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Lei Shi, Ge Peng, and John J. Bates

Abstract

High-latitude ocean surface air temperature and humidity derived from intersatellite-calibrated High-Resolution Infrared Radiation Sounder (HIRS) measurements are examined. A neural network approach is used to develop retrieval algorithms. HIRS simultaneous nadir overpass observations from high latitudes are used to intercalibrate observations from different satellites. Investigation shows that if HIRS observations were not intercalibrated, then it could lead to intersatellite biases of 1°C in the air temperature and 1–2 g kg−1 in the specific humidity for high-latitude ocean surface retrievals. Using a full year of measurements from a high-latitude moored buoy site as ground truth, the instantaneous (matched within a half-hour) root-mean-square (RMS) errors of HIRS retrievals are 1.50°C for air temperature and 0.86 g kg−1 for specific humidity. Compared to a large set of operational moored and drifting buoys in both northern and southern oceans greater than 50° latitude, the retrieval instantaneous RMS errors are within 2.6°C for air temperature and 1.4 g kg−1 for specific humidity. Compared to 5 yr of International Maritime Meteorological Archive in situ data, the HIRS specific humidity retrievals show less than 0.5 g kg−1 of differences over the majority of northern high-latitude open oceans.

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H. N. Lee and J. K. Shi

Abstract

A pseudospectral method and its numerical solution algorithm for application to boundary layer problems in the atmosphere are presented. The method introduces the evaluation of a polynomial function when the solution is expressed as the sum of a periodic function and a polynomial function. The periodic function is then treated by Fourier expansion. In the paper, the accuracy of method has been demonstrated. Numerical results for a system of time dependent equations, modeling the atmospheric planetary boundary layer flow and nocturnal flow over terrain are encouraging. The method offers a promising alternative to finite-difference techniques.

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Lei Shi, John J. Bates, and Changyong Cao

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Measurements from the simultaneous nadir overpass (SNO) observations of the High Resolution Infrared Radiation Sounder (HIRS) are examined. The SNOs are the measurements taken at the orbital intersections of each pair of satellites viewing the same Earth target within a few seconds at high latitudes. The dataset includes satellites from NOAA-6 through NOAA-17 from 1981 to 2004. The authors found that for many channels, intersatellite biases vary significantly with respect to scene radiances. For a number of these channels, the change of the intersatellite bias within a channel can be larger than 1 mW (m2 sr cm−1)−1, which is approximately 1 K in brightness temperature, across the channel scene radiance ranges. Many of the channels with large variations of intersatellite biases are the tropospheric sounding channels centered along the sharp slope of the transmission line. These channels are particularly sensitive to the difference in spectral response functions from satellite to satellite. This radiance-dependency feature of the biases is an important factor to consider when performing intersatellite calibrations.

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Yuning Shi, Kenneth J. Davis, Fuqing Zhang, and Christopher J. Duffy

Abstract

Land surface models (LSMs) and hydrologic models are parameterized models. The number of involved parameters is often large. Sensitivity analysis (SA) is a key step to understand the complex relationships between parameters and between state variables and parameters. SA is also critical to understand system dynamics and to examine the parameter identifiability. In this paper, parameter SA for a fully coupled, physically based, distributed land surface hydrologic model, namely, the Flux–Penn State Integrated Hydrologic Model (Flux–PIHM), is performed. Multiparameter and single-parameter tests are performed to examine the three dimensions of identifiability: distinguishability, observability, and simplicity. Results show that Flux–PIHM model predictions of discharge, water table depth, soil moisture, land surface temperature, and surface heat fluxes are very sensitive to the selection of parameter values. Parameter uncertainties produce large uncertainties in hydrologic and land surface variable predictions. The van Genuchten parameters α and β and the Zilitinkevich parameter C zil are the most identifiable among the 20 tested parameters. Results indicate that the land surface and the subsurface are closely coupled. Hydrologic parameters have significant influence on land surface simulations. At the same time, land surface parameters have considerable impacts on hydrologic simulations; the evapotranspiration prediction prior to a strong precipitation event is critical for initializing accurate prediction of discharge peaks. Results also show that parameter identifiability depends on seasons and canopy wetness. Parameter identifiability at high and low flow conditions can be extremely different. Complex system dynamics have been revealed during the SA.

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Yuning Shi, Kenneth J. Davis, Christopher J. Duffy, and Xuan Yu

Abstract

A fully coupled land surface hydrologic model, Flux-PIHM, is developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater at spatial resolutions sufficient to resolve upland stream networks, Flux-PIHM is able to represent heterogeneities due to topography and soils at high resolution, including spatial structure in the link between groundwater and the surface energy balance (SEB). Flux-PIHM has been implemented at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Multistate observations of discharge, water table depth, soil moisture, soil temperature, and sensible and latent heat fluxes in June and July 2009 are used to manually calibrate Flux-PIHM at hourly temporal resolution. Model predictions from 1 March to 1 December 2009 are evaluated. Both hydrologic predictions and SEB predictions show good agreement with observations. Comparisons of model predictions between Flux-PIHM and the original PIHM show that the inclusion of the complex SEB simulation only brings slight improvement in hourly model discharge predictions. Flux-PIHM adds the ability of simulating SEB to PIHM and does improve the prediction of hourly evapotranspiration, the prediction of total runoff (discharge), and the predictions of some peak discharge events, especially after extended dry periods. Model results reveal that annual average sensible and latent heat fluxes are strongly correlated with water table depth, and the correlation is especially strong for the model grids near the stream.

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Do Hyuk Kang, Xiaogang Shi, Huilin Gao, and Stephen J. Déry

Abstract

This paper presents an application of the Variable Infiltration Capacity (VIC) model to the Fraser River basin (FRB) of British Columbia (BC), Canada, over the latter half of the twentieth century. The Fraser River is the longest waterway in BC and supports the world’s most abundant Pacific Ocean salmon populations. Previous modeling and observational studies have demonstrated that the FRB is a snow-dominated system, but with climate change, it may evolve to a pluvial regime. Thus, the goal of this study is to evaluate the changing contribution of snow to the hydrology of the FRB over the latter half of the twentieth century. To this end, a 0.25° atmospheric forcing dataset is used to drive the VIC model from 1949 to 2006 (water years) at a daily time step over a domain covering the entire FRB. A model evaluation is first conducted over 11 major subwatersheds of the FRB to quantitatively assess the spatial variations of snow water equivalent (SWE) and runoff (R). The ratio of the spatially averaged maximum SWE to R (R SR) is used to quantify the contribution of snow to the runoff in the 11 subwatersheds of interest. From 1949 to 2006, R SR exhibits a significant decline in 9 of the 11 subwatersheds (with p < 0.05 according to the Mann–Kendall test statistics). To determine the sensitivity of R SR, the air temperature and precipitation in the forcing dataset are then perturbed. The ratio R SR decreases more significantly, especially during the 1990s and 2000s, when air temperatures have warmed considerably compared to the 1950s. On the other hand, increasing precipitation by a multiplicative factor of 1.1 causes R SR to decrease. As the climate continues to warm, ecological processes and human usage of natural resources in the FRB may be substantially affected by its transition from a snow to a hybrid (nival/pluvial) and even a rain-dominated system.

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Jainn J. Shi, Scott A. Braun, Zhining Tao, and Toshihisa Matsui

Abstract

This study uses a model with aerosol–cloud–radiation coupling to examine the impact of Saharan dust and other aerosols on Hurricane Nadine (2012). To study aerosol direct (radiation) and indirect (cloud microphysics) effects from individual, as well as all aerosol species, eight different NU-WRF Model simulations were conducted. In several simulations, aerosols led to storm strengthening, followed by weakening relative to the control simulation. This variability of the aerosol impact may be related to whether aerosols are ingested into clouds within the outer rainbands or the eyewall. Upper-tropospheric aerosol concentrations indicate vertical transport of all aerosol types in the outer bands but only vertical transport of sea salt in the inner core. The results suggest that aerosols, particularly sea salt, may have contributed to a stronger initial intensification but that aerosol ingestion into the outer bands at later times may have weakened the storm in the longer term. In most aerosol experiments, aerosols led to a reduction in cloud and precipitation hydrometeors, the exception being the dust-only case that produced periods of enhanced hydrometeor growth. The Saharan air layer (SAL) also impacted Nadine by causing a region of strong easterlies impinging on the eastern side of the storm. At the leading edge of these easterlies, cool and dry air near the top of the SAL was being ingested into the outer-band convection. This midlevel low-equivalent-potential-temperature air gradually lowered toward the surface and eventually contributed to significant cold-pool activity in the eastern rainband and in the northeast quadrant of the storm. Such enhanced downdraft activity could have led to weakening of the storm, but it is not presently possible to quantify this impact.

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Carl J. Schreck III, Lei Shi, James P. Kossin, and John J. Bates

Abstract

The Madden–Julian oscillation (MJO) and convectively coupled equatorial waves are the dominant modes of synoptic-to-subseasonal variability in the tropics. These systems have frequently been examined with proxies for convection such as outgoing longwave radiation (OLR). However, upper-tropospheric water vapor (UTWV) gives a more complete picture of tropical circulations because it is more sensitive to the drying and warming associated with subsidence. Previous studies examined tropical variability using relatively short (3–7 yr) UTWV datasets. Intersatellite calibration of data from the High Resolution Infrared Radiation Sounder (HIRS) has recently produced a homogeneous 32-yr climate data record of UTWV for 200–500 hPa. This study explores the utility of HIRS UTWV for identifying the MJO and equatorial waves.

Spectral analysis shows that the MJO and equatorial waves stand out above the low-frequency background in UTWV, similar to previous findings with OLR. The fraction of variance associated with the MJO and equatorial Rossby waves is actually greater in UTWV than in OLR. Kelvin waves, on the other hand, are overshadowed in UTWV by horizontal advection from extratropical Rossby waves.

For the MJO, UTWV identifies subsidence drying in the subtropics, poleward of the convection. These dry anomalies are associated with the MJO’s subtropical Rossby gyres. MJO events with dry anomalies over the central North Pacific Ocean also amplify the 200-hPa flow pattern over North America 7 days later. These events cannot be identified using equatorial OLR alone, which demonstrates that UTWV is a useful supplement for identifying the MJO, equatorial waves.

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Masao Kanamitsu, Wesley Ebisuzaki, Jack Woollen, Shi-Keng Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter

The NCEP–DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the “50-year” (1948–present) NCEP–NCAR Reanalysis Project. NCEP–DOE AMIP-II re-analysis covers the “20-year” satellite period of 1979 to the present and uses an updated forecast model, updated data assimilation system, improved diagnostic outputs, and fixes for the known processing problems of the NCEP–NCAR reanalysis. Only minor differences are found in the primary analysis variables such as free atmospheric geopotential height and winds in the Northern Hemisphere extratropics, while significant improvements upon NCEP–NCAR reanalysis are made in land surface parameters and land–ocean fluxes. This analysis can be used as a supplement to the NCEP–NCAR reanalysis especially where the original analysis has problems. The differences between the two analyses also provide a measure of uncertainty in current analyses.

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Shi-Keng Yang, Yu-Tai Hou, Alvin J. Miller, and Kenneth A. Campana

Abstract

This study presents an evaluation of the NCEP–NCAR Reanalysis (the reanalysis) by comparing its components of the earth radiation budget to satellite data. Monthly mean clear sky (CS) and total sky of outgoing longwave radiation (OLR), as well as reflected solar radiation (RSW) for 1985 and 1986, are compared to the top-of-the-atmosphere (TOA) measurements from the Earth Radiation Budget Experiment (ERBE). The ERBE-derived data of Staylor and Wilbur are also utilized to validate surface albedo. There are two objectives to this study: (i) to document the general quality of the reanalysis radiation budget, and (ii) to identify some of the general problem areas in the reanalysis global data assimilation system (GDAS).

The OLR comparisons show that the global annual mean from the reanalysis is approximately 1.5% higher than that of ERBE. The zonal-average differences are strongly seasonal, which is particularly evident at high latitudes for the CS OLR, and at most latitudes for total-sky OLR. For the geographical distribution, the synoptic patterns from the reanalysis are in good agreement with the observations. Yet many regions in the Tropics and subtropics pose significant systematic biases. Possible causes are from shortcomings in the the cloud/moisture parameterizations of the reanalysis GDAS. The complex topography unresolvable by the T62 model could also be the cause for the biases in tall mountain regions.

The global RSW comparisons show that the CS data from the reanalysis is in very good agreement with ERBE, while the total-sky RSW data overestimate ERBE by 12.6 W m−2 (∼10%) globally. Persistent overestimates of RSW throughout the period indicate that the global energy budget for the reanalysis is not balanced. This result also is consistent with the finding in OLR suggesting that the reanalysis GDAS contains shortcomings in the cloud/moisture parameterizations. Another possibility for the difference in RSW is deficiencies in the GDAS shortwave parameterizations.

Over the Sahara Desert, the reanalysis underestimates RSW, and overestimates OLR, both in the clear-sky and total-sky conditions. Comparison with the Staylor and Wilber ERBE-derived surface albedo suggests that GDAS surface albedo in this region should be increased by up to 0.1 (in albedo units). A comparison with the interannual variations of the satellite data for the boreal summer illustrates that the radiation budget data of the reanalysis contains a realistic climate signal.

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