The most important aggregate measure of the long run health of the productive component of the agricultural economy is agricultural total factor productivity (TFP). Between 1948 and 2011, average annual input growth in US agriculture averaged approximately 0.07% while annual average output growth averaged roughly 1.5%. That translates into an annual average agricultural TFP growth rate of approximately 1.43%. That growth has led to a remarkable expansion of the productive ability of the US agricultural sector. However, climate change poses unprecedented challenges to U.S. agricultural production because of the sensitivity of agricultural productivity and costs to changing climate conditions. Some studies have examined the effect of climate change on U.S. agriculture. But none has investigated how climate affects the overall U.S. agricultural productivity. This study intends to find out climate change impacts on U.S. agricultural TFP change (TFPC). By correlation analysis with data in 1979-2005, we found that precipitation and temperature had significant positive or negative correlations with U.S. agricultural TFPC. Those correlation coefficients ranged from -0.8 to 0.8. And significant correlations, whether positive or negative, existed in different regions and different seasons. This is important information for policy-makers in decisions to support U.S. agriculture sustainability.
The ecosystem risk assessment is an essential decision making system for predicting the reconstruction and recovery of a
damaged ecosystem after intensive mankind activities. The sustainability of environment and resources of the lake
ecosystem in arid districts have been paid close attention to by international communities as well as numerous experts
and scholars. The ecological risk assessment offered a scientific foundation for making the decision and execution of
ecological risk management. Bosten Lake, the largest inland freshwater lake in China, is the main water source of the
industrial and agricultural production as well as the local residence in Yanqi basin, Kuara city and Yuri County in the
southern Xinjiang. Bosten Lake also provides a direct water source for emergency transportation in the Lower Reaches
of Tarim River. However, with the intensive utilizations of water and soil resources, the environmental condition in the
Bosten Lake has become more and more serious. In this study, the theory and method of landscape ecological risk
assessment has been practiced using 3S technologies combined with the frontier theory of landscape ecology. Defining
the mainly risk resource including flood, drought, water pollution and rich nutrition of water has been evaluated based on
the ecosystem risk assessment system. The main process includes five stages: regional natural resources analysis, risk
receptor selection, risk sources evaluation, exposure and hazard analysis, and integrated risk assessment. Based on the
risk assessment results, the environmental risk management countermeasure has been determined.
Better understanding the dynamics of the East Asian monsoon system is essential to address its climate variability and predictability. Regional climate models are useful tools for this endeavor, but require a rigorous evaluation to first establish a suite of physical parameterizations that best simulate observations. To this end, the present study focuses on the CWRF (Climate extension of WRF) simulation of the 1998 summer flood over east China and its sensitivity to cumulus parameterizations on CWRF performance. The CWRF using the Kain-Fritsch and Grell-Devenyi cumulus schemes both capture the observed major characteristics of geographic distributions and daily variations of precipitation, indicating a high credibility in downscaling the monsoon. Important regional differences, however, are simulated by the two schemes. The Kain-Fritsch scheme produces the better precipitation patterns with smaller root-mean-square errors and higher temporal correlation coefficients, while overestimating the magnitude and coverage. In contrast, the Grell-Devenyi ensemble scheme, using equal weights on all closure members, overall underestimates rainfall amount, suggesting for future improvement with varying weights depending on climate regimes.
Multifilter rotating shadowband radiometers are deployed in the United States, Canada, and New Zealand by the USDA
(United States Department of Agriculture) UV-B (ultraviolet-B) Monitoring and Research Program to measure UV-B
irradiances at seven discrete wavelengths. A synthetic model is used to construct the continuous spectral distribution,
from which irradiance integrals can be performed for various purposes. The derived spectral data are posted for public
use through a web accessible database. Although the synthetic model has been validated with a certain data set, few
works have been seen to compare the results of the synthetic model with simulations of other widely accepted models
such as TUV. Through this comparison the validation of the synthetic model can be further confirmed and alternative
techniques for constructing spectral irradiances from discrete narrowband measurements can also be explored.
In this study the data from the USDA UV-B Monitoring and Research Program are used to evaluate the synthetic model
and to explore the capability of the TUV model for constructing continuous spectra from discrete measurements.
Simulations of the TUV model are compared with discrete measurements, erythema-weighted broadband measurements,
and the results of the synthetic model. Good agreements between derived results by using TUV model and the synthetic
model with measurements in general further confirm the validation of the synthetic model. Generally, the spectral
irradiances constructed by using synthetic model are lower than those by using the TUV model at very shorter
wavelengths (<301 nm) and at the wavelengths of 315-342 nm, but are higher at other wavelengths. The ratio of
erythemal doses derived by using the TUV simulation to broadband measurements varies between 0.87-1.02.
Constructed erythemal doses by using the TUV simulation are closer to broadband measurements than those obtained by
using the synthetic model. These results suggest that the TUV model may be a good alternative to accurately estimate
continuous spectral distributions from discrete measurements.
The capability of the Climate extension of the Weather Research and Forecasting (CWRF) model in simulating the 1991 and 1998 summer floods in China is evaluated with 4-month continuous integrations as driven by the NCEP/NCAR observational reanalysis. It is shown that CWRF has a pronounced downscaling skill, capturing the key characteristics in the spatial patterns and temporal evolutions of precipitation in both severe anomalous monsoon cases. The result gives a high perspective for future CWRF applications in understanding and predicting China monsoon variability.
Ultraviolet (UV) radiation is the source energy for tropospheric photolysis processes, while harmful for living
organism of the earth. It is thus necessary to incorporate UV radiation for an integrated earth modeling system to predict
interactions between climate, chemistry and ecosystem processed. The widely-used NCAR TUV (Tropospheric
Ultraviolet and Visible) radiation model has been coupled with the state-of-the-art mesoscale CWRF (Climate extension
of the Weather Research and Forecasting model) to predict the UV dependence of local climate conditions and its
impacts on air quality and crop growth. The original TUV v4.2 has been significantly improved by (1) replacing the core
radiation transfer solver, DISORT v1.1 with the latest v2.0beta; (2) adding a new aerosol scheme based on the Shettle
(1989); (3) recoding the entire model to follow the CWRF F90 standard with dynamic memory allocation and modular
design; and (4) developing a flexible interface for coupling with CWRF.
Given the lack of detailed cloud information in observations, this study focuses on validation of the TUV module
in a standalone mode against the USDA UV-B data under clear-sky conditions. To facilitate this, a cloud detection
scheme based on Long and Ackerman (2000) is incorporated to distinguish clear versus cloudy sky conditions from the
UV-B observations. The model input includes in situ measurements of the column ozone and total aerosol optical depth;
TOMS retrievals of the column ozone (in case missing in situ) and climatologically surface reflectivity; and the NARR
(North American Regional Analysis) meteorological conditions. The TUV results agree well with the UV-B
measurements at 7 narrow spectral bands (300, 305, 311, 317, 325, 332, 368 nm).
GOSSYM is a comprehensive crop growth model that has been continuously developed since the late 1970s and widely applied to assist cotton growers, crop consultants, and researchers. The state-of-art CWRF (Climate-Weather Research and Forecasting model) demonstrated skillful simulations of regional water and energy cycle processes that are keenly important to cotton growth. This study focuses on coupling GOSSYM and CWRF to study crop-climate interactions. The coupling procedures include (1) recoding the GOSSYM to follow the CWRF F90 modular implementation; (2) replacing the soil dynamic module of the GOSSYM with the CWRF-predicted soil temperature and moisture while integrating the crop field management or cultural practice component (e.g., irrigation, tillage); (3) providing the GOSSYM with surface air temperature, precipitation, and surface solar radiation from the CWRF; (4) constructing crop height and coverage, leaf and stem area indices, greenness and root profile from the GOSSYM as inputs for the CWRF to represent the crop feedback on solar albedo and infrared emissivity, precipitation interception, and evapotranspiration. This study presents the preliminary results of the GOSSYM driven by the CWRF simulated climate conditions and discusses the model performance on cotton yield, leaf area index and height and their responses to water stress under the irrigation and non-irrigation conditions.
A new parameterization of snow-free land surface albedo is developed using the MODerate resolution Imaging Spectroradiometer (MODIS) products of broadband black-sky and white-sky reflectance and vegetation information as well as the North American and Global Land Data Assimilation System (LDAS) outputs of soil moisture during 2000-20003. It represents the predictable albedo dependences on solar zenith angle, surface soil moisture, fractional vegetation cover, and leaf plus stem area index, while including a statistic correction for static effects specific of local surface characteristics. All parameters are estimated by solving optimization problems of a physically based conceptual model for the minimization of the bulk variances between simulations and observations. A preliminary result showed that, for composites of all temporal and spatial samples of a same land cover category over North America, correlation coefficients between the new parameterization with the MODIS data range from 0.6 to 0.9, while relative errors vary within 5-20%. This is a substantial improvement over the existing state-of-the art Common Land Model (CLM) abide scheme, which has correlation coefficients from -0.5 to 0.5 and relative errors of 20-100%.
Given the strategic development of industry and economy over northwest China, the ecosystem over the region will dramatically change. In particular, an increasing proportion of the land is expected to be covered by vegetation, including grass, trees and crops. At the present, most of the region is in desert or semi-desert conditions, where vegetation is very sparse and precipitation is low. A serious issue is the sustainability of vegetation: will the future regional climate conditions favor the maintenance of the vegetation under managed or unmanaged environments? As an initial step, a high-resolution regional climate model (RCM) is used to study the climate responses to an extreme case, where the dominant land cover over Xinjiang, currently barren or sparsely vegetated, is all replaced with grasslands. The simulations show that, in response to the grassland replacement, Xinjiang summer mean precipitation will increase, surface air temperature will decrease, and surface soil wetness will rise. In addition, the diurnal range of precipitation (temperature) will be enhanced (reduced). These changes result mainly from the increased surface evaporation which in turn is attributed to the enhanced surface water availability (greater green vegetation cover and wetter soils) for regional recycling, while the surface albedo and roughness effects are relatively small. The resulting climate responses tend to favor the grasslands to naturally grow in and be adapted to the new regional environment over Xinjiang. On the other hand, precipitation will decline over the Inner Mongolia, which is particularly damaging since the regional grassland there is currently China’s main pastureland and is experiencing dramatic desertification. The uncertainty in the credibility of the RCM results, however, warrants further comprehensive studies, where an interactive ecosystem and global climate changes must be incorporated.