Why does the health sector need weather information ?

Medium-Range EPS Forecasts for the Health Sector:Heat WavesChristina Koppe& Paul BeckerGerman Weather Service, Department: Human Biometeorology

Relationship between atmospheric environment and health outcomes direct indirect Why does the health sector need weather information ? • thermoregulation (heat, cold) • extreme events (storms, floods) • accidents (street conditions) • vector-borne diseases (malaria)  early weather information targeted to the health system can prevent negative health impacts Introduction

Aim EuroHEAT: identify relevant heat situation asap Introduction

environmental aspect temperature, radiant fluxes, humidity, wind velocity human health aspect fitness, physiological parameters, thermoregulatory response, adaptation THRESHOLD Aim EuroHEAT: identify relevant heat situation asap Introduction

environmental aspect temperature, radiant fluxes, humidity, wind velocity human health aspect fitness, physiological parameters, thermoregulatory response, adaptation THRESHOLD Aim EuroHEAT: identify relevant heat situation asap • heat budget models Introduction

environmental aspect temperature, radiant fluxes, humidity, wind velocity human health aspect fitness, physiological parameters, thermoregulatory response,adaptation THRESHOLD Aim EuroHEAT: identify relevant heat situation asap • heat budget models • HeRATE approach Introduction

absolute threshold for heat load based on VDI standards relative threshold short-term adaptation to heat load (backward Gaussian Filter) ºC 38 32 26 20 HeRate threshold = 2/3 absolute + 1/3 relative Philosophy of HeRATE Introduction

Assessment based on fixed thresholds Introduction

Assessment based on variable thresholds Introduction

Relative mortality: BW 1968-2003 • significant differences in mean relative mortality • mean relative mortality increases with increasing thermal load intensity Mortality (% EV) Thermal load categories Introduction

Aim EuroHEAT: identify relevant heat situation asap • use ECMWF EPS forecasts with lead times up to 10 days • use HeRATE approach but simplify • first step: parameters T850 hPa (P130) and T2m (P167) tested  case study: summer 2003 in Europe Introduction

Case study: summer 2003 in Europe • How was the reliability of the EPS forecasts? • Brier Scores and Brier Skill Scores when compared to HeRATE threshold? • Did the EPS show the heat wave signal? • ? Can medium-range forecast be applied to forecast heat / heat impacts on human health ? Case study 2003

Human Biometeorology Comparison of PDFs Differences between the analysed and forecasted 50% percentile t (850 hPa) lead time 60 h t (2m) Case study 2003

> 0.20 0.15 - 0.20 0.10 - 0.15 0.05 - 0.10 0 - 0.05 1.0 0.8 - 1.0 0.6 - 0.8 0.4 - 0.6 0.2 - 0.4 0.0 - 0.2 -0.4 - 0.0 < -0.4 Human Biometeorology Spatial variation of BS and BSS summer 2003 Case study 2003

T(850hPa) reduced to ground level 0 0.0 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 0.4 - 0.5 0.5 - 0.6 0.6 - 0.7 0.7 - 0.8 0.8 - 0.9 0.9 - 1.0 Human Biometeorology Probability Forecasts of t(850 hPa) and t(2m) for 10.08.2003 (lead times 2.5; 5.5 and 8.5 days) Case study 2003

0 0.0 - 0.1 0.1 - 0.2 0.2 - 0.3 0.3 - 0.4 0.4 - 0.5 0.5 - 0.6 0.6 - 0.7 0.7 - 0.8 0.8 - 0.9 0.9 - 1.0 Human Biometeorology Heat wave in 2003 lead time 5 days 14802 4175 Case study 2003

Case study: Conclusions • use 850 hPa temperature and extrapolate to ground • application of a complex index? • forecasts up to 5 days useful • probabilities for health sector • to react depend on individual • cost-loss ratios Conclusions

Why does the health sector need weather information ?