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Taotao Qian
,
Aiguo Dai
, and
Kevin E. Trenberth

Abstract

The trends of the surface water and energy budget components in the Mississippi River basin from 1948 to 2004 are investigated using a combination of hydrometeorological observations and observation-constrained simulations of the land surface conditions using the latest version of the Community Land Model version 3 (CLM3). The atmospheric forcing data for the CLM3 were constructed by adding the intramonthly variations from the 6-hourly National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis to observation-based analyses of monthly precipitation, surface air temperature, and cloud cover. The model-based analysis suggests that, for the surface water budget, the observed increase in basin-averaged precipitation is compensated by increases in both runoff and evapotranspiration. For the surface energy budget, the decrease of net shortwave radiation associated with observed increases in cloudiness is compensated by decreases in both net longwave radiation and sensible heat flux, while the latent heat flux increases in association with wetter soil conditions. Both the simulated surface water and energy budgets support the view that evapotranspiration has increased in the Mississippi River basin from 1948 to 2004. Sensitivity experiments show that the precipitation change dominates the evapotranspiration trend, while the temperature and solar radiation changes have only small effects. Large spatial variations within the Mississippi River basin and the contiguous United States are also found. However, the increased evapotranspiration is ubiquitous despite spatial variations in hydrometeorology.

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Chunlüe Zhou
,
Aiguo Dai
,
Junhong Wang
, and
Deliang Chen
Open access
Kevin E. Trenberth
,
Lesley Smith
,
Taotao Qian
,
Aiguo Dai
, and
John Fasullo

Abstract

A brief review is given of research in the Climate Analysis Section at NCAR on the water cycle. Results are used to provide a new estimate of the global hydrological cycle for long-term annual means that includes estimates of the main reservoirs of water as well as the flows of water among them. For precipitation P over land a comparison among three datasets enables uncertainties to be estimated. In addition, results are presented for the mean annual cycle of the atmospheric hydrological cycle based on 1979–2000 data. These include monthly estimates of P, evapotranspiration E, atmospheric moisture convergence over land, and changes in atmospheric storage, for the major continental landmasses, zonal means over land, hemispheric land means, and global land means. The evapotranspiration is computed from the Community Land Model run with realistic atmospheric forcings, including precipitation that is constrained by observations for monthly means but with high-frequency information taken from atmospheric reanalyses. Results for EP are contrasted with those from atmospheric moisture budgets based on 40-yr ECMWF Re-Analysis (ERA-40) data. The latter show physically unrealistic results, because evaporation often exceeds precipitation over land, especially in the Tropics and subtropics.

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Taotao Qian
,
Aiguo Dai
,
Kevin E. Trenberth
, and
Keith W. Oleson

Abstract

Because of a lack of observations, historical simulations of land surface conditions using land surface models are needed for studying variability and changes in the continental water cycle and for providing initial conditions for seasonal climate predictions. Atmospheric forcing datasets are also needed for land surface model development. The quality of atmospheric forcing data greatly affects the ability of land surface models to realistically simulate land surface conditions. Here a carefully constructed global forcing dataset for 1948–2004 with 3-hourly and T62 (∼1.875°) resolution is described, and historical simulations using the latest version of the Community Land Model version 3.0 (CLM3) are evaluated using available observations of streamflow, continental freshwater discharge, surface runoff, and soil moisture. The forcing dataset was derived by combining observation-based analyses of monthly precipitation and surface air temperature with intramonthly variations from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis, which is shown to have spurious trends and biases in surface temperature and precipitation. Surface downward solar radiation from the reanalysis was first adjusted for variations and trends using monthly station records of cloud cover anomaly and then for mean biases using satellite observations during recent decades. Surface specific humidity from the reanalysis was adjusted using the adjusted surface air temperature and reanalysis relative humidity. Surface wind speed and air pressure were interpolated directly from the 6-hourly reanalysis data. Sensitivity experiments show that the precipitation adjustment (to the reanalysis data) leads to the largest improvement, while the temperature and radiation adjustments have only small effects.

When forced by this dataset, the CLM3 reproduces many aspects of the long-term mean, annual cycle, interannual and decadal variations, and trends of streamflow for many large rivers (e.g., the Orinoco, Changjiang, Mississippi, etc.), although substantial biases exist. The simulated long-term-mean freshwater discharge into the global and individual oceans is comparable to 921 river-based observational estimates. Observed soil moisture variations over Illinois and parts of Eurasia are generally simulated well, with the dominant influence coming from precipitation. The results suggest that the CLM3 simulations are useful for climate change analysis. It is also shown that unrealistically low intensity and high frequency of precipitation, as in most model-simulated precipitation or observed time-averaged fields, result in too much evaporation and too little runoff, which leads to lower than observed river flows. This problem can be reduced by adjusting the precipitation rates using observed-precipitation frequency maps.

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Curt Covey
,
Aiguo Dai
,
Dan Marsh
, and
Richard S. Lindzen

Abstract

Although atmospheric tides driven by solar heating are readily detectable at the earth’s surface as variations in air pressure, their simulations in current coupled global climate models have not been fully examined. This work examines near-surface-pressure tides in climate models that contributed to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC); it compares them with tides both from observations and from the Whole Atmosphere Community Climate Model (WACCM), which extends from the earth’s surface to the thermosphere. Surprising consistency is found among observations and all model simulations, despite variation of the altitudes of model upper boundaries from 32 to 76 km in the IPCC models and at 135 km for WACCM. These results are consistent with previous suggestions that placing a model’s upper boundary at low altitude leads to partly compensating errors—such as reducing the forcing of the tides by ozone heating, but also introducing spurious waves at the upper boundary, which propagate to the surface.

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Ying Sun
,
Susan Solomon
,
Aiguo Dai
, and
Robert W. Portmann

Abstract

Daily precipitation data from worldwide stations and gridded analyses and from 18 coupled global climate models are used to evaluate the models' performance in simulating the precipitation frequency, intensity, and the number of rainy days contributing to most (i.e., 67%) of the annual precipitation total. Although the models examined here are able to simulate the land precipitation amount well, most of them are unable to reproduce the spatial patterns of the precipitation frequency and intensity. For light precipitation (1–10 mm day−1), most models overestimate the frequency but produce patterns of the intensity that are in broad agreement with observations. In contrast, for heavy precipitation (>10 mm day−1), most models considerably underestimate the intensity but simulate the frequency relatively well. The average number of rainy days contributing to most of the annual precipitation is a simple index that captures the combined effects of precipitation frequency and intensity on the water supply. The different measures of precipitation characteristics examined in this paper reveal region-to-region differences in the observations and models of relevance for climate variability, water resources, and climate change.

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Tianjun Zhou
,
Rucong Yu
,
Haoming Chen
,
Aiguo Dai
, and
Yang Pan

Abstract

Hourly or 3-hourly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Tropical Rainfall Measuring Mission (TRMM) 3B42 satellite products and rain gauge records are used to characterize East Asian summer monsoon rainfall, including spatial patterns in June–August (JJA) mean precipitation amount, frequency, and intensity, as well as the diurnal and semidiurnal cycles. The results show that the satellite products are comparable to rain gauge data in revealing the spatial patterns of JJA precipitation amount, frequency, and intensity, with pattern correlation coefficients for five subregions ranging from 0.66 to 0.94. The pattern correlation of rainfall amount is higher than that of frequency and intensity. Relative to PERSIANN, the TRMM product has a better resemblance with rain gauge observations in terms of both the pattern correlation and root-mean-square error. The satellite products overestimate rainfall frequency but underestimate its intensity. The diurnal (24 h) harmonic dominates subdaily variations of precipitation over most of eastern China. A late-afternoon maximum over southeastern and northeastern China and a near-midnight maximum over the eastern periphery of the Tibetan Plateau are seen in the rain gauge data. The diurnal phases of precipitation frequency and intensity are similar to those of rainfall amount in most regions, except for the middle Yangtze River valley. Both frequency and intensity contribute to the diurnal variation of rainfall amount over most of eastern China. The contribution of frequency to the diurnal cycle of rainfall amount is generally overestimated in both satellite products. Both satellite products capture well the nocturnal peak over the eastern periphery of the Tibetan Plateau and the late-afternoon peak in southern and northeastern China. Rain gauge data over the region between the Yangtze and Yellow Rivers show two peaks, with one in the early morning and the other later in the afternoon. The satellite products only capture the major late-afternoon peak.

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Aiguo Dai
,
Kevin E. Trenberth
, and
Thomas R. Karl

Abstract

The diurnal range of surface air temperature (DTR) has decreased worldwide during the last 4–5 decades and changes in cloud cover are often cited as one of the likely causes. To determine how clouds and moisture affect DTR physically on daily bases, the authors analyze the 30-min averaged data of surface meteorological variables and energy fluxes from the the First International Satellite Land Surface Climatology Project Field Experiment and the synoptic weather reports of 1980–1991 from about 6500 stations worldwide. The statistical relationships are also examined more thoroughly in the historical monthly records of DTR, cloud cover, precipitation, and streamflow of this century.

It is found that clouds, combined with secondary damping effects from soil moisture and precipitation, can reduce DTR by 25%–50% compared with clear-sky days over most land areas; while atmospheric water vapor increases both nighttime and daytime temperatures and has small effects on DTR. Clouds, which largely determine the geographic patterns of DTR, greatly reduce DTR by sharply decreasing surface solar radiation while soil moisture decreases DTR by increasing daytime surface evaporative cooling. Clouds with low bases are most efficient in reducing the daytime maximum temperature and DTR mainly because they are very effective in reflecting the sunlight, while middle and high clouds have only moderate damping effects on DTR. The DTR reduction by clouds is largest in warm and dry seasons such as autumn over northern midlatitudes when latent heat release is limited by the soil moisture content. The net effects of clouds on the nighttime minimum temperature is small except in the winter high latitudes where the greenhouse warming effect of clouds exceeds their solar cooling effect.

The historical records of DTR of the twentieth century covary inversely with cloud cover and precipitation on interannual to multidecadal timescales over the United States, Australia, midlatitude Canada, and former U.S.S.R., and up to 80% of the DTR variance can be explained by the cloud and precipitation records. Given the strong damping effect of clouds on the daytime maximum temperature and DTR, the well-established worldwide asymmetric trends of the daytime and nighttime temperatures and the DTR decreases during the last 4–5 decades are consistent with the reported increasing trends in cloud cover and precipitation over many land areas and support the notion that the hydrologic cycle has intensified.

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Jiao Chen
,
Aiguo Dai
,
Yaocun Zhang
, and
Kristen L. Rasmussen

Abstract

Atmospheric convective available potential energy (CAPE) is expected to increase under greenhouse gas–induced global warming, but a recent regional study also suggests enhanced convective inhibition (CIN) over land although its cause is not well understood. In this study, a global climate model is first evaluated by comparing its CAPE and CIN with reanalysis data, and then their future changes and the underlying causes are examined. The climate model reasonably captures the present-day CAPE and CIN patterns seen in the reanalysis, and projects increased CAPE almost everywhere and stronger CIN over most land under global warming. Over land, the cases or times with medium to strong CAPE or CIN would increase while cases with weak CAPE or CIN would decrease, leading to an overall strengthening in their mean values. These projected changes are confirmed by convection-permitting 4-km model simulations over the United States. The CAPE increase results mainly from increased low-level specific humidity, which leads to more latent heating and buoyancy for a lifted parcel above the level of free convection (LFC) and also a higher level of neutral buoyancy. The enhanced CIN over most land results mainly from reduced low-level relative humidity (RH), which leads to a higher lifting condensation level and a higher LFC and thus more negative buoyancy. Over tropical oceans, the near-surface RH increases slightly, leading to slight weakening of CIN. Over the subtropical eastern Pacific and Atlantic Ocean, the impact of reduced low-level atmospheric lapse rates overshadows the effect of increased specific humidity, leading to decreased CAPE.

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Binhe Luo
,
Dehai Luo
,
Aiguo Dai
,
I. Simmonds
, and
Lixin Wu

Abstract

Winter surface air temperature (SAT) over North America exhibits pronounced variability on subseasonal, interannual, decadal, and interdecadal time scales. Here, reanalysis data from 1950–2017 are analyzed to investigate the atmospheric and surface ocean conditions associated with its subseasonal to interannual variability. Detrended daily SAT data reveal a known warm west/cold east (WWCE) dipole over midlatitude North America and a cold north/warm south (CNWS) dipole over eastern North America. It is found that while the North Pacific blocking (PB) is important for the WWCE and CNWS dipoles, they also depend on the phase of the North Atlantic Oscillation (NAO). When a negative-phase NAO (NAO) coincides with PB, the WWCE dipole is enhanced (compared with the PB alone case) and it also leads to a warm north/cold south dipole anomaly in eastern North America; but when PB occurs with a positive-phase NAO (NAO+), the WWCE dipole weakens and the CNWS dipole is enhanced. The PB events concurrent with the NAO (NAO+) and SAT WWCE (CNWS) dipole are favored by the Pacific El Niño–like (La Niña–like) sea surface temperature mode and the positive (negative) North Pacific mode. The PB-NAO+ has a larger component projecting onto the SAT WWCE dipole during the La Niña winter than during the El Niño winter because a more zonal wave train is formed. Strong North American SAT WWCE dipoles and enhanced projections of PB-NAO+ events onto the SAT WWCE dipole component are also readily seen for the positive North Pacific mode. The North Pacific mode seems to play a bigger role in the North American SAT variability than ENSO.

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