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Mechanical forcing of the North American monsoon
by orography
William Boos ( william.boos@berkeley.edu )
University of California, Berkeley
Salvatore Pascale
University of Bologna
Physical Sciences - Article
Keywords: monsoon, rainfall, global climate change
DOI: https://doi.org/10.21203/rs.3.rs-514304/v1
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
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Mechanical forcing of the North American monsoon1
by orography2
William R. Boos1,2,* and Salvatore Pascale3
3
1Department of Earth and Planetary Science, University of California, Berkeley, USA4
2Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, USA5
3Department of Physics and Astronomy, University of Bologna, Italy6
*billboos@alum.mit.edu7
ABSTRACT
8
The core of the North American monsoon consists of a band of intense rainfall along the west coast of Mexico
1,2
and is
commonly thought to be caused by thermal forcing from both land and the elevated terrain of that region
3–5
. Here we use
observations, a global climate model, and stationary wave solutions to show that this rainfall maximum is instead generated
when Mexico’s Sierra Madre mountains mechanically force an adiabatic stationary wave by diverting extratropical eastward
winds toward the equator; eastward, upslope flow in that wave lifts warm and moist air to produce convective rainfall. Land
surface heat fluxes do precondition the atmosphere for convection, particularly in summer afternoons, but even if amplified are
insufficient for producing the observed rainfall maximum. These results, together with dynamical structures in observations and
models, indicate that the core monsoon should be understood as convectively enhanced orographic rainfall in a mechanically
forced stationary wave, not as a classic, thermally forced tropical monsoon. This has implications for the response of the North
American monsoon to past and future global climate change, making trends in jet stream interactions with orography of central
importance.
9
1 Introduction10
Tropical monsoons occur when a surface of low heat capacity transfers the energy of intense summer solar radiation to the
11
overlying atmosphere, creating thermally direct, precipitating flow. Such circulations supply water to billions of people and set
12
the climate of large swaths of Earth’s surface. The North American monsoon (NAM) is commonly viewed in this paradigm,
13
being a low-latitude summer circulation crucial for the hydrology of western Mexico and the southwestern US1,2,6,7.14
As in many tropical regions, North American orography alters the simple description of monsoon flow provided above. The
15
core NAM consists of a narrow tongue of high precipitation stretching over 1,000 km north-south along the western side of
16
the Sierra Madre Occidental (SMO) mountains (Fig. 1a). Drier conditions lie east of this precipitation maximum, in central
17
Mexico and Texas, and atmospheric subsidence occurs to the west-northwest due to baroclinic Rossby waves forced by the
18
latent heating8–10.19
The mechanisms that produce this strong organization of NAM precipitation around orography remain unclear. Early global
20
climate model (GCM) simulations showed that NAM rainfall decreases greatly when mountains are flattened globally
11
. Some
21
argue that this occurs because sensible heat fluxes from orography into elevated levels of the atmosphere cause NAM rainfall
3
,
22
drawing water vapor from the Gulf of California up SMO slopes to condense and precipitate
2,12,13
. The high-amplitude diurnal
23
cycle of precipitation in the NAM has also been taken to suggest the importance of orographic thermal forcing. Shallow
24
convection begins around noon over SMO peaks and deep convection follows a few hours later on the western slopes
14
.
25
Near-surface air flows upslope during the day and downslope at night
15,16
, as expected for a sea breeze or mountain-valley
26
breeze driven by solar heating. Despite the prominence of this diurnal cycle, horizontal moisture fluxes produced by transients
27
(e.g., diurnally reversing sea breeze circulations) are an order of magnitude smaller in the core NAM than those produced by
28
seasonal mean winds
16
. Thus, sea breeze circulations are observationally striking in the NAM, but their winds average to zero
29
over 24 hours; core NAM precipitation must be controlled by the forcings that produce seasonal mean flow.30
The mechanical, rather than thermal, effects of orography are known to drive the summer circulation east and northeast of
31
the NAM, in the central US. A GCM and stationary wave model were used to show that the eastern Sierra Madre deflect trade
32
winds northward to become the Great Plains low level jet
17,18
, which transports water into the central US from the Gulf of
33
Mexico but is not traditionally seen as a main NAM component. Some authors
19
have considered orographic elevated heating
34
and orographic blocking of zonal winds to both be plausible NAM causes, but models integrated at resolutions fine enough to
35
resolve the SMO and core NAM20–22 have not been used to distinguish between these possibilities.36
Our goal is to determine the mechanisms that cause the intense rainfall maximum in the core NAM. Is it generated primarily
37
by a thermodynamic forcing (e.g. elevated heating) or a mechanical one (mechanical blocking)? Given the prior finding that
38
time-mean vertically integrated moisture flux convergence in the core NAM is produced by time-mean winds
16
, this task
39
amounts to determining the cause of the seasonal-mean eastward, upslope flow over the SMO.40
2 Net response to orography41
We integrate a high-resolution (0.25
◦
-grid spacing) GCM twice: once with observed orography (Control) and again with
42
surface height set to zero over nearly all of Mexico (FlatMex). This GCM, which uses prescribed sea surface temperature
43
(SST), produces a realistic seasonal cycle and spatial pattern of NAM precipitation and wind in the Control run (Fig. 1a, b
44
and Supplementary Figs. S1-S3; the model has a positive precipitation bias but its climatology falls in the range of observed
45
interannual variability). The model resolves the SMO as a
∼
3 km-high ridge along Mexico’s west coast, and reproduces
46
observed eastward low-level winds extending roughly 1000 km west of that ridge (Fig. 1a, b). This wind distribution is
47
suggestive of the midlatitude eastward jet being deflected toward the equator by the SMO; the broader North American
48
cordillera is known to deflect the jet in such a stationary wave
17
, but the equatorial part of that wave has not previously been
49
argued to play a role in the NAM, nor has it been adequately resolved in stationary wave models of the region.50
We obtain the net response to all dynamic and thermodynamic effects of Mexico’s orography by subtracting the FlatMex
51
state from the Control. Nearly all core NAM precipitation is caused by local orography, with the rainfall maximum on Mexico’s
52
west coast disappearing in the FlatMex state despite the continued land surface thermal forcing (Fig. 1c). Without the SMO,
53
westward trade winds span most of Mexico, separating two zones of eastward flow: one in the extratropics and another in
54
the oceanic intertropical convergence zone (ITCZ) south of Mexico (near 15
◦
N). The region of high near-surface moist static
55
energy (MSE), which in observations and the Control is confined to the Gulf of California and the Gulf of Mexico, expands
56
inland to cover central Mexico when orography is flattened (Fig. 1d; surface air MSE is hereafter written
hs
and expressed in
57
temperature units through normalization by the specific heat of air). In the FlatMex state, the distributions of
hs
, precipitation,
58
and wind behave as expected for tropical monsoons, with peak rainfall and low-level eastward flow on the equatorial side of the
59
high-hsregion23,24.60
The wind and
hs
response to the SMO suggests that core NAM precipitation is not forced primarily by orographic elevated
61
heating, which would work by driving the overlying atmospheric column toward a higher-energy state than it would realize
62
over the same surface at sea level
25
. The dynamical response to tropical heatings typically includes poleward flow through the
63
heated region, in Sverdrup balance, with a low-level cyclone to the west
26,27
. Instead, we see anomalous eastward flow over the
64
orographic forcing, with a low-level cyclone to the north and anticyclonic flow to the southwest (Fig. 1d). Orography decreases
65
local
hs
over the SMO and continental Mexico, whereas orographic elevated heating would increase it
25
. However, since much
66
of this reasoning employs comparisons with previous idealized solutions that might be complicated by strong background flows,
67
we now systematically assess the response to separate mechanical and thermal forcings.68
3 Mechanically forced response69
We estimate the response to the mechanical influence of orography with a stationary wave model that has been used to study
70
the Great Plains low-level jet
17
and other orographically influenced circulations
28,29
, but integrated at finer resolution than
71
used previously (see Methods). We impose as a basic state the three-dimensional summer-mean flow from the FlatMex GCM,
72
then use this model to find the adiabatic response to Mexico’s orography (the forcing is the Control-FlatMex surface height
73
anomaly).74
This mechanically forced response consists of a meridional dipole in low-level vorticity, with a cyclone over much of the
75
western US and an anticyclone southwest of Mexico (Fig. 2c). The dynamical structure strongly resembles the GCM response
76
(Control-FlatMex; Fig. 2a), even though the GCM also includes diabatic feedbacks and any orographic thermal forcing. The
77
stationary wave includes anomalous eastward flow upstream of and over the SMO, with a vertical structure and amplitude
78
similar to that of the net GCM response (Fig. 2b, d). This anomalous flow opposes the westward trade winds stretching across
79
Mexico in the basic state. Between the surface and
∼
850 hPa, the total flow (basic state plus stationary wave anomaly) is
80
eastward upstream of and over the SMO western slopes (orange contours in Fig. 2b, d). The stationary wave thus produces the
81
time-mean upslope wind over the western SMO that is observationally associated with moisture convergence and precipitation
82
there16.83
The stationary wave is nonlinear, with isentropes (constant potential temperature surfaces) intersecting orography instead
84
of bowing upward around it
8
(Fig. 2b, d; Supplementary Fig. S4 shows the linear response). Nevertheless, this response is
85
straightforward to understand. When orography is high enough to block zonal winds, adiabatic flow, which in the time mean
86
follows isentropes, must deviate northward or southward depending on where isentropes intersect the ground. In contrast with
87
the basic state used in prior studies of flow perturbed by narrow orography
8
, peak temperatures lie near 38
◦
N, so isentropes over
88
Mexico tilt downward to the north, intersecting the ground over the southwestern US (Fig. 2a, c, and Supplementary Fig. S5).89
2/12
Adiabatic zonal flow must thus ascend and turn southward as it encounters the SMO, because northward flow is blocked as it
90
follows isentropes into the ground. Lower-resolution stationary wave solutions have a weaker anticyclone south of Mexico
91
and give greater prominence to the Great Plains low-level jet (Supplementary Fig. S6), perhaps explaining why orographic
92
mechanical forcing has previously been more closely associated with that circulation17.93
4 Seasonal and diurnal thermodynamic maxima94
How do we reconcile observations of a strong diurnal cycle of precipitation in the core NAM
14–16
with evidence that upslope
95
flow there is produced by a stationary wave? Moist convection requires both a reservoir of convective available potential
96
energy (CAPE) and, typically, some lifting to overcome convective inhibition or release conditional instability. CAPE generally
97
increases with
hs30,31
, and high time-mean
hs
lies over the warm Gulf of California and Gulf of Mexico (Fig. 1d). However,
98
maximum
hs
is achieved in late afternoon over western SMO slopes, at least in one observational estimate (Fig. 3a). The strong
99
diurnal cycle of
hs
, particularly prominent over elevated terrain (Fig. 3b), is caused by solar heating of land, which increases
hs
100
through surface enthalpy fluxes (there is observational uncertainty in the magnitude of the
hs
maximum over the western SMO,
101
but all estimates show high
hs
there with a large diurnal cycle). Thus, a warm and moist air layer from the Gulf of California
102
flows eastward at low levels in the mechanically forced stationary wave, and its MSE is increased further by daytime surface
103
heat fluxes while its temperature drops adiabatically due to upslope flow. In a convectively stable atmosphere this scenario
104
would produce large-scale, stratiform condensation, but nonzero CAPE allows convection to occur. Prior work19 showed that105
the observed CAPE distribution does not explain why NAM precipitation favors the west coast of Mexico versus the east coast;
106
release of CAPE through upslope flow in the stationary wave resolves this issue.107
These effects can be synthesized by examining the seasonal cycle of
hs
and near-surface zonal wind averaged in and
108
upstream of the core NAM region, respectively. Upslope flow peaks in spring, before the observed rainy season, but
hs
is low
109
then so ample convective precipitation is not produced (Fig. 3c). Peak precipitation occurs a few months later when upslope flow
110
is still strong and
hs
has increased to its summer peak. Flattening Mexico’s orography produces a slight increase in summer
hs
,
111
presumably because orography blocks the inland penetration of warm and moist oceanic air, yet NAM precipitation decreases
112
greatly as upslope flow is reduced (Fig. 1c). The seasonality of NAM precipitation thus seems to arise from the seasonal cycle
113
in
hs
(and CAPE) but, consistent with CAPE being a necessary but insufficient condition for convection, mechanically forced
114
ascent in the stationary wave is needed to turn that thermodynamic seasonal cycle into rainfall.115
The
hs
distribution (Fig. 3a) also illustrates the deviation of the spatial structure of the NAM from that of a classic tropical
116
monsoon. In the latter we expect peak rainfall and peak low-level eastward wind on the equatorial side of the
hs
maximum
23,24
.
117
Instead, we observe peak NAM rainfall slightly east of (or even directly over) the peak
hs
, and low-level eastward winds west
118
of the peak
hs
. This suggests that the thermally forced tropical monsoon in the North American region consists of the oceanic
119
precipitation maximum just south of Mexico, which would exist without Mexico’s orography (Fig. 1c); southward deflection of
120
prevailing extratropical winds by the North American cordillera (including the SMO) superimposes on that tropical monsoon
121
the intense band of rainfall along Mexico’s west coast.122
5 Response to a pure thermal forcing123
We now show that if the core NAM were driven primarily by a thermal forcing, it would have a dynamical structure distinct
124
from that in observations. We conduct a third GCM integration with the albedo of the surface that was flattened (most of
125
Mexico) reduced to 0.05 (FlatMexLowAlb). This provides a strong thermal forcing, with land albedo in much of the NAM
126
region reduced below that of open ocean, yielding a local increase of about 20 W m
−2
in the net energy input to the atmosphere
127
(NEI; the sum of radiative and surface turbulent fluxes into each atmospheric column; Fig. 4a). In response, the high
hs
region
128
expands poleward and the oceanic precipitation maximum follows, expanding inland (compare Figs. 4b and 1c, d). Anomalous
129
low-level poleward flow over the region in which the albedo forcing was applied is consistent with the Sverdrup balance
130
achieved in the linear response to tropical thermal forcings
26
. As expected for a thermally forced tropical monsoon
23,24
, peak
131
rainfall lies on the equatorial side of the high-
hs
region, and precipitation increases by about 2 mm day
−1
over the broad region
132
of the albedo forcing (Fig. 1c). In FlatMexLowAlb, there is no precipitation maximum along Mexico’s west coast and no
133
eastward flow extending 1000 km west of the SMO.134
These GCM simulations also suggest that core NAM rainfall is not produced by rectification of the diurnal cycle of
135
precipitation to produce seasonal-mean heating, a hypothesis proposed to explain the enhancement of time-mean precipitation
136
over small islands
32
although not explicitly raised for the NAM. If such a mechanism operated in the NAM, it would need to
137
have an effect stronger than that achieved by the increase in
hs
produced in the FlatMexLowAlb model (Fig. 4) and be confined
138
to the western slopes of the SMO; it would not explain how the SMO produces eastward low-level winds stretching 1000 km
139
west of Mexico.140
3/12
6 Discussion and conclusions141
The NAM is commonly categorized as a thermally forced tropical monsoon. Although one early study stated that it was difficult
142
to determine whether mechanical or thermal effects of orography dominated in forcing the NAM
19
, most previous work has
143
described the NAM as either (i) similar to though smaller in scale than the South Asian monsoon
15
, with a central role played
144
by elevated plateau heating3, or (ii) caused by land-ocean thermal contrast4,8,33.145
We found that a mechanically forced stationary wave produces the seasonal-mean upslope flow associated in prior work
13,16
146
with the water vapor convergence needed to sustain core NAM rainfall. Such stationary waves dominate North American
147
climate in winter
34
, but in summer they have been identified primarily with the Great Plains low level jet
17
. Stationary waves
148
are also forced by the Rockies and other parts of the North American Cordillera, and Baja peninsula orography seems to steer
149
eastward winds toward the equator (Fig. 1c). However, our results suggest that core NAM precipitation requires the SMO,
150
which produce eastward, upslope flow in the region of high hs.151
Mechanically forced stationary waves will be modified in the real atmosphere by moist convective heating, but the
152
resemblance between horizontal winds in the adiabatic stationary wave solutions and in the moist GCM suggests this has only a
153
modest effect on horizontal flow (Fig. 2). Upward motions will be amplified by moist convection; such amplification has been
154
represented using various forms of a reduced effective static stability for convectively coupled equatorial waves
35
, transient
155
off-equatorial vortices
36
, and extratropical precipitation extremes
37
, but a similar theory for moist convective amplification of
156
orographic upslope flow has not been developed.157
These findings have implications for past and future NAM variability, placing new emphasis on the jet stream and trade
158
winds, and their interaction with orography. Changes in the jet stream and trade winds may have been of central importance for
159
NAM changes in paleoclimates. Accurate dynamical forecasts of NAM rainfall will require models with an unbiased jet stream,
160
in addition to resolutions fine enough to represent the SMO. Thermodynamic controls on convection, long thought to dominate
161
NAM rainfall, are important, but their representation in models should be evaluated in terms of how they affect convection in
162
upslope flow. In contrast, surface conditions and convective stability over central Mexico may primarily affect the low amounts
163
(1-2 mm day
−1
) of local summer rainfall received there. Finally, global climate change may alter the NAM through changes
164
in the extratropical jet stream and through changes in convective stability in regions of upslope flow, rather than through its
165
influence on more general land-ocean thermodynamic contrasts.166
7 Methods167
7.1 Observations168
We obtain estimates of Earth’s atmospheric state from ERA5, the fifth-generation atmospheric reanalysis from the European
169
Centre for Medium-Range Weather Forecasts
38–40
. For years 1979-2019, we use ERA5 surface air temperature, surface air
170
dewpoint (which we convert to specific humidity to calculate
hs
), surface height, and 100-meter zonal wind. We also obtain
171
surface air temperature, surface air dewpoint, and surface height from the Modern-Era Retrospective analysis for Research and
172
Applications, Version 2 (MERRA2)
41
. Precipitation estimates are drawn from the Global Precipitation Measurement Mission
173
(GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), Final Precipitation L3 Daily 0.1 degree
×
0.1 degree V06
174
product (GPM_3IMERGDF)42. We averaged years 2001-2020 to obtain the precipitation climatology shown in Fig. 1a. Plots175
of surface height use estimates from the ETOPO1 global relief model
43,44
at 1 arc-minute resolution; surface height used in
176
calculating reanalyzed hsis taken from ERA5 and MERRA2. All quantities are averaged July-September.177
Surface air MSE is also computed for stations along a transect near 28
◦
N using observations of temperature, specific
178
humidity, and height from the North American Monsoon GPS Transect Experiment 2013
45
(measurements collected June-
179
September 2013), and the 2017 North American Monsoon GPS Hydrometeorological Network
46
(hereafter referred to as GPS
180
Hydromet 2017, measurements collected June-September 2017), which uses some of the permanent observation sites of the
181
Trans-boundary, Land and Atmosphere Long-term Observational and Collaborative Network (TLALOCNet)
47
. Data from the
182
GPS Transect Experiment 2013 are available every minute while GPS Hydromet 2017 are at 5-minute intervals. We compute183
hs
for all minutes within the 01 UTC and 13 UTC hours, corresponding to late afternoon and early morning in local time,
184
respectively. We average for all days from July through September for both datasets, and retain only those stations for which
185
there are less then ten days of missing data. Data for stations within 0.5◦latitude of 28◦N were used for the transect.186
7.2 Models187
7.2.1 Global climate model188
Simulations were performed using the Community Atmospheric Model, version 5.1 (CAM5)
48
coupled to the Community
189
Land Model, version 4
49
, within the software infrastructure of the Community Earth System Model (CESM) version 2.1.3.
190
We use the finite-volume dynamical core, which is typically configured with a horizontal resolution of 0.9
◦
(latitude) by 1.3
◦
191
(longitude); to better resolve the topography of the NAM region, we use a global horizontal resolution of 0.23
◦×
0.31
◦
(i.e.,
192
4/12
approximately 25 km at the equator) with 30 vertical levels. We use the Sea ICE model (CICE) version 5 with prescribed ice
193
cover and prescribed cyclic sea surface temperature (SST) from the year 2000. This model configuration is largely the same
194
as that used in projections of the future behavior of tropical cyclones
50,51
, and prior work has shown that the finer horizontal
195
resolution used here improves the representation of the NAM in CAM522.196
As discussed in previous work
20,21,52
, climate models with relatively coarse horizontal resolution fail to resolve features
197
like the Gulf of California and the Sierra Madres, thereby misrepresenting key NAM processes such as Gulf of California
198
moisture surges
2,53,54
, land-sea contrast
55
, and mechanical flow-blocking by orography
56
. Furthermore, SST biases in coupled
199
GCMs can have a detrimental impact on simulation of the NAM, biasing its seasonal evolution to produce a late withdrawal
200
and thus an overly wet late summer and autumn
57–59
. Therefore, using a high resolution configuration with climatological SST
201
reduces the model’s bias and brings the regional circulation closer to observations (Supplementary Figs. S1-S3).202
To assess the influence of elevated terrain on the core NAM, we integrate the model with standard orography (Control) and
203
again with flattened orography over most of Mexico (FlatMex). In the integration with flattened orography over Mexico, we
204
set both the surface height and the subgrid-scale standard deviation of orography to zero within a quadrilateral having these
205
vertices: (33
◦
N, 245
◦
E), (29
◦
N, 265
◦
E), (15
◦
N, 257
◦
E), and (15
◦
N, 265
◦
E). Orography on the Baja Peninsula is unaltered (it
206
lies outside this quadrilateral). To avoid creating a high vertical wall of orography at the northern edge of this quadrilateral,
207
where Mexico’s orography joins the greater North American cordillera, the surface height is set to decrease linearly to zero over
208
2
◦
of latitude immediately south of the northern edge of the quadrilateral; the same procedure is used for the subgrid-scale
209
standard deviation of orography. To help distinguish between the thermal and mechanical influence of orography, we conduct a
210
third integration in which the surface albedo of the flattened land is set to 0.05 (FlatMexLowAlb); this is done for both the
211
direct and diffuse albedo by altering the land model (CLM4). To be clear, this third integration has both flattened orography
212
over Mexico and reduced surface albedo, in an attempt to impose an enhanced thermal forcing without the mechanical effects
213
of orography. All three of these model configurations are run for 11 years of simulated time, with the last 10 years analyzed.214
To understand how orography deflects the midlatitude westerlies toward the equator and then forces convection through
215
upslope flow (Fig. 1), we analyze the time-mean zonal wind on a terrain-following level located within a typical subcloud layer
216
(the atmospheric layer that lies below cloud base). For ERA5 we choose the level 100 m above Earth’s surface, while for the
217
GCM we use the horizontal wind on the third model level above the surface (level 957.5).218
7.2.2 Stationary wave model219
To isolate the mechanical influence of Mexico’s orography on the atmospheric circulation we use a fully nonlinear stationary
220
wave model. The model was introduced by Ting and Yu (1998)
60
, and solves the primitive equations in terms of vorticity,
221
divergence, temperature, and the logarithm of surface pressure, using spherical harmonics
29,61,62
. Important distinctions with
222
the GCM are that the stationary wave model (i) solves these equations for anomalies relative to a specific three-dimensional
223
basic state and (ii) is adiabatic aside from a 15-day Newtonian relaxation of temperature toward the basic state, as used in
224
prior work
34,60
. Transients, such as midlatitude baroclinic instabilities, are suppressed using drag and scale-selective diffusion.
225
Specifically, interior Rayleigh drag on the anomalies is imposed with a 15-day time scale, with surface drag represented by
226
gradually reducing this time scale to 0.3 days over the lowest 4 levels. Biharmonic diffusion with a coefficient of
1017
m
4
227
s
−1
acts on vorticity, divergence, and temperature. The original version of this stationary wave model
60
was created with a
228
rhomboidal truncation at wavenumber 15 (R15 spectral resolution) and 12 vertical levels. Later work integrated the model at
229
R30 resolution with 14 vertical levels28 and R30 resolution with 24 vertical levels29. We enhanced the resolution to R63 with230
24 levels, based on code supplied by Isla Simpson.231
The model was forced by imposing Mexico’s orography on a basic state obtained by time-averaging the summer atmospheric
232
state from the GCM without that orography. Specifically, we obtain the basic state by taking the 10-year July-September
233
average atmospheric state from the FlatMex GCM run, and use the surface height difference between the Control and FlatMex
234
GCM runs as the forcing. The stationary wave model nears a steady state after about 20 days, and is run for 90 days of simulated
235
time with the last 20 used for analysis.236
Data Availability237
The ERA5 monthly averaged data by hour of day were downloaded from the Copernicus Climate Change Service Climate Data
238
Store (identifiers cited in Methods). MERRA-2 and GPM data were downloaded from the NASA Goddard Earth Sciences
239
Data and Information Services Center (GES DISC; identifiers cited in Methods). ETOPO1 data were downloaded from the
240
National Centers for Environmental Information at NOAA, identifiers cited in Methods). David K. Adams provided access to
241
GPS Hydromet 2017, TLALOCNet, and GPS Transect Experiment 2013 data.242
5/12
Code Availability243
The CESM model, which is supported primarily by the National Science Foundation, was obtained from
https://www.244
cesm.ucar.edu
. Isla Simpson provided code for the stationary wave model, the original version of which was written by
245
Mingfang Ting and Linhai Yu.246
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Acknowledgements372
This material is based on work supported by the U.S. Department of Energy, Office of Science, Office of Biological and
373
Environmental Research, Climate and Environmental Sciences Division, Regional and Global Model Analysis Program, under
374
Award DE-SC0019367. It used resources of the National Energy Research Scientific Computing Center (NERSC), which is a
375
DOE Office of Science User Facility. This paper benefited from discussions with Quentin Nicolas, David Adams, Inez Fung,
376
and John C. H. Chiang.377
Author contributions378
WRB conceived the study, devised and performed the GCM and stationary wave model integrations, and analyzed model output.
379
SP assessed the GCM bias. Both authors analyzed observations and contributed to writing the manuscript.380
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Additional information381
Supplementary information is available in the online version of the paper. Reprints and permissions information is available
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online at www.nature.com/reprints. Correspondence and requests for materials should be addressed to WRB.383
Competing financial interests384
The authors declare no competing financial interests.385
Figure 1. Influence of orography on rain and low-level wind. Summer precipitation (shading, mm day−1) and
near-surface eastward wind (orange contours, interval 1 m s
−1
, with the zero contour bold and negative values omitted) for (a)
observations, (b) the control GCM, and (c) the GCM with flattened orography over Mexico. Panel (d) shows the anomalous 700
hPa horizontal wind (vectors) produced by Mexico’s orography in the GCM, and the extent of the region with high surface air
moist static energy (defined as a 2-meter value larger than 345 kJ kg−1) in the control model (black stippling) and the model
with flattened orography over Mexico (red shading). Surface height of 1.5 km is contoured in magenta in all panels.
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Figure 2. Generation of eastward flow across western Mexico by the mechanically forced stationary wave.
Left panels
show streamfunction of the anomalous 700 hPa horizontal wind (shading, in meters; air flows clockwise around maxima) for
(a) the Control-FlatMex GCM integrations and (c) the stationary wave model forced by the Control-FlatMex surface height (1.5
km surface height is contoured in green). The thick orange line is the zero contour of the basic state zonal wind, which near
35◦N divides westward trade winds from prevailing eastward extratropical flow. Thin blue lines show 700 hPa potential
temperature (in K). Right panels show anomalous zonal wind at 26◦N (shading, in m s−1) for (b) the Control-FlatMex GCM
and (d) the stationary wave model, with isentropes plotted in blue (5 K contour interval) and orography masked in white; the
total zonal wind (basic state plus response to orography) is contoured in orange, with a contour interval of 2 m s−1, negative
contours omitted, and the zero contour in bold. Note the total wind is eastward at low levels west of the SMO. Streamfunction
has been normalized by the gravitational acceleration and the value of the Coriolis parameter at 45◦N, giving it the units of
geopotential height.
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Figure 3. Diurnal and seasonal cycles in the North American monsoon. (a) Observed surface air moist static energy
(MSE; shading, from ERA5) at the time of day when MSE peaks (6 pm local time in western Mexico) and orography (1.5 km
surface height contoured in magenta). Blue line marks the location of the zonal section of surface air MSE and surface height
shown in (b), which illustrates the migration of peak MSE from the Gulf of California at 6 am (blue) toward the western Sierra
Madre at 6 pm (orange) local time. In (b), MSE is from the ERA5 (solid lines) and MERRA2 (dashed lines) reanalyses
41
, and
from station data (stars), indicating robustness in the amplitude of the diurnal cycle and the rough location of maxima despite
observational uncertainty. (c) Seasonal cycle of surface air MSE averaged over the NAM region (red lines) and near-surface
zonal wind averaged over and upstream (i.e., west) of that region (black lines; see Supplementary Fig. S7 for averaging regions).
Note the large reduction in eastward flow and small increase in MSE during monsoon season when orography is flattened.
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Figure 4. Response to a pure thermal forcing.
(a) Anomalies, produced by imposing a reduced surface albedo in the GCM
with flattened orography over Mexico, in 700 hPa horizontal wind (vectors) and net energy input through the top and bottom
boundaries of the atmosphere (shading, W m−2). (b) Total precipitation (mm day−1) and the extent of the region with high
surface air moist static energy (defined as a 2-meter value larger than 345 kJ kg−1; black stippling) in the same GCM with
flattened orography and reduced albedo. Compare stippling in (b) with red shading in Fig. 1d to infer the MSE response to the
thermal forcing, and compare shading in (b) with shading in Fig. 1c to infer the precipitation response.
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