A high-resolution ocean-atmosphere coupled downscaling of the present climate over California

A fully coupled regional ocean-atmosphere model system that consists of the regional spectral model and the regional ocean modeling system for atmosphere and ocean components, respectively, is applied to downscale the present climate (1985–1994) over California from a global simulation of the Community Climate System Model 3.0 (CCSM3). The horizontal resolution of the regional coupled modeling system is 10 km, while that of the CCSM3 is at a spectral truncation of T85 (approximately 1.4°). The effects of the coupling along the California coast in the boreal summer and winter are highlighted. Evaluation of the sea surface temperature (SST) and 2-m air temperature climatology shows that alleviation of the warm bias along the California coast in the global model output is clear in the regional coupled model run. The 10-m wind is also improved by reducing the northwesterly winds along the coast. The higher resolution coupling effect on the temperature and specific humidity is the largest near the surface, while the significant impact on the wind magnitude appears at a height of approximately 850-hPa heights. The frequency of the Catalina Eddy and its duration are increased by more than 60 % in the coupled downscaling, which is attributed to enhanced offshore sea-breeze. Our study indicates that coupling is vital to regional climate downscaling of mesoscale phenomena over coastal areas.     

Projected climate change scenario over California by a regional ocean–atmosphere coupled model system

This study examines a future climate change scenario over California in a 10-km coupled regional downscaling system of the Regional Spectral Model for the atmosphere and the Regional Ocean Modeling System for the ocean forced by the global Community Climate System Model version 3.0 (CCSM3). In summer, the coupled and uncoupled downscaled experiments capture the warming trend of surface air temperature, consistent with the driving CCSM3 forcing. However, the surface warming change along the California coast is weaker in the coupled downscaled experiment than it is in the uncoupled downscaling. Atmospheric cooling due to upwelling along the coast commonly appears in both the present and future climates, but the effect of upwelling is not fully compensated for by the projected large-scale warming in the coupled downscaling experiment. The projected change of extreme warm events is quite different between the coupled and uncoupled downscaling experiments, with the former projecting a more moderate change. The projected future change in precipitation is not significantly different between coupled and uncoupled downscaling. Both the coupled and uncoupled downscaling integrations predict increased onshore sea breeze change in summer daytime and reduced offshore land breeze change in summer nighttime along the coast from the Bay area to Point Conception. Compared to the simulation of present climate, the coupled and uncoupled downscaling experiments predict 17.5 % and 27.5 % fewer Catalina eddy hours in future climate respectively.     

ENSO anomalies over the Western United States: present and future patterns in regional climate simulations

Surface temperature, precipitation, specific humidity and wind anomalies associated with the warm and cold phases of ENSO simulated by WRF and HadRM are examined for the present and future decades. WRF is driven by ECHAM5 and CCSM3, respectively, and HadRM is driven by HadCM3. For the current decades, all simulations show some capability in resolving the observed warm-dry and cool-wet teleconnection patterns over the PNW and the Southwest U.S. for warm and cold ENSO. Differences in the regional simulations originate primarily from the respective driving fields. For the future decades, the warm-dry and cool-wet teleconnection patterns in association with ENSO are still represented in ECHAM5-WRF and HadRM. However, there are indications of changes in the ENSO teleconnection patterns for CCSM3-WRF in the future, with wet anomalies dominating in the PNW and the Southwest U.S. for both warm and cold ENSO, in contrast to the canonical patterns of precipitation anomalies. Interaction of anomalous wind flow with local terrain plays a critical role in the generation of anomalous precipitation over the western U.S. Anomalous dry conditions are always associated with anomalous airflow that runs parallel to local mountains and wet conditions with airflow that runs perpendicular to local mountains. Future changes in temperature and precipitation associated with the ENSO events in the regional simulations indicate varying responses depending on the variables examined as well as depending on the phase of ENSO.     

High resolution regional climate model simulations for Germany: part I—validation

A five-member ensemble of regional climate model (RCM) simulations for Europe, with a high resolution nest over Germany, is analysed in a two-part paper: Part I (the current paper) presents the performance of the models for the control period, and Part II presents results for near future climate changes. Two different RCMs, CLM and WRF, were used to dynamically downscale simulations with the ECHAM5 and CCCma3 global climate models (GCMs), as well as the ERA40-reanalysis for validation purposes. Three realisations of ECHAM5 and one with CCCma3 were downscaled with CLM, and additionally one realisation of ECHAM5 with WRF. An approach of double nesting was used, first to an approximately 50 km resolution for entire Europe and then to a domain of approximately 7 km covering Germany and its near surroundings. Comparisons of the fine nest simulations are made to earlier high resolution simulations for the region with the RCM REMO for two ECHAM5 realisations. Biases from the GCMs are generally carried over to the RCMs, which can then reduce or worsen the biases. The bias of the coarse nest is carried over to the fine nest but does not change in amplitude, i.e. the fine nest does not add additional mean bias to the simulations. The spatial pattern of the wet bias over central Europe is similar for all CLM simulations, and leads to a stronger bias in the fine nest simulations compared to that of WRF and REMO. The wet bias in the CLM model is found to be due to a too frequent drizzle, but for higher intensities the distributions are well simulated with both CLM and WRF at the 50 and 7 km resolutions. Also the spatial distributions are close to high resolution gridded observations. The REMO model has low biases in the domain averages over Germany and no drizzle problem, but has a shift in the mean precipitation patterns and a strong overestimation of higher intensities. The GCMs perform well in simulating the intensity distribution of precipitation at their own resolution, but the RCMs add value to the distributions when compared to observations at the fine nest resolution.     

Relative impacts of increased greenhouse gas concentrations and land cover change on the surface climate in arid and semi-arid regions of China

Four dynamical downscaling simulations are performed with different combinations of land cover maps and greenhouse gas (GHG) levels using the Weather Research and Forecasting (WRF) model nested in the Community Earth System (CESM) model. A pseudo-global warming downscaling method is used to effectively separate the anthropogenic signals from the internal noises of climate models. Based on these simulations, we investigate the impacts of anthropogenic increase in GHG concentrations and land use and land cover change (LULCC) on mean climate and extreme events in the arid and semi-arid regions of China. The results suggest that increased GHG concentrations lead to significant increases in the surface air temperature at 2 m height (T2m) by 1–1.5 °C and greater increase in the warm day temperature (TX90p) than the cold day temperature (TX10p) in the arid and semi-arid regions. Moreover, precipitation increases by 30–50% in the arid region in cold season (November to March) due to the GHG-induced increase in moisture recycling rate and precipitation efficiency. LULCC leads to significant decreases in the T2m, TX90p, and TX10p by approximately 0.3 °C. The regional LULCC accounts for 66 and 68% decrease in T2m in warm and cold seasons, respectively. The rest changes in T2m results from the changes in lateral boundary condition induced by the global LULCC. In response to LULCC, both the warm and cold day temperatures show a significant decrease in cold seasons, which primarily results from the regional LULCC. LULCC-induced changes in precipitation are generally weak in the arid and semi-arid regions of China.     

Scale dependency of regional climate modeling of current and future climate extremes in Germany

A 26-year simulation (1980–2005) was performed with the Weather Research and Forecast (WRF) model over the Volta Basin in West Africa. This was to investigate the ability of a climate version of WRF to reproduce present day temperature and precipitation over the Volta Basin. The ERA-Interim reanalysis and one realization of the ECHAM6 global circulation model (GCM) data were dynamically downscaled using two nested domains within the WRF model. The outer domain had a horizontal resolution of 50 km and covered the whole of West Africa while the inner domain had a horizontal resolution of 10 km. It was observed that biases in the respective forcing data were carried over to the RCM, but also the RCM itself contributed to the mean bias of the model. Also, the biases in the 50-km domain were transferred unchanged, especially in the case of temperature, to the 10-km domain, but, for precipitation, the higher-resolution simulations increased the mean bias in some cases. While in general, WRF underestimated temperature in both the outer (mean biases of ?1.6 and ?2.3 K for ERA-Interim and ECHAM6, respectively) and the inner (mean biases of ?0.9 K for the reanalysis and ?1.8 K for the GCM) domains, WRF slightly underestimated precipitation in the coarser domain but overestimated precipitation in the finer domain over the Volta Basin. The performance of the GCM, in general, is good, particularly for temperature with mean bias of ?0.7 K over the outer domain. However, for precipitation, the added value of the RCM cannot be overlooked, especially over the whole West African region on the annual time scale (mean biases of ?3% for WRF and ?8% for ECHAM6). Over the whole Volta Basin and the Soudano-Sahel for the month of April and spring (MAM) rainfall, respectively, mean bias close to 0% was simulated. Biases in the interannual variability in both temperature and precipitation over the basin were smaller in the WRF than the ECHAM6. High spatial pattern correlations between 0.7 and 0.8 were achieved for the autumn precipitation and low spatial correlation in the range of 0.0 and 0.2 for the winter season precipitation over the whole basin and all the three belts over the basin.     

The atmospheric component of the Mediterranean Sea water budget in a WRF multi-physics ensemble and observations

The use of high resolution atmosphere–ocean coupled regional climate models to study possible future climate changes in the Mediterranean Sea requires an accurate simulation of the atmospheric component of the water budget (i.e., evaporation, precipitation and runoff). A specific configuration of the version 3.1 of the weather research and forecasting (WRF) regional climate model was shown to systematically overestimate the Mediterranean Sea water budget mainly due to an excess of evaporation (~1,450 mm yr^?1) compared with observed estimations (~1,150 mm yr^?1). In this article, a 70-member multi-physics ensemble is used to try to understand the relative importance of various sub-grid scale processes in the Mediterranean Sea water budget and to evaluate its representation by comparing simulated results with observed-based estimates. The physics ensemble was constructed by performing 70 1-year long simulations using version 3.3 of the WRF model by combining six cumulus, four surface/planetary boundary layer and three radiation schemes. Results show that evaporation variability across the multi-physics ensemble (～10 % of the mean evaporation) is dominated by the choice of the surface layer scheme that explains more than ～70 % of the total variance and that the overestimation of evaporation in WRF simulations is generally related with an overestimation of surface exchange coefficients due to too large values of the surface roughness parameter and/or the simulation of too unstable surface conditions. Although the influence of radiation schemes on evaporation variability is small (～13 % of the total variance), radiation schemes strongly influence exchange coefficients and vertical humidity gradients near the surface due to modifications of temperature lapse rates. The precipitation variability across the physics ensemble (～35 % of the mean precipitation) is dominated by the choice of both cumulus (～55 % of the total variance) and planetary boundary layer (～32 % of the total variance) schemes with a strong regional dependence. Most members of the ensemble underestimate total precipitation amounts with biases as large as 250 mm yr^?1 over the whole Mediterranean Sea compared with ERA Interim reanalysis mainly due to an underestimation of the number of wet days. The larger number of dry days in simulations is associated with a deficit in the activation of cumulus schemes. Both radiation and planetary boundary layer schemes influence precipitation through modifications on the available water vapor in the boundary layer generally tied with changes in evaporation.     

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.     

Intercomparison of the performance of MM5/WRF with and without satellite data assimilation in short-range forecast applications over the Indian region

The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed.     

Evaluation of the twenty-first century RCM simulations driven by multiple GCMs over the Eastern Mediterranean–Black Sea region

In this study, human-induced climate change over the Eastern Mediterranean–Black Sea region has been analyzed for the twenty-first century by performing regional climate model simulations forced with large-scale fields from three different global circulation models (GCMs). Climate projections have been produced with Special Report on Emissions Scenarios A2, A1FI and B1 scenarios, which provide greater diversity in climate information for future period. The gradual increases for temperature are widely apparent during the twenty-first century for each scenario simulation, but ECHAM5-driven simulation generally has a weaker signal for all seasons compared to CCSM3 simulations except for the Fertile Crescent. The contrast in future temperature change between the winter and summer seasons is very strong for CCSM3-A2-driven and HadCM3-A2-driven simulations over Carpathians and Balkans, 4–5 °C. In addition, winter runoff over mountainous region of Turkey, which feeds many river systems including the Euphrates and Tigris, increases in second half of the century since the snowmelt process accelerates where the elevation is higher than 1,500 m. Moreover, analysis of daily temperature outputs reveals that the gradual decrease in daily minimum temperature variability for January during the twenty-first century is apparent over Carpathians and Balkans. Analysis of daily precipitation extremes shows that positive trend is clear during the last two decades of the twenty-first century over Carpathians for both CCSM3-driven and ECHAM5-driven simulations. Multiple-GCM driven regional climate simulations contribute to the quantification of the range of climate change over a region by performing detailed comparisons between the simulations.     

Influences of climate change on California and Nevada regions revealed by a high-resolution dynamical downscaling study

In this study, the influence of climate change to California and Nevada regions was investigated through high-resolution (4-km grid spacing) dynamical downscaling using the WRF (Weather Research & Forecasting) model. The dynamical downscaling was performed to both the GFS (Global forecast model) reanalysis (called GFS-WRF runs) from 2000?C2006 and PCM (Parallel Climate Model) simulations (called PCM-WRF runs) from 1997?C2006 and 2047?C2056. The downscaling results were first validated by comparing current model outputs with the observational analysis PRISM (Parameter-elevation Regressions on Independent Slopes Model) dataset. In general, the dominant features from GFS-WRF runs and PCM-WRF runs were consistent with each other, as well as with PRISM results. The influences of climate change on the California and Nevada regions can be inferred from the model future runs. The averaged temperature showed a positive trend in the future, as in other studies. The temperature increases by around 1?C2°C under the assumption of business as usual over 50?years. This leads to an upward shifting of the freezing level (the contour line of 0°C temperature) and more rain instead of snow in winter (December, January, and February). More hot days (>32.2°C or 90°F) and extreme hot days (>37.8°C or 100°F) are predicted in the Sacramento Valley and the southern parts of California and Nevada during summer (June, July, and August). More precipitation is predicted in northern California but not in southern California. Rainfall frequency slightly increases in the coast regions, but not in the inland area. No obvious trend of the surface wind was indicated. The probability distribution functions (PDF) of daily temperature, wind and precipitation for California and Nevada showed no significant change in shape in either winter or summer. The spatial distributions of precipitation frequency from GFS-WRF and PCM-WRF were highly correlated (r?=?0.83). However, overall positive shifts were seen in the temperature field; increases of 2°C for California and 3°C for Nevada in summer and 2.5°C for California and 1.5°C for Nevada in winter. The PDFs predicted higher precipitation in winter and lower precipitation in the summer for both California and Nevada.     

Effects of atmospheric river landfalls on the cold season precipitation in California

Effects of atmospheric river (AR) landfalls in the California coast on the cold-season precipitation in California are examined for the cold seasons of 10 water years (WYs) 2001–2010 using observed data and regional modeling in conjunction with AR-landfall inventory based on visual inspections of precipitable water vapor (PWV) from remote sensing and reanalysis. The PWV in the SSM/I and SSMIS retrievals and the ERA-Interim reanalysis shows 95 AR-landfall days in the California coast that are almost evenly split between the northern and southern coasts across 37.5N. The CPC/NCEP gridded daily precipitation analysis shows that 10–30% of the cold-season precipitation totals in California have occurred during these AR landfalls. The analysis also reveals that the percentage of precipitation and the precipitation intensity during AR landfalls in California are characterized by strong north-to-south gradient. This north–south contrast in the AR precipitation is reversed for the non-AR precipitation in the coastal range. The frequency of AR landfalls and the cold-season precipitation totals in the Sierra Nevada region are only marginally correlated. Instead, AR landfalls are closely related with the occurrence of heavy precipitation events. The freezing-level altitudes are systematically higher for AR wet days than non-AR wet days indicating warmer low-troposphere during AR storms. Cold season simulations for the 10 WYs 2001–2010 show that the Weather Research and Forecast (WRF) model can reasonably simulate important features in both the seasonal and AR precipitation totals. The daily pattern correlation coefficients between the simulated and ERA-Interim upper-air fields exceed 0.9 for most of the period. This suggests that the simulated temporal variations in the atmospheric circulation agree reasonably with the reanalysis over seasonal time scales, characteristics critical for reliable simulations of regional scale hydrologic cycle. The simulated seasonal and AR precipitation totals also agree reasonably with the CPC/NCEP precipitation analysis. The most notable model errors include the overestimation (underestimation) of the season-total and AR precipitation in the northern (southern) California region. The differences in the freezing-level altitudes during the AR- and non-AR wet days in the simulation agree with those from the ERA-Interim reanalysis. The freezing level altitudes are systematically overestimated in the simulations, suggesting warm biases in the low troposphere. Overall, WRF appears to perform reasonably in simulating the key features in the cold season precipitation related with AR landfalls, an important capability for assessing the impact of global climate variations and change on future hydrology in California.     

Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.     

Regional climate model simulation of the AMMA Special Observing Period #3 and the pre-Helene easterly wave

The study examines results of dynamic downscaling of two global analyses: the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis II and the Global Forecast System final analysis (FNL). Downscaling to a 0.5° grid over West Africa and the adjacent Atlantic Ocean is accomplished by each of two regional models, the Regional Model, version 3 (RM3) of the Center for Climate Systems Research and the Weather, Research and Forecasting model (WRF). Simulations are for September 2006, the African Monsoon Multidisciplinary Analysis (AMMA) Special Observing Period #3 (SOP-3). The aim of this study is to exploit the increased spatial detail in the simulations and representations of climate fields by the regional models to analyze meteorological systems within the SOP-3 area of interest and time frame. In particular, the paper focuses on the regional models’ representations of the structure and movement of a prominent easterly wave during September 10–13th, the precursor of Tropical Storm/Hurricane Helene. It describes the RM3 simulated structure of the developing storm in terms of circulation, precipitation, vertical motion, cumulus heating rates, and cross-sections of wind and geopotential height anomalies. Simulated cumulus heating rates within the wave’s main precipitation area imply a lowering of the bases of active cumulus in the transition from the African continent to the Atlantic, indicating that the ocean environment promotes greater upward latent heat flux that in turn intensifies overlying storms. RM3 circulation, precipitation patterns, and storm trajectory are reasonably consistent with observational evidence. Experiments show that precipitation rates near 6°N over the eastern North Atlantic are sensitive to vertical thermal stability, such that they are enhanced by warmer in situ sea-surface temperatures (SSTs) and diminished by colder SSTs. However, prescribing colder SST causes increases in precipitation north of 9°N within areas of large scale upward vertical motion where rainfall rates are less sensitive to in situ SSTs. The evaluation of WRF indicates that its storm propagation is too fast over West Africa, where associated WRF precipitation rates are exaggerated, but its performance is improved over the Atlantic.     

Simulation of the annual and diurnal cycles of rainfall over South Africa by a regional climate model

The capability of a current state-of-the-art regional climate model for simulating the diurnal and annual cycles of rainfall over a complex subtropical region is documented here. Hourly rainfall is simulated over Southern Africa for 1998–2006 by the non-hydrostatic model weather research and forecasting (WRF), and compared to a network of 103 stations covering South Africa. We used five simulations, four of which consist of different parameterizations for atmospheric convection at a 0.5 × 0.5° resolution, performed to test the physic-dependency of the results. The fifth experiment uses explicit convection over tropical South Africa at a 1/30° resolution. WRF simulates realistic mean rainfall fields, albeit wet biases over tropical Africa. The model mean biases are strongly modulated by the convective scheme used for the simulations. The annual cycle of rainfall is well simulated over South Africa, mostly influenced by tropical summer rainfall except in the Western Cape region experiencing winter rainfall. The diurnal cycle shows a timing bias, with atmospheric convection occurring too early in the afternoon, and causing too abundant rainfall. This result, particularly true in summer over the northeastern part of the country, is weakly physic-dependent. Cloud-resolving simulations do not clearly reduce the diurnal cycle biases. In the end, the rainfall overestimations appear to be mostly imputable to the afternoon hours of the austral summer rainy season, i.e., the periods during which convective activity is intense over the region.     

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.     

Modeling the impact of urbanization on the local and regional climate in Yangtze River Delta, China

The Yangtze River Delta Economic Belt is one of the most active and developed areas in China and has experienced quick urbanization with fast economic development. The weather research and forecasting model (WRF), with a single-layer urban canopy parameterization scheme, is used to simulate the influence of urbanization on climate at local and regional scales in this area. The months January and July, over a 5-year period (2003–2007), were selected to represent the winter and summer climate. Two simulation scenarios were designed to investigate the impacts of urbanization: (1) no urban areas and (2) urban land cover determined by MODIS satellite observations in 2005. Simulated near-surface temperature, wind speed and specific humidity agree well with the corresponding measurements. By comparing the simulations of the two scenarios, differences in near-surface temperature, wind speed and precipitation were quantified. The conversion of rural land (mostly irrigation cropland) to urban land cover results in significant changes to near-surface temperature, humidity, wind speed and precipitation. The mean near-surface temperature in urbanized areas increases on average by 0.45?±?0.43°C in winter and 1.9?±?0.55°C in summer; the diurnal temperature range in urbanized areas decreases on average by 0.13?±?0.73°C in winter and 0.55?±?0.84°C in summer. Precipitation increases about 15% over urban or leeward areas in summer and changes slightly in winter. The urbanization impact in summer is stronger and covers a larger area than that in winter due to the regional east-Asian monsoon climate characterized by warm, wet summers and cool, dry winters.     

Modeling and analysis of the potential impacts on regional climate due to vegetation degradation over arid and semi-arid regions of China

The regional climate effects of vegetation change in arid and semi-arid regions of China, which has experienced serious grassland degradation, are investigated in this study using the Weather Research and Forecasting (WRF) regional climate model. Two long-term simulation experiments (from January 1, 1980 to March 1, 2010), one with the land cover derived from the original United States Geological Survey’s (USGS) data (denoted as CTL) and the other (denoted as SEN) with a modification of the former one by vegetation degradation in arid and semi-arid regions of China, are undertaken to investigate the influence of land cover change on regional climate over arid and semi-arid regions of China. The possible mechanisms of how land cover change affects the regional climate in arid and semi-arid regions of China are also examined. The simulation results indicate that when compared with the observation datasets, the WRF model simulates the spatial pattern of observed temperature and precipitation quite well. After vegetation degradation over the arid and semi-arid regions of China, the net radiation and evaporation are reduced mainly within the degraded areas in summer, consistent with the reduction in precipitation and the increase in 2-m air temperature (T2 m).     

Modeling Study of Foehn Wind Events in Antarctic Peninsula with WRF Forced by CCSM

Significant changes have occurred in the Antarctic Peninsula (AP) including warmer temperatures, accelerated melting of glaciers, and breakup of ice shelves. This study uses the Weather Research and Forecasting model (WRF) forced by the Community Climate System Model 4 (CCSM) simulations to study foehn wind warming in AP. Weather systems responsible for generating the foehn events are two cyclonic systems that move toward and/or cross over AP. WRF simulates the movement of cyclonic systems and the resulting foehn wind warming that is absent in CCSM. It is found that the warming extent along a transect across the central AP toward Larsen C Ice Shelf (LCIS) varies during the simulation period and the maximum warming moves from near the base of leeward slopes to over 40 km away extending toward the attached LCIS. Our analysis suggests that the foehn wind warming is negatively correlated with the incoming air temperature and the mountain top temperature during periods without significant precipitation, in which isentropic drawdown is the dominant heating mechanism. On the other hand, when significant precipitation occurs along the windward side of AP, latent heating is the major heating mechanism evidenced by positive relations between the foehn wind warming and 1) incoming air temperature, 2) windward precipitation, and 3) latent heating. Foehn wind warming caused by isentropic drawdown also tends to be stronger than that caused by latent heating. Comparison of WRF simulations forced by original and corrected CCSM data indicates that foehn wind warming is stronger in the original CCSM forced simulation when no significant windward precipitation is present. The foehn wind warming becomes weaker in both simulations when there is significant windward precipitation. This suggests that model’s ability to resolve the foehn warming varies with the forcing data, but the precipitation impact on the leeward warming is consistent.