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Hong-Yi Li, L. Ruby Leung, Augusto Getirana, Maoyi Huang, Huan Wu, Yubin Xu, Jiali Guo, and Nathalie Voisin

Abstract

Accurately simulating hydrological processes such as streamflow is important in land surface modeling because they can influence other land surface processes, such as carbon cycle dynamics, through various interaction pathways. This study aims to evaluate the global application of a recently developed Model for Scale Adaptive River Transport (MOSART) coupled with the Community Land Model, version 4 (CLM4). To support the global implementation of MOSART, a comprehensive global hydrography dataset has been derived at multiple resolutions from different sources. The simulated runoff fields are first evaluated against the composite runoff map from the Global Runoff Data Centre (GRDC). The simulated streamflow is then shown to reproduce reasonably well the observed daily and monthly streamflow at over 1600 of the world’s major river stations in terms of annual, seasonal, and daily flow statistics. The impacts of model structure complexity are evaluated, and results show that the spatial and temporal variability of river velocity simulated by MOSART is necessary for capturing streamflow seasonality and annual maximum flood. Other sources of the simulation bias include uncertainties in the atmospheric forcing, as revealed by simulations driven by four different climate datasets, and human influences, based on a classification framework that quantifies the impact levels of large dams on the streamflow worldwide.

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Yuan Wang, Jonathan H. Jiang, Hui Su, Yong-Sang Choi, Lei Huang, Jianping Guo, and Yuk L. Yung

Abstract

Observations show that the Arctic sea ice cover has been shrinking at an unprecedented rate since the 1970s. Even though the accumulation of greenhouse gases in the atmosphere has been closely linked with the loss of Arctic sea ice, the role of atmospheric aerosols in past and future Arctic climate change remains elusive. Using a state-of-the-art fully coupled climate model, the authors assess the equilibrium responses of the Arctic sea ice to the different aerosol emission scenarios and investigate the pathways by which aerosols impose their influence in the Arctic. These sensitivity experiments show that the impacts of aerosol perturbations on the pace of sea ice melt effectively modulate the ocean circulation and atmospheric feedbacks. Because of the contrasting evolutions of particulate pollution in the developed and developing countries since the 1970s, the opposite aerosol forcings from different midlatitude regions are nearly canceled out in the Arctic during the boreal summer, resulting in a muted aerosol effect on the recent sea ice changes. Consequently, the greenhouse forcing alone can largely explain the observed Arctic sea ice loss up to the present. In the next few decades, the projected alleviation of particulate pollution in the Northern Hemisphere can contribute up to 20% of the total Arctic sea ice loss and 0.7°C surface warming over the Arctic. The authors’ model simulations further show that aerosol microphysical effects on the Arctic clouds are the major component in the total aerosol radiative forcing over the Arctic. Compared to the aerosol-induced energy imbalance in lower latitudes outside the Arctic, the local radiative forcing by aerosol variations within the Arctic, due to either local emissions or long-range transports, is more efficient in determining the sea ice changes and Arctic climate change.

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Zeng-Zhen Hu, Arun Kumar, Bohua Huang, Jieshun Zhu, Michelle L’Heureux, Michael J. McPhaden, and Jin-Yi Yu

Abstract

Following the interdecadal shift of El Niño–Southern Oscillation (ENSO) properties that occurred in 1976/77, another regime shift happened in 1999/2000 that featured a decrease of variability and an increase in ENSO frequency. Specifically, the frequency spectrum of Niño-3.4 sea surface temperature shifted from dominant variations at quasi-quadrennial (~4 yr) periods during 1979–99 to weaker fluctuations at quasi-biennial (~2 yr) periods during 2000–18. Also, the spectrum of warm water volume (WWV) index had almost no peak in 2000–18, implying a nearly white noise process. The regime shift was associated with an enhanced zonal gradient of the mean state, a westward shift in the atmosphere–ocean coupling in the tropical Pacific, and an increase in the static stability of the troposphere. This shift had several important implications. The whitening of the subsurface ocean temperature led to a breakdown of the relationship between WWV and ENSO, reducing the efficacy of WWV as a key predictor for ENSO and thus leading to a decrease in ENSO prediction skill. Another consequence of the higher ENSO frequency after 1999/2000 was that the forecasted peak of sea surface temperature anomaly often lagged that observed by several months, and the lag increased with the lead time. The ENSO regime shift may have altered ENSO influences on extratropical climate. Thus, the regime shift of ENSO in 1999/2000 as well as the model default may account for the higher false alarm and lower skill in predicting ENSO since 1999/2000.

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X. M. Chen, S.-H. Chen, J. S. Haase, B. J. Murphy, K.-N. Wang, J. L. Garrison, S. Y. Chen, C. Y. Huang, L. Adhikari, and F. Xie

Abstract

This study evaluates, for the first time, the impact of airborne global positioning system radio occultation (ARO) observations on a hurricane forecast. A case study was conducted of Hurricane Karl during the Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field campaign in 2010. The assimilation of ARO data was developed for the three-dimensional variational (3DVAR) analysis system of the Weather Research and Forecasting (WRF) Model version 3.2. The impact of ARO data on Karl forecasts was evaluated through data assimilation (DA) experiments of local refractivity and nonlocal excess phase (EPH), in which the latter accounts for the integrated horizontal sampling along the signal ray path. The tangent point positions (closest point of an RO ray path to Earth’s surface) drift horizontally, and the drifting distance of ARO data is about 2 to 3 times that of spaceborne RO, which was taken into account in these simulations.

Results indicate that in the absence of other satellite observations, the assimilation of ARO EPH resulted in a larger impact on the analysis than local refractivity did. In particular, the assimilation of ARO observations at the actual tangent point locations resulted in more accurate forecasts of the rapid intensification of the storm. Among all experiments, the best forecast was obtained by assimilating ARO data with the most accurate geometric representation, that is, the use of nonlocal EPH operators with tangent point drift, which reduced the error in the storm’s predicted minimum sea level pressure (SLP) by 43% beyond that of the control experiment.

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W. L. Smith, H. E. Revercomb, H. B. Howell, H-L. Huang, R. O. Knuteson, E. W. Koenig, D. D. LaPorte, S. Silverman, L. A. Sromovsky, and H. M. Woolf

Abstract

A high spectral resolution interferometer sounder (GHIS) has been designed for flight on future geostationary meteorological satellites. It incorporates the measurement principles of an aircraft prototype instrument, which has demonstrated the capability to observe the earth-emitted radiance spectrum with high accuracy. The aircraft results indicate that the theoretical expectation of 1°C temperature and 2°–3°C dewpoint retrieval accuracy will be achieved. The vertical resolution of the water vapor profile appears good enough to enable moisture tracking in numerous vertical layers thereby providing wind profile information as well as thermodynamic profiles of temperature and water vapor.

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Seiji Kato, Fred G. Rose, David A. Rutan, Tyler J. Thorsen, Norman G. Loeb, David R. Doelling, Xianglei Huang, William L. Smith, Wenying Su, and Seung-Hee Ham

Abstract

The algorithm to produce the Clouds and the Earth’s Radiant Energy System (CERES) Edition 4.0 (Ed4) Energy Balanced and Filled (EBAF)-surface data product is explained. The algorithm forces computed top-of-atmosphere (TOA) irradiances to match with Ed4 EBAF-TOA irradiances by adjusting surface, cloud, and atmospheric properties. Surface irradiances are subsequently adjusted using radiative kernels. The adjustment process is composed of two parts: bias correction and Lagrange multiplier. The bias in temperature and specific humidity between 200 and 500 hPa used for the irradiance computation is corrected based on observations by Atmospheric Infrared Sounder (AIRS). Similarly, the bias in the cloud fraction is corrected based on observations by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat. Remaining errors in surface, cloud, and atmospheric properties are corrected in the Lagrange multiplier process. Ed4 global annual mean (January 2005 through December 2014) surface net shortwave (SW) and longwave (LW) irradiances increase by 1.3 W m−2 and decrease by 0.2 W m−2, respectively, compared to EBAF Edition 2.8 (Ed2.8) counterparts (the previous version), resulting in an increase in net SW + LW surface irradiance of 1.1 W m−2. The uncertainty in surface irradiances over ocean, land, and polar regions at various spatial scales are estimated. The uncertainties in all-sky global annual mean upward and downward shortwave irradiance are 3 and 4 W m−2, respectively, and the uncertainties in upward and downward longwave irradiance are 3 and 6 W m−2, respectively. With an assumption of all errors being independent, the uncertainty in the global annual mean surface LW + SW net irradiance is 8 W m−2.

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Jieshun Zhu, Bohua Huang, Ben Cash, James L. Kinter, Julia Manganello, Rondrotiana Barimalala, Eric Altshuler, Frederic Vitart, Franco Molteni, and Peter Towers

Abstract

This study examines El Niño–Southern Oscillation (ENSO) prediction in Project Minerva, a recent collaboration between the Center for Ocean–Land–Atmosphere Studies (COLA) and the European Centre for Medium-Range Weather Forecasts (ECMWF). The focus is primarily on the impact of the atmospheric horizontal resolution on ENSO prediction, but the effect from different ensemble sizes is also discussed. Particularly, three sets of 7-month hindcasts performed with ECMWF prediction system are compared, starting from 1 May (1 November) during 1982–2011 (1982–2010): spectral T319 atmospheric resolution with 15 ensembles, spectral T639 with 15 ensembles, and spectral T319 with 51 ensembles. The analysis herein shows that simply increasing either ensemble size from 15 to 51 or atmospheric horizontal resolution from T319 to T639 does not necessarily lead to major improvement in the ENSO prediction skill with current climate models. For deterministic prediction skill metrics, the three sets of predictions do not produce a significant difference in either anomaly correlation or root-mean-square error (RMSE). For probabilistic metrics, the increased atmospheric horizontal resolution generates larger ensemble spread, and thus increases the ratio between the intraensemble spread and RMSE. However, there is little change in the categorical distributions of predicted SST anomalies, and consequently there is little difference among the three sets of hindcasts in terms of probabilistic metrics or prediction reliability.

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Benjamin A. Cash, James L. Kinter III, Jennifer Adams, Eric Altshuler, Bohua Huang, Emilia K. Jin, Julia Manganello, Larry Marx, and Thomas Jung

Abstract

Regional variations in seasonal mean Indian summer monsoon rainfall and circulation for the period 1979–2009 are investigated using multiple data products. The focus is on four separate regions: the Western Ghats (WG), the Ganges basin (GB), the Bay of Bengal (BB), and Bangladesh–northeastern India (BD). Data reliability varies strongly by region, with particularly low correlations between different products for the BB and BD regions. Correlations between regions are generally not statistically significant, indicating rainfall varies independently in these four regions. The diagnosed associations between rainfall, circulation, and sea surface temperatures can be sensitive to the choice of rainfall product, and multiple precipitation products may need to be analyzed in this region to ensure that the results are robust.

Enhanced precipitation in the BD region is associated with anomalous anticyclonic circulation at 850 mb and westerly anomalies along the foothills of the Tibetan Plateau, while precipitation in the other regions is associated with cyclonic flow and easterlies. These associations provide a dynamical explanation for previously reported weak, negative correlations between BD and the other regions.

In addition to observed products, atmosphere-only simulations made using the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) during Project Athena are analyzed. While the simulations do not reproduce the observed interannual variations in rainfall, the fidelity of the simulated precipitation and circulation structure is comparable to or even outperforms the different state-of-the-art reanalysis products considered. Accuracy in representing interannual variability and regional structure thus appears to be independent.

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Xu Liu, Wan Wu, Bruce A. Wielicki, Qiguang Yang, Susan H. Kizer, Xianglei Huang, Xiuhong Chen, Seiji Kato, Yolanda L. Shea, and Martin G. Mlynczak

Abstract

Detecting climate trends of atmospheric temperature, moisture, cloud, and surface temperature requires accurately calibrated satellite instruments such as the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Previous studies have evaluated the CLARREO measurement requirements for achieving climate change accuracy goals in orbit. The present study further quantifies the spectrally dependent IR instrument calibration requirement for detecting trends of atmospheric temperature and moisture profiles. The temperature, water vapor, and surface skin temperature variability and the associated correlation time are derived using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The results are further validated using climate model simulation results. With the derived natural variability as the reference, the calibration requirement is established by carrying out a simulation study for CLARREO observations of various atmospheric states under all-sky conditions. A 0.04-K (k = 2; 95% confidence) radiometric calibration requirement baseline is derived using a spectral fingerprinting method. It is also demonstrated that the requirement is spectrally dependent and that some spectral regions can be relaxed as a result of the hyperspectral nature of the CLARREO instrument. Relaxing the requirement to 0.06 K (k = 2) is discussed further based on the uncertainties associated with the temperature and water vapor natural variability and relatively small delay in the time to detect for trends relative to the baseline case. The methodology used in this study can be extended to other parameters (such as clouds and CO2) and other instrument configurations.

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Julia V. Manganello, Kevin I. Hodges, James L. Kinter III, Benjamin A. Cash, Lawrence Marx, Thomas Jung, Deepthi Achuthavarier, Jennifer M. Adams, Eric L. Altshuler, Bohua Huang, Emilia K. Jin, Cristiana Stan, Peter Towers, and Nils Wedi

Abstract

Northern Hemisphere tropical cyclone (TC) activity is investigated in multiyear global climate simulations with the ECMWF Integrated Forecast System (IFS) at 10-km resolution forced by the observed records of sea surface temperature and sea ice. The results are compared to analogous simulations with the 16-, 39-, and 125-km versions of the model as well as observations.

In the North Atlantic, mean TC frequency in the 10-km model is comparable to the observed frequency, whereas it is too low in the other versions. While spatial distributions of the genesis and track densities improve systematically with increasing resolution, the 10-km model displays qualitatively more realistic simulation of the track density in the western subtropical North Atlantic. In the North Pacific, the TC count tends to be too high in the west and too low in the east for all resolutions. These model errors appear to be associated with the errors in the large-scale environmental conditions that are fairly similar in this region for all model versions.

The largest benefits of the 10-km simulation are the dramatically more accurate representation of the TC intensity distribution and the structure of the most intense storms. The model can generate a supertyphoon with a maximum surface wind speed of 68.4 m s−1. The life cycle of an intense TC comprises intensity fluctuations that occur in apparent connection with the variations of the eyewall/rainband structure. These findings suggest that a hydrostatic model with cumulus parameterization and of high enough resolution could be efficiently used to simulate the TC intensity response (and the associated structural changes) to future climate change.

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