{'fraction_non_alphanumeric': 0.02566088893192602, 'fraction_numerical': 0.04464026338723734, 'mean_word_length': 4.990719257540603, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Large carbon cycle sensitivities to climate across a permafrost thaw gradient in subarctic 1 Sweden 2 3

Abstract. Permafrost peatlands store large amounts of carbon potentially vulnerable to
decomposition. However, the fate of that carbon in a changing climate remains
uncertain in models due to complex interactions among hydrological,
biogeochemical, microbial, and plant processes. In this study, we estimated
effects of climate forcing biases present in global climate reanalysis
products on carbon cycle predictions at a thawing permafrost peatland in
subarctic Sweden. The analysis was conducted with a comprehensive
biogeochemical model (ecosys) across a permafrost thaw gradient
encompassing intact permafrost palsa with an ice core and a shallow active
layer, partly thawed bog with a deeper active layer and a variable water
table, and fen with a water table close to the surface, each with distinct
vegetation and microbiota. Using in situ observations to correct
local cold and wet biases found in the Global Soil Wetness Project Phase 3
(GSWP3) climate reanalysis forcing, we demonstrate good model performance by
comparing predicted and observed carbon dioxide (CO2) and methane
(CH4) exchanges, thaw depth, and water table depth. The simulations
driven by the bias-corrected climate suggest that the three peatland types
currently accumulate carbon from the atmosphere, although the bog and fen
sites can have annual positive radiative forcing impacts due to their higher
CH4 emissions. Our simulations indicate that projected precipitation
increases could accelerate CH4 emissions from the palsa area, even
without further degradation of palsa permafrost. The GSWP3 cold and wet
biases for this site significantly alter simulation results and lead to
erroneous active layer depth (ALD) and carbon budget estimates. Biases in
simulated CO2 and CH4 exchanges from biased climate forcing
are as large as those among the thaw stages themselves at a landscape scale
across the examined permafrost thaw gradient. Future studies should thus not
only focus on changes in carbon budget associated with morphological changes
in thawing permafrost, but also recognize the effects of climate forcing
uncertainty on carbon cycling.



Introduction 52
Confidence in future climate projections depends on the accuracy of terrestrial The meteorological conditions for all the simulations were based on the hourly 273 data extracted from the GSWP3 climate reanalysis dataset (section 2.3). The monthly 274 mean bias of the GSWP3 for this location was calculated by comparing it to the air 275 temperature and precipitation measured at the ANS, for years 1913 to 2010 (section 3.1). 276 The full series of air temperature and precipitation extracted from GSWP3 were then 277 bias-corrected using the monthly mean bias calculated from 1913 to 2010; we label this 278 model scenario CTRL. Our bias correction was conceptually similar to the one used in 279 outputs adjusted by the corresponding bias calculated from observations in a reference 281

period. 282
The simulation results from CTRL should represent the reliability of applying 283 ecosys at the Stordalen Mire because CTRL is driven by the best local climate 284 description. We first evaluated predicted thaw depth, water table depth, and CO 2 and CH 4 285 exchanges using the CTRL simulation (section 3.2 to 3.4). In the second set of 286 simulations, BIASED-COLD, the biased GSWP3 air temperature data was used, and we 287 corrected only the GSWP3 precipitation. Deviations between CTRL and BIASED-COLD 288 reflect biased air temperature's effects on responses across the thaw gradient. In the third 289 set of simulations, BIASED-WET, we bias-corrected the air temperature extracted from 290 GSWP3, which allows us to quantify the effects of biased precipitation. Finally, we used 291 the meteorological conditions directly extracted from GSWP3 to drive our fourth set of 292 simulations, BIASED-COLD&BIASED-WET, which reveals the uncertainty range of 293 subarctic peatland simulation associated with the local biases in GSWP3 climate forcing.  Similarly, the GSWP3 annual total precipitation data correlates well with ANS 321 measurements (r = 0.80) but has a wet bias of 380 mm y -1 between 1913 and 2010 322 ( Figure 2b). An increasing trend in annual total precipitation was recorded in both time 323 series from the early 20 th century to present (0.47 mm y -2 [ANS] and 1.07 mm y -2 324 [GSWP3]), although a decreasing trend was found from 1980 to 2010 (-0.56 mm y -2 325 that measured at the ANS, with a very high correlation coefficient (r = 0.99; Figure 3a). 328 The underestimation bias and inter-annual variability of GSWP3 air temperature are 329 greater in winter (maximum underestimate in December, at -4.52 °C with inter-annual 330 variability of 3.53 °C) and smaller in summer (minimum underestimate in July, at -1.52 331 °C with inter-annual variability of 1.65 °C), respectively. 332 The magnitude and inter-annual variability of the GSWP3 monthly mean 333 precipitation are comparable between winter and summer, while the ANS measurements 334 exhibit stronger seasonality with lower magnitudes during winter. Despite the differences 335 found in seasonal patterns, a high correlation coefficient (r = 0.64) was found between the 336 monthly mean precipitation extracted from GSWP3 and the ANS measurements. The 337 overestimation of monthly mean precipitation was greatest in December (43.25 mm 338 month -1 ) and smallest in August (18.75 mm month -1 ). 339 These comparisons suggest that GSPW3 air temperature and precipitation data 340 reasonably capture measured seasonal and long-term trends over past decades, but are 341

Thaw depth 350
We first evaluated ecosys against observations using bias-corrected climate 351 forcing (i.e., the CTRL simulation). Predicted thaw depth agrees well with measurements 352 as surface ice thaws in spring, but there were no measurements to confirm those events. 375 The correlation coefficients of the simulated and observed daily NEE ranged from 0.58 to 376 0.60, and most of the discrepancies between the simulations and observations were within 377 the ranges of NEE variability measured at different subsites (automated chambers) within 378 the same peatland type. The simulated CO 2 uptake rates in the bog were greater than the 379 observations in summer, which could be due to overestimated plant biomass or 380 overestimated CO 2 uptake rate per plant biomass. However, we currently do not have 381 data to examine the cause of this overestimation because the CO 2 flux derived from 382 automated chambers only represents the aggregated results of all controlling factors. 383 As described in section 2.2, simulated CO 2 exchanges were evaluated for 3-hourly 384 and daily time steps when quality-controlled measurements were available (R 2 values and 385 relative root mean squared errors (RRMSEs) shown in Table 2  counterpart, which could be related to comparatively lesser CH 4 emission variability 430 measured across subsites within the same peatland type (Figure 6b, d).   (Table 1). 452

Carbon budget responses to climate 502
Simulations with the four climate forcing datasets (section 2.5) indicate annual 503 mean (from 2003 to 2007) CO 2 sinks and CH 4 sources, except the weak CO 2 emissions 504 simulated in the fen in experiment BIASED-COLD&BIASED-WET due to reduced 505 sedge productivity driven by increased temperature and oxygen stresses (Figure 9a,b). 506 Our results also indicate that differences in annual CO 2 and CH 4 exchanges across the 507 four climate forcing datasets for a single peatland type are as large as those across peatland types for a single climate forcing dataset (Figure 9a,b). These large CO 2 and 509 CH 4 exchanges climate sensitivities demonstrate that the peatland's dynamical responses 510 to climate have stronger effects on the carbon cycle than on ALDs (Figure 8). 511 With bias-corrected precipitation, increased air temperature (CTRL vs. BIASED-512 COLD) leads to stronger CO 2 uptake and greater CH 4 emissions at all the examined 513 peatland types (Figure 9a  NGGB simulated in the palsa is generally negative (i.e., a net sink from the atmosphere) 560 due to lower CH 4 emissions, except for the simulation conducted without any climate bias 561 correction (correcting only air temperature increased CH 4 emissions but not enough to 562 compensate for the significantly higher CO 2 sink). Our results indicate that the simulated 563 NGGB would be biased by 298, -66, and -252 g CO 2 -eq m -2 y -1 in the palsa, bog, and fen, 564 respectively, without proper bias correction for the GSWP3 climate reanalysis dataset 565 (BIASED-COLD&BIASED-WET vs. CTRL). Using the GSWP3 products directly thus 566 effectively eliminates the positive radiative forcing from the expanding bog and fen, 567 while creating a potentially dramatically inaccurate positive radiative forcing from the 568 shrinking palsa. 569 570

Climate sensitivity versus landscape heterogeneity 571
Climate sensitivity and landscape heterogeneity are defined here as variability 572 across the four climate forcing datasets for a single peatland type, and variability across 573 three peatland types with bias-corrected climate (CTRL), respectively. We estimated 574 carbon cycle variability associated with climate sensitivity and landscape heterogeneity to 575 quantify the corresponding uncertainty in our annual carbon cycle assessments from 2003 576 to 2007. Our results indicate that differences in simulated annual mean CO 2 exchanges and NCB from climate sensitivity are greater than those from landscape heterogeneity 578 (Figure 9a,c); i.e., annual CO 2 uptake strength is more sensitive to climate forcing 579 uncertainty than to peatland type representation. In terms of the simulated annual mean 580 CH 4 emissions and NGGB, our results indicate that variability from climate sensitivity is 581 comparable to those from landscape heterogeneity (Figure 9b,d). Therefore, bias-582 corrected climate and realistic peatland characterization are both necessary to reduce the 583 uncertainty in representing carbon cycling dynamics and their radiative forcing effects.    The inset r values are the correlation coefficients calculated between the two time series. 998