JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, D05108, doi: /2009jd011706, 2010

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1 Click Here for Full Article JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115,, doi: /2009jd011706, 2010 Changes in synoptic weather patterns and Greenland precipitation in the 20th and 21st centuries: 2. Analysis of 21st century atmospheric changes using self-organizing maps Keah C. Schuenemann 1 and John J. Cassano 2 Received 4 January 2009; revised 13 September 2009; accepted 2 October 2009; published 13 March [1] Using a three-model ensemble, predictions of increasing Greenland precipitation over the 21st century are analyzed using self-organizing maps (SOMs). The models that make up the three-model ensemble (CCCMA-CGCM3.1(T63), MIROC3.2(hires), and MPI- ECHAM5), which are all atmosphere-ocean global circulation models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report, were chosen due to their ability to best reproduce North Atlantic surface synoptic climatology and Greenland precipitation from ERA-40. Daily sea level pressure and precipitation data from model simulations for years , , and are compared, where future simulations are based on the SRES A1B emissions scenario. Results indicate that the North Atlantic storm track is predicted to shift northward through the 21st century and Greenland precipitation is predicted to increase from 35.8 cm yr 1 to 45.8 cm yr 1 by the end of the 21st century, a 27.8% increase. The precipitation change is attributed to changes in atmospheric circulation, which are due to changes in synoptic pattern frequency of occurrence, and changes in the amount of precipitation that occurs when a given synoptic circulation pattern occurs, termed intrapattern variability, during the future time periods. The northward shift in storm track results in less precipitation being produced dynamically over the southeast coast of Greenland, but an increase in precipitation over the remainder of the ice sheet, with largest increases over the southwest coast of Greenland and the eastern region. Intrapattern variability changes, however, dominate the future precipitation changes, accounting for 82.5% of the total change. This is due to an increase in precipitable water in the atmosphere in response to rising temperatures. Changes in sea ice and ocean temperature are also thought to contribute to this change. Citation: Schuenemann, K. C., and J. J. Cassano (2010), Changes in synoptic weather patterns and Greenland precipitation in the 20th and 21st centuries: 2. Analysis of 21st century atmospheric changes using self-organizing maps, J. Geophys. Res., 115,, doi: /2009jd Introduction [2] The fate of the Greenland ice sheet under global warming conditions lies in the magnitude of changes in the terms that make up the mass balance equation for the ice sheet. These terms, all predicted to increase under higher global temperatures, are precipitation, evaporation and sublimation, melt, and ice sheet dynamics. The ice sheet s potential to raise sea level by 7.2 m if eliminated [Church et al., 2001] motivates further analysis of these terms. This 1 Earth and Atmospheric Sciences, Metropolitan State College of Denver, Denver, Colorado, USA. 2 Cooperative Institute for Research in Environmental Sciences and Department of Atmospheric and Oceanic Sciences, University of Colorado at Boulder, Boulder, Colorado, USA. Copyright 2010 by the American Geophysical Union /10/2009JD paper will focus solely on changes in the input term to the mass balance equation, Greenland precipitation. Currently, precipitation on the Greenland ice sheet is not enough to balance the loss terms and the ice sheet as a whole is experiencing a net loss of mass equivalent to 0.21 ± 0.07 mm yr 1 sea level rise [Alley et al., 2007]. [3] A changing climate will undoubtedly affect the magnitude of precipitation produced over the Greenland ice sheet through the 21st century and beyond. Several mechanisms in the climate system will act to change Greenland precipitation. Atmospheric changes are the focus of this research, but changes in the land, cryosphere, and ocean systems are already integrated into the coupled atmosphereocean models used for this analysis. Atmospheric changes can be summarized into two main categories, the changing atmospheric circulation patterns of the Northern Hemisphere, and the increasing availability of atmospheric precipitable water due to the amplification of the hydrological 1of18

2 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 cycle. These two major atmospheric changes are driven by a complex system of feedbacks in the climate system. [4] A change in the atmospheric circulation of the Northern Hemisphere would change Greenland precipitation by changing the frequency of occurrence of weather patterns near Greenland. Generally, precipitation is created over Greenland when extratropical cyclones create onshore flow onto the ice sheet, which creates strong orographic lift and results in precipitation, where the topography of Greenland consists of steep margins rising to a peak elevation of 3208 m at Summit, Greenland (Figure 1) [Schuenemann et al., 2009; Serreze and Barry, 2005]. Predicting changes in atmospheric circulation under global warming scenarios is complex, as several cyclone feedbacks may compete against each other in a warmer atmosphere. Cyclones develop along strong meridional temperature gradients, yet throughout their lifecycle they mix the atmosphere on a synoptic scale by transferring heat poleward, acting to reduce this temperature gradient. Therefore, an increase in frequency or intensity of cyclones may act to decrease the temperature gradient that drives cyclone development [Held, 1993]. Polar amplification also acts to reduce meridional surface temperature gradients. The Greenland region adds complexity to the global warming scenario for cyclones because the ice sheet margin creates an area of sharp temperature gradients that can act to intensify cyclones, or help them to redevelop near the ice sheet [Tsukernik et al., 2007; Schuenemann et al., 2009], and this temperature gradient could change over time. Current observations suggest an increase in frequency of heavy precipitation events over land, globally, and a strengthening of the midlatitude westerly winds since the 1960s [Alley et al., 2007]. Wang et al. [2006] found a 181 km northward shift in mean storm track position over the North Atlantic during winter (JFM) for in reanalyses using a cyclone tracking algorithm. Moving beyond these observed changes, IPCC AR4 AOGCMs (Intergovernmental Panel on Climate Change Fourth Assessment Report Atmosphere-Ocean General Circulation Models) predict the northward shift in cyclones to continue into the 21st century [Yin, 2005; Alley et al., 2007]. The analysis presented in this paper shows predicted changes in atmospheric circulation for the North Atlantic domain and explores how this will affect Greenland precipitation. [5] The availability of atmospheric moisture in a warmer climate will also affect Greenland precipitation. Higher global temperatures will lead to increased evaporation rates, but also higher saturation vapor pressures, and therefore, more moisture will need to be present in the atmosphere for the air to become saturated. This will increase the amount of precipitable water in the atmosphere. Increased atmospheric moisture availability would lead to more latent heat of condensation release in cyclones, thereby reducing the static stability of the cyclone and act to intensify it. Also, cyclones would become more efficient at mixing the atmosphere due to increased poleward latent heat transport due to more water vapor being evaporated at the equator and being mixed poleward where it condenses [Held, 1993]. Again, this may act to reduce the meridional temperature gradient by more intensely mixing the atmosphere, which could lead to less frequent precipitation events. However, these cyclone events could lead to higher magnitudes of precipitation being produced [Trenberth, 1999]. Another important factor for Greenland precipitation is that the ice sheet is located near Arctic sea ice. Currently, sea ice surrounds much of Greenland during the winter, with annual maximum sea ice extent in March. At the sea ice maximum, the Arctic Ocean north of Greenland is covered in sea ice, as are Baffin Bay and Davis Strait west of Greenland, while a thin extent of sea ice extends along east coast of Greenland [Serreze and Barry, 2005]. At its minimum in September, sea ice retreats to only cover the Arctic Ocean just north of Greenland, and in some years, a thin strip along the northeast coast of Greenland extending southward to 70 N. The annual cycle of sea ice extent will change in the future, exposing more open sea to the atmosphere, which will further enhance atmospheric moisture. The average atmospheric water vapor content has already been observed to increase in the atmosphere at least since the 1980s [Alley et al., 2007]. Further increases in atmospheric moisture will affect Greenland precipitation. [6] Taken together, the affects of these mechanisms of change with global warming are unknown in the Greenland region. Here, a three-model ensemble of IPCC AR4 AOGCMs, described in part 1 of this paper [Schuenemann and Cassano, 2009], will be used to analyze the role of predicted changes of synoptic patterns and Greenland precipitation during the 21st century under the SRES A1B (Special Report on Emission Scenarios) emissions scenario, using the method of self-organizing maps (SOMs). 2. Data [7] Motivated by the need to capture synoptic-scale events, daily sea level pressure (SLP) and precipitation data are the basis for the analysis presented in this paper. These data were obtained for fifteen IPCC AR4 AOGCMs from the World Climate Research Programme s (WCRP s) Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel data set for the 20c3m simulation for , and SRES A1B scenario simulations for and Data from the European Centre for Medium-Range Forecasts (ECMWF) ERA-40 reanalysis for was also used [Uppala et al., 2005]. The time periods used in our analysis were chosen based on the overlapping availability of daily data from all of the models during these periods. [8] The simulations of future daily SLP and precipitation are based on atmospheric greenhouse gas concentrations from the SRES A1B scenario [Alley et al., 2007]. This scenario describes a future with very rapid economic growth, population that peaks midcentury and then declines, and the rapid introduction of new and more efficient technologies. Technological change in the energy system includes a balance between fossil fuel and non-fossil-fuel energy sources. In this scenario the emission of carbon dioxide peaks midcentury and then declines, which causes concentrations to reach greater than 500 ppm by 2050 and approximately 700 ppm by Sulfate aerosol in this scenario peaks by year 2020 and then declines. The best estimate of global average surface temperature change from several AOGCMs between and is 2of18

3 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 1. Map of analysis domain with inset map showing domain location relative to the pan-arctic. Greenland ice sheet elevation is contoured every 500 m beginning with the 2000 m line in bold. A scale bar in the bottom right corner shows a distance of 200 km, which is the Equal-Area Scalable Earth (EASE) grid resolution that all data are interpolated to. an increase of 2.8 C, with a likely range of 1.7 to 4.4 C under this scenario [Alley et al., 2007]. [9] The analysis presented in this paper is done using the self-organizing map (SOM) technique. The SOM algorithm is a neural network algorithm that uses an unsupervised, iterative training procedure to analyze large amounts of data [Kohonen, 2000]. Here it is used to cluster daily sea level pressure (SLP) anomaly patterns from several decades and several data sets into a manageable number (35) of groupings. The algorithm produces an organized, two-dimensional array of patterns that represent the range of conditions found in the input data. Recently, SOMs have been used in the field of climatology and have been validated for this use by Reusch et al. [2005, 2007] and Liu et al. [2006]. Hewitson and Crane [2002] present several basic techniques for using SOMs with meteorological data. Cassano et al. [2007] introduce SOM techniques used here for attributing precipitation changes to changes in weather pattern frequency and within-pattern changes in precipitation. This SOM analysis used the SOM-PAK software, which is available for downloading at [Kohonen et al., 1996]. [10] Several SOMs were trained using all of the daily SLP anomaly data for 20th and 21st century time periods for the fifteen IPCC AR4 AOGCMs and for the 20th century for ERA-40, except SLP data over Greenland, which was ignored due to the difficulty of adjusting high-elevation surface pressures to sea level [Streten, 1980]. The master SOM chosen for this analysis was carefully chosen through a quantitative process of measuring which SOMs best fit the input data. A 7 5 SOM with 35 nodes and training parameters set to a learning rate of 0.01, a radius of 3, neighborhood function set to bubble, and a running length of 12 million steps, was chosen as the master SOM. This master SOM is shown by the SLP anomalies (black contour lines) in Figure 4, and the same master SOM is shown without precipitation overlays in Figure 2 in part 1 of this paper [Schuenemann and Cassano, 2009]. To ensure reliable results from the SOM analysis, the daily SLP and precipitation from each of the models were interpolated to a 200 km Equal-Area Scalable Earth (EASE) grid [Armstrong and Brodzik, 1995] over the domain in Figure 1 to assure equal weight of data at high and low latitudes. A scale bar is included in Figure 1 to show the 200 km grid distance used. [11] In part 1 of this paper [Schuenemann and Cassano, 2009], for fifteen models, the 20c3m daily SLP and precipitation data for was compared to that of ERA- 40, our best approximation of reality [Schuenemann et al., 2009]. Each daily SLP anomaly pattern in the model data best fits to one of the 35 nodes on the SOM. The matching node is found by calculating the average square distance between a day s SLP anomaly data and the vector representing each node. The minimum distance indicates the best match node for that day on the SOM. The frequency of occurrence of synoptic patterns within each of the models for was compared to that of ERA-40. A threemodel ensemble of models that best reproduced the frequency of occurrence of synoptic patterns was created. The three models in the three-model ensemble had high annual and seasonal correlations of node frequency of occurrence to ERA-40 and were chosen based on their ability to reproduce the ERA-40 SLP synoptic climatology. The three-model ensemble performed better than any individual model, a five-model ensemble, and a 15-model ensemble. The three IPCC AR4 AOGCMs that make up this ensemble used for the primary analysis presented in this paper are the CCCMA-CGCM3.1(T63), the MPI-ECHAM5, and the MIROC3.2(hires). The CCCMA and the ECHAM both have horizontal resolution of T63 ( ) and 31 vertical levels. The MIROC3.2(hires) has a horizontal resolution of T106 ( ) with 56 vertical levels. More information on the models can be found in Table 8.1 of the IPCC AR4 Working Group 1 Report [Alley et al., 2007] and in Table 1 of part 1 of this paper [Schuenemann and Cassano, 2009]. For discussion of comparisons between ERA-40 precipitation and other Greenland precipitation data sets, refer to Schuenemann et al. [2009]. For a complete analysis of the small differences between three-model ensemble and ERA-40 synoptic climatology, refer to part 1 of this paper [Schuenemann and Cassano, 2009]. The daily Greenland precipitation for this ensemble was also compared to ERA-40 precipitation. The ensemble reproduced the same mean annual Greenland precipitation as ERA-40, 35.8 cm yr 1, but the precipitation is produced differently 3of18

4 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 2. Mean annual precipitation and precipitation differences over the domain (cm yr 1 ) for (a) , (b) minus , (c) minus , and (d) minus Contour interval is 10 cm yr 1 for Figure 2a, and contour interval is 2 cm yr 1 for Figures 2b 2d, with dotted contours for negative values. by each of the models, the three-model ensemble, and ERA-40. These differences are attributed to differences in synoptic pattern frequency differences as well as intrapattern variability differences. This is discussed in great detail by Schuenemann and Cassano [2009]. ERA-40 Greenland precipitation increases over the time period from 1961 to 1999, but this trend is not statistically significant. The CCCMA and MIROC models simulate an increase in Greenland precipitation from 1961 to 1999 consistent with what is seen in ERA-40 and in observational data, but as with the ERA-40 data, the trend is not statistically significant. The ECHAM5, however, has a slight decrease in precipitation over this same time period, although this is also not a statistically significant trend. Despite these differences, there is high confidence in the three-model ensemble to produce the correct (ERA-40) Greenland precipitation over the past ( ) and, therefore, will be used here to analyze predicted future Greenland precipitation. 3. Results and Analysis 3.1. Mean Annual Data [12] Mean annual precipitation for , as simulated by the three-model ensemble, is shown in Figure 2a. Predicted changes in mean annual precipitation by are shown in Figure 2b. Changes in the later half of the 21st century are shown in Figure 2c and changes over the entire 21st century are shown in Figure 2d. Precipitation over Greenland increases everywhere, and the only areas of the analysis domain where precipitation decreases is along the southern edge of the domain near 40 N as well as off the southeast coast of Greenland for the first half of the 21st 4of18

5 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 3. Three-model ensemble mean SLP (hpa) for (a) , (b) , and (c) where the 1007 hpa contour is bold in each map. Three-model ensemble mean SLP difference for (d) minus , (e) minus , and (f) minus , where solid contours are positive differences (later period SLP is higher) and dashed contours are negative differences (later period SLP is lower). Contour interval for Figures 3a 3c is 1 hpa, and contour interval for Figures 3d 3f is 0.25 hpa. century, both of which may be attributed to a northward shift in storm track. Figure 2d indicates a predicted increase in precipitation over the upper east coast of Greenland of up to more than 16 cm yr 1 and precipitation over southern Greenland increases by 14 to 22 cm yr 1, approximately 75% of which takes place by and 25% of which takes place from to Note that the time segments between time periods are not equal. The difference between the middle year in and the central year in is 75 years. The difference between the later two periods is 35 years. The source of this precipitation increase over all of Greenland will be further investigated throughout the remainder of this paper. [13] Mean SLP and SLP differences for each time period are plotted over the domain in Figure 3 in order to view the changes in mean SLP over the three time periods. The 1007 hpa contour is thickened for easy comparison of the mean SLP among the three time periods in Figures 3a, 3b, and 3c. Figure 3a shows, for , the Icelandic Low east of southern Greenland, the Azores High in the southeast corner of the domain, and high pressure over Greenland itself, which is a result of adjusting cold, high-elevation pressures to sea level. The predicted three-model ensemble mean SLP for and then indicate an expansion of the area of the Icelandic Low, particularly toward the northeast. The differences between SLP in each of these time periods as well as the full time period are plotted in Figures 3d, 3e, and 3f. These mean SLP differences have magnitudes of only 0 to 2.25 hpa. Upon comparing the change in mean annual SLP (Figure 3) to the change in mean annual precipitation (Figure 2), the forcing for the change in precipitation cannot be ascertained. One possible forcing mechanism for the change could be the slightly lower pressures in the northern half of the domain, which could indicate more cyclone activity or more intense cyclones. The SOM analysis presented by Cassano et al. [2007] 5of18

6 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 4. Master SOM node anomaly SLP (solid contour lines for positive SLP anomalies and dashed contour lines for negative SLP anomalies with 2hPa contour intervals) and node-averaged three-model ensemble precipitation anomaly for , , and (cm d 1 ) (blue shading indicates positive precipitation anomalies, and orange shading indicates negative precipitation anomalies). provides a method for attributing change in precipitation to changes in synoptic forcing and precipitation amount generated by fixed atmospheric circulation patterns, and is used here to analyze the processes responsible for the increase in Greenland precipitation over the 21st century. This method uses daily data which has a time scale that is similar to the time scale at which precipitation is generated Master Self-Organizing Map [14] The master SOM (Figure 4) consists of 35 synoptic patterns which best represent the range of synoptic patterns that occur in this domain. In Figure 4, solid contours show areas of high pressure (positive SLP anomalies) while closed dashed contours indicate the locations of low pressure (negative SLP anomalies), or cyclones. The precipitation, shown by color shading in this plot, will be discussed in section The 35 nodes on the SOM are categorized into six subgroupings based on cyclone position. These groups are outlined and labeled in Figure 4 and are discussed in great detail in part 1 of this paper. Weak cyclones (W) appear in the upper left corner of the SOM and include nodes with weak synoptic patterns. Labrador cyclones (LC) are located at the top right of the SOM and have cyclones with centers of circulation in the Labrador Sea southwest of Greenland. Baffin Bay cyclones (BB) are located in the upper right corner of the SOM and include nodes with cyclones located west of Greenland in Baffin Bay. Icelandic cyclone (IL) nodes have cyclones with centers east of Greenland and these nodes are located in the bottom right corner of the SOM. North Atlantic cyclone (NA) nodes are in the bottom left of the SOM and have cyclones far away from Greenland in the North Atlantic. Southern tip (ST) cyclones are located in the left central portion of the SOM and cyclone centers in these nodes are located near the southern tip of Greenland, wrapping strong onshore flow onto the southeast coast Frequency [15] The frequency of occurrence of synoptic patterns, or nodes, on the master SOM (Figure 4) in the three-model ensemble from 1961 to 1999 is plotted in Figure 5a. Nodes with frequencies that are statistically different from equal occurrence of all 35 nodes are bold for values above a 95% confidence interval and bold, italic for values below the confidence interval. These node frequencies are then subtracted from the predicted node frequency of occurrence for 6of18

7 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 5. Three-model ensemble node frequency of occurrence (%) for (a) , (b) minus , (c) minus , and (d) minus Contour interval for Figure 5a is 0.5%, and contour interval for Figures 5b, 5c, and 5d is 0.2%. the time period in order to show nodes that occur more frequently in the future (Figure 5b, solid contours) and nodes that occur less frequently in the future (Figure 5b, dashed contours). Future frequencies that are significantly different, at the 95% confidence level, than the past frequencies are indicated, once again, by bold and italic fonts. Similarly, the time period node frequencies are subtracted from the predicted node frequencies to show changes in frequency taking place in the later half of the 21st century (Figure 5c). Finally, to show the change in frequency over the whole 21st century, the past ( ) node frequencies are subtracted from the node frequencies (Figure 5d). This same sequence of time periods found in Figure 5 will be used throughout this analysis to display the individual time increments as well as the full predicted change from the past period to the end of the 21st century. [16] Changes in node frequency of occurrence from to show a robust pattern in the frequency difference plot (Figure 5b) of increasing frequencies of most SLP patterns represented by BB and IL nodes on the right side of the SOM, which are nodes with lowpressure systems located in the northern portion of the domain as well as high pressure over the southeast corner of the domain in the Azores High region. Frequencies of many of the W, LC, ST, and NA nodes decrease by The time increment from to also has an increase in frequency of nodes in the far right column of the SOM, but also shows small increases in frequency of nodes in some of the other SOM groups (Figure 5c). [17] The summary of both of these time increments shows the change in frequency from to in Figure 5d. Nodes on the right of the SOM, all BB and some 7of18

8 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 6. Node average daily net Greenland precipitation (cm d 1 ) for time period (a) , and precipitation differences for (b) minus , (c) minus , and (d) minus In Figures 6b 6d, solid contours show an increase in precipitation while negative contours show a decrease in precipitation. Nodes included in the darkest shades are the highest precipitation magnitudes. IL and LC nodes are predicted to increase in frequency over the 21st century. The synoptic patterns that are predicted to increase in frequency of occurrence are those that take place most often in the summer (JJA) and fall (SON) seasons and consist of cyclones located in the northern portions of the domain. The increase of warm season synoptic patterns in a global warming scenario is physically reasonable. On the other hand, most NA, ST, and W nodes decrease in frequency, as well as IL nodes (3,4) and (3,3) and LC node (4,0). These decreasing frequency nodes all have synoptic patterns that include low-pressure systems in the southern portion of the domain. [18] The statistically significant increase or decrease of 22 of 35 nodes shows a robust pattern of a northward shift in the North Atlantic storm track under a global warming scenario, confirming the results of Wang et al. [2006], who found a northward shift in storm track in the 20th century, and Yin [2005] and Alley et al. [2007] who predict a northward shift during the 21st century. This northward shift in the storm track is also found when the individual models that make up the three-model ensemble or the entire 15-model ensemble are analyzed. Patterns with cyclones located near Greenland, rather than south of it, increase in frequency over the 21st century. From the mean SLP difference in Figures 3c, 3e, and 3f it is evident that pressure is predicted to increase in the southern half of the domain and decrease in the northern half, but the use of the SOM as an analysis tool allows an analysis of daily time scale data to clearly see that cyclones themselves are occurring more frequently at higher latitudes. The northward shift in storm track, as represented by a change in SOM node frequencies, will undoubtedly affect precipitation over the Greenland ice sheet in the future. 8of18

9 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART Precipitation Precipitation in the SOM Framework [19] Knowing which days match most closely to each node on the SOM, the daily precipitation data for each day matching to each individual node is averaged to create a two dimensional average daily gridded precipitation for each node. Precipitation data are drawn from all three time periods. This is the daily precipitation expected to take place whenever this synoptic pattern occurs in the atmosphere. Daily precipitation anomalies are calculated relative to the average precipitation map and are plotted in the SOM in Figure 4 in cm d 1. Blue shades represent areas with positive precipitation anomalies, or areas where synoptic patterns produce higher than average precipitation amounts. Orange shades show portions of the domain that receive less than average precipitation amounts. SLP anomaly contours are overlaid on the precipitation for easy reference to the synoptic pattern and cyclone position for each node. [20] Each group of nodes on the SOM receives Greenland precipitation as a result of the interaction of onshore flow from cyclones placed in different positions around the ice sheet and the ice sheet topography. The Greenland ice sheet is divided into five regions based on precipitation patterns, indicated in Figure 1 by dotted white lines. The five regions are the northern, western, central, eastern, and southern regions. Cyclones in ST nodes create onshore flow over the southeast coast of Greenland. The onshore flow interacts with the steep margins of the ice sheet, indicated by the close proximity of the 2000 m elevation contour to the coast in Figure 1, inducing orographic lift and resulting in precipitation. LC nodes have cyclones that wrap air onto southern Greenland, producing large magnitudes of precipitation over much of the southern region of Greenland. BB nodes have cyclone centers further north than that of LC nodes, causing large amounts of precipitation over the southwest coast of Greenland and the western region. The cyclones in IL nodes enhance precipitation in the eastern region and sometimes the northern region due to onshore flow. W and NA nodes have cyclones too far from the ice sheet or too weak to force large amounts of Greenland precipitation Greenland Precipitation Node Average Daily Net Greenland Precipitation [21] Rather than focusing on the whole domain, precipitation over Greenland alone now becomes the focus of this analysis. Figure 6a shows the node average daily net Greenland precipitation (cm d 1 ) for , which was calculated by averaging the Greenland precipitation for all days within that match each node. This was done for each time period. The changes in node average daily net Greenland precipitation are plotted in Figure 6b for to , Figure 6c is the change from to , and Figure 6d the change over the whole period, to With minor exceptions in the three-model ensemble, the magnitude of daily Greenland precipitation expected when a synoptic pattern on the SOM takes place is predicted to increase over time. This result is true in each of the three models that make up the three-model ensemble as well. This is consistent with the analysis of predicted 21st century changes over the Arctic by Cassano et al. [2007]. Some of the nodes with the largest predicted increases in node average daily net Greenland precipitation over the 21st century are those that advect air from the northernmost portions of the domain where sea ice retreat allows for the highest increases in precipitable water, such as nodes (6,4) and (6,3) on the right of the SOM, for example Mean Annual Node Contribution to Greenland Precipitation [22] In order to understand how annual Greenland precipitation is predicted to change during the 21st century, it is necessary to sum the precipitation from synoptic-scale systems affecting the ice sheet annually during the 21st century. To understand how the increases in daily precipitation discussed in the previous section affect the 21st century annual Greenland precipitation, the change in circulation of the atmosphere must also be considered by taking the frequency of occurrence of each synoptic pattern into consideration, which can be expressed mathematically as P annual ¼ X35 n¼1 365 day yr f np n ; In equation (1), the node averaged daily net Greenland precipitation, p n (Figure 6), is multiplied by the frequency of occurrence of each node, f n (Figure 5), and 365 d yr 1 to get the mean annual node contribution to Greenland precipitation (cm yr 1 ). This was done for each of the three time periods and then the differences between the time periods were calculated. Figure 7a shows the annual Greenland precipitation contribution by node for Figures 7b, 7c, and 7d show the change in mean annual node contribution to Greenland precipitation during the given time increments (the same that were used in Figures 4, 5, and 6). BB and IL nodes have the largest increase in annual Greenland precipitation contribution due to their large increase in frequency combined with their increase in node average daily net precipitation. Synoptic patterns represented by BB nodes (6,1) and (6,2) and IL node (6,3) on the right side of the SOM contribute over 1cmyr 1 more to Greenland precipitation at the end of the 21st century than during the past ( ). [23] Upon summing the mean annual node contribution to Greenland precipitation from each node for (Figure 7a), or performing the summation in equation (1), the annual contribution to Greenland precipitation is 35.8 cm yr 1. The differences in mean annual node contribution to Greenland precipitation in Figures 7b, 7c, and 7d can also be summed to find changes in mean annual precipitation. The predicted northward shift in storm track along with the increase in moisture availability in the atmosphere cause a 6.6 cm yr 1 increase of Greenland precipitation from to and a further increase of 3.4 cm yr 1 from to for a total increase of 10.0 cm yr 1 from to , from a average value of 35.8 cm yr 1. The individual models that make up the three-model ensemble all indicate an increase in Greenland precipitation. The MPI-ECHAM5 model mean annual Greenland precipitation increases to 51.6 cm yr 1 by from 42.9 cm yr 1 for the time period , a 8.9 cm yr 1 increase. The MIRO- ð1þ 9of18

10 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 7. (a) Mean annual node contribution to Greenland Precipitation (cm yr 1 ) for time period , and precipitation differences for (b) minus , (c) minus , and (d) minus C3.2(hires) model indicates a 13.1 cm yr 1 increase in precipitation over the 21st century, from 36.9 cm yr 1 to 50.0 cm yr 1. The CCCMA-CGCM3.1(T63) model shows a 8.1 cm yr 1 increase, from 27.6 cm yr 1 to 35.7 cm yr Attribution of Changes in Greenland Precipitation Using SOMs [24] This change in precipitation over time can be attributed to a combination of changes resulting from future circulation changes (referred to here as a pattern frequency change component) or changes in the magnitude of precipitation produced when a circulation pattern takes place in the future (referred to here as the intrapattern variability change component). The method presented by Cassano et al. [2007] and in part 1 of this paper will be used to attribute the predicted 21st century changes in precipitation to these components. [25] For this analysis, the past ( ) annual precipitation is the initial time period from which changes will be considered and can be calculated by equation (1). In the future, for example, the frequency of nodes can be represented as the past, or initial, frequency, (f n ) (Figure 5a), plus a change in frequency (Df n ) from to (Figure 5d). The future frequency term then becomes (f n + Df n ). Similarly, the future precipitation term can now be written as (p n + Dp n ), where the future precipitation is represented as the past node average daily net Greenland precipitation, (p n ) (Figure 6a), plus the change in precipitation from the past to the future (Dp n ) (Figure 6d). Substituting these terms into equation (1), the future mean annual precipitation is calculated as P annualfuture ¼ 365 day yr X 35 n¼1 ðf n þ Df n Þðp n þ Dp n Þ: ð2þ The terms in equation (2) can be multiplied to give P annualfuture ¼ 365 day yr X 35 n¼1 ðf n p n þ f n Dp n þ Df n p n þ Df n Dp n Þ; ð3þ 10 of 18

11 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 8. (a) Total change in Greenland precipitation from to by node. (b) Change attributed to the intrapattern variability change component by node. (c) Change attributed to the pattern frequency change component by node. (d) Change attributed to combined change by node. The sum of all 35 nodes is listed at the bottom of each plot as the total. Each number corresponds to the node in the same position on the master SOM (Figure 4). All numbers have units of cm yr 1. which when summed over all 35 nodes and multiplied by 365 d yr 1, equals the mean annual future Greenland precipitation (cm yr 1 ). The first term in equation (3), (f n p n ) represents the past ( ) precipitation and the remaining three terms sum to equal the total change in precipitation for the two time periods considered. Figure 8a displays the total change in mean annual net Greenland precipitation from to by node, which is the same as Figure 7d. Upon performing the summation over all nodes, the total change, or the result of summing the last three terms in equation (3), appears at the bottom of Figure 8a as 10.0 cm yr 1. That is to say, on average, the precipitation falling over Greenland during any year from 2081 to 2100 will be 10.0 cm greater than the precipitation falling over Greenland from 1961 to 1999, as simulated by the three-model ensemble. The total change is divided into attributions from intrapattern variability change, pattern frequency change, and combined change, the final three terms in equation (3). [26] The first total change term, f n Dp n, represents what would take place if only changes in daily precipitation are taken into consideration while the frequency stays the same as it was in the past. Therefore, this term represents future changes that result from changes in the magnitude of Greenland precipitation falling when a particular synoptic pattern takes place. These changes are termed intrapattern variability changes since the changes occur for a given synoptic pattern. This includes atmospheric thermodynamic processes that change the amount of precipitation produced when a given synoptic pattern takes place. One explanation for this intrapattern variability increase in precipitation is that a warmer atmosphere results in an increased rate of evaporation and higher saturation vapor pressures, and therefore, more available water vapor, or precipitable water, in the air. Changes in sea ice extent or SST are two other factors which likely contribute to this precipitation change term in our analysis. [27] Figure 8b shows the Greenland precipitation contribution from each node to intrapattern variability changes from to The frequency used to calculate this term is given in Figure 5a and the precipitation change is given in Figure 6d. Because each node average daily net Greenland precipitation value in Figure 6d was positive, each node contributes positively to intrapattern variability changes. In other words, when each synoptic pattern represented by the node on the SOM occurs, it will produce more precipitation in the future than it has in the past. Some IL and BB nodes produce more than 0.40 cm yr 1 11 of 18

12 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 more Greenland precipitation in the future due to intrapattern variability changes. Nodes on the right side of the SOM increase precipitation more than those on the left side of the SOM (Figure 8b). [28] One hypothesis for the magnitude of the increase in precipitation being larger for nodes with cyclones in the more northern portions of the domain (nodes on the right of the SOM), is that negative trends in sea ice extent, particularly during the summer and autumn, but even into the winter season, leave more open water in the future and therefore, an open available water source where evaporation increases the amount of precipitable water in the atmosphere near Greenland. Nodes with cyclones in the more southern portion of the domain already have available water because the North Atlantic water is open year round, and therefore, would not have the amplified increase in available water vapor due to changes in sea ice that nodes on the right of the SOM would. All nodes, however, would have increases in precipitable water available due to generally higher atmospheric temperatures and the associated increase in evaporation. Specific humidity and temperature are predicted to increase over each of the Greenland regions. Summing the intrapattern variability changes of all 35 nodes gives a total contribution to precipitation change of 8.2 cm yr 1, 82.5% of the total Greenland precipitation change from to [29] The second change term in equation (3), Df n p n,is the pattern frequency change, or atmospheric circulation change term. The change in frequency used in this calculation was plotted in Figure 5d, while the past precipitation used in the calculation was plotted in Figure 6a. By keeping the daily precipitation values of the past constant in this term, changes due to changes in the frequency of occurrence of synoptic patterns can be isolated. The term represents changes in atmospheric circulation, represented by certain synoptic patterns, or nodes, occurring more frequently in the future time period than in the past, and other nodes occurring less frequently. As discussed in section 3.3 and observed in Figure 5, nodes on the right side of the SOM occur more frequently in the future, representing a northward shift in storm track. This pattern frequency change term embodies the changes in precipitation attributed to the northward shift in storm track in the future. Figure 8c shows the mean annual contribution to circulation changes from each node from to Nodes on the right of the SOM contribute up to 0.8 cm yr 1 more in than they did in due to changes in atmospheric circulation. Nodes in the left portion of the SOM, such as ST, NA, and most W nodes, contribute up to 0.3 cm yr 1 less in the future than in the past due to their less frequent occurrence. One feature to note regarding the pattern frequency change term is that because the 35 node frequencies are fractions of the total number of days, or percentages, the sum of the node frequency changes must be zero. Therefore, when summing this term over all nodes, the pattern frequency change can only be nonzero if nodes that occur more frequently in the future have different precipitation values than those nodes occurring less frequently in the future. In this case, they do (Figure 6d), and therefore, the pattern frequency change, or circulation change, when summed over all nodes, is 1.3 cm yr 1 (13.1% of the net change), which is smaller than the intrapattern variability changes. [30] The last term in equation (3), Df n Dp n, represents changes due to changes in node frequency (Figure 5d) acting on changes in precipitation (Figure 6d). This term contributes only 4.4% to changes in Greenland precipitation, more so from nodes on the right side of the SOM. This term is generally smaller than the other change terms and is called the combined change term. [31] The mean annual Greenland precipitation, as well of that of five Greenland regions, defined in Figure 1 by white dotted lines, are shown in Table 1. These precipitation values are regionally averaged values and would have to be weighted by area before averaging to equal the whole Greenland precipitation. The southern region receives the highest magnitudes of precipitation. For the past period, liquid equivalent precipitation amounts of 65.0cm yr 1 fall on average over the southern region. The eastern and western regions receive 23.7 and 25.4 cm yr 1, respectively. The smallest annual precipitation magnitudes fall in the central interior and northern regions, only receiving 15.6 and 16.7 cm yr 1, respectively. Schuenemann et al. [2009] used the same regions and calculated ERA-40 precipitation. The three-model ensemble used here is 1.2 cm yr 1 wetter than ERA-40 in the southern region, 4.2 cm yr 1 too dry in the western region, 5.5 cm yr 1 too wet in the eastern region, 1.1 cm too dry in the central interior of the ice sheet, and only 0.3 cm wetter in the northern region. [32] The predicted mean annual precipitation for Greenland and its five regions for (42.4 cm yr 1 for Greenland) as well as (46.8 cm yr 1 for Greenland) are also displayed in Table 1 in the rows labeled Precipitation for each region and in columns labeled by time period. The change in Greenland precipitation between each time period as well as the whole time period was also calculated and divided into its contributions from intrapattern variability change, pattern frequency/circulation change, and combined changes, and are displayed in Table 1. The change in precipitation over the first half of the 21st century, from to , is listed for each region in the Total change row and column labeled First Half 21st Century. Greenland precipitation is predicted to increase 6.6 cm yr 1 over this period (Table 1), which is an 18.3% increase from the Greenland precipitation, where percent increases are displayed in Table 2. This change is then divided into its attributions from Intrapattern variability, Pattern frequency, and Combined change components, found in their respective rows below the Total change row in Table 1. Intrapattern variability change is responsible for 5.6 cm yr 1 of the 6.6 cm yr 1 increase in precipitation, which is 86.0% of the total change. Pattern frequency change contributes 10.8% of the change and the combined change is responsible for 3.2% of the increase in precipitation. The change during the second half of the 21st century, from to , appears in the Second Half 21st Century column in Table 1. The Greenland precipitation during this time increment is predicted to increase by 3.4 cm yr 1. [33] The change over the whole 21st century ( to ) is listed in the last column, labeled Whole 21st Century. Greenland precipitation increases from 35.8 cm yr 1 to 45.8 cm yr 1, an increase of 10.0 cm yr 1, a 27.8% increase in annual Greenland precipitation (Table 2). Over the whole century, 82.5% of the precipitation increase 12 of 18

13 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Table 1. Three-Model Ensemble Precipitation for Greenland and Five Greenland Regions for Three Time Periods, , , , the Changes Between Those Time Periods, and the Total Change From the First to the Last Time Period a Region Description (cm/yr) First Half 21st Century to Change (cm/yr) Percent of Total Rate (cm/yr 2 ) (cm/yr) Second Half 21st Century to Change (cm/yr) Percent of Total Rate (cm/yr 2 ) (cm/yr) Whole 21st Century to Change (cm/yr) Percent of Total Rate (cm/yr 2 ) Greenland Precipitation Total change 6.6 (0.087) 3.4 (0.097) 10.0 (0.091) Intrapattern variability 5.6 (86.0) (0.075) 2.7 (79.1) (0.077) 8.2 (82.5) (0.075) Pattern frequency 0.7 (10.8) (0.009) 0.6 (17.6) (0.017) 1.3 (13.1) (0.012) Combined 0.2 (3.2) (0.003) 0.1 (3.3) (0.003) 0.4 (4.4) (0.004) Southern Precipitation Total change 8.5 (0.114) 4.9 (0.140) 13.4 (0.122) Intrapattern variability 7.4 (86.3) (0.098) 3.8 (78.3) (0.109) 11.1 (82.3) (0.101) Pattern frequency 0.9 (10.8) (0.012) 0.9 (18.0) (0.025) 1.8 (13.5) (0.017) Combined 0.3 (2.9) (0.003) 0.2 (3.7) (0.005) 0.6 (4.2) (0.005) Eastern Precipitation Total change 9.9 (0.132) 3.8 (0.110) 13.8 (0.125) Intrapattern variability 8.4 (84.8) (0.112) 3.4 (88.5) (0.097) 11.8 (85.4) (0.107) Pattern frequency 1.3 (12.7) (0.017) 0.4 (10.4) (0.011) 1.6 (11.7) (0.015) Combined 0.2 (2.5) (0.003) 0.0 (1.0) (0.001) 0.4 (2.8) (0.004) Central Precipitation Total change 3.7 (0.050) 1.9 (0.054) 5.6 (0.051) Intrapattern variability 3.2 (86.4) (0.043) 1.5 (76.8) (0.042) 4.6 (81.6) (0.042) Pattern frequency 0.4 (9.6) (0.005) 0.4 (19.2) (0.010) 0.7 (12.9) (0.007) Combined 0.2 (4.0) (0.002) 0.1 (4.0%) (0.002) 0.3 (5.5%) (0.003) Western Precipitation Total change 4.2 (0.055) 2.5 (0.073) 6.7 (0.061) Intrapattern variability 3.5 (83.7) (0.046) 1.8 (70.2) (0.051) 5.1 (75.8) (0.046) Pattern frequency 0.5 (12.9) (0.007) 0.6 (25.3) (0.018) 1.2 (18.4) (0.011) Combined 0.1 (3.4) (0.002) 0.1 (4.4) (0.003) 0.4 (5.8) (0.004) Northern Precipitation Total change 7.0 (0.094) 3.0 (0.085) 10.0 (0.091) Intrapattern variability 6.2 (88.2) (0.083) 2.6 (86.8) (0.074) 8.7 (87.4) (0.080) Pattern frequency 0.6 (7.9) (0.007) 0.3 (11.5) (0.010) 0.8 (7.9) (0.007) Combined 0.3 (3.9) (0.004) 0.1 (1.8) (0.001) 0.5 (4.7) (0.004) a Precipitation given in cm yr 1. Regional numbers are regionally averaged and will not total to the entirety of Greenland unless they are properly weighted by the area of the region. The rate of change of precipitation is displayed in parentheses to the right of the total change under the Rate heading (cm yr 2 ). Total change (cm yr 1 ) is divided into contributions from intrapattern variability component change, pattern frequency component change, and combined change. The change components are represented as a percentage (%) of the total change and are listed in parentheses under the Percent of Total heading and are also represented as a rate of change (cm yr 2 ) listed under the Rate heading. is due to intrapattern variability changes, 13.1% to pattern frequency changes, and 4.4% to combined changes. These results are quite similar among the three individual models, where the MPI-ECHAM5, MIROC3.2(hires), and CCCMA- CGCM3.1(T63) models have intrapattern variability change components of 78%, 83%, and 84%, a pattern frequency change components of 15%, 14%, and 10%, and a combined change components of 7%, 3%, and 6%, respectively. [34] Because the length of time between the three time periods , , and are not consistent, a rate of change per year can be calculated taking the uneven time intervals into consideration. Assuming each time period is represented by the middle year in that period, the first and second time periods are 75 years apart and the second and third time periods are 35 years apart. The rate of change per year is actually larger (0.097) over the second half of the 21st century than the first half (0.087) for Greenland as a whole (Table 1, Rate column). These calculations are also performed for each of the five Greenland regions and these results will be discussed later. [35] These calculations of total change and its components can also be done spatially by performing the summation calculations in equation (3) where the precipitation is the grid point precipitation on the EASE grid. The resulting maps showing the total annual precipitation difference over Table 2. Predicted Increase in Regional Precipitation Over the First Half, Second Half, and Whole 21st Century a Region First Half to Percent Increase in Regional Precipitation Second Half to Whole to Greenland Southern Eastern Central Western Northern a Change in precipitation represented as a percentage of precipitation. 13 of 18

14 SCHUENEMANN AND CASSANO: GREENLAND PRECIPITATION PART 2 Figure 9. Change in mean annual precipitation (cm yr 1 ) for three time periods is attributed spatially to the intrapattern variability change component, pattern frequency change component, and combined change component. Contour intervals are different for each column; see color bars for proper interval. the first half, second half, and whole 21st century, as well as the maps showing the contribution to the total change by the intrapattern variability change component, pattern frequency change component, and combined change component are in Figure 9. Note that the scale of the color bar and contour intervals varies for the different columns (see Figure 9, bottom). [36] The total change in precipitation is positive (increasing) over much of the domain, except the southernmost area of the domain near 40 N where precipitation decreases by up to 10 cm yr 1 (Figure 9). This decrease in precipitation is from a combination of all of the three change terms, but the largest decreases in this region, by up to 9 cm yr 1, come from the pattern frequency change component as a result of a northward shift in storm track. This is from a reduction in NA and ST nodes that bring large amounts of precipitation to the North Atlantic. [37] As discussed above, precipitation over all of Greenland increases through the 21st century and this is clearly seen in Figure 9. The following discussion will present regional changes, which are summarized in Tables 1 and 2, and which can be understood by considering Figure 9. Note that the maps in Figure 9 look similar in each of the three models, although they are not shown here individually. [38] In the southern region, precipitation is predicted to increase over the whole century by 13.4 cm yr 1, a 20.7% increase, while in the western region will increase by 6.7 cm yr 1, a 26.3% increase. However, pattern frequency changes have a drying affect on the southeastern coast of Greenland and cause precipitation to decrease by up to 7.5 cm yr 1 over the whole century just off the coast, while the southwestern coast extending into the western region becomes wetter by up to 7.5 cm yr 1 (Figure 9). This is the result of decreasing frequency of ST cyclones that drop large amounts of precipitation over the southeast coast, and an increase in frequency of BB nodes that create precipitation over the southwest coast and western region (Figures 8c, 5d, and 4). The pattern frequency change is responsible for a 1.8 cm yr 1 (13.5%) increase in precipitation in the southern region and 1.2 cm yr 1 (18.4%) increase in the western region (Table 1). Intrapattern variability changes increase precipitation over the southern region by 11.1 cm yr 1 (82.3% of total change) and the western region by 5.1 cm yr 1 over the whole century (75.8% of total change). [39] The central interior region of the ice sheet receives small amounts of precipitation due to the inability of heavy precipitation from cyclones to penetrate that deeply into the high elevations of the interior of the ice sheet, but precipitation increases over the 21st century by 5.6 cm yr 1,a 36.2% increase in precipitation. 14 of 18