Abstract. The Saharan heat low (SHL) is a key component of the west African climate system and an important driver of the west African monsoon across a range of timescales of variability. The physical mechanisms driving the variability in the SHL remain uncertain, although water vapour has been implicated as of primary importance. Here, we quantify the independent effects of variability in dust and water vapour on the radiation budget and atmospheric heating of the region using a radiative transfer model configured with observational input data from the Fennec field campaign at the location of Bordj Badji Mokhtar (BBM) in southern Algeria (21.4 • N, 0.9 • E), close to the SHL core for June 2011. Overall, we find dust aerosol and water vapour to be of similar importance in driving variability in the top-of-atmosphere (TOA) radiation budget and therefore the column-integrated heating over the SHL (∼ 7 W m −2 per standard deviation of dust aerosol optical depth -AOD). As such, we infer that SHL intensity is likely to be similarly enhanced by the effects of dust and water vapour surge events. However, the details of the processes differ. Dust generates substantial radiative cooling at the surface (∼ 11 W m −2 per standard deviation of dust AOD), presumably leading to reduced sensible heat flux in the boundary layer, which is more than compensated by direct radiative heating from shortwave (SW) absorption by dust in the dusty boundary layer. In contrast, water vapour invokes a radiative warming at the surface of ∼ 6 W m −2 per standard deviation of column-integrated water vapour in kg m −2 . Net effects involve a pronounced net atmospheric radiative convergence with heating rates on average of 0.5 K day −1 and up to 6 K day −1 during synoptic/mesoscale dust events from monsoon surges and convective cold-pool outflows ("haboobs"). On this basis, we make inferences on the processes driving variability in the SHL associated with radiative and advective heating/cooling. Depending on the synoptic context over the region, processes driving variability involve both independent effects of water vapour and dust and compensating events in which dust and water vapour are co-varying. Forecast models typically have biases of up to 2 kg m −2 in column-integrated water vapour (equivalent to a change in 2.6 W m −2 TOA net flux) and typically lack variability in dust and thus are expected to poorly represent these couplings. An improved representation of dust and water vapour and quantification of associated radiative impact in models is thus imperative to further understand the SHL and related climate processes.

<p>Heavy rainfall events are devastating, could trigger flash urban and rural river floods in some environmental settings. If we can better predict those floods, we will better protect the communities and vulnerable people. Here, we present some high-resolution regional climate model simulations to reproduce the January 2017 heavy rainfall events that occurred in Southern Thailand, causing major flash and river floods with high death tolls and significant socioeconomic impacts in the region of Krabi and Nakhon Si Thammarat provinces.  High rainfall events persisted in the region starting from January 4, 2017, peaking around January 6, and lasted until January 10. To reproduce the detailed timeline and spatial changes of heavy rainfall events, we have run the community Weather Research Forecasting (WRF) model with different combinations of cloud microphysical schemes.  The initial and lateral boundary conditions for our WRF simulations are based on the ERA5 reanalysis. The model simulations cover the period from 1st to 18th January 2017 using two nested domains with horizontal resolutions at 3-km and 9-km for the inner and outer domains, respectively. Four simulations were conducted with different cloud microphysics (WSM-6 scheme, Goddard scheme, Thompson scheme, and Purdue-Lin scheme) while keeping all other model configurations the same. In addition to these four experiments, we have also carried out one further experiment with a single domain at 3-km horizontal resolution. WRF simulations are compared using two satellite-derived measurements: 1) NASA Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) and 2) Climate Data Prediction Morphing (CMORPH). </p><p> </p><p>Our WRF simulations have reproduced the spatial distribution of this particular rainfall event, but the rainfall magnitude (intensity) is underestimated as compared with observations. Furthermore, different microphysical schemes have resulted in varying magnitudes of rainfall intensities with WSM-6 and Purdue-Lin schemes performing much better as compared with both Goddard and Thompson schemes. We also found the 3-km single domain run including spectral nudging has the best result of rainfall magnitude and spatial distribution as compared with the four nested runs. This paper re-emphasizes that with some careful selection of model configurations, WRF can reproduce detailed regional atmospheric processes. The best WRF model configuration can then be used in our dynamical downscaling of the IPCC AR5 CESM model run under the RCP6.0 from 2080 to 2100.</p>

<p><strong>Abstract.</strong> The Saharan heat low (SHL) is a key component of the West African climate system and an important driver of the West African Monsoon across a range of timescales of variability. The physical mechanisms driving the variability in the SHL remain uncertain, although water vapour has been implicated as of primary importance. Here, we quantify the independent effects of variability in dust and water vapour on the radiation budget and atmospheric heating of the region using a radiative transfer model configured with observational input data from the Fennec field campaign at the location of Bordj Badji Mokhtar (BBM) in southern Algeria (0.9E, 21.4N), close to the SHL core, for June 2011. Overall, we find dust aerosol and water vapour to be of similar importance in driving variability in the top of atmosphere (TOA) radiation budget and therefore the column integrated heating over the SHL (~7 W m<sup>−2</sup> per standard deviation of dust AOD). As such we infer that SHL intensity is likely to be similarly enhanced by the effects of dust and water vapour surge events. However, the details of the processes differ. Dust generates substantial radiative cooling at the surface (~11 W m<sup>−2</sup> per standard deviation of dust AOD), presumably leading to reduced sensible heat flux into the boundary layer, which is more than compensated by direct radiative heating from SW absorption by dust in the dusty boundary layer. In contrast water vapour invokes a longwave radiative warming of at the surface of ~6 W m<sup>−2</sup> per standard deviation of column integrated water vapour in Kg m<sup>−2</sup>. Net effects involve a pronounced net atmospheric radiative convergence with heating rates on average of 0.5 K day<sup>−1</sup> and up to 6 K day<sup>−1</sup> during synoptic/meso-scale dust events from monsoon surges and convective cold pool outflows (‘haboobs’). On this basis we make inferences on the processes driving variability in the SHL associated with radiative and advective heating/cooling. Depending on the synoptic context over the region processes driving variability involve both independent effects of water vapour and dust and compensating events in which dust and water vapour are co-varying. Forecast models typically have biases of up to 2 kg m<sup>−2</sup> in column integrated water vapour (equivalent to a change in 2.6 W m<sup>−2</sup> TOA net flux) and typically lack variability in dust, and so are expected to poorly represent these couplings. An improved representation dust and water vapour and quantification of associated radiative impact is thus imperative in quest for the answer to what remains to be uncertain related with the climate system of the SHL region.</p>

Flooding is one of the most commonly occurring natural disasters across the world. Its occurrence is predicted to become more frequent with climate change and associated rainfall increases. This study used a bespoke software Flowroute-i, developed by Ambiental, UK specialists in flood risk assessment and modelling, utlising meteorological and spatial data to produce flood maps. The study was conducted in 6 catchments in southern Thailand modelling flood depth and extent associated with high rainfall events with return periods of 20, 50 and 100 years. Both a present-day scenario and a future scenario (RCP 6.0) with projections to 2100 were modelled. The models suggest that there could be an increase of up to 37.5% in flood extent, particularly in the middle of the catchment. This was particularly evident on the eastern side of the Thai peninsula, Nakhon Si Thammarat, in part as a result of the large flat coastal plain adjacent to steep basin geomorphology. These results should allow appropriate agencies to initiate flood mitigation measures, as the impacts of present-day flood events in the studied areas have been noted to be particularly devastating to life, livelihoods, and infrastructure and this looks set to worsen in a warming world.

<p>The Thai-coast project aims to improve scientific understanding of the vulnerability of Thailand's shoreline and coastal communities to hydro-meteorological hazards, including storms, floods and coastal erosion, under future climate change scenarios. Coastal erosion and flooding affect more than 11 million people living in Thailand’s coastal zone communities (17% of the country's population). Each year erosion causes Thailand to lose 30 km<sup>2</sup> of coastal land (Department of Marine and Coastal Resources (DMCR), Ministry of Natural Resources and Environment). Sea level is predicted to rise by 1 metre in the next 40 -100 years, impacting at least 3,200 km<sup>2</sup> of coastal land, through erosion and flooding, at a potential financial cost to Thailand of 3 billion baht [~ £70 million; Office of Natural Resources and Environmental Policy and Planning]. We address an urgent need to enhance the resilience and adaptation potential of coastal communities, applying scientific research to inform more robust and cost-effective governance and institutional arrangements.</p><p>The Thai-coast project has established causal links between climate change, erosion and flooding and is using this information to assess natural and social processes’ interactions to enhance coastal community resilience and future sustainability. We focus on two study areas, Nakhon Si Thammarat Province and Krabi Province, selected on the basis of DMCR coastal erosion data and with contrasting natural and socio-economic characteristics. Using a multidisciplinary approach, we integrate climate science, geomorphology, socio-economics, health and wellbeing science and geo-information technology to improve understanding of hydro-meteorological hazard occurrence, their physical and socioeconomic, health and wellbeing impacts on Thailand's coastal zone and the ways in which governance and institutional arrangements mitigate their impact. Examining future scenarios of climate change hydrometeorology, coastal landform and land use change scenarios we have assessed and modelled impacts (erosion, flooding, coastal community vulnerability), and population and community adaptation. Our collaborative team of natural and social scientists, from UK, US and Thai research institutions work closely with Thai Government and UK and Thai industry partners to ensure that results are policy and practice-relevant.</p><p>Key findings indicate that erosion and accretion rates are more dramatic on mangrove coastlines (-34.5 and 21.7 m/year) compared with sandy coastlines (-4.1 and 4 m/year). Modelled future climate changes indicate more extended and severe floods in Southern Thailand with the risk of flash floods increasing significantly. Socio-economic resilience is generally higher in more urbanized areas but there are greater variations amongst subdistricts. Different communities within the coastal regions have different levels of resilience and adopt different coping strategies when faced with emergency situations. When physical and socio-economic indices are compared, Krabi Province has a higher level of physical vulnerability than Nakhon Si Thammarat (NST), whilst NST is has a higher level of socio-economic vulnerability than Krabi.  When physical and socio-economic factors are combined to generate the Coastal Vulnerability Index (CVI), the results show that the two provinces have relatively comparable CVI despite the underlying variability in physical and socio-economic resilience.</p>