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Sumant Nigam
,
Chul Chung
, and
Eric DeWeaver

Abstract

Diabatic heating associated with El Niño–Southern Oscillation (ENSO) variability is residually diagnosed from the European Centre for Medium-Range Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) atmospheric reanalysis datasets during the overlapping 1979–93 period. Quantitative characterization of the horizontal and vertical structure of ENSO heating anomalies, including estimates of uncertainty, provides observationally constrained validation targets for GCM physical parameterizations.

The diagnosed ENSO heating anomalies have similar horizontal structure, but the vertically averaged ECMWF heating is stronger and in better agreement with the Xie–Arkin precipitation anomalies, particularly with respect to precipitation reduction over the western tropical Pacific. Comparison of heating vertical structures in the central equatorial Pacific shows ECMWF heating to be considerably stronger in the lower troposphere, where it exhibits a local maximum.

The ENSO covariant tropospheric temperature in the two reanalyses was also examined along the equator and found to have an intriguing vertical structure, with sizeable amplitude in the lower and upper troposphere and vanishing amplitude in between. The largest temperature anomalies in the lower troposphere are at the surface, and the ECMWF one is about 50% stronger.

The three-dimensional heating anomalies diagnosed from the reanalyses are used to evaluate the ENSO heating distribution produced by NCAR’s Community Climate Model, version 3 (CCM3) atmospheric GCM, when integrated in a climate simulation mode. At least, in context of ENSO variability, the differences in ECMWF and NCEP heating anomalies are small in comparison with CCM3’s heating departures from either of these anomalies, allowing characterization of the CCM3’s ENSO heating structure: horizontally, as a more meridional redistribution (“Hadley-like”), and vertically, as a substantially “bottom-heavy” profile, relative to the reanalyses anomalies.

In a companion paper, deficiencies in the simulated ENSO surface winds are related to specific features of the CCM3’s heating error, from diagnostic modeling.

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Alfredo Ruiz-Barradas
and
Sumant Nigam

Abstract

The present study assesses the potential of the U.S. Climate Variability and Predictability (CLIVAR) Drought Working Group (DWG) models in simulating interannual precipitation variability over North America, especially the Great Plains. It also provides targets for the idealized DWG model experiments investigating drought origin. The century-long Atmospheric Model Intercomparison Project (AMIP) simulations produced by version 3.5 of NCAR’s Community Atmosphere Model (CAM3.5), the Lamont-Doherty Earth Observatory’s Community Climate Model (CCM3), and NASA’s Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric models are analyzed; CCM3 and NSIPP-1 models have 16- and 14-ensemble simulations, respectively, while CAM3.5 only has 1.

The standard deviation of summer precipitation is different in AMIP simulations. The maximum over the central United States seen in observations is placed farther to the west in simulations. Over the central plains the models exhibit modest skill in simulating low-frequency precipitation variability, a Palmer drought severity index proxy. The presence of a linear trend increases correlations in the period 1950–99 when compared with those for the whole century. The SST links of the Great Plains drought index have features in common with observations over both the Pacific and Atlantic Oceans.

Interestingly, summer-to-fall precipitation regressions of the warm Trend, cold Pacific, and warm Atlantic modes of annual mean SST variability (used in forcing the DWG idealized model experiments) tend to dry the southwestern, midwestern, and southeastern regions of the United States in the observations and, to a lesser extent, in the simulations.

The similarity of the idealized SST-forced droughts in DWG modeling experiments with AMIP precipitation regressions of the corresponding SST principal components, evident especially in the case of the cold Pacific pattern, suggests that the routinely conducted AMIP simulations could have served as an effective proxy for the more elaborated suite of DWG modeling experiments.

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Sumant Nigam
and
Steven C. Chan

Abstract

This study revisits the question posed by Hoskins on why the Northern Hemisphere Pacific sea level pressure (SLP) anticyclone is strongest and maximally extended in summer when the Hadley cell descent in the northern subtropics is the weakest. The paradoxical evolution is revisited because anticyclone buildup to the majestic summer structure is gradual, spread evenly over the preceding 4–6 months, and not just confined to the monsoon-onset period, which is interesting, as monsoons are posited to be the cause of the summer vigor of the anticyclone.

Anticyclone buildup is moreover found focused in the extratropics, not the subtropics, where SLP seasonality is shown to be much weaker, generating a related paradox within the context of the Hadley cell’s striking seasonality. Showing this seasonality to arise from, and thus represent, remarkable descent variations in the Asian monsoon sector, but not over the central-eastern ocean basins, leads to the resolution of this paradox.

Evolution of other prominent anticyclones is analyzed to critique the development mechanisms: the Azores high evolves like the Pacific one, but without a monsoon to its immediate west. The Mascarene high evolves differently, peaking in austral winter. Monsoons are not implicated in both cases.

Diagnostic modeling of seasonal circulation development in the Pacific sector concludes this inquiry. Of the three forcing regions examined, the Pacific midlatitudes are found to be the most influential, accounting for over two-thirds of the winter-to-summer SLP development in the extratropics (6–8 hPa), with the bulk coming from the abatement of winter storm-track heating and transients. The Asian monsoon contribution (2–3 hPa) is dominant in the Pacific (and Atlantic) subtropics.

The modeling results resonate with observational findings and attest to the demise of winter storm tracks as the principal cause of the summer vigor of the Pacific anticyclone.

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Sumant Nigam
and
Horng-Syi Shen

Abstract

The recurrent modes of combined oceanic and atmospheric low-frequency variability over the tropical Pacific and Indian oceans are calculated to provide quantitatively and structurally well-defined targets for simulation/prediction studies of ocean-atmosphere variability. Within the atmosphere, this study focuses on the structure of the large-scale near-surface flow variability.

The structure of combined variability of outgoing longwave radiation (OLR) and the Comprehensive Ocean-Atmosphere Data Set (COADS) SSTs and surface winds (1974–87) is analyzed using the covariance-based rotated principal component analysis technique during three nonoverlapping periods of the calendar year. The leading combined variability mode in each of these periods is found to be EJ Niño related, and the structural relationships among its four components quite revealing. For example, the surface divergence is found to be largely determined by the meridional winds, and while there is broad correspondence between the similarly signed OLR and surface divergence anomalies across the Pacific, pronounced oppositely signed anomalies are also present, notably over the Maritime Continent during the December–February (DJF) months.

The second leading mode of combined variability during the DJF months is robust, has nondescript equatorial SST or OLR anomalies, and represents coherent Jarge-scale expansion/contraction of the Pacific trade-wind system-north-south in case of the northeast trades and cast-west in case of the southeast trades.

In a related modeling study, the leading combined variability mode ~ on COADS observations was used to provide both the input (its OLR component) and the target (its surface wind components) for a simplified “Gill-type” model of the tropics (the atmospheric component of the Cane-Zebiak model) in order to ascertain the quality of its surface wind simulation.

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Natalie Thomas
and
Sumant Nigam

Abstract

Twentieth-century trends in seasonal temperature and precipitation over the African continent are analyzed from observational datasets and historical climate simulations. Given the agricultural economy of the continent, a seasonal perspective is adopted as it is more pertinent than an annual-average one, which can mask offsetting but agriculturally sensitive seasonal hydroclimate variations. Examination of linear trends in seasonal surface air temperature (SAT) shows that heat stress has increased in several regions, including Sudan and northern Africa where the largest SAT trends occur in the warm season. Broadly speaking, the northern continent has warmed more than the southern one in all seasons. Precipitation trends are varied but notable declining trends are found in the countries along the Gulf of Guinea, especially in the source region of the Niger River in West Africa, and in the Congo River basin. Rainfall over the African Great Lakes—one of the largest freshwater repositories—has, however, increased. It is shown that the Sahara Desert has expanded significantly over the twentieth century, by 11%–18% depending on the season, and by 10% when defined using annual rainfall. The expansion rate is sensitively dependent on the analysis period in view of the multidecadal periods of desert expansion (including from the drying of the Sahel in the 1950s–80s) and contraction in the 1902–2013 record, and the stability of the rain gauge network. The desert expanded southward in summer, reflecting retreat of the northern edge of the Sahel rainfall belt, and to the north in winter, indicating potential impact of the widening of the tropics. Specific mechanisms for the expansion are investigated. Finally, this observational analysis is used to evaluate the state-of-the-art climate simulations from a comparison of the twentieth-century hydroclimate trends. The evaluation shows that modeling regional hydroclimate change over the African continent remains challenging, warranting caution in the development of adaptation and mitigation strategies.

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Alfredo Ruiz-Barradas
and
Sumant Nigam

Abstract

The Department of Energy Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site data are analyzed to provide insight into atmosphere–land surface interactions generating summertime precipitation variability. Pentad-averaged (5 days) data are analyzed; the average is long enough to suppress synoptic variability but sufficiently short to resolve atmosphere–land surface interactions. Intercomparison with the precipitation-assimilating North American Regional Reanalysis (NARR) helps with in-depth investigation of the processes. The analysis seeks to ascertain the process sequence, especially the role of evapotranspiration and soil-moisture–radiation feedbacks in the generation of regional precipitation variability at this temporal scale.

Transported moisture dominates over evapotranspiration in precipitation variability over the region, from both magnitude of the contribution to regional water balance and its apparent temporal lead at pentad resolution. Antecedent and contemporaneous evapotranspiration are found to be negatively correlated with precipitation, albeit statistically insignificant; only lagging correlations are positive, peaking at 2-pentad lag following precipitation, substantiating the authors’ characterization of the water balance over SGP, and extending the authors’ previous findings on the dominance of moisture flux convergence in generating precipitation variability at monthly scales.

Precipitation episodes are linked with net negative surface radiation anomalies (i.e., with an energy-deprived land surface state that cannot fuel evapotranspiration), ruling out radiatively driven positive feedback on precipitation. Although the net longwave signal is positive because of a colder land surface (less upward terrestrial radiation), it is more than offset by the cloudiness-related reduction in downward shortwave radiation. Thus, ARM (NARR) data do not support the soil-moisture–precipitation feedback hypothesis over the SGP at pentad time scales; however, it may work at subpentad resolution and over other regions.

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Alfredo Ruiz-Barradas
and
Sumant Nigam

Abstract

The present work assesses spring and summer precipitation over North America as well as summer precipitation variability over the central United States and its SST links in simulations of the twentieth-century climate and projections of the twenty-first- and twenty-second-century climates for the A1B scenario.

The observed spatial structure of spring and summer precipitation poses a challenge for models, particularly over the western and central United States. Tendencies in spring precipitation in the twenty-first century agree with the observed ones at the end of the twentieth century over a wetter north-central and a drier southwestern United States, and a drier southeastern Mexico. Projected wetter springs over the Great Plains in the twenty-first and twenty-second centuries are associated with an increase in the number of extreme springs. In contrast, projected summer tendencies have demonstrated little consistency. The associated observed changes in SSTs bear the global warming footprint, which is not well captured in the twentieth-century climate simulations.

Precipitation variability over the Great Plains presents a coherent picture in spring but not in summer. Models project an increase in springtime precipitation variability owing to an increased number of extreme springs. The number of extreme droughty (pluvial) events during the spring–fall part of the year is under(over)estimated in the twentieth century without consistent projections.

Summer precipitation variability over the Great Plains is linked to SSTs over the Pacific and Atlantic Oceans, with no apparent ENSO link in spite of the exaggerated variability in the equatorial Pacific in climate simulations; this has been identified already in observations and atmospheric models forced with historical SSTs. This link is concealed due to the increased warming in the twenty-first century. Deficiencies in land surface–atmosphere interactions and global teleconnections in the climate models prevent them from a better portrayal of summer precipitation variability in the central United States.

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Scott J. Weaver
and
Sumant Nigam

Abstract

The evolution of supersynoptic (i.e., pentad) Great Plains low-level jet (GPLLJ) variability, its precipitation impacts, and large-scale circulation context are analyzed in the North American Regional Reanalysis (NARR)—a high-resolution precipitation-assimilating dataset—and the NCEP–NCAR reanalysis. The analysis strategy leans on the extended EOF technique, which targets both spatial and temporal recurrence of a variability episode.

Pentad GPLLJ variability structures are found to be spatially similar to those in the monthly analysis. The temporal evolution of the supersynoptic GPLLJ-induced precipitation anomalies reveal interesting lead and lag relationships highlighted by GPLLJ variability-leading precipitation anomalies. Interestingly, similar temporal phasing of the GPLLJ and precipitation anomalies were operative during the 1993 (1988) floods (drought) over the Great Plains, indicating the importance of these submonthly GPLLJ variability modes in the instigation of extreme hydroclimatic episodes. The northward-shifted (dry) GPLLJ variability mode is linked to large-scale circulation variations emanating from remote regions that are modified by interaction with the Rocky Mountains, suggesting that the supersynoptic GPLLJ fluctuations may have their origin in orographic modulation of baroclinic development.

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Alfredo Ruiz-Barradas
and
Sumant Nigam

Abstract

The Mekong River is the lifeblood of the Southeast (SE) Asian economies. In situ and satellite-based precipitation are analyzed to assess the amount of water received as precipitation in the river basin (Mekong basin water), in particular, the amount each country receives. Laos, Thailand, and Cambodia contribute ~75% of the basin water during March–September, whereas China’s contribution is 10%–15%, except in winter when it rises to 25%. The processing of Mekong basin water into Mekong streamflow entails accounting for the uncertain water losses but, interestingly, interannual variations in Mekong basin water can be processed into Mekong streamflow using a simple hydrologic model, which is validated using monthly river discharge data from four stations. Preliminary evidence for the impact of upbasin dams on downstream flow, especially the timing of peak summer flow, is presented. Characterization of El Niño’s influence on SE Asian rainfall reveals significant rainfall reductions in the fall preceding and the spring following El Niño’s peak phase (winter); such reductions at the bookends of the dry season in SE Asia (winter) generate droughts, as in 2015–16. The linear trend in twentieth-century rainfall assesses the vulnerability of the region to climate change. The analysis indicates the feasibility of streamflow prediction using a simple hydrologic model driven by high-resolution precipitation observations and forecasts. It raises the prospects of drought prediction based on El Niño’s emergence/forecast. Finally, by showing the Mekong to be largely a rain-fed and not snowmelt-fed river, it provides quantitative context for assessing the notion of Chinese control on the lower Mekong via upbasin dams.

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Alfredo Ruiz-Barradas
and
Sumant Nigam

Abstract

The annual cycle of precipitation and the interannual variability of the North American hydroclimate during summer months are analyzed in coupled simulations of the twentieth-century climate. The state-of-the-art general circulation models, participating in the Fourth Assessment Report for the Intergovernmental Panel on Climate Change (IPCC), included in the present study are the U.S. Community Climate System Model version 3 (CCSM3), the Parallel Climate Model (PCM), the Goddard Institute for Space Studies model version EH (GISS-EH), and the Geophysical Fluid Dynamics Laboratory Coupled Model version 2.1 (GFDL-CM2.1); the Met Office’s Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO-HadCM3); and the Japanese Model for Interdisciplinary Research on Climate version 3.2 [MIROC3.2(hires)]. Datasets with proven high quality such as NCEP’s North American Regional Reanalysis (NARR), and the Climate Prediction Center (CPC) U.S.–Mexico precipitation analysis are used as targets for simulations.

Climatological precipitation is not easily simulated. While models capture winter precipitation very well over the U.S. northwest, they encounter failure over the U.S. southeast in the same season. Summer precipitation over the central United States and Mexico is also a great challenge for models, particularly the timing. In general the UKMO-HadCM3 is closest to the observations.

The models’ potential in simulating interannual hydroclimate variability over North America during the warm season is varied and limited to the central United States. Models like PCM, and in particular UKMO-HadCM3, exhibit reasonably well the observed distribution and relative importance of remote and local contributions to precipitation variability over the region (i.e., convergence of remote moisture fluxes dominate over local evapotranspiration). However, in models like CCSM3 and GFDL-CM2.1 local contributions dominate over remote ones, in contrast with warm-season observations. In the other extreme are models like GISS-EH and MIROC3.2(hires) that prioritize the remote influence of moisture fluxes and neglect the local influence of land surface processes to the regional precipitation variability.

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