The impact of ecosystem functional type changes on the La Plata Basin climate

In this paper, the effects of land cover changes on the climate of the La Plata Basin in southern South America are investigated using the Weather and Research Forecasting (WRF) Model configured on a 30/10km two-way interactive nested grid. To assess the regional climate changes resulting from land surface changes, the standard land cover types are replaced by time-varying Ecosystem Functional Types (EFTs), which is a newly devised land-cover classification that characterizes the spatial and interannual variability of surface vegetation dynamics. These variations indicate that natural and anthropogenic activities have caused changes in the surface physical parameters of the basin, such as albedo and roughness length, that contributed to regional climate changes. EFTs are obtained from functional attributes of vegetation computed from properties of the Normalized Difference Vegetation Index (NDVI) to represent patches of the land surface with homogeneous energy and gas exchanges with the atmosphere. Four simulations are conducted, each experimental period ranging from September to November in two contrasting years, 1988 and 1998. The influence of an identical EFT change on the surface heat fluxes, 2-m temperature and humidity, 10-m winds, convective instabilities and large-scale moisture fluxes and precipitation are explored for 1988 (a dry year) and 1998 (a wet year). Results show that the surface and atmospheric climate has a larger response to the same EFT changes in a dry year for 2-m temperature and 10-m wind; the response is larger in a wet year for 2-m water vapor mixing ratio, convective available potential energy, vertically integrated moisture fluxes and surface precipitation. For EFTs with high productivity and a weak seasonal cycle, the nearsurface temperature during the spring of 1988 and 1998 increased by as much as 1℃ in the central and western portions of La Plata Basin. Additionally, for higher productivity EFTs, precipitation differences were generally positive in both dry and wet years, although the patterns are not uniform and exhibit certain patchiness with drier conditions.     

Effects of land use change on North American climate: impact of surface datasets and model biogeophysics

This study examines the impact of historical land-cover change on North American surface climate, focusing on the robustness of the climate signal with respect to representation of sub-grid heterogeneity and land biogeophysics within a climate model. We performed four paired climate simulations with the Community Atmosphere Model using two contrasting land models and two different representations of land-cover change. One representation used a biome classification without subgrid-scale heterogeneity while the other used high-resolution satellite data to prescribe multiple vegetation types within a grid cell. Present-day and natural vegetation datasets were created for both representations. All four sets of climate simulations showed that present-day vegetation has cooled the summer climate in regions of North America compared to natural vegetation. The simulated magnitude and spatial extent of summer cooling due to land-cover change was reduced when the biome-derived land-cover change datasets were replaced by the satellite-derived datasets. The diminished cooling is partly due to reduced intensity of agriculture in the satellite-derived datasets. Comparison of the two land-surface models showed that the use of a comparatively warmer and drier land model in conjunction with satellite-derived datasets further reduced the simulated magnitude of summer cooling. These results suggest that the cooling signal associated with North American land-cover change is robust but the magnitude and therefore detection of the signal depends on the realism of the datasets used to represent land-cover change and the parametrisation of land biogeophysics.     

用WRF与MM5模拟1998年三次暴雨过程的对比分析

使用NCAR和NOAA的新一代中尺度模式WRF(WeatherResearchandForecast)和UCAR/PSU的MM5 (v3)模式 ,对 1998年发生在中国的三次强降水过程 ,即 5月的 1次华南暴雨过程 ,7月初的 1次淮河流域暴雨过程和 7月下旬的 1次长江流域暴雨过程进行了数值模拟。模拟结果表明 ,WRF模式能够成功模拟这几次不同性质的降水过程 ;与MM5对比 ,WRF更好地模拟了引起这几次降水过程中的主要天气系统的位置和移动过程 ,从而使WRF模拟的降水落区好于MM5。但在这几次过程中WRF模拟的降水都较MM 5为小 ,也小于实况值 ,分析可见 ,WRF模拟的垂直速度明显小于MM5的模拟结果 ,这可能是导致模拟的降水偏小的原因之一。     

Vegetation patterns in South America associated with rising CO2: uncertainties related to sea surface temperatures

Spatially precise forecasts of the impacts of climate change on the distribution of major vegetation types are essential for the implementation of effective conservation and land use policy. However, existing studies frequently omit major sources of climate variability that can significantly increase the uncertainty of projections. In this study we demonstrate how different predictions for sea surface temperature (SST) for the first half of the twenty-first century increase the uncertainty associated with forecasts of the future distribution of major ecosystems in South America. This is demonstrated through a numerical experiment using a coupled climate–vegetation model (CCM3-IBIS) for IPCC emission scenario A2 that incorporates the SST data from ten different models. The study reveals an increasing uncertainty in the ability to forecast future vegetation patterns, such that by 2050 the simulation is unable to robustly forecast the vegetation cover in an area equivalent to 28 % in South America (5?×?10⁶ km²). The future of the central and northeastern regions of Brazil is especially uncertain, with outcomes, ranging from savanna, and open shrubland to grassland. Recognizing and managing such uncertainty should be a priority for decision makers.     

Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China

The default green vegetation fraction (GVF) in the Weather Research and Forecasting (WRF) Model version 3.7.1 was derived between 1985 and 1990 from the 1990s Normalized Difference Vegetation Index (NDVI) achieved from the NOAA Advanced Very High Resolution Radiometer (AVHRR), and its representation is deteriorating when used to simulate recent weather and climate events. In this study, we applied in WRF v3.7.1 the updated GVF estimated by the real-time NDVI of the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide a better representation of the prescribed surface GVF condition. A one-year simulation was carried out in China, and the simulated 2-m air temperature and specific humidity were compared between the WRF model control experiment that employs the default GVF data (WRF-CTL), the WRF simulations with updated GVF (WRF-MODIS), and the observations from 824 weather stations in China. Results are significantly improved for both the 2-m air temperature and the specific humidity by WRF-MODIS, which has effectively reproduced the observed pattern and increased the correlation coefficient between the model simulations and observations. The RMSE and bias of specific humidity are also reduced in WRF-MODIS. In general, the real-time MODIS-NDVI based GVF reflected the realistic increase of vegetation cover in China when comparing to the WRF default GVF, and also provided a more accurate seasonal variation for the simulated year of 2009. As a result, the WRF-MODIS simulation significantly improves its representation in the simulated 2-m air temperature and specific humidity, both in spatial distributions and seasonal variations, due to the GVF’s great contribution in modulating the coupled land-atmosphere interactions.     

Development of satellite green vegetation fraction time series for use in mesoscale modeling: application to the European heat wave 2006

A method is presented for development of satellite green vegetation fraction (GVF) time series for use in the Weather Research and Forecasting (WRF) model. The GVF data is in the WRF model used to describe the temporal evolution of many land surface parameters, in addition to the evolution of vegetation. Several high-resolution GVF products, derived from high-quality satellite retrievals from Moderate Resolution Imaging Spectroradiometer images, were produced and their performance was evaluated in long-term WRF simulations. The atmospheric conditions during the 2006 heat wave year over Europe were simulated since significant interannual variability in vegetation seasonality was found. Such interannual variability is expected to increase in the coming decades due to climatic changes. The simulation using a quadratic normalized difference vegetation index to GVF relationship resulted in consistent improvements of modeled temperatures. The model mean temperature cold bias was reduced by 10 % for the whole domain and by 20–45 % in areas affected by the heat wave. The study shows that WRF simulations during heat waves and droughts, when vegetation conditions deviate from the climatology, require concurrent land surface properties in order to produce accurate results.     

CLM4.5冠层截留方案的敏感性试验与改进

为探究陆气系统对于冠层截留过程敏的感性,研究基于NCAR CAM-CLM陆气耦合模式探讨了截留参数对于全球陆地蒸发、降水、径流及气温的可能影响,揭示了冠层截留与植被光合作用之间的潜在联系。通过GLEAMv3.0a陆面蒸散发数据评估了CLM4.5冠层截留方案,并指出该方案高估了低茎叶面积指数植被的冠层蒸发,而低估了高茎叶面积指数植被的冠层蒸发。在CLM4.5中引入冠层截留偏差校正方案则可在一定程度上提高了全球林区冠层蒸发和陆面蒸散发的模拟能力。     

Responses of urban heat island in Atlanta to different land-use scenarios

The urban heat island (UHI) effect changes heat and water cycles in urban areas, and has been accused of elevating energy consumption, deteriorating living environment, and increasing mortality rates. Understanding various UHI effects necessitates a systematic modeling approach. A major problem in UHI simulations is that urban areas were either considered to have only one category of land use/cover or outdated in land use/cover patterns due to the lack of high resolution data. Therefore, this study aims at integrating up-to-date remotely sensed land use/cover data with the Weather Research and Forecasting (WRF/UCM)/Urban Canopy Model modeling systems to simulate surface temperature patterns in Atlanta, Georgia. In addition, three land-use scenarios, i.e., spontaneous scenario (SS), concentrated scenario (CS), and local policy scenario (LPS), were designed and incorporated into the modeling. Five numerical experiments were conducted by using the Weather Research and Forecasting (WRF) model to explore the impact of urbanization-induced land-cover changes on temperature patterns. Land use and land-cover patterns under all three scenarios suggested that urban growth would continue through in-filling development and outward expansion. Compared to temperature simulations in 2011, temperature maps corresponding to the three urban growth scenarios showed warmer and cooler temperature patterns outside and inside the urban core, respectively. Analysis of the mean diurnal temperature cycle suggested that the highest temperature difference of 3.9 K was observed between 2011 and the LPS, and occurred around 22:00 local time. Overall, the simulations showed different UHI effects respond to the land-use scenarios in the summer. It is recommended for urban managers and policy makers to reflect on the potential impacts of alternative urban growth policies on thermal environment.     

Hydro-climatic effects of future land-cover/land-use change in montane mainland southeast Asia

Regional climate model simulations with RegCM3 were performed to investigate how future land-cover/land-use (LCLU) change in Montane Mainland Southeast Asia (MMSEA) could affect regional climate. Simulation land-surface parameterizations included present day and plausible 2050 land-covers, as well as two extreme deforestation simulations. In the simulations, the original land cover map of RegCM3, based on AVHRR 1992–93 observations, was replaced with one obtained from MODIS 2001 observations; and the model was set to work at two different spatial resolutions using the sub-grid feature of the land surface model: 27.79 km for the atmosphere and 9.26 km for the land surface. During validation, modeled precipitation closely matched observed precipitation over southern China, but underestimated precipitation in the Indochina Peninsula. The plausible 2050 LCLU simulation predicted little change in regional climate. However, an extreme irrigated crop parameterization caused precipitation to increase slightly in the Indochina Peninsula, decrease substantially in southeastern China, and increase significantly in the South China Sea. The extreme short-grass parameterization caused substantial precipitation decreases in MMSEA, but few changes elsewhere. These simulations indicate in order for significant climatological changes to occur, substantially more LCLU conversion is required than the 16 % change we incorporated into the plausible 2050 land-cover scenario.     

On the relationship between vegetation and climate in tropical and northern Africa

Vegetation cover is a crucial component of the Earth’s climate system but, still, our understanding of the mechanisms governing the reciprocal influence between atmosphere and vegetation is limited. In this study, we investigate the unilateral atmospheric impact on vegetation cover in tropical and northern Africa, differentiated into regions with different circulation regimes and into detailed land-cover classes. In contrast to former studies, climate predictors from a regional climate model are used as input for a multiple regression model. Climate models provide consistent data without gaps at high spatial resolution, a considerably larger set of available climate variables and the perspective to transfer the statistical relationships to future projections, e.g., in the context of anthropogenic climate change. Indeed, robust climate predictors which drive up to 70 % of observed interannual vegetation variability could be extracted from the climate model. Besides precipitation and temperature, global radiation, and relative humidity play an important role. The statistical transfer functions are plausible in terms of the affected regions and land-cover classes and draw a rather complex picture of the atmosphere–vegetation relation in Africa.     

Dynamic downscaling of summer precipitation prediction over China in 1998 using WRF and CCSM4

To study the prediction of the anomalous precipitation and general circulation for the summer(June–July–August) of1998, the Community Climate System Model Version 4.0(CCSM4.0) integrations were used to drive version 3.2 of the Weather Research and Forecasting(WRF3.2) regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model,but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.     

建立η坐标系下的假不压模式及其数值试验

滤除声波的大气运动方程中不包含声波,基于滤除声波方程建立的数值模式可以用较大的时间步长进行数值积分。Durran在1989年提出了一种新的滤除声波的方法,命名为“假不可压”方程,该方程考虑了温度扰动引起的密度变化,忽略了气压扰动引起的密度变化。本文根据Durran提出的假不可压理论,推导出了一组地形追随坐标下的通量形式的假不可压方程。该方程在形式上与WRF（Weather Research and Forecasting）模式中ARW（Advanced Research WRF）动力框架的控制方程非常接近。我们进一步将推导出的假不可压控制方程改写到了WRF模式中,建立了基于WRF模式框架的假不可压模式。用构建的假不可压模式和WRF模式做了两组对比试验:湿热泡对流试验和重力流试验。比较两种模式的模拟结果,可以看出假不可压模式的模拟结果与WRF模式的模拟结果非常接近,说明在WRF模式框架下建立的假不可压模式是合理可信的。     

Observation-based blended projections from ensembles of regional climate models

We consider the problem of projecting future climate from ensembles of regional climate model (RCM) simulations using results from the North American Regional Climate Change Assessment Program (NARCCAP). To this end, we develop a hierarchical Bayesian space-time model that quantifies the discrepancies between different members of an ensemble of RCMs corresponding to present day conditions, and observational records. Discrepancies are then propagated into the future to obtain high resolution blended projections of 21st century climate. In addition to blended projections, the proposed method provides location-dependent comparisons between the different simulations by estimating the different modes of spatial variability, and using the climate model-specific coefficients of the spatial factors for comparisons. The approach has the flexibility to provide projections at customizable scales of potential interest to stakeholders while accounting for the uncertainties associated with projections at these scales based on a comprehensive statistical framework. We demonstrate the methodology with simulations from the Weather Research & Forecasting regional model (WRF) using three different boundary conditions. We use simulations for two time periods: current climate conditions, covering 1971 to 2000, and future climate conditions under the Special Report on Emissions Scenarios (SRES) A2 emissions scenario, covering 2041 to 2070. We investigate and project yearly mean summer and winter temperatures for a domain in the South West of the United States.     

Climate change predictions for South America

Some of the characteristics of predicted climate changes for South America are analysed for the years 2010 and 2050. These predictions are based on the results of three-dimensional Global Circulation Models (GCMs). The results differ between models (GISS, NCAR-CCMs and GFDL), particularly when applied to regional and sub-regional scales and to time scales of less than one-year intervals. It is concluded that these differences are due to the particular structure of each model as well as to the lack of sufficient basic data from the South American sub-continent. The dynamics of vegetation cover play an important role in future water balance changes. The changes in surface temperatures predicted by the GISS model are discussed in relation to changes in the climatic-dynamic base stemming from anthropogenic changes in the vegetation cover.     

Simulation of South American wintertime climate with a nesting system

A numerical nesting system is developed to simulate wintertime climate of the eastern South Pacific-South America-western South Atlantic region, and preliminary results are presented. The nesting system consists of a large-scale global atmospheric general circulation model (GCM) and a regional climate model (RCM). The latter is driven at its boundaries by the GCM. The particularity of this nesting system is that the GCM itself has a variable horizontal resolution (stretched grid). Our main purpose is to assess the plausibility of such a technique to improve climate representation over South America. In order to evaluate how this nesting system represents the main features of the regional circulation, several mean fields have been analyzed. The global model, despite its relatively low resolution, could simulate reasonably well the more significant large-scale circulation patterns. The use of the regional model often results in improvements, but not universally. Many of the systematic errors of the global model are also present in the regional model, although the biases tend to be rectified. Our preliminary results suggest that nesting technique is a computationally low-cost alternative for simulating regional climate features. However, additional simulations, parametrizations tuning and further diagnosis are clearly needed to represent local patterns more precisely. Received: 18 February 1999 / Accepted: 31 May 2000     

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

区域气候模式不同积云对流参数化方案对新疆气候模拟的影响研究

使用NCEP-FNL全球分析资料作为WRF模式的初始场和边界场,利用该模式中7种积云对流参数化方案对新疆地区进行2006年10月1日至2008年3月1日的模拟积分试验,重点考察模式在水平分辨率为10 km下不同积云对流参数化方案对新疆地区气象要素模拟的敏感性。结果表明:1）采用7种积云对流参数化方案的模式都能较好地模拟出年、雨季总降水量、平均温度的空间分布及大气的垂直结构。2）对于不同区域来说,采用各种积云对流参数化方案的模式都能模拟出候降水及候平均温度随时间演变,模式候降水与观测的相关系数在0.20~0.85之间,而候平均温度与观测的相关系数在0.98以上。对于整个新疆地区来说,采用各方案模式模拟的低层偏干偏冷,大气层结较稳定导致降水较观测偏少,而其中天山地区模式模拟的低层较观测偏湿偏暖,大气层结偏向不稳定导致降水偏多。3）采用新的Grell和Kain-Fritsch（new Eta）方案模式模拟的效果综合来看较好。因此利用WRF模式开展新疆地区数值模拟研究时应该考虑不同积云对流参数化方案适用范围。     

Extreme precipitation in WRF during the Newcastle East Coast Low of 2007

In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8^th of June 2007 along the coast of eastern Australia (abbreviated “Newy”). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ～10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.     

Evaluation of a climate simulation in Europe based on the WRF–NOAH model system: precipitation in Germany

The Weather Research and Forecast (WRF) model with its land surface model NOAH was set up and applied as regional climate model over Europe. It was forced with the latest ERA-interim reanalysis data from 1989 to 2008 and operated with 0.33° and 0.11° resolution. This study focuses on the verification of monthly and seasonal mean precipitation over Germany, where a high quality precipitation dataset of the German Weather Service is available. In particular, the precipitation is studied in the orographic terrain of southwestern Germany and the dry lowlands of northeastern Germany. In both regions precipitation data is very important for end users such as hydrologists and farmers. Both WRF simulations show a systematic positive precipitation bias not apparent in ERA-interim and an overestimation of wet day frequency. The downscaling experiment improved the annual cycle of the precipitation intensity, which is underestimated by ERA-interim. Normalized Taylor diagrams, i.e., those discarding the systematic bias by normalizing the quantities, demonstrate that downscaling with WRF provides a better spatial distribution than the ERA interim precipitation analyses in southwestern Germany and most of the whole of Germany but degrades the results for northeastern Germany. At the applied model resolution of 0.11°, WRF shows typical systematic errors of RCMs in orographic terrain such as the windward–lee effect. A convection permitting case study set up for summer 2007 improved the precipitation simulations with respect to the location of precipitation maxima in the mountainous regions and the spatial correlation of precipitation. This result indicates the high value of regional climate simulations on the convection-permitting scale.