Hsin-I Chang

Impacts of land use/land cover change on climate and future research priorities.

Several recommendations have been proposed for detecting land use and land cover change (LULCC) on the environment from, observed climatic records and to modeling to improve its understanding and its impacts on climate. Researchers need to detect LULCCs accurately at appropriate scales within a specified time period to better understand their impacts on climate and provide improved estimates of future climate. The US Climate Reference Network (USCRN) can be helpful in monitoring impacts of LULCC on near-surface atmospheric conditions, including temperature. The USCRN measures temperature, precipitation, solar radiation, and ground or skin temperature. It is recommended that the National Climatic Data Center (NCDC) and other climate monitoring agencies develop plans and seek funds to address any monitoring biases that are identified and for which detailed analyses have not been completed.

Can a regional climate model improve the ability to forecast the North American monsoon

AbstractGlobal climate models are challenged to represent the North American monsoon, in terms of its climatology and interannual variability. To investigate whether a regional atmospheric model can improve warm season forecasts in North America, a retrospective Climate Forecast System (CFS) model reforecast (1982–2000) and the corresponding NCEP–NCAR reanalysis are dynamically downscaled with the Weather Research and Forecasting model (WRF), with similar parameterization options as used for high-resolution numerical weather prediction and a new spectral nudging capability. The regional model improves the climatological representation of monsoon precipitation because of its more realistic representation of the diurnal cycle of convection. However, it is challenged to capture organized, propagating convection at a distance from terrain, regardless of the boundary forcing data used. Dynamical downscaling of CFS generally yields modest improvement in surface temperature and precipitation anomaly correlations...

The more extreme nature of North American Monsoon precipitation in the Southwestern United States as revealed by a historical climatology of simulated severe weather events

AbstractLong-term changes in North American monsoon (NAM) precipitation intensity in the Southwest U.S. are evaluated through the use of convective-permitting model simulations of objectively identified severe weather events during “historical past” (1950-1970) and “present day” (1991-2010) periods. Severe weather events are days when the highest atmospheric instability and moisture occur within a long-term regional climate simulation. Severe weather event day simulations are performed with convective-permitting (2.5 km) grid spacing, and these simulations are compared to available observed precipitation data to evaluate the model performance and verify any statistically significant model simulated trends in precipitation. Statistical evaluation of precipitation extremes is performed using peaks-over-threshold approach with a generalized Pareto distribution. A statistically significant long-term increase in atmospheric moisture and instability is associated with an increase in extreme monsoon precipitatio...

The more extreme nature of U.S. warm season climate in the recent observational record and two “well‐performing” dynamically downscaled CMIP3 models

Arid and semiarid regions located in subtropical zones are projected to experience the most adverse impacts of climate change. During the warm season, observations and Intergovernmental Panel on Climate Change global climate models generally support a “wet gets wetter, dry gets drier” hypothesis in these regions, which acts to amplify the climatological transitions in the context of the annual cycle. In this study, we consider changes in U.S. early warm season precipitation in the observational record and regional climate model simulations driven by two “well-performing” dynamically downscaled Coupled Model Intercomparison Project phase 3 (CMIP3) models (Hadley Centre Coupled Model, version 3 and Max Planck Institute (MPI) European Centre/Hamburg Model 5) that have a robust climatological representation of the North American Monsoon System (NAMS). Both observations and model results show amplification in historical seasonal transitions of temperature and precipitation associated with NAMS development, with Weather Research and Forecasting (WRF)-MPI better representing the observed signal. Assuming the influence of remote Pacific sea surface temperature (SST) forcing associated with the El Nino–Southern Oscillation and Pacific Decadal Variability (ENSO-PDV) on U.S. regional climate remains the same in the 21st century, similar extreme trends are also projected by WRF-MPI for the next 30 years. A methodology is also developed to objectively analyze how climate change may be synergistically interacting with ENSO-PDV variability during the early warm season. Our analysis suggests that interannual variability of warm season temperature and precipitation associated with Pacific SST forcing is becoming more extreme, and the signal is stronger in the observed record.

Objective Climatological Analysis of Extreme Weather Events in Arizona during the North American Monsoon

Strategic Environmental Research and Development Program (SERDP) through the U.S. Departments of Defense and Energy [RC-2205]; U.S. Environmental Protection Agency; Universidad Nacional Autonoma de Mexico Programa de Apoyo a Proyectos de Investigation e Innovation Tecnologica (UNAM PAPIIT) [IA100916]

Multi-year climate variability in the Southwestern United States within a context of a dynamically downscaled twentieth century reanalysis

This investigation evaluates whether there is coherency in warm and cool season precipitation at the low-frequency scale that may be responsible for multi-year droughts in the US Southwest. This low-frequency climate variability at the decadal scale and longer is studied within the context of a twentieth-century reanalysis (20CR) and its dynamically-downscaled version (DD-20CR). A spectral domain matrix methods technique (Multiple-Taper-Method Singular Value Decomposition) is applied to these datasets to identify statistically significant spatiotemporal precipitation patterns for the cool (November–April) and warm (July–August) seasons. The low-frequency variability in the 20CR is evaluated by exploring global to continental-scale spatiotemporal variability in moisture flux convergence (MFC) to the occurrence of multiyear droughts and pluvials in Central America, as this region has a demonstrated anti-phase relationship in low-frequency climate variability with northern Mexico and the southwestern US By using the MFC in lieu of precipitation, this study reveals that the 20CR is able to resolve well the low-frequency, multiyear climate variability. In the context of the DD-20CR, multiyear droughts and pluvials in the southwestern US (in the early twentieth century) are significantly related to this low-frequency climate variability. The precipitation anomalies at these low-frequency timescales are in phase between the cool and warm seasons, consistent with the concept of dual-season drought as has been suggested in tree ring studies.