Climate change in Central America and Mexico: regional climate model validation and climate change projections

Central America has high biodiversity, it harbors high-value ecosystems and it??s important to provide regional climate change information to assist in adaptation and mitigation work in the region. Here we study climate change projections for Central America and Mexico using a regional climate model. The model evaluation shows its success in simulating spatial and temporal variability of temperature and precipitation and also in capturing regional climate features such as the bimodal annual cycle of precipitation and the Caribbean low-level jet. A variety of climate regimes within the model domain are also better identified in the regional model simulation due to improved resolution of topographic features. Although, the model suffers from large precipitation biases, it shows improvements over the coarse-resolution driving model in simulating precipitation amounts. The model shows a dry bias in the wet season and a wet bias in the dry season suggesting that it??s unable to capture the full range of precipitation variability. Projected warming under the A2 scenario is higher in the wet season than that in the dry season with the Yucatan Peninsula experiencing highest warming. A large reduction in precipitation in the wet season is projected for the region, whereas parts of Central America that receive a considerable amount of moisture in the form of orographic precipitation show significant decreases in precipitation in the dry season. Projected climatic changes can have detrimental impacts on biodiversity as they are spatially similar, but far greater in magnitude, than those observed during the El Ni?o events in recent decades that adversely affected species in the region.     

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia.     

Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF

Regional climate model (RCM) is a valuable scientific tool to address the mechanisms of regional atmospheric systems such as the West African monsoon (WAM). This study aims to improve our understanding of the impact of some physical schemes of RCM on the WAM representation. The weather research and forecasting model has been used by performing six simulations of the 2006 summer WAM season. These simulations use all combinations of three convective parameterization schemes (CPSs) and two planetary boundary layer schemes (PBLSs). By comparing the simulations to a large set of observations and analysis products, we have evaluated the ability of these RCM parameterizations to reproduce different aspects of the regional atmospheric circulation of the WAM. This study focuses in particular on the WAM onset and the rainfall variability simulated over this domain. According to the different parameterizations tested, the PBLSs seem to have the strongest effect on temperature, humidity vertical distribution and rainfall amount. On the other hand, dynamics and precipitation variability are strongly influenced by CPSs. In particular, the Mellor?CYamada?CJanjic PBLS attributes more realistic values of humidity and temperature. Combined with the Kain?CFritsch CPS, the WAM onset is well represented. The different schemes combination tested also reveal the role of different regional climate features on WAM dynamics, namely the low level circulation, the land?Catmosphere interactions and the meridional temperature gradient between the Guinean coast and the Sahel.     

How well are daily intense rainfall events captured by current climate models over Africa?

The ability of state-of-the-art climate models to capture the mean spatial and temporal characteristics of daily intense rainfall events over Africa is evaluated by analyzing regional climate model (RCM) simulations at 90- and 30-km along with output from four atmospheric general circulation models (AGCMs) and coupled atmosphere–ocean general circulation models (AOGCMs) of the Climate Model Intercomparison Project 5. Daily intense rainfall events are extracted at grid point scale using a 95th percentile threshold approach applied to all rainy days (i.e., daily rainfall ≥1 mm day^?1) over the 1998–2008 period for which two satellite-derived precipitation products are available. Both RCM simulations provide similar results. They accurately capture the spatial and temporal characteristics of intense events, while they tend to overestimate their number and underestimate their intensity. The skill of AGCMs and AOGCMs is generally similar over the African continent and similar to previous global climate model generations. The majority of the AGCMs and AOGCMs greatly overestimate the frequency of intense events, particularly in the tropics, generally fail at simulating the observed intensity, and systematically overestimate their spatial coverage. The RCM performs at least as well as the most accurate global climate model, demonstrating a clear added value to general circulation model simulations and the usefulness of regional modeling for investigating the physics leading to intense events and their change under global warming.     

High-resolution simulations of West African climate using regional climate model (RegCM3) with different lateral boundary conditions

To downscale climate change scenarios, long-term regional climatologies employing global model forcing are needed for West Africa. As a first step, this work examines present-day integrations (1981–2000) with a regional climate model (RCM) over West Africa nested in both reanalysis data and output from a coupled atmospheric–ocean general circulation model (AOGCM). Precipitation and temperature from both simulations are compared to the Climate Research Unit observations. Their spatial distributions are shown to be realistic. Annual cycles are considerably correlated. Simulations are also evaluated with respect to the driving large-scale fields. RCM offers some improvements compared to the AOGCM driving field. Evaluation of seasonal precipitation biases reveals that RCM dry biases are highest on June–August around mountains. They are associated to cold biases in temperature which, in turn, are connected to wet biases in precipitation outside orographic zones. Biases brought through AOGCM forcing are relatively low. Despite these errors, the simulations produce encouraging results and show the ability of the AOGCM to drive the RCM for future projections.     

The observed teleconnection between the equatorial Amazon and the Intra-Americas Seas

Using observations of rainfall and SST analysis it is shown that there is a robust relationship with two-season lag between the austral summer (December–January–February [DJF]) Equatorial Amazon (EA) rainfall and the following boreal summer season (June–July–August [JJA]) Intra-Americas Seas (IAS) Sea Surface Temperature Anomalies (SSTA). It is observed that in wetter than normal austral summer seasons over EA, the SSTA in the IAS are cooler than normal in the following JJA season. This teleconnection also manifests in the ocean heat content of the IAS region. Our analysis indicates that the net surface heat flux into the ocean (particularly the surface longwave and the shortwave radiative fluxes) dictates the strongest influence on the JJA Caribbean SSTA, the core region of the IAS where the observed teleconnection with EA rainfall is strongest. This study also finds that this teleconnection is in fact a manifestation of the remote ENSO forcing on the Caribbean SSTA through its modulation of the EA rainfall anomalies. In a wet DJF year over EA, the Atlantic Inter-Tropical Convergence Zone (ITCZ) moves further southward than climatology. This causes the dry limb of the associated overturning circulation of the Atlantic ITCZ to reside over the Caribbean Sea region in the subsequent March–April–May and JJA seasons. As a result of this large-scale descent in the wet DJF year over EA, there is a net decrease in the heat flux into the ocean from increased emission of surface longwave radiation in the presence of anomalously dry atmosphere. In a dry DJF year over EA the Atlantic ITCZ is nearly co-located in the core region of the IAS, which is northward than the climatological location, resulting in the descending limb of the overturning location to be located further south of the Caribbean Sea leading to warmer SSTA.     

Precipitation extremes and the impacts of climate change on stormwater infrastructure in Washington State

The design of stormwater infrastructure is based on an underlying assumption that the probability distribution of precipitation extremes is statistically stationary. This assumption is called into question by climate change, resulting in uncertainty about the future performance of systems constructed under this paradigm. We therefore examined both historical precipitation records and simulations of future rainfall to evaluate past and prospective changes in the probability distributions of precipitation extremes across Washington State. Our historical analyses were based on hourly precipitation records for the time period 1949–2007 from weather stations in and near the state’s three major metropolitan areas: the Puget Sound region, Vancouver (WA), and Spokane. Changes in future precipitation were evaluated using two runs of the Weather Research and Forecast (WRF) regional climate model (RCM) for the time periods 1970–2000 and 2020–2050, dynamically downscaled from the ECHAM5 and CCSM3 global climate models. Bias-corrected and statistically downscaled hourly precipitation sequences were then used as input to the HSPF hydrologic model to simulate streamflow in two urban watersheds in central Puget Sound. Few statistically significant changes were observed in the historical records, with the possible exception of the Puget Sound region. Although RCM simulations generally predict increases in extreme rainfall magnitudes, the range of these projections is too large at present to provide a basis for engineering design, and can only be narrowed through consideration of a larger sample of simulated climate data. Nonetheless, the evidence suggests that drainage infrastructure designed using mid-20th century rainfall records may be subject to a future rainfall regime that differs from current design standards.     

Spatial variability of Holocene changes in the annual precipitation pattern: a model-data synthesis for the Asian monsoon region

This study provides a detailed analysis of the mid-Holocene to present-day precipitation change in the Asian monsoon region. We compare for the first time results of high resolution climate model simulations with a standardised set of mid-Holocene moisture reconstructions. Changes in the simulated summer monsoon characteristics (onset, withdrawal, length and associated rainfall) and the mechanisms causing the Holocene precipitation changes are investigated. According to the model, most parts of the Indian subcontinent received more precipitation (up to 5 mm/day) at mid-Holocene than at present-day. This is related to a stronger Indian summer monsoon accompanied by an intensified vertically integrated moisture flux convergence. The East Asian monsoon region exhibits local inhomogeneities in the simulated annual precipitation signal. The sign of this signal depends on the balance of decreased pre-monsoon and increased monsoon precipitation at mid-Holocene compared to present-day. Hence, rainfall changes in the East Asian monsoon domain are not solely associated with modifications in the summer monsoon circulation but also depend on changes in the mid-latitudinal westerly wind system that dominates the circulation during the pre-monsoon season. The proxy-based climate reconstructions confirm the regional dissimilarities in the annual precipitation signal and agree well with the model results. Our results highlight the importance of including the pre-monsoon season in climate studies of the Asian monsoon system and point out the complex response of this system to the Holocene insolation forcing. The comparison with a coarse climate model simulation reveals that this complex response can only be resolved in high resolution simulations.     

Sources of systematic errors in the climatology of a regional climate model over Europe

 Two ten-year simulations made with a European regional climate model (RCM) are compared. They are driven by the same observed sea surface temperatures but use different lateral boundary forcing. For one simulation, RCM AMIP, this forcing is obtained from a standard integration of a global general circulation model (GCM AMIP), whereas for the other simulation, RCM ASSIM, it is derived from a time series of operational analyses. The archive of analysis fields (surface pressure plus winds and temperatures on various pressure levels) is not sufficiently comprehensive to provide directly the full set of driving fields required for the RCM (in particular, no moisture fields are present), so these are obtained via a GCM integration, GCM ASSIM, in which the model is continuously relaxed towards the analysis fields using a data assimilation technique. Errors in RCM AMIP can arise either from the internal RCM physics or from errors in the lateral boundary forcing inherited from GCM AMIP. Errors in RCM ASSIM can arise from the internal RCM physics or the boundary moisture forcing but not from the driving circulation. Although previous studies have considered RCM integrations driven either by output from standard GCM integrations or operational analyses, our study is the first to compare parallel integrations of each type. This allows the total systematic error in an RCM integration driven by standard GCM output to be partitioned into components arising from the driving circulation and the internal RCM physics. These components indicate the scope for reducing regional simulation biases by improving either the driving GCM or the RCM itself. The results relate mainly to elements of surface climate likely to be influenced by both the driving circulation and regional physical processes operating in the RCM. For cloud cover, errors are found to arise largely from the internal RCM physics. Values are too low despite a positive relative humidity bias, indicating shortcomings in the parametrisation scheme used to calculate cloud cover. In summer, surface temperature and precipitation errors are also explained principally by regional processes. For example excessive solar heating leads to anomalously high surface temperatures over southern Europe and excessive drying of the soil reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing also exerts some influence, mainly via a tropospheric cold bias which partially offsets the warming over southern Europe and also increases precipitation. In other seasons the lateral boundary forcing and the regional physics both contribute significantly to the errors in surface temperature and precipitation. In winter the boundary forcing (apart from moisture) is responsible for about 60% of the total error variance for temperature and about 40% for precipitation, due to the cold bias and circulation errors such as a southward shift in the storm track. The remaining errors arise from the regional physics, although for precipitation an excessive supply of moisture from the lateral boundaries also contributes. The skill of the mesoscale component of the surface temperature and precipitation distributions exceeds previous estimates, due to more realistic observed climatology. The mesoscale patterns are very similar in the two RCM simulations indicating that errors in the simulation of fine scale detail arise mainly from inadequate representations of local forcings rather than errors in the large-scale circulation. Circulation errors in RCM AMIP (e.g. cold bias, southward shift of storm track) are also present in GCM AMIP, but are largely absent in RCM ASSIM except in summer. This confirms evidence from previous work that the key to reducing most circulation errors in the RCM lies in improving the driving GCM. Regional processes only make a major contribution to circulation errors in summer, when reduced advection from the boundaries allows errors in surface temperature to be transmitted more effectively into the troposphere. Finally, we find evidence of error balances in the GCM which act to minimise biases in important climatological variables. This reflects tuning of the model physics at GCM resolution. In order to achieve simultaneous optimisation of the RCM and GCM at widely differing resolutions it may be necessary to introduce explicit scale dependences into some aspects of the physics. Received: 17 September 1997/Accepted: 10 March 1998     

Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors

Monthly-mean precipitation, mean (T_AVG), maximum (T_MAX) and minimum (T_MIN) surface air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) hindcast experiment are evaluated for model skill and systematic biases. All RCMs simulate basic climatological features of these variables reasonably, but systematic biases also occur across these models. All RCMs show higher fidelity in simulating precipitation for the west part of Africa than for the east part, and for the tropics than for northern Sahara. Interannual variation in the wet season rainfall is better simulated for the western Sahel than for the Ethiopian Highlands. RCM skill is higher for T_AVG and T_MAX than for T_MIN, and regionally, for the subtropics than for the tropics. RCM skill in simulating cloudiness is generally lower than for precipitation or temperatures. For all variables, multi-model ensemble (ENS) generally outperforms individual models included in ENS. An overarching conclusion in this study is that some model biases vary systematically for regions, variables, and metrics, posing difficulties in defining a single representative index to measure model fidelity, especially for constructing ENS. This is an important concern in climate change impact assessment studies because most assessment models are run for specific regions/sectors with forcing data derived from model outputs. Thus, model evaluation and ENS construction must be performed separately for regions, variables, and metrics as required by specific analysis and/or assessments. Evaluations using multiple reference datasets reveal that cross-examination, quality control, and uncertainty estimates of reference data are crucial in model evaluations.     

Diurnal variations of circulation and precipitation in the vicinity of the Tibetan Plateau in early summer

A regional climate model (RCM) has been applied to simulate the diurnal variations of the Asian summer monsoon during the early summer period. The ERA40 reanalysis data and the TRMM precipitation data are used to evaluate the performance of the model. The 5-year simulations show that the RCM could simulate well the diurnal cycle of the monsoon circulation over the region. A strong diurnal variation of circulation over the Tibetan Plateau (TP) can be observed at the 500-hPa level, with strong convergence and upward motion in the late afternoon. The diurnal variation of the 500-hPa relative vorticity over the TP associated with the corresponding diurnal variation of convergence may lead to the formation of a prominent plateau-scale cyclonic circulation over the TP during the evening to midnight period. The simulated diurnal variation of precipitation over land is generally better than that over the ocean, particularly over the regions close to the TP such as the Bangladesh region in the southern flank of the TP, where the well-known nocturnal maximum in precipitation is well captured by the RCM. However, the late-afternoon maximum in precipitation over the Southeast Asia region is not well simulated by the RCM. The model results suggest that the diurnal variation of precipitation over the southern flank of the TP is associated with the strong diurnal variation in the circulation over the TP.     

Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments

Seasonal simulations of the Indian summer monsoon using a 50-km regional climate model (RCM) are described. Results from three versions of the RCM distinguished by different domain sizes are compared against those of the driving global general circulation model (AGCM). Precipitation over land is 20% larger in the RCMs due to stronger vertical motions arising from finer horizontal resolution. The resulting increase in condensational heating helps to intensify the monsoon trough relative to the AGCM. The RCM precipitation distributions show a strong orographically forced mesoscale component (similar in each version). This component is not present in the AGCM. The RCMs produce two qualitatively realistic intraseasonal oscillations (ISOs) associated respectively with monsoon depressions which propagate northwestward from the Bay of Bengal and repeated northward migrations of the regional tropical convergence zone. The RCM simulations are relatively insensitive to domain size in several respects: (1) the mean bias relative to the AGCM is similar for all three domains; (2) the variability simulated by the RCM is strongly correlated with that of the driving AGCM on both daily and seasonal time scales, even for the largest domain; (3) the mesoscale features and ISOs are not damped by the relative proximity of the lateral boundaries in the version with the smallest domain. Results (1) and (2) contrast strongly with a previous study for Europe carried out with the same model, probably due to inherent differences between mid-latitude and tropical dynamics.     

Future climate of the Caribbean from a super-high-resolution atmospheric general circulation model

Present-day (1979–2003) and future (2075–2099) simulations of mean and extreme rainfall and temperature are examined using data from the Meteorological Research Institute super-high-resolution atmospheric general circulation model. Analyses are performed over the 20-km model grid for (1) a main Caribbean basin, (2) sub-regional zones, and (3) specific Caribbean islands. Though the model’s topography underestimates heights over the eastern Caribbean, it captures well the present-day spatial and temporal variations of seasonal and annual climates. Temperature underestimations range from 0.1 °C to 2 °C with respect to the Japanese Reanalysis and the Climatic Research Unit datasets. The model also captures fairly well sub-regional scale variations in the rainfall climatology. End-of-century projections under the Intergovernmental Panel on Climate Change SRES A1B scenario indicate declines in rainfall amounts by 10–20 % for most of the Caribbean during the early (May–July) and late (August–October) rainy seasons relative to the 1979–2003 baselines. The early dry season (November–January) is also projected to get wetter in the far north and south Caribbean by approximately 10 %. The model also projects a warming of 2–3 °C over the Caribbean region. Analysis of future climate extremes indicate a 5–10 % decrease in the simple daily precipitation intensity but no significant change in the number of consecutive dry days for Cuba, Jamaica, southern Bahamas, and Haiti. There is also indication that the number of hot days and nights will significantly increase over the main Caribbean basin.     

Simulation and Projection of Changes in Rainy Season Precipitation over China Using the WRF Model

The Weather Research and Forecasting (WRF) model is used in a regional climate model configuration to simulate past precipitation climate of China during the rainy season (May-September) of 1981-2000, and to investigate potential future (2041-2060 and 2081-2100) changes in precipitation over China relative to the reference period 1981-2000. WRF is run with initial conditions from a coupled general circulation model, i.e., the high-resolution version of MIROC (Model for Interdisciplinary Research on Climate). WRF reproduces the observed distribution of rainy season precipitation in 1981-2000 and its interannual variations better than MIROC. MIROC projects increases in rainy season precipitation over most parts of China and decreases of more than 25 mm over parts of Taiwan and central Tibet by the mid-21st century. WRF projects decreases in rainfall over southern Tibetan Plateau, Southwest China, and northwestern part of Northeast China, and increases in rainfall by more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River during 2041-2060. MIROC projects further increases in rainfall over most of China by the end of the 21st century, although simulated rainfall decreases by more than 25 mm over parts of Taiwan, Guangxi, Guizhou, and central Tibet. WRF projects increased rainfall of more than 100 mm along the southeastern margin of the Tibetan Plateau and over the lower reaches of the Yangtze River and decreased rainfall over Southwest China, and southern Tibetan Plateau by the end of the 21st century.     

Sub-Saharan Northern African climate at the end of the twenty-first century: forcing factors and climate change processes

A regional climate model, the Weather Research and Forecasting (WRF) Model, is forced with increased atmospheric CO₂ and anomalous SSTs and lateral boundary conditions derived from nine coupled atmosphere–ocean general circulation models to produce an ensemble set of nine future climate simulations for northern Africa at the end of the twenty-first century. A well validated control simulation, agreement among ensemble members, and a physical understanding of the future climate change enhance confidence in the predictions. The regional model ensembles produce consistent precipitation projections over much of northern tropical Africa. A moisture budget analysis is used to identify the circulation changes that support future precipitation anomalies. The projected midsummer drought over the Guinean Coast region is related partly to weakened monsoon flow. Since the rainfall maximum demonstrates a southward bias in the control simulation in July–August, this may be indicative of future summer drying over the Sahel. Wetter conditions in late summer over the Sahel are associated with enhanced moisture transport by the West African westerly jet, a strengthening of the jet itself, and moisture transport from the Mediterranean. Severe drought in East Africa during August and September is accompanied by a weakened Indian monsoon and Somali jet. Simulations with projected and idealized SST forcing suggest that overall SST warming in part supports this regional model ensemble agreement, although changes in SST gradients are important over West Africa in spring and fall. Simulations which isolate the role of individual climate forcings suggest that the spatial distribution of the rainfall predictions is controlled by the anomalous SST and lateral boundary conditions, while CO₂ forcing within the regional model domain plays an important secondary role and generally produces wetter conditions.     

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.     

Climate change projections for the Texas High Plains and Rolling Plains

Potential changes in future climate in the Texas Plains region were investigated in the context of agriculture by analyzing three climate model projections under the A2 climate scenario (medium–high emission scenario). Spatially downscaled historic (1971–2000) and future (2041–2070) climate datasets (rainfall and temperature) were downloaded from the North American Regional Climate Change Assessment Program (NARCCAP). Climate variables predicted by three regional climate models (RCMs) namely the Regional Climate Model Version3–Geophysical Fluid Dynamics Laboratory (RCM3-GFDL), Regional Climate Model Version3–Third Generation Coupled Global Climate Model (RCM3-CGCM3), and Canadian Regional Climate Model–Community Climate System Model (CRCM-CCSM) were evaluated in this study. Gaussian and Gamma distribution mapping techniques were employed to remove the bias in temperature and rainfall data, respectively. Both the minimum and maximum temperatures across the study region in the future showed an upward trend, with the temperatures increasing in the range of 1.9 to 2.9 °C and 2.0 to 3.2 °C, respectively. All three climate models predicted a decline in rainfall within a range of 30 to 127 mm in majority of counties across the study region. In addition, they predicted an increase in the intensity of extreme rainfall events in the future. The frost-free season as predicted by the three models showed an increase by 2.6–3.4 weeks across the region, and the number of frost days declined by 17.9 to 30 %. Overall, these projections indicate considerable changes to the climate in the Texas Plains region in the future, and these changes could potentially impact agriculture in this region.

     

Climate change in the northeastern US: regional climate model validation and climate change projections

A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Different types of uncertainties in climate simulations are examined by driving the RCM with different boundary data, applying different emissions scenarios, and running an ensemble of simulations with different initial conditions. Empirical orthogonal functions analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature (SAT) and precipitation variability. The RCM simulations tend to overestimate SAT, especially over the northern part of the domain in winter and over the western part in summer. Statistically significant increases in seasonal SAT under both higher and lower emissions scenarios over the whole RCM domain suggest the robustness of future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, though the changes are not statistically significant. The greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change.     

Soil-precipitation feedbacks during the South American Monsoon as simulated by a regional climate model

We summarize the recent progress in regional climate modeling in South America with the Rossby Centre regional atmospheric climate model (RCA3-E), with emphasis on soil moisture processes. A series of climatological integrations using a continental scale domain nested in reanalysis data were carried out for the initial and mature stages of the South American Monsoon System (SAMS) of 1993–92 and were analyzed on seasonal and monthly timescales. The role of including a spatially varying soil depth, which extends to 8 m in tropical forest, was evaluated against the standard constant soil depth of the model of about 2 m, through two five member ensemble simulations. The influence of the soil depth was relatively weak, with both beneficial and detrimental effects on the simulation of the seasonal mean rainfall. Secondly, two ensembles that differ in their initial state of soil moisture were prepared to study the influence of anomalously dry and wet soil moisture initial conditions on the intraseasonal development of the SAMS. In these simulations the austral winter soil moisture initial condition has a strong influence on wet season rainfall over feed back upon the monsoon, not only over the Amazon region but in subtropical South America as well. Finally, we calculated the soil moisture–precipitation coupling strength through comparing a ten member ensemble forced by the same space–time series of soil moisture fields with an ensemble with interactive soil moisture. Coupling strength is defined as the degree to which the prescribed boundary conditions affect some atmospheric quantity in a climate model, in this context a quantification of the fraction of atmospheric variability that can be ascribed to soil moisture anomalies. La Plata Basin appears as a region where the precipitation is partly controlled by soil moisture, especially in November and January. The continental convective monsoon regions and subtropical South America appears as a region with relatively high coupling strength during the mature phase of monsoon development.