Wanli Wu - Academia.edu (original) (raw)

Papers by Wanli Wu

Remote Sensing and Modeling of Ecosystems for Sustainability III, 2006

Soil moisture and related hydrological process play an important role in regional and global clim... more Soil moisture and related hydrological process play an important role in regional and global climates. However, large-scale and long-term observation of soil moisture is sparse. In this study, the latest NCAR Community Land Model is used to simulate regional soil moisture in East Asia for recent 25 years with the atmospheric forcing provided by NCEP/DOE reanalysis. A 50-year simulation has been conducted with the first 25 years as the model spins up for soil moisture to reach steady state. The last 25 years simulation provides a soil moisture dataset with physical consistency and spatio-temporal continuity. Our analysis focuses on spatial and temporal variability of the regional soil moisture based on the last 25-year modeling. Additionally, The trend in the regional soil moisture and its possible link to climate warming is examined. The main conclusions can be summarized as follows: 1. Simulated soil moisture exhibits clear sensitivity to its initial condition. Such sensitivity is a function of soil depth. This study indicates that the equilibrium time of soil moisture increases with the depth of soil layers. It takes about 20 years to reach equilibrium below 1.5m. Therefore either a longer spin-up (20 years or more) or accurate initial soil moisture is necessary for a quality land surface modeling. 2. In comparison with the reanalysis and in-situ measurements, the model reproduces the observed large-scale structure reasonably well. The simulation shows mesoscale spatial variation as well.

Global seasonal forecasts of precipitation are currently produced by the major weather centers. T... more Global seasonal forecasts of precipitation are currently produced by the major weather centers. These predictions are available several months in advance at horizontal resolutions of ~200 km grid-size. They have proved useful to providing an estimate of the expected precipitation over large areas. However, their value is limited for regional applications, for example, hydrological applications such as water resources planning

Seasonal precipitation prediction has significant societal and economic impact, particularly for ... more Seasonal precipitation prediction has significant societal and economic impact, particularly for arid and semiarid regions. Current seasonal predictions generally rely on general circulation models (GCMs), which have coarse resolution (~300km). The GCM forecasts provide overall guidance in terms of large and synoptic scale perspectives, but are lack of regional and local details and accuracy that are needed by hydrological applications

Earth Interactions, 2006

... Corresponding author address: Dr. Sheldon Drobot, Colorado ... Howell (July) suggest that the... more ... Corresponding author address: Dr. Sheldon Drobot, Colorado ... Howell (July) suggest that there is little agreement among most of the datasets (Table 4). From January ... is significantly larger than the other datasets, owing to the issues discussed in Serreze and Hurst (Serreze and ...

Earth Interactions, 2008

The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncerta... more The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncertainties of simulated hydrologic and ecosystem dynamics of the western Arctic in the context of 1) uncertainties in the data available to drive the models and 2) different approaches to simulating regional hydrology and ecosystem dynamics. Analyses of datasets on climate available for driving hydrologic and ecosystem models within the western Arctic during the late twentieth century indicate that there are substantial differences among the mean states of datasets for temperature, precipitation, vapor pressure, and radiation variables. Among the studies that examined temporal trends among the alternative climate datasets, there is not much consensus on trends among the datasets. In contrast, monthly and interannual variations of some variables showed some correlation across the datasets. The application of hydrology models driven by alternative climate drivers revealed that the simulation of regional hydrology was sensitive to precipitation and water vapor differences among the driving datasets and that accurate simulation of regional water balance is limited by biases in the forcing data. Satellitebased analyses for the region indicate that vegetation productivity of the region increased during the last two decades of the twentieth century because of earlier spring thaw, and the temporal variability of vegetation productivity simulated by different models from 1980 to 2000 was generally consistent with estimates based on the satellite record for applications driven with alternative climate datasets. However, the magnitude of the fluxes differed by as much as a factor of 2.5 among applications driven with different climate data, and spatial patterns of temporal trends in carbon dynamics were quite different among simulations. Finally, the study identified that the simulation of fire by ecosystem models is particularly sensitive to alternative climate datasets, with little or no fire simulated for some datasets. The results of WALE identify the importance of conducting retrospective analyses prior to coupling hydrology and ecosystem models with climate system models. For applications of hydrology and Earth Interactions • Volume 12 (2008) • Paper No. 7 • Page 2 ecosystem models driven by projections of future climate, the authors recommend a coupling strategy in which future changes from climate model simulations are superimposed on the present mean climate of the most reliable datasets of historical climate.

Journal of Wind Engineering and Industrial Aerodynamics, 2011

This paper describes an advanced multi-scale weather modeling system, WRFRTFDDALES, designed to... more This paper describes an advanced multi-scale weather modeling system, WRFRTFDDALES, designed to simulate synoptic scale (∼ 2000km) to small-and micro-scale (∼ 100m) circulations of real weather in wind farms on simultaneous nested grids. This modeling ...

Earth Interactions, 2007

... Sheldon Drobot ... In addition, 4) temperature approximations derived from Advanced Very High... more ... Sheldon Drobot ... In addition, 4) temperature approximations derived from Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder data (PATH or ... for investigations of precipitation data from NCEPNCAR and ERA reanalyses to Serreze and Hurst (Serreze and ...

Bulletin of the American Meteorological Society, 2009

Collaboration between observationalists, theoreticians, and process and climate modelers leads to... more Collaboration between observationalists, theoreticians, and process and climate modelers leads to new understanding of oceanic overflows, and hence to improved representation in ocean climate models.

Atmospheric Research, 2012

ABSTRACT Most of the annual rainfall in the Southeastern Mediterranean falls in the wet season fr... more ABSTRACT Most of the annual rainfall in the Southeastern Mediterranean falls in the wet season from November to March. It is associated with Mediterranean cyclones, and is sensitive to climate variability. Predicting the wet season precipitation with a few months advance is highly valuable for water resource planning and climate-associated risk management in this semi-arid region. The regional water resource managements and climate-sensitive economic activities have relied on seasonal forecasts from global climate prediction centers. However due to their coarse resolutions, global seasonal forecasts lack regional and local scale information required by regional and local water resource managements. In this study, an analog statistical-downscaling algorithm, k-nearest neighbors (KNN), was introduced to bridge the gap between the coarse forecasts from global models and the needed fine-scale information for the Southeastern Mediterranean. The algorithm, driven by the NCEP Climate Forecast System (CFS) operational forecast and the NCEP/DOE reanalysis, provides monthly precipitations at 2–4 months of lead-time at 18 stations within the major regional hydrological basins. Large-scale predictors for KNN were objectively determined by the correlations between the station historic daily precipitation and variables in reanalysis and CFS reforecast. Besides a single deterministic forecast, this study constructed sixty ensemble members for probabilistic estimates. The KNN algorithm demonstrated its robustness when validated with NCEP/DOE reanalysis from 1981 to 2009 as hindcasts before applied to downscale CFS forecasts. The downscaled predictions show fine-scale information, such as station-to-station variability. The verification against observations shows improved skills of this downscaling utility relative to the CFS model. The KNN-based downscaling system has been in operation for the Israel Water Authority predicting precipitation and driving hydrologic models estimating river flow and aquifer charge for water supply.

mmm.ucar.edu

It is well known that nudging fourdimensional data assimilation (FDDA) is an effective and effici... more It is well known that nudging fourdimensional data assimilation (FDDA) is an effective and efficient way to reduce model errors (Stauffer and Seaman 1990). The nudging technique has several major uses. Firstly, it can be used to create four-dimensional dynamically ...