25.3°C), and Grand Cayman (31.3°C) since 1990 and 1971, respectively, and the highest absolute maximum temperature was observed for Dominica (35.5°C) in the 45-year record.

### (ii) Precipitation

While annual rainfall for 2015 was below normal for most of the Caribbean, contrasting rainfall anomalies were observed in some territories during the first quarter of the year. The January–March rainfall was above normal for Dominican Republic, Grenada, Aruba, Barbados, and eastern Jamaica, and below normal for Anguilla, Antigua and Barbuda, and St. Maarten. St. Thomas, U.S. Virgin Islands, recorded its wettest February (339.1 mm) since 1953. The transition to drier conditions commenced in the second quarter for Aruba, Dominican Republic, and Jamaica, with Dominica, Guadeloupe, St. Kitts, and St. Lucia also recording very dry conditions.

<figure><img src="image_245.png" /><figcaption>**FIG. 7.9.** Annual (a) temperature anomalies (°C) and (b) percent of normal (%) rainfall for 2015 across the Caribbean basin with respect to the 1981–2010 annual mean. (Source: Caribbean Institute for Meteorology and Hydrology and the Instituto de Meteorología de la República de Cuba.)</figcaption></figure>
Dry weather persisted from July to September across much of the Caribbean, including Aruba, Barbados, central Cuba, Grand Cayman, Dominica, southern and eastern Dominican Republic, Grenada, western Jamaica, the Leewards, and St. Lucia, though in August, wet conditions were recorded for Dominica and below-normal to near-normal rainfall for Puerto Rico. This is consistent with a below-normal Atlantic hurricane season (see section 4e2) in relation to El Niño that produced strong vertical wind shear, increased atmospheric stability, and subsidence over the Atlantic. July was the driest on record for St. Maarten (8.4 mm) since 1953 and second driest for St. Thomas (5.6 mm). Tobago had its fifth driest August (83.3 mm) since 1969.

For the last quarter, very dry conditions were recorded in Antigua, Aruba, Dominica, and north-western Dominican Republic, with very wet conditions in northern Dominican Republic and western Puerto Rico. Antigua's all island-averaged rainfall for December was 49.0 mm, its 10th driest on record, and rainfall for the three-month period of October–December was the ninth lowest on record (246.1 mm) since 1928. Record-low October–December rainfall was also observed at a number of stations, including Bowmanston, Barbados, (245.1 mm) since records began in 1981, and Rio San Juan and Villa Vasquez in Dominican Republic (230.7 and 31 mm, respectively) since 1971.

A number of territories and stations recorded their driest year (Table 7.2). The second driest year was observed at Hewanorra, St. Lucia, (1336.6 mm) since 1973 and the third driest for Jamaica (1308.0 mm) since 1881 and St. Croix (586.0 mm) since 1951. Conversely, St. Thomas (1276.4 mm) observed its sixth wettest year on record since 1953.

### (iii) Notable events

Several significant events impacted the Caribbean in 2015:

* Prevailing droughts were observed in Antigua, Barbados, Cuba, Dominica, Dominican Republic, Jamaica, Puerto Rico, St. Kitts and Nevis, and St. Lucia, with widespread agricultural losses and/or very low water production and rationed distribution. St. Lucia declared a water emergency for the period May to August amid continuing drought.

* Water shortage was experienced in the eastern half of Puerto Rico, with San Juan (capital of Puerto Rico) having strict water rationing for much of 2015.

* Low rainfall totals in 2015 in Antigua led to Pot-

<table><caption>TABLE 7.2. List of Caribbean territories and stations that had their driest year in 2015.</caption><thead><tr><td>Station/Country</td><td>Annual rainfall recorded (mm)</td><td>Year records began</td></tr></thead><tbody><tr><td>Antigua</td><td>574.5</td><td>1928</td></tr><tr><td>Aruba</td><td>134.2</td><td>1971</td></tr><tr><td>St. Barths</td><td>465.6</td><td>1971</td></tr><tr><td>St. Maarten</td><td>495.4</td><td>1953</td></tr><tr><td>Tobago</td><td>1064.6</td><td>1969</td></tr><tr><td>Grantley Adams, Barbados</td><td>789.5</td><td>1979</td></tr><tr><td>Santo Domingo, Dominican Republic</td><td>813.8</td><td>1971</td></tr><tr><td>Potsdam, Jamaica</td><td>762.0</td><td>1971</td></tr><tr><td>George F. L. Charles Airport, St. Lucia</td><td>1148.6</td><td>1967</td></tr></tbody></table>

works Dam, with a capacity of 1 billion gallons, being completely dry. There were more bushfires than usual, and 65% of farmers were forced out of business. The drought continued throughout 2015 and was deemed the worst on record. The duration of the drought conditions in Antigua was the second longest of any drought on record and, by far, the greatest deficit of rainfall (records date to 1928). The longest drought occurred in 1964–67, lasting 32 months. The return period for 2015 rainfall is 1 in 500 years.

* On 27 August, flash floods from Tropical Storm Erika caused catastrophic damage across Dominica, dumping over 320.5 mm of rain in 12 hours, with 225.0 mm in less than six hours.

### d. South America

Positive SST anomalies were present along the tropical equatorial Pacific since the beginning of 2015. With the onset of El Niño, SST anomalies increased and expanded along the southeastern Pacific Ocean during the second half of the year. As is typical, El Niño influenced regional weather conditions in South America during most of 2015 (Fig. 7.10).

The annual temperature and precipitation anomalies were computed using data from 1190 stations provided by national meteorological services from South America and processed by El Centro International para la Investigación del Fenómeno de El Niño (CIIFEN). Air temperature was above normal across most of the continent, with anomalies 0.5°–2.0°C (Fig. 7.11a) above average. El Niño impacts across
<figure><img src="image_246.png" /><figcaption>FIG. 7.10. Seasonal mean sea surface temperature anomalies (°C) for 30°N–60°S, 120°–60°W (base period: 1971–2000). Data source: NOAA–NCEP (Processed by CIIFEN, 2016).</figcaption></figure>

<figure><img src="image_247.png" /><figcaption>FIG. 7.11. 2015 South American annual (a) temperature anomalies (°C) and (b) precipitation anomalies (%; base period: 1981–2010). (Sources: Data from 1190 stations provided by National Meteorological Services of Argentina, Brazil, Bolivia, Chile, Colombia, Guyanas, Ecuador, Paraguay, Peru, Suriname, Uruguay, and Venezuela. The data were compiled and processed by CIIFEN 2016).</figcaption></figure>

South America generally include, but are not limited to, drier-than-average conditions across northern South America, with wetter-than-average conditions across the southeast. Dry conditions, observed since 2014, persisted and, in some instances, deteriorated during 2015, especially in northern South America. Above-normal precipitation with severe impacts was observed in southeastern South America (Fig. 7.11b). Along the west coast of South America, the El Niño effects during the last quarter of the year were modulated by regional factors such as the persistent positive sea level pressure anomalies in the southeastern Pacific Ocean and strong winds, which reduced convection near Ecuador and northern Peru.

All anomalies in this section are with respect to the 1981–2010 average unless otherwise noted.

1) **NORTHERN SOUTH AMERICA AND THE TROPICAL ANDES**—R. Martínez, A. Malheiros, J. Arévalo, G. Carrasco, L. López Álvarez, J. Bazo, J. Nieto, and E. Zambrano

This subsection covers Bolivia, Colombia, Ecuador, Peru, and Venezuela.

### (i) Temperature

Above-normal temperatures were predominant across Venezuela throughout the year. In the highlands (Tolima) and Caribbean coast (Cesar) of Colombia, record maximum temperatures were observed in September and December, respectively, with anomalies as high as +5°C. In Ecuador, above-average temperatures were present most of the year, with anomalies of +1.5°C to +2.0°C. Temperatures across Peru were above normal during March–May and June–August. During July and August, above-average temperatures (between +1°C and +4°C) were observed along the coastal zone, in some instances surpassing record high temperatures set in 1998. In Bolivia, temperatures were near- to above normal most of the year. From August to November, at least 12 maximum temperature records were reported at stations in central and eastern Bolivia.

### (ii) Precipitation

Venezuela and Colombia experienced drier-than-normal conditions during 2015. During the first half of the year, anomalous subsidence was the main driver for the lack of precipitation in northern and southeastern Venezuela, which was just 40%–60% of normal. On the Caribbean coast of Colombia a slight precipitation deficit was also observed in this period. During the second half of the year, as a consequence of the El Niño onset, precipitation anomalies were 50%–70% of normal across most of Venezuela.
and as little as 20% of normal in the Andean region (Departments of Tolima, Huila, Cauca, Valle) and Caribbean (central and northern) regions in Colombia. In Ecuador, precipitation was above normal during the first half of the year, with anomalies up to 200% of normal on the central coast. During the second half of the year, precipitation over the Amazon region was 50%-80% of normal; meanwhile, precipitation was 120%-150% of normal in the northern and central coastal regions during September-November. In Peru, extreme below-normal precipitation was observed in the northwest of the country and in the southern Andes. Above-normal precipitation prevailed during the second half of 2015 in the southern and central Amazon region.

In northern Bolivia, precipitation was above normal from January to August, with anomalies up to 159% of normal during March-May. During September-November, 88% of normal precipitation was observed. Over the Altiplano region (western Bolivia), precipitation was predominately above normal with anomalies ranging from 117% to 149% of normal throughout the year. In central Bolivia, precipitation was near normal. Above-normal precipitation (up to 150% of normal) was recorded in southeastern Bolivia during June-August. Below-normal precipitation (63% of normal) was observed during September-November.

### (iii) Notable events

On 24 March, unusually heavy rainfall caused landslides in the District of Lurigancho-Chosica (Lima region), Peru, leading to eight fatalities and destroying over 150 houses.

During April, northwestern Venezuela experienced a week-long heat wave, with some stations registering daily maximum temperatures as high as 40°C (April average maximum temperature is 34.9°C).

Northern Ecuador was affected by flooding during December that caused crop and cattle losses.

Colombia and Venezuela were impacted by a severe drought during most of the year, causing restrictions in water supply for human consumption, agriculture, and hydropower generation.

## 2) TROPICAL SOUTH AMERICA EAST OF THE ANDES—
J. A. Marengo, J. C. Espinoza, J. Ronchail, and L. M. Alves

This region includes Brazil, Paraguay, southern Venezuela, and the Amazon lowland sectors of Peru, Colombia and Bolivia.

### (i) Temperature

Monthly mean temperatures across most of

the region were about 1°-3°C higher than average most of the year. In São Paulo, Brazil, the January mean temperature was 3.5°C above normal—the second warmest January since 1943. In October, temperatures were about 4°-5°C above normal in southeastern and west central Brazil, with the most notable warmth in Rio de Janeiro, which recorded a maximum temperature of 40°C, compared to the average October maximum temperature of 25°C. Maximum temperatures were slightly above average for autumn (March-May) and winter (June-August), with a mean temperature anomaly of +1.0°C. Notable temperatures of 2.0°-3.0°C above average were observed across Paraguay in June.

Various cold fronts during May-September brought well-below-freezing temperatures, hail, and the highest snowfall in 10 years in the Andean region, located more than 3500 meters a.s.l.

### (ii) Precipitation

Below-average rainfall (20%-75% of normal) was observed over southeastern Brazil, eastern Bolivia, and Paraguay during January-March. An atmospheric blocking pattern and a high pressure system over large parts of tropical Brazil and the South Atlantic, together with the absence of the South Atlantic convergence zone during January, were responsible for the lack of precipitation over most of subtropical South America east of the Andes, which lasted through mid-February. Between April and December, rainfall totals of 20%-50% of normal were recorded in northeastern Brazil, north-central Amazonia, eastern Peru, and the Amazon lowland sectors of Colombia and Venezuela. A weak and/or anomalously northward displaced intertropical convergence zone contributed to the below-average precipitation.

### (iii) Notable events

Drought conditions in southeastern Brazil that began in January 2014 (Nobre et al. 2016) continued through April 2015, particularly over the Cantareira reservoir system, which supplies water to nearly half of São Paulo's population (about 18 million residents). Summer (December-February 2014/15) rainfall was marginally less than average. However, during November and December 2015, above-average rain (100-150 mm month⁻¹ above normal) fell over the region, allowing the Cantareira Reservoir system to recover its volume.

The drought conditions that started in 2012 in northeast Brazil continued to persist in 2015, however, with less severity (Fig. 7.12a). Figure 7.12b shows that very dry conditions were present across the northern
<figure><img src="image_248.png" /><figcaption>FIG. 7.12. (a) Average rainfall anomalies (mm month⁻¹) during the peak rainy season (Feb–May) in northeast Brazil for 1951–2015. (Source: Global Precipitation Climatology Centre; updates from Marengo et al. 2013.) (b) Categories of observed precipitation based on percentiles for northeast Brazil during the hydrological year Oct–September (b) 2011/12, (c) 2012/13, (d) 2013/14, and (e) 2014/15. (Source: CEMADEN.)</figcaption></figure>

part of the state of Bahia, and particularly in the semiarid region of northern northeast Brazil and the region between southern Bahia and the northern parts of the state of Minas Gerais. The extreme dry conditions observed in this region contributed to an increase in wildfires and damages to crops, with local residents depending on water to be trucked in.

Between January and April, 32000 families were affected by heavy rains in the lowlands of Bolivia, with the worst impacts occurring on 20 February when the Acre River flooded the city of Cobija, capital of Pando in western Amazonia.

As a result of heavy rains in the northwesternmost Amazonian regions (north of the Peruvian Amazon and western state of Amazonas in Brazil), the Peruvian government declared a state of emergency on 9 April. During March and April, more than 115000 people were affected by floods. Also, in April, flood-

ing and landslides affected more than 20000 people in Colombia. On 29 June, heavy rainfall in southern and southwestern Venezuela caused flooding, with more than 40000 people affected. On 4 April, a severe storm hit several towns in the department of Concepción in northern Paraguay, affecting houses, crops, and farm animals. Authorities estimate that 5000 people were affected. Precipitation patterns shifted in October, as is typical during the presence of El Niño in the tropical Pacific Ocean (see section 4b), resulting in above-average rainfall across the same region. Abundant rainfall over southern Brazil and most of the La Plata basin caused significant floods.

During 8–10 July, minimum temperatures between –18°C and –22°C were measured in high areas of the Arequipa, Moquegua, Tacna, and Puno regions of the Peruvian southern Andes. According to the Empresa de Pesquisa Agropecuária e de Extensão Rural of the state of Santa Catarina (EPAGRI) in southern Brazil, the same cold spell affected the southern region of Brazil, with minimum temperatures ranging between –3.0°C and 2.0°C in the highland city of São Joaquim on 5 July, compared with the average July minimum temperature of 6.1°C.

The above-normal rainy season in southeastern South America, which typically starts in October and ends in May, was 100–300 mm above normal in December 2015, leading to floods in Paraguay, Bolivia, and southern Brazil due to the overflow of the main rivers. The highest levels in 110 years were recorded along the Paraguay River, which produced slow-onset flooding that forced the evacuation of 18545 families in the city of Asunción. Four people died and 130000 were evacuated by the end of the year.

3) SOUTHERN SOUTH AMERICA—M. Bidegain, J. L. Stella, M. L. Bettolli, and J. Quintana

Argentina, Chile, Uruguay, and adjacent areas of southern Brazil are considered here.

### (i) Temperature

Above-normal temperatures were observed over most of southern South America (SSA) during 2015, with mean temperature anomalies between +0.5°C and +1.5°C (Fig. 7.11a). According to preliminary analysis of the official data for 2015, the mean temperature anomaly for Argentina and Uruguay was estimated to be +0.71°C and +0.51°C, respectively. Argentina had its second warmest year in the country's 55-year period of record, behind 2012, with the past four years (2012–15) the four warmest on record. The cities of Buenos Aires, Iguazú, Santa Fé, Rosario, and Pehuajó were each record warm in 2015. Chile observed warmer-than-
average monthly temperatures most of the year. The largest positive annual anomalies were observed in the northern (+1.1°C) and central (+1.0°C) regions; however, September and October were cooler than average in the central and southern regions. Above-normal maximum temperatures were observed in Chile, particularly in the central region, with anomalies between +1.0° and +1.5°C.

Summer (December–February) 2014/15 had near-average temperatures, with no significant heat waves observed across Argentina and Uruguay. In Chile, anomalies of –0.8°C were observed across the north coast.

Autumn (March–May) was extremely warm. The most notable warmth was observed during April and May, with mean temperature anomalies as high as +2.0°C and +2.5°C in central Argentina and Uruguay, respectively. Argentina observed its warmest autumn since national records began in 1961, with a mean temperature 1.51°C above average. Chile had above-average temperatures during March–May, with much of the central to northwest regions 1.5°–3.0°C above average.

Above-average temperatures were observed across much of SSA during winter (June–August), with the most notable warmth across northeastern Argentina, Uruguay, southern Brazil, and Chile, where mean temperatures anomalies were as high as +3.0°C. Argentina also had its warmest winter on record. Much warmer-than-average conditions dominated the country during August, with many locations experiencing record high temperatures.

Below-average temperatures were present across Argentina, Uruguay, and Chile during spring (September–November). In Chile and central and southern Argentina, an increase in frequency of frontal systems and abundant cloudiness resulted in the region's coldest October on record. In Argentina, anomalies were 6°–7°C below average in some areas and more than 35% of stations set new daily low temperature records. Extremely cold conditions, including rare snowfalls and late frosts, affected Buenos Aires province during September and the Cuyo region during October.

### (ii) Precipitation

Drier-than-average conditions were observed during January–July, especially from March to July, in eastern Argentina (Corrientes, Entre Ríos, and Buenos Aires provinces), northeastern Argentina (Misiones province), Uruguay, and central Chile. During August–December, above-average precipitation fell across central and northeastern Argentina,

northern Uruguay, southern Brazil, and central Chile, as is typical during El Niño. The 2015 annual rainfall for Argentina and Uruguay was 109% and 103% of normal, respectively, and marked the second consecutive year since 2013 in which precipitation was above average in Argentina. However, some regions south of 34°S in Uruguay and Buenos Aires province recorded below-normal precipitation in 2015. As a result of severe water deficit, the Minister of Agriculture in Uruguay declared an “agricultural emergency” in May to assist farmers. Santiago, the capital of Chile, had its driest June on record, with no precipitation recorded for the first time since records began in 1866. During the second half of 2015, especially during October–December, some locations in northeastern Argentina and northern Uruguay were severely affected by floods, especially cities located near the Paraná and Uruguay Rivers.

### (iii) Notable events

Some areas of southern Chile experienced their driest January in at least 65 years. In northern Chile, unusually heavy rainfall during 24–26 March impacted the extremely dry regions of Atacama and Antofagasta. Some areas received well over their annual rainfall during this event. Antofagasta received 24.4 mm of rainfall in a 24-h period during 25–26 March (normal annual average rainfall for this location is 1.7 mm). Three people were killed by the impacts of the floods in Antofagasta and 23 people perished in Atacama.

Heavy precipitation fell across parts of northeastern Argentina in August. The downpours overflowed rivers and produced floods. The highest rainfall totals during August were in eastern Argentina, mainly in the south of the province of Corrientes, Entre Ríos, and northeast of Santa Fé, where values reached 300 mm. There was also significant precipitation in the province of Buenos Aires, with 200–250 mm recorded in August. Many other locations set new August precipitation total records (Table 7.3).

During December, abundant precipitation fell over northeastern Argentina and Uruguay, with several locations setting new records for the month (Table 7.4). Heavy rainfall mainly affected Corrientes and Misiones provinces in Argentina, with thousands of people forced to evacuate.

Above-normal temperatures and below-normal rainfall at the beginning of 2015 in Patagonia (southern Argentina) favored the development of one of the largest wildfires in the history of Argentina. The fire lasted nearly two months and burned 41 000 hectares of native forests.
<table><caption>TABLE 7.3. Locations in Argentina that set new August precipitation totals (mm) in 2015.</caption><thead><tr><th>Locations</th><th>2015 Record (mm)</th><th>Previous Record (mm)</th></tr></thead><tbody><tr><td>Reconquista</td><td>330.2</td><td>138.8 (1956)</td></tr><tr><td>Mercedes Aero</td><td>170.0</td><td>134.3 (1975)</td></tr><tr><td>Paso de los Libres Aero</td><td>188.0</td><td>182.9 (1971)</td></tr><tr><td>Monte Caseros Aero</td><td>262.6</td><td>218.0 (1972)</td></tr><tr><td>Concordia Aero</td><td>358.8</td><td>198.0 (2012)</td></tr><tr><td>Junin Aero</td><td>201.0</td><td>151.4 (1976)</td></tr><tr><td>San Fernando</td><td>252.1</td><td>237.1 (2012)</td></tr></tbody></table>

<table><caption>TABLE 7.4. Locations in Argentina that set new December precipitation totals (mm) in 2015.</caption><thead><tr><th>Locations</th><th>2015 Record (mm)</th><th>Previous Record (mm)</th></tr></thead><tbody><tr><td>Formosa</td><td>425.3</td><td>357.5 set in 1979</td></tr><tr><td>Posadas Aero</td><td>466.9</td><td>416.1 set in 2012</td></tr><tr><td>Oberá</td><td>477.0</td><td>447.5 set in 2012</td></tr><tr><td>Mercedes Aero</td><td>458.1</td><td>337.0 set in 1968</td></tr><tr><td>El Calafate</td><td>42.2</td><td>30.5 set in 2012</td></tr></tbody></table>

### e. Africa

In 2015, most of Africa experienced above-average temperatures and below-average precipitation. Extreme weather caused loss of life and property damage in many parts of the continent. This extreme weather included torrential rains across western Africa and heavy rainfall related to a tropical storm over western Indian Ocean island countries. In contrast, eastern African countries, including Ethiopia, Somalia, and parts of Kenya, were impacted by drought. The drought in Ethiopia, the worst in several decades, was associated with the El Niño that developed early in the year. Extreme high temperatures were observed over northern, southern, and southwestern parts of Africa.

The 2015 climate assessment for Africa is based on the 1981–2010 reference period. Both observed and reanalysis datasets are presented for analysis.

#### 1) NORTHERN AFRICA—K. Kabidi, A. Sayouri, M. ElKharrim, A. Ebrahim, and A. Mekonnen

Countries considered in this region are Morocco, Algeria, and Egypt. Overall, below-normal precipitation and above-normal temperature conditions dominated during 2015. The annual temperature was the warmest since 1960 over Morocco, and successive heat waves were observed both during winter and summer in Egypt. Heavy downpours were reported in May and August 2015 in Morocco.

#### (i) Temperature

The annual mean maximum temperature over northwestern Morocco was about 1°C higher than normal. However, temperatures during January and February were markedly below average in association with a cold air surge from the Black Sea to the Maghreb (northwestern African countries). In January, temperatures were 2.4°C below normal in northeastern Morocco. In February they were 2.7°C below normal in southern Morocco. Generally, the winter (December–February 2014/15) mean surface seasonal temperatures over Algeria and Morocco were about 1°C below normal (Fig. 7.13), while winter surface temperatures over Egypt were mainly above normal. However, minimum temperatures as low as 1°C were observed in January in northeastern Egypt.

Temperatures during spring, summer, and autumn were all above normal in Morocco and Algeria. The average mean monthly temperature in Morocco and Algeria was 3°C above normal in May (Fig. 7.14). Overall, summer temperatures in Egypt were above normal, while isolated locations recorded below-average temperatures.

#### (ii) Precipitation

Annual precipitation was marked by deficits over southern Egypt and surpluses over the northern regions. Winter precipitation was about 50% of normal over western Egypt, while heavy rainfall events

<figure><img src="image_249.png" /><figcaption>FIG. 7.13. Dec–Feb 2014/15 mean temperature anomaly (°C; base period 1981–2010). (Source: NCEP–NCAR reanalysis.)</figcaption></figure>

<figure><img src="image_250.png" /><figcaption>FIG. 7.14. May 2015 mean temperature anomaly (°C; base period 1981–2010). (Source: NCEP–NCAR reanalysis.)</figcaption></figure>
were observed in January. Winter precipitation over Morocco was also highly variable. The average deficit in Morocco was about 89% of normal in January and 71% of normal in February (Fig. 7.15). Lack of rainfall was associated with dominant atmospheric high pressure conditions on the Moroccan Atlantic coast and in western Europe.

Monthly precipitation in spring was generally below normal in Morocco. However, above-normal rainfall ranging between 145% and 230% of normal was observed in March across central Morocco. New 24-h rainfall records ranging between 20 and 55 mm were observed during 23–25 May at various places in Morocco.

Convective precipitation brought extreme weather conditions in summer, especially during July and August, leading to excess rainfall, with an average amount of around 158% of normal over Morocco. Total precipitation received during August was well above normal (e.g., 45 mm at Marrakech compared to the normal of 2.7 mm; 23.2 mm at Sidi Ifni compared to the normal of 2.1 mm).

Unlike the recent autumns of 2013 and 2014, which were marked by a series of above-normal rainy conditions, autumn precipitation in 2015 was generally below normal over most of Morocco. Monthly rainfall ranged from 7% of normal at Casablanca to about 86% of normal at Midelt.

### (iii) Notable events

During January and February, a series of cold spells affected the region, resulting in heavy snow. Three meters of snow fell over northeastern Morocco during February, the highest total for February in the past 30 years. In Egypt, Alexandria received much-above-normal rainfall in October (238% of normal). A record rainfall of 127 mm was observed on 6 October 2015 at Alexandria.

Conversely, May, July, and August were marked by several heat waves (defined as daily maximum temperatures much higher than the daily mean),

resulting in high maximum temperatures. These heat waves were associated with continental dry air intrusions from the intense heat source in the Sahara. The heat waves, associated with an east wind, caused several forest fires, which devastated hundreds of hectares of forest, especially in northern Morocco. In Luxor, Egypt, a record temperature of 48°C was observed on 28 May.

## 2) WEST AFRICA—S. Hagos, I. A. Ijampy, F. Sima, S. D. Francis, and Z. Feng

West Africa refers to the region between 17.5°W (eastern Atlantic coast) and approximately 15°E (along the western border of Chad) and north of the equator (near Guinea coast) to about 20°N. Countries included are Senegal, the Gambia, Guinea-Bissau, Guinea, Sierra Leone, Liberia, southern regions of Mali and Niger, Burkina-Faso, Côte d'Ivoire, Ghana, Togo, Benin, Cameroon, and Nigeria. It is often divided into two climatically distinct sub regions: the semiarid Sahel region (north of about 12°N) and the relatively wet coast of Guinea region to the south.

### (i) Temperature

The annual mean temperature over West Africa was slightly above the 1981–2010 average with much of the northwestern Sahel region about 0.5°C above average. In May, much warmer-than-average conditions were reported over the region, with record warmth observed in Togo, Benin, and Burkina Faso. The majority of northern cities in Nigeria experienced above-average mean temperatures. Minna, Yelwa, Zaria, Katsina, and Kano experienced the highest annual mean temperature departures for 2015, as did Benin, Ikom, Ondo, and Warri in the South. Similarly, record high temperatures were observed across eastern Senegal in June, while Sierra Leone, central Mauritania, and eastern Nigeria recorded temperatures up to 3°C above normal in July (Fig. 7.16). The maximum temperature over the western part of The Gambia was higher than normal (by 3%–6%), while the minimum temperature increased by 5%–8% compared with normal in the central and eastern part of the country. Warmer-than-average conditions persisted over most of West Africa during August and September.

### (ii) Precipitation

Wetter-than-average conditions persisted over most of the Sahel region. Rainfall totals for June–September, during which time the West African monsoon provides much of the annual precipitation, are shown in Fig. 7.17a. Relatively dry conditions prevailed over most of the coast of the Gulf of Guinea

<figure><img src="image_251.png" /><figcaption>FIG. 7.15. Dec–Feb 2014/15 mean precipitation anomaly (mm day⁻¹; base period 1981–2010). (Source: NCEP–NCAR reanalysis.)</figcaption></figure>
<figure><img src="image_252.png" /></figure>

**FIG. 7.16.** Temperature anomalies (°C) for West Africa in Jul 2015 (base period: 1981–2010). (Source: NOAA–NCEP reanalysis.)

<figure><img src="image_253.png" /></figure>

**FIG. 7.17.** (a) Jun–Sep 2015 precipitation (mm) for West Africa as total accumulated precipitation. The red dashed and solid lines mark 100 mm and 600 mm isohyets. (b) Jun–Sep 2015 precipitation anomaly, departure from 1981–2010 normal. (Source: NOAA–NCEP Reanalysis.)

region from Liberia to Cameroon. Specifically, much drier-than-normal conditions over the Niger Delta and wetter-than-normal conditions in the Lake Chad region were observed during summer. Rainfall over most parts of Nigeria was near normal. However,

wetter-than-normal conditions were experienced over parts of central and northern Nigeria and drier conditions over pockets in the southwestern and eastern parts. The Gambia experienced a late onset of rains with late withdrawal and, overall, received above-normal rainfall for the season. Significant rainfall amounts prevailed during July–September, with the highest amounts, between 275 and 475 mm, recorded in August. The greater part of The Gambia experienced significant annual rainfall, ranging from 750 mm to more than 1000 mm. The country average seasonal rainfall during 2015 stood at 960.5 mm, 136% of the 1981–2010 mean (705.1 mm). The above-average rainfall over much of West Africa resulted in an above-average harvest according to the Famine Early Warning Systems Network. The dipole-like precipitation with a dry Guinean coast and wet Sahel region (Fig. 7.17b) often occurs as the intertropical convergence zone (ITCZ) precipitation is shifted farther north due to warmer SSTs over northeastern subtropical Atlantic and cooler-than-average SST conditions over the southeastern subtropical Atlantic (e.g., Hagos and Cook 2008). This condition persisted throughout the summer, especially notable during August and then into September. El Niño, typically associated with dry conditions over the Sahel (Janicot et al. 1998), had relatively little impact this year.

### (iii) Notable events

In northern Nigeria, torrential rain led to the failure of a dam in August. According to the UN Office for the Coordination of Humanitarian Affairs, 300 000 people were affected by the associated floods associated. Flash floods were also reported in some states. The floods led to 53 fatalities and destruction of property in about 11 states, and displaced about 100 000 people from their homes.

In early June, Togo, Benin, and Ghana experienced significant flooding; on 3 June, 84 mm of rain fell in Cotonou, Benin, in a 24-h period. Local media reported that flooding damaged several homes and blocked streets in the largest city and economic center of Benin.

The 2015 wet season (July–September) for The Gambia was characterized by several extreme events, including floods, lightning, and windstorms, resulting in loss of life and significant disruption in livelihood.

### 3) EASTERN AFRICA—G. Mengistu Tsidu

Eastern Africa refers to countries located within 20°–50°E and 15°S–20°N. The region is comprised of the Sudan, South Sudan, Ethiopia, Eritrea, Djib
bouti, and north and central Somalia, which are located north of 5°N, with the main rainfall season in June-September; southern Somalia, Kenya, northern Tanzania, Uganda, Rwanda, and Burundi, located between 5°N and 5°S, with the main rainfall season in March-May; and central and southern Tanzania, located south of 5°S, with the main rainfall season in December-February. Note also that Somalia, Kenya, northern Tanzania, Uganda, Rwanda, Burundi, and southern and southeastern Ethiopia receive a significant portion of their annual rainfall in autumn, with a peak rainfall shifting from October over Ethiopia and Somalia to November over the rest of the countries following the annual migration of the ITCZ. Therefore, rainfall analysis is also included for the extended September-December rainfall season.

The assessment for this region is based on rainfall from the latest version-2 Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data and European Centre for Medium-Range Weather Forecasts (ECMWF) Interim re-analysis (ERA-Interim) daily mean temperatures at a horizontal resolution of 0.25°.

### (i) Temperature

The December-February 2014/15 mean temperature was above normal over Sudan, Eritrea, western Ethiopia, Djibouti, Uganda, Rwanda, Burundi, most parts of Kenya, and northwestern Tanzania (Fig. 7.18a). Near-normal temperatures over the eastern half of Ethiopia and cold anomalies of up to -2°C were observed over part of northern Tanzania. The warm anomalies observed in December-February expanded eastward to cover most parts of Ethiopia while cold anomalies over Tanzania during the same season expanded northeastward to cover Kenya, southeastern Ethiopia, and Somalia during March-May (Fig. 7.18b). During June-August, the whole region experienced warm anomalies exceeding +2°C, with the exception of some pockets over northern Tanzania, western Kenya, and southwestern Ethiopia, which

reported normal to below-normal temperatures (Fig. 7.18c). The mean temperature remained above normal during September-November over most parts of the region, with the exception of below-normal temperatures at places in northern Tanzania and along the Ethiopia-Somalia border (Fig. 7.18d).

### (ii) Precipitation

During December-February 2014/15, southern Uganda, Rwanda, Burundi, northern Tanzania, and southern Kenya received substantially below-normal rainfall. However, some places in Tanzania and southern Kenya along the coast received 110%-150% of their normal precipitation (Fig. 7.19a). Rainfall during March-May was normal to above normal

<figure><img src="image_254.png" /><figcaption>FIG. 7.18. Eastern Africa seasonally averaged mean temperature anomalies (°C) for (a) DJF 2014/15 and (b) MAM, (c) JJA, and (d) SON 2015, with respect to the 1981-2010 base period.</figcaption></figure>
<figure><img src="image_255.png" /><figcaption>**FIG. 7.19.** Eastern Africa seasonal total rainfall (% of average) for (a) DJF 2014/15 and (b) MAM, (c) JJAS, and (d) SOND 2015, with respect to the 1981–2010 base period.</figcaption></figure>

over southwestern and southeastern lowlands of Ethiopia, adjoining areas over South Sudan, most parts of Somalia, Kenya, and Tanzania except for small pockets over the southern tip of Tanzania, the southeastern highlands of Ethiopia and southeastern Ethiopia, and Somalia border areas, which received 50%–90% of normal rainfall (Fig. 7.19b). Most parts of Ethiopia, with the exception of southeastern lowlands, South Sudan, and southern parts of the Sudan, receive their main rainfall during June–September. However, below-average rainfall, associated with the strong El Niño event (see section 4b), dominated the region in 2015. As a result, northern, central, and southeastern Ethiopian highlands received 50%–90% of their normal rainfall. The most affected north-eastern highlands of Ethiopia received as little as

30% of normal rainfall (Fig. 7.19c). The dry conditions persisted during the usual September–December rainfall season over central and southeastern highlands of Ethiopia (Fig. 7.19d).

### (iii) Notable events

The failure of rainfall in Ethiopia in the summer of 2015, attributed to El Niño, led to the worst drought in decades, as reported by media outlets and later confirmed by the government of Ethiopia. According to the UN Office for the Coordination of Humanitarian Affairs, about 8.2 million people were in need of emergency food aid in Ethiopia.

The 2015 drought event can be illustrated using the standardized precipitation index (SPI) which provides a better representation of abnormal wetness and dryness than many other indices (Guttman 1998; McKee et al. 1993, 1995; Hayes et al. 1999). To account for the accumulation of drought effects over time, the SPI on 3-, 6-, 9-, and 12-month time scales during October 2014–September 2015 are considered based on the climatology of 1981–2015 for the region. Figure 7.20a shows 3-month SPIs from July to September 2015, which reveal moderate (SPI values between –1.0 and –1.49) to extreme (SPI values less than –2.0) drought over central, northern, and south-

eastern Ethiopian highlands as well as central Rift Valley of Ethiopia. Southern South Sudan and adjoining northern Uganda experienced moderate to severe (SPI values between –1.5 and –1.99) drought. However, the moderate to severe drought disappeared in the 6-month-SPI (April–September 2015) over these areas while the moderate to extreme drought over Ethiopia persisted (Fig. 7.20b). The moderate to extreme drought over Ethiopia continued to prevail in the 9-month (January–September 2015) and 12-month (October 2014–September 2015) SPIs (Figs. 7.20c,d) consistent with the prolonged observed rainfall anomalies in 2015 over Ethiopia. Thus, both the observed rainfall anomalies during the different seasons and the SPI confirm the failure of rains over a longer period of time.
<figure><img src="image_256.png" /><figcaption>FIG. 7.20. SPI indices for eastern Africa for Oct 2014–September 2015 at (a) 3-month, (b) 6-month, (c) 9-month, and (d) 12-month times scales, based on 1981–2015 rainfall climatology.</figcaption></figure>

4) SOUTHERN AFRICA BETWEEN 5° AND 30°S—
G. Mengistu Tsidu

This region comprises countries bordering the Ka-
lahari Desert within 5°-30°S and 10°-40°E, including
Angola, Zambia, Botswana, Zimbabwe, and Namibia.
The climate ranges from semiarid and subhumid in
the east to arid in the west. Also included are Malawi
and Mozambique, located in the east, with climate
conditions ranging from dry to moist subtropical
to midlatitude types. This region is located between
two semipermanent high pressure systems over the
South Atlantic and south Indian Oceans. The region
is prone to frequent droughts and uneven rainfall
distribution with two distinct seasons: a wet season
from roughly November to April and a dry sea-

son roughly from May to October.
The east coast is influenced by the
southward-flowing Mozambique
Current, which brings warm water
and humid air from the equator and
creates a humid, warm climate while
the west coast is influenced by the
cold Benguela Current from the At-
lantic Ocean, which produces a drier
climate. Total seasonal rainfall ex-
hibits a strong spatial gradient along
an axis oriented southwestward
from above 700 mm over Zambia,
Malawi, and Mozambique to below
25 mm over southern and eastern
Namibia, southeastern Botswana,
and eastern Angola during the peak
rainy period of December–February
(not shown).

Analyses are based on the same
data sources as for section 7e3.

(i) *Temperature*

During December–February 2014/15, temperatures were well above normal over southern Angola, much of Namibia, and Botswana, and moderately above normal along the border between Malawi and Zambia (Fig. 7.21a). In contrast, the rest of the region had normal to below-normal temperatures. Warm anomalies exceeding +2°C were observed over the region bordering Namibia, Botswana, and Angola. The warm anomalies in the southwestern part of the region expanded eastward in March–May (Fig. 7.21b)

and covered nearly the whole region in June–August (Fig. 7.21c) and September–November (Fig. 7.21d). The only exceptions were near-normal temperatures over areas that extended from the Mozambique–Zimbabwe border to close to the Mozambique–Malawi border during June–August and northern Angola and Zambia during September–November. Extreme warm anomalies exceeding +2°C during this period covered wider areas including the western half of Botswana, eastern half of Namibia, and southern part of Angola and Zambia (Fig. 7.21d).

(ii) Precipitation

In December–February, southern Africa received
substantially lower-than-normal rainfall with the
<figure><img src="image_257.png" /></figure>

**FIG. 7.21.** Southern Africa seasonally-averaged mean temperature anomalies (°C) for (a) DJF 2014/15 and (b) MAM, (c) JJA, and (d) SON 2015, with respect to the 1981–2010 average.

Anomaly (°C)

exception of an isolated zonal band of normal to wet anomalies over northern Zimbabwe bordering Zambia and Mozambique, extending across Malawi to eastern Mozambique (Fig. 7.22a). Scattered normal-to-wet anomalies were observed in March–May (Fig. 7.22b) and June–August (Fig. 7.22c). The whole region received below-normal rainfall again during September–November (Fig. 7.22d). The deficit during this period is significant, as October and November constitute part of the extended climatological rainy period. Thus, overall rainfall over southern Africa was below normal in 2015.

### (iii) Notable events

The below-normal rainfall was also investigated using the standardized precipitation index (SPI) on the 3-, 6-, 9-, and 12-month time scales from May 2014 to April 2015 which encompasses the peak rainy months over the region based on the climatology of 1981–2015 (not shown). The analyses revealed the presence of moderate to severe drought over the northern half of the region. On 10 November, the BBC reported that, as a result of the drought, significant portions of the population in Malawi and Zimbabwe needed food aid, citing a UNICEF assessment.

Southern Hemisphere heat waves were observed during SON over much of the region. The 90th percentile of heat wave duration (TXHW90, the maximum number of consecutive days with maximum temperatures higher than the 90th percentile calculated for each calendar day based on the 1981–2010

<figure><img src="image_258.png" /></figure>

**FIG. 7.22.** Southern Africa seasonal total rainfall (% of normal) for (a) DJF 2014/15 and (b) MAM, (c) JJA, and (d) SON 2015, with respect to the 1981–2010 average.

normal using running 5-day windows) is used (de Lima et al. 2013; Zhou and Ren 2011). In 2015, the longest period of consecutive days warmer than the 90th percentile of the normal maximum was, on average, more than 20 days over northern Namibia during September–November (Fig. 7.23d). Large parts of Botswana, Namibia, and southern Angola experienced 9- to 15-day periods warmer than the 90th percentile of normal maximum. There were warm anomalies of longer duration during other seasons over approximately the same areas (Figs. 7.23a–c).

## 5) SOUTH AFRICA—A. C. Kruger and C. McBride

The year 2015 was dominated by dry and abnormally hot conditions over most of the country.

### (i) Temperature

In some parts of interior South Africa, mean maximum temperature deviations for January were more than 3°C above normal. Many areas in Western Cape, Free State, Limpopo Province, and Northern Cape had maximum temperature deviations in excess of +2° to +3°C during the first three months of the year.

The annual mean temperature anomaly for 2015 (based on data from 26 climate stations) was 0.86°C above the reference period (1981–2010), making it the warmest year for South Africa since records began in 1951 (Fig. 7.24). A warming trend of 0.14°C decade⁻¹ is indicated by the data of these particular climate stations, statistically significant at the 5% level.
<figure><img src="image_259.png" /></figure>

**FIG. 7.23.** The 90th percentile TXHW90 anomalies (in days) for Southern Africa during (a) DJF 2014/15 and (b) MAM, (c) JJA, and (d) SON 2015, with respect to the 1981–2010 climatology.

#### (ii) Precipitation

Figure 7.25 presents the annual rainfall anomalies for 2015 compared to the 1981–2010 reference period. The most significant feature was below-normal rainfall across most of the country, with particularly dry conditions in northern KwaZulu-Natal province, the far northeast and western North West, and northeastern Northern Cape provinces.

The beginning of the year was characterized by dry conditions in the western and northwestern interior and, due to below-normal rainfall conditions during the 2014/15 austral summer rainfall season, the northern and northeastern parts were already classified as very dry.

In June and July, the western half of the country, as well as some parts in the east, got temporary relief from the dry conditions, with most places receiving more than double their average rainfall for the month. In September the rainy season in the summer-rainfall areas commenced well, with comparatively high rainfall totals reported in the northern interior. However, (austral) spring and beginning of summer of 2015 had dry conditions accompanied by recurring heat waves in many places.

The July–June 2014/15 period was on average the driest season for South Africa since 1991/92 and the third driest since 1932/33.

#### (iii) Notable events

With drought conditions firmly in place, by February

<figure><img src="image_260.png" /></figure>

**FIG. 7.24.** Annual mean temperature anomalies (°C; base period 1981–2010) of 26 climate stations in South Africa, as indicated in the map, for the period 1951–2015. The linear trend is indicated. (Source: South African Weather Service.)

<figure><img src="image_261.png" /></figure>

**FIG. 7.25.** Rainfall anomalies (% of normal; base period 1981–2010) for South Africa during 2015 (Source: South African Weather Service.)

some agricultural organizations requested that provinces, such as North West, be declared drought-stricken. In KwaZulu-Natal, a substantial loss in the sugarcane yield was expected, while water restrictions were in place over much of the province. By March, other provinces also considered applying to be declared drought-stricken areas, including the Western Cape, Free State, and Limpopo Province. The provinces of Northern Cape, North West, KwaZulu-Natal, Mpumalanga, and Limpopo, and the Free State were all declared drought disaster areas in November. By the end of (austral) summer, the prolonged drought conditions severely affected maize, sugar cane, and sorghum harvests.

In the spring, record high temperatures were broken on a regular basis, with Vredendal recording a temperature of 48.4°C on 27 October 2015, setting a new global record for the highest temperature ever observed for this month. The previous highest maximum temperature for this station was 42.5°C,