ENSO modulates wildfire activity in China.

China is a key region for understanding fire activity and the drivers of its variability under strict fire suppression policies. Here, we present a detailed fire occurrence dataset for China, the Wildfire Atlas of China (WFAC; 2005-2018), based on continuous monitoring from multiple satellites and calibrated against field observations. We find that wildfires across China mostly occur in the winter season from January to April and those fire occurrences generally show a decreasing trend after reaching a peak in 2007. Most wildfires (84%) occur in subtropical China, with two distinct clusters in its southwestern and southeastern parts. In southeastern China, wildfires are mainly promoted by low precipitation and high diurnal temperature ranges, the combination of which dries out plant tissue and fuel. In southwestern China, wildfires are mainly promoted by warm conditions that enhance evaporation from litter and dormant plant tissues. We further find a fire occurrence dipole between southwestern and southeastern China that is modulated by the El Niño-Southern Oscillation (ENSO).

A tree-ring δ18O based reconstruction of East Asia summer monsoon over the past two centuries.

The East Asian summer monsoon (EASM) exhibits considerable decadal variations since the late 20th century. Efforts to examine long-term behaviors and dynamics of the EASM are impeded largely due to the shortness of instrumental meteorological records. So far, reconstructions of the EASM with annual resolution from its core regions remain limited. We conduct the first 200-year robust EASM reconstruction based on tree-ring cellulose δ18O records derived from Pinus massoniana trees growing in the middle Yangtze River basin, one of the core EASM areas. The δ18O chronology accounts for 46.2% of the actual variation in an index of the EASM from 1948 to 2014. The reconstructed EASM indicates that the monsoon intensity was below average before the 1950s, peaked in the 1950s-1970s, and then began to decline. The reconstructed EASM is negatively correlated with the El Niño-Southern Oscillation (ENSO), but this teleconnection is dynamic through time, i.e. enhanced (reduced) ENSO variability coheres with strong (weak) EASM-ENSO connections. In addition, despite high ENSO variability since the 1980s, the EASM-ENSO relationship weakened possibly due to anthropogenic impact, particularly aerosol emissions.

Development and Evaluation of an Ensemble-Based Data Assimilation System for Regional Reanalysis Over the Tibetan Plateau and Surrounding Regions.

The Tibetan Plateau is regarded as the Earth's Third Pole, which is the source region of several major rivers that impact more 20% the world population. This high-altitude region is reported to have been undergoing much greater rate of weather changes under global warming, but the existing reanalysis products are inadequate for depicting the state of the atmosphere, particularly with regard to the amount of precipitation and its diurnal cycle. An ensemble Kalman filter (EnKF) data assimilation system based on the limited-area Weather Research and Forecasting (WRF) model was evaluated for use in developing a regional reanalysis over the Tibetan Plateau and the surrounding regions. A 3-month prototype reanalysis over the summer months (June-August) of 2015 using WRF-EnKF at a 30-km grid spacing to assimilate nonradiance observations from the Global Telecommunications System was developed and evaluated against independent sounding and satellite observations in comparison to the ERA-Interim and fifth European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) global reanalysis. Results showed that both the posterior analysis and the subsequent 6- to 12-hr WRF forecasts of the prototype regional reanalysis compared favorably with independent sounding observations, satellite-based precipitation versus those from ERA-Interim and ERA5 during the same period. In particular, the prototype regional reanalysis had clear advantages over the global reanalyses of ERA-Interim and ERA5 in the analysis accuracy of atmospheric humidity, as well as in the subsequent downscale-simulated precipitation intensity, spatial distribution, diurnal evolution, and extreme occurrence.

The relationship between birch pollen, air pollution and weather types and their effect on antihistamine purchase in two Swedish cities.

Exposure to elevated air pollution levels can aggravate pollen allergy symptoms. The aim of this study was to investigate the relationships between airborne birch (Betula) pollen, urban air pollutants NO2, O3 and PM10 and their effects on antihistamine demand in Gothenburg and Malmö, Sweden, 2006-2012. Further, the influence of large-scale weather pattern on pollen-/pollution-related risk, using Lamb weather types (LWTs), was analysed. Daily LWTs were obtained by comparing the atmospheric pressure over a 16-point grid system over southern Sweden (scale ~3000 km). They include two non-directional types, cyclonic (C) and anticyclonic (A) and eight directional types depending on the wind direction (N, NE, E…). Birch pollen levels were exceptionally high under LWTs E and SE in both cities. Furthermore, LWTs with dry and moderately calm meteorological character (A, NE, E, SE) were associated with strongly elevated air pollution (NO2 and PM10) in Gothenburg. For most weather situations in both cities, simultaneously high birch pollen together with high air pollution had larger over-the-counter (OTC) sales of antihistamines than situations with high birch pollen alone. LWTs NE, E, SE and S had the highest OTC sales in both cities. In Gothenburg, the city with a higher load of both birch pollen and air pollution, the higher OTC sales were especially obvious and indicate an increased effect on allergic symptoms from air pollution. Furthermore, Gothenburg LWTs A, NE, E and SE were associated with high pollen and air pollution levels and thus classified as high-risk weather types. In Malmö, corresponding high-risk LWTs were NE, E, SE and S. Furthermore, occurrence of high pollen and air pollutants as well as OTC sales correlated strongly with vapour pressure deficit and temperature in Gothenburg (much less so in Malmö). This provides evidence that the combination of meteorological properties associated with LWTs can explain high levels of birch pollen and air pollution. Our study shows that LWTs represent a useful tool for integrated daily air quality forecasting/warning.

Earlier occurrence and increased explanatory power of climate for the first incidence of potato late blight caused by Phytophthora infestans in Fennoscandia.

BACKGROUND: Late blight (caused by Phytophthora infestans) is a devastating potato disease that has been found to occur earlier in the season over the last decades in Fennoscandia. Up until now the reasons for this change have not been investigated. Possible explanations for this change are climate alterations, changes in potato production or changes in pathogen biology, such as increased fitness or changes in gene flow within P. infestans populations. The first incidence of late blight is of high economic importance since fungicidal applications should be typically applied two weeks before the first signs of late blight and are repeated on average once a week. METHODS: We use field observations of first incidence of late blight in experimental potato fields from five sites in Sweden and Finland covering a total of 30 years and investigate whether the earlier incidence of late blight can be related to the climate. RESULTS: We linked the field data to meteorological data and found that the previous assumption, used in common late blight models, that the disease only develops at relative humidity levels above 90% had to be rejected. Rather than the typically assumed threshold relationship between late blight disease development and relative humidity we found a linear relationship. Our model furthermore showed two distinct responses of late blight to climate. At the beginning of the observation time (in Sweden until the early 90s and in Finland until the 2000s) the link between climate and first incidence was very weak. However, for the remainder of the time period the link was highly significant, indicating a change in the biological properties of the pathogen which could for example be a change in the dominating reproduction mode or a physiological change in the response of the pathogen to climate. CONCLUSIONS: The study shows that models used in decision support systems need to be checked and re-parametrized regularly to be able to capture changes in pathogen biology. While this study was performed with data from Fennoscandia this new pathogen biology and late blight might spread to (or already be present at) other parts of the world as well. The strong link between climate and first incidence together with the presented model offers a tool to assess late blight incidence in future climates.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.