William K. M. Lau

Bio: William K. M. Lau is an academic researcher from Texas A&M University. The author has contributed to research in topics: Sea surface temperature & Monsoon. The author has an hindex of 2, co-authored 3 publications receiving 174 citations. Previous affiliations of William K. M. Lau include University of Maryland, College Park.

Intercomparison and analyses of the climatology of the West African Monsoon in the West African Monsoon Modeling and Evaluation project (WAMME) first model intercomparison experiment

Abstract: This paper briefly presents the West African Monsoon (WAM) Modeling and Evaluation Project (WAMME) and evaluates WAMME general circulation models’ (GCM) performances in simulating variability of WAM precipitation, surface temperature, and major circulation features at seasonal and intraseasonal scales in the first WAMME experiment. The analyses indicate that models with specified sea surface temperature generally have reasonable simulations of the pattern of spatial distribution of WAM seasonal mean precipitation and surface temperature as well as the averaged zonal wind in latitude-height cross-section and low level circulation. But there are large differences among models in simulating spatial correlation, intensity, and variance of precipitation compared with observations. Furthermore, the majority of models fail to produce proper intensities of the African Easterly Jet (AEJ) and the tropical easterly jet. AMMA Land Surface Model Intercomparison Project (ALMIP) data are used to analyze the association between simulated surface processes and the WAM and to investigate the WAM mechanism. It has been identified that the spatial distributions of surface sensible heat flux, surface temperature, and moisture convergence are closely associated with the simulated spatial distribution of precipitation; while surface latent heat flux is closely associated with the AEJ and contributes to divergence in AEJ simulation. Common empirical orthogonal functions (CEOF) analysis is applied to characterize the WAM precipitation evolution and has identified a major WAM precipitation mode and two temperature modes (Sahara mode and Sahel mode). Results indicate that the WAMME models produce reasonable temporal evolutions of major CEOF modes but have deficiencies/uncertainties in producing variances explained by major modes. Furthermore, the CEOF analysis shows that WAM precipitation evolution is closely related to the enhanced Sahara mode and the weakened Sahel mode, supporting the evidence revealed in the analysis using ALMIP data. An analysis of variability of CEOF modes suggests that the Sahara mode leads the WAM evolution, and divergence in simulating this mode contributes to discrepancies in the precipitation simulation.

Competing influences of greenhouse warming and aerosols on Asian Summer Monsoon circulation and rainfall.

Abstract: In this paper, we have compared and contrasted competing and amplifying influences on the global and regional drivers, circulation and rainfall responses of the Asian monsoon under global greenhouse warming (GHG) and aerosol forcing, based on CMIP5 historical simulations. Under GHG-only forcing, the land warms much faster than the ocean, magnifying the pre-industrial climatological land-ocean thermal contrast and hemispheric asymmetry, i.e., warmer northern than southern hemisphere. A steady increasing warm-ocean-warmer-land (WOWL) trend has been in effect since the 1950's substantially increasing moisture transport from adjacent oceans, and enhancing rainfall over the Asian monsoon regions. However, under GHG warming, increased atmospheric stability due to strong reduction in mid-tropospheric and near surface relative humidity coupled to an expanding subsidence areas, associated with the Deep Tropical Squeeze (DTS, Lau and Kim, 2015b) strongly suppress monsoon convection and rainfall over subtropical and extratropical land, leading to a weakening of the Asian monsoon meridional circulation. The inclusion of aerosol emissions strongly masks WOWL, by over 60% over the northern hemisphere, negating to a large extent the rainfall increase due to GHG warming, and leading to a further weakening of the monsoon circulation, through increasing atmospheric stability, most likely associated with aerosol solar dimming and semi-direct effects. Overall, we find that GHG exerts stronger positive rainfall sensitivity, but less negative circulation sensitivity in SASM compared to EASM. In contrast, aerosols exert stronger negative impacts on rainfall, but less negative impacts on circulation in EASM compared to SASM.

Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

Abstract: This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

Anthropogenic aerosols and the weakening of the South Asian summer monsoon

Abstract: Changes in monsoon rainfall are caused by human-produced aerosols slowing the tropical atmospheric circulation. Observations show that South Asia underwent a widespread summertime drying during the second half of the 20th century, but it is unclear whether this trend was due to natural variations or human activities. We used a series of climate model experiments to investigate the South Asian monsoon response to natural and anthropogenic forcings. We find that the observed precipitation decrease can be attributed mainly to human-influenced aerosol emissions. The drying is a robust outcome of a slowdown of the tropical meridional overturning circulation, which compensates for the aerosol-induced energy imbalance between the Northern and Southern Hemispheres. These results provide compelling evidence of the prominent role of aerosols in shaping regional climate change over South Asia.

Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations

Abstract: An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of ~50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989–2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precip...

Climate Simulations Using MRI-AGCM3.2 with 20-km Grid

Abstract: A new version of the atmospheric general circulation model of the Meteorological Research Institute (MRI), with a horizontal grid size of about 20 km, has been developed. The previous version of the 20-km model, MRIAGCM3.1, which was developed from an operational numerical weather-prediction model, provided information on possible climate change induced by global warming, including future changes in tropical cyclones, the East Asian monsoon, extreme events, and blockings. For the new version, MRI-AGCM3.2, we have introduced various new parameterization schemes that improve the model climate. Using the new model, we performed a present-day climate experiment using observed sea surface temperature. The model shows improvements in simulating heavy monthly-mean precipitation around the tropical Western Pacific, the global distribution of tropical cyclones, the seasonal march of East Asian summer monsoon, and blockings in the Pacific. Improvements in the model climatologies were confirmed numerically using skill scores (e.g., Taylor’s skill score).

Short-term modulation of Indian summer monsoon rainfall by West Asian dust

Abstract: The Indian summer monsoon is influenced by numerous factors, including aerosol-induced changes to clouds, surface and atmospheric heating, and atmospheric circulation. An analysis of satellite data and global climate model simulations suggests that dust aerosol levels over the Arabian Sea, West Asia and the Arabian Peninsula are positively correlated with the intensity of the Indian summer monsoon.

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation

Abstract: West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the 21st century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options difficult. Further efforts are needed to improve modelling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, the response of the crops to such changes and in the potential for adaptation.