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Abstract: Melt ponds are significant physical features on the ice surface throughout the Arctic summer, and the scarcity of observational data has resulted in a vague understanding about it. This study employs satellite data and multi-model averaged outputs from CMIP6 to analyze the spatiotemporal evolution characteristics of Arctic melt ponds and their relationship with sea ice thickness (SIT) and atmospheric energy flux. The ponds first emerge at lower latitudes and gradually extend to cover central ice areas as the season progresses, then persisting longer and covering larger total areas in the central region, with peak areas exceeding 0.6 million km2, which is 4 to 5 times that of other marginal areas. Over the past two decades, pond coverage has exhibited markedly different trends with slight decreases in the marginal seas but significant increases in the central area. Both CMIP6 and satellite data indicate that the sea ice carrying capacity, related to thickness, plays a crucial role in creating these differences. There is a marked increasing pond in areas with thicker ice. When the SIT falls below a certain threshold, however, sea ice melting results in decreased pond coverage. Additionally, the energy balance on the ice surface also dramatically impacts pond changes. For instance, the overall pond changes in central area are influenced by net longwave radiation (NLR) and latent heat (LH), with anomalies in these fluxes correlating highly (up to 0.8) with pond anomalies. Meanwhile, net shortwave radiation (NSR) primarily causes local pond anomalies through the pond-shortwave feedback only under the clear weather conditions.
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Key words:
- Ice-atmosphere interaction /
- Melt ponds /
- Sea ice thickness /
- Energy flux
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Figure 1. The evolution of melt ponds in the Arctic region from 2002 to 2022. (a) The RMPF and MPA change with SIT, the gray shaded is the standard deviation of RMPF. The dashed line and spatial map show the RMPF evolution in 2007. (b) the variation of RMPF and MPA with latitude.
Figure 2. The variation of melt ponds in various Arctic seas from 2002 to 2022.The black and red solid line represents RMPF and total MPA respectively, the gray shaded is the standard deviation of RMPF.
Figure 3. Inter-annual variation of melt ponds in the Arctic from 2002 to 2022. (a) the black and red solid line represents RMPF and total MPA respectively. The red dashed line indicates the linear trend, which passes the 95% significance test. The blue bar is SIT. (b) the inter-annual variation of RMPF and MPA with latitude, * indicates passing the 95% significance test.
Figure 4. Distribution of summer ponds in the central Arctic from 2002 to 2022. (a) and (b) represent the distribution of RMPF and total MPA, respectively. The small graph on the right shows the trend of pond in the central arctic and marginal seas
Figure 5. Average RMPF in the central Arctic under different CMIP6 emission scenarios (a) the SSP1-2.6 scenario, with the black solid line representing the change in RMPF and the black dashed line representing the linear trend that passes the 95% significance test. (b) and (c) are similar to (a) but correspond to the SSP2-4.5 and SSP5-8.5 scenarios, respectively.
Figure 6. Distribution of summer RMPF and MPA and their relationship with SIT. (a)(b) represent the average RMPF distribution and their relationship with SIT for June, the marginal bar showing the density distribution of SIT and RMPF in different areas. (c)(d) follow the same format but for MPA. e, f, g, h; i, j, k, l is similar to a, b, c, d but for July and Aug respectively.
Figure 7. Spatial distribution of summer pond trends and their relationship with sea ice thickness including the period spanning 2002-2022. (a) The spatial distribution of the RMPF trends. (b) The relationship between RMPF and SIT. The red and blue dots represent central arctic and marginal area, respectively. (c) and (d) are similar to (a) and (b) but for MPA. (e)The 30-year moving-correlation between RMPF and SIT in the central region under different future emission scenarios, with the bold solid line indicating parts that pass the 95% significance test.
Figure 8. The connection between summer ponds and energy flux anomalies in the central Arctic from 2002 to 2022 (a) the inter-annual anomalies of RMPF, LH, NLR and NSR. The grey dashed line represents the standard deviation of RMPF. (b) The composite distribution of RMPF, NLR, LH, NSR anomalies.
Figure 9. Changes in atmospheric variable anomalies during the positive melt pond event on July 11, 2020. (a)(b) The energy flux anomaly of the lag days. (c) The shade and black line indicates the SLP anomaly and 500hPa geopotential height anomaly, respectively. The vector indicates that the integrated moisture transport. (d−f) The low cloud cover anomaly, the NLR anomaly and RMPF anomaly respectively.
Table 1. The models that output melt ponds in CMIP6
Num Model Country Group Grid 1 HadGEM3-GC31-LL UK Hadley Center 330×360 2 GISS-E2-1-G US NASA 90×144 3 GISS-E2-1-H US NASA 90×144 4 GISS-E2-2-G US NASA 90×144 5 ACCESS-CM2 Australian CSIRO 300×360 6 UKESM1-0-L UK NCAS & Hadley Center 330×360 7 NorESM2-MM Norway NCC 384×360 8 NorESM2-LM Norway NCC 384×360 
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Table 2. Correlation between melt ponds and various influencing factors anomalies in the central Arctic from 2002 to 2022. Bold and * indicate passing the 95% significance test.
SIT NLR NSR LH SH RMPF −0.16 0.81* −0.66* 0.83* 0.55* MPA 0.21 0.58* −0.42 0.69* 0.33
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