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Future changes in the North American monsoon, a circulation system that brings abundant summer rains to vast areas of the North American Southwest, could have significant consequences for regional water resources. How this monsoon will change with increasing greenhouse gases, however, remains unclear, not least because coarse horizontal resolution and systematic sea-surface temperature biases limit the reliability of its numerical model simulations. Here we investigate the monsoon response to increased atmospheric carbon dioxide (CO2) concentrations using a 50-km-resolution global climate model which features a realistic representation of the monsoon climatology and its synoptic-scale variability. It is found that the monsoon response to CO2 doubling is sensitive to sea-surface temperature biases. When minimizing these biases, the model projects a robust reduction in monsoonal precipitation over the southwestern United States, contrasting with previous multi-model assessments. Most of this precipitation decline can be attributed to increased atmospheric stability, and hence weakened convection, caused by uniform sea-surface warming. These results suggest improved adaptation measures, particularly water resource planning, will be required to cope with projected reductions in monsoon rainfall in the American Southwest.
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Accepted version1
This is the author’s version of the work. It is posted here for personal use, not for redistribution. The2
definitive version will be published in Nature Climate Change on Vol. 7, November issue.3
Weakening of the North American monsoon with global warming4
5
Salvatore Pascale1,2,William R. Boos3, Simona Bordoni4, Thomas L. Delworth2, Sarah B.6
Kapnick2, Hiroyuki Murakami1,2, Gabriel A. Vecchi5, Wei Zhang6
7
1Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, NJ 08540, USA8
2Geophysical Fluid Dynamics Laboratory/NOAA, Princeton, NJ 08540, USA9
3Department of Earth and Planetary Science, University of California, Berkeley, and Climate and Ecosystem10
Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA11
4California Institute of Technology, Pasadena, CA 91125, USA12
5Department of Geosciences, Princeton University, Princeton, NJ 08544,USA13
6IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242, USA14
Corresponding author’s address: Princeton University, and NOAA/Geophysical Fluid Dy-15
namics Laboratory, Princeton, New Jersey 08540, USA16
E-mail: Salvatore.Pascale@noaa.gov17
Previously at: California Institute of Technology, Pasadena, California 91125, USA18
1
Future changes in the North American monsoon, a circulation system that brings19
abundant summer rains to vast areas of the North American Southwest [1, 2], could20
have significant consequences for regional water resources [3]. How this monsoon21
will change with increasing greenhouse gases, however, remains unclear [4, 5, 6],22
not least because coarse horizontal resolution and systematic sea surface temper-23
ature biases limit the reliability of its numerical model simulations [5, 7]. Here we24
investigate the monsoon response to increased atmospheric carbon dioxide (CO2)25
concentrations using a 50 km-resolution global climate model which features a real-26
istic representation of the monsoon and its synoptic-scale variability [8]. It is found27
that the monsoon response to CO2doubling is sensitive to sea surface temperature28
biases. When minimising these biases, the model projects a robust reduction in mon-29
soonal precipitation over the southwestern United States, contrasting with previous30
multi-model assessments [4, 9]. Most of this precipitation decline can be attributed to31
increased atmospheric stability, and hence weakened convection, caused by uniform32
sea surface warming. These results suggest improved adaptation measures, partic-33
ularly water resource planning, will be required to cope with projected reductions in34
monsoon rainfall in the American Southwest.35
State-of-the-art general circulation models (GCMs) forced with greenhouse gas emission36
scenarios project a reduction of annual precipitation over a broad area of North America37
south of 35N [10]. While wintertime precipitation is robustly projected to decline in this38
region due to a poleward expansion of the subtropical dry zones [11], summertime precip-39
itation projections remain uncertain. This is due to a weak consensus across GCMs [10]40
and incomplete comprehension of the mechanisms through which global warming will im-41
pact the summertime North American monsoon (NAM). The NAM is shaped by both the42
complex regional geography (Supplementary Fig. 1) and remote larger-scale drivers [2, 12],43
which makes its simulation challenging [7, 13]. GCMs project a June-July reduction and44
2
a September-October increase in precipitation in the monsoon region [4, 9]. This early-to-45
late redistribution of rainfall has been conjectured to arise from two competing mechanisms46
[14]: a stronger tropospheric stability due to a remote sea surface temperature (SST) rise in47
spring that persists through early summer (a remote mechanism); and increased evapora-48
tion and near-surface moist static energy, driven by larger radiative fluxes at the surface (a49
local mechanism). The local mechanism is speculated to overcome the stabilizing effect of50
remote SST rise at the end of the summer [9]. However, the coarse horizontal resolution and51
existence of SST biases in coupled GCM simulations raise the question of how reliable such52
projections are for the NAM, which involves interactions across many spatial and temporal53
scales [12].54
Horizontal resolution is critical for adequately representing the NAM in models. It has55
been recently shown [8] that GCMs with horizontal grid spacing coarser than 100 km (as56
most models participating in the Coupled Model Intercomparison Project, Phase 3 and 5,57
CMIP3 and CMIP5) do not accurately resolve the summertime low-level flow along the Gulf58
of California (GoC), with detrimental impacts on simulated precipitation in parts of the south-59
western U.S. [1, 2]. For this reason, limited-area regional climate models have been used,60
suggesting drying of the monsoon region with warming [5]. Yet regional climate models lack61
two-way coupling with the larger-scale circulation and suffer from inherent boundary condi-62
tion biases [15], making them a questionable tool for studying the climate change response.63
GCM simulations of North American climate are affected by SST biases. In particu-64
lar, negative SST anomalies in the North Atlantic can substantially influence the North At-65
lantic subtropical high through the upstream influence of a Gill-type Rossby wave response66
[16, 17, 18]. This results in unrealistically strong easterly low-level moisture flux across the67
Caribbean region, causing the well-known monsoon retreat bias, i.e., excessive monsoonal68
precipitation in the fall [7, 13]. These biases are thus a substantial source of uncertainty for69
the projected NAM response to CO2forcing.70
3
To address these issues, here we investigate the response of the NAM to increased71
CO2and its sensitivity to both horizontal resolution and SST biases with the high resolu-72
tion (0.5×0.5in the land/atmosphere) Forecast-Oriented Low Ocean Resolution (FLOR)73
model [19, 20], developed at the National Oceanic and Atmospheric Administration (NOAA)74
Geophysical Fluid Dynamics Laboratory (GFDL). In addition to the standard configuration,75
the model can be run at coarser horizontal resolution (LOAR, 2×2in the land/atmosphere)76
or in a flux-adjusted version (FLOR-FA; see Methods).77
Compared to LOAR, increased horizontal resolution in FLOR allows for a better repre-78
sentation of the fall retreat at the end of the warm season (Fig. 1f) and a more realistic79
pattern of near-surface moist static energy (Supplementary Fig. 2). FLOR also better re-80
solves the seasonal cycle of low-level moisture flux along the GoC (Supplementary Fig. 3)81
and synoptic-scale variability within the monsoon [8]. These factors combine to create a82
more realistic simulation of the spatial pattern of mean rainfall (Fig. 1d) and the seasonal83
evolution of rainfall (Fig. 1f).84
To assess the impact of SST biases [7, 13], we contrast the free-running coupled FLOR85
with its flux-adjusted version, FLOR-FA. The flux adjustment adds a modification term to86
surface fluxes of enthalpy, momentum, and freshwater, reducing SST biases in the basic87
state (Supplementary Fig. 4b), and leading to a realistic GoC SST annual cycle (Supple-88
mentary Fig. 5). Globally, flux adjustment improves the simulations of tropical cyclones [20],89
trade winds, dry zones in the Pacific, and El Niño [21]. Specifically to the NAM, one impor-90
tant improvement is the more realistic representation of the monsoon retreat (Fig. 1f). Other91
regional improvements include better representation of the high near-surface moist static en-92
ergy along the GoC (Supplementary Fig. 2e), the GoC low-level jet (Supplementary Fig. 3),93
the Caribbean low-level jet, and the East Pacific Intertropical Convergence Zone. These94
results quantify that the separate impacts of both increased horizontal resolution and SST95
bias reduction enhance the simulation of the present-day NAM. The improvements seen96
4
in FLOR-FA suggest that this model is an excellent tool for investigations of the monsoon97
response to climate change.98
When atmospheric CO2concentration is doubled (2CO2_FLOR-FA vs. CTRL_FLOR-FA;99
Table 1), no statistically significant change is seen in mean June precipitation over the NAM100
region (Fig. 2a). A significant rainfall reduction is instead observed during July-August both101
in the core NAM region south of 28N and in its northern edge north of 28N (Supplemen-102
tary Fig. 6). Because of the large difference in mean summertime precipitation, this drying is103
substantial in percentage terms primarily in the northern edge of the monsoon (40%), be-104
coming increasingly smaller south of 28N (Fig. 2b). The drying persists – albeit weakened105
– over Arizona and northwestern Mexico during September-October, with no significant pre-106
cipitation changes seen along the monsoon coastal regions (Fig. 2c). Similar results are107
found in a second ensemble member, and in additional runs at 25 km atmospheric horizon-108
tal resolution (not shown). These trends are in line with observations, which suggest that109
precipitation has decreased in Arizona in recent decades [22].110
What determines the precipitation reduction over land during the mature monsoon sea-111
son? We answer this question by estimating changes in the vertical buoyancy [23]112
b=h10mh(1)
induced by temperature and specific humidity changes. Here h10mis the near-surface moist113
static energy and hthe saturation moist static energy (see Methods). Fig. 3 illustrates114
changes in buoyancy and cumulus convective mass flux under doubled CO2concentrations115
following a transect from the tropical eastern Pacific across the Sierra Madre Occidental116
into the southwestern U.S. (Fig. 1a). In June, convection is mostly unchanged over the117
western slopes of the Sierra Madre Occidental and south of 32N, consistent with modest,118
insignificant changes in vertical stability (Fig. 3a, d). In July-August, buoyancy decreases119
substantially between the lifted condensation level and the level of free convection over the120
most actively convecting regions on the Sierra Madre Occidental western slopes (Fig. 3b).121
5
Consistently, cumulus convective mass fluxes weaken substantially over the Sierra Madre122
Occidental western slopes (10-30%) and elevated terrain in Arizona (25-50%; Fig. 3e). In123
September-October, the region of negative buoyancy differences narrows and disappears124
almost everywhere except north of 30N. These patterns are consistent with those of con-125
vective mass flux changes (Fig. 3c,f).126
Importantly, when SST biases are not substantially reduced (i.e., 2CO2FLOR vs. CTRL_FLOR),127
the response to CO2doubling is different (Fig. 2d-f), with a drier (20-30% rainfall reduc-128
tion) June over both the southwestern U.S. and most of western Mexico (Supplementary129
Fig. 6), a substantially unaffected July-August (statistically insignificant differences), and a130
more pronounced tendency for larger rainfall rates along the coastal areas of western Mexico131
in September-October. This is consistent with the progressive increase from June to Octo-132
ber in evaporation anomalies (Supplementary Fig. 7a-f) and decrease in sensible heat flux133
anomalies (Supplementary Fig. 7g-l). The changes evident in FLOR without flux adjustment134
follow the consensus based on CMIP3 and CMIP5 model assessments [4, 14, 9], which in-135
vokes a late summer evaporation increase – and with it a near-surface moist static energy136
increase – that balances the larger radiative fluxes at the surface. This compensation results137
in the suppression or even reversal of the early summer rainfall reduction (local mechanism).138
This similarity between FLOR and most of the CMIP5 models may be due indeed to their139
similar SST biases [16].140
This picture is notably different in the southwestern U.S. and northwestern Mexico when141
SST biases are reduced (2CO2_FLOR-FA vs. CTRL_FLOR-FA): the strongest rainfall de-142
crease occurs in July-August (Fig. 2b) rather than in June. This more persistent drying in143
FLOR-FA reduces soil moisture availability and evaporation; hence, the local mechanism144
cannot reverse the drying, which persists until late summer. SST biases can thus substan-145
tially alter the intensity and effectiveness of the local mechanism [14, 9], leading to a change146
in the sign of the monsoon response to CO2forcing. One caveat is that the northernmost147
6
GoC is not resolved in FLOR [8]; this may artificially reduce precipitation in the Southwest148
U.S. [24] and weaken the impact of the local mechanism during the late summer season.149
The sensitivity of simulated rainfall changes to SST bias raises the question of how robust150
the projections shown in Fig. 2-3 are and what is the main driver of rainfall change. Although151
tropical precipitation changes produced by greenhouse gas warming are expected to be lo-152
cally correlated with SST changes [25], it has been argued that the precipitation response153
over land is insensitive to patterns of SST change [26]. To understand the cause of our sim-154
ulated precipitation changes, we use additional FLOR simulations in which SSTs are relaxed155
to a prescribed distribution (Table 1): (1) CLISST, where SSTs are relaxed to climatological156
1971-2012 observed values; (2) 2CO2, where CO2concentration is doubled and SSTs are157
relaxed to climatological values as in CLISST; (3) +2K, where SSTs are relaxed to climato-158
logical values augmented by a uniform 2 K anomaly; (4) 2CO2_+2K, which is a combination159
of +2K and 2CO2; and (5) 2CO2_pattern, where CO2concentration is doubled and SSTs160
are relaxed to climatological values augmented by a nonuniform anomaly pattern derived161
from the long-term 2CO2FLOR experiment, with global mean warming of +2.1 K. As shown162
in Fig. 4, the July-October NAM drying is in large part reproduced by 2CO2_pattern. Direct163
CO2forcing [27] causes a significant increase in June precipitation due to land and lower-164
troposphere warming [28], and compensates for the drying effect of SST rise. Although a165
uniform +2K warming generally increases convective inhibition over land and decreases pre-166
cipitation, the spatial structure of the SST rise (2CO2_pattern minus 2CO2_+2K) provides an167
important contribution to the total changes, as it leads to an additional and substantial reduc-168
tion of rainfall (Fig. 4b). This additional drying is explained by the impact of spatial variations169
in the SST rise, characterized by enhanced near-equatorial warming and off-equatorial rel-170
ative cooling in the eastern subtropical Pacific (Fig. 4c). As a consequence, subtropical171
subsidence intensifies as the sea surface warms more at the equator than in the subtropics.172
This response is in line with the “warmer-get-wetter” paradigm [25]; here we highlight the173
7
potential consequences of this response for the NAM region.174
The strong sensitivity of the NAM response to SST biases shows that these may be a175
large source of uncertainty for regional hydroclimate change [29]. Here we demonstrate176
that, when SST biases are reduced, a CO2increase causes a reduction of summertime177
precipitation in the NAM region, especially over northwestern Mexico and the southwestern178
U.S. (40%). These precipitation reductions are driven by the global mean SST rise, but,179
unlike what is seen in other tropical and subtropical land regions [26], they are substantially180
amplified by sea surface warming patterns. Interestingly, direct CO2radiative forcing [27, 28]181
has a negligible impact on the NAM, a circumstance that, along with the high interannual and182
interdecadal variability of NAM rainfall [2], may explain the difficulty to detect rainfall trends183
from historical observations [30].184
Although our results are based on a single climate model, this model is integrated in mul-185
tiple configurations and has a highly realistic representation of the monsoon compared to186
CMIP models. Our results highlight the possibility of a strong precipitation reduction in the187
northern edge of the monsoon in response to warming, with potential consequences for re-188
gional water resources, agriculture and ecosystems [3]. In addition to this mean precipitation189
response, changes in precipitation extremes [31] with warming will also have a significant190
impact in the monsoon region’s hydrology. We will explore them in future studies. Further191
study of the sensitivity to key parameterized processes such as cumulus convection and land192
surface physics will improve understanding of the monsoon response. Additional progress193
is within reach, as increasing horizontal resolution in state-of-the-art GCMs will soon allow194
new comparative and idealized studies in this critical region.195
References196
[1] Adams D. K. and A. C. Comrie. The North American monsoon. Bull. Amer. Meteor.197
Soc., 78:2197–2213, 1997.198
8
[2] Higgins R. W., Y. Yao, and X. L. Wang. Influence of the North American monsoon199
system on the U.S. summer precipitation regime. J. Climate, 10:298–306, 1997.200
[3] Ray A. J., G. M. Garfin, M. Wilder, M. Vasquez-León, M. Lenart, and A. C. Comrie.201
Applications of monsoon research: opportunities to inform decision making and reduce202
regional vulnerability. J. Climate, 20:1608–1627, 2007.203
[4] Cook B. I. and R. Seager. The response of the North American monsoon to increased204
greenhouse gas forcing. J. Geophys. Res., 118(4):1690–1699, 2013.205
[5] Bukovsky M. S., C. M. Carrillo, D. J. Gochis, D. M. Hammerling, R. R. McCrary, and L. O.206
Mearns. Toward assessing NARCCAP regional climate model credibility for the North207
American monsoon: Future climate simulations. J. Climate, 28:6707–6728, 2015.208
[6] Meyer J. D. D. and J. Jin. The response of future projections of the North American209
monsoon when combining dynamical downscaling and bias correction of CCSM4 out-210
put. Climate Dyn., 49:433–447, 2017.211
[7] Geil K. L., Y. L. Serra, and X. Zeng. Assessment of CMIP5 model simulations of the212
North American monsoon system. J. Climate, 26:8787–8801, 2013.213
[8] Pascale S., S. Bordoni, S. B. Kapnick, G. A. Vecchi, L. Jia, T. L. Delworth, S. Un-214
derwood, and W. Anderson. The Impact of horizontal resolution on North American215
monsoon Gulf of California moisture surges in a suite of coupled global climate models.216
J. Climate, 29:7911–7936, 2016.217
[9] Seth A., S. A. Rauscher, M. Rojas, A. Giannini, and S. J. Camargo. Enhanced spring218
convective barrier for monsoons in a warmer world? Clim. Chang., 104:403–414, 2011.219
[10] Maloney E. D., S. J. Camargo, E. Chang, B. Colle, R. Fu, K. L. Geil, Q. Hu, X. Jiang,220
N. Johnson, K. B. Karnauskas, J. Kinter, B. Kirtman, S. Kumar, B. Langenbrunner,221
K. Lombardo, L. N. Long, A. Mariotti, J. E. Meyerson, K. C. M, J. D. Neelin, Z. Pan,222
R. Seager, Y. Serra, A. Seth, J. Sheffield, J. Stroeve, J. Thibeault, S.-P. Xie, C. Wang,223
B. Wyman, and M. Zhao. North American climate in CMIP5 experiments: Part III:224
9
Assessment of twenty-first-century projections. J. Climate, 27:2230–2270, 2014.225
[11] Seager R. and G. A. Vecchi. Greenhouse warming and the 21st century hydroclimate226
of southwestern North America. Proc. Natl. Acad. Sci. (USA), 107:21277–21282, 2010.227
[12] Pascale S. and S. Bordoni. Tropical and extratropical controls of Gulf of California228
surges and summertime precipitation over the southwestern United States. Mon. Wea.229
Rev., 144:2695–2718, 2016.230
[13] Liang X.-Z., J. Zhu, K. E. Kunkel, M. Ting, and J. X. L. Wang. Do CGCMs simulate231
the North American monsoon precipitation seasonal-interannual variability? J. Climate,232
21:4424–4448, 2008.233
[14] Giannini A. Mechanisms of climate change in the semiarid African Sahel: The local234
view . J. Climate, 23:743–756, 2010.235
[15] Lorenz P. and D. Jacob. Influence of regional scale information on the global circulation:236
A two-way nesting climate simulation. Geophys. Res. Lett., 32:L18706, 2005.237
[16] Wang C., L. Zhang, S.-K. Lee, L. Wu, and C. R. Mechoso. A global perspective on238
CMIP5 climate model biases. Nature Climate Change, 4:201–205, 2014.239
[17] Sutton R. T. and D. L. R. Hodson. Climate response to basin-scale warming and cooling240
of the North Atlantic ocean. J. Climate, 20:891–907, 2006.241
[18] Kushnir Y., R. Seager, M. Ting, N. Naik, and J. Nakamura. Mechanisms of tropical242
Atlantic SST influence on North American precipitation variability. J. Climate, 23:5610–243
5628, 2010.244
[19] Delworth T. L., A. Rosati, W. Anderson, A. J. Adcroft, V. Balaji, R. Benson, K. Dixon,245
S. M. Griffies, H.-C. Lee, R. C. Pacanowski, G. A. Vecchi, A. T. Wittenberg, F. Zeng, and246
R. Zhang. Simulated climate and climate change in the GFDL CM2.5 high-resolution247
coupled climate model. J. Climate, 25:2755–2781, 2012.248
[20] Vecchi G. A., T. Delworth, R. Gudgel, S. Kapnick, A. Rosati, A. T. Wittenberg, F. Zeng,249
W. Andersona, V. Balaji, K. Dixon, L. Jia, H.-S. Kim, L. Krishnamurthy, R. Msadek,250
10
W. F. Stern, S. D. Underwood, G. Villarini, X. Yang, and S. Zhang. On the seasonal251
forecasting of regional tropical cyclone activity. J. Climate, 27:7994–8016, 2014.252
[21] Manganello J.V. and B. Huang. The influence of systematic errors in the Southeast253
Pacific on ENSO variability and prediction in a coupled GCM. Clim. Dyn., 32:1015–254
1034, 2009.255
[22] Luong T. M., C. L. Castro, H.-I Chang, T. Lahmers, D. K. Adams, and C. A. Ochoa-Moya.256
The more extreme nature of North American monsoon precipitation in the southwestern257
U.S. as revealed by a historical climatology of simulated severe weather events. J. Appl.258
Meteor. Climatol., pages doi.org/10.1175/JAMC–D–16–0358.1, in press, 2017.259
[23] Randall D. An introduction to the global circulation of the atmosphere. Princeton Uni-260
versity, Princeton, New Jersey, 456 pp, 2015.261
[24] Mitchell D. L., D. Ivanova, R. Rabin, T. J. Brown, and K. Redmond. Gulf of California262
sea surface temperatures and the North American monsoon: mechanistic implications263
from observations. J. Climate, 15:2261–2281, 2002.264
[25] Xie S.-P., C. Deser, G.A. Vecchi, J. Ma, H. Teng, and A.T. Wittenberg. Global warming265
pattern formation: Sea surface temperature and rainfall. J. Climate, 23:966–986, 2010.266
[26] Chadwick R. Which aspects of CO2forcing and SST warming cause most uncertainty267
in projections of tropical rainfall change over land and ocean? J. Climate, 29:2493–,268
2016.269
[27] Bony S., G. Bellon, D. Klocke, S. Sherwood, S. Fermepin, and S. Denvil. Robust di-270
rect effect of carbon dioxide on tropical circulation and regional precipitation. Nature271
Geoscience, 22:4213–4227, 2013.272
[28] Richardson T. B., P. M. Forster, T. Andrews, and D. J. Parker. Understanding the rapid273
precipitation response to CO2and aerosol forcing on a regional scale. J. Climate,274
29:583–594, 2016.275
[29] Zhou Z.-Q. and S.-P. Xie. Effects of climatological model biases on the projection of276
11
tropical climate change. J. Climate, 28:9909–9917, 2015.277
[30] Anderson B. T., J. Wang, G. Salvucci, S. Gopal, and S. Islam. Observed trends in278
summertime precipitation over the southwestern United States. J. Climate, 23:1937–279
1944, 2010.280
[31] Pfahl S., P. A. O’Gorman, and E. M. Fischer. Understanding the regional pattern of281
projected future changes in extreme precipitation. Nature Climate Change, 7:423–427,282
2017.283
Methods284
Experiments. We use the NOAA GFDL coupled Forecast-Oriented Low Ocean Resolution285
(FLOR) model [20], derived from the GFDL Coupled Model version 2.5 (CM2.5) [19]. CM2.5286
features a 0.5×0.5atmospheric horizontal resolution with 32 vertical levels and has been287
successfully used for studies of regional hydroclimate change [1, 2]. FLOR is identical to288
CM2.5 but features a coarser ocean horizontal resolution (1×1versus 0.25×0.25). The289
land model component is the Land Model, version 3 [3], with a horizontal resolution equal290
to that of the atmospheric model. The sea ice model is the Sea Ice Simulator, version 1,291
as in [19]. A second model called LOAR (Low Ocean Atmosphere Resolution) is also used292
to test the impact of atmospheric horizontal resolution. The LOAR model has a horizontal293
atmospheric resolution of 2×2and is otherwise identical to FLOR [4].294
As in most of CMIP5 models [16], FLOR features positive (negative) SST bias in the295
eastern (western) North Pacific and a negative SST bias in the North Atlantic (Supplemen-296
tary Fig. 4). SST biases have a negative impact on simulations of the NAM in present-day297
climate [13] and are a source of uncertainty for projected changes in the tropics [29]. To re-298
duce them, we use a flux-adjusted version of FLOR. In this configuration, which is otherwise299
identical to the standard FLOR configuration, fluxes of momentum, enthalpy and freshwater300
12
are “adjusted” to bring the model’s climatology of SST, as well as surface wind stress and301
salinity, closer to observational estimates. We refer to this configuration as FLOR-FA. De-302
tails about the flux adjustment procedure can be found in [20]. FLOR-FA features reduced303
SST biases as compared to FLOR, especially in the Pacific and Atlantic oceans (Fig. S4).304
In both FLOR and FLOR-FA, long-term control simulations are performed with atmospheric305
CO2concentration held fixed at 1990 values. In the 2CO2experiments, we increase CO2
306
concentration at 1% per year starting from 1990 levels. After it has doubled (after approxi-307
mately seventy years), we hold it constant and let the model run for additional two hundred308
years. In this experiment, the flux adjustment correction term remains the same as in the309
control run. As for freely-coupled models (i.e., developing systematic SST biases), the un-310
derlying assumption for applying the same adjustment correction under CO2forcing is that311
the emergent error in the SST climatology is the same in present and future climates.312
Nudged-SST simulations. Mechanisms of NAM changes in response to CO2doubling are313
investigated with additional nudged-SST numerical simulations. In these simulations, sim-314
ulated SSTs are restored toward a given field SST0while allowing high-frequency (i.e., on315
timescales smaller than the restoration timescale) SST fluctuations and ocean-atmosphere316
interactions. This is obtained by adding a restoration term (SST0SST)to the SST317
tendency equation:318
d SS T/dt = (d SST /dt)C+ (SST0SST)(2)
where τ= 10 days is the restoration timescale and (d SST /dt)Cthe SST tendency as com-319
puted in the coupled model. Specifically, we perform five nudged-SST simulations in which:320
(1) SST0is the observed 1971-2012 climatological monthly-varying mean and CO2concen-321
trations are held constant at 1990 values (CLISST); (2) SST0is the observed climatolog-322
ical monthly-varying SST mean and CO2concentration is doubled relative to 1990 values323
(2CO2); (3) SST0is the observed climatological monthly-varying SST increased globally by324
2K and CO2concentration is kept at 1990 values (+2K); (4) SST0is the observed climatolog-325
13
ical monthly-varying SST increased globally by 2K and CO2concentration is doubled relative326
to 1990 values (2CO2_+2K); (5) SST0is the observed climatological monthly-varying SST327
plus a nonuniform SST anomaly taken from the long-term 2CO2FLOR climatology and CO2
328
is doubled relative to 1990 values (2CO2_pattern). Further details about these nudged-SST329
simulations and their purpose can be found in Table 1.330
Observations. To validate the FLOR and FLOR-FA simulations, we use several obser-331
vational datasets. For precipitation, we use the Global Precipitation Climatology Centre332
(GPCC) dataset [5]. GPCC is based on statistically interpolated in situ rain measurements333
and cover all land areas at monthly temporal resolution for the period 19012010. GPCC334
monthly precipitation data were obtained at 0.5×0.5horizontal resolution from the NOAA335
Physical Science Division Climate and Weather data website (www.esrl.noaa.gov/psd/data/).336
We use the Modern Era Retrospective-analysis for Research and Applications (MERRA) [6]337
for monthly and daily precipitation, near-surface moisture and winds. MERRA is a reanalysis338
with improved representation of the atmospheric branch of the hydrological cycle developed339
by NASA’s Global Modeling and Assimilation Office (NASA Earth Observing System Data340
and Information System website: https://earthdata.nasa.gov/). Finally, the observed SST0
341
field from the Met Office Hadley Centre Sea Ice and SST dataset [7] is used for the nudged-342
SST runs (Eq. 2) and to evaluate FLOR SST biases (Supplementary Fig. 4).343
Buoyancy and convection diagnostics. The buoyancy of a saturated ascending air par-344
cel, as measured by the difference between its temperature Tcand the temperature of the345
environment T, is proportional to the difference between the saturation moist static energy346
of the environment and the moist static energy of the ascending cloudy air [23]:347
cp(TcT) = hch
1 + γ,(3)
where h=cpT+g z +L q is the moist static energy, hthe saturation moist static energy, hc
348
the moist static energy of the ascending parcel, qis the specific humidity, gis the gravitational349
acceleration, cp= 1004 J K1kg1is the isobaric specific heat of dry air, L= 2.5×106J kg1
350
14
latent heat of condensation, q(T, p)the saturation specific humidity that we calculate using351
the August-Roche-Magnus formula [8] and γ= (L/cp)(q/∂ T )p. Since the ascending parcel352
is lifted adiabatically from near surface, and thus lifted conserves its moist static energy, hc
353
is well approximated by the near-surface moist static energy, i.e. hcp
h10m=cpT10m+354
g z10m+L q10m, here computed at the model’s reference height z10m=10 m. The parameter355
γis positive and of order 1 [23], thus h10mhis approximately twice the buoyancy value.356
To detect changes in the atmospheric convective instability, we estimate the buoyancy index357
b=h10mhat each horizontal grid point xand vertical level pabove the lifted condensation358
level, and then the buoyancy index anomaly bas:359
b= ∆(h10mh),(4)
where the difference is taken between the perturbed and the control simulation and posi-360
tive (negative) values of bindicating upward (downward) acceleration.361
Changes in the intensity of convection are assessed through changes in the diagnosed362
cumulus convective mass flux from the relaxed-Arakawa-Schubert scheme [9] employed in363
the GFDL models.364
Statistical significance. We estimate statistical significance for differences shown in Fig. 2-365
3 and in Supplementary Fig. 7 using a two-sided Student’s t-test at the 95% significance366
level. Confidence intervals for the mean differences shown in Fig. 4 are determined through367
applying 104bootstrap resampling, as we randomly reshuffle the two time series (forced and368
control run) 10,000 times and the construct a probability distribution for the mean difference.369
Data availability The data that support the findings of this study are available from the370
corresponding author upon request.371
15
References372
[1] Kapnick S. B., T. L. Delworth, M. Ashfaq, S. Malyshev, and P. C. D. Milly. Snowfall less373
sensitive to warming in Karakoram than in Himalayas due to a unique seasonal cycle.374
Nature Geoscience, 7:834 – 840, 2014.375
[2] Delworth T. L. and F. Zeng. Regional rainfall decline in Australia attributed to anthro-376
pogenic greenhouse gases and ozone levels. Nature Geoscience, 7:583–587, 2014.377
[3] Milly P. C. D., S. L. Malyshev, E. Shevliakova, K. A. Dunne, K. L. Findell, T. Gleeson,378
Z. Liang, P. Phillipps, R. J. Stouffer, and S. Swenson. An enhanced model of land water379
and energy for global hydrologic and earth-system studies. J. Hydrometeor., 15:1739–380
1761, 2014.381
[4] van der Wiel K., S. B. Kapnick, G. A. Vecchi, W. F. Cooke, T. L. Delworth, L. Jia, H. Mu-382
rakami, S. Underwood, and F. Zeng. The resolution dependence of contiguous U.S.383
precipitation extremes in response to CO2forcing. J. Climate, 29:7991–8012, 2016.384
[5] Schneider U., E. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese, and B. Rudolf.385
GPCC’s new land surface precipitation climatology based on quality-controlled in situ386
data and its role in quantifying the global water cycle. Theoretical and Applied Clima-387
tology, 115(1-2):15–40, 2013.388
[6] Rienecker M. M., M. J. Suarez, R. Gelaro, R. Todling, J. Bacmeister, E. Liu, M. G.389
Bosilovich, S. D. Schubert, L. Takacs, G.-K. Kim, S. Bloom, J. Chen, D. Collins,390
A. Conaty, A. da Silva, W. Gu, J. Joiner, R. D. Koster, R. Lucchesi, A. Molod, T. Owens,391
S. Pawson, P. Pegion, C. R. Redder, R. Reichle, F. R. Robertson, A. G. Ruddick,392
M. Sienkiewicz, and J. Woollen. MERRA: NASA’s Modern-Era Retrospective analy-393
sis for Research and Applications. J. Climate, 24:3624–3648, 2011.394
[7] Rayner N., D. E. Parker, E. Horton, C. Folland, L. Alexander, D. Rowell, E. Kent, and395
A. Kaplan. Global analyses of sea surface temperature, sea ice, and night marine air396
temperature since the late nineteenth century. J. Geophys. Res., 108:4407, 2003.397
16
[8] World Meteorological Organization. Technical Regulations. Volume 1, WMO-No. 49,398
Geneva, 1988.399
[9] Moorthi S. and M J Suarez. Relaxed Arakawa-Schubert: A parameterization of moist400
convection for general circulation models . Mon. Wea. Rev., 120:978–1002, 1992.401
17
Acknowledgements402
S. P. was supported by the NOAA Climate and Global Change Postdoctoral Fellowship Pro-403
gram, administered by the University Corporation for Atmospheric Research, Boulder, Col-404
orado and by the NOAA CICS grant - NA14OAR4320106. S.B. acknowledges support from405
the Caltech Davidow Discovery Fund. The authors thank Nathaniel Johnson and Honghai406
Zhang for comments on the manuscript.407
Author contributions408
S.P. designed the research and performed the analysis of the data. S. P. lead the writing409
with the assistance of S.B., S.B.K. and W.R.B.. S.P., W.R.B., S.B. and T.L.D. contributed to410
define the methods and to interpret the results. All authors took part in the discussion of the411
results and refined and improved the manuscript. H. M. and G. A. V. designed the model412
experiments. H. M. and W. Z. performed the simulations.413
Competing financial interests414
The authors declare no competing financial interests.415
18
1 Figures416
19
110W 100W 90W 80W 80W
10N
20N
30N
40N
Observed precipitation--GPCC
120W120W 120W
120W120W
110W 100W 90W
10N
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MERRA
80g/kg*ms-1
80
80g/kg*ms-1
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LOAR
110W 100W 90W 80W
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FLOR
110W 100W 90W 80W
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0.5 1 1.5 2 2.5 3 4 6 8 10 12 15
Precipitation (mm/day)
NAM
domain
a b c
d e f
2 4 6 8 10 12
0
50
100
150
Rainfall seasonality
monthly precipitation (mm)
GPCC
LOAR
FLOR-FA
FLOR
Months
Figure 1: High-resolution flux-adjusted models better capture regional features of the North
American monsoon. a, Time-mean (July-August) observed precipitation from GPCC (1971-2010).
The blue contour delimits the area used for averaging over the North American monsoon in fand the
magenta line the transect used for vertical cross-sections in Fig. 3. Precipitation (shading) and 10m-
moisture flux (vectors) in b, MERRA reanalysis (1979-2010); c, LOAR, d; FLOR and e, FLOR-FA
control runs (see Table 1 for description of experiments). f, Seasonal cycle of monthly precipitation
averaged over the North American monsoon domain in observations and models. Shading denotes
the interannual variability spread in observations.
20
110W 100W 90W 80W
10N
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30N
40N
June
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-50 -40 -30 -25 -20 -15 -10 -2 2 10 15 20 25 30 40 50
Precipitation Change (%)
a b c
d e f
1
4
1
Figure 2: Impact of increased CO2concentration and SST biases on the North American mon-
soon precipitation. Percent precipitation change induced by CO2doubling in FLOR-FA simula-
tions (%, color shading; 2CO2_FLOR-FA minus CTRL_FLOR-FA) in aJune, b, July-August, and c,
September-October. d-f, As in a-cbut for FLOR simulations (2CO2_FLOR minus CTRL_FLOR).
Grey contours denote climatological values of precipitation (mm/day) in the respective control runs.
Stippling indicates regions where precipitation differences are statistically significant at the 5 % level
on the basis of a t-test.
21
0
5 10 15 20 25 30 35 40
1000
800
600
400
200
Pressure (hPa)
0
10
5 10 15 20 25 30 35 40
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800
600
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5 10 15 20 25 30 35 40
Latitude
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Latitude
-5 -4 -3 -2 -1 -0.5 -0.1 0 0.1 0.5 1 2 3 4 5
kJ kg 10 kg m s
SMO
SMO
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SMO
SMO
SMO
LFC
LFC
LFC
LCL
LCL
LCL
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-20
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-1
a d
b e
c f
Figure 3: CO2-induced warming strengthens convective inhibition and weakens convection
over land. Difference in a, June, b, July-August and c, September-October mean buoyancy between
doubled CO2and control FLOR-FA simulations (color shading; see Methods for details on buoyancy
calculations). Stippling denotes statistical significance, black lines denote climatological values of
buoyancy, LFC the level of free convection (zero buoyancy), and LCL the lifted condensation level.
Buoyancy values below the LCL are not shown because the relationship between buoyancy and moist
static energy does not hold for an unsaturated parcel. d-f, As in a-cbut for the cumulus convective
mass flux. The vertical transect is at 108W (pink line in Fig. 1a) and intersects the Sierra Madre
Occidental (SMO) at approximately 28N. The blue line encircles areas over land where there is a
significant buoyancy negative anomaly. 22
120W 100W 80W 60W 40W
0
10N
20N
30N
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60W140W
Figure 4: Attribution of projected North American monsoon precipitation changes. a, North
American monsoon area-averaged (defined in Fig. 1) precipitation change attributed to each experi-
ment (Table 1): 2CO2(red), +2K (green), 2CO2_+2K (blue), 2CO2_pattern (brown) and the coupled
2CO2_FLOR-FA simulations (yellow for the ensemble member 1, orange for the ensemble member
2). Error bars denote the 95% confidence interval. b, Percent July precipitation change induced by
patterns of SST anomalies (2CO2_pattern minus 2CO2_+2K). Yellow contours denote the 2CO2_+2K
climatology (mm/day). c, Areas of SST cooling and warming in the 2CO2_pattern run relative to the
2CO2_+2K run (uniform +2 K rise). Pink contours denote the 2CO2_+2K climatology (K). In both b
and c, stippling indicates regions where precipitation differences are statistically significant at the 5 %
level on the basis of a t-test. 23
List of Figures417
1High-resolution flux-adjusted models better capture regional features of418
the North American monsoon. a, Time-mean (July-August) observed pre-419
cipitation from GPCC (1971-2010). The blue contour delimits the area used420
for averaging over the North American monsoon in fand the magenta line the421
transect used for vertical cross-sections in Fig. 3. Precipitation (shading) and422
10m-moisture flux (vectors) in b, MERRA reanalysis (1979-2010); c, LOAR,423
d; FLOR and e, FLOR-FA control runs (see Table 1 for description of exper-424
iments). f, Seasonal cycle of monthly precipitation averaged over the North425
American monsoon domain in observations and models. Shading denotes426
the interannual variability spread in observations. . . . . . . . . . . . . . . . 20427
2Impact of increased CO2concentration and SST biases on the North428
American monsoon precipitation. Percent precipitation change induced by429
CO2doubling in FLOR-FA simulations (%, color shading; 2CO2_FLOR-FA mi-430
nus CTRL_FLOR-FA) in aJune, b, July-August, and c, September-October.431
d-f, As in a-cbut for FLOR simulations (2CO2_FLOR minus CTRL_FLOR).432
Grey contours denote climatological values of precipitation (mm/day) in the433
respective control runs. Stippling indicates regions where precipitation differ-434
ences are statistically significant at the 5 % level on the basis of a t-test. . . . 21435
24
3CO2-induced warming strengthens convective inhibition and weakens436
convection over land. Difference in a, June, b, July-August and c, September-437
October mean buoyancy between doubled CO2and control FLOR-FA simula-438
tions (color shading; see Methods for details on buoyancy calculations). Stip-439
pling denotes statistical significance, black lines denote climatological values440
of buoyancy, LFC the level of free convection (zero buoyancy), and LCL the441
lifted condensation level. Buoyancy values below the LCL are not shown be-442
cause the relationship between buoyancy and moist static energy does not443
hold for an unsaturated parcel. d-f, As in a-cbut for the cumulus convective444
mass flux. The vertical transect is at 108W (pink line in Fig. 1a) and inter-445
sects the Sierra Madre Occidental (SMO) at approximately 28N. The blue446
line encircles areas over land where there is a significant buoyancy negative447
anomaly. ...................................... 22448
4Attribution of projected North American monsoon precipitation changes.449
a, North American monsoon area-averaged (defined in Fig. 1) precipitation450
change attributed to each experiment (Table 1): 2CO2(red), +2K (green),451
2CO2_+2K (blue), 2CO2_pattern (brown) and the coupled 2CO2_FLOR-FA452
simulations (yellow for the ensemble member 1, orange for the ensemble453
member 2). Error bars denote the 95% confidence interval. b, Percent July454
precipitation change induced by patterns of SST anomalies (2CO2_pattern455
minus 2CO2_+2K). Yellow contours denote the 2CO2_+2K climatology (mm/day).456
c, Areas of SST cooling and warming in the 2CO2_pattern run relative to the457
2CO2_+2K run (uniform +2 K rise). Pink contours denote the 2CO2_+2K cli-458
matology (K). In both band c, stippling indicates regions where precipitation459
differences are statistically significant at the 5 % level on the basis of a t-test. 23460
25
Experiment yrs Radiative forcing/boundary conditions Purpose
a) CTRL_FLOR 200 CO2constant at 1990 levels Control run
b) CTRL_FLOR-FA 200 CO2constant at 1990 levels Control run; Reduce SST biases
c) 2CO2_FLOR 200 CO2doubles in 70 yrs, then constant CO2forcing
d) 2CO2_FLOR-FA 200 CO2doubles in 70 yrs, then constant CO2forcing; Reduce SST biases
1) CLISST 50 Model SST restored to observed climatological (1971-2012) values Remove SST biases
2) 2CO250 Model SST restored as in CLISST; atmospheric CO2concentration is Impact of 2CO2only
doubled relative to 1990 levels
3) +2K 50 Model SST restored to observed climatological SST plus 2K (no warming Impact of mean SST increase only
pattern); CO2concentration is held at 1990 values
4) 2CO2_+2K 50 Model SST restored to observed climatological SST plus 2K (no warming Combined impact of mean
pattern); CO2is doubled relative to 1990 levels SST increase and 2CO2
5) 2CO2_pattern 50 Model SST restored to observed climatological SST plus warming pattern Combined impact of nonuniform
from a long coupled 2CO2run; CO2is doubled relative to 1990 levels SST anomaly and 2CO2
Table 1: Description of the coupled (a-d) and nudged-SST (1-5) experiments used in this study (see Methods for further details). Two ensemble members
are available for experiments CTRL_FLOR, CTRL_FLOR-FA, 2CO2_FLOR and 2CO2_FLOR-FA.
26
... This finding is consistent with the 'warmer-get-wetter' paradigm, which posits that the largest increases in precipitation co-occur with regions with the warmest SST anomalies, especially in the tropics (25). This mechanism has also been shown to play a role in future simulations of the NAM in models (26). To assess the Plio-Pleistocene relationship between coastal warming and monsoon rainfall, we compare our XD ? ...
... Indeed, a bias-corrected global model shows robust decreases in monsoon rainfall across all seasons (26,36), in contrast to previous work (14,33). This result is due in part to reduced California margin warming compared to the tropical eastern Pacific (26,37). ...
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... Identifying effects of climate variation on black-headed grosbeak populations and their habitats will be critical for the conservation of this and other species that utilize seasonally arid habitats across western North America given observed and predicted climatic shifts due to climate change. Some observed and predicted effects of climate change in areas used by this species across the annual cycle include severe drought and reduced vegetation productivity on breeding grounds (Diffenbaugh et al., 2015;Goulden & Bales, 2019;Trujillo et al., 2012;Williams et al., 2020), changes in the timing and amount of rainfall on the molting grounds (Cook & Seager, 2013;Grantz et al., 2007;Méndez-Barroso et al., 2009;Pascale et al., 2017), and warmer drier conditions on the wintering grounds (Karmalkar et al., 2011;Neelin et al., 2006). (Wang et al., 2016), with a goal of assessing potential environmental drivers of vital rates and population dynamics in two breeding regions, the Sierra Nevada mountain range of California (hereafter Sierra Nevada) and along the coast and Central Valley of (hereafter Coastal California). ...
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... Studies have noted such rainfall biases that reduce the confidence in NAM climate projections, including local and remote biases that can lead to large uncertainties. In particular, horizontal resolution are critical for representing the NAM in models, with horizontal grid spacing coarser than 100 km failing to fully resolve key topographic features and low-level flow along the Gulf of California, as well as the influence of subgrid-scale model parameterization (Pascale et al., 2016(Pascale et al., , 2017. Additionally, stronger SST biases from the tropical Atlantic stimulate overestimation in precipitation in the western United States and Mexico (Johnson et al., 2020). ...
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... There is much larger uncertainty in forecasts of warm-season precipitation driven by the North American Monsoon, which, on average, contributes approximately 40% of annual precipitation in the southwestern United States (Higgins et al., 1999). While some models show a weakening of warm-season precipitation (Pascale et al., 2017), others have forecasted no change and mixed responses (Colorado-Ruiz et al., 2018;Cook & Seager, 2013;Seth et al., 2011), or increases in North American Monsoon moisture (Luong et al., 2017). Regional forecasts that are better able to incorporate topography than many general circulation models generally show high elevation sites will likely have future increases, and low elevation sites may experience decreases in monsoon precipitation (Pascale et al., 2019). ...
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Primary production in dryland ecosystems is limited by water availability and projected to be strongly affected by future shifts in seasonal precipitation. Warm‐season precipitation derived from the North American Monsoon contributes 40% of annual precipitation to dryland ecosystems in the southwestern U.S. and is projected to become more variable. However, there is large uncertainty on whether this variability will be expressed as either extreme wet or dry years and how primary production of different plant functional types will respond across widespread elevation gradients in this region. We experimentally imposed extreme drought and water addition treatments from 2016 – 2020, during which ambient warm‐season precipitation declined to reach historic lows, to understand production sensitivity of dominant plant functional types along a 1,000 m elevation gradient. We found that the production responses of plant functional types to monsoon precipitation extremes were dependent on the number of treatment years that occurred across sites along the elevation gradient. C4 perennial grasses were most responsive to precipitation manipulation treatments, followed by C3 perennial grasses and annuals, while perennial forbs and shrubs had weak or no responses. C4 perennial grass reductions due to extreme drought were generally stronger or occurred earlier at low elevation sites, while multi‐year extreme drought extended negative effects to C3 perennial grasses at high elevation, and all sites showed delayed responses to multi‐year water addition. We found that the sensitivity of C3 perennial grass production differed for extreme drought and water addition compared to ambient precipitation at one site, but other sites and plant functional types had similar sensitivities to the different treatment types. Synthesis. The upward advance of primary production responsiveness from single‐ to multi‐year extreme changes in warm‐season precipitation suggests more immediate shifts in functional composition and carbon cycling at low elevation, while high elevation ecosystems may become less resistant as the effects of extreme precipitation compound through time.
... This could allow more time between each event for instability to build up, leading to increased convective available potential energy (CAPE) and more intense precipitation when deep convection does occur. Increased CIN under warming in convective regions has been found by several modeling studies (Pascale et al. 2017;Chen et al. 2020;Grabowski and Prein 2019;Kendon et al. 2019). In Chen et al. (2020) and Grabowski and Prein (2019) the increased CIN was mainly associated with a reduction in RH over land, which is driven by a greater increase of land temperatures than of the moisture supply from the oceans (Chadwick et al. 2016;Byrne and O'Gorman 2016), combined with changes in plant physiology and soil moisture (Berg et al. 2016). ...
Article
Global warming is changing the intensity distribution of daily precipitation, with an increased frequency of heavy precipitation and reduced frequency of light/moderate precipitation in general circulation model (GCM) projections. Projected future CMIP5 GCM changes in regional daily precipitation distribution can be described by a combination of two idealized modes: a frequency decrease mode, representing a reduction in the frequency of precipitation at all rain rates; and a frequency shift mode, where the distribution shifts toward heavier rain rates. A decrease in daily precipitation frequency and an increase in intensity are projected in most regions, but the magnitude of change shows large regional variations. The two modes generally capture the projected shift from light/moderate to heavy rain rates but do not recreate GCM changes at the very highest and lowest rain rates. We propose a simple framework for deep convective precipitation change based on the dry static energy (DSE) budget, which provides a physical explanation of these idealized modes in regions and seasons where deep convection dominates precipitation. One possibility is that a frequency decrease mode is driven by increased convective inhibition (CIN). In this DSE framework, increased moisture under warming could influence the shape of the precipitation intensity distribution, particularly at the highest rain rates, but does not govern the overall magnitude of the shift to heavier rain rates, which is not well described by the Clausius–Clapeyron relationship. Changes in daily regional precipitation are not free to respond only to local changes (in e.g., moisture) but are also constrained by the DSE budget, particularly by DSE transport associated with the large-scale circulation.
... In the western US-where population centers and important transportation, water, and power infrastructure are situated at elevations ranging from sea level to above 2000 m-understanding current and future elevation profiles of extreme heat stress would aid in assessing the competing effects of projected large extreme-temperature increases (Barnston et al 2020): circulation and vegetation changes lead to strong drying and heightened wildfire risk (Mankin et al 2017, Brown et al 2021, but a weaker North American Monsoon and stronger evapotranspiration lead to increases in water vapor (Pascale et al 2017). In the eastern US, elevation variability is smaller than in the West but absolute humidities and thus baseline heat stress values are higher, creating the potential for notable divergence from regional means in mountain and coastal communities. ...
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Increasing severity of extreme heat is a hallmark of climate change. Its impacts depend on temperature but also on moisture and solar radiation, each with distinct spatial patterns and vertical profiles. Here, we consider these variables’ combined effect on extreme heat stress, as measured by the environmental stress index, using a suite of high-resolution climate simulations for historical (1980-2005) and future (2074-2099, RCP8.5) periods. We find that observed extreme heat stress drops off nearly linearly with elevation above a coastal zone, at a rate that is larger in more humid regions. Future projections indicate dramatic relative increases whereby the historical top-1% summer heat stress value may occur on about 25-50% of future summer days under the RCP8.5 scenario. Heat stress increases tend to be larger at higher latitudes and in areas of greater temperature increase, although in the southern and eastern US moisture increases are nearly as important. Imprinted on top of this dominant pattern we find secondary effects of smaller heat stress increases near ocean coastlines, notably along the Pacific coast, and larger increases in mountains, notably the Sierra Nevada and southern Appalachians. This differential warming is attributable to the greater warming of land relative to ocean, and to larger temperature increases at higher elevations outweighing larger water-vapor increases at lower elevations. All together, our results aid in furthering knowledge about drivers and characteristics that shape future extreme heat stress at scales difficult to capture in global assessments.
... In the Southwestern U.S., some models predict little change in total summer precipitation (Gutzler and Robbins, 2011). Other models forecast increasingly extreme and irregular rain events delivering less rain overall (Seager et al., 2007) and extended pre-monsoon hyper-arid periods (Notaro et al., 2010;Cook and Seager, 2013;Pascale et al., 2017). However, empirical evidence in these regions demonstrates that aridity is increasing (Maurer et al., 2020), and prolonged and severe droughts are already occurring (Cook et al., 2021;Zhang et al., 2021). ...
Article
Predicted climate change extremes, such as severe or prolonged drought, may considerably impact carbon (C) and nitrogen (N) cycling in water-limited ecosystems. However, we lack a clear and mechanistic understanding of how extreme climate change events impact ecosystem processes belowground. This study investigates the effects of five years of reoccurring extreme growing season drought (66% reduction, extreme drought treatment) and two-month delay in monsoon precipitation (delayed monsoon treatment) on belowground productivity and biogeochemistry in two geographically adjacent semi-arid grasslands: Chihuahuan Desert grassland dominated by Bouteloua eriopoda and Great Plains grassland dominated by B. gracilis. After five years, extreme drought reduced belowground net primary productivity (BNPP) in the Chihuahuan Desert grassland but not in the Great Plains grassland. Across both grasslands, extreme drought increased soil pH and available soil nutrients nitrate and phosphate. The delayed monsoon treatment reduced BNPP in both grasslands. However, while available soil nitrate decreased in the Chihuahuan Desert grassland, the delayed monsoon treatment had little effect on soil ecosystem properties. Extreme drought and delayed monsoon treatments did not significantly impact soil microbial biomass, exoenzyme potentials, or soil C stocks relative to ambient conditions. Our study demonstrates that soil microbial biomass and exoenzyme activity in semi-arid grasslands are resistant to five years of extreme and prolonged growing season drought despite changes to soil moisture, belowground productivity, soil pH, and nutrient availability.
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Extremes in temperature and precipitation are associated with damaging floods, prolonged drought, destructive wildfires, agricultural challenges, compromised human health, vulnerable infrastructure, and threatened ecosystems and species. Often, the steady and progressive trends (or presses) of rising global temperature are the central focus in how climate impacts are described. However, observations of extreme weather events (or pulses) increasingly show that the intensity, duration and/or frequency of acute events are also changing, resulting in greater impacts on communities and the environment. Describing how the influence of extreme events may shape water management in the Colorado River Basin in clear terms is critical to sound future planning and efforts to manage risk. Three scenario planning workshops in 2019 and 2020 were held as part of a Colorado River Conversations series, identifying potential impacts from multiple intersecting extreme events. Water managers identified climate‐related events of concern in the Colorado River Basin that necessitate greater attention and adaptive responses. To support efforts to include consideration of climate‐change‐driven extremes in water management and planning, we explore the current state of knowledge at the confluence of long‐term climate shifts and extreme weather in the Colorado River Basin related to the events of concern that were identified by scenario planning participants.
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Long-term changes in North American monsoon (NAM) precipitation intensity in the southwestern United States are evaluated through the use of convective-permitting model simulations of objectively identified severe weather events during "historical past" (1950-70) and "present day" (1991-2010) periods. Severe weather events are the days on which the highest atmospheric instability and moisture occur within a long-term regional climate simulation. Simulations of severe weather event days are performed with convective-permitting (2.5 km) grid spacing, and these simulations are compared with available observed precipitation data to evaluate the model performance and to verify any statistically significant model-simulated trends in precipitation. Statistical evaluation of precipitation extremes is performed using a peaks-over-threshold approach with a generalized Pareto distribution. A statistically significant long-term increase in atmospheric moisture and instability is associated with an increase in extreme monsoon precipitation in observations and simulations of severe weather events, corresponding to similar behavior in station-based precipitation observations in the Southwest. Precipitation is becoming more intense within the context of the diurnal cycle of convection. The largest modeled increases in extreme-event precipitation occur in central and southwestern Arizona, where mesoscale convective systems account for a majority of monsoon precipitation and where relatively large modeled increases in precipitable water occur. Therefore, it is concluded that a more favorable thermodynamic environment in the southwestern United States is facilitating stronger organized monsoon convection during at least the last 20 years.
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Changes in extreme precipitation are among the most impact-relevant consequences of climate warming, yet regional projections remain uncertain due to natural variability and model deficiencies in relevant physical processes. To better understand changes in extreme precipitation, they may be decomposed into contributions from atmospheric thermodynamics and dynamics, but these are typically diagnosed with spatially aggregated data or using a statistical approach that is not valid at all locations. Here we decompose the forced response of daily regional scale extreme precipitation in climate-model simulations into thermodynamic and dynamic contributions using a robust physical diagnostic. We show that thermodynamics alone would lead to a spatially homogeneous fractional increase, which is consistent across models and dominates the sign of the change in most regions. However, the dynamic contribution modifies regional responses, amplifying increases, for instance, in the Asian monsoon region, but weakening them across the Mediterranean, South Africa and Australia. Over subtropical oceans, the dynamic contribution is strong enough to cause robust regional decreases in extreme precipitation, which may partly result from a poleward circulation shift. The dynamic contribution is key to reducing uncertainties in future projections of regional extreme precipitation. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.
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A 20-km regional climate model (RCM) dynamically downscaled the Community Climate System Model version 4 (CCSM4) to compare 32-year historical and future “end-of-the-century” climatologies of the North American Monsoon (NAM). CCSM4 and other phase 5 Coupled Model Intercomparison Project models have indicated a delayed NAM and overall general drying trend. Here, we test the suggested mechanism for this drier NAM where increasing atmospheric static stability and reduced early-season evapotranspiration under global warming will limit early-season convection and compress the mature-season of the NAM. Through our higher resolution RCM, we found the role of accelerated evaporation under a warmer climate is likely understated in coarse resolution models such as CCSM4. Improving the representation of mesoscale interactions associated with the Gulf of California and surrounding topography produced additional surface evaporation, which overwhelmed the convection-suppressing effects of a warmer troposphere. Furthermore, the improved land–sea temperature gradient helped drive stronger southerly winds and greater moisture transport. Finally, we addressed limitations from inherent CCSM4 biases through a form of mean bias correction, which resulted in a more accurate seasonality of the atmospheric thermodynamic profile. After bias correction, greater surface evaporation from average peak GoC SSTs of 32 °C compared to 29 °C from the original CCSM4 led to roughly 50 % larger changes to low-level moist static energy compared to that produced by the downscaled original CCSM4. The increasing destabilization of the NAM environment produced onset dates that were one to 2 weeks earlier in the core of the NAM and northern extent, respectively. Furthermore, a significantly more vigorous NAM signal was produced after bias correction, with >50 mm month−1 increases to the June–September precipitation found along east and west coasts of Mexico and into parts of Texas. A shift towards more extreme daily precipitation was found in both downscaled climatologies, with the bias-corrected climatology containing a much more apparent and extreme shift.
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Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2° × 2° grid cells (typical resolution in the CMIP5 archive) to 0.25° × 0.25° (tropical cyclone permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities, and seasonal timing. In response to 2 × CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3%–4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the U.S. Southeast; this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.
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The impact of atmosphere and ocean horizontal resolution on the climatology of North American Monsoon Gulf of California (GoC) moisture surges is examined in a suite of global circulation models (CM2.1, FLOR, CM2.5, CM2.6, HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These models feature essentially the same physical parameterizations, but differ in horizontal resolution in either the atmosphere (≃200, 50 and 25 km) or the ocean (≃1°, 0.25°, 0.1°). Increasing horizontal atmospheric resolution from 200 km to 50 km results in a drastic improvement in the model’s capability of accurately simulating surge events. The climatological near-surface flow and moisture and precipitation anomalies associated with GoC surges are overall satisfactorily simulated in all higher-resolution models. The number of surge events agrees well with reanalyses but models tend to underestimate July-August surge-related precipitation and overestimate September surge-related rainfall in the southwestern United States. Large-scale controls supporting the development of GoC surges, such as tropical easterly waves (TEWs), tropical cyclones (TCs) and trans-Pacific Rossby wave trains (RWTs), are also well captured, although models tend to underestimate the TEW/TC magnitude and number. Near-surface GoC surge features and their large-scale forcings (TEWs, TCs, RWTs) do not appear to be substantially affected by a finer representation of the GoC at higher ocean resolution. However, the substantial reduction of the eastern Pacific warm sea surface temperature bias through flux adjustment in the FLOR model leads to an overall improvement of tropical-extratropical controls on GoC moisture surges and the seasonal cycle of precipitation in the southwestern United States.
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In this study ERA-Interim data are used to study the influence of Gulf of California (GoC) moisture surges on the North American monsoon (NAM) precipitation over Arizona and western New Mexico (AZWNM), as well as the connection with larger-scale tropical and extratropical variability. To identify GoC surges, an improved index based on principal component analyses of the near-surface GoC winds is introduced. It is found that GoC surges explain up to 70% of the summertime rainfall over AZWNM. The number of surges that lead to enhanced rainfall in this region varies from 4 to 18 per year and is positively correlated with annual summertime precipitation. Regression analyses are performed to explore the relationship between GoC surges, AZWNM precipitation, and tropical and extratropical atmospheric variability at the synoptic (2-8 days), quasi-biweekly (10-20 days), and subseasonal (25-90 days) time scales. It is found that tropical and extratropical waves, responsible for intrusions of moist tropical air into midlatitudes, interact on all three time scales, with direct impacts on the development of GoC surges and positive precipitation anomalies over AZWNM. Strong precipitation events in this region are, however, found to be associated with time scales longer than synoptic, with the quasi-biweekly and subseasonal modes playing a dominant role in the occurrence of these more extreme events.
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The sources of intermodel uncertainty in regional tropical rainfall projections are examined using a framework of atmosphere-only experiments. Uncertainty is dominated by model disagreement on shifts in convective regions, but the drivers of this uncertainty differ between land and ocean. Over the tropical oceans SST pattern uncertainty plays a substantial role, although it is not the only cause of uncertainty. Over land SST pattern uncertainty appears to be much less influential, and the largest source of uncertainty comes from the response to uniform SST warming, with a secondary contribution from the response to direct CO2 forcing. This may be because a larger number of processes can cause rainfall change in response to uniform SST warming than direct CO2 forcing, and so there is more potential for models to disagree. However, new experiments designed to more accurately decompose the regional climate responses of coupled models, combined with results from high-resolution climate modeling, are needed before these results can be considered robust. The pattern of present-day rainfall does not in general provide emergent constraints on future regional rainfall change. Correlations between relative humidity (RH) change and spatial shifts in convection over many land regions suggest that a proposed causal influence of RH change on dynamical rainfall change is plausible, although causality is not demonstrated here.
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Climate models suffer from long-standing biases, including the double intertropical convergence zone (ITCZ) problem and the excessive westward extension of the equatorial Pacific cold tongue. An atmospheric general circulation model is used to investigate how model biases in the mean state affect the projection of tropical climate change. The model is forced with a pattern of sea surface temperature (SST) increase derived from a coupled simulation of global warming but uses an SST climatology derived from either observations or a coupled historical simulation. The comparison of the experiments reveals that the climatological biases have important impacts on projected changes in the tropics. Specifically, during February-April when the climatological ITCZ displaces spuriously into the Southern Hemisphere, the model overestimates (underestimates) the projected rainfall increase in the warmer climate south (north) of the equator over the eastern Pacific. Furthermore, the global warming-induced Walker circulation slowdown is biased weak in the projection using coupled model climatology, suggesting that the projection of the reduced equatorial Pacific trade winds may also be underestimated. This is related to the bias that the climatological Walker circulation is too weak in the model, which is in turn due to a too-weak mean SST gradient in the zonal direction. The results highlight the importance of improving the climatological simulation for more reliable projections of regional climate change.
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Precipitation exhibits a significant rapid adjustment in response to forcing, which is important for understanding long-term climate change. In this study, fixed sea surface temperature (SST) simulations are used to analyze the spatial pattern of the rapid precipitation response. Three different forcing scenarios are investigated using data obtained from phase 5 of CMIP (CMIP5): an abrupt quadrupling of CO2, an abrupt increase in sulfate, and an abrupt increase in all anthropogenic aerosol levels from preindustrial to present day. Analysis of the local energy budget is used to understand the mechanisms that drive the observed changes. It is found that the spatial pattern of the rapid precipitation response to forcing is primarily driven by rapid land surface temperature change, rather than the change in tropospheric diabatic cooling. As a result, the pattern of response due to increased CO2 opposes that due to sulfate and all anthropogenic aerosols, because of the opposing surface forcing. The rapid regional precipitation response to increased CO2 is robust among models, implying that the uncertainty in long-term changes is mainly associated with the response to SST-mediated feedbacks. Increased CO2 causes rapid warming of the land surface, which destabilizes the troposphere, enhancing convection and precipitation over land in the tropics. Precipitation is reduced over most tropical oceans because of a weakening of overturning circulation and a general shift of convection to over land. Over most land regions in the midlatitudes, circulation changes are small. Reduced tropospheric cooling therefore leads to drying over many midlatitude land regions.
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This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for the North American monsoon system in the southwestern United States and northwestern Mexico. The focus is on changes in precipitation and the processes driving the projected changes from the regional climate simulations and their driving coupled atmosphere-ocean global climate models. The effect of known biases on the projections is also examined. Overall, there is strong ensemble agreement for a large decrease in precipitation during the monsoon season; however, this agreement and the magnitude of the ensemble-mean change is likely deceiving, as the greatest decreases are produced by the simulations that are the most biased in the baseline/current climate. Furthermore, some of the greatest decreases in precipitation are being driven by changes in processes/phenomena that are less credible (e.g., changes in El Niño-Southern Oscillation, when it is initially not simulated well). In other simulations, the processes driving the precipitation change may be plausible, but other biases (e.g., biases in low-level moisture or precipitation intensity) appear to be affecting the magnitude of the projected changes. The most and least credible simulations are clearly identified, while the other simulations are mixed in their abilities to produce projections of value.